ALBERT

Description: Drought is one of the most common natural disasters on a global scale and has a wide range of socioeconomic impacts. In this study, we analyzed the spatiotemporal variations of meteorological drought in a typical agricultural province of China (i.e., Shaanxi Province) based on the Standard Precipitation Evapotranspiration Index (SPEI). We also investigated the response of winter wheat and summer maize yields to drought by a correlation analysis between the detrended SPEI and the time series of yield anomaly during the crop growing season. Moreover, agricultural drought risks were assessed across the province using a conceptual risk assessment model that emphasizes the combined role of drought hazard and vulnerability. The results indicated that droughts have become more severe and frequent in the study area after 1995. The four typical timescales of SPEI showed a consistent decreasing trend during the period 1960–2016; the central plains of the province showed the most significant decreasing trend, where is the main producing area of the province’s grain. Furthermore, the frequency and intensity of drought increased significantly after 1995; the most severe drought episodes occurred in 2015–2016. Our results also showed that the sensitivity of crop yield to drought varies with the timescales of droughts. Droughts at six-month timescales that occurred in March can explain the yield losses for winter wheat to the greatest extent, while the yield losses of summer maize are more sensitive to droughts at three-month timescales that occurred in August. The assessment agricultural drought risk showed that some areas in the north of the province are exposed to a higher risk of drought and other regions are dominated by low risk.

Description: The magnetic targeting drug delivery system is an effective way of targeting therapy. In this study, the monodisperse Fe3O4 nanoparticles with a particles size of about 180 nm were first prepared via a solvothermal method. Subsequently, the core-shell structure Fe3O4/SiO2 and Fe3O4/SiO2/polypyrrole (PPy) composite nanospheres were successfully synthesized by coating Fe3O4 nanoparticles with SiO2 shell layer using the Stöber method and PPy shell by solvothermal method in turn. The as-prepared nanoparticles were characterized using transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), vibrating sample magnetometer (VSM), thermogravimetric analysis (TGA), and Ultraviolet-Visible spectrophotometer (UV-Vis). The results indicated that the as-prepared composite nanospheres displayed a well-defined core-shell structure and monodispersity. The thicknesses of SiO2 shell and PPy shell were ~6 nm and ~19 nm, respectively. Additionally, the as-prepared nanoparticles exhibited high saturation magnetization of 104 emu/g, 77 emu/g, and 24 emu/g, and have great potential applications in drug delivery. The drug loading and drug release of the Fe3O4/SiO2 and Fe3O4/SiO2/PPy composite nanospheres to ibuprofen (IBU) under stirring and ultrasonication were investigated. Their drug loading efficiency and drug release efficiency under ultrasonication were all higher than 33% and 90%, respectively. The drug release analyses showed sustained release of IBU from nanospheres and followed the Korsmeyer-Peppas model.

Description: A hierarchical support vector regression (SVR) model (HSVRM) was employed to correlate the compositions and mechanical properties of bicomponent stents composed of poly(lactic-co-glycolic acid) (PGLA) film and poly(glycolic acid) (PGA) fibers for urethral repair for the first time. PGLA film and PGA fibers could provide ureteral stents with good compressive and tensile properties, respectively. In bicomponent stents, high film content led to high stiffness, while high fiber content resulted in poor compressional properties. To simplify the procedures to optimize the ratio of PGLA film and PGA fiber in the stents, a hierarchical support vector regression model (HSVRM) and particle swarm optimization (PSO) algorithm were used to construct relationships between the film-to-fiber weight ratio and the measured compressional/tensile properties of the stents. The experimental data and simulated data fit well, proving that the HSVRM could closely reflect the relationship between the component ratio and performance properties of the ureteral stents.

