1,262 research outputs found
Vacuum Stability of the wrong sign Scalar Field Theory
We apply the effective potential method to study the vacuum stability of the
bounded from above (unstable) quantum field potential. The
stability ( and the mass renormalization
( conditions force the effective
potential of this theory to be bounded from below (stable). Since bounded from
below potentials are always associated with localized wave functions, the
algorithm we use replaces the boundary condition applied to the wave functions
in the complex contour method by two stability conditions on the effective
potential obtained. To test the validity of our calculations, we show that our
variational predictions can reproduce exactly the results in the literature for
the -symmetric theory. We then extend the applications
of the algorithm to the unstudied stability problem of the bounded from above
scalar field theory where classical analysis prohibits the
existence of a stable spectrum. Concerning this, we calculated the effective
potential up to first order in the couplings in space-time dimensions. We
find that a Hermitian effective theory is instable while a non-Hermitian but
-symmetric effective theory characterized by a pure imaginary
vacuum condensate is stable (bounded from below) which is against the classical
predictions of the instability of the theory. We assert that the work presented
here represents the first calculations that advocates the stability of the
scalar potential.Comment: 21pages, 12 figures. In this version, we updated the text and added
some figure
Reactions with 5-Arylazo- and 5-Arylidene-4-thiohydantoin Derivatives
5-Arylazo-3-phenyl-4-thiohydantoins (IIa-g) have been prepared
and then treated with primary aromatic amines to afford the
corresponding 5-arylazo-4-arylimino-3-phenyl hydantoins (VIIa-c).
3-Phenyl-4-thiohydantoin reacted with aromatic aldehydes in the
presence of glacial acetic acid and fused sodium acetate to give
5-arylidene-3-phenyl-4-thiohydantoin derivatives (VIIIa-e). In the
coloured arylidene derivatives (VIII,a d, e) on treatment with alkyland/
or arylmagnesium halide addition occurs to the exocyclic
double bond to give the products (IXa-e). The Grignard product
(Xa) was oxidised with a mixture of chromic acid in glacial acetic
acid to give phenyl parabanic acid and ethyl phenyl ketone
Detection and identification of Apple stem pitting virus and Apple stem grooving virus affecting apple and pear trees in Egypt
Apple stem pitting virus (ASPV) and Apple stem grooving virus (ASGV) are economically important and infect either individually or in mixed infection commercial apple and pear cultivars causing yield loses. Young green bud and/or base of petiole were collected from naturally infected apple and pear trees from different locations in Egypt. Both viruses were detected frequently in apple and pear samples. A total of 420 trees from 9 different orchards were tested using one-step RT-PCR; 13% and 17% of these samples were infected with ASPV and ASGV, respectively. Mixed infection with both viruses occurred in 4% of the tested trees. ELISA was reliable for detection of ASGV but not ASPV. Total RNA for one-step RT-PCR was isolated from 100 mg fresh affected apple and pear leaf tissue using Qiagen RNeasy plant mini-kit (Qiagen, Crawley, UK), according to the manufacturer’s instructions. The one step-RTPCR method was performed using ASPV and ASGV-specific primers for each virus. A 316 bp fragment for ASPV and 524bp fragment for ASGV were amplified and detected by gel electrophoresis analysis which indicated the presence of ASPV and ASGV in affected apple and pear cultivars. Southern blot hybridization of the amplified products to digoxigenin (DIG)-labeled cDNA probe for ASPV or ASGV confirmed the results obtained by electrophoresis analysis. No product was detected in amplified extracts of uninfected apple and pear samples. The detection of ASPV and ASGV by one step-RT-PCR assay was successful and appears useful for testing pome fruit germplasm in quarantine and budwood in certification programs.Keywords: Apple and pear, ASPV, ASGV, virus detection, One step RT-PCR, Southern blot hybridizatio
The effect of albumin administration on renal dysfunction after experimental surgical obstructive jaundice in male rats
AbstractThe aim was to study the influence of albumin supplementation on the changes of the kidney function and structure in cirrhotic rats induced by common bile duct ligation (BDL). Twenty-four male albino rats weighing 200–250g were divided into Group I: 6 rats underwent laparotomy alone, and the bile duct was only dissected from the surrounding tissue; Group II: 6 rats underwent a sham operation and received 2% albumin in their drinking water; Group III: 6 rats were subjected to bile duct ligation only; and Group IV: 6 rats were subjected to bile duct ligation and received a daily albumin 2% in drinking water. All rats were sacrificed after 4 weeks. We measured the liver and kidney functions and oxidative stress markers in the renal tissue and conducted a histological evaluation of the liver and kidney. The liver enzymes were decreased, but there was no significant difference in the bilirubin levels in group IV compared to group III. There was a significant elevation of serum creatinine in group III compared to group II, and serum creatinine was attenuated in group IV. The renal tissue catalase activity and reduced glutathione, as well as the nitric oxide levels, were significantly increased in group IV and were elevated in group III. Histologically, the livers of group IV showed degeneration and inflammatory cell infiltration with regeneration areas in which normal hepatocytes appeared. The kidneys of group IV showed recovery as well as areas of inflammatory cell infiltration. Some tubules appeared with normal epithelial lining. In conclusion, the results suggest that albumin partially improves the renal functions and structures after their disturbances as a result of BDL
Study on Quality of Pair Distribution Function for Direct Space Approach of Structure Investigation
