Mantle-derived gaseous components in ore-forming fluids of the Xiangshan uranium

The Xiangshan U deposit, the largest hydrothermal U deposit in China, is hosted in late Jurassic felsic volcanic rocks although the U mineralization post dates the volcanics by at least 20 Ma. The mineralization coincides with intrusion of local mantle-derived mafic dykes formed during Cretaceous crustal extension in South China. Ore-forming fluids are rich in CO2, and U in the fluid is thought to have been dissolved in the form of UO2 (CO3)22− and UO2 (CO3) 34− complexes. This paper provides He and Ar isotope data of fluid inclusions in pyrites and C isotope data of calcites associated with U mineralization (pitchblende) in the Xiangshan U deposit. He isotopic compositions range between 0.1 and 2.0Ra (where Ra is the 3He/4He ratio of air=1.39×10−6) and correlates with 40Ar/36Ar; although there is potential for significant 3He production via 6Li(n,α)3H(β)3He reactions in a U deposit (due to abundant neutrons), nucleogenic production cannot account for either the 3He concentration in these fluids, nor the correlations between He and Ar isotopic compositions. It is more likely that the high 3He/4He ratios represent trapped mantle-derived gases. A mantle origin for the volatiles of Xiangshan is consistent with the δ13C values of calcites, which vary from −3.5‰ to −7.7‰, overlapping the range of mantle CO2. The He, Ar and CO2 characteristics of the ore-forming fluids responsible for the deposit are consistent with mixing between 3He- and CO2-rich mantle-derived fluids and CO2-poor meteoric fluids. These fluids were likely produced during Cretaceous extension and dyke intrusion which permitted mantle-derived CO2 to migrate upward and remobilize U from the acid volcanic source rocks, resulting in the formation of the U deposit. Subsequent decay of U within the fluid inclusions has reduced the 3He/4He ratio, and variations in U/3He result in the range in 3He/4He observed with U/3He ratios in the range 5–17×103 likely corresponding to U concentrations in the fluids b0.2 ppm.

Parameter Sensitive Detectors

Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and then train separate classifiers for each portion. However, with continuous spaces the partitions tend to be arbitrary since there are no natural boundaries (for example, consider the continuous range of human body poses). In this paper, a new formulation is proposed, where the detectors themselves are associated with continuous parameters, and reside in a parameterized function space. There are two advantages of this strategy. First, a-priori partitioning of the parameter space is not needed; the detectors themselves are in a parameterized space. Second, the underlying parameters for object variations can be learned from training data in an unsupervised manner. In profile face detection experiments, at a fixed false alarm number of 90, our method attains a detection rate of 75% vs. 70% for the method of Viola-Jones. In hand shape detection, at a false positive rate of 0.1%, our method achieves a detection rate of 99.5% vs. 98% for partition based methods. In pedestrian detection, our method reduces the miss detection rate by a factor of three at a false positive rate of 1%, compared with the method of Dalal-Triggs.

Learning a Family of Detectors

Object detection and recognition are important problems in computer vision. The challenges of these problems come from the presence of noise, background clutter, large within class variations of the object class and limited training data. In addition, the computational complexity in the recognition process is also a concern in practice. In this thesis, we propose one approach to handle the problem of detecting an object class that exhibits large within-class variations, and a second approach to speed up the classification processes. In the first approach, we show that foreground-background classification (detection) and within-class classification of the foreground class (pose estimation) can be jointly solved with using a multiplicative form of two kernel functions. One kernel measures similarity for foreground-background classification. The other kernel accounts for latent factors that control within-class variation and implicitly enables feature sharing among foreground training samples. For applications where explicit parameterization of the within-class states is unavailable, a nonparametric formulation of the kernel can be constructed with a proper foreground distance/similarity measure. Detector training is accomplished via standard Support Vector Machine learning. The resulting detectors are tuned to specific variations in the foreground class. They also serve to evaluate hypotheses of the foreground state. When the image masks for foreground objects are provided in training, the detectors can also produce object segmentation. Methods for generating a representative sample set of detectors are proposed that can enable efficient detection and tracking. In addition, because individual detectors verify hypotheses of foreground state, they can also be incorporated in a tracking-by-detection frame work to recover foreground state in image sequences. To run the detectors efficiently at the online stage, an input-sensitive speedup strategy is proposed to select the most relevant detectors quickly. The proposed approach is tested on data sets of human hands, vehicles and human faces. On all data sets, the proposed approach achieves improved detection accuracy over the best competing approaches. In the second part of the thesis, we formulate a filter-and-refine scheme to speed up recognition processes. The binary outputs of the weak classifiers in a boosted detector are used to identify a small number of candidate foreground state hypotheses quickly via Hamming distance or weighted Hamming distance. The approach is evaluated in three applications: face recognition on the face recognition grand challenge version 2 data set, hand shape detection and parameter estimation on a hand data set, and vehicle detection and estimation of the view angle on a multi-pose vehicle data set. On all data sets, our approach is at least five times faster than simply evaluating all foreground state hypotheses with virtually no loss in classification accuracy.

