Method for determining gene knockouts

DOEpatents

Maranas, Costa D; Burgard, Anthony R; Pharkya, Priti

2013-06-04

A method for determining candidates for gene deletions and additions using a model of a metabolic network associated with an organism, the model includes a plurality of metabolic reactions defining metabolite relationships, the method includes selecting a bioengineering objective for the organism, selecting at least one cellular objective, forming an optimization problem that couples the at least one cellular objective with the bioengineering objective, and solving the optimization problem to yield at least one candidate.

Mathematical Optimization Algorithm for Minimizing the Cost Function of GHG Emission in AS/RS Using Positive Selection Based Clonal Selection Principle

NASA Astrophysics Data System (ADS)

Mahalakshmi; Murugesan, R.

2018-04-01

This paper regards with the minimization of total cost of Greenhouse Gas (GHG) efficiency in Automated Storage and Retrieval System (AS/RS). A mathematical model is constructed based on tax cost, penalty cost and discount cost of GHG emission of AS/RS. A two stage algorithm namely positive selection based clonal selection principle (PSBCSP) is used to find the optimal solution of the constructed model. In the first stage positive selection principle is used to reduce the search space of the optimal solution by fixing a threshold value. In the later stage clonal selection principle is used to generate best solutions. The obtained results are compared with other existing algorithms in the literature, which shows that the proposed algorithm yields a better result compared to others.

Optimization of furfural production from D-xylose with formic acid as catalyst in a reactive extraction system.

PubMed

Yang, Wandian; Li, Pingli; Bo, Dechen; Chang, Heying; Wang, Xiaowei; Zhu, Tao

2013-04-01

Furfural is one of the most promising platform chemicals derived from biomass. In this study, response surface methodology (RSM) was utilized to determine four important parameters including reaction temperature (170-210°C), formic acid concentration (5-25 g/L), o-nitrotoluene volume percentage (20-80 vt.%), and residence time (40-200 min). The maximum furfural yield of 74% and selectivity of 86% were achieved at 190°C for 20 g/L formic acid concentration and 75 vt.% o-nitrotoluene by 75 min. The high boiling solvent, o-nitrotoluene, was recommended as extraction solvent in a reactive extraction system to obtain high furfural yield and reduce furfural-solvent separation costs. Although the addition of halides to the xylose solutions enhanced the furfural yield and selectivity, the concentration of halides was not an important factor on the furfural yield and selectivity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi-Response Optimization of Granaticinic Acid Production by Endophytic Streptomyces thermoviolaceus NT1, Using Response Surface Methodology

PubMed Central

Roy, Sudipta; Halder, Suman Kumar; Banerjee, Debdulal

2016-01-01

Streptomyces thermoviolaceus NT1, an endophytic isolate, was studied for optimization of granaticinic acid production. It is an antimicrobial metabolite active against even drug resistant bacteria. Different media, optimum glucose concentration, initial media pH, incubation temperature, incubation period, and inoculum size were among the selected parameters optimized in the one-variable-at-a-time (OVAT) approach, where glucose concentration, pH, and temperature were found to play a critical role in antibiotic production by this strain. Finally, the Box–Behnken experimental design (BBD) was employed with three key factors (selected after OVAT studies) for response surface methodological (RSM) analysis of this optimization study.RSM analysis revealed a multifactorial combination; glucose 0.38%, pH 7.02, and temperature 36.53 °C as the optimum conditions for maximum antimicrobial yield. Experimental verification of model analysis led to 3.30-fold (61.35 mg/L as compared to 18.64 mg/L produced in un-optimized condition) enhanced granaticinic acid production in ISP2 medium with 5% inoculum and a suitable incubation period of 10 days. So, the conjugated optimization study for maximum antibiotic production from Streptomyces thermoviolaceus NT1 was found to result in significantly higher yield, which might be exploited in industrial applications. PMID:28952581

Proposal of a super trait for the optimum selection of popcorn progenies based on path analysis.

PubMed

do Amaral Júnior, A T; Dos Santos, A; Gerhardt, I F S; Kurosawa, R N F; Moreira, N F; Pereira, M G; de A Gravina, G; de L Silva, F H

2016-12-19

A challenge faced by popcorn breeding programs is the existence of a negative correlation between the two main traits, popping expansion and yield, which hinders simultaneous gains. The objective of this study was to investigate the use of a new variable or super trait, which favors the reliable selection of superior progenies. The super trait 'expanded popcorn volume per hectare' was introduced in the evaluation of 200 full-sib families of the eighth recurrent intrapopulation selection cycle, which were arranged in randomized blocks with three replicates in two environments. Although the inability to obtain simultaneous gains through selection via popping expansion or yield was confirmed, the super trait was positively associated with both yield and popping expansion, allowing simultaneous gains via indirect selection using 'expanded popcorn volume per hectare' as the main trait. This approach is recommended because this super trait can be used in breeding programs to optimize selective gains for the crop.

Optimal age at first calving for U.S. dairy cattle

USDA-ARS?s Scientific Manuscript database

Heifer rearing is a major expense for the US dairy industry that accounts for 15 to 20% of the total cost of producing milk. Selecting for an optimal age at first calving (AFC) in US dairy cattle could reduce these costs while still providing animals with high lifetime yields. Records from 9,502,802...

Constrained Optimization Problems in Cost and Managerial Accounting--Spreadsheet Tools

ERIC Educational Resources Information Center

Amlie, Thomas T.

2009-01-01

A common problem addressed in Managerial and Cost Accounting classes is that of selecting an optimal production mix given scarce resources. That is, if a firm produces a number of different products, and is faced with scarce resources (e.g., limitations on labor, materials, or machine time), what combination of products yields the greatest profit…

Optimization of supercritical fluid extraction and HPLC identification of wedelolactone from Wedelia calendulacea by orthogonal array design.

PubMed

Patil, Ajit A; Sachin, Bhusari S; Wakte, Pravin S; Shinde, Devanand B

2014-11-01

The purpose of this work is to provide a complete study of the influence of operational parameters of the supercritical carbon dioxide assisted extraction (SC CO2E) on yield of wedelolactone from Wedelia calendulacea Less., and to find an optimal combination of factors that maximize the wedelolactone yield. In order to determine the optimal combination of the four factors viz. operating pressure, temperature, modifier concentration and extraction time, a Taguchi experimental design approach was used: four variables (three levels) in L9 orthogonal array. Wedelolactone content was determined using validated HPLC methodology. Optimum extraction conditions were found to be as follows: extraction pressure, 25 MPa; temperature, 40 °C; modifier concentration, 10% and extraction time, 90 min. Optimum extraction conditions demonstrated wedelolactone yield of 8.01 ± 0.34 mg/100 g W. calendulacea Less. Pressure, temperature and time showed significant (p < 0.05) effect on the wedelolactone yield. The supercritical carbon dioxide extraction showed higher selectivity than the conventional Soxhlet assisted extraction method.

Optimization of supercritical fluid extraction and HPLC identification of wedelolactone from Wedelia calendulacea by orthogonal array design

PubMed Central

Patil, Ajit A.; Sachin, Bhusari S.; Wakte, Pravin S.; Shinde, Devanand B.

2013-01-01

The purpose of this work is to provide a complete study of the influence of operational parameters of the supercritical carbon dioxide assisted extraction (SC CO2E) on yield of wedelolactone from Wedelia calendulacea Less., and to find an optimal combination of factors that maximize the wedelolactone yield. In order to determine the optimal combination of the four factors viz. operating pressure, temperature, modifier concentration and extraction time, a Taguchi experimental design approach was used: four variables (three levels) in L9 orthogonal array. Wedelolactone content was determined using validated HPLC methodology. Optimum extraction conditions were found to be as follows: extraction pressure, 25 MPa; temperature, 40 °C; modifier concentration, 10% and extraction time, 90 min. Optimum extraction conditions demonstrated wedelolactone yield of 8.01 ± 0.34 mg/100 g W. calendulacea Less. Pressure, temperature and time showed significant (p < 0.05) effect on the wedelolactone yield. The supercritical carbon dioxide extraction showed higher selectivity than the conventional Soxhlet assisted extraction method. PMID:25687584

Optimized Periocular Template Selection for Human Recognition

PubMed Central

Sa, Pankaj K.; Majhi, Banshidhar

2013-01-01

A novel approach for selecting a rectangular template around periocular region optimally potential for human recognition is proposed. A comparatively larger template of periocular image than the optimal one can be slightly more potent for recognition, but the larger template heavily slows down the biometric system by making feature extraction computationally intensive and increasing the database size. A smaller template, on the contrary, cannot yield desirable recognition though the smaller template performs faster due to low computation for feature extraction. These two contradictory objectives (namely, (a) to minimize the size of periocular template and (b) to maximize the recognition through the template) are aimed to be optimized through the proposed research. This paper proposes four different approaches for dynamic optimal template selection from periocular region. The proposed methods are tested on publicly available unconstrained UBIRISv2 and FERET databases and satisfactory results have been achieved. Thus obtained template can be used for recognition of individuals in an organization and can be generalized to recognize every citizen of a nation. PMID:23984370

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Customization of copolymers to optimize selectivity and yield in polymer-driven antibody purification processes.

PubMed

Capito, Florian; Skudas, Romas; Stanislawski, Bernd; Kolmar, Harald

2013-01-01

This manuscript describes customization of copolymers to be used for polymer-driven protein purification in bioprocessing. To understand how copolymer customization can be used for fine-tuning, precipitation behavior was analyzed for five target antibodies (mAbs) and BSA as model impurity protein, at ionic strength similar to undiluted cell culture fluid. In contrast to the use of standardized homopolymers, customized copolymers, composed of 2-acrylamido-2-methylpropane sulfonic acid (AMPS) and 4-(acryloylamino)benzoic acid (ABZ), exhibited antibody precipitation yields exceeding 90%. Additionally, copolymer average molecular weight (Mw ) was varied and its influence on precipitation yield and contaminant coprecipitation was investigated. Results revealed copolymer composition as the major driving force for precipitation selectivity, which was also dependent on protein hydrophobicity. By adjusting ABZ content and Mw of the precipitant for each of the mAbs, conditions were found that allowed for high precipitation yield and selectivity. These findings may open up new avenues for using polymers in antibody purification processes. © 2013 American Institute of Chemical Engineers.

Synthesis of cis-C-Iodo-N-Tosyl-Aziridines using Diiodomethyllithium: Reaction Optimization, Product Scope and Stability, and a Protocol for Selection of Stationary Phase for Chromatography

PubMed Central

2013-01-01

The preparation of C-iodo-N-Ts-aziridines with excellent cis-diastereoselectivity has been achieved in high yields by the addition of diiodomethyllithium to N-tosylimines and N-tosylimine–HSO2Tol adducts. This addition-cyclization protocol successfully provided a wide range of cis-iodoaziridines, including the first examples of alkyl-substituted iodoaziridines, with the reaction tolerating both aryl imines and alkyl imines. An ortho-chlorophenyl imine afforded a β-amino gem-diiodide under the optimized reaction conditions due to a postulated coordinated intermediate preventing cyclization. An effective protocol to assess the stability of the sensitive iodoaziridine functional group to chromatography was also developed. As a result of the judicious choice of stationary phase, the iodoaziridines could be purified by column chromatography; the use of deactivated basic alumina (activity IV) afforded high yield and purity. Rearrangements of electron-rich aryl-iodoaziridines have been promoted, selectively affording either novel α-iodo-N-Ts-imines or α-iodo-aldehydes in high yield. PMID:23738857

Direct and efficient xylitol production from xylan by Saccharomyces cerevisiae through transcriptional level and fermentation processing optimizations.

PubMed

Li, Zhe; Qu, Hongnan; Li, Chun; Zhou, Xiaohong

2013-12-01

In this study, four engineered Saccharomyces cerevisiae carrying xylanase, β-xylosidase and xylose reductase genes by different transcriptional regulations were constructed to directly convert xylan to xylitol. According to the results, the high-copy number plasmid required a rigid selection for promoter characteristics, on the contrast, the selection of promoters could be more flexible for low-copy number plasmid. For cell growth and xylitol production, glucose and galactose were found more efficient than other sugars. The semi-aerobic condition and feeding of co-substrates were taken to improve the yield of xylitol. It was found that the strain containing high-copy number plasmid had the highest xylitol yield, but it was sensitive to the change of fermentation. However, the strain carrying low-copy number plasmid was more adaptable to different processes. By optimization of the transcriptional regulation and fermentation processes, the xylitol concentration could be increased of 1.7 folds and the yield was 0.71 g xylitol/g xylan. Copyright © 2013 Elsevier Ltd. All rights reserved.

In vitro selection and amplification protocols for isolation of aptameric sensors for small molecules

PubMed Central

Yang, Kyung-Ae; Pei, Renjun; Stojanovic, Milan N.

2016-01-01

We recently optimized a procedure that directly yields aptameric sensors for small molecules in so-called structure-switching format. The protocol has a high success rate, short time, and is sufficiently simple to be readily implemented in a non-specialist laboratory. We provide a stepwise guide to this selection protocol. PMID:27155227

Toward optimal feature and time segment selection by divergence method for EEG signals classification.

PubMed

Wang, Jie; Feng, Zuren; Lu, Na; Luo, Jing

2018-06-01

Feature selection plays an important role in the field of EEG signals based motor imagery pattern classification. It is a process that aims to select an optimal feature subset from the original set. Two significant advantages involved are: lowering the computational burden so as to speed up the learning procedure and removing redundant and irrelevant features so as to improve the classification performance. Therefore, feature selection is widely employed in the classification of EEG signals in practical brain-computer interface systems. In this paper, we present a novel statistical model to select the optimal feature subset based on the Kullback-Leibler divergence measure, and automatically select the optimal subject-specific time segment. The proposed method comprises four successive stages: a broad frequency band filtering and common spatial pattern enhancement as preprocessing, features extraction by autoregressive model and log-variance, the Kullback-Leibler divergence based optimal feature and time segment selection and linear discriminate analysis classification. More importantly, this paper provides a potential framework for combining other feature extraction models and classification algorithms with the proposed method for EEG signals classification. Experiments on single-trial EEG signals from two public competition datasets not only demonstrate that the proposed method is effective in selecting discriminative features and time segment, but also show that the proposed method yields relatively better classification results in comparison with other competitive methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimizing Winter Wheat Resilience to Climate Change in Rain Fed Crop Systems of Turkey and Iran.

PubMed

Lopes, Marta S; Royo, Conxita; Alvaro, Fanny; Sanchez-Garcia, Miguel; Ozer, Emel; Ozdemir, Fatih; Karaman, Mehmet; Roustaii, Mozaffar; Jalal-Kamali, Mohammad R; Pequeno, Diego

2018-01-01

Erratic weather patterns associated with increased temperatures and decreasing rainfall pose unique challenges for wheat breeders playing a key part in the fight to ensure global food security. Within rain fed winter wheat areas of Turkey and Iran, unusual weather patterns may prevent attaining maximum potential increases in winter wheat genetic gains. This is primarily related to the fact that the yield ranking of tested genotypes may change from one year to the next. Changing weather patterns may interfere with the decisions breeders make about the ideotype(s) they should aim for during selection. To inform breeding decisions, this study aimed to optimize major traits by modeling different combinations of environments (locations and years) and by defining a probabilistic range of trait variations [phenology and plant height (PH)] that maximized grain yields (GYs; one wheat line with optimal heading and height is suggested for use as a testing line to aid selection calibration decisions). Research revealed that optimal phenology was highly related to the temperature and to rainfall at which winter wheat genotypes were exposed around heading time (20 days before and after heading). Specifically, later winter wheat genotypes were exposed to higher temperatures both before and after heading, increased rainfall at the vegetative stage, and reduced rainfall during grain filling compared to early genotypes. These variations in exposure to weather conditions resulted in shorter grain filling duration and lower GYs in long-duration genotypes. This research tested if diversity within species may increase resilience to erratic weather patterns. For the study, calculated production of a selection of five high yielding genotypes (if grown in five plots) was tested against monoculture (if only a single genotype grown in the same area) and revealed that a set of diverse genotypes with different phenologies and PHs was not beneficial. New strategies of progeny selection are discussed: narrow range of variation for phenology in families may facilitate the discovery and selection of new drought-resistant and avoidant wheat lines targeting specific locations.

Optimizing Winter Wheat Resilience to Climate Change in Rain Fed Crop Systems of Turkey and Iran

PubMed Central

Lopes, Marta S.; Royo, Conxita; Alvaro, Fanny; Sanchez-Garcia, Miguel; Ozer, Emel; Ozdemir, Fatih; Karaman, Mehmet; Roustaii, Mozaffar; Jalal-Kamali, Mohammad R.; Pequeno, Diego

2018-01-01

Erratic weather patterns associated with increased temperatures and decreasing rainfall pose unique challenges for wheat breeders playing a key part in the fight to ensure global food security. Within rain fed winter wheat areas of Turkey and Iran, unusual weather patterns may prevent attaining maximum potential increases in winter wheat genetic gains. This is primarily related to the fact that the yield ranking of tested genotypes may change from one year to the next. Changing weather patterns may interfere with the decisions breeders make about the ideotype(s) they should aim for during selection. To inform breeding decisions, this study aimed to optimize major traits by modeling different combinations of environments (locations and years) and by defining a probabilistic range of trait variations [phenology and plant height (PH)] that maximized grain yields (GYs; one wheat line with optimal heading and height is suggested for use as a testing line to aid selection calibration decisions). Research revealed that optimal phenology was highly related to the temperature and to rainfall at which winter wheat genotypes were exposed around heading time (20 days before and after heading). Specifically, later winter wheat genotypes were exposed to higher temperatures both before and after heading, increased rainfall at the vegetative stage, and reduced rainfall during grain filling compared to early genotypes. These variations in exposure to weather conditions resulted in shorter grain filling duration and lower GYs in long-duration genotypes. This research tested if diversity within species may increase resilience to erratic weather patterns. For the study, calculated production of a selection of five high yielding genotypes (if grown in five plots) was tested against monoculture (if only a single genotype grown in the same area) and revealed that a set of diverse genotypes with different phenologies and PHs was not beneficial. New strategies of progeny selection are discussed: narrow range of variation for phenology in families may facilitate the discovery and selection of new drought-resistant and avoidant wheat lines targeting specific locations. PMID:29765385

Statistical Optimization of 1,3-Propanediol (1,3-PD) Production from Crude Glycerol by Considering Four Objectives: 1,3-PD Concentration, Yield, Selectivity, and Productivity.

PubMed

Supaporn, Pansuwan; Yeom, Sung Ho

2018-04-30

This study investigated the biological conversion of crude glycerol generated from a commercial biodiesel production plant as a by-product to 1,3-propanediol (1,3-PD). Statistical analysis was employed to derive a statistical model for the individual and interactive effects of glycerol, (NH 4 ) 2 SO 4 , trace elements, pH, and cultivation time on the four objectives: 1,3-PD concentration, yield, selectivity, and productivity. Optimum conditions for each objective with its maximum value were predicted by statistical optimization, and experiments under the optimum conditions verified the predictions. In addition, by systematic analysis of the values of four objectives, optimum conditions for 1,3-PD concentration (49.8 g/L initial glycerol, 4.0 g/L of (NH 4 ) 2 SO 4 , 2.0 mL/L of trace element, pH 7.5, and 11.2 h of cultivation time) were determined to be the global optimum culture conditions for 1,3-PD production. Under these conditions, we could achieve high 1,3-PD yield (47.4%), 1,3-PD selectivity (88.8%), and 1,3-PD productivity (2.1/g/L/h) as well as high 1,3-PD concentration (23.6 g/L).

Application of Ionic Liquids in the Microwave-Assisted Extraction of Proanthocyanidins from Larix gmelini Bark

PubMed Central

Yang, Lei; Sun, Xiaowei; Yang, Fengjian; Zhao, Chunjian; Zhang, Lin; Zu, Yuangang

2012-01-01

Ionic liquid based, microwave-assisted extraction (ILMAE) was successfully applied to the extraction of proanthocyanidins from Larix gmelini bark. In this work, in order to evaluate the performance of ionic liquids in the microwave-assisted extraction process, a series of 1-alkyl-3-methylimidazolium ionic liquids with different cations and anions were evaluated for extraction yield, and 1-butyl-3-methylimidazolium bromide was selected as the optimal solvent. In addition, the ILMAE procedure for the proanthocyanidins was optimized and compared with other conventional extraction techniques. Under the optimized conditions, satisfactory extraction yield of the proanthocyanidins was obtained. Relative to other methods, the proposed approach provided higher extraction yield and lower energy consumption. The Larix gmelini bark samples before and after extraction were analyzed by Thermal gravimetric analysis, Fourier-transform infrared spectroscopy and characterized by scanning electron microscopy. The results showed that the ILMAE method is a simple and efficient technique for sample preparation. PMID:22606036

Batch, design optimization, and DNA sequencing study for continuous 1,3-propanediol production from waste glycerol by a soil-based inoculum.

PubMed

Kanjilal, Baishali; Noshadi, Iman; Bautista, Eddy J; Srivastava, Ranjan; Parnas, Richard S

2015-03-01

1,3-propanediol (1,3-PD) was produced with a robust fermentation process using waste glycerol feedstock from biodiesel production and a soil-based bacterial inoculum. An iterative inoculation method was developed to achieve independence from soil and selectively breed bacterial populations capable of glycerol metabolism to 1,3-PD. The inoculum showed high resistance to impurities in the feedstock. 1,3-PD selectivity and yield in batch fermentations was optimized by appropriate nutrient compositions and pH control. The batch yield of 1,3-PD was maximized to ~0.7 mol/mol for industrial glycerol which was higher than that for pure glycerin. 16S rDNA sequencing results show a systematic selective enrichment of 1,3-PD producing bacteria with iterative inoculation and subsequent process control. A statistical design of experiments was carried out on industrial glycerol batches to optimize conditions, which were used to run two continuous flow stirred-tank reactor (CSTR) experiments over a period of >500 h each. A detailed analysis of steady states at three dilution rates is presented. Enhanced specific 1,3-PD productivity was observed with faster dilution rates due to lower levels of solvent degeneration. 1,3-PD productivity, specific productivity, and yield of 1.1 g/l hr, 1.5 g/g hr, and 0.6 mol/mol of glycerol were obtained at a dilution rate of 0.1 h(-1)which is bettered only by pure strains in pure glycerin feeds.

Exploratory use of a UAV platform for variety selection in peanut

NASA Astrophysics Data System (ADS)

Balota, Maria; Oakes, Joseph

2016-05-01

Variety choice is the most important production decision farmers make because high yielding varieties can increase profit with no additional production costs. Therefore, yield improvement has been the major objective for peanut (Arachis hypogaea L.) breeding programs worldwide, but the current breeding approach (selecting for yield under optimal production conditions) is slow and inconsistent with the needs derived from population demand and climate change. To improve the rate of genetic gain, breeders have used target physiological traits such as leaf chlorophyll content using SPAD chlorophyll meter, Normalized Difference Vegetation Index (NDVI) from canopy reflectance in visible and near infra-red (NIR) wavelength bands, and canopy temperature (CT) manually measured with infra-red (IR) thermometers at the canopy level; but its use for routine selection was hampered by the time required to walk hundreds of plots. Recent developments in remote sensing-based high throughput phenotyping platforms using unmanned aerial vehicles (UAV) have shown good potential for future breeding advancements. Recently, we initiated a study for the evaluation of suitability of digital imagery, NDVI, and CT taken from an UAV platform for peanut variety differentiation. Peanut is unique for setting its yield underground and resilience to drought and heat, for which yield is difficult to pre-harvest estimate; although the need for early yield estimation within the breeding programs exists. Twenty-six peanut cultivars and breeding lines were grown in replicated plots either optimally or deficiently irrigated under rain exclusion shelters at Suffolk, Virginia. At the beginning maturity growth stage, approximately a month before digging, NDVI and CT were taken with ground-based sensors at the same time with red, blue, green (RGB) images from a Sony camera mounted on an UAV platform. Disease ratings were also taken pre-harvest. Ground and UAV derived vegetation indices were analyzed for disease and yield prediction and further presented in this paper.

Increased genetic gains in sheep, beef and dairy breeding programs from using female reproductive technologies combined with optimal contribution selection and genomic breeding values.

PubMed

Granleese, Tom; Clark, Samuel A; Swan, Andrew A; van der Werf, Julius H J

2015-09-14

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and embryo transfer (JIVET) can boost rates of genetic gain but they can also increase rates of inbreeding. Inbreeding can be managed using the principles of optimal contribution selection (OCS), which maximizes genetic gain while placing a penalty on the rate of inbreeding. We evaluated the potential benefits and synergies that exist between genomic selection (GS) and reproductive technologies under OCS for sheep and cattle breeding programs. Various breeding program scenarios were simulated stochastically including: (1) a sheep breeding program for the selection of a single trait that could be measured either early or late in life; (2) a beef breeding program with an early or late trait; and (3) a dairy breeding program with a sex limited trait. OCS was applied using a range of penalties (severe to no penalty) on co-ancestry of selection candidates, with the possibility of using multiple ovulation and embryo transfer (MOET) and/or juvenile in vitro embryo production and embryo transfer (JIVET) for females. Each breeding program was simulated with and without genomic selection. All breeding programs could be penalized to result in an inbreeding rate of 1 % increase per generation. The addition of MOET to artificial insemination or natural breeding (AI/N), without the use of GS yielded an extra 25 to 60 % genetic gain. The further addition of JIVET did not yield an extra genetic gain. When GS was used, MOET and MOET + JIVET programs increased rates of genetic gain by 38 to 76 % and 51 to 81 % compared to AI/N, respectively. Large increases in genetic gain were found across species when female reproductive technologies combined with genomic selection were applied and inbreeding was managed, especially for breeding programs that focus on the selection of traits measured late in life or that are sex-limited. Optimal contribution selection was an effective tool to optimally allocate different combinations of reproductive technologies. Applying a range of penalties to co-ancestry of selection candidates allows a comprehensive exploration of the inbreeding vs. genetic gain space.

Optimizing an Actuator Array for the Control of Multi-Frequency Noise in Aircraft Interiors

NASA Technical Reports Server (NTRS)

Palumbo, D. L.; Padula, S. L.

1997-01-01

Techniques developed for selecting an optimized actuator array for interior noise reduction at a single frequency are extended to the multi-frequency case. Transfer functions for 64 actuators were obtained at 5 frequencies from ground testing the rear section of a fully trimmed DC-9 fuselage. A single loudspeaker facing the left side of the aircraft was the primary source. A combinatorial search procedure (tabu search) was employed to find optimum actuator subsets of from 2 to 16 actuators. Noise reduction predictions derived from the transfer functions were used as a basis for evaluating actuator subsets during optimization. Results indicate that it is necessary to constrain actuator forces during optimization. Unconstrained optimizations selected actuators which require unrealistically large forces. Two methods of constraint are evaluated. It is shown that a fast, but approximate, method yields results equivalent to an accurate, but computationally expensive, method.

WFIRST: Exoplanet Target Selection and Scheduling with Greedy Optimization

NASA Astrophysics Data System (ADS)

Keithly, Dean; Garrett, Daniel; Delacroix, Christian; Savransky, Dmitry

2018-01-01

We present target selection and scheduling algorithms for missions with direct imaging of exoplanets, and the Wide Field Infrared Survey Telescope (WFIRST) in particular, which will be equipped with a coronagraphic instrument (CGI). Optimal scheduling of CGI targets can maximize the expected value of directly imaged exoplanets (completeness). Using target completeness as a reward metric and integration time plus overhead time as a cost metric, we can maximize the sum completeness for a mission with a fixed duration. We optimize over these metrics to create a list of target stars using a greedy optimization algorithm based off altruistic yield optimization (AYO) under ideal conditions. We simulate full missions using EXOSIMS by observing targets in this list for their predetermined integration times. In this poster, we report the theoretical maximum sum completeness, mean number of detected exoplanets from Monte Carlo simulations, and the ideal expected value of the simulated missions.

Choosing non-redundant representative subsets of protein sequence data sets using submodular optimization.

PubMed

Libbrecht, Maxwell W; Bilmes, Jeffrey A; Noble, William Stafford

2018-04-01

Selecting a non-redundant representative subset of sequences is a common step in many bioinformatics workflows, such as the creation of non-redundant training sets for sequence and structural models or selection of "operational taxonomic units" from metagenomics data. Previous methods for this task, such as CD-HIT, PISCES, and UCLUST, apply a heuristic threshold-based algorithm that has no theoretical guarantees. We propose a new approach based on submodular optimization. Submodular optimization, a discrete analogue to continuous convex optimization, has been used with great success for other representative set selection problems. We demonstrate that the submodular optimization approach results in representative protein sequence subsets with greater structural diversity than sets chosen by existing methods, using as a gold standard the SCOPe library of protein domain structures. In this setting, submodular optimization consistently yields protein sequence subsets that include more SCOPe domain families than sets of the same size selected by competing approaches. We also show how the optimization framework allows us to design a mixture objective function that performs well for both large and small representative sets. The framework we describe is the best possible in polynomial time (under some assumptions), and it is flexible and intuitive because it applies a suite of generic methods to optimize one of a variety of objective functions. © 2018 Wiley Periodicals, Inc.

Multidimensional density shaping by sigmoids.

PubMed

Roth, Z; Baram, Y

1996-01-01

An estimate of the probability density function of a random vector is obtained by maximizing the output entropy of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's optimization method, applied to the estimated density, yields a recursive estimator for a random variable or a random sequence. A constrained connectivity structure yields a linear estimator, which is particularly suitable for "real time" prediction. A Gaussian nonlinearity yields a closed-form solution for the network's parameters, which may also be used for initializing the optimization algorithm when other nonlinearities are employed. A triangular connectivity between the neurons and the input, which is naturally suggested by the statistical setting, reduces the number of parameters. Applications to classification and forecasting problems are demonstrated.

Application of a Box-Behnken design for optimizing the extraction process of agave fructans (Agave tequilana Weber var. Azul).

PubMed

Flores-Girón, Emmanuel; Salazar-Montoya, Juan Alfredo; Ramos-Ramírez, Emma Gloria

2016-08-01

Agave (Agave tequilana Weber var. Azul) is an industrially important crop in México since it is the only raw material appropriate to produce tequila, an alcoholic beverage. Nowadays, however, these plants have also a nutritional interest as a source of functional food ingredients, owing to the prebiotic potential of agave fructans. In this study, a Box-Behnken design was employed to determine the influence of temperature, liquid:solid ratio and time in a maceration process for agave fructan extraction and optimization. The developed regression model indicates that the selected study variables were statistical determinants for the extraction yield, and the optimal conditions for maximum extraction were a temperature of 60 °C, a liquid:solid ratio of 10:1 (v/w) and a time of 26.7 min, corresponding to a predicted extraction yield of 37.84%. Through selective separation via precipitation with ethanol, fructans with a degree of polymerization of 29.1 were obtained. Box-Behnken designs are useful statistical methods for optimizing the extraction process of agave fructans. A mixture of carbohydrates was obtained from agave powder. This optimized method can be used to obtain fructans for use as prebiotics or as raw material for obtaining functional oligosaccharides. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Optimization of laccase production by Pleurotus ostreatus IMI 395545 using the Taguchi DOE methodology.

PubMed

Periasamy, Rathinasamy; Palvannan, Thayumanavan

2010-12-01

Production of laccase using a submerged culture of Pleurotus orstreatus IMI 395545 was optimized by the Taguchi orthogonal array (OA) design of experiments (DOE) methodology. This approach facilitates the study of the interactions of a large number of variables spanned by factors and their settings, with a small number of experiments, leading to considerable savings in time and cost for process optimization. This methodology optimizes the number of impact factors and enables to calculate their interaction in the production of industrial enzymes. Eight factors, viz. glucose, yeast extract, malt extract, inoculum, mineral solution, inducer (1 mM CuSO₄) and amino acid (l-asparagine) at three levels and pH at two levels, with an OA layout of L18 (2¹ × 3⁷) were selected for the proposed experimental design. The laccase yield obtained from the 18 sets of fermentation experiments performed with the selected factors and levels was further processed with Qualitek-4 software. The optimized conditions shared an enhanced laccase expression of 86.8% (from 485.0 to 906.3 U). The combination of factors was further validated for laccase production and reactive blue 221 decolorization. The results revealed an enhanced laccase yield of 32.6% and dye decolorization up to 84.6%. This methodology allows the complete evaluation of main and interaction factors. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Response Surface Methodology Optimization of Ultrasonic-Assisted Extraction of Acer Truncatum Leaves for Maximal Phenolic Yield and Antioxidant Activity.

PubMed

Yang, Lingguang; Yin, Peipei; Fan, Hang; Xue, Qiang; Li, Ke; Li, Xiang; Sun, Liwei; Liu, Yujun

2017-02-04

This study is the first to report the use of response surface methodology to improve phenolic yield and antioxidant activity of Acer truncatum leaves extracts (ATLs) obtained by ultrasonic-assisted extraction. The phenolic composition in ATLs extracted under the optimized conditions were characterized by UPLC-QTOF-MS/MS. Solvent and extraction time were selected based on preliminary experiments, and a four-factors-three-levels central composite design was conducted to optimize solvent concentration ( X ₁), material-to-liquid ratio ( X ₂), ultrasonic temperature ( X ₃) and power ( X ₄) for an optimal total phenol yield ( Y ₁) and DPPH• antioxidant activity ( Y ₂). The results showed that the optimal combination was ethanol:water ( v : v ) 66.21%, material-to-liquid ratio 1:15.31 g/mL, ultrasonic bath temperature 60 °C, power 267.30 W, and time 30 min with three extractions, giving a maximal total phenol yield of 7593.62 mg gallic acid equivalent/100 g d.w. and a maximal DPPH• antioxidant activity of 74,241.61 μmol Trolox equivalent/100 g d.w. Furthermore, 22 phenolics were first identified in ATL extract obtained under the optimized conditions, indicating that gallates, gallotannins, quercetin, myricetin and chlorogenic acid derivatives were the main phenolic components in ATL. What's more, a gallotannins pathway existing in ATL from gallic acid to penta- O -galloylglucoside was proposed. All these results provide practical information aiming at full utilization of phenolics in ATL, together with fundamental knowledge for further research.

Evaluation and optimization of microbial DNA extraction from fecal samples of wild Antarctic bird species

PubMed Central

Eriksson, Per; Mourkas, Evangelos; González-Acuna, Daniel; Olsen, Björn; Ellström, Patrik

2017-01-01

ABSTRACT Introduction: Advances in the development of nucleic acid-based methods have dramatically facilitated studies of host–microbial interactions. Fecal DNA analysis can provide information about the host’s microbiota and gastrointestinal pathogen burden. Numerous studies have been conducted in mammals, yet birds are less well studied. Avian fecal DNA extraction has proved challenging, partly due to the mixture of fecal and urinary excretions and the deficiency of optimized protocols. This study presents an evaluation of the performance in avian fecal DNA extraction of six commercial kits from different bird species, focusing on penguins. Material and methods: Six DNA extraction kits were first tested according to the manufacturers’ instructions using mallard feces. The kit giving the highest DNA yield was selected for further optimization and evaluation using Antarctic bird feces. Results: Penguin feces constitute a challenging sample type: most of the DNA extraction kits failed to yield acceptable amounts of DNA. The QIAamp cador Pathogen kit (Qiagen) performed the best in the initial investigation. Further optimization of the protocol resulted in good yields of high-quality DNA from seven bird species of different avian orders. Conclusion: This study presents an optimized approach to DNA extraction from challenging avian fecal samples. PMID:29152162

Strategies for Fermentation Medium Optimization: An In-Depth Review

PubMed Central

Singh, Vineeta; Haque, Shafiul; Niwas, Ram; Srivastava, Akansha; Pasupuleti, Mukesh; Tripathi, C. K. M.

2017-01-01

Optimization of production medium is required to maximize the metabolite yield. This can be achieved by using a wide range of techniques from classical “one-factor-at-a-time” to modern statistical and mathematical techniques, viz. artificial neural network (ANN), genetic algorithm (GA) etc. Every technique comes with its own advantages and disadvantages, and despite drawbacks some techniques are applied to obtain best results. Use of various optimization techniques in combination also provides the desirable results. In this article an attempt has been made to review the currently used media optimization techniques applied during fermentation process of metabolite production. Comparative analysis of the merits and demerits of various conventional as well as modern optimization techniques have been done and logical selection basis for the designing of fermentation medium has been given in the present review. Overall, this review will provide the rationale for the selection of suitable optimization technique for media designing employed during the fermentation process of metabolite production. PMID:28111566

Optimizing cropland cover for stable food production in Sub-Saharan Africa using simulated yield and Modern Portfolio Theory

NASA Astrophysics Data System (ADS)

Bodin, P.; Olin, S.; Pugh, T. A. M.; Arneth, A.

2014-12-01

Food security can be defined as stable access to food of good nutritional quality. In Sub Saharan Africa access to food is strongly linked to local food production and the capacity to generate enough calories to sustain the local population. Therefore it is important in these regions to generate not only sufficiently high yields but also to reduce interannual variability in food production. Traditionally, climate impact simulation studies have focused on factors that underlie maximum productivity ignoring the variability in yield. By using Modern Portfolio Theory, a method stemming from economics, we here calculate optimum current and future crop selection that maintain current yield while minimizing variance, vs. maintaining variance while maximizing yield. Based on simulated yield using the LPJ-GUESS dynamic vegetation model, the results show that current cropland distribution for many crops is close to these optimum distributions. Even so, the optimizations displayed substantial potential to either increase food production and/or to decrease its variance regionally. Our approach can also be seen as a method to create future scenarios for the sown areas of crops in regions where local food production is important for food security.

Optimizing Training Population Size and Genotyping Strategy for Genomic Prediction Using Association Study Results and Pedigree Information. A Case of Study in Advanced Wheat Breeding Lines.

PubMed

Cericola, Fabio; Jahoor, Ahmed; Orabi, Jihad; Andersen, Jeppe R; Janss, Luc L; Jensen, Just

2017-01-01

Wheat breeding programs generate a large amount of variation which cannot be completely explored because of limited phenotyping throughput. Genomic prediction (GP) has been proposed as a new tool which provides breeding values estimations without the need of phenotyping all the material produced but only a subset of it named training population (TP). However, genotyping of all the accessions under analysis is needed and, therefore, optimizing TP dimension and genotyping strategy is pivotal to implement GP in commercial breeding schemes. Here, we explored the optimum TP size and we integrated pedigree records and genome wide association studies (GWAS) results to optimize the genotyping strategy. A total of 988 advanced wheat breeding lines were genotyped with the Illumina 15K SNPs wheat chip and phenotyped across several years and locations for yield, lodging, and starch content. Cross-validation using the largest possible TP size and all the SNPs available after editing (~11k), yielded predictive abilities (rGP) ranging between 0.5-0.6. In order to explore the Training population size, rGP were computed using progressively smaller TP. These exercises showed that TP of around 700 lines were enough to yield the highest observed rGP. Moreover, rGP were calculated by randomly reducing the SNPs number. This showed that around 1K markers were enough to reach the highest observed rGP. GWAS was used to identify markers associated with the traits analyzed. A GWAS-based selection of SNPs resulted in increased rGP when compared with random selection and few hundreds SNPs were sufficient to obtain the highest observed rGP. For each of these scenarios, advantages of adding the pedigree information were shown. Our results indicate that moderate TP sizes were enough to yield high rGP and that pedigree information and GWAS results can be used to greatly optimize the genotyping strategy.

Biomass fast pyrolysis for bio-oil production in a fluidized bed reactor under hot flue atmosphere.

PubMed

Li, Ning; Wang, Xiang; Bai, Xueyuan; Li, Zhihe; Zhang, Ying

2015-10-01

Fast pyrolysis experiments of corn stalk were performed to investigate the optimal pyrolysis conditions of temperature and bed material for maximum bio-oil production under flue gas atmosphere. Under the optimized pyrolysis conditions, furfural residue, xylose residue and kelp seaweed were pyrolyzed to examine their yield distributions of products, and the physical characteristics of bio-oil were studied. The best flow rate of the flue gas at selected temperature is obtained, and the pyrolysis temperature at 500 degrees C and dolomite as bed material could give a maximum bio-oil yield. The highest bio-oil yield of 43.3% (W/W) was achieved from corn stalk under the optimal conditions. Two main fractions were recovered from the stratified bio-oils: light oils and heavy oils. The physical properties of heavy oils from all feedstocks varied little. The calorific values of heavy oils were much higher than that of light oils. The pyrolysis gas could be used as a gaseous fuel due to a relatively high calorific value of 6.5-8.5 MJ/m3.

Technologies for Decreasing Mining Losses

NASA Astrophysics Data System (ADS)

Valgma, Ingo; Väizene, Vivika; Kolats, Margit; Saarnak, Martin

2013-12-01

In case of stratified deposits like oil shale deposit in Estonia, mining losses depend on mining technologies. Current research focuses on extraction and separation possibilities of mineral resources. Selective mining, selective crushing and separation tests have been performed, showing possibilities of decreasing mining losses. Rock crushing and screening process simulations were used for optimizing rock fractions. In addition mine backfilling, fine separation, and optimized drilling and blasting have been analyzed. All tested methods show potential and depend on mineral usage. Usage in addition depends on the utilization technology. The questions like stability of the material flow and influences of the quality fluctuations to the final yield are raised.

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

NASA Astrophysics Data System (ADS)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

PubMed

Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

2018-05-01

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli. We develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Intensification of marrubiin concentration by optimization of microwave-assisted (low CO2 yielding) extraction process for Marrubium vulgare using central composite design and antioxidant evaluation.

PubMed

Mittal, Vineet; Nanda, Arun

2017-12-01

Marrubium vulgare Linn (Lamiaceae) was generally extracted by conventional methods with low yield of marrubiin; these processes were not considered environment friendly. This study extracts the whole plant of M. vulgare by microwave assisted extraction (MAE) and optimizes the effect of various extraction parameters on the marrubiin yield by using Central Composite Design (CCD). The selected medicinal plant was extracted using ethanol: water (1:1) as solvent by MAE. The plant material was also extracted using a Soxhlet and the various extracts were analyzed by HPTLC to quantify the marrubiin concentration. The optimized conditions for the microwave-assisted extraction of selected medicinal plant was microwave power of 539 W, irradiation time of 373 s and solvent to drug ratio, 32 mL per g of the drug. The marrubiin concentration in MAE almost doubled relative to the traditional method (0.69 ± 0.08 to 1.35 ± 0.04%). The IC 50 for DPPH was reduced to 66.28 ± 0.6 μg/mL as compared to conventional extract (84.14 ± 0.7 μg/mL). The scanning electron micrographs of the treated and untreated drug samples further support the results. The CCD can be successfully applied to optimize the extraction parameters (MAE) for M. vulgare. Moreover, in terms of environmental impact, the MAE technique could be assumed as a 'Green approach' because the MAE approach for extraction of plant released only 92.3 g of CO 2 as compared to 3207.6 g CO 2 using the Soxhlet method of extraction.

Quantitative NMR Approach to Optimize the Formation of Chemical Building Blocks from Abundant Carbohydrates.

PubMed

Elliot, Samuel G; Tolborg, Søren; Sádaba, Irantzu; Taarning, Esben; Meier, Sebastian

2017-07-21

The future role of biomass-derived chemicals relies on the formation of diverse functional monomers in high yields from carbohydrates. Recently, it has become clear that a series of α-hydroxy acids, esters, and lactones can be formed from carbohydrates in alcohol and water solvents using tin-containing catalysts such as Sn-Beta. These compounds are potential building blocks for polyesters bearing additional olefin and alcohol functionalities. An NMR approach was used to identify, quantify, and optimize the formation of these building blocks in the Sn-Beta-catalyzed transformation of abundant carbohydrates. Record yields of the target molecules can be achieved by obstructing competing reactions through solvent selection. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes.

PubMed

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M

2018-04-12

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes

PubMed Central

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M.

2018-01-01

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods. PMID:29649114

Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins.

PubMed

He, Jun; Xu, Jiaqi; Wu, Xiao-Lin; Bauck, Stewart; Lee, Jungjae; Morota, Gota; Kachman, Stephen D; Spangler, Matthew L

2018-04-01

SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K genotypes were between 0.817 and 0.821 for daughter pregnancy rate, between 0.838 and 0.844 for fat yield, and between 0.850 and 0.863 for milk yield. The two SNP panels optimized on the three major factors had the highest genomic prediction accuracy (0.821-0.863), and these accuracies were very close to those obtained using observed 80K genotypes (0.825-0.868). Further exploration of the underlying relationships showed that genomic prediction accuracies did not respond linearly to imputation accuracies, but were significantly affected by genotype (imputation) errors of SNPs in association with the traits to be predicted. SNPs optimal for map coverage and MAF were favorable for obtaining accurate imputation of genotypes whereas trait-associated SNPs improved genomic prediction accuracies. Thus, optimal LD SNP panels were the ones that combined both strengths. The present results have practical implications on the design of LD SNP chips for imputation-enabled genomic prediction.

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

PubMed

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

2015-10-21

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

Optimization of Saanen sperm genes amplification: evaluation of standardized protocols in genetically uncharacterized rural goats reared under a subtropical environment.

PubMed

Barbour, Elie K; Saade, Maya F; Sleiman, Fawwak T; Hamadeh, Shady K; Mouneimne, Youssef; Kassaifi, Zeina; Kayali, Ghazi; Harakeh, Steve; Jaber, Lina S; Shaib, Houssam A

2012-10-01

The purpose of this research is to optimize quantitatively the amplification of specific sperm genes in reference genomically characterized Saanen goat and to evaluate the standardized protocols applicability on sperms of uncharacterized genome of rural goats reared under subtropical environment for inclusion in future selection programs. The optimization of the protocols in Saanen sperms included three production genes (growth hormone (GH) exons 2, 3, and 4, αS1-casein (CSN1S1), and α-lactalbumin) and two health genes (MHC class II DRB and prion (PrP)). The optimization was based on varying the primers concentrations and the inclusion of a PCR cosolvent (Triton X). The impact of the studied variables on statistically significant increase in the yield of amplicons was noticed in four out of five (80%) optimized protocols, namely in those related to GH, CSN1S1, α-lactalbumin, and PrP genes (P < 0.05). There was no significant difference in the yield of amplicons related to MHC class II DRB gene, regardless of the variables used (P > 0.05). The applicability of the optimized protocols of Saanen sperm genes on amplification of uncharacterized rural goat sperms revealed a 100% success in tested individuals for amplification of GH, CSN1S1, α-lactalbumin, and MHC class II DRB genes and a 75% success for the PrP gene. The significant success in applicability of the Saanen quantitatively optimized protocols to other uncharacterized genome of rural goats allows for their inclusion in future selection, targeting the sustainability of this farming system in a subtropical environment and the improvement of the farmers livelihood.

Algorithm for selection of optimized EPR distance restraints for de novo protein structure determination

PubMed Central

Kazmier, Kelli; Alexander, Nathan S.; Meiler, Jens; Mchaourab, Hassane S.

2010-01-01

A hybrid protein structure determination approach combining sparse Electron Paramagnetic Resonance (EPR) distance restraints and Rosetta de novo protein folding has been previously demonstrated to yield high quality models (Alexander et al., 2008). However, widespread application of this methodology to proteins of unknown structures is hindered by the lack of a general strategy to place spin label pairs in the primary sequence. In this work, we report the development of an algorithm that optimally selects spin labeling positions for the purpose of distance measurements by EPR. For the α-helical subdomain of T4 lysozyme (T4L), simulated restraints that maximize sequence separation between the two spin labels while simultaneously ensuring pairwise connectivity of secondary structure elements yielded vastly improved models by Rosetta folding. 50% of all these models have the correct fold compared to only 21% and 8% correctly folded models when randomly placed restraints or no restraints are used, respectively. Moreover, the improvements in model quality require a limited number of optimized restraints, the number of which is determined by the pairwise connectivities of T4L α-helices. The predicted improvement in Rosetta model quality was verified by experimental determination of distances between spin labels pairs selected by the algorithm. Overall, our results reinforce the rationale for the combined use of sparse EPR distance restraints and de novo folding. By alleviating the experimental bottleneck associated with restraint selection, this algorithm sets the stage for extending computational structure determination to larger, traditionally elusive protein topologies of critical structural and biochemical importance. PMID:21074624

Optimizing pressurized liquid extraction of microbial lipids using the response surface method.

PubMed

Cescut, J; Severac, E; Molina-Jouve, C; Uribelarrea, J-L

2011-01-21

Response surface methodology (RSM) was used for the determination of optimum extraction parameters to reach maximum lipid extraction yield with yeast. Total lipids were extracted from oleaginous yeast (Rhodotorula glutinis) using pressurized liquid extraction (PLE). The effects of extraction parameters on lipid extraction yield were studied by employing a second-order central composite design. The optimal condition was obtained as three cycles of 15 min at 100°C with a ratio of 144 g of hydromatrix per 100 g of dry cell weight. Different analysis methods were used to compare the optimized PLE method with two conventional methods (Soxhlet and modification of Bligh and Dyer methods) under efficiency, selectivity and reproducibility criteria thanks to gravimetric analysis, GC with flame ionization detector, High Performance Liquid Chromatography linked to Evaporative Light Scattering Detector (HPLC-ELSD) and thin-layer chromatographic analysis. For each sample, the lipid extraction yield with optimized PLE was higher than those obtained with referenced methods (Soxhlet and Bligh and Dyer methods with, respectively, a recovery of 78% and 85% compared to PLE method). Moreover, the use of PLE led to major advantages such as an analysis time reduction by a factor of 10 and solvent quantity reduction by 70%, compared with traditional extraction methods. Copyright © 2010 Elsevier B.V. All rights reserved.

Automatic CT simulation optimization for radiation therapy: A general strategy.

PubMed

Li, Hua; Yu, Lifeng; Anastasio, Mark A; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M; Low, Daniel A; Mutic, Sasa

2014-03-01

In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube potentials for patient sizes of 38, 43, 48, 53, and 58 cm were 120, 140, 140, 140, and 140 kVp, respectively, and the corresponding minimum CTDIvol for achieving the optimal image quality index 4.4 were 9.8, 32.2, 100.9, 241.4, and 274.1 mGy, respectively. For patients with lateral sizes of 43-58 cm, 120-kVp scan protocols yielded up to 165% greater radiation dose relative to 140-kVp protocols, and 140-kVp protocols always yielded a greater image quality index compared to the same dose-level 120-kVp protocols. The trace of target and organ dosimetry coverage and the γ passing rates of seven IMRT dose distribution pairs indicated the feasibility of the proposed image quality index for the predication strategy. A general strategy to predict the optimal CT simulation protocols in a flexible and quantitative way was developed that takes into account patient size, treatment planning task, and radiation dose. The experimental study indicated that the optimal CT simulation protocol and the corresponding radiation dose varied significantly for different patient sizes, contouring accuracy, and radiation treatment planning tasks.

Response Surface Methodology for Optimizing the Production of Biosurfactant by Candida tropicalis on Industrial Waste Substrates

PubMed Central

Almeida, Darne G.; Soares da Silva, Rita de Cássia F.; Luna, Juliana M.; Rufino, Raquel D.; Santos, Valdemir A.; Sarubbo, Leonie A.

2017-01-01

Biosurfactant production optimization by Candida tropicalis UCP0996 was studied combining central composite rotational design (CCRD) and response surface methodology (RSM). The factors selected for optimization of the culture conditions were sugarcane molasses, corn steep liquor, waste frying oil concentrations and inoculum size. The response variables were surface tension and biosurfactant yield. All factors studied were important within the ranges investigated. The two empirical forecast models developed through RSM were found to be adequate for describing biosurfactant production with regard to surface tension (R2 = 0.99833) and biosurfactant yield (R2 = 0.98927) and a very strong, negative, linear correlation was found between the two response variables studied (r = −0.95). The maximum reduction in surface tension and the highest biosurfactant yield were 29.98 mNm−1 and 4.19 gL−1, respectively, which were simultaneously obtained under the optimum conditions of 2.5% waste frying oil, 2.5%, corn steep liquor, 2.5% molasses, and 2% inoculum size. To validate the efficiency of the statistically optimized variables, biosurfactant production was also carried out in 2 and 50 L bioreactors, with yields of 5.87 and 7.36 gL−1, respectively. Finally, the biosurfactant was applied in motor oil dispersion, reaching up to 75% dispersion. Results demonstrated that the CCRD was suitable for identifying the optimum production conditions and that the new biosurfactant is a promising dispersant for application in the oil industry. PMID:28223971

Application of response surface methodology to optimize microwave-assisted extraction of silymarin from milk thistle seeds

USDA-ARS?s Scientific Manuscript database

Several parameters of Microwave-assisted extraction (MAE) including extraction time, extraction temperature, ethanol concentration and solid-liquid ratio were selected to describe the MAE processing. The silybin content, measured by an UV-Vis spectrophotometry, was considered as the silymarin yield....

A systematic approach to parameter selection for CAD-virtual reality data translation using response surface methodology and MOGA-II.

PubMed

Abidi, Mustufa Haider; Al-Ahmari, Abdulrahman; Ahmad, Ali

2018-01-01

Advanced graphics capabilities have enabled the use of virtual reality as an efficient design technique. The integration of virtual reality in the design phase still faces impediment because of issues linked to the integration of CAD and virtual reality software. A set of empirical tests using the selected conversion parameters was found to yield properly represented virtual reality models. The reduced model yields an R-sq (pred) value of 72.71% and an R-sq (adjusted) value of 86.64%, indicating that 86.64% of the response variability can be explained by the model. The R-sq (pred) is 67.45%, which is not very high, indicating that the model should be further reduced by eliminating insignificant terms. The reduced model yields an R-sq (pred) value of 73.32% and an R-sq (adjusted) value of 79.49%, indicating that 79.49% of the response variability can be explained by the model. Using the optimization software MODE Frontier (Optimization, MOGA-II, 2014), four types of response surfaces for the three considered response variables were tested for the data of DOE. The parameter values obtained using the proposed experimental design methodology result in better graphics quality, and other necessary design attributes.

Heat tolerance around flowering in wheat identified as a key trait for increased yield potential in Europe under climate change

PubMed Central

Stratonovitch, Pierre; Semenov, Mikhail A.

2015-01-01

To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Projected climatic and environmental changes emphasize the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost, and drought. Heat stress around sensitive stages of wheat development has been identified as a possible threat to wheat production in Europe. However, no estimates have been made to assess yield losses due to increased frequency and magnitude of heat stress under climate change. Using existing experimental data, the Sirius wheat model was refined by incorporating the effects of extreme temperature during flowering and grain filling on accelerated leaf senescence, grain number, and grain weight. This allowed us, for the first time, to quantify yield losses resulting from heat stress under climate change. The model was used to optimize wheat ideotypes for CMIP5-based climate scenarios for 2050 at six sites in Europe with diverse climates. The yield potential for heat-tolerant ideotypes can be substantially increased in the future (e.g. by 80% at Seville, 100% at Debrecen) compared with the current cultivars by selecting an optimal combination of wheat traits, e.g. optimal phenology and extended duration of grain filling. However, at two sites, Seville and Debrecen, the grain yields of heat-sensitive ideotypes were substantially lower (by 54% and 16%) and more variable compared with heat-tolerant ideotypes, because the extended grain filling required for the increased yield potential was in conflict with episodes of high temperature during flowering and grain filling. Despite much earlier flowering at these sites, the risk of heat stress affecting yields of heat-sensitive ideotypes remained high. Therefore, heat tolerance in wheat is likely to become a key trait for increased yield potential and yield stability in southern Europe in the future. PMID:25750425

Synergism of virtual screening and medicinal chemistry: identification and optimization of allosteric antagonists of metabotropic glutamate receptor 1.

PubMed

Noeske, Tobias; Trifanova, Dina; Kauss, Valerjans; Renner, Steffen; Parsons, Christopher G; Schneider, Gisbert; Weil, Tanja

2009-08-01

We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by virtual screening and subsequent hit optimization. For ligand-based virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC(50)=0.74+/-0.29 microM). Hit optimization yielded lead structure 16 with an affinity of K(i)=0.024+/-0.001 microM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.

Use of Taguchi methodology to enhance the yield of caffeine removal with growing cultures of Pseudomonas pseudoalcaligenes.

PubMed

Ashengroph, Morahem; Ababaf, Sajad

2014-12-01

Microbial caffeine removal is a green solution for treatment of caffeinated products and agro-industrial effluents. We directed this investigation to optimizing a bio-decaffeination process with growing cultures of Pseudomonas pseudoalcaligenes through Taguchi methodology which is a structured statistical approach that can be lowered variations in a process through Design of Experiments (DOE). Five parameters, i.e. initial fructose, tryptone, Zn(+2) ion and caffeine concentrations and also incubation time selected and an L16 orthogonal array was applied to design experiments with four 4-level factors and one 3-level factor (4(4) × 1(3)). Data analysis was performed using the statistical analysis of variance (ANOVA) method. Furthermore, the optimal conditions were determined by combining the optimal levels of the significant factors and verified by a confirming experiment. Measurement of residual caffeine concentration in the reaction mixture was performed using high-performance liquid chromatography (HPLC). Use of Taguchi methodology for optimization of design parameters resulted in about 86.14% reduction of caffeine in 48 h incubation when 5g/l fructose, 3 mM Zn(+2) ion and 4.5 g/l of caffeine are present in the designed media. Under the optimized conditions, the yield of degradation of caffeine (4.5 g/l) by the native strain of Pseudomonas pseudoalcaligenes TPS8 has been increased from 15.8% to 86.14% which is 5.4 fold higher than the normal yield. According to the experimental results, Taguchi methodology provides a powerful methodology for identifying the favorable parameters on caffeine removal using strain TPS8 which suggests that the approach also has potential application with similar strains to improve the yield of caffeine removal from caffeine containing solutions.

Evaluation of Selected Model Constraints and Variables on Simulated Sustainable Yield from the Mississippi River Valley Alluvial Aquifer System in Arkansas

USGS Publications Warehouse

Czarnecki, John B.

2008-01-01

An existing conjunctive use optimization model of the Mississippi River Valley alluvial aquifer was used to evaluate the effect of selected constraints and model variables on ground-water sustainable yield. Modifications to the optimization model were made to evaluate the effects of varying (1) the upper limit of ground-water withdrawal rates, (2) the streamflow constraint associated with the White River, and (3) the specified stage of the White River. Upper limits of ground-water withdrawal rates were reduced to 75, 50, and 25 percent of the 1997 ground-water withdrawal rates. As the upper limit is reduced, the spatial distribution of sustainable pumping increases, although the total sustainable pumping from the entire model area decreases. In addition, the number of binding constraint points decreases. In a separate analysis, the streamflow constraint associated with the White River was optimized, resulting in an estimate of the maximum sustainable streamflow at DeValls Bluff, Arkansas, the site of potential surface-water withdrawals from the White River for the Grand Prairie Area Demonstration Project. The maximum sustainable streamflow, however, is less than the amount of streamflow allocated in the spring during the paddlefish spawning period. Finally, decreasing the specified stage of the White River was done to evaluate a hypothetical river stage that might result if the White River were to breach the Melinda Head Cut Structure, one of several manmade diversions that prevents the White River from permanently joining the Arkansas River. A reduction in the stage of the White River causes reductions in the sustainable yield of ground water.

Optimization of Fermentation Conditions and Rheological Properties of Exopolysaccharide Produced by Deep-Sea Bacterium Zunongwangia profunda SM-A87

PubMed Central

Liu, Sheng-Bo; Qiao, Li-Ping; He, Hai-Lun; Zhang, Qian; Chen, Xiu-Lan; Zhou, Wei-Zhi; Zhou, Bai-Cheng; Zhang, Yu-Zhong

2011-01-01

Zunongwangia profunda SM-A87 isolated from deep-sea sediment can secrete large quantity of exopolysaccharide (EPS). Response surface methodology was applied to optimize the culture conditions for EPS production. Single-factor experiment showed that lactose was the best carbon source. Based on the Plackett–Burman design, lactose, peptone and temperature were selected as significant variables, which were further optimized by the steepest ascent (descent) method and central composite design. The optimal culture conditions for EPS production and broth viscosity were determined as 32.21 g/L lactose, 8.87 g/L peptone and an incubation temperature of 9.8°C. Under these conditions, the maximum EPS yield and broth viscosity were 8.90 g/L and 6551 mPa•s, respectively, which is the first report of such high yield of EPS from a marine bacterium. The aqueous solution of the EPS displayed high viscosity, interesting shearing thinning property and great tolerance to high temperature, a wide range of pH, and high salinity. PMID:22096500

Bioprospecting for hyper-lipid producing microalgal strains for sustainable biofuel production.

PubMed

Mutanda, T; Ramesh, D; Karthikeyan, S; Kumari, S; Anandraj, A; Bux, F

2011-01-01

Global petroleum reserves are shrinking at a fast pace, increasing the demand for alternate fuels. Microalgae have the ability to grow rapidly, and synthesize and accumulate large amounts (approximately 20-50% of dry weight) of neutral lipid stored in cytosolic lipid bodies. A successful and economically viable algae based biofuel industry mainly depends on the selection of appropriate algal strains. The main focus of bioprospecting for microalgae is to identify unique high lipid producing microalgae from different habitats. Indigenous species of microalgae with high lipid yields are especially valuable in the biofuel industry. Isolation, purification and identification of natural microalgal assemblages using conventional techniques is generally time consuming. However, the recent use of micromanipulation as a rapid isolating tool allows for a higher screening throughput. The appropriate media and growth conditions are also important for successful microalgal proliferation. Environmental parameters recorded at the sampling site are necessary to optimize in vitro growth. Identification of species generally requires a combination of morphological and genetic characterization. The selected microalgal strains are grown in upscale systems such as raceway ponds or photobireactors for biomass and lipid production. This paper reviews the recent methodologies adopted for site selection, sampling, strain selection and identification, optimization of cultural conditions for superior lipid yield for biofuel production. Energy generation routes of microalgal lipids and biomass are discussed in detail. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evaluation of parameters affecting switchgrass tissue culture: toward a consolidated procedure for Agrobacterium-mediated transformation of switchgrass (Panicum virgatum)

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

Lin, Chien-Yuan; Donohoe, Bryon S.; Ahuja, Neha

Switchgrass (Panicum virgatum), a robust perennial C4-type grass, has been evaluated and designated as a model bioenergy crop by the U.S. DOE and USDA. Conventional breeding of switchgrass biomass is difficult because it displays self-incompatible hindrance. Therefore, direct genetic modifications of switchgrass have been considered the more effective approach to tailor switchgrass with traits of interest. Successful transformations have demonstrated increased biomass yields, reduction in the recalcitrance of cell walls and enhanced saccharification efficiency. Several tissue culture protocols have been previously described to produce transgenic switchgrass lines using different nutrient-based media, co-cultivation approaches, and antibiotic strengths for selection. After evaluatingmore » the published protocols, we consolidated these approaches and optimized the process to develop a more efficient protocol for producing transgenic switchgrass. First, seed sterilization was optimized, which led to a 20% increase in yield of induced calluses. Second, we have selected a N 6 macronutrient/B 5 micronutrient (NB)-based medium for callus induction from mature seeds of the Alamo cultivar, and chose a Murashige and Skoog-based medium to regenerate both Type I and Type II calluses. Third, Agrobacterium-mediated transformation was adopted that resulted in 50-100% positive regenerated transformants after three rounds (2 weeks/round) of selection with antibiotic. Genomic DNA PCR, RT-PCR, Southern blot, visualization of the red fluorescent protein and histochemical β-glucuronidase (GUS) staining were conducted to confirm the positive switchgrass transformants. The optimized methods developed here provide an improved strategy to promote the production and selection of callus and generation of transgenic switchgrass lines. The process for switchgrass transformation has been evaluated and consolidated to devise an improved approach for transgenic switchgrass production. With the optimization of seed sterilization, callus induction, and regeneration steps, a reliable and effective protocol is established to facilitate switchgrass engineering.« less

Evaluation of parameters affecting switchgrass tissue culture: toward a consolidated procedure for Agrobacterium-mediated transformation of switchgrass (Panicum virgatum)

DOE PAGES

Lin, Chien-Yuan; Donohoe, Bryon S.; Ahuja, Neha; ...

2017-12-19

Switchgrass (Panicum virgatum), a robust perennial C4-type grass, has been evaluated and designated as a model bioenergy crop by the U.S. DOE and USDA. Conventional breeding of switchgrass biomass is difficult because it displays self-incompatible hindrance. Therefore, direct genetic modifications of switchgrass have been considered the more effective approach to tailor switchgrass with traits of interest. Successful transformations have demonstrated increased biomass yields, reduction in the recalcitrance of cell walls and enhanced saccharification efficiency. Several tissue culture protocols have been previously described to produce transgenic switchgrass lines using different nutrient-based media, co-cultivation approaches, and antibiotic strengths for selection. After evaluatingmore » the published protocols, we consolidated these approaches and optimized the process to develop a more efficient protocol for producing transgenic switchgrass. First, seed sterilization was optimized, which led to a 20% increase in yield of induced calluses. Second, we have selected a N 6 macronutrient/B 5 micronutrient (NB)-based medium for callus induction from mature seeds of the Alamo cultivar, and chose a Murashige and Skoog-based medium to regenerate both Type I and Type II calluses. Third, Agrobacterium-mediated transformation was adopted that resulted in 50-100% positive regenerated transformants after three rounds (2 weeks/round) of selection with antibiotic. Genomic DNA PCR, RT-PCR, Southern blot, visualization of the red fluorescent protein and histochemical β-glucuronidase (GUS) staining were conducted to confirm the positive switchgrass transformants. The optimized methods developed here provide an improved strategy to promote the production and selection of callus and generation of transgenic switchgrass lines. The process for switchgrass transformation has been evaluated and consolidated to devise an improved approach for transgenic switchgrass production. With the optimization of seed sterilization, callus induction, and regeneration steps, a reliable and effective protocol is established to facilitate switchgrass engineering.« less

A study to identify and compare airborne systems for in-situ measurements of launch vehicle effluents

NASA Technical Reports Server (NTRS)

Thomas, T. J.; Chace, A. S.

1974-01-01

An in-situ system for monitoring the concentration of HCl, CO, CO2, and Al2O3 in the cloud of reaction products that form as a result of a launch of solid propellant launch vehicle is studied. A wide array of instrumentation and platforms are reviewed to yield the recommended system. An airborne system suited to monitoring pollution concentrations over urban areas for the purpose of calibrating remote sensors is then selected using a similar methodology to yield the optimal configuration.

Design of experiments utilization to map the processing capabilities of a micro-spray dryer: particle design and throughput optimization in support of drug discovery.

PubMed

Ormes, James D; Zhang, Dan; Chen, Alex M; Hou, Shirley; Krueger, Davida; Nelson, Todd; Templeton, Allen

2013-02-01

There has been a growing interest in amorphous solid dispersions for bioavailability enhancement in drug discovery. Spray drying, as shown in this study, is well suited to produce prototype amorphous dispersions in the Candidate Selection stage where drug supply is limited. This investigation mapped the processing window of a micro-spray dryer to achieve desired particle characteristics and optimize throughput/yield. Effects of processing variables on the properties of hypromellose acetate succinate were evaluated by a fractional factorial design of experiments. Parameters studied include solid loading, atomization, nozzle size, and spray rate. Response variables include particle size, morphology and yield. Unlike most other commercial small-scale spray dryers, the ProCepT was capable of producing particles with a relatively wide mean particle size, ca. 2-35 µm, allowing material properties to be tailored to support various applications. In addition, an optimized throughput of 35 g/hour with a yield of 75-95% was achieved, which affords to support studies from Lead-identification/Lead-optimization to early safety studies. A regression model was constructed to quantify the relationship between processing parameters and the response variables. The response surface curves provide a useful tool to design processing conditions, leading to a reduction in development time and drug usage to support drug discovery.

[Study on the optimal extraction process of chaihushugan powder].

PubMed

Wang, Chun-yan; Zhang, Wan-ming; Zhang, Dan-shen; An, Fang; Tian, Jia-ming

2009-11-01

To study the optimal extraction process of chaihushugan powder by orthogonal design. RP-HPLC method was developed for the determination of saikosaponin a, ferulic acid, hesperidin and paeoniflorin in chaihushugan powder. The contents of the components and the extraction yield were selected as assessment indices. Four factors were study by L9 (3(4)), including the alcohol concentration, amount of alcohol, duration of extraction and times of extraction. The optimal extracting condition was 80% alcohol consumed as 10 times of crude herb amount, and extracting two times for 90 min each time. This study supplies theoretical base for the development of chaihushugan powder formulation.

Reliability-based structural optimization: A proposed analytical-experimental study

NASA Technical Reports Server (NTRS)

Stroud, W. Jefferson; Nikolaidis, Efstratios

1993-01-01

An analytical and experimental study for assessing the potential of reliability-based structural optimization is proposed and described. In the study, competing designs obtained by deterministic and reliability-based optimization are compared. The experimental portion of the study is practical because the structure selected is a modular, actively and passively controlled truss that consists of many identical members, and because the competing designs are compared in terms of their dynamic performance and are not destroyed if failure occurs. The analytical portion of this study is illustrated on a 10-bar truss example. In the illustrative example, it is shown that reliability-based optimization can yield a design that is superior to an alternative design obtained by deterministic optimization. These analytical results provide motivation for the proposed study, which is underway.

