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The task of Group Activity Recognition (GAR) aims to predict the activity category of the group by learning the actor spatial-temporal interaction relation in the group. Therefore, an effective actor relation learning method is crucial for the GAR task. The previous works mainly learn the interaction relation by the well-designed GCNs or Transformers. For example, to infer the actor interaction relation, GCNs need a learnable adjacency, and Transformers need to calculate the self-attention. Although the above methods can model the interaction relation effectively, they also increase the complexity of the model (the number of parameters and computations). In this paper, we design a novel MLP-based method for Actor Interaction Relation learning (MLP-AIR) in GAR. Compared with GCNs and Transformers, our method has a competitive but conceptually and technically simple alternative, significantly reducing the complexity. Specifically, MLP-AIR includes three sub-modules: MLP-based Spatial relation modeling module (MLP-S), MLP-based Temporal relation modeling module (MLP-T), and MLP-based Relation refining module (MLP-R). MLP-S is used to model the spatial relation between different actors in each frame. MLP-T is used to model the temporal relation between different frames for each actor. MLP-R is used further to refine the relation between different dimensions of relation features to improve the feature's expression ability. To evaluate the MLP-AIR, we conduct extensive experiments on two widely used benchmarks, including the Volleyball and Collective Activity datasets. Experimental results demonstrate that MLP-AIR can get competitive results but with low complexity., Comment: Submit to Neurocomputing

River morphology plays a vital role in the transport of substance within them. However, our understanding of how natural and artificial morphologies redistribute different potentially toxic elements in acid mine drainage (AMD)-contaminated rivers remains poor. In this study, we linked morphological river features and physicochemical sediment characteristics to trace the redistribution of various potentially toxic elements and elucidate their implications for remediating rivers prone to AMD pollution. A dense network of sediment/soil samples was collected from different river morphological units, such as channels, dam reservoirs, pools, floodplain sandbars and wetlands in an AMD-impacted river. The analyses showed that the contaminant levels in channel generally decreased downstream from the headwater mine site, however, local fluctuations in certain areas were observed due to the trapping effect of various dams along the river. The As and Pb concentrations were higher at floodplain sandbars, while river channels exhibited higher Cd and Zn contamination. The concentrations and geochemical fractions of As, Cd, Cu, Pb and Zn in sediment/soil cores from sandbar and river channel also varied. Additionally, structural equation modeling analysis indicated that spatial variations in contaminant distributions were directly affected by physicochemical properties (such as the soil/sediment Fe, Zn, and S concentrations, and pH), which are indirectly affected by river morphology. The diverse morphology of the river redistributed AMDderived contaminants and could be used to identify contamination hotspots. Our analyses suggested that the feasibility and efficiency of previously proposed countermeasures varied for contaminants in different geomorphological units. In river channels, As uptake from sediments by aquatic plants may be less efficient than Cd, Cu, and Zn uptake due to its lower bioavailability. Moreover, vegetation prevented contaminant enriched soil particle erosion mo, Funding Agencies|Natural Science Foundation of Guangdong Province, China [2018A030310309]; Famous Overseas Teachers Project in Guangdong Province, China [2020A1414010173]

We provide two sufficient and necessary conditions to characterize any $n$-bit partial Boolean function with exact quantum 1-query complexity. Using the first characterization, we present all $n$-bit partial Boolean functions that depend on $n$ bits and have exact quantum 1-query complexity. Due to the second characterization, we construct a function $F$ that maps any $n$-bit partial Boolean function to some integer, and if an $n$-bit partial Boolean function $f$ depends on $k$ bits and has exact quantum 1-query complexity, then $F(f)$ is non-positive. In addition, we show that the number of all $n$-bit partial Boolean functions that depend on $k$ bits and have exact quantum 1-query complexity is not bigger than $n^{2}2^{2^{n-1}(1+2^{2-k})+2n^{2}}$ for all $n\geq 3$ and $k\geq 2$., Comment: 11pages; comments are welcome

