Many-body localization in incommensurate models with a mobility edge

We review the physics of many-body localization in models with incommensurate potentials. In particular, we consider one-dimensional quasiperiodic models with single-particle mobility edges. Although a conventional perspective suggests that delocalized states act as a thermalizing bath for the localized states in the presence of of interactions, there is evidence that such systems can display non-ergodicity. This is in part due to the fact that the delocalized states do not have any kind of protection due to symmetry or topology and are thus susceptible to localization. A study of non-interacting incommensurate models shows that they admit extended, partially extended, and fully localized many-body states. These models cannot thermalize dynamically and remain localized upon the introduction of interactions. In particular, for a certain range of energy, the system can host a non-ergodic extended (i.e. metallic) phase in which the energy eigenstates violate the eigenstate thermalization hypothesis (ETH) but the entanglement entropy obeys volume-law scaling. The level statistics and entanglement growth also indicate the lack of ergodicity in these models. The phenomenon of localization and non-ergodicity in a system with interactions despite the presence of single-particle delocalized states is closely related to the so-called "many-body proximity effect" and can also be observed in models with disorder coupled to systems with delocalized degrees of freedom. Many-body localization in systems with incommensurate potentials (without single-particle mobility edges) have been realized experimentally, and we show how this can be modified to study the the effects of such mobility edges. Demonstrating the failure of thermalization in the presence of a single-particle mobility edge in the thermodynamic limit would indicate a more robust violation of the ETH.Comment: 17 pages, 14 figures, Review articl

Whisper-to-speech conversion using restricted Boltzmann machine arrays

Whispers are a natural vocal communication mechanism, in which vocal cords do not vibrate normally. Lack of glottal-induced pitch leads to low energy, and an inherent noise-like spectral distribution reduces intelligibility. Much research has been devoted to processing of whispers, including conversion of whispers to speech. Unfortunately, among several approaches, the best reconstructed speech to date still contains obviously artificial muffles and suffers from an unnatural prosody. To address these issues, the novel use of multiple restricted Boltzmann machines (RBMs) is reported as a statistical conversion model between whisper and speech spectral envelopes. Moreover, the accuracy of estimated pitch is improved using machine learning techniques for pitch estimation within only voiced (V) regions. Both objective and subjective evaluations show that this new method improves the quality of whisper-reconstructed speech compared with the state-of-the-art approaches

A novel multifunctional biomedical material based on polyacrylonitrile:preparation and characterization

Wet spun microfibers have great potential in the design of multifunctional controlled release materials. Curcumin (Cur) and vitamin E acetate (Vit. E Ac) were used as a model drug system to evaluate the potential application of the drug-loaded microfiber system for enhanced delivery. The drugs and polyacrylonitrile (PAN) were blended together and spun to produce the target drug-loaded microfiber using an improved wet-spinning method and then the microfibers were successfully woven into fabrics. Morphological, mechanical properties, thermal behavior, drug release performance characteristics, and cytocompatibility were determined. The drug-loaded microfiber had a lobed “kidney” shape with a height of 50 ~ 100 μm and width of 100 ~ 200 μm. The addition of Cur and Vit. E Ac had a great influence on the surface and cross section structure of the microfiber, leading to a rough surface having microvoids. X-ray diffraction and Fourier transform infrared spectroscopy indicated that the drugs were successfully encapsulated and dispersed evenly in the microfilament fiber. After drug loading, the mechanical performance of the microfilament changed, with the breaking strength improved slightly, but the tensile elongation increased significantly. Thermogravimetric results showed that the drug load had no apparent adverse effect on the thermal properties of the microfibers. However, drug release from the fiber, as determined through in-vitro experiments, is relatively low and this property is maintained over time. Furthermore, in-vitro cytocompatibility testing showed that no cytotoxicty on the L929 cells was found up to 5% and 10% respectively of the theoretical drug loading content (TDLC) of curcumin and vitamin E acetate. This study provides reference data to aid the development of multifunctional textiles and to explore their use in the biomedical material field

Prevalence of internet addiction disorder in Chinese university students: A comprehensive meta-analysis of observational studies