Description: In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL), for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Projections and nonparametric Kernelized Least-squares Policy Iteration (KLSPI). Random Projections are a fast, non-adaptive dimensionality reduction framework in which high-dimensionality data is projected onto a random lower-dimension subspace via spherically random rotation and coordination sampling. KLSPI introduce kernel trick into the LSPI framework for Reinforcement Learning, often achieving faster convergence and providing automatic feature selection via various kernel sparsification approaches. In this approach, policies are computed in a low-dimensional subspace generated by projecting the high-dimensional features onto a set of random basis. We first show how Random Projections constitute an efficient sparsification technique and how our method often converges faster than regular LSPI, while at lower computational costs. Theoretical foundation underlying this approach is a fast approximation of Singular Value Decomposition (SVD). Finally, simulation results are exhibited on benchmark MDP domains, which confirm gains both in computation time and in performance in large feature spaces.

Description: The change in river flows at the basin scale reflects the combined influences of changes in various environmental factors associated with climatic and underlying surface properties. Distinguishing the relative contribution of each of these factors to runoff change is critical for sustainable water resource management, but it is also challenging. The headstream region of the Yangtze River, known as “China’s Water Tower”, has undergone a significant runoff change over the past decades. However, the relative contribution of environmental factors to runoff change is still unclear. Here, we designed a series of detrending experiments based on a grid-based hydrological model to quantify the combined influences of multiple environmental factors on runoff change and the relative contribution of an individual factor to runoff change. The results indicate that changes in climate and vegetation significantly increased water yield in the study basin over the past three decades, and the increase in water yield primarily came from the contribution from the upstream of the basin. On the basin scale, the change in precipitation dominated the runoff change that contributed up to 113.2% of the runoff change, followed by the wind speed change with a contribution rate of −15.1%. Other factors, including changes in temperature, relative humidity, sunshine duration (as a surrogate for net radiation), and albedo (as a surrogate for vegetation) had limited effects on runoff change, and the contribution rate of these factors to runoff change ranged from −5% to 5%. On spatial patterns, the influences of changes in some environmental factors on runoff changes were affected by elevation, particularly for temperature. The rising temperature had mixed effects on runoff change, which generally increased water yield at high altitudes of the basin but decreased water yield at low altitudes of the basin.

Description: Persistent scatterer interferometry (PSI) has the ability to acquire submeter-scale digital elevation model (DEM) and millimeter-scale deformation. A limitation to the application of PSI is that only single persistent scatterers (SPSs) are detected, and pixels with multiple dominant scatterers from different sources are discarded in PSI processing. Synthetic aperture radar (SAR) tomography is a promising technique capable of resolving layovers. In this paper, new approaches based on a novel two-tier network aimed at robust and efficient detection of persistent scatterers (PSs) are presented. The calibration of atmospheric phase screen (APS) and the detection of PSs can be jointly implemented in the novel two-tier network. A residue-to-signal ratio (RSR) estimator is proposed to evaluate whether the APS is effectively calibrated and to select reliable PSs with accurate estimation. In the first-tier network, a Delaunay triangulation network is constructed for APS calibration and SPS detection. RSR thresholding is used to adjust the first-tier network by discarding arcs and SPS candidates (SPSCs) with inaccurate estimation, yielding more than one main network in the first-tier network. After network adjustment, we attempt to establish reliable SPS arcs to connect the main isolated networks, and the expanded largest connected network is then formed with more manual structure information subtracted. Furthermore, rather than the weighted least square (WLS) estimator, a network decomposition WLS (ND-WLS) estimator is proposed to accelerate the retrieval of absolute parameters from the expanded largest connected network, which is quite useful for large network inversion. In the second-tier network, the remaining SPSs and all the double PSs (DPSs) are detected and estimated with reference to the expanded largest connected network. Compared with traditional two-tier network-based methods, more PSs can be robustly and efficiently detected by the proposed new approaches. Experiments on interferometric high resolution TerraSAR-X SAR images are given to demonstrate the merits of the new approaches.