Computational alternatives to obtain time optimal jet engine control. M.S. Thesis

NASA Technical Reports Server (NTRS)

Basso, R. J.; Leake, R. J.

1976-01-01

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

Metabolite and transcript markers for the prediction of potato drought tolerance.

PubMed

Sprenger, Heike; Erban, Alexander; Seddig, Sylvia; Rudack, Katharina; Thalhammer, Anja; Le, Mai Q; Walther, Dirk; Zuther, Ellen; Köhl, Karin I; Kopka, Joachim; Hincha, Dirk K

2018-04-01

Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker-assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT-PCR and GC-MS profiling, respectively. Transcript marker candidates were selected from a published RNA-Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Fast microwave-assisted catalytic co-pyrolysis of corn stover and scum for bio-oil production with CaO and HZSM-5 as the catalyst.

PubMed

Liu, Shiyu; Xie, Qinglong; Zhang, Bo; Cheng, Yanling; Liu, Yuhuan; Chen, Paul; Ruan, Roger

2016-03-01

This study investigated fast microwave-assisted catalytic co-pyrolysis of corn stover and scum for bio-oil production with CaO and HZSM-5 as the catalyst. Effects of reaction temperature, CaO/HZSM-5 ratio, and corn stover/scum ratio on co-pyrolysis product fractional yields and selectivity were investigated. Results showed that co-pyrolysis temperature was selected as 550°C, which provides the maximum bio-oil and aromatic yields. Mixed CaO and HZSM-5 catalyst with the weight ratio of 1:4 increased the aromatic yield to 35.77 wt.% of feedstock, which was 17% higher than that with HZSM-5 alone. Scum as the hydrogen donor, had a significant synergistic effect with corn stover to promote the production of bio-oil and aromatic hydrocarbons when the H/C(eff) value exceeded 1. The maximum yield of aromatic hydrocarbons (29.3 wt.%) were obtained when the optimal corn stover to scum ratio was 1:2. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of atypical flight patterns

NASA Technical Reports Server (NTRS)

Statler, Irving C. (Inventor); Ferryman, Thomas A. (Inventor); Amidan, Brett G. (Inventor); Whitney, Paul D. (Inventor); White, Amanda M. (Inventor); Willse, Alan R. (Inventor); Cooley, Scott K. (Inventor); Jay, Joseph Griffith (Inventor); Lawrence, Robert E. (Inventor); Mosbrucker, Chris (Inventor)

2005-01-01

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis.

Analytical optimal pulse shapes obtained with the aid of genetic algorithms

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

Guerrero, Rubén D., E-mail: rdguerrerom@unal.edu.co; Arango, Carlos A.; Reyes, Andrés

2015-09-28

We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function using genetic algorithms. As a first application of the methodology, we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data recorded along the evolution of the genetic algorithm contained important information regarding themore » interplay between radiative and diabatic processes. We performed a principal component analysis on these data to retrieve the most relevant processes along the optimal path. Our proposed methodology could be useful for performing quantum optimal control on more complex systems by employing a wider variety of pulse shape functions.« less

Highly Constrained Bicyclic Scaffolds for the Discovery of Protease-Stable Peptides via mRNA Display.

PubMed

Hacker, David E; Hoinka, Jan; Iqbal, Emil S; Przytycka, Teresa M; Hartman, Matthew C T

2017-03-17

Highly constrained peptides such as the knotted peptide natural products are promising medicinal agents because of their impressive biostability and potent activity. Yet, libraries of highly constrained peptides are challenging to prepare. Here, we present a method which utilizes two robust, orthogonal chemical steps to create highly constrained bicyclic peptide libraries. This technology was optimized to be compatible with in vitro selections by mRNA display. We performed side-by-side monocyclic and bicyclic selections against a model protein (streptavidin). Both selections resulted in peptides with mid-nanomolar affinity, and the bicyclic selection yielded a peptide with remarkable protease resistance.

Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection.

PubMed

Pan, Xiaoyong; Hu, Xiaohua; Zhang, Yu Hang; Feng, Kaiyan; Wang, Shao Peng; Chen, Lei; Huang, Tao; Cai, Yu Dong

2018-04-12

Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew's correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles.

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

On computing the global time-optimal motions of robotic manipulators in the presence of obstacles

NASA Technical Reports Server (NTRS)

Shiller, Zvi; Dubowsky, Steven

1991-01-01

A method for computing the time-optimal motions of robotic manipulators is presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem is reduced to a search for the time-optimal path in the n-dimensional position space. A small set of near-optimal paths is first efficiently selected from a grid, using a branch and bound search and a series of lower bound estimates on the traveling time along a given path. These paths are further optimized with a local path optimization to yield the global optimal solution. Obstacles are considered by eliminating the collision points from the tessellated space and by adding a penalty function to the motion time in the local optimization. The computational efficiency of the method stems from the reduced dimensionality of the searched spaced and from combining the grid search with a local optimization. The method is demonstrated in several examples for two- and six-degree-of-freedom manipulators with obstacles.

Optimization of radiotherapy. Some notes on the principles and practice of optimization in cancer treatment and implications for clinical research.

PubMed

Andrews, J R

1981-01-01

Two methods dominate cancer treatment--one, the traditional best practice, individualized treatment method and two, the a priori determined decision method of the interinstitutional, cooperative, clinical trial. In the first, choices are infinite and can be made at the time of treatment; in the second, choices are finite and are made in advance of treatment on a random basis. Neither method systematically selects, identifies, or formalizes the optimum level of effect in the treatment chosen. Of the two, it can be argued that the first, other things being equal, is more likely to select the optimum treatment. The determination of level of effect for the optimization of cancer treatment requires the generation of dose-response relationships for both benefit and risk and the introduction of benefit and risk considerations and judgements. The clinical trial, as presently constituted, doses not yield this kind of information, it being, generally, of the binary yes or no, better or worse type. The best practice, individualized treatment method can yield, when adequately documented, both a range of dose-response relationships and a variety of benefit and risk considerations. The presentation will be limited to a consideration of a single modality of cancer treatment, radiation therapy, but an analogy with other modalities of cancer treatment will be inferred. Criteria for optimization will be developed and graphic means for its identification and formalization will be demonstrated with examples taken from the radiotherapy literature. The general problem of optimization theory and practice will be discussed; the necessity for its exploration in relation to the increasing complexity of cancer treatment will be developed; and recommendations for clinical research will be made including a proposal for the support of clinics as an alternative to the support of programs.

Single-step microwave-assisted hot water extraction of hemicelluloses from selected lignocellulosic materials - A biorefinery approach.

PubMed

Mihiretu, Gezahegn T; Brodin, Malin; Chimphango, Annie F; Øyaas, Karin; Hoff, Bård H; Görgens, Johann F

2017-10-01

The viability of single-step microwave-induced pressurized hot water conditions for co-production of xylan-based biopolymers and bioethanol from aspenwood sawdust and sugarcane trash was investigated. Extraction of hemicelluloses was conducted using microwave-assisted pressurized hot water system. The effects of temperature and time on extraction yield and enzymatic digestibility of resulting solids were determined. Temperatures between 170-200°C for aspenwood and 165-195°C for sugarcane trash; retention times between 8-22min for both feedstocks, were selected for optimization purpose. Maximum xylan extraction yields of 66 and 50%, and highest cellulose digestibilities of 78 and 74%, were attained for aspenwood and sugarcane trash respectively. Monomeric xylose yields for both feedstocks were below 7%, showing that the xylan extracts were predominantly in non-monomeric form. Thus, single-step microwave-assisted hot water method is viable biorefinery approach to extract xylan from lignocelluloses while rendering the solid residues sufficiently digestible for ethanol production. Copyright © 2017 Elsevier Ltd. All rights reserved.

Enhanced and green extraction polyphenols and furanocoumarins from Fig (Ficus carica L.) leaves using deep eutectic solvents.

PubMed

Wang, Tong; Jiao, Jiao; Gai, Qing-Yan; Wang, Peng; Guo, Na; Niu, Li-Li; Fu, Yu-Jie

2017-10-25

Nowadays, green extraction of bioactive compounds from medicinal plants has gained increasing attention. As green solvent, deep eutectic solvent (DES) have been highly rated to replace toxic organic solvents in extraction process. In present study, to simultaneous extraction five main bioactive compounds from fig leaves, DES was tailor-made. The tailor-made DES composed of a 3:3:3 molar ratio of glycerol, xylitol and D-(-)-Fructose showed enhanced extraction yields for five target compounds simultaneously compared with traditional methanol and non-tailor DESs. Then, the tailor-made DES based extraction methods have compared and microwave-assisted extraction was selected and optimized due to its high extraction yields with lower time consumption. The influencing parameters including extraction temperature, liquid-solid ratio, and extraction time were optimized using response surface methodology (RSM). Under optimal conditions the extraction yield of caffeoylmalic acid, psoralic acid-glucoside, rutin, psoralen and bergapten was 6.482mg/g, 16.34mg/g, 5.207mg/g, 15.22mg/g and 2.475mg/g, respectively. Macroporous resin D101 has been used to recovery target compounds with recovery yields of 79.2%, 83.4%, 85.5%, 81.2% and 75.3% for caffeoylmalic acid, psoralic acid-glucoside, rutin, psoralen and bergapten, respectively. The present study suggests that DESs are truly designer and efficient solvents and the method we developed was efficient and sustainable for extraction main compounds from Fig leaves.mg/g. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Optimization of Production Conditions for Protoplasts and Polyethylene Glycol-Mediated Transformation of Gaeumannomyces tritici.

PubMed

Wang, Mei; Zhang, Jie; Wang, Lanying; Han, Lirong; Zhang, Xing; Feng, Juntao

2018-05-24

Take-all, caused by Gaeumannomyces tritici , is one of the most important wheat root diseases worldwide, as it results in serious yield losses. In this study, G. tritici was transformed to express the hygromycin B phosphotransferase using a combined protoplast and polyethylene glycol (PEG)-mediated transformation technique. Based on a series of single-factor experimental results, three major factors-temperature, enzyme lysis time, and concentration of the lysing enzyme-were selected as the independent variables, which were optimized using the response surface methodology. A higher protoplast yield of 9.83 × 10⁷ protoplasts/mL was observed, and the protoplast vitality was also high, reaching 96.27% after optimization. Protoplasts were isolated under the optimal conditions, with the highest transformation frequency (46⁻54 transformants/μg DNA). Polymerase chain reaction and Southern blotting detection indicated that the genes of hygromycin phosphotransferase were successfully inserted into the genome of G. tritici . An optimised PEG-mediated protoplast transformation system for G. tritici was established. The techniques and procedures described will lay the foundation for establishing a good mutation library of G. tritici and could be used to transform other fungi.

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

PubMed

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the proposed methodology results in fewer catheters without a clinically significant loss in plan quality. The proposed approach can be used as a decision support tool that guides the user to find the ideal number and configuration of catheters. © 2017 American Association of Physicists in Medicine.

Selective One-Pot Production of High-Grade Diesel-Range Alkanes from Furfural and 2-Methylfuran over Pd/NbOPO4.

PubMed

Xia, Qineng; Xia, Yinjiang; Xi, Jinxu; Liu, Xiaohui; Zhang, Yongguang; Guo, Yong; Wang, Yanqin

2017-02-22

A one-pot method for the selective production of high-grade diesel-range alkanes from biomass-derived furfural and 2-methylfuran (2-MF) was developed by combining the hydroxyalkylation/alkylation (HAA) condensation of furfural with 2-MF and the subsequent hydrodeoxygenation (HDO) over a multifunctional Pd/NbOPO 4 catalyst. The effects of various reaction conditions as well as a variety of solid-acid catalysts and metal-loaded NbOPO 4 catalysts were systematically investigated to optimize the reaction conditions for both reactions. Under the optimal reaction conditions up to 89.1 % total yield of diesel-range alkanes was obtained from furfural and 2-MF by this one-pot method. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A high plant density reduces the ability of maize to use soil nitrogen

PubMed Central

Yan, Peng; Pan, Junxiao; Zhang, Wenjie; Shi, Junfang; Chen, Xinping; Cui, Zhenling

2017-01-01

Understanding the physiological changes associated with high grain yield and high N use efficiency (NUE) is important when increasing the plant density and N rate to develop optimal agronomic management. We tested the hypothesis that high plant densities resulting in crowding stress reduce the ability of plants to use the N supply post-silking, thus decreasing the grain yield and NUE. In 2013 and 2014, a field experiment, with five N-application rates and three plant densities (6.0, 7.5, and 9.0 plants m–2), was conducted in the North China Plain (NCP). The calculated maximum grain yield and agronomic use efficiency (AEN) at a density of 7.5 plants m–2 were 12.4 Mg ha–1 and 39.3 kg kg–1, respectively, which were significantly higher than the values obtained at densities of 6.0 (11.3 Mg ha–1 and 30.2 kg kg–1) and 9.0 plant m–2 (11.7 Mg ha–1 and 27.8 kg kg–1). A high plant density of 9.0 plants m–2 decreased the post-silking N accumulation, leaf N concentration and net photosynthesis, which reduced the post-silking dry matter production, resulting in a low yield and NUE. Although a relatively low grain yield was observed at a density of 9.0 plants m–2, the optimal N rate increased from 150 to 186 kg N ha-1 at a density of 7.5 plants m–2. These results indicate that high plant densities with crowding stress reduce the ability of plants to use soil N during the post-silking period, and high rate of N fertilizer was needed to increase grain yield. We conclude that selecting the appropriate plant density combined with optimal N management could increase grain yields and the NUE in the NCP. PMID:28234970

Optimization of sample preparation variables for wedelolactone from Eclipta alba using Box-Behnken experimental design followed by HPLC identification.

PubMed

Patil, A A; Sachin, B S; Shinde, D B; Wakte, P S

2013-07-01

Coumestan wedelolactone is an important phytocomponent from Eclipta alba (L.) Hassk. It possesses diverse pharmacological activities, which have prompted the development of various extraction techniques and strategies for its better utilization. The aim of the present study is to develop and optimize supercritical carbon dioxide assisted sample preparation and HPLC identification of wedelolactone from E. alba (L.) Hassk. The response surface methodology was employed to study the optimization of sample preparation using supercritical carbon dioxide for wedelolactone from E. alba (L.) Hassk. The optimized sample preparation involves the investigation of quantitative effects of sample preparation parameters viz. operating pressure, temperature, modifier concentration and time on yield of wedelolactone using Box-Behnken design. The wedelolactone content was determined using validated HPLC methodology. The experimental data were fitted to second-order polynomial equation using multiple regression analysis and analyzed using the appropriate statistical method. By solving the regression equation and analyzing 3D plots, the optimum extraction conditions were found to be: extraction pressure, 25 MPa; temperature, 56 °C; modifier concentration, 9.44% and extraction time, 60 min. Optimum extraction conditions demonstrated wedelolactone yield of 15.37 ± 0.63 mg/100 g E. alba (L.) Hassk, which was in good agreement with the predicted values. Temperature and modifier concentration showed significant effect on the wedelolactone yield. The supercritical carbon dioxide extraction showed higher selectivity than the conventional Soxhlet assisted extraction method. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

The MORPHEUS II protein crystallization screen

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

Gorrec, Fabrice, E-mail: fgorrec@mrc-lmb.cam.ac.uk

2015-06-27

MORPHEUS II is a 96-condition initial crystallization screen formulated de novo. The screen incorporates reagents selected from the Protein Data Bank to yield crystals that are not observed in traditional conditions. In addition, the formulation facilitates the optimization and cryoprotection of crystals. High-quality macromolecular crystals are a prerequisite for the process of protein structure determination by X-ray diffraction. Unfortunately, the relative yield of diffraction-quality crystals from crystallization experiments is often very low. In this context, innovative crystallization screen formulations are continuously being developed. In the past, MORPHEUS, a screen in which each condition integrates a mix of additives selected frommore » the Protein Data Bank, a cryoprotectant and a buffer system, was developed. Here, MORPHEUS II, a follow-up to the original 96-condition initial screen, is described. Reagents were selected to yield crystals when none might be observed in traditional initial screens. Besides, the screen includes heavy atoms for experimental phasing and small polyols to ensure the cryoprotection of crystals. The suitability of the resulting novel conditions is shown by the crystallization of a broad variety of protein samples and their efficiency is compared with commercially available conditions.« less

From biomass to chemicals: synthesis of precursors of biodegradable surfactants from 5-hydroxymethylfurfural.

PubMed

Arias, K S; Al-Resayes, Saud I; Climent, Maria J; Corma, Avelino; Iborra, Sara

2013-01-01

The selective acetalization of 5-hydroxymethylfurfural (HMF) with long-chain alkyl alcohols has been performed to obtain precursors of molecules with surfactant properties. If direct acetalization of HMF with n-octanol is performed in the presence of strong acids (homogeneous and heterogeneous catalysts), an increase in etherification versus acetalization occurs. Beta zeolite catalyzes both reactions. However, if the acidity of a zeolite (Beta) was controlled by partial exchange of H(+) with Na(+), the dioctyl acetal of HMF can be achieved in 95% yield by transacetalization. It is possible to achieve a high yield in a very short reaction time through a two-step one-pot process, which includes the synthesis of the dimethyl acetal of HMF followed by transacetalization with n-octanol. The one-pot process could be extended to other alcohols that contain 6-12 carbon atoms to afford 87-98% yield of the corresponding dialkyl acetal with a selectivity higher than 96%. The optimized catalyst with an adequate Na content (1.5NaBeta) could be recycled without loss of activity or selectivity. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Photocatalytic reduction of CO2 to CO over copper decorated g-C3N4 nanosheets with enhanced yield and selectivity

NASA Astrophysics Data System (ADS)

Shi, Guodong; Yang, Lin; Liu, Zhuowen; Chen, Xiao; Zhou, Jianqing; Yu, Ying

2018-01-01

Photocatalytic reduction of CO2 to fuel has attracted considerable attention due to the consumption of fossil fuels and serious environmental problems. Although there are many photocatalysts reported for CO2 reduction, the improvement of activity and selectivity is still in great need of. In this work, a series of Cu nanoparticle decorated g-C3N4 nanosheets with different Cu loadings were fabricated by a facile secondary calcination and subsequent microwave hydrothermal method. The designed catalysts shown good photocatalytic activity and selectivity for CO2 reduction to CO. The optimal sample exhibited a 3-fold augmentation of the CO yield in comparison with pristine g-C3N4 under visible light. It is revealed that with the loading of Cu nanoparticles, the resulting photocatalyst possessed an improved charge carrier transfer and separation efficiency as well as increased surface reactive sites, resulting in a significant enhancement of CO yield. It is anticipated that the designed Cu/C3N4 photocatalyst may provide new insights for two dimensional layer materials and non-noble particles applied to CO2 reduction.

Enantioselective oxidative biaryl coupling reactions catalyzed by 1,5-diazadecalin metal complexes.

PubMed

Li, X; Yang, J; Kozlowski, M C

2001-04-19

[reaction: see text]. Chiral 1,5-diaza-cis-decalins have been examined as ligands in the enantioselective oxidative biaryl coupling of substituted 2-naphthol derivatives. Under the optimal conditions employing a 1,5-diaza-cis-decalin copper(I) iodide complex with oxygen as the oxidant, rapid and highly selective couplings could be achieved (90-93% ee, 85% yield).

Effect of Additives on Green Sand Molding Properties using Design of Experiments and Taguchi's Quality Loss Function - An Experimental Study

NASA Astrophysics Data System (ADS)

Desai, Bhagyashree; Mokashi, Pavani; Anand, R. L.; Burli, S. B.; Khandal, S. V.

2016-09-01

The experimental study aims to underseek the effect of various additives on the green sand molding properties as a particular combination of additives could yield desired sand properties. The input parameters (factors) selected were water and powder (Fly ash, Coconut shell and Tamarind) in three levels. Experiments were planned using design of experiments (DOE). On the basis of plans, experiments were conducted to understand the behavior of sand mould properties such as compression strength, shear strength, permeability number with various additives. From the experimental results it could be concluded that the factors have significant effect on the sand properties as P-value found to be less than 0.05 for all the cases studied. The optimization based on quality loss function was also performed. The study revealed that the quality loss associated with the tamarind powder was lesser compared to other additives selected for the study. The optimization based on quality loss function and the parametric analysis using ANOVA suggested that the tamarind powder of 8 gm per Kg of molding sand and moisture content of 7% yield better properties to obtain sound castings.

[Extraction Optimization of Rhizome of Curcuma longa by Response Surface Methodology and Support Vector Regression].

PubMed

Zhou, Pei-pei; Shan, Jin-feng; Jiang, Jian-lan

2015-12-01

To optimize the optimal microwave-assisted extraction method of curcuminoids from Curcuma longa. On the base of single factor experiment, the ethanol concentration, the ratio of liquid to solid and the microwave time were selected for further optimization. Support Vector Regression (SVR) and Central Composite Design-Response Surface Methodology (CCD) algorithm were utilized to design and establish models respectively, while Particle Swarm Optimization (PSO) was introduced to optimize the parameters of SVR models and to search optimal points of models. The evaluation indicator, the sum of curcumin, demethoxycurcumin and bisdemethoxycurcumin by HPLC, were used. The optimal parameters of microwave-assisted extraction were as follows: ethanol concentration of 69%, ratio of liquid to solid of 21 : 1, microwave time of 55 s. On those conditions, the sum of three curcuminoids was 28.97 mg/g (per gram of rhizomes powder). Both the CCD model and the SVR model were credible, for they have predicted the similar process condition and the deviation of yield were less than 1.2%.

A predictive machine learning approach for microstructure optimization and materials design

NASA Astrophysics Data System (ADS)

Liu, Ruoqian; Kumar, Abhishek; Chen, Zhengzhang; Agrawal, Ankit; Sundararaghavan, Veera; Choudhary, Alok

2015-06-01

This paper addresses an important materials engineering question: How can one identify the complete space (or as much of it as possible) of microstructures that are theoretically predicted to yield the desired combination of properties demanded by a selected application? We present a problem involving design of magnetoelastic Fe-Ga alloy microstructure for enhanced elastic, plastic and magnetostrictive properties. While theoretical models for computing properties given the microstructure are known for this alloy, inversion of these relationships to obtain microstructures that lead to desired properties is challenging, primarily due to the high dimensionality of microstructure space, multi-objective design requirement and non-uniqueness of solutions. These challenges render traditional search-based optimization methods incompetent in terms of both searching efficiency and result optimality. In this paper, a route to address these challenges using a machine learning methodology is proposed. A systematic framework consisting of random data generation, feature selection and classification algorithms is developed. Experiments with five design problems that involve identification of microstructures that satisfy both linear and nonlinear property constraints show that our framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.

Shifts in growth strategies reflect tradeoffs in cellular economics

PubMed Central

Molenaar, Douwe; van Berlo, Rogier; de Ridder, Dick; Teusink, Bas

2009-01-01

The growth rate-dependent regulation of cell size, ribosomal content, and metabolic efficiency follows a common pattern in unicellular organisms: with increasing growth rates, cell size and ribosomal content increase and a shift to energetically inefficient metabolism takes place. The latter two phenomena are also observed in fast growing tumour cells and cell lines. These patterns suggest a fundamental principle of design. In biology such designs can often be understood as the result of the optimization of fitness. Here we show that in basic models of self-replicating systems these patterns are the consequence of maximizing the growth rate. Whereas most models of cellular growth consider a part of physiology, for instance only metabolism, the approach presented here integrates several subsystems to a complete self-replicating system. Such models can yield fundamentally different optimal strategies. In particular, it is shown how the shift in metabolic efficiency originates from a tradeoff between investments in enzyme synthesis and metabolic yields for alternative catabolic pathways. The models elucidate how the optimization of growth by natural selection shapes growth strategies. PMID:19888218

Optimization conditions for extracting polysaccharide from Angelica sinensis and its antioxidant activities.

PubMed

Tian, Suyang; Hao, Changchun; Xu, Guangkuan; Yang, Juanjuan; Sun, Runguang

2017-10-01

In this study, polysaccharides from Angelica sinensis were extracted using the ultrasound-assisted extraction method. Based on the results of single factor experiments and orthogonal tests, three independent variables-water/raw material ratio, ultrasound time, and ultrasound power-were selected for investigation. Then, we used response surface methodology to optimize the extraction conditions. The experimental data were fitted to a quadratic equation using multiple regression analysis, and the optimal conditions were as follows: water/raw material ratio, 43.31 mL/g; ultrasonic time, 28.06 minutes; power, 396.83 W. Under such conditions, the polysaccharide yield was 21.89±0.21%, which was well matched with the predicted yield. In vitro assays, scavenging activity of superoxide anion radicals, hydroxyl radicals, and 2,2-diphenyl-1-picry-hydrazyl radical showed that polysaccharides had certain antioxidant activities and that hydroxyl radicals have a remarkable scavenging capability. Therefore, these studies provide reference for further research and rational development of A. sinensis polysaccharide. Copyright © 2016. Published by Elsevier B.V.

Conjunctive-use optimization model of the Mississippi River Valley alluvial aquifer of northeastern Arkansas

USGS Publications Warehouse

Czarnecki, John B.; Clark, Brian R.; Reed, Thomas B.

2003-01-01

The Mississippi River Valley alluvial aquifer is a water-bearing assemblage of gravels and sands that underlies about 32,000 square miles of Missouri, Kentucky, Tennessee, Mississippi, Louisiana, and Arkansas. Because of the heavy demands placed on the aquifer, several large cones of depression over 100 feet deep have formed in the potentiometric surface, resulting in lower well yields and degraded water quality in some areas. A ground-water flow model of the alluvial aquifer was previously developed for an area covering 14,104 square miles, extending northeast from the Arkansas River into the northeast corner of Arkansas and parts of southeastern Missouri. The flow model showed that continued ground-water withdrawals at rates commensurate with those of 1997 could not be sustained indefinitely without causing water levels to decline below half the original saturated thickness of the aquifer. To develop estimates of withdrawal rates that could be sustained in compliance with the constraints of critical ground-water area designation, conjunctive-use optimization modeling was applied to the flow model of the alluvial aquifer in northeastern Arkansas. Ground-water withdrawal rates form the basis for estimates of sustainable yield from the alluvial aquifer and from rivers specified within the alluvial aquifer model. A management problem was formulated as one of maximizing the sustainable yield from all ground-water and surface-water withdrawal cells within limits imposed by plausible withdrawal rates, and within specified constraints involving hydraulic head and streamflow. Steady-state flow conditions were selected because the maximized withdrawals are intended to represent sustainable yield of the system (a rate that can be maintained indefinitely). Within the optimization model, 11 rivers are specified. Surface-water diversion rates that occurred in 2000 were subtracted from specified overland flow at the appropriate river cells. Included in these diversions were the planned diversions of 63,339,248 ft3/d for the Bayou Meto project area and 55,078,367 ft3/d for the Grand Prairie project area, which factor in an additional 30 and 40 percent transmission loss, respectively. Streamflow constraints were specified at all 1,165 river cells based on average 7-day minimum flows for 10 years. Sustainable yield for all rivers ranged from 0 (Current, Little Red, and Bayou Meto Rivers) to almost 5 billion cubic feet per day for the Arkansas River. Total sustainable yield from all rivers combined was 12.8 billion cubic feet per day, which represents a substantial source for supplementing ground water to meet the total water demand. Sustainable-yield estimates are affected by the allowable upper limit on withdrawals from wells specified in the optimization model. Ground-water withdrawal rates were allowed to vary as much as 200 percent of the withdrawal rate in 1997. As the overall upper limit on withdrawals is increased, the sustainable yield generally increases. Tests with the optimization model show that without limits on pumping, wells adjacent to sources of water would have optimized withdrawal rates that were orders of magnitude larger than rates corresponding to those of 1997. The sustainable yield from ground water for the entire study area while setting the maximum upper limit as the amount withdrawn in 1997 is 360 million cubic feet per day, which is only about 57 percent of the amount withdrawn in 1997 (635.6 million cubic feet per day). Optimal sustainable yields from within the Bayou Meto irrigation project area and within the Grand Prairie irrigation project area are 18.1 and 9.1 million cubic feet per day, respectively, assuming a maximum allowable withdrawal rate equal to 1997 rates. These values of sustainable yield represent 35 and 30 percent respectively of the amount pumped from these project areas in 1997. Unmet demand (defined as the difference between the optimized withdrawal rate or sustainable yield, a

Modification of c and n sources for enhanced production of cyclosporin ‘a’ by Aspergillus Terreus

PubMed Central

Tanseer, Sundas; Anjum, Tehmina

2011-01-01

Most of the studies regarding cyclosporin ‘A’ production through fungi concentrate around Tolypocladium inflatum. This is mainly due to lower reported production of this drug in other fungi. The present study was therefore conducted to explore indigenous isolates of Aspergillus terreus for synthesis of this drug and defining a production medium for obtaining high yield of cyclosporin ‘A’. For this purpose carbon and nitrogen sources were optimized for the selected best strain of A. terreus. Overall results depicted that the best cyclosporin ‘A’ yield from selected Aspergillus terreus (FCBP58) could be obtained by using production medium containing glucose 10% as carbon source and peptone 0.5% as nitrogen source. This modification in production medium enhanced drug synthesis by selected fungi significantly. The production capabilities when compared with biomass of fungi there was found no relationship between the two confirming that the medium modification increased overall drug synthesis powers of the fungi. PMID:24031766

A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class.

PubMed

Ni, Qianwu; Chen, Lei

2017-01-01

Correct prediction of protein structural class is beneficial to investigation on protein functions, regulations and interactions. In recent years, several computational methods have been proposed in this regard. However, based on various features, it is still a great challenge to select proper classification algorithm and extract essential features to participate in classification. In this study, a feature and algorithm selection method was presented for improving the accuracy of protein structural class prediction. The amino acid compositions and physiochemical features were adopted to represent features and thirty-eight machine learning algorithms collected in Weka were employed. All features were first analyzed by a feature selection method, minimum redundancy maximum relevance (mRMR), producing a feature list. Then, several feature sets were constructed by adding features in the list one by one. For each feature set, thirtyeight algorithms were executed on a dataset, in which proteins were represented by features in the set. The predicted classes yielded by these algorithms and true class of each protein were collected to construct a dataset, which were analyzed by mRMR method, yielding an algorithm list. From the algorithm list, the algorithm was taken one by one to build an ensemble prediction model. Finally, we selected the ensemble prediction model with the best performance as the optimal ensemble prediction model. Experimental results indicate that the constructed model is much superior to models using single algorithm and other models that only adopt feature selection procedure or algorithm selection procedure. The feature selection procedure or algorithm selection procedure are really helpful for building an ensemble prediction model that can yield a better performance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Evaluation of commercial DNA and RNA extraction methods for high-throughput sequencing of FFPE samples.

PubMed

Kresse, Stine H; Namløs, Heidi M; Lorenz, Susanne; Berner, Jeanne-Marie; Myklebost, Ola; Bjerkehagen, Bodil; Meza-Zepeda, Leonardo A

2018-01-01

Nucleic acid material of adequate quality is crucial for successful high-throughput sequencing (HTS) analysis. DNA and RNA isolated from archival FFPE material are frequently degraded and not readily amplifiable due to chemical damage introduced during fixation. To identify optimal nucleic acid extraction kits, DNA and RNA quantity, quality and performance in HTS applications were evaluated. DNA and RNA were isolated from five sarcoma archival FFPE blocks, using eight extraction protocols from seven kits from three different commercial vendors. For DNA extraction, the truXTRAC FFPE DNA kit from Covaris gave higher yields and better amplifiable DNA, but all protocols gave comparable HTS library yields using Agilent SureSelect XT and performed well in downstream variant calling. For RNA extraction, all protocols gave comparable yields and amplifiable RNA. However, for fusion gene detection using the Archer FusionPlex Sarcoma Assay, the truXTRAC FFPE RNA kit from Covaris and Agencourt FormaPure kit from Beckman Coulter showed the highest percentage of unique read-pairs, providing higher complexity of HTS data and more frequent detection of recurrent fusion genes. truXTRAC simultaneous DNA and RNA extraction gave similar outputs as individual protocols. These findings show that although successful HTS libraries could be generated in most cases, the different protocols gave variable quantity and quality for FFPE nucleic acid extraction. Selecting the optimal procedure is highly valuable and may generate results in borderline quality specimens.

Evaluating Varied Label Designs for Use with Medical Devices: Optimized Labels Outperform Existing Labels in the Correct Selection of Devices and Time to Select.

PubMed

Bix, Laura; Seo, Do Chan; Ladoni, Moslem; Brunk, Eric; Becker, Mark W

2016-01-01

Effective standardization of medical device labels requires objective study of varied designs. Insufficient empirical evidence exists regarding how practitioners utilize and view labeling. Measure the effect of graphic elements (boxing information, grouping information, symbol use and color-coding) to optimize a label for comparison with those typical of commercial medical devices. Participants viewed 54 trials on a computer screen. Trials were comprised of two labels that were identical with regard to graphics, but differed in one aspect of information (e.g., one had latex, the other did not). Participants were instructed to select the label along a given criteria (e.g., latex containing) as quickly as possible. Dependent variables were binary (correct selection) and continuous (time to correct selection). Eighty-nine healthcare professionals were recruited at Association of Surgical Technologists (AST) conferences, and using a targeted e-mail of AST members. Symbol presence, color coding and grouping critical pieces of information all significantly improved selection rates and sped time to correct selection (α = 0.05). Conversely, when critical information was graphically boxed, probability of correct selection and time to selection were impaired (α = 0.05). Subsequently, responses from trials containing optimal treatments (color coded, critical information grouped with symbols) were compared to two labels created based on a review of those commercially available. Optimal labels yielded a significant positive benefit regarding the probability of correct choice ((P<0.0001) LSM; UCL, LCL: 97.3%; 98.4%, 95.5%)), as compared to the two labels we created based on commercial designs (92.0%; 94.7%, 87.9% and 89.8%; 93.0%, 85.3%) and time to selection. Our study provides data regarding design factors, namely: color coding, symbol use and grouping of critical information that can be used to significantly enhance the performance of medical device labels.

Adaptive Modeling Procedure Selection by Data Perturbation.

PubMed

Zhang, Yongli; Shen, Xiaotong

2015-10-01

Many procedures have been developed to deal with the high-dimensional problem that is emerging in various business and economics areas. To evaluate and compare these procedures, modeling uncertainty caused by model selection and parameter estimation has to be assessed and integrated into a modeling process. To do this, a data perturbation method estimates the modeling uncertainty inherited in a selection process by perturbing the data. Critical to data perturbation is the size of perturbation, as the perturbed data should resemble the original dataset. To account for the modeling uncertainty, we derive the optimal size of perturbation, which adapts to the data, the model space, and other relevant factors in the context of linear regression. On this basis, we develop an adaptive data-perturbation method that, unlike its nonadaptive counterpart, performs well in different situations. This leads to a data-adaptive model selection method. Both theoretical and numerical analysis suggest that the data-adaptive model selection method adapts to distinct situations in that it yields consistent model selection and optimal prediction, without knowing which situation exists a priori. The proposed method is applied to real data from the commodity market and outperforms its competitors in terms of price forecasting accuracy.

Global Optimization of Emergency Evacuation Assignments

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

Han, Lee; Yuan, Fang; Chin, Shih-Miao

2006-01-01

Conventional emergency evacuation plans often assign evacuees to fixed routes or destinations based mainly on geographic proximity. Such approaches can be inefficient if the roads are congested, blocked, or otherwise dangerous because of the emergency. By not constraining evacuees to prespecified destinations, a one-destination evacuation approach provides flexibility in the optimization process. We present a framework for the simultaneous optimization of evacuation-traffic distribution and assignment. Based on the one-destination evacuation concept, we can obtain the optimal destination and route assignment by solving a one-destination traffic-assignment problem on a modified network representation. In a county-wide, large-scale evacuation case study, the one-destinationmore » model yields substantial improvement over the conventional approach, with the overall evacuation time reduced by more than 60 percent. More importantly, emergency planners can easily implement this framework by instructing evacuees to go to destinations that the one-destination optimization process selects.« less

Improving predicted protein loop structure ranking using a Pareto-optimality consensus method.

PubMed

Li, Yaohang; Rata, Ionel; Chiu, See-wing; Jakobsson, Eric

2010-07-20

Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction. We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy dominance relationship to the rest of the models. We apply the POC method to a large number of decoy sets for loops of 4- to 12-residue in length using a functional space composed of several carefully-selected scoring functions: Rosetta, DOPE, DDFIRE, OPLS-AA, and a triplet backbone dihedral potential developed in our lab. Our computational results show that the sets of Pareto-optimal decoys, which are typically composed of approximately 20% or less of the overall decoys in a set, have a good coverage of the best or near-best decoys in more than 99% of the loop targets. Compared to the individual scoring function yielding best selection accuracy in the decoy sets, the POC method yields 23%, 37%, and 64% less false positives in distinguishing the native conformation, indentifying a near-native model (RMSD < 0.5A from the native) as top-ranked, and selecting at least one near-native model in the top-5-ranked models, respectively. Similar effectiveness of the POC method is also found in the decoy sets from membrane protein loops. Furthermore, the POC method outperforms the other popularly-used consensus strategies in model ranking, such as rank-by-number, rank-by-rank, rank-by-vote, and regression-based methods. By integrating multiple knowledge- and physics-based scoring functions based on Pareto optimality and fuzzy dominance, the POC method is effective in distinguishing the best loop models from the other ones within a loop model set.

Improving predicted protein loop structure ranking using a Pareto-optimality consensus method

PubMed Central

2010-01-01

Background Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction. Results We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy dominance relationship to the rest of the models. We apply the POC method to a large number of decoy sets for loops of 4- to 12-residue in length using a functional space composed of several carefully-selected scoring functions: Rosetta, DOPE, DDFIRE, OPLS-AA, and a triplet backbone dihedral potential developed in our lab. Our computational results show that the sets of Pareto-optimal decoys, which are typically composed of ~20% or less of the overall decoys in a set, have a good coverage of the best or near-best decoys in more than 99% of the loop targets. Compared to the individual scoring function yielding best selection accuracy in the decoy sets, the POC method yields 23%, 37%, and 64% less false positives in distinguishing the native conformation, indentifying a near-native model (RMSD < 0.5A from the native) as top-ranked, and selecting at least one near-native model in the top-5-ranked models, respectively. Similar effectiveness of the POC method is also found in the decoy sets from membrane protein loops. Furthermore, the POC method outperforms the other popularly-used consensus strategies in model ranking, such as rank-by-number, rank-by-rank, rank-by-vote, and regression-based methods. Conclusions By integrating multiple knowledge- and physics-based scoring functions based on Pareto optimality and fuzzy dominance, the POC method is effective in distinguishing the best loop models from the other ones within a loop model set. PMID:20642859

Harvests from bone marrow donors who weigh less than their recipients are associated with a significantly increased probability of a suboptimal harvest yield.

PubMed

Anthias, Chloe; Billen, Annelies; Arkwright, Rebecca; Szydlo, Richard M; Madrigal, J Alejandro; Shaw, Bronwen E

2016-05-01

Previous studies have demonstrated the importance of bone marrow (BM) harvest yield in determining transplant outcomes, but little is known regarding donor and procedure variables associated with achievement of an optimal yield. We hypothesized that donor demographics and variables relating to the procedure were likely to impact the yield (total nucleated cells [TNCs]/kg recipient weight) and quality (TNCs/mL) of the harvest. To test our hypothesis, BM harvests of 110 consecutive unrelated donors were evaluated. The relationship between donor or procedure characteristics and the BM harvest yield was examined. The relationship between donor and recipient weight significantly influenced the harvest yield; only 14% of BM harvests from donors who weighed less than their recipient achieved a TNC count of more than 4 × 10(8) /kg compared to 56% of harvests from donors heavier than their recipient (p = 0.001). Higher-volume harvests were significantly less likely to achieve an optimal yield than lower-volume harvests (32% vs. 78%; p = 0.007), and higher-volume harvests contained significantly fewer TNCs/mL, indicating peripheral blood contamination. BM harvest quality also varied significantly between collection centers adding to recent concerns regarding maintenance of BM harvest expertise within the transplant community. Since the relationship between donor and recipient weight has a critical influence yield, we recommend prioritizing this secondary donor characteristic when selecting from multiple well-matched donors. Given the declining number of requests for BM harvests, it is crucial that systems are developed to train operators and ensure expertise in this procedure is retained. © 2016 AABB.

Efficient production of soluble recombinant single chain Fv fragments by a Pseudomonas putida strain KT2440 cell factory.

PubMed

Dammeyer, Thorben; Steinwand, Miriam; Krüger, Sarah-C; Dübel, Stefan; Hust, Michael; Timmis, Kenneth N

2011-02-21

Recombinant antibody fragments have a wide range of applications in research, diagnostics and therapy. For many of these, small fragments like single chain fragment variables (scFv) function well and can be produced inexpensively in bacterial expression systems. Although Escherichia coli K-12 production systems are convenient, yields of different fragments, even those produced from codon-optimized expression systems, vary significantly. Where yields are inadequate, alternative production systems are needed. Pseudomonas putida strain KT2440 is a versatile biosafety strain known for good expression of heterologous genes, so we have explored its utility as a cell factory for production of scFvs. We have generated new broad host range scFv expression constructs and assessed their production in the Pseudomonas putida KT2440 host. Two scFvs bind either to human C-reactive protein or to mucin1, proteins of significant medical diagnostic and therapeutic interest, whereas a third is a model anti-lysozyme scFv. The KT2440 antibody expression systems produce scFvs targeted to the periplasmic space that were processed precisely and were easily recovered and purified by single-step or tandem affinity chromatography. The influence of promoter system, codon optimization for P. putida, and medium on scFv yield was examined. Yields of up to 3.5 mg/l of pure, soluble, active scFv fragments were obtained from shake flask cultures of constructs based on the original codon usage and expressed from the Ptac expression system, yields that were 2.5-4 times higher than those from equivalent cultures of an E. coli K-12 expression host. Pseudomonas putida KT2440 is a good cell factory for the production of scFvs, and the broad host range constructs we have produced allow yield assessment in a number of different expression hosts when yields in one initially selected are insufficient. High cell density cultivation and further optimization and refinement of the KT2440 cell factory will achieve additional increases in the yields of scFvs.

Conjunctive-use optimization model of the Mississippi River Valley alluvial aquifer of Southeastern Arkansas

USGS Publications Warehouse

Czarnecki, John B.; Clark, Brian R.; Stanton, Gregory P.

2003-01-01

The Mississippi River Valley alluvial aquifer is a water-bearing assemblage of gravels and sands that underlies about 32,000 square miles of Missouri, Kentucky, Tennessee, Mississippi, Louisiana, and Arkansas. Because of the heavy demands placed on the aquifer, several large cones of depression have formed in the potentiometric surface, resulting in lower well yields and degraded water quality in some areas. A ground-water flow model of the alluvial aquifer was previously developed for an area covering 3,826 square miles, extending south from the Arkansas River into the southeastern corner of Arkansas, parts of northeastern Louisiana, and western Mississippi. The flow-model results indicated that continued ground-water withdrawals at rates commensurate with those of 1997 could not be sustained indefinitely without causing water levels to decline below half the original saturated thickness of the aquifer. Conjunctive-use optimization modeling was applied to the flow model of the alluvial aquifer to develop withdrawal rates that could be sustained relative to the constraints of critical ground-water area designation. These withdrawal rates form the basis for estimates of sustainable yield from the alluvial aquifer and from rivers specified within the alluvial aquifer model. A management problem was formulated as one of maximizing the sustainable yield from all ground-water and surface-water withdrawal cells within limits imposed by plausible withdrawal rates, and within specified constraints involving hydraulic head and streamflow. Steady-state conditions were selected because the maximized withdrawals are intended to represent sustainable yield of the system (a rate that can be maintained indefinitely).One point along the Arkansas River and one point along Bayou Bartholomew were specified for obtaining surface-water sustainable-yield estimates within the optimization model. Streamflow constraints were specified at two river cells based on average 7-day low flows with 10-year recurrence intervals. Sustainable-yield estimates were affected by the allowable upper limit on withdrawals from wells specified in the optimization model. Withdrawal rates were allowed to increase to 200 percent of the withdrawal rate in 1997. As the overall upper limit is increased, the sustainable yield generally increases. Tests with the optimization model show that without limits on pumping, wells adjacent to sources of water, such as large rivers, would have optimal withdrawal rates that were orders of magnitude larger than rates corresponding to those of 1997. Specifying an upper withdrawal limit of 100 percent of the 1997 withdrawal rate, the sustainable yield from ground water for the entire study area is 70.3 million cubic feet per day, which is about 96 percent of the amount withdrawn in 1997 (73.5 million cubic feet per day). If the upper withdrawal limit is increased to 150 percent of the 1997 withdrawal rate, the sustainable yield from ground water for the entire study area is 80.6 million cubic feet per day, which is about 110 percent of the amount withdrawn in 1997. If the upper withdrawal limit is increased to 200 percent of the 1997 withdrawal rate, the sustainable yield from ground water for the entire study area is 110.2 million cubic feet per day, which is about 150 percent of the amount withdrawn in 1997. Total sustainable yield from the Arkansas River and Bayou Bartholomew is about 4,900 million cubic feet per day, or about 6,700 percent of the amount of ground-water withdrawn in 1997. The large, sustainable yields from surface water represent a potential source of water that could supplement ground water and meet the total water demand. Unmet demand (defined as the difference between the optimized withdrawal rate or sustainable yield, and the anticipated demand) was calculated using different demand rates based on multiples of the 1997-withdrawal rate. Assuming that demand is the 1997 withdrawal rate, and that sustainable-

150-nm DR contact holes die-to-database inspection

NASA Astrophysics Data System (ADS)

Kuo, Shen C.; Wu, Clare; Eran, Yair; Staud, Wolfgang; Hemar, Shirley; Lindman, Ofer

2000-07-01

Using a failure analysis-driven yield enhancements concept, based on an optimization of the mask manufacturing process and UV reticle inspection is studied and shown to improve the contact layer quality. This is achieved by relating various manufacturing processes to very fine tuned contact defect detection. In this way, selecting an optimized manufacturing process with fine-tuned inspection setup is achieved in a controlled manner. This paper presents a study, performed on a specially designed test reticle, which simulates production contact layers of design rule 250nm, 180nm and 150nm. This paper focuses on the use of advanced UV reticle inspection techniques as part of the process optimization cycle. Current inspection equipment uses traditional and insufficient methods of small contact-hole inspection and review.

Optimization of individualized graft composition: CD3/CD19 depletion combined with CD34 selection for haploidentical transplantation.

PubMed

Huenecke, Sabine; Bremm, Melanie; Cappel, Claudia; Esser, Ruth; Quaiser, Andrea; Bonig, Halvard; Jarisch, Andrea; Soerensen, Jan; Klingebiel, Thomas; Bader, Peter; Koehl, Ulrike

2016-09-01

Excessive T-cell depletion (TCD) is a prerequisite for graft manufacturing in haploidentical stem cell (SC) transplantation by using either CD34 selection or direct TCD such as CD3/CD19 depletion. To optimize graft composition we compared 1) direct or indirect TCD only, 2) a combination of CD3/CD19-depleted with CD34-selected grafts, or 3) TCD twice for depletion improvement based on our 10-year experience with 320 separations in graft manufacturing and quality control. SC recovery was significantly higher (85%, n = 187 vs. 73%, n = 115; p < 0.0001), but TCD was inferior (median log depletion, -3.6 vs. -5.2) for CD3/CD19 depletion compared to CD34 selection, respectively. For end products with less than -2.5 log TCD, a second depletion step led to a successful improvement in TCD. Thawing of grafts showed a high viability and recovery of SCs, but low NK-cell yield. To optimize individualized graft engineering, a calculator was developed to estimate the results of the final graft based on the content of CD34+ and CD3+ cells in the leukapheresis product. Finally, calculated splitting of the starting product followed by CD3/19 depletion together with CD34+ graft manipulation may enable the composition of optimized grafts with high CD34+-cell and minimal T-cell content. © 2016 AABB.

Optimizing rice yields while minimizing yield-scaled global warming potential.

PubMed

Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

2014-05-01

To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

Method for the rapid synthesis of large quantities of metal oxide nanowires at low temperatures

DOEpatents

Sunkara, Mahendra Kumar [Louisville, KY; Vaddiraju, Sreeram [Mountain View, CA; Mozetic, Miran [Ljubljan, SI; Cvelbar, Uros [Idrija, SI

2009-09-22

A process for the rapid synthesis of metal oxide nanoparticles at low temperatures and methods which facilitate the fabrication of long metal oxide nanowires. The method is based on treatment of metals with oxygen plasma. Using oxygen plasma at low temperatures allows for rapid growth unlike other synthesis methods where nanomaterials take a long time to grow. Density of neutral oxygen atoms in plasma is a controlling factor for the yield of nanowires. The oxygen atom density window differs for different materials. By selecting the optimal oxygen atom density for various materials the yield can be maximized for nanowire synthesis of the metal.

Bispecific small molecule-antibody conjugate targeting prostate cancer.

PubMed

Kim, Chan Hyuk; Axup, Jun Y; Lawson, Brian R; Yun, Hwayoung; Tardif, Virginie; Choi, Sei Hyun; Zhou, Quan; Dubrovska, Anna; Biroc, Sandra L; Marsden, Robin; Pinstaff, Jason; Smider, Vaughn V; Schultz, Peter G

2013-10-29

Bispecific antibodies, which simultaneously target CD3 on T cells and tumor-associated antigens to recruit cytotoxic T cells to cancer cells, are a promising new approach to the treatment of hormone-refractory prostate cancer. Here we report a site-specific, semisynthetic method for the production of bispecific antibody-like therapeutics in which a derivative of the prostate-specific membrane antigen-binding small molecule DUPA was selectively conjugated to a mutant αCD3 Fab containing the unnatural amino acid, p-acetylphenylalanine, at a defined site. Homogeneous conjugates were generated in excellent yields and had good solubility. The efficacy of the conjugate was optimized by modifying the linker structure, relative binding orientation, and stoichiometry of the ligand. The optimized conjugate showed potent and selective in vitro activity (EC50 ~ 100 pM), good serum half-life, and potent in vivo activity in prophylactic and treatment xenograft mouse models. This semisynthetic approach is likely to be applicable to the generation of additional bispecific agents using drug-like ligands selective for other cell-surface receptors.

Optimized bioregenerative space diet selection with crew choice

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Enhancement in multiple lignolytic enzymes production for optimized lignin degradation and selectivity in fungal pretreatment of sweet sorghum bagasse.

PubMed

Mishra, Vartika; Jana, Asim K; Jana, Mithu Maiti; Gupta, Antriksh

2017-07-01

The objective of this work was to study the increase in multiple lignolytic enzyme productions through the use of supplements in combination in pretreatment of sweet sorghum bagasse (SSB) by Coriolus versicolor such that enzymes act synergistically to maximize the lignin degradation and selectivity. Enzyme activities were enhanced by metallic salts and phenolic compound supplements in SSF. Supplement of syringic acid increased the activities of LiP, AAO and laccase; gallic acid increased MnP; CuSO 4 increased laccase and PPO to improve the lignin degradations and selectivity individually, higher than control. Combination of supplements optimized by RSM increased the production of laccase, LiP, MnP, PPO and AAO by 17.2, 45.5, 3.5, 2.4 and 3.6 folds respectively for synergistic action leading to highest lignin degradation (2.3 folds) and selectivity (7.1 folds). Enzymatic hydrolysis of pretreated SSB yielded ∼2.43 times fermentable sugar. This technique could be widely applied for pretreatment and enzyme productions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Are extraction methods in quantitative assays of pharmacopoeia monographs exhaustive? A comparison with pressurized liquid extraction.

PubMed

Basalo, Carlos; Mohn, Tobias; Hamburger, Matthias

2006-10-01

The extraction methods in selected monographs of the European and the Swiss Pharmacopoeia were compared to pressurized liquid extraction (PLE) with respect to the yield of constituents to be dosed in the quantitative assay for the respective herbal drugs. The study included five drugs, Belladonnae folium, Colae semen, Boldo folium, Tanaceti herba and Agni casti fructus. They were selected to cover different classes of compounds to be analyzed and different extraction methods to be used according to the monographs. Extraction protocols for PLE were optimized by varying the solvents and number of extraction cycles. In PLE, yields > 97 % of extractable analytes were typically achieved with two extraction cycles. For alkaloid-containing drugs, the addition of ammonia prior to extraction significantly increased the yield and reduced the number of extraction cycles required for exhaustive extraction. PLE was in all cases superior to the extraction protocol of the pharmacopoeia monographs (taken as 100 %), with differences ranging from 108 % in case of parthenolide in Tanaceti herba to 343 % in case of alkaloids in Boldo folium.

Optimizing carbon efficiency of jet fuel range alkanes from cellulose co-fed with polyethylene via catalytically combined processes.

PubMed

Zhang, Xuesong; Lei, Hanwu; Zhu, Lei; Zhu, Xiaolu; Qian, Moriko; Yadavalli, Gayatri; Yan, Di; Wu, Joan; Chen, Shulin

2016-08-01

Enhanced carbon yields of renewable alkanes for jet fuels were obtained through the catalytic microwave-induced co-pyrolysis and hydrogenation process. The well-promoted ZSM-5 catalyst had high selectivity toward C8-C16 aromatic hydrocarbons. The raw organics with improved carbon yield (∼44%) were more principally lumped in the jet fuel range at the catalytic temperature of 375°C with the LDPE to cellulose (representing waste plastics to lignocellulose) mass ratio of 0.75. It was also observed that the four species of raw organics from the catalytic microwave co-pyrolysis were almost completely converted into saturated hydrocarbons; the hydrogenation process was conducted in the n-heptane medium by using home-made Raney Ni catalyst under a low-severity condition. The overall carbon yield (with regards to co-reactants of cellulose and LDPE) of hydrogenated organics that mostly match jet fuels was sustainably enhanced to above 39%. Meanwhile, ∼90% selectivity toward jet fuel range alkanes was attained. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimizing catalysis conditions to decrease aromatic hydrocarbons and increase alkanes for improving jet biofuel quality.

PubMed

Cheng, Jun; Li, Tao; Huang, Rui; Zhou, Junhu; Cen, Kefa

2014-04-01

To produce quality jet biofuel with high amount of alkanes and low amount of aromatic hydrocarbons, two zeolites of HY and HZSM-5 supporting Ni and Mo were used as catalysts to convert soybean oil into jet fuel. Zeolite HY exhibited higher jet range alkane selectivity (40.3%) and lower jet range aromatic hydrocarbon selectivity (23.8%) than zeolite HZSM-5 (13.8% and 58.9%). When reaction temperature increased from 330 to 390°C, yield of jet fuel over Ni-Mo/HY catalyst at 4 MPa hydrogen pressure increased from 0% to 49.1% due to the shift of reaction pathway from oligomerization to cracking reaction. Further increase of reaction temperature from 390 to 410°C resulted in increased yield of jet range aromatic hydrocarbons from 18.7% to 30%, which decreased jet fuel quality. A high yield of jet fuel (48.2%) was obtained at 1 MPa low hydrogen pressure over Ni (8 wt.%)-Mo (12 wt.%)/HY catalyst. Copyright © 2014 Elsevier Ltd. All rights reserved.

Switches in Genomic GC Content Drive Shifts of Optimal Codons under Sustained Selection on Synonymous Sites

PubMed Central

Sun, Yu; Tamarit, Daniel

2017-01-01

Abstract The major codon preference model suggests that codons read by tRNAs in high concentrations are preferentially utilized in highly expressed genes. However, the identity of the optimal codons differs between species although the forces driving such changes are poorly understood. We suggest that these questions can be tackled by placing codon usage studies in a phylogenetic framework and that bacterial genomes with extreme nucleotide composition biases provide informative model systems. Switches in the background substitution biases from GC to AT have occurred in Gardnerella vaginalis (GC = 32%), and from AT to GC in Lactobacillus delbrueckii (GC = 62%) and Lactobacillus fermentum (GC = 63%). We show that despite the large effects on codon usage patterns by these switches, all three species evolve under selection on synonymous sites. In G. vaginalis, the dramatic codon frequency changes coincide with shifts of optimal codons. In contrast, the optimal codons have not shifted in the two Lactobacillus genomes despite an increased fraction of GC-ending codons. We suggest that all three species are in different phases of an on-going shift of optimal codons, and attribute the difference to a stronger background substitution bias and/or longer time since the switch in G. vaginalis. We show that comparative and correlative methods for optimal codon identification yield conflicting results for genomes in flux and discuss possible reasons for the mispredictions. We conclude that switches in the direction of the background substitution biases can drive major shifts in codon preference patterns even under sustained selection on synonymous codon sites. PMID:27540085

Does the choice of nucleotide substitution models matter topologically?

PubMed

Hoff, Michael; Orf, Stefan; Riehm, Benedikt; Darriba, Diego; Stamatakis, Alexandros

2016-03-24

In the context of a master level programming practical at the computer science department of the Karlsruhe Institute of Technology, we developed and make available an open-source code for testing all 203 possible nucleotide substitution models in the Maximum Likelihood (ML) setting under the common Akaike, corrected Akaike, and Bayesian information criteria. We address the question if model selection matters topologically, that is, if conducting ML inferences under the optimal, instead of a standard General Time Reversible model, yields different tree topologies. We also assess, to which degree models selected and trees inferred under the three standard criteria (AIC, AICc, BIC) differ. Finally, we assess if the definition of the sample size (#sites versus #sites × #taxa) yields different models and, as a consequence, different tree topologies. We find that, all three factors (by order of impact: nucleotide model selection, information criterion used, sample size definition) can yield topologically substantially different final tree topologies (topological difference exceeding 10 %) for approximately 5 % of the tree inferences conducted on the 39 empirical datasets used in our study. We find that, using the best-fit nucleotide substitution model may change the final ML tree topology compared to an inference under a default GTR model. The effect is less pronounced when comparing distinct information criteria. Nonetheless, in some cases we did obtain substantial topological differences.

A Practical Method for the Vinylation of Aromatic Halides using Inexpensive Organosilicon Reagents

PubMed Central

Denmark, Scott E.; Butler, Christopher R.

2009-01-01

The preparation of styrenes by palladium-catalyzed cross-coupling of aromatic iodides and bromides with divinyltetramethyldisiloxane (DVDS) in the presence of inexpensive silanolate activators has been developed. To facilitate the discovery of optimal reaction conditions, Design of Experiment protocols were used. By the guided selection of reagents, stoichiometries, temperatures, and solvents the vinylation reaction was rapidly optimized with three stages consisting of ca. 175 experiments (of a possible 1440 combinations). A variety of aromatic iodides undergo cross-coupling at room temperature in the presence of potassium trimethylsilanoate using Pd(dba)2 in DMF in good yields. Triphenylphosphine oxide is needed to extend catalyst lifetime. Application of these conditions to aryl bromides was accomplished by the development of two complementary protocols. First, the direct implementation of the successful reaction conditions using aryl iodides at elevated temperature in THF provided the corresponding styrenes in good to excellent yields. Alternatively, the use of potassium triethylsilanolate and a bulky “Buchwald-type” ligand allows for the vinylation reactions to occur at or just above room temperature. A wide range of bromides underwent coupling in good yields for each of the protocols described. PMID:18303892

High levels of bioplastic are produced in fertile transplastomic tobacco plants engineered with a synthetic operon for the production of polyhydroxybutyrate.

PubMed

Bohmert-Tatarev, Karen; McAvoy, Susan; Daughtry, Sean; Peoples, Oliver P; Snell, Kristi D

2011-04-01

An optimized genetic construct for plastid transformation of tobacco (Nicotiana tabacum) for the production of the renewable, biodegradable plastic polyhydroxybutyrate (PHB) was designed using an operon extension strategy. Bacterial genes encoding the PHB pathway enzymes were selected for use in this construct based on their similarity to the codon usage and GC content of the tobacco plastome. Regulatory elements with limited homology to the host plastome yet known to yield high levels of plastidial recombinant protein production were used to enhance the expression of the transgenes. A partial transcriptional unit, containing genes of the PHB pathway and a selectable marker gene encoding spectinomycin resistance, was flanked at the 5' end by the host plant's psbA coding sequence and at the 3' end by the host plant's 3' psbA untranslated region. This design allowed insertion of the transgenes into the plastome as an extension of the psbA operon, rendering the addition of a promoter to drive the expression of the transgenes unnecessary. Transformation of the optimized construct into tobacco and subsequent spectinomycin selection of transgenic plants yielded T0 plants that were capable of producing up to 18.8% dry weight PHB in samples of leaf tissue. These plants were fertile and produced viable seed. T1 plants producing up to 17.3% dry weight PHB in samples of leaf tissue and 8.8% dry weight PHB in the total biomass of the plant were also isolated.

A predictive machine learning approach for microstructure optimization and materials design

DOE PAGES

Liu, Ruoqian; Kumar, Abhishek; Chen, Zhengzhang; ...

2015-06-23

This paper addresses an important materials engineering question: How can one identify the complete space (or as much of it as possible) of microstructures that are theoretically predicted to yield the desired combination of properties demanded by a selected application? We present a problem involving design of magnetoelastic Fe-Ga alloy microstructure for enhanced elastic, plastic and magnetostrictive properties. While theoretical models for computing properties given the microstructure are known for this alloy, inversion of these relationships to obtain microstructures that lead to desired properties is challenging, primarily due to the high dimensionality of microstructure space, multi-objective design requirement and non-uniquenessmore » of solutions. These challenges render traditional search-based optimization methods incompetent in terms of both searching efficiency and result optimality. In this paper, a route to address these challenges using a machine learning methodology is proposed. A systematic framework consisting of random data generation, feature selection and classification algorithms is developed. In conclusion, experiments with five design problems that involve identification of microstructures that satisfy both linear and nonlinear property constraints show that our framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.« less

Structure-based design of Trifarotene (CD5789), a potent and selective RARγ agonist for the treatment of acne.

PubMed

Thoreau, Etienne; Arlabosse, Jean-Marie; Bouix-Peter, Claire; Chambon, Sandrine; Chantalat, Laurent; Daver, Sébastien; Dumais, Laurence; Duvert, Gwenaëlle; Feret, Angélique; Ouvry, Gilles; Pascau, Jonathan; Raffin, Catherine; Rodeville, Nicolas; Soulet, Catherine; Tabet, Samuel; Talano, Sandrine; Portal, Thibaud

2018-06-01

Retinoids have a dominant role in topical acne therapy and to date, only RARβ and RARγ dual agonists have reached the market. Given the tissue distribution of RAR isoforms, it was hypothesized that developing RARγ -selective agonists could yield a new generation of topical acne treatments that would increase safety margins while maintaining the robust efficacy of previous drugs. Structural knowledge derived from the X-ray structure of known γ-selective CD437, suggested the design of a novel triaryl series of agonists which was optimized and ultimately led to the discovery of Trifarotene/CD5789. Copyright © 2018 Elsevier Ltd. All rights reserved.

CANCER PHARMACOGENOMICS

PubMed Central

Paugh, SW; Stocco, G; McCorkle, JR; Diouf, B; Crews, KR; Evans, WE

2013-01-01

Pharmacogenomics research is yielding molecular diagnostic tools that can be used to optimize the selection of medications and their doses for individual patients. Given the narrow therapeutic index of most anticancer agents and the serious consequences of undertreatment, cancer chemotherapy is a compelling therapeutic area for translation of pharmacogenomics to the clinic. This review addresses how inherited (germline) and acquired (somatic) sources of genome variability can alter the toxicity or efficacy of cancer chemotherapy. PMID:21796115

Selective aerobic alcohol oxidation method for conversion of lignin into simple aromatic compounds

DOEpatents

Stahl, Shannon S; Rahimi, Alireza

2015-03-03

Described is a method to oxidize lignin or lignin sub-units. The method includes oxidation of secondary benzylic alcohol in the lignin or lignin sub-unit to a corresponding ketone in the presence of unprotected primarily aliphatic alcohol in the lignin or lignin sub-unit. The optimal catalyst system consists of HNO.sub.3 in combination with another Bronsted acid, in the absence of a metal-containing catalyst, thereby yielding a selectively oxidized lignin or lignin sub-unit. The method may be carried out in the presence or absence of additional reagents including TEMPO and TEMPO derivatives.

Protecting-group-free synthesis of amines: synthesis of primary amines from aldehydes via reductive amination.

PubMed

Dangerfield, Emma M; Plunkett, Catherine H; Win-Mason, Anna L; Stocker, Bridget L; Timmer, Mattie S M

2010-08-20

New methodology for the protecting-group-free synthesis of primary amines is presented. By optimizing the metal hydride/ammonia mediated reductive amination of aldehydes and hemiacetals, primary amines were selectively prepared with no or minimal formation of the usual secondary and tertiary amine byproduct. The methodology was performed on a range of functionalized aldehyde substrates, including in situ formed aldehydes from a Vasella reaction. These reductive amination conditions provide a valuable synthetic tool for the selective production of primary amines in fewer steps, in good yields, and without the use of protecting groups.

Efficient synthesis of hydroxystyrenes via biocatalytic decarboxylation/deacetylation of substituted cinnamic acids by newly isolated Pantoea agglomerans strains.

PubMed

Sharma, Upendra K; Sharma, Nandini; Salwan, Richa; Kumar, Rakesh; Kasana, Ramesh C; Sinha, Arun K

2012-02-01

Decarboxylation of substituted cinnamic acids is a predominantly followed pathway for obtaining hydroxystyrenes-one of the most extensively explored bioactive compounds in the food and flavor industry (e.g. FEMA GRAS approved 4-vinylguaiacol). For this, mild and green strategies providing good yields with high product selectivity are needed. Two newly isolated bacterial strains, i.e. Pantoea agglomerans KJLPB4 and P. agglomerans KJPB2, are reported for mild and effective decarboxylation of substituted cinnamic acids into corresponding hydroxystyrenes. Key operational parameters for the process, such as incubation temperature, incubation time, substrate concentration and effect of co-solvent, were optimized using ferulic acid as a model substrate. With strain KJLPB4, 1.51 g L⁻¹ 4-vinyl guaiacol (98% yield) was selectively obtained from 2 g L⁻¹ ferulic acid at 28 °C after 48 h incubation. However, KJPB2 provided vanillic acid in 85% yield after 72 h following the oxidative decarboxylation pathway. In addition, KJLPB4 was effectively exploited for the deacetylation of acetylated α-phenylcinnamic acids, providing corresponding compounds in 65-95% yields. Two newly isolated microbial strains are reported for the mild and selective decarboxylation of substituted cinnamic acids into hydroxystyrenes. Preparative-scale synthesis of vinyl guaiacol and utilization of renewable feedstock (ferulic acid extracted from maize bran) have been demonstrated to enhance the practical utility of the process. Copyright © 2011 Society of Chemical Industry.

Efficient estimation of the maximum metabolic productivity of batch systems.

PubMed

St John, Peter C; Crowley, Michael F; Bomble, Yannick J

2017-01-01

Production of chemicals from engineered organisms in a batch culture involves an inherent trade-off between productivity, yield, and titer. Existing strategies for strain design typically focus on designing mutations that achieve the highest yield possible while maintaining growth viability. While these methods are computationally tractable, an optimum productivity could be achieved by a dynamic strategy in which the intracellular division of resources is permitted to change with time. New methods for the design and implementation of dynamic microbial processes, both computational and experimental, have therefore been explored to maximize productivity. However, solving for the optimal metabolic behavior under the assumption that all fluxes in the cell are free to vary is a challenging numerical task. Previous studies have therefore typically focused on simpler strategies that are more feasible to implement in practice, such as the time-dependent control of a single flux or control variable. This work presents an efficient method for the calculation of a maximum theoretical productivity of a batch culture system using a dynamic optimization framework. The proposed method follows traditional assumptions of dynamic flux balance analysis: first, that internal metabolite fluxes are governed by a pseudo-steady state, and secondly that external metabolite fluxes are dynamically bounded. The optimization is achieved via collocation on finite elements, and accounts explicitly for an arbitrary number of flux changes. The method can be further extended to calculate the complete Pareto surface of productivity as a function of yield. We apply this method to succinate production in two engineered microbial hosts, Escherichia coli and Actinobacillus succinogenes , and demonstrate that maximum productivities can be more than doubled under dynamic control regimes. The maximum theoretical yield is a measure that is well established in the metabolic engineering literature and whose use helps guide strain and pathway selection. We present a robust, efficient method to calculate the maximum theoretical productivity: a metric that will similarly help guide and evaluate the development of dynamic microbial bioconversions. Our results demonstrate that nearly optimal yields and productivities can be achieved with only two discrete flux stages, indicating that near-theoretical productivities might be achievable in practice.

