Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation

A Novel Variable Index and Excision CFAR Based Ship Detection Method on SAR Imagery

When applying the constant false alarm rate (CFAR) detector to ship detection on synthetic aperture radar (SAR) imagery, multiple interferers such as upwelling, breaking waves, ambiguities, and neighboring ships in a dense traffic area will degrade the probability of detection. In this paper, we propose a novel variable index and excision CFAR (VIE-CFAR) based ship detection method to alleviate the masking effect of multiple interferers. Firstly, we improve the variable index (VI) CFAR with an excision procedure, which censors the multiple interferers from the reference cells. And then, the paper integrates the novel CFAR concept into a ship detection scheme on SAR imagery, which adopts the VIE-CFAR to screen reference cells and the distribution to derive detection threshold. Finally, we analyze the performances of the VIE-CFAR under different environments and validate the proposed method on both ENVISAT and TerraSAR-X SAR data. The results demonstrate that the proposed method outperforms other existing detectors, especially in the presence of multiple interferers

A 3D-printed microfluidic-enabled hollow microneedle architecture for transdermal drug delivery.

Embedding microfluidic architectures with microneedles enables fluid management capabilities that present new degrees of freedom for transdermal drug delivery. To this end, fabrication schemes that can simultaneously create and integrate complex millimeter/centimeter-long microfluidic structures and micrometer-scale microneedle features are necessary. Accordingly, three-dimensional (3D) printing techniques are suitable candidates because they allow the rapid realization of customizable yet intricate microfluidic and microneedle features. However, previously reported 3D-printing approaches utilized costly instrumentation that lacked the desired versatility to print both features in a single step and the throughput to render components within distinct length-scales. Here, for the first time in literature, we devise a fabrication scheme to create hollow microneedles interfaced with microfluidic structures in a single step. Our method utilizes stereolithography 3D-printing and pushes its boundaries (achieving print resolutions below the full width half maximum laser spot size resolution) to create complex architectures with lower cost and higher print speed and throughput than previously reported methods. To demonstrate a potential application, a microfluidic-enabled microneedle architecture was printed to render hydrodynamic mixing and transdermal drug delivery within a single device. The presented architectures can be adopted in future biomedical devices to facilitate new modes of operations for transdermal drug delivery applications such as combinational therapy for preclinical testing of biologic treatments

Effects of Saline and Alkaline Stresses on Growth and Physiological Changes in Oat (Avena sativa L.) Seedlings

Two neutral salts (NaCl and Na2SO4) and alkaline salts (NaHCO3 and Na2CO3) were both mixed in 2:1 ratio, and the effects of saline and alkaline stresses on growth and physiological changes in oat seedlings were explored. The result showed that biomass, water content and chlorophyll content decreased while cell membrane permeability significantly increased under alkaline stress. Saline stress did not have an obvious effect on pH value in tissue fluids of shoot and root, but alkaline stress increased pH value in the root tissue fluid. The contents of Na+, Na+/K+, SO42- increased more, and K+, NO3-, H2PO4- decreased more under alkaline stress, the Cl- content increased obviously under saline stress but had little change under alkaline stress. The increments of proline and organic acid were both greater under alkaline stress, but organic acid content kept the same level under saline stress. Alkaline stress caused more harmful effects on growth and physiological changes in oat seedlings especially broke the pH stability in the root tissue fluid. Physiological adaptive mechanisms of oat seedlings under saline stress and alkaline stress were different, which mainly took the way of accumulating organic acid under alkali stress but accumulating Cl- under saline stress

Robust Inventory Financing Model with Partial Information

Given current fast-changing market conditions and difficulty in obtaining financing for small- and medium-sized enterprises, this paper studies the robust inventory financing model under partial information, that is, where the demand distribution is partly known. Two demand information cases are discussed: (1) the mean and variance and (2) the support of the demand distribution. In this setting, the robust method that maximizes the worst-case profit and minimizes the firm’s maximum possible regret of not acting optimally would be used to formulate the optimal sales quantity. We show that the approach used in this paper is tractable, and we provide an explicit expression for the robust optimal policy. We then use numerical examples to compare the firm’s losses under two demand information cases with those occurring under demand certainty. More importantly, the numerical examples indicate that our robust inventory financing model can obtain a robust but not conservative solution

Actual Application of a H 2

To evaluate the actual performance of the H2-based polyvinyl chloride hollow fiber membrane biofilm reactor (HF-MBfR), we used HF-MBfR to remove nitrate from the nitrate contaminated groundwater with the dissolved oxygen (~6.2 mg/L) in Zhangqiu city (Jinan, China). The reactor was operated over 135 days with the actual nitrate contaminated groundwater. The result showed that maximum of nitrate denitrification rate achieved was over 133.8 g NO3--N/m3d (1.18 g NO3--N/m2d) and the total nitrogen removal was more than 95.0% at the conditions of influent nitrate 50 mg/L, hydrogen pressure 0.05 MPa, and dissolved oxygen (DO) 6.2 mg/L, with the nitrate in effluent under the value limits of drinking water. The fluxes analysis showed that the electron-equivalent fluxes of nitrate, sulfate, and oxygen account for about 81.2%, 15.2%, and 3.6%, respectively, which indicated that nitrate reduction could consume more electrons than that of sulfate reduction and dissolved oxygen reduction. The nitrate reduction was not significantly influenced by sulfate reduction and the dissolved oxygen reduction. Based on the actual groundwater quality on site, the Langelier Saturation Index (LSI) was 0.4, and the membrane could be at the risk of surface scaling

Biodegradable double-network GelMA-ACNM hydrogel microneedles for transdermal drug delivery

As a minimally invasive drug delivery platform, microneedles (MNs) overcome many drawbacks of the conventional transdermal drug delivery systems, therefore are favorable in biomedical applications. Microneedles with a combined burst and sustained release profile and maintained therapeutic molecular bioactivity could further broaden its applications as therapeutics. Here, we developed a double-network microneedles (DN MNs) based on gelatin methacrylate and acellular neural matrix (GelMA-ACNM). ACNM could function as an early drug release matrix, whereas the addition of GelMA facilitates sustained drug release. In particular, the double-network microneedles comprising GelMA-ACNM hydrogel has distinctive biological features in maintaining drug activity to meet the needs of application in treating different diseases. In this study, we prepared the double-network microneedles and evaluated its morphology, mechanical properties, drug release properties and biocompatibility, which shows great potential for delivery of therapeutic molecules that needs different release profiles in transdermal treatment