A direct calculation of critical exponents of two-dimensional anisotropic Ising model

Using an exact solution of the one-dimensional (1D) quantum transverse-field Ising model (TFIM), we calculate the critical exponents of the two-dimensional (2D) anisotropic classical Ising model (IM). We verify that the exponents are the same as those of isotropic classical IM. Our approach provides an alternative means of obtaining and verifying these well-known results.Comment: 3 pages, no figures, accepted by Commun. Theor. Phys.(IPCAS

RFID Technology Enhancing Supply Chain Competence and E-Business: An Opportunity or a Threat?

Radio Frequency Identification (RFID), which uses radio waves to identify objects, was discovered in 1930s for military purposes and it transformed into commercial uses in 1980s in the United States. In this paper, we explore the research domains in RFID technology, innovation and diffusion theory, and supply chain management within the existing literature for exploring whether RFID enhances supply chain competence and ebusiness. This paper also forms a preliminary study base for researchers who may wish to carry on future research in this area

Symmetric duality for a class of nondifferentiable multi-objective fractional variational problems

AbstractWe introduce a symmetric dual pair for a class of nondifferentiable multi-objective fractional variational problems. Weak, strong, converse and self duality relations are established under certain invexity assumptions. The paper includes extensions of previous symmetric duality results for multi-objective fractional variational problems obtained by Kim, Lee and Schaible [D.S. Kim, W.J. Lee, S. Schaible, Symmetric duality for invex multiobjective fractional variational problems, J. Math. Anal. Appl. 289 (2004) 505–521] and symmetric duality results for the static case obtained by Yang, Wang and Deng [X.M. Yang, S.Y. Wang, X.T. Deng, Symmetric duality for a class of multiobjective fractional programming problems, J. Math. Anal. Appl. 274 (2002) 279–295] to the dynamic case

Tweet topics and sentiments relating to COVID-19 vaccination among Australian Twitter users: Machine learning analysis

Background: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment, there have been no signs of remission, and there is no proven effective cure. Vaccination is the primary biomedical preventive measure against the novel coronavirus. However, public bias or sentiments, as reflected on social media, may have a significant impact on the progression toward achieving herd immunity. Objective: This study aimed to use machine learning methods to extract topics and sentiments relating to COVID-19 vaccination on Twitter. Methods: We collected 31,100 English tweets containing COVID-19 vaccine–related keywords between January and October 2020 from Australian Twitter users. Specifically, we analyzed tweets by visualizing high-frequency word clouds and correlations between word tokens. We built a latent Dirichlet allocation (LDA) topic model to identify commonly discussed topics in a large sample of tweets. We also performed sentiment analysis to understand the overall sentiments and emotions related to COVID-19 vaccination in Australia. Results: Our analysis identified 3 LDA topics: (1) attitudes toward COVID-19 and its vaccination, (2) advocating infection control measures against COVID-19, and (3) misconceptions and complaints about COVID-19 control. Nearly two-thirds of the sentiments of all tweets expressed a positive public opinion about the COVID-19 vaccine; around one-third were negative. Among the 8 basic emotions, trust and anticipation were the two prominent positive emotions observed in the tweets, while fear was the top negative emotion. Conclusions: Our findings indicate that some Twitter users in Australia supported infection control measures against COVID-19 and refuted misinformation. However, those who underestimated the risks and severity of COVID-19 may have rationalized their position on COVID-19 vaccination with conspiracy theories. We also noticed that the level of positive sentiment among the public may not be sufficient to increase vaccination coverage to a level high enough to achieve vaccination-induced herd immunity. Governments should explore public opinion and sentiments toward COVID-19 and COVID-19 vaccination, and implement an effective vaccination promotion scheme in addition to supporting the development and clinical administration of COVID-19 vaccines

The Discrete AKNS-D Hierarchy

In this paper, we consider the discrete AKNS-D hierarchy, find the construction of the hierarchy, prove the bilinear identity and give the construction of the $\tau$-functions of this hierarchy.Comment: 11 page

