1,143 research outputs found
Wave Profile for Anti-force Waves with Maximum Possible Currents
In the theoretical investigation of the electrical breakdown of a gas, we apply a one-dimensional, steady state, constant velocity, three component fluid model and consider the electrons to be the main element in propagation of the wave. The electron gas temperature, and therefore the electron gas partial pressure, is considered to be large enough to provide the driving force. The wave is considered to have a shock front, followed by a thin dynamical transition region. Our set of electron fluid-dynamical equations consists of the equations of conservation of mass, momentum, and energy, plus the Poisson\u27s equation. The set of equations is referred to as the electron fluid dynamical equations; and a successful solution therefor must meet a set of acceptable physical conditions at the trailing edge of the wave. For breakdown waves with a significant current behind the shock front, modifications must be made to the set of electron fluid dynamical equations, as well as the shock condition on electron temperature. Considering existence of current behind the shock front, we have derived the shock condition on electron temperature, and for a set of experimentally measured wave speeds, we have been able to find maximum current values for which solutions to our set of electron velocity, electron temperature, and electron number density within the dynamical transition region of the wave
Efficient Optimal Minimum Error Discrimination of Symmetric Quantum States
This paper deals with the quantum optimal discrimination among mixed quantum
states enjoying geometrical uniform symmetry with respect to a reference
density operator . It is well-known that the minimal error probability
is given by the positive operator-valued measure (POVM) obtained as a solution
of a convex optimization problem, namely a set of operators satisfying
geometrical symmetry, with respect to a reference operator , and
maximizing . In this paper, by resolving the dual
problem, we show that the same result is obtained by minimizing the trace of a
semidefinite positive operator commuting with the symmetry operator and
such that . The new formulation gives a deeper insight into the
optimization problem and allows to obtain closed-form analytical solutions, as
shown by a simple but not trivial explanatory example. Besides the theoretical
interest, the result leads to semidefinite programming solutions of reduced
complexity, allowing to extend the numerical performance evaluation to quantum
communication systems modeled in Hilbert spaces of large dimension.Comment: 5 pages, 1 Table, no figure
Effect of stimuli-responsive nano hydrogel finishing on cotton fabric properties
Cotton fabrics have been prepared with smart properties by functional finishing with stimuli-responsive nano gel. A biopolymer (chitosan) and a synthetic polymer (poly-NiPAAm) have been used for the synthesis of nano gel through semi-batch surfactant-free dispersion polymerization (SB-SFDP) method. The incorporation of nano gel to textile fabrics is achieved by pad-dry-cure procedure, using an aqueous nano gel dispersion and 1,2,3,4-butantetracarboxylic acid as a crosslinking agent. With this cross linking method, it is possible to integrate the nano gel into the cotton fabric’s structure with good resistance to washing. The changes in physiological comfort parameters of cotton fabric such as the water vapor transmission rate, air permeability and vertical wicking as well properties such as the thickness, crease recovery angle, yellowness index and washing fastness of cotton fabric after smart finishing have also been assessed. The results show that the application of nano gel as a smart finishing system not only impairs the intrinsic properties of cotton but also improves the common textile quality by providing new features of stimuli-responsiveness.
Economic value added of intellectual capital on the market value of listed companies in Tehran Stock Exchange
The present research studies the effects of the economic value added (EVA) and the intellectual capital on value of the listed companies’ value in Tehran Stock Exchange. The research was based on an applicable goal and it is descriptive and post-event in terms of nature. The sample of the research consists of 89 companies listed in Tehran Stock Exchange and the research period was from 2004 to 2011. In order to examine the research hypothesis, a multivariate regression is utilized using panel data. The results indicate spontaneous use of intellectual capital variable and the remaining profit according to the accepted principles of accounting increase description power of the market value fluctuations of the corporate remarkably
Economic value added of intellectual capital on the market value of listed companies in Tehran Stock Exchange
The present research studies the effects of the economic value added (EVA) and the intellectual capital on value of the listed companies’ value in Tehran Stock Exchange. The research was based on an applicable goal and it is descriptive and post-event in terms of nature. The sample of the research consists of 89 companies listed in Tehran Stock Exchange and the research period was from 2004 to 2011. In order to examine the research hypothesis, a multivariate regression is utilized using panel data. The results indicate spontaneous use of intellectual capital variable and the remaining profit according to the accepted principles of accounting increase description power of the market value fluctuations of the corporate remarkably
Economic value added of intellectual capital on the market value of listed companies in Tehran Stock Exchange
The present research studies the effects of the economic value added (EVA) and the intellectual capital on value of the listed companies’ value in Tehran Stock Exchange. The research was based on an applicable goal and it is descriptive and post-event in terms of nature. The sample of the research consists of 89 companies listed in Tehran Stock Exchange and the research period was from 2004 to 2011. In order to examine the research hypothesis, a multivariate regression is utilized using panel data. The results indicate spontaneous use of intellectual capital variable and the remaining profit according to the accepted principles of accounting increase description power of the market value fluctuations of the corporate remarkably
