Dynamical systems theory for music dynamics

We show that, when music pieces are cast in the form of time series of pitch variations, the concepts and tools of dynamical systems theory can be applied to the analysis of temporal dynamics in music. (i) Phase space portraits are constructed from the time series wherefrom the dimensionality is evaluated as a measure of the global dynamics of each piece. (ii) Spectral analysis of the time series yields power spectra ( approximately f(-nu)) close to red noise (nu approximately 2) in the low frequency range. (iii) We define an information entropy which provides a measure of the local dynamics in the musical piece; the entropy can be interpreted as an evaluation of the degree of complexity in the music, but there is no evidence of an analytical relation between local and global dynamics. These findings are based on computations performed on eighty sequences sampled in the music literature from the 18th to the 20th century. (c) 1995 American Institute of Physics.     

Digitalized Mirror Array and Its Application in Large Telescope： Principle and Case Studies

In this article, we report the principle and conceptual design of a fundamentally different technology in fabricating high precision aberration free optical devices. The tip-tilt of facet in a mirror array is produced by digitally controlled line-tilts of rows and columns. It has not only provided a cost-effective designing methodology in optical physics but also led to a much finer precision of 1 mili arc sec or less. As examples of the application of the proposed digitalised optics, two case studies have been given： a 10 m Schmidt telescope （off-axis） and an 8 m Cassegrain telescope （on-axis）.     

Multifunctional carbon-coated magnetic sensing graphene oxide-cyclodextrin nanohybrid for potential cancer theranosis

Journal of Nanoparticle Research - Over the last years, an environmentally friendly and economically efficient way of nanoparticle production has been found in the biosynthesis of metal...     

Effect of water vapour on particulate matter emission during oxyfuel combustion of char and in situ volatiles generated from rapid pyrolysis of chromated-copper-arsenate-treated wood

This paper reports the effect of water vapour on particulate matter (PM) during the separate combustion of in situ volatiles and char generated from chromated-copper-arsenate-treated (CCAT) wood at 1300 °C. Combustion of in situ volatiles produces only PM with aerodynamic diameter?<1?µm (i.e., PM₁), dominantly PM with aerodynamic diameter?<0.1?µm (i.e., PM_0.1). Water vapour could significantly enhance the nucleation, coagulation and condensation of fine particles and reduce the capture of Na and K by the alumina reactor tube via reduced formation of alkali aluminates, leading to increases in both yield and modal diameter of PM_0.1. Water vapour could also enhance char fragmentation hence increase the yield of PM with aerodynamic diameter between 1 and 10?µm (i.e., PM_1–10) during char combustion. For trace elements, during in situ volatiles combustion, volatile elements (As, Cr, Ni, Cu and Pb) are only presented in PM₁ and water vapour alters the particle size distributions (PSDs) but has little effect on the yields of these trace elements. During char combustion, As, Cr, Cu and Ni are present in both PM₁ and PM_1–10 while the non-volatile Mn and Ti are only present in PM_1–10. Increasing water vapour content increases the yields of As, Cr, Cu, Ni, Mn and Ti in PM_1-10 due to enhanced char fragmentation. During char combustion, water vapour also originates less oxidising conditions locally for enhancing As release, promotes the generation of gaseous chromium oxyhydroxides and inhabits the production of NiCl₂ (g), leading to increased yields of As and Cr and decreased yield of Ni in PM_0.1.     

