Experimental Setup and Data Analysis Considerations for DNA- and RNA-SIP Experiments in the Omics Era

2019 ◽  
pp. 1-15
Author(s):  
Roey Angel
Keyword(s):  
Data Analysis ◽  
Experimental Setup ◽  
Dna And Rna

Settling Characteristics of Polymeric Additives in Dodecane

2018 ◽  
Author(s):  
Gurjap Singh ◽  
Stephen Pitts ◽  
Elio Lopes ◽  
Albert Ratner
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Experimental Setup ◽  
Objective Data ◽  
Polymeric Additives ◽  
Burning Rates ◽  
Settling Behavior ◽  
Settling Characteristics

Recent studies have shown that adding polymeric additives to hydrocarbon-based fuels can lead to suppression of their splashing behavior, as well as enhance their burning rates. However, there is a lack of objective data on polymeric additives settling times in these fuels. Choosing Dodecane as a representative of diesel-based fuels, present research experimentally investigates the settling behavior of polymeric additives (graphene) when mixed in with Dodecane, and the effects of various surfactants on such behavior. Methodology for experimental setup, data collection and data analysis is presented. Various concentrations of additives and surfactants are analyzed, and trends for settling times are shown.

DNA and RNA: NMR studies of conformations and dynamics in solution

1987 ◽  
Vol 20 (1-2) ◽  
pp. 35-112 ◽  
Author(s):  
Dinshaw J. Patel ◽  
Lawrence Shapiro ◽  
Dennis Hare
Keyword(s):  
Aqueous Solution ◽  
Data Analysis ◽  
Nucleic Acids ◽  
Nmr Studies ◽  
Magnet Design ◽  
Dna And Rna ◽  
Qualitative Nature ◽  
Abundant Supply

The early NMR research on nucleic acids was of a qualitative nature and was restricted to partial characterization of short oligonucleotides in aqueous solution. Major advances in magnet design, spectrometer electronics, pulse techniques, data analysis and computational capabilities coupled with the availability of pure and abundant supply of long oligonucleotides have extended these studies towards the determination of the 3-D structure of nucleic acids in solution.

Data-driven thinking for measuring the human experience in the built environment

2021 ◽  
pp. 147807712110251
Author(s):  
Bige Tunçer ◽  
Francisco Benita
Keyword(s):  
Data Analysis ◽  
Built Environment ◽  
Urban Design ◽  
Learning Experience ◽  
Landscape Design ◽  
Data Driven ◽  
Sensor Data ◽  
Experimental Setup ◽  
Collection Data

This article introduces a methodology to implement Data-driven Thinking in the context of urban design. We present the results of a case study based on a 7-day workshop with 10 participants with landscape design and architecture background. The goal of the workshop was to expose participants to Data-driven Thinking through experimental design, multi-sensor data collection, data analysis, visualization, and insight generation. We evaluate their learning experience in designing an experimental setup, collecting real-time immediate environmental and physiological body reactions data. Our results from the workshop show that participants increased their knowledge about measuring, visualizing and understanding data of the surrounding built environment.

Study of proton transfer processes in solution using the laser induced pH-jump: A new experimental setup and an improved data analysis based on genetic algorithms

1998 ◽  
Vol 69 (1) ◽  
pp. 270-276 ◽  
Author(s):  
Cristiano Viappiani ◽  
Germano Bonetti ◽  
Mauro Carcelli ◽  
Francesco Ferrari ◽  
Armando Sternieri
Keyword(s):  
Genetic Algorithms ◽  
Data Analysis ◽  
Proton Transfer ◽  
Experimental Setup ◽  
Transfer Processes ◽  
Ph Jump

A fast methodology to determine the characteristics of thousands of grains using three-dimensional X-ray diffraction. I. Overlapping diffraction peaks and parameters of the experimental setup

2012 ◽  
Vol 45 (4) ◽  
pp. 693-704 ◽  
Author(s):  
Hemant Sharma ◽  
Richard M. Huizenga ◽  
S. Erik Offerman
Keyword(s):  
Data Analysis ◽  
Three Dimensional ◽  
Experimental Setup ◽  
Centre Of Mass ◽  
X Ray Diffraction ◽  
X Ray ◽  
Overlapping Peaks ◽  
Diffraction Peaks ◽  
Mass Position

