38,711 research outputs found
To be or not to Be? - First Evidence for Neutrinoless Double Beta Decay
Double beta decay is indispensable to solve the question of the neutrino mass
matrix together with oscillation experiments. Recent analysis of the most
sensitive experiment since nine years - the HEIDELBERG-MOSCOW experiment in
Gran-Sasso - yields a first indication for the neutrinoless decay mode. This
result is the first evidence for lepton number violation and proves the
neutrino to be a Majorana particle. We give the present status of the analysis
in this report. It excludes several of the neutrino mass scenarios allowed from
present neutrino oscillation experiments - only degenerate scenarios and those
with inverse mass hierarchy survive. This result allows neutrinos to still play
an important role as dark matter in the Universe. To improve the accuracy of
the present result, considerably enlarged experiments are required, such as
GENIUS. A GENIUS Test Facility has been funded and will come into operation by
early 2003.Comment: 16 pages, latex, 10 figures, Talk was presented at International
Conference "Neutrinos and Implications for Physics Beyond the Standard
Model", Oct. 11-13, 2002, Stony Brook, USA, Proc. (2003) ed. by R. Shrock,
also see Home Page of Heidelberg Non-Accelerator Particle Physics Group:
http://www.mpi-hd.mpg.de/non_acc
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How significant is the impact of irrigation on the local hydroclimate in Californias Central Valley? Comparison of model results with ground and remote-sensing data
The effect of irrigation on regional climate has been studied over the years. However, in most studies, the model was usually set at coarse resolution, and the soil moisture was set to field capacity at each time step. We reinvestigated this issue over the Central Valley of California's agricultural area by: (1) using the regional climate model at different resolutions down to the finest resolution of 4 km for the most inner domain, covering California's Central Valley, the central coast, the Sierra Nevada Mountains, and water; (2) using a more realistic irrigation scheme in the model through the use of different allowable soil water depletion configurations; and (3) evaluating the simulated results against satellite and in situ observations available through the California Irrigation Management Information System (CIMIS). The simulation results with fine model resolution and with the more realistic irrigation scheme indicate that the surface meteorological fields are noticeably improved when compared with observations from the CIMIS network and Moderate Resolution Imaging Spectroradiometer data. Our results also indicate that irrigation has significant impacts on local meteorological fields by decreasing temperature by 3°-7°C and increasing relative humidity by 9-20%, depending on model resolutions and allowable soil water depletion configurations. More significantly, our results using the improved model show that the effects of irrigation on weather and climate do not extend very far into nonirrigated regions. Copyright 2011 by the American Geophysical Union
Analysis of the Cytisetea scopario-striati scrubs in the south-west-centre of the Iberian Peninsula
The statistical and phytosociological study of 255 relevés taken in the south-west of the Iberian Peninsula and
made up of our own samples and previous publications reveals how close these relevés, previously ascribed to different
syntaxa, really are. Our re-arrangement of the data leads us to propose for the territory the 15 associations already published
and three new ones, namely: Genisto floridae-Adenocarpetum argyrophylli ass. nova hoc loco, Cytisetum bourgaei-
eriocarpi nova, Lavandulo viridis-Cytisetum striati ass. nova hoc. loco. We also suggest a name correction,
Adenocarpo anisochili-Cytisetum scoparii J.C. Costa et al. 2000 corr., and a status change, namely, Ulici latebracteati-
Cytisetum striati (Costa et al. 2000) status novo
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Daytime precipitation estimation using bispectral cloud classification system
Two previously developed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) algorithms that incorporate cloud classification system (PERSIANN-CCS) and multispectral analysis (PERSIANN-MSA) are integrated and employed to analyze the role of cloud albedo from Geostationary Operational Environmental Satellite-12 (GOES-12) visible (0.65 μm) channel in supplementing infrared (10.7 mm) data. The integrated technique derives finescale (0.04° × 0.04° latitudelongitude every 30 min) rain rate for each grid box through four major steps: 1) segmenting clouds into a number of cloud patches using infrared or albedo images; 2) classification of cloud patches into a number of cloud types using radiative, geometrical, and textural features for each individual cloud patch; 3) classification of each cloud type into a number of subclasses and assigning rain rates to each subclass using a multidimensional histogram matching method; and 4) associating satellite gridbox information to the appropriate corresponding cloud type and subclass to estimate rain rate in grid scale. The technique was applied over a study region that includes the U.S. landmass east of 115°W. One reference infrared-only and three different bis-pectral (visible and infrared) rain estimation scenarios were compared to investigate the technique's ability to address two major drawbacks of infrared-only methods: 1) underestimating warm rainfall and 2) the inability to screen out no-rain thin cirrus clouds. Radar estimates were used to evaluate the scenarios at a range of temporal (3 and 6 hourly) and spatial (0.04°, 0.08°, 0.12°, and 0.24° latitude-longitude) scales. Overall, the results using daytime data during June-August 2006 indicate that significant gain over infrared-only technique is obtained once albedo is used for cloud segmentation followed by bispectral cloud classification and rainfall estimation. At 3-h, 0.04° resolution, the observed improvement using bispectral information was about 66% for equitable threat score and 26% for the correlation coefficient. At coarser 0.24° resolution, the gains were 34% and 32% for the two performance measures, respectively. © 2010 American Meteorological Society
Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation
Most recent approaches use the sequence-to-sequence model for paraphrase
generation. The existing sequence-to-sequence model tends to memorize the words
and the patterns in the training dataset instead of learning the meaning of the
words. Therefore, the generated sentences are often grammatically correct but
semantically improper. In this work, we introduce a novel model based on the
encoder-decoder framework, called Word Embedding Attention Network (WEAN). Our
proposed model generates the words by querying distributed word representations
(i.e. neural word embeddings), hoping to capturing the meaning of the according
words. Following previous work, we evaluate our model on two
paraphrase-oriented tasks, namely text simplification and short text
abstractive summarization. Experimental results show that our model outperforms
the sequence-to-sequence baseline by the BLEU score of 6.3 and 5.5 on two
English text simplification datasets, and the ROUGE-2 F1 score of 5.7 on a
Chinese summarization dataset. Moreover, our model achieves state-of-the-art
performances on these three benchmark datasets.Comment: arXiv admin note: text overlap with arXiv:1710.0231
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