Thallium (Tl) is a trace metal of severe toxicity. Its health concerns via consumption of contaminated vegetables have often been overlooked or underestimated. This study was designed to gain insight into the actual level and distribution characteristics of Tl and metal (loid)s (Pb, Cd, Cr, Sb, Mn, Cu, Zn, Ni, and Co) in agricultural soils and common vegetables cultivated in different zones (upstream, midstream, and downstream) of a densely populated residential area in a typical mine city, which has been open-pit exploiting Tl-bearing pyrite minerals since 1960s. The results show that most of the agricultural soils exhibit contaminated levels of Tl, with Tl contents (upstream: 1.35–4.31 mg/kg, midstream: 2.43–5.19 mg/kg, and downstream: 0.65–2.33 mg/kg) mostly exceeding the maximum permissible level (MPL) for agricultural land use (1 mg/kg). Sequential extraction procedure indicates that even Tl is predominantly retained in the residual fraction, significant levels of Tl are still present in the geochemically mobile fractions. Besides, metals like Cu, Cd, Mn, and Co are mostly distributed in the labile fractions. Almost all metal (loid)s in edible parts of the vegetables exceed their corresponding MPL for consumption. The chronic daily intake (CDI) and hazard quotient (HQ) values calculated for inhabitants at different ages indicate non-negligible Tl risks via consumption of local vegetables, especially for children. Therefore, it is critical to establish effective measures for hazardous waste management and enforceable regulations in Tl-polluted area to mitigate potential severe impacts of Tl on human health through food chain. © 2019 Elsevier Ltd; Alarming levels of toxic thallium were widely detected in vegetables and soils in a typical pyrite mining city. © 2019 Elsevier Ltd

With the emergence of edge computing in various applications domains, end users are now surrounded by a fast growing volume of data from edge devices belonging to different stakeholders. However, these edge devices cannot cooperate to share big data because of the distrust among them. In this paper, the blockchain is deployed in collaborative edges by exploiting the non-repudiation and non-tampering properties to enable trust. First, we develop a blockchain based big data sharing framework in collaborative edges for adapting to the limited computational and storage resources in edge devices. Then, a consensus mechanism called Proof-of-Collaboration (PoC) is proposed for computational resources reduction in our proposed framework, where edge devices offer their credits of PoC to compete for the block generation. Moreover, we put forward a futile transaction filter algorithm for transaction offloading, greatly reducing the storage resources occupied by the blockchain in edges. Extensive experiments are performed to demonstrate the superior performance of our proposal. © 2018 IEEE.

This paper presents a novel method for converting any unstructured quadrilateral or hexahedral mesh to a generalized T-spline surface or solid T-spline, based on the rational T-spline basis functions. Our conversion algorithm consists of two stages: the topology stage and the geometry stage. In the topology stage, the input quadrilateral or hexahedral mesh is taken as the initial T-mesh. To construct a gap-free T-spline, templates are designed for each type of node and applied to elements in the input mesh. In the geometry stage, an efficient surface fitting technique is developed to improve the surface accuracy with sharp feature preservation. The constructed T-spline surface and solid T-spline interpolate every boundary node in the input mesh, with C2- continuity everywhere except the local region around irregular nodes. Finally, a B'ezier extraction technique is developed and linear independence of the constructed T-splines is studied to facilitate T-spline based isogeometric analysis.

In this paper, several discrete schemes for Gaussian curvature are surveyed. The convergence property of a modified discrete scheme for the Gaussian curvature is considered. Furthermore, a new discrete scheme for Gaussian curvature is resented. We prove that the new scheme converges at the regular vertex with valence not less than 5. By constructing a counterexample, we also show that it is impossible for building a discrete scheme for Gaussian curvature which converges over the regular vertex with valence 4. Finally, asymptotic errors of several discrete scheme for Gaussian curvature are compared.