Background and aims: Internet addiction disorder (IAD) is common in university students. A number of studies have examined the prevalence of IAD in Chinese university students, but the results have been inconsistent. This is a meta-analysis of the prevalence of IAD and its associated factors in Chinese university students. Methods: Both English (PubMed, PsycINFO, and Embase) and Chinese (Wan Fang Database and Chinese National Knowledge Infrastructure) databases were systematically and independently searched from their inception until January 16, 2017. Results: Altogether 70 studies covering 122,454 university students were included in the meta-analysis. Using the random-effects model, the pooled overall prevalence of IAD was 11.3% (95% CI: 10.1%–12.5%). When using the 8-item Young Diagnostic Questionnaire, the 10-item modified Young Diagnostic Questionnaire, the 20-item Internet Addiction Test, and the 26-item Chen Internet Addiction Scale, the pooled prevalence of IAD was 8.4% (95% CI: 6.7%–10.4%), 9.3% (95% CI: 7.6%–11.4%), 11.2% (95% CI: 8.8%–14.3%), and 14.0% (95% CI: 10.6%–18.4%), respectively. Subgroup analyses revealed that the pooled prevalence of IAD was significantly associated with the measurement instrument (Q = 9.41, p = .024). Male gender, higher grade, and urban abode were also significantly associated with IAD. The prevalence of IAD was also higher in eastern and central of China than in its northern and western regions (10.7% vs. 8.1%, Q = 4.90, p = .027). Conclusions: IAD is common among Chinese university students. Appropriate strategies for the prevention and treatment of IAD in this population need greater attention

Effects of span-to-depth ratios on moment connection damage evolution under catenary action

This paper proposes an improved method for determining the gravity resistance of a moment resisting beam-column assembly following an interior column loss. The proposed method accounts for the connection\u27s damage evolution and for the catenary mechanism developed by the assembly as it deflects downward. Through a full-scale laboratory test and finite element simulations, the complete responses of moment resisting beam-column assemblies including the connection\u27s damage evolution are investigated under different beam span-to-depth ratios. The welded unreinforced flange-bolted web (WUF-BW) connection method is used for its robustness in developing the catenary action. It is found that, under the same span-to-depth ratio, beam-column assemblies exhibit similar normalized load-rotation relationships, even with different beam depths. The assembly with a larger span-to-depth ratio is able to develop the gravity resistance earlier, and provides a higher ultimate resistance by developing a more effective catenary mechanism. On the other hand, the assembly with a smaller span-to-depth ratio exhibits a more ductile response. A simplified curve model of the gravity resistance development of a moment beam-column assembly with damage evolution has been proposed for a convenient assessment of the progressive collapse resistance following a central column loss

Relaxed stability conditions based on Taylor series membership functions for polynomial fuzzy-model-based control systems

© 2014 IEEE. In this paper, we investigate the stability of polynomial fuzzy-model-based (PFMB) control systems, aiming to relax stability conditions by considering the information of membership functions. To facilitate the stability analysis, we propose a general form of approximated membership functions, which is implemented by Taylor series expansion. Taylor series membership functions (TSMF) can be brought into stability conditions such that the relation between membership grades and system states is expressed. To further reduce the con-servativeness, different types of information are taken into account: the boundary of membership functions, the property of membership functions, and the boundary of operating domain. Stability conditions are obtained from Lyapunov stability theory by sum of squares (SOS) approach. Simulation examples demonstrate the effect of each piece of information

Salient Object Detection via Structured Matrix Decomposition

Low-rank recovery models have shown potential for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient objects. Two deficiencies, however, still exist. First, previous work typically assumes the elements in the sparse matrix are mutually independent, ignoring the spatial and pattern relations of image regions. Second, when the low-rank and sparse matrices are relatively coherent, e.g., when there are similarities between the salient objects and background or when the background is complicated, it is difficult for previous models to disentangle them. To address these problems, we propose a novel structured matrix decomposition model with two structural regularizations: (1) a tree-structured sparsity-inducing regularization that captures the image structure and enforces patches from the same object to have similar saliency values, and (2) a Laplacian regularization that enlarges the gaps between salient objects and the background in feature space. Furthermore, high-level priors are integrated to guide the matrix decomposition and boost the detection. We evaluate our model for salient object detection on five challenging datasets including single object, multiple objects and complex scene images, and show competitive results as compared with 24 state-of-the-art methods in terms of seven performance metrics