Comparative Data Mining Analysis for Information Retrieval of MODIS Images: Monitoring Lake Turbidity Changes at Lake Okeechobee, Florida

In the remote sensing field, a frequently recurring question is: Which computational intelligence or data mining algorithms are most suitable for the retrieval of essential information given that most natural systems exhibit very high non-linearity. Among potential candidates might be empirical regression, neural network model, support vector machine, genetic algorithm/genetic programming, analytical equation, etc. This paper compares three types of data mining techniques, including multiple non-linear regression, artificial neural networks, and genetic programming, for estimating multi-temporal turbidity changes following hurricane events at Lake Okeechobee, Florida. This retrospective analysis aims to identify how the major hurricanes impacted the water quality management in 2003-2004. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite imageries were used to retrieve the spatial patterns of turbidity distributions for comparison against the visual patterns discernible in the in-situ observations. By evaluating four statistical parameters, the genetic programming model was finally selected as the most suitable data mining tool for classification in which the MODIS band 1 image and wind speed were recognized as the major determinants by the model. The multi-temporal turbidity maps generated before and after the major hurricane events in 2003-2004 showed that turbidity levels were substantially higher after hurricane episodes. The spatial patterns of turbidity confirm that sediment-laden water travels to the shore where it reduces the intensity of the light necessary to submerged plants for photosynthesis. This reduction results in substantial loss of biomass during the post-hurricane period

Flux dynamics and vortex phase diagram of the new superconductor MgB2MgB_2

Magnetic critical current density and relaxation rate have been measured on $MgB_2$ bulks from 1.6 K to $T_c$ at magnetic fields up to 8 Tesla. A vortex phase diagram is depicted based on these measurement. Two phase boundaries $H_{irr}^{bulk}(T)$ and $H_{irr}^{g}(T)$ characterizing different irreversible flux motions are found. The $H_{irr}^{bulk}(T)$ is characterized by the appearance of the linear resistivity and is attributed to quantum vortex melting induced by quantum fluctuation of vortices in the rather clean system. The second boundary $H_{irr}^g(T)$ reflects the irreversible flux motion in some local regions due to either very strong pinning or the surface barrier on the tiny grains.Comment: 4 pages, 5 figure

Down-regulation of Toll-like receptor 4 gene expression by short interfering RNA attenuates bone cancer pain in a rat model

<p>Abstract</p> <p>Background</p> <p>This study demonstrates a critical role in CNS innate immunity of the microglial Toll-like receptor 4 (TLR4) in the induction and maintenance of behavioral hypersensitivity in a rat model of bone cancer pain with the technique of RNA interference (RNAi). We hypothesized that after intramedullary injection of Walker 256 cells (a breast cancer cell line) into the tibia, CNS neuroimmune activation and subsequent cytokine expression are triggered by the stimulation of microglial membrane-bound TLR4.</p> <p>Results</p> <p>We assessed tactile allodynia and spontaneous pain in female Sprague-Dawley (SD) rats after intramedullary injection of Walker 256 cells into the tibia. In a complementary study, TLR4 small interfering RNA(siRNA) was administered intrathecally to bone cancer pain rats to reduce the expression of spinal TLR4. The bone cancer pain rats treated with TLR4 siRNA displayed significantly attenuated behavioral hypersensitivity and decreased expression of spinal microglial markers and proinflammatory cytokines compared with controls. Only intrathecal injection of TRL4 siRNA at post-inoculation day 4 could prevent initial development of bone cancer pain; intrathecal injection of TRL4 siRNA at post-inoculation day 9 could attenuate, but not completely block, well-established bone cancer pain.</p> <p>Conclusions</p> <p>TLR4 might be the main mediator in the induction of bone cancer pain. Further study of this early, specific, and innate CNS/microglial response, and how it leads to sustained glial/neuronal hypersensitivity, might lead to new therapies for the prevention and treatment of bone cancer pain syndromes.</p

Variation of Natural Streamflow since 1470 in the Middle Yellow River, China

Nowadays, as the available water resources throughout the World are becoming depleted, in order to manage and plan water resource better, more and more attention is being paid into the fluctuating characteristics of water discharges. However, the preexisting research was mainly focused on the last half century. In this paper, the natural streamflow observed since 1470 at the Sanmenxia station in the middle Yellow River basin was collected, and the methods of variation coefficient, moving average, Mann-Kendall test and wavelet transform were applied to analyze the dynamic characteristics of the streamflow. The results showed that, (1) between 1470 and 2007, the natural streamflow changed 200–919 × 108 m3, and water discharge varied moderately; (2) in the middle Yellow River basin, it appears that the most severe and most persistent droughts during circa 1868–1990, the periods of 1470s–1490s, 1920s–1930s and 1990s–2000s also presented the condition of sustained low flows; (3) the natural streamflow series shows increasing and decreasing trends during the periods of 1470–1880 and 1881–2007, respectively, but both trends are not significant at >95% confidence; in addition, it is still found the streamflow series shows abrupt changes circa 1845, 1935 and 1960, respectively; (4) within a 250-year scale, there are circa 11, 26, 67 and 120-year periods for natural streamflow at the Sanmenxia station, and the periodicity of the 120-year one is the strongest. The dynamic characteristics of natural streamflow is the comprehensive result by many influencing factors, such as precipitation, temperature, El Niño-Southern Oscillation, sunspots, human activity, etc

AFe2As2 (A = Ca, Sr, Ba, Eu) and SrFe_(2-x)TM_(x)As2 (TM = Mn, Co, Ni): crystal structure, charge doping, magnetism and superconductivity

The electronic structure and physical properties of the pnictide compound families $RE$OFeAs ($RE$ = La, Ce, Pr, Nd, Sm), $A$Fe$_{2}$As$_{2}$ ($A$ = Ca, Sr, Ba, Eu), LiFeAs and FeSe are quite similar. Here, we focus on the members of the $A$Fe$_{2}$As$_{2}$ family whose sample composition, quality and single crystal growth are better controllable compared to the other systems. Using first principles band structure calculations we focus on understanding the relationship between the crystal structure, charge doping and magnetism in $A$Fe$_{2}$As$_{2}$ systems. We will elaborate on the tetragonal to orthorhombic structural distortion along with the associated magnetic order and anisotropy, influence of doping on the $A$ site as well as on the Fe site, and the changes in the electronic structure as a function of pressure. Experimentally, we investigate the substitution of Fe in SrFe$_{2-x}TM_{x}$As$_{2}$ by other 3$d$ transition metals, $TM$ = Mn, Co, Ni. In contrast to a partial substitution of Fe by Co or Ni (electron doping) a corresponding Mn partial substitution does not lead to the supression of the antiferromagnetic order or the appearance of superconductivity. Most calculated properties agree well with the measured properties, but several of them are sensitive to the As $z$ position. For a microscopic understanding of the electronic structure of this new family of superconductors this structural feature related to the Fe-As interplay is crucial, but its correct ab initio treatment still remains an open question.Comment: 27 pages, single colum