A comparison of land-use determinations using data from ERTS-1 and high altitude aircraft

A manual interpretation of ERTS-1 MSS system corrected imagery has been performed on a study area within the Houston Area Test Site to classify land use using the Level 1 categories proposed by the Department of the Interior. The two types of imagery used included: (1) black and white transparencies of each band enlarged to a scale of approximately 1:250,000 and (2) color transparencies composited from the computer compatible tapes using the film recorder on a multispectral data analysis station. The results of this interpretation have been compared with the 1970 land use inventory of HATS which was compiled using color ektachrome imagery from high altitude aircraft (scale 1:120,000). Urban data from the same scene was also analyzed using a computer-aided (clustering) technique. The resulting clusters, representing areas of similar content, were compared with existing land use patterns in Houston. A technique was developed to correlate the spectral clusters to specific urban features on aircraft imagery by the location of specific, high contrast objects in particular resolution elements. It was concluded that ERTS-1 data could be used to develop Level 1 and many Level 2 land use categories for regional inventories and perhaps to some degree on a local level

First-Order Type Effects in YBa2_2Cu3_3O6+x_{6+x} at the Onset of Superconductivity

We present results of Raman scattering experiments on tetragonal ${\rm (Y_{1-y}Ca_{y})Ba_{2}Cu_{3}O_{6+x}}$ for doping levels $p(x,y)$ between 0 and 0.07 holes/CuO$_2$. Below the onset of superconductivity at $p_{\rm sc1} \approx 0.06$, we find evidence of a diagonal superstructure. At $p_{\rm sc1}$, lattice and electron dynamics change discontinuously with the charge and spin properties being renormalized at all energy scales. The results indicate that charge ordering is intimately related to the transition at $p_{\rm sc1}$ and that the maximal transition temperature to superconductivity at optimal doping $T_{c}^{\rm max}$ depends on the type of ordering at $p>p_{\rm sc1}$.Comment: 4 pages, 4 figure

Ursinus College Bulletin Vol. 11, No. 1, October 1894

A digitized copy of the October 1894 Ursinus College Bulletin.https://digitalcommons.ursinus.edu/ucbulletin/1098/thumbnail.jp

Ursinus College Bulletin Vol. 11, No. 4, January 1895

A digitized copy of the January 1895 Ursinus College Bulletin.https://digitalcommons.ursinus.edu/ucbulletin/1101/thumbnail.jp

Ursinus College Bulletin Vol. 11, No. 2, November 1894

A digitized copy of the November 1894 Ursinus College Bulletin.https://digitalcommons.ursinus.edu/ucbulletin/1099/thumbnail.jp

Stressor- and Corticotropin releasing Factor-induced Reinstatement and Active Stress-related Behavioral Responses are Augmented Following Long-access Cocaine Self-administration by Rats

Rationale Stressful events during periods of drug abstinence likely contribute to relapse in cocaine-dependent individuals. Excessive cocaine use may increase susceptibility to stressor-induced relapse through alterations in brain corticotropin-releasing factor (CRF) responsiveness. Objectives This study examined stressor- and CRF-induced cocaine seeking and other stress-related behaviors in rats with different histories of cocaine self-administration (SA). Materials and methods Rats self-administered cocaine under short-access (ShA; 2 h daily) or long-access (LgA; 6 h daily) conditions for 14 days or were provided access to saline and were tested for reinstatement by a stressor (electric footshock), cocaine or an icv injection of CRF and for behavioral responsiveness on the elevated plus maze, in a novel environment and in the light–dark box after a 14- to 17-day extinction/withdrawal period. Results LgA rats showed escalating patterns of cocaine SA and were more susceptible to reinstatement by cocaine, EFS, or icv CRF than ShA rats. Overall, cocaine SA increased activity in the center field of a novel environment, on the open arms of the elevated plus maze, and in the light compartment of a light–dark box. In most cases, the effects of cocaine SA were dependent on the pattern/amount of cocaine intake with statistically significant differences from saline self-administering controls only observed in LgA rats. Conclusions When examined after several weeks of extinction/ withdrawal, cocaine SA promotes a more active pattern of behavior during times of stress that is associated with a heightened susceptibility to stressor-induced cocaine-seeking behavior and may be the consequence of augmented CRF regulation of addiction-related neurocircuitry

Interpolation with the polynomial kernels

The polynomial kernels are widely used in machine learning and they are one of the default choices to develop kernel-based classification and regression models. However, they are rarely used and considered in numerical analysis due to their lack of strict positive definiteness. In particular they do not enjoy the usual property of unisolvency for arbitrary point sets, which is one of the key properties used to build kernel-based interpolation methods. This paper is devoted to establish some initial results for the study of these kernels, and their related interpolation algorithms, in the context of approximation theory. We will first prove necessary and sufficient conditions on point sets which guarantee the existence and uniqueness of an interpolant. We will then study the Reproducing Kernel Hilbert Spaces (or native spaces) of these kernels and their norms, and provide inclusion relations between spaces corresponding to different kernel parameters. With these spaces at hand, it will be further possible to derive generic error estimates which apply to sufficiently smooth functions, thus escaping the native space. Finally, we will show how to employ an efficient stable algorithm to these kernels to obtain accurate interpolants, and we will test them in some numerical experiment. After this analysis several computational and theoretical aspects remain open, and we will outline possible further research directions in a concluding section. This work builds some bridges between kernel and polynomial interpolation, two topics to which the authors, to different extents, have been introduced under the supervision or through the work of Stefano De Marchi. For this reason, they wish to dedicate this work to him in the occasion of his 60th birthday