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- Abgrall, N., et al.
(författare)
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The large enriched germanium experiment for neutrinoless double beta decay (LEGEND)
- 2017
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Ingår i: AIP Conference Proceedings. - : Author(s). - 1551-7616 .- 0094-243X. ; 1894
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Konferensbidrag (refereegranskat)abstract
- The observation of neutrinoless double-beta decay (0νββ) would show that lepton number is violated, reveal that neu-trinos are Majorana particles, and provide information on neutrino mass. A discovery-capable experiment covering the inverted ordering region, with effective Majorana neutrino masses of 15 - 50 meV, will require a tonne-scale experiment with excellent energy resolution and extremely low backgrounds, at the level of ∼0.1 count /(FWHM·t·yr) in the region of the signal. The current generation 76Ge experiments GERDA and the Majorana Demonstrator, utilizing high purity Germanium detectors with an intrinsic energy resolution of 0.12%, have achieved the lowest backgrounds by over an order of magnitude in the 0νββ signal region of all 0νββ experiments. Building on this success, the LEGEND collaboration has been formed to pursue a tonne-scale 76Ge experiment. The collaboration aims to develop a phased 0νββ experimental program with discovery potential at a half-life approaching or at 1028 years, using existing resources as appropriate to expedite physics results.
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| 4. |
- Haj-Hosseini, Neda, 1980-, et al.
(författare)
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Photobleaching behavior of protoporphyrin IX during 5-aminolevulinic acid marked glioblastoma detection
- 2009
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Ingår i: PHOTONIC THERAPEUTICS AND DIAGNOSTICS V. - : SPIE. - 0277-786X .- 1996-756X. - 9780819474070 ; 7161
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Konferensbidrag (refereegranskat)abstract
- The highly malignant brain tumor, glioblastoma multiforme (GBM), is difficult to fully delineate during surgical resection due to its infiltrative ingrowth and morphological similarities to surrounding functioning brain tissue. Selectiveness of GBM to 5-aminolevulinic acid (5-ALA) induced protoporphyrin IX (PpIX) is reported by other researchers to visualize tumor margins under blue light microscopy. To allow objective detection of GBM, a compact and portable fiber optic based fluorescence spectroscopy system is developed. This system is able to deliver excitation laser light (405 nm) in both the continuous and pulsed mode. PpIX fluorescence peaks are detected at 635 and 704 nm, using a fiber-coupled spectrometer. It is necessary to optimize the detection efficiency of the system as the PpIX quickly photobleaches during the laser illumination. A light dose of 2.5 mJ (fluence rate = 9 mJ/mm(2)) is experimentally approved to excite an acceptable level of fluourescence signal arising from glioblastoma. In pulsed illumination mode, an excitation dose of 2.5 mJ, with a dark interval of 0.5 s (duty cycle 50\%) shows a significantly shorter photobleaching time in comparison to the continuous illumination mode with the same laser power (p < 0.05). To avoid photobleaching (the remaining signal is more than 90\% of its initial value) when measuring with 2.5 mJ delivered energy, the time for continuous and pulsed illumination should be restricted to 2.5 and 1.1 s, respectively.
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| 7. |
- Zeng, Jingna, et al.
(författare)
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Giving Future(s) to Transactional Memory
- 2020
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Ingår i: Annual ACM Symposium on Parallelism in Algorithms and Architectures. - New York, NY, USA : Association for Computing Machinery. ; , s. 587-589
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Konferensbidrag (refereegranskat)abstract
- This paper extends the Transactional Memory (TM) paradigm by proposing a new powerful abstraction, the transactional future. Transactional futures, as the name suggests, combine TM with futures, by allowing programmers to exploit intra-transaction parallelism via the abstraction of futures, while delegating to TM the complexity of regulating concurrent access to shared data. The main contribution of this paper is the definition of a set of semantics for transactional futures that explore different trade-offs between simplicity and efficiency.
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| 8. |
- Zeng, Jingna, et al.
(författare)
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Online tuning of parallelism degree in parallel nesting transactional memory
- 2018
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Ingår i: Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538643686 ; , s. 474-483
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Konferensbidrag (refereegranskat)abstract
- This paper addresses the problem of self-Tuning the parallelism degree in Transactional Memory (TM) systems that support parallel nesting (PN-TM). This problem has been long investigated for TMs not supporting nesting, but, to the best of our knowledge, has never been studied in the context of PN-TMs. Indeed, the problem complexity is inherently exacerbated in PN-TMs, since these require to identify the optimal parallelism degree not only for top-level transactions but also for nested sub-Transactions. The increase of the problem dimensionality raises new challenges (e.g., increase of the search space, and proneness to suffer from local maxima), which are unsatisfactorily addressed by self-Tuning solutions conceived for flat nesting TMs. We tackle these challenges by proposing AUTOPN, an on-line self-Tuning system that combines model-driven learning techniques with localized search heuristics in order to pursue a twofold goal: i) enhance convergence speed by identifying the most promising region of the search space via model-driven techniques, while ii) increasing robustness against modeling errors, via a final local search phase aimed at refining the model's prediction. We further address the problem of tuning the duration of the monitoring windows used to collect feedback on the system's performance, by introducing novel, domain-specific, mechanisms aimed to strike an optimal trade-off between latency and accuracy of the self-Tuning process. We integrated AUTOPN with a state of the art PN-TM (JVSTM) and evaluated it via an extensive experimental study. The results of this study highlight that AUTOPN can achieve gains of up to 45× in terms of increased accuracy and 4× faster convergence speed, when compared with several on-line optimization techniques (gradient descent, simulated annealing and genetic algorithm), some of which were already successfully used in the context of flat nesting TMs.
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| 9. |
- Zeng, Jingna, et al.
(författare)
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The Future(s) of Transactional Memory
- 2016
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Ingår i: Proceedings of the International Conference on Parallel Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509028238 ; , s. 442-451
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Konferensbidrag (refereegranskat)abstract
- This work investigates how to combine two powerful abstractions to manage concurrent programming: Transactional Memory (TM) and futures. The former hides from programmers the complexity of synchronizing concurrent access to shared data, via the familiar abstraction of atomic transactions. The latter serves to schedule and synchronize the parallel execution of computations whose results are not immediately required. While TM and futures are two widely investigated topics, the problem of how to exploit these two abstractions in synergy is still largely unexplored in the literature. This paper fills this gap by introducing Java Transactional Futures (JTF), a Java-based TM implementation that allows programmers to use futures to coordinate the execution of parallel tasks, while leveraging transactions to synchronize accesses to shared data. JTF provides a simple and intuitive semantic regarding the admissible serialization orders of the futures spawned by transactions, by ensuring that the results produced by a future are always consistent with those that one would obtain by executing the future sequentially. Our experimental results show that the use of futures in a TM allows not only to unlock parallelism within transactions, but also to reduce the cost of conflicts among top-level transactions in high contention workloads.
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