scholarly journals Effects of processing conditions on the caseinolytic activity of crude extracts of Cynara cardunculus L/Efectos de las condiciones de extracción sobre la actividad caseinolítica de los extractos de Cynara cardunculus L

1996 ◽  
Vol 2 (4) ◽  
pp. 255-263 ◽  
Author(s):  
M.J. Sousa ◽  
F.X. Malcata
Keyword(s):  
Large Scale ◽  
Salt Content ◽  
Processing Parameters ◽  
Quadratic Model ◽  
Cynara Cardunculus ◽  
Local Maxima ◽  
Homogenization Time ◽  
Caseinolytic Activity ◽  
Surface Response Method ◽  
Response Method

Four processing parameters (time of grinding, pH of buffer, salt concentration of buffer, and homogenization time) involved in the liquid extraction of proteinases from flowers of the wild thistle ( Cynara cardunculus), were studied for their effects on final caseinolytic activity by a surface response method. The caseinolytic activity was assayed spectrophotometrically using o-phthal dialdehyde. An empirical quadratic model was applied to experimental data pertaining to the average enzymatic activity and equations describing the optimal conditions were obtained. Simultaneous solution of these equations for the local maxima indicated that, within the range tested, the maximum (estimated) specific caseinolytic activity (around 9.5 μmol of equivalent leucine/min.g of thistle flower) was obtained by grinding the flowers for 36 s, using an extrac tion buffer with a pH of 5.9 and a salt content of 0% (w/w), and homogenizing the ground flower/buffer suspension for 15 min. These data are of use in the optimization of extraction proce dures, which are of relevance to the production of standardized plant rennets suitable for the large scale manufacture of ewe's milk cheese.

scholarly journals Rapid Single Image-Based DTM Estimation from ExoMars TGO CaSSIS Images Using Generative Adversarial U-Nets

2021 ◽  
Vol 13 (15) ◽  
pp. 2877
Author(s):  
Yu Tao ◽  
Siting Xiong ◽  
Susan J. Conway ◽  
Jan-Peter Muller ◽  
Anthony Guimpier ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Imaging System ◽  
Landing Site ◽  
Parameter Tuning ◽  
Processing Parameters ◽  
Input Image ◽  
Large Area ◽  
Laser Altimeter ◽  
Imaging Science

The lack of adequate stereo coverage and where available, lengthy processing time, various artefacts, and unsatisfactory quality and complexity of automating the selection of the best set of processing parameters, have long been big barriers for large-area planetary 3D mapping. In this paper, we propose a deep learning-based solution, called MADNet (Multi-scale generative Adversarial u-net with Dense convolutional and up-projection blocks), that avoids or resolves all of the above issues. We demonstrate the wide applicability of this technique with the ExoMars Trace Gas Orbiter Colour and Stereo Surface Imaging System (CaSSIS) 4.6 m/pixel images on Mars. Only a single input image and a coarse global 3D reference are required, without knowing any camera models or imaging parameters, to produce high-quality and high-resolution full-strip Digital Terrain Models (DTMs) in a few seconds. In this paper, we discuss technical details of the MADNet system and provide detailed comparisons and assessments of the results. The resultant MADNet 8 m/pixel CaSSIS DTMs are qualitatively very similar to the 1 m/pixel HiRISE DTMs. The resultant MADNet CaSSIS DTMs display excellent agreement with nested Mars Reconnaissance Orbiter Context Camera (CTX), Mars Express’s High-Resolution Stereo Camera (HRSC), and Mars Orbiter Laser Altimeter (MOLA) DTMs at large-scale, and meanwhile, show fairly good correlation with the High-Resolution Imaging Science Experiment (HiRISE) DTMs for fine-scale details. In addition, we show how MADNet outperforms traditional photogrammetric methods, both on speed and quality, for other datasets like HRSC, CTX, and HiRISE, without any parameter tuning or re-training of the model. We demonstrate the results for Oxia Planum (the landing site of the European Space Agency’s Rosalind Franklin ExoMars rover 2023) and a couple of sites of high scientific interest.

scholarly journals Parallel Framework for Dimensionality Reduction of Large-Scale Datasets