Observation of magnetoelectric behavior at room temperature in Pb(Fe1-xTix)O3

The coexistence of ferroelectric and ferromagnetic properties at room temperature is very rarely observed. We have been successful in converting ferroelectric PbTiO3 into a magnetoelectric material by partly substituting Fe at the Ti site. The Pb(Fe1-xTix)O3 system exhibits ferroelectric and ferromagnetic ordering at room temperature. Even more remarkably, our results demonstrate a coupling between the two order parameters. Hence it could be a futuristic material to provide cost effective and simple path for designing novel electromagnetic devices.Comment: Total 14 pages of text and figure

Effect of yaw angle on flow structure and cross-flow force around a circular cylinder

Flow around an inclined circular cylinder at yaw angles of α = 0°, 30°, 45°, and 60° has been numerically studied using the delayed detached eddy simulation at a Reynolds number of 1.4 × 104. Periodic boundary conditions are utilized to minimize the end effect. The focus is to explore the effect of yaw angle on the flow structure and the spatial distribution of the cross-flow forces. For the normal flow case, the modulation of the span-wise averaged lift force coefficient is found to be related to the unstable shear layer. For the inclined cases, contours of the sectional lift force coefficient show that the local vortex shedding staggers in time along the axial span at the early stage of the simulation, when the flow approaches the cylinder. After the flow reaches the quasi-periodic state, the axial difference disappears for α \u3e 45° but not for α = 30°. In particular, the axial difference of the sectional lift force coefficient results in a near-zero value of the span-wise averaged lift force coefficient. The transition from a two-dimensional flow to a three-dimensional one is not captured in the current simulation. However, wake visualization indicates a mitigation of von Kármán vortex shedding when the yaw angle is greater than 30°. Although the Strouhal number is well predicted by the Independence Principle (IP), other flow properties are less agreeable with the prediction by IP

Slower Speed and Stronger Coupling: Adaptive Mechanisms of Self-Organized Chaos Synchronization

We show that two initially weakly coupled chaotic systems can achieve self-organized synchronization by adaptively reducing their speed and/or enhancing the coupling strength. Explicit adaptive algorithms for speed-reduction and coupling-enhancement are provided. We apply these algorithms to the self-organized synchronization of two coupled Lorenz systems. It is found that after a long-time self-organized process, the two coupled chaotic systems can achieve synchronization with almost minimum required coupling-speed ratio.Comment: 4 pages, 5 figure

Confocal/two-photon microscopy in studying colonisation of cancer cells in bone using xenograft mouse models

Confocal and two-photon microscopy has been widely used in bone research to not only produce high quality, three-dimensional images but also to provide valuable structural and quantitative information. In this article, we describe step-by-step protocols for confocal and two-photon microscopy to investigate earlier cellular events during colonisation of cancer cells in bone using xenograft mouse models. This includes confocal/two-photon microscopy imaging of paraformaldehyde fixed thick bone sections and frozen bone samples

Optimal Sizing of Waste Heat Recovery Systems for Dynamic Engine Conditions

In this study, a methodology for optimal sizing of waste heat recovery (WHR) systems is presented. It deals with dynamic engine conditions. This study focuses on Euro-VI truck applications with a mechanically coupled Organic Rankine Cycle-based WHR system. An alternating optimization architecture is developed for optimal system sizing and control of the WHR system. The sizing problem is formulated as a fuel consumption and system cost optimization problem using a newly developed, scalable WHR system model. Constraints related to safe WHR operation and system mass are included in this methodology. The components scaled in this study are the expander and the EGR and exhaust gas evaporators. The WHR system size is optimized over a hot World Harmonized Transient Cycle (WHTC), which consists of urban, rural and highway driving conditions. The optimal component sizes are found to vary for these different driving conditions. By implementing a switching model predictive control (MPC) strategy on the optimally sized WHR system, its performance is validated. The net fuel consumption is found to be reduced by 1.1% as compared to the originally sized WHR system over the total WHTC