Quantum Corrals, Eigenmodes and Quantum Mirages in s-wave Superconductors

We study the electronic structure of magnetic and non-magnetic quantum corrals embedded in s-wave superconductors. We demonstrate that a quantum mirage of an impurity bound state peak can be projected from the occupied into the empty focus of a non-magnetic quantum corral via the excitation of the corral's eigenmodes. We observe an enhanced coupling between magnetic impurities inside the corral, which can be varied through oscillations in the corral's impurity potential. Finally, we discuss the form of eigenmodes in magnetic quantum corrals.Comment: 4 pages, 4 figure

Aerothermal modeling. Executive summary

One of the significant ways in which the performance level of aircraft turbine engines has been improved is by the use of advanced materials and cooling concepts that allow a significant increase in turbine inlet temperature level, with attendant thermodynamic cycle benefits. Further cycle improvements have been achieved with higher pressure ratio compressors. The higher turbine inlet temperatures and compressor pressure ratios with corresponding higher temperature cooling air has created a very hostile environment for the hot section components. To provide the technology needed to reduce the hot section maintenance costs, NASA has initiated the Hot Section Technology (HOST) program. One key element of this overall program is the Aerothermal Modeling Program. The overall objective of his program is to evolve and validate improved analysis methods for use in the design of aircraft turbine engine combustors. The use of such combustor analysis capabilities can be expected to provide significant improvement in the life and durability characteristics of both combustor and turbine components

Flourishing Scale: Evidence of Its Suitability to the Brazilian Context

The present study aimed to support the psychometric adequacy of the Flourishing Scale in the Brazilian context. It counted with a non-probabilistic sample of 171 undergraduate students (Study 1) and 177 individuals from the general population (Study 2). Participants answered to the Flourishing Scale, the Positivity Scale, and demographic questions. The studies showed a one-factor solution, with satisfactory internal consistency, providing empirical evidence of convergent validity through the average variance extracted and showing positive correlation with the construct of positivity. Furthermore, a confirmatory factor analysis (ML) corroborated the recommended one-factor model. This measure demonstrated to be psychometrically suitable for use in the Brazilian context. Thus, this study provided a brief and low-cost measure of well-being from the perspective of flourishing, being adequate to be used in the research field.The present study aimed to support the psychometric adequacy of the Flourishing Scale in the Brazilian context. It counted with a non-probabilistic sample of 171 undergraduate students (Study 1) and 177 individuals from the general population (Study 2). Participants answered to the Flourishing Scale, the Positivity Scale, and demographic questions. The studies showed a one-factor solution, with satisfactory internal consistency, providing empirical evidence of convergent validity through the average variance extracted and showing positive correlation with the construct of positivity. Furthermore, a confirmatory factor analysis (ML) corroborated the recommended one-factor model. This measure demonstrated to be psychometrically suitable for use in the Brazilian context. Thus, this study provided a brief and low-cost measure of well-being from the perspective of flourishing, being adequate to be used in the research field

Ladders for Wilson Loops Beyond Leading Order

We set up a general scheme to resum ladder diagrams for the quark-anti-quark potential in N=4 super-Yang-Mills theory, and do explicit calculations at the next-to-leading order. The results perfectly agree with string theory in AdS(5)xS(5) when continued to strong coupling, in spite of a potential order-of-limits problem.Comment: 18 pages, 5 figure

Using probe electrospray ionization mass spectrometry and machine learning for detecting pancreatic cancer with high performance

A rapid blood-based diagnostic modality to detect pancreatic ductal adenocarcinoma (PDAC) with high accuracy is an unmet medical need. The study aimed to validate a unique diagnosis system using Probe Electrospray Ionization Mass Spectrometry (PESI-MS) and Machine Learning to the diagnosis of PDAC. Peripheral blood samples were collected from a total of 322 consecutive PDAC patients and 265 controls with a family history of PDAC. Five µl of serum samples were analyzed using PESI-MS system. The mass spectra from each specimen were then fed into machine learning algorithms to discriminate between control and cancer cases. A total of 587 serum samples were analyzed. The sensitivity of the machine learning algorithm using PESI-MS profiles to identify PDAC is 90.8% with specificity of 91.7% (95% CI 83.9%-97.4% and 82.8%-97.7% respectively). Combined PESI-MS profiles with age and CA19-9 as predictors, the accuracy for stage 1 or 2 of PDAC is 92.9% and for stage 3 or 4 is 93% (95% CI 86.3-98.2; 87.9-97.4 respectively). The accuracy and simplicity of the PESI-MS profiles combined with machine learning provide an opportunity to detect PDAC at an early stage and must be applicable to the examination of at-risk populations. [Abstract copyright: AJTR Copyright © 2020.