Words Matter: Documents of the Departed

As families begin to experience the passing of loved ones from a ‘silent generation’, they will be forced to make decisions about the physical belongings of those who lived in a Depression Era mentality. Some of these choices will be easy, as one may possess little sentiment over a clock or a set of dishes. Other decisions will be trying, as these items will surely invoke conversations that make us reconsider the meaning of the words keep, want, need, and discard. This paper discusses the documents of Dr. Lloyd Mills (1927-2013), Professor Emeritus of English, at Kent State University. For Dr. Mills, words mattered. Amassing more than a personal archive, the family discovered an estimated collection of 275,000 to 325,000 hand written and typed documents upon his death and were in no way prepared to make so many necessary decisions with a collection this size. While one conscientiously makes choices in their own life about the documents they desire to keep, intimately preserve, and discard, many of us will be forced to become a personal archivist to a scholarly family member and make critical choices that challenge our associations to these documents as they relate to significance, nostalgia, and ownership

RF channel characterization for cognitive radio using support vector machines

Cognitive Radio promises to revolutionize the ways in which a user interfaces with a communications device. In addition to connecting a user with the rest of the world, a Cognitive Radio will know how the user wants to connect to the rest of the world as well as how to best take advantage of unused spectrum, commonly called white space\u27. Through the concept of Dynamic Spectrum Acccess a Cognitive Radio will be able to take advantage of the white space in the spectrum by first identifying where the white space is located and designing a transmit plan for a particular white space. In general a Cognitive Radio melds the capabilities of a Software Defined Radio and a Cognition Engine. The Cognition Engine is responsible for learning how the user interfaces with the device and how to use the available radio resources while the SDR is the interface to the RF world. At the heart of a Cognition Engine are Machine Learning Algorithms that decide how best to use the available radio resources and can learn how the user interfaces to the CR. To decide how best to use the available radio resources, we can group Machine Learning Algorithms into three general categories which are, in order of computational cost: 1.) Linear Least Squares Type Algorithms, e.g. Discrete Fourier Transform (DFT) and their kernel versions, 2.) Linear Support Vector Machines (SVMs) and their kernel versions, and 3.) Neural Networks and/or Genetic Algorithms. Before deciding on what to transmit, a Cognitive Radio must decide where the white space is located. This research is focused on the task of identifying where the white space resides in the spectrum, herein called RF Channel Characterization. Since previous research into the use of Machine Learning Algorithms for this task has focused on Neural Networks and Genetic Algorithms, this research will focus on the use of Machine Learning Algorithms that follow the Support Vector optimization criterion for this task. These Machine Learning Algorithms are commonly called Support Vector Machines. Results obtained using Support Vector Machines for this task are compared with results obtained from using Least Squares Algorithms, most notably, implementations of the Fast Fourier Transform. After a thorough theoretical investigation of the ability of Support Vector Machines to perform the RF Channel Characterization task, we present results of using Support Vector Machines for this task on experimental data collected at the University of New Mexico.\u2

cyclo-Tri-μ-oxido-tris­{[(η5,η5)-1,2-bis­(cyclo­penta­dien­yl)-1,1,2,2-tetra­methyl­disilane]zirconium(IV)}: a trimeric disila-bridged oxidozirconocene

The title compound, [Zr3(C14H20Si2)3O3], consists of three disila-bridged zirconocene units, which are connected via an oxide ligand, forming a nearly planar six-membered ring with a maximum displacement of 0.0191 (8) Å. The compound was isolated as a by-product from a mixture of [(C5H4SiMe2)2ZrCl2] and Li[AlH4] in Et2O

Sentinel-based Surveillance of Coyotes to Detect Bovine Tuberculosis, Michigan

Coyotes could be used as sentinels to detect Mycobacterium bovis in the wild

Test of a gasolene motor car

Thesis (BS)--University of Illinois, 1903Typescrip

Probing photon helicity in radiative B decays via charmonium resonance interference

We investigate a new method to probe the helicity of the photon emitted in the b -> s gamma transition. The method relies on the observation of interference effects between two resonance contributions, B -> K*(K gamma) gamma and B -> eta_c(gamma gamma) K or B -> chi_c0(gamma gamma) K to the same final state K gamma gamma. Decays of the type B -> K_res(K gamma) gamma dominate the B -> K gamma gamma yield throughout most of the phase space, and may be accessible at current B meson facilities already.Comment: elsart, 11 pages, 4 figures; added comments on strong phase (final version Phys. Lett. B

