Sex differences in the effect of ethionine upon rat liver metabolism prompted our investigation into possible sex differences
in the effect of ethionine upon bile acid metabolism. The bile ducts of 24 rats, 12 male and 12 female, were cannulated. After
1 hr of bile collection, 6 rats of each sex were given ethionine, 1 mg/g body wt, by feeding tube. The bile acid composition
of the bile collected during the subsequent 4 hr was analyzed by combined thin layer and gas chromatography. Ethionine induced
a reduction in bile flow (3rd and 4th hr) and in bile acid concentration (4th hr) in female rats. The amino acid had no effect
upon bile flow but did increase biliary secretion of bile acids (1st and 2nd hr) in male rats. Cholic acid accounted for the
bulk of the reduction in total bile acid secretion in the female studies. The increase in total bile acid secretion in the
male studies involved all bile acids. The effects of ethionine upon bile acid secretion were delayed in the female studies,
immediate in the male. The changes in bile acid secretion involved only the taurine conjugates in the female studies, both
taurine and glycine conjugates in the male. There are substantial sex differences in the effect of ethionine upon bile acid
metabolism in the rat. 相似文献
With lower costs and greater availability, heavy fuel oil appears as an attractive alternative to the conventional gas oil used in industrial gas turbines. However, higher levels of radiation and smoke are expected, and this note reports on some preliminary tests made with a combustion chamber burning fuels of different carbon content, ranging from kerosine to a 25% blend of residual fuel oil in gas oil, at a chamber pressure of 10 atm*. The combustion rig was equipped with a total-radiation pyrometer and black-body furnace capable of measurement at different axial stations along the spray-stabilized flame. The presence of the residual fuel oil in the gas oil was found to promote significant increases in the mean levels of radiation, emissivity and smoke density, with a modest increase in liner temperature. 相似文献
With the growing use of service-oriented architecture for designing next generation software systems,the service composition problem and its execution complexity have become even more important in resp... 相似文献
Software design patterns are well-known solutions for solving commonly occurring problems in software design. Detecting design patterns used in the code can help to understand the structure and behavior of the software, evaluate the quality of the software, and trace important design decisions. To develop and maintain a software system, we need sufficient knowledge of design decisions and software implementation processes. However, the acquisition of knowledge related to design patterns used in complex software systems is a challenging, time-consuming, and costly task. Therefore, using a suitable method to detect the design patterns used in the code reduces software development and maintenance costs. In this paper, we proposed a new method based on conceptual signatures to improve the accuracy of design pattern detection. So we used the conceptual signatures based on the purpose of patterns to detect the patterns’ instances that conform to the standard structure of patterns, and cover more instances of patterns’ variants and implementation versions of the patterns and improve the accuracy of pattern detection. The proposed method is a specific process in two main phases. In the first phase, the conceptual signature and detection formula for each pattern is determined manually. Then in the second phase, each pattern in the code is detected in a semi-automatic process using the conceptual signature and pattern detection formula. To implement the proposed method, we focused on GoF design patterns and their variants. We evaluated the accuracy of our proposed method on five open-source projects, namely, Junit v3.7, JHotDraw v5.1, QuickUML 2001, JRefactory v2.6.24, and MapperXML v1.9.7. Also, we performed our experiments on a set of source codes containing the instances of GoF design patterns’ variants for a comprehensive and fair evaluation. The evaluation results indicate that the proposed method has improved the accuracy of design pattern detection in the code.
Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection approaches. However, the current approaches have challenges in detecting intrusions, which may affect the performance of the overall detection system as well as network performance. For the time being, one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains trust between individuals no matter how far apart they are. Recently, blockchain was integrated into intrusion detection systems to enhance their overall performance. Blockchain has also been adopted in healthcare, supply chain management, and the Internet of Things. Blockchain uses robust cryptography with private and public keys, and it has numerous properties that have leveraged security’s performance over peer-to-peer networks without the need for a third party. To explore and highlight the importance of integrating blockchain with intrusion detection systems, this paper provides a comprehensive background of intrusion detection systems and blockchain technology. Furthermore, a comprehensive review of emerging intrusion detection systems based on blockchain technology is presented. Finally, this paper suggests important future research directions and trending topics in intrusion detection systems based on blockchain technology. 相似文献
This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are discussed. All experiments use the Hidden Markov Model Toolkit (HTK) and the Language Data Consortium (LDC) WestPoint Modern Standard Arabic (MSA) database. Results confirm that these Arabic distinct consonants are a major source of difficulty for Arabic ASR. While the recognition rate for certain of these unique consonants such as // can drop below 35% when uttered by non-native speakers, there is advantage to include non-native speakers in ASR. Besides, regional differences in pronunciation of MSA by native Arabic speakers require the attention of Arabic ASR research. 相似文献
This work is focused on the study of combined heat and mass transfer or double-diffusive convection near a vertical truncated cone embedded in a fluid-saturated porous medium in the presence of thermal radiation, magnetic field and variable viscosity effects. The viscosity of the fluid is assumed to be an inverse linear function of the fluid temperature. A boundary-layer analysis is employed to derive the non-dimensional governing equations. The governing equations for this investigation are transformed into a set of non-similar equations and solved numerically using the fourth-order Runge–Kutta integration scheme with the Newton–Raphson shooting technique. Comparisons with previously published work on special cases of the problem are performed and the results are found to be in excellent agreement. A parametric study illustrating the influence of the radiation parameter, magnetic field parameter, viscosity-variation parameter, buoyancy ratio and the Lewis number on the fluid velocity, temperature and solute concentration profiles as well as the Nusselt number and Sherwood number is conducted. The results of this parametric study are shown graphically and the physical aspects of the problem are highlighted and discussed. 相似文献
A multilayer feedforward neural network with two hidden layers was designed and developed for prediction of the phosphorus
content of electroless Ni–P coatings. The input parameters of the network were the pH, metal turnover, and loading of an electroless
bath. The output parameter was the phosphorus content of the electroless Ni–P coatings. The temperature and molar rate of
the bath were constant (
91° \textC, 0.4 \textNi\text + + /\textH2 \textPO2 - - 91^\circ {\text{C}},\:0.4\,{\text{Ni}}^{{{\text{ + + }}}} /{\text{H}}_{2} {\text{PO}}_{2}^{{ - - }} ). The network was trained and tested using the data gathered from our own experiments. The goal of the study was to estimate
the accuracy of this type of neural network in prediction of the phosphorus content. The study result shows that this type
of network has high accuracy even when the number of hidden neurons is very low. Some comparison between the network’s predictions
and own experimental data are given. 相似文献