Wind and solar powered turbine

A power generating station having a generator driven by solar heat assisted ambient wind is described. A first plurality of radially extendng air passages direct ambient wind to a radial flow wind turbine disposed in a centrally located opening in a substantially disc-shaped structure. A solar radiation collecting surface having black bodies is disposed above the fist plurality of air passages and in communication with a second plurality of radial air passages. A cover plate enclosing the second plurality of radial air passages is transparent so as to permit solar radiation to effectively reach the black bodies. The second plurality of air passages direct ambient wind and thermal updrafts generated by the black bodies to an axial flow turbine. The rotating shaft of the turbines drive the generator. The solar and wind drien power generating system operates in electrical cogeneration mode with a fuel powered prime mover

MM Algorithms for Minimizing Nonsmoothly Penalized Objective Functions

In this paper, we propose a general class of algorithms for optimizing an extensive variety of nonsmoothly penalized objective functions that satisfy certain regularity conditions. The proposed framework utilizes the majorization-minimization (MM) algorithm as its core optimization engine. The resulting algorithms rely on iterated soft-thresholding, implemented componentwise, allowing for fast, stable updating that avoids the need for any high-dimensional matrix inversion. We establish a local convergence theory for this class of algorithms under weaker assumptions than previously considered in the statistical literature. We also demonstrate the exceptional effectiveness of new acceleration methods, originally proposed for the EM algorithm, in this class of problems. Simulation results and a microarray data example are provided to demonstrate the algorithm's capabilities and versatility.Comment: A revised version of this paper has been published in the Electronic Journal of Statistic

Alternative resonance energy transfer mechanisms in polymer light harvesting

Dendrimeric polymers are a subject of considerable interest, particularly for their applications in energy harvesting devices, but also in organic light-emitting diodes, photosensitizers, quantum logic devices and low-threshold lasers. The distinctive light harvesting characteristics of these materials owe their origin to the speed, efficiency and highly directed nature of the multi-step processes that deliver captured light energy to the core. Recently it has been shown how iterative calculations, based on a matrix representation of the connectivity and propensity for energy transfer between different chromophores, effectively model the time-dependent flux of energy within dendrimer materials. This paper reports the formulation and results of an extended approach, accommodating additional mechanisms by means of which excitations of energy higher than the incoming photons can be generated and propagated towards a trap. It is also shown how the structure of the dendrimer and the operation of a spectroscopic gradient affect this energy flow. These mechanisms explain experimental observations in which energy coupling of four photons or more is observed in large aryl ether azodendrimers, at relatively low levels of irradiance

Resource management implications of ERTS-1 data to Ohio

Initial experimental analysis of ERTS-1 imagery has demonstrated that remote sensing from space is a means of delineating and inventorying Ohio's strip-mined areas, detecting power plant smoke plumes, and proving the data necessary for periodically compiling land use maps for the entire state. The nature and extent of these problems throughout Ohio, how ERTS data can contribute to their solution, and estimates of the long term significance of these initial findings to overall resource management interests in Ohio are summarized

Earthquake recurrence as a record breaking process

Extending the central concept of recurrence times for a point process to recurrent events in space-time allows us to characterize seismicity as a record breaking process using only spatiotemporal relations among events. Linking record breaking events with edges between nodes in a graph generates a complex dynamical network isolated from any length, time or magnitude scales set by the observer. For Southern California, the network of recurrences reveals new statistical features of seismicity with robust scaling laws. The rupture length and its scaling with magnitude emerges as a generic measure for distance between recurrent events. Further, the relative separations for subsequent records in space (or time) form a hierarchy with unexpected scaling properties

A study of possible sea state information in the sample and hold gate statistics for the GEOS-3 satellite altimeter

The statistical variations in the sample gate outputs of the GEOS-3 satellite altimeter were studied for possible sea state information. After examination of a large number of statistical characteristics of the altimeter waveforms, it was found that the best sea predictor for H-1/3 in the range of 0 to 3 meters was the 75th percentile of sample and hold gate number 11

Photon signature analysis using template matching

We describe an approach to detect improvised explosive devices (IEDs) by using a template matching procedure. This approach relies on the signature due to backstreaming ? photons from various targets. In this work we have simulated cylindrical targets of aluminum, iron, copper, water and ammonium nitrate (nitrogen-rich fertilizer). We simulate 3.5 MeV source photons distributed on a plane inside a shielded area using Monte Carlo N-Particle (MCNP TM) code version 5 (V5). The 3.5 MeV source gamma rays yield 511 keV peaks due to pair production and scattered gamma rays. In this work, we simulate capture of those photons that backstream, after impinging on the target element, toward a NaI detector. The captured backstreamed photons are expected to produce a unique spectrum that will become part of a simple signal processing recognition system based on the template matching method. Different elements were simulated using different sets of random numbers in the Monte Carlo simulation. To date, the sum of absolute differences (SAD) method has been used to match the template. In the examples investigated, template matching was found to detect all elements correctly