True Triaxial Strength Testing of Sandstones

Laboratory rock mechanical tests allow estimation of rock strength and deformation behaviour under stress states similar to the in-situ conditions. In general, the in-situ stresses are described by three principal stresses, the vertical, maximum and minimum horizontal stresses. However, most of rock mechanical properties are obtained using only two different stresses, as in conventional triaxial tests where an axial load and an isotropic confining pressure are applied on a cylindrical rock sample. Also the most commonly used failure criterion, the Mohr-Coulomb criterion, is usually applied using only the maximum and minimum applied stresses and thus ignores the effect of the intermediate stress. Experimental and theoretical studies of rocks under true triaxial stress conditions have proved that describing their mechanical properties while ignoring the effect of σ, cannot reflect the rock behaviour under true stress states. In this paper the lab results of an on-going study on deformation behaviour of synthetic sandstones in a true triaxial cell are presented. The effect of both σ and σ has been examined by conducting compressional tests in different stress levels and σ /σ ratios. The results show the impact of changing stress magnitudes and anisotropy on rock strength and deformation behaviour

Circadian Entrainment Triggers Maturation of Human In Vitro Islets

Stem-cell-derived tissues could transform disease research and therapy, yet most methods generate functionally immature products. We investigate how human pluripotent stem cells (hPSCs) differentiate into pancreatic islets in vitro by profiling DNA methylation, chromatin accessibility, and histone modification changes. We find that enhancer potential is reset upon lineage commitment and show how pervasive epigenetic priming steers endocrine cell fates. Modeling islet differentiation and maturation regulatory circuits reveals genes critical for generating endocrine cells and identifies circadian control as limiting for in vitro islet function. Entrainment to circadian feeding/fasting cycles triggers islet metabolic maturation by inducing cyclic synthesis of energy metabolism and insulin secretion effectors, including antiphasic insulin and glucagon pulses. Following entrainment, hPSC-derived islets gain persistent chromatin changes and rhythmic insulin responses with a raised glucose threshold, a hallmark of functional maturity, and function within days of transplantation. Thus, hPSC-derived tissues are amenable to functional improvement by circadian modulation

Ectoparasite infection of Carassius carassius in water resources of west Azerbaijan, Iran

Various parasite species were found in Carassius carassius including Diplostomum spathaceum, Dactylogyrus sp.,Gyrodactylus sp. Ichthyophthirius multifiliis and Trichodinia sp . They were found in four rivers in West Azerbaijan Province (North-Western Iran) . A total of 207 live Carassius carassius from four rivers including Aras (72) Zariyneh (42) Nazlo (58) and Barandoz (35) were studied. Parasitological surveys were carried out on gills and external organs. The results showed that Diplostomum spathaceum (70.83%) Dactylogyrus sp. (38.88%) Gyrodactylus sp. ) 22.22%) Ichthyophthirius multifiliis (48.61%) Trichodinia sp. (8.33%) Chilodonella sp. (12.50%) and Argulus sp. (76.19%) were found in fish from Aras Rive so that the result showed, Spathaceum (63.79%) Dactylogyrus sp. (36.20%) Gyrodactylus sp. (25.86%) Ichthyophthirius multifiliis (44.82%) Trichodinia sp. (18.96%) Chilodonella sp. (12.06%) and Argulus sp. (6.89%). Argulus prevalence was greater in Barandoz River while Chilodonella in Zariyneh rud River . In Barandoz River, Diplostomum spathaceum (65.71%) Dactylogyrus sp. (37.14%) Gyrodactylus sp. (22.85%) Ichthyophthirius multifiliis (31.42%) Trichodinia sp. (25.71%) Chilodonella sp. (8.57%) and Argulus sp. (5.71%) were reported, respectively. Finally, in Zariyneh rud river, the followings have been reported: Diplostomum spathaceum (76.19%) Dactylogyrus sp. (21.42%) Gyrodactylus sp. (14.28%) Ichthyophthirius multifiliis (52.38%) Trichodinia sp. (23.80%) Chilodonella sp. (14.28%) and Argulus sp. (7.14%). It should be noted that prevalence , intensity and host parasite relationship will be discussed in details in this article

Runaway electron energy measurement using hard x-ray spectroscopy in "Damavand" tokamak

Set of experiments has been developed to study existing runaway electrons in "Damavand" tokamak plasma upon characteristics of hard x-ray emissions produced by collision of the runaway electrons with the plasma particles and limiters. As a first step, spatial distribution of hard x-ray emissions on the equatorial plane of the torus was considered. Obtained spectra of hard x-ray emissions for different alignments of shielded detector indicate isotropic emissivity in the equatorial plane. This is in agreement with wide angle cone of bremsstrahlung radiations, deduced from the mean value of energy of the runaway electrons. The mean energy was calculated from the slope of the energy spectrum of hard x-ray photons. In the second stage in order to investigate time evolution of energy of the runaway electrons, similar technique were applied to obtain hard x-ray energy in every 3 ms intervals, from the beginning to the end of plasma. The mean energy of the runaway electrons increases during the ramp up phase and reaches its maximum between 3 and 9 ms after plasma formation. Also considering the time dependence of the counted photons in each energy range shows that energetic photons are emitted during the ramp up phase of the plasma current in Damavand tokamak

Quantum mechanics and geodesic deviation in the brane world

We investigate the induced geodesic deviation equations in the brane world models, in which all the matter forces except gravity are confined on the 3-brane. Also, the Newtonian limit of induced geodesic deviation equation is studied. We show that in the first Randall-Sundrum model the Bohr-Sommerfeld quantization rule is as a result of consistency between the geodesic and geodesic deviation equations. This indicates that the path of test particle is made up of integral multiples of a fundamental Compton-type unit of length $h/mc$.Comment: 5 pages, no figure

