Prospective study on observations of γ-ray sources in the Galaxy using the HADAR experiment

The High Altitude Detection of Astronomical Radiation (HADAR) experiment is a refracting terrestrial telescope array based on the atmospheric Cherenkov imaging technique. It focuses the Cherenkov light emitted by extensive air showers through a large aperture water-lens system for observing very-high-energy γ-rays and cosmic rays. With the advantages of a large field-of-view (FOV) and low energy threshold, the HADAR experiment operates in a large-scale sky scanning mode to observe galactic sources. This study presents the prospects of using the HADAR experiment for the sky survey of TeV γ-ray sources from TeVCat and provids a one-year survey of statistical significance. Results from the simulation show that a total of 23 galactic point sources, including five supernova remnant sources and superbubbles, four pulsar wind nebula sources, and 14 unidentified sources, were detected in the HADAR FOV with a significance greater than 5 standard deviations (σ). The statistical significance for the Crab Nebula during one year of operation reached 346.0 σ and the one-year integral sensitivity of HADAR above 1 TeV was ~1.3%–2.4% of the flux from the Crab Nebula.     

Multilevel Deep Feature Generation Framework for Automated Detection of Retinal Abnormalities Using OCT Images

Optical coherence tomography (OCT) images coupled with many learning techniques have been developed to diagnose retinal disorders. This work aims to develop a novel framework for extracting deep features from 18 pre-trained convolutional neural networks (CNN) and to attain high performance using OCT images. In this work, we have developed a new framework for automated detection of retinal disorders using transfer learning. This model consists of three phases: deep fused and multilevel feature extraction, using 18 pre-trained networks and tent maximal pooling, feature selection with ReliefF, and classification using the optimized classifier. The novelty of this proposed framework is the feature generation using widely used CNNs and to select the most suitable features for classification. The extracted features using our proposed intelligent feature extractor are fed to iterative ReliefF (IRF) to automatically select the best feature vector. The quadratic support vector machine (QSVM) is utilized as a classifier in this work. We have developed our model using two public OCT image datasets, and they are named database 1 (DB1) and database 2 (DB2). The proposed framework can attain 97.40% and 100% classification accuracies using the two OCT datasets, DB1 and DB2, respectively. These results illustrate the success of our model.     

Effect of Temperature and Comonomer Content on Thermal Behavior and Crystallization Property of the Propylene–Ethylene Random Copolymers

The effects of ethylene units content and crystallization temperature on the conformations, and the thermal and crystallization behavior were investigated by a combination of Fourier transform infrared (FTIR) spectroscopy, wide angle X-ray diffraction (WAXD), and differential scanning calorimetry (DSC). The characterization of FTIR spectroscopy proves that the longer helical conformation sequences of the propylene–ethylene random (PER) samples decrease, whereas the shorter helical conformation sequences increase with the increase in ethylene units content. The increase of the shorter helical conformation sequences is favorable for the formation of the γ-phase in the crystals. A group of broad endothermic peaks can be seen clearly in the DSC curves of PER copolymers, which may be associated with the melting of mixtures of the α- and γ-forms in the crystals. The melting point, crystallization temperature, and crystallinity degree of the PER copolymers decrease with the increase in ethylene units contents. Three typical melting peaks of the PER copolymers crystallized isothermally between 80°C and 130°C were observed. The two higher melting peaks result from melting of the α- and γ-phase in the crystals, whereas the materials crystallized on quenching give the lowest peak. The WAXD results confirm that the PER copolymers crystallize from the melt, as mixtures of α and γ forms, in a wide temperature range. The critical number ζ_lim of the crystallizable units for the α-form increases with the increase in crystallization temperature for PER copolymers, which is favorable for the formation of the γ phases. The amount of γ-form increases with the increase in crystallization temperature at the expense of its α component, then reaches a maximum value at the crystallization temperature of 115°C, and finally decreases with further increase in the crystallization temperature.     

Nonisothermal Crystallization Behavior of Polypropylene Grafted Silane and Styrene Using γ-Ray Irradiation

Polypropylene grafted silane and styrene (named PP-g-Si/St in this article) was successfully prepared by radical graft polymerization initiated by γ-ray irradiation. The influence of total absorbed dose on the graft ratio of vinyltrimethoxysilane onto PP and the melt flow rate (MFR) of the PP-g-Si/St product were studied. The effect of graft ratios of vinyltrimethoxysilane on the melting point and nonisothermal crystallization kinetics of PP-g-Si/St was investigated by the method of differential scanning calorimetry (DSC). With increasing vinyltrimethoxysilane and styrene (used as viscosity modifier and free radical source) grafted on PP, the melting point of PP-g-Si/St became lower. Several different analysis methods, including those of Avrami, Jeziorny, and Mo and colleagues, were employed to describe the nonisothermal crystallization process of the grafted samples. The results indicate that the peak temperature of crystallization of PP-g-Si/St sample was lower than that of virgin PP. Crystallization kinetics revealed that the rates of nucleation and growth were affected differently by the graft ratio of vinyltrimethoxysilane onto PP. The activation energy was calculated on the basis of the method of Kissinger, and the values were 253.6 and 215.7 kJ/mol for virgin PP and PP-g-Si/St, respectively.     