Characterization of porosity in a 19th century painting ground by synchrotron radiation X-ray tomography

The study of the early oeuvre of the Swiss painter Cuno Amiet (1868–1961) has revealed that, up to 1907, many of his grounds were hand applied and are mainly composed of chalk, bound in protein. These grounds are not only lean and absorbent, but also, as Synchrotron radiation X-ray microtomography has shown, porous. Our approach to the characterization of pore structure and quantity, their connectivity, and homogeneity is based on image segmentation and application of a clustering algorithm to high-resolution X-ray tomographic data. The issues associated with the segmentation of the different components of a ground sample based on X-ray imaging data are discussed. The approach applied to a sample taken from “Portrait of Max Leu” (1899) by Amiet revealed the presence of three sublayers within the ground with distinct porosity features, which had not been observed optically in cross-section. The upper and lower layers are highly porous with important connectivity and thus prone to water uptake/storage. The middle layer however shows low and nonconnected porosity at the resolution level of the X-ray tomography images, so that few direct water absorption paths through the entire sample exist. The potential of the method to characterize porosity and to understand moisture-related issues in paint layer degradation are discussed.     

Semiconductor Emitters in Entropy Sources for Quantum Random Number Generation

Random number generation (RNG) is needed for a myriad of applications ranging from secure communication encryption to numerical simulations to sports and games. However, generating truly random numbers can be elusive. Pseudorandom bit generation using computer algorithms provides a high random bit generation rate. Nevertheless, the reliance on predefined algorithms makes it deterministic and predictable once initial conditions are known. Relying on physical phenomena (such as measuring electrical noise or even rolling dice) can achieve a less predictable sequence of bits. Furthermore, if the physical phenomena originate from quantum effects, they can be truly random and completely unpredictable due to quantum indeterminacy. Traditionally, physical RNG is significantly slower than pseudorandom techniques. To meet the demand for high-speed RNG with perfect unpredictability, semiconductor light sources are adopted as parts of the sources of randomness, i.e., entropy sources, in quantum RNG (QRNG) systems. The high speed of their noise, the high efficiency, and the small scale of these devices make them ideal for chip-scale QRNG. Here, the applications and recent advances of QRNG are reviewed using semiconductor emitters. Finally, the performance of these emitters is compared and discuss their potential in future technologies.     

Improved Stabilities of Labeling Probes for the Selective Modification of Endogenous Proteins in Living Cells and In Vivo

To date, various affinity-based protein labeling probes have been developed and applied in biological research to modify endogenous proteins in cell lysates and on the cell surface. However, the reactive groups on the labeling probes are also the cause of probe instability and nonselective labeling in a more complex environment, e. g., intracellular and in vivo. Here, we show that labeling probes composed of a sterically stabilized difluorophenyl pivalate can achieve efficient and selective labeling of endogenous proteins on the cell surface, inside living cells and in vivo. As compared with the existing protein labeling probes, probes with the difluorophenyl pivalate exhibit several advantages, including long-term stability in stock solutions, resistance to enzymatic hydrolysis and can be customized easily with diverse fluorophores and protein ligands. With this probe design, endogenous hypoxia biomarker in living cells and nude mice were successfully labeled and validated by in vivo, ex vivo, and immunohistochemistry imaging.     

Cluster fusion-fission dynamics in the Singapore stock exchange

In this paper, we investigate how the cross-correlations between stocks in the Singapore stock exchange (SGX) evolve over 2008 and 2009 within overlapping one-month time windows. In particular, we examine how these cross-correlations change before, during, and after the Sep–Oct 2008 Lehman Brothers Crisis. To do this, we extend the complete-linkage hierarchical clustering algorithm, to obtain robust clusters of stocks with stronger intracluster correlations, and weaker intercluster correlations. After we identify the robust clusters in all time windows, we visualize how these change in the form of a fusion-fission diagram. Such a diagram depicts graphically how the cluster sizes evolve, the exchange of stocks between clusters, as well as how strongly the clusters mix. From the fusion-fission diagram, we see a giant cluster growing and disintegrating in the SGX, up till the Lehman Brothers Crisis in September 2008 and the market crashes of October 2008. After the Lehman Brothers Crisis, clusters in the SGX remain small for few months before giant clusters emerge once again. In the aftermath of the crisis, we also find strong mixing of component stocks between clusters. As a result, the correlation between initially strongly-correlated pairs of stocks decay exponentially with average life time of about a month. These observations impact strongly how portfolios and trading strategies should be formulated.