scholarly journals Gravitational instantons with faster than quadratic curvature decay (II)

2019 ◽  
Vol 2019 (756) ◽  
pp. 259-284 ◽  
Author(s):  
Gao Chen ◽  
Xiuxiong Chen
Keyword(s):  
Gravitational Instantons ◽  
Gravitational Instanton ◽  
Asymptotic Rate ◽  
Curvature Decay ◽  
Standard Models

AbstractThis is our second paper in a series to study gravitational instantons, i.e. complete hyperkähler 4-manifolds with faster than quadratic curvature decay. We prove two main theorems: (i) The asymptotic rate of gravitational instantons to the standard models can be improved automatically. (ii) Any ALF-D_{k} gravitational instanton must be the Cherkis–Hitchin–Ivanov–Kapustin–Lindström–Roček metric.

scholarly journals GRAVITATIONAL INSTANTON AND COSMOLOGICAL TERM

2009 ◽  
Vol 24 (20n21) ◽  
pp. 3865-3891 ◽  
Author(s):  
SHE-SHENG XUE
Keyword(s):  
Black Holes ◽  
Energy Density ◽  
Radiation Energy ◽  
Flat Space ◽  
Cosmological Term ◽  
Radiation Energy Density ◽  
Gravitational Instantons ◽  
Gravitational Instanton ◽  
Inflationary Phase ◽  
The Universe

Quantum fluctuation of unstable modes about gravitational instantons causes the instability of flat space at finite temperature, leading to the spontaneous process of nucleating quantum black holes. The energy-density of quantum black holes, depending on the initial temperature, gives the cosmological term, which naturally accounts for the inflationary phase of the early universe. The reheating phase is attributed to the Hawking radiation and annihilation of these quantum black holes. Then, the radiation energy-density dominates over the energy-density of quantum black holes, the universe started the standard cosmology phase. In this phase the energy-density of quantum black holes depends on the reheating temperature. It asymptotically approaches to the cosmological constant in matter domination phase, consistently with current observations.

scholarly journals Entropy Product Formula for Gravitational Instanton

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Parthapratim Pradhan
Keyword(s):  
Black Hole ◽  
Product Formula ◽  
Schwarzschild Black Hole ◽  
Gravitational Instantons ◽  
Gravitational Instanton ◽  
Entropy Product ◽  
Independent Features

We investigate the entropy product formula for various gravitational instantons. We speculate that due to the mass-independent features of the said instatons they are universal as well as quantized. For isolated Euclidean Schwarzschild black hole, these properties simply fail.

Quantum Calculation of Proton and Other Charge Transfer Steps in Voltage Sensing in the Kv1.2 Channel

2019 ◽  
Author(s):  
Alisher M Kariev ◽  
Michael Green
Keyword(s):  
Charge Transfer ◽  
Energy Charge ◽  
Quantum Calculation ◽  
Quantum Calculations ◽  
Gating Current ◽  
Transmembrane Segment ◽  
Voltage Sensing ◽  
Standard Models ◽  
Charge Displacement ◽  
Voltage Sensing Domain

Quantum calculations on 976 atoms of the voltage sensing domain of the K<sub>v</sub>1.2 channel, with protons in several positions, give energy, charge transfer, and other properties. Motion of the S4 transmembrane segment that accounts for gating current in standard models is shown not to occur; there is H<sup>+ </sup>transfer instead. The potential at which two proton positions cross in energy approximately corresponds to the gating potential for the channel. The charge displacement seems approximately correct for the gating current. Two mutations are accounted for (Y266F, R300cit, cit =citrulline). The primary conclusion is that voltage sensing depends on H<sup>+</sup> transfer, not motion of arginine charges.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

Boolean-valued structures

2018 ◽  
Author(s):  
Tim Button ◽  
Sean Walsh
Keyword(s):  
Model Theory ◽  
Order Logic ◽  
First Order Logic ◽  
Inference Rules ◽  
Mathematical Concepts ◽  
Semantic Framework ◽  
First Order ◽  
Standard Models ◽  
Boolean Valued Model ◽  
Semantic Values

