Quartz-in-garnet elastic barometry vs. conventional thermobarometers: a comparison across diverse tectonic settings

2021 ◽  
Author(s):  
Miguel Cisneros ◽  
Whitney Behr
Keyword(s):  
Subduction Zone ◽  
Initial Conditions ◽  
Experimental Studies ◽  
Garnet Growth ◽  
Experimental Conditions ◽  
Data Set ◽  
Franciscan Complex ◽  
Quartz Inclusion ◽  
The Alps ◽  
The Himalaya

<p>In recent years, elastic thermobarometry has gained wider acceptance and utility within the petrologic community and beyond. In particular, quartz-in-garnet (qtz-in-grt) elastic barometry is widely used because of the ubiquity of garnet in metamorphic rocks. The technique is based on using Raman spectroscopy to quantify strains recorded by inclusions, and modeling the elastic evolution of the inclusion-host pair to constrain the initial conditions of inclusion entrapment. Recent studies have validated the technique experimentally by comparing pressures from the qtz-in-grt barometer with experimental conditions of garnet growth and entrapment of quartz, and have shown that the barometer can provide reliable pressure conditions of garnet growth. However, current experimental studies fail to capture the reliability of the technique under disparate pressure (P), temperature (T) and deformation conditions, and studies that systematically compare qtz-in-grt barometry and conventional thermobarometry are lacking. </p><p>In this work, we compare P conditions from qtz-in-grt barometry and conventional thermobarometry from the following locations: spatially and temporally variant high P/T subduction zone eclogite blocks from the Franciscan Complex in California, high P/T subduction zone rocks of varying compositions from Syros, Greece, high P/T and low P/T rocks of varying compositions from the Betics system in Spain, low P/T schists from the Jajarkot and Karnali klippen in the Himalaya, high-P rocks from the Alps, and low P/T metapelites from northeast Nevada. Qtz-in-grt barometry constraints from the Franciscan and Syros show good agreement with some reference P-T conditions, but disagree with some thermodynamic equilibria constraints and subsets of multi-mineral thermobarometry calibrations. Qtz-in-grt barometry constraints from the Himalaya are in excellent agreement with reference P constraints. Measurements of samples from other localities are currently in progress. This set of quartz inclusion analyses further allows us to evaluate the effects of inclusion geometry, anisotropy, P and T conditions of garnet growth, and P and T paths on the ultimate P conditions recorded by the qtz-in-grt barometer. The data-set also provides insights into the possible limitations of other techniques (e.g., conventional thermobarometry).</p>

scholarly journals Linking gas and particle ejection dynamics to boundary conditions in scaled shock-tube experiments

2021 ◽  
Vol 83 (8) ◽  
Author(s):  
Valeria Cigala ◽  
Ulrich Kueppers ◽  
Juan José Peña Fernández ◽  
Donald B. Dingwell
Keyword(s):  
Particle Size ◽  
Shock Tube ◽  
Initial Conditions ◽  
Volcanic Eruptions ◽  
Tube Length ◽  
Experimental Investigations ◽  
Clear Correlation ◽  
Angular Deviation ◽  
Dynamic Nature ◽  
Experimental Conditions

AbstractPredicting the onset, style and duration of explosive volcanic eruptions remains a great challenge. While the fundamental underlying processes are thought to be known, a clear correlation between eruptive features observable above Earth’s surface and conditions and properties in the immediate subsurface is far from complete. Furthermore, the highly dynamic nature and inaccessibility of explosive events means that progress in the field investigation of such events remains slow. Scaled experimental investigations represent an opportunity to study individual volcanic processes separately and, despite their highly dynamic nature, to quantify them systematically. Here, impulsively generated vertical gas-particle jets were generated using rapid decompression shock-tube experiments. The angular deviation from the vertical, defined as the “spreading angle”, has been quantified for gas and particles on both sides of the jets at different time steps using high-speed video analysis. The experimental variables investigated are 1) vent geometry, 2) tube length, 3) particle load, 4) particle size, and 5) temperature. Immediately prior to the first above-vent observations, gas expansion accommodates the initial gas overpressure. All experimental jets inevitably start with a particle-free gas phase (gas-only), which is typically clearly visible due to expansion-induced cooling and condensation. We record that the gas spreading angle is directly influenced by 1) vent geometry and 2) the duration of the initial gas-only phase. After some delay, whose length depends on the experimental conditions, the jet incorporates particles becoming a gas-particle jet. Below we quantify how our experimental conditions affect the temporal evolution of these two phases (gas-only and gas-particle) of each jet. As expected, the gas spreading angle is always at least as large as the particle spreading angle. The latter is positively correlated with particle load and negatively correlated with particle size. Such empirical experimentally derived relationships between the observable features of the gas-particle jets and known initial conditions can serve as input for the parameterisation of equivalent observations at active volcanoes, alleviating the circumstances where an a priori knowledge of magma textures and ascent rate, temperature and gas overpressure and/or the geometry of the shallow plumbing system is typically chronically lacking. The generation of experimental parameterisations raises the possibility that detailed field investigations on gas-particle jets at frequently erupting volcanoes might be used for elucidating subsurface parameters and their temporal variability, with all the implications that may have for better defining hazard assessment.

