D3G: Exploring Gaussian Prior for Temporal Sentence Grounding with Glance Annotation

Temporal sentence grounding (TSG) aims to locate a specific moment from an untrimmed video with a given natural language query. Recently, weakly supervised methods still have a large performance gap compared to fully supervised ones, while the latter requires laborious timestamp annotations. In this study, we aim to reduce the annotation cost yet keep competitive performance for TSG task compared to fully supervised ones. To achieve this goal, we investigate a recently proposed glance-supervised temporal sentence grounding task, which requires only single frame annotation (referred to as glance annotation) for each query. Under this setup, we propose a Dynamic Gaussian prior based Grounding framework with Glance annotation (D3G), which consists of a Semantic Alignment Group Contrastive Learning module (SA-GCL) and a Dynamic Gaussian prior Adjustment module (DGA). Specifically, SA-GCL samples reliable positive moments from a 2D temporal map via jointly leveraging Gaussian prior and semantic consistency, which contributes to aligning the positive sentence-moment pairs in the joint embedding space. Moreover, to alleviate the annotation bias resulting from glance annotation and model complex queries consisting of multiple events, we propose the DGA module, which adjusts the distribution dynamically to approximate the ground truth of target moments. Extensive experiments on three challenging benchmarks verify the effectiveness of the proposed D3G. It outperforms the state-of-the-art weakly supervised methods by a large margin and narrows the performance gap compared to fully supervised methods. Code is available at https://github.com/solicucu/D3G.Comment: ICCV202

Impacts of Land Use and Salinization on Soil Inorganic and Organic Carbon in the Middle-lower Yellow River Delta

ACKNOWLEDGEMENTS This study was financially supported by the National Natural Science Foundation of China (Nos. 41877028 and 41205104). This work also contributes to the activities of N-Circle projects, a UK-China Virtual Joint Centre on Nitrogen, funded by the Newton Fund via Biotechnology and Biological Sciences Research Council (BBSRC) (No. BB/N013484/1Peer reviewedPostprin

Automated Mapping of Ms 7.0 Jiuzhaigou Earthquake (China) Post-Disaster Landslides Based on High-Resolution UAV Imagery

The Ms 7.0 Jiuzhaigou earthquake that occurred on 8 August 2017 triggered hundreds of landslides in the Jiuzhaigou valley scenic and historic-interest area in Sichuan, China, causing heavy casualties and serious property losses. Quick and accurate mapping of post-disaster landslide distribution is of paramount importance for earthquake emergency rescue and the analysis of post-seismic landslides distribution characteristics. The automatic identification of landslides is mostly based on medium- and low-resolution satellite-borne optical remote-sensing imageries, and the high-accuracy interpretation of earthquake-triggered landslides still relies on time-consuming manual interpretation. This paper describes a methodology based on the use of 1 m high-resolution unmanned aerial vehicle (UAV) imagery acquired after the earthquake, and proposes a support vector machine (SVM) classification method combining the roads and villages mask from pre-seismic remote sensing imagery to accurately and automatically map the landslide inventory. Compared with the results of manual visual interpretation, the automatic recognition accuracy could reach 99.89%, and the Kappa coefficient was higher than 0.9, suggesting that the proposed method and 1 m high-resolution UAV imagery greatly improved the mapping accuracy of the landslide area. We also analyzed the spatial-distribution characteristics of earthquake-triggered landslides with the influenced factors of altitude, slope gradient, slope aspect, and the nearest faults, which provided important support for the further study of post-disaster landslide distribution characteristics, susceptibility prediction, and risk assessment.This work was funded by the National Key Research and Development Program of China (Project No. 2018YFC1505202), the National Natural Science Foundation of China (41941019), the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (SKLGP2020Z012), the project on identification and monitoring of potential geological hazards with remote sensing in Sichuan Province (510201202076888) and the Everest Scientific Project at Chengdu University of Technology (2020ZF114103)