Exchange inlet optimization by genetic algorithm for improved RBCC performance

NASA Astrophysics Data System (ADS)

Chorkawy, G.; Etele, J.

2017-09-01

A genetic algorithm based on real parameter representation using a variable selection pressure and variable probability of mutation is used to optimize an annular air breathing rocket inlet called the Exchange Inlet. A rapid and accurate design method which provides estimates for air breathing, mixing, and isentropic flow performance is used as the engine of the optimization routine. Comparison to detailed numerical simulations show that the design method yields desired exit Mach numbers to within approximately 1% over 75% of the annular exit area and predicts entrained air massflows to between 1% and 9% of numerically simulated values depending on the flight condition. Optimum designs are shown to be obtained within approximately 8000 fitness function evaluations in a search space on the order of 106. The method is also shown to be able to identify beneficial values for particular alleles when they exist while showing the ability to handle cases where physical and aphysical designs co-exist at particular values of a subset of alleles within a gene. For an air breathing engine based on a hydrogen fuelled rocket an exchange inlet is designed which yields a predicted air entrainment ratio within 95% of the theoretical maximum.

Experimental design of a twin-column countercurrent gradient purification process.

PubMed

Steinebach, Fabian; Ulmer, Nicole; Decker, Lara; Aumann, Lars; Morbidelli, Massimo

2017-04-07

As typical for separation processes, single unit batch chromatography exhibits a trade-off between purity and yield. The twin-column MCSGP (multi-column countercurrent solvent gradient purification) process allows alleviating such trade-offs, particularly in the case of difficult separations. In this work an efficient and reliable procedure for the design of the twin-column MCSGP process is developed. This is based on a single batch chromatogram, which is selected as the design chromatogram. The derived MCSGP operation is not intended to provide optimal performance, but it provides the target product in the selected fraction of the batch chromatogram, but with higher yield. The design procedure is illustrated for the isolation of the main charge isoform of a monoclonal antibody from Protein A eluate with ion-exchange chromatography. The main charge isoform was obtained at a purity and yield larger than 90%. At the same time process related impurities such as HCP and leached Protein A as well as aggregates were at least equally well removed. Additionally, the impact of several design parameters on the process performance in terms of purity, yield, productivity and buffer consumption is discussed. The obtained results can be used for further fine-tuning of the process parameters so as to improve its performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining Mechanical Strength Characteristics of Selective Inhibition Sintered HDPE Specimens Using RSM and Desirability Approach

NASA Astrophysics Data System (ADS)

Rajamani, D.; Esakki, Balasubramanian

2017-09-01

Selective inhibition sintering (SIS) is a powder based additive manufacturing (AM) technique to produce functional parts with an inexpensive system compared with other AM processes. Mechanical properties of SIS fabricated parts are of high dependence on various process parameters importantly layer thickness, heat energy, heater feedrate, and printer feedrate. In this paper, examining the influence of these process parameters on evaluating mechanical properties such as tensile and flexural strength using Response Surface Methodology (RSM) is carried out. The test specimens are fabricated using high density polyethylene (HDPE) and mathematical models are developed to correlate the control factors to the respective experimental design response. Further, optimal SIS process parameters are determined using desirability approach to enhance the mechanical properties of HDPE specimens. Optimization studies reveal that, combination of high heat energy, low layer thickness, medium heater feedrate and printer feedrate yielded superior mechanical strength characteristics.

Application of Molecular Imprinted Magnetic Fe3O4@SiO2 Nanoparticles for Selective Immobilization of Cellulase.

PubMed

Tao, Qing-Lan; Li, Yue; Shi, Ying; Liu, Rui-Jiang; Zhang, Ye-Wang; Guo, Jianyong

2016-06-01

Magnetic Fe3O4@SiO2 nanoparticles were prepared with molecular imprinting method using cellulase as the template. And the surface of the nanoparticles was chemically modified with arginine. The prepared nanoparticles were used as support for specific immobilization of cellulase. SDS-PAGE results indicated that the adsorption of cellulase onto the modified imprinted nanoparticles was selective. The immobilization yield and efficiency were obtained more than 70% after the optimization. Characterization of the immobilized cellulase revealed that the immobilization didn't change the optimal pH and temperature. The half-life of the immobilized cellulase was 2-fold higher than that of the free enzyme at 50 degrees C. After 7 cycles reusing, the immobilized enzyme still retained 77% of the original activity. These results suggest that the prepared imprinted nanoparticles have the potential industrial applications for the purification or immobilization of enzymes.

Encoded library technology as a source of hits for the discovery and lead optimization of a potent and selective class of bactericidal direct inhibitors of Mycobacterium tuberculosis InhA.

PubMed

Encinas, Lourdes; O'Keefe, Heather; Neu, Margarete; Remuiñán, Modesto J; Patel, Amish M; Guardia, Ana; Davie, Christopher P; Pérez-Macías, Natalia; Yang, Hongfang; Convery, Maire A; Messer, Jeff A; Pérez-Herrán, Esther; Centrella, Paolo A; Alvarez-Gómez, Daniel; Clark, Matthew A; Huss, Sophie; O'Donovan, Gary K; Ortega-Muro, Fátima; McDowell, William; Castañeda, Pablo; Arico-Muendel, Christopher C; Pajk, Stane; Rullás, Joaquín; Angulo-Barturen, Iñigo; Alvarez-Ruíz, Emilio; Mendoza-Losana, Alfonso; Ballell Pages, Lluís; Castro-Pichel, Julia; Evindar, Ghotas

2014-02-27

Tuberculosis (TB) is one of the world's oldest and deadliest diseases, killing a person every 20 s. InhA, the enoyl-ACP reductase from Mycobacterium tuberculosis, is the target of the frontline antitubercular drug isoniazid (INH). Compounds that directly target InhA and do not require activation by mycobacterial catalase peroxidase KatG are promising candidates for treating infections caused by INH resistant strains. The application of the encoded library technology (ELT) to the discovery of direct InhA inhibitors yielded compound 7 endowed with good enzymatic potency but with low antitubercular potency. This work reports the hit identification, the selected strategy for potency optimization, the structure-activity relationships of a hundred analogues synthesized, and the results of the in vivo efficacy studies performed with the lead compound 65.

Emerging engineering principles for yield improvement in microbial cell design.

PubMed

Comba, Santiago; Arabolaza, Ana; Gramajo, Hugo

2012-01-01

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

Emerging engineering principles for yield improvement in microbial cell design

PubMed Central

Comba, Santiago; Arabolaza, Ana; Gramajo, Hugo

2012-01-01

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

Multi-objective LQR with optimum weight selection to design FOPID controllers for delayed fractional order processes.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu

2015-09-01

An optimal trade-off design for fractional order (FO)-PID controller is proposed with a Linear Quadratic Regulator (LQR) based technique using two conflicting time domain objectives. A class of delayed FO systems with single non-integer order element, exhibiting both sluggish and oscillatory open loop responses, have been controlled here. The FO time delay processes are handled within a multi-objective optimization (MOO) formalism of LQR based FOPID design. A comparison is made between two contemporary approaches of stabilizing time-delay systems withinLQR. The MOO control design methodology yields the Pareto optimal trade-off solutions between the tracking performance and total variation (TV) of the control signal. Tuning rules are formed for the optimal LQR-FOPID controller parameters, using median of the non-dominated Pareto solutions to handle delayed FO processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Wheat seed transcriptome reveals genes controlling key traits for human preference and crop adaptation.

PubMed

Henry, Robert J; Furtado, Agnelo; Rangan, Parimalan

2018-05-17

Analysis of the transcriptome of the developing wheat grain has associated expression of genes with traits involving production (e.g. yield) and quality (e.g. bread quality). Photosynthesis in the grain may be important in retaining carbon that would be lost in respiration during grain filling and may contribute to yield in the late stages of seed formation under warm and dry environments. A small number of genes have been identified as having been selected by humans to optimize the performance of wheat for foods such as bread. Genes determining flour yield in milling have been discovered. Hardness is explained by variations in expression of pin genes. Knowledge of these genes should dramatically improve the efficiency of breeding better climate adapted wheat genotypes. Copyright © 2018. Published by Elsevier Ltd.

Optimization of ultrasonic circulating extraction of samara oil from Acer saccharum using combination of Plackett-Burman design and Box-Behnken design.

PubMed

Chen, Fengli; Zhang, Qiang; Fei, Shimin; Gu, Huiyan; Yang, Lei

2017-03-01

In this study, ultrasonic circulating extraction (UCE) technique was firstly and successfully applied for extraction of samara oil from Acer saccharum. The extraction kinetics were fitted and described, and the extraction mechanism was discussed. Through comparison, n-hexane was selected as the extraction solvent, the influence of solvent type on the responses was detailedly interpreted based on the influence of their properties on the occurrence and intensity of cavitation. Seven parameters potentially influencing the extraction yield of samara oil and content of nervonic acid, including ultrasound irradiation time, ultrasound irradiation power, ultrasound temperature, liquid-solid ratio, soaking time, particle size and stirring rate, were screened through Plackett-Burman design to determine the significant variables. Then, three parameters performed statistically significant, including liquid-solid ratio, ultrasound irradiation time and ultrasound irradiation power, were further optimized using Box-Behnken design to predict optimum extraction conditions. Satisfactory yield of samara oil (11.72±0.38%) and content of nervonic acid (5.28±0.18%) were achieved using the optimal conditions. 1% proportion of ethanol in extraction solvent, 120°C of drying temperature and 6.4% moisture were selected and applied for effective extraction. There were no distinct differences in the physicochemical properties of samara oil obtained by UCE and Soxhlet extraction, and the samara oil obtained by UCE exhibited better antioxidant activities. Therefore, UCE method has enormous potential for efficient extraction of edible oil with high quality from plant materials. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistical optimization for enhanced yields of probiotic Bacillus coagulans and its phage resistant mutants followed by kinetic modelling of the process.

PubMed

Pandey, Kavita R; Joshi, Chetan; Vakil, Babu V

2016-01-01

Probiotics are microorganisms which when administered in adequate amounts confer health benefits to the host. A leading pharmaceutical company producing Bacillus coagulans as a probiotic was facing the problem of recurring phage attacks. Two mutants viz. B. co PIII and B. co MIII that were isolated as phage resistant mutants after UV irradiation and MMS treatment of phage sensitive B. coagulans parental culture were characterized at functional and molecular level and were noted to have undergone interesting genetic changes. The non-specific genetic alterations induced by mutagenesis can also lead to alterations in cell performance. Hence, in the current study the parental strain and the two mutants were selected for shake flask optimization. Plackett-Burman design was used to select the significant culture variables affecting biomass production. Evolutionary operation method was applied for further optimization. The study showed wide variations in the nutritional requirements of phage resistant mutants, post exposure to mutagens. An increment of 150, 134 and 152 % was observed in the biomass productions of B. coagulans (parental type) and mutants B.co PIII and B.co MIII respectively, compared to the yield from one-factor-at-a-time technique. Using Logistic and modified Leudeking-Piret equations, biomass accumulation and substrate utilization efficiency of the bioprocess were determined. The experimental data was in agreement with the results predicted by statistical analysis and modelling. The developed model may be useful for controlling the growth and substrate consumption kinetics in large scale fermentation using B. coagulans .

A study of metaheuristic algorithms for high dimensional feature selection on microarray data

NASA Astrophysics Data System (ADS)

Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

2017-11-01

Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

Critical design criteria for minimal antibiotic-free plasmid vectors necessary to combine robust RNA Pol II and Pol III-mediated eukaryotic expression with high bacterial production yields

PubMed Central

Carnes, Aaron E.; Luke, Jeremy M.; Vincent, Justin M.; Anderson, Sheryl; Schukar, Angela; Hodgson, Clague P.; Williams, James A.

2010-01-01

Background For safety considerations, regulatory agencies recommend elimination of antibiotic resistance markers and nonessential sequences from plasmid DNA-based gene medicines. In the present study we analyzed antibiotic-free (AF) vector design criteria impacting bacterial production and mammalian transgene expression. Methods Both CMV-HTLV-I R RNA Pol II promoter (protein transgene) and murine U6 RNA Pol III promoter (RNA transgene) vector designs were studied. Plasmid production yield was assessed through inducible fed-batch fermentation. RNA Pol II-directed EGFP and RNA Pol III-directed RNA expression were quantified by fluorometry and quantitative real-time polymerase chain reaction (RT-PCR), respectively, after transfection of human HEK293 cells. Results Sucrose-selectable minimalized protein and therapeutic RNA expression vector designs that combined an RNA-based AF selection with highly productive fermentation manufacturing (>1,000 mg/L plasmid DNA) and high level in vivo expression of encoded products were identified. The AF selectable marker was also successfully applied to convert existing kanamycin-resistant DNA vaccine plasmids gWIZ and pVAX1 into AF vectors, demonstrating a general utility for retrofitting existing vectors. A minimum vector size for high yield plasmid fermentation was identified. A strategy for stable fermentation of plasmid dimers with improved vector potency and fermentation yields up to 1,740 mg/L was developed. Conclusions We report the development of potent high yield AF gene medicine expression vectors for protein or RNA (e.g. short hairpin RNA or microRNA) products. These AF expression vectors were optimized to exceed a newly identified size threshold for high copy plasmid replication and direct higher transgene expression levels than alternative vectors. PMID:20806425

Chemically Adjusting Plasma Temperature, Energy and Reactivity (CAPTEAR) Method Using NOx and Combustion for Selective Synthesis of Sc3N@C80 Metallic Nitride Fullerenes

PubMed Central

Stevenson, Steven; Thompson, M. Corey; Coumbe, H. Louie; Mackey, Mary A.; Coumbe, Curtis E.; Phillips, J. Paige

2008-01-01

Goals are (1) to selectively synthesize MNFs in lieu of empty-cage fullerenes (e.g., C60, C70) without compromising MNF yield and (2) to test our hypothesis that MNFs possess a different set of optimal formation parameters than empty-cage fullerenes. In this work, we introduce a novel approach for the selective synthesis of metallic nitride fullerenes (MNFs). This new method is “Chemically Adjusting Plasma Temperature, Energy and Reactivity” (CAPTEAR). The CAPTEAR approach with copper nitrate hydrate uses NOx vapor from NOx generating solid reagents, air and combustion to “tune” the temperature, energy and reactivity of the plasma environment. The extent of temperature, energy and reactive environment is stoichiometrically varied until optimal conditions for selective MNF synthesis are achieved. Analysis of soot extracts indicate that percentages of C60 and Sc3N@C80 are inversely related, whereas the percentages of C70 and higher empty-cage C2n fullerenes are largely unaffected. Hence, there may be a “competitive link” in the formation and mechanism of C60 and Sc3N@C80. Using this CAPTEAR method, purified MNFs (96% Sc3N@C80, 12 mg) have been obtained in soot extracts without a significant penalty in milligram yield when compared to control soot extracts (4% Sc3N@C80, 13 mg Sc3N@C80). The CAPTEAR process with Cu(NO3)2·2.5 H2O uses an exothermic nitrate moiety to suppress empty-cage fullerene formation, whereas Cu functions as a catalyst additive to offset the reactive plasma environment and boost the Sc3N@C80 MNF production. PMID:18052069

Optimization and production of curdlan gum using Bacillus cereus PR3 isolated from rhizosphere of leguminous plant.

PubMed

Prakash, S; Rajeswari, K; Divya, P; Ferlin, M; Rajeshwari, C T; Vanavil, B

2018-05-28

Curdlan gum is a neutral water-insoluble bacterial exopolysaccharide composed primarily of linear β-(1,3) glycosidic linkages. Recently, there has been increasing interest in the applications of curdlan and its derivatives. Curdlan is found to inhibit tumors and its sulfated derivative possess anti-HIV activity. Curdlan is biodegradable, non-toxic towards human, environment and edible which makes it suitable as drug-delivery vehicles for sustained drug release. The increasing demand for the growing applications of curdlan requires an efficient high yield fermentation production process so as to satisfy the industrial needs. In this perspective, the present work is aimed to screen and isolate an efficient curdlan gum producing bacteria from rhizosphere of ground nut plant using aniline-blue agar. High yielding isolate was selected based on curdlan yield and identified as Bacillus cereus using gas-chromatography fatty acid methyl ester analysis. B. cereus PR3 curdlan gum was characterized using FT-IR spectroscopy, SEM, XRD and TGA. Fermentation time for curdlan production using B. cereus PR3 was optimized. Media constituents like carbon, nitrogen and mineral sources were screened using Plackett-Burman design. Subsequent statistical analysis revealed that Starch, NH 4 NO 3 , K 2 HPO 4 , Na 2 SO 4 , KH 2 SO 4 and CaCl 2 were significant media constituents and these concentrations were optimized for enhancement of curdlan production up to 20.88 g/l.

Energy-efficient growth of phage Q Beta in Escherichia coli.

PubMed

Kim, Hwijin; Yin, John

2004-10-20

The role of natural selection in the optimal design of organisms is controversial. Optimal forms, functions, or behaviors of organisms have long been claimed without knowledge of how genotype contributes to phenotype, delineation of design constraints, or reference to alternative designs. Moreover, arguments for optimal designs have been often based on models that were difficult, if not impossible, to test. Here, we begin to address these issues by developing and probing a kinetic model for the intracellular growth of bacteriophage Q beta in Escherichia coli. The model accounts for the energetic costs of all template-dependent polymerization reactions, in ATP equivalents, including RNA-dependent RNA elongation by the phage replicase and synthesis of all phage proteins by the translation machinery of the E. coli host cell. We found that translation dominated phage growth, requiring 85% of the total energy expenditure. Only 10% of the total energy was applied to activities other than the direct synthesis of progeny phage components, reflecting primarily the cost of making the negative-strand RNA template that is needed for replication of phage genomic RNA. Further, we defined an energy efficiency of phage growth and showed its direct relationship to the yield of phage progeny. Finally, we performed a sensitivity analysis and found that the growth of wild-type phage was optimized for progeny yield or energy efficiency, suggesting that phage Q beta has evolved to optimally utilize the finite resources of its host cells.

Optimization of a low-cost defined medium for alcoholic fermentation--a case study for potential application in bioethanol production from industrial wastewaters.

PubMed

Comelli, Raúl N; Seluy, Lisandro G; Isla, Miguel A

2016-01-25

In bioethanol production processes, the media composition has an impact on product concentration, yields and the overall process economics. The main purpose of this research was to develop a low-cost mineral-based supplement for successful alcoholic fermentation in an attempt to provide an economically feasible alternative to produce bioethanol from novel sources, for example, sugary industrial wastewaters. Statistical experimental designs were used to select essential nutrients for yeast fermentation, and its optimal concentrations were estimated by Response Surface Methodology. Fermentations were performed on synthetic media inoculated with 2.0 g L(-1) of yeast, and the evolution of biomass, sugar, ethanol, CO2 and glycerol were monitored over time. A mix of salts [10.6 g L(-1) (NH4)2HPO4; 6.4 g L(-1) MgSO4·7H2O and 7.5 mg L(-1) ZnSO4·7H2O] was found to be optimal. It led to the complete fermentation of the sugars in less than 12h with an average ethanol yield of 0.42 g ethanol/g sugar. A general C-balance indicated that no carbonaceous compounds different from biomass, ethanol, CO2 or glycerol were produced in significant amounts in the fermentation process. Similar results were obtained when soft drink wastewaters were tested to evaluate the potential industrial application of this supplement. The ethanol yields were very close to those obtained when yeast extract was used as the supplement, but the optimized mineral-based medium is six times cheaper, which favorably impacts the process economics and makes this supplement more attractive from an industrial viewpoint. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimization of the multi-turn injection efficiency for a medical synchrotron

NASA Astrophysics Data System (ADS)

Kim, J.; Yoon, M.; Yim, H.

2016-09-01

We present a method for optimizing the multi-turn injection efficiency for a medical synchrotron. We show that for a given injection energy, the injection efficiency can be greatly enhanced by choosing transverse tunes appropriately and by optimizing the injection bump and the number of turns required for beam injection. We verify our study by applying the method to the Korea Heavy Ion Medical Accelerator (KHIMA) synchrotron which is currently being built at the campus of Dongnam Institute of Radiological and Medical Sciences (DIRAMS) in Busan, Korea. First the frequency map analysis was performed with the help of the ELEGANT and the ACCSIM codes. The tunes that yielded good injection efficiency were then selected. With these tunes, the injection bump and the number of turns required for injection were then optimized by tracking a number of particles for up to one thousand turns after injection, beyond which no further beam loss occurred. Results for the optimization of the injection efficiency for proton ions are presented.

Adaptation, Growth, and Resilience in Biological Distribution Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.

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

Chen Qing; Department of Modern Physics, University of Science and Technology of China, Hefei 230026; Cheng Jianhua

In this paper we demonstrate that optimal 1{yields}M phase-covariant cloning quantum cloning is available via free dynamical evolution of spin networks. By properly designing the network and the couplings between spins, we show that optimal 1{yields}M phase-covariant cloning can be achieved if the initial state is prepared as a specific symmetric state. Especially, when M is an odd number, the optimal phase-covariant cloning can be achieved without ancillas. Moreover, we demonstrate that the same framework is capable for optimal 1{yields}2 universal cloning.

Assessing pretreatment reactor scaling through empirical analysis

DOE PAGES

Lischeske, James J.; Crawford, Nathan C.; Kuhn, Erik; ...

2016-10-10

Pretreatment is a critical step in the biochemical conversion of lignocellulosic biomass to fuels and chemicals. Due to the complexity of the physicochemical transformations involved, predictively scaling up technology from bench- to pilot-scale is difficult. This study examines how pretreatment effectiveness under nominally similar reaction conditions is influenced by pretreatment reactor design and scale using four different pretreatment reaction systems ranging from a 3 g batch reactor to a 10 dry-ton/d continuous reactor. The reactor systems examined were an Automated Solvent Extractor (ASE), Steam Explosion Reactor (SER), ZipperClave(R) reactor (ZCR), and Large Continuous Horizontal-Screw Reactor (LHR). To our knowledge, thismore » is the first such study performed on pretreatment reactors across a range of reaction conditions (time and temperature) and at different reactor scales. The comparative pretreatment performance results obtained for each reactor system were used to develop response surface models for total xylose yield after pretreatment and total sugar yield after pretreatment followed by enzymatic hydrolysis. Near- and very-near-optimal regions were defined as the set of conditions that the model identified as producing yields within one and two standard deviations of the optimum yield. Optimal conditions identified in the smallest-scale system (the ASE) were within the near-optimal region of the largest scale reactor system evaluated. A reaction severity factor modeling approach was shown to inadequately describe the optimal conditions in the ASE, incorrectly identifying a large set of sub-optimal conditions (as defined by the RSM) as optimal. The maximum total sugar yields for the ASE and LHR were 95%, while 89% was the optimum observed in the ZipperClave. The optimum condition identified using the automated and less costly to operate ASE system was within the very-near-optimal space for the total xylose yield of both the ZCR and the LHR, and was within the near-optimal space for total sugar yield for the LHR. This indicates that the ASE is a good tool for cost effectively finding near-optimal conditions for operating pilot-scale systems, which may be used as starting points for further optimization. Additionally, using a severity-factor approach to optimization was found to be inadequate compared to a multivariate optimization method. As a result, the ASE and the LHR were able to enable significantly higher total sugar yields after enzymatic hydrolysis relative to the ZCR, despite having similar optimal conditions and total xylose yields. This underscores the importance of incorporating mechanical disruption into pretreatment reactor designs to achieve high enzymatic digestibilities.« less

Assessing pretreatment reactor scaling through empirical analysis

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

Lischeske, James J.; Crawford, Nathan C.; Kuhn, Erik

Pretreatment is a critical step in the biochemical conversion of lignocellulosic biomass to fuels and chemicals. Due to the complexity of the physicochemical transformations involved, predictively scaling up technology from bench- to pilot-scale is difficult. This study examines how pretreatment effectiveness under nominally similar reaction conditions is influenced by pretreatment reactor design and scale using four different pretreatment reaction systems ranging from a 3 g batch reactor to a 10 dry-ton/d continuous reactor. The reactor systems examined were an Automated Solvent Extractor (ASE), Steam Explosion Reactor (SER), ZipperClave(R) reactor (ZCR), and Large Continuous Horizontal-Screw Reactor (LHR). To our knowledge, thismore » is the first such study performed on pretreatment reactors across a range of reaction conditions (time and temperature) and at different reactor scales. The comparative pretreatment performance results obtained for each reactor system were used to develop response surface models for total xylose yield after pretreatment and total sugar yield after pretreatment followed by enzymatic hydrolysis. Near- and very-near-optimal regions were defined as the set of conditions that the model identified as producing yields within one and two standard deviations of the optimum yield. Optimal conditions identified in the smallest-scale system (the ASE) were within the near-optimal region of the largest scale reactor system evaluated. A reaction severity factor modeling approach was shown to inadequately describe the optimal conditions in the ASE, incorrectly identifying a large set of sub-optimal conditions (as defined by the RSM) as optimal. The maximum total sugar yields for the ASE and LHR were 95%, while 89% was the optimum observed in the ZipperClave. The optimum condition identified using the automated and less costly to operate ASE system was within the very-near-optimal space for the total xylose yield of both the ZCR and the LHR, and was within the near-optimal space for total sugar yield for the LHR. This indicates that the ASE is a good tool for cost effectively finding near-optimal conditions for operating pilot-scale systems, which may be used as starting points for further optimization. Additionally, using a severity-factor approach to optimization was found to be inadequate compared to a multivariate optimization method. As a result, the ASE and the LHR were able to enable significantly higher total sugar yields after enzymatic hydrolysis relative to the ZCR, despite having similar optimal conditions and total xylose yields. This underscores the importance of incorporating mechanical disruption into pretreatment reactor designs to achieve high enzymatic digestibilities.« less

Optimal design and experimental validation of a simulated moving bed chromatography for continuous recovery of formic acid in a model mixture of three organic acids from Actinobacillus bacteria fermentation.

PubMed

Park, Chanhun; Nam, Hee-Geun; Lee, Ki Bong; Mun, Sungyong

2014-10-24

The economically-efficient separation of formic acid from acetic acid and succinic acid has been a key issue in the production of formic acid with the Actinobacillus bacteria fermentation. To address this issue, an optimal three-zone simulated moving bed (SMB) chromatography for continuous separation of formic acid from acetic acid and succinic acid was developed in this study. As a first step for this task, the adsorption isotherm and mass-transfer parameters of each organic acid on the qualified adsorbent (Amberchrom-CG300C) were determined through a series of multiple frontal experiments. The determined parameters were then used in optimizing the SMB process for the considered separation. During such optimization, the additional investigation for selecting a proper SMB port configuration, which could be more advantageous for attaining better process performances, was carried out between two possible configurations. It was found that if the properly selected port configuration was adopted in the SMB of interest, the throughout and the formic-acid product concentration could be increased by 82% and 181% respectively. Finally, the optimized SMB process based on the properly selected port configuration was tested experimentally using a self-assembled SMB unit with three zones. The SMB experimental results and the relevant computer simulation verified that the developed process in this study was successful in continuous recovery of formic acid from a ternary organic-acid mixture of interest with high throughput, high purity, high yield, and high product concentration. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer optimization of cutting yield from multiple ripped boards

Treesearch

A.R. Stern; K.A. McDonald

1978-01-01

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

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

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

Ghosh, Indro Neil; Landick, Robert

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

DOE PAGES

Ghosh, Indro Neil; Landick, Robert

2016-07-16

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

Economic repercussions of fisheries-induced evolution

PubMed Central

Eikeset, Anne Maria; Richter, Andries; Dunlop, Erin S.; Dieckmann, Ulf; Stenseth, Nils Chr.

2013-01-01

Fish stocks experiencing high fishing mortality show a tendency to mature earlier and at a smaller size, which may have a genetic component and therefore long-lasting economic and biological effects. To date, the economic effects of such ecoevolutionary dynamics have not been empirically investigated. Using 70 y of data, we develop a bioeconomic model for Northeast Arctic cod to compare the economic yield in a model in which life-history traits can vary only through phenotypic plasticity with a model in which, in addition, genetic changes can occur. We find that evolutionary changes toward faster growth and earlier maturation occur consistently even if a stock is optimally managed. However, if a stock is managed optimally, the evolutionary changes actually increase economic yield because faster growth and earlier maturation raise the stock’s productivity. The optimal fishing mortality is almost identical for the evolutionary and nonevolutionary model and substantially lower than what it has been historically. Therefore, the costs of ignoring evolution under optimal management regimes are negligible. However, if fishing mortality is as high as it has been historically, evolutionary changes may result in economic losses, but only if the fishery is selecting for medium-sized individuals. Because evolution facilitates growth, the fish are younger and still immature when they are susceptible to getting caught, which outweighs the increase in productivity due to fish spawning at an earlier age. PMID:23836660

Extraction optimization of mucilage from Basil (Ocimum basilicum L.) seeds using response surface methodology.

PubMed

Nazir, Sadaf; Wani, Idrees Ahmed; Masoodi, Farooq Ahmad

2017-05-01

Aqueous extraction of basil seed mucilage was optimized using response surface methodology. A Central Composite Rotatable Design (CCRD) for modeling of three independent variables: temperature (40-91 °C); extraction time (1.6-3.3 h) and water/seed ratio (18:1-77:1) was used to study the response for yield. Experimental values for extraction yield ranged from 7.86 to 20.5 g/100 g. Extraction yield was significantly ( P  < 0.05) affected by all the variables. Temperature and water/seed ratio were found to have pronounced effect while the extraction time was found to have minor possible effects. Graphical optimization determined the optimal conditions for the extraction of mucilage. The optimal condition predicted an extraction yield of 20.49 g/100 g at 56.7 °C, 1.6 h, and a water/seed ratio of 66.84:1. Optimal conditions were determined to obtain highest extraction yield. Results indicated that water/seed ratio was the most significant parameter, followed by temperature and time.

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

Stark, Christopher C.; Roberge, Aki; Mandell, Avi

ExoEarth yield is a critical science metric for future exoplanet imaging missions. Here we estimate exoEarth candidate yield using single visit completeness for a variety of mission design and astrophysical parameters. We review the methods used in previous yield calculations and show that the method choice can significantly impact yield estimates as well as how the yield responds to mission parameters. We introduce a method, called Altruistic Yield Optimization, that optimizes the target list and exposure times to maximize mission yield, adapts maximally to changes in mission parameters, and increases exoEarth candidate yield by up to 100% compared to previousmore » methods. We use Altruistic Yield Optimization to estimate exoEarth candidate yield for a large suite of mission and astrophysical parameters using single visit completeness. We find that exoEarth candidate yield is most sensitive to telescope diameter, followed by coronagraph inner working angle, followed by coronagraph contrast, and finally coronagraph contrast noise floor. We find a surprisingly weak dependence of exoEarth candidate yield on exozodi level. Additionally, we provide a quantitative approach to defining a yield goal for future exoEarth-imaging missions.« less

Diethyl Ether Production during Catalytic Dehydration of Ethanol over Ru- and Pt- modified H-beta Zeolite Catalysts.

PubMed

Kamsuwan, Tanutporn; Praserthdam, Piyasan; Jongsomjit, Bunjerd

2017-01-01

In the present study, the catalytic dehydration of ethanol over H-beta zeolite (HBZ) catalyst with ruthenium (Ru-HBZ) and platinum (Pt-HBZ) modification was investigated. Upon the reaction temperature between 200 and 400°C, it revealed that ethanol conversion and ethylene selectivity increased with increasing temperature for both Ru and Pt modification. At lower temperature (200 to 250°C), diethyl ether (DEE) was the major product. It was found that Ru and Pt modification on HBZ catalyst can result in increased DEE yield at low reaction temperature due to increased ethanol conversion without a significant change in DEE selectivity. By comparing the DEE yield of all catalysts in this study, the Ru-HBZ catalyst apparently exhibited the highest DEE yield (ca. 47%) at 250°C. However, at temperature from 350 to 400°C, the effect of Ru and Pt was less pronounced on ethylene yield. With various characterization techniques, the effects of Ru and Pt modification on HBZ catalyst were elucidated. It revealed that Ru and Pt were present in the highly dispersed forms and well distributed in the catalyst granules. It appeared that the weak acid sites measured by NH 3 temperature-programmed desorption technique also decreased with Ru and Pt promotion. Thus, the increased DEE yields with the Ru and Pt modification can be attributed to the presence of optimal weak acid sites leading to increased intrinsic activity of the catalysts. It can be concluded that the modification of Ru and Pt on HBZ catalyst can improve the DEE yields by ca. 10%.

Bispecific small molecule–antibody conjugate targeting prostate cancer

PubMed Central

Kim, Chan Hyuk; Axup, Jun Y.; Lawson, Brian R.; Yun, Hwayoung; Tardif, Virginie; Choi, Sei Hyun; Zhou, Quan; Dubrovska, Anna; Biroc, Sandra L.; Marsden, Robin; Pinstaff, Jason; Smider, Vaughn V.; Schultz, Peter G.

2013-01-01

Bispecific antibodies, which simultaneously target CD3 on T cells and tumor-associated antigens to recruit cytotoxic T cells to cancer cells, are a promising new approach to the treatment of hormone-refractory prostate cancer. Here we report a site-specific, semisynthetic method for the production of bispecific antibody-like therapeutics in which a derivative of the prostate-specific membrane antigen-binding small molecule DUPA was selectively conjugated to a mutant αCD3 Fab containing the unnatural amino acid, p-acetylphenylalanine, at a defined site. Homogeneous conjugates were generated in excellent yields and had good solubility. The efficacy of the conjugate was optimized by modifying the linker structure, relative binding orientation, and stoichiometry of the ligand. The optimized conjugate showed potent and selective in vitro activity (EC50 ∼100 pM), good serum half-life, and potent in vivo activity in prophylactic and treatment xenograft mouse models. This semisynthetic approach is likely to be applicable to the generation of additional bispecific agents using drug-like ligands selective for other cell-surface receptors. PMID:24127589

Optimizing the nitrogen application rate for maize and wheat based on yield and environment on the Northern China Plain.

PubMed

Zhang, Yitao; Wang, Hongyuan; Lei, Qiuliang; Luo, Jiafa; Lindsey, Stuart; Zhang, Jizong; Zhai, Limei; Wu, Shuxia; Zhang, Jingsuo; Liu, Xiaoxia; Ren, Tianzhi; Liu, Hongbin

2018-03-15

Optimizing the nitrogen (N) application rate can increase crop yield while reducing the environmental risks. However, the optimal N rates vary substantially when different targets such as maximum yield or maximum economic benefit are considered. Taking the wheat-maize rotation cropping system on the North China Plain as a case study, we quantified the variation of N application rates when targeting constraints on yield, economic performance, N uptake and N utilization, by conducting field experiments between 2011 and 2013. Results showed that the optimal N application rate was highest when targeting N uptake (240kgha -1 for maize, and 326kgha -1 for wheat), followed by crop yield (208kgha -1 for maize, and 277kgha -1 for wheat) and economic income (191kgha -1 for maize, and 253kgha -1 for wheat). If environmental costs were considered, the optimal N application rates were further reduced by 20-30% compared to those when targeting maximum economic income. However, the optimal N rate, with environmental cost included, may result in soil nutrient mining under maize, and an extra input of 43kgNha -1 was needed to make the soil N balanced and maintain soil fertility in the long term. To obtain a win-win situation for both yield and environment, the optimal N rate should be controlled at 179kgha -1 for maize, which could achieve above 99.5% of maximum yield and have a favorable N balance, and at 202kgha -1 for wheat to achieve 97.4% of maximum yield, which was about 20kgNha -1 higher than that when N surplus was nil. Although these optimal N rates vary on spatial and temporal scales, they are still effective for the North China Plain where 32% of China's total maize and 45% of China's total wheat are produced. More experiments are still needed to determine the optimal N application rates in other regions. Use of these different optimal N rates would contribute to improving the sustainability of agricultural development in China. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of the Ethanol Recycling Reflux Extraction Process for Saponins Using a Design Space Approach

PubMed Central

Gong, Xingchu; Zhang, Ying; Pan, Jianyang; Qu, Haibin

2014-01-01

A solvent recycling reflux extraction process for Panax notoginseng was optimized using a design space approach to improve the batch-to-batch consistency of the extract. Saponin yields, total saponin purity, and pigment yield were defined as the process critical quality attributes (CQAs). Ethanol content, extraction time, and the ratio of the recycling ethanol flow rate and initial solvent volume in the extraction tank (RES) were identified as the critical process parameters (CPPs) via quantitative risk assessment. Box-Behnken design experiments were performed. Quadratic models between CPPs and process CQAs were developed, with determination coefficients higher than 0.88. As the ethanol concentration decreases, saponin yields first increase and then decrease. A longer extraction time leads to higher yields of the ginsenosides Rb1 and Rd. The total saponin purity increases as the ethanol concentration increases. The pigment yield increases as the ethanol concentration decreases or extraction time increases. The design space was calculated using a Monte-Carlo simulation method with an acceptable probability of 0.90. Normal operation ranges to attain process CQA criteria with a probability of more than 0.914 are recommended as follows: ethanol content of 79–82%, extraction time of 6.1–7.1 h, and RES of 0.039–0.040 min−1. Most of the results of the verification experiments agreed well with the predictions. The verification experiment results showed that the selection of proper operating ethanol content, extraction time, and RES within the design space can ensure that the CQA criteria are met. PMID:25470598

PSMA-targeted bispecific Fab conjugates that engage T cells.

PubMed

Patterson, James T; Isaacson, Jason; Kerwin, Lisa; Atassi, Ghazi; Duggal, Rohit; Bresson, Damien; Zhu, Tong; Zhou, Heyue; Fu, Yanwen; Kaufmann, Gunnar F

2017-12-15

Bioconjugate formats provide alternative strategies for antigen targeting with bispecific antibodies. Here, PSMA-targeted Fab conjugates were generated using different bispecific formats. Interchain disulfide bridging of an αCD3 Fab enabled installation of either the PSMA-targeting small molecule DUPA (SynFab) or the attachment of an αPSMA Fab (BisFab) by covalent linkage. Optimization of the reducing conditions was critical for selective interchain disulfide reduction and good bioconjugate yield. Activity of αPSMA/CD3 Fab conjugates was tested by in vitro cytotoxicity assays using prostate cancer cell lines. Both bispecific formats demonstrated excellent potency and antigen selectivity. Copyright © 2017. Published by Elsevier Ltd.

Synthesis of sodium lignosulphonate from oil palm empty fruit bunches's lignin

NASA Astrophysics Data System (ADS)

Prakoso, Nurcahyo Iman; Purwono, Suryo; Rochmadi

2017-03-01

Synthesis of sodium lignosulphonate have been done by using batch method. Optimation of synthesis method was achieved through this study. The study was conducted on the optimation of mass ratio of lignin to the NaHSO3 solution, the concentration of NaHSO3 solution, reaction temperature, and reaction time. Of all the treatments, it was found that the optimum mass ratio of lignin to the NaHSO3 solution, concentration of NaHSO3 solution, reaction temperature, and reaction time respectively, 0.3 M, 0.1 M 97 °C, and the reaction was carried out for 4 hours. Excellent yields and selective products were obtained (90-92%)

Bio-oil upgrading strategies to improve PHA production from selected aerobic mixed cultures.

PubMed

Moita Fidalgo, Rita; Ortigueira, Joana; Freches, André; Pelica, João; Gonçalves, Magarida; Mendes, Benilde; Lemos, Paulo C

2014-06-25

Recent research on polyhydroxyalkanoates (PHAs) has focused on developing cost-effective production processes using low-value or industrial waste/surplus as substrate. One of such substrates is the liquid fraction resulting from pyrolysis processes, bio-oil. In this study, valorisation of bio-oil through PHA production was investigated. The impact of the complex bio-oil matrix on PHA production by an enriched mixed culture was examined. The performance of the direct utilization of pure bio-oil was compared with the utilization of three defined substrates contained in this bio-oil: acetate, glucose and xylose. When compared with acetate, bio-oil revealed lower capacity for polymer production as a result of a lower polymer yield on substrate and a lower PHA cell content. Two strategies for bio-oil upgrade were performed, anaerobic fermentation and vacuum distillation, and the resulting liquid streams were tested for polymer production. The first one was enriched in volatile fatty acids and the second one mainly on phenolic and long-chain fatty acids. PHA accumulation assays using the upgraded bio-oils attained polymer yields on substrate similar or higher than the one achieved with acetate, although with a lower PHA content. The capacity to use the enriched fractions for polymer production has yet to be optimized. The anaerobic digestion of bio-oil could also open-up the possibility to use the fermented bio-oil directly in the enrichment process of the mixed culture. This would increase the selective pressure toward an optimized PHA accumulating culture selection. Copyright © 2013 Elsevier B.V. All rights reserved.

High Levels of Bioplastic Are Produced in Fertile Transplastomic Tobacco Plants Engineered with a Synthetic Operon for the Production of Polyhydroxybutyrate1[C][OA

PubMed Central

Bohmert-Tatarev, Karen; McAvoy, Susan; Daughtry, Sean; Peoples, Oliver P.; Snell, Kristi D.

2011-01-01

An optimized genetic construct for plastid transformation of tobacco (Nicotiana tabacum) for the production of the renewable, biodegradable plastic polyhydroxybutyrate (PHB) was designed using an operon extension strategy. Bacterial genes encoding the PHB pathway enzymes were selected for use in this construct based on their similarity to the codon usage and GC content of the tobacco plastome. Regulatory elements with limited homology to the host plastome yet known to yield high levels of plastidial recombinant protein production were used to enhance the expression of the transgenes. A partial transcriptional unit, containing genes of the PHB pathway and a selectable marker gene encoding spectinomycin resistance, was flanked at the 5′ end by the host plant’s psbA coding sequence and at the 3′ end by the host plant’s 3′ psbA untranslated region. This design allowed insertion of the transgenes into the plastome as an extension of the psbA operon, rendering the addition of a promoter to drive the expression of the transgenes unnecessary. Transformation of the optimized construct into tobacco and subsequent spectinomycin selection of transgenic plants yielded T0 plants that were capable of producing up to 18.8% dry weight PHB in samples of leaf tissue. These plants were fertile and produced viable seed. T1 plants producing up to 17.3% dry weight PHB in samples of leaf tissue and 8.8% dry weight PHB in the total biomass of the plant were also isolated. PMID:21325565

Reinforcement Learning Strategies for Clinical Trials in Non-small Cell Lung Cancer

PubMed Central

Zhao, Yufan; Zeng, Donglin; Socinski, Mark A.; Kosorok, Michael R.

2010-01-01

Summary Typical regimens for advanced metastatic stage IIIB/IV non-small cell lung cancer (NSCLC) consist of multiple lines of treatment. We present an adaptive reinforcement learning approach to discover optimal individualized treatment regimens from a specially designed clinical trial (a “clinical reinforcement trial”) of an experimental treatment for patients with advanced NSCLC who have not been treated previously with systemic therapy. In addition to the complexity of the problem of selecting optimal compounds for first and second-line treatments based on prognostic factors, another primary goal is to determine the optimal time to initiate second-line therapy, either immediately or delayed after induction therapy, yielding the longest overall survival time. A reinforcement learning method called Q-learning is utilized which involves learning an optimal regimen from patient data generated from the clinical reinforcement trial. Approximating the Q-function with time-indexed parameters can be achieved by using a modification of support vector regression which can utilize censored data. Within this framework, a simulation study shows that the procedure can extract optimal regimens for two lines of treatment directly from clinical data without prior knowledge of the treatment effect mechanism. In addition, we demonstrate that the design reliably selects the best initial time for second-line therapy while taking into account the heterogeneity of NSCLC across patients. PMID:21385164

End-to-End Assessment of a Large Aperture Segmented Ultraviolet Optical Infrared (UVOIR) Telescope Architecture

NASA Technical Reports Server (NTRS)

Feinberg, Lee; Rioux, Norman; Bolcar, Matthew; Liu, Alice; Guyon, Oliver; Stark, Chris; Arenberg, Jon

2016-01-01

Key challenges of a future large aperture, segmented Ultraviolet Optical Infrared (UVOIR) Telescope capable of performing a spectroscopic survey of hundreds of Exoplanets will be sufficient stability to achieve 10^-10 contrast measurements and sufficient throughput and sensitivity for high yield Exo-Earth spectroscopic detection. Our team has collectively assessed an optimized end to end architecture including a high throughput coronagraph capable of working with a segmented telescope, a cost-effective and heritage based stable segmented telescope, a control architecture that minimizes the amount of new technologies, and an Exo-Earth yield assessment to evaluate potential performance. These efforts are combined through integrated modeling, coronagraph evaluations, and Exo-Earth yield calculations to assess the potential performance of the selected architecture. In addition, we discusses the scalability of this architecture to larger apertures and the technological tall poles to enabling it.

Indices estimated using REML/BLUP and introduction of a super-trait for the selection of progenies in popcorn.

PubMed

Vittorazzi, C; Amaral Junior, A T; Guimarães, A G; Viana, A P; Silva, F H L; Pena, G F; Daher, R F; Gerhardt, I F S; Oliveira, G H F; Pereira, M G

2017-09-27

Selection indices commonly utilize economic weights, which become arbitrary genetic gains. In popcorn, this is even more evident due to the negative correlation between the main characteristics of economic importance - grain yield and popping expansion. As an option in the use of classical biometrics as a selection index, the optimal procedure restricted maximum likelihood/best linear unbiased predictor (REML/BLUP) allows the simultaneous estimation of genetic parameters and the prediction of genotypic values. Based on the mixed model methodology, the objective of this study was to investigate the comparative efficiency of eight selection indices estimated by REML/BLUP for the effective selection of superior popcorn families in the eighth intrapopulation recurrent selection cycle. We also investigated the efficiency of the inclusion of the variable "expanded popcorn volume per hectare" in the most advantageous selection of superior progenies. In total, 200 full-sib families were evaluated in two different areas in the North and Northwest regions of the State of Rio de Janeiro, Brazil. The REML/BLUP procedure resulted in higher estimated gains than those obtained with classical biometric selection index methodologies and should be incorporated into the selection of progenies. The following indices resulted in higher gains in the characteristics of greatest economic importance: the classical selection index/values attributed by trial, via REML/BLUP, and the greatest genotypic values/expanded popcorn volume per hectare, via REML. The expanded popcorn volume per hectare characteristic enabled satisfactory gains in grain yield and popping expansion; this characteristic should be considered super-trait in popcorn breeding programs.

Catalytic Activity of Nanosized CuO-ZnO Supported on Titanium Chips in Hydrogenation of Carbon Dioxide to Methyl Alcohol.

PubMed

Ahn, Ho-Geun; Lee, Hwan-Gyu; Chung, Min-Chul; Park, Kwon-Pil; Kim, Ki-Joong; Kang, Byeong-Mo; Jeong, Woon-Jo; Jung, Sang-Chul; Lee, Do-Jin

2016-02-01

In this study, titanium chips (TC) generated from industrial facilities was utilized as TiO2 support for hydrogenation of carbon dioxide (CO2) to methyl alcohol (CH3OH) over Cu-based catalysts. Nano-sized CuO and ZnO catalysts were deposited on TiO2 support using a co-precipitation (CP) method (CuO-ZnO/TiO2), where the thermal treatment of TC and the particle size of TiC2 are optimized on CO2 conversion under different reaction temperature and contact time. Direct hydrogenation of CO2 to CH3OH over CuO-ZnO/TiO2 catalysts was achieved and the maximum selectivity (22%) and yield (18.2%) of CH3OH were obtained in the range of reaction temperature 210-240 degrees C under the 30 bar. The selectivity was readily increased by increasing the flow rate, which does not affect much to the CO2 conversion and CH3OH yield.

Comparing organic farming and land sparing: optimizing yield and butterfly populations at a landscape scale.

PubMed

Hodgson, Jenny A; Kunin, William E; Thomas, Chris D; Benton, Tim G; Gabriel, Doreen

2010-11-01

Organic farming aims to be wildlife-friendly, but it may not benefit wildlife overall if much greater areas are needed to produce a given quantity of food. We measured the density and species richness of butterflies on organic farms, conventional farms and grassland nature reserves in 16 landscapes. Organic farms supported a higher density of butterflies than conventional farms, but a lower density than reserves. Using our data, we predict the optimal land-use strategy to maintain yield whilst maximizing butterfly abundance under different scenarios. Farming conventionally and sparing land as nature reserves is better for butterflies when the organic yield per hectare falls below 87% of conventional yield. However, if the spared land is simply extra field margins, organic farming is optimal whenever organic yields are over 35% of conventional yields. The optimal balance of land sparing and wildlife-friendly farming to maintain production and biodiversity will differ between landscapes. © 2010 Blackwell Publishing Ltd/CNRS.

Green ultrasound-assisted extraction of anthocyanin and phenolic compounds from purple sweet potato using response surface methodology

NASA Astrophysics Data System (ADS)

Zhu, Zhenzhou; Guan, Qingyan; Guo, Ying; He, Jingren; Liu, Gang; Li, Shuyi; Barba, Francisco J.; Jaffrin, Michel Y.

2016-01-01

Response surface methodology was used to optimize experimental conditions for ultrasound-assisted extraction of valuable components (anthocyanins and phenolics) from purple sweet potatoes using water as a solvent. The Box-Behnken design was used for optimizing extraction responses of anthocyanin extraction yield, phenolic extraction yield, and specific energy consumption. Conditions to obtain maximal anthocyanin extraction yield, maximal phenolic extraction yield, and minimal specific energy consumption were different; an overall desirability function was used to search for overall optimal conditions: extraction temperature of 68ºC, ultrasonic treatment time of 52 min, and a liquid/solid ratio of 20. The optimized anthocyanin extraction yield, phenolic extraction yield, and specific energy consumption were 4.91 mg 100 g-1 fresh weight, 3.24 mg g-1 fresh weight, and 2.07 kWh g-1, respectively, with a desirability of 0.99. This study indicates that ultrasound-assisted extraction should contribute to a green process for valorization of purple sweet potatoes.

The development and use of a molecular model for soybean maturity groups.

PubMed

Langewisch, Tiffany; Lenis, Julian; Jiang, Guo-Liang; Wang, Dechun; Pantalone, Vince; Bilyeu, Kristin

2017-05-30

Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments.

Selectivity on-target of bromodomain chemical probes by structure-guided medicinal chemistry and chemical biology

PubMed Central

Galdeano, Carles; Ciulli, Alessio

2017-01-01

Targeting epigenetic proteins is a rapidly growing area for medicinal chemistry and drug discovery. Recent years have seen an explosion of interest in developing small molecules binding to bromodomains, the readers of acetyl-lysine modifications. A plethora of co-crystal structures has motivated focused fragment-based design and optimization programs within both industry and academia. These efforts have yielded several compounds entering the clinic, and many more are increasingly being used as chemical probes to interrogate bromodomain biology. High selectivity of chemical probes is necessary to ensure biological activity is due to an on-target effect. Here, we review the state-of-the-art of bromodomain-targeting compounds, focusing on the structural basis for their on-target selectivity or lack thereof. We also highlight chemical biology approaches to enhance on-target selectivity. PMID:27193077

Chemical library subset selection algorithms: a unified derivation using spatial statistics.

PubMed

Hamprecht, Fred A; Thiel, Walter; van Gunsteren, Wilfred F

2002-01-01

If similar compounds have similar activity, rational subset selection becomes superior to random selection in screening for pharmacological lead discovery programs. Traditional approaches to this experimental design problem fall into two classes: (i) a linear or quadratic response function is assumed (ii) some space filling criterion is optimized. The assumptions underlying the first approach are clear but not always defendable; the second approach yields more intuitive designs but lacks a clear theoretical foundation. We model activity in a bioassay as realization of a stochastic process and use the best linear unbiased estimator to construct spatial sampling designs that optimize the integrated mean square prediction error, the maximum mean square prediction error, or the entropy. We argue that our approach constitutes a unifying framework encompassing most proposed techniques as limiting cases and sheds light on their underlying assumptions. In particular, vector quantization is obtained, in dimensions up to eight, in the limiting case of very smooth response surfaces for the integrated mean square error criterion. Closest packing is obtained for very rough surfaces under the integrated mean square error and entropy criteria. We suggest to use either the integrated mean square prediction error or the entropy as optimization criteria rather than approximations thereof and propose a scheme for direct iterative minimization of the integrated mean square prediction error. Finally, we discuss how the quality of chemical descriptors manifests itself and clarify the assumptions underlying the selection of diverse or representative subsets.

Super-optimal CO2 reduces seed yield but not vegetative growth in wheat

NASA Technical Reports Server (NTRS)

Grotenhuis, T. P.; Bugbee, B.

1997-01-01

Although terrestrial atmospheric CO2 levels will not reach 1000 micromoles mol-1 (0.1%) for decades, CO2 levels in growth chambers and greenhouses routinely exceed that concentration. CO2 levels in life support systems in space can exceed 10000 micromoles mol-1(1%). Numerous studies have examined CO2 effects up to 1000 micromoles mol-1, but biochemical measurements indicate that the beneficial effects of CO2 can continue beyond this concentration. We studied the effects of near-optimal (approximately 1200 micromoles mol-1) and super-optimal CO2 levels (2400 micromoles mol-1) on yield of two cultivars of hydroponically grown wheat (Triticum aestivum L.) in 12 trials in growth chambers. Increasing CO2 from sub-optimal to near-optimal (350-1200 micromoles mol-1) increased vegetative growth by 25% and seed yield by 15% in both cultivars. Yield increases were primarily the result of an increased number of heads per square meter. Further elevation of CO2 to 2500 micromoles mol-1 reduced seed yield by 22% (P < 0.001) in cv. Veery-10 and by 15% (P < 0.001) in cv. USU-Apogee. Super-optimal CO2 did not decrease the number of heads per square meter, but reduced seeds per head by 10% and mass per seed by 11%. The toxic effect of CO2 was similar over a range of light levels from half to full sunlight. Subsequent trials revealed that super-optimal CO2 during the interval between 2 wk before and after anthesis mimicked the effect of constant super-optimal CO2. Furthermore, near-optimal CO2 during the same interval mimicked the effect of constant near-optimal CO2. Nutrient concentration of leaves and heads was not affected by CO2. These results suggest that super-optimal CO2 inhibits some process that occurs near the time of seed set resulting in decreased seed set, seed mass, and yield.

Effect of optimal daily fertigation on migration of water and salt in soil, root growth and fruit yield of cucumber (Cucumis sativus L.) in solar-greenhouse.

PubMed

Liang, Xinshu; Gao, Yinan; Zhang, Xiaoying; Tian, Yongqiang; Zhang, Zhenxian; Gao, Lihong

2014-01-01

Inappropriate and excessive irrigation and fertilization have led to the predominant decline of crop yields, and water and fertilizer use efficiency in intensive vegetable production systems in China. For many vegetables, fertigation can be applied daily according to the actual water and nutrient requirement of crops. A greenhouse study was therefore conducted to investigate the effect of daily fertigation on migration of water and salt in soil, and root growth and fruit yield of cucumber. The treatments included conventional interval fertigation, optimal interval fertigation and optimal daily fertigation. Generally, although soil under the treatment optimal interval fertigation received much lower fertilizers than soil under conventional interval fertigation, the treatment optimal interval fertigation did not statistically decrease the economic yield and fruit nutrition quality of cucumber when compare to conventional interval fertigation. In addition, the treatment optimal interval fertigation effectively avoided inorganic nitrogen accumulation in soil and significantly (P<0.05) increased the partial factor productivity of applied nitrogen by 88% and 209% in the early-spring and autumn-winter seasons, respectively, when compared to conventional interval fertigation. Although soils under the treatments optimal interval fertigation and optimal daily fertigation received the same amount of fertilizers, the treatment optimal daily fertigation maintained the relatively stable water, electrical conductivity and mineral nitrogen levels in surface soils, promoted fine root (<1.5 mm diameter) growth of cucumber, and eventually increased cucumber economic yield by 6.2% and 8.3% and partial factor productivity of applied nitrogen by 55% and 75% in the early-spring and autumn-winter seasons, respectively, when compared to the treatment optimal interval fertigation. These results suggested that optimal daily fertigation is a beneficial practice for improving crop yield and the water and fertilizers use efficiency in solar greenhouse.

Effect of Optimal Daily Fertigation on Migration of Water and Salt in Soil, Root Growth and Fruit Yield of Cucumber (Cucumis sativus L.) in Solar-Greenhouse

PubMed Central

Liang, Xinshu; Gao, Yinan; Zhang, Xiaoying; Tian, Yongqiang; Zhang, Zhenxian; Gao, Lihong

2014-01-01

Inappropriate and excessive irrigation and fertilization have led to the predominant decline of crop yields, and water and fertilizer use efficiency in intensive vegetable production systems in China. For many vegetables, fertigation can be applied daily according to the actual water and nutrient requirement of crops. A greenhouse study was therefore conducted to investigate the effect of daily fertigation on migration of water and salt in soil, and root growth and fruit yield of cucumber. The treatments included conventional interval fertigation, optimal interval fertigation and optimal daily fertigation. Generally, although soil under the treatment optimal interval fertigation received much lower fertilizers than soil under conventional interval fertigation, the treatment optimal interval fertigation did not statistically decrease the economic yield and fruit nutrition quality of cucumber when compare to conventional interval fertigation. In addition, the treatment optimal interval fertigation effectively avoided inorganic nitrogen accumulation in soil and significantly (P<0.05) increased the partial factor productivity of applied nitrogen by 88% and 209% in the early-spring and autumn-winter seasons, respectively, when compared to conventional interval fertigation. Although soils under the treatments optimal interval fertigation and optimal daily fertigation received the same amount of fertilizers, the treatment optimal daily fertigation maintained the relatively stable water, electrical conductivity and mineral nitrogen levels in surface soils, promoted fine root (<1.5 mm diameter) growth of cucumber, and eventually increased cucumber economic yield by 6.2% and 8.3% and partial factor productivity of applied nitrogen by 55% and 75% in the early-spring and autumn-winter seasons, respectively, when compared to the treatment optimal interval fertigation. These results suggested that optimal daily fertigation is a beneficial practice for improving crop yield and the water and fertilizers use efficiency in solar greenhouse. PMID:24475204

Optimization of cultural conditions for conversion of glycerol to ethanol by Enterobacter aerogenes S012

PubMed Central

2013-01-01

The aim of this research is to optimize the cultural conditions for the conversion of glycerol to ethanol by Enterobacter aerogenes S012. Taguchi method was used to screen the cultural conditions based on their signal to noise ratio (SN). Temperature (°C), agitation speed (rpm) and time (h) were found to have the highest influence on both glycerol utilization and ethanol production by the organism while pH had the lowest. Full factorial design, statistical analysis, and regression model equation were used to optimize the selected cultural parameters for maximum ethanol production. The result showed that fermentation at 38°C and 200 rpm for 48 h would be ideal for the bacteria to produce maximum amount of ethanol from glycerol. At these optimum conditions, ethanol production, yield and productivity were 25.4 g/l, 0.53 g/l/h, and 1.12 mol/mol-glycerol, repectively. Ethanol production increased to 26.5 g/l while yield and productivity decreased to 1.04 mol/mol-glycerol and 0.37 g/l/h, respectively, after 72 h. Analysis of the fermentation products was performed using HPLC, while anaerobic condition was created by purging the fermentation vessel with nitrogen gas. PMID:23388539

Accounting for soil biotic effects on soil health and crop productivity in the design of crop rotations.

PubMed

Dias, Teresa; Dukes, Angela; Antunes, Pedro M

2015-02-01

There is an urgent need for novel agronomic improvements capable of boosting crop yields while alleviating environmental impacts. One such approach is the use of optimized crop rotations. However, a set of measurements that can serve as guiding principles for the design of crop rotations is lacking. Crop rotations take advantage of niche complementarity, enabling the optimization of nutrient use and the reduction of pests and specialist pathogen loads. However, despite the recognized importance of plant-soil microbial interactions and feedbacks for crop yield and soil health, this is ignored in the selection and management of crops for rotation systems. We review the literature and propose criteria for the design of crop rotations focusing on the roles of soil biota and feedback on crop productivity and soil health. We consider that identifying specific key organisms or consortia capable of influencing plant productivity is more important as a predictor of soil health and crop productivity than assessing the overall soil microbial diversity per se. As such, we propose that setting up soil feedback studies and applying genetic sequencing tools towards the development of soil biotic community databases has a strong potential to enable the establishment of improved soil health indicators for optimized crop rotations. © 2014 Society of Chemical Industry.

A CYP21A2 based whole-cell system in Escherichia coli for the biotechnological production of premedrol.

PubMed

Brixius-Anderko, Simone; Schiffer, Lina; Hannemann, Frank; Janocha, Bernd; Bernhardt, Rita

2015-09-15

Synthetic glucocorticoids like methylprednisolone (medrol) are of high pharmaceutical interest and represent powerful drugs due to their anti-inflammatory and immunosuppressive effects. Since the chemical hydroxylation of carbon atom 21, a crucial step in the synthesis of the medrol precursor premedrol, exhibits a low overall yield because of a poor stereo- and regioselectivity, there is high interest in a more sustainable and efficient biocatalytic process. One promising candidate is the mammalian cytochrome P450 CYP21A2 which is involved in steroid hormone biosynthesis and performs a selective oxyfunctionalization of C21 to provide the precursors of aldosterone, the main mineralocorticoid, and cortisol, the most important glucocorticoid. In this work, we demonstrate the high potential of CYP21A2 for a biotechnological production of premedrol, an important precursor of medrol. We successfully developed a CYP21A2-based whole-cell system in Escherichia coli by coexpressing the cDNAs of bovine CYP21A2 and its redox partner, the NADPH-dependent cytochrome P450 reductase (CPR), via a bicistronic vector. The synthetic substrate medrane was selectively 21-hydroxylated to premedrol with a max. yield of 90 mg L(-1) d(-1). To further improve the biocatalytic activity of the system by a more effective electron supply, we exchanged the CPR with constructs containing five alternative redox systems. A comparison of the constructs revealed that the redox system with the highest endpoint yield converted 70 % of the substrate within the first 2 h showing a doubled initial reaction rate compared with the other constructs. Using the best system we could increase the overall yield of premedrol to a maximum of 320 mg L(-1) d(-1) in shaking flasks. Optimization of the biotransformation in a bioreactor could further improve the premedrol gain to a maximum of 0.65 g L(-1) d(-1). We successfully established a CYP21-based whole-cell system for the biotechnological production of premedrol, a pharmaceutically relevant glucocorticoid, in E. coli and could improve the system by optimizing the redox system concerning reaction velocity and endpoint yield. This is the first step for a sustainable replacement of a complicated chemical low-yield hydroxylation by a biocatalytic cytochrome P450-based whole-cell system.

Synthesis of Oligosaccharides Derived from Lactulose (OsLu) Using Soluble and Immobilized Aspergillus oryzae β-Galactosidase

PubMed Central

Cardelle-Cobas, Alejandra; Olano, Agustin; Irazoqui, Gabriela; Giacomini, Cecilia; Batista-Viera, Francisco; Corzo, Nieves; Corzo-Martínez, Marta

2016-01-01

β-Galactosidase from Aspergillus oryzae offers a high yield for the synthesis of oligosaccharides derived from lactulose (OsLu) by transgalactosylation. Oligosaccharides with degree of polymerization (DP) ≥ 3 have shown to possess higher in vitro bifidogenic effect than di- and tetrasaccharides. Thus, in this work, an optimization of reaction conditions affecting the specific selectivity of A. oryzae β-galactosidase for synthesis of OsLu has been carried out to enhance OsLu with DP ≥ 3 production. Assays with β-galactosidase immobilized onto a glutaraldehyde–agarose support were also carried out with the aim of making the process cost-effective and industrially viable. Optimal conditions with both soluble and immobilized enzyme for the synthesis of OsLu with DP ≥ 3 were 50 °C, pH 6.5, 450 g/L of lactulose, and 8 U/mL of enzyme, reaching yields of ca. 50% (w/v) of total OsLu and ca. 20% (w/v) of OsLu with DP 3, being 6′-galactosyl-lactulose the major one, after a short reaction time. Selective formation of disaccharides, however, was favored at 60 °C, pH 4.5, 450 g/L of lactulose and 8 U/mL of enzyme. Immobilization increased the enzymatic stability to temperature changes and allowed to reuse the enzyme. We can conclude that the use, under determined optimal conditions, of the A. oryzae β-galactosidase immobilized on a support of glutaraldehyde–agarose constitutes an efficient and cost-effective alternative to the use of soluble β-galactosidases for the synthesis of prebiotic OsLu mixtures. PMID:27014684

Analysis of materials used for Greenhouse roof covering - structure using CFD

NASA Astrophysics Data System (ADS)

Subin, M. C.; Savio Lourence, Jason; Karthikeyan, Ram; Periasamy, C.

2018-04-01

Greenhouse is widely used to create a suitable environment for the growth of plant. During summer, high temperatures cause harm to the plant. This work calculates characteristics required to optimize the above-mentioned parameters using different roof structure covering materials for the greenhouse. Moreover, this work also presents a simulation of the cooling and heating system. In addition, a computer model based on Ansys Fluent has been using to predict the temperature profiles inside the greenhouse. Greenhouse roof structure shading may have a time-dependent effect the production, water and nutrient uptake in plants. An experiment was conducted in the emirate of Dubai in United Arab Emirates to discover the impact of different materials in order to have an optimal plant growth zone and yield production. These structures were poly ethylene and poly carbonate sheets of 2 different configurations. Results showed that poly carbonate sheets configuration of optimal thickness has given a high result in terms of yield production. Therefore, there is a need for appropriate material selection of greenhouse roof structure in this area of UAE. Major parameters and properties need to be considered while selecting a greenhouse roof structure are the resistance to solar radiation, weathering, thermal as well as mechanical properties and good abrasion resistance. In the present study, an experiment has been conducted to find out the material suitability of the greenhouse roof structure in terms of developing proper ambient conditions especially to minimize the energy lose by reducing the HVAC and lighting expenses. The configuration verified using the CFD, so it has been concluded that polycarbonate can be safely used in the greenhouse than other roof structure material having white or green colour.

QbD-enabled systematic development of gastroretentive multiple-unit microballoons of itopride hydrochloride.

PubMed

Bansal, Sanjay; Beg, Sarwar; Asthana, Abhay; Garg, Babita; Asthana, Gyati Shilakari; Kapil, Rishi; Singh, Bhupinder

2016-01-01

The objectives of present studies were to develop the systematically optimized multiple-unit gastroretentive microballoons, i.e. hollow microspheres of itopride hydrochloride (ITH) employing quality by design (QbD)-based approach. Initially, the patient-centric QTPP and CQAs were earmarked, and preliminary studies were conducted to screen the suitable polymer, solvent, solvent ratio, pH and temperature conditions. Microspheres were prepared by non-aqueous solvent evaporation method employing Eudragit S-100. Risk assessment studies carried out by constructing Ishikawa cause-effect fish-bone diagram, and techniques like risk estimation matrix (REM) and failure mode effect analysis (FMEA) facilitated the selection of plausible factors affecting the drug product CQAs, i.e. percent yield, entrapment efficiency (EE) and percent buoyancy. A 3(3) Box-Behnken design (BBD) was employed for optimizing CMAs and CPPs selected during factor screening studies employing Taguchi design, i.e. drug-polymer ratio (X1), stirring temperature (X2) and stirring speed (X3). The hollow microspheres, as per BBD, were evaluated for EE, particle size and drug release characteristics. The optimum formulation was embarked upon using numerical desirability function yielding excellent floatation characteristics along with adequate drug release control. Drug-excipient compatibility studies employing FT-IR, DSC and powder XRD revealed absence of significant interaction among the formulation excipients. The SEM studies on the optimized formulation showed hollow and spherical nature of the prepared microspheres. In vivo X-ray imaging studies in rabbits confirmed the buoyant nature of the hollow microspheres for 8 h in the upper GI tract. In a nutshell, the current investigations report the successful development of gastroretentive floating microspheres for once-a-day administration of ITH.

Experiences in flip chip production of radiation detectors

NASA Astrophysics Data System (ADS)

Savolainen-Pulli, Satu; Salonen, Jaakko; Salmi, Jorma; Vähänen, Sami

2006-09-01

Modern imaging devices often require heterogeneous integration of different materials and technologies. Because of yield considerations, material availability, and various technological limitations, an extremely fine pitch is necessary to realize high-resolution images. Thus, there is a need for a hybridization technology that is able to join together readout amplifiers and pixel detectors at a very fine pitch. This paper describes radiation detector flip chip production at VTT. Our flip chip technology utilizes 25-μm diameter tin-lead solder bumps at a 50-μm pitch and is based on flux-free bonding. When preprocessed wafers are used, as is the case here, the total yield is defined only partly by the flip chip process. Wafer preprocessing done by a third-party silicon foundry and the flip chip process create different process defects. Wafer-level yield maps (based on probing) provided by the customer are used to select good readout chips for assembly. Wafer probing is often done outside of a real clean room environment, resulting in particle contamination and/or scratches on the wafers. Factors affecting the total yield of flip chip bonded detectors are discussed, and some yield numbers of the process are given. Ways to improve yield are considered, and finally guidelines for process planning and device design with respect to yield optimization are given.

