Scheduling algorithm for mission planning and logistics evaluation users' guide

The scheduling algorithm for mission planning and logistics evaluation (SAMPLE) program is a mission planning tool composed of three subsystems; the mission payloads subsystem (MPLS), which generates a list of feasible combinations from a payload model for a given calendar year; GREEDY, which is a heuristic model used to find the best traffic model; and the operations simulation and resources scheduling subsystem (OSARS), which determines traffic model feasibility for available resources. The SAMPLE provides the user with options to allow the execution of MPLS, GREEDY, GREEDY-OSARS, or MPLS-GREEDY-OSARS

The BcB_c Decays to PP-wave Charmonium by Improved Bethe-Salpeter Approach

We re-calculate the exclusive semileptonic and nonleptonic decays of $B_c$ meson to a $P$-wave charmonium in terms of the improved Bethe-Salpeter (B-S) approach, which is developed recently. Here the widths for the exclusive semileptonic and nonleptonic decays, the form factors, and the charged lepton spectrums for the semileptonic decays are precisely calculated. To test the concerned approach by comparing with experimental measurements when the experimental data are available, and to have comparisons with the other approaches the results obtained by the approach and those by some approaches else as well as the original B-S approach, which appeared in literature, are comparatively presented and discussed.Comment: 33 pages, 5 figures, 3 table

The NLO QCD Corrections to BcB_c Meson Production in Z0Z^0 Decays

The decay width of $Z^0$ to $B_c$ meson is evaluated at the next-to-leading order(NLO) accuracy in strong interaction. Numerical calculation shows that the NLO correction to this process is remarkable. The quantum chromodynamics(QCD)renormalization scale dependence of the results is obviously depressed, and hence the uncertainties lying in the leading order calculation are reduced.Comment: 14 pages, 7 figures; references added; expressions and typos ammende

Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting

For person re-identification, existing deep networks often focus on representation learning. However, without transfer learning, the learned model is fixed as is, which is not adaptable for handling various unseen scenarios. In this paper, beyond representation learning, we consider how to formulate person image matching directly in deep feature maps. We treat image matching as finding local correspondences in feature maps, and construct query-adaptive convolution kernels on the fly to achieve local matching. In this way, the matching process and results are interpretable, and this explicit matching is more generalizable than representation features to unseen scenarios, such as unknown misalignments, pose or viewpoint changes. To facilitate end-to-end training of this architecture, we further build a class memory module to cache feature maps of the most recent samples of each class, so as to compute image matching losses for metric learning. Through direct cross-dataset evaluation, the proposed Query-Adaptive Convolution (QAConv) method gains large improvements over popular learning methods (about 10%+ mAP), and achieves comparable results to many transfer learning methods. Besides, a model-free temporal cooccurrence based score weighting method called TLift is proposed, which improves the performance to a further extent, achieving state-of-the-art results in cross-dataset person re-identification. Code is available at https://github.com/ShengcaiLiao/QAConv.Comment: This is the ECCV 2020 version, including the appendi

Durability testing at one atmosphere of advanced catalysts and catalyst supports for automotive gas turbine engine combustors, part 1

The durability of catalysts and catalyst supports in a combustion environment was experimentally demonstrated. A test of 1000 hours duration was completed with two catalysts, using diesel fuel and operating at catalytically supported thermal combustion conditions. The performance of the catalysts was determined by monitoring emissions throughout the test, and by examining the physical condition of the catalyst core at the conclusion of the test. The test catalysts proved to be capable of low emissions operation after 1000 hours diesel aging, with no apparent physical degradation of the catalyst support