Incidence of Agro-Climate Variability over Grass-Fed Cattle Markets.

The marginal contribution of each of the selected variables was quantified in terms of premiums and discounts and mapped as dynamic iso-price regions that illustrate geographic and seasonal permanent price patterns for feeder cattle, as well as changing market conditions derived from unexpected climate and weather variability. The graphic representation of how price patterns may change with climate variability allows for a better understanding of short term market disequilibrium derived from this type of variability. This may help cattle operators and producers improve farm management and making informed decisions.cattle prices, climate variability, agro-ecological conditions, seasonal effects, price formation, differentiated products, Demand and Price Analysis, Livestock Production/Industries,

Renormalization Group Study of the Standard Model and its Extensions: II. the Minimal Supersymmetric Standard Model

In this paper we summarize the minimal supersymmetric standard model as well as the renormalization group equations of its parameters. We proceed to examine the feasability of the model when the breaking of supersymmetry is parametrized by the soft terms suggested by supergravity theories. In such models, the electroweak symmetry is exact at tree level and is broken spontaneously at one loop order. We make the additional assumption that the GUT-inspired relation $m_b=m_\tau$ be valid at the scale where the gauge coupling constants unify, which constrains the value of the top quark mass. For all types of soft breaking terms expected in supergravity theories, we present the results of numerical runs which yield electroweak breaking at the required scale. These yield not only the allowed ranges for the soft supersymmetry breaking parameters, but also the value of the supersymmetric partner' masses. For example in the strict no-scale model, in which global supersymmetry breaking arises solely from soft supersymmetry breaking parameters, but also the value of the supersymmetric partner' masses. For example in the strict no-scale model, in which global supersymmetry breaking arises solely from soft gaugino masses, we find that $M_t$ can be no heavier than $\sim 127$ GeV.Comment: 41 pages. ReVTeX typeset. 8 figures not included but available (as well as a full postscript version of the paper including the figures) by anonymous FTP at uful07.phys.ufl.edu in the het/UFIFT-HEP-93-18 directory. Report No. UFIFT-HEP-93-1

Ctrl-MORE: A Framework to Integrate Controllers of Multi-DoF Robot for Developers and Users

In recent years, many different feedback controllers for robotic applications have been proposed and implemented. However, the high coupling between the different software modules made their integration into one common architecture difficult. Consequently, this has hindered the ability of a user to employ the different controllers into a single, general and modular framework. To address this problem, we present Ctrl-MORE, a software architecture developed to fill the gap between control developers and other users in robotic applications. On one hand, Ctrl-MORE aims to provide developers with an opportunity to integrate easily and share their controllers with other roboticists working in different areas. For example, manipulation, locomotion, vision and so on. On the other hand, it provides to end-users a tool to apply the additional control strategies that guarantee the execution of desired behaviors in a transparent, yet efficient way. The proposed control architecture allows an easier integration of general purpose feedback controllers, such as stabilizers, with higher control layers such as trajectory planners, increasing the robustness of the overall system

ADDRESSING THE IMPACT ON SOIL DEGRADATION OF CHANGE FROM GRASSLAND TO CROPLAND: A CASE STUDY IN THE URUGUAYAN GRASSLANDS

Globally, there has been large-scale conversion of natural grassland to cropland ecosystems which this has led to land degradation that could reduce future food security, other ecosystem services and even climate. Currently, there is a dearth of quantitative information assessing the severity, distribution, and causes of this land degradation. For practical purposes, this information is needed to develop improved methods of land use (LU) conversion. Uruguay, in contrast with many other regions, still has a high proportion of unimproved grasslands but, during the last 15 years, there has been extensive conversion to grow grain crops. The fundamental goal of this dissertation was to quantify soil degradation resulting from this LU change. Two aspects of soil degradation were studied, soil organic carbon (SOC) and erosion by water. The Environmental Policy Integrated Climate biophysical simulation model (EPIC) was used to model the grassland and cropping systems. The study consisted of three steps: (1) calibration and validation of the model for the Uruguayan agroecosystems, and development of a spatial version, (2) identification of the LU change areas, and (3) quantification of soil degradation as a result of the LU changes. The EPIC model adequately reproduced the field-scale SOC dynamics and erosion in field validation sites. Further, the spatial version of the model was found to simulate spatial and temporal performance adequately. LU change areas during 2000-2013 were mapped and found to cover an area of 410,000 ha, about 13% of potential area for commercial agriculture. LU greatly affected soil degradation. It was greatest for continuous Soybean cultivation with no crop rotation, and lowest for grassland (no conversion to cropping). In addition to LU, slope and initial SOC had significant effects on degradation. The main conclusions were that the recent and continuing conversion from grassland to cropland has caused significant soil degradation, but that some modifications of LU can reduce the risk of degradation

Semi-Supervised Data Summarization: Using Spectral Libraries to Improve Hyperspectral Clustering

Hyperspectral imagers produce very large images, with each pixel recorded at hundreds or thousands of different wavelengths. The ability to automatically generate summaries of these data sets enables several important applications, such as quickly browsing through a large image repository or determining the best use of a limited bandwidth link (e.g., determining which images are most critical for full transmission). Clustering algorithms can be used to generate these summaries, but traditional clustering methods make decisions based only on the information contained in the data set. In contrast, we present a new method that additionally leverages existing spectral libraries to identify materials that are likely to be present in the image target area. We find that this approach simultaneously reduces runtime and produces summaries that are more relevant to science goals

Quantitative Assessment of Cancer Vascular Architecture by Skeletonization of High-resolution 3-D Contrast-enhanced Ultrasound Images: Role of Liposomes and Microbubbles.

