Search

The LUX (Large Underground Xenon) detector is a two-phase xenon Time Projection Chamber (TPC) designed to search for WIMP-nucleon dark matter interactions. As with all noble element detectors, continuous purification of the detector medium is essential to produce a large ($>$1ms) electron lifetime; this is necessary for efficient measurement of the electron signal which in turn is essential for achieving robust discrimination of signal from background events. In this paper we describe the development of a novel purification system deployed in a prototype detector. The results from the operation of this prototype indicated heat exchange with an efficiency above 94% up to a flow rate of 42 slpm, allowing for an electron drift length greater than 1 meter to be achieved in approximately two days and sustained for the duration of the testing period., 12 pages, 9 figures

Geant4 has been used throughout the nuclear and high-energy physics community to simulate energy depositions in various detectors and materials. These simulations have mostly been run with a source beam outside the detector. In the case of low-background physics, however, a primary concern is the effect on the detector from radioactivity inherent in the detector parts themselves. From this standpoint, there is no single source or beam, but rather a collection of sources with potentially complicated spatial extent. LUXSim is a simulation framework used by the LUX collaboration that takes a component-centric approach to event generation and recording. A new set of classes allows for multiple radioactive sources to be set within any number of components at run time, with the entire collection of sources handled within a single simulation run. Various levels of information can also be recorded from the individual components, with these record levels also being set at runtime. This flexibility in both source generation and information recording is possible without the need to recompile, reducing the complexity of code management and the proliferation of versions. Within the code itself, casting geometry objects within this new set of classes rather than as the default Geant4 classes automatically extends this flexibility to every individual component. No additional work is required on the part of the developer, reducing development time and increasing confidence in the results. We describe the guiding principles behind LUXSim, detail some of its unique classes and methods, and give examples of usage. * Corresponding author, kareem@llnl.gov, 45 pages, 15 figures

The objective of this research is to identify and quantify the motivations for organic grain farming in the United States. Survey data of US organic grain producers were used in regression models to find the statistical determinants of three motivations for organic grain production, including profit maximization, environmental stewardship, and an organic lifestyle. Results provide evidence that many organic grain producers had more than a single motivation and that younger farmers are more likely to be motivated by environmental and lifestyle goals than older farmers. Organic grain producers exhibited a diversity of motivations, including profit and stewardship.

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Evaluating the impact of using different starting conditions in econometric models is increasingly critical. This study demonstrates implications of using alternative starting value conditions and how these implications vary with econometric model complexity. This piece also proposes a universal approach in developing appropriate starting values for use in subsequent model estimation.

In this research, we work with data of futures contracts on foreign exchange rates for British pound (BP), Canadian dollar (CD), and Japanese yen (JY) that are traded at the Chicago Mercantile Exchange (CME) against US dollars. We model relationships between exchange rates in these currencies using linear models, feed forward artificial neural networks (ANN), and three versions of recurrent neural networks (RNN1, RNN2 and RNN3) for predicting exchange rates in these currencies against the US dollar. Our results on forecast evaluations based on AGS test the tests of forecast equivalence between any two competing models among the entire models employed for each of the series show that ANN and the three versions of RNN models offer superior forecasts for predicting BP, CD and JY exchange rates although the forecast evaluations based on MGN test are in sharp contrast. On the other hand forecast based on SIGN test shows that ANN and all the versions of RNN models offer superior forecasts for BP and CD in exception of JY exchange rates. The results for forecast evaluation for all the models for each of the series based on summary measures of forecast evaluations show that RNN3 model appears to offer the most accurate predictions of BP and RNN1 for JP exchange rates. However, none of the RNN models appear to be statistically superior to the benchmark (i.e., linear model) for predicting CD exchange rates.

To understand risk issues of U.S. organic grain farmers, six listening sessions were conducted in parts of the major grain producing regions in spring 2004. The views expressed at these sessions suggested the importance and uniqueness of risks in organic grain farming. Regional differences were observed, but many problems were common, including the limited availability of market information, shortfall of crop insurance policies, and revenue losses from on-farm storage, emergent marketing channels, and potential contamination. Our findings clearly imply a role for public and private institutions to collect and offer information on the organic markets and to educate the sectors supporting organic producers.

