National University of Defense Technology

About: National University of Defense Technology is a education organization based out in Changsha, China. It is known for research contribution in the topics: Computer science & Radar. The organization has 39430 authors who have published 40181 publications receiving 358979 citations. The organization is also known as: Guófáng Kēxuéjìshù Dàxué & NUDT.

Fabrication of pH-sensitive graphene oxide–drug supramolecular hydrogels as controlled release systems

Abstract: A novel graphene oxide (GO)-based hydrogel with drug molecules as crosslinking agents was fabricated. Metformin hydrochloride (MFH), which has no aromatic groups, but only has N-containing functionalities, was chosen as a model drug. When a very small amount of MFH was introduced into a GO solution, a supramolecular assembled hydrogel was rapidly formed without any polymers or chemical additives. The gelation process can be influenced by the weight ratio of MFH to GO. The driving forces were hydrogen bonding and electrostatic attraction. Both air-dried and freeze-dried samples of GO–MFH hydrogels were utilized for controlled drug release in water (pH = 7) and hydrochloric acid (pH = 1, 3 and 5). The release mechanism of capsulated MFH was Fickian diffusion according to the fitted results. Both the freeze-dried and air-dried samples released around 74% of the MFH in a strongly acidic medium after 70 h, but only 50% in a neutral solution. This pH-sensitivity makes it a potential candidate for the controlled release of drugs in the acidic environment of the stomach.

A Tensor Decomposition-Based Anomaly Detection Algorithm for Hyperspectral Image

Abstract: Anomalies usually refer to targets with a spot of pixels (even subpixels) that stand out from their neighboring background clutter pixels in hyperspectral imagery (HSI). Compared to backgrounds, anomalies have two main characteristics. One is the spectral anomaly, i.e., their spectral signatures are different from those associated to their surrounding backgrounds; another is the spatial anomaly, i.e., anomalies occur as few pixels (even subpixels) embedded in the local homogeneous backgrounds. However, most of the existing anomaly detection algorithms for HSI only employed the spectral anomaly. If the two characteristics are exploited in a detection method simultaneously, better performance may be achieved. The third-order (two modes for space and one mode for spectra) tensor representation of HSI has been proved to be an effective tool to describe the spatial and spectral information equivalently; therefore, tensor representation is convenient for exhibiting the two characteristics of anomalies simultaneously. In this paper, a new anomaly detection method based on tensor decomposition is proposed and divided into three steps. Three factor matrices and a core tensor are first estimated from the third-order tensor that is constructed from the HSI data cube by using the Tucker decomposition, and their major and minor principal components (PCs) are more likely to correspond to the spectral signatures of the backgrounds and the anomalies, respectively. In the second step, a reconstruction-error-based method is presented to find the first largest PCs along each mode to eliminate the spectral signatures of the backgrounds as much as possible, and thus, the remaining data may be modeled as the spectral signatures of the anomalies with a Gaussian noise. Finally, a CFAR test is implemented to detect the anomalies from the remaining data. Experiments with simulated, synthetic, and real HSI data sets reveal that the proposed method outperforms those spectral-anomaly-based methods with better detection probability and less false alarm rate.

Tsunami Damage Investigation of Built-Up Areas Using Multitemporal Spaceborne Full Polarimetric SAR Images

Abstract: This paper explores the use of full polarimetric synthetic aperture radar (PolSAR) images for tsunami damage investigation from the polarimetric viewpoint. The great tsunami induced by the earthquake of March 11th, 2011, which occurred beneath the Pacific off the northeastern coast of Japan, is adopted as the study case using the Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar multitemporal PolSAR images. The polarimetric scattering mechanism changes were quantitatively examined with model-based decomposition. It is clear that the observed reduction in the double-bounce scattering was due to a change into odd-bounce scattering, since a number of buildings were completely washed away, leaving relatively a rough surface. Polarization orientation (PO) angles in built-up areas are also investigated. After the tsunami, PO angle distributions from damaged areas spread to a wider range and fluctuated more strongly than those from the before-tsunami period. Two polarimetric indicators are proposed for damage level discrimination at the city block scale. One is the ratio of the dominant double-bounce scattering mechanism observed after-tsunami to that observed before-tsunami, which can directly reflect the amount of destroyed ground-wall structures in built-up areas. The second indicator is the standard deviation of the PO angle differences, which is used to interpret the homogeneity reduction of PO angles. Experimental results from after- and before-tsunami comparisons validate the efficiency of these indexes, since the built-up areas with different damage levels can be well discriminated. In addition, comparisons between before-tsunami pairs further confirm the stability of the two polarimetric indexes over a long temporal duration. These interesting results also demonstrate the importance of full polarimetric information for natural disaster assessment.

Genome-wide adaptive complexes to underground stresses in blind mole rats Spalax

Abstract: The blind mole rat (BMR), Spalax galili, is an excellent model for studying mammalian adaptation to life underground and medical applications. The BMR spends its entire life underground, protecting itself from predators and climatic fluctuations while challenging it with multiple stressors such as darkness, hypoxia, hypercapnia, energetics and high pathonecity. Here we sequence and analyse the BMR genome and transcriptome, highlighting the possible genomic adaptive responses to the underground stressors. Our results show high rates of RNA/DNA editing, reduced chromosome rearrangements, an over-representation of short interspersed elements (SINEs) probably linked to hypoxia tolerance, degeneration of vision and progression of photoperiodic perception, tolerance to hypercapnia and hypoxia and resistance to cancer. The remarkable traits of the BMR, together with its genomic and transcriptomic information, enhance our understanding of adaptation to extreme environments and will enable the utilization of BMR models for biomedical research in the fight against cancer, stroke and cardiovascular diseases.

Practical quantum random number generator based on measuring the shot noise of vacuum states

Abstract: The shot noise of vacuum states is a kind of quantum noise and is totally random. In this paper a nondeterministic random number generation scheme based on measuring the shot noise of vacuum states is presented and experimentally demonstrated. We use a homodyne detector to measure the shot noise of vacuum states. Considering that the frequency bandwidth of our detector is limited, we derive the optimal sampling rate so that sampling points have the least correlation with each other. We also choose a method to extract random numbers from sampling values, and prove that the influence of classical noise can be avoided with this method so that the detector does not have to be shot-noise limited. The random numbers generated with this scheme have passed ent and diehard tests.