Chapters 6-12 are driven by questions about the ability to pin down mathematical entities and to articulate mathematical concepts. This chapter is driven by similar questions about the ability to pin down the semantic frameworks of language. It transpires that there are not just non-standard models, but non-standard ways of doing model theory itself. In more detail: whilst we normally outline a two-valued semantics which makes sentences True or False in a model, the inference rules for first-order logic are compatible with a four-valued semantics; or a semantics with countably many values; or what-have-you. The appropriate level of generality here is that of a Boolean-valued model, which we introduce. And the plurality of possible semantic values gives rise to perhaps the ‘deepest’ level of indeterminacy questions: How can humans pin down the semantic framework for their languages? We consider three different ways for inferentialists to respond to this question.

Effective Field Theory in Particle Physics and Cosmology

2020 ◽  
Keyword(s):  
Field Theory ◽  
Effective Field Theory ◽  
Particle Physics ◽  
Large Scale ◽  
Effective Field ◽  
Effective Theory ◽  
Soft Collinear Effective Theory ◽  
Multiple Length Scales ◽  
Cosmological Observations ◽  
Standard Models

Effective field theory (EFT) is a general method for describing quantum systems with multiple-length scales in a tractable fashion. It allows us to perform precise calculations in established models (such as the standard models of particle physics and cosmology), as well as to concisely parametrize possible effects from physics beyond the standard models. EFTs have become key tools in the theoretical analysis of particle physics experiments and cosmological observations, despite being absent from many textbooks. This volume aims to provide a comprehensive introduction to many of the EFTs in use today, and covers topics that include large-scale structure, WIMPs, dark matter, heavy quark effective theory, flavour physics, soft-collinear effective theory, and more.

On the Relationship between Alonso's Theory of Movement and Wilson's Family of Spatial-Interaction Models

1981 ◽  
Vol 13 (2) ◽  
pp. 217-224 ◽  
Author(s):  
J Ledent
Keyword(s):  
Input Data ◽  
Spatial Interaction ◽  
System Of Equations ◽  
Interaction Models ◽  
Spatial Interaction Models ◽  
Standard Family ◽  
Original Contribution ◽  
Standard Models ◽  
The Relationship

This paper compares the system of equations underlying Alonso's theory of movement with that of Wilson's standard family of spatial-interaction models. It is shown that the Alonso model is equivalent to one of Wilson's four standard models depending on the assumption at the outset about which of the total outflows and/or inflows are known. This result turns out to supersede earlier findings—inconsistent only in appearance—which were derived independently by Wilson and Ledent. In addition to this, an original contribution of this paper—obtained as a byproduct of the process leading to the aforementioned result—is to provide an exact methodology permitting one to solve the Alonso model for each possible choice of the input data.

A complementary webometric ranking system based on the website quality and traffic measures: A study focusing on top-ranked world universities

2021 ◽  
pp. 1-18
Author(s):  
Sajjad Farashi ◽  
Saeed Bashirian
Keyword(s):  
Weight Vector ◽  
Quality Factors ◽  
Ranking System ◽  
Web Based ◽  
Website Quality ◽  
Scientific Advancement ◽  
Standard Models ◽  
Algorithm Framework ◽  
Scientific Results ◽  
Optimal Weight Vector

Ranking of universities regarding their web-based activities plays a pivotal role in promoting scientific advancement since it motivates the open access accessibility to scientific results. In this study, a new ranking system based on the website quality factors and traffic evaluation was proposed. Since top-ranked universities are usually considered as the standard models for lower ranked ones, the focus of this study was on top-ranked universities. The proposed ranking was compared with well-known Webometrics ranking system. The website traffic and quality assessment were acquired for websites of top-ranked world universities and the correlation between these indices and the Webometrics ranking was evaluated. The summation of the weighted value of obtained measures according to an optimal weight vector obtained by a genetic algorithm framework was used for ranking purposes. The results showed that the website total traffic size was correlated with Webometrics rank (R≈-0.6, p< 0.01). Also, using the weighted value of website quality and traffic measures, the proposed ranking system could predict Webometrics ranking by the accuracy of up to 69%. Even though the method was proposed for universities, it could be applied for ranking other types of centers or companies, provided that the suitable cost function for the genetics algorithm framework was defined.

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