This paper provides an overview of the development of the Management Analysis and Strategic Thinking (MAST) program conducted by Kansas State University. This intensive management training course for progressive farm and agribusiness operators is being delivered successfully using a combination of face-to-face and distance extension delivery techniques. We find that some parts of the program are best delivered face to face and other parts are best delivered via distance. Of participants surveyed, 94% would recommend the MAST program to their peers, and 100% believe the program will have a positive impact on their businesses' bottom line.

Agricultural lenders in today’s environment face many challenges when evaluating the creditworthiness of farm borrowers. To address these challenges, a survey was conducted with financial institutions in Kansas and Indiana where agricultural lenders were asked for their responses to hypothetical agricultural loan requests. Each loan request differed by the borrower’s character, financial record keeping, productive standing, Fair Isaac credit bureau score, and credit risk. Lenders provided information about themselves and their financial institutions. The survey data obtained determine the relative importance of financial and nonfinancial information when analyzing agricultural loan applications. Tobit models are estimated to identify the borrower and lender characteristics that are important in determining loan approval, while OLS models are used to investigate the factors that affect interest rates offered to farm borrowers. The results offer a comparison of agricultural lending between two important agricultural states and provide lenders with insight on the factors that influence the decision‐making process of other agricultural lenders.

The objective of this study was to determine if site-specific application of postemergence herbicide was economically viable with current technologies. This objective was accomplished by: developing an algorithm that determined the economic optimal postemergence herbicide rate; creating models to determine the impact that postemergence herbicide rate has on yield; and determining whether site-specific application of postemergence herbicide has greater net returns than those from a uniform application of postemergence herbicide. Weed species identification and population counts were done on a regular grid in five fields across Kansas. A decision algorithm was developed to determine the economic optimal rate of postemergence herbicide for each grid cell. The site-specific herbicide rate and four standard herbicide rates [0, 0.5, 0.75, and full (1×) label rate] were applied according to a split-plot design. Weed population observations made three weeks after application showed that the site-specific treatment controlled the weeds present in the fields. Production functions developed to determine whether postemergence herbicide rate had an impact on yield showed that it had a positive, yet statistically insignificant, effect on yield. The difference in estimated net returns between applications of site-specific rate and uniform full-label rate covered all of the costs associated with site-specific application of postemergence herbicide. The margin between the estimated net returns for site-specific and uniform application of the economic optimal rate covered only a portion of the costs associated with site-specific application of postemergence herbicide.

One obstacle to successful modeling and prediction of crop yields using remotely sensed imagery is the identification of image masks. Image masking involves restricting an analysis to a subset of a region's pixels rather than using all of the pixels in the scene. Cropland masking, where all sufficiently cropped pixels are included in the mask regardless of crop type, has been shown to generally improve crop yield forecasting ability, but it requires the availability of a land cover map depicting the location of cropland. The authors present an alternative image masking technique, called yield-correlation masking, which can be used for the development and implementation of regional crop yield forecasting models and eliminates the need for a land cover map. The procedure requires an adequate time series of imagery and a corresponding record of the region's crop yields, and involves correlating historical, pixel-level imagery values with historical regional yield values. Imagery used for this study consisted of 1-km, biweekly AVHRR NDVI composites from 1989 to 2000. Using a rigorous evaluation framework involving five performance measures and three typical forecasting opportunities, yield-correlation masking is shown to have comparable performance to cropland masking across eight major U.S. region-crop forecasting scenarios in a 12-year cross-validation study. Our results also suggest that 11 years of time series AVHRR NDVI data may not be enough to estimate reliable linear crop yield models using more than one NDVI-based variable. A robust, but sub-optimal, all-subsets regression modeling procedure is described and used for testing, and historical United States Department of Agriculture crop yield estimates and linear trend estimates are used to gauge model performance.

In 1997, the Black Vermillion Dairy Environmental Cooperative (DEC) was started with an Environmental Protection Agency 319A grant. The DEC partially funded construction of manure storage projects at ten of thirty-seven Kansas dairies located in the Black Vermillion Watershed. The facilities were later studied using net present value (NPV) to evaluate their cost effectiveness. The NPV analysis showed that in most cases, investing in a manure storage structure can be profitable for the dairy. However, cost-share assistance often will be needed in order to have positive pre-tax and after-tax NPVs. Copyright 2005, Oxford University Press.