Elevating optimal human nutrition to a central goal of plant breeding and production of plant-based foods

PubMed Central

Sands, David C.; Morris, Cindy E.; Dratz, Edward A.; Pilgeram, Alice

2010-01-01

High-yielding cereals and other staples have produced adequate calories to ward off starvation for much of the world over several decades. However, deficiencies in certain amino acids, minerals, vitamins and fatty acids in staple crops, and animal diets derived from them, have aggravated the problem of malnutrition and the increasing incidence of certain chronic diseases in nominally well-nourished people (the so-called diseases of civilization). Enhanced global nutrition has great potential to reduce acute and chronic disease, the need for health care, the cost of health care, and to increase educational attainment, economic productivity and the quality of life. However, nutrition is currently not an important driver of most plant breeding efforts, and there are only a few well-known efforts to breed crops that are adapted to the needs of optimal human nutrition. Technological tools are available to greatly enhance the nutritional value of our staple crops. However, enhanced nutrition in major crops might only be achieved if nutritional traits are introduced in tandem with important agronomic yield drivers, such as resistance to emerging pests or diseases, to drought and salinity, to herbicides, parasitic plants, frost or heat. In this way we might circumvent a natural tendency for high yield and low production cost to effectively select against the best human nutrition. Here we discuss the need and means for agriculture, food processing, food transport, sociology, nutrition and medicine to be integrated into new approaches to food production with optimal human nutrition as a principle goal. PMID:20467463

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

PubMed

Ashengroph, Morahem; Nahvi, Iraj; Amini, Jahanshir

2013-01-01

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

Optimization of flask culture medium and conditions for hyaluronic acid production by a Streptococcus equisimilis mutant nc2168.

PubMed

Chen, Yong-Hao; Li, Jun; Liu, Li; Liu, Hong-Zhi; Wang, Qiang

2012-10-01

A mutant designated NC2168, which was selected from wild-type Streptococcus equisimilis CVCC55116 by ultraviolet ray combined with(60)Co-γ ray treatment and does not produce streptolysin, was employed to produce hyaluronic acid (HA). In order to increase the output of HA in a flask, the culture medium and conditions for NC2168 were optimized in this study. The influence of culture medium ingredients including carbon sources, nitrogen sources and metal ions on HA production was evaluated using factional factorial design. The mathematical model, which represented the effect of each medium component and their interaction on the yield of HA, was established by the quadratic rotary combination design and response surface method. The model estimated that, a maximal yield of HA could be obtained when the concentrations of yeast extract, peptone, glucose, and MgSO4 were set at 3 g/100 mL, 2 g/100 mL, 0.5 g/100 mL and 0.15 g/100 mL, respectively. Compared with the values obtained by other runs in the experimental design, the optimized medium resulted in a remarkable increase in the output of HA and the maximum of the predicted HA production was 174.76 mg/L. The model developed was accurate and reliable for predicting the production of HA by NC2168.Cultivation conditions were optimized by an orthogonal experimental design and the optimal conditions were as follows: temperature 33°C, pH 7.8, agitation speed 200 rpm, medium volume 20 mL.

Analysis of the trade-off between high crop yield and low yield instability at the global scale

NASA Astrophysics Data System (ADS)

Ben-Ari, Tamara; Makowski, David

2016-10-01

Yield dynamics of major crops species vary remarkably among continents. Worldwide distribution of cropland influences both the expected levels and the interannual variability of global yields. An expansion of cultivated land in the most productive areas could theoretically increase global production, but also increase global yield instability if the most productive regions are characterized by high interannual yield variability. In this letter, we use portfolio analysis to quantify the tradeoff between the expected values and the interannual variance of global yield. We compute optimal frontiers for four crop species i.e., maize, rice, soybean and wheat and show how the distribution of cropland among large world regions can be optimized to either increase expected global crop production or decrease its interannual variability. We also show that a preferential allocation of cropland in the most productive regions can increase global expected yield at the expense of yield stability. Theoretically, optimizing the distribution of a small fraction of total cultivated areas can help find a good compromise between low instability and high crop yields at the global scale.

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

Catalytic conversion of carbohydrates to 5-hydroxymethylfurfural from the waste liquid of acid hydrolysis NCC.

PubMed

Sun, Yonghui; Liu, Pengtao; Liu, Zhong

2016-05-20

The principal goal of this work was to reuse the carbohydrates and recycle sulfuric acid in the waste liquid of acid hydrolysis nanocrystalline cellulose (NCC). Therefore, in this work, the optimizations of further hydrolysis of waste liquid of acid hydrolysis NCC and catalytic conversion of L4 to 5-hydroxymethylfurfural (5-HMF) were studied. Sulfuric acid was separated by spiral wound diffusion dialysis (SWDD). The results revealed that cellulose can be hydrolyze to glucose absolutely under the condition of temperature 35 °C, 3 h, and sulfuric acid's concentration 62 wt%. And 78.3% sulfuric acid was recovered by SWDD. The yield of 5-HMF was highest in aqueous solution under the optimal condition was as follows, temperature 160 °C, 3 h, and sulfuric acid's concentration 12 wt%. Then the effect of biphasic solvent systems catalytic conversion and inorganic salt as additives were still examined. The results showed that both of them contributed to prepare 5-HMF. The yield and selectivity of 5-HMF was up to 21.0% and 31.4%, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Formulation and characterization of Turkish oregano microcapsules prepared by spray-drying technology.

PubMed

Baranauskaite, Juste; Ivanauskas, Liudas; Masteikova, Ruta; Kopustinskiene, Dalia; Baranauskas, Algirdas; Bernatoniene, Jurga

2017-09-01

The aim of this study was optimization of spray-drying process conditions for microencapsulation of Turkish oregano extract. Different concentrations of maltodextrin and gum arabic as encapsulating agents (wall material) as well as influence of selected processing variables were evaluated. The optimal conditions were maintained on the basis of the load of main bioactive compounds - ursolic, rosmarinic acids and carvacrol - in prepared microparticles after comparison of all significant response variables using desirability function. Physicomechanical properties of powders such as flowability, wettability, solubility, moisture content as well as product yield, encapsulation efficiency (EE), density, morphology and size distribution of prepared microparticles have been determined. The results demonstrated that the optimal conditions for spray-drying mixture consisted of two parts of wall material solution and one part of ethanolic oregano extract when the feed flow rate was 40 mL/min and air inlet temperature -170 °C. Optimal concentration of wall materials in solution was 20% while the ratio of maltodextrin and gum arabic was 8.74:1.26.

A near-optimal low complexity sensor fusion technique for accurate indoor localization based on ultrasound time of arrival measurements from low-quality sensors

NASA Astrophysics Data System (ADS)

Mitilineos, Stelios A.; Argyreas, Nick D.; Thomopoulos, Stelios C. A.

2009-05-01

A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.

Organic antireflective coatings for 193-nm lithography

NASA Astrophysics Data System (ADS)

Trefonas, Peter, III; Blacksmith, Robert F.; Szmanda, Charles R.; Kavanagh, Robert J.; Adams, Timothy G.; Taylor, Gary N.; Coley, Suzanne; Pohlers, Gerd

1999-06-01

Organic anti-reflective coatings (ARCs) continue to play an important role in semiconductor manufacturing. These materials provide a convenient means of greatly reducing the resist photospeed swing and reflective notching. In this paper, we describe a novel class of ARC materials optimized for lithographic applications using 193 nm exposure tools. These ARCs are based upon polymers containing hydroxyl-alkyl methacrylate monomers for crosslinkable sites, styrene for a chromophore at 193 nm, and additional alkyl-methacrylate monomers as property modifiers. A glycouril crosslinker and a thermally-activated acidic catalyst provide a route to forming an impervious crosslinked film activate data high bake temperatures. ARC compositions can be adjusted to optimize the film's real and imaginary refractive indices. Selection of optimal target indices for 193 nm lithographic processing through simulations is described. Potential chromophores for 193 nm were explored using ZNDO modeling. We show how these theoretical studies were combined with material selection criteria to yield a versatile organic anti-reflectant film, Shipley 193 G0 ARC. Lithographic process data indicates the materials is capable of supporting high resolution patterning, with the line features displaying a sharp resist/ARC interface with low line edge roughness. The resist Eo swing is successfully reduced from 43 percent to 6 percent.

Discovery of CREBBP Bromodomain Inhibitors by High-Throughput Docking and Hit Optimization Guided by Molecular Dynamics.

PubMed

Xu, Min; Unzue, Andrea; Dong, Jing; Spiliotopoulos, Dimitrios; Nevado, Cristina; Caflisch, Amedeo

2016-02-25

We have identified two chemotypes of CREBBP bromodomain ligands by fragment-based high-throughput docking. Only 17 molecules from the original library of two-million compounds were tested in vitro. Optimization of the two low-micromolar hits, the 4-acylpyrrole 1 and acylbenzene 9, was driven by molecular dynamics results which suggested improvement of the polar interactions with the Arg1173 side chain at the rim of the binding site. The synthesis of only two derivatives of 1 yielded the 4-acylpyrrole 6 which shows a single-digit micromolar affinity for the CREBBP bromodomain and a ligand efficiency of 0.34 kcal/mol per non-hydrogen atom. Optimization of the acylbenzene hit 9 resulted in a series of derivatives with nanomolar potencies, good ligand efficiency and selectivity (see Unzue, A.; Xu, M.; Dong, J.; Wiedmer, L.; Spiliotopoulos, D.; Caflisch, A.; Nevado, C.Fragment-Based Design of Selective Nanomolar Ligands of the CREBBP Bromodomain. J. Med. Chem. 2015, DOI: 10.1021/acs.jmedchem.5b00172). The in silico predicted binding mode of the acylbenzene derivative 10 was validated by solving the structure of the complex with the CREBBP bromodomain.

Heuristic for Critical Machine Based a Lot Streaming for Two-Stage Hybrid Production Environment

NASA Astrophysics Data System (ADS)

Vivek, P.; Saravanan, R.; Chandrasekaran, M.; Pugazhenthi, R.

2017-03-01

Lot streaming in Hybrid flowshop [HFS] is encountered in many real world problems. This paper deals with a heuristic approach for Lot streaming based on critical machine consideration for a two stage Hybrid Flowshop. The first stage has two identical parallel machines and the second stage has only one machine. In the second stage machine is considered as a critical by valid reasons these kind of problems is known as NP hard. A mathematical model developed for the selected problem. The simulation modelling and analysis were carried out in Extend V6 software. The heuristic developed for obtaining optimal lot streaming schedule. The eleven cases of lot streaming were considered. The proposed heuristic was verified and validated by real time simulation experiments. All possible lot streaming strategies and possible sequence under each lot streaming strategy were simulated and examined. The heuristic consistently yielded optimal schedule consistently in all eleven cases. The identification procedure for select best lot streaming strategy was suggested.

Separation of sodium chloride from the evaporated residue of the reverse osmosis reject generated in the leather industry--optimization by response surface methodology.

PubMed

Boopathy, R; Sekaran, G

2014-08-01

Reverse osmosis (RO) concentrate is being evaporated by solar/thermal evaporators to meet zero liquid discharge standards. The resulted evaporated residue (ER) is contaminated with both organic and inorganic mixture of salts. The generation of ER is exceedingly huge in the leather industry, which is being collected and stored under the shelter to avoid groundwater contamination by the leachate. In the present investigation, a novel process for the separation of sodium chloride from ER was developed, to reduce the environmental impact on RO concentrate discharge. The sodium chloride was selectively separated by the reactive precipitation method using hydrogen chloride gas. The selected process variables were optimized for maximum yield ofNaCl from the ER (optimum conditions were pH, 8.0; temperature, 35 degrees C; concentration of ER, 600 g/L and HCl purging time, 3 min). The recovered NaCl purity was verified using a cyclic voltagramm.

Ultrasound-assisted enzymatic extraction and antioxidant activity of polysaccharides from pumpkin (Cucurbita moschata).

PubMed

Wu, Hao; Zhu, Junxiang; Diao, Wenchao; Wang, Chengrong

2014-11-26

An efficient ultrasound-assisted enzymatic extraction (UAEE) of Cucurbita moschata polysaccharides (CMCP) was established and the CMCP antioxidant activities were studied. The UAEE operating parameters (extraction temperature, ultrasonic power, pH, and liquid-to-material ratio) were optimized using the central composite design (CCD) and the mass transfer kinetic study in UAEE procedure was used to select the optimal extraction time. Enzymolysis and ultrasonication that were simultaneously conducted was selected as the UAEE synergistic model and the optimum extraction conditions with a maximum polysaccharide yield of 4.33 ± 0.15% were as follows: extraction temperature, 51.5 °C; ultrasonic power, 440 W; pH, 5.0; liquid-to-material ratio, 5.70:1 mL/g; and extraction time, 20 min. Evaluation of the antioxidant activity in vitro suggested that CMCP has good potential as a natural antioxidant used in the food or medicine industry because of their high reducing power and positive radical scavenging activity for DPPH radical. Copyright © 2014 Elsevier Ltd. All rights reserved.

Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets.

PubMed

Feinstein, Wei P; Brylinski, Michal

2015-01-01

Computational approaches have emerged as an instrumental methodology in modern research. For example, virtual screening by molecular docking is routinely used in computer-aided drug discovery. One of the critical parameters for ligand docking is the size of a search space used to identify low-energy binding poses of drug candidates. Currently available docking packages often come with a default protocol for calculating the box size, however, many of these procedures have not been systematically evaluated. In this study, we investigate how the docking accuracy of AutoDock Vina is affected by the selection of a search space. We propose a new procedure for calculating the optimal docking box size that maximizes the accuracy of binding pose prediction against a non-redundant and representative dataset of 3,659 protein-ligand complexes selected from the Protein Data Bank. Subsequently, we use the Directory of Useful Decoys, Enhanced to demonstrate that the optimized docking box size also yields an improved ranking in virtual screening. Binding pockets in both datasets are derived from the experimental complex structures and, additionally, predicted by eFindSite. A systematic analysis of ligand binding poses generated by AutoDock Vina shows that the highest accuracy is achieved when the dimensions of the search space are 2.9 times larger than the radius of gyration of a docking compound. Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking. For instance, using predicted ligand binding sites, the average enrichment factor calculated for the top 1 % (10 %) of the screening library is 8.20 (3.28) for the optimized protocol, compared to 7.67 (3.19) for the default procedure. Depending on the evaluation metric, the optimal docking box size gives better ranking in virtual screening for about two-thirds of target proteins. This fully automated procedure can be used to optimize docking protocols in order to improve the ranking accuracy in production virtual screening simulations. Importantly, the optimized search space systematically yields better results than the default method not only for experimental pockets, but also for those predicted from protein structures. A script for calculating the optimal docking box size is freely available at www.brylinski.org/content/docking-box-size. Graphical AbstractWe developed a procedure to optimize the box size in molecular docking calculations. Left panel shows the predicted binding pose of NADP (green sticks) compared to the experimental complex structure of human aldose reductase (blue sticks) using a default protocol. Right panel shows the docking accuracy using an optimized box size.

Optimized conditions for chelation of yttrium-90-DOTA immunoconjugates.

PubMed

Kukis, D L; DeNardo, S J; DeNardo, G L; O'Donnell, R T; Meares, C F

1998-12-01

Radioimmunotherapy (RIT) with 90Y-labeled immunoconjugates has shown promise in clinical trials. The macrocyclic chelating agent 1,4,7,10-tetraazacyclododecane-N,N',N",N"'-tetraacetic acid (DOTA) binds 90Y with extraordinary stability, minimizing the toxicity of 90Y-DOTA immunoconjugates arising from loss of 90Y to bone. However, reported 90Y-DOTA immunoconjugate product yields have been typically only < or =50%. Improved yields are needed for RIT with 90Y-DOTA immunoconjugates to be practical. (S) 2-[p-(bromoacetamido)benzyl]-DOTA (BAD) was conjugated to the monoclonal antibody Lym-1 via 2-iminothiolane (2IT). The immunoconjugate product, 2IT-BAD-Lym-1, was labeled in excess yttrium in various buffers over a range of concentrations and pH. Kinetic studies were performed in selected buffers to estimate radiolabeling reaction times under prospective radiopharmacy labeling conditions. The effect of temperature on reaction kinetics was examined. Optimal radiolabeling conditions were identified and used in eight radiolabeling experiments with 2IT-BAD-Lym-1 and a second immunoconjugate, DOTA-peptide-chimeric L6, with 248-492 MBq (6.7-13.3 mCi) of 90Y. Ammonium acetate buffer (0.5 M) was associated with the highest uptake of yttrium. On the basis of kinetic data, the time required to chelate 94% of 90Y (four half-times) under prospective radiopharmacy labeling conditions in 0.5 M ammonium acetate was 17-148 min at pH 6.5, but it was only 1-10 min at pH 7.5. Raising the reaction temperature from 25 degrees C to 37 degrees C markedly increased the chelation rate. Optimal radiolabeling conditions were identified as: 30-min reaction time, 0.5 M ammonium acetate buffer, pH 7-7.5 and 37 degrees C. In eight labeling experiments under optimal conditions, a mean product yield (+/- s.d.) of 91%+/-8% was achieved, comparable to iodination yields. The specific activity of final products was 74-130 MBq (2.0-3.5 mCi) of 90Y per mg of monoclonal antibody. The immunoreactivity of 90Y-labeled immunoconjugates was 100%+/-11%. The optimization of 90Y-DOTA chelation conditions represents an important advance in 90Y RIT because it facilitates the dependable and cost-effective preparation of 90Y-DOTA pharmaceuticals.

[Analyzing and modeling methods of near infrared spectroscopy for in-situ prediction of oil yield from oil shale].

PubMed

Liu, Jie; Zhang, Fu-Dong; Teng, Fei; Li, Jun; Wang, Zhi-Hong

2014-10-01

In order to in-situ detect the oil yield of oil shale, based on portable near infrared spectroscopy analytical technology, with 66 rock core samples from No. 2 well drilling of Fuyu oil shale base in Jilin, the modeling and analyzing methods for in-situ detection were researched. By the developed portable spectrometer, 3 data formats (reflectance, absorbance and K-M function) spectra were acquired. With 4 different modeling data optimization methods: principal component-mahalanobis distance (PCA-MD) for eliminating abnormal samples, uninformative variables elimination (UVE) for wavelength selection and their combina- tions: PCA-MD + UVE and UVE + PCA-MD, 2 modeling methods: partial least square (PLS) and back propagation artificial neural network (BPANN), and the same data pre-processing, the modeling and analyzing experiment were performed to determine the optimum analysis model and method. The results show that the data format, modeling data optimization method and modeling method all affect the analysis precision of model. Results show that whether or not using the optimization method, reflectance or K-M function is the proper spectrum format of the modeling database for two modeling methods. Using two different modeling methods and four different data optimization methods, the model precisions of the same modeling database are different. For PLS modeling method, the PCA-MD and UVE + PCA-MD data optimization methods can improve the modeling precision of database using K-M function spectrum data format. For BPANN modeling method, UVE, UVE + PCA-MD and PCA- MD + UVE data optimization methods can improve the modeling precision of database using any of the 3 spectrum data formats. In addition to using the reflectance spectra and PCA-MD data optimization method, modeling precision by BPANN method is better than that by PLS method. And modeling with reflectance spectra, UVE optimization method and BPANN modeling method, the model gets the highest analysis precision, its correlation coefficient (Rp) is 0.92, and its standard error of prediction (SEP) is 0.69%.

Increasing efficiency of human mesenchymal stromal cell culture by optimization of microcarrier concentration and design of medium feed.

PubMed

Chen, Allen Kuan-Liang; Chew, Yi Kong; Tan, Hong Yu; Reuveny, Shaul; Weng Oh, Steve Kah

2015-02-01

Large amounts of human mesenchymal stromal cells (MSCs) are needed for clinical cellular therapy. In a previous publication, we described a microcarrier-based process for expansion of MSCs. The present study optimized this process by selecting suitable basal media, microcarrier concentration and feeding regime to achieve higher cell yields and more efficient medium utilization. MSCs were expanded in stirred cultures on Cytodex 3 microcarriers with media containing 10% fetal bovine serum. Process optimization was carried out in spinner flasks. A 2-L bioreactor with an automated feeding system was used to validate the optimized parameters explored in spinner flask cultures. Minimum essential medium-α-based medium supported faster MSC growth on microcarriers than did Dulbecco's modified Eagle's medium (doubling time, 31.6 ± 1.4 vs 42 ± 1.7 h) and shortened the process time. At microcarrier concentration of 8 mg/mL, a high cell concentration of 1.08 × 10(6) cells/mL with confluent cell concentration of 4.7 × 10(4)cells/cm(2) was achieved. Instead of 50% medium exchange every 2 days, we have designed a full medium feed that is based on glucose consumption rate. The optimal medium feed that consisted of 1.5 g/L glucose supported MSC growth to full confluency while achieving the low medium usage efficiency of 3.29 mL/10(6)cells. Finally, a controlled bioreactor with the optimized parameters achieved maximal confluent cell concentration with 16-fold expansion and a further improved medium usage efficiency of 1.68 mL/10(6)cells. We have optimized the microcarrier-based platform for expansion of MSCs that generated high cell yields in a more efficient and cost-effective manner. This study highlighted the critical parameters in the optimization of MSC production process. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

A Bayesian multi-stage cost-effectiveness design for animal studies in stroke research

PubMed Central

Cai, Chunyan; Ning, Jing; Huang, Xuelin

2017-01-01

Much progress has been made in the area of adaptive designs for clinical trials. However, little has been done regarding adaptive designs to identify optimal treatment strategies in animal studies. Motivated by an animal study of a novel strategy for treating strokes, we propose a Bayesian multi-stage cost-effectiveness design to simultaneously identify the optimal dose and determine the therapeutic treatment window for administrating the experimental agent. We consider a non-monotonic pattern for the dose-schedule-efficacy relationship and develop an adaptive shrinkage algorithm to assign more cohorts to admissible strategies. We conduct simulation studies to evaluate the performance of the proposed design by comparing it with two standard designs. These simulation studies show that the proposed design yields a significantly higher probability of selecting the optimal strategy, while it is generally more efficient and practical in terms of resource usage. PMID:27405325

The quasi-optimality criterion in the linear functional strategy

NASA Astrophysics Data System (ADS)

Kindermann, Stefan; Pereverzyev, Sergiy, Jr.; Pilipenko, Andrey

2018-07-01

The linear functional strategy for the regularization of inverse problems is considered. For selecting the regularization parameter therein, we propose the heuristic quasi-optimality principle and some modifications including the smoothness of the linear functionals. We prove convergence rates for the linear functional strategy with these heuristic rules taking into account the smoothness of the solution and the functionals and imposing a structural condition on the noise. Furthermore, we study these noise conditions in both a deterministic and stochastic setup and verify that for mildly-ill-posed problems and Gaussian noise, these conditions are satisfied almost surely, where on the contrary, in the severely-ill-posed case and in a similar setup, the corresponding noise condition fails to hold. Moreover, we propose an aggregation method for adaptively optimizing the parameter choice rule by making use of improved rates for linear functionals. Numerical results indicate that this method yields better results than the standard heuristic rule.

Improving sperm banking efficiency in endangered species through the use of a sperm selection method in brown bear (Ursus arctos) thawed sperm.

PubMed

Anel-Lopez, L; Ortega-Ferrusola, C; Álvarez, M; Borragán, S; Chamorro, C; Peña, F J; Morrell, J; Anel, L; de Paz, P

2017-06-26

Sperm selection methods such as Single Layer Centrifugation (SLC) have been demonstrated to be a useful tool to improve the quality of sperm samples and therefore to increase the efficiency of other artificial reproductive techniques in several species. This procedure could help to improve the quality of genetic resource banks, which is essential for endangered species. In contrast, these sperm selection methods are optimized and focused on farm animals, where the recovery task is not as important as in endangered species because of their higher sperm availability. The aim of this study was to evaluate two centrifugation methods (300 x g/20 min and 600 x g/10 min) and three concentrations of SLC media (Androcoll-Bear -80, 65 and 50%) to optimise the procedure in order to recover as many sperm with the highest quality as possible. Sperm morphology could be important in the hydrodynamic relationship between the cell and centrifugation medium and thus the effect of sperm head morphometry on sperm yield and its hydrodynamic relationship were studied. The samples selected with Androcoll-Bear 65% showed a very good yield (53.1 ± 2.9) although the yield from Androcoll-Bear 80% was lower (19.3 ± 3.3). The latter showed higher values of motility than the control immediately after post-thawing selection. However, both concentrations of colloid (65 and 80%) showed higher values of viable sperm and viable sperm with intact acrosome than the control. After an incubation of 2 h at 37 °C, the samples from Androcoll-Bear 80% had higher kinematics and proportion of viable sperm with intact acrosome. In the morphometric analysis, the sperm selected by the Androcoll-Bear 80% showed a head with a bigger area which was more elongated than the sperm from other treatments. We conclude that sperm selection with Androcoll-Bear at either 65% or 80% is a suitable technique that allows a sperm population with better quality than the initial sample to be obtained. We recommend the use of Androcoll-Bear 65% since the yield is better than Androcoll-Bear 80%. Our findings pave the way for further research on application of sperm selection techniques to sperm banking in the brown bear.

Optimal low thrust geocentric transfer. [mission analysis computer program

NASA Technical Reports Server (NTRS)

Edelbaum, T. N.; Sackett, L. L.; Malchow, H. L.

1973-01-01

A computer code which will rapidly calculate time-optimal low thrust transfers is being developed as a mission analysis tool. The final program will apply to NEP or SEP missions and will include a variety of environmental effects. The current program assumes constant acceleration. The oblateness effect and shadowing may be included. Detailed state and costate equations are given for the thrust effect, oblateness effect, and shadowing. A simple but adequate model yields analytical formulas for power degradation due to the Van Allen radiation belts for SEP missions. The program avoids the classical singularities by the use of equinoctial orbital elements. Kryloff-Bogoliuboff averaging is used to facilitate rapid calculation. Results for selected cases using the current program are given.

Preliminary Design of a Manned Nuclear Electric Propulsion Vehicle Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Irwin, Ryan W.; Tinker, Michael L.

2005-01-01

Nuclear electric propulsion (NEP) vehicles will be needed for future manned missions to Mars and beyond. Candidate designs must be identified for further detailed design from a large array of possibilities. Genetic algorithms have proven their utility in conceptual design studies by effectively searching a large design space to pinpoint unique optimal designs. This research combined analysis codes for NEP subsystems with a genetic algorithm. The use of penalty functions with scaling ratios was investigated to increase computational efficiency. Also, the selection of design variables for optimization was considered to reduce computation time without losing beneficial design search space. Finally, trend analysis of a reference mission to the asteroids yielded a group of candidate designs for further analysis.

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

PubMed

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

2009-01-01

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

Optimization of Enzymatic Saccharification of Alkali Pretreated Parthenium sp. Using Response Surface Methodology

PubMed Central

Pandiyan, K.; Tiwari, Rameshwar; Singh, Surender; Nain, Pawan K. S.; Rana, Sarika; Arora, Anju; Singh, Shashi B.; Nain, Lata

2014-01-01

Parthenium sp. is a noxious weed which threatens the environment and biodiversity due to its rapid invasion. This lignocellulosic weed was investigated for its potential in biofuel production by subjecting it to mild alkali pretreatment followed by enzymatic saccharification which resulted in significant amount of fermentable sugar yield (76.6%). Optimization of enzymatic hydrolysis variables such as temperature, pH, enzyme, and substrate loading was carried out using central composite design (CCD) in response to surface methodology (RSM) to achieve the maximum saccharification yield. Data obtained from RSM was validated using ANOVA. After the optimization process, a model was proposed with predicted value of 80.08% saccharification yield under optimum conditions which was confirmed by the experimental value of 85.80%. This illustrated a good agreement between predicted and experimental response (saccharification yield). The saccharification yield was enhanced by enzyme loading and reduced by temperature and substrate loading. This study reveals that under optimized condition, sugar yield was significantly increased which was higher than earlier reports and promises the use of Parthenium sp. biomass as a feedstock for bioethanol production. PMID:24900917

QTL mapping of root traits in phosphorus-deficient soils reveals important genomic regions for improving NDVI and grain yield in barley.

PubMed

Gong, Xue; McDonald, Glenn

2017-09-01

Major QTLs for root rhizosheath size are not correlated with grain yield or yield response to phosphorus. Important QTLs were found to improve phosphorus efficiency. Root traits are important for phosphorus (P) acquisition, but they are often difficult to characterize and their breeding values are seldom assessed under field conditions. This has shed doubts on using seedling-based criteria of root traits to select and breed for P efficiency. Eight root traits were assessed under controlled conditions in a barley doubled-haploid population in soils differing in P levels. The population was also phenotyped for grain yield, normalized difference vegetation index (NDVI), grain P uptake and P utilization efficiency at maturity (PutE GY ) under field conditions. Several quantitative traits loci (QTLs) from the root screening and the field trials were co-incident. QTLs for root rhizosheath size and root diameter explained the highest phenotypic variation in comparison to QTLs for other root traits. Shared QTLs were found between root diameter and grain yield, and total root length and PutE GY . A common major QTL for rhizosheath size and NDVI was mapped to the HvMATE gene marker on chromosome 4H. Collocations between major QTLs for NDVI and grain yield were detected on chromosomes 6H and 7H. When results from BIP and MET were combined, QTLs detected for grain yield were also those QTLs found for NDVI. QTLs qGY5H, qGY6H and qGY7Hb on 7H were robust QTLs in improving P efficiency. A selection of multiple loci may be needed to optimize the breeding outcomes due to the QTL x Environment interaction. We suggest that rhizosheath size alone is not a reliable trait to predict P efficiency or grain yield.

The Effect of Carbonaceous Reductant Selection on Chromite Pre-reduction

NASA Astrophysics Data System (ADS)

Kleynhans, E. L. J.; Beukes, J. P.; Van Zyl, P. G.; Bunt, J. R.; Nkosi, N. S. B.; Venter, M.

2017-04-01

Ferrochrome (FeCr) production is an energy-intensive process. Currently, the pelletized chromite pre-reduction process, also referred to as solid-state reduction of chromite, is most likely the FeCr production process with the lowest specific electricity consumption, i.e., MWh/t FeCr produced. In this study, the effects of carbonaceous reductant selection on chromite pre-reduction and cured pellet strength were investigated. Multiple linear regression analysis was employed to evaluate the effect of reductant characteristics on the aforementioned two parameters. This yielded mathematical solutions that can be used by FeCr producers to select reductants more optimally in future. Additionally, the results indicated that hydrogen (H)- (24 pct) and volatile content (45.8 pct) were the most significant contributors for predicting variance in pre-reduction and compressive strength, respectively. The role of H within this context is postulated to be linked to the ability of a reductant to release H that can induce reduction. Therefore, contrary to the current operational selection criteria, the authors believe that thermally untreated reductants ( e.g., anthracite, as opposed to coke or char), with volatile contents close to the currently applied specification (to ensure pellet strength), would be optimal, since it would maximize H content that would enhance pre-reduction.

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece.

PubMed

Economopoulou, M A; Economopoulou, A A; Economopoulos, A P

2013-11-01

The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/or wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 milliont/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin. Copyright © 2013 Elsevier Ltd. All rights reserved.

One-step synthesis of high-yield biodiesel from waste cooking oils by a novel and highly methanol-tolerant immobilized lipase.

PubMed

Wang, Xiumei; Qin, Xiaoli; Li, Daoming; Yang, Bo; Wang, Yonghua

2017-07-01

This study reported a novel immobilized MAS1 lipase from marine Streptomyces sp. strain W007 for synthesizing high-yield biodiesel from waste cooking oils (WCO) with one-step addition of methanol in a solvent-free system. Immobilized MAS1 lipase was selected for the transesterification reactions with one-step addition of methanol due to its much more higher biodiesel yield (89.50%) when compared with the other three commercial immobilized lipases (<10%). The highest biodiesel yield (95.45%) was acquired with one-step addition of methanol under the optimized conditions. Moreover, it was observed that immobilized MAS1 lipase retained approximately 70% of its initial activity after being used for four batch cycles. Finally, the obtained biodiesel was further characterized using FT-IR, 1 H and 13 C NMR spectroscopy. These findings indicated that immobilized MAS1 lipase is a promising catalyst for biodiesel production from WCO with one-step addition of methanol under high methanol concentration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of parameter and interaction between parameter of the microwave assisted transesterification process of coconut oil using response surface methodology

NASA Astrophysics Data System (ADS)

Hidayanti, Nur; Suryanto, A.; Qadariyah, L.; Prihatini, P.; Mahfud, Mahfud

2015-12-01

A simple batch process was designed for the transesterification of coconut oil to alkyl esters using microwave assisted method. The product with yield above 93.225% of alkyl ester is called the biodiesel fuel. Response surface methodology was used to design the experiment and obtain the maximum possible yield of biodiesel in the microwave-assisted reaction from coconut oil with KOH as the catalyst. The results showed that the time reaction and concentration of KOH catalyst have significant effects on yield of alkyl ester. Based on the response surface methodology using the selected operating conditions, the time of reaction and concentration of KOH catalyst in transesterification process were 150 second and 0.25%w/w, respectively. The largest predicted and experimental yield of alkyl esters (biodiesel) under the optimal conditions are 101.385% and 93.225%, respectively. Our findings confirmed the successful development of process for the transesterification reaction of coconut oil by microwave-assisted heating, which is effective and time-saving for alkyl ester production.

Estimation of biogas and methane yields in an UASB treating potato starch processing wastewater with backpropagation artificial neural network.

PubMed

Antwi, Philip; Li, Jianzheng; Boadi, Portia Opoku; Meng, Jia; Shi, En; Deng, Kaiwen; Bondinuba, Francis Kwesi

2017-03-01

Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW). Anaerobic process parameters were optimized to identify their importance on methanation. pH, total chemical oxygen demand, ammonium, alkalinity, total Kjeldahl nitrogen, total phosphorus, volatile fatty acids and hydraulic retention time selected based on principal component analysis were used as input variables, whiles biogas and methane yield were employed as target variables. Quasi-Newton method and conjugate gradient backpropagation algorithms were best among eleven training algorithms. Coefficient of determination (R 2 ) of the BP-ANN reached 98.72% and 97.93% whiles MnLR model attained 93.9% and 91.08% for biogas and methane yield, respectively. Compared with the MnLR model, BP-ANN model demonstrated significant performance, suggesting possible control of the anaerobic digestion process with the BP-ANN model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization of contoured hypersonic scramjet inlets with a least-squares parabolized Navier-Stokes procedure

NASA Technical Reports Server (NTRS)

Korte, J. J.; Auslender, A. H.

1993-01-01

A new optimization procedure, in which a parabolized Navier-Stokes solver is coupled with a non-linear least-squares optimization algorithm, is applied to the design of a Mach 14, laminar two-dimensional hypersonic subscale flight inlet with an internal contraction ratio of 15:1 and a length-to-throat half-height ratio of 150:1. An automated numerical search of multiple geometric wall contours, which are defined by polynomical splines, results in an optimal geometry that yields the maximum total-pressure recovery for the compression process. Optimal inlet geometry is obtained for both inviscid and viscous flows, with the assumption that the gas is either calorically or thermally perfect. The analysis with a calorically perfect gas results in an optimized inviscid inlet design that is defined by two cubic splines and yields a mass-weighted total-pressure recovery of 0.787, which is a 23% improvement compared with the optimized shock-canceled two-ramp inlet design. Similarly, the design procedure obtains the optimized contour for a viscous calorically perfect gas to yield a mass-weighted total-pressure recovery value of 0.749. Additionally, an optimized contour for a viscous thermally perfect gas is obtained to yield a mass-weighted total-pressure recovery value of 0.768. The design methodology incorporates both complex fluid dynamic physics and optimal search techniques without an excessive compromise of computational speed; hence, this methodology is a practical technique that is applicable to optimal inlet design procedures.

Cold adaptation generates mutations associated with the growth of influenza B vaccine viruses.

PubMed

Kim, Hyunsuh; Velkov, Tony; Camuglia, Sarina; Rockman, Steven P; Tannock, Gregory A

2015-10-26

Seasonal inactivated influenza vaccines are usually trivalent or quadrivalent and are prepared from accredited seed viruses. Yields of influenza A seed viruses can be enhanced by gene reassortment with high-yielding donor strains, but similar approaches for influenza B seed viruses have been largely unsuccessful. For vaccine manufacture influenza B seed viruses are usually adapted for high-growth by serial passage. Influenza B antigen yields so obtained are often unpredictable and selection of influenza B seed viruses by this method can be a rate-limiting step in seasonal influenza vaccine manufacture. We recently have shown that selection of stable cold-adapted mutants from seasonal epidemic influenza B viruses is associated with improved growth. In this study, specific mutations were identified that were responsible for growth enhancement as a consequence of adaptation to growth at lower temperatures. Molecular analysis revealed that the following mutations in the HA, NP and NA genes are required for enhanced viral growth: G156/N160 in the HA, E253, G375 in the NP and T146 in the NA genes. These results demonstrate that the growth of seasonal influenza B viruses can be optimized or improved significantly by specific gene modifications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improving database enrichment through ensemble docking

NASA Astrophysics Data System (ADS)

Rao, Shashidhar; Sanschagrin, Paul C.; Greenwood, Jeremy R.; Repasky, Matthew P.; Sherman, Woody; Farid, Ramy

2008-09-01

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.

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

PubMed Central

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

2011-01-01

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

The emotion system promotes diversity and evolvability

PubMed Central

Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J.; Aksnes, Dag L.; Mangel, Marc; Jørgensen, Christian

2014-01-01

Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels. PMID:25100697

The emotion system promotes diversity and evolvability.

PubMed

Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J; Aksnes, Dag L; Mangel, Marc; Jørgensen, Christian

2014-09-22

Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels.

Precipitation-runoff modeling system; user's manual

USGS Publications Warehouse

Leavesley, G.H.; Lichty, R.W.; Troutman, B.M.; Saindon, L.G.

1983-01-01

The concepts, structure, theoretical development, and data requirements of the precipitation-runoff modeling system (PRMS) are described. The precipitation-runoff modeling system is a modular-design, deterministic, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on streamflow, sediment yields, and general basin hydrology. Basin response to normal and extreme rainfall and snowmelt can be simulated to evaluate changes in water balance relationships, flow regimes, flood peaks and volumes, soil-water relationships, sediment yields, and groundwater recharge. Parameter-optimization and sensitivity analysis capabilites are provided to fit selected model parameters and evaluate their individual and joint effects on model output. The modular design provides a flexible framework for continued model system enhancement and hydrologic modeling research and development. (Author 's abstract)

SU-D-12A-06: A Comprehensive Parameter Analysis for Low Dose Cone-Beam CT Reconstruction

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

Lu, W; Southern Medical University, Guangzhou; Yan, H

Purpose: There is always a parameter in compressive sensing based iterative reconstruction (IR) methods low dose cone-beam CT (CBCT), which controls the weight of regularization relative to data fidelity. A clear understanding of the relationship between image quality and parameter values is important. The purpose of this study is to investigate this subject based on experimental data and a representative advanced IR algorithm using Tight-frame (TF) regularization. Methods: Three data sets of a Catphan phantom acquired at low, regular and high dose levels are used. For each tests, 90 projections covering a 200-degree scan range are used for reconstruction. Threemore » different regions-of-interest (ROIs) of different contrasts are used to calculate contrast-to-noise ratios (CNR) for contrast evaluation. A single point structure is used to measure modulation transfer function (MTF) for spatial-resolution evaluation. Finally, we analyze CNRs and MTFs to study the relationship between image quality and parameter selections. Results: It was found that: 1) there is no universal optimal parameter. The optimal parameter value depends on specific task and dose level. 2) There is a clear trade-off between CNR and resolution. The parameter for the best CNR is always smaller than that for the best resolution. 3) Optimal parameters are also dose-specific. Data acquired under a high dose protocol require less regularization, yielding smaller optimal parameter values. 4) Comparing with conventional FDK images, TF-based CBCT images are better under a certain optimally selected parameters. The advantages are more obvious for low dose data. Conclusion: We have investigated the relationship between image quality and parameter values in the TF-based IR algorithm. Preliminary results indicate optimal parameters are specific to both the task types and dose levels, providing guidance for selecting parameters in advanced IR algorithms. This work is supported in part by NIH (1R01CA154747-01)« less

Formulation and optimization of solid lipid nanoparticle formulation for pulmonary delivery of budesonide using Taguchi and Box-Behnken design.

PubMed

Emami, J; Mohiti, H; Hamishehkar, H; Varshosaz, J

2015-01-01

Budesonide is a potent non-halogenated corticosteroid with high anti-inflammatory effects. The lungs are an attractive route for non-invasive drug delivery with advantages for both systemic and local applications. The aim of the present study was to develop, characterize and optimize a solid lipid nanoparticle system to deliver budesonide to the lungs. Budesonide-loaded solid lipid nanoparticles were prepared by the emulsification-solvent diffusion method. The impact of various processing variables including surfactant type and concentration, lipid content organic and aqueous volume, and sonication time were assessed on the particle size, zeta potential, entrapment efficiency, loading percent and mean dissolution time. Taguchi design with 12 formulations along with Box-Behnken design with 17 formulations was developed. The impact of each factor upon the eventual responses was evaluated, and the optimized formulation was finally selected. The size and morphology of the prepared nanoparticles were studied using scanning electron microscope. Based on the optimization made by Design Expert 7(®) software, a formulation made of glycerol monostearate, 1.2 % polyvinyl alcohol (PVA), weight ratio of lipid/drug of 10 and sonication time of 90 s was selected. Particle size, zeta potential, entrapment efficiency, loading percent, and mean dissolution time of adopted formulation were predicted and confirmed to be 218.2 ± 6.6 nm, -26.7 ± 1.9 mV, 92.5 ± 0.52 %, 5.8 ± 0.3 %, and 10.4 ± 0.29 h, respectively. Since the preparation and evaluation of the selected formulation within the laboratory yielded acceptable results with low error percent, the modeling and optimization was justified. The optimized formulation co-spray dried with lactose (hybrid microparticles) displayed desirable fine particle fraction, mass median aerodynamic diameter (MMAD), and geometric standard deviation of 49.5%, 2.06 μm, and 2.98 μm; respectively. Our results provide fundamental data for the application of SLNs in pulmonary delivery system of budesonide.

Formulation and optimization of solid lipid nanoparticle formulation for pulmonary delivery of budesonide using Taguchi and Box-Behnken design

PubMed Central

Emami, J.; Mohiti, H.; Hamishehkar, H.; Varshosaz, J.

2015-01-01

Budesonide is a potent non-halogenated corticosteroid with high anti-inflammatory effects. The lungs are an attractive route for non-invasive drug delivery with advantages for both systemic and local applications. The aim of the present study was to develop, characterize and optimize a solid lipid nanoparticle system to deliver budesonide to the lungs. Budesonide-loaded solid lipid nanoparticles were prepared by the emulsification-solvent diffusion method. The impact of various processing variables including surfactant type and concentration, lipid content organic and aqueous volume, and sonication time were assessed on the particle size, zeta potential, entrapment efficiency, loading percent and mean dissolution time. Taguchi design with 12 formulations along with Box-Behnken design with 17 formulations was developed. The impact of each factor upon the eventual responses was evaluated, and the optimized formulation was finally selected. The size and morphology of the prepared nanoparticles were studied using scanning electron microscope. Based on the optimization made by Design Expert 7® software, a formulation made of glycerol monostearate, 1.2 % polyvinyl alcohol (PVA), weight ratio of lipid/drug of 10 and sonication time of 90 s was selected. Particle size, zeta potential, entrapment efficiency, loading percent, and mean dissolution time of adopted formulation were predicted and confirmed to be 218.2 ± 6.6 nm, -26.7 ± 1.9 mV, 92.5 ± 0.52 %, 5.8 ± 0.3 %, and 10.4 ± 0.29 h, respectively. Since the preparation and evaluation of the selected formulation within the laboratory yielded acceptable results with low error percent, the modeling and optimization was justified. The optimized formulation co-spray dried with lactose (hybrid microparticles) displayed desirable fine particle fraction, mass median aerodynamic diameter (MMAD), and geometric standard deviation of 49.5%, 2.06 μm, and 2.98 μm; respectively. Our results provide fundamental data for the application of SLNs in pulmonary delivery system of budesonide. PMID:26430454

Assessment of Cultivation Factors that Affect Biomass and Geraniol Production in Transgenic Tobacco Cell Suspension Cultures

PubMed Central

Vasilev, Nikolay; Schmitz, Christian; Grömping, Ulrike; Fischer, Rainer; Schillberg, Stefan

2014-01-01

A large-scale statistical experimental design was used to determine essential cultivation parameters that affect biomass accumulation and geraniol production in transgenic tobacco (Nicotiana tabacum cv. Samsun NN) cell suspension cultures. The carbohydrate source played a major role in determining the geraniol yield and factors such as filling volume, inoculum size and light were less important. Sucrose, filling volume and inoculum size had a positive effect on geraniol yield by boosting growth of plant cell cultures whereas illumination of the cultures stimulated the geraniol biosynthesis. We also found that the carbohydrates sucrose and mannitol showed polarizing effects on biomass and geraniol accumulation. Factors such as shaking frequency, the presence of conditioned medium and solubilizers had minor influence on both plant cell growth and geraniol content. When cells were cultivated under the screened conditions for all the investigated factors, the cultures produced ∼5.2 mg/l geraniol after 12 days of cultivation in shaking flasks which is comparable to the yield obtained in microbial expression systems. Our data suggest that industrial experimental designs based on orthogonal arrays are suitable for the selection of initial cultivation parameters prior to the essential medium optimization steps. Such designs are particularly beneficial in the early optimization steps when many factors must be screened, increasing the statistical power of the experiments without increasing the demand on time and resources. PMID:25117009

Assessment of cultivation factors that affect biomass and geraniol production in transgenic tobacco cell suspension cultures.

PubMed

Vasilev, Nikolay; Schmitz, Christian; Grömping, Ulrike; Fischer, Rainer; Schillberg, Stefan

2014-01-01

A large-scale statistical experimental design was used to determine essential cultivation parameters that affect biomass accumulation and geraniol production in transgenic tobacco (Nicotiana tabacum cv. Samsun NN) cell suspension cultures. The carbohydrate source played a major role in determining the geraniol yield and factors such as filling volume, inoculum size and light were less important. Sucrose, filling volume and inoculum size had a positive effect on geraniol yield by boosting growth of plant cell cultures whereas illumination of the cultures stimulated the geraniol biosynthesis. We also found that the carbohydrates sucrose and mannitol showed polarizing effects on biomass and geraniol accumulation. Factors such as shaking frequency, the presence of conditioned medium and solubilizers had minor influence on both plant cell growth and geraniol content. When cells were cultivated under the screened conditions for all the investigated factors, the cultures produced ∼ 5.2 mg/l geraniol after 12 days of cultivation in shaking flasks which is comparable to the yield obtained in microbial expression systems. Our data suggest that industrial experimental designs based on orthogonal arrays are suitable for the selection of initial cultivation parameters prior to the essential medium optimization steps. Such designs are particularly beneficial in the early optimization steps when many factors must be screened, increasing the statistical power of the experiments without increasing the demand on time and resources.

Optimizing anti-coking abilities of zeolites by ethylene diamine tetraacetie acid modification on catalytic fast pyrolysis of corn stalk

NASA Astrophysics Data System (ADS)

Zhang, Bo; Zhong, Zhaoping; Song, Zuwei; Ding, Kuan; Chen, Paul; Ruan, Roger

2015-12-01

In order to minimize coke yield during biomass catalytic fast pyrolysis (CFP) process, ethylene diamine tetraacetie acid (EDTA) chemical modification method is carried out to selectively remove the external framework aluminum of HZSM-5 catalyst. X-ray diffraction (XRD), nitrogen (N2)-adsorption and ammonia-temperature programmed desorption (NH3-TPD) techniques are employed to investigate the porosity and acidity characteristics of original and modified HZSM-5 samples. Py-GC/MS and thermo-gravimetric analyzer (TGA) experiments are further conducted to explore the catalytic effect of modified HZSM-5 samples on biomass CFP and to verify the positive effect on coke reduction. Results show that EDTA treatment does not damage the crystal structure of HZSM-5 zeolites, but leads to a slight increase of pore volume and pore size. Meanwhile, the elimination of the strong acid peak indicates the dealumination of outer surface of HZSM-5 zeolites. Treatment time of 2 h (labeled EDTA-2H) is optimal for acid removal and hydrocarbon formation. Among all modified catalysts, EDTA-2H performs the best for deacidification and can obviously increase the yields of positive chemical compositions in pyrolysis products. Besides, EDTA modification can improve the anti-coking properties of HZSM-5 zeolites, and EDTA-2H gives rise to the lowest coke yield.

Increasing crop yield and resilience with trehalose 6-phosphate: targeting a feast-famine mechanism in cereals for better source-sink optimization.

PubMed

Paul, Matthew J; Oszvald, Maria; Jesus, Claudia; Rajulu, Charukesi; Griffiths, Cara A

2017-07-20

Food security is a pressing global issue. New approaches are required to break through a yield ceiling that has developed in recent years for the major crops. As important as increasing yield potential is the protection of yield from abiotic stresses in an increasingly variable and unpredictable climate. Current strategies to improve yield include conventional breeding, marker-assisted breeding, quantitative trait loci (QTLs), mutagenesis, creation of hybrids, genetic modification (GM), emerging genome-editing technologies, and chemical approaches. A regulatory mechanism amenable to three of these approaches has great promise for large yield improvements. Trehalose 6-phosphate (T6P) synthesized in the low-flux trehalose biosynthetic pathway signals the availability of sucrose in plant cells as part of a whole-plant sucrose homeostatic mechanism. Modifying T6P content by GM, marker-assisted selection, and novel chemistry has improved yield in three major cereals under a range of water availabilities from severe drought through to flooding. Yield improvements have been achieved by altering carbon allocation and how carbon is used. Targeting T6P both temporally and spatially offers great promise for large yield improvements in productive (up to 20%) and marginal environments (up to 120%). This opinion paper highlights this important breakthrough in fundamental science for crop improvement. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Gas flow parameters in laser cutting of wood- nozzle design

Treesearch

Kali Mukherjee; Tom Grendzwell; Parwaiz A.A. Khan; Charles McMillin

1990-01-01

The Automated Lumber Processing System (ALPS) is an ongoing team research effort to optimize the yield of parts in a furniture rough mill. The process is designed to couple aspects of computer vision, computer optimization of yield, and laser cutting. This research is focused on optimizing laser wood cutting. Laser machining of lumber has the advantage over...

Solvent selection and optimization of α-chymotrypsin-catalyzed synthesis of N-Ac-Phe-Tyr-NH2 using mixture design and response surface methodology.

PubMed

Hu, Shih-Hao; Kuo, Chia-Hung; Chang, Chieh-Ming J; Liu, Yung-Chuan; Chiang, Wen-Dee; Shieh, Chwen-Jen

2012-01-01

A peptide, N-Ac-Phe-Tyr-NH(2) , with angiotensin I-converting enzyme (ACE) inhibitor activity was synthesized by an α-chymotrypsin-catalyzed condensation reaction of N-acetyl phenylalanine ethyl ester (N-Ac-Phe-OEt) and tyrosinamide (Tyr-NH(2) ). Three kinds of solvents: a Tris-HCl buffer (80 mM, pH 9.0), dimethylsulfoxide (DMSO), and acetonitrile were employed in this study. The optimum reaction solvent component was determined by simplex centroid mixture design. The synthesis efficiency was enhanced in an organic-aqueous solvent (Tris-HCl buffer: DMSO: acetonitrile = 2:1:1) in which 73.55% of the yield of N-Ac-Phe-Tyr-NH(2) could be achieved. Furthermore, the effect of reaction parameters on the yield was evaluated by response surface methodology (RSM) using a central composite rotatable design (CCRD). Based on a ridge max analysis, the optimum condition for this peptide synthesis included a reaction time of 7.4 min, a reaction temperature of 28.1°C, an enzyme activity of 98.9 U, and a substrate molar ratio (Phe:Tyr) of 1:2.8. The predicted and the actual (experimental) yields were 87.6 and 85.5%, respectively. The experimental design and RSM performed well in the optimization of synthesis of N-Ac-Phe-Tyr-NH(2) , so it is expected to be an effective method for obtaining a good yield of enzymatic peptide. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

A trust region approach with multivariate Padé model for optimal circuit design

NASA Astrophysics Data System (ADS)

Abdel-Malek, Hany L.; Ebid, Shaimaa E. K.; Mohamed, Ahmed S. A.

2017-11-01

Since the optimization process requires a significant number of consecutive function evaluations, it is recommended to replace the function by an easily evaluated approximation model during the optimization process. The model suggested in this article is based on a multivariate Padé approximation. This model is constructed using data points of ?, where ? is the number of parameters. The model is updated over a sequence of trust regions. This model avoids the slow convergence of linear models of ? and has features of quadratic models that need interpolation data points of ?. The proposed approach is tested by applying it to several benchmark problems. Yield optimization using such a direct method is applied to some practical circuit examples. Minimax solution leads to a suitable initial point to carry out the yield optimization process. The yield is optimized by the proposed derivative-free method for active and passive filter examples.

Selection and Characterization of Vegetable Crop Cultivars for use in Advanced Life Support Systems

NASA Technical Reports Server (NTRS)

Langhans, Robert W.

1997-01-01

Cultivar evaluation for controlled environments is a lengthy and multifaceted activity. The chapters of this thesis cover eight steps preparatory to yield trials, and the final step of cultivar selection after data are collected. The steps are as follows: 1. Examination of the literature on the crop and crop cultivars to assess the state of knowledge. 2. Selection of standard cultivars with which to explore crop response to major growth factors and determine set points for screening and, later, production. 3. Determination of practical growing techniques for the crop in controlled environments. 4. Design of experiments for determination of crop responses to the major growth factors, with particular emphasis on photoperiod, daily light integral and air temperature. 5. Developing a way of measuring yield appropriate to the crop type by sampling through the harvest period and calculating a productivity function. 6. Narrowing down the pool of cultivars and breeding lines according to a set of criteria and breeding history. 7. Determination of environmental set points for cultivar evaluation through calculating production cost as a function of set points and size of target facility. 8. Design of screening and yield trial experiments emphasizing efficient use of space. 9. Final evaluation of cultivars after data collection, in terms of production cost and value to the consumer. For each of the steps, relevant issues are addressed. In selecting standards to determine set points for screening, set points that optimize cost of production for the standards may not be applicable to all cultivars. Production of uniform and equivalent- sized seedlings is considered as a means of countering possible differences in seed vigor. Issues of spacing and re-spacing are also discussed.

Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.; Benediktsson, Jon Atli; Chanussot, Jocelyn

2011-01-01

The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

Development of an industrializable fermentation process for propionic acid production.

PubMed

Stowers, Chris C; Cox, Brad M; Rodriguez, Brandon A

2014-05-01

Propionic acid (PA) is a short-chain fatty acid with wide industrial application including uses in pharmaceuticals, herbicides, cosmetics, and food preservatives. As a three-carbon building block, PA also has potential as a precursor for high-volume commodity chemicals such as propylene. Currently, most PA is manufactured through petrochemical routes, which can be tied to increasing prices and volatility due to difficulty in demand forecasting and feedstock availability. Herein described are research advancements to develop an industrially feasible, renewable route to PA. Seventeen Propionibacterium strains were screened using glucose and sucrose as the carbon source to identify the best platform strain. Propionibacterium acidipropionici ATCC 4875 was selected as the platform strain and subsequent fermentation optimization studies were performed to maximize productivity and yield. Fermentation productivity was improved three-fold to exceed 2 g/l/h by densifying the inoculum source. Byproduct levels, particularly lactic and succinic acid, were reduced by optimizing fermentor headspace pressure and shear. Following achievement of commercially viable productivities, the lab-grade medium components were replaced with industrial counterparts to further reduce fermentation costs. A pure enzymatically treated corn mash (ECM) medium improved the apparent PA yield to 0.6 g/g (PA produced/glucose consumed), but it came at the cost of reduced productivity. Supplementation of ECM with cyanocobalamin restored productivity to near lab-grade media levels. The optimized ECM recipe achieved a productivity of 0.5 g/l/h with an apparent PA yield of 0.60 g/g corresponding to a media cost <1 USD/kg of PA. These improvements significantly narrow the gap between the fermentation and incumbent petrochemical processes, which is estimated to have a manufacturing cost of 0.82 USD/kg in 2017.

Comparison of supercritical fluid extraction and ultrasound-assisted extraction of fatty acids from quince (Cydonia oblonga Miller) seed using response surface methodology and central composite design.

PubMed

Daneshvand, Behnaz; Ara, Katayoun Mahdavi; Raofie, Farhad

2012-08-24

Fatty acids of Cydonia oblonga Miller cultivated in Iran were obtained by supercritical (carbon dioxide) extraction and ultrasound-assisted extraction methods. The oils were analyzed by capillary gas chromatography using mass spectrometric detections. The compounds were identified according to their retention indices and mass spectra (EI, 70eV). The experimental parameters of SFE such as pressure, temperature, modifier volume, static and dynamic extraction time were optimized using a Central Composite Design (CCD) after a 2(5) factorial design. Pressure and dynamic extraction time had significant effect on the extraction yield, while the other factors (temperature, static extraction time and modifier volume) were not identified as significant factors under the selected conditions. The results of chemometrics analysis showed the highest yield for SFE (24.32%), which was obtained at a pressure of 353bar, temperature of 35°C, modifier (methanol) volume of 150μL, and static and dynamic extraction times of 10 and 60min, respectively. Ultrasound-assisted extraction (UAE) of Fatty acids from C. oblonga Miller was optimized, using a rotatable central composite design. The optimum conditions were as follows: solvent (n-hexane) volume, 22mL; extraction time, 30min; and extraction temperature, 55°C. This resulted in a maximum oil recovery of 19.5%. The extracts with higher yield from both methods were subjected to transesterification and GC-MS analysis. The results show that the oil obtained by SFE with the optimal operating conditions allowed a fatty acid composition similar to the oil obtained by UAE in optimum condition and no significant differences were found. The major components of oil extract were Linoleic, Palmitic, Oleic, Stearic and Eicosanoic acids. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimizing concentration of shifter additive for plastic scintillators of different size

NASA Astrophysics Data System (ADS)

Adadurov, A. F.; Zhmurin, P. N.; Lebedev, V. N.; Titskaya, V. D.

2009-02-01

This paper concerns the influence of wavelength shifting (secondary) luminescent additive (LA 2) on the light yield of polystyrene-based plastic scintillator (PS) taking self-absorption into account. Calculations of light yield dependence on concentration of 1.4-bis(2-(5-phenyloxazolyl)-benzene (POPOP) as LA 2 were made for various path lengths of photons in PS. It is shown that there is an optimal POPOP concentration ( Copt), which provides a maximum light yield for a given path length. This optimal concentration is determined by the competition of luminescence and self-reflection processes. Copt values were calculated for PS of different dimensions. For small PS, Copt≈0.02%, which agree with a common (standard) value of POPOP concentration. For higher PS dimensions, the optimal POPOP concentration is decreased (to Copt≈0.006% for 320×30×2 cm sample), reducing the light yield from PS by almost 35%.

Glycerol etherification with TBA: high yield to poly-ethers using a membrane assisted batch reactor.

PubMed

Cannilla, Catia; Bonura, Giuseppe; Frusteri, Leone; Frusteri, Francesco

2014-05-20

In this work, a novel approach to obtain high yield to poly-tert-butylglycerolethers by glycerol etherification reaction with tert-butyl alcohol (TBA) is proposed. The limit of this reaction is the production of poly-ethers, which inhibits the formation of poly-ethers potentially usable in the blend with conventional diesel for transportation. The results herein reported demonstrate that the use of a water permselective membrane offers the possibility to shift the equilibrium toward the formation of poly-ethers since the water formed during reaction is continuously and selectively removed from the reaction medium by the recirculation of the gas phase. Using a proper catalyst and optimizing the reaction conditions, in a single experiment, a total glycerol conversion can be reached with a yield to poly-ethers close to 70%, which represents data never before reached using TBA as reactant. The approach here proposed could open up new opportunities for all catalytic reactions affected by water formation.

Acid-catalysed xylose dehydration into furfural in the presence of kraft lignin.

PubMed

Lamminpää, Kaisa; Ahola, Juha; Tanskanen, Juha

2015-02-01

In this study, the effects of kraft lignin (Indulin AT) on acid-catalysed xylose dehydration into furfural were studied in formic and sulphuric acids. The study was done using D-optimal design. Three variables in both acids were included in the design: time (20-80 min), temperature (160-180°C) and initial lignin concentration (0-20 g/l). The dependent variables were xylose conversion, furfural yield, furfural selectivity and pH change. The results showed that the xylose conversion and furfural yield decreased in sulphuric acid, while in formic acid the changes were minor. Additionally, it was showed that lignin has an acid-neutralising capacity, and the added lignin increased the pH of reactant solutions in both acids. The pH rise was considerably lower in formic acid than in sulphuric acid. However, the higher pH did not explain all the changes in conversion and yield, and thus lignin evidently inhibits the formation of furfural. Copyright © 2014 Elsevier Ltd. All rights reserved.

The limits of crop productivity: validating theoretical estimates and determining the factors that limit crop yields in optimal environments

NASA Technical Reports Server (NTRS)

Bugbee, B.; Monje, O.

1992-01-01

Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.

Efficient production of Aschersonia placenta protoplasts for transformation using optimization algorithms.

PubMed

Wei, Xiuyan; Song, Xinyue; Dong, Dong; Keyhani, Nemat O; Yao, Lindan; Zang, Xiangyun; Dong, Lili; Gu, Zijian; Fu, Delai; Liu, Xingzhong; Qiu, Junzhi; Guan, Xiong

2016-07-01

The insect pathogenic fungus Aschersonia placenta is a highly effective pathogen of whiteflies and scale insects. However, few genetic tools are currently available for studying this organism. Here we report on the conditions for the production of transformable A. placenta protoplasts using an optimized protocol based on the response surface method (RSM). Critical parameters for protoplast production were modelled by using a Box-Behnken design (BBD) involving 3 levels of 3 variables that was subsequently tested to verify its ability to predict protoplast production (R(2) = 0.9465). The optimized conditions resulted in the highest yield of protoplasts ((4.41 ± 0.02) × 10(7) cells/mL of culture, mean ± SE) when fungal cells were treated with 26.1 mg/mL of lywallzyme for 4 h of digestion, and subsequently allowed to recover for 64.6 h in 0.7 mol/L NaCl-Tris buffer. The latter was used as an osmotic stabilizer. The yield of protoplasts was approximately 10-fold higher than that of the nonoptimized conditions. Generated protoplasts were transformed with vector PbarGPE containing the bar gene as the selection marker. Transformation efficiency was 300 colonies/(μg DNA·10(7) protoplasts), and integration of the vector DNA was confirmed by PCR. The results show that rational design strategies (RSM and BBD methods) are useful to increase the production of fungal protoplasts for a variety of downstream applications.

Optimization of polyhydroxybutyrate production utilizing waste water as nutrient source by Botryococcus braunii Kütz using response surface methodology.

PubMed

Kavitha, Ganapathy; Kurinjimalar, Chidambaram; Sivakumar, Krishnan; Kaarthik, Muthukumar; Aravind, Rajamani; Palani, Perumal; Rengasamy, Ramasamy

2016-12-01

Investigations have been made to optimize various factors including pH, temperature, and substrate for enhanced polyhydroxybutyrate (PHB) production in Botryococcus braunii which serves as a pioneer for production of bioplastic (PHB). Polyhydroxybutyrate is a natural, decomposable polymers accumulated by the microorganism under different nutritional condition. Strain selection was done by staining method using Sudan black and Nile red dye. Using response surface methodology (RSM), three level- three variables Box Behnken design (BBD), the best potential combination of pH (4-11), temperature (30-50°C) and sewage waste water as substrate fed at different concentrations at 20%-100% for maximum PHB production was investigated. Maximum yield (247±0.42mg/L) of PHB dry weight was achieved from the 60% concentration of sewage waste water as a growth medium at pH 7.5 at 40°C. It was well in close agreement with the value predicted by RSM model yield (246± 0.32mg/L). Thus the study shows the production of PHB by B. braunii along with the basic characterization of PHB by using FTIR and TEM analysis. These preliminary studies indicated that PHB can also be produced by B. braunii utilizing waste water. There is no report on the optimization of PHB production in this microalgae have been documented. Copyright © 2016 Elsevier B.V. All rights reserved.

Enhanced photocatalytic CO2 reduction to CH4 over separated dual co-catalysts Au and RuO2

NASA Astrophysics Data System (ADS)

Dong, Chunyang; Hu, Songchang; Xing, Mingyang; Zhang, Jinlong

2018-04-01

A spatially separated, dual co-catalyst photocatalytic system was constructed by the stepwise introduction of RuO2 and Au nanoparticles (NPs) at the internal and external surfaces of a three dimensional, hierarchically ordered TiO2-SiO2 (HTSO) framework (the final photocatalyst was denoted as Au/HRTSO). Characterization by HR-TEM, EDS-mapping, XRD and XPS confirmed the existence and spatially separated locations of Au and RuO2. In CO2 photocatalytic reduction (CO2PR), Au/HRTSO (0.8%) shows the optimal performance in both the activity and selectivity towards CH4; the CH4 yield is almost twice that of the singular Au/HTSO or HRTSO (0.8%, weight percentage of RuO2) counterparts. Generally, Au NPs at the external surface act as electron trapping agents and RuO2 NPs at the inner surface act as hole collectors. This advanced spatial configuration could promote charge separation and transfer efficiency, leading to enhanced CO2PR performance in both the yield and selectivity toward CH4 under simulated solar light irradiation.

Testing atomic mass models with radioactive beams

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

Haustein, P.E.

1989-01-01

Significantly increased yields of new or poorly characterized exotic isotopes that lie far from beta-decay stability can be expected when radioactive beams are used to produce these nuclides. Measurements of the masses of these new species are very important. Such measurements are motivated by the general tendency of mass models to diverge from one another upon excursions from the line of beta-stability. Therefore in these regions (where atomic mass data are presently nonexistent or sparse) the models can be tested rigorously to highlight the features that affect the quality of their short-range and long-range extrapolation properties. Selection of systems tomore » study can be guided, in part, by a desire to probe those mass regions where distinctions among mass models are most apparent and where yields of exotic isotopes, produced via radioactive beams, can be optimized. Identification of models in such regions that have good predictive properties will aid materially in guiding the selection of additional experiments which ultimately will provide expansion of the atomic mass database for further refinement of the mass models. 6 refs., 5 figs.« less

Measurement of resistant starch by enzymatic digestion in starch and selected plant materials: collaborative study.

PubMed

McCleary, Barry V; McNally, Marian; Rossiter, Patricia

2002-01-01

Interlaboratory performance statistics was determined for a method developed to measure the resistant starch (RS) content of selected plant food products and a range of commercial starch samples. Food materials examined contained RS (cooked kidney beans, green banana, and corn flakes) and commercial starches, most of which naturally contain, or were processed to yield, elevated RS levels. The method evaluated was optimized to yield RS values in agreement with those reported for in vivo studies. Thirty-seven laboratories tested 8 pairs of blind duplicate starch or plant material samples with RS values between 0.6 (regular maize starch) and 64% (fresh weight basis). For matrixes excluding regular maize starch, repeatability relative standard deviation (RSDr) values ranged from 1.97 to 4.2%, and reproducibility relative standard deviation (RSDR) values ranged from 4.58 to 10.9%. The range of applicability of the test is 2-64% RS. The method is not suitable for products with <1% RS (e.g., regular maize starch; 0.6% RS). For such products, RSDr and RSDR values are unacceptably high.

Selective oxidation of trimethylolpropane to 2,2-bis(hydroxymethyl)butyric acid using growing cells of Corynebacterium sp. ATCC 21245.

PubMed

Sayed, Mahmoud; Dishisha, Tarek; Sayed, Waiel F; Salem, Wesam M; Temerk, Hanan A; Pyo, Sang-Hyun

2016-03-10

Multifunctional chemicals including hydroxycarboxylic acids are gaining increasing interest due to their growing applications in the polymer industry. One approach for their production is a biological selective oxidation of polyols, which is difficult to achieve by conventional chemical catalysis. In the present study, trimethylolpropane (TMP), a trihydric alcohol, was subjected to selective oxidation using growing cells of Corynebacterium sp. ATCC 21245 as a biocatalyst and yielding the dihydroxy-monocarboxylic acid, 2,2-bis(hydroxymethyl)butyric acid (BHMB). The study revealed that co-substrates are crucial for this reaction. Among the different evaluated co-substrates, a mixture of glucose, xylose and acetate at a ratio of 5:5:2 was found optimum. The optimal conditions for biotransformation were pH 8, 1v/v/m airflow and 500rpm stirring speed. In batch mode of operation, 70.6% of 5g/l TMP was converted to BHMB in 10 days. For recovery of the product the adsorption pattern of BHMB to the anion exchange resin, Ambersep(®) 900 (OH(-)), was investigated in batch and column experiments giving maximum static and dynamic binding capacities of 135 and 144mg/g resin, respectively. BHMB was separated with 89.7% of recovery yield from the fermentation broth. The approach is applicable for selective oxidation of other highly branched polyols by biotransformation. Copyright © 2016 Elsevier B.V. All rights reserved.