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Sai Kiranmayee Samudrala ◽  
Jaroslaw Zola ◽  
Srinivas Aluru ◽  
Baskar Ganapathysubramanian
Keyword(s):  
Dimensionality Reduction ◽  
Organic Solar Cells ◽  
Large Scale ◽  
Parallel Implementation ◽  
High Dimensional Data ◽  
Real Life ◽  
Processing Parameters ◽  
High Dimensional ◽  
Morphology Evolution ◽  
Reduction Techniques

Dimensionality reduction refers to a set of mathematical techniques used to reduce complexity of the original high-dimensional data, while preserving its selected properties. Improvements in simulation strategies and experimental data collection methods are resulting in a deluge of heterogeneous and high-dimensional data, which often makes dimensionality reduction the only viable way to gain qualitative and quantitative understanding of the data. However, existing dimensionality reduction software often does not scale to datasets arising in real-life applications, which may consist of thousands of points with millions of dimensions. In this paper, we propose a parallel framework for dimensionality reduction of large-scale data. We identify key components underlying the spectral dimensionality reduction techniques, and propose their efficient parallel implementation. We show that the resulting framework can be used to process datasets consisting of millions of points when executed on a 16,000-core cluster, which is beyond the reach of currently available methods. To further demonstrate applicability of our framework we perform dimensionality reduction of 75,000 images representing morphology evolution during manufacturing of organic solar cells in order to identify how processing parameters affect morphology evolution.

scholarly journals Performance of silver-coated red soil nanocomposites in water disinfection

2018 ◽  
Vol 54 (1) ◽  
pp. 70-78 ◽  
Author(s):  
Ebrahim Mahmoudi ◽  
Farid Moeinpour
Keyword(s):  
Contact Time ◽  
Elimination Rate ◽  
Red Soil ◽  
Water Disinfection ◽  
Box Behnken Design ◽  
E Coli ◽  
Surface Response Method ◽  
Research Findings ◽  
Response Method ◽  
Bacterial Effect

Abstract The present research studied the anti-bacterial effect of silver-coated red soil nanoparticles on Gram-negative bacteria Escherichia coli (E. coli) from water. The effects of disinfectant concentration (0.02, 0.05 and 0.1 g/mL), contact time (10, 20 and 30 minutes) and bacteria number (102, 104 and 106 CFU/mL) have been also investigated. To obtain important factors, the interactions between factors and optimal experimental design in surface response method were used based on Box-Behnken design. According to the research findings, the system is efficient in eliminating E. coli. The results showed that E. coli elimination efficiency intensified through increasing the amount of disinfectant from 0.02 to 0.1 g/mL. Expanding contact time from 10 minutes to 30 minutes also heightened the E. coli elimination rate. R2 for E. coli elimination is 0.9956 indicating a good agreement between model experimental data and forecasting data.

Application of variothermal heating concepts for the production of microstructured films using the extrusion embossing process

2012 ◽  
Vol 32 (2) ◽  
Author(s):  
Walter Michaeli ◽  
Stephan Eilbracht ◽  
Micha Scharf ◽  
Claudia Hartmann ◽  
Kirsten Bobzin ◽  
...  
Keyword(s):  
Temperature Profile ◽  
Large Scale ◽  
Cost Effective ◽  
Processing Parameters ◽  
Surface Structures ◽  
Structured Surfaces ◽  
Heating Systems ◽  
External Heating

Abstract The application of the extrusion embossing process is a fast and cost-effective way to produce large-scale films with structured surfaces. In principle, microscopic and macroscopic surface structures can be manufactured this way. Particularly for the fabrication of microscopic structures, the reproduction accuracy can be remarkably improved by applying variothermal heating concepts for the embossing roll. In this article, two possible heating concepts are investigated: one laser-based and another using an inductor. The generated temperature profile along the circumference of the embossing roll is studied, taking the material of the embossing roll as well as different processing parameters into account. Both external heating systems (laser vs. inductor) are tested and compared. Furthermore, the improvement of the accuracy of the replicated microstructures is examined.

