1,574 research outputs found
Stabilizing polar phases in binary metal oxides by hole doping
The recent observation of ferroelectricity in the metastable phases of binary metal oxides, such as HfO2, ZrO2, Hf0.5Zr0.5O2, and Ga2O3, has garnered a lot of attention. These metastable ferroelectric phases are typically stabilized using epitaxial strain, alloying, or defect engineering. Here, we propose that hole doping plays a key role in the stabilization of polar phases in binary metal oxides. Using first-principles density-functional-theory calculations, we show that holes in these oxides mainly occupy one of the two oxygen sublattices. This hole localization, which is more pronounced in the polar phase than in the nonpolar phase, lowers the electrostatic energy of the system, and makes the polar phase more stable at sufficiently large concentrations.We demonstrate that this electrostatic mechanism is responsible for stabilization of the ferroelectric phase of HfO2 aliovalently doped with elements that introduce holes to the system, such as La and N. Finally, we show that spontaneous polarization in HfO2 is robust to hole doping, and a large polarization persists even under a high concentration of holes
Tensor singular spectral analysis for 3D feature extraction in hyperspectral images.
Due to the cubic structure of a hyperspectral image (HSI), how to characterize its spectral and spatial properties in three dimensions is challenging. Conventional spectral-spatial methods usually extract spectral and spatial information separately, ignoring their intrinsic correlations. Recently, some 3D feature extraction methods are developed for the extraction of spectral and spatial features simultaneously, although they rely on local spatial-spectral regions and thus ignore the global spectral similarity and spatial consistency. Meanwhile, some of these methods contain huge model parameters which require a large number of training samples. In this paper, a novel Tensor Singular Spectral Analysis (TensorSSA) method is proposed to extract global and low-rank features of HSI. In TensorSSA, an adaptive embedding operation is first proposed to construct a trajectory tensor corresponding to the entire HSI, which takes full advantage of the spatial similarity and improves the adequate representation of the global low-rank properties of the HSI. Moreover, the obtained trajectory tensor, which contains the global and local spatial and spectral information of the HSI, is decomposed by the Tensor singular value decomposition (t-SVD) to explore its low-rank intrinsic features. Finally, the efficacy of the extracted features is evaluated using the accuracy of image classification with a support vector machine (SVM) classifier. Experimental results on three publicly available datasets have fully demonstrated the superiority of the proposed TensorSSA over a few state-of-the-art 2D/3D feature extraction and deep learning algorithms, even with a limited number of training samples
Perceptually Motivated Wavelet Packet Transform for Bioacoustic Signal Enhancement
A significant and often unavoidable problem in bioacoustic signal processing is the presence of background noise due to an adverse recording environment. This paper proposes a new bioacoustic signal enhancement technique which can be used on a wide range of species. The technique is based on a perceptually scaled wavelet packet decomposition using a species-specific Greenwood scale function. Spectral estimation techniques, similar to those used for human speech enhancement, are used for estimation of clean signal wavelet coefficients under an additive noise model. The new approach is compared to several other techniques, including basic bandpass filtering as well as classical speech enhancement methods such as spectral subtraction, Wiener filtering, and Ephraim–Malah filtering. Vocalizations recorded from several species are used for evaluation, including the ortolan bunting (Emberiza hortulana), rhesus monkey (Macaca mulatta), and humpback whale (Megaptera novaeanglia), with both additive white Gaussian noise and environment recording noise added across a range of signal-to-noise ratios (SNRs). Results, measured by both SNR and segmental SNR of the enhanced wave forms, indicate that the proposed method outperforms other approaches for a wide range of noise conditions
Synergistic anti-atherosclerotic effect of Yerba Maté (Illex Paraguariensis) polyphenols and Lox-1 silencing in foam cell model
