Uncertainty Quantification of Multi-Component Isotope-Separation Cascade Model

Monte Carlo uncertainty quantification (UQ) capability has been added to a code for modeling multi-component steady-state isotope-separation enrichment cascades to characterize the propagation of uncertainties in input data that define the cascade and the feed. Random samples of error for every computational input are drawn from its individual uncertainty distribution and added to the inputs, creating a set of enrichment cascade problems with perturbed inputs. The set of problems is solved using the verified code. The cascade outputs are then characterized using the empirical cumulative distribution. The uncertainty output data are analyzed to gain new insights into the behaviors of enrichment cascades. The UQ capability is an investigative tool that can be used to explore current and new questions of interest regarding enrichment

Inductive and Transductive Few-Shot Video Classification via Appearance and Temporal Alignments

We present a novel method for few-shot video classification, which performs appearance and temporal alignments. In particular, given a pair of query and support videos, we conduct appearance alignment via frame-level feature matching to achieve the appearance similarity score between the videos, while utilizing temporal order-preserving priors for obtaining the temporal similarity score between the videos. Moreover, we introduce a few-shot video classification framework that leverages the above appearance and temporal similarity scores across multiple steps, namely prototype-based training and testing as well as inductive and transductive prototype refinement. To the best of our knowledge, our work is the first to explore transductive few-shot video classification. Extensive experiments on both Kinetics and Something-Something V2 datasets show that both appearance and temporal alignments are crucial for datasets with temporal order sensitivity such as Something-Something V2. Our approach achieves similar or better results than previous methods on both datasets. Our code is available at https://github.com/VinAIResearch/fsvc-ata.Comment: Accepted to ECCV 202

Single Z' production at CLIC based on e^- gamma collisions

We analyze the potential of CLIC based on e- gamma collisions to search for new $Z'$ gauge boson. Single Z' production at e-gamma colliders in two SU(3)_C X SU(3)_L X U(1)_N models: the minimal model and the model with right-handed (RH) neutrinos is studied in detail. Results show that new Z' gauge bosons can be observed at the CLIC, and the cross sections in the model with RH neutrinos are bigger than those in the minimal one.Comment: 11 pages, 4 figures, To appear in JET

(g-2)_{e, mu} and decays e_b--> e_a\gamma in a SU(4)_L x U(1)_X model with inverse seesaw neutrinos

We will show that the 3-4-1 model with heavy right-handed neutrinos can explain the recent experimental data of (g-2)_{e, mu} anomalies of charged leptons and neutrino oscillations through the inverse seesaw mechanism. In addition, the model can predict large lepton flavor violating decay rates mu --> e gamma and tau --> mu gamma, e gamma up to the recent experimental sensitivitiesComment: 28 pages, 8 figure

BIOLOGICAL AMMONIA REMOVAL BY SUBMERGED AERATED FILTER FROM HANOI GROUND WATER

Joint Research on Environmental Science and Technology for the Eart