A multi-depot location routing problem to reduce the differences between the vehicles’ traveled distances; a comparative study of heuristics
Microencapsulation of saffron petal anthocyanins with cress seed gum compared with Arabic gum through freeze drying
In this research, encapsulation efficiency of cress seed gum (CSG) as a native hydrocolloid was compared with Arabic gum (AG) and maltodextrin (dextrose equivalent of 20 (M20), and 7 (M7)) for saffron (Crocus sativus) petal's extract by freeze drying method. Combinations of CSG-M20, AG-M20, and M7-M20 with ratios of 50:50 and M20 alone (100%) were used as wall materials. A mixture of 1:5 (based on dry matter) between core (concentrated anthocyanin extract of saffron petal) and wall materials were freeze dried and stability of encapsulated anthocyanins along with color parameters (a∗, b∗, L∗, C, H° and TCD) of final powders were measured during 10 weeks of storage (at 35 °C as an accelerated method). Total anthocyanins were determined through pH differential method every week. Four prepared formulations of encapsulated powders didn't show any significant differences (P > 0.01) in terms of total anthocyanin content measured immediately after production and after 10 weeks storage. AG-M20 mixture and M20 alone showed the highest and lowest TCD, respectively. The mixture of CSG-M20 in comparison with AG-M20 and M20 had the same protecting effect (P < 0.01) but showed a relatively high TCD (9.33). © 2015 Elsevier Ltd. All rights reserved
Simvastatin decreases hepatic ischaemia/reperfusion-induced liver and lung injury in rats
Liver failure is still a significant clinical problem after transplantation surgery,
tissue resections (the Pringle manoeuvre) and haemorrhagic shock. The restoration
of blood flow to an ischaemic region leads to tissue injury at a greater
rate than the original ischaemic insult, an event termed "ischaemia-reperfusion
injury" (I/R). Despite advances in surgical techniques, I/R still poses a problem
of clinical importance. In this research, we studied the effect of simvastatin
pretreatment on liver and lung injury induced by hepatic I/R.
Rats were subjected to 30 min of ischaemia followed by 24 h of reperfusion.
Simvastatin (10 mg/kg) was administered orally from three days before the
operation. After the reperfusion time, serum ALT, AST, LDH and TNF a levels
were studied and liver and lung tissues were stained with haematoxylin and
eosin and TUNEL to detect apoptotic cells.
Serum aminotransferase activity and LDH and TNFα levels were increased markedly
by hepatic I/R, and these were suppressed significantly by simvastatin. The
tissue injury index and the number of apoptotic cells via TUNEL staining in the
liver and lungs were higher in the I/R group than in the I/R + simvastatin group.
These results suggest that simvastatin ameliorates I/R-induced liver and lung tissue
damage by inhibiting the level of inflammation and the apoptotic pathways.
Simvastatin administration may therefore provide protection against the adverse
effects of I/R injury in liver transplantation
An advanced computational intelligent framework to predict shear sonic velocity with application to mechanical rock classification
Shear sonic wave velocity (Vs) has a wide variety of implications, from reservoir management and development to geomechanical and geophysical studies. In the current study, two approaches were adopted to predict shear sonic wave velocities (Vs) from several petrophysical well logs, including gamma ray (GR), density (RHOB), neutron (NPHI), and compressional sonic wave velocity (Vp). For this purpose, five intelligent models of random forest (RF), extra tree (ET), Gaussian process regression (GPR), and the integration of adaptive neuro fuzzy inference system (ANFIS) with differential evolution (DE) and imperialist competitive algorithm (ICA) optimizers were implemented. In the first approach, the target was estimated based only on Vp, and the second scenario predicted Vs from the integration of Vp, GR, RHOB, and NPHI inputs. In each scenario, 8061 data points belonging to an oilfield located in the southwest of Iran were investigated. The ET model showed a lower average absolute percent relative error (AAPRE) compared to other models for both approaches. Considering the first approach in which the Vp was the only input, the obtained AAPRE values for RF, ET, GPR, ANFIS + DE, and ANFIS + ICA models are 1.54%, 1.34%, 1.54%, 1.56%, and 1.57%, respectively. In the second scenario, the achieved AAPRE values for RF, ET, GPR, ANFIS + DE, and ANFIS + ICA models are 1.25%, 1.03%, 1.16%, 1.63%, and 1.49%, respectively. The Williams plot proved the validity of both one-input and four-inputs ET model. Regarding the ET model constructed based on only one variable,Williams plot interestingly showed that all 8061 data points are valid data. Also, the outcome of the Leverage approach for the ET model designed with four inputs highlighted that there are only 240 "out of leverage" data sets. In addition, only 169 data are suspected. Also, the sensitivity analysis results typified that the Vp has a higher effect on the target parameter (Vs) than other implemented inputs. Overall, the second scenario demonstrated more satisfactory Vs predictions due to the lower obtained errors of its developed models. Finally, the two ET models with the linear regression model, which is of high interest to the industry, were applied to diagnose candidate layers along the formation for hydraulic fracturing. While the linear regression model fails to accurately trace variations of rock properties, the intelligent models successfully detect brittle intervals consistent with field measurements
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