Purpose: To elucidate the anti-atherosclerotic effect of Yerba Mate polyphenols (MP) as well as the anti-atherosclerotic effect of a combination of MP and silencing of lectin-like oxidized low-density lipoprotein receptor-1 interference group (LOX)-1.Methods: The anti-atherosclerotic effects of control group (CG), simvastatin group (SG), MP group (MP), LOX-1 interference group (LOX) and MP + LOX-1 interference group (MP-LOX) were determined using Oil Red O staining, enzyme-linked immunosorbent assay (ELISA) and Western blot assay.Results: The levels of foam cells, intracellular lipids, viz, total cholesterol (TC), free cholesterol (FC), cholesterol ester (CE) and acyl-coenzyme A: cholesterol acyltransferase 1 (ACAT1); LOX-1, inflammation (TNF-alpha, IL-6 and pNF-ÎşB/NF-ÎşB); adhesion molecular status (ICAM-1 and VCAM-1), and monocyte chemotactic protein-1 in SG and in MP, LOX and MP-LOX groups were significantly decreased, when compared with CG (p < 0.01). The levels of these parameters were much lower in MPLOX group than in SG (p < 0.01). However, they were synergistically reduced in MP-LOX group, relative to MP group or LOX group (p < 0.01). Combination of LOX-1 gene silencing with MP produced synergistic anti-atherosclerotic effect which was reflected in decreases in foam cell formation, intracellular lipids, inflammatory status, adhesion molecular status, and MCP-1-mediated migration and infiltration of macrophages in foam cells.Conclusion: The synergistic anti-atherosclerotic effects of MP and LOX-1 gene silencing may be potential tools for development of anti-atherosclerotic agents
Coherent narrow-band light source for miniature endoscopes.
In this work, we report the successful implementation of a coherent narrow-band light source for miniature endoscopy applications. An RGB laser module that provides much higher luminosity than traditional incoherent white light sources is used for illumination, taking advantages of the laser light's high spatial coherence for efficient light coupling. Notably, the narrow spectral band of the laser light sources also enables spectrally resolved imaging, to distinguish certain biological tissues or components. A monochrome CMOS camera is employed to synchronize with the time lapsed RGB laser module illumination for color image acquisition and reconstruction, which provides better spatial resolution than a color CMOS camera of comparable pixel number, in addition to spectral resolving
The relations between 3-year changes in physical fitness and academic performance in nationally representative sample of junior high school students
Abstract The objective of the current study was to examine the relationship between different components of physical fitness across 3 years of junior high school with academic performance assessed at the end of the period. Two nationwide representative datasets were used. The first was the physical fitness profile assessed at the beginning of each of the three school years. The second contained the scores on a standardized test administered at the end of the third year. All data were standardized by calculating percentile rank (PR). Students were classified as “High-fit” if their fitness scores ≧ top 25% PR on the age- and sex-adjusted norms. All other students were classified as “not high-fit”. The relationships between fitness and exam performance were tested adjusting for sex, body mass index, and level of urbanization. Students who were in the high-fit group in both years 1 and 3 academically outperformed those who were outside this classification during both assessments. The degree of outperformance was greatest for those who were aerobically fit, followed by those who were high-fit in terms of muscular endurance, muscular strength, and flexibility, respectively. It is therefore concluded that the relationship between physical fitness and academic performance in Taiwanese junior high school students is strongest in the case of aerobic fitness
Serotype Competence and Penicillin Resistance in Streptococcus pneumoniae
Enhanced molecular surveillance of virulent clones with higher competence can detect serotype switching
Effects of attachment preferences on coevolution of opinions and networks
In the coevolution of network structures and opinion formation, we
investigate the effects of a mixed population with distinctive relinking
preferences on both the convergence time and the network structures. It has
been found that a heterogeneous network structure is easier to be reached with
more high-degree-preferential(HDP) nodes. There exists high correlation between
the convergence time and the network heterogeneity. The heterogeneous degree
distribution caused by preferential attachment accelerates the convergence to a
consensus state and the shortened convergence time inhibits the occurrence of
the following disquieting situation that occurs in a continuously evolving
network: with preferential attachment and long-time evolvement, most of the
nodes would become separated and only a few leaders would have immediate
neighbors. Analytical calculations based on mean field theory reveal that both
the transition point ptr and the consensus time tc depend upon the standard
deviation of the degree distribution.ptr increases while tc decreases with the
rise of it.Functions of ptr and tc are found.Theoretical analyses are in
accordance with simulation data.Comment: 10 page
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