Fast and Accurate Neural Word Segmentation for Chinese

Neural models with minimal feature engineering have achieved competitive performance against traditional methods for the task of Chinese word segmentation. However, both training and working procedures of the current neural models are computationally inefficient. This paper presents a greedy neural word segmenter with balanced word and character embedding inputs to alleviate the existing drawbacks. Our segmenter is truly end-to-end, capable of performing segmentation much faster and even more accurate than state-of-the-art neural models on Chinese benchmark datasets.Comment: To appear in ACL201

Tectonic dynamics of the Zhongjiannan Basin in the western South China Sea since the late Miocene

The Zhongjiannan Basin is located west of the South China Sea (SCS) and was affected by the left-lateral strike-slip of the Red River Fault (RRF), the West Edge Fault of the South China Sea (WEFSCS) and the continental rifting of the South China Sea in the early Cenozoic. The Zhongjiannan Basin formed in a strike-pull basin with an S‒N distribution. During the middle Miocene, the sea spreading of the SCS stopped, but the dynamic mechanism of the Zhongjiannan Basin, which controlled the sedimentary and the structural evolution after the late Miocene, remains unclear. In this paper, through the segment interpretation of the latest seismic section in the Zhongjiannan Basin, we conduct a comparative study of the sedimentary structure in the southern and northern Zhongjiannan Basin since the late Miocene. Combined with the regional tectonic dynamics analysis, we propose that the sedimentary and structural evolution of the Zhongjiannan Basin since the late Miocene was mainly controlled by residual magmatic activity in the Southwest Subbasin (SWSB) after expansion stopped, and the compressional structure stress field weakened gradually from south to north. The compressional tectonic stress field from north to south was formed in the northern basin under the dextral strike-slip movement of the RRF. The sedimentary and structural environment was relatively stable in the middle basin. Therefore, the sedimentary-structure evolution of the Zhongjiannan Basin since the late Miocene was controlled by the two different structural stress fields. The above knowledge not only has guiding significance for oil and gas exploration in the Zhongjiannan Basin but also provides a reference for studying the initiation time of dextral strike-slip along the Red River Fault Zone, as well as the junction position between the RRF and the WEFSCS

Hyperbolic Face Anti-Spoofing

Learning generalized face anti-spoofing (FAS) models against presentation attacks is essential for the security of face recognition systems. Previous FAS methods usually encourage models to extract discriminative features, of which the distances within the same class (bonafide or attack) are pushed close while those between bonafide and attack are pulled away. However, these methods are designed based on Euclidean distance, which lacks generalization ability for unseen attack detection due to poor hierarchy embedding ability. According to the evidence that different spoofing attacks are intrinsically hierarchical, we propose to learn richer hierarchical and discriminative spoofing cues in hyperbolic space. Specifically, for unimodal FAS learning, the feature embeddings are projected into the Poincar\'e ball, and then the hyperbolic binary logistic regression layer is cascaded for classification. To further improve generalization, we conduct hyperbolic contrastive learning for the bonafide only while relaxing the constraints on diverse spoofing attacks. To alleviate the vanishing gradient problem in hyperbolic space, a new feature clipping method is proposed to enhance the training stability of hyperbolic models. Besides, we further design a multimodal FAS framework with Euclidean multimodal feature decomposition and hyperbolic multimodal feature fusion & classification. Extensive experiments on three benchmark datasets (i.e., WMCA, PADISI-Face, and SiW-M) with diverse attack types demonstrate that the proposed method can bring significant improvement compared to the Euclidean baselines on unseen attack detection. In addition, the proposed framework is also generalized well on four benchmark datasets (i.e., MSU-MFSD, IDIAP REPLAY-ATTACK, CASIA-FASD, and OULU-NPU) with a limited number of attack types

S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens

Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a face recognition system by presenting spoofed faces. State-of-the-art FAS techniques predominantly rely on deep learning models but their cross-domain generalization capabilities are often hindered by the domain shift problem, which arises due to different distributions between training and testing data. In this study, we develop a generalized FAS method under the Efficient Parameter Transfer Learning (EPTL) paradigm, where we adapt the pre-trained Vision Transformer models for the FAS task. During training, the adapter modules are inserted into the pre-trained ViT model, and the adapters are updated while other pre-trained parameters remain fixed. We find the limitations of previous vanilla adapters in that they are based on linear layers, which lack a spoofing-aware inductive bias and thus restrict the cross-domain generalization. To address this limitation and achieve cross-domain generalized FAS, we propose a novel Statistical Adapter (S-Adapter) that gathers local discriminative and statistical information from localized token histograms. To further improve the generalization of the statistical tokens, we propose a novel Token Style Regularization (TSR), which aims to reduce domain style variance by regularizing Gram matrices extracted from tokens across different domains. Our experimental results demonstrate that our proposed S-Adapter and TSR provide significant benefits in both zero-shot and few-shot cross-domain testing, outperforming state-of-the-art methods on several benchmark tests. We will release the source code upon acceptance

Radioactive ^(198)Au-Doped Nanostructures with Different Shapes for In Vivo Analyses of Their Biodistribution, Tumor Uptake, and Intratumoral Distribution

With Au nanocages as an example, we recently demonstrated that radioactive ^(198)Au could be incorporated into the crystal lattice of Au nanostructures for simple and reliable quantification of their in vivo biodistribution by measuring the γ radiation from ^(198)Au decay and for optical imaging by detecting the Cerenkov radiation. Here we extend the capability of this strategy to synthesize radioactive ^(198)Au nanostructures with a similar size but different shapes and then compare their biodistribution, tumor uptake, and intratumoral distribution using a murine EMT6 breast cancer model. Specifically, we investigated Au nanospheres, nanodisks, nanorods, and cubic nanocages. After PEGylation, an aqueous suspension of the radioactive Au nanostructures was injected into a tumor-bearing mouse intravenously, and their biodistribution was measured from the γ radiation while their tumor uptake was directly imaged using the Cerenkov radiation. Significantly higher tumor uptake was observed for the Au nanospheres and nanodisks relative to the Au nanorods and nanocages at 24 h postinjection. Furthermore, autoradiographic imaging was performed on thin slices of the tumor after excision to resolve the intratumoral distributions of the nanostructures. While both the Au nanospheres and nanodisks were only observed on the surfaces of the tumors, the Au nanorods and nanocages were distributed throughout the tumors

Experimental study on dynamic characteristics of saturated remolded soft clay with sand particles

Long-term cyclic tests for different frequencies were carried out on remolded soft clay with different sand contents, investigating how the frequency impacted the stress–strain, the dynamic shear modulus, and the damping ratio of the remolded samples. Accordingly, when the sand content of the remolded specimen was 1.7%, the slope of the hysteresis curve of the remolded specimen tended to increase gradually with the increasing frequency, the hysteresis circle was slender, and the area of the hysteresis circle tended to decrease gradually; when the sand content of the remolded specimen was 20%, the cumulative deformation of the specimen presented a gradual increase with the loading frequency, and the slope of the hysteresis curve decreased gradually. The hysteresis curve shows a gradually decreasing slope, and the enclosed hysteresis circle area also tends to decrease. In addition, the higher the loading frequency, the stronger the deformation-resistant ability held by the specimen, particularly because the pore water pressure between soils’ internal particles is not discharged in time, which makes the contact between the internal particles of the soil close, and the closer the structure of the soil, the smaller the compressive deformation of the soil, and the more stable the soil