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin

2017-03-01

Abdominal obesity is strongly associated with a number of diseases and accurately assessment of subtypes of adipose tissue volume plays a significant role in predicting disease risk, diagnosis and prognosis. The objective of this study is to develop and evaluate a new computer-aided detection (CAD) scheme based on deep learning models to automatically segment subcutaneous fat areas (SFA) and visceral (VFA) fat areas depicting on CT images. A dataset involving CT images from 40 patients were retrospectively collected and equally divided into two independent groups (i.e. training and testing group). The new CAD scheme consisted of two sequential convolutional neural networks (CNNs) namely, Selection-CNN and Segmentation-CNN. Selection-CNN was trained using 2,240 CT slices to automatically select CT slices belonging to abdomen areas and SegmentationCNN was trained using 84,000 fat-pixel patches to classify fat-pixels as belonging to SFA or VFA. Then, data from the testing group was used to evaluate the performance of the optimized CAD scheme. Comparing to manually labelled results, the classification accuracy of CT slices selection generated by Selection-CNN yielded 95.8%, while the accuracy of fat pixel segmentation using Segmentation-CNN yielded 96.8%. Therefore, this study demonstrated the feasibility of using deep learning based CAD scheme to recognize human abdominal section from CT scans and segment SFA and VFA from CT slices with high agreement compared with subjective segmentation results.

Dynamic programming for optimization of timber production and grazing in ponderosa pine

Treesearch

Kurt H. Riitters; J. Douglas Brodie; David W. Hann

1982-01-01

Dynamic programming procedures are presented for optimizing thinning and rotation of even-aged ponderosa pine by using the four descriptors: age, basal area, number of trees, and time since thinning. Because both timber yield and grazing yield are functions of stand density, the two outputs-forage and timber-can both be optimized. The soil expectation values for single...

A recombinant CYP11B1 dependent Escherichia coli biocatalyst for selective cortisol production and optimization towards a preparative scale.

PubMed

Schiffer, Lina; Anderko, Simone; Hobler, Anna; Hannemann, Frank; Kagawa, Norio; Bernhardt, Rita

2015-02-25

Human mitochondrial CYP11B1 catalyzes a one-step regio- and stereoselective 11β-hydroxylation of 11-deoxycortisol yielding cortisol which constitutes not only the major human stress hormone but also represents a commercially relevant therapeutic drug due to its anti-inflammatory and immunosuppressive properties. Moreover, it is an important intermediate in the industrial production of synthetic pharmaceutical glucocorticoids. CYP11B1 thus offers a great potential for biotechnological application in large-scale synthesis of cortisol. Because of its nature as external monooxygenase, CYP11B1-dependent steroid hydroxylation requires reducing equivalents which are provided from NADPH via a redox chain, consisting of adrenodoxin reductase (AdR) and adrenodoxin (Adx). We established an Escherichia coli based whole-cell system for selective cortisol production from 11-deoxycortisol by recombinant co-expression of the demanded 3 proteins. For the subsequent optimization of the whole-cell activity 3 different approaches were pursued: Firstly, CYP11B1 expression was enhanced 3.3-fold to 257 nmol∗L(-1) by site-directed mutagenesis of position 23 from glycine to arginine, which was accompanied by a 2.6-fold increase in cortisol yield. Secondly, the electron transfer chain was engineered in a quantitative manner by introducing additional copies of the Adx cDNA in order to enhance Adx expression on transcriptional level. In the presence of 2 and 3 copies the initial linear conversion rate was greatly accelerated and the final product concentration was improved 1.4-fold. Thirdly, we developed a screening system for directed evolution of CYP11B1 towards higher hydroxylation activity. A culture down-scale to microtiter plates was performed and a robot-assisted, fluorescence-based conversion assay was applied for the selection of more efficient mutants from a random library. Under optimized conditions a maximum productivity of 0.84 g cortisol∗L(-1)∗d(-1) was achieved, which clearly shows the potential of the developed system for application in the pharmaceutical industry.

High-resolution comparative modeling with RosettaCM.

PubMed

Song, Yifan; DiMaio, Frank; Wang, Ray Yu-Ruei; Kim, David; Miles, Chris; Brunette, Tj; Thompson, James; Baker, David

2013-10-08

We describe an improved method for comparative modeling, RosettaCM, which optimizes a physically realistic all-atom energy function over the conformational space defined by homologous structures. Given a set of sequence alignments, RosettaCM assembles topologies by recombining aligned segments in Cartesian space and building unaligned regions de novo in torsion space. The junctions between segments are regularized using a loop closure method combining fragment superposition with gradient-based minimization. The energies of the resulting models are optimized by all-atom refinement, and the most representative low-energy model is selected. The CASP10 experiment suggests that RosettaCM yields models with more accurate side-chain and backbone conformations than other methods when the sequence identity to the templates is greater than ∼15%. Copyright © 2013 Elsevier Ltd. All rights reserved.

Content dependent selection of image enhancement parameters for mobile displays

NASA Astrophysics Data System (ADS)

Lee, Yoon-Gyoo; Kang, Yoo-Jin; Kim, Han-Eol; Kim, Ka-Hee; Kim, Choon-Woo

2011-01-01

Mobile devices such as cellular phones and portable multimedia player with capability of playing terrestrial digital multimedia broadcasting (T-DMB) contents have been introduced into consumer market. In this paper, content dependent image quality enhancement method for sharpness and colorfulness and noise reduction is presented to improve perceived image quality on mobile displays. Human visual experiments are performed to analyze viewers' preference. Relationship between the objective measures and the optimal values of image control parameters are modeled by simple lookup tables based on the results of human visual experiments. Content dependent values of image control parameters are determined based on the calculated measures and predetermined lookup tables. Experimental results indicate that dynamic selection of image control parameters yields better image quality.

Automatic motor task selection via a bandit algorithm for a brain-controlled button

NASA Astrophysics Data System (ADS)

Fruitet, Joan; Carpentier, Alexandra; Munos, Rémi; Clerc, Maureen

2013-02-01

Objective. Brain-computer interfaces (BCIs) based on sensorimotor rhythms use a variety of motor tasks, such as imagining moving the right or left hand, the feet or the tongue. Finding the tasks that yield best performance, specifically to each user, is a time-consuming preliminary phase to a BCI experiment. This study presents a new adaptive procedure to automatically select (online) the most promising motor task for an asynchronous brain-controlled button. Approach. We develop for this purpose an adaptive algorithm UCB-classif based on the stochastic bandit theory and design an EEG experiment to test our method. We compare (offline) the adaptive algorithm to a naïve selection strategy which uses uniformly distributed samples from each task. We also run the adaptive algorithm online to fully validate the approach. Main results. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. More precisely, the offline analysis reveals that the use of this algorithm can reduce the time needed to select the most appropriate task by almost half without loss in precision, or alternatively, allow us to investigate twice the number of tasks within a similar time span. Online tests confirm that the method leads to an optimal task selection. Significance. This study is the first one to optimize the task selection phase by an adaptive procedure. By increasing the number of tasks that can be tested in a given time span, the proposed method could contribute to reducing ‘BCI illiteracy’.

Optimization of MR fluid Yield stress using Taguchi Method and Response Surface Methodology Techniques

NASA Astrophysics Data System (ADS)

Mangal, S. K.; Sharma, Vivek

2018-02-01

Magneto rheological fluids belong to a class of smart materials whose rheological characteristics such as yield stress, viscosity etc. changes in the presence of applied magnetic field. In this paper, optimization of MR fluid constituents is obtained with on-state yield stress as response parameter. For this, 18 samples of MR fluids are prepared using L-18 Orthogonal Array. These samples are experimentally tested on a developed & fabricated electromagnet setup. It has been found that the yield stress of MR fluid mainly depends on the volume fraction of the iron particles and type of carrier fluid used in it. The optimal combination of the input parameters for the fluid are found to be as Mineral oil with a volume percentage of 67%, iron powder of 300 mesh size with a volume percentage of 32%, oleic acid with a volume percentage of 0.5% and tetra-methyl-ammonium-hydroxide with a volume percentage of 0.7%. This optimal combination of input parameters has given the on-state yield stress as 48.197 kPa numerically. An experimental confirmation test on the optimized MR fluid sample has been then carried out and the response parameter thus obtained has found matching quite well (less than 1% error) with the numerically obtained values.

Formulation and optimization of doxorubicin loaded polymeric nanoparticles using Box-Behnken design: ex-vivo stability and in-vitro activity.

PubMed

Shaikh, Muhammad Vaseem; Kala, Manika; Nivsarkar, Manish

2017-03-30

Biodegradable nanoparticles (NPs) have gained tremendous interest for targeting chemotherapeutic drugs to the tumor environment. Inspite of several advances sufficient encapsulation along with the controlled release and desired size range have remained as considerable challenges. Hence, the present study examines the formulation optimization of doxorubicin loaded PLGA NPs (DOX-PLGA-NPs), prepared by single emulsion method for cancer targeting. Critical process parameters (CPP) were selected by initial screening. Later, Box-Behnken design (BBD) was used for analyzing the effect of the selected CPP on critical quality attributes (CQA) and to generate a design space. The optimized formulation was stabilized by lyophilization and was used for in-vitro drug release and in-vitro activity on A549 cell line. Moreover, colloidal stability of the NPs in the biological milieu was assessed. Amount of PLGA and PVA, oil:water ratio and sonication time were the selected independent factors for BBD. The statistical data showed that a quadratic model was fitted to the data obtained. Additionally, the lack of fit values for the models was not significant. The delivery system showed sustained release behavior over a period of 120h and was governed by Fickian diffusion. The multipoint analysis at 24, 48 and 72h showed gradual reduction in IC50 value of DOX-PLGA-NPs (p<0.05, Fig. 9). DOX-PLGA-NPs were found to be stable in the biological fluids indicating their in-vivo applicability. In conclusion, optimization of the DOX-PLGA-NPs by BBD yielded in a promising drug carrier for doxorubicin that could provide a novel treatment modality for cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimum allocation of test resources and comparison of breeding strategies for hybrid wheat.

PubMed

Longin, C Friedrich H; Mi, Xuefei; Melchinger, Albrecht E; Reif, Jochen C; Würschum, Tobias

2014-10-01

The use of a breeding strategy combining the evaluation of line per se with testcross performance maximizes annual selection gain for hybrid wheat breeding. Recent experimental studies confirmed a high commercial potential for hybrid wheat requiring the design of optimum breeding strategies. Our objectives were to (1) determine the optimum allocation of the type and number of testers, the number of test locations and the number of doubled haploid lines for different breeding strategies, (2) identify the best breeding strategy and (3) elaborate key parameters for an efficient hybrid wheat breeding program. We performed model calculations using the selection gain for grain yield as target variable to optimize the number of lines, testers and test locations in four different breeding strategies. A breeding strategy (BS2) combining the evaluation of line per se performance and general combining ability (GCA) had a far larger annual selection gain across all considered scenarios than a breeding strategy (BS1) focusing only on GCA. In the combined strategy, the production of testcross seed conducted in parallel with the first yield trial for line per se performance (BS2rapid) resulted in a further increase of the annual selection gain. For the current situation in hybrid wheat, this relative superiority of the strategy BS2rapid amounted to 67 % in annual selection gain compared to BS1. Varying a large number of parameters, we identified the high costs for hybrid seed production and the low variance of GCA in hybrid wheat breeding as key parameters limiting selection gain in BS2rapid.

Quantitative and qualitative optimization of allergen extraction from peanut and selected tree nuts. Part 2. Optimization of buffer and ionic strength using a full factorial experimental design.

PubMed

L'Hocine, Lamia; Pitre, Mélanie

2016-03-01

A full factorial design was used to assess the single and interactive effects of three non-denaturing aqueous (phosphate, borate, and carbonate) buffers at various ionic strengths (I) on allergen extractability from and immunoglobulin E (IgE) immunoreactivity of peanut, almond, hazelnut, and pistachio. The results indicated that the type and ionic strength of the buffer had different effects on protein recovery from the nuts under study. Substantial differences in protein profiles, abundance, and IgE-binding intensity with different combinations of pH and ionic strength were found. A significant interaction between pH and ionic strength was observed for pistachio and almond. The optimal buffer system conditions, which maximized the IgE-binding efficiency of allergens and provided satisfactory to superior protein recovery yield and profiles, were carbonate buffer at an ionic strength of I=0.075 for peanut, carbonate buffer at I=0.15 for almond, phosphate buffer at I=0.5 for hazelnut, and borate at I=0.15 for pistachio. The buffer type and its ionic strength could be manipulated to achieve the selective solubility of desired allergens. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Testing the limits of optimality: the effect of base rates in the Monty Hall dilemma.

PubMed

Herbranson, Walter T; Wang, Shanglun

2014-03-01

The Monty Hall dilemma is a probability puzzle in which a player tries to guess which of three doors conceals a desirable prize. After an initial selection, one of the nonchosen doors is opened, revealing that it is not a winner, and the player is given the choice of staying with the initial selection or switching to the other remaining door. Pigeons and humans were tested on two variants of the Monty Hall dilemma, in which one of the three doors had either a higher or a lower chance of containing the prize than did the other two options. The optimal strategy in both cases was to initially choose the lowest-probability door available and then switch away from it. Whereas pigeons learned to approximate the optimal strategy, humans failed to do so on both accounts: They did not show a preference for low-probability options, and they did not consistently switch. An analysis of performance over the course of training indicated that pigeons learned to perform a sequence of responses on each trial, and that sequence was one that yielded the highest possible rate of reinforcement. Humans, in contrast, continued to vary their responses throughout the experiment, possibly in search of a more complex strategy that would exceed the maximum possible win rate.

Efficient QoS-aware Service Composition

NASA Astrophysics Data System (ADS)

Alrifai, Mohammad; Risse, Thomas

Web service composition requests are usually combined with endto-end QoS requirements, which are specified in terms of non-functional properties (e.g. response time, throughput and price). The goal of QoS-aware service composition is to find the best combination of services such that their aggregated QoS values meet these end-to-end requirements. Local selection techniques are very efficient but fail short in handling global QoS constraints. Global optimization techniques, on the other hand, can handle global constraints, but their poor performance render them inappropriate for applications with dynamic and real-time requirements. In this paper we address this problem and propose a solution that combines global optimization with local selection techniques for achieving a better performance. The proposed solution consists of two steps: first we use mixed integer linear programming (MILP) to find the optimal decomposition of global QoS constraints into local constraints. Second, we use local search to find the best web services that satisfy these local constraints. Unlike existing MILP-based global planning solutions, the size of the MILP model in our case is much smaller and independent on the number of available services, yields faster computation and more scalability. Preliminary experiments have been conducted to evaluate the performance of the proposed solution.

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

PubMed

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

2016-02-24

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

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

PubMed Central

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

2016-01-01

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

Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

NASA Astrophysics Data System (ADS)

Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

2017-04-01

Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed to evaluate the influence of each parameter mentioned above on the winter wheat yield formation. Finally, six parameters that sensitivity index more than 0.1 as sensitivity factors were chose, which are TSUM1, SLATB1, SLATB2, SPAN, EFFTB3 and TMPF4. To other parameters, we confirmed them via practical measurement and calculation, available literature or WOFOST default. Eventually, we completed the regulation of WOFOST parameters. (3) Look-up table algorithm was used to realize single-point yield estimation through the assimilation of the WOFOST model and the retrieval LAI. This simulation achieved a high accuracy which perfectly meet the purpose of assimilation (R2=0.941 and RMSE=194.58kg/hm2). In this paper, the optimum value of sensitivity parameters were confirmed and the estimation of single-point yield were finished. Key words: yield estimation of winter wheat, LAI, WOFOST crop growth model, assimilation

Optimizing Dense Plasma Focus Neutron Yields with Fast Gas Jets

NASA Astrophysics Data System (ADS)

McMahon, Matthew; Kueny, Christopher; Stein, Elizabeth; Link, Anthony; Schmidt, Andrea

2016-10-01

We report a study using the particle-in-cell code LSP to perform fully kinetic simulations modeling dense plasma focus (DPF) devices with high density gas jets on axis. The high density jet models fast gas puffs which allow for more mass on axis while maintaining the optimal pressure for the DPF. As the density of the jet compared to the background fill increases we find the neutron yield increases, as does the variability in the neutron yield. Introducing perturbations in the jet density allow for consistent seeding of the m =0 instability leading to more consistent ion acceleration and higher neutron yields with less variability. Jets with higher on axis density are found to have the greatest yield. The optimal jet configuration is explored. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Accelerated iterative beam angle selection in IMRT

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

Bangert, Mark, E-mail: m.bangert@dkfz.de; Unkelbach, Jan

2016-03-15

Purpose: Iterative methods for beam angle selection (BAS) for intensity-modulated radiation therapy (IMRT) planning sequentially construct a beneficial ensemble of beam directions. In a naïve implementation, the nth beam is selected by adding beam orientations one-by-one from a discrete set of candidates to an existing ensemble of (n − 1) beams. The best beam orientation is identified in a time consuming process by solving the fluence map optimization (FMO) problem for every candidate beam and selecting the beam that yields the largest improvement to the objective function value. This paper evaluates two alternative methods to accelerate iterative BAS based onmore » surrogates for the FMO objective function value. Methods: We suggest to select candidate beams not based on the FMO objective function value after convergence but (1) based on the objective function value after five FMO iterations of a gradient based algorithm and (2) based on a projected gradient of the FMO problem in the first iteration. The performance of the objective function surrogates is evaluated based on the resulting objective function values and dose statistics in a treatment planning study comprising three intracranial, three pancreas, and three prostate cases. Furthermore, iterative BAS is evaluated for an application in which a small number of noncoplanar beams complement a set of coplanar beam orientations. This scenario is of practical interest as noncoplanar setups may require additional attention of the treatment personnel for every couch rotation. Results: Iterative BAS relying on objective function surrogates yields similar results compared to naïve BAS with regard to the objective function values and dose statistics. At the same time, early stopping of the FMO and using the projected gradient during the first iteration enable reductions in computation time by approximately one to two orders of magnitude. With regard to the clinical delivery of noncoplanar IMRT treatments, we could show that optimized beam ensembles using only a few noncoplanar beam orientations often approach the plan quality of fully noncoplanar ensembles. Conclusions: We conclude that iterative BAS in combination with objective function surrogates can be a viable option to implement automated BAS at clinically acceptable computation times.« less

Accelerated iterative beam angle selection in IMRT.

PubMed

Bangert, Mark; Unkelbach, Jan

2016-03-01

Iterative methods for beam angle selection (BAS) for intensity-modulated radiation therapy (IMRT) planning sequentially construct a beneficial ensemble of beam directions. In a naïve implementation, the nth beam is selected by adding beam orientations one-by-one from a discrete set of candidates to an existing ensemble of (n - 1) beams. The best beam orientation is identified in a time consuming process by solving the fluence map optimization (FMO) problem for every candidate beam and selecting the beam that yields the largest improvement to the objective function value. This paper evaluates two alternative methods to accelerate iterative BAS based on surrogates for the FMO objective function value. We suggest to select candidate beams not based on the FMO objective function value after convergence but (1) based on the objective function value after five FMO iterations of a gradient based algorithm and (2) based on a projected gradient of the FMO problem in the first iteration. The performance of the objective function surrogates is evaluated based on the resulting objective function values and dose statistics in a treatment planning study comprising three intracranial, three pancreas, and three prostate cases. Furthermore, iterative BAS is evaluated for an application in which a small number of noncoplanar beams complement a set of coplanar beam orientations. This scenario is of practical interest as noncoplanar setups may require additional attention of the treatment personnel for every couch rotation. Iterative BAS relying on objective function surrogates yields similar results compared to naïve BAS with regard to the objective function values and dose statistics. At the same time, early stopping of the FMO and using the projected gradient during the first iteration enable reductions in computation time by approximately one to two orders of magnitude. With regard to the clinical delivery of noncoplanar IMRT treatments, we could show that optimized beam ensembles using only a few noncoplanar beam orientations often approach the plan quality of fully noncoplanar ensembles. We conclude that iterative BAS in combination with objective function surrogates can be a viable option to implement automated BAS at clinically acceptable computation times.

Optimization of mechanical properties, biocorrosion properties and antibacterial properties of wrought Ti-3Cu alloy by heat treatment.

PubMed

Bao, Mianmian; Liu, Ying; Wang, Xiaoyan; Yang, Lei; Li, Shengyi; Ren, Jing; Qin, Gaowu; Zhang, Erlin

2018-03-01

Previous study has shown that Ti-3Cu alloy shows good antibacterial properties (>90% antibacterial rate), but the mechanical properties still need to be improved. In this paper, a series of heat-treatment processes were selected to adjust the microstructure in order to optimize the properties of Ti-3Cu alloy. Microstructure, mechanical properties, biocorrosion properties and antibacterial properties of wrought Ti-3Cu alloy at different conditions was systematically investigated by X-ray diffraction, optical microscope, scanning electron microscope, transmission electron microscopy, electrochemical measurements, tensile test, fatigue test and antibacterial test. Heat treatment could significantly improve the mechanical properties, corrosion resistance and antibacterial rate due to the redistribution of copper elements and precipitation of Ti 2 Cu phase. Solid solution treatment increased the yield strength from 400 to 740 MPa and improved the antibacterial rate from 33% to 65.2% while aging treatment enhanced the yield strength to 800-850 MPa and antibacterial rate (>91.32%). It was demonstrated that homogeneous distribution and fine Ti 2 Cu phase plays a very important role in mechanical properties, corrosion resistance and antibacterial properties.

Low-cost production of 6G-fructofuranosidase with high value-added astaxanthin by Xanthophyllomyces dendrorhous.

PubMed

Ning, Yawei; Li, Qiang; Chen, Feng; Yang, Na; Jin, Zhengyu; Xu, Xueming

2012-01-01

The effects of medium composition and culture conditions on the production of (6)G-fructofuranosidase with value-added astaxanthin were investigated to reduce the capital cost of neo-fructooligosaccharides (neo-FOS) production by Xanthophyllomyces dendrorhous. The sucrose and corn steep liquor (CSL) were found to be the optimal carbon source and nitrogen source, respectively. CSL and initial pH were selected as the critical factors using Plackett-Burman design. Maximum (6)G-fructofuranosidase 242.57 U/mL with 5.23 mg/L value-added astaxanthin was obtained at CSL 52.5 mL/L and pH 7.89 by central composite design. Neo-FOS yield could reach 238.12 g/L under the optimized medium conditions. Cost analysis suggested 66.3% of substrate cost was reduced compared with that before optimization. These results demonstrated that the optimized medium and culture conditions could significantly enhance the production of (6)G-fructofuranosidase with value-added astaxanthin and remarkably decrease the substrate cost, which opened up possibilities to produce neo-FOS industrially. Copyright © 2011 Elsevier Ltd. All rights reserved.

Passive designs and renewable energy systems optimization of a net zero energy building in Embrun/France

NASA Astrophysics Data System (ADS)

Harkouss, F.; Biwole, P. H.; Fardoun, F.

2018-05-01

Buildings’ optimization is a smart method to inspect the available design choices starting from passive strategies, to energy efficient systems and finally towards the adequate renewable energy system to be implemented. This paper outlines the methodology and the cost-effectiveness potential for optimizing the design of net-zero energy building in a French city; Embrun. The non-dominated sorting genetic algorithm is chosen in order to minimize thermal, electrical demands and life cycle cost while reaching the net zero energy balance; and thus getting the Pareto-front. Elimination and Choice Expressing the Reality decision making method is applied to the Pareto-front so as to obtain one optimal solution. A wide range of energy efficiency measures are investigated, besides solar energy systems are employed to produce required electricity and hot water for domestic purposes. The results indicate that the appropriate selection of the passive parameters is very important and critical in reducing the building energy consumption. The optimum design parameters yield to a decrease of building’s thermal loads and life cycle cost by 32.96% and 14.47% respectively.

Analysis and optimization of cyclic methods in orbit computation

NASA Technical Reports Server (NTRS)

Pierce, S.

1973-01-01

The mathematical analysis and computation of the K=3, order 4; K=4, order 6; and K=5, order 7 cyclic methods and the K=5, order 6 Cowell method and some results of optimizing the 3 backpoint cyclic multistep methods for solving ordinary differential equations are presented. Cyclic methods have the advantage over traditional methods of having higher order for a given number of backpoints while at the same time having more free parameters. After considering several error sources the primary source for the cyclic methods has been isolated. The free parameters for three backpoint methods were used to minimize the effects of some of these error sources. They now yield more accuracy with the same computing time as Cowell's method on selected problems. This work is being extended to the five backpoint methods. The analysis and optimization are more difficult here since the matrices are larger and the dimension of the optimizing space is larger. Indications are that the primary error source can be reduced. This will still leave several parameters free to minimize other sources.

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.

Enzymatic hydrolysis of pretreated Alfa fibers (Stipa tenacissima) using β-d-glucosidase and xylanase of Talaromyces thermophilus from solid-state fermentation.

PubMed

Mallek-Fakhfakh, Hanen; Fakhfakh, Jawhar; Walha, Kamel; Hassairi, Hajer; Gargouri, Ali; Belghith, Hafedh

2017-10-01

This work aims at realizing an optimal hydrolysis of pretreated Alfa fibers (Stipa tenacissima) through the use of enzymes produced from Talaromyces thermophilus AX4, namely β-d-glucosidase and xylanase, by a solid state fermentation process of an agro-industrial waste (wheat bran supplemented with lactose). The carbon source was firstly selected and the optimal values of three other parameters were determined: substrate loading (10g), moisture content (85%) and production time (10days); which led to an optimized enzymatic juice. The outcome was then supplemented with cellulases of T. reesei and used to optimize the enzymatic saccharification of alkali-pretreated Alfa fibers (PAF). The maximum saccharification yield of 83.23% was achieved under optimized conditions (substrate concentration 3.7% (w/v), time 144h and enzyme loading of 0.8 FPU, 15U CMCase, 60U β-d-glucosidase and 125U xylanase).The structural modification of PAF due to enzymatic saccharification was supported by the changes of morphologic and chemical composition observed through macroscopic representation, FTIR and X-Ray analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Synthesis and Purification of Iodoaziridines Involving Quantitative Selection of the Optimal Stationary Phase for Chromatography

PubMed Central

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

2014-01-01

The highly diastereoselective preparation of cis-N-Ts-iodoaziridines through reaction of diiodomethyllithium with N-Ts aldimines is described. Diiodomethyllithium is prepared by the deprotonation of diiodomethane with LiHMDS, in a THF/diethyl ether mixture, at -78 °Cin the dark. These conditions are essential for the stability of the LiCHI2 reagent generated. The subsequent dropwise addition of N-Ts aldimines to the preformed diiodomethyllithium solution affords an amino-diiodide intermediate, which is not isolated. Rapid warming of the reaction mixture to 0 °C promotes cyclization to afford iodoaziridines with exclusive cis-diastereoselectivity. The addition and cyclization stages of the reaction are mediated in one reaction flask by careful temperature control. Due to the sensitivity of the iodoaziridines to purification, assessment of suitable methods of purification is required. A protocol to assess the stability of sensitive compounds to stationary phases for column chromatography is described. This method is suitable to apply to new iodoaziridines, or other potentially sensitive novel compounds. Consequently this method may find application in range of synthetic projects. The procedure involves firstly the assessment of the reaction yield, prior to purification, by 1H NMR spectroscopy with comparison to an internal standard. Portions of impure product mixture are then exposed to slurries of various stationary phases appropriate for chromatography, in a solvent system suitable as the eluent in flash chromatography. After stirring for 30 min to mimic chromatography, followed by filtering, the samples are analyzed by 1H NMR spectroscopy. Calculated yields for each stationary phase are then compared to that initially obtained from the crude reaction mixture. The results obtained provide a quantitative assessment of the stability of the compound to the different stationary phases; hence the optimal can be selected. The choice of basic alumina, modified to activity IV, as a suitable stationary phase has allowed isolation of certain iodoaziridines in excellent yield and purity. PMID:24893769

A sampling and classification item selection approach with content balancing.

PubMed

Chen, Pei-Hua

2015-03-01

Existing automated test assembly methods typically employ constrained combinatorial optimization. Constructing forms sequentially based on an optimization approach usually results in unparallel forms and requires heuristic modifications. Methods based on a random search approach have the major advantage of producing parallel forms sequentially without further adjustment. This study incorporated a flexible content-balancing element into the statistical perspective item selection method of the cell-only method (Chen et al. in Educational and Psychological Measurement, 72(6), 933-953, 2012). The new method was compared with a sequential interitem distance weighted deviation model (IID WDM) (Swanson & Stocking in Applied Psychological Measurement, 17(2), 151-166, 1993), a simultaneous IID WDM, and a big-shadow-test mixed integer programming (BST MIP) method to construct multiple parallel forms based on matching a reference form item-by-item. The results showed that the cell-only method with content balancing and the sequential and simultaneous versions of IID WDM yielded results comparable to those obtained using the BST MIP method. The cell-only method with content balancing is computationally less intensive than the sequential and simultaneous versions of IID WDM.

Integrated Application of Active Controls (IAAC) technology to an advanced subsonic transport project: Current and advanced act control system definition study, volume 1

NASA Technical Reports Server (NTRS)

Hanks, G. W.; Shomber, H. A.; Dethman, H. A.; Gratzer, L. B.; Maeshiro, A.; Gangsaas, D.; Blight, J. D.; Buchan, S. M.; Crumb, C. B.; Dorwart, R. J.

1981-01-01

An active controls technology (ACT) system architecture was selected based on current technology system elements and optimal control theory was evaluated for use in analyzing and synthesizing ACT multiple control laws. The system selected employs three redundant computers to implement all of the ACT functions, four redundant smaller computers to implement the crucial pitch-augmented stability function, and a separate maintenance and display computer. The reliability objective of probability of crucial function failure of less than 1 x 10 to the -9th power per flight of 1 hr can be met with current technology system components, if the software is assumed fault free and coverage approaching 1.0 can be provided. The optimal control theory approach to ACT control law synthesis yielded comparable control law performance much more systematically and directly than the classical s-domain approach. The ACT control law performance, although somewhat degraded by the inclusion of representative nonlinearities, remained quite effective. Certain high-frequency gust-load alleviation functions may require increased surface rate capability.

Sunflower Hybrid Breeding: From Markers to Genomic Selection

PubMed Central

Dimitrijevic, Aleksandra; Horn, Renate

2018-01-01

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches combining omic technologies (genomics, transcriptomics, proteomics, metabolomics and phenomics) using bioinformatic tools will facilitate the identification of target genes and markers for complex traits and will give a better insight into the mechanisms behind the traits. PMID:29387071

T2-weighted signal intensity-selected volumetry for prediction of pathological complete response after preoperative chemoradiotherapy in locally advanced rectal cancer.

PubMed

Kim, Sungwon; Han, Kyunghwa; Seo, Nieun; Kim, Hye Jin; Kim, Myeong-Jin; Koom, Woong Sub; Ahn, Joong Bae; Lim, Joon Seok

2018-06-01

To evaluate the diagnostic value of signal intensity (SI)-selected volumetry findings in T2-weighted magnetic resonance imaging (MRI) as a potential biomarker for predicting pathological complete response (pCR) to preoperative chemoradiotherapy (CRT) in patients with rectal cancer. Forty consecutive patients with pCR after preoperative CRT were compared with 80 age- and sex-matched non-pCR patients in a case-control study. SI-selected tumor volume was measured on post-CRT T2-weighted MRI, which included voxels of the treated tumor exceeding the SI (obturator internus muscle SI + [ischiorectal fossa fat SI - obturator internus muscle SI] × 0.2). Three blinded readers independently rated five-point pCR confidence scores and compared the diagnostic outcome with SI-selected volumetry findings. The SI-selected volumetry protocol was validated in 30 additional rectal cancer patients. The area under the receiver-operating characteristic curve (AUC) of SI-selected volumetry for pCR prediction was 0.831, with an optimal cutoff value of 649.6 mm 3 (sensitivity 0.850, specificity 0.725). The AUC of the SI-selected tumor volume was significantly greater than the pooled AUC of readers (0.707, p < 0.001). At this cutoff, the validation trial yielded an accuracy of 0.87. SI-selected volumetry in post-CRT T2-weighted MRI can help predict pCR after preoperative CRT in patients with rectal cancer. • Fibrosis and viable tumor MRI signal intensities (SIs) are difficult to distinguish. • T2 SI-selected volumetry yields high diagnostic performance for assessing pathological complete response. • T2 SI-selected volumetry is significantly more accurate than readers and non-SI-selected volumetry. • Post-chemoradiation therapy T2-weighted MRI SI-selected volumetry facilitates prediction of pathological complete response.

Synthesis of perfluoroalkylene dianilines

NASA Technical Reports Server (NTRS)

Paciorek, K. L.; Ito, T. I.; Harris, D. H.; Beechan, C. M.; Nakaham, J. H.; Kratzer, R. H.

1981-01-01

The objective of this contrast was to optimize and scale-up the synthesis of 2,2-bis(4-aminophenyl)-hexafluoropropane and 1,3-bis(4-aminophenyl)hexafluoropropane, as well as to explore avenues to other perfluoroalkyl-bridged dianilines. Routes other than Friedel-Crafts reaction leading to 2,2-bis(4-aminophenyl)hexafluoropropane were investigated. The processes utilizing bisphenol-AF were all unsuccessful; reactions aimed at the production of 4-(hexafluoro-2-halo-isopropyl)aniline from the hydroxyl intermediate failed to yield the desired products. Tailoring the conditions of the Friedel-Crafts reaction of 4-(hexafluoro-2-hydroxyisopropyl)aniline, aniline, and aluminum chloride by using hydrochloride salts and selecting optimum reagent ratios, reaction times, and temperature resulted in approx. 20% yield of pure crystallized 2,2-bis(4-aminophenyl)hexafluoropropane in 0.2 mole reaction batches. Yields up to approx. 40% were realized in small, approx. 0.01 mole, batches. The synthesis of 1,3-bis(4-aminophenyl)hexafluoropropane starting with perfluoroglutarimidine was reinvestigated. The yield of the 4-step reaction sequence giving 1,3-bis(4-acetamidophenyl)hexafluoropropane was raised to 44%. The yield of the subsequent hydrolysis process was improved by a factor of approx. 2. Approaches to prepare other perfluoroalkyl-bridged dianilines were unsuccessful. Reactions reported to proceed readily with trifluoromethyl substituents failed when longer chain perfluoroalkyl groups were employed.

Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Akgöl, Batuhan; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2017-02-01

Early generation genomic selection is superior to conventional phenotypic selection in line breeding and can be strongly improved by including additional information from preliminary yield trials. The selection of lines that enter resource-demanding multi-environment trials is a crucial decision in every line breeding program as a large amount of resources are allocated for thoroughly testing these potential varietal candidates. We compared conventional phenotypic selection with various genomic selection approaches across multiple years as well as the merit of integrating phenotypic information from preliminary yield trials into the genomic selection framework. The prediction accuracy using only phenotypic data was rather low (r = 0.21) for grain yield but could be improved by modeling genetic relationships in unreplicated preliminary yield trials (r = 0.33). Genomic selection models were nevertheless found to be superior to conventional phenotypic selection for predicting grain yield performance of lines across years (r = 0.39). We subsequently simplified the problem of predicting untested lines in untested years to predicting tested lines in untested years by combining breeding values from preliminary yield trials and predictions from genomic selection models by a heritability index. This genomic assisted selection led to a 20% increase in prediction accuracy, which could be further enhanced by an appropriate marker selection for both grain yield (r = 0.48) and protein content (r = 0.63). The easy to implement and robust genomic assisted selection gave thus a higher prediction accuracy than either conventional phenotypic or genomic selection alone. The proposed method took the complex inheritance of both low and high heritable traits into account and appears capable to support breeders in their selection decisions to develop enhanced varieties more efficiently.

Fewer not more leaves - Key to obtaining the needed jump in crop yield potential and water use efficiency

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Kumar, P.; Long, S.

2013-12-01

Word food and feed supply needs to increase by 75% by 2050 to meet the increasing demands of our growing population. Soybean which is the world`s fourth most important crop in terms of total production at 250 million Mt/yr is a key protein source, and together with rice and wheat, are experiencing declining global yield increases year on year. At present rates of improvement, 2050 targets cannot be reached without new innovations. In this study we demonstrate an innovative approach that could provide a yield jump. While, natural selection favors individual plants to maximize leaf production to maximize light interception and shade competitors, the presence of this trait in domestic crops could be disadvantageous. In addition, rising CO2 causes increased leaf production further exacerbating the problem. Here, we show by mathematical model and field experiment that, a modern cultivar growing at the center of US soy cultivation produces too many leaves and reduction to an optimal level would increase yield. Our model results indicate that an LAI of 3.5 and 3.8 produces maximal rates of net canopy assimilation under ambient and elevated CO2 conditions respectively. However, observed peak LAI values are 6.9 and 7.5 under ambient and elevated CO2 conditions respectively. This results in a NPP loss of 30% and 20% under ambient and elevated CO2 conditions respectively. Furthermore, the optimal LAI results in a decreased transpiration of up to 30% thus increasing water use efficiency. We show that as LAI increases, the tradeoffs between diminishing day time gains in NPP, and increasing losses in respiration is responsible for this effect. By designing a more optimum canopy, we can increase NPP and this potentially translates to increased seed yield. To test this model result, we perform canopy manipulation experiments on soybean plants, where we artificially decrease LAI by periodically removing young and emerging leaves throughout the growing season (after pod onset), and measure the seed yield under ambient and elevated CO2 conditions. Our experimental results show that an LAI reduction of 0.5 results in an increased seed yield of 8.1% validating our model results. We propose that, by achieving a stronger LAI reduction, we can improve seed yields by up to 24% providing the much needed jump in yield to achieve future food security.

Multi-objective optimization of chromatographic rare earth element separation.

PubMed

Knutson, Hans-Kristian; Holmqvist, Anders; Nilsson, Bernt

2015-10-16

The importance of rare earth elements in modern technological industry grows, and as a result the interest for developing separation processes increases. This work is a part of developing chromatography as a rare earth element processing method. Process optimization is an important step in process development, and there are several competing objectives that need to be considered in a chromatographic separation process. Most studies are limited to evaluating the two competing objectives productivity and yield, and studies of scenarios with tri-objective optimizations are scarce. Tri-objective optimizations are much needed when evaluating the chromatographic separation of rare earth elements due to the importance of product pool concentration along with productivity and yield as process objectives. In this work, a multi-objective optimization strategy considering productivity, yield and pool concentration is proposed. This was carried out in the frame of a model based optimization study on a batch chromatography separation of the rare earth elements samarium, europium and gadolinium. The findings from the multi-objective optimization were used to provide with a general strategy for achieving desirable operation points, resulting in a productivity ranging between 0.61 and 0.75 kgEu/mcolumn(3), h(-1) and a pool concentration between 0.52 and 0.79 kgEu/m(3), while maintaining a purity above 99% and never falling below an 80% yield for the main target component europium. Copyright © 2015 Elsevier B.V. All rights reserved.

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking

NASA Astrophysics Data System (ADS)

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Optimization of enzyme complexes for efficient hydrolysis of corn stover to produce glucose.

PubMed

Yu, Xiaoxiao; Liu, Yan; Meng, Jiatong; Cheng, Qiyue; Zhang, Zaixiao; Cui, Yuxiao; Liu, Jiajing; Teng, Lirong; Lu, Jiahui; Meng, Qingfan; Ren, Xiaodong

2015-05-01

Hydrolysis of cellulose to glucose is the critical step for transferring the lignocellulose to the industrial chemicals. For improving the conversion rate of cellulose of corn stover to glucose, the cocktail of celllulase with other auxiliary enzymes and chemicals was studied in this work. Single factor tests and Response Surface Methodology (RSM) were applied to optimize the enzyme mixture, targeting maximum glucose release from corn stover. The increasing rate of glucan-to-glucose conversion got the higher levels while the cellulase was added 1.7μl tween-80/g cellulose, 300μg β-glucosidase/g cellulose, 400μg pectinase/g cellulose and 0.75mg/ml sodium thiosulphate separately in single factor tests. To improve the glucan conversion, the β-glucosidase, pectinase and sodium thiosulphate were selected for next step optimization with RSM. It is showed that the maximum increasing yield was 45.8% at 377μg/g cellulose Novozyme 188, 171μg/g cellulose pectinase and 1mg/ml sodium thiosulphate.

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

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking.

PubMed

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J; Jian, Yifan; Sarunic, Marinko V

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Chemical coagulation of combined sewer overflow: heavy metal removal and treatment optimization.

PubMed

El Samrani, A G; Lartiges, B S; Villiéras, F

2008-02-01

The coagulation of combined sewer overflow (CSO) was investigated by jar-testing with two commercial coagulants, a ferric chloride solution (CLARFER) and a polyaluminium chloride (WAC HB). CSO samples were collected as a function of time during various wet-weather events from the inlet of Boudonville retention basin, Nancy, France. Jar-tests showed that an efficient turbidity removal can be achieved with both coagulants, though lower optimum dosages and higher re-stabilization concentrations were obtained with the aluminum-based coagulant. Optimum turbidity removal also yielded effective heavy metal elimination. However, the evolution with coagulant dosage of Cu, Zn, Pb, Cr, soluble and suspended solids contents followed various patterns. The removal behaviors can be explained by a selective aggregation of heavy metal carriers present in CSO and a specific interaction between hydrolyzed coagulant species and soluble metals. Stoichiometric relationships were established between optimal coagulant concentration, range of optimal dosing, and CSO conductivity, thus providing useful guidelines to adjust the coagulant demand during the course of CSO events.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Syngas production by chemical-looping gasification of wheat straw with Fe-based oxygen carrier.

PubMed

Hu, Jianjun; Li, Chong; Guo, Qianhui; Dang, Jiatao; Zhang, Quanguo; Lee, Duu-Jong; Yang, Yunlong

2018-05-03

The iron-based oxygen carriers (OC's), Fe 2 O 3 /support (Al 2 O 3 , TiO 2 , SiO 2 and ZrO 2 ), for chemical looping gasification of wheat straw were prepared using impregnation method. The surface morphology, crystal structure, carbon deposition potential, lattice oxygen activity and selectivity of the yielded OCs were examined. The Fe 2 O 3 /Al 2 O 3 OCs at 60% loading has the highest H 2 yield, H 2 /CO ratio, gas yield, and carbon conversion amongst the tested OC's. Parametric studies revealed that an optimal loading Fe 2 O 3 of 60%, steam-to-biomass ratio of 0.8 and oxygen carrier-to-biomass ratio of 1.0 led to the maximum H 2 /CO ratio, gas yield, H 2  + CO ratio, and carbon conversion from the gasified wheat straw. High temperature, up to 950 °C, enhanced the gasification performance. A kinetic network interpreted the noted experimental results. The lattice oxygen provided by the prepared Fe 2 O 3 /Al 2 O 3 oxygen carriers promotes chemical looping gasification efficiencies from wheat straw. Copyright © 2018 Elsevier Ltd. All rights reserved.

Toward Optimal Target Placement for Neural Prosthetic Devices

PubMed Central

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

2008-01-01

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

Multi-objective design optimization of antenna structures using sequential domain patching with automated patch size determination

NASA Astrophysics Data System (ADS)

Koziel, Slawomir; Bekasiewicz, Adrian

2018-02-01

In this article, a simple yet efficient and reliable technique for fully automated multi-objective design optimization of antenna structures using sequential domain patching (SDP) is discussed. The optimization procedure according to SDP is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between considered conflicting objectives, and (ii) Pareto set refinement for yielding the optimal designs at the high-fidelity electromagnetic (EM) simulation model level. For the sake of computational efficiency, the first step is realized at the level of a low-fidelity (coarse-discretization) EM model by sequential construction and relocation of small design space segments (patches) in order to create a path connecting the extreme Pareto front designs obtained beforehand. The second stage involves response correction techniques and local response surface approximation models constructed by reusing EM simulation data acquired in the first step. A major contribution of this work is an automated procedure for determining the patch dimensions. It allows for appropriate selection of the number of patches for each geometry variable so as to ensure reliability of the optimization process while maintaining its low cost. The importance of this procedure is demonstrated by comparing it with uniform patch dimensions.

Optimizing antibody expression: The nuts and bolts.

PubMed

Ayyar, B Vijayalakshmi; Arora, Sushrut; Ravi, Shiva Shankar

2017-03-01

Antibodies are extensively utilized entities in biomedical research, and in the development of diagnostics and therapeutics. Many of these applications require high amounts of antibodies. However, meeting this ever-increasing demand of antibodies in the global market is one of the outstanding challenges. The need to maintain a balance between demand and supply of antibodies has led the researchers to discover better means and methods for optimizing their expression. These strategies aim to increase the volumetric productivity of the antibodies along with the reduction of associated manufacturing costs. Recent years have witnessed major advances in recombinant protein technology, owing to the introduction of novel cloning strategies, gene manipulation techniques, and an array of cell and vector engineering techniques, together with the progress in fermentation technologies. These innovations were also highly beneficial for antibody expression. Antibody expression depends upon the complex interplay of multiple factors that may require fine tuning at diverse levels to achieve maximum yields. However, each antibody is unique and requires individual consideration and customization for optimizing the associated expression parameters. This review provides a comprehensive overview of several state-of-the-art approaches, such as host selection, strain engineering, codon optimization, gene optimization, vector modification and process optimization that are deemed suitable for enhancing antibody expression. Copyright © 2017 Elsevier Inc. All rights reserved.

Possibilities for specific utilization of material properties for an optimal part design

NASA Astrophysics Data System (ADS)

Beier, T.; Gerlach, J.; Roettger, R.; Kuhn, P.

2017-09-01

High-strength, cold-formable steels offer great potential for meeting cost and safety requirements in the automotive industry. In view of strengths of up to 1200 MPa now attainable, certain aspects need to be analysed and evaluated in advance in the development process using these materials. In addition to early assessment of crash properties, it is also highly important to adapt the forming process to match the material potential. The steel making companies have widened their portfolios of cold-rolled dual-phase steels well beyond the conventional high-strength steels. There are added new grades which offer a customized selection of high energy absorption, deformation resistance or enhanced cold-forming properties. In this article the necessary components for material modelling for finite element simulation are discussed. Additionally the required tests for material model calibration are presented and the potentials of the thyssenkrupp Steel material data base are introduced. Besides classical tensile tests at different angles to rolling direction and the forming limit curve, the hydraulic bulge test is now available for a wide range of modern steel grades. Using the conventional DP-K®60/98 and the DP-K®700Y980T with higher yield strength the method for calibrating yield locus, hardening and formability is given. With reference to the examples of an A-pillar reinforcement and different crash tests the procedure is shown how the customer can evaluate an optimal steel grade for specific requirements. Although the investigated materials have different yield strengths, no large differences in the forming process between the two steel grades can be found. However some advantages of the high-yield grade can be detected in crash performance depending on the specific boundary and loading conditions.

Serum and supplement optimization for EU GMP-compliance in cardiospheres cell culture

PubMed Central

Chimenti, Isotta; Gaetani, Roberto; Forte, Elvira; Angelini, Francesco; De Falco, Elena; Zoccai, Giuseppe Biondi; Messina, Elisa; Frati, Giacomo; Giacomello, Alessandro

2014-01-01

Cardiac progenitor cells (CPCs) isolated as cardiospheres (CSs) and CS-derived cells (CDCs) are a promising tool for cardiac cell therapy in heart failure patients, having CDCs already been used in a phase I/II clinical trial. Culture standardization according to Good Manufacturing Practices (GMPs) is a mandatory step for clinical translation. One of the main issues raised is the use of xenogenic additives (e.g. FBS, foetal bovine serum) in cell culture media, which carries the risk of contamination with infectious viral/prion agents, and the possible induction of immunizing effects in the final recipient. In this study, B27 supplement and sera requirements to comply with European GMPs were investigated in CSs and CDCs cultures, in terms of process yield/efficiency and final cell product gene expression levels, as well as phenotype. B27− free CS cultures produced a significantly reduced yield and a 10-fold drop in c-kit expression levels versus B27+ media. Moreover, autologous human serum (aHS) and two different commercially available GMP AB HSs were compared with standard research-grade FBS. CPCs from all HSs explants had reduced growth rate, assumed a senescent-like morphology with time in culture, and/or displayed a significant shift towards the endothelial phenotype. Among three different GMP gamma-irradiated FBSs (giFBSs) tested, two provided unsatisfactory cell yields, while one performed optimally, in terms of CPCs yield/phenotype. In conclusion, the use of HSs for the isolation and expansion of CSs/CDCs has to be excluded because of altered proliferation and/or commitment, while media supplemented with B27 and the selected giFBS allows successful EU GMP-complying CPCs culture. PMID:24444305

A methodology for optimal MSW management, with an application in the waste transportation of Attica Region, Greece

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

Economopoulou, M.A.; Economopoulou, A.A.; Economopoulos, A.P., E-mail: eco@otenet.gr

2013-11-15

Highlights: • A two-step (strategic and detailed optimal planning) methodology is used for solving complex MSW management problems. • A software package is outlined, which can be used for generating detailed optimal plans. • Sensitivity analysis compares alternative scenarios that address objections and/or wishes of local communities. • A case study shows the application of the above procedure in practice and demonstrates the results and benefits obtained. - Abstract: The paper describes a software system capable of formulating alternative optimal Municipal Solid Wastes (MSWs) management plans, each of which meets a set of constraints that may reflect selected objections and/ormore » wishes of local communities. The objective function to be minimized in each plan is the sum of the annualized capital investment and annual operating cost of all transportation, treatment and final disposal operations involved, taking into consideration the possible income from the sale of products and any other financial incentives or disincentives that may exist. For each plan formulated, the system generates several reports that define the plan, analyze its cost elements and yield an indicative profile of selected types of installations, as well as data files that facilitate the geographic representation of the optimal solution in maps through the use of GIS. A number of these reports compare the technical and economic data from all scenarios considered at the study area, municipality and installation level constituting in effect sensitivity analysis. The generation of alternative plans offers local authorities the opportunity of choice and the results of the sensitivity analysis allow them to choose wisely and with consensus. The paper presents also an application of this software system in the capital Region of Attica in Greece, for the purpose of developing an optimal waste transportation system in line with its approved waste management plan. The formulated plan was able to: (a) serve 113 Municipalities and Communities that generate nearly 2 million t/y of comingled MSW with distinctly different waste collection patterns, (b) take into consideration several existing waste transfer stations (WTS) and optimize their use within the overall plan, (c) select the most appropriate sites among the potentially suitable (new and in use) ones, (d) generate the optimal profile of each WTS proposed, and (e) perform sensitivity analysis so as to define the impact of selected sets of constraints (limitations in the availability of sites and in the capacity of their installations) on the design and cost of the ensuing optimal waste transfer system. The results show that optimal planning offers significant economic savings to municipalities, while reducing at the same time the present levels of traffic, fuel consumptions and air emissions in the congested Athens basin.« less

Activated carbon enhanced anaerobic digestion of food waste - Laboratory-scale and Pilot-scale operation.

PubMed

Zhang, Le; Zhang, Jingxin; Loh, Kai-Chee

2018-05-01

Effects of activated carbon (AC) supplementation on anaerobic digestion (AD) of food waste were elucidated in lab- and pilot-scales. Lab-scale AD was performed in 1 L and 8 L digesters, while pilot-scale AD was conducted in a 1000 L digester. Based on the optimal dose of 15 g AC per working volume derived from the 1 L digester, for the same AC dosage in the 8 L digester, an improved operation stability coupled with a higher methane yield was achieved even when digesters without AC supplementation failed after 59 days due to accumulation of substantial organic intermediates. At the same time, color removal from the liquid phase of the digestate was dramatically enhanced and the particle size of the digestate solids was increased by 53% through AC supplementation after running for 59 days. Pyrosequencing of 16S rRNA gene showed the abundance of predominant phyla Firmicutes, Elusimicrobia and Proteobacteria selectively enhanced by 1.7-fold, 2.9-fold and 2.1-fold, respectively. Pilot-scale digester without AC gave an average methane yield of 0.466 L⋅(gVS) -1 ⋅d -1 at a composition of 53-61% v/v methane. With AC augmentation, an increase of 41% in methane yield was achieved in the 1000 L digester under optimal organic loading rate (1.6 g VS FW ·L -1 ·d -1 ). Copyright © 2018 Elsevier Ltd. All rights reserved.

Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers.

PubMed

Maniruzzaman, Md; Rahman, Md Jahanur; Al-MehediHasan, Md; Suri, Harman S; Abedin, Md Menhazul; El-Baz, Ayman; Suri, Jasjit S

2018-04-10

Diabetes mellitus is a group of metabolic diseases in which blood sugar levels are too high. About 8.8% of the world was diabetic in 2017. It is projected that this will reach nearly 10% by 2045. The major challenge is that when machine learning-based classifiers are applied to such data sets for risk stratification, leads to lower performance. Thus, our objective is to develop an optimized and robust machine learning (ML) system under the assumption that missing values or outliers if replaced by a median configuration will yield higher risk stratification accuracy. This ML-based risk stratification is designed, optimized and evaluated, where: (i) the features are extracted and optimized from the six feature selection techniques (random forest, logistic regression, mutual information, principal component analysis, analysis of variance, and Fisher discriminant ratio) and combined with ten different types of classifiers (linear discriminant analysis, quadratic discriminant analysis, naïve Bayes, Gaussian process classification, support vector machine, artificial neural network, Adaboost, logistic regression, decision tree, and random forest) under the hypothesis that both missing values and outliers when replaced by computed medians will improve the risk stratification accuracy. Pima Indian diabetic dataset (768 patients: 268 diabetic and 500 controls) was used. Our results demonstrate that on replacing the missing values and outliers by group median and median values, respectively and further using the combination of random forest feature selection and random forest classification technique yields an accuracy, sensitivity, specificity, positive predictive value, negative predictive value and area under the curve as: 92.26%, 95.96%, 79.72%, 91.14%, 91.20%, and 0.93, respectively. This is an improvement of 10% over previously developed techniques published in literature. The system was validated for its stability and reliability. RF-based model showed the best performance when outliers are replaced by median values.

Information content of visible and midinfrared radiances for retrieving tropical ice cloud properties

NASA Astrophysics Data System (ADS)

Chang, Kai-Wei; L'Ecuyer, Tristan S.; Kahn, Brian H.; Natraj, Vijay

2017-05-01

Hyperspectral instruments such as Atmospheric Infrared Sounder (AIRS) have spectrally dense observations effective for ice cloud retrievals. However, due to the large number of channels, only a small subset is typically used. It is crucial that this subset of channels be chosen to contain the maximum possible information about the retrieved variables. This study describes an information content analysis designed to select optimal channels for ice cloud retrievals. To account for variations in ice cloud properties, we perform channel selection over an ensemble of cloud regimes, extracted with a clustering algorithm, from a multiyear database at a tropical Atmospheric Radiation Measurement site. Multiple satellite viewing angles over land and ocean surfaces are considered to simulate the variations in observation scenarios. The results suggest that AIRS channels near wavelengths of 14, 10.4, 4.2, and 3.8 μm contain the most information. With an eye toward developing a joint AIRS-MODIS (Moderate Resolution Imaging Spectroradiometer) retrieval, the analysis is also applied to combined measurements from both instruments. While application of this method to MODIS yields results consistent with previous channel sensitivity studies, the analysis shows that this combination may yield substantial improvement in cloud retrievals. MODIS provides most information on optical thickness and particle size, aided by a better constraint on cloud vertical placement from AIRS. An alternate scenario where cloud top boundaries are supplied by the active sensors in the A-train is also explored. The more robust cloud placement afforded by active sensors shifts the optimal channels toward the window region and shortwave infrared, further constraining optical thickness and particle size.

Utilization of optimized BCR three-step sequential and dilute HCl single extraction procedures for soil-plant metal transfer predictions in contaminated lands.

PubMed

Kubová, Jana; Matús, Peter; Bujdos, Marek; Hagarová, Ingrid; Medved', Ján

2008-05-30

The prediction of soil metal phytoavailability using the chemical extractions is a conventional approach routinely used in soil testing. The adequacy of such soil tests for this purpose is commonly assessed through a comparison of extraction results with metal contents in relevant plants. In this work, the fractions of selected risk metals (Al, As, Cd, Cu, Fe, Mn, Ni, Pb, Zn) that can be taken up by various plants were obtained by optimized BCR (Community Bureau of Reference) three-step sequential extraction procedure (SEP) and by single 0.5 mol L(-1) HCl extraction. These procedures were validated using five soil and sediment reference materials (SRM 2710, SRM 2711, CRM 483, CRM 701, SRM RTH 912) and applied to significantly different acidified soils for the fractionation of studied metals. The new indicative values of Al, Cd, Cu, Fe, Mn, P, Pb and Zn fractional concentrations for these reference materials were obtained by the dilute HCl single extraction. The influence of various soil genesis, content of essential elements (Ca, Mg, K, P) and different anthropogenic sources of acidification on extraction yields of individual risk metal fractions was investigated. The concentrations of studied elements were determined by atomic spectrometry methods (flame, graphite furnace and hydride generation atomic absorption spectrometry and inductively coupled plasma optical emission spectrometry). It can be concluded that the data of extraction yields from first BCR SEP acid extractable step and soil-plant transfer coefficients can be applied to the prediction of qualitative mobility of selected risk metals in different soil systems.

Feature selection and classification of multiparametric medical images using bagging and SVM

NASA Astrophysics Data System (ADS)

Fan, Yong; Resnick, Susan M.; Davatzikos, Christos

2008-03-01

This paper presents a framework for brain classification based on multi-parametric medical images. This method takes advantage of multi-parametric imaging to provide a set of discriminative features for classifier construction by using a regional feature extraction method which takes into account joint correlations among different image parameters; in the experiments herein, MRI and PET images of the brain are used. Support vector machine classifiers are then trained based on the most discriminative features selected from the feature set. To facilitate robust classification and optimal selection of parameters involved in classification, in view of the well-known "curse of dimensionality", base classifiers are constructed in a bagging (bootstrap aggregating) framework for building an ensemble classifier and the classification parameters of these base classifiers are optimized by means of maximizing the area under the ROC (receiver operating characteristic) curve estimated from their prediction performance on left-out samples of bootstrap sampling. This classification system is tested on a sex classification problem, where it yields over 90% classification rates for unseen subjects. The proposed classification method is also compared with other commonly used classification algorithms, with favorable results. These results illustrate that the methods built upon information jointly extracted from multi-parametric images have the potential to perform individual classification with high sensitivity and specificity.

Selective Hydrogenation of CO2 to Ethanol over Cobalt Catalysts.

PubMed

Wang, Lingxiang; Wang, Liang; Zhang, Jian; Liu, Xiaolong; Wang, Hai; Zhang, Wei; Yang, Qi; Ma, Jingyuan; Dong, Xue; Yoo, Seung Jo; Kim, Jin-Gyu; Meng, Xiangju; Xiao, Feng-Shou

2018-05-22

Methods for the hydrogenation of CO 2 into valuable chemicals are in great demand but their development is still challenging. Herein, we report the selective hydrogenation of CO 2 into ethanol over non-noble cobalt catalysts (CoAlO x ), presenting a significant advance for the conversion of CO 2 into ethanol as the major product. By adjusting the composition of the catalysts through the use of different prereduction temperatures, the efficiency of CO 2 to ethanol hydrogenation was optimized; the catalyst reduced at 600 ° gave an ethanol selectivity of 92.1 % at 140 °C with an ethanol time yield of 0.444 mmol g -1  h -1 . Operando FT-IR spectroscopy revealed that the high ethanol selectivity over the CoAlO x catalyst might be due to the formation of acetate from formate by insertion of *CH x , a key intermediate in the production of ethanol by CO 2 hydrogenation. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Selective Extraction of Flavonoids from Sophora flavescens Ait. by Mechanochemistry.

PubMed

Zhang, Qihong; Yu, Jingbo; Wang, Yingyao; Su, Weike

2016-07-29

Flavonoids from Sophora flavescens were selectively extracted by mechanochemical-promoted extraction technology (MPET) after using response surface methodology to determine the optimal extraction parameters. The highest yield of 35.17 mg/g was achieved by grinding the roots with Na₂CO₃ (15%) at 440 rpm/min for 17.0 min and water was used as the sole solvent with a ratio of solvent to solid material of 25 mL/g. Flavonoids prepared by MPET demonstrated relatively higher antioxidant activities in subsequent DPPH and hydroxyl radical scavenging assays. Main constituents in the extracts, including kurarinol, kushenol I/N and kurarinone, were characterized by HPLC-MS/MS, indicating good selective extraction by MPET. Physicochemical property changes of powder during mechanochemical milling were identified by scanning electron microscopy, X-ray powder diffraction, and UV-Vis diffuse-reflectance spectroscopy. Compared with traditional extraction methods, MPET possesses notable advantages of higher selectivity, lower extraction temperature, shorter extraction time, and organic solvent free properties.

Exploring Tyrosine-Triazolinedione (TAD) Reactions for the Selective Conjugation and Cross-Linking of N-Carboxyanhydride (NCA) Derived Synthetic Copolypeptides.

PubMed

Hanay, Saltuk B; Ritzen, Bas; Brougham, Dermot; Dias, Aylvin A; Heise, Andreas

2017-07-01

Highly efficient functionalization and cross-linking of polypeptides is achieved via tyrosine-triazolinedione (TAD) conjugation chemistry. The feasibility of the reaction is demonstrated by the reaction of 4-phenyl-1,2,4-triazoline-3,5-dione (PTAD) with tyrosine containing block copolymer poly(ethylene glycol)-Tyr 4 as well as a statistical copolymer of tyrosine and lysine (poly(Lys 40 -st-Tyr 10 )) prepared form N-carboxyanhydride polymerization. Selective reaction of PTAD with the tyrosine units is obtained and verified by size exclusion chromatography and NMR spectroscopy. Moreover, two monofunctional and two difunctional TAD molecules are synthesized. It is found that their stability in the aqueous reaction media significantly varied. Under optimized reaction conditions selective functionalization and cross-linking, yielding polypeptide hydrogels, can be achieved. TAD-mediated conjugation can offer an interesting addition in the toolbox of selective (click-like) polypeptide conjugation methodologies as it does not require functional non-natural amino acids. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Effect of gene optimization on the expression and purification of HDV small antigen produced by genetic engineering].

PubMed

Ding, Jun-Ying; Meng, Qing-Ling; Guo, Min-Zhuo; Yi, Yao; Su, Qiu-Dong; Lu, Xue-Xin; Qiu, Feng; Bi, Sheng-Li

2012-10-01

To study the effect of gene optimization on the expression and purification of HDV small antigen produced by genetic engineering. Based on the colon preference of E. coli, the HDV small antigen original gene from GenBank was optimized. Both the original gene and the optimized gene expressed in prokaryotic cells, SDS-PAGE was made to analyze the protein expression yield and to decide which protein expression style was more proportion than the other. Furthermore, two antigens were purified by chromatography in order to compare the purity by SDS-PAGE and Image Lab software. SDS-PAGE indicated that the molecular weight of target proteins from two groups were the same as we expected. Gene optimization resulted in the higher yield and it could make the product more soluble. After chromatography, the purity of target protein from optimized gene was up to 96.3%, obviously purer than that from original gene. Gene optimization could increase the protein expression yield and solubility of genetic engineering HDV small antigen. In addition, the product from the optimized gene group was easier to be purified for diagnosis usage.

Incorporating a constrained optimization algorithm into remote sensing/precision agriculture methodology

NASA Astrophysics Data System (ADS)

Moreenthaler, George W.; Khatib, Nader; Kim, Byoungsoo

2003-08-01

For two decades now, the use of Remote Sensing/Precision Agriculture to improve farm yields while reducing the use of polluting chemicals and the limited water supply has been a major goal. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, farm efficiency must increase to meet future food requirements and to make farming a sustainable, profitable occupation. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The real goal is to increase farm profitability by identifying the additional treatments of chemicals and water that increase revenues more than they increase costs and do no exceed pollution standards (constrained optimization). Even though the economic and environmental benefits appear to be great, Remote Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now in place, but other needed factors have been missing. Commercial satellite systems can now image the Earth (multi-spectrally) with a resolution as fine as 2.5 m. Precision variable dispensing systems using GPS are now available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been developed. Personal computers and internet access are now in place in most farm homes and can provide a mechanism for periodically disseminating advice on what quantities of water and chemicals are needed in specific regions of each field. Several processes have been selected that fuse the disparate sources of information on the current and historic states of the crop and soil, and the remaining resource levels available, with the critical decisions that farmers are required to make. These are done in a way that is easy for the farmer to understand and profitable to implement. A "Constrained Optimization Algorithm" to further improve these processes will be presented. The objective function of the model will used to maximize the farmer's profit via increasing yields while decreasing environmental damage and decreasing applications of costly treatments. This model will incorporate information from Remote Sensing, from in-situ weather sources, from soil history, and from tacit farmer knowledge of the relative productivity of selected "Management Zones" of the farm, to provide incremental advice throughout the growing season on the optimum usage of water and chemical treatments.

Development and validation of ultrasound-assisted solid-liquid extraction of phenolic compounds from waste spent coffee grounds.

PubMed

Al-Dhabi, Naif Abdullah; Ponmurugan, Karuppiah; Maran Jeganathan, Prakash

2017-01-01

In this current work, Box-Behnken statistical experimental design (BBD) was adopted to evaluate and optimize USLE (ultrasound-assisted solid-liquid extraction) of phytochemicals from spent coffee grounds. Factors employed in this study are ultrasonic power, temperature, time and solid-liquid (SL) ratio. Individual and interactive effect of independent variables over the extraction yield was depicted through mathematical models, which are generated from the experimental data. Determined optimum process conditions are 244W of ultrasonic power, 40°C of temperature, 34min of time and 1:17g/ml of SL ratio. The predicted values were in correlation with experimental values with 95% confidence level, under the determined optimal conditions. This indicates the significance of selected method for USLE of phytochemicals from SCG. Copyright © 2016 Elsevier B.V. All rights reserved.

Separation science is the key to successful biopharmaceuticals.

PubMed

Guiochon, Georges; Beaver, Lois Ann

2011-12-09

The impact of economic change, advances in science, therapy and production processes resulted in considerable growth in the area of biopharmaceuticals. Progress in selection of microorganisms and improvements in cell culture and bioreactors is evidenced by increased yields of the desired products in the complex fermentation mixture. At this stage the downstream process of extraction and purification of the desired biopharmaceutical requires considerable attention in the design and operation of the units used for preparative chromatography. Understanding of the process, optimization of column design and experimental conditions have become critical to the biopharmaceutical industry in order to minimize production costs while satisfying new regulatory requirements. Optimization of the purification of biopharmaceuticals by preparative liquid chromatography including an examination of column preparation and bed properties is the focus of this manuscript. Copyright © 2011 Elsevier B.V. All rights reserved.

P300 Chinese input system based on Bayesian LDA.

PubMed

Jin, Jing; Allison, Brendan Z; Brunner, Clemens; Wang, Bei; Wang, Xingyu; Zhang, Jianhua; Neuper, Christa; Pfurtscheller, Gert

2010-02-01

A brain-computer interface (BCI) is a new communication channel between humans and computers that translates brain activity into recognizable command and control signals. Attended events can evoke P300 potentials in the electroencephalogram. Hence, the P300 has been used in BCI systems to spell, control cursors or robotic devices, and other tasks. This paper introduces a novel P300 BCI to communicate Chinese characters. To improve classification accuracy, an optimization algorithm (particle swarm optimization, PSO) is used for channel selection (i.e., identifying the best electrode configuration). The effects of different electrode configurations on classification accuracy were tested by Bayesian linear discriminant analysis offline. The offline results from 11 subjects show that this new P300 BCI can effectively communicate Chinese characters and that the features extracted from the electrodes obtained by PSO yield good performance.

