The Split Window Microwave Radiometer (SWMR) for hurricane wind speed measurement from space

The monitoring of hurricanes demands considerable resources each year by the National Oceanic and Atmospheric Administration. Even with the extensive use of satellite and airborne probing of those storms, there is still much uncertainty involved in predicting landfall for timely evacuation of people subject to the threat. The concept of the Split Window Microwave Radiometer (SWMR) is to add an additional capability of remotely measuring surface winds to hopefully improve prediction capabilities or at least define the severity of the storm while it is far from land. Some of the present science and observational needs are addressed in this report as are remote sensing limitations which impact the design of a minimal system which can be launched into low earth orbit by a low cost launch system. This study has concluded that wind speed and rain rate maps of hurricanes can be generated with an X-Band radiometer system with an antenna whose aperture is 2 m on a side

Posner molecules: From atomic structure to nuclear spins

We investigate "Posner molecules", calcium phosphate clusters with chemical formula Ca$_9$(PO$_4$)$_6$. Originally identified in hydroxyapatite, Posner molecules have also been observed as free-floating molecules $in$ $vitro$. The formation and aggregation of Posner molecules have important implications for bone growth, and may also play a role in other biological processes such as the modulation of calcium and phosphate ion concentrations within the mitochondrial matrix. In this work, we use a first-principles computational methodology to study the structure of Posner molecules, their vibrational spectra, their interactions with other cations, and the process of pairwise bonding. Additionally, we show that the Posner molecule provides an ideal environment for the six constituent $^{31}\text{P}$ nuclear spins to obtain very long spin coherence times. $In$ $vitro$, the spins could provide a platform for liquid-state nuclear magnetic resonance quantum computation. $In$ $vivo$, the spins may have medical imaging applications. The spins have also been suggested as "neural qubits" in a proposed mechanism for quantum processing in the brain.Comment: 8 pages, 6 figure

Viscosity and density of methanol/water mixtures at low temperatures

Viscosity and density are measured at low temperatures for three methanol/water mixtures. Viscosity is determined by a modified falling cylinder method or a calibrated viscometer. Density is determined by the volume of each mixture contained in a calibrated glass cell placed in a constant-temperature bath

Conditions for T2T^2 resistivity from electron-electron scattering

Many complex oxides (including titanates, nickelates and cuprates) show a regime in which resistivity follows a power law in temperature ($\rho\propto T^2$). By analogy to a similar phenomenon observed in some metals at low temperature, this has often been attributed to electron-electron (Baber) scattering. We show that Baber scattering results in a $T^2$ power law only under several crucial assumptions which may not hold for complex oxides. We illustrate this with sodium metal ($\rho_\text{el-el}\propto T^2$) and strontium titanate ($\rho_\text{el-el}\not\propto T^2$). We conclude that an observation of $\rho\propto T^2$ is not sufficient evidence for electron-electron scattering.Comment: 5 pages, 4 figure

Airborne laser topographic mapping results from initial joint NASA/US Army Corps of Engineers experiment

Initial results from a series of joint NASA/US Army Corps of Engineers experiments are presented. The NASA Airborne Oceanographic Lidar (AOL) was exercised over various terrain conditions, collecting both profile and scan data from which river basin cross sections are extracted. Comparisons of the laser data with both photogrammetry and ground surveys are made, with 12 to 27 cm agreement observed over open ground. Foliage penetration tests, utilizing the unique time-waveform sampling capability of the AOL, indicate 50 cm agreement with photogrammetry (known to have difficulty in foliage covered terrain)

Sds22 regulates aurora B activity and microtubule-kinetochore interactions at mitosis

Sds22 defines protein phosphatase 1 location and function at kinetochores and subsequent activity of aurora B in mitosis

Non-Iterative Characteristics Analysis for High-Pressure Ramp Loading

In the canonical ramp compression experiment, a smoothly-increasing load is applied to the surface of the sample, and the particle velocity history is measured at two or more different distances into the sample, at interfaces where the surface of the sample can be probed. The velocity histories are used to deduce a stress-density relation, usually using iterative Lagrangian analysis to account for the perturbing effect of the impedance mismatch at the interface. In that technique, a stress- density relation is assumed in order to correct for the perturbation, and is adjusted until it becomes consistent with the deduced stress-density relation. This process is subject to the usual difficulties of nonlinear optimization, such as the existence of local minima (sensitivity to the initial guess), possible failure to converge, and relatively large computational effort. We show that, by considering the interaction of successive characteristics reaching the interfaces, the stress-density relation can be deduced directly by recursion rather than iteration. This calculation is orders of magnitude faster than iterative analysis, and does not require an initial guess. Direct recursion may be less suitable for very noisy data, but it was robust when applied to trial data. The stress-density relation deduced was identical to the result from iterative Lagrangian analysis

Soft computing for intelligent data analysis

Intelligent data analysis (IDA) is an interdisciplinary study concerned with the effective analysis of data. The paper briefly looks at some of the key issues in intelligent data analysis, discusses the opportunities for soft computing in this context, and presents several IDA case studies in which soft computing has played key roles. These studies are all concerned with complex real-world problem solving, including consistency checking between mass spectral data with proposed chemical structures, screening for glaucoma and other eye diseases, forecasting of visual field deterioration, and diagnosis in an oil refinery involving multivariate time series. Bayesian networks, evolutionary computation, neural networks, and machine learning in general are some of those soft computing techniques effectively used in these studies