Forecast performance of artificial neural network models are investigated using Ashley et al. (1980) and the neural network nonlinearity test proposed by Lee et al. (1993) is employed to find possible existence of business cycle asymmetries in Canada, France, Japan, UK and USA real GDP growth rates. The results show that neural network models are more accurate than linear models for in-sample forecasts. However, when comparing the out-of-sample, linear models performed better than neural network models in all series. Results from neural network tests show that business cycle asymmetries do prevail in all the series.

Farm machinery is a vital part of most farming operations, from the physical work it performs in the production process to the enjoyment provided from its operation. As technological advancements in machinery and the crop production process evolve, farm sizes increase and profit margins often decrease. Therefore, efficient use of machinery and its contribution to a producer’s relative cost of production is increasingly important. Machinery costs can be determined from farm records or cost estimators; however, these methods often result in generalized whole farm or per machine costs, rather than per unit (e.g., acre, ton, bale, etc.) machinery costs. One alternative to calculating the myriad of machinery costs is to use custom farming rates. Custom farming rates are rates paid for an operator to perform an operation, such as harvesting, planting, tillage, etc., and are usually based on a per unit charge (i.e. acre, ton, bales, etc.). However, with the large amount of neighbor-to-neighbor work, and family custom farming done, whether published custom rates truly represent full machinery ownership and operating costs is often questioned. If the full cost to perform these operations is known, it will allow an individual farm to evaluate its relative machinery costs and allow its crop machinery costs to be benchmarked against an expected cost.

Thirty-one dairy producers participated in the Kansas Farm Management Association (KFMA) dairy enterprise analysis each year from 2002 to 2004. The dairy farms were sorted based on 3-year average returns over total costs and were categorized as high-, medium-, and low-profit farms. The highestprofit farms earned an average of $795 more per cow ($4.20 per cwt of milk) than the lowprofit farms earned. High-profit farms averaged $521 more milk sales per cow than lowprofit farms did. This difference in profitability was due entirely to greater milk production, inasmuch as milk prices among profit groups did not differ from each other. Highprofit farms produced almost 4,000 lb more milk per cow per year and had slightly lower costs than low-profit farms had. Returns for the mid-profit farms were more than $400 per cow less than returns of the top farms, but were more than $350 per cow greater than those of low-profit farms. The mid-profit farms had production levels similar to those of the high-profit farms, but their costs were significantly greater. Over the 3 years analyzed, it was better to have high production and high costs than to have low production and low costs. But these 3-year averages indicate that dairies can achieve high production levels while keeping costs in check, and these operations are significantly more profitable than other dairies. (

Several “best management practices” (BMPs) aimed at reducing movement of nutrients, pesticides, and sediment into surface water resources have been developed and promoted by Extension and other agencies over the past several years. This study utilizes actual farm-level economic and BMP adoption data to rigorously analyze the relationship between BMP use and farm profitability. Results indicate that adoption of nutrient BMPs has a significant positive effect on net farm income (NFI) for wheat and corn, while herbicide BMP adoption, particularly use of BMPs related to the application of atrazine on corn, has a small (but statistically significant) negative impact on income. Adoption of soil conservation BMPs is not shown to have a statistically significant impact on farm income. Copyright 2004, Oxford University Press.

Recently emerged technologies permitting precision fanning provide opportunities to collect and evaluate vast amounts of data; yet, a formal method for incorporating additional yield-affecting information into fertilizer-yield response models is still largely unavailable to site-specific managers. This research develops an integrated yield model that combines laboratory-based fertilizer recommendations with data from multiple independent variables. Kansas wheat (Triticum aestivum L. sp. aestivum) was the target crop, and simulated soil test and yield data were characteristic of data from the literature and this geographic area. Independent variables in the plateau-type yield model included fertilizer N and P, soil test N (STN) and soil test P (STP), and Z (representing all other causal factors). Consideration of the potential benefits of managing STP is an explicit outcome of this research. To expand the modeling procedures to include actual farm information, data from a northwest Kansas farm were used to replace the simulated Z variable. Additionally, maximum entropy (ME) was examined as a statistical technique for using the farm's N and P data to modify the predicted N- and P-response of laboratory-based models. Based on out-of-sample yield prediction accuracy, the ME models were generally the most accurate, improving root mean squared prediction error by as much as 14% relative to a model estimated with only farm data. Because the ME models were the most accurate and provided fertilizer recommendations similar to those from soil testing laboratories, this approach should provide a reliable framework for developing site-specific fertilizer recommendations that depend on factors other than STN and STP.

