Clay minerals in the Pliocene–Quaternary sediments of the southern Yangtze coast, China: Sediment sources and palaeoclimate implications

AbstractClay mineralogy was used as an indicator of the sediment source and prevailing climate and five suites (I–V) were identified throughout the borehole. Smectite was dominant in the bottom suite of the borehole, indicating the sediment was mainly derived from the local basalt when the study area stood as uplands during the Pliocene. The sharp reduction of smectite in suites II and III (Early Pleistocene) reflects a broader sediment provenance due to neo-tectonic subsidence of the study area. Significant climate fluctuations are indicated by distinct variations in the ratios of illite versus smectite and kaolinite, and by the illite crystallinity in suites II and IV. Especially the suite IV, which forms mottled muddy sediments that underwent pedogenesis, possibly represents glacial/interglacial cycles during the Mid-Pleistocene climate transition (MPT). The rare presence of smectite in suite V which formed during the Late Quaternary suggests a significant contribution of fine-grained sediment derived from the upstream of the Yangtze catchment. Such changes in sediment sources are consistent with the evolution of regional sedimentary environments, which evolved towards an open coast/deltaic setting and imply that the study area became the depositional basin of the Yangtze fine-grained sediment due to the final submergence of the Wu-Nan-Sha and Fukien-Reinan Massifs since the Late Quaternary

Development of SCAR Marker Related to Summer Stress Tolerance in Tall Fescue (Festuca arundinacea)

Summer stress tolerance (SST) is one of the most important breeding objectives in tall fescue (Festuca arundinacea), an important perennial cool-season grass. However, breeding for better SST is generally complicated by the many environmental factors involved during the growing season. Utilizing the bulked segregant analysis (BSA), we were able to identify one marker related to SST from 100 inter-simple sequence repeat (ISSR) markers and 800 random amplified polymorphic DNA (RAPD) markers, and successfully developed a dominant sequence characterized amplified region (SCAR) marker T_SC856 from the UBC856 sequence. Furthermore, the SCAR marker was tested in different clones of new populations, which were identified under complex summer stress (high temperature and humidity, Pythium blight, and brown patch), and it exhibited relatively high consistency (77%) with the phenotype. We believe that with more markers obtained in the future, better efficiency is likely to be achieved in breeding for improved SST in tall fescue and possibly other species as well. Further studies that analyze the factors relating to the SCAR marker are needed

Honest Score Client Selection Scheme: Preventing Federated Learning Label Flipping Attacks in Non-IID Scenarios

Federated Learning (FL) is a promising technology that enables multiple actors to build a joint model without sharing their raw data. The distributed nature makes FL vulnerable to various poisoning attacks, including model poisoning attacks and data poisoning attacks. Today, many byzantine-resilient FL methods have been introduced to mitigate the model poisoning attack, while the effectiveness when defending against data poisoning attacks still remains unclear. In this paper, we focus on the most representative data poisoning attack - "label flipping attack" and monitor its effectiveness when attacking the existing FL methods. The results show that the existing FL methods perform similarly in Independent and identically distributed (IID) settings but fail to maintain the model robustness in Non-IID settings. To mitigate the weaknesses of existing FL methods in Non-IID scenarios, we introduce the Honest Score Client Selection (HSCS) scheme and the corresponding HSCSFL framework. In the HSCSFL, The server collects a clean dataset for evaluation. Under each iteration, the server collects the gradients from clients and then perform HSCS to select aggregation candidates. The server first evaluates the performance of each class of the global model and generates the corresponding risk vector to indicate which class could be potentially attacked. Similarly, the server evaluates the client's model and records the performance of each class as the accuracy vector. The dot product of each client's accuracy vector and global risk vector is generated as the client's host score; only the top p\% host score clients are included in the following aggregation. Finally, server aggregates the gradients and uses the outcome to update the global model. The comprehensive experimental results show our HSCSFL effectively enhances the FL robustness and defends against the "label flipping attack.

Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion

Accurate 3D reconstruction of the hand and object shape from a hand-object image is important for understanding human-object interaction as well as human daily activities. Different from bare hand pose estimation, hand-object interaction poses a strong constraint on both the hand and its manipulated object, which suggests that hand configuration may be crucial contextual information for the object, and vice versa. However, current approaches address this task by training a two-branch network to reconstruct the hand and object separately with little communication between the two branches. In this work, we propose to consider hand and object jointly in feature space and explore the reciprocity of the two branches. We extensively investigate cross-branch feature fusion architectures with MLP or LSTM units. Among the investigated architectures, a variant with LSTM units that enhances object feature with hand feature shows the best performance gain. Moreover, we employ an auxiliary depth estimation module to augment the input RGB image with the estimated depth map, which further improves the reconstruction accuracy. Experiments conducted on public datasets demonstrate that our approach significantly outperforms existing approaches in terms of the reconstruction accuracy of objects.Comment: Accepted by IEEE Transactions on Image Processing (TIP