Unified and Dynamic Graph for Temporal Character Grouping in Long Videos

Video temporal character grouping locates appearing moments of major characters within a video according to their identities. To this end, recent works have evolved from unsupervised clustering to graph-based supervised clustering. However, graph methods are built upon the premise of fixed affinity graphs, bringing many inexact connections. Besides, they extract multi-modal features with kinds of models, which are unfriendly to deployment. In this paper, we present a unified and dynamic graph (UniDG) framework for temporal character grouping. This is accomplished firstly by a unified representation network that learns representations of multiple modalities within the same space and still preserves the modality's uniqueness simultaneously. Secondly, we present a dynamic graph clustering where the neighbors of different quantities are dynamically constructed for each node via a cyclic matching strategy, leading to a more reliable affinity graph. Thirdly, a progressive association method is introduced to exploit spatial and temporal contexts among different modalities, allowing multi-modal clustering results to be well fused. As current datasets only provide pre-extracted features, we evaluate our UniDG method on a collected dataset named MTCG, which contains each character's appearing clips of face and body and speaking voice tracks. We also evaluate our key components on existing clustering and retrieval datasets to verify the generalization ability. Experimental results manifest that our method can achieve promising results and outperform several state-of-the-art approaches

Improved strategy for post-traumatic hydrocephalus following decompressive craniectomy: Experience of a single center

BackgroundPatients with head trauma may develop hydrocephalus after decompressive craniectomy. Many studies have referred one-stage cranioplasty (CP) and ventriculoperitoneal shunt (VPS) was applied to treat cranial defect with post-traumatic hydrocephalus (PTH), but the safety and efficiency of the procedure remain controversial.MethodsThis is a retrospective cohort study including 70 patients of PTH following decompressive craniectomy who underwent simultaneous (50) and separated (20) procedures of cranioplasty and VPS from March 2014 to March 2021 at the authors’ institution with at least 30 days of follow-up. Patient characteristics, clinical findings, and complications were collected and analyzed.ResultsFifty patients with PTH underwent improved simultaneous procedures and 20 patients underwent staged surgeries. Among the cases, the overall complication rate was 22.86%. Complications suffered by patients who underwent one-stage procedure of CP and VPS did not differ significantly, compared with patients in the group of staged procedures (22% vs. 25%, p = 0.763). The significant difference was not observed in the two groups, regarding the complications of subdural/epidural fluid collection (4%/6% vs. 0/2%, p = 1.000/1.000), epidural hemorrhage (6% vs. 4%, p = 0.942), dysfunction of shunting system (0 vs. 2%, p = 0.286), postoperative seizure (8% vs. 4%, p = 1.000), and reoperation case (0 vs. 2%, p = 0.286). No case of subdural hemorrhage, incision/intracranial/abdominal infection, shunting system dysfunction, or reoperation was observed in the group of simultaneous procedure. Complications including subdural/epidural fluid collection, subdural hemorrhage, and incision/intracranial infection were not shown in the case series of the staged procedure group.ConclusionThe improved simultaneous procedure of cranioplasty and VPS is effective and safe to treat cranial defect and post-traumatic hydrocephalus with low risk of complications

Atomic H-Induced Mo_2C Hybrid as an Active and Stable Bifunctional Electrocatalyst

Mo_2C nanocrystals (NCs) anchored on vertically aligned graphene nanoribbons (VA-GNR) as hybrid nanocatalysts (Mo_2C-GNR) are synthesized through the direct carbonization of metallic Mo with atomic H treatment. The growth mechanism of Mo2C NCs with atomic H treatment is discussed. The Mo_2C-GNR hybrid exhibits highly active and durable electrocatalytic performance for the hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR). For HER, in an acidic solution the Mo_2C-GNR has an onset potential of 39 mV and a Tafel slope of 65 mV dec^(-1), in a basic solution Mo_2C-GNR has an onset potential of 53 mV, and Tafel slope of 54 mV dec^(-1). It is stable in both acidic and basic media. Mo2C-GNR is a high activity ORR catalyst with a high peak current density of 2.01 mA cm^(-2), an onset potential of 0.94 V that is more positive vs reversible hydrogen electrode, a high electron transfer number n (∼3.86) and long-term stability

Direct observation of layer-stacking and oriented wrinkles in multilayer hexagonal boron nitride