Selection of optimal combinations of inputs in a partial least squares model for prediction of soil organic matter

Abstract

Partial least squares model is widely used in estimation of soil physical and chemical parameters such as soil organic matter and moisture content, due to its advantages in dealing with collinearity of variables like hyperspectral reflectance. However, it is hard to determine optimal combination of partial least squares model input for soil organic matter prediction since there are lots of possibilities such as, different mathematical transformation of spectral reflectance, wavelength ranges, and spectral resolution. Laboratory hyperspectral reflectance of soils in Songnen plain were analyzed in this study, and the orthogonal experimental design method for deriving optimal combination of input variables for soil organic matter prediction models was introduced. For intercalating orthogonal experimental design table, five different levels which commonly used by researchers were assigned to factors. Results show that the optimal combination input for single black soil is using the derivative logarithmic reciprocal reflectance in the wavelength range selected by multiple stepwise regression at a spectral resolution of 5?nm (R²=?0.95, RMSE?=?0.21, and RPD?=?4.49), and different soils is using continuum removed in the wavelength range selected by MSR at a spectral resolution of 5?nm (R²?=?0.77, RMSE?=?0.74, and RPD?=?2.08). With optimal combination input, the partial least squares model prediction ability was evaluated as excellent for single black soil, possible for different soils. This study illustrates the orthogonal experimental design method can be an effective way to identify the optimal input variables of a partial least squares model for soil organic matter prediction, and multiple stepwise regression can be a preprocessing step to reduce hyperspectral data redundancy before using partial least squares to predict soil organic matter. Overall, this study provides a new approach for determining optimal input of partial least squares predicting model.     

Phase transformations and structural characteristics of AL–Cu–Co(–Si) decagonal phase

The phase transformations and structural characteristics of the Al-Cu-Co-Si alloy have been studied by neutron diffraction and high-resolution electron microscopy. The Al₆₅Cu_17.5Co_17.5 decagonal phase is stable in the temperature range between 973 K and 1350 K. At the low-temperature end, it relaxes to a microcrystalline approximant structure. At the high-temperature end, it melts directly into liquid. Two distinct orthorhombic phases are identified in the Al₆₃Cu_17.5Co_17.5Si₂ microcrystalline structure. They are composed of several structure units that can also construct the Penrose tiling. Because of lack of units, a single orthorhombic phase cannot undergo the transformation towards the high-temperature decagonal phase. An analysis of the orientation relationships between the CsCl and orthorhombic phases leads to the definition of Penrose tiling-like subnetworks inside the orthorhombic unit cells so that these orthorhombic phases can be regarded as the periodic patchworks of quasiperiodic subnetworks.     

激光产生温稠密物质的微观动力学过程及状态诊断

随着大型激光装置的建立和精密测量技术的发展,强激光与固体相互作用成为实验室产生温稠密物质的一个重要手段。温稠密物质的结构复杂性、瞬态性和非平衡性给理论建模和实验测量带来了巨大挑战。本文系统介绍了激光产生温稠密物质的实验手段和理论模拟方法方面的重要进展,分析了其中的电子激发动力学、电子-离子能量弛豫过程、离子动力学等物理过程,总结了温稠密物质状态诊断的实验技术和理论方法,并论述了激光产生温稠密物质的发展趋势。     

HgCdTe薄膜的输运特性及其应力调控

窄禁带直接带隙半导体材料碲镉汞(Hg1–xCdxTe)是一种在红外探测与自旋轨道耦合效应基础研究方面都具有重要应用意义的材料.本文对单晶生长的体材料Hg0.851Cd0.149Te进行阳极氧化以形成表面反型层,将样品粘贴在压电陶瓷上减薄后进行磁输运测试,在压电陶瓷未加电压时观察到了明显的SdH振荡效应.对填充因子与磁场倒数进行线性拟合,获得样品反型层二维电子气的载流子浓度为ns=1.25×10^16m^-2.在不同磁场下,利用压电陶瓷对样品进行应力调控,观测到具有不同特征的现象,分析应是样品中存在二维电子气与体材料两个导电通道.零磁场下体材料主导的电阻的变化应来源于应力导致的带隙的改变;而高场下产生类振荡现象的原因应为应力导致的二维电子气能级的分裂.     

Geometric phase of an open double-quantum-dot system detected by a quantum point contact

We study theoretically the geometric phase of a double-quantum-dot(DQD) system measured by a quantum point contact(QPC) in the pure dephasing and dissipative environments, respectively. The results show that in these two environments, the coupling strength between the quantum dots has an enhanced impact on the geometric phase during a quasiperiod. This is due to the fact that the expansion of the width of the tunneling channel connecting the two quantum dots accelerates the oscillations of the electron between the quantum dots and makes the length of the evolution path longer.In addition, there is a notable near-zero region in the geometric phase because the stronger coupling between the system and the QPC freezes the electron in one quantum dot and the solid angle enclosed by the evolution path is approximately zero,which is associated with the quantum Zeno effect. For the pure dephasing environment, the geometric phase is suppressed as the dephasing rate increases which is caused only by the phase damping of the system. In the dissipative environment,the geometric phase is reduced with the increase of the relaxation rate which results from both the energy dissipation and phase damping of the system. Our results are helpful for using the geometric phase to construct the fault-tolerant quantum devices based on quantum dot systems in quantum information.