Characteristic analysis of a flash flood-affected creek catchment using LiDAR-derived DEM

Flooding occurred across a large area of southern and central Queensland in December 2010 and January 2011. Intense rainfall over the Gowrie Creek catchment caused severe flash flooding through the Toowoomba CBD (Central Business District) on the afternoon of Monday, 10 January 2011, taking lives and damaging the community. Flash floods are sudden and unexpected floods that arise from intense rainfall, generally over a small, steep catchment area. Smaller and steeper catchments have shorter critical storm duration, and they respond more quickly to rainfall events. The resulting flood wave is characterized by very high water flows and velocities and abrupt water level rises, leading to extremely hazardous conditions. Effective flash flood forecasting for specific locations is a big challenge because of the behaviour of intense thunderstorms. A flash flood forecasting and warning system calls for accurate spatial information on catchment characteristics. A high-resolution DEM is a key spatial dataset for the characterization of a catchment to design possible flood mitigation measures. The characteristics of a catchment have a strong influence on its hydrological response. The nature of floods is dependent on both the intensity and duration of the rainfall and the catchment characteristics such as catchment area, drainage patterns and waterway steepness. Therefore, analysis of catchment characteristics is critical for hydrologic modelling and planning for flood risk mitigation. The analysis of catchment characteristics can support hydrological modelling and planning for flood risk mitigation. For example, the shape indices of sub-catchments can be used to compare the hydrological behaviour of different subcatchments. The longitudinal profiles of the creeks illustrate the slope gradients of the waterways. A hypsometric curve for each sub-catchment provides an overall view of the slope of a catchment and is closely related to ground slope characteristics of a catchment. Airborne light detection and ranging (LiDAR), also referred to as airborne laser scanning (ALS), is one of the most effective means of terrain data collection. Using LiDAR data for generation of DEMs is becoming a standard practice in the spatial science community. This study used airborne LiDAR data to generate a high-resolution DEM for characteristic analysis of Gowrie Creek catchment in Toowoomba, Queensland, Australia, which was affected by a flash flood in January 2011. Drainage networks and sub-catchment boundaries were extracted from LiDAR-derived DEM. Catchment characteristics including sub-catchment areas and shape indices, longitudinal profiles of creeks and hypsometric curves of sub-catchments were calculated and analysed

The signal of Z±(4430)Z^\pm(4430) in nucleon-antinucleon scattering

We study the production of $Z^\pm(4430)$ at a nucleon-antinucleon scattering experiment. Considering the PANDA experiment to be an ideal platform to explore the production of the charmonium and charmonim-like states, we suggest the forthcoming PANDA experiment to pay attention to the production of $Z^\pm(4430)$.Comment: 6 pages, 15 figures. Published version in EPJ

Performance of Cross-layer Design with Multiple Outdated Estimates in Multiuser MIMO System

By combining adaptive modulation (AM) and automatic repeat request (ARQ) protocol as well as user scheduling, the cross-layer design scheme of multiuser MIMO system with imperfect feedback is presented, and multiple outdated estimates method is proposed to improve the system performance. Based on this method and imperfect feedback information, the closed-form expressions of spectral efficiency (SE) and packet error rate (PER) of the system subject to the target PER constraint are respectively derived. With these expressions, the system performance can be effectively evaluated. To mitigate the effect of delayed feedback, the variable thresholds (VTs) are also derived by means of the maximum a posteriori method, and these VTs include the conventional fixed thresholds (FTs) as special cases. Simulation results show that the theoretical SE and PER are in good agreement with the corresponding simulation. The proposed CLD scheme with multiple estimates can obtain higher SE than the existing CLD scheme with single estimate, especially for large delay. Moreover, the CLD scheme with VTs outperforms that with conventional FTs

Superior removal of arsenic from water with zirconium metal-organic framework UiO-66

10.1038/srep16613Scientific Reports51661

Extending twin support vector machine classifier for multi-category classification problems

© 2013 – IOS Press and the authors. All rights reservedTwin support vector machine classifier (TWSVM) was proposed by Jayadeva et al., which was used for binary classification problems. TWSVM not only overcomes the difficulties in handling the problem of exemplar unbalance in binary classification problems, but also it is four times faster in training a classifier than classical support vector machines. This paper proposes one-versus-all twin support vector machine classifiers (OVA-TWSVM) for multi-category classification problems by utilizing the strengths of TWSVM. OVA-TWSVM extends TWSVM to solve k-category classification problems by developing k TWSVM where in the ith TWSVM, we only solve the Quadratic Programming Problems (QPPs) for the ith class, and get the ith nonparallel hyperplane corresponding to the ith class data. OVA-TWSVM uses the well known one-versus-all (OVA) approach to construct a corresponding twin support vector machine classifier. We analyze the efficiency of the OVA-TWSVM theoretically, and perform experiments to test its efficiency on both synthetic data sets and several benchmark data sets from the UCI machine learning repository. Both the theoretical analysis and experimental results demonstrate that OVA-TWSVM can outperform the traditional OVA-SVMs classifier. Further experimental comparisons with other multiclass classifiers demonstrated that comparable performance could be achieved.This work is supported in part by the grant of the Fundamental Research Funds for the Central Universities of GK201102007 in PR China, and is also supported by Natural Science Basis Research Plan in Shaanxi Province of China (Program No.2010JM3004), and is at the same time supported by Chinese Academy of Sciences under the Innovative Group Overseas Partnership Grant as well as Natural Science Foundation of China Major International Joint Research Project (NO.71110107026)