The accurate characterization and description of the vascular network of a cancer lesion is of paramount importance in clinical practice and cancer research in order to improve diagnostic accuracy or to assess the effectiveness of a treatment. The aim of this study was to show the effectiveness of liposomes as an ultrasound contrast agent to describe the 3-D vascular architecture of a tumor. Eight C57BL/6 mice grafted with syngeneic B16-F10 murine melanoma cells were injected with a bolus of 1,2-Distearoyl-sn-glycero-3-phosphocoline (DSPC)-based non-targeted liposomes and with a bolus of microbubbles. 3-D contrast-enhanced images of the tumor lesions were acquired in three conditions: pre-contrast, after the injection of micro bubbles, and after the injection of liposomes. By using a previously developed reconstruction and characterization image processing technique, we obtained the 3-D representation of the vascular architecture in these three conditions. Six descriptive parameters of these networks were also computed: the number of vascular trees (NT), the vascular density (VD), the number of branches, the 2-D curvature measure, the number of vascular flexes of the vessels, and the 3-D curvature. Results showed that all the vascular descriptors obtained by liposome-based images were statistically equal to those obtained by using microbubbles, except the VD which was found to be lower for liposome images. All the six descriptors computed in pre-contrast conditions had values that were statistically lower than those computed in presence of contrast, both for liposomes and microbubbles. Liposomes have already been used in cancer therapy for the selective ultrasound-mediated delivery of drugs. This work demonstrated their effectiveness also as vascular diagnostic contrast agents, therefore proving that liposomes can be used as efficient “theranostic” (i.e. therapeutic 1 diagnostic) ultrasound probes

Sheath parameters for non-Debye plasmas: simulations and arc damage

This paper describes the surface environment of the dense plasma arcs that damage rf accelerators, tokamaks and other high gradient structures. We simulate the dense, non-ideal plasma sheath near a metallic surface using Molecular Dynamics (MD) to evaluate sheaths in the non-Debye region for high density, low temperature plasmas. We use direct two-component MD simulations where the interactions between all electrons and ions are computed explicitly. We find that the non-Debye sheath can be extrapolated from the Debye sheath parameters with small corrections. We find that these parameters are roughly consistent with previous PIC code estimates, pointing to densities in the range $10^{24} - 10^{25}\mathrm{m}^{-3}$. The high surface fields implied by these results could produce field emission that would short the sheath and cause an instability in the time evolution of the arc, and this mechanism could limit the maximum density and surface field in the arc. These results also provide a way of understanding how the "burn voltage" of an arc is generated, and the relation between self sputtering and the burn voltage, while not well understood, seems to be closely correlated. Using these results, and equating surface tension and plasma pressure, it is possible to infer a range of plasma densities and sheath potentials from SEM images of arc damage. We find that the high density plasma these results imply and the level of plasma pressure they would produce is consistent with arc damage on a scale 100 nm or less, in examples where the liquid metal would cool before this structure would be lost. We find that the sub-micron component of arc damage, the burn voltage, and fluctuations in the visible light production of arcs may be the most direct indicators of the parameters of the dense plasma arc, and the most useful diagnostics of the mechanisms limiting gradients in accelerators.Comment: 8 pages, 16 figure

A method for colocating satellite X_(CO₂) data to ground-based data and its application to ACOS-GOSAT and TCCON

Satellite measurements are often compared with higher-precision ground-based measurements as part of validation efforts. The satellite soundings are rarely perfectly coincident in space and time with the ground-based measurements, so a colocation methodology is needed to aggregate "nearby" soundings into what the instrument would have seen at the location and time of interest. We are particularly interested in validation efforts for satellite-retrieved total column carbon dioxide (X_(CO₂)), where X_(CO₂) data from Greenhouse Gas Observing Satellite (GOSAT) retrievals (ACOS, NIES, RemoteC, PPDF, etc.) or SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) are often colocated and compared to ground-based column X_(CO₂) measurement from Total Carbon Column Observing Network (TCCON). Current colocation methodologies for comparing satellite measurements of total column dry-air mole fractions of CO₂ (X_(CO₂)) with ground-based measurements typically involve locating and averaging the satellite measurements within a latitudinal, longitudinal, and temporal window. We examine a geostatistical colocation methodology that takes a weighted average of satellite observations depending on the "distance" of each observation from a ground-based location of interest. The "distance" function that we use is a modified Euclidian distance with respect to latitude, longitude, time, and midtropospheric temperature at 700 hPa. We apply this methodology to X_(CO₂) retrieved from GOSAT spectra by the ACOS team, cross-validate the results to TCCON X_(CO₂) ground-based data, and present some comparisons between our methodology and standard existing colocation methods showing that, in general, geostatistical colocation produces smaller mean-squared error