An Investigation of the Casimir Energy for a Fermion Coupled to the Sine-Gordon Soliton with Parity Decomposition

We consider a fermion chirally coupled to a prescribed pseudoscalar field in the form of the soliton of the sine-Gordon model and calculate and investigate the Casimir energy and all of the relevant quantities for each parity channel, separately. We present and use a simple prescription to construct the simultaneous eigenstates of the Hamiltonian and parity in the continua from the scattering states. We also use a prescription we had introduced earlier to calculate unique expressions for the phase shifts and check their consistency with both the weak and strong forms of the Levinson theorem. In the graphs of the total and parity decomposed Casimir energies as a function of the parameters of the pseudoscalar field distinctive deformations appear whenever a fermionic bound state energy level with definite parity crosses the line of zero energy. However, the latter graphs reveal some properties of the system which cannot be seen from the graph of the total Casimir energy. Finally we consider a system consisting of a valence fermion in the ground state and find that the most energetically favorable configuration is the one with a soliton of winding number one, and this conclusion does not hold for each parity, separately.Comment: 13 pages, 8 figure

Correlation between Subjective Nasal Patency and Intranasal Airflow Distribution

Objectives (1) Analyze the relationship between intranasal airflow distribution and subjective nasal patency in healthy and nasal airway obstruction (NAO) cohorts using computational fluid dynamics (CFD). (2) Determine whether intranasal airflow distribution is an important objective measure of airflow sensation that should be considered in future NAO virtual surgery planning. Study Design Cross-sectional. Setting Academic tertiary medical center and academic dental clinic. Subjects and Methods Three-dimensional models of nasal anatomy were created based on computed tomography scans of 15 patients with NAO and 15 healthy subjects and used to run CFD simulations of nasal airflow and mucosal cooling. Subjective nasal patency was quantified with a visual analog scale (VAS) and the Nasal Obstruction Symptom Evaluation (NOSE). Regional distribution of nasal airflow (inferior, middle, and superior) was quantified in coronal cross sections in the narrowest nasal cavity. The Pearson correlation coefficient was used to quantify the correlation between subjective scores and regional airflows. Results Healthy subjects had significantly higher middle airflow than patients with NAO. Subjective nasal patency had no correlation with inferior and superior airflows but a high correlation with middle airflow (|r| = 0.64 and |r| = 0.76 for VAS and NOSE, respectively). Anterior septal deviations tended to shift airflow inferiorly, reducing middle airflow and reducing mucosal cooling in some patients with NAO. Conclusion Reduced middle airflow correlates with the sensation of nasal obstruction, possibly due to a reduction in mucosal cooling in this region. Further research is needed to elucidate the role of intranasal airflow distribution in the sensation of nasal airflow

Comparative Analysis of the Chemical Composition of Juniperus Excelsa Ssp. Polycarpos Bark and Wood Extracts

In the present study, extracts from the bark and wood of Juniperus excelsa ssp. polycarpos were obtained with acetone solvent. Chemical composition were analyzed and compared by gas chromatography-mass spectrometry (GC-MS). The results showed that the major components identified in the bark acetone extract as trimethylsilyl (TMS) derivatives were β-d-glucofuranose, 1,2,3,5,6-pentakis-O-(TMS) (19.97%), followed by pimaric acid TMS (18.89%), d-mannopyranose, 1,2,3,4,6-pentakis-O-(TMS) (13.90%), d-fructose, 1,3,4,5,6-pentakis-O-(TMS) (12.37%). The major components identified in the wood acetone extract as trimethylsilyl (TMS) derivatives were pimaric acid TMS (24.56%), followed by α-d-glucopyranoside, 1,3,4,6-tetrakis-O-(TMS)-β-d-fructofuranosyl 2,3,4,6-tetrakis-O-(TMS) (21.39%), β-d-galactopyranose, 1,2,3,4,6-pentakis-O-(TMS) (12.10%), d-glucose, 2,3,4,5,6-pentakis-O-(TMS) (9.97%), trifluoromethyl-bis-(TMS)methyl ketone (9.32%). One of the more important components identified both in the bark and wood extracts was pimaric acid TMS. Cedrol as the essential oil was found in the acetone wood extract (0.72%)