Soil, grain and water chemistry and human selenium imbalances in Enshi district, Hubei Province, China

Many elements which are essential to human and other animal health in small doses can be toxic if ingested in excess. Selenium (Se), a naturally occurring metalloid element is found in all natural materials on earth including rocks, soils, waters, air, plant and animal tissues. Since the early 1930’s, it has been recognised that Se toxicity causes hoof disorders and hair loss in livestock. Se was also identified as an essential trace element to humans and other animals in the late 1950’s. It forms a vital constituent of the biologically important enzyme glutathione peroxidase which acts as an anti-oxidant preventing cell degeneration. Se deficiency has been implicated in the aetiology of several diseases including cancer, muscular dystrophy, muscular sclerosis and cystic fibrosis. Se can be assimilated in humans through several pathways including food, drinking water and inhalation of Se-bearing particles from the atmosphere. In the majority of situations, food is the most important source of Se, as levels in water are very low. The narrow range between deficiency levels (<40 pg per day) and toxic levels in susceptible people (> 900 pg per day) makes it necessary to carefully control the amount of Se in the diet. In China, Se deficiency has been linked to an endemic degenerative heart disease known as Keshan Disease (KD) and an endemic osteoarthropathy which causes deformity of affected joints, known as Kaschin-Beck Disease. These diseases occur in a geographic belt stretching from Heilongjiang Province in north-east China to Yunnan Province in the south-west. In the period between 1959 and 1970, peak KD incidence rates exceeded 40 per 100 000 (approximately 8500 cases per annum) with 1400 - 3000 deaths recorded each year. Incidence rates have since fallen to less than 5 per 100 000 with approximately 1000 new cases reported annually (Levander, 1986). Se toxicity (selenosis) resulting in hair and nail loss and disorders of the nervous system in the human population, has also been recorded in Enshi District, Hubei Province and in Ziyang County, Shanxi Province. China possesses one of the best epidemiological databases in the world on Se-related diseases which has been used in conjunction with geochemical data to demonstrate a significant geochemical control on human Se exposure. However, the precise geographical areas at risk and the geochemical controls on selenium availability have yet to be established

Identification of photons in double beta-decay experiments using segmented germanium detectors - studies with a GERDA Phase II prototype detector

The sensitivity of experiments searching for neutrinoless double beta-decay of germanium was so far limited by the background induced by external gamma-radiation. Segmented germanium detectors can be used to identify photons and thus reduce this background component. The GERmanium Detector Array, GERDA, will use highly segmented germanium detectors in its second phase. The identification of photonic events is investigated using a prototype detector. The results are compared with Monte Carlo data.Comment: 20 pages, 7 figures, to be submitted to NIM-

Asymptotic properties of eigenmatrices of a large sample covariance matrix

Let $S_n=\frac{1}{n}X_nX_n^*$ where $X_n=\{X_{ij}\}$ is a $p\times n$ matrix with i.i.d. complex standardized entries having finite fourth moments. Let $Y_n(\mathbf {t}_1,\mathbf {t}_2,\sigma)=\sqrt{p}({\mathbf {x}}_n(\mathbf {t}_1)^*(S_n+\sigma I)^{-1}{\mathbf {x}}_n(\mathbf {t}_2)-{\mathbf {x}}_n(\mathbf {t}_1)^*{\mathbf {x}}_n(\mathbf {t}_2)m_n(\sigma))$ in which $\sigma>0$ and $m_n(\sigma)=\int\frac{dF_{y_n}(x)}{x+\sigma}$ where $F_{y_n}(x)$ is the Mar\v{c}enko--Pastur law with parameter $y_n=p/n$; which converges to a positive constant as $n\to\infty$, and ${\mathbf {x}}_n(\mathbf {t}_1)$ and ${\mathbf {x}}_n(\mathbf {t}_2)$ are unit vectors in ${\Bbb{C}}^p$, having indices $\mathbf {t}_1$ and $\mathbf {t}_2$, ranging in a compact subset of a finite-dimensional Euclidean space. In this paper, we prove that the sequence $Y_n(\mathbf {t}_1,\mathbf {t}_2,\sigma)$ converges weakly to a $(2m+1)$-dimensional Gaussian process. This result provides further evidence in support of the conjecture that the distribution of the eigenmatrix of $S_n$ is asymptotically close to that of a Haar-distributed unitary matrix.Comment: Published in at http://dx.doi.org/10.1214/10-AAP748 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org