Deep Learning Based Classification of Time Series of Chaotic Systems over Graphic Images

2021 ◽  
Author(s):  
Süleyman UZUN ◽  
Sezgin KAÇAR ◽  
Burak ARICIOĞLU
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Transfer Learning ◽  
Chaotic Systems ◽  
Initial Conditions ◽  
Step Size ◽  
Learning Methods ◽  
Data Set ◽  
Graphic Images ◽  
Different Chaotic Systems

Abstract In this study, for the first time in the literature, identification of different chaotic systems by classifying graphic images of their time series with deep learning methods is aimed. For this purpose, a data set is generated that consists of the graphic images of time series of the most known three chaotic systems: Lorenz, Chen, and Rossler systems. The time series are obtained for different parameter values, initial conditions, step size and time lengths. After generating the data set, a high-accuracy classification is performed by using transfer learning method. In the study, the most accepted deep learning models of the transfer learning methods are employed. These models are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet and GoogLeNet. As a result of the study, classification accuracy is found between 96% and 97% depending on the problem. Thus, this study makes association of real time random signals with a mathematical system possible.

Investigation of Regression-Based Effect Size Methods Developed in Single-Subject Studies

2021 ◽  
pp. 014544552110540
Author(s):  
Nihal Sen
Keyword(s):  
Effect Size ◽  
Experimental Studies ◽  
Single Subject ◽  
Single Subject Design ◽  
Data Set ◽  
Design Studies ◽  
Sample Data ◽  
The Difference ◽  
D Values ◽  
Effect Size Calculation

The purpose of this study is to provide a brief introduction to effect size calculation in single-subject design studies, including a description of nonparametric and regression-based effect sizes. We then focus the rest of the tutorial on common regression-based methods used to calculate effect size in single-subject experimental studies. We start by first describing the difference between five regression-based methods (Gorsuch, White et al., Center et al., Allison and Gorman, Huitema and McKean). This is followed by an example using the five regression-based effect size methods and a demonstration how these methods can be applied using a sample data set. In this way, the question of how the values obtained from different effect size methods differ was answered. The specific regression models used in these five regression-based methods and how these models can be obtained from the SPSS program were shown. R2 values obtained from these five methods were converted to Cohen’s d value and compared in this study. The d values obtained from the same data set were estimated as 0.003, 0.357, 2.180, 3.470, and 2.108 for the Allison and Gorman, Gorsuch, White et al., Center et al., as well as for Huitema and McKean methods, respectively. A brief description of selected statistical programs available to conduct regression-based methods was given.

MONITORING AND CLASSIFYING THE STATE OF HARD DISKS USING RECURRENT NEURAL NETWORKS

2021 ◽  
pp. 36-43
Author(s):  
L. A. Demidova ◽  
A. V. Filatov
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Experimental Studies ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
Dense Layer ◽  
Hard Disks ◽  
Destructive Testing ◽  
Data Set ◽  
State Classification

The article considers an approach to solving the problem of monitoring and classifying the states of hard disks, which is solved on a regular basis, within the framework of the concept of non-destructive testing. It is proposed to solve this problem by developing a classification model using machine learning algorithms, in particular, using recurrent neural networks with Simple RNN, LSTM and GRU architectures. To develop a classification model, a data set based on the values of SMART sensors installed on hard disks it used. It represents a group of multidimensional time series. At the same time, the structure of the classification model contains two layers of a neural network with one of the recurrent architectures, as well as a Dropout layer and a Dense layer. The results of experimental studies confirming the advantages of LSTM and GRU architectures as part of hard disk state classification models are presented.

