Assessing the effects of technological progress on energy efficiency in the construction industry: A case of China

Energy-saving technologies in buildings have received great attention from energy efficiency researchers in the construction sector. Traditional research tends to focus on the energy used during building operation and in construction materials production, but it usually neglects the energy consumed in the building construction process. Very few studies have explored the impacts of technological progress on energy efficiency in the construction industry. This paper presents a model of the building construction process based on Cobb-Douglas production function. The model estimates the effects of technological progress on energy efficiency with the objective to examine the role that technological progress plays in energy savings in China's construction industry. The modeling results indicated that technological progress improved energy efficiency by an average of 7.1% per year from 1997 to 2014. Furthermore, three main technological progress factors (the efficiency of machinery and equipment, the proportion change of the energy structure, and research and development investment) were selected to analyze their effects on energy efficiency improvement. These positive effects were verified, and results show the effects of first two factors are significant. Finally, recommendations for promoting energy efficiency in the construction industry are proposed

Simplifying the mosaic description of DNA sequences

By using the Jensen-Shannon divergence, genomic DNA can be divided into compositionally distinct domains through a standard recursive segmentation procedure. Each domain, while significantly different from its neighbours, may however share compositional similarity with one or more distant (non--neighbouring) domains. We thus obtain a coarse--grained description of the given DNA string in terms of a smaller set of distinct domain labels. This yields a minimal domain description of a given DNA sequence, significantly reducing its organizational complexity. This procedure gives a new means of evaluating genomic complexity as one examines organisms ranging from bacteria to human. The mosaic organization of DNA sequences could have originated from the insertion of fragments of one genome (the parasite) inside another (the host), and we present numerical experiments that are suggestive of this scenario.Comment: 16 pages, 1 figure, Accepted for publication in Phys. Rev.

Concepts of quantum non-Markovianity: a hierarchy

Markovian approximation is a widely-employed idea in descriptions of the dynamics of open quantum systems (OQSs). Although it is usually claimed to be a concept inspired by classical Markovianity, the term quantum Markovianity is used inconsistently and often unrigorously in the literature. In this report we compare the descriptions of classical stochastic processes and quantum stochastic processes (as arising in OQSs), and show that there are inherent differences that lead to the non-trivial problem of characterizing quantum non-Markovianity. Rather than proposing a single definition of quantum Markovianity, we study a host of Markov-related concepts in the quantum regime. Some of these concepts have long been used in quantum theory, such as quantum white noise, factorization approximation, divisibility, Lindblad master equation, etc.. Others are first proposed in this report, including those we call past-future independence, no (quantum) information backflow, and composability. All of these concepts are defined under a unified framework, which allows us to rigorously build hierarchy relations among them. With various examples, we argue that the current most often used definitions of quantum Markovianity in the literature do not fully capture the memoryless property of OQSs. In fact, quantum non-Markovianity is highly context-dependent. The results in this report, summarized as a hierarchy figure, bring clarity to the nature of quantum non-Markovianity.Comment: Clarifications and references added; discussion of the related classical hierarchy significantly improved. To appear in Physics Report

Evolutionary computation enabled game theory based modelling of electricity market behaviours and applications

The collapse of the Californian electricity market system in 2001 has highlighted urgency in research in intelligent electricity trading systems and strategies involving both suppliers and customs. In their trading systems, power generation companies under the new electricity trading arrangement (NETA) of the UK are now developing gaming strategies. However, modelling of such "intelligent" market behaviours is extremely challenging, because traditional mathematical and computer modelling techniques cannot cope with the involvement of game theory. In this paper, evolutionary computation enabled modelling of such system is presented. Both competitive and cooperative game theory strategies are taken into account in evolving the intelligent model. The model then leads to intelligent trading strategy development and decision support. Experimental tests, verification and validation are carried out with various strategies, using different model scales and data published by NETA. Results show that evolutionary computation enabled game theory involved modelling and decision making provides an effective tool for NETA trading analysis, prediction and support

Existence results for mean field equations

Let $\Omega$ be an annulus. We prove that the mean field equation -\Delta\psi=\frac{e\sp{-\beta\psi}}{\int\sb{\Omega}e\sp{-\beta\psi}} admits a solution with zero boundary for $\beta\in (-16\pi,-8\pi)$. This is a supercritical case for the Moser-Trudinger inequality.Comment: Filling a gap in the argument and adding 2 referrence

A macro-level model for investigating the effect of directional bias on network coverage

Random walks have been proposed as a simple method of efficiently searching, or disseminating information throughout, communication and sensor networks. In nature, animals (such as ants) tend to follow correlated random walks, i.e., random walks that are biased towards their current heading. In this paper, we investigate whether or not complementing random walks with directional bias can decrease the expected discovery and coverage times in networks. To do so, we develop a macro-level model of a directionally biased random walk based on Markov chains. By focussing on regular, connected networks, the model allows us to efficiently calculate expected coverage times for different network sizes and biases. Our analysis shows that directional bias can significantly reduce coverage time, but only when the bias is below a certain value which is dependent on the network size.Comment: 15 page

Soliton solution of continuum magnetization-equation in conducting ferromagnet with a spin-polarized current

Exact soliton solutions of a modified Landau-Lifshitz equation for the magnetization of conducting ferromagnet in the presence of a spin-polarized current are obtained by means of inverse scattering transformation. From the analytical solution effects of spin-current on the frequency, wave number, and dispersion law of spin wave are investigated. The one-soliton solution indicates obviously current-driven precession and periodic shape-variation as well. The inelastic collision of solitons by which we mean the shape change before and after collision appears due to the spin current. We, moreover, show that complete inelastic collisions can be achieved by adjusting spectrum and current parameters. This may lead to a potential technique for shape control of spin wave.Comment: 8 pages, 2 figure

Avalanche to streamer transition in particle simulations

The avalanche to streamer transition is studied and illustrated in a particle model. The results are similar to those of fluid models. However, when super-particles are introduced, numerical artefacts become visible. This underscores the need of models that are hybrid in space.Comment: 2 pages, 1 figur