This study compares a variety of farm tractor depreciation methods to determine which most accurately estimates farm tractor values. These alternative depreciation methods consider different factors for estimating remaining value and vary in difficulty of use. Pairwise comparisons of mean absolute percentage error and forecast accuracy regression models were used to evaluate the accuracy of the depreciation methods, which depend on age, intensity of use, and manufacturer. Based on the results of this study, the Cross and Perry method was generally the most accurate. Copyright 2003, Oxford University Press.

This research introduces an industrial targeting system intended to improve local decision making related to selection of targets for business recruitment. The Plains Economic Targeting System (PETS) consists of a series of econometric equations that match industry input and market requirements with community characteristics to generate a probability of new business location over a given time period. The system matches location requirements for 78 industry sectors to local characteristics for 414 counties in six Great Plains states. Further, the coefficients generated for a given county are transformed into marginal impacts, providing important information relating to local policies that can improve the probability of attracting a given industry. Copyright 2002, Oxford University Press.

This study compares how well three semi-nonparametric functions, the Fourier flexible form, asymptotically ideal model, and neural networks, approximate simulated production data. Results show that higher order series expansions better approximate the true technology for data sets that have little or no measurement error. For highly nonlinear technologies and much measurement error, lower order expansions may be appropriate.

Parametric, non-parametric, and semi-parametric approaches are commonly used for modeling correlated distributions. Semi-parametric and non-parametric approaches are used to examine the risk situation for Kansas agriculture. Results from the model indicate that 2000 will be another difficult year for Kansas farmers, although crop income will increase slightly from 1999. However, unless another supplemental infusion of government payments occurs, crop income is expected to be the lowest since 1992.

Recent evidence suggests that cyclical cattle inventories are driven by exogenous shocks. This article examines a second possible contributing factor to the cattle cycle: a market timing effect that arises from individual attempts to maintain countercyclical inventories. The model uncovers an important conceptual point: to the extent that cycles are driven by exogenous shocks, a representative producer should outperform one who maintains a constant inventory; whereas, for cycles induced by market timing, a representative producer should underperform one with a constant inventory. Simulated net returns over 1974−98 reveal that a constant-inventory manager significantly outperformed the representative U.S. producer, which indicates that market timing influences the cattle cycle. Copyright 2000, Oxford University Press.

This research examined whether university extension and research marketing economists have similar or different views regarding marketing strategies, price forecasts, and futures market efficiency. Results from surveys conducted of extension and research marketing economists found that perceptions differed in seven of twelve questions posed to both groups. Three important findings of this study were (a) that both groups tended to not believe in the efficient market hypothesis, (b) that extension and researchers disagreed as to whether marketing strategies should be based on statistically significant findings, and (c) that extension and research economists rarely collaborate.

This paper uses semi-nonparametric and Diewert-flexible forms to estimate substitution elasticities between capital and labor. Results show that capital and labor are substitutes. Estimated elasticities from semi-nonparametric forms vary more over time than those from Diewert-flexible forms.

Price and yield risk are among the most important factors influencing the production and marketing actions of agricultural producers. Price risk is especially important to agricultural producers. In the survey which is the focus of this study, 67 percent of Kansas crop farmers indicated that output and/or input price uncertainty was the major source of risk faced by their farm operation. Price risk management is of continuing interest to producers as well as to academic researchers and extension educators. Methods for managing price risk include forward pricing, hedging, options trading, and commodity storage. Marketing practices of agricultural producers have received considerable attention in recent years. Much of this research has focused on producers' adoption of forward and futures pricing methods. Hill; Asplund, Forster, and Stout; Makus et al.; Shapiro and Brorsen; and Goodwin and Schroeder evaluated producers' adoption of forward pricing techniques. Through this research a better understanding of the characteristics of producers associated with one dimension of agricultural marketing, forward pricing, has emerged. In general, these studies have revealed that the adoption of forward pricing techniques increases with farm size, producer education, and financial leverage. Although recent research has enhanced understanding of forward pricing adoption, almost no information exists about the frequency of marketing (the total number of times in a crop year that a portion of the crop is sold). While state-wide crop marketing percentages are readily available by month, little is known about individual producer behavior, and in particular marketing frequency. Marketing and risk management plans have become increasingly complex and in many cases involve more frequent marketings. Knowledge about the relationships between producers' chara teristics and their marketings frequencies will add to the current understanding of producer marke ing practices. This research should be of interest to those providing marketing advisory serv ces, helping them to better target their clientele. F r example, a marketing advisory firm whose comparative advantage lies in multiplemarketings strategies should be especially interes ed in understanding factors that may be associated with marketing frequency. The objective of this analysis is to evaluate the frequency of crop marketings for a sample of 572 Kansas wheat, corn, milo (grain sorghum), and soybean producers.' Characteristics of the producers and farm operations will be evaluated for their effects on the frequency of marketing.