Description: Automatic image registration for multi-sensors has always been an important task for remote sensing applications. However, registration for images with large resolution differences has not been fully considered. A coarse-to-fine registration strategy for images with large differences in resolution is presented. The strategy consists of three phases. First, the feature-base registration method is applied on the resampled sensed image and the reference image. Edge point features acquired from the edge strength map (ESM) of the images are used to pre-register two images quickly and robustly. Second, normalized mutual information-based registration is applied on the two images for more accurate transformation parameters. Third, the final transform parameters are acquired through direct registration between the original high- and low-resolution images. Ant colony optimization (ACO) for continuous domain is adopted to optimize the similarity metrics throughout the three phases. The proposed method has been tested on image pairs with different resolution ratios from different sensors, including satellite and aerial sensors. Control points (CPs) extracted from the images are used to calculate the registration accuracy of the proposed method and other state-of-the-art methods. The feature-based preregistration validation experiment shows that the proposed method effectively narrows the value range of registration parameters. The registration results indicate that the proposed method performs the best and achieves sub-pixel registration accuracy of images with resolution differences from 1 to 50 times.

Description: Currently, the geometric and radiometric calibration of on-board satellite sensors utilizes different ground targets using some form of manual intervention. Point source targets provide high precision geometric and radiometric information and have the potential to become a new tool for joint geometric and radiometric calibration. In this paper, an automatic recognition and positioning method for point source target images is proposed. First, the template matching method was used to effectively reduce nonpoint source target image pixels in the satellite imagery. The point source target images were then identified using particular feature parameters. Using the template matching method, the weighted centroid method, and the Gaussian fitting method, the positions of the centroid of the point source target images were calculated. The maximum position detection error obtained using the three methods was 0.07 pixels, which is comparably better than artificial targets currently in use. The experimental results show point source targets provide high precision geometric information, which can become a suitable alternative for automatic joint geometric and radiometric calibration of spaceborne optical sensors.

Description: Materials, Vol. 11, Pages 1498: Mechanical and Dielectric Properties of Two Types of Si3N4 Fibers Annealed at Elevated Temperatures Materials doi: 10.3390/ma11091498 Authors: Jie Zhou Fang Ye Xuefeng Cui Laifei Cheng Jianping Li Yongsheng Liu Litong Zhang The mechanical and dielectric properties of two types of amorphous silicon nitride (Si3N4) fibers prior to and following annealing at 800 °C were studied. The tensile strengths of the Si3N4 fiber bundles were measured using unidirectional tensile experimentation at room temperature, whereas the permittivity values were measured at 8.2–12.4 GHz using the waveguide method. The results demonstrated that the tensile strength and dielectric properties of Si3N4 fibers were correlated to the corresponding composition, microstructure, and intrinsic performance of electrical resistance. The Si3N4 fibers with a lower content of amorphous SiNxOy presented an improved thermal stability, a higher tensile strength, a higher conductivity, and a significantly stable wave-transparent property. These were mainly attributed to the highly pure composition and decomposition of less amorphous SiNxOy.

Description: Minerals, Vol. 7, Pages 211: Effect of Heating Rate on Pyrolysis Behavior and Kinetic Characteristics of Siderite Minerals doi: 10.3390/min7110211 Authors: Xiaolong Zhang Yuexin Han Yanjun Li Yongsheng Sun The pyrolysis characteristics of siderite at different heating rates under the neutral atmosphere were investigated using various tools, including comprehensive thermal analyzer, tube furnace, X-ray diffraction (XRD), scanning electron microscope (SEM), energy-dispersive spectrometry (EDS) and vibrating specimen magnetometer (VSM) measurements. The reaction of siderite pyrolysis followed the one-step reaction under the neutral atmosphere: FeCO3 → Fe3O4 + CO2 + CO. As the increasing of heating rate, the start and end pyrolysis temperatures and temperate where maximum weight loss rate occurred increased, while the total mass loss were essentially the same. Increasing heating rate within a certain range was in favor of shortening the time of each reaction stage, and the maximum conversion rate could be reached with a short time. The most probable mechanism function for non-isothermal pyrolysis of siderite at different heating rates was A1/2 reaction model (nucleation and growth reaction). With increasing heating rate, the corresponding activation energies and the pre-exponential factors increased, from 446.13 to 505.19 kJ∙mol−1, and from 6.67 × 10−18 to 2.40 × 10−21, respectively. All siderite was transformed into magnetite with a porous structure after pyrolysis, and some micro-cracks were formed into the particles. The magnetization intensity and specific susceptibility increased significantly, which created favorable conditions for the further effective concentration of iron ore.