Hexagonal boron nitride (h-BN) has long been recognized as an ideal substrate for electronic devices due to its dangling-bond-free surface, insulating nature and thermal/chemical stability. Therefore, to analyse the lattice structure and orientation of h-BN crystals becomes important. Here, the stacking order and wrinkles of h-BN are investigated by transmission electron microscopy (TEM). It is experimentally confirmed that the layers in the h-BN flakes are arranged in the AA' stacking. The wrinkles in a form of threefold network throughout the h-BN crystal are oriented along the armchair direction, and their formation mechanism was further explored by molecular dynamics simulations. Our findings provide a deep insight about the microstructure of h-BN and shed light on the structural design/electronic modulations of two-dimensional crystals.Comment: 7 pages, 5 figure

Seaweed polysaccharide relieves hexavalent chromium-induced gut microbial homeostasis

Heavy metals released in the environment pose a huge threat to soil and water quality, food safety and public health. Additionally, humans and other mammals may also be directly exposed to heavy metals or exposed to heavy metals through the food chain, which seriously threatens the health of animals and humans. Chromium, especially hexavalent chromium [Cr (VI)], as a common heavy metal, has been shown to cause serious environmental pollution as well as intestinal damage. Thus, increasing research is devoted to finding drugs to mitigate the negative health effects of hexavalent chromium exposure. Seaweed polysaccharides have been demonstrated to have many pharmacological effects, but whether it can alleviate gut microbial dysbiosis caused by hexavalent chromium exposure has not been well characterized. Here, we hypothesized that seaweed polysaccharides could alleviate hexavalent chromium exposure-induced poor health in mice. Mice in Cr and seaweed polysaccharide treatment group was compulsively receive K2Cr2O7. At the end of the experiment, all mice were euthanized, and colon contents were collected for DNA sequencing analysis. Results showed that seaweed polysaccharide administration can restore the gut microbial dysbiosis and the reduction of gut microbial diversity caused by hexavalent chromium exposure in mice. Hexavalent chromium exposure also caused significant changes in the gut microbial composition of mice, including an increase in some pathogenic bacteria and a decrease in beneficial bacteria. However, seaweed polysaccharides administration could ameliorate the composition of gut microbiota. In conclusion, this study showed that seaweed polysaccharides can restore the negative effects of hexavalent chromium exposure in mice, including gut microbial dysbiosis. Meanwhile, this research also lays the foundation for the application of seaweed polysaccharides

Minimizing the programming power of phase change memory by using graphene nanoribbon edge-contact

Nonvolatile phase change random access memory (PCRAM) is regarded as one of promising candidates for emerging mass storage in the era of Big Data. However, relatively high programming energy hurdles the further reduction of power consumption in PCRAM. Utilizing narrow edge-contact of graphene can effectively reduce the active volume of phase change material in each cell, and therefore realize low-power operation. Here, we demonstrate that a write energy can be reduced to about ~53.7 fJ in a cell with ~3 nm-wide graphene nanoribbon (GNR) as edge-contact, whose cross-sectional area is only ~1 nm2. It is found that the cycle endurance exhibits an obvious dependence on the bias polarity in the cell with structure asymmetry. If a positive bias was applied to graphene electrode, the endurance can be extended at least one order longer than the case with reversal of polarity. The work represents a great technological advance for the low power PCRAM and could benefit for in-memory computing in future.Comment: 14 pages, 4 figure

Atomic H-Induced Mo_2C Hybrid as an Active and Stable Bifunctional Electrocatalyst

Mo_2C nanocrystals (NCs) anchored on vertically aligned graphene nanoribbons (VA-GNR) as hybrid nanocatalysts (Mo_2C-GNR) are synthesized through the direct carbonization of metallic Mo with atomic H treatment. The growth mechanism of Mo2C NCs with atomic H treatment is discussed. The Mo_2C-GNR hybrid exhibits highly active and durable electrocatalytic performance for the hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR). For HER, in an acidic solution the Mo_2C-GNR has an onset potential of 39 mV and a Tafel slope of 65 mV dec^(-1), in a basic solution Mo_2C-GNR has an onset potential of 53 mV, and Tafel slope of 54 mV dec^(-1). It is stable in both acidic and basic media. Mo2C-GNR is a high activity ORR catalyst with a high peak current density of 2.01 mA cm^(-2), an onset potential of 0.94 V that is more positive vs reversible hydrogen electrode, a high electron transfer number n (∼3.86) and long-term stability