An out-of-sample prediction of Kansas farmers' responses to five surveyed questions involving risk is used to compare ordered multinomial logistic regression models with feedforward backpropagation neural network models. Although the logistic models often predict more accurately than the neural network models in a mean-squared error sense, the neural network models are shown to be more accommodating of loss functions associated with a desire to predict certain combinations of categorical responses more accurately than others. Copyright 1996, Oxford University Press.

Out-of-sample forecasting of annual U.S. per capita food consumption, applying data from 1923 to 1992, is used as a basis for model selection among the absolute price Rotterdam model, a first-differenced linear approximate almost ideal demand system (FDLA/ALIDS) model, and a first-differenced double-log demand system. Conditional-on-price consumption forecasts derived from elasticities are determined to be superior to direct statistical model forecasts. Models with consumer theory imposed through parametric restrictions provide better forecasts than models with little theory-imposition. For these data, a double-log demand system is a superior forecaster to the Rotterdam model, which is superior to the FDLA/ALIDS model. Copyright 1996, Oxford University Press.

LUX is a two-phase (liquid/gas) xenon time projection chamber designed to detect nuclear recoils from interactions with dark matter particles. Signals from the LUX detector are processed by custom-built analog electronics which provide properly shaped signals for the trigger and data acquisition (DAQ) systems. The DAQ is composed of commercial digitizers with firmware customized for the LUX experiment. Data acquisition systems in rare-event searches must accommodate high rate and large dynamic range during precision calibrations involving radioactive sources, while also delivering low threshold for maximum sensitivity. The LUX DAQ meets these challenges using real-time baseline suppression that allows for a maximum event acquisition rate in excess of 1.5 kHz with virtually no deadtime. This paper describes the LUX DAQ and the novel acquisition techniques employed in the LUX experiment. © 2011 Elsevier B.V. All rights reserved.

The Large Underground Xenon (LUX) collaboration has designed and constructed a dual-phase xenon detector, in order to conduct a search for Weakly Interacting Massive Particles(WIMPs), a leading dark matter candidate. The goal of the LUX detector is to clearly detect (or exclude) WIMPS with a spin independent cross section per nucleon of $2\times 10^{-46}$ cm$^{2}$, equivalent to $\sim$1 event/100 kg/month in the inner 100-kg fiducial volume (FV) of the 370-kg detector. The overall background goals are set to have $, Comment: 50 pages, 16 figures

We report results of a search for light (3.5x10^{-42} cm^2, for a dark matter particle mass m_{\chi}=8 GeV. We find that our data strongly constrain recent elastic dark matter interpretations of excess low-energy events observed by CoGeNT and CRESST-II, as well as the DAMA annual modulation signal., Comment: Manuscript identical to v2 (published version) but also contains erratum. Note v3==v2 but without \linenumbers

Liquid Xenon (LXe) is an excellent material for experiments designed to detect dark matter in the form of Weakly Interacting Massive Particles (WIMPs). A low energy detection threshold is essential for a sensitive WIMP search. The understanding of the relative scintillation efficiency (Leff) and ionization yield of low energy nuclear recoils in LXe is limited for energies below 10 keV. In this paper, we present new measurements that extend the energy down to 4 keV, finding that Leff decreases with decreasing energy. We also measure the quenching of scintillation efficiency due to the electric field in LXe, finding no significant field dependence., Comment: 10 pages, 15 figures On version v4 we describe in more detail the trigger setup and have edited several figure to help the reader understand them

XENON10 is the first two-phase xenon time projection chamber (TPC) developed within the XENON dark matter search program. The TPC, with an active liquid xenon (LXe) mass of about 14 kg, was installed at the Gran Sasso underground laboratory (LNGS) in Italy, and operated for more than one year, with excellent stability and performance. Results from a dark matter search with XENON10 have been published elsewhere. In this paper, we summarize the design and performance of the detector and its subsystems, based on calibration data using sources of gamma-rays and neutrons as well as background and Monte Carlo simulations data. The results on the detector's energy threshold, energy and position resolution, and overall efficiency show a performance that exceeds design specifications, in view of the very low energy threshold achieved (

