Cosmology, Standard Models, and Homogeneous Rotating Models

2018 ◽  
pp. 185-268
Keyword(s):  
Standard Models

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.

Indigenization in a downgraded continuum: Ideologies behind phonetic variation in Namibian Afrikaans

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Gerald Stell
Keyword(s):  
South Africa ◽  
Power Relations ◽  
African Country ◽  
Language Ideologies ◽  
Ethnically Diverse ◽  
Official Language ◽  
Phonetic Variation ◽  
Variation Patterns ◽  
Standard Models

AbstractThis study generally looks at indigenization in languages historically introduced and promoted by colonial regimes. The case study that it presents involves Namibia, a Subsaharan African country formerly administered by South Africa, where Afrikaans was the dominant official language before being replaced by English upon independence. Afrikaans in Namibia still functions as an informal urban lingua franca while being spoken as a native language by substantial White and Coloured minorities. To what extent does the downranking of Afrikaans in Namibia co-occur with divergence from standard models historically located in South Africa? To answer this question, the study identifies variation patterns in Namibian Afrikaans phonetic data elicited from ethnically diverse young urban informants and links these patterns with perceptions and language ideologies. The phonetic data reveal divergence between Whites and Non-Whites and some convergence among Black L2 Afrikaans-speakers with Coloured varieties, while suggesting that a distinctive Black variety is emerging. The observed trends generally reflect perceived ethnoracial distinctions and segregation. They must be read against the background of shifting inter-group power relations and sociolinguistic prestige norms in independent Namibia, as well as of emergent ethnically inclusive Black urban identities.

scholarly journals PHL 417: a zirconium-rich pulsating hot subdwarf (V366 Aquarid) discovered in K2 data

2020 ◽  
Vol 499 (3) ◽  
pp. 3738-3748
Author(s):  
R H Østensen ◽  
C S Jeffery ◽  
H Saio ◽  
J J Hermes ◽  
J H Telting ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Helium Abundance ◽  
The Sun ◽  
The Third ◽  
Short Period ◽  
Standard Models ◽  
Hot Subdwarfs ◽  
Amplitude Mode ◽  
Rare Group

ABSTRACT The Kepler spacecraft observed the hot subdwarf star PHL 417 during its extended K2 mission, and the high-precision photometric light curve reveals the presence of 17 pulsation modes with periods between 38 and 105 min. From follow-up ground-based spectroscopy, we find that the object has a relatively high temperature of 35 600 K, a surface gravity of $\log g / {\rm cm\, s^{-2}}\, =\, 5.75$ and a supersolar helium abundance. Remarkably, it also shows strong zirconium lines corresponding to an apparent +3.9 dex overabundance compared with the Sun. These properties clearly identify this object as the third member of the rare group of pulsating heavy-metal stars, the V366-Aquarii pulsators. These stars are intriguing in that the pulsations are inconsistent with the standard models for pulsations in hot subdwarfs, which predicts that they should display short-period pulsations rather than the observed longer periods. We perform a stability analysis of the pulsation modes based on data from two campaigns with K2. The highest amplitude mode is found to be stable with a period drift, $\dot{P}$, of less than 1.1 × 10−9 s s−1. This result rules out pulsations driven during the rapid stages of helium flash ignition.

The distributional structure of finite moving-average processes

1988 ◽  
Vol 25 (02) ◽  
pp. 313-321 ◽  
Author(s):  
ED McKenzie
Keyword(s):  
Moving Average ◽  
Markov Property ◽  
Covariance Structure ◽  
Time Reversibility ◽  
Linear Processes ◽  
Joint Distributions ◽  
Moving Average Processes ◽  
Standard Models ◽  
Non Gaussian ◽  
Analysis Of Time Series

Analysis of time-series models has, in the past, concentrated mainly on second-order properties, i.e. the covariance structure. Recent interest in non-Gaussian and non-linear processes has necessitated exploration of more general properties, even for standard models. We demonstrate that the powerful Markov property which greatly simplifies the distributional structure of finite autoregressions has an analogue in the (non-Markovian) finite moving-average processes. In fact, all the joint distributions of samples of a qth-order moving average may be constructed from only the (q + 1)th-order distribution. The usefulness of this result is illustrated by references to three areas of application: time-reversibility; asymptotic behaviour; and sums and associated point and count processes. Generalizations of the result are also considered.

scholarly journals Directionally-Enhanced Binary Multi-Objective Particle Swarm Optimisation for Load Balancing in Software Defined Networks

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3356
Author(s):  
Mustafa Hasan Albowarab ◽  
Nurul Azma Zakaria ◽  
Zaheera Zainal Abidin
Keyword(s):  
Particle Swarm Optimization ◽  
Load Balancing ◽  
Mathematical Formulation ◽  
Particle Swarm ◽  
Solution Space ◽  
Particle Swarm Optimisation ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Crowding Distance ◽  
Standard Models

Various aspects of task execution load balancing of Internet of Things (IoTs) networks can be optimised using intelligent algorithms provided by software-defined networking (SDN). These load balancing aspects include makespan, energy consumption, and execution cost. While past studies have evaluated load balancing from one or two aspects, none has explored the possibility of simultaneously optimising all aspects, namely, reliability, energy, cost, and execution time. For the purposes of load balancing, implementing multi-objective optimisation (MOO) based on meta-heuristic searching algorithms requires assurances that the solution space will be thoroughly explored. Optimising load balancing provides not only decision makers with optimised solutions but a rich set of candidate solutions to choose from. Therefore, the purposes of this study were (1) to propose a joint mathematical formulation to solve load balancing challenges in cloud computing and (2) to propose two multi-objective particle swarm optimisation (MP) models; distance angle multi-objective particle swarm optimization (DAMP) and angle multi-objective particle swarm optimization (AMP). Unlike existing models that only use crowding distance as a criterion for solution selection, our MP models probabilistically combine both crowding distance and crowding angle. More specifically, we only selected solutions that had more than a 0.5 probability of higher crowding distance and higher angular distribution. In addition, binary variants of the approaches were generated based on transfer function, and they were denoted by binary DAMP (BDAMP) and binary AMP (BAMP). After using MOO mathematical functions to compare our models, BDAMP and BAMP, with state of the standard models, BMP, BDMP and BPSO, they were tested using the proposed load balancing model. Both tests proved that our DAMP and AMP models were far superior to the state of the art standard models, MP, crowding distance multi-objective particle swarm optimisation (DMP), and PSO. Therefore, this study enables the incorporation of meta-heuristic in the management layer of cloud networks.

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