The potential for using canopy spectral reflectance as an indirect selection tool for yield improvement in winter wheat

NASA Astrophysics Data System (ADS)

Prasad, Bishwajit

Scope and methods of study. Complementing breeding effort by deploying alternative methods of identifying higher yielding genotypes in a wheat breeding program is important for obtaining greater genetic gains. Spectral reflectance indices (SRI) are one of the many indirect selection tools that have been reported to be associated with different physiological process of wheat. A total of five experiments (a set of 25 released cultivars from winter wheat breeding programs of the U.S. Great Plains and four populations of randomly derived recombinant inbred lines having 25 entries in each population) were conducted in two years under Great Plains winter wheat rainfed environments at Oklahoma State University research farms. Grain yield was measured in each experiment and biomass was measured in three experiments at three growth stages (booting, heading, and grainfilling). Canopy spectral reflectance was measured at three growth stages and eleven SRI were calculated. Correlation (phenotypic and genetic) between grain yield and SRI, biomass and SRI, heritability (broad sense) of the SRI and yield, response to selection and correlated response, relative selection efficiency of the SRI, and efficiency in selecting the higher yielding genotypes by the SRI were assessed. Findings and conclusions. The genetic correlation coefficients revealed that the water based near infrared indices (WI and NWI) were strongly associated with grain yield and biomass production. The regression analysis detected a linear relationship between the water based indices with grain yield and biomass. The two newly developed indices (NWI-3 and NWI-4) gave higher broad sense heritability than grain yield, higher direct response to selection compared to grain yield, correlated response equal to or higher than direct response for grain yield, relative selection efficiency greater than one, and higher efficiency in selecting higher yielding genotypes. Based on the overall genetic analysis required to establish any trait as an efficient indirect selection tool, the water based SRI (especially NWI-3 and NWI-4) have the potential to complement the classical breeding effort for selecting genotypes with higher yield potential in a winter wheat breeding program.

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

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo

We analyze quantum algorithms for cloning of a quantum measurement. Our aim is to mimic two uses of a device performing an unknown von Neumann measurement with a single use of the device. When the unknown device has to be used before the bipartite state to be measured is available we talk about 1{yields}2 learning of the measurement, otherwise the task is called 1{yields}2 cloning of a measurement. We perform the optimization for both learning and cloning for arbitrary dimension d of the Hilbert space. For 1{yields}2 cloning we also propose a simple quantum network that achieves the optimal fidelity.more » The optimal fidelity for 1{yields}2 learning just slightly outperforms the estimate and prepare strategy in which one first estimates the unknown measurement and depending on the result suitably prepares the duplicate.« less

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

PubMed

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

2015-10-15

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

Measurement of the top-quark mass with dilepton events selected using neuroevolution at CDF.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Copic, K; Cordelli, M; Cortiana, G; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kusakabe, Y; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, S W; Leone, S; Lewis, J D; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlok, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyrla, A; Shalhout, S Z; Shears, T; Shekhar, R; Shepard, P F; Sherman, D; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Whiteson, S; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S

2009-04-17

We report a measurement of the top-quark mass M_{t} in the dilepton decay channel tt[over ] --> bl;{'+} nu_{l};{'}b[over ]l;{-}nu[over ]_{l}. Events are selected with a neural network which has been directly optimized for statistical precision in top-quark mass using neuroevolution, a technique modeled on biological evolution. The top-quark mass is extracted from per-event probability densities that are formed by the convolution of leading order matrix elements and detector resolution functions. The joint probability is the product of the probability densities from 344 candidate events in 2.0 fb;{-1} of pp[over ] collisions collected with the CDF II detector, yielding a measurement of M_{t} = 171.2 +/- 2.7(stat) +/- 2.9(syst) GeV / c;{2}.

Selective destruction of mouse islet beta cells by human T lymphocytes in a newly-established humanized type 1 diabetic model

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

Zhao, Yong, E-mail: yongzhao@uic.edu; Guo, Chengshan; Hwang, David

2010-09-03

Research highlights: {yields} Establish a human immune-mediated type 1 diabetic model in NOD-scid IL2r{gamma}{sup null} mice. {yields} Using the irradiated diabetic NOD mouse spleen mononuclear cells as trigger. {yields} The islet {beta} cells were selectively destroyed by infiltrated human T cells. {yields} The model can facilitate translational research to find a cure for type 1 diabetes. -- Abstract: Type 1 diabetes (T1D) is caused by a T cell-mediated autoimmune response that leads to the loss of insulin-producing {beta} cells. The optimal preclinical testing of promising therapies would be aided by a humanized immune-mediated T1D model. We develop this model inmore » NOD-scid IL2r{gamma}{sup null} mice. The selective destruction of pancreatic islet {beta} cells was mediated by human T lymphocytes after an initial trigger was supplied by the injection of irradiated spleen mononuclear cells (SMC) from diabetic nonobese diabetic (NOD) mice. This resulted in severe insulitis, a marked loss of total {beta}-cell mass, and other related phenotypes of T1D. The migration of human T cells to pancreatic islets was controlled by the {beta} cell-produced highly conserved chemokine stromal cell-derived factor 1 (SDF-1) and its receptor C-X-C chemokine receptor (CXCR) 4, as demonstrated by in vivo blocking experiments using antibody to CXCR4. The specificity of humanized T cell-mediated immune responses against islet {beta} cells was generated by the local inflammatory microenvironment in pancreatic islets including human CD4{sup +} T cell infiltration and clonal expansion, and the mouse islet {beta}-cell-derived CD1d-mediated human iNKT activation. The selective destruction of mouse islet {beta} cells by a human T cell-mediated immune response in this humanized T1D model can mimic those observed in T1D patients. This model can provide a valuable tool for translational research into T1D.« less

Discovery of highly selective inhibitors of p38alpha.

PubMed

Popa-Burke, Ioana; Birkos, Steve; Blackwell, Leonard; Cheatham, Lynn; Clark, Jennifer; Dickson, John K; Galasinski, Scott; Janzen, William P; Mendoza, Jose; Miller, Jennifer L; Mohney, Robert P; Steed, Paul M; Hodge, C Nicholas

2005-01-01

The p38 MAP kinases are a family of serine/threonine protein kinases that play a key role in cellular pathways leading to pro-inflammatory responses. We have developed and implemented a method for rapidly identifying and optimizing potent and selective p38alpha inhibitors, which is amenable to other targets and target classes. A diverse library of druggable, purified and quantitated molecules was assembled and standardized enzymatic assays were performed in a microfluidic format that provided very accurate and precise inhibition data allowing for development of SAR directly from the primary HTS. All compounds were screened against a collection of more than 60 enzymes (kinases, proteases and phosphatases), allowing for removal of promiscuous and non-selective inhibitors very early in the discovery process. Follow-up enzymological studies included measurement of concentration of compound in buffer, yielding accurate determination of K(i) and IC50 values, as well as mechanism of action. In addition, active compounds were screened against less desirable properties such as inhibition of the enzyme activity by aggregation, irreversible binding, and time-dependence. Screening of an 88,634-compound library through the above-described process led to the rapid identification of multiple scaffolds (>5 active compounds per scaffold) of potential drug leads for p38alpha that are highly selective against all other enzymes tested, including the three other p38 isoforms. Potency and selectivity data allowed prioritization of the identified scaffolds for optimization. Herein we present results around our 3-thio-1,2,4-triazole lead series of p38- selective inhibitors, including identification, SAR, synthesis, selectivity profile, enzymatic and cellular data in their progression towards drug candidates.

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

Chen Lin; Chen Yixin

We show that no universal quantum cloning machine exists that can broadcast an arbitrary mixed qubit with a constant fidelity. Based on this result, we investigate the dependent quantum cloner in the sense that some parameter of the input qubit {rho}{sub s}({theta},{omega},{lambda}) is regarded as constant in the fidelity. For the case of constant {omega}, we establish the 1{yields}2 optimal symmetric dependent cloner with a fidelity 1/2. It is also shown that the 1{yields}M optimal quantum cloning machine for pure qubits is also optimal for mixed qubits, when {lambda} is the unique parameter in the fidelity. For general N{yields}M broadcastingmore » of mixed qubits, the situation is very different.« less

Enhanced size-dependent trapping of particles using microvortices

PubMed Central

Zhou, Jian; Kasper, Susan; Papautsky, Ian

2013-01-01

Inertial microfluidics has been attracting considerable interest for size-based separation of particles and cells. The inertial forces can be manipulated by expanding the microchannel geometry, leading to formation of microvortices which selectively isolate and trap particles or cells from a mixture. In this work, we aim to enhance our understanding of particle trapping in such microvortices by developing a model of selective particle trapping. Design and operational parameters including flow conditions, size of the trapping region, and target particle concentration are explored to elucidate their influence on trapping behavior. Our results show that the size dependence of trapping is characterized by a threshold Reynolds number, which governs the selective entry of particles into microvortices from the main flow. We show that concentration enhancement on the order of 100,000× and isolation of targets at concentrations in the 1/mL is possible. Ultimately, the insights gained from our systematic investigation suggest optimization solutions that enhance device performance (efficiency, size selectivity, and yield) and are applicable to selective isolation and trapping of large rare cells as well as other applications. PMID:24187531

Lactic acid and methane: improved exploitation of biowaste potential.

PubMed

Dreschke, G; Probst, M; Walter, A; Pümpel, T; Walde, J; Insam, H

2015-01-01

This feasibility study investigated a two-step biorefining approach to increase the value gained by recycling of organic municipal solid waste. Firstly, lactic acid was produced via batch fermentation at 37°C using the indigenous microbiome. Experiments revealed an optimal fermentation period of 24h resulting in high yields of lactic acid (up to 37gkg(-1)). The lactic acid proportion of total volatile fatty acid content reached up to 83%. Lactobacilli were selectively enriched to up to 75% of the bacterial community. Additionally conversion of organic matter to lactic acid was increased from 22% to 30% through counteracting end product inhibition by continuous lactic acid extraction. Secondly, fermentation residues were used as co-substrate in biomethane production yielding up to 618±41Nmlbiomethaneg(-1) volatile solids. Digestate, the only end product of this process can be used as organic fertilizer. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Deep Learning Approach to Examine Ischemic ST Changes in Ambulatory ECG Recordings.

PubMed

Xiao, Ran; Xu, Yuan; Pelter, Michele M; Mortara, David W; Hu, Xiao

2018-01-01

Patients with suspected acute coronary syndrome (ACS) are at risk of transient myocardial ischemia (TMI), which could lead to serious morbidity or even mortality. Early detection of myocardial ischemia can reduce damage to heart tissues and improve patient condition. Significant ST change in the electrocardiogram (ECG) is an important marker for detecting myocardial ischemia during the rule-out phase of potential ACS. However, current ECG monitoring software is vastly underused due to excessive false alarms. The present study aims to tackle this problem by combining a novel image-based approach with deep learning techniques to improve the detection accuracy of significant ST depression change. The obtained convolutional neural network (CNN) model yields an average area under the curve (AUC) at 89.6% from an independent testing set. At selected optimal cutoff thresholds, the proposed model yields a mean sensitivity at 84.4% while maintaining specificity at 84.9%.

Efficient catalytic system for the direct transformation of lignocellulosic biomass to furfural and 5-hydroxymethylfurfural.

PubMed

Zhang, Luxin; Xi, Guoyun; Zhang, Jiaxin; Yu, Hongbing; Wang, Xiaochang

2017-01-01

A feasible approach was developed for the co-production of 5-hydroxymethylfurfural (5-HMF) and furfural from corncob via a new porous polytriphenylamine-SO 3 H (SPTPA) solid acid catalyst in lactone solvents. XRD, SEM, XPS, N 2 adsorption-desorption, elemental analysis, TG-DTA, acid-base titration and FTIR spectroscopy techniques were used to characterize the catalyst. This study demonstrates and optimizes the catalytic performance of SPTPA and solvent selection. SPTPA was found to exhibit superior catalytic ability in γ-valerolactone (GVL). Under the optimum reaction conditions, simultaneously encouraging yields of furfural (73.9%) and 5-HMF (32.3%) were achieved at 448K. The main advantages of this process include reasonable yields of both 5-HMF and furfural in the same reaction system, practical simplicity for the raw biomass utilization, and the use of a safe and environmentally benign solvent. Copyright © 2016 Elsevier Ltd. All rights reserved.

Continuously tunable nucleic acid hybridization probes.

PubMed

Wu, Lucia R; Wang, Juexiao Sherry; Fang, John Z; Evans, Emily R; Pinto, Alessandro; Pekker, Irena; Boykin, Richard; Ngouenet, Celine; Webster, Philippa J; Beechem, Joseph; Zhang, David Yu

2015-12-01

In silico-designed nucleic acid probes and primers often do not achieve favorable specificity and sensitivity tradeoffs on the first try, and iterative empirical sequence-based optimization is needed, particularly in multiplexed assays. We present a novel, on-the-fly method of tuning probe affinity and selectivity by adjusting the stoichiometry of auxiliary species, which allows for independent and decoupled adjustment of the hybridization yield for different probes in multiplexed assays. Using this method, we achieved near-continuous tuning of probe effective free energy. To demonstrate our approach, we enforced uniform capture efficiency of 31 DNA molecules (GC content, 0-100%), maximized the signal difference for 11 pairs of single-nucleotide variants and performed tunable hybrid capture of mRNA from total RNA. Using the Nanostring nCounter platform, we applied stoichiometric tuning to simultaneously adjust yields for a 24-plex assay, and we show multiplexed quantitation of RNA sequences and variants from formalin-fixed, paraffin-embedded samples.

X-ray computed tomography to study rice (Oryza sativa L.) panicle development

PubMed Central

Jhala, Vibhuti M.; Thaker, Vrinda S.

2015-01-01

Computational tomography is an important technique for developing digital agricultural models that may help farmers and breeders for increasing crop quality and yield. In the present study an attempt has been made to understand rice seed development within the panicle at different developmental stages using this technique. During the first phase of cell division the Hounsfield Unit (HU) value remained low, increased in the dry matter accumulation phase, and finally reached a maximum at the maturation stage. HU value and seed dry weight showed a linear relationship in the varieties studied. This relationship was confirmed subsequently using seven other varieties. This is therefore an easy, simple, and non-invasive technique which may help breeders to select the best varieties. In addition, it may also help farmers to optimize post-anthesis agronomic practices as well as deciding the crop harvest time for higher grain yield. PMID:26265763

Production of bio-oil and biochar from soapstock via microwave-assisted co-catalytic fast pyrolysis.

PubMed

Dai, Leilei; Fan, Liangliang; Liu, Yuhuan; Ruan, Roger; Wang, Yunpu; Zhou, Yue; Zhao, Yunfeng; Yu, Zhenting

2017-02-01

In this study, production of bio-oil and biochar from soapstock via microwave-assisted co-catalytic fast pyrolysis combining the advantages of in-situ and ex-situ catalysis was performed. The effects of catalyst and pyrolysis temperature on product fractional yields and bio-oil chemical compositions were investigated. From the perspective of bio-oil yield, the optimal pyrolysis temperature was 550°C. The use of catalysts reduced the water content, and the addition of bentonite increased the bio-oil yield. Up to 84.16wt.% selectivity of hydrocarbons in the bio-oil was obtained in the co-catalytic process. In addition, the co-catalytic process can reduce the proportion of oxygenates in the bio-oil to 15.84wt.% and eliminate the N-containing compounds completely. The addition of bentonite enhanced the BET surface area of bio-char. In addition, the bio-char removal efficiency of Cd 2+ from soapstock pyrolysis in presence of bentonite was 27.4wt.% higher than without bentonite. Copyright © 2016 Elsevier Ltd. All rights reserved.

Studies on the factors modulating indole-3-acetic acid production in endophytic bacterial isolates from Piper nigrum and molecular analysis of ipdc gene.

PubMed

Jasim, B; Jimtha John, C; Shimil, V; Jyothis, M; Radhakrishnan, E K

2014-09-01

The study mainly aimed quantitative analysis of IAA produced by endophytic bacteria under various conditions including the presence of extract from Piper nigrum. Analysis of genetic basis of IAA production was also conducted by studying the presence and diversity of the ipdc gene among the selected isolates. Five endophytic bacteria isolated previously from P. nigrum were used for the study. The effect of temperature, pH, agitation, tryptophan concentration and plant extract on modulating IAA production of selected isolates was analysed by colorimetric method. Comparative and quantitative analysis of IAA production by colorimetric isolates under optimal culture condition was analysed by HPTLC method. Presence of ipdc gene and thereby biosynthetic basis of IAA production among the selected isolates were studied by PCR-based amplification and subsequent insilico analysis of sequence obtained. Among the selected bacterial isolates from P. nigrum, isolate PnB 8 (Klebsiella pneumoniae) was found to have the maximum yield of IAA under various conditions optimized and was confirmed by colorimetric, HPLC and HPTLC analysis. Very interestingly, the study showed stimulating effect of phytochemicals from P. nigrum on IAA production by endophytic bacteria isolated from same plant. This study is unique because of the selection of endophytes from same source for comparative and quantitative analysis of IAA production under various conditions. Study on stimulatory effect of phytochemicals on bacterial IAA production as explained in the study is a novel approach. Studies on molecular basis of IAA production which was confirmed by sequence analysis of ipdc gene make the study scientifically attractive. Even though microbial production of IAA is well known, current report on detailed optimization, effect of plant extract and molecular confirmation of IAA biosynthesis is comparatively novel in its approach. © 2014 The Society for Applied Microbiology.

Selective enrichment in bioactive compound from Kniphofia uvaria by super/subcritical fluid extraction and centrifugal partition chromatography.

PubMed

Duval, Johanna; Destandau, Emilie; Pecher, Virginie; Poujol, Marion; Tranchant, Jean-François; Lesellier, Eric

2016-05-20

Nowadays, a large portion of synthetic products (active cosmetic and therapeutic ingredients) have their origin in natural products. Kniphofia uvaria is a plant from Africa which has proved in the past by in-vivo tests an antioxidant activity due to compounds present in roots. Recently, we have observed anthraquinones in K. uvaria seeds extracts. These derivatives are natural colorants which could have interesting bioactive potential. The aim of this study was to obtain an extract enriched in anthraquinones from K. uvaria seeds which mainly contains glycerides. First, the separation of the seed compounds was studied by using supercritical fluid chromatography (SFC) in the goal to provide a rapid quantification method of these bioactive compounds. A screening of numerous polar stationary phases was achieved for selecting the most suited phase to the separation of the four anthraquinones founded in the seeds. A gradient elution was optimized for improving the separation of the bioactive compounds from the numerous other families of major compounds of the extracts (fatty acids, di- and triglycerides). Besides, a non-selective and green Supercritical Fluid Extraction (SFE) with pure CO2 was applied to seeds followed by a Centrifugal Partition Chromatography (CPC). The CPC system was optimized by using the Arizona phase system, to enrich the extract in anthraquinones. Two systems were selected to isolate the bioactive compounds from the oily extract with varied purity target. The effect of the injection mode for these very viscous samples was also studied. Finally, in order to directly apply a selective process of extraction to the seeds, the super/subcritical fluid extraction was optimized to increase the anthraquinone yield in the final extract, by studying varied modifier compositions and nature, as well as different temperatures and backpressures. Conditions suited to favour an enrichment factor bases on the ratio of anthraquinone and trilycerides extracted are described. Copyright © 2016 Elsevier B.V. All rights reserved.

Expression of codon-optmized phosphoenolpyruvate carboxylase gene from Glaciecola sp. HTCC2999 in Escherichia coli and its application for C4 chemical production.

PubMed

Park, Soohyun; Pack, Seung Pil; Lee, Jinwon

2012-08-01

We examined the expression of the phosphoenolpyruvate carboxylase (PEPC) gene from marine bacteria in Escherichia coli using codon optimization. The codon-optimized PEPC gene was expressed in the E. coli K-12 strain W3110. SDS-PAGE analysis revealed that the codon-optimized PEPC gene was only expressed in E. coli, and measurement of enzyme activity indicated the highest PEPC activity in the E. coli SGJS112 strain that contained the codon-optimized PEPC gene. In fermentation assays, the E. coli SGJS112 produced the highest yield of oxaloacetate using glucose as the source and produced a 20-times increase in the yield of malate compared to the control. We concluded that the codon optimization enabled E. coli to express the PEPC gene derived from the Glaciecola sp. HTCC2999. Also, the expressed protein exhibited an enzymatic activity similar to that of E. coli PEPC and increased the yield of oxaloacetate and malate in an E. coli system.

Selection of Drought Tolerant Maize Hybrids Using Path Coefficient Analysis and Selection Index.

PubMed

Dao, Abdalla; Sanou, Jacob; V S Traore, Edgar; Gracen, Vernon; Danquah, Eric Y

2017-01-01

In drought-prone environments, direct selection for yield is not adequate because of the variable environment and genotype x environment interaction. Therefore, the use of secondary traits in addition to yield has been suggested. The relative usefulness of secondary traits as indirect selection criteria for maize grain yield is determined by the magnitudes of their genetic variance, heritability and genetic correlation with the grain yield. Forty eight testcross hybrids derived from lines with different genetic background and geographical origins plus 7 checks were evaluated in both well-watered and water-stressed conditions over two years for grain yield and secondary traits to determine the most appropriate secondary traits and select drought tolerant hybrids. Study found that broad-sense heritability of grain yield and Ear Per Plant (EPP) increased under drought stress. Ear aspect (EASP) and ear height (EHT) had larger correlation coefficients and direct effect on grain yield but in opposite direction, negative and positive respectively. Traits like, EPP, Tassel Size (TS) and Plant Recovery (PR) contributed to increase yield via EASP by a large negative indirect effect. Under drought stress, EHT had positive and high direct effect and negative indirect effect via plant height on grain yield indicating that the ratio between ear and plant heights (R-EPH) was associated to grain yield. Path coefficient analysis showed that traits EPP, TS, PR, EASP, R-EPH were important secondary traits in the present experiment. These traits were used in a selection index to classify hybrids according to their performance under drought. The selection procedure included also a Relative Decrease in Yield (RDY) index. Some secondary traits reported as significant selection criteria for selection under drought stress were not finally established in the present study. This is because the relationship between grain and secondary traits can be affected by various factors including germplasm, environment and applied statistical analysis. Therefore, different traits and selection procedure should be applied in the selection process of drought tolerant genotypes for diverse genetic materials and growing conditions.

The kinetic study of hydrogen bacteria and methanotrophs in pure and defined mixed cultures

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

Arora, D.K.

The kinetics of pure and mixed cultures of Alcaligenes eutrophus H 16 and Methylobacterium organophilum CRL 26 under double substrate limited conditions were studied. In pure culture growth kinetics, a non-interactive model was found to fit the experimental data best. The yield of biomass on limiting substrate was found to vary with the dilution rate. The variation in the biomass yield may be attributed to the change in metabolic pathways resulting from a shift in the limiting substrates. Both species exhibited wall growth in the chemostat under dark conditions. However, under illuminated conditions, there was significant reduction in wall growth.more » Poly-{beta}-hydroxybutyric acid was synthesized by both species under ammonia and oxygen limiting conditions. The feed gas mixture was optimized to achieve the steady-state coexistence of these two species in a chemostate for the first time. In mixed cultures, the biomass species assays were differentiated on the basis of their selective growth on particular compounds: Sarcosine and D-arabinose were selected for hydrogen bacteria and methylotrophs, respectively. The kinetics parameters estimated from pure cultures were used to predict the growth kinetics of these species in defined mixed cultures.« less

Object-based classification of earthquake damage from high-resolution optical imagery using machine learning

NASA Astrophysics Data System (ADS)

Bialas, James; Oommen, Thomas; Rebbapragada, Umaa; Levin, Eugene

2016-07-01

Object-based approaches in the segmentation and classification of remotely sensed images yield more promising results compared to pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods are often used, but yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time-sensitive applications, such as earthquake damage assessment. Herein, we used a systematic approach in evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely sensed imagery. We tested a variety of algorithms and parameters on post-event aerial imagery for the 2011 earthquake in Christchurch, New Zealand. Results were compared against manually selected test cases representing different classes. In doing so, we can evaluate the effectiveness of the segmentation and classification of different classes and compare different levels of multistep image segmentations. Our classifier is compared against recent pixel-based and object-based classification studies for postevent imagery of earthquake damage. Our results show an improvement against both pixel-based and object-based methods for classifying earthquake damage in high resolution, post-event imagery.

The Optimal Forest Rotation: A Discussion and Annotated Bibliography

Treesearch

David H. Newman

1988-01-01

The literature contains six different criteria of the optimal forest rotation: (1) maximum single-rotation physical yield, (2) maximum single-rotation annual yield, (3) maximum single-rotation discounted net revenues, (4) maximum discounted net revenues from an infinite series of rotations, (5) maximum annual net revenues, and (6) maximum internal rate of return. First...

Pareto-optimal reversed-phase chromatography separation of three insulin variants with a solubility constraint.

PubMed

Arkell, Karolina; Knutson, Hans-Kristian; Frederiksen, Søren S; Breil, Martin P; Nilsson, Bernt

2018-01-12

With the shift of focus of the regulatory bodies, from fixed process conditions towards flexible ones based on process understanding, model-based optimization is becoming an important tool for process development within the biopharmaceutical industry. In this paper, a multi-objective optimization study of separation of three insulin variants by reversed-phase chromatography (RPC) is presented. The decision variables were the load factor, the concentrations of ethanol and KCl in the eluent, and the cut points for the product pooling. In addition to the purity constraints, a solubility constraint on the total insulin concentration was applied. The insulin solubility is a function of the ethanol concentration in the mobile phase, and the main aim was to investigate the effect of this constraint on the maximal productivity. Multi-objective optimization was performed with and without the solubility constraint, and visualized as Pareto fronts, showing the optimal combinations of the two objectives productivity and yield for each case. Comparison of the constrained and unconstrained Pareto fronts showed that the former diverges when the constraint becomes active, because the increase in productivity with decreasing yield is almost halted. Consequently, we suggest the operating point at which the total outlet concentration of insulin reaches the solubility limit as the most suitable one. According to the results from the constrained optimizations, the maximal productivity on the C 4 adsorbent (0.41 kg/(m 3  column h)) is less than half of that on the C 18 adsorbent (0.87 kg/(m 3  column h)). This is partly caused by the higher selectivity between the insulin variants on the C 18 adsorbent, but the main reason is the difference in how the solubility constraint affects the processes. Since the optimal ethanol concentration for elution on the C 18 adsorbent is higher than for the C 4 one, the insulin solubility is also higher, allowing a higher pool concentration. An alternative method of finding the suggested operating point was also evaluated, and it was shown to give very satisfactory results for well-mapped Pareto fronts. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of pre-sowing magnetic field doses through RSM in pea

NASA Astrophysics Data System (ADS)

Iqbal, M.; Ahmad, I.; Hussain, S. M.; Khera, R. A.; Bokhari, T. H.; Shehzad, M. A.

2013-09-01

Seed pre-sowing magnetic field treatment was reported to induce biochemical and physiological changes. In the present study, response surface methodology was used for deduction of optimal magnetic field doses. Improved growth and yield responses in the pea cultivar were achieved using a rotatable central composite design and multivariate data analysis. The growth parameters such as root and shoot fresh masses and lengths as well as yield were enhanced at a certain magnetic field level. The chlorophyll contents were also enhanced significantly vs. the control. The low magnetic field strength for longer duration of exposure/ high strength for shorter exposure were found to be optimal points for maximum responses in root fresh mass, chlorophyll `a' contents, and green pod yield/plant, respectively and a similar trend was observed for other measured parameters. The results indicate that the magnetic field pre-sowing seed treatment can be used practically to enhance the growth and yield in pea cultivar and response surface methodology was found an efficient experimental tool for optimization of the treatment level to obtain maximum response of interest.

Optimization of focused ultrasonic extraction of propellant components determined by gas chromatography/mass spectrometry.

PubMed

Fryš, Ondřej; Česla, Petr; Bajerová, Petra; Adam, Martin; Ventura, Karel

2012-09-15

A method for focused ultrasonic extraction of nitroglycerin, triphenyl amine and acetyl tributyl citrate presented in double-base propellant samples following by the gas chromatography/mass spectrometry analysis was developed. A face-centered central composite design of the experiments and response surface modeling was used for optimization of the time, amplitude and sample amount. The dichloromethane was used as the extractant solvent. The optimal extraction conditions with respect to the maximum yield of the lowest abundant compound triphenyl amine were found at the 20 min extraction time, 35% amplitude of ultrasonic waves and 2.5 g of the propellant sample. The results obtained under optimal conditions were compared with the results achieved with validated Soxhlet extraction method, which is typically used for isolation and pre-concentration of compounds from the samples of explosives. The extraction yields for acetyl tributyl citrate using both extraction methods were comparable; however, the yield of ultrasonic extraction of nitroglycerin and triphenyl amine was lower than using Soxhlet extraction. The possible sources of different extraction yields are estimated and discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

Improved strategy for recombinant production and purification of antimicrobial peptide tachyplesin I and its analogs with high cell selectivity.

PubMed

Panteleev, Pavel V; Ovchinnikova, Tatiana V

2017-01-01

Here, we report an efficient procedure for recombinant production and purification of tachyplesin I (THI) with a final yield of 17 mg/L of the culture medium. The peptide was expressed in Escherichia coli as a part of the thioredoxin fusion protein. With the use of soluble expression followed by immobilized metal-ion affinity chromatography, the recombinant protein cleavage and reversed-phase high-performance liquid chromatography, a yield of THI did not exceed 6.5 mg/L of the culture medium. Further optimization studies were carried out to improve the protein expression level and simplify purification procedure of the target peptide. To achieve better yield of the peptide, we used high-cell-density bacterial expression. The formed inclusion bodies were highly enriched with the fusion protein, which allowed us to perform direct chemical cleavage of the inclusion bodies solubilized in 6 M guanidine-HCl with subsequent selective precipitation of proteins with trifluoroacetic acid. This enabled us to avoid an extra step of purification by immobilized metal-ion affinity chromatography. The developed procedure has made it possible to obtain biologically active THI and was used for screening a number of its mutant analogs. As a result, several selective and nonhemolytic analogs were developed. Significant reduction in hemolytic activity without losing antimicrobial activity was achieved by substitution of tyrosine or isoleucine residue in the β-turn region of the molecule with hydrophilic serine. The present study affords further insight into molecular mechanism of antimicrobial action of tachyplesin and gains a better understanding of structure-activity relationships in its analogs. This is aimed at searching for novel antibiotics on the basis of antimicrobial peptides with reduced cytotoxicity. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

Mass spectrometric directed system for the continuous-flow synthesis and purification of diphenhydramine† †Electronic supplementary information (ESI) available: NMR spectra of selected product, mass spectra of selected products, crystallization information, and experimental procedures are supplied. See DOI: 10.1039/c7sc00905d Click here for additional data file.

PubMed Central

Loren, Bradley P.; Wleklinski, Michael; Koswara, Andy; Yammine, Kathryn; Hu, Yanyang

2017-01-01

A highly integrated approach to the development of a process for the continuous synthesis and purification of diphenhydramine is reported. Mass spectrometry (MS) is utilized throughout the system for on-line reaction monitoring, off-line yield quantitation, and as a reaction screening module that exploits reaction acceleration in charged microdroplets for high throughput route screening. This effort has enabled the discovery and optimization of multiple routes to diphenhydramine in glass microreactors using MS as a process analytical tool (PAT). The ability to rapidly screen conditions in charged microdroplets was used to guide optimization of the process in a microfluidic reactor. A quantitative MS method was developed and used to measure the reaction kinetics. Integration of the continuous-flow reactor/on-line MS methodology with a miniaturized crystallization platform for continuous reaction monitoring and controlled crystallization of diphenhydramine was also achieved. Our findings suggest a robust approach for the continuous manufacture of pharmaceutical drug products, exemplified in the particular case of diphenhydramine, and optimized for efficiency and crystal size, and guided by real-time analytics to produce the agent in a form that is readily adapted to continuous synthesis. PMID:28979759

A method to validate quantitative high-frequency power doppler ultrasound with fluorescence in vivo video microscopy.

PubMed

Pinter, Stephen Z; Kim, Dae-Ro; Hague, M Nicole; Chambers, Ann F; MacDonald, Ian C; Lacefield, James C

2014-08-01

Flow quantification with high-frequency (>20 MHz) power Doppler ultrasound can be performed objectively using the wall-filter selection curve (WFSC) method to select the cutoff velocity that yields a best-estimate color pixel density (CPD). An in vivo video microscopy system (IVVM) is combined with high-frequency power Doppler ultrasound to provide a method for validation of CPD measurements based on WFSCs in mouse testicular vessels. The ultrasound and IVVM systems are instrumented so that the mouse remains on the same imaging platform when switching between the two modalities. In vivo video microscopy provides gold-standard measurements of vascular diameter to validate power Doppler CPD estimates. Measurements in four image planes from three mice exhibit wide variation in the optimal cutoff velocity and indicate that a predetermined cutoff velocity setting can introduce significant errors in studies intended to quantify vascularity. Consistent with previously published flow-phantom data, in vivo WFSCs exhibited three characteristic regions and detectable plateaus. Selection of a cutoff velocity at the right end of the plateau yielded a CPD close to the gold-standard vascular volume fraction estimated using IVVM. An investigator can implement the WFSC method to help adapt cutoff velocity to current blood flow conditions and thereby improve the accuracy of power Doppler for quantitative microvascular imaging. Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Invited review: Genetic considerations for various pasture-based dairy systems.

PubMed

Washburn, S P; Mullen, K A E

2014-10-01

Pasture-based dairy systems use grazing to supply significant percentages of the dry matter intake of cows and heifers. Such systems vary from those for which pasture is used only as a supplemental feed for cows primarily fed a total mixed ration to those for which pasture is the primary source of dry matter for the herd. Cows that are optimal in a pasture system share many general characteristics with cows that are appropriate for a nonpasture system, including feed efficiency, maintenance of body condition, reproductive fitness, udder health, longevity, and the ability to adapt to various management systems. However, in such divergent feeding systems, the relative importance of various traits can differ. In pasture systems where cow nutrient demand intentionally coincides with seasonal forage availability, the focus of selection has emphasized fertility and other fitness traits, as well as yields of milk or milk components. Breeds or strains with higher yields of protein and fat typically have advantages in grazing systems that supply milk to solids-based or cheese markets. Holstein cows with high percentages of North American ancestry can work well in grazing systems that include supplemental concentrates or partial mixed rations, particularly if calving intervals are less restrictive. Crossbred cows can be selected for use in specific grazing systems as well as for specific milk markets, with the added advantage of heterosis. Breeds and crosses with high fertility are important for seasonal breeding and calving. The ability of cattle to both milk and maintain sufficient body condition for reproduction is important for any dairy production system but is critical in a seasonal system. Dairy farms that depend on pasture for most of dry matter for cows typically have lower production per cow than nongrazing dairies but have the potential to be economically competitive because of lower operating and overhead costs. Although the principles of selection are similar across a variety of pasture-based and nonpasture systems, we document from studies and observations covered herein that optimal breeds, breed strains, and selection strategies can differ based on varying management constraints and objectives. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Using normalized difference vegetation index (NDVI) to estimate sugarcane yield and yield components

USDA-ARS?s Scientific Manuscript database

Sugarcane (Saccharum spp.) yield and yield components are important traits for growers and scientists to evaluate and select cultivars. Collection of these yield data would be labor intensive and time consuming in the early selection stages of sugarcane breeding cultivar development programs with a ...

OPTIMAL TIME-SERIES SELECTION OF QUASARS

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

Butler, Nathaniel R.; Bloom, Joshua S.

2011-03-15

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

Optimization of the Alkaline Pretreatment of Rice Straw for Enhanced Methane Yield

PubMed Central

Song, Zilin; Yang, Gaihe; Han, Xinhui; Feng, Yongzhong; Ren, Guangxin

2013-01-01

The lime pretreatment process for rice straw was optimized to enhance the biodegradation performance and increase biogas yield. The optimization was implemented using response surface methodology (RSM) and Box-Behnken experimental design. The effects of biodegradation, as well as the interactive effects of Ca(OH)2 concentration, pretreatment time, and inoculum amount on biogas improvement, were investigated. Rice straw compounds, such as lignin, cellulose, and hemicellulose, were significantly degraded with increasing Ca(OH)2 concentration. The optimal conditions for the use of pretreated rice straw in anaerobic digestion were 9.81% Ca(OH)2 (w/w TS), 5.89 d treatment time, and 45.12% inoculum content, which resulted in a methane yield of 225.3 mL/g VS. A determination coefficient (R 2) of 96% was obtained, indicating that the model used to predict the anabolic digestion process shows a favorable fit with the experimental parameters. PMID:23509824

Optimization study of Chromalaena odorata essential oil extracted using solventless extraction technique

NASA Astrophysics Data System (ADS)

Nasshorudin, Dalila; Ahmad, Muhammad Syarhabil; Mamat, Awang Soh; Rosli, Suraya

2015-05-01

Solventless extraction process of Chromalaena odorata using reduced pressure and temperature has been investigated. The percentage yield of essential oil produce was calculated for every experiment with different experimental condition. The effect of different parameters, such as temperature and extraction time on the yield was investigated using the Response Surface Methodology (RSM) through Central Composite Design (CCD). The temperature and extraction time were found to have significant effect on the yield of extract. A final essential oil yield was 0.095% could be extracted under the following optimized conditions; a temperature of 80 °C and a time of 8 hours.

Irrigation offsets wheat yield reductions from warming temperatures

NASA Astrophysics Data System (ADS)

Tack, Jesse; Barkley, Andrew; Hendricks, Nathan

2017-11-01

Temperature increases due to climate change are expected to cause substantial reductions in global wheat yields. However, uncertainty remains regarding the potential role for irrigation as an adaptation strategy to offset heat impacts. Here we utilize over 7000 observations spanning eleven Kansas field-trial locations, 180 varieties, and 29 years to show that irrigation significantly reduces the negative impact of warming temperatures on winter wheat yields. Dryland wheat yields are estimated to decrease about eight percent for every one-degree Celsius increase in temperature, yet irrigation completely offsets this negative impact in our sample. As in previous studies, we find that important interactions exist between heat stress and precipitation for dryland production. Here, uniquely, we observe both dryland and irrigated trials side-by-side at the same locations and find that precipitation does not provide the same reduction in heat stress as irrigation. This is likely to be because the timing, intensity, and volume of water applications influence wheat yields, so the ability to irrigate—rather than relying on rainfall alone—has a stronger influence on heat stress. We find evidence of extensive differences of water-deficit stress impacts across varieties. This provides some evidence of the potential for adapting to hotter and drier climate conditions using optimal variety selection. Overall, our results highlight the critical role of water management for future global food security. Water scarcity not only reduces crop yields through water-deficit stress, but also amplifies the negative effects of warming temperatures.

An Efficient, Optimized Synthesis of Fentanyl and Related Analogs

DOE PAGES

Valdez, Carlos A.; Leif, Roald N.; Mayer, Brian P.; ...

2014-09-18

The alternate and optimized syntheses of the parent opioid fentanyl and its analogs are described. The routes presented exhibit high-yielding transformations leading to these powerful analgesics after optimization studies were carried out for each synthetic step. The general three-step strategy produced a panel of four fentanyls in excellent yields (73–78%) along with their more commonly encountered hydrochloride and citric acid salts. In conclusion, the following strategy offers the opportunity for the gram-scale, efficient production of this interesting class of opioid alkaloids.

An Efficient, Optimized Synthesis of Fentanyl and Related Analogs

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

Valdez, Carlos A.; Leif, Roald N.; Mayer, Brian P.

The alternate and optimized syntheses of the parent opioid fentanyl and its analogs are described. The routes presented exhibit high-yielding transformations leading to these powerful analgesics after optimization studies were carried out for each synthetic step. The general three-step strategy produced a panel of four fentanyls in excellent yields (73–78%) along with their more commonly encountered hydrochloride and citric acid salts. In conclusion, the following strategy offers the opportunity for the gram-scale, efficient production of this interesting class of opioid alkaloids.

Optimization of suitable ethanol blend ratio for motorcycle engine using response surface method.

PubMed

Chen, Yu-Liang; Chen, Suming; Tsai, Jin-Ming; Tsai, Chao-Yin; Fang, Hsin-Hsiung; Yang, I-Chang; Liu, Sen-Yuan

2012-01-01

In view of energy shortage and air pollution, ethanol-gasoline blended fuel used for motorcycle engine was studied in this work. The emissions of carbon monoxide (CO), nitrogen oxides (NO(X)) and engine performance of a 125 cc four-stroke motorcycle engine with original carburetor using ethanol-gasoline fuels were investigated. The model of three-variable Box Behnken design (BBD) was used for experimental design, the ethanol blend ratios were prepared at 0, 10, 20 vol%; the speeds of motorcycle were selected as 30, 45, 60 km/h; and the throttle positions were set at 30, 60, 90 %. Both engine performance and air pollutant emissions were then analyzed by response surface method (RSM) to yield optimum operation parameters for tolerable pollutant emissions and maximum engine performance. The RSM optimization analysis indicated that the most suitable ethanol-gasoline blended ratio was found at the range of 3.92-4.12 vol% to yield a comparable fuel conversion efficiency, while considerable reductions of exhaust pollutant emissions of CO (-29 %) and NO(X) (-12 %) when compared to pure gasoline fuel. This study demonstrated low ethanol-gasoline blended fuels could be used in motorcycle carburetor engines without any modification to keep engine power while reducing exhaust pollutants.

An efficient algorithm for building locally refined hp - adaptive H-PCFE: Application to uncertainty quantification

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2017-12-01

Hybrid polynomial correlated function expansion (H-PCFE) is a novel metamodel formulated by coupling polynomial correlated function expansion (PCFE) and Kriging. Unlike commonly available metamodels, H-PCFE performs a bi-level approximation and hence, yields more accurate results. However, till date, it is only applicable to medium scaled problems. In order to address this apparent void, this paper presents an improved H-PCFE, referred to as locally refined hp - adaptive H-PCFE. The proposed framework computes the optimal polynomial order and important component functions of PCFE, which is an integral part of H-PCFE, by using global variance based sensitivity analysis. Optimal number of training points are selected by using distribution adaptive sequential experimental design. Additionally, the formulated model is locally refined by utilizing the prediction error, which is inherently obtained in H-PCFE. Applicability of the proposed approach has been illustrated with two academic and two industrial problems. To illustrate the superior performance of the proposed approach, results obtained have been compared with those obtained using hp - adaptive PCFE. It is observed that the proposed approach yields highly accurate results. Furthermore, as compared to hp - adaptive PCFE, significantly less number of actual function evaluations are required for obtaining results of similar accuracy.

The missing biology in land carbon models (Invited)

NASA Astrophysics Data System (ADS)

Prentice, I. C.; Cornwell, W.; Dong, N.; Maire, V.; Wang, H.; Wright, I.

2013-12-01

Models of terrestrial carbon cycling give divergent results, and recent developments - notably the inclusion of nitrogen-carbon cycle coupling - have apparently made matters worse. More extensive benchmarking of models would be highly desirable, but is not a panacea. Problems with current models include overparameterization (assigning separate sets of parameter values for each plant functional type can easily obscure more fundamental model limitations), and the widespread persistence of incorrect paradigms to describe plant responses to environment. Next-generation models require a more sound basis in observations and theory. A possible way forward will be outlined. It will be shown how the principle of optimization by natural selection can yield testable, general hypotheses about plant function. A specific optimality hypothesis about the control of CO2 drawdown versus water loss by leaves will be shown to yield global and quantitatively verifable predictions of plant behaviour as demonstrated in field gas-exchange measurements across species from different environments, and in the global pattern of stable carbon isotope discrimination by plants. Combined with the co-limitation hypothesis for the control of photosynthetic capacity and an economic approach to the costs of nutrient acquisition, this hypothesis provides a potential foundation for a comprehensive predictive understanding of the controls of primary production on land.

Automatic weight determination in nonlinear model predictive control of wind turbines using swarm optimization technique

NASA Astrophysics Data System (ADS)

Tofighi, Elham; Mahdizadeh, Amin

2016-09-01

This paper addresses the problem of automatic tuning of weighting coefficients for the nonlinear model predictive control (NMPC) of wind turbines. The choice of weighting coefficients in NMPC is critical due to their explicit impact on efficiency of the wind turbine control. Classically, these weights are selected based on intuitive understanding of the system dynamics and control objectives. The empirical methods, however, may not yield optimal solutions especially when the number of parameters to be tuned and the nonlinearity of the system increase. In this paper, the problem of determining weighting coefficients for the cost function of the NMPC controller is formulated as a two-level optimization process in which the upper- level PSO-based optimization computes the weighting coefficients for the lower-level NMPC controller which generates control signals for the wind turbine. The proposed method is implemented to tune the weighting coefficients of a NMPC controller which drives the NREL 5-MW wind turbine. The results are compared with similar simulations for a manually tuned NMPC controller. Comparison verify the improved performance of the controller for weights computed with the PSO-based technique.

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PubMed Central

Gang, Grace J.; Zbijewski, Wojciech; Webster Stayman, J.; Siewerdsen, Jeffrey H.

2012-01-01

Purpose: Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization. Methods: The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d′). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d′ as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background. Results: Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans. Conclusions: This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose. PMID:22894440

Economic weights for genetic improvement of lactation persistency and milk yield.

PubMed

Togashi, K; Lin, C Y

2009-06-01

This study aimed to establish a criterion for measuring the relative weight of lactation persistency (the ratio of yield at 280 d in milk to peak yield) in restricted selection index for the improvement of net merit comprising 3-parity total yield and total lactation persistency. The restricted selection index was compared with selection based on first-lactation total milk yield (I(1)), the first-two-lactation total yield (I(2)), and first-three-lactation total yield (I(3)). Results show that genetic response in net merit due to selection on restricted selection index could be greater than, equal to, or less than that due to the unrestricted index depending upon the relative weight of lactation persistency and the restriction level imposed. When the relative weight of total lactation persistency is equal to the criterion, the restricted selection index is equal to the selection method compared (I(1), I(2), or I(3)). The restricted selection index yielded a greater response when the relative weight of total lactation persistency was above the criterion, but a lower response when it was below the criterion. The criterion varied depending upon the restriction level (c) imposed and the selection criteria compared. A curvilinear relationship (concave curve) exists between the criterion and the restricted level. The criterion increases as the restriction level deviates in either direction from 1.5. Without prior information of the economic weight of lactation persistency, the imposition of the restriction level of 1.5 on lactation persistency would maximize change in net merit. The procedure presented allows for simultaneous modification of multi-parity lactation curves.

Modulation Depth Estimation and Variable Selection in State-Space Models for Neural Interfaces

PubMed Central

Hochberg, Leigh R.; Donoghue, John P.; Brown, Emery N.

2015-01-01

Rapid developments in neural interface technology are making it possible to record increasingly large signal sets of neural activity. Various factors such as asymmetrical information distribution and across-channel redundancy may, however, limit the benefit of high-dimensional signal sets, and the increased computational complexity may not yield corresponding improvement in system performance. High-dimensional system models may also lead to overfitting and lack of generalizability. To address these issues, we present a generalized modulation depth measure using the state-space framework that quantifies the tuning of a neural signal channel to relevant behavioral covariates. For a dynamical system, we develop computationally efficient procedures for estimating modulation depth from multivariate data. We show that this measure can be used to rank neural signals and select an optimal channel subset for inclusion in the neural decoding algorithm. We present a scheme for choosing the optimal subset based on model order selection criteria. We apply this method to neuronal ensemble spike-rate decoding in neural interfaces, using our framework to relate motor cortical activity with intended movement kinematics. With offline analysis of intracortical motor imagery data obtained from individuals with tetraplegia using the BrainGate neural interface, we demonstrate that our variable selection scheme is useful for identifying and ranking the most information-rich neural signals. We demonstrate that our approach offers several orders of magnitude lower complexity but virtually identical decoding performance compared to greedy search and other selection schemes. Our statistical analysis shows that the modulation depth of human motor cortical single-unit signals is well characterized by the generalized Pareto distribution. Our variable selection scheme has wide applicability in problems involving multisensor signal modeling and estimation in biomedical engineering systems. PMID:25265627

Nonlinear programming models to optimize uneven-aged loblolly pine management

Treesearch

Benedict J. Schulte; Joseph. Buongiorno; Kenneth Skog

1999-01-01

Nonlinear programming models of uneven-aged loblolly pine (Pinus taeda L.) management were developed to identify sustainable management regimes which optimize: 1) soil expectation value (SEV), 2) tree diversity, or 3) annual sawtimber yields. The models use the equations of SouthPro, a site- and density-dependent, multi-species matrix growth and yield model that...

Radiotherapy Dose Fractionation under Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Davison, Matt; Kim, Daero; Keller, Harald

2011-11-01

In radiotherapy, radiation is directed to damage a tumor while avoiding surrounding healthy tissue. Tradeoffs ensue because dose cannot be exactly shaped to the tumor. It is particularly important to ensure that sensitive biological structures near the tumor are not damaged more than a certain amount. Biological tissue is known to have a nonlinear response to incident radiation. The linear quadratic dose response model, which requires the specification of two clinically and experimentally observed response coefficients, is commonly used to model this effect. This model yields an optimization problem giving two different types of optimal dose sequences (fractionation schedules). Which fractionation schedule is preferred depends on the response coefficients. These coefficients are uncertainly known and may differ from patient to patient. Because of this not only the expected outcomes but also the uncertainty around these outcomes are important, and it might not be prudent to select the strategy with the best expected outcome.

Optimization of Dissolution Compartments in a Biorelevant Dissolution Apparatus Golem v2, Supported by Multivariate Analysis.

PubMed

Stupák, Ivan; Pavloková, Sylvie; Vysloužil, Jakub; Dohnal, Jiří; Čulen, Martin

2017-11-23

Biorelevant dissolution instruments represent an important tool for pharmaceutical research and development. These instruments are designed to simulate the dissolution of drug formulations in conditions most closely mimicking the gastrointestinal tract. In this work, we focused on the optimization of dissolution compartments/vessels for an updated version of the biorelevant dissolution apparatus-Golem v2. We designed eight compartments of uniform size but different inner geometry. The dissolution performance of the compartments was tested using immediate release caffeine tablets and evaluated by standard statistical methods and principal component analysis. Based on two phases of dissolution testing (using 250 and 100 mL of dissolution medium), we selected two compartment types yielding the highest measurement reproducibility. We also confirmed a statistically ssignificant effect of agitation rate and dissolution volume on the extent of drug dissolved and measurement reproducibility.

Optimized formation of detergent micelles of beta-carotene and retinal production using recombinant human beta,beta-carotene 15,15'-monooxygenase.

PubMed

Kim, Nam-Hee; Kim, Yeong-Su; Kim, Hye-Jung; Oh, Deok-Kun

2008-01-01

The formation of beta-carotene detergent micelles and their conversion into retinal by recombinant human beta,beta-carotene 15,15'-monooxygenase was optimized under aqueous conditions. Toluene was the most hydrophobic among the organic solvents tested; thus, it was used to dissolve beta-carotene, which is a hydrophobic compound. Tween 80 was selected as the detergent because it supported the highest level of retinal production among all of the detergents tested. The maximum production of retinal was achieved in detergent micelles containing 200 mg/L of beta-carotene and 2.4% (w/v) Tween 80. Under these conditions, the recombinant enzyme produced 97 mg/L of retinal after 16 h with a conversion yield of 48.5% (w/w). The amount of retinal produced, which is the highest ever reported, is a result of the ability of our system to dissolve large amounts of beta-carotene.

Biohydrogen Production from Hydrolysates of Selected Tropical Biomass Wastes with Clostridium Butyricum

NASA Astrophysics Data System (ADS)

Dan Jiang; Fang, Zhen; Chin, Siew-Xian; Tian, Xiao-Fei; Su, Tong-Chao

2016-06-01

Biohydrogen production has received widespread attention from researchers in industry and academic fields. Response surface methodology (RSM) was applied to evaluate the effects of several key variables in anaerobic fermentation of glucose with Clostridium butyrium, and achieved the highest production rate and yield of hydrogen. Highest H2 yield of 2.02 mol H2/mol-glucose was achieved from 24 h bottle fermentation of glucose at 35 °C, while the composition of medium was (g/L): 15.66 glucose, 6.04 yeast extract, 4 tryptone, 3 K2HPO4, 3 KH2PO4, 0.05 L-cysteine, 0.05 MgSO4·7H2O, 0.1 MnSO4·H2O and 0.3 FeSO4·7H2O, which was very different from that for cell growth. Sugarcane bagasse and Jatropha hulls were selected as typical tropical biomass wastes to produce sugars via a two-step acid hydrolysis for hydrogen production. Under the optimized fermentation conditions, H2 yield (mol H2/mol-total reducing sugar) was 2.15 for glucose, 2.06 for bagasse hydrolysate and 1.95 for Jatropha hull hydrolysate in a 3L fermenter for 24 h at 35 °C, with H2 purity of 49.7-64.34%. The results provide useful information and basic data for practical use of tropical plant wastes to produce hydrogen.

Frameless robotically targeted stereotactic brain biopsy: feasibility, diagnostic yield, and safety.

PubMed

Bekelis, Kimon; Radwan, Tarek A; Desai, Atman; Roberts, David W

2012-05-01

Frameless stereotactic brain biopsy has become an established procedure in many neurosurgical centers worldwide. Robotic modifications of image-guided frameless stereotaxy hold promise for making these procedures safer, more effective, and more efficient. The authors hypothesized that robotic brain biopsy is a safe, accurate procedure, with a high diagnostic yield and a safety profile comparable to other stereotactic biopsy methods. This retrospective study included 41 patients undergoing frameless stereotactic brain biopsy of lesions (mean size 2.9 cm) for diagnostic purposes. All patients underwent image-guided, robotic biopsy in which the SurgiScope system was used in conjunction with scalp fiducial markers and a preoperatively selected target and trajectory. Forty-five procedures, with 50 supratentorial targets selected, were performed. The mean operative time was 44.6 minutes for the robotic biopsy procedures. This decreased over the second half of the study by 37%, from 54.7 to 34.5 minutes (p < 0.025). The diagnostic yield was 97.8% per procedure, with a second procedure being diagnostic in the single nondiagnostic case. Complications included one transient worsening of a preexisting deficit (2%) and another deficit that was permanent (2%). There were no infections. Robotic biopsy involving a preselected target and trajectory is safe, accurate, efficient, and comparable to other procedures employing either frame-based stereotaxy or frameless, nonrobotic stereotaxy. It permits biopsy in all patients, including those with small target lesions. Robotic biopsy planning facilitates careful preoperative study and optimization of needle trajectory to avoid sulcal vessels, bridging veins, and ventricular penetration.

Methodology for extracting local constants from petroleum cracking flows

DOEpatents

Chang, Shen-Lin; Lottes, Steven A.; Zhou, Chenn Q.

2000-01-01

A methodology provides for the extraction of local chemical kinetic model constants for use in a reacting flow computational fluid dynamics (CFD) computer code with chemical kinetic computations to optimize the operating conditions or design of the system, including retrofit design improvements to existing systems. The coupled CFD and kinetic computer code are used in combination with data obtained from a matrix of experimental tests to extract the kinetic constants. Local fluid dynamic effects are implicitly included in the extracted local kinetic constants for each particular application system to which the methodology is applied. The extracted local kinetic model constants work well over a fairly broad range of operating conditions for specific and complex reaction sets in specific and complex reactor systems. While disclosed in terms of use in a Fluid Catalytic Cracking (FCC) riser, the inventive methodology has application in virtually any reaction set to extract constants for any particular application and reaction set formulation. The methodology includes the step of: (1) selecting the test data sets for various conditions; (2) establishing the general trend of the parametric effect on the measured product yields; (3) calculating product yields for the selected test conditions using coupled computational fluid dynamics and chemical kinetics; (4) adjusting the local kinetic constants to match calculated product yields with experimental data; and (5) validating the determined set of local kinetic constants by comparing the calculated results with experimental data from additional test runs at different operating conditions.

Bioconversion of D-galactose to D-tagatose: continuous packed bed reaction with an immobilized thermostable L-arabinose isomerase and efficient purification by selective microbial degradation.

PubMed

Liang, Min; Chen, Min; Liu, Xinying; Zhai, Yafei; Liu, Xian-wei; Zhang, Houcheng; Xiao, Min; Wang, Peng

2012-02-01

The continuous enzymatic conversion of D-galactose to D-tagatose with an immobilized thermostable L-arabinose isomerase in packed-bed reactor and a novel method for D-tagatose purification were studied. L-arabinose isomerase from Thermoanaerobacter mathranii (TMAI) was recombinantly overexpressed and immobilized in calcium alginate. The effects of pH and temperature on D-tagatose production reaction catalyzed by free and immobilized TMAI were investigated. The optimal condition for free enzyme was pH 8.0, 60°C, 5 mM MnCl(2). However, that for immobilized enzyme was pH 7.5, 75°C, 5 mM MnCl(2). In addition, the catalytic activity of immobilized enzyme at high temperature and low pH was significantly improved compared with free enzyme. The optimum reaction yield with immobilized TMAI increased by four percentage points to 43.9% compared with that of free TMAI. The highest productivity of 10 g/L h was achieved with the yield of 23.3%. Continuous production was performed at 70°C; after 168 h, the reaction yield was still above 30%. The resultant syrup was then incubated with Saccharomyces cerevisiae L1 cells. The selective degradation of D-galactose was achieved, obtaining D-tagatose with the purity above 95%. The established production and separation methods further potentiate the industrial production of D-tagatose via bioconversion and biopurification processes.

Biohydrogen Production from Hydrolysates of Selected Tropical Biomass Wastes with Clostridium Butyricum

PubMed Central

Dan Jiang; Fang, Zhen; Chin, Siew-xian; Tian, Xiao-fei; Su, Tong-chao

2016-01-01

Biohydrogen production has received widespread attention from researchers in industry and academic fields. Response surface methodology (RSM) was applied to evaluate the effects of several key variables in anaerobic fermentation of glucose with Clostridium butyrium, and achieved the highest production rate and yield of hydrogen. Highest H2 yield of 2.02 mol H2/mol-glucose was achieved from 24 h bottle fermentation of glucose at 35 °C, while the composition of medium was (g/L): 15.66 glucose, 6.04 yeast extract, 4 tryptone, 3 K2HPO4, 3 KH2PO4, 0.05 L-cysteine, 0.05 MgSO4·7H2O, 0.1 MnSO4·H2O and 0.3 FeSO4·7H2O, which was very different from that for cell growth. Sugarcane bagasse and Jatropha hulls were selected as typical tropical biomass wastes to produce sugars via a two-step acid hydrolysis for hydrogen production. Under the optimized fermentation conditions, H2 yield (mol H2/mol-total reducing sugar) was 2.15 for glucose, 2.06 for bagasse hydrolysate and 1.95 for Jatropha hull hydrolysate in a 3L fermenter for 24 h at 35 °C, with H2 purity of 49.7–64.34%. The results provide useful information and basic data for practical use of tropical plant wastes to produce hydrogen. PMID:27251222

Removal of caffeine from green tea by microwave-enhanced vacuum ice water extraction.

PubMed

Lou, Zaixiang; Er, Chaojuan; Li, Jing; Wang, Hongxin; Zhu, Song; Sun, Juntao

2012-02-24

In order to selectively remove caffeine from green tea, a microwave-enhanced vacuum ice water extraction (MVIE) method was proposed. The effects of MVIE variables including extraction time, microwave power, and solvent to solid radio on the removal yield of caffeine and the loss of total phenolics (TP) from green tea were investigated. The optimized conditions were as follows: solvent (mL) to solid (g) ratio was 10:1, microwave extraction time was 6 min, microwave power was 350 W and 2.5 h of vacuum ice water extraction. The removal yield of caffeine by MVIE was 87.6%, which was significantly higher than that by hot water extraction, indicating a significant improvement of removal efficiency. Moreover, the loss of TP of green tea in the proposed method was much lower than that in the hot water extraction. After decaffeination by MVIE, the removal yield of TP tea was 36.2%, and the content of TP in green tea was still higher than 170 mg g(-1). Therefore, the proposed microwave-enhanced vacuum ice water extraction was selective, more efficient for the removal of caffeine. The main phenolic compounds of green tea were also determined, and the results indicated that the contents of several catechins were almost not changed in MVIE. This study suggests that MVIE is a new and good alternative for the removal of caffeine from green tea, with a great potential for industrial application. Copyright © 2011 Elsevier B.V. All rights reserved.

Application of ionic liquids based microwave-assisted simultaneous extraction of carnosic acid, rosmarinic acid and essential oil from Rosmarinus officinalis.

PubMed

Liu, Tingting; Sui, Xiaoyu; Zhang, Rongrui; Yang, Lei; Zu, Yuangang; Zhang, Lin; Zhang, Ying; Zhang, Zhonghua

2011-11-25

An ionic liquid based microwave-assisted simultaneous extraction and distillation (ILMSED) method has been developed for the effective extraction of carnosic acid (CA), rosmarinic acid (RA) and essential oil (EO) from Rosmarinus officinalis. A series of 1-alkyl-3-methylimidazolium ionic liquids differing in composition of anion and cation were evaluated for extraction yield in this work. The results obtained indicated that the anions and cations of ionic liquids had influences on the extraction of CA and RA, 1.0M 1-octyl-3-methylimidazolium bromide ([C8mim]Br) solution was selected as solvent. In addition, the ILMSED procedures for the three target ingredients were optimized and compared with other conventional extraction techniques. ILMSED gave the best result due to the highest extraction yield within the shortest extraction time for CA and RA. The novel process developed offered advantages in term of yield and selectivity of EO and shorter isolation time (20 min in comparison of 4h of hydrodistillation), and provides a more valuable EO (with high amount of oxygenated compounds). The microstructures and chemical structures of rosemary samples before and after extraction were also investigated. Moreover, the proposed method was validated by the stability, repeatability and recovery experiments. The results indicated that the developed ILMSED method provided a good alternative for the both extraction of non-volatile compounds (CA and RA) and EO from rosemary as well as other herbs. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimization of β-cyclodextrin-based flavonol extraction from apple pomace using response surface methodology.

PubMed

Parmar, Indu; Sharma, Sowmya; Rupasinghe, H P Vasantha

2015-04-01

The present study investigated five cyclodextrins (CDs) for the extraction of flavonols from apple pomace powder and optimized β-CD based extraction of total flavonols using response surface methodology. A 2(3) central composite design with β-CD concentration (0-5 g 100 mL(-1)), extraction temperature (20-72 °C), extraction time (6-48 h) and second-order quadratic model for the total flavonol yield (mg 100 g(-1) DM) was selected to generate the response surface curves. The optimal conditions obtained were: β-CD concentration, 2.8 g 100 mL(-1); extraction temperature, 45 °C and extraction time, 25.6 h that predicted the extraction of 166.6 mg total flavonols 100 g(-1) DM. The predicted amount was comparable to the experimental amount of 151.5 mg total flavonols 100 g(-1) DM obtained from optimal β-CD based parameters, thereby giving a low absolute error and adequacy of fitted model. In addition, the results from optimized extraction conditions showed values similar to those obtained through previously established solvent based sonication assisted flavonol extraction procedure. To the best of our knowledge, this is the first study to optimize aqueous β-CD based flavonol extraction which presents an environmentally safe method for value-addition to under-utilized bio resources.

Optimization of the pyrolysis process of empty fruit bunch (EFB) in a fixed-bed reactor through a central composite design (CCD)

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

Mohamed, Alina Rahayu; Hamzah, Zainab; Daud, Mohamed Zulkali Mohamed

2014-07-10

The production of crude palm oil from the processing of palm fresh fruit bunches in the palm oil mills in Malaysia hs resulted in a huge quantity of empty fruit bunch (EFB) accumulated. The EFB was used as a feedstock in the pyrolysis process using a fixed-bed reactor in the present study. The optimization of process parameters such as pyrolysis temperature (factor A), biomass particle size (factor B) and holding time (factor C) were investigated through Central Composite Design (CCD) using Stat-Ease Design Expert software version 7 with bio-oil yield considered as the response. Twenty experimental runs were conducted. Themore » results were completely analyzed by Analysis of Variance (ANOVA). The model was statistically significant. All factors studied were significant with p-values < 0.05. The pyrolysis temperature (factor A) was considered as the most significant parameter because its F-value of 116.29 was the highest. The value of R{sup 2} was 0.9564 which indicated that the selected factors and its levels showed high correlation to the production of bio-oil from EFB pyrolysis process. A quadratic model equation was developed and employed to predict the highest theoretical bio-oil yield. The maximum bio-oil yield of 46.2 % was achieved at pyrolysis temperature of 442.15 °C using the EFB particle size of 866 μm which corresponded to the EFB particle size in the range of 710–1000 μm and holding time of 483 seconds.« less

Optimization of the pyrolysis process of empty fruit bunch (EFB) in a fixed-bed reactor through a central composite design (CCD)

NASA Astrophysics Data System (ADS)

Mohamed, Alina Rahayu; Hamzah, Zainab; Daud, Mohamed Zulkali Mohamed

2014-07-01

The production of crude palm oil from the processing of palm fresh fruit bunches in the palm oil mills in Malaysia hs resulted in a huge quantity of empty fruit bunch (EFB) accumulated. The EFB was used as a feedstock in the pyrolysis process using a fixed-bed reactor in the present study. The optimization of process parameters such as pyrolysis temperature (factor A), biomass particle size (factor B) and holding time (factor C) were investigated through Central Composite Design (CCD) using Stat-Ease Design Expert software version 7 with bio-oil yield considered as the response. Twenty experimental runs were conducted. The results were completely analyzed by Analysis of Variance (ANOVA). The model was statistically significant. All factors studied were significant with p-values < 0.05. The pyrolysis temperature (factor A) was considered as the most significant parameter because its F-value of 116.29 was the highest. The value of R2 was 0.9564 which indicated that the selected factors and its levels showed high correlation to the production of bio-oil from EFB pyrolysis process. A quadratic model equation was developed and employed to predict the highest theoretical bio-oil yield. The maximum bio-oil yield of 46.2 % was achieved at pyrolysis temperature of 442.15 °C using the EFB particle size of 866 μm which corresponded to the EFB particle size in the range of 710-1000 μm and holding time of 483 seconds.

Wheat plant selection for high yields entailed improvement of leaf anatomical and biochemical traits including tolerance to non-optimal temperature conditions.

PubMed

Brestic, Marian; Zivcak, Marek; Hauptvogel, Pavol; Misheva, Svetlana; Kocheva, Konstantina; Yang, Xinghong; Li, Xiangnan; Allakhverdiev, Suleyman I

2018-05-01

Assessment of photosynthetic traits and temperature tolerance was performed on field-grown modern genotype (MG), and the local landrace (LR) of wheat (Triticum aestivum L.) as well as the wild relative species (Aegilops cylindrica Host.). The comparison was based on measurements of the gas exchange (A/c i , light and temperature response curves), slow and fast chlorophyll fluorescence kinetics, and some growth and leaf parameters. In MG, we observed the highest CO 2 assimilation rate [Formula: see text] electron transport rate (J max ) and maximum carboxylation rate [Formula: see text]. The Aegilops leaves had substantially lower values of all photosynthetic parameters; this fact correlated with its lower biomass production. The mesophyll conductance was almost the same in Aegilops and MG, despite the significant differences in leaf phenotype. In contrary, in LR with a higher dry mass per leaf area, the half mesophyll conductance (g m ) values indicated more limited CO 2 diffusion. In Aegilops, we found much lower carboxylation capacity; this can be attributed mainly to thin leaves and lower Rubisco activity. The difference in CO 2 assimilation rate between MG and others was diminished because of its higher mitochondrial respiration activity indicating more intense metabolism. Assessment of temperature response showed lower temperature optimum and a narrow ecological valence (i.e., the range determining the tolerance limits of a species to an environmental factor) in Aegilops. In addition, analysis of photosynthetic thermostability identified the LR as the most sensitive. Our results support the idea that the selection for high yields was accompanied by the increase of photosynthetic productivity through unintentional improvement of leaf anatomical and biochemical traits including tolerance to non-optimal temperature conditions.

SU-E-T-191: First Principle Calculation of Quantum Yield in Photodynamic Therapy

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

Abolfath, R; Guo, F; Chen, Z

Purpose: We present a first-principle method to calculate the spin transfer efficiency in oxygen induced by any photon fields especially in MeV energy range. The optical pumping is mediated through photosensitizers, e.g., porphyrin and/or ensemble of quantum dots. Methods: Under normal conditions, oxygen molecules are in the relatively non-reactive triplet state. In the presence of certain photosensitizer compounds such as porphyrins, electromagnetic radiation of specific wavelengths can excite oxygen to highly reactive singlet state. With selective uptake of photosensitizers by certain malignant cells, photon irradiation of phosensitized tumors can lead to selective killing of cancer cells. This is the basismore » of photodynamic therapy (PDT). Despite several attempts, PDT has not been clinically successful except in limited superficial cancers. Many parameters such as photon energy, conjugation with quantum dots etc. can be potentially combined with PDT in order to extend the role of PDT in cancer management. The key quantity for this optimization is the spin transfer efficiency in oxygen by any photon field. The first principle calculation model presented here, is an attempt to fill this need. We employ stochastic density matrix description of the quantum jumps and the rate equation methods in quantum optics based on Markov/Poisson processes and calculate time evolution of the population of the optically pumped singlet oxygen. Results: The results demonstrate the feasibility of our model in showing the dependence of the optical yield in generating spin-singlet oxygen on the experimental conditions. The adjustable variables can be tuned to maximize the population of the singlet oxygen hence the efficacy of the photodynamic therapy. Conclusion: The present model can be employed to fit and analyze the experimental data and possibly to assist researchers in optimizing the experimental conditions in photodynamic therapy.« less

Gene expression profiling gut microbiota in different races of humans

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Yu-Hang; Huang, Tao; Cai, Yu-Dong

2016-03-01

The gut microbiome is shaped and modified by the polymorphisms of microorganisms in the intestinal tract. Its composition shows strong individual specificity and may play a crucial role in the human digestive system and metabolism. Several factors can affect the composition of the gut microbiome, such as eating habits, living environment, and antibiotic usage. Thus, various races are characterized by different gut microbiome characteristics. In this present study, we studied the gut microbiomes of three different races, including individuals of Asian, European and American races. The gut microbiome and the expression levels of gut microbiome genes were analyzed in these individuals. Advanced feature selection methods (minimum redundancy maximum relevance and incremental feature selection) and four machine-learning algorithms (random forest, nearest neighbor algorithm, sequential minimal optimization, Dagging) were employed to capture key differentially expressed genes. As a result, sequential minimal optimization was found to yield the best performance using the 454 genes, which could effectively distinguish the gut microbiomes of different races. Our analyses of extracted genes support the widely accepted hypotheses that eating habits, living environments and metabolic levels in different races can influence the characteristics of the gut microbiome.