The Large Underground Xenon (LUX) dark matter search experiment is currently being deployed at the Homestake Laboratory in South Dakota. We will highlight the main elements of design which make the experiment a very strong competitor in the field of direct detection, as well as an easily scalable concept. We will also present its potential reach for supersymmetric dark matter detection, within various timeframes ranging from 1 year to 5 years or more., 4 pages, in proceedings of the SUSY09 conference

We report results from tests of $^{83}$Kr$^{\mathrm{m}}$, as a calibration source in liquid argon and liquid neon. $^{83}$Kr$^{\mathrm{m}}$ atoms are produced in the decay of $^{83}$Rb, and a clear $^{83}$Kr$^{\mathrm{m}}$ scintillation peak at 41.5 keV appears in both liquids when filling our detector through a piece of zeolite coated with $^{83}$Rb. Based on this scintillation peak, we observe 6.0 photoelectrons/keV in liquid argon with a resolution of 6% ($\sigma$/E) and 3.0 photoelectrons/keV in liquid neon with a resolution of 19% ($\sigma$/E). The observed peak intensity subsequently decays with the $^{83}$Kr$^{\mathrm{m}}$ half-life after stopping the fill, and we find evidence that the spatial location of $^{83}$Kr$^{\mathrm{m}}$ atoms in the chamber can be resolved. $^{83}$Kr$^{\mathrm{m}}$ will be a useful calibration source for liquid argon and neon dark matter and solar neutrino detectors., Comment: 7 pages, 12 figures

We report the preparation of a Kr-83m source and its subsequent use in calibrating a liquid xenon detector. Kr-83m atoms were produced through the decay of Rb-83 atoms trapped in zeolite molecular sieve and were then introduced into liquid xenon. Decaying Kr-83m nuclei were detected through liquid xenon scintillation. Conversion electrons with energies of 9.4 keV and 32.1 keV from the decay of Kr-83m were both observed. This calibration source will allow the characterization of the scintillation and ionization response of noble liquid detectors at low energies, highly valuable for the search for WIMP dark matter. Kr-83m may also be useful for measuring fluid flow dynamics, both to understand purification in noble liquid-based particle detectors, as well as for studies of classical and quantum turbulence in superfluid helium., Comment: Minor edits to match published version

XENON10 is an experiment designed to directly detect particle dark matter. It is a dual phase (liquid/gas) xenon time-projection chamber with 3D position imaging. Particle interactions generate a primary scintillation signal (S1) and ionization signal (S2), which are both functions of the deposited recoil energy and the incident particle type. We present a new precision measurement of the relative scintillation yield \leff and the absolute ionization yield Q_y, for nuclear recoils in xenon. A dark matter particle is expected to deposit energy by scattering from a xenon nucleus. Knowledge of \leff is therefore crucial for establishing the energy threshold of the experiment; this in turn determines the sensitivity to particle dark matter. Our \leff measurement is in agreement with recent theoretical predictions above 15 keV nuclear recoil energy, and the energy threshold of the measurement is 4 keV. A knowledge of the ionization yield \Qy is necessary to establish the trigger threshold of the experiment. The ionization yield \Qy is measured in two ways, both in agreement with previous measurements and with a factor of 10 lower energy threshold., 8 pages, 9 figures. To be published in Nucl. Instrum. Methods A

XENON10 is an experiment to directly detect weakly interacting massive particle (WIMPs), which may comprise the bulk of the non-baryonic dark matter in our Universe. We report new results for spin-dependent WIMP-nucleon interactions with 129-Xe and 131-Xe from 58.6 live-days of operation at the Laboratori Nazionali del Gran Sasso (LNGS). Based on the non-observation of a WIMP signal in 5.4 kg of fiducial liquid xenon mass, we exclude previously unexplored regions in the theoretically allowed parameter space for neutralinos. We also exclude a heavy Majorana neutrino with a mass in the range of 10 GeV -2 TeV as a dark matter candidate under standard assumptions for its density and distribution in the galactic halo., 4 pages, 4 figures; final version published in PRL (added DAMA region to Figure 1)