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The adsorption technology has been widely applied in water remediation for contamination removal of dyes and bacteria, by virtue of the advantages of adsorption technology including high efficiency, energy conservation and ease of operation. Simultaneous removal of dyes and bacteria has been realized by some reported materials, but to achieve satisfactory adsorption amounts and rates remain an unmet goal for decades. Herein, a poly(methacrylatoethyl trimethyl ammonium chloride-co-methyl methacrylate) copolymer was synthesized, and then blended with polyethersulfone for the fabrication of nanofibrous membranes via electrospinning for the use of fast and massive removal of dyes and bacteria. Owing to the introduction of abundant quaternary ammonium groups, the maximum adsorption amount for methyl orange was up to 909.8 mg g−1. In addition, the modified nanofibrous membranes showed good recyclability, broad applications in severe environments, selective adsorption ability, and excellent dynamic removal performance. Especially, thanks to the abundant functional groups, the membranes showed fast adsorption ability for bacteria through electrostatic interaction. It should be noted that the clearance ratio for Staphylococcus aureus or Escherichia coli by 6 min of static adsorption could reach 93 % or 90 % for each. Additionally, dynamic removal ratio via filtration with the nanofibrous membranes could reach 99.7 % for Staphylococcus aureus or 98.7 % for Escherichia coli in 90 s. Therefore, the proposed approach towards the quaternary ammonium modified polyethersulfone nanofibrous membranes creates a new route for ultra-high adsorption capacity and ultra-fast removal rates for dyes and bacteria in water remediation.

Patients with chronic kidney disease are at high risk of hyperkalemia that is associated with various life-threatening complications. Treatments primarily rely on orally administered potassium binding agents, along with low curative effects and various side effects. Herein, direct serum potassium uptake was realized via zeolite–heparin-mimicking-polymer hybrid microbeads. The preparation process involved the synthesis of the heparin-mimicking polymer via the in situ cross-linking polymerization of acrylic acid and N-vinylpyrrolidone in polyethersulfone solution, the fabrication of microbeads via zeolite-mixing, electro-spraying and phase-inversion, and the subsequent aqueous-phase modifications based on ion-exchange and metal-leaching. An ultra-high (about 88%) amount of zeolite could be incorporated and well locked inside the polymer matrix. Potassium uptake capability was verified in water, normal saline and human serum, showing high selectivity and fast adsorption. The microbeads exhibited satisfying blood compatibility, negligible hemolysis ratio, prolonged clotting time, inhibited contact activation, and enhanced antifouling property toward serum proteins and cells. The proposed approach toward zeolite–heparin-mimicking-polymer hybrid microbeads provided a cheap, efficient and safe treatment protocol of hyperkalemia for the high-risk patients., Graphical abstract Image 1, Highlights • Zeolite–heparin-mimicking-polymer hybrid microbeads were prepared for potassium uptake. • An ultra-high (~88%) amount of zeolite could be well locked inside the polymer matrix. • Potassium uptake by microbeads exhibited high selectivity and fast adsorption. • The microbeads exhibited excellent blood compatibility. • The proposed method is cheap, efficient and safe to treat hyperkalemia.

On-chip optical gas sensors, which use resonant shifts of cavities to detect molecular concentrations, have the advantages of high sensitivity, real-time detection, and compact footprint. However, such sensors are usually limited by a serious cross-sensitivity issue induced by environmental temperature variations. To overcome this limitation, we study a dual-mode graphene-on-microring resonator to accurately measure gas concentrations without suffering from temperature variations. To be specific, the influences of gas-induced graphene’s optical conductivity changes and environmental temperature variations on effective refractive indices of TE0 and TE1 modes in the resonator can be decoupled based on the modal linear independent responses. With this method, we designed a nitrogen dioxide sensor with a sensitivity of 0.02 nm/ppm and a limit of detection of 0.5 ppm. Our study paves the way for developing on-chip optical gas sensors with excellent sensitivity and temperature stability.

The stable carbon and hydrogen isotopes of light crude oils from deep reservoirs of Cambrian-Ordovician strata in Tazhong area of Tarim Basin, NW China were investigated. The δ13C and δD values det...

Recently, combining inorganic and organic components to develop a dual-functional surface (antibacterial and antifouling) has resulted in widespread investigations. However, the preparation of the ...

Several algorithms have been developed to simplify buildings based on their local structure in past decades. However, different local structures are defined for certain purposes, and no algorithm can appropriately simplify all buildings. We propose a combined building simplification approach based on local structure classification and backtracking strategy. In this approach, local structures are classified and their based operations are defined by considering the buildings’ orthogonal and non-orthogonal features. Each building is simplified to target scale with a selected local-structure-based operation progressively scale-by-scale. Rules are built to support the selection of local-structure-based operations with a binary decision tree, and a backtracking strategy is used when an invalid operation is applied. When the building is too small or the evaluation shows that it cannot be simplified based on local structures, template matching or enlargement algorithms are applied to simplify the building. A dataset (1:10k) collected from the Ordnance Survey was used for the experiment and simplified scale of 1:25k. Results satisfied legibility constraints and the change in area, orientation and position of simplified buildings are controlled within certain range by comparing with the results generated based on other four simplification algorithms. Possible use of our approach for continuous scale transformation of buildings is also discussed.

The Vision Meets Drone Object Detection in Image Challenge (VisDrone-DET 2020) is the third annual object detector benchmarking activity. Compared with the previous VisDrone-DET 2018 and VisDrone-DET 2019 challenges, many submitted object detectors exceed the recent state-of-the-art detectors. Based on the selected 29 robust detection methods, we discuss the experimental results comprehensively, which shows the effectiveness of ensemble learning and data augmentation in drone captured object detection. The full challenge results are publicly available at the website http://aiskyeye.com/leaderboard/.

Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint. However, there are few algorithms focusing on crowd counting on the drone-captured data due to the lack of comprehensive datasets. To this end, we collect a large-scale dataset and organize the Vision Meets Drone Crowd Counting Challenge (VisDrone-CC2020) in conjunction with the 16th European Conference on Computer Vision (ECCV 2020) to promote the developments in the related fields. The collected dataset is formed by $3,360$ images, including $2,460$ images for training, and $900$ images for testing. Specifically, we manually annotate persons with points in each video frame. There are $14$ algorithms from $15$ institutes submitted to the VisDrone-CC2020 Challenge. We provide a detailed analysis of the evaluation results and conclude the challenge. More information can be found at the website: \url{http://www.aiskyeye.com/}., The method description of A7 Mutil-Scale Aware based SFANet (M-SFANet) is updated and missing references are added

Hydrocarbon aromatization involves the cleavage of multiple C–H bonds and the dehydrogenation of aliphatic rings, with a resultant fractionation of stable hydrogen between aromatic hydrocarbons and...

Information on spatial distribution of buildings must be explored as part of the process of map generalization. A new approach is proposed in this article, which combines building classification an...

Spatial conflicts can remain unresolved during map generalization if only displacement is used, especially for urban building maps. To solve all possible spatial conflicts during urban building map generalization, we propose a collaborative displacement method, combining aggregation, elimination, and constrained reshape. After applying an improved vector field-based displacement for solution of initial conflicts, two types of sequential conflicts are detected and evaluated to identify additional displacement solutions based on a trial and error strategy. If no displacement solution is available, aggregation, elimination, or constrained reshape are selected and applied for the unsolved sequential conflicts based on cartographic rules. For a more reasonable generalization result, an improved constrained reshape approach is also introduced for buildings in conflicts along roads. Two data sets with scales of 1:5000 and 1:25 000 for urban building map were selected to validate this approach. The results indicate that it is reasonable and feasible to solve all defined spatial conflicts in urban building map generalization using our proposed method.

Given the complexity of pollutants in wastewater, development of facile and effective multifunctional materials, which can not only kill bacteria but also remove dyes from wastewater, is in high demand. Herein, a facile strategy for the preparation of positively-charged nanofibrous membranes (NFMs) is reported via the combination of electrospinning and in-situ cross-linked polymerization of poly ([2-(methacryloyloxy)-ethyl] trimethyl ammonium chloride) (PMETAC) in poly (ether sulfone) (PES) solution. The quaternary ammonium salt polymer of PMETAC enabled the NFMs with positive charge to kill bacteria and remove anionic dyes. The antibacterial tests including agar plate counting and live/dead staining indicate that the NFMs show strong antibacterial ability with bacterial killing ratios of nearly 99% for both Escherichia coli and Staphylococcus aureus, as well as remarkable recyclability towards killing bacteria. The dyes adsorption experiments show that the NFMs exhibit high adsorption capacity for anionic dyes up to 208 mg g−1 for Congo Red (CR) and good reusability toward CR. Impressively, the membrane adsorption column test indicates that the CR dye removal ratio is up to 100% for the first time, and that is still as high as 96.5% for the third time with a fresh dye solution. Given the above advantages, such fascinating NFMs may provide new perspectives in the exploitation of multifunctional membrane materials for complex water remediation.

Research on tree-type irrigation pipe networks is an important component of agricultural water-saving projects. The optimal design of tree-type irrigation pipe networks is a key aspect regarding the profitability of irrigated agriculture. Meanwhile, swarm intelligence optimization algorithms have good computational ability and can be applied to solve many optimization problems in agricultural engineering. To identify the lowest investment cost for a pipe network, this study defined the concept of an upper water node to ensure the connectivity of tree-type irrigation pipe networks, and therefore, improve the pipe network planning model without using preliminary network connection diagrams. In addition, this study proposed an improved chicken swarm optimization algorithm (Improved Chicken Swarm Optimization using Adaptive Search and Variation, ICSO-ASV), which was applied to solve 12 test functions of different dimensions. The test results show that, compared to the traditional chicken swarm algorithm and other algorithms in the control group, the ICSO-ASV algorithm could effectively improve the global search capability. Finally, the ICSO-ASV algorithm was used to plan and design 15-node and 40-node pipe networks. The calculation results show that the average investment costs of the two pipe networks generated by the ICSO-ASV algorithm were 42.20% and 31.09% lower than those generated by the traditional chicken swarm algorithm, which further verified the feasibility of applying ICSO-ASV to design tree-type irrigation pipe networks. Thus, the design method proposed in this study can solve the optimal problems of tree-type irrigation pipe networks with varying topologies. The optimal solutions can be generated automatically using the ICSO-ASV algorithm if essential parameters of the pipe network planning model are provided.

In map generalization, scale reduction and feature symbolization inevitably generate problems of overlapping objects or map congestion. To solve the legibility problem with respect to the generalization of dispersed rural buildings, selection of buildings is necessary and can be transformed into an optimization problem. In this paper, an improved genetic algorithm for building selection is designed to be able to incorporate cartographic constraints related to the building selection problem. Part of the local constraints for building selection is used to constrain the encoding and genetic operation. To satisfy other local constraints, a preparation phase is necessary before building selection, which includes building enlargement, local displacement, conflict detection, and attribute enrichment. The contextual constraints are used to ascertain a fitness function. The experimental results indicate that the algorithm proposed in this article can obtain good results for building selection whilst preserving the spatial distribution characteristics of buildings.