Development of a GEM Electronic Board (GEB) for triple-GEM detectors

Developed for use with triple GEM detectors, the GEM Electronic Board (GEB) forms a crucial part of the electronics readout system being developed as part of the CMS muon upgrade program. The objective of the GEB is threefold; to provide stable powering and ground for the VFAT3 front ends, to enable high-speed communication between 24 VFAT3 front ends and an optohybrid, and to shield the GEM detector from electromagnetic interference. The paper describes the concept and design of a large-size GEB in detail, highlighting the challenges in terms of design and feasibility of this deceptively difficult system component.

Forward and inverse transport of particulate matter and gaseous pollutants affecting the region bordering the English Channel

The ATTMA "Aerosol Transport in the Trans-Manche Atmosphere" project investigates the transportation and dispersion of air pollutants across the English Channel, in collaboration with local authorities and other Universities in Southern England and Northern France. The research is concerned with both forward and inverse (receptor based) tracking. Two alternative dispersion simulation methods are used: (a) Lagrangian Particle Dispersion (LPD) models, (b) Eulerian Finite Volume type models. This paper is concerned with part (a), the simulations based on LPD models. Two widely applied LPD models are used and compared. Since in many observed episodes the source of pollution is traced outside the region of interest, long range, trans-continental transport is also investigated.

The direction aftereffect is driven by adaptation of local motion detectors

The processing of motion information by the visual system can be decomposed into two general stages; point-by-point local motion extraction, followed by global motion extraction through the pooling of the local motion signals. The direction aftereVect (DAE) is a well known phenomenon in which prior adaptation to a unidirectional moving pattern results in an exaggerated perceived direction diVerence between the adapted direction and a subsequently viewed stimulus moving in a diVerent direction. The experiments in this paper sought to identify where the adaptation underlying the DAE occurs within the motion processing hierarchy. We found that the DAE exhibits interocular transfer, thus demonstrating that the underlying adapted neural mechanisms are binocularly driven and must, therefore, reside in the visual cortex. The remaining experiments measured the speed tuning of the DAE, and used the derived function to test a number of local and global models of the phenomenon. Our data provide compelling evidence that the DAE is driven by the adaptation of motion-sensitive neurons at the local-processing stage of motion encoding. This is in contrast to earlier research showing that direction repulsion, which can be viewed as a simultaneous presentation counterpart to the DAE, is a global motion process. This leads us to conclude that the DAE and direction repulsion reflect interactions between motion-sensitive neural mechanisms at different levels of the motion-processing hierarchy.

Emission lines of [Cl II] in the optical spectra of gaseous nebulae

Recent R-matrix calculations of electron impact excitation rates among the 3s(2)3p(4) levels of Cl II are used to derive the nebular emission-line intensity ratios R-1=I(6161.8 Angstrom)/I(8578.7 Angstrom) and R-2=I(6161.8 Angstrom)/I(9123.6 Angstrom) as a function of electron temperature (T-e) and density (N-e). The ratios are found to be very sensitive to changes in T-e but not N-e for densities lower than 10(5) cm(-3). Hence, they should, in principle, provide excellent optical T-e diagnostics for planetary nebulae. The observed values of R-1 and R-2 for the planetary nebulae NGC 6741 and IC 5117, measured from spectra obtained with the Hamilton echelle spectrograph on the 3 m Shane Telescope, imply temperatures in excellent agreement with those derived from other diagnostic lines formed in the same region of the nebula as [Cl II]. This provides some observational support for the accuracy of the [Cl II] line ratio calculations and hence the atomic data on which they are based. The [Cl II] 8578.7 and 9123.6 Angstrom lines are identified for the first time (to our knowledge) in a high-resolution spectrum of the symbiotic star RR Telescopii, obtained with the University College London Echelle Spectrograph on the 3.9 m Anglo- Australian Telescope. However, the 6161.8 Angstrom feature is unfortunately too weak to be identified in the RR Telescopii observations, consistent with its predicted line strength.

Emission-line ratios for [N II] in gaseous nebulae and a comparison between theory and observation

R-matrix calculations of electron impact excitation rates among the 2s(2)2p(2) P-3, D-1, S-1, and 2s2p(3) S-5 levels of N II are presented. These results are used in conjunction with other recent calculations of electron impact excitation rates and Einstein A-coefficients for N II to derive the emission-line ratio: ratio diagrams and where (R-1, R-2) (R-1, R-3), where R-1 = I(5756.2 Angstrom)/I(6549.9 + 6585.2 Angstrom), R-2 = I(2143.5 Angstrom)/I(6549.9 + 6585.2 Angstrom), and R-3 = I(2139.7 Angstrom)/I(6549.9 + 658.2 Angstrom), for a range of electron temperatures (T-e = 5000-20,000 K) and electron densities (N-e = 10(2)-10(7) cm(-3)) appropriate to gaseous nebulae. These diagrams should, in principle, allow the simultaneous determination of T-e and N-e from measurements of the [N II] lines in a spectrum. Plasma parameters deduced for a sample of gaseous nebulae, using observational data obtained from ground-based telescopes plus the International Ultraviolet Explorer and Hubble Space Telescope satellites, are found to show generally excellent internal consistency and to be in good agreement with the values of T-e and N-e estimated from other line ratios. These results provide observational support for the accuracy of the theoretical ratios and hence the atomic data adopted in their derivation. Theoretical ratios are also presented for the infrared line pair R-4 = I(122 mum)/I(205 mum), and the usefulness of R-4 as an electron density diagnostic is briefly discussed.