scholarly journals Lifestyle Behaviors and Mental Health of American Adults

2007 ◽  
Vol 100 (1) ◽  
pp. 294-302 ◽  
Author(s):  
Elizabeth H. Chaney ◽  
J. Don Chaney ◽  
Min Qi Wang ◽  
James M. Eddy
Keyword(s):  
Mental Health ◽  
Healthy Lifestyle ◽  
Descriptive Analysis ◽  
Experimental Studies ◽  
Poor Mental Health ◽  
Behavioral Risk ◽  
Lifestyle Behaviors ◽  
Unhealthy Lifestyle ◽  
Data Set ◽  
Health Related

The purpose of this study was to test the hypothesis that individuals reporting healthy lifestyle behaviors would also report better self-rated mental health. Logistic regression analyses were conducted utilizing SUDAAN on the Behavioral Risk Factor Surveillance Survey data set. This descriptive analysis suggests that persons reporting poor mental health were more likely to report unhealthy lifestyle behaviors. This set of findings encourages careful design of experimental studies of empirically based associations of mental health and life style, using psychometrically sound measures. Then public health programs focused on change of health-related behaviors might be more suitably devised.

scholarly journals Computational Design of Sensitized Combustion Chemistry Experiments

2021 ◽  
Vol 7 ◽  
Author(s):  
Cody Ising ◽  
Pedro Rodriguez ◽  
Daniel Lopez ◽  
Jeffrey Santner
Keyword(s):  
Shock Tube ◽  
Initial Conditions ◽  
Computational Design ◽  
Reaction Rates ◽  
Oxidation Reactions ◽  
Combustion Chemistry ◽  
Experimental Conditions ◽  
As Species ◽  
User Friendly

In combustion chemistry experiments, reaction rates are often extracted from complex experiments using detailed models. To aid in this process, experiments are performed such that measurable quantities, such as species concentrations, flame speed, and ignition delay, are sensitive to reaction rates of interest. In this work, a systematic method for determining such sensitized experimental conditions is demonstrated. An open-source python script was created using the Cantera module to simulate thousands of 0D and hundreds of 1D combustion chemistry experiments in parallel across a broad, user-defined range of mixture conditions. The results of the simulation are post-processed to normalize and compare sensitivity values among reactions and across initial conditions for time-varying and steady-state simulations, in order to determine the “most useful” experimental conditions. This software can be utilized by researchers as a fast, user-friendly screening tool to determine the thermodynamic and mixture parameters for an experimental campaign. We demonstrate this software through two case studies comparing results of the 0D script against a shock tube experiment and results of the 1D script against a spherical flame experiment. In the shock tube case study we present mixture conditions compared to those used in the literature to study H + O2 (+M)→HO2(+M). In the flame case study, we present mixture conditions compared to those in the literature to study formyl radical (HCO) decomposition and oxidation reactions. The systematically determined experimental conditions identified in the present work are similar to the conditions chosen in the literature.

scholarly journals Mechanism of the process of decomposition of apatitis with phosphoric acid

2019 ◽  
Vol 81 (1) ◽  
pp. 294-297
Author(s):  
R. F. Sabirov ◽  
A. F. Makhotkin ◽  
Yu. N. Sakharov ◽  
I. A. Makhotkin ◽  
I. Yu. Sakharov
Keyword(s):  
Phosphoric Acid ◽  
Ph Value ◽  
Batch Reactor ◽  
Experimental Studies ◽  
Hydrogen Ions ◽  
Experimental Conditions ◽  
Monocalcium Phosphate ◽  
Ph Values ◽  
Whole Process ◽  
Proportional Increase

Experimental studies of the kinetics and mechanism of the process, decomposition of apatite by phosphoric acid, in the Apatite-H3PO4-H2O system without the addition of sulfuric acid have been performed. The study of the decomposition process of Kovdorsky apatite with certain particle sizes was carried out in a batch reactor with a volume of 1 dm3 with stirring of the reaction mixture, and an initial concentration of phosphoric acid of 17% by weight, at a temperature of 78–82 °C. Observation of the process was carried out by determining the concentration of phosphoric acid and the concentration of monocalcium phosphate. The acidity of the reaction mixture was determined by the pH meter readings (pH-105 MA with a glass combined-ESC-10603 electrode). It was shown that during the whole process a constant smooth increase in the pH value of the reaction mixture to pH 6 occurs. Comparison of the pH values of the reaction mixture during the actual at the time of determining the concentration of phosphoric acid and pH of phosphoric acid of the corresponding concentration in the aqueous solution shows that the pH value of the reaction mixture is significantly affected by the presence of monocalcium phosphate gel. During the process, during the first thirty minutes, the concentration of phosphoric acid decreases from 17 to 10% by weight, the corresponding quantitative formation of monocalcium phosphate gel and a proportional increase in the pH of the reaction mixture. Then, as the concentration of phosphoric acid decreases, the process slows down and does not proceed to the end under the experimental conditions. The dependence of the concentration of hydrogen ions in the reaction mixture on the time of the process of decomposition of apatite in phosphoric acid, which is presented in logarithmic coordinates, shows that the mechanism of formation of hydrogen ions during the whole process does not change. Thus, it is shown that the process of decomposition of apatite by phosphoric acid in the Apatite-H3PO4-H2O system proceeds with the formation of an intermediate product - monocalcium phosphate gel. When this occurs, a corresponding significant change in the pH values of the reaction mixture occurs. During the whole process there is a constant decrease in the concentration of phosphoric acid.