Study of the structure characteristics of solid materials is a key for development of technological applications. Potential of direct space approach for structure determination and refinement using powder X-ray diffraction data depend on the quality of pair distribution function (PDF) plot. So, the effect of data collection conditions and diffractogram characteristics on the quality of PDF plot has been investigated in detail. In addition, errors and possible tolerance have been estimated. Some parameters affect only either the X-ray diffractogram or PDF plots and others affect both. Considering the errors and tolerance, direct space approach can be confidently used for structure refinement, where the error did not exceed 10.0 % for inter-atomic radial distance longer than » 2.0 ? and 5.0 % for longer than » 4.0 ?, which is accepted for structure refinement. As tolerance is considered, every time the value of the lattice parameter is changed to smaller or larger than the correct value (+ 8.0 %), it comes back to the initial correct one. Although, advanced synchrotron radiation shows better data, conventional source can be used successfully for structure investigation applying direct space approach
Precise Cerebrovascular Segmentation
© 2020 IEEE. Analyzing cerebrovascular changes using Time-of-Flight Magnetic Resonance Angiography (ToF-MRA) images can detect the presence of serious diseases and track their progress, e.g., hypertension. Such analysis requires accurate segmentation of the vasculature from the surroundings, which motivated us to propose a fully automated cerebral vasculature segmentation approach based on extracting both prior and current appearance features that capture the appearance of macro and micro-vessels. The appearance prior is modeled with a novel translation and rotation invariant Markov-Gibbs Random Field (MGRF) of voxel intensities with pairwise interaction analytically identified from a set of training data sets, while the current appearance is represented with a marginal probability distribution of voxel intensities by using a Linear Combination of Discrete Gaussians (LCDG) whose parameters are estimated by a modified Expectation-Maximization (EM) algorithm. The proposed approach was validated on 190 data sets using three metrics, which revealed high accuracy compared to existing approaches
Growth of N-dimensional Spherical Bubble within Viscous, Superheated Liquid Analytical Solution
In this paper, we present the study of the behavior of spherical bubble in N-di-mensions fluid. The fluid is a mixture of vapor and superheated liquid. The math-ematical model is formulated in N-dimensions fluid on the basis of continuity and momentum equations, and solved its analytically. The variable viscosity is taken into an account problem. The obtained results show that the radius of bubble in-creases with the decreasing of the value of N-dimensions. © 2021 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This is an open access article distributed under the CC BY-NC-ND 4.0 terms and conditions
PHYTOPHENOLICS COMPOSITION, HYPOLIPIDEMIC, HYPOGLYCEMIC AND ANTIOXIDATIVE EFFECTS OF THE LEAVES OF FORTUNELLA JAPONICA (THUNB.) SWINGLE
Objective: Fortunella japonica (Thunb.) Swingle is an evergreen shrub, its whole fruit, including the peel, is eaten. There have been few detailed phytophenolics composition reports on this genus and the hypoglycemic and hypolipidemic effects of the plant were not evaluated. Methods: Structures of the isolated compounds were elucidated by spectral analysis. Serum glucose level, activities of liver enzymes, total protein content, serum lipid profiles, antioxidant parameters and some glycolytic and gluconeogenic enzymes in streptozotocin (STZ)-induced diabetic rats were determined. The evaluation also carried out through determination of liver disorder biomarkers and histopathological examination of liver, kidney and pancreas. Results: Six phytophenolics were isolated, for the first time from the genus Fortunella as well as a sterol compound. Treatment with the ethanolic extract of F. japonica leaves effectively meliorated antioxidant markers and glycolytic enzymes. The histopathological analyzes also confirmed the experimental findings.Conclusion: The results show that the ethanolic extract has hypoglycemic, hypotriglyceridemic and antioxidant effects in STZ-induced diabetic rats, suggesting that this extract supplementation can be useful in preventing diabetic complications associated with hyperlipidemia and oxidative stress.Â
Application of Genetic Algorithm for the Discovery of Hidden Temporal Patterns in Earthquakes Data
<p style="text-align: justify; line-height: normal; margin: 0cm 30.5pt 10pt 21.3pt; unicode-bidi: embed; direction: ltr;" class="MsoNormal"><span style="font-family: "Times New Roman","serif"; font-size: 12pt; mso-ascii-theme-font: major-bidi; mso-hansi-theme-font: major-bidi; mso-bidi-theme-font: major-bidi;">Time Series Data mining (TSDM) is one of the most widely used technique that deals with temporal patterns. Genetic algorithm (GA) is a predictive TSDM search technique that is used for solving search/optimization problems. GA is based on the principles and mechanisms of natural selections to find the most nearest optimal solution available from a list of solutions. GA relies on a set of important fundamentals, such as chromosome, crossover and mutation. GA is applied to earthquakes data in the year 2003-2004 in the Suez Gulf in Egypt, gathered from the Egyptian National Seismic Network. The study does not aim to building time series models from the point of time, since the analysis neither include the time nor the prediction of when an earth quake will occur, but to determine the possibility of occurrence of a strong magnitude earthquake after specific sequence of previous earthquakes as temporal pattern. The temporal pattern cluster used is a "circle". The objective function used is a function that gives the highest percentage of correct classification. Empirical results show that crossover and mutation probabilities are 0.4 and .01 respectively for both the training and the testing sample. The algorithm yields 96.98% correct classification for the training sample, and 95.35% for the testing sample.</span></p
- …