Model-based dose selection for phase III rivaroxaban study in Japanese patients with non-valvular atrial fibrillation.

PubMed

Tanigawa, Takahiko; Kaneko, Masato; Hashizume, Kensei; Kajikawa, Mariko; Ueda, Hitoshi; Tajiri, Masahiro; Paolini, John F; Mueck, Wolfgang

2013-01-01

The global ROCKET AF phase III trial evaluated rivaroxaban 20 mg once daily (o.d.) for stroke prevention in atrial fibrillation (AF). Based on rivaroxaban pharmacokinetics in Japanese subjects and lower anticoagulation preferences in Japan, particularly in elderly patients, the optimal dose regimen for Japanese AF patients was considered. The aim of this analysis was dose selection for Japanese patients from a pharmacokinetic aspect by comparison of simulated exposure in Japanese patients with those in Caucasian patients. As a result of population pharmacokinetics-pharmacodynamics analyses, a one-compartment pharmacokinetic model with first-order absorption and direct link pharmacokinetic-pharmacodynamic models optimally described the plasma concentration and pharmacodynamic models (Factor Xa activity, prothrombin time, activated partial thromboplastin time, and HepTest), which were also consistent with previous works. Steady-state simulations indicated 15 mg rivaroxaban o.d. doses in Japanese patients with AF would yield exposures comparable to the 20 mg o.d. dose in Caucasian patients with AF. In conclusion, in the context of the lower anticoagulation targets in Japanese practice, the population pharmacokinetic and pharmacodynamic modeling supports 15 mg o.d. as the principal rivaroxaban dose in J-ROCKET AF.

Improved Compressive Sensing of Natural Scenes Using Localized Random Sampling

PubMed Central

Barranca, Victor J.; Kovačič, Gregor; Zhou, Douglas; Cai, David

2016-01-01

Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, localized random sampling, which yields significantly improved CS image reconstructions. For each set of localized image measurements, our sampling method first randomly selects an image pixel and then measures its nearby pixels with probability depending on their distance from the initially selected pixel. We compare the uniformly-random and localized random sampling methods over a large space of sampling parameters, and show that, for the optimal parameter choices, higher quality image reconstructions can be consistently obtained by using localized random sampling. In addition, we argue that the localized random CS optimal parameter choice is stable with respect to diverse natural images, and scales with the number of samples used for reconstruction. We expect that the localized random sampling protocol helps to explain the evolutionarily advantageous nature of receptive field structure in visual systems and suggests several future research areas in CS theory and its application to brain imaging. PMID:27555464

Gene expression profiling gut microbiota in different races of humans

PubMed Central

Chen, Lei; Zhang, Yu-Hang; Huang, Tao; Cai, Yu-Dong

2016-01-01

The gut microbiome is shaped and modified by the polymorphisms of microorganisms in the intestinal tract. Its composition shows strong individual specificity and may play a crucial role in the human digestive system and metabolism. Several factors can affect the composition of the gut microbiome, such as eating habits, living environment, and antibiotic usage. Thus, various races are characterized by different gut microbiome characteristics. In this present study, we studied the gut microbiomes of three different races, including individuals of Asian, European and American races. The gut microbiome and the expression levels of gut microbiome genes were analyzed in these individuals. Advanced feature selection methods (minimum redundancy maximum relevance and incremental feature selection) and four machine-learning algorithms (random forest, nearest neighbor algorithm, sequential minimal optimization, Dagging) were employed to capture key differentially expressed genes. As a result, sequential minimal optimization was found to yield the best performance using the 454 genes, which could effectively distinguish the gut microbiomes of different races. Our analyses of extracted genes support the widely accepted hypotheses that eating habits, living environments and metabolic levels in different races can influence the characteristics of the gut microbiome. PMID:26975620

Sequence-controlled RNA self-processing: computational design, biochemical analysis, and visualization by AFM

PubMed Central

Petkovic, Sonja; Badelt, Stefan; Flamm, Christoph; Delcea, Mihaela

2015-01-01

Reversible chemistry allowing for assembly and disassembly of molecular entities is important for biological self-organization. Thus, ribozymes that support both cleavage and formation of phosphodiester bonds may have contributed to the emergence of functional diversity and increasing complexity of regulatory RNAs in early life. We have previously engineered a variant of the hairpin ribozyme that shows how ribozymes may have circularized or extended their own length by forming concatemers. Using the Vienna RNA package, we now optimized this hairpin ribozyme variant and selected four different RNA sequences that were expected to circularize more efficiently or form longer concatemers upon transcription. (Two-dimensional) PAGE analysis confirms that (i) all four selected ribozymes are catalytically active and (ii) high yields of cyclic species are obtained. AFM imaging in combination with RNA structure prediction enabled us to calculate the distributions of monomers and self-concatenated dimers and trimers. Our results show that computationally optimized molecules do form reasonable amounts of trimers, which has not been observed for the original system so far, and we demonstrate that the combination of theoretical prediction, biochemical and physical analysis is a promising approach toward accurate prediction of ribozyme behavior and design of ribozymes with predefined functions. PMID:25999318

Optimisation of Croton gratissimus Oil Extraction by n-Hexane and Ethyl Acetate Using Response Surface Methodology.

PubMed

Jiyane, Phiwe Charles; Tumba, Kaniki; Musonge, Paul

2018-04-01

The extraction of oil from Croton gratissimus seeds was studied using the three-factor five-level full-factorial central composite rotatable design (CCRD) of the response surface methodology (RSM). The effect of the three factors selected, viz., extraction time, extraction temperature and solvent-to-feed ratio on the extraction oil yield was investigated when n-hexane and ethyl acetate were used as extraction solvents. The coefficients of determination (R 2 ) of the models developed were 0.98 for n-hexane extraction and 0.97 for ethyl acetate extraction. These results demonstrated that the models developed adequately represented the processes they described. From the optimized model, maximum extraction yield obtained from n-hexane and ethyl acetate extraction were 23.88% and 23.25%, respectively. In both cases the extraction temperature and solvent-to-feed ratio were 35°C and 5 mL/g, respectively. In n-hexane extraction the maximum conditions were reached only after 6 min whereas in ethyl acetate extraction it took 20 min to get the maximum extraction oil yield. Oil extraction of Croton gratissimus seeds, in this work, favoured the use of n-hexane as an extraction solvent as it offered higher oil yields at low temperatures and reduced residence times.

Enhanced styrene recovery from waste polystyrene pyrolysis using response surface methodology coupled with Box-Behnken design.

PubMed

Mo, Yu; Zhao, Lei; Wang, Zhonghui; Chen, Chia-Lung; Tan, Giin-Yu Amy; Wang, Jing-Yuan

2014-04-01

A work applied response surface methodology coupled with Box-Behnken design (RSM-BBD) has been developed to enhance styrene recovery from waste polystyrene (WPS) through pyrolysis. The relationship between styrene yield and three selected operating parameters (i.e., temperature, heating rate, and carrier gas flow rate) was investigated. A second order polynomial equation was successfully built to describe the process and predict styrene yield under the study conditions. The factors identified as statistically significant to styrene production were: temperature, with a quadratic effect; heating rate, with a linear effect; carrier gas flow rate, with a quadratic effect; interaction between temperature and carrier gas flow rate; and interaction between heating rate and carrier gas flow rate. The optimum conditions for the current system were determined to be at a temperature range of 470-505°C, a heating rate of 40°C/min, and a carrier gas flow rate range of 115-140mL/min. Under such conditions, 64.52% WPS was recovered as styrene, which was 12% more than the highest reported yield for reactors of similar size. It is concluded that RSM-BBD is an effective approach for yield optimization of styrene recovery from WPS pyrolysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

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

Kim, Minsun, E-mail: mk688@uw.edu; Stewart, Robert D.; Phillips, Mark H.

2015-11-15

Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T{sub d}), and the size and location of tumormore » target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D{sub mean} ≤ 45 Gy), lungs (D{sub mean} ≤ 20 Gy), cord (D{sub max} ≤ 45 Gy), esophagus (D{sub max} ≤ 63 Gy), and unspecified tissues (D{sub 05} ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D{sub 95} of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T{sub d} (3–100 days), tumor lag-time (T{sub k} = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D{sub 95} were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T{sub d} and T{sub k} used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with T{sub d} less than 10 days, there was no significant increase in tumor BED but the treatment course could be shortened without a loss in tumor BED. The improvement in the tumor mean BED was more pronounced with smaller tumors (p-value = 0.08). Conclusions: Spatiotemporal optimization of patient plans has the potential to significantly improve local tumor control (larger BED/EUD) of patients with a favorable geometry, such as smaller tumors with larger distances between the tumor target and nearby OAR. In patients with a less favorable geometry and for fast growing tumors, plans optimized using spatiotemporal optimization and conventional (spatial-only) optimization are equivalent (negligible differences in tumor BED/EUD). However, spatiotemporal optimization yields shorter treatment courses than conventional spatial-only optimization. Personalized, spatiotemporal optimization of treatment schedules can increase patient convenience and help with the efficient allocation of clinical resources. Spatiotemporal optimization can also help identify a subset of patients that might benefit from nonconventional (large dose per fraction) treatments that are ineligible for the current practice of stereotactic body radiation therapy.« less

Optimization of Biomass and 5-Aminolevulinic Acid Production by Rhodobacter sphaeroides ATCC17023 via Response Surface Methodology.

PubMed

Liu, Shuli; Zhang, Guangming; Li, Jianzheng; Li, Xiangkun; Zhang, Jie

2016-06-01

Microbial 5-aminolevulinic acid (ALA) produced from wastewater is considered as potential renewable energy. However, many hurdles are needed to be overcome such as the regulation of key influencing factors on ALA yield. Biomass and ALA production by Rhodobacter sphaeroides was optimized using response surface methodology. The culturing medium was artificial volatile fatty acids wastewater. Three additives were optimized, namely succinate and glycine that are precursors of ALA biosynthesis, and D-glucose that is an inhibitor of ALA dehydratase. The optimal conditions were achieved by analyzing the response surface plots. Statistical analysis showed that succinate at 8.56 mmol/L, glycine at 5.06 mmol/L, and D-glucose at 7.82 mmol/L were the best conditions. Under these optimal conditions, the highest biomass production and ALA yield of 3.55 g/L and 5.49 mg/g-biomass were achieved. Subsequent verification experiments at optimal values had the maximum biomass production of 3.41 ± 0.002 g/L and ALA yield of 5.78 ± 0.08 mg/g-biomass.

Bridging Scales: A Model-Based Assessment of the Technical Tidal-Stream Energy Resource off Massachusetts, USA

NASA Astrophysics Data System (ADS)

Cowles, G. W.; Hakim, A.; Churchill, J. H.

2016-02-01

Tidal in-stream energy conversion (TISEC) facilities provide a highly predictable and dependable source of energy. Given the economic and social incentives to migrate towards renewable energy sources there has been tremendous interest in the technology. Key challenges to the design process stem from the wide range of problem scales extending from device to array. In the present approach we apply a multi-model approach to bridge the scales of interest and select optimal device geometries to estimate the technical resource for several realistic sites in the coastal waters of Massachusetts, USA. The approach links two computational models. To establish flow conditions at site scales ( 10m), a barotropic setup of the unstructured grid ocean model FVCOM is employed. The model is validated using shipboard and fixed ADCP as well as pressure data. For device scale, the structured multiblock flow solver SUmb is selected. A large ensemble of simulations of 2D cross-flow tidal turbines is used to construct a surrogate design model. The surrogate model is then queried using velocity profiles extracted from the tidal model to determine the optimal geometry for the conditions at each site. After device selection, the annual technical yield of the array is evaluated with FVCOM using a linear momentum actuator disk approach to model the turbines. Results for several key Massachusetts sites including comparison with theoretical approaches will be presented.

Continuous co-production of ethanol and xylitol from rice straw hydrolysate in a membrane bioreactor.

PubMed

Zahed, Omid; Jouzani, Gholamreza Salehi; Abbasalizadeh, Saeed; Khodaiyan, Faramarz; Tabatabaei, Meisam

2016-05-01

The present study was set to develop a robust and economic biorefinery process for continuous co-production of ethanol and xylitol from rice straw in a membrane bioreactor. Acid pretreatment, enzymatic hydrolysis, detoxification, yeast strains selection, single and co-culture batch fermentation, and finally continuous co-fermentation were optimized. The combination of diluted acid pretreatment (3.5 %) and enzymatic conversion (1:10 enzyme (63 floating-point unit (FPU)/mL)/biomass ratio) resulted in the maximum sugar yield (81 % conversion). By concentrating the hydrolysates, sugars level increased by threefold while that of furfural reduced by 50 % (0.56 to 0.28 g/L). Combined application of active carbon and resin led to complete removal of furfural, hydroxyl methyl furfural, and acetic acid. The strains Saccharomyces cerevisiae NCIM 3090 with 66.4 g/L ethanol production and Candida tropicalis NCIM 3119 with 9.9 g/L xylitol production were selected. The maximum concentrations of ethanol and xylitol in the single cultures were recorded at 31.5 g/L (0.42 g/g yield) and 26.5 g/L (0.58 g/g yield), respectively. In the batch co-culture system, the ethanol and xylitol productions were 33.4 g/L (0.44 g/g yield) and 25.1 g/L (0.55 g/g yield), respectively. The maximum ethanol and xylitol volumetric productivity values in the batch co-culture system were 65 and 58 % after 25 and 60 h, but were improved in the continuous co-culture mode and reached 80 % (55 g/L) and 68 % (31 g/L) at the dilution rate of 0.03 L per hour, respectively. Hence, the continuous co-production strategy developed in this study could be recommended for producing value-added products from this hugely generated lignocellulosic waste.

Separation and purification of both tea seed polysaccharide and saponin from camellia cake extract using macroporous resin.

PubMed

Yang, Pengjie; Zhou, Mingda; Zhou, Chengyun; Wang, Qian; Zhang, Fangfang; Chen, Jian

2015-02-01

A novel method to separate and purify tea seed polysaccharide and tea seed saponin from camellia cake extract by macroporous resin was developed. Among four kinds of resins (AB-8, NKA-9, XDA-6, and D4020) tested, AB-8 macroporous resin possessed optimal separating capacity for the two substances and thus was selected for the separation, in which deionized water was used to elute tea seed polysaccharide, 0.25% NaOH solution to remove the undesired pigments, and 90% ethanol to elute tea seed saponin. Further dynamic adsorption/desorption experiments on AB-8 resin-based column chromatography were conducted to obtain the optimal parameters. Under optimal dynamic adsorption and desorption conditions, 18.7 and 11.8% yield of tea seed polysaccharide and tea seed saponin were obtained with purities of 89.2 and 96.0%, respectively. The developed method provides a potential approach for the large-scale production of tea seed polysaccharide and tea seed saponin from camellia cake. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of a statistical design to the optimization of parameters and culture medium for alpha-amylase production by Aspergillus oryzae CBS 819.72 grown on gruel (wheat grinding by-product).

PubMed

Kammoun, Radhouane; Naili, Belgacem; Bejar, Samir

2008-09-01

The production optimization of alpha-amylase (E.C.3.2.1.1) from Aspergillus oryzae CBS 819.72 fungus, using a by-product of wheat grinding (gruel) as sole carbon source, was performed with statistical methodology based on three experimental designs. The optimisation of temperature, agitation and inoculum size was attempted using a Box-Behnken design under the response surface methodology. The screening of nineteen nutrients for their influence on alpha-amylase production was achieved using a Plackett-Burman design. KH(2)PO(4), urea, glycerol, (NH(4))(2)SO(4), CoCl(2), casein hydrolysate, soybean meal hydrolysate, MgSO(4) were selected based on their positive influence on enzyme formation. The optimized nutrients concentration was obtained using a Taguchi experimental design and the analysis of the data predicts a theoretical increase in the alpha-amylase expression of 73.2% (from 40.1 to 151.1 U/ml). These conditions were validated experimentally and revealed an enhanced alpha-amylase yield of 72.7%.

Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks.

PubMed

Feng, Lei; Zhu, Susu; Lin, Fucheng; Su, Zhenzhu; Yuan, Kangpei; Zhao, Yiying; He, Yong; Zhang, Chu

2018-06-15

Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874⁻1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA) scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA) was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN), evolutionary neural network (ENN), extreme learning machine (ELM), general regression neural network (GRNN) and radial basis neural network (RBNN) were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts.

Robust Spatial Approximation of Laser Scanner Point Clouds by Means of Free-form Curve Approaches in Deformation Analysis

NASA Astrophysics Data System (ADS)

Bureick, Johannes; Alkhatib, Hamza; Neumann, Ingo

2016-03-01

In many geodetic engineering applications it is necessary to solve the problem of describing a measured data point cloud, measured, e. g. by laser scanner, by means of free-form curves or surfaces, e. g., with B-Splines as basis functions. The state of the art approaches to determine B-Splines yields results which are seriously manipulated by the occurrence of data gaps and outliers. Optimal and robust B-Spline fitting depend, however, on optimal selection of the knot vector. Hence we combine in our approach Monte-Carlo methods and the location and curvature of the measured data in order to determine the knot vector of the B-Spline in such a way that no oscillating effects at the edges of data gaps occur. We introduce an optimized approach based on computed weights by means of resampling techniques. In order to minimize the effect of outliers, we apply robust M-estimators for the estimation of control points. The above mentioned approach will be applied to a multi-sensor system based on kinematic terrestrial laserscanning in the field of rail track inspection.

Application of polynomial control to design a robust oscillation-damping controller in a multimachine power system.

PubMed

Hasanvand, Hamed; Mozafari, Babak; Arvan, Mohammad R; Amraee, Turaj

2015-11-01

This paper addresses the application of a static Var compensator (SVC) to improve the damping of interarea oscillations. Optimal location and size of SVC are defined using bifurcation and modal analysis to satisfy its primary application. Furthermore, the best-input signal for damping controller is selected using Hankel singular values and right half plane-zeros. The proposed approach is aimed to design a robust PI controller based on interval plants and Kharitonov's theorem. The objective here is to determine the stability region to attain robust stability, the desired phase margin, gain margin, and bandwidth. The intersection of the resulting stability regions yields the set of kp-ki parameters. In addition, optimal multiobjective design of PI controller using particle swarm optimization (PSO) algorithm is presented. The effectiveness of the suggested controllers in damping of local and interarea oscillation modes of a multimachine power system, over a wide range of loading conditions and system configurations, is confirmed through eigenvalue analysis and nonlinear time domain simulation. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Exobiopolymer production of Ophiocordyceps dipterigena BCC 2073: optimization, production in bioreactor and characterization

PubMed Central

2010-01-01

Background Biopolymers have various applications in medicine, food and petroleum industries. The ascomycetous fungus Ophiocordyceps dipterigena BCC 2073 produces an exobiopolymer, a (1→3)-β-D-glucan, in low quantity under screening conditions. Optimization of O. dipterigena BCC 2073 exobiopolymer production using experimental designs, a scale-up in 5 liter bioreactor, analysis of molecular weight at different cultivation times, and levels of induction of interleukin-8 synthesis are described in this study. Results In order to improve and certify the productivity of this strain, a sequential approach of 4 steps was followed. The first step was the qualitative selection of the most appropriate carbon and nitrogen sources (general factorial design) and the second step was quantitative optimization of 5 physiological factors (fractional factorial design). The best carbon and nitrogen source was glucose and malt extract respectively. From an initial production of 2.53 g·L-1, over 13 g·L-1 could be obtained in flasks under the improved conditions (5-fold increase). The third step was cultivation in a 5 L bioreactor, which produced a specific growth rate, biomass yield, exobiopolymer yield and exobiopolymer production rate of 0.014 h-1, 0.32 g·g-1 glucose, 2.95 g·g biomass-1 (1.31 g·g-1 sugar), and 0.65 g.(L·d)-1, respectively. A maximum yield of 41.2 g·L-1 was obtained after 377 h, a dramatic improvement in comparison to the initial production. In the last step, the basic characteristics of the biopolymer were determined. The molecular weight of the polymer was in the range of 6.3 × 105 - 7.7 × 105 Da. The exobiopolymer, at 50 and 100. μg·mL-1, induced synthesis in normal dermal human fibroblasts of 2227 and 3363 pg·mL-1 interleukin-8 respectively. Conclusions High exobiopolymer yield produced by O. dipterigena BCC 2073 after optimization by qualitative and quantitative methods is attractive for various applications. It induced high IL-8 production by normal dermal fibroblasts, which makes it promising for application as wound healing material. However, there are still other possible applications for this biopolymer, such as an alternative source of biopolymer substitute for hyaluronic acid, which is costly, as a thickening agent in the cosmetic industry due to its high viscosity property, as a moisturizer, and in encapsulation. PMID:20624309

SU-E-T-07: 4DCT Robust Optimization for Esophageal Cancer Using Intensity Modulated Proton Therapy

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

Liao, L; Department of Industrial Engineering, University of Houston, Houston, TX; Yu, J

2015-06-15

Purpose: To develop a 4DCT robust optimization method to reduce the dosimetric impact from respiratory motion in intensity modulated proton therapy (IMPT) for esophageal cancer. Methods: Four esophageal cancer patients were selected for this study. The different phases of CT from a set of 4DCT were incorporated into the worst-case dose distribution robust optimization algorithm. 4DCT robust treatment plans were designed and compared with the conventional non-robust plans. Result doses were calculated on the average and maximum inhale/exhale phases of 4DCT. Dose volume histogram (DVH) band graphic and ΔD95%, ΔD98%, ΔD5%, ΔD2% of CTV between different phases were used tomore » evaluate the robustness of the plans. Results: Compare to the IMPT plans optimized using conventional methods, the 4DCT robust IMPT plans can achieve the same quality in nominal cases, while yield a better robustness to breathing motion. The mean ΔD95%, ΔD98%, ΔD5% and ΔD2% of CTV are 6%, 3.2%, 0.9% and 1% for the robustly optimized plans vs. 16.2%, 11.8%, 1.6% and 3.3% from the conventional non-robust plans. Conclusion: A 4DCT robust optimization method was proposed for esophageal cancer using IMPT. We demonstrate that the 4DCT robust optimization can mitigate the dose deviation caused by the diaphragm motion.« less

Upper Limits for Power Yield in Thermal, Chemical, and Electrochemical Systems

NASA Astrophysics Data System (ADS)

Sieniutycz, Stanislaw

2010-03-01

We consider modeling and power optimization of energy converters, such as thermal, solar and chemical engines and fuel cells. Thermodynamic principles lead to expressions for converter's efficiency and generated power. Efficiency equations serve to solve the problems of upgrading or downgrading a resource. Power yield is a cumulative effect in a system consisting of a resource, engines, and an infinite bath. While optimization of steady state systems requires using the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. The primary result of static optimization is the upper limit of power, whereas that of dynamic optimization is a finite-rate counterpart of classical reversible work (exergy). The latter quantity depends on the end state coordinates and a dissipation index, h, which is the Hamiltonian of the problem of minimum entropy production. In reacting systems, an active part of chemical affinity constitutes a major component of the overall efficiency. The theory is also applied to fuel cells regarded as electrochemical flow engines. Enhanced bounds on power yield follow, which are stronger than those predicted by the reversible work potential.

Spectral reflectance indices as a selection criterion for yield improvement in wheat

NASA Astrophysics Data System (ADS)

Babar, Md. Ali

2005-11-01

Scope and methods of study. Yield in wheat ( Triticum aestivum L.) is a complex trait and influenced by many environmental factors, and yield improvement is a daunting task for wheat breeders. Spectral reflectance indices (SRIs) have been used to study different physiological traits in wheat. SRIs have the potential to differentiate genotypes for grain yield. SRIs strongly associated with grain yield can be used to achieve effective genetic gain in wheat under different environments. Three experiments (15 adapted genotypes, 25 and 36 random sister lines derived from two different crosses) under irrigated conditions, and three experiments (each with 30 advanced genotypes) under water-limited conditions were conducted in three successive years in Northwest Mexico at the CIMMYT (International Maize and wheat Improvement Center) experimental station. SRIs and different agronomic data were collected for three years, and biomass was harvested for two years. Phenotypic and genetic correlations between SRIs and grain yield, between SRIs and biomass, realized and broad sense heritability, direct and correlated selection responses for grain yield, and SRIs were calculated. Findings and conclusion. Seven SRIs were calculated, and three near infrared based indices (WI, NWI-1 and NWI-2) showed higher level of genetic and phenotypic correlations with grain yield, yield components and biomass than other SRIs (PRI, RNDVI, GNDVI, and SR) under both irrigated and water limiting environments. Moderate to high realized and broad sense heritability, and selection response were demonstrated by the three NIR based indices. High efficiency of correlated response for yield estimation was demonstrated by the three NIR based indices. The ratio between the correlated response to grain yield based on the three NIR based indices and direct selection response for grain yield was very close to one. The NIR based indices showed very high accuracy in selecting superior genotypes for grain yield under both well-watered and water-limited conditions. These results demonstrated that effective genetic gain in grain yield improvement can be achieved by making selections with the three NIR based indices.

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

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

Dong, P; Xing, L; Ma, L

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

Maximum soil organic carbon storage in Midwest U.S. cropping systems when crops are optimally nitrogen-fertilized

USDA-ARS?s Scientific Manuscript database

Nitrogen fertilizer is critical to optimize short-term crop yield, but its long-term effect on soil organic C (SOC) is actively debated. Using 60 site-years of maize (Zea mays L.) yield response to a wide range of N fertilizer rates in continuous maize and annually rotated maize-soybean [Glycine max...

Identification of Swallowing Tasks from a Modified Barium Swallow Study That Optimize the Detection of Physiological Impairment

ERIC Educational Resources Information Center

Hazelwood, R. Jordan; Armeson, Kent E.; Hill, Elizabeth G.; Bonilha, Heather Shaw; Martin-Harris, Bonnie

2017-01-01

Purpose: The purpose of this study was to identify which swallowing task(s) yielded the worst performance during a standardized modified barium swallow study (MBSS) in order to optimize the detection of swallowing impairment. Method: This secondary data analysis of adult MBSSs estimated the probability of each swallowing task yielding the derived…

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

Optimization of Supercritical CO2 Extraction of Fish Oil from Viscera of African Catfish (Clarias gariepinus)

PubMed Central

Sarker, Mohamed Zaidul Islam; Selamat, Jinap; Habib, Abu Sayem Md. Ahsan; Ferdosh, Sahena; Akanda, Mohamed Jahurul Haque; Jaffri, Juliana Mohamed

2012-01-01

Fish oil was extracted from the viscera of African Catfish using supercritical carbon dioxide (SC-CO2). A Central Composite Design of Response Surface methodology (RSM) was employed to optimize the SC-CO2 extraction parameters. The oil yield (Y) as response variable was executed against the four independent variables, namely pressure, temperature, flow rate and soaking time. The oil yield varied with the linear, quadratic and interaction of pressure, temperature, flow rate and soaking time. Optimum points were observed within the variables of temperature from 35 °C to 80 °C, pressure from 10 MPa to 40 MPa, flow rate from 1 mL/min to 3 mL/min and soaking time from 1 h to 4 h. However, the extraction parameters were found to be optimized at temperature 57.5 °C, pressure 40 MPa, flow rate 2.0 mL/min and soaking time 2.5 h. At this optimized condition, the highest oil yields were found to be 67.0% (g oil/100 g sample on dry basis) in the viscera of catfish which was reasonable to the yields of 78.0% extracted using the Soxhlet method. PMID:23109854

Optimization of processing parameters of UAV integral structural components based on yield response

NASA Astrophysics Data System (ADS)

Chen, Yunsheng

2018-05-01

In order to improve the overall strength of unmanned aerial vehicle (UAV), it is necessary to optimize the processing parameters of UAV structural components, which is affected by initial residual stress in the process of UAV structural components processing. Because machining errors are easy to occur, an optimization model for machining parameters of UAV integral structural components based on yield response is proposed. The finite element method is used to simulate the machining parameters of UAV integral structural components. The prediction model of workpiece surface machining error is established, and the influence of the path of walking knife on residual stress of UAV integral structure is studied, according to the stress of UAV integral component. The yield response of the time-varying stiffness is analyzed, and the yield response and the stress evolution mechanism of the UAV integral structure are analyzed. The simulation results show that this method is used to optimize the machining parameters of UAV integral structural components and improve the precision of UAV milling processing. The machining error is reduced, and the deformation prediction and error compensation of UAV integral structural parts are realized, thus improving the quality of machining.

Fast flux module detection using matroid theory.

PubMed

Reimers, Arne C; Bruggeman, Frank J; Olivier, Brett G; Stougie, Leen

2015-05-01

Flux balance analysis (FBA) is one of the most often applied methods on genome-scale metabolic networks. Although FBA uniquely determines the optimal yield, the pathway that achieves this is usually not unique. The analysis of the optimal-yield flux space has been an open challenge. Flux variability analysis is only capturing some properties of the flux space, while elementary mode analysis is intractable due to the enormous number of elementary modes. However, it has been found by Kelk et al. (2012) that the space of optimal-yield fluxes decomposes into flux modules. These decompositions allow a much easier but still comprehensive analysis of the optimal-yield flux space. Using the mathematical definition of module introduced by Müller and Bockmayr (2013b), we discovered useful connections to matroid theory, through which efficient algorithms enable us to compute the decomposition into modules in a few seconds for genome-scale networks. Using that every module can be represented by one reaction that represents its function, in this article, we also present a method that uses this decomposition to visualize the interplay of modules. We expect the new method to replace flux variability analysis in the pipelines for metabolic networks.

Modelling and Optimization of Nannochloropsis and Chlorella Growth for Various Locations and Seasons

NASA Astrophysics Data System (ADS)

Gharagozloo, P. E.

2014-12-01

Efficient production of algal biofuels could reduce dependence on foreign oil providing domestic renewable energy. Algae-based biofuels are attractive for their large oil yield potential despite decreased land use and natural-resource requirements compared to terrestrial energy crops. Important factors controlling algal-lipid productivity include temperature, nutrient availability, salinity, pH, and the light-to-biomass conversion rate. Computational approaches allow for inexpensive predictions of algae-growth kinetics for various bioreactor sizes and geometries without multiple, expensive measurement systems. In this work, we parameterize our physics-based computational algae growth model for the marine Nannochloropsis oceanica and freshwater Chlorella species. We then compare modelling results with experiments conducted in identical raceway ponds at six geographical locations in the United States (Hawaii, California, Arizona, Ohio, Georgia, and Florida) and three seasons through the Algae Testbed Public Private Partnership - Unified Field Studies. Results show that the computational model effectively predicts algae growth in systems across varying environments and identifies the causes for reductions in algal productivities. The model is then used to identify improvements to the cultivation system to produce higher biomass yields. This model could be used to study the effects of scale-up including the effects of predation, depth-decay of light (light extinction), and optimized nutrient and CO2 delivery. As more multifactorial data are accumulated for a variety of algal strains, the model could be used to select appropriate algal species for various geographic and climatic locations and seasons. Applying the model facilitates optimization of pond designs based on location and season.

Selective Detection of Peptide-Oligonucleotide Heteroconjugates Utilizing Capillary HPLC-ICPMS

NASA Astrophysics Data System (ADS)

Catron, Brittany; Caruso, Joseph A.; Limbach, Patrick A.

2012-06-01

A method for the selective detection and quantification of peptide:oligonucleotide heteroconjugates, such as those generated by protein:nucleic acid cross-links, using capillary reversed-phase high performance liquid chromatography (cap-RPHPLC) coupled with inductively coupled plasma mass spectrometry detection (ICPMS) is described. The selective detection of phosphorus as 31P+, the only natural isotope, in peptide-oligonucleotide heteroconjugates is enabled by the elemental detection capabilities of the ICPMS. Mobile phase conditions that allow separation of heteroconjugates while maintaining ICPMS compatibility were investigated. We found that trifluoroacetic acid (TFA) mobile phases, used in conventional peptide separations, and hexafluoroisopropanol/triethylamine (HFIP/TEA) mobile phases, used in conventional oligonucleotide separations, both are compatible with ICPMS and enable heteroconjugate separation. The TFA-based separations yielded limits of detection (LOD) of ~40 ppb phosphorus, which is nearly seven times lower than the LOD for HFIP/TEA-based separations. Using the TFA mobile phase, 1-2 pmol of a model heteroconjugate were routinely separated and detected by this optimized capLC-ICPMS method.

One-pot synthesis and sigma receptor binding studies of novel spirocyclic-2,6-diketopiperazine derivatives.

PubMed

Ghandi, Mehdi; Sherafat, Fatemeh; Sadeghzadeh, Masoud; Alirezapour, Behrouz

2016-06-01

New spirocyclic-2,6-diketopiperazine derivatives containing benzylpiperidine and cycloalkane moieties were synthesized by a one-pot two-step sequential Ugi/intramolecular N-amidation process in moderate to good yields. The in vitro ligand-binding profile studies performed on the sigma-1 and sigma-2 receptors revealed that the σ1 affinities and subtype selectivities of three spirocyclic piperidine derivatives are generally comparable to those of spirocycloalkane analogues. Compared to the low σ1 affinities obtained for cycloalkyl-substituted spirocyclic-2,6-diketopiperazines with n=2, those with n=1 proved to have optimal fitting with σ2 subtype by exhibiting higher affinities. Moreover, the best binding affinity and subtype selectivity was identified for compound 3c with Kiσ1=5.9±0.5nM and Kiσ2=563±21nM as well as 95-fold σ1/σ2 selectivity ratio, respectively. Copyright © 2016. Published by Elsevier Ltd.

Risk-adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Kim, Yusung

Currently, there is great interest in integrating biological information into intensity-modulated radiotherapy (IMRT) treatment planning with the aim of boosting high-risk tumor subvolumes. Selective boosting of tumor subvolumes can be accomplished without violating normal tissue complication constraints using information from functional imaging. In this work we have developed a risk-adaptive optimization-framework that utilizes a nonlinear biological objective function. Employing risk-adaptive radiotherapy for prostate cancer, it is possible to increase the equivalent uniform dose (EUD) by up to 35.4 Gy in tumor subvolumes having the highest risk classification without increasing normal tissue complications. Subsequently, we have studied the impact of functional imaging accuracy, and found on the one hand that loss in sensitivity had a large impact on expected local tumor control, which was maximal when a low-risk classification for the remaining low risk PTV was chosen. While on the other hand loss in specificity appeared to have a minimal impact on normal tissue sparing. Therefore, it appears that in order to improve the therapeutic ratio a functional imaging technique with a high sensitivity, rather than specificity, is needed. Last but not least a comparison study between selective boosting IMRT strategies and uniform-boosting IMRT strategies yielding the same EUD to the overall PTV was carried out, and found that selective boosting IMRT considerably improves expected TCP compared to uniform-boosting IMRT, especially when lack of control of the high-risk tumor subvolumes is the cause of expected therapy failure. Furthermore, while selective boosting IMRT, using physical dose-volume objectives, did yield similar rectal and bladder sparing when compared its equivalent uniform-boosting IMRT plan, risk-adaptive radiotherapy, utilizing biological objective functions, did yield a 5.3% reduction in NTCP for the rectum. Hence, in risk-adaptive radiotherapy the therapeutic ratio can be increased over that which can be achieved with conventional selective boosting IMRT using physical dose-volume objectives. In conclusion, a novel risk-adaptive radiotherapy strategy is proposed and promises increased expected local control for locoregionally advanced tumors with equivalent or better normal tissue sparing.

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

Optimizing Dense Plasma Focus Neutron Yields With Fast Gas Jets

NASA Astrophysics Data System (ADS)

McMahon, Matthew; Stein, Elizabeth; Higginson, Drew; Kueny, Christopher; Link, Anthony; Schmidt, Andrea

2017-10-01

We report a study using the particle-in-cell code LSP to perform fully kinetic simulations modeling dense plasma focus (DPF) devices with high density gas jets on axis. The high-density jets are modeled in the large-eddy Navier-Stokes code CharlesX, which is suitable for modeling both sub-sonic and supersonic gas flow. The gas pattern, which is essentially static on z-pinch time scales, is imported from CharlesX to LSP for neutron yield predictions. Fast gas puffs allow for more mass on axis while maintaining the optimal pressure for the DPF. As the density of a subsonic jet increases relative to the background fill, we find the neutron yield increases, as does the variability in the neutron yield. Introducing perturbations in the jet density via super-sonic flow (also known as Mach diamonds) allow for consistent seeding of the m =0 instability leading to more consistent ion acceleration and higher neutron yields with less variability. Jets with higher on axis density are found to have the greatest yield. The optimal jet configuration and the necessary jet conditions for increasing neutron yield and reducing yield variability are explored. Simulations of realistic jet profiles are performed and compared to the ideal scenario. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the Laboratory Directed Research and Development Program (15-ERD-034) at LLNL.

Contribution of morphoagronomic traits to grain yield and earliness in grain sorghum.

PubMed

da Silva, K J; Teodoro, P E; de Menezes, C B; Júlio, M P M; de Souza, V F; da Silva, M J; Pimentel, L D; Borém, A

2017-05-04

Given the importance of selecting lines to obtain hybrids, we aimed to verify the relationship between morphological traits that can be used as the criteria for the selection of sorghum lines with high grain yield and earliness. A total of 18 traits were evaluated in 160 sorghum elite lines, in an incomplete block design with two replicates. A correlation network was used to graphically express the estimates of phenotypic and genotypic correlations between the traits. Two path analyses were processed, the first considering grain yield and the second considering flowering as the principle dependent variable. In general, most of the variation in the grain yield and flowering of sorghum lines was explained by the traits evaluated. Selecting sorghum lines with greater width of the third leaf blade from flag leaf, panicle weight, and panicle harvest index might lead to increased grain yield, and selecting sorghum genotypes with higher plant height might lead to reduced earliness and increased grain yield. Thus, the results suggest the establishment of selection indices aiming at simultaneously increasing the grain yield and earliness in sorghum genotypes.

The filter-feeding ciliates Colpidium striatum and Tetrahymena pyriformis display selective feeding behaviours in the presence of mixed, equally-sized, bacterial prey.

PubMed

Thurman, Jill; Parry, Jacqueline D; Hill, Philip J; Laybourn-Parry, Johanna

2010-10-01

This study examined whether two ciliates could discriminate between equally-sized bacterial prey in mixture and if so, how selectivity might benefit the ciliate population. Live Klebsiella aerogenes, K. ozaenae and Escherichia coli, expressing different coloured fluorescent proteins, were cultured in such a way as to provide populations containing equally-sized cells (to prevent size-selective grazing taking place) and these prey were fed to each ciliate in 50:50 mixtures. Colpidium striatum selected K. aerogenes over K. ozaenae which itself was selected over E. coli. Tetrahymena pyriformis showed no selectivity between K. aerogenes and E. coli but K. aerogenes was selected over K. ozaenae while E. coli was not. This apparent selection of K. aerogenes over K. ozaenae was sustained in ciliate populations with different feeding histories and when K. aerogenes comprised only 20% of the prey mixture, suggesting possible optimal foraging behaviour. The metabolic benefits for selecting K. aerogenes were identified as possibly being an increase in cell biovolume and yield for C. striatum and T. pyriformis, respectively. The mechanism by which these ciliates selected specific bacterial cells in mixture is currently unknown but the use of live fluorescent bacteria, in prey mixtures, offers an exciting avenue for further investigation of selective feeding by protozoa. Copyright 2010 Elsevier Ltd. All rights reserved.

Numerical Approach for Goaf-Side Entry Layout and Yield Pillar Design in Fractured Ground Conditions

NASA Astrophysics Data System (ADS)

Jiang, Lishuai; Zhang, Peipeng; Chen, Lianjun; Hao, Zhen; Sainoki, Atsushi; Mitri, Hani S.; Wang, Qingbiao

2017-11-01

Entry driven along goaf-side (EDG), which is the development of an entry of the next longwall panel along the goaf-side and the isolation of the entry from the goaf with a small-width yield pillar, has been widely employed in China over the past several decades . The width of such a yield pillar has a crucial effect on EDG layout in terms of the ground control, isolation effect and resource recovery rate. Based on a case study, this paper presents an approach for evaluating, designing and optimizing EDG and yield pillar by considering the results from numerical simulations and field practice. To rigorously analyze the ground stability, the numerical study begins with the simulation of goaf-side stress and ground conditions. Four global models with identical conditions, except for the width of the yield pillar, are built, and the effect of pillar width on ground stability is investigated by comparing aspects of stress distribution, failure propagation, and displacement evolution during the entire service life of the entry. Based on simulation results, the isolation effect of the pillar acquired from field practice is also considered. The suggested optimal yield pillar design is validated using a field test in the same mine. Thus, the presented numerical approach provides references and can be utilized for the evaluation, design and optimization of EDG and yield pillars under similar geological and geotechnical circumstances.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

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

Zhou, Z; Folkert, M; Wang, J

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidentialmore » reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.« less

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

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

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

Artificial neural network models: A decision support tool for enhancing seedling selection in sugarcane

USDA-ARS?s Scientific Manuscript database

Currently, sugarcane selection begins at the seedling stage with visual selection for cane yield and other yield-related traits. Although subjective and inefficient, visual selection remains the primary method for selection. Visual selection is inefficient because of the confounding effect of genoty...

Using multiscale texture and density features for near-term breast cancer risk analysis

PubMed Central

Sun, Wenqing; Tseng, Tzu-Liang (Bill); Qian, Wei; Zhang, Jianying; Saltzstein, Edward C.; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

2015-01-01

Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. Methods: The authors’ dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the “prior” screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. Results: From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). Conclusions: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations. PMID:26127038

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

Iblisdir, S.; Gisin, N.; Acin, A.

We investigate the optimal distribution of quantum information over multipartite systems in asymmetric settings. We introduce cloning transformations that take N identical replicas of a pure state in any dimension as input and yield a collection of clones with nonidentical fidelities. As an example, if the clones are partitioned into a set of M{sub A} clones with fidelity F{sup A} and another set of M{sub B} clones with fidelity F{sup B}, the trade-off between these fidelities is analyzed, and particular cases of optimal N{yields}M{sub A}+M{sub B} cloning machines are exhibited. We also present an optimal 1{yields}1+1+1 cloning machine, which ismore » an example of a tripartite fully asymmetric cloner. Finally, it is shown how these cloning machines can be optically realized.« less

Recent advances in reconstructing microbial secondary metabolites biosynthesis in Aspergillus spp.

PubMed

He, Yi; Wang, Bin; Chen, Wanping; Cox, Russell J; He, Jingren; Chen, Fusheng

High throughput genome sequencing has revealed a multitude of potential secondary metabolites biosynthetic pathways that remain cryptic. Pathway reconstruction coupled with genetic engineering via heterologous expression enables discovery of novel compounds, elucidation of biosynthetic pathways, and optimization of product yields. Apart from Escherichia coli and yeast, fungi, especially Aspergillus spp., are well known and efficient heterologous hosts. This review summarizes recent advances in heterologous expression of microbial secondary metabolite biosynthesis in Aspergillus spp. We also discuss the technological challenges and successes in regard to heterologous host selection and DNA assembly behind the reconstruction of microbial secondary metabolite biosynthesis. Copyright © 2018 Elsevier Inc. All rights reserved.

Kinematic analysis of the finger exoskeleton using MATLAB/Simulink.

PubMed

Nasiłowski, Krzysztof; Awrejcewicz, Jan; Lewandowski, Donat

2014-01-01

A paralyzed and not fully functional part of human body can be supported by the properly designed exoskeleton system with motoric abilities. It can help in rehabilitation, or movement of a disabled/paralyzed limb. Both suitably selected geometry and specialized software are studied applying the MATLAB environment. A finger exoskeleton was the base for MATLAB/Simulink model. Specialized software, such as MATLAB/Simulink give us an opportunity to optimize calculation reaching precise results, which help in next steps of design process. The calculations carried out yield information regarding movement relation between three functionally connected actuators and showed distance and velocity changes during the whole simulation time.

Finding the perfect spot for fluorine: improving potency up to 40-fold during a rational fluorine scan of a Bruton's Tyrosine Kinase (BTK) inhibitor scaffold.

PubMed

Lou, Yan; Sweeney, Zachary K; Kuglstatter, Andreas; Davis, Dana; Goldstein, David M; Han, Xiaochun; Hong, Junbae; Kocer, Buelent; Kondru, Rama K; Litman, Renee; McIntosh, Joel; Sarma, Keshab; Suh, Judy; Taygerly, Joshua; Owens, Timothy D

2015-01-15

A rational fluorine scan based on co-crystal structures was explored to increase the potency of a series of selective BTK inhibitors. While fluorine substitution on a saturated bicyclic ring system yields no apparent benefit, the same operation on an unsaturated bicyclic ring can increase HWB activity by up to 40-fold. Comparison of co-crystal structures of parent molecules and fluorinated counterparts revealed the importance of placing fluorine at the optimal position to achieve favorable interactions with protein side chains. Copyright © 2014 Elsevier Ltd. All rights reserved.

Maleic anhydride-g-low density polyethylene: Modification of LDPE molecular structure by γ-irradiation

NASA Astrophysics Data System (ADS)

Sheeja, Manaf, O.; Sujith, A.

2017-06-01

Polymer modification by radiation grafting of monomers onto polymers has received much attention recently. In the current study, γ-irradiation technique was used to achieve graft copolymerization of maleic anhydride (MA) onto low-density polyethylene (LDPE). To optimize, the process was performed at different γ-irradiation doses and MA concentration. The microstructure of grafted polymer film has been characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, differential scanning calorimetry, field emission-scanning electron microscopy, and atomic force microscopy. The studies performed made possible the selection of experimental protocols adequate for the production of new copolymeric materials with high grafting yield.

Production and engineering methods for CARB: TEK (trade name) batteries in fork lift trucks

NASA Astrophysics Data System (ADS)

Schaefer, J. C.

1975-03-01

The purpose of this program is to develop the manufacturing technology of the Carb Tek molten salt Li/Cl battery to the prototype level. This purpose is being accomplished by actually constructing cells on a pilot line, optimizing process steps, establishing quality control procedures, and engineering appropriate changes. The majority of the cell work is performed in a controlled argon atmosphere. Results show that the carbon selected for the cell cathode can develop the required 5 Whr/cubic inch even when damaged by stress cracks. Anode contamination and fabrication problems have been reduced by a new alloying technique. Cell yields are dependent on weld quality.

Mechanocatalytic depolymerization of cellulose with perfluorinated sulfonic acid ionomers

NASA Astrophysics Data System (ADS)

Karam, Ayman; Amaniampong, Prince N.; García Fernández, José M.; Oldani, Claudio; Marinkovic, Sinisa; Estrine, Boris; De Oliveira Vigier, Karine; Jérôme, François

2018-03-01

Here, we investigated that the mechanocatalytic depolymerization of cellulose in the presence of Aquivion, a sulfonated perfluorinated ionomer. Under optimized conditions, yields of water soluble sugars of 90-97 % were obtained using Aquivion PW98 and PW66, respectively, as a solid acid catalyst. The detailed characterization of the water soluble fraction revealed (i) the selective formation of oligosaccharides with a DP up to 11 and (ii) that depolymerization and reversion reactions concomitantly occurred during the mechanocatalytic process, although the first largely predominated. More importantly, we discussed on the critical role of water contained in Aquivion and cellulose on the efficiency of the mechanocatalytic process.

Mechanocatalytic Depolymerization of Cellulose With Perfluorinated Sulfonic Acid Ionomers

PubMed Central

Karam, Ayman; Amaniampong, Prince N.; García Fernández, José M.; Oldani, Claudio; Marinkovic, Sinisa; Estrine, Boris; De Oliveira Vigier, Karine; Jérôme, François

2018-01-01

Here, we investigated that the mechanocatalytic depolymerization of cellulose in the presence of Aquivion, a sulfonated perfluorinated ionomer. Under optimized conditions, yields of water soluble sugars of 90–97% were obtained using Aquivion PW98 and PW66, respectively, as a solid acid catalyst. The detailed characterization of the water soluble fraction revealed (i) the selective formation of oligosaccharides with a DP up to 11 and (ii) that depolymerization and reversion reactions concomitantly occurred during the mechanocatalytic process, although the first largely predominated. More importantly, we discussed on the critical role of water contained in Aquivion and cellulose on the efficiency of the mechanocatalytic process. PMID:29623273

Mechanocatalytic Depolymerization of Cellulose With Perfluorinated Sulfonic Acid Ionomers.

PubMed

Karam, Ayman; Amaniampong, Prince N; García Fernández, José M; Oldani, Claudio; Marinkovic, Sinisa; Estrine, Boris; De Oliveira Vigier, Karine; Jérôme, François

2018-01-01

Here, we investigated that the mechanocatalytic depolymerization of cellulose in the presence of Aquivion, a sulfonated perfluorinated ionomer. Under optimized conditions, yields of water soluble sugars of 90-97% were obtained using Aquivion PW98 and PW66, respectively, as a solid acid catalyst. The detailed characterization of the water soluble fraction revealed (i) the selective formation of oligosaccharides with a DP up to 11 and (ii) that depolymerization and reversion reactions concomitantly occurred during the mechanocatalytic process, although the first largely predominated. More importantly, we discussed on the critical role of water contained in Aquivion and cellulose on the efficiency of the mechanocatalytic process.

Managing the Public Sector Research and Development Portfolio Selection Process: A Case Study of Quantitative Selection and Optimization

DTIC Science & Technology

2016-09-01

PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION by Jason A. Schwartz...PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION 5. FUNDING NUMBERS 6...describing how public sector organizations can implement a research and development (R&D) portfolio optimization strategy to maximize the cost

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

Durt, Thomas; Fiurasek, Jaromir; Department of Optics, Palacky University, 17. listopadu 50, 77200 Olomouc

The possibility of cloning a d-dimensional quantum system without an ancilla is explored, extending on the economical phase-covariant cloning machine for qubits found in Phys. Rev. A 60, 2764 (1999). We prove the impossibility of constructing an economical version of the optimal universal 1{yields}2 cloning machine in any dimension. We also show, using an ansatz on the generic form of cloning machines, that the d-dimensional 1{yields}2 phase-covariant cloner, which optimally clones all balanced superpositions with arbitrary phases, can be realized economically only in dimension d=2. The used ansatz is supported by numerical evidence up to d=7. An economical phase-covariant clonermore » can nevertheless be constructed for d>2, albeit with a slightly lower fidelity than that of the optimal cloner requiring an ancilla. Finally, using again an ansatz on cloning machines, we show that an economical version of the 1{yields}2 Fourier-covariant cloner, which optimally clones the computational basis and its Fourier transform, is also possible only in dimension d=2.« less

Optimal management strategies in variable environments: Stochastic optimal control methods

USGS Publications Warehouse

Williams, B.K.

1985-01-01

Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both the discount rate and the climatic patterns on optimal harvest strategics. In general, decreases in either the discount rate or in the frequency of favorable weather patterns lcd to a more conservative defoliation policy. This did not hold, however, for plants in states of low vigor. Optimal control for shadscale and winterfat tended to stabilize on a policy of heavy defoliation stress, followed by one or more seasons of rest. Big sagebrush required a policy of heavy summer defoliation when sufficient active shoot material is present at the beginning of the growing season. The comparison of fixed and optimal strategies indicated considerable improvement in defoliation yields when optimal strategies are followed. The superior performance was attributable to increased defoliation of plants in states of high vigor. Improvements were found for both discounted and undiscounted yields.

Developing Methods for Detection of Munitions and Explosives of Concern in Offshore Wind Energy Areas

NASA Astrophysics Data System (ADS)

DuVal, C.; Trembanis, A. C.; Miller, J. K.; Carton, G.

2016-12-01

Munitions and Explosives of Concern (MEC) have been acknowledged globally as a topic of concern. Increasing use of coastal and continental shelf environments for renewable energy development and other activities has and continues to place humans in contact with legacy military munitions. The Bureau of Ocean Energy Management (BOEM) recognized the need to develop guidance concerning methods for MEC detection in the case of offshore energy development. The study was designed to identify the most likely MEC to be encountered in the Atlantic Outer Continental Shelf (OCS) Wind Energy Areas (WEA), review available technologies and develop a process for selecting appropriate technologies and methodologies for their detection. The process for selecting and optimizing technologies and methods for detection of MEC in BOEM OCS WEAs was developed and tested through the synthesis of historical research, physical site characterization, remote sensing technology review, and in-field trials. To test the selected approach, designated personnel were tasked with seeding a portion of the Delaware WEA with munitions surrogates, while a second group of researchers not privy to the surrogate locations, tested and optimized the selected methodology. The effectiveness of a methodology will be related to ease of detection and other associated parameters. The approach for the in-field trial consists of a combination of wide-area assessment surveying by vessel mounted 230/550 kHz Edgetech 6205 Phase Measuring sonar and near-seafloor surveying using a Teledyne Gavia autonomous underwater vehicle (AUV) equipped with high-resolution 900/1800 kHz Marine Sonics side-scan sonar, Geometrics G880-AUV cesium-vapor magnetometer, and 2 megapixel Point Grey color camera. Survey parameters (e.g. track-line spacing, coverage overlap, AUV altitude) were varied to determine the optimal survey methods, as well as simulate MEC burial to test magnetometer range performance. Preliminary results indicate the combination of high-resolution, near-bed side-scan sonar and magnetometry yields promising results for MEC identification, addressing the potential for both surficial and buried MEC.

Framework for the rapid optimization of soluble protein expression in Escherichia coli combining microscale experiments and statistical experimental design.

PubMed

Islam, R S; Tisi, D; Levy, M S; Lye, G J

2007-01-01

A major bottleneck in drug discovery is the production of soluble human recombinant protein in sufficient quantities for analysis. This problem is compounded by the complex relationship between protein yield and the large number of variables which affect it. Here, we describe a generic framework for the rapid identification and optimization of factors affecting soluble protein yield in microwell plate fermentations as a prelude to the predictive and reliable scaleup of optimized culture conditions. Recombinant expression of firefly luciferase in Escherichia coli was used as a model system. Two rounds of statistical design of experiments (DoE) were employed to first screen (D-optimal design) and then optimize (central composite face design) the yield of soluble protein. Biological variables from the initial screening experiments included medium type and growth and induction conditions. To provide insight into the impact of the engineering environment on cell growth and expression, plate geometry, shaking speed, and liquid fill volume were included as factors since these strongly influence oxygen transfer into the wells. Compared to standard reference conditions, both the screening and optimization designs gave up to 3-fold increases in the soluble protein yield, i.e., a 9-fold increase overall. In general the highest protein yields were obtained when cells were induced at a relatively low biomass concentration and then allowed to grow slowly up to a high final biomass concentration, >8 g.L-1. Consideration and analysis of the model results showed 6 of the original 10 variables to be important at the screening stage and 3 after optimization. The latter included the microwell plate shaking speeds pre- and postinduction, indicating the importance of oxygen transfer into the microwells and identifying this as a critical parameter for subsequent scale translation studies. The optimization process, also known as response surface methodology (RSM), predicted there to be a distinct optimum set of conditions for protein expression which could be verified experimentally. This work provides a generic approach to protein expression optimization in which both biological and engineering variables are investigated from the initial screening stage. The application of DoE reduces the total number of experiments needed to be performed, while experimentation at the microwell scale increases experimental throughput and reduces cost.

Medium optimization for ε-poly-L-lysine production by Streptomyces diastatochromogenes using response surface methodology.

PubMed

Guo, F; Zheng, H; Cheng, Y; Song, S; Zheng, Z; Jia, S

2018-02-01

Poly-ε-L-lysine is a natural homo-polyamide of L-lysine with excellent antimicrobial properties, which can be used as a novel preservative and has a wide range of applications. In this paper, the fermentation medium for ε-PL production by Streptomyces diastatochromogenes 6#-7 was optimized by Response Surface Methodology. The results of Plackett-Burman design showed that glucose, yeast extract and (NH 4 ) 2 SO 4 were the major influencing factors in ε-PL production of S. diastatochromogenes 6#-7. The optimal concentrations of glucose, yeast extract and (NH 4 ) 2 SO 4 were determined to be 60, 7·5 and 7·5 g l -1 according to Box-Behnken experiment and regression analysis, respectively. Under the optimized conditions, the ε-PL yield in shake-flask fermentation was 0·948 ± 0·030 g l -1 , which was in good agreement with the predicted value of 0·970 g l -1 . The yield was improved by 43·1% from that with the initial medium. In 5 l jar-fermenter the ε-PL yield reached 25·5 g l -1 , which was increased by 56·4% from the original medium. In addition, the fermentation time was reduced from 174 to 120 h. Medium optimization is a very practical and valuable tool for fermentation industry to improve product yield and minimize by-products as well as reduce overall manufacturing costs. The response surface methodology is not new, but it is still a very effective method in medium optimization research. This study used ε-polylysine fermentation as an example to demonstrate how the product yield can be significantly increased by medium optimization through surface response methodology. Similar approach can be used in other microbial fermentations such as in pharmaceutical, food, agricultural and energy industries. As an example, ε-polylysine is one of a few newly approved natural food-grade antimicrobials for food and beverages preservations. Yield improvement is economically beneficial to not only ε-polylysine manufacturers but also to their users and consumers due to lower costs and price. © 2017 The Society for Applied Microbiology.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

A cohort study of a general surgery electronic consultation system: safety implications and impact on surgical yield.

PubMed

Ulloa, Jesus G; Russell, Marika D; Chen, Alice Hm; Tuot, Delphine S

2017-06-23

Electronic consultation (eConsult) systems have enhanced access to specialty expertise and enhanced care coordination among primary care and specialty care providers, while maintaining high primary care provider (PCP), specialist and patient satisfaction. Little is known about their impact on the efficiency of specialty care delivery, in particular surgical yield (percent of ambulatory visits resulting in a scheduled surgical case). Retrospective cohort of a random selection of 150 electronic consults from PCPs to a safety-net general surgery clinic for the three most common general surgery procedures (herniorrhaphy, cholecystectomy, anorectal procedures) in 2014. Electronic consultation requests were reviewed for the presence/absence of consult domains: symptom acuity/severity, diagnostic evaluation, concurrent medical conditions, and attempted diagnosis. Logic regression was used to examine the association between completeness of consult requests and scheduling an ambulatory clinic visit. Surgical yield was also calculated, as was the percentage of patients requiring unanticipated healthcare visits. In 2014, 1743 electronic consultations were submitted to general surgery. Among the 150 abstracted, the presence of consult domains ranged from 49% to 99%. Consult completeness was not associated with greater likelihood of scheduling an ambulatory visit. Seventy-six percent of consult requests (114/150) were scheduled for a clinic appointment and surgical yield was 46%; without an eConsult system, surgical yield would have been 35% (p=0.07). Among patients not scheduled for a clinic visit (n=36), 4 had related unanticipated emergency department visits. Econsult systems can be used to safely optimize the surgical yield of a safety-net general surgery service.

MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection

PubMed Central

Ou, Yangming; Resnick, Susan M.; Gur, Ruben C.; Gur, Raquel E.; Satterthwaite, Theodore D.; Furth, Susan; Davatzikos, Christos

2016-01-01

Atlas-based automated anatomical labeling is a fundamental tool in medical image segmentation, as it defines regions of interest for subsequent analysis of structural and functional image data. The extensive investigation of multi-atlas warping and fusion techniques over the past 5 or more years has clearly demonstrated the advantages of consensus-based segmentation. However, the common approach is to use multiple atlases with a single registration method and parameter set, which is not necessarily optimal for every individual scan, anatomical region, and problem/data-type. Different registration criteria and parameter sets yield different solutions, each providing complementary information. Herein, we present a consensus labeling framework that generates a broad ensemble of labeled atlases in target image space via the use of several warping algorithms, regularization parameters, and atlases. The label fusion integrates two complementary sources of information: a local similarity ranking to select locally optimal atlases and a boundary modulation term to refine the segmentation consistently with the target image's intensity profile. The ensemble approach consistently outperforms segmentations using individual warping methods alone, achieving high accuracy on several benchmark datasets. The MUSE methodology has been used for processing thousands of scans from various datasets, producing robust and consistent results. MUSE is publicly available both as a downloadable software package, and as an application that can be run on the CBICA Image Processing Portal (https://ipp.cbica.upenn.edu), a web based platform for remote processing of medical images. PMID:26679328

Perspective and prospective of pretreatment of corn straw for butanol production.

PubMed

Baral, Nawa Raj; Li, Jiangzheng; Jha, Ajay Kumar

2014-01-01

Corn straw, lignocellulosic biomass, is a potential substrate for microbial production of bio-butanol. Bio-butanol is a superior second generation biofuel among its kinds. Present researches are focused on the selection of butanol tolerant clostridium strain(s) to optimize butanol yield in the fermentation broth because of toxicity of bio-butanol to the clostridium strain(s) itself. However, whatever the type of the strain(s) used, pretreatment process always affects not only the total sugar yield before fermentation but also the performance and growth of microbes during fermentation due to the formation of hydroxyl-methyl furfural, furfural and phenolic compounds. In addition, the lignocellulosic biomasses also resist physical and biological attacks. Thus, selection of best pretreatment process and its parameters is crucial. In this context, worldwide research efforts are increased in past 12 years and researchers are tried to identify the best pretreatment method, pretreatment conditions for the actual biomass. In this review, effect of particle size, status of most common pretreatment method and enzymatic hydrolysis particularly for corn straw as a substrate is presented. This paper also highlights crucial parameters necessary to consider during most common pretreatment processes such as hydrothermal, steam explosion, ammonia explosion, sulfuric acid, and sodium hydroxide pretreatment. Moreover, the prospective of pretreatment methods and challenges is discussed.

Hydroxyacetone: A Glycerol-Based Platform for Electrocatalytic Hydrogenation and Hydrodeoxygenation Processes.

PubMed

Sauter, Waldemar; Bergmann, Olaf L; Schröder, Uwe

2017-08-10

Here, we propose the use of hydroxyacetone, a dehydration product of glycerol, as a platform for the electrocatalytic synthesis of acetone, 1,2-propanediol, and 2-propanol. 11 non-noble metals were investigated as electrode materials in combination with three different electrolyte compositions toward the selectivity, Coulombic efficiency (CE), and reaction rates of the electrocatalytic hydrogenation (formation of 1,2-propanediol) and hydrodeoxygenation (formation of acetone and propanol) of hydroxyacetone. With a selectivity of 84.5 %, a reaction rate of 782 mmol h -1  m -2 and a CE of 32 % (for 0.09 m hydroxyacetone), iron electrodes, in a chloride electrolyte, yielded the best 1,2 propanediol formation. A further enhancement of the performance can be achieved upon increasing the educt concentration to 0.5 m, yielding a reaction rate of 2248.1 mmol h -1  m -2 and a CE of 64.5 %. Acetone formation was optimal at copper and lead electrodes in chloride solution, with lead showing the lowest tendency of side product formation. 2-propanol formation can be achieved using a consecutive oxidation of the formed acetone (at iron electrodes). 1-propanol formation was observed only in traces. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neutron Tomography of a Fuel Cell: Statistical Learning Implementation of a Penalized Likelihood Method

NASA Astrophysics Data System (ADS)

Coakley, Kevin J.; Vecchia, Dominic F.; Hussey, Daniel S.; Jacobson, David L.

2013-10-01

At the NIST Neutron Imaging Facility, we collect neutron projection data for both the dry and wet states of a Proton-Exchange-Membrane (PEM) fuel cell. Transmitted thermal neutrons captured in a scintillator doped with lithium-6 produce scintillation light that is detected by an amorphous silicon detector. Based on joint analysis of the dry and wet state projection data, we reconstruct a residual neutron attenuation image with a Penalized Likelihood method with an edge-preserving Huber penalty function that has two parameters that control how well jumps in the reconstruction are preserved and how well noisy fluctuations are smoothed out. The choice of these parameters greatly influences the resulting reconstruction. We present a data-driven method that objectively selects these parameters, and study its performance for both simulated and experimental data. Before reconstruction, we transform the projection data so that the variance-to-mean ratio is approximately one. For both simulated and measured projection data, the Penalized Likelihood method reconstruction is visually sharper than a reconstruction yielded by a standard Filtered Back Projection method. In an idealized simulation experiment, we demonstrate that the cross validation procedure selects regularization parameters that yield a reconstruction that is nearly optimal according to a root-mean-square prediction error criterion.

Two years of experience with the [ 18F]FDG production module

NASA Astrophysics Data System (ADS)

Kim, Sang Wook; Hur, Min Goo; Chai, Jong-Seo; Park, Jeong Hoon; Yu, Kook Hyun; Jeong, Cheol Ki; Lee, Goung Jin; Min, Young Don; Yang, Seung Dae

2007-08-01

Chemistry module for a conventional [18F]FDG production by using tetrabutylammonium bicarbonate (TBA) and an acidic hydrolysis has been manufactured and evaluated. In this experiment, 75 mM (pH 7.5-7.8) of TBA solution and a ca. 2-curies order of [18F]-fluoride have been used for the evaluation. The commercial acidic purification cartridge was purchased from GE or UKE. The operation system (OS) was programmed with Lab-View which was selected because of its easy customization of the OS. Small sized solenoid valves (Burkert; type 6124) were selected to reduce the module dimensions (W 350 × D 270 × H 250). The total time for the synthesis of [18F]FDG was 30 ± 3 min. The production yield of [18F]FDG was 60 ± 2% on an average at EOS, with the decay uncorrected. This experimental data show that the traditional chemistry module can provide a good [18F]FDG production yield by optimizing the operational conditions. The radiochemical purity, radionuclidic purity, acidity, residual solvent, osmolality and endotoxin were determined to assess the quality of [18F]FDG. The examined contents for the quality control of [18F]FDG were found to be suitable for a clinical application.

Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data.

PubMed

Ooi, Chia Huey; Chetty, Madhu; Teng, Shyh Wei

2006-06-23

Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gene expression-based tissue classification while improving accuracy at the same time. Surprisingly, this does not appear to be the case for all multiclass microarray datasets. The reason is that many feature selection techniques applied on microarray datasets are either rank-based and hence do not take into account correlations between genes, or are wrapper-based, which require high computational cost, and often yield difficult-to-reproduce results. In studies where correlations between genes are considered, attempts to establish the merit of the proposed techniques are hampered by evaluation procedures which are less than meticulous, resulting in overly optimistic estimates of accuracy. We present two realistically evaluated correlation-based feature selection techniques which incorporate, in addition to the two existing criteria involved in forming a predictor set (relevance and redundancy), a third criterion called the degree of differential prioritization (DDP). DDP functions as a parameter to strike the balance between relevance and redundancy, providing our techniques with the novel ability to differentially prioritize the optimization of relevance against redundancy (and vice versa). This ability proves useful in producing optimal classification accuracy while using reasonably small predictor set sizes for nine well-known multiclass microarray datasets. For multiclass microarray datasets, especially the GCM and NCI60 datasets, DDP enables our filter-based techniques to produce accuracies better than those reported in previous studies which employed similarly realistic evaluation procedures.

Biodiesel production using waste frying oil

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

Charpe, Trupti W.; Rathod, Virendra K., E-mail: vk.rathod@ictmumbai.edu.in

2011-01-15

Research highlights: {yields} Waste sunflower frying oil is successfully converted to biodiesel using lipase as catalyst. {yields} Various process parameters that affects the conversion of transesterification reaction such as temperature, enzyme concentration, methanol: oil ratio and solvent are optimized. {yields} Inhibitory effect of methanol on lipase is reduced by adding methanol in three stages. {yields} Polar solvents like n-hexane and n-heptane increases the conversion of tranesterification reaction. - Abstract: Waste sunflower frying oil is used in biodiesel production by transesterification using an enzyme as a catalyst in a batch reactor. Various microbial lipases have been used in transesterification reaction tomore » select an optimum lipase. The effects of various parameters such as temperature, methanol:oil ratio, enzyme concentration and solvent on the conversion of methyl ester have been studied. The Pseudomonas fluorescens enzyme yielded the highest conversion. Using the P. fluorescens enzyme, the optimum conditions included a temperature of 45 deg. C, an enzyme concentration of 5% and a methanol:oil molar ratio 3:1. To avoid an inhibitory effect, the addition of methanol was performed in three stages. The conversion obtained after 24 h of reaction increased from 55.8% to 63.84% because of the stage-wise addition of methanol. The addition of a non-polar solvent result in a higher conversion compared to polar solvents. Transesterification of waste sunflower frying oil under the optimum conditions and single-stage methanol addition was compared to the refined sunflower oil.« less

Media milling process optimization for manufacture of drug nanoparticles using design of experiments (DOE).