An integrated neural network algorithm for optimum performance assessment of auto industry with multiple outputs and corrupted data and noise

In the real world encountering with noisy and corrupted data is unavoidable. Auto industry sector (AIS) as a one of the significant industry encounters with noisy and corrupted data regarding to its rapid development. Therefore, developing the performance assessment in this situation is so helpful for this industry. As Data envelopment Analysis (DEA) could not deal with noisy and corrupted data, the alternative method(s) is very important. As one of excellent and promising feature of artificial neural networks (ANNs) are theirs flexibility and robustness in noisy situation, they are a good alternative. This study proposes a non-parametric efficiency frontier analysis method based on the adaptive neural network technique for measuring efficiency as a complementary tool for the common techniques for efficiency assessment in the previous studies. The proposed computational method is able to find a stochastic frontier based on a set of input–output observational data and do not require explicit assumptions about the function structure of the stochastic frontier. In this algorithm, for calculating the efficiency scores of auto industry in various countries, a similar approach to econometric methods has been used. Moreover, the effect of the return to scale of AIS on its efficiency is included and the unit used for the correction is selected by notice of its scale (under constant return to scale assumption). Another feature of proposed algorithm is its ability to calculate efficiency for multiple outputs. An example using real data is presented for illustrative purposes. In the application to the auto industries, we find that the neural network provide more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored. To test the robustness of the efficiency results of the proposed method, the ability of proposed ANN algorithm in dealing with noisy and corrupted data is compared with Data Envelopment Analysis (DEA). Results of the robustness check show that the proposed algorithm is much more robust to the noise and corruption in input data than DEA

The missing dwarf galaxies of the Local Group

We study the Local Group (LG) dwarf galaxy population predicted by the APOSTLE ΛCDM cosmological hydrodynamics simulations. These indicate that: (i) the total mass within 3 Mpc of the Milky Way-Andromeda midpoint (M3Mpc) typically exceeds ∼3 times the sum of the virial masses (M200crit) of the two primaries and (ii) the dwarf galaxy formation efficiency per unit mass is uniform throughout the volume. This suggests that the satellite population within the virial radii of the Milky Way and Andromeda should make up fewer than one third of all LG dwarfs within 3 Mpc. This is consistent with the fraction of observed LG galaxies with stellar mass M* > 107 M⊙ that are satellites (12 out of 42; i.e., 28 per cent). For the APOSTLE galaxy mass-halo mass relation, the total number of such galaxies further suggests a LG mass of M3Mpc ∼ 1013 M⊙. At lower galaxy masses, however, the observed satellite fraction is substantially higher (42 per cent for M* > 105 M⊙). If this is due to incompleteness in the field sample, then ∼50 dwarf galaxies at least as massive as the Draco dwarf spheroidal must be missing from the current LG field dwarf inventory. The incompleteness interpretation is supported by the pronounced flattening of the LG luminosity function below M* ∼ 107 M⊙, and by the scarcity of low-surface brightness LG field galaxies compared to satellites. The simulations indicate that most missing dwarfs should lie near the virial boundaries of the two LG primaries, and predict a trove of nearby dwarfs that await discovery by upcoming wide-field imaging surveys

Wood-based construction project supplier selection under uncertain starting date

There is a growing interest in supply management systems in today's competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers' control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this paper, we address the supplier selection problem (SSP) in wood-based construction industry (housing projects) in the presence of project commencement uncertainties. Based on the suppliers' (vendors') reaction towards these uncertainties in the delivery time, we explore two cases: (a) supplier selection with buyer penalty for a delay (SSPD) where the price of product increases with the delay; (b) supplier selection with quantity reduction for a buyer delay (SSQRD). Three heuristic-based supplier selection approaches are proposed and tested on randomly generated data sets. The proposed approaches show promising result