Sentinel-based Surveillance of Coyotes to Detect Bovine Tuberculosis, Michigan

Bovine tuberculosis (TB) is endemic in white-tailed deer (Odocoileus virginianus) in the northeastern portion of Michigan’s Lower Peninsula. Bovine TB in deer and cattle has created immense fi nancial consequences for the livestock industry and hunting public. Surveillance identified coyotes (Canis latrans) as potential bio-accumulators of Mycobacterium bovis, a finding that generated interest in their potential to serve as sentinels for monitoring disease risk. We sampled 175 coyotes in the bovine TB–endemic area. Fifty-eight tested positive, and infection prevalence by county ranged from 19% to 52% (statistical mean 33%, SE 0.07). By contrast, prevalence in deer (n = 3,817) was lower (i.e., 1.49%; Mann-Whitney U4,4 = 14, pM. bovis by 40%. As a result of reduced sampling intensity, sentinel coyote surveys have the potential to be practical indicators of M. bovis presence in wildlife and livestock

Preliminary paleohistological observations of the StW 573 ('Little Foot') skull

Numerous aspects of early hominin biology remain debated or simply unknown. However, recent developments in high-resolution imaging techniques have opened new avenues in the field of paleoanthropology. More specifically, X-ray synchrotron-based analytical imaging techniques have the potential to provide crucial details on the ontogeny, physiology, biomechanics, and biological identity of fossil specimens. Here we present preliminary results of our X-ray synchrotron-based investigation of the skull of the 3.67-million-year-old Australopithecus specimen StW 573 ('Little Foot') at the I12 beamline of the Diamond Light Source (United Kingdom). Besides showing fine details of the enamel (i.e., hypoplasias) and cementum (i.e., incremental lines), as well as of the cranial bone microarchitecture (e.g., diploic channels), our synchrotron-based investigation reveals for the first time the 3D spatial organization of the Haversian systems in the mandibular symphysis of an early hominin

Preliminary paleohistological observations of the StW 573 ('Little Foot') skull.

Numerous aspects of early hominin biology remain debated or simply unknown. However, recent developments in high-resolution imaging techniques have opened new avenues in the field of paleoanthropology. More specifically, X-ray synchrotron-based analytical imaging techniques have the potential to provide crucial details on the ontogeny, physiology, biomechanics, and biological identity of fossil specimens. Here we present preliminary results of our X-ray synchrotron-based investigation of the skull of the 3.67-million-year-old Australopithecus specimen StW 573 ('Little Foot') at the I12 beamline of the Diamond Light Source (United Kingdom). Besides showing fine details of the enamel (i.e., hypoplasias) and cementum (i.e., incremental lines), as well as of the cranial bone microarchitecture (e.g., diploic channels), our synchrotron-based investigation reveals for the first time the 3D spatial organization of the Haversian systems in the mandibular symphysis of an early hominin

Remote Vibration Estimation Using Displaced-Phase-Center Antenna SAR for Strong Clutter Environments

It has been previously demonstrated that it is possible to perform remote vibrometry using synthetic aperture radar (SAR) in conjunction with the discrete fractional Fourier transform (DFrFT). Specifically, the DFrFT estimates the chirp parameters (related to the instantaneous acceleration of a vibrating object) of a slow-time signal associated with the SAR image. However, ground clutter surrounding a vibrating object introduces uncertainties in the estimate of the chirp parameter retrieved via the DFrFT method. To overcome this shortcoming, various techniques based on subspace decomposition of the SAR slow-time signal have been developed. Nonetheless, the effectiveness of these techniques is limited to values of signal-to-clutter ratio ≥5 dB. In this paper, a new vibrometry technique based on displaced-phase-center antenna (DPCA) SAR is proposed. The main characteristic of a DPCA-SAR is that the clutter signal can be canceled, ideally, while retaining information on the instantaneous position and velocity of a target. In this paper, a novel method based on the extended Kalman filter (EKF) is introduced for performing vibrometry using the slow-time signal of a DPCA-SAR. The DPCA-SAR signal model for a vibrating target, the mathematical characterization of the EKF technique, and vibration estimation results for various types of vibration dynamics are presented