PubMed

Nekkanti, Vijaykumar; Marwah, Ashwani; Pillai, Raviraj

2015-01-01

Design of experiments (DOE), a component of Quality by Design (QbD), is systematic and simultaneous evaluation of process variables to develop a product with predetermined quality attributes. This article presents a case study to understand the effects of process variables in a bead milling process used for manufacture of drug nanoparticles. Experiments were designed and results were computed according to a 3-factor, 3-level face-centered central composite design (CCD). The factors investigated were motor speed, pump speed and bead volume. Responses analyzed for evaluating these effects and interactions were milling time, particle size and process yield. Process validation batches were executed using the optimum process conditions obtained from software Design-Expert® to evaluate both the repeatability and reproducibility of bead milling technique. Milling time was optimized to <5 h to obtain the desired particle size (d90 < 400 nm). The desirability function used to optimize the response variables and observed responses were in agreement with experimental values. These results demonstrated the reliability of selected model for manufacture of drug nanoparticles with predictable quality attributes. The optimization of bead milling process variables by applying DOE resulted in considerable decrease in milling time to achieve the desired particle size. The study indicates the applicability of DOE approach to optimize critical process parameters in the manufacture of drug nanoparticles.

Optimization of remotely delivered intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-IN study protocol.

PubMed

Pellegrini, Christine A; Hoffman, Sara A; Collins, Linda M; Spring, Bonnie

2014-07-01

Obesity-attributable medical expenditures remain high, and interventions that are both effective and cost-effective have not been adequately developed. The Opt-IN study is a theory-guided trial using the Multiphase Optimization Strategy (MOST) to develop an optimized, scalable version of a technology-supported weight loss intervention. Opt-IN aims to identify which of 5 treatment components or component levels contribute most meaningfully and cost-efficiently to the improvement of weight loss over a 6 month period. Five hundred and sixty obese adults (BMI 30-40 kg/m(2)) between 18 and 60 years old will be randomized to one of 16 conditions in a fractional factorial design involving five intervention components: treatment intensity (12 vs. 24 coaching calls), reports sent to primary care physician (No vs. Yes), text messaging (No vs. Yes), meal replacement recommendations (No vs. Yes), and training of a participant's self-selected support buddy (No vs. Yes). During the 6-month intervention, participants will monitor weight, diet, and physical activity on the Opt-IN smartphone application downloaded to their personal phone. Weight will be assessed at baseline, 3, and 6 months. The Opt-IN trial is the first study to use the MOST framework to develop a weight loss treatment that will be optimized to yield the best weight loss outcome attainable for $500 or less. Copyright © 2014 Elsevier Inc. All rights reserved.

Optimization of multi-color laser waveform for high-order harmonic generation

NASA Astrophysics Data System (ADS)

Jin, Cheng; Lin, C. D.

2016-09-01

With the development of laser technologies, multi-color light-field synthesis with complete amplitude and phase control would make it possible to generate arbitrary optical waveforms. A practical optimization algorithm is needed to generate such a waveform in order to control strong-field processes. We review some recent theoretical works of the optimization of amplitudes and phases of multi-color lasers to modify the single-atom high-order harmonic generation based on genetic algorithm. By choosing different fitness criteria, we demonstrate that: (i) harmonic yields can be enhanced by 10 to 100 times, (ii) harmonic cutoff energy can be substantially extended, (iii) specific harmonic orders can be selectively enhanced, and (iv) single attosecond pulses can be efficiently generated. The possibility of optimizing macroscopic conditions for the improved phase matching and low divergence of high harmonics is also discussed. The waveform control and optimization are expected to be new drivers for the next wave of breakthrough in the strong-field physics in the coming years. Project supported by the Fundamental Research Funds for the Central Universities of China (Grant No. 30916011207), Chemical Sciences, Geosciences and Biosciences Division, Office of Basic Energy Sciences, Office of Science, U. S. Department of Energy (Grant No. DE-FG02-86ER13491), and Air Force Office of Scientific Research, USA (Grant No. FA9550-14-1-0255).

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

PubMed

Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Improving monoclonal antibody selection and engineering using measurements of colloidal protein interactions

PubMed Central

Geng, Steven B.; Cheung, Jason K.; Narasimhan, Chakravarthy; Shameem, Mohammed; Tessier, Peter M.

2014-01-01

A limitation of using monoclonal antibodies as therapeutic molecules is their propensity to associate with themselves and/or with other molecules via non-affinity (colloidal) interactions. This can lead to a variety of problems ranging from low solubility and high viscosity to off-target binding and fast antibody clearance. Measuring such colloidal interactions is challenging given that they are weak and potentially involve diverse target molecules. Nevertheless, assessing these weak interactions – especially during early antibody discovery and lead candidate optimization – is critical to preventing problems that can arise later in the development process. Here we review advances in developing and implementing sensitive methods for measuring antibody colloidal interactions as well as using these measurements for guiding antibody selection and engineering. These systematic efforts to minimize non-affinity interactions are expected to yield more effective and stable monoclonal antibodies for diverse therapeutic applications. PMID:25209466

Simple, Rapid, and Selective Isolation of 2S Albumins from Allergenic Seeds and Nuts.

PubMed

Hummel, Marlene; Wigger, Tina; Höper, Tessa; Westkamp, Imke; Brockmeyer, Jens

2015-07-08

The 2S albumins belong to the group of seed storage proteins present in different seeds and nuts. Due to their pronounced allergenic potential, which is often associated with severe allergic reactions, this protein family is of special interest in the field of allergen research. Here we present a simple, rapid, and selective method for the purification of 2S albumins directly from allergenic seeds and nuts. We systematically optimized the parameters "buffer system", "extraction temperature", "buffer molarity", and "pH " and were able to achieve 2S albumin purities of about 99% without further purification and demonstrate transferability of this method to nine different allergenic food matrices. Compared to conventional isolation routines, significant reduction of hands-on time and required laboratory equipment is achieved, but nonetheless higher protein yields are obtained. The presented method allows for the rapid purification of different 2S albumins including the corresponding isoforms from natural material.

Policosanol fabrication from insect wax and optimization by response surface methodology.

PubMed

Ma, Jinju; Ma, Liyi; Zhang, Hong; Zhang, Zhongquan; Wang, Youqiong; Li, Kai; Chen, Xiaoming

2018-01-01

Insect wax is a famous biological resource for the role in economic production in China. Insect wax is a good source of policosanol, which may is a candidate supplement in foodstuff and pharmaceuticals that has important physiological activities. Therefore, this work aims to investigate a high-yield and rapid method for policosanol fabrication from insect wax. The conditions for policosanol fabrication were optimized as follows: an oil bath temperature of 112.7°C and reductant dosage of 0.97 g (used for the reduction of 10.00 g of insect wax). The yield of policosanol reached 83.20%, which was 4 times greater than that of existing methods, such as saponification. The total content of policosanol obtained under the optimal conditions reached 87%. In other words, a high yield of policosanol was obtained from insect wax (723.84 mg/g), that was 55 times higher than that generated from beeswax-brown via saponification. The concentrations of metal residues in policosanol were within the limits of the European Union regulations and EFSA stipulation. The LD50 values for oral doses of insect wax and policosanol were both > 5 g/kg. Policosanol was fabricated via solvent-free reduction from insect wax using LiAlH4 at a high yield. The fabrication conditions were optimized. Policosanol and insect wax showed high security, which made them potential candidates as supplements in foods, pharmaceuticals and cosmetics. The rapid and high-yield method has great potential for commercial manufacturing of policosanol.

Metabolic Engineering toward Sustainable Production of Nylon-6.

PubMed

Turk, Stefan C H J; Kloosterman, Wigard P; Ninaber, Dennis K; Kolen, Karin P A M; Knutova, Julia; Suir, Erwin; Schürmann, Martin; Raemakers-Franken, Petronella C; Müller, Monika; de Wildeman, Stefaan M A; Raamsdonk, Leonie M; van der Pol, Ruud; Wu, Liang; Temudo, Margarida F; van der Hoeven, Rob A M; Akeroyd, Michiel; van der Stoel, Roland E; Noorman, Henk J; Bovenberg, Roel A L; Trefzer, Axel C

2016-01-15

Nylon-6 is a bulk polymer used for many applications. It consists of the non-natural building block 6-aminocaproic acid, the linear form of caprolactam. Via a retro-synthetic approach, two synthetic pathways were identified for the fermentative production of 6-aminocaproic acid. Both pathways require yet unreported novel biocatalytic steps. We demonstrated proof of these bioconversions by in vitro enzyme assays with a set of selected candidate proteins expressed in Escherichia coli. One of the biosynthetic pathways starts with 2-oxoglutarate and contains bioconversions of the ketoacid elongation pathway known from methanogenic archaea. This pathway was selected for implementation in E. coli and yielded 6-aminocaproic acid at levels up to 160 mg/L in lab-scale batch fermentations. The total amount of 6-aminocaproic acid and related intermediates generated by this pathway exceeded 2 g/L in lab-scale fed-batch fermentations, indicating its potential for further optimization toward large-scale sustainable production of nylon-6.

Statistical optimization of culture conditions for bacterial cellulose production using Box-Behnken design.

PubMed

Bae, Sangok; Shoda, Makoto

2005-04-05

Culture conditions in a jar fermentor for bacterial cellulose (BC) production from A. xylinum BPR2001 were optimized by statistical analysis using Box-Behnken design. Response surface methodology was used to predict the levels of the factors, fructose (X1), corn steep liquor (CSL) (X2), dissolved oxygen (DO) (X3), and agar concentration (X4). Total 27 experimental runs by combination of each factor were carried out in a 10-L jar fermentor, and a three-dimensional response surface was generated to determine the effect of the factors and to find out the optimum concentration of each factor for maximum BC production and BC yield. The fructose and agar concentration highly influenced the BC production and BC yield. However, the optimum conditions according to changes in CSL and DO concentrations were predicted at almost central values of tested ranges. The predicted results showed that BC production was 14.3 g/L under the condition of 4.99% fructose, 2.85% CSL, 28.33% DO, and 0.38% agar concentration. On the other hand, BC yield was predicted in 0.34 g/g under the condition of 3.63% fructose, 2.90% CSL, 31.14% DO, and 0.42% agar concentration. Under optimized culture conditions, improvement of BC production and BC yield were experimentally confirmed, which increased 76% and 57%, respectively, compared to BC production and BC yield before optimizing the culture conditions. Copyright (c) 2005 Wiley Periodicals, Inc.

Policosanol fabrication from insect wax and optimization by response surface methodology

PubMed Central

Ma, Jinju; Zhang, Hong

2018-01-01

Background Insect wax is a famous biological resource for the role in economic production in China. Insect wax is a good source of policosanol, which may is a candidate supplement in foodstuff and pharmaceuticals that has important physiological activities. Therefore, this work aims to investigate a high-yield and rapid method for policosanol fabrication from insect wax. Results The conditions for policosanol fabrication were optimized as follows: an oil bath temperature of 112.7°C and reductant dosage of 0.97 g (used for the reduction of 10.00 g of insect wax). The yield of policosanol reached 83.20%, which was 4 times greater than that of existing methods, such as saponification. The total content of policosanol obtained under the optimal conditions reached 87%. In other words, a high yield of policosanol was obtained from insect wax (723.84 mg/g), that was 55 times higher than that generated from beeswax-brown via saponification. The concentrations of metal residues in policosanol were within the limits of the European Union regulations and EFSA stipulation. The LD50 values for oral doses of insect wax and policosanol were both > 5 g/kg. Conclusion Policosanol was fabricated via solvent-free reduction from insect wax using LiAlH4 at a high yield. The fabrication conditions were optimized. Policosanol and insect wax showed high security, which made them potential candidates as supplements in foods, pharmaceuticals and cosmetics. The rapid and high-yield method has great potential for commercial manufacturing of policosanol. PMID:29763430

Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

PubMed

Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

2017-10-01

Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P < .001). Means of software machine-derived values differed significantly from actual PLT yield, 4.72 × 10 11 vs.6.12 × 10 11 , respectively, (P < .001). The following equation was developed to adjust these values: actual PLT yield= 0.221 + (1.254 × theoretical platelet yield). ROC curve model showed an optimal apheresis device software prediction cut-off of 4.65 × 10 11 to obtain a DP, with a sensitivity of 82.2%, specificity of 93.3%, and an area under the curve (AUC) of 0.909. Trima Accel v6.0 software consistently underestimated PLT yields. Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

Changes in rainfed and irrigated crop yield response to climate in the western US

NASA Astrophysics Data System (ADS)

Li, X.; Troy, T. J.

2018-06-01

As the global population increases and the climate changes, ensuring a secure food supply is increasingly important. One strategy is irrigation, which allows for crops to be grown outside their optimal climate growing regions and which buffers against climate variability. Although irrigation is a positive climate adaptation mechanism for agriculture, it has a potentially negative effect on water resources as it can lead to groundwater depletion and diminished surface water supplies. This study quantifies how crop yields are affected by climate variability and extremes and the impact of irrigation on crop yield increases under various growing-season climate conditions. To do this, we use historical climate data and county-level rainfed and irrigated crop yields for maize, soybean, winter and spring wheat over the US to analyze the relationship between climate, crop yields, and irrigation. We find that there are optimal climates, specific to each crop, where irrigation provides a benefit and other conditions where irrigation proves to have marginal, if any, benefits. Furthermore, the relationship between crop yields and climate has changed over the last decades, with a changing sensitivity in the relationship of soybean and winter wheat yields to certain climate variables, like crop reference evapotranspiration. These two conclusions have important implications for agricultural and water resource system planning, as it implies there are more optimal climate conditions where irrigation is particularly productive and regions where irrigation should be reconsidered as there is not a significant agricultural benefit and the water could be used more productively.

WAMA: a method of optimizing reticle/die placement to increase litho cell productivity

NASA Astrophysics Data System (ADS)

Dor, Amos; Schwarz, Yoram

2005-05-01

This paper focuses on reticle/field placement methodology issues, the disadvantages of typical methods used in the industry, and the innovative way that the WAMA software solution achieves optimized placement. Typical wafer placement methodologies used in the semiconductor industry considers a very limited number of parameters, like placing the maximum amount of die on the wafer circle and manually modifying die placement to minimize edge yield degradation. This paper describes how WAMA software takes into account process characteristics, manufacturing constraints and business objectives to optimize placement for maximum stepper productivity and maximum good die (yield) on the wafer.

Enhanced production of medicinal polysaccharide by submerged fermentation of Lingzhi or Reishi medicinal mushroom Ganoderma lucidium (W.Curt.:Fr.) P. Karst. Using statistical and evolutionary optimization methods.

PubMed

Baskar, Gurunathan; Sathya, Shree Rajesh K

2011-01-01

Statistical and evolutionary optimization of media composition was employed for the production of medicinal exopolysaccharide (EPS) by Lingzhi or Reishi medicinal mushroom Ganoderma lucidium MTCC 1039 using soya bean meal flour as low-cost substrate. Soya bean meal flour, ammonium chloride, glucose, and pH were identified as the most important variables for EPS yield using the two-level Plackett-Burman design and further optimized using the central composite design (CCD) and the artificial neural network (ANN)-linked genetic algorithm (GA). The high value of coefficient of determination of ANN (R² = 0.982) indicates that the ANN model was more accurate than the second-order polynomial model of CCD (R² = 0.91) for representing the effect of media composition on EPS yield. The predicted optimum media composition using ANN-linked GA was soybean meal flour 2.98%, glucose 3.26%, ammonium chloride 0.25%, and initial pH 7.5 for the maximum predicted EPS yield of 1005.55 mg/L. The experimental EPS yield obtained using the predicted optimum media composition was 1012.36 mg/L, which validates the high degree of accuracy of evolutionary optimization for enhanced production of EPS by submerged fermentation of G. lucidium.

Optimal generation of spatially coherent soft X-ray isolated attosecond pulses in a gas-filled waveguide using two-color synthesized laser pulses

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

Jin, Cheng; Hong, Kyung -Han; Lin, C. D.

2016-12-08

Here, we numerically demonstrate the generation of intense, low-divergence soft X-ray isolated attosecond pulses in a gas-filled hollow waveguide using synthesized few-cycle two-color laser waveforms. The waveform is a superposition of a fundamental and its second harmonic optimized such that highest harmonic yields are emitted from each atom. We then optimize the gas pressure and the length and radius of the waveguide such that bright coherent high-order harmonics with angular divergence smaller than 1 mrad are generated, for photon energy from the extreme ultraviolet to soft X-rays. By selecting a proper spectral range enhanced isolated attosecond pulses are generated. Wemore » study how dynamic phase matching caused by the interplay among waveguide mode, neutral atomic dispersion, and plasma effect is achieved at the optimal macroscopic conditions, by performing time-frequency analysis and by analyzing the evolution of the driving laser’s electric field during the propagation. Our results, when combined with the on-going push of high-repetition-rate lasers (sub- to few MHz’s) may eventually lead to the generation of high-flux, low-divergence soft X-ray tabletop isolated attosecond pulses for applications.« less

Robust Group Sparse Beamforming for Multicast Green Cloud-RAN With Imperfect CSI

NASA Astrophysics Data System (ADS)

Shi, Yuanming; Zhang, Jun; Letaief, Khaled B.

2015-09-01

In this paper, we investigate the network power minimization problem for the multicast cloud radio access network (Cloud-RAN) with imperfect channel state information (CSI). The key observation is that network power minimization can be achieved by adaptively selecting active remote radio heads (RRHs) via controlling the group-sparsity structure of the beamforming vector. However, this yields a non-convex combinatorial optimization problem, for which we propose a three-stage robust group sparse beamforming algorithm. In the first stage, a quadratic variational formulation of the weighted mixed l1/l2-norm is proposed to induce the group-sparsity structure in the aggregated beamforming vector, which indicates those RRHs that can be switched off. A perturbed alternating optimization algorithm is then proposed to solve the resultant non-convex group-sparsity inducing optimization problem by exploiting its convex substructures. In the second stage, we propose a PhaseLift technique based algorithm to solve the feasibility problem with a given active RRH set, which helps determine the active RRHs. Finally, the semidefinite relaxation (SDR) technique is adopted to determine the robust multicast beamformers. Simulation results will demonstrate the convergence of the perturbed alternating optimization algorithm, as well as, the effectiveness of the proposed algorithm to minimize the network power consumption for multicast Cloud-RAN.

Optimal planning for the sustainable utilization of municipal solid waste.

PubMed

Santibañez-Aguilar, José Ezequiel; Ponce-Ortega, José María; Betzabe González-Campos, J; Serna-González, Medardo; El-Halwagi, Mahmoud M

2013-12-01

The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimization of waste combinations during in-vessel composting of agricultural waste.

PubMed

Varma, V Sudharsan; Kalamdhad, Ajay S; Kumar, Bimlesh

2017-01-01

In-vessel composting of agricultural waste is a well-described approach for stabilization of compost within a short time period. Although composting studies have shown the different combinations of waste materials for producing good quality compost, studies of the particular ratio of the waste materials in the mix are still limited. In the present study, composting was conducted with a combination of vegetable waste, cow dung, sawdust and dry leaves using a 550 L rotary drum composter. Application of a radial basis functional neural network was used to simulate the composting process. The model utilizes physico-chemical parameters with different waste materials as input variables and three output variables: volatile solids, soluble biochemical oxygen demand and carbon dioxide evolution. For the selected model, the coefficient of determination reached the high value of 0.997. The complicated interaction of agricultural waste components during composting makes it a nonlinear problem so it is difficult to find the optimal waste combinations for producing quality compost. Optimization of a trained radial basis functional model has yielded the optimal proportion as 62 kg, 17 kg and 9 kg for vegetable waste, cow dung and sawdust, respectively. The results showed that the predictive radial basis functional model described for drum composting of agricultural waste was well suited for organic matter degradation and can be successfully applied.

Exploring the Pareto frontier using multisexual evolutionary algorithms: an application to a flexible manufacturing problem

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.; Subbu, Raj

2002-12-01

In multi-objective optimization (MOO) problems we need to optimize many possibly conflicting objectives. For instance, in manufacturing planning we might want to minimize the cost and production time while maximizing the product's quality. We propose the use of evolutionary algorithms (EAs) to solve these problems. Solutions are represented as individuals in a population and are assigned scores according to a fitness function that determines their relative quality. Strong solutions are selected for reproduction, and pass their genetic material to the next generation. Weak solutions are removed from the population. The fitness function evaluates each solution and returns a related score. In MOO problems, this fitness function is vector-valued, i.e. it returns a value for each objective. Therefore, instead of a global optimum, we try to find the Pareto-optimal or non-dominated frontier. We use multi-sexual EAs with as many genders as optimization criteria. We have created new crossover and gender assignment functions, and experimented with various parameters to determine the best setting (yielding the highest number of non-dominated solutions.) These experiments are conducted using a variety of fitness functions, and the algorithms are later evaluated on a flexible manufacturing problem with total cost and time minimization objectives.

Atomic mass measurements with radioactive beams and/or targets: Where to start

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

Haustein, P.E.

1989-01-01

Radioactive beams or radioactive targets (or both) can significantly increase the yields of exotic isotopes, allowing studies to be performed in regions which are currently inaccessible. An important goal to pursue with these exotic species is a broad program of nuclidic mass measurements. This is motivated by the observation that mass model predictions generally diverge from one another in regions far from beta-decay stability where well measured masses are sparse or nonexistent. Stringent tests of mass models are therefore possible and these can highlight important features in the mass models that affect the quality of their short-range and long-range extrapolationmore » properties. Selection of systems to study can be guided, in part, by a desire to probe those regions where distinctions among mass models are most apparent and where exotic isotope yields will be optimal. Several examples will be presented to highlight future opportunities in this area. 10 refs., 5 figs.« less

Continuously Tunable Nucleic Acid Hybridization Probes

PubMed Central

Wu, Lucia R.; Wang, J. Sherry; Fang, John Z.; Reiser, Emily; Pinto, Alessandro; Pekker, Irena; Boykin, Richard; Ngouenet, Celine; Webster, Philippa J.; Beechem, Joseph; Zhang, David Yu

2015-01-01

In silico designed nucleic acid probes and primers often fail to achieve favorable specificity and sensitivity tradeoffs on the first try, and iterative empirical sequence-based optimization is needed, particularly in multiplexed assays. Here, we present a novel, on-the-fly method of tuning probe affinity and selectivity via the stoichiometry of auxiliary species, allowing independent and decoupled adjustment of hybridization yield for different probes in multiplexed assays. Using this method, we achieve near-continuous tuning of probe effective free energy (0.03 kcal·mol−1 granularity). As applications, we enforced uniform capture efficiency of 31 DNA molecules (GC content 0% – 100%), maximized signal difference for 11 pairs of single nucleotide variants, and performed tunable hybrid-capture of mRNA from total RNA. Using the Nanostring nCounter platform, we applied stoichiometric tuning to simultaneously adjust yields for a 24-plex assay, and we show multiplexed quantitation of RNA sequences and variants from formalin-fixed, paraffin-embedded samples (FFPE). PMID:26480474

Optimization of extraction process by response surface methodology and preliminary structural analysis of polysaccharides from defatted peanut (Arachis hypogaea) cakes.

PubMed

Song, Yi; Du, Bingjian; Zhou, Ting; Han, Bing; Yu, Fei; Yang, Rui; Hu, Xiaosong; Ni, Yuanying; Li, Quanhong

2011-02-01

In this work, response surface methodology was used to determine optimum conditions for extraction of polysaccharides from defatted peanut cake. A central composite design including independent variables, such as extraction temperature (x(1)), extraction time (x(2)), and ethanol concentration (x(3)) was used. Selected response which evaluates the extraction process was polysaccharide yield, and the second-order model obtained for polysaccharide yield revealed coefficient of determination of 97.81%. The independent variable with the largest effect on response was ethanol concentration (x(3)). The optimum extraction conditions were found to be extraction temperature 48.7°C, extraction time 1.52 h, and ethanol concentration of 61.9% (v/v), respectively. Under these conditions, the extraction efficiency of polysaccharide can increase to 25.89%. The results of structural analysis showed that the main composition of defatted peanut cake polysaccharide was α-galactose. 2010 Elsevier Ltd. All rights reserved.

An Efficient Method for Genomic DNA Extraction from Different Molluscs Species

PubMed Central

Pereira, Jorge C.; Chaves, Raquel; Bastos, Estela; Leitão, Alexandra; Guedes-Pinto, Henrique

2011-01-01

The selection of a DNA extraction method is a critical step when subsequent analysis depends on the DNA quality and quantity. Unlike mammals, for which several capable DNA extraction methods have been developed, for molluscs the availability of optimized genomic DNA extraction protocols is clearly insufficient. Several aspects such as animal physiology, the type (e.g., adductor muscle or gills) or quantity of tissue, can explain the lack of efficiency (quality and yield) in molluscs genomic DNA extraction procedure. In an attempt to overcome these aspects, this work describes an efficient method for molluscs genomic DNA extraction that was tested in several species from different orders: Veneridae, Ostreidae, Anomiidae, Cardiidae (Bivalvia) and Muricidae (Gastropoda), with different weight sample tissues. The isolated DNA was of high molecular weight with high yield and purity, even with reduced quantities of tissue. Moreover, the genomic DNA isolated, demonstrated to be suitable for several downstream molecular techniques, such as PCR sequencing among others. PMID:22174651

Effect of alkaline addition on anaerobic sludge digestion with combined pretreatment of alkaline and high pressure homogenization.

PubMed

Fang, Wei; Zhang, Panyue; Zhang, Guangming; Jin, Shuguang; Li, Dongyi; Zhang, Meixia; Xu, Xiangzhe

2014-09-01

To improve anaerobic digestion efficiency, combination pretreatment of alkaline and high pressure homogenization was applied to pretreat sewage sludge. Effect of alkaline dosage on anaerobic sludge digestion was investigated in detail. SCOD of sludge supernatant significantly increased with the alkaline dosage increase after the combined pretreatment because of sludge disintegration. Organics were significantly degraded after the anaerobic digestion, and the maximal SCOD, TCOD and VS removal was 73.5%, 61.3% and 43.5%, respectively. Cumulative biogas production, methane content in biogas and biogas production rate obviously increased with the alkaline dosage increase. Considering both the biogas production and alkaline dosage, the optimal alkaline dosage was selected as 0.04 mol/L. Relationships between biogas production and sludge disintegration showed that the accumulative biogas was mainly enhanced by the sludge disintegration. The methane yield linearly increased with the DDCOD increase as Methane yield (ml/gVS)=4.66 DDCOD-9.69. Copyright © 2014 Elsevier Ltd. All rights reserved.

Biodiesel synthesis by direct transesterification of microalga Botryococcus braunii with continuous methanol reflux.

PubMed

Hidalgo, Pamela; Ciudad, Gustavo; Schober, Sigurd; Mittelbach, Martin; Navia, Rodrigo

2015-04-01

Direct transesterification of Botryococcus braunii with continuous acyl acceptor reflux was evaluated. This method combines in one step lipid extraction and esterification/transesterification. Fatty acid methyl esters (FAME) synthesis by direct conversion of microalgal biomass was carried out using sulfuric acid as catalyst and methanol as acyl acceptor. In this system, once lipids are extracted, they are contacted with the catalyst and methanol reaching 82%wt of FAME yield. To optimize the reaction conditions, a factorial design using surface response methodology was applied. The effects of catalyst concentration and co-solvent concentration were studied. Hexane was used as co-solvent for increasing lipid extraction performance. The incorporation of hexane in the reaction provoked an increase in FAME yield from 82% (pure methanol) to 95% when a 47%v/v of hexane was incorporated in the reaction. However, the selectivity towards non-saponifiable lipids such as sterols was increased, negatively affecting biodiesel quality. Copyright © 2015 Elsevier Ltd. All rights reserved.

InP Based Ternary And Quaternary Thin Film Structures On Large Areas Grown By LP-MOVPE

NASA Astrophysics Data System (ADS)

Schmitz, D.; Strauch, , G.; Jurgensen, H.; Heyen, M.; Harde, P.

1989-11-01

Using low pressure MOVPE and higher linear flow velocities high purity GalnAs/lnP and GalnAsP heterostructures can be prepared. Excellent homogeneity in thickness, composition, and doping on a 2" InP substrate can be realized by this approach for optimized conditions. The low growth rates required for the deposition of very narrow well structures are achieved by selecting reduced pressures of the group III and group V compounds used for deposition. The method yields structures with high electron mobilities of the two dimensional electron gas in the well and narrow PL (i.e. 2.2 meV for 20 nm wells) line widths, which is indicative of low impurity incorporation and abrupt heterojunctions. The observed energy shifts (up to 528 meV) demonstrate the large range of bandgap variation attainable by this method. A study of dopant incorporation shows, that Zn yields steep transitions in InGaAs.

Optimization of Lipase-Mediated Synthesis of 1-Nonene Oxide Using Phenylacetic Acid and Hydrogen Peroxide

PubMed Central

Abdulmalek, Emilia; Arumugam, Mahashanon; Basri, Mahiran; Rahman, Mohd Basyaruddin Abdul

2012-01-01

Herein, an efficient epoxidation of 1-nonene is described. In a simple epoxidation system, commercially available Novozym 435, an immobilized Candida antarctica lipase B, and hydrogen peroxide (H2O2) were utilized to facilitate the in situ oxidation of phenylacetic acid to the corresponding peroxy acid which then reacted with 1-nonene to give 1-nonene oxide with high yield and selectivity. The aliphatic terminal alkene was epoxidised efficiently in chloroform to give an excellent yield (97%–99%) under the optimum reaction conditions, including temperature (35 °C), initial H2O2 concentration (30%), H2O2 amount (4.4 mmol), H2O2 addition rate (one step), acid amount (8.8 mmol), and stirring speed (250 rpm). Interestingly, the enzyme was stable under the single-step addition of H2O2 with a catalytic activity of 190.0 Ug−1. The entire epoxidation process was carried out within 12 h using a conventional water bath shaker. PMID:23202943

How do I provide leukapheresis products? Blood center experience and evidence for process improvement.

PubMed

Ginzburg, Yelena; Kessler, Debra; Narici, Manlio; Caltabiano, Melinda; Rebosa, Mark; Strauss, Donna; Shaz, Beth

2013-10-01

The past few decades have seen a resurgence of interest in leukapheresis products to improve the survival of infected patients with neutropenia. These products have a short shelf life and require donor stimulation with dexamethasone before collection. Additionally, a system with good communications and logistical support is essential. A recent survey of blood centers in North America revealed that the majority of centers collecting leukapheresis products use steroid-stimulated donors. The survey results suggested that an analysis of the process and potential process improvement would be of interest to the transfusion medicine community. Data from 2008 to 2011 regarding donor selection, donor dexamethasone stimulation, leukapheresis collection, and correlations between potentially pertinent variables for process improvement were analyzed. Results from an analysis of cost are also included. We evaluate 432 leukapheresis donations and demonstrate correlations between 1) pre- and poststimulation white blood cell (WBC) count (p<0.0001), 2) interval (donor stimulation to collection) and poststimulation WBC count (p<0.0001), and 3) poststimulation WBC count and leukapheresis product granulocyte yield (p<0.0001). Significant improvement in granulocyte quality and yield can be accomplished in dexamethasone-stimulated donors, by selecting eligible donors with relatively high normal prestimulation WBC counts and/or previously good responses to dexamethasone, increasing the duration between dexamethasone stimulation and granulocyte collection, and maintaining optimal hematocrit (5%-10%) in granulocyte collections. Because the majority of surveyed blood centers collecting stimulated granulocytes use steroids alone, modifications presented here may prove useful. Further assessment of correlation between granulocyte yield and clinical outcome will await results of additional studies. © 2012 American Association of Blood Banks.

[Studying on purification technology of Resina Draconis phenol extracts based on design space method].

PubMed

Zhang, Jian; Zhang, Xin; Bi, Yu-An; Xu, Gui-Hong; Huang, Wen-Zhe; Wang, Zhen-Zhong; Xiao, Wei

2017-09-01

The "design space" method was used to optimize the purification process of Resina Draconis phenol extracts by using the concept of "quality derived from design" (QbD). The content and transfer rate of laurin B and 7,4'-dihydroxyflavone and yield of extract were selected as the critical quality attributes (CQA). Plackett-Burman design showed that the critical process parameters (CPP) were concentration of alkali, the amount of alkali and the temperature of alkali dissolution. Then the Box-Behnken design was used to establish the mathematical model between CQA and CPP. The variance analysis results showed that the P values of the five models were less than 0.05 and the mismatch values were all greater than 0.05, indicating that the model could well describe the relationship between CQA and CPP. Finally, the control limits of the above 5 indicators (content and transfer rate of laurine B and 7,4'-dihydroxyflavone, as well as the extract yield) were set, and then the probability-based design space was calculated by Monte Carlo simulation and verified. The results of the design space validation showed that the optimized purification method can ensure the stability of the Resina Draconis phenol extracts refining process, which would help to improve the quality uniformity between batches of phenol extracts and provide data support for production automation control. Copyright© by the Chinese Pharmaceutical Association.

Multivariate Approach for Alzheimer's Disease Detection Using Stationary Wavelet Entropy and Predator-Prey Particle Swarm Optimization.

PubMed

Zhang, Yudong; Wang, Shuihua; Sui, Yuxiu; Yang, Ming; Liu, Bin; Cheng, Hong; Sun, Junding; Jia, Wenjuan; Phillips, Preetha; Gorriz, Juan Manuel

2017-07-17

The number of patients with Alzheimer's disease is increasing rapidly every year. Scholars often use computer vision and machine learning methods to develop an automatic diagnosis system. In this study, we developed a novel machine learning system that can make diagnoses automatically from brain magnetic resonance images. First, the brain imaging was processed, including skull stripping and spatial normalization. Second, one axial slice was selected from the volumetric image, and stationary wavelet entropy (SWE) was done to extract the texture features. Third, a single-hidden-layer neural network was used as the classifier. Finally, a predator-prey particle swarm optimization was proposed to train the weights and biases of the classifier. Our method used 4-level decomposition and yielded 13 SWE features. The classification yielded an overall accuracy of 92.73±1.03%, a sensitivity of 92.69±1.29%, and a specificity of 92.78±1.51%. The area under the curve is 0.95±0.02. Additionally, this method only cost 0.88 s to identify a subject in online stage, after its volumetric image is preprocessed. In terms of classification performance, our method performs better than 10 state-of-the-art approaches and the performance of human observers. Therefore, this proposed method is effective in the detection of Alzheimer's disease.

Screening of Pro-Asp Sequences Exposed on Bacteriophage M13 as an Ideal Anchor for Gold Nanocubes.

PubMed

Lee, Hwa Kyoung; Lee, Yujean; Kim, Hyori; Lee, Hye-Eun; Chang, Hyejin; Nam, Ki Tae; Jeong, Dae Hong; Chung, Junho

2017-09-15

Bacteriophages are thought to be ideal vehicles for linking antibodies to nanoparticles. Here, we define the sequence of peptides exposed as a fusion protein on M13 bacteriophages to yield optimal binding of gold nanocubes and efficient bacteriophage amplification. We generated five helper bacteriophage libraries using AE(X) 2 DP, AE(X) 3 DP, AE(X) 4 DP, AE(X) 5 DP, and AE(X) 6 DP as the exposed portion of pVIII, in which X was a randomized amino acid residue encoded by the nucleotide sequence NNK. Efficient phage amplification was achievable only in the AE(X) 2 DP, AE(X) 3 DP, and AE(X) 4 DP libraries. Through biopanning with gold nanocubes, we enriched the phage clones and selected the clone with the highest fold change after enrichment. This clone displayed Pro-Asp on the surface of the bacteriophage and had amplification yields similar to those of the wild-type helper bacteriophage (VCSM13). The clone displayed even binding of gold nanocubes along its length and minimal aggregation after binding. We conclude that, for efficient amplification, the exposed pVIII amino acid length should be limited to six residues and Ala-Glu-Pro-Asp-Asp-Pro (AEPDDP) is the ideal fusion protein sequence for guaranteeing the optimal formation of a complex with gold nanocubes.

Optimization of analytical parameters for inferring relationships among Escherichia coli isolates from repetitive-element PCR by maximizing correspondence with multilocus sequence typing data.

PubMed

Goldberg, Tony L; Gillespie, Thomas R; Singer, Randall S

2006-09-01

Repetitive-element PCR (rep-PCR) is a method for genotyping bacteria based on the selective amplification of repetitive genetic elements dispersed throughout bacterial chromosomes. The method has great potential for large-scale epidemiological studies because of its speed and simplicity; however, objective guidelines for inferring relationships among bacterial isolates from rep-PCR data are lacking. We used multilocus sequence typing (MLST) as a "gold standard" to optimize the analytical parameters for inferring relationships among Escherichia coli isolates from rep-PCR data. We chose 12 isolates from a large database to represent a wide range of pairwise genetic distances, based on the initial evaluation of their rep-PCR fingerprints. We conducted MLST with these same isolates and systematically varied the analytical parameters to maximize the correspondence between the relationships inferred from rep-PCR and those inferred from MLST. Methods that compared the shapes of densitometric profiles ("curve-based" methods) yielded consistently higher correspondence values between data types than did methods that calculated indices of similarity based on shared and different bands (maximum correspondences of 84.5% and 80.3%, respectively). Curve-based methods were also markedly more robust in accommodating variations in user-specified analytical parameter values than were "band-sharing coefficient" methods, and they enhanced the reproducibility of rep-PCR. Phylogenetic analyses of rep-PCR data yielded trees with high topological correspondence to trees based on MLST and high statistical support for major clades. These results indicate that rep-PCR yields accurate information for inferring relationships among E. coli isolates and that accuracy can be enhanced with the use of analytical methods that consider the shapes of densitometric profiles.

Optimization of the extraction of the p-menthadienol isomers and aristolone contained in the essential oil from Elyonurus hensii using a 23 full factorial design.

PubMed

Loumouamou, Aubin Nestor; Bikindou, Kévin; Bitemou, Ernest; Chalard, Pierre; Silou, Thomas; Figueredo, Gilles

2017-05-01

The aim of this study was to optimize the extraction of p -menthadienol isomers and aristolone from the essential oil of Elyonurus hensii by hydrodistillation. The study of the seasonal variation in the chemical composition has shown that the plant material has been subject to a natural selection regarding the biosynthesis of the p -menthadienol isomers: during periods of water stress, the extracts are rich in cis and trans-p -mentha-1(7),8-dien-2-ol and poor in cis and trans-p -mentha-2,8-dien-1-ol. Regarding the modeling, eight experiments were carried out by considering three easily interpretable factors (the extraction duration, the residual water content and the state of the division of the plant material). The average yield was 1.33% for the aerial part and 0.74% for the roots. The residual water content is the most important factor, which significantly influences the average yield of the essential oil and the content of the major constituents. Regarding the aerial part, a low residual water content of the plant material varies the essential oil yield (from 0.40% to 2.11%) and the content of cis and trans - p -mentha-2.8-dien-1-ol (from 15.87% to 23.24%). At the root level, the samples that have a very low residual water content provide extracts richer in aristolone. The combined effects of the extraction duration, the state of division, and the residual water content influence greatly the extraction of aristolone (from 36.68% to 54.55%). However, these interactions are more complex and difficult to assess.

Automatic yield-line analysis of slabs using discontinuity layout optimization

PubMed Central

Gilbert, Matthew; He, Linwei; Smith, Colin C.; Le, Canh V.

2014-01-01

The yield-line method of analysis is a long established and extremely effective means of estimating the maximum load sustainable by a slab or plate. However, although numerous attempts to automate the process of directly identifying the critical pattern of yield-lines have been made over the past few decades, to date none has proved capable of reliably analysing slabs of arbitrary geometry. Here, it is demonstrated that the discontinuity layout optimization (DLO) procedure can successfully be applied to such problems. The procedure involves discretization of the problem using nodes inter-connected by potential yield-line discontinuities, with the critical layout of these then identified using linear programming. The procedure is applied to various benchmark problems, demonstrating that highly accurate solutions can be obtained, and showing that DLO provides a truly systematic means of directly and reliably automatically identifying yield-line patterns. Finally, since the critical yield-line patterns for many problems are found to be quite complex in form, a means of automatically simplifying these is presented. PMID:25104905

Lactation persistency as a component trait of the selection index and increase in reliability by using single nucleotide polymorphism in net merit defined as the first five lactation milk yields and herd life.

PubMed

Togashi, K; Hagiya, K; Osawa, T; Nakanishi, T; Yamazaki, T; Nagamine, Y; Lin, C Y; Matsumoto, S; Aihara, M; Hayasaka, K

2012-08-01

We first sought to clarify the effects of discounted rate, survival rate, and lactation persistency as a component trait of the selection index on net merit, defined as the first five lactation milks and herd life (HL) weighted by 1 and 0.389 (currently used in Japan), respectively, in units of genetic standard deviation. Survival rate increased the relative economic importance of later lactation traits and the first five lactation milk yields during the first 120 months from the start of the breeding scheme. In contrast, reliabilities of the estimated breeding value (EBV) in later lactation traits are lower than those of earlier lactation traits. We then sought to clarify the effects of applying single nucleotide polymorphism (SNP) on net merit to improve the reliability of EBV of later lactation traits to maximize their increased economic importance due to increase in survival rate. Net merit, selection accuracy, and HL increased by adding lactation persistency to the selection index whose component traits were only milk yields. Lactation persistency of the second and (especially) third parities contributed to increasing HL while maintaining the first five lactation milk yields compared with the selection index whose only component traits were milk yields. A selection index comprising the first three lactation milk yields and persistency accounted for 99.4% of net merit derived from a selection index whose components were identical to those for net merit. We consider that the selection index comprising the first three lactation milk yields and persistency is a practical method for increasing lifetime milk yield in the absence of data regarding HL. Applying SNP to the second- and third-lactation traits and HL increased net merit and HL by maximizing the increased economic importance of later lactation traits, reducing the effect of first-lactation milk yield on HL (genetic correlation (rG) = -0.006), and by augmenting the effects of the second- and third-lactation milk yields on HL (rG = 0.118 and 0.257, respectively).

Direct and correlated responses to selection for milk yield: results and conclusions of regional project NC-2, "improvement of dairy cattle through breeding, with emphasis on selection". NC-2 Technical Committee.

PubMed

Kelm, S C; Freeman, A E

2000-12-01

Measurement of direct and correlated responses to single-trait selection for milk yield was the major objective of regional project NC-2. The NC-2 Technical Committee included representatives from Alaska, Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Nebraska, South Dakota, Wisconsin, and the USDA. All representatives, except Illinois, Kansas and Nebraska, maintained a selection line formed by using AI sires selected for high estimated transmitting abilities for milk and a second line that served as some type of a control. Stations varied in criteria for selection of bulls for control lines. Farms were managed similarly, including feeding and management of selection and control lines as one herd, random mating within line, and restricted culling policies. Selection for milk yield effectively increased milk production. All selection lines increased milk and net income per lactation more than control lines. Realized gains matched or exceeded gains expected from estimates of breeding values. Yields of milk components increased, but component percentages decreased appreciably for selection lines. Reproduction of nulliparous animals was not affected, but days open for lactating selection cows increased in some of the individual projects. Selected cows tended to have larger health costs, specifically for mammary treatment. Udder and conformation traits did not deteriorate for selection lines, although control lines with selection of sires on genetic evaluations for type received higher type scores. There should be few reservations about undesirable responses correlated with selection for milk yield.

Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe

2016-11-01

Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately.

Efficacy outcome selection in the therapeutic hypothermia after pediatric cardiac arrest trials.

PubMed

Holubkov, Richard; Clark, Amy E; Moler, Frank W; Slomine, Beth S; Christensen, James R; Silverstein, Faye S; Meert, Kathleen L; Pollack, Murray M; Dean, J Michael

2015-01-01

The Therapeutic Hypothermia After Pediatric Cardiac Arrest trials will determine whether therapeutic hypothermia improves survival with good neurobehavioral outcome, as assessed by the Vineland Adaptive Behavior Scales Second Edition, in children resuscitated after cardiac arrest in the in-hospital and out-of-hospital settings. We describe the innovative efficacy outcome selection process during Therapeutic Hypothermia After Pediatric Cardiac Arrest protocol development. Consensus assessment of potential outcomes and evaluation timepoints. None. We evaluated practical and technical advantages of several follow-up timepoints and continuous/categorical outcome variants. Simulations estimated power assuming varying hypothermia benefit on mortality and on neurobehavioral function among survivors. Twelve months after arrest was selected as the optimal assessment timepoint for pragmatic and clinical reasons. Change in Vineland Adaptive Behavior Scales Second Edition from prearrest level, measured as quasicontinuous with death and vegetative status being worst-possible levels, yielded optimal statistical power. However, clinicians preferred simpler multicategorical or binary outcomes because of easier interpretability and favored outcomes based solely on postarrest status because of concerns about accurate parental assessment of prearrest status and differing clinical impact of a given Vineland Adaptive Behavior Scales Second Edition change depending on prearrest status. Simulations found only modest power loss from categorizing or dichotomizing quasicontinuous outcomes because of high expected mortality. The primary outcome selected was survival with 12-month Vineland Adaptive Behavior Scales Second Edition no less than two SD below a reference population mean (70 points), necessarily evaluated only among children with prearrest Vineland Adaptive Behavior Scales Second Edition greater than or equal to 70. Two secondary efficacy outcomes, 12-month survival and quasicontinuous Vineland Adaptive Behavior Scales Second Edition change from prearrest level, will be evaluated among all randomized children, including those with compromised function prearrest. Extensive discussion of optimal efficacy assessment timing, and of the advantages versus drawbacks of incorporating prearrest status and using quasicontinuous versus simpler outcomes, was highly beneficial to the final Therapeutic Hypothermia After Pediatric Cardiac Arrest design. A relatively simple, binary primary outcome evaluated at 12 months was selected, with two secondary outcomes that address the potential disadvantages of primary outcome.

Enhancing crop yield with the use of N-based fertilizers co-applied with plant hormones or growth regulators.

PubMed

Zaman, Mohammad; Kurepin, Leonid V; Catto, Warwick; Pharis, Richard P

2015-07-01

Crop yield, vegetative or reproductive, depends on access to an adequate supply of essential mineral nutrients. At the same time, a crop plant's growth and development, and thus yield, also depend on in situ production of plant hormones. Thus optimizing mineral nutrition and providing supplemental hormones are two mechanisms for gaining appreciable yield increases. Optimizing the mineral nutrient supply is a common and accepted agricultural practice, but the co-application of nitrogen-based fertilizers with plant hormones or plant growth regulators is relatively uncommon. Our review discusses possible uses of plant hormones (gibberellins, auxins, cytokinins, abscisic acid and ethylene) and specific growth regulators (glycine betaine and polyamines) to enhance and optimize crop yield when co-applied with nitrogen-based fertilizers. We conclude that use of growth-active gibberellins, together with a nitrogen-based fertilizer, can result in appreciable and significant additive increases in shoot dry biomass of crops, including forage crops growing under low-temperature conditions. There may also be a potential for use of an auxin or cytokinin, together with a nitrogen-based fertilizer, for obtaining additive increases in dry shoot biomass and/or reproductive yield. Further research, though, is needed to determine the potential of co-application of nitrogen-based fertilizers with abscisic acid, ethylene and other growth regulators. © 2014 Society of Chemical Industry.

Antitumor Agents. 272. Structure–Activity Relationships and In Vivo Selective Anti-Breast Cancer Activity of Novel Neo-tanshinlactone Analogs

PubMed Central

Dong, Yizhou; Shi, Qian; Pai, Huei-Chen; Peng, Chieh-Yu; Pan, Shiow-Lin; Teng, Che-Ming; Nakagawa-Goto, Kyoko; Yu, Donglei; Liu, Yi-Nan; Wu, Pei-Chi; Bastow, Kenneth F.; Morris-Natschke, Susan L.; Brossi, Arnold; Lang, Jing-Yu; Hsu, Jennifer L.; Hung, Mien-Chie; Lee, Eva Y.-H. P.; Lee, Kuo-Hsiung

2010-01-01

Neo-tanshinlactone (1) and its previously reported analogs, such as 2, are potent and selective in vitro anti-breast cancer agents. The synthetic pathway to 2 was optimized from seven to five steps, with a better overall yield. Structure–activity relationships studies on these compounds revealed some key molecular determinants for this family of anti-breast agents. Several derivatives (19-21 and 24) exerted potent and selective anti-breast cancer activity with IC50 values of 0.3, 0.2, 0.1 and 0.1 μg/mL, respectively, against the ZR-75-1 cell lines. Compound 24 was two- to three-fold more potent than 1 against SK-BR-3 and ZR-75-1. Importantly, 21 exhibited high selectivity; it was 23 times more active against ZR-75-1 than MCF-7. Compound 20 had an approximately 12-fold ratio of SK-BR-3/MCF-7 selectivity. In addition, analog 2 showed potent activity against a ZR-75-1 xenograft model, but not PC-3 and MDA-MB-231 xenografts, as well as high selectivity against breast cancer cell line compared with normal breast tissue-derived cell lines. Further development of lead compounds 19-21 and 24 as clinical trial candidates is warranted. PMID:20148565

Cross-validation pitfalls when selecting and assessing regression and classification models.

PubMed

Krstajic, Damjan; Buturovic, Ljubomir J; Leahy, David E; Thomas, Simon

2014-03-29

We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. A key operational component of the proposed methods is cloud computing which enables routine use of previously infeasible approaches. We describe in detail an algorithm for repeated grid-search V-fold cross-validation for parameter tuning in classification and regression, and we define a repeated nested cross-validation algorithm for model assessment. As regards variable selection and parameter tuning we define two algorithms (repeated grid-search cross-validation and double cross-validation), and provide arguments for using the repeated grid-search in the general case. We show results of our algorithms on seven QSAR datasets. The variation of the prediction performance, which is the result of choosing different splits of the dataset in V-fold cross-validation, needs to be taken into account when selecting and assessing classification and regression models. We demonstrate the importance of repeating cross-validation when selecting an optimal model, as well as the importance of repeating nested cross-validation when assessing a prediction error.

Climate change and maize yield in southern Africa: what can farm management do?

PubMed

Rurinda, Jairos; van Wijk, Mark T; Mapfumo, Paul; Descheemaeker, Katrien; Supit, Iwan; Giller, Ken E

2015-12-01

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid-December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010-2039 and 2040-2069 and by 20% for 2070-2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070-2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change. © 2015 John Wiley & Sons Ltd.

Optimization of laccase production from Marasmiellus palmivorus LA1 by Taguchi method of Design of experiments.

PubMed

Chenthamarakshan, Aiswarya; Parambayil, Nayana; Miziriya, Nafeesathul; Soumya, P S; Lakshmi, M S Kiran; Ramgopal, Anala; Dileep, Anuja; Nambisan, Padma

2017-02-13

Fungal laccase has profound applications in different fields of biotechnology due to its broad specificity and high redox potential. Any successful application of the enzyme requires large scale production. As laccase production is highly dependent on medium components and cultural conditions, optimization of the same is essential for efficient product production. Production of laccase by fungal strain Marasmiellus palmivorus LA1 under solid state fermentation was optimized by the Taguchi design of experiments (DOE) methodology. An orthogonal array (L8) was designed using Qualitek-4 software to study the interactions and relative influence of the seven selected factors by one factor at a time approach. The optimum condition formulated was temperature (28 °C), pH (5), galactose (0.8%w/v), cupric sulphate (3 mM), inoculum concentration (number of mycelial agar pieces) (6Nos.) and substrate length (0.05 m). Overall yield increase of 17.6 fold was obtained after optimization. Statistical optimization leads to the elimination of an insignificant medium component ammonium dihydrogen phosphate from the process and contributes to a 1.06 fold increase in enzyme production. A final production of 667.4 ± 13 IU/mL laccase activity paves way for the application of this strain for industrial applications. Study optimized lignin degrading laccases from Marasmiellus palmivorus LA1. This laccases can thus be used for further applications in different scales of production after analyzing the properties of the enzyme. Study also confirmed the use of taguchi method for optimizations of product production.

Transparent ceramic garnet scintillator optimization via composition and co-doping for high-energy resolution gamma spectrometers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cherepy, Nerine J.; Payne, Stephen A.; Seeley, Zachary M.; Beck, Patrick R.; Swanberg, Erik L.; Hunter, Steven L.

2016-09-01

Breakthrough energy resolution, R(662keV) <4%, has been achieved with an oxide scintillator, Cerium-doped Gadolinium Yttrium Gallium Aluminum Garnet, or GYGAG(Ce), by optimizing fabrication conditions. Here we describe the dependence of scintillation light yield and energy resolution on several variables: (1) Stoichiometry, in particular Gd/Y and Ga/Al ratios which modify the bandgap energy, (2) Processing methods, including vacuum vs. oxygen sintering, and (3) Trace co-dopants that influence the formation of Ce4+ and modify the intra-bandgap trap distribution. To learn about how chemical composition influences the scintillation properties of transparent ceramic garnet scintillators, we have measured: scintillation decay component amplitudes; intensity and duration of afterglow; thermoluminescence glow curve peak positions and amplitudes; integrated light yield; light yield non-proportionality, as measured in the Scintillator Light Yield Non-Proportionality Characterization Instrument (SLYNCI); and energy resolution for gamma spectroscopy. Optimized GYGAG(Ce) provides R(662 keV) =3.0%, for 0.05 cm3 size ceramics with Silicon photodiode readout, and R(662 keV) =4.6%, at 2 in3 size with PMT readout.

Maximizing RNA yield from archival renal tumors and optimizing gene expression analysis.

PubMed

Glenn, Sean T; Head, Karen L; Teh, Bin T; Gross, Kenneth W; Kim, Hyung L

2010-01-01

Formalin-fixed, paraffin-embedded tissues are widely available for gene expression analysis using TaqMan PCR. Five methods, including 4 commercial kits, for recovering RNA from paraffin-embedded renal tumor tissue were compared. The MasterPure kit from Epicentre produced the highest RNA yield. However, the difference in RNA yield between the kit from Epicenter and Invitrogen's TRIzol method was not significant. Using the top 3 RNA isolation methods, the manufacturers' protocols were modified to include an overnight Proteinase K digestion. Overnight protein digestion resulted in a significant increase in RNA yield. To optimize the reverse transcription reaction, conventional reverse transcription with random oligonucleotide primers was compared to reverse transcription using primers specific for genes of interest. Reverse transcription using gene-specific primers significantly increased the quantity of cDNA detectable by TaqMan PCR. Therefore, expression profiling of formalin-fixed, paraffin-embedded tissue using TaqMan qPCR can be optimized by using the MasterPure RNA isolation kit modified to include an overnight Proteinase K digestion and gene-specific primers during the reverse transcription.

Pyrolysis of low density polyethylene waste in subcritical water optimized by response surface methodology.

PubMed

Wong, S L; Ngadi, N; Amin, N A S; Abdullah, T A T; Inuwa, I M

2016-01-01

Pyrolysis of low density polyethylene (LDPE) waste from local waste separation company in subcritical water was conducted to investigate the effect of reaction time, temperature, as well as the mass ratio of water to polymer on the liquid yield. The data obtained from the study were used to optimize the liquid yield using response surface methodology. The range of reaction temperature used was 162-338°C, while the reaction time ranged from 37 min to 143 min, and the ratio of water to polymer ranged from 1.9 to 7.1. It was found that pyrolysis of LDPE waste in subcritical water produced hydrogen, methane, carbon monoxide and carbon dioxide, while the liquid product contained alkanes and alkenes with 10-50 carbons atoms, as well as heptadecanone, dichloroacetic acid and heptadecyl ester. The optimized conditions were 152.3°C, reaction time of 1.2 min and ratio of water solution to polymer of 32.7, with the optimum liquid yield of 13.6 wt% and gases yield of 2.6 wt%.

Deficit irrigation effects on yield and yield components of grain sorghum

USDA-ARS?s Scientific Manuscript database

Development of sustainable and efficient irrigation strategies is a priority for producers faced with water shortages. A promising management strategy for improving water use efficiency (WUE) is managed deficit irrigation (MDI), which attempts to optimize yield and WUE by synchronizing crop water u...

Measurement of Moisture Sorption Isotherm by DVS Hydrosorb

NASA Astrophysics Data System (ADS)

Kurniawan, Y. R.; Purwanto, Y. A.; Purwanti, N.; Budijanto, S.

2018-05-01

Artificial rice made from corn flour, sago, glycerol monostearate, vegetable oil, water and jelly powder was developed by extrusion method through the process stages of material mixing, extrusion, drying, packaging and storage. Sorption isotherm pattern information on food ingredients used to design and optimize the drying process, packaging, storage. Sorption isotherm of water of artificial rice was measured using humidity generating method with Dynamic Vapor Sorption device that has an advantage of equilibration time is about 10 to 100 times faster than saturated salt slurry method. Relative humidity modification technique are controlled automatically by adjusting the proportion of mixture of dry air and water saturated air. This paper aims to develop moisture sorption isotherm using the Hydrosorb 1000 Water Vapor Sorption Analyzer. Sample preparation was conducted by degassing sample in a heating mantle of 65°C. Analysis parameters need to be fulfilled were determination of Po, sample data, selection of water activity points, and equilibrium conditions. The selected analytical temperatures were 30°C and 45°C. Analysis lasted for 45 hours and curves of adsorption and desorption were obtained. Selected bottom point of water activity 0.05 at 30°C and 45°C yielded adsorbed mass of 0.1466 mg/g and 0.3455 mg/g, respectively, whereas selected top water activity point 0.95 at 30°C and 45°C yielded adsorbed mass of 190.8734 mg/g and 242.4161mg/g, respectively. Moisture sorption isotherm measurements of articial rice made from corn flour at temperature of 30°C and 45°C using Hydrosorb showed that the moisture sorption curve approximates sigmoid-shaped type II curve commonly found in corn-based foodstuffs (high- carbohydrate).

[Studies on extraction process of the main saponin constituents from the stem bark of Kalopanax septemlobus in Guangxi].

PubMed

Yang, Yue; Yang, Xin-ping; Liu, Xiao-fu; Jiang, Xiao-jun

2009-09-01

Using orthogonal experiment design, the total saponin constituents were obtained by refluxing extraction with alcohol and separated by macroporous adsorption resin and n-Butyl alcohol from the stem bark of Kalopanax septemlobus. According to the purity analysis and the yield, the extraction process was optimized. The results showed that the main saponin constituents were gained with a yield of 1.32% by using macroporous adsorption resin but 1.05% by using n-Butyl alcohol. The former was more efficient than the latter on both yield and color. The optimal process with isolation by macroporous adsorption resin is cheap, simple and practical.

Highly efficient and selective pressure-assisted photon-induced polymerization of styrene

NASA Astrophysics Data System (ADS)

Guan, Jiwen; Song, Yang

2016-06-01

The polymerization process of condensed styrene to produce polystyrene as an industrially important polymeric material was investigated using a novel approach by combining external compression with ultraviolet radiation. The reaction evolution was monitored as a function of time and the reaction products were characterized by in situ Fourier transform infrared spectroscopy. By optimizing the loading pressures, we observed highly efficient and selective production of polystyrene of different tacticities. Specifically, at relatively low loading pressures, infrared spectra suggest that styrene monomers transform to amorphous atactic polystyrene (APS) with minor crystalline isotactic polystyrene. In contrast, APS was found to be the sole product when polymerization occurs at relatively higher loading pressures. The time-dependent reaction profiles allow the examination of the polymerization kinetics by analyzing the rate constant and activation volume as a function of pressure. As a result, an optimized pressure condition, which allows a barrierless reaction to proceed, was identified and attributed to the very desirable reaction yield and kinetics. Finally, the photoinitiated reaction mechanism and the growth geometry of the polymer chains were investigated from the energy diagram of styrene and by the topology analysis of the crystal styrene. This study shows strong promise to produce functional polymeric materials in a highly efficient and controlled manner.

Optimization of municipal sludge and grease co-digestion using disintegration technologies.

PubMed

Bouchy, L; Pérez, A; Camacho, P; Rubio, P; Silvestre, G; Fernández, B; Cano, R; Polanco, M; Díaz, N

2012-01-01

Many drivers tend to foster the development of renewable energy production in wastewater treatment plants as many expectations rely upon energy recovery from sewage sludge, for example through biogas use. This paper is focused on the assessment of grease waste (GW) as an adequate substrate for co-digestion with municipal sludge, as it has a methane potential of 479-710 LCH(4)/kg VS, as well as the evaluation of disintegration technologies as a method to optimize the co-digestion process. With this objective three different pre-treatments have been selected for evaluation: thermal hydrolysis, ultrasound and enzymatic treatment. Results have shown that co-digestion processes without pre-treatment had a maximum increment of 128% of the volumetric methane productivity when GW addition was 23% inlet (at 20 days of HRT and with an OLR of 3.0 kg COD/m(3)d), compared with conventional digestion of sewage sludge alone. Concerning the application of the selected disintegration technologies, all pre-treatments showed improvements in terms of methane yield (51.8, 89.5 and 57.6% more for thermal hydrolysis, ultrasound and enzymatic treatment, respectively, compared with non-pretreated wastes), thermal hydrolysis of GW and secondary sludge being the best configuration as it improved the solubilization of the organic matter and the hydrodynamic characteristics of digestates.

Levelized cost of energy (LCOE) metric to characterize solar absorber coatings for the CSP industry

DOE PAGES

Boubault, Antoine; Ho, Clifford K.; Hall, Aaron; ...

2015-07-08

The contribution of each component of a power generation plant to the levelized cost of energy (LCOE) can be estimated and used to increase the power output while reducing system operation and maintenance costs. The LCOE is used in order to quantify solar receiver coating influence on the LCOE of solar power towers. Two new parameters are introduced: the absolute levelized cost of coating (LCOC) and the LCOC efficiency. Depending on the material properties, aging, costs, and temperature, the absolute LCOC enables quantifying the cost-effectiveness of absorber coatings, as well as finding optimal operating conditions. The absolute LCOC is investigatedmore » for different hypothetic coatings and is demonstrated on Pyromark 2500 paint. Results show that absorber coatings yield lower LCOE values in most cases, even at significant costs. Optimal reapplication intervals range from one to five years. At receiver temperatures greater than 700 °C, non-selective coatings are not always worthwhile while durable selective coatings consistently reduce the LCOE—up to 12% of the value obtained for an uncoated receiver. Moreover the absolute LCOC is a powerful tool to characterize and compare different coatings, not only considering their initial efficiencies but also including their durability.« less

Optimizing Vowel Formant Measurements in Four Acoustic Analysis Systems for Diverse Speaker Groups

PubMed Central

Derdemezis, Ekaterini; Kent, Ray D.; Fourakis, Marios; Reinicke, Emily L.; Bolt, Daniel M.

2016-01-01

Purpose This study systematically assessed the effects of select linear predictive coding (LPC) analysis parameter manipulations on vowel formant measurements for diverse speaker groups using 4 trademarked Speech Acoustic Analysis Software Packages (SAASPs): CSL, Praat, TF32, and WaveSurfer. Method Productions of 4 words containing the corner vowels were recorded from 4 speaker groups with typical development (male and female adults and male and female children) and 4 speaker groups with Down syndrome (male and female adults and male and female children). Formant frequencies were determined from manual measurements using a consensus analysis procedure to establish formant reference values, and from the 4 SAASPs (using both the default analysis parameters and with adjustments or manipulations to select parameters). Smaller differences between values obtained from the SAASPs and the consensus analysis implied more optimal analysis parameter settings. Results Manipulations of default analysis parameters in CSL, Praat, and TF32 yielded more accurate formant measurements, though the benefit was not uniform across speaker groups and formants. In WaveSurfer, manipulations did not improve formant measurements. Conclusions The effects of analysis parameter manipulations on accuracy of formant-frequency measurements varied by SAASP, speaker group, and formant. The information from this study helps to guide clinical and research applications of SAASPs. PMID:26501214

Bayesian Optimal Interval Design: A Simple and Well-Performing Design for Phase I Oncology Trials

PubMed Central

Yuan, Ying; Hess, Kenneth R.; Hilsenbeck, Susan G.; Gilbert, Mark R.

2016-01-01

Despite more than two decades of publications that offer more innovative model-based designs, the classical 3+3 design remains the most dominant phase I trial design in practice. In this article, we introduce a new trial design, the Bayesian optimal interval (BOIN) design. The BOIN design is easy to implement in a way similar to the 3+3 design, but is more flexible for choosing the target toxicity rate and cohort size and yields a substantially better performance that is comparable to that of more complex model-based designs. The BOIN design contains the 3+3 design and the accelerated titration design as special cases, thus linking it to established phase I approaches. A numerical study shows that the BOIN design generally outperforms the 3+3 design and the modified toxicity probability interval (mTPI) design. The BOIN design is more likely than the 3+3 design to correctly select the maximum tolerated dose (MTD) and allocate more patients to the MTD. Compared to the mTPI design, the BOIN design has a substantially lower risk of overdosing patients and generally a higher probability of correctly selecting the MTD. User-friendly software is freely available to facilitate the application of the BOIN design. PMID:27407096

Spectrally Selective Mirrors with Combined Optical and Thermal Benefit for Photovoltaic Module Thermal Management

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

Slauch, Ian M.; Deceglie, Michael G.; Silverman, Timothy J.

Waste heat generated during daytime operation of a solar module will raise its temperature and reduce cell efficiency. In addition to thermalization and carrier recombination, one major source of excess heat in modules is the parasitic absorption of light with sub-bandgap energy. Parasitic absorption can be prevented if sub-bandgap radiation is reflected away from the module. We report on the design considerations and projected changes to module energy yield for photonic reflectors capable of reflecting a portion of sub-bandgap radiation while maintaining or improving transmission of light with energy greater than the semiconductor bandgap. Using a previously developed, self-consistent opto-electro-thermalmore » finite-element simulation, we calculate the total additional energy generated by a module, including various photonic reflectors, and decompose these benefits into thermal and optical effects. We show that the greatest total energy yield improvement comes from photonic mirrors designed for the outside of the glass, but that mirrors placed between the glass and the encapsulant can have significant thermal benefit. We then show that optimal photonic mirror design requires consideration of all angles of incidence, despite unequal amounts of radiation arriving at each angle. We find that optimized photonic mirrors will be omnidirectional in the sense that they have beneficial performance, regardless of the angle of incidence of radiation. By fulfilling these criteria, photonic mirrors can be used at different geographic locations or different tilt angles than their original optimization conditions with only marginal changes in performance. We show designs that improve energy output in Golden, Colorado by 3.7% over a full year. This work demonstrates the importance of considering real-world irradiance and weather conditions when designing optical structures for solar applications.« less

Magnetic resonance imaging: A tool to monitor and optimize enzyme distribution during porcine pancreas distention for islet isolation

PubMed Central

Scott, WE; Weegman, BP; Balamurugan, AN; Ferrer-Fabrega, J; Anazawa, T; Karatzas, T; Jie, T; Hammer, BE; Matsumoto, S; Avgoustiniatos, ES; Maynard, KS; Sutherland, DER; Hering, BJ; Papas, KK

2014-01-01

Background Porcine islet xenotransplantation is emerging as a potential alternative for allogeneic clinical islet transplantation. Optimization of porcine islet isolation in terms of yield and quality is critical for the success and cost effectiveness of this approach. Incomplete pancreas distension and inhomogeneous enzyme distribution have been identified as key factors for limiting viable islet yield per porcine pancreas. The aim of this study was to explore the utility of Magnetic Resonance Imaging (MRI) as a tool to investigate the homogeneity of enzyme delivery in porcine pancreata. Traditional and novel methods for enzyme delivery aimed at optimizing enzyme distribution were examined. Methods Pancreata were procured from Landrace pigs via en bloc viscerectomy. The main pancreatic duct was then cannulated with an 18g winged catheter and MRI performed at 1.5 T. Images were collected before and after ductal infusion of chilled MRI contrast agent (gadolinium) in physiological saline. Results Regions of the distal aspect of the splenic lobe and portions of the connecting lobe and bridge exhibited reduced delivery of solution when traditional methods of distension were utilized. Use of alternative methods of delivery (such as selective re-cannulation and distension of identified problem regions) resolved these issues and MRI was successfully utilized as a guide and assessment tool for improved delivery. Conclusion Current methods of porcine pancreas distension do not consistently deliver enzyme uniformly or adequately to all regions of the pancreas. Novel methods of enzyme delivery should be investigated and implemented for improved enzyme distribution. MRI serves as a valuable tool to visualize and evaluate the efficacy of current and prospective methods of pancreas distension and enzyme delivery. PMID:24986758