| 1. |
- Abelev, Betty, et al.
(författare)
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Long-range angular correlations on the near and away side in p-Pb collisions at root S-NN=5.02 TeV
- 2013
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Ingår i: Physics Letters. Section B: Nuclear, Elementary Particle and High-Energy Physics. - : Elsevier BV. - 0370-2693. ; 719:1-3, s. 29-41
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Tidskriftsartikel (refereegranskat)abstract
- Angular correlations between charged trigger and associated particles are measured by the ALICE detector in p-Pb collisions at a nucleon-nucleon centre-of-mass energy of 5.02 TeV for transverse momentum ranges within 0.5 < P-T,P-assoc < P-T,P-trig < 4 GeV/c. The correlations are measured over two units of pseudorapidity and full azimuthal angle in different intervals of event multiplicity, and expressed as associated yield per trigger particle. Two long-range ridge-like structures, one on the near side and one on the away side, are observed when the per-trigger yield obtained in low-multiplicity events is subtracted from the one in high-multiplicity events. The excess on the near-side is qualitatively similar to that recently reported by the CMS Collaboration, while the excess on the away-side is reported for the first time. The two-ridge structure projected onto azimuthal angle is quantified with the second and third Fourier coefficients as well as by near-side and away-side yields and widths. The yields on the near side and on the away side are equal within the uncertainties for all studied event multiplicity and p(T) bins, and the widths show no significant evolution with event multiplicity or p(T). These findings suggest that the near-side ridge is accompanied by an essentially identical away-side ridge. (c) 2013 CERN. Published by Elsevier B.V. All rights reserved.
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| 2. |
- Abelev, Betty, et al.
(författare)
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Measurement of prompt J/psi and beauty hadron production cross sections at mid-rapidity in pp collisions at root s=7 TeV
- 2012
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Ingår i: Journal of High Energy Physics. - 1029-8479. ; :11
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Tidskriftsartikel (refereegranskat)abstract
- The ALICE experiment at the LHC has studied J/psi production at mid-rapidity in pp collisions at root s = 7 TeV through its electron pair decay on a data sample corresponding to an integrated luminosity L-int = 5.6 nb(-1). The fraction of J/psi from the decay of long-lived beauty hadrons was determined for J/psi candidates with transverse momentum p(t) > 1,3 GeV/c and rapidity vertical bar y vertical bar < 0.9. The cross section for prompt J/psi mesons, i.e. directly produced J/psi and prompt decays of heavier charmonium states such as the psi(2S) and chi(c) resonances, is sigma(prompt J/psi) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 8.3 +/- 0.8(stat.) +/- 1.1 (syst.)(-1.4)(+1.5) (syst. pol.) mu b. The cross section for the production of b-hadrons decaying to J/psi with p(t) > 1.3 GeV/c and vertical bar y vertical bar < 0.9 is a sigma(J/psi <- hB) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 1.46 +/- 0.38 (stat.)(-0.32)(+0.26) (syst.) mu b. The results are compared to QCD model predictions. The shape of the p(t) and y distributions of b-quarks predicted by perturbative QCD model calculations are used to extrapolate the measured cross section to derive the b (b) over bar pair total cross section and d sigma/dy at mid-rapidity.
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| 3. |
- Ma, Zhaoying, et al.
(författare)
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Mineralogical and magnetic variations of periglacial loess in SE Tibet reveal mid-Pleistocene expansion of Tibetan glacial activity
- 2024
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Ingår i: Quaternary Science Reviews. - : Elsevier. - 0277-3791 .- 1873-457X. ; 330
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Tidskriftsartikel (refereegranskat)abstract
- The formation and evolution of the cryosphere on the Tibetan Plateau is of great significance in understanding the Earth's carbon and climatic system. Periglacial loess deposits in southeastern Tibet offer a means to constrain this history as they contain critical information on glacial grinding and frost shattering processes in high-altitude mountain regions through time, which yield lithogenic fractions of largely loess silts and sands. Based on combined analyses of lithogenic magnetic properties and mineralogical composition, here we find that increasing high mountain production and supply of fresh detrital components since the mid-Pleistocene climate transition (MPT, 1.2–0.7 Ma) led to a substantial increase of the lithogenic susceptibility and decrease in chemical weathering intensity of periglacial loess in southeastern Tibet. The agreement of these findings with similar results from eolian loess on the northern margins of the Tibetan Plateau suggests a plateau-wide glacier expansion during the MPT. Enhanced glacial erosion and freeze-thaw activities occurred in the high-altitude mountain regions of the plateau during the MPT, thereby providing vast amounts of fresh detritus for the formation of loess deposits. High and constant values of lithogenic magnetic parameters in the loess deposits after 0.7–0.6 Ma further indicate that the Middle Pleistocene is a critical period for the establishment of modern-like glacial and periglacial landforms on the Tibetan Plateau. Our results further suggest that enhanced Quaternary glaciation in SE Tibet occurred earlier than in the north, which we attribute to climate cooling combined with regional seasonal snowline lowering. As such, a close relationship exists between global climate changes, development of pan-Tibetan glaciations, and large-scale dust emission.