A data-analysis methodology is presented for the characterization of three-dimensional microstructures of polycrystalline materials from data acquired using three-dimensional X-ray diffraction (3DXRD). The method is developed for 3DXRD microscopy using a far-field detector and yields information about the centre-of-mass position, crystallographic orientation, volume and strain state for thousands of grains. This first part deals with pre-processing of the diffraction data for input into the algorithms presented in the second part [Sharma, Huizenga & Offerman (2012).J. Appl. Cryst.45, 705–718] for determination of the grain characteristics. An algorithm is presented for accurate identification of overlapping diffraction peaks from X-ray diffraction images, which has been an issue limiting the accuracy of experiments of this type. The algorithm works in two stages, namely the identification of overlapping peaks using a seeded watershed algorithm, and then the fitting of the peaks with a pseudo-Voigt shape function to yield an accurate centre-of-mass position and integrated intensity for the peaks. Regions consisting of up to six overlapping peaks can be successfully fitted. Two simulations and an experiment are used to verify the results of the algorithms. An example of the processing of diffraction images acquired in a 3DXRD experiment with a sample consisting of more than 1600 grains is shown. Furthermore, a procedure for the determination of the parameters of the experimental setup (global parameters) without the need for a calibration sample is presented and validated using simulations. This is immensely beneficial for simplifying experiments and the subsequent data analysis.

From experimental setup to data analysis in transcriptomics: copper metabolism in the human pathogenCandida albicans

2009 ◽  
Vol 2 (4) ◽  
pp. 262-268 ◽  
Author(s):  
Nicole C. Hauser ◽  
Marija Dukalska ◽  
Kurt Fellenberg ◽  
Steffen Rupp
Keyword(s):  
Data Analysis ◽  
Copper Metabolism ◽  
Experimental Setup

Permeability determination of the medium according to the analysis of laboratory hydraulic fracturing curves.

2021 ◽  
Author(s):  
Helen Novikova ◽  
Mariia Trimonova
Keyword(s):  
Data Analysis ◽  
Hydraulic Fracturing ◽  
Laboratory Experiments ◽  
Similarity Criteria ◽  
Real Field ◽  
Experimental Setup ◽  
Time Period ◽  
Fracture Closure ◽  
Fracturing Process

<p>Recently, attention to the development of low-permeable reservoirs has been increasing. More and more attention is being paid to the search for various methods of data analysis of mini-hydraulic fracturing and computer modeling of the hydraulic fracturing process, which will simplify the entire procedure of hydraulic fracturing in a real field and reduce financial costs. The increase in interest is due to the fact that the results of the hydraulic fracturing are used to determine some important characteristics of the formation.</p><p>One of such important characteristics of a reservoir is permeability. In the course of this study, the data obtained from a series of laboratory experiments on mini-hydraulic fracturing were processed. The main goal was to determine the value of permeability of the medium in which the hydraulic fracture was formed and propagated, with the help of various standard methods. The second objective of the study was to compare the calculated values with real ones known from preliminary conducted laboratory experiments.</p><p>In the frame of the work, the laboratory experiments on mini-hydraulic fracturing were carried out using a special experimental setup [1]. The uniqueness of this experimental setup lies in the fact that it allows to perform a triaxial loading of the sample under consideration. The sample material was selected according to the similarity criteria between the fracturing process in the experiment and the fracturing process in the real field. These features make it possible to approximate the conditions of a laboratory experiment on hydraulic fracturing to real field conditions.</p><p>As a result, pressure-time dependencies were obtained for series of laboratory experiments. Further analysis of the curves was carried out in the time period after fracture closure.</p><p>In the course of data analysis, the flow regimes in the medium during the time period after fracture closure were estimated. After that, the values of permeability were calculated using approach introduced by Nolte [2, 3]. The permeability values were also estimated using the method proposed by Horner [4] and later modified by Nolte [5]. All theoretically obtained values were compared with real values of permeabilities.</p><p><strong>Acknowledgements</strong></p><p>The reported study was funded by RFBR, project number 20-35-80018, and state task 0146-2019-0007.</p><p><strong>References</strong></p><p>1. Trimonova M., Baryshnikov N., Zenchenko E., Zenchenko P., Turuntaev S.: “The Study of the Unstable Fracture Propagation in the Injection Well: Numerical and Laboratory Modelling,” (2017).</p><p>2. Nolte, K. G.: “Determination of Fracture Parameters from Fracturing Pressure Decline,” Las Vegas (1979).</p><p>3. Nolte, K. G.: “A General Analysis of Fracturing Pressure Decline With Application to Three Models,” (1986).</p><p>4. Horner, D. R.: “Pressure Build-Up in Wells,” Netherlands (1951).</p><p>5. Nolte, K. G., Maniere, J. L., Owens, K. A.: “After-Closure Analysis of Fracture Calibration Tests,” Texas (1997).</p>

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