University of New Mexico

About: University of New Mexico is a education organization based out in Albuquerque, New Mexico, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 28870 authors who have published 64767 publications receiving 2578371 citations. The organization is also known as: UNM & Universitatis Novus Mexico.

Effects of changing spatial scale on the analysis of landscape pattern

Abstract: The purpose of this study was to observe the effects of changing the grain (the first level of spatial resolution possible with a given data set) and extent (the total area of the study) of landscape data on observed spatial patterns and to identify some general rules for comparing measures obtained at different scales. Simple random maps, maps with contagion (i.e., clusters of the same land cover type), and actual landscape data from USGS land use (LUDA) data maps were used in the analyses. Landscape patterns were compared using indices measuring diversity (H), dominance (D) and contagion (C). Rare land cover types were lost as grain became coarser. This loss could be predicted analytically for random maps with two land cover types, and it was observed in actual landscapes as grain was increased experimentally. However, the rate of loss was influenced by the spatial pattern. Land cover types that were clumped disappeared slowly or were retained with increasing grain, whereas cover types that were dispersed were lost rapidly. The diversity index decreased linearly with increasing grain size, but dominance and contagion did not show a linear relationship. The indices D and C increased with increasing extent, but H exhibited a variable response. The indices were sensitive to the number (m) of cover types observed in the data set and the fraction of the landscape occupied by each cover type (P k); both m and P kvaried with grain and extent. Qualitative and quantitative changes in measurements across spatial scales will differ depending on how scale is defined. Characterizing the relationships between ecological measurements and the grain or extent of the data may make it possible to predict or correct for the loss of information with changes in spatial scale.

Measurement of neutrino oscillation with KamLAND: evidence of spectral distortion.

Abstract: We present results of a study of neutrino oscillation based on a 766 ton/year exposure of KamLAND to reactor antineutrinos. We observe 258 [overline nu ]e candidate events with energies above 3.4 MeV compared to 365.2±23.7 events expected in the absence of neutrino oscillation. Accounting for 17.8±7.3 expected background events, the statistical significance for reactor [overline nu ]e disappearance is 99.998%. The observed energy spectrum disagrees with the expected spectral shape in the absence of neutrino oscillation at 99.6% significance and prefers the distortion expected from [overline nu ]e oscillation effects. A two-neutrino oscillation analysis of the KamLAND data gives Deltam2=7.9 -0.5 +0.6 ×10-5 eV2. A global analysis of data from KamLAND and solar-neutrino experiments yields Deltam2=7.9 -0.5 +0.6 ×10-5 eV2 and tan2theta=0.40 -0.07 +0.10 , the most precise determination to date.

Biochemistry of exercise-induced metabolic acidosis

Abstract: The development of acidosis during intense exercise has traditionally been explained by the increased production of lactic acid, causing the release of a proton and the formation of the acid salt sodium lactate. On the basis of this explanation, if the rate of lactate production is high enough, the cellular proton buffering capacity can be exceeded, resulting in a decrease in cellular pH. These biochemical events have been termed lactic acidosis. The lactic acidosis of exercise has been a classic explanation of the biochemistry of acidosis for more than 80 years. This belief has led to the interpretation that lactate production causes acidosis and, in turn, that increased lactate production is one of the several causes of muscle fatigue during intense exercise. This review presents clear evidence that there is no biochemical support for lactate production causing acidosis. Lactate production retards, not causes, acidosis. Similarly, there is a wealth of research evidence to show that acidosis is caused by reactions other than lactate production, Every time ATP is broken down to ADP and Pi, a proton is released. When the ATP demand of muscle contraction is met by mitochondrial respiration, there is no proton accumulation in the cell, as protons are used by the mitochondria for oxidative phosphorylation and to maintain the proton gradient in the intermembranous space. It is only when the exercise intensity increases beyond steady state that there is a need for greater reliance on ATP regeneration from glycolysis and the phosphagen system. The ATP that is supplied from these nonmitochondrial sources and is eventually used to fuel muscle contraction increases proton release and causes the acidosis of intense exercise. Lactate production increases under these cellular conditions to prevent pyruvate accumulation and supply the NAD+ needed for phase 2 of glycolysis. Thus increased lactate production coincides with cellular acidosis and remains a good indirect marker for cell metabolic conditions that induce metabolic acidosis. If muscle did not produce lactate, acidosis and muscle fatigue would occur more quickly and exercise performance would be severely impaired.

Getting the Focus and the Group: Enhancing Analytical Rigor in Focus Group Research:

Abstract: In the literature on focus groups, far more attention has been devoted to how groups are organized and conducted than to issues of analysis. Although exploitation of group dynamics is touted as a virtue of focus groups, there is very little guidance in the literature with respect to how differences between group and individual discourse impact the analysis and interpretation of focus group data. In this article, the authors describe analytical challenges inherent in the interpretation of focus group data and suggest approaches for enhancing the rigor of analysis and the reliability and validity of focus group findings.