Effects Comparison of Different Resilience Enhancing Strategies for Municipal Water Distribution Network: A Multidimensional Approach

Water distribution network (WDN) is critical to the city service, economic rehabilitation, public health, and safety. Reconstructing the WDN to improve its resilience in seismic disaster is an important and ongoing issue. Although a considerable body of research has examined the effects of different reconstruction strategies on seismic resistance, it is still hard for decision-makers to choose optimal resilience enhancing strategy. Taking the pipeline ductile retrofitting and network meshed expansion as demonstration, we proposed a feasible framework to contrast the resilience enhancing effects of two reconstruction strategies—units retrofitting strategy and network optimization strategy—in technical and organizational dimension. We also developed a new performance response function (PRF) which is based on network equilibrium theory to conduct the effects comparison in integrated technical and organizational dimension. Through the case study of municipal WDN in Lianyungang, China, the comparison results were thoroughly shown and the holistic decision-making support was provided

Radar Waveform Design for Extended Target Recognition under Detection Constraints

We address the problem of radar phase-coded waveform design for extended target recognition in the presence of colored Gaussian disturbance. Phase-coded waveforms are selected since they can fully exploit the transmit power with sufficient variability. An important constraint, target detection performance, is considered to meet the practical requirements. The waveform is designed to achieve maximum recognition performance under a control on the achievable signal-to-noise ratio (SNR) of every possible target hypothesis. We formulate the code design in terms of a nonconvex, NP-hard quadratic optimization problem in the cases of both continuous and discrete phases. Techniques based on semidefinite relaxation (SDR) and randomization are proposed to approximate the optimal solutions. Simulation results show that the recognition performance and the detection requirements are well balanced and accurate approximations are achieved

Phase-Modulated Waveform Design for Extended Target Detection in the Presence of Clutter

The problem to be addressed in this paper is a phase-modulated waveform design for the detection of extended targets contaminated by signal-dependent noise (clutter) and additive noise in practical radar systems. An optimal waveform design method that leads to the energy spectral density (ESD) of signal under the maximum signal-to-clutter-and-noise ratio (SCNR) criterion is introduced first. In order to make full use of the transmission power, a novel phase-iterative algorithm is then proposed for designing the phase-modulated waveform with a constant envelope, whose ESD matches the optimal one. This method is proven to be able to achieve a small SCNR loss by minimizing the mean-square spectral distance between the optimal waveform and the designed waveform. The results of extensive simulations demonstrate that our approach provides less than 1 dB SCNR loss when the signal duration is greater than 1 μs, and outperforms the stationary phase method and other phase-modulated waveform design methods

Delayed Antarctic melt season reduces albedo feedback

Article discusses how Antarctica's response to climate change varies greatly both spatially and temporally. The authors used a 43-year record of Antarctic snow melt seasons from space-borne microwave radiometers with a machine-learning algorithm to show that both the onset and the end of the melt season are being delayed

Reduced expression of N-Myc downstream-regulated gene 2 in human thyroid cancer

<p>Abstract</p> <p>Background</p> <p><it>NDRG</it>2 (N-Myc downstream-regulated gene 2) was initially cloned in our laboratory. Previous results have shown that <it>NDRG</it>2 expressed differentially in normal and cancer tissues. Specifically, <it>NDRG</it>2 mRNA was down-regulated or undetectable in several human cancers, and over-expression of <it>NDRG</it>2 inhibited the proliferation of cancer cells. <it>NDRG</it>2 also exerts important functions in cell differentiation and tumor suppression. However, it remains unclear whether <it>NDRG</it>2 participates in carcinogenesis of the thyroid.</p> <p>Methods</p> <p>In this study, we investigated the expression profile of human <it>NDRG</it>2 in thyroid adenomas and carcinomas, by examining tissues from individuals with thyroid adenomas (n = 40) and carcinomas (n = 35), along with corresponding normal tissues. Immunohistochemistry, quantitative RT-PCR and western blot methods were utilized to determine both the protein and mRNA expression status of Ndrg2 and c-Myc.</p> <p>Results</p> <p>The immunostaining analysis revealed a decrease of Ndrg2 expression in thyroid carcinomas. When comparing adenomas or carcinomas with adjacent normal tissue from the same individual, the mRNA expression level of <it>NDRG</it>2 was significantly decreased in thyroid carcinoma tissues, while there was little difference in adenoma tissues. This differential expression was confirmed at the protein level by western blotting. However, there were no significant correlations of <it>NDRG</it>2 expression with gender, age, different histotypes of thyroid cancers or distant metastases.</p> <p>Conclusion</p> <p>Our data indicates that <it>NDRG</it>2 may participate in thyroid carcinogenesis. This finding provides novel insight into the important role of <it>NDRG2 </it>in the development of thyroid carcinomas. Future studies are needed to address whether the down-regulation of <it>NDRG</it>2 is a cause or a consequence of the progression from a normal thyroid to a carcinoma.</p

Forest Canopy Height Mapping by Synergizing ICESat-2, Sentinel-1, Sentinel-2 and Topographic Information Based on Machine Learning Methods

Spaceborne LiDAR has been widely used to obtain forest canopy heights over large areas, but it is still a challenge to obtain spatio-continuous forest canopy heights with this technology. In order to make up for this deficiency and take advantage of the complementary for multi-source remote sensing data in forest canopy height mapping, a new method to estimate forest canopy height was proposed by synergizing the spaceborne LiDAR (ICESat-2) data, Synthetic Aperture Radar (SAR) data, multi-spectral images, and topographic data considering forest types. In this study, National Geographical Condition Monitoring (NGCM) data was used to extract the distributions of coniferous forest (CF), broadleaf forest (BF), and mixed forest (MF) in Hua’ nan forest area in Heilongjiang Province, China. Accordingly, the forest canopy height estimation models for whole forest (all forests together without distinguishing types, WF), CF, BF, and MF were established, respectively, by Radom Forest (RF) and Gradient Boosting Decision Tree (GBDT). The accuracy for established models and the forest canopy height obtained based on estimation models were validated consequently. The results showed that the forest canopy height estimation models considering forest types had better performance than the model grouping all types of forest together. Compared with GBDT, RF with optimal variables had better performance in forest canopy height estimation with Pearson’s correlation coefficient (R) and the root-mean-squared error (RMSE) values for CF, BF, and MF of 0.72, 0.59, 0.62, and 3.15, 3.37, 3.26 m, respectively. It has been validated that a synergy of ICESat-2 with other remote sensing data can make a crucial contribution to spatio-continuous forest canopy height mapping, especially for areas covered by different types of forest