A Data-driven Model for Predicting the Yield of Recoverable Sugar from Sugarcane

IntroductionSugarcane is a strategic agricultural product and increasing productivity and self-sufficiency in its production is of special importance. The most important product of sugarcane is sugar. Various factors like climatic and management conditions affect the yield of sugarcane and recoverable sugar. Crop yield forecasting is one of the most important topics in precision agriculture, which is used to estimate yield, match product supply with demand and manage product to increase productivity. The purpose of this study is to predict and model the factors affecting sugar extracted from sugarcane (recoverable sugar) in the farms of Amir-Kabir sugarcane agro-industry Company of Khuzestan province using machine learning methods.Materials and MethodsTo conduct this study, data from the agro-industrial company Amir-Kabir in the province of Khuzestan from 2010 to 2017 were used. This data has 3223 records which include four sets of data: climate, soil, crop and farm management. This data includes continuous and discrete variables. Discrete variables include production management, soil type, farm, variety, age (cane class), the month of harvest and times irrigation. Continuous variables include area, chemical fertilizer consumption, water consumption per hectare, total water consumption, drain, crop season duration, yield (cane yield) soil EC, purity, time interval drying off to crop harvest, precipitation, min and max temperature, min and max relative humidity, wind speed and evaporation. The recoverable sugar variable is considered as the target variable and is divided into two classes, values greater than or equal to 9 are in the optimal class and less than 9 are in the undesirable class. The other variables are considered as predictor variables. For modeling using the Holdout method the data were randomly divided into two independent sets, a training set and a test set. 70% of the data which includes 2256 records were used for training and 30% of the data which includes 967 records were used for testing. The modeling of this study was performed with the Python programming language version 3.8.6 in the Jupyter notebook environment. Random Forest, Adaboost, XGBoost and SVM (support vector machine) algorithms were used for modeling.Results and DiscussionTo evaluate the models, metrics of accuracy, precision, recall, f1 score and k-fold cross validation were used. The XGBoost model with 94.8% accuracy on the training set and the Adaboost model with 92.4% accuracy on the test set, are the best models. Based on precision and recall metrics Adaboost model with 87% precision and SVM model with 87% recall have better performance than the other models. Based on Repeated 10-fold stratified cross validation using two repeats the SVM model with 92.3% accuracy is the best model. The variables of purity, time interval drying off to crop harvest and crop season duration are the most important variables in predicting the recoverable sugar.ConclusionIn this study a new approach based on machine learning methods for predicting recoverable sugar from sugarcane was presented. The most important innovation of this study is the simultaneous consideration of management and climatic factors, along with other factors such as soil and crop characteristics for modeling and classification the recoverable sugar percentage from sugarcane. The results show that the performance of all models is acceptable and machine learning methods and ensemble learning algorithms can be used to predict crop yield. The results of this study and the analysis of the rules obtained from the set of decision trees made in the random forest model can be used for managers of different agro-industries in determining appropriate strategies and preparing the conditions to achieve optimal production.For future research as well as policy making and decision making Amir-Kabir sugarcane agro-industry Company the following suggestions are offered: more samples can be used to obtain more reliable results. Also can be used Deep learning methods, time series analysis and image processing. Use of IOT equipment to collect and real-time processing data on Amir-Kabir sugarcane agro-industry farms

Suggesting a full two level experimental factorial model with three factors to optimize Ti-HA biocomposite properties

A metal matrix composites (MMCs) is introduced to serve as synthetic bone grafts. The MMC was synthetized via powder metallurgical method after milling raw powder mixture of hydroxyapatite (HA) particles and pure titanium (Ti) powder. A full two level experimental factorial model with three factors (2^3) was developed to study the effect of three main parameters of synthetizing process on the hardness, density, and crystallite size of the composite. The synthetizing process parameters under consideration were the mechanical alloying time as well as the ceramic powder initial size and its mass fraction in the mixed powder. The results demonstrate that the composite’s hardness is increasing with higher HA mass fraction (W/W) of the composite and longer milling time. The analysis of data also show that the initial HA particle size has insignificant influence on the composite’s hardness, while higher HA content fraction in the MMC decreases the density of the composite

The Lipogenic Enzymes DGAT1, FAS, and LPL in Adipose Tissue: Effects of Obesity, Insulin Resistance, and TZD Treatment

Acyl-coenzyme A:diacylglycerol transferase (DGAT), fatty acid synthetase (FAS), and LPL are three enzymes important in adipose tissue triglyceride accumulation. To study the relationship of DGAT1, FAS, and LPL with insulin, we examined adipose mRNA expression of these genes in subjects with a wide range of insulin sensitivity (SI). DGAT1 and FAS (but not LPL) expression were strongly correlated with SI. In addition, the expression of DGAT1 and FAS (but not LPL) were higher in normal glucose-tolerant subjects compared with subjects with impaired glucose tolerance (IGT) (P \u3c 0.005). To study the effects of insulin sensitizers, subjects with IGT were treated with pioglitazone or metformin for 10 weeks, and lipogenic enzymes were measured in adipose tissue. After pioglitazone treatment, DGAT1 expression was increased by 33 ± 10% (P \u3c 0.05) and FAS expression increased by 63 ± 8% (P \u3c 0.05); however, LPL expression was not altered. DGAT1, FAS, and LPL mRNA expression were not significantly changed after metformin treatment. The treatment of mice with rosiglitazone also resulted in an increase in adipose expression of DGAT1 by 2- to 3-fold, as did the treatment of 3T3 F442A adipocytes in vitro with thiazolidinediones. These data support a more global concept suggesting that adipose lipid storage functions to prevent peripheral lipotoxicity