scholarly journals ADSORPTION OF PHOSPHATE IONS ON RED SLUDGE

2017 ◽  
Vol 60 (8) ◽  
pp. 80
Author(s):  
Svetlana M. Kramer ◽  
Mariya V. Terekhova ◽  
Inna V. Artamonova
Keyword(s):  
Hydrochloric Acid ◽  
Experimental Studies ◽  
Aluminum Production ◽  
Quantitative Composition ◽  
Experimental Conditions ◽  
Initial Concentration ◽  
Phosphate Ions ◽  
Frumkin’S Isotherm ◽  
Ph Range ◽  
Red Sludge

In work the possibility of red sludge (waste of aluminum production by Bayer's method) to adsorb phosphate ions from water solutions at various concentration of ions and in the pH range from 3 to 10 is studied. Relevance of use of red sludge for receiving on its basis of sorbents is reasoned. For identification of the studied object the qualitative and quantitative composition of red sludge was established by the method of the X-ray phase analysis. The technique of red slage activation by hydrochloric acid, and also an adsorption technique of phosphate ions on the red sludge surface is described. Experimental studies of adsorption of phosphate ions on the surface of the red slage activated by hydrochloric acid depending on рН and concentration of initial solution were conducted. The dependence of adsorption phosphate ions on the red slage activated by НСl on рН and on the initial concentration of phosphate ions in solution is presented. These dependences of a relative fraction of distribution of various ions of phosphoric acid on рН are given in work. The form of ion phosphate having the greatest adsorptive activity on the red slage activated by hydrochloric acid in experimental conditions is revealed. Experimental data on dependence of adsorption of phosphate ions on their initial concentration in solution are described by Frumkin's isotherm. The constant of the adsorptive balance, limit adsorption, the parameter of intermolecular interaction of the adsorbed particles are calculated. Optimum conditions for adsorption of phosphate ions on red slage are established.Forcitation:Kramer S.M., Terekhova M.V., Artamonova I.V. Adsorption of phosphate ions on red sludge. Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol. 2017. V. 60. N 8. P. 80-83.

scholarly journals Empirical inference of circuitry and plasticity in a kinase signaling network

2015 ◽  
Vol 112 (25) ◽  
pp. 7719-7724 ◽  
Author(s):  
Edmund H. Wilkes ◽  
Camille Terfve ◽  
John G. Gribben ◽  
Julio Saez-Rodriguez ◽  
Pedro Rodriguez Cutillas
Keyword(s):  
Cell Biology ◽  
Initial Conditions ◽  
Phenotypic Diversity ◽  
Signaling Network ◽  
Network Activity ◽  
Erk Signaling ◽  
Signaling Networks ◽  
Experimental Conditions ◽  
Acquired Drug Resistance ◽  
Combination Treatments

Our understanding of physiology and disease is hampered by the difficulty of measuring the circuitry and plasticity of signaling networks that regulate cell biology, and how these relate to phenotypes. Here, using mass spectrometry-based phosphoproteomics, we systematically characterized the topology of a network comprising the PI3K/Akt/mTOR and MEK/ERK signaling axes and confirmed its biological relevance by assessing its dynamics upon EGF and IGF1 stimulation. Measuring the activity of this network in models of acquired drug resistance revealed that cells chronically treated with PI3K or mTORC1/2 inhibitors differed in the way their networks were remodeled. Unexpectedly, we also observed a degree of heterogeneity in the network state between cells resistant to the same inhibitor, indicating that even identical and carefully controlled experimental conditions can give rise to the evolution of distinct kinase network statuses. These data suggest that the initial conditions of the system do not necessarily determine the mechanism by which cancer cells become resistant to PI3K/mTOR targeted therapies. The patterns of signaling network activity observed in the resistant cells mirrored the patterns of response to several drug combination treatments, suggesting that the activity of the defined signaling network truly reflected the evolved phenotypic diversity.

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