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| 4. |
- Zhang, Tao, et al.
(författare)
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JL-GFDN : A Novel Gabor Filter-Based Deep Network Using Joint Spectral-Spatial Local Binary Pattern for Hyperspectral Image Classification
- 2020
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Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 12:12
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Tidskriftsartikel (refereegranskat)abstract
- The traditional local binary pattern (LBP, hereinafter we also call it a two-dimensional local binary pattern 2D-LBP) is unable to depict the spectral characteristics of a hyperspectral image (HSI). To cure this deficiency, this paper develops a joint spectral-spatial 2D-LBP feature (J2D-LBP) by averaging three different 2D-LBP features in a three-dimensional hyperspectral data cube. Subsequently, J2D-LBP is added into the Gabor filter-based deep network (GFDN), and then a novel classification method JL-GFDN is proposed. Different from the original GFDN framework, JL-GFDN further fuses the spectral and spatial features together for HSI classification. Three real data sets are adopted to evaluate the effectiveness of JL-GFDN, and the experimental results verify that (i) JL-GFDN has a better classification accuracy than the original GFDN; (ii) J2D-LBP is more effective in HSI classification in comparison with the traditional 2D-LBP.
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| 5. |
- Abelev, Betty, et al.
(författare)
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Underlying Event measurements in pp collisions at root s=0.9 and 7 TeV with the ALICE experiment at the LHC
- 2012
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Ingår i: Journal of High Energy Physics. - 1029-8479. ; :7
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Tidskriftsartikel (refereegranskat)abstract
- We present measurements of Underlying Event observables in pp collisions at root s = 0 : 9 and 7 TeV. The analysis is performed as a function of the highest charged-particle transverse momentum p(T),L-T in the event. Different regions are defined with respect to the azimuthal direction of the leading (highest transverse momentum) track: Toward, Transverse and Away. The Toward and Away regions collect the fragmentation products of the hardest partonic interaction. The Transverse region is expected to be most sensitive to the Underlying Event activity. The study is performed with charged particles above three different p(T) thresholds: 0.15, 0.5 and 1.0 GeV/c. In the Transverse region we observe an increase in the multiplicity of a factor 2-3 between the lower and higher collision energies, depending on the track p(T) threshold considered. Data are compared to PYTHIA 6.4, PYTHIA 8.1 and PHOJET. On average, all models considered underestimate the multiplicity and summed p(T) in the Transverse region by about 10-30%.
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| 6. |
- Zhang, Weilin, et al.
(författare)
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Federated Machine Learning for Resource Allocation in Multi-domain Fog Ecosystems
- 2023
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Ingår i: 2023 IEEE 12th International Conference on Cloud Networking, CLOUDNET. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350313062 - 9798350313079 ; , s. 290-298
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Konferensbidrag (refereegranskat)abstract
- The proliferation of the Internet of Things (IoT) has incentivised extending cloud resources to the edge in what is deemed fog computing. The latter is manifesting as an ecosystem of connected clouds, geo-dispersed and of diverse capacities. In such ecosystem, workload allocation to fog services becomes a non-trivial challenge. Users' demand at the edge is diverse, which does not lend to straightforward resource planning. Conversely, running services at the edge may leverage proximity, but it comes at higher operational cost let alone increasing risk of resource straining. Consequently, there is a need for intelligent yet scalable allocation solutions that counter the adversity of demand, while efficiently distributing load between the edge and farther clouds. Machine learning is increasingly adopted in resource planning. This paper proposes a federated deep reinforcement learning system, based on deep Q-learning network (DQN), for workload distribution in a fog ecosystem. The proposed solution adapts a DQN to optimize local workload allocations, made by single gateways. Federated learning is incorporated to allow multiple gateways in a network to collaboratively build knowledge of users' demand. This is leveraged to establish consensus on the fraction of workload allocated to different fog nodes, using lower data supply and computation resources. System performance is evaluated using realistic demand from Google Cluster Workload Traces 2019. Evaluation results show over 50% reduction in failed allocations when spreading users over larger number of gateways, given fixed number of fog nodes. The results further illustrate the trade-offs between performance and cost under different conditions.
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