On the Progress of Combustion Synthesis of Si3N4 Ceramic: From Laboratory Research to Industrial Production

2007 ◽  
Vol 336-338 ◽  
pp. 911-915 ◽  
Author(s):  
Jiang Tao Li ◽  
Yun Yang ◽  
Hai Bo Jin
Keyword(s):  
Mechanical Activation ◽  
Combustion Synthesis ◽  
Industrial Production ◽  
Large Scale ◽  
Processing Parameters ◽  
Nitrogen Pressure ◽  
Chemical Stimulation ◽  
Ammonium Salts ◽  
Laboratory Research ◽  
The Past

The progress on the combustion synthesis of Si3N4 powders during the past decades was summarized with the emphasis on the recently developed mechano-chemically activated combustion synthesis (MACS) method. The effects of processing parameters such as the addition of diluent and ammonium salts into the green mixtures, the variation of nitrogen pressure as well as the mechanical activation treatment on the degree of Si to α-Si3N4 conversion was evaluated. The combination of mechanical activation and chemical stimulation was effective in enhancing the reactivity of Si powder reactants, which was responsible for the extension of the minimum nitrogen pressure normally required for the combustion synthesis of Si3N4. This breakthrough indicates that nitriding combustion of silicon in pressurized nitrogen could be promoted by activating the solid reactants instead of by increasing the pre-exerted nitrogen pressure. The MACS process was successfully applied to the industrial production of Si3N4 powders, the regularities for the large-scale synthesis were reported, and the as-synthesized Si3N4 powder products were systematically characterized.

A new route to bulk nanocrystalline materials

2003 ◽  
Vol 18 (8) ◽  
pp. 1757-1760 ◽  
Author(s):  
Jian-Qing Su ◽  
Tracy W. Nelson ◽  
Colin J. Sterling
Keyword(s):  
Large Scale ◽  
Thin Sheet ◽  
Processing Parameters ◽  
Friction Stir ◽  
Grain Sizes ◽  
Processed Material ◽  
Average Grain Size ◽  
Structural Applications ◽  
Bulk Nanocrystalline ◽  
The Cost

Despite their interesting properties, nanostructured materials have found limited use as a result of the cost of preparation and the difficulty in scaling up. Herein, the authors report a technique, friction stir processing (FSP), to refine grain sizes to a nanoscale. Nanocrystalline 7075 Al with an average grain size of 100 nm was successfully obtained using FSP. It may be possible to further control the microstructure of the processed material by changing the processing parameters and the cooling rate. In principle, by applying multiple overlapping passes, it should be possible to produce any desired size thin sheet to nanostructure using this technique. We expect that the FSP technique may pave the way to large-scale structural applications of nanostructured metals and alloys.

scholarly journals Importance of the Cutoff Value in the Quadratic Adaptive Integrate-and-Fire Model

2009 ◽  
Vol 21 (8) ◽  
pp. 2114-2122 ◽  
Author(s):  
Jonathan Touboul
Keyword(s):  
Membrane Potential ◽  
Cortical Neurons ◽  
Large Scale ◽  
Quadratic Model ◽  
Fixed Amount ◽  
Cutoff Value ◽  
Fire Model ◽  
Integrate And Fire ◽  
Large Scale Simulations ◽  
Adaptation Variable

The quadratic adaptive integrate-and-fire model (Izhikevich, 2003 , 2007 ) is able to reproduce various firing patterns of cortical neurons and is widely used in large-scale simulations of neural networks. This model describes the dynamics of the membrane potential by a differential equation that is quadratic in the voltage, coupled to a second equation for adaptation. Integration is stopped during the rise phase of a spike at a voltage cutoff value Vc or when it blows up. Subsequently the membrane potential is reset, and the adaptation variable is increased by a fixed amount. We show in this note that in the absence of a cutoff value, not only the voltage but also the adaptation variable diverges in finite time during spike generation in the quadratic model. The divergence of the adaptation variable makes the system very sensitive to the cutoff: changing Vc can dramatically alter the spike patterns. Furthermore, from a computational viewpoint, the divergence of the adaptation variable implies that the time steps for numerical simulation need to be small and adaptive. However, divergence of the adaptation variable does not occur for the quartic model (Touboul, 2008 ) and the adaptive exponential integrate-and-fire model (Brette & Gerstner, 2005 ). Hence, these models are robust to changes in the cutoff value.

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