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Abstract Based on new and published cosmic-ray exposure chronologies, we show that glacier extent in the tropical Andes and the north Atlantic regions (TANAR) varied in-phase on millennial timescales during the Holocene, distinct from other regions. Glaciers experienced an early Holocene maximum extent, followed by a strong mid-Holocene retreat and a re-advance in the late Holocene. We further explore the potential forcing of TANAR glacier variations using transient climate simulations. Since the Atlantic Meridional Overturning Circulation (AMOC) evolution is poorly represented in these transient simulations, we develop a semi-empirical model to estimate the “AMOC-corrected” temperature and precipitation footprint at regional scales. We show that variations in the AMOC strength during the Holocene are consistent with the observed glacier changes. Our findings highlight the need to better constrain past AMOC behavior, as it may be an important driver of TANAR glacier variations during the Holocene, superimposed on other forcing mechanisms. 

The state-of-the-art of fully-supervised methods for temporal action localization from untrimmed videos has achieved impressive results. Yet, it remains unsatisfactory for the weakly-supervised temporal action localization, where only video-level action labels are given without the timestamp annotation on when the actions occur. The main reason comes from that, the weakly-supervised networks only focus on the highly discriminative frames, but there are some ambiguous frames in both background and action classes. The ambiguous frames in background class are very similar to the real actions, which may be treated as target actions and result in false positives. On the other hand, the ambiguous frames in action class which possibly contain action instances, are prone to be false negatives by the weakly-supervised networks and result in a coarse localization. To solve these problems, we introduce a novel weakly-supervised Action Completeness Modeling with Back- ground Aware Networks (ACM-BANets). Our Background Aware Network (BANet) contains a weight-sharing two-branch architecture, with an action guided Background aware Temporal Attention Module (B-TAM) and an asymmetrical training strategy, to suppress both highly discriminative and ambiguous background frames to remove the false positives. Our action completeness modeling contains multiple BANets, and the BANets are forced to discover different but complementary action instances to completely localize the action instances in both highly discriminative and ambiguous action frames. In the 𝑖-th iteration, the 𝑖-th BANet discovers the discriminative features, which are then erased from the feature map. The partially-erased feature map is fed into the (i+1)-th BANet of the next iteration to force this BANet to discover discriminative features different from the 𝑖-th BANet. Evaluated on two challenging untrimmed video datasets, THUMOS14 and ActivityNet1.3, our approach outperforms all the current weakly-supervised methods for temporal action localization. 

The superτ-charm facility (STCF) is an electron–positron collider proposed by the Chinese particle physics community. It is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of 0.5 × 10³⁵cm⁻²·s⁻¹or higher. The STCF will produce a data sample about a factor of 100 larger than that of the presentτ-charm factory — the BEPCII, providing a unique platform for exploring the asymmetry of matter-antimatter (charge-parity violation), in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions, as well as searching for exotic hadrons and physics beyond the Standard Model. The STCF project in China is under development with an extensive R&D program. This document presents the physics opportunities at the STCF, describes conceptual designs of the STCF detector system, and discusses future plans for detector R&D and physics case studies.