Classical Keggin intercalated into layered double hydroxides: facile preparation and catalytic efficiency in Knoevenagel condensation reaction

The family of polyoxometalate (POM) intercalated layered double hydroxides (LDHs) composite materials has shown great promise for the design of functional materials with numerous applications. It is known that intercalation of the classical Keggin polyoxometalate (POM) of [PW12O40]3- (PW12) into layered double hydroxides (LDHs) is very unlikely to take place by conventional ion exchange methods due to spatial and geometrical restrictions. In this paper, such intercalated compound of Mg0.73Al0.22(OH)2 [PW12O40]0.04•0.98H2O (Mg3Al-PW12) has been successfully obtained by adopting a spontaneous flocculation method. The Mg3Al-PW12 has been fully characterized using a wide range of methods (XRD, SEM, TEM, XPS, EDX, XPS, FT-IR, NMR, BET). XRD patterns of Mg3Al-PW12 exhibit no impurity phase usually observed next to the (003) diffraction peak. Subsequent application of the Mg3Al-PW12 as catalyst in Knoevenagel condensation reactions of various aldehydes and ketones with Z–CH2-Z‘ type substrates (ethyl-cyanoacetate and malononitrile) at 60 oC in mixed solvents (Vi-propanol:Vwater = 2 : 1) demonstrated highly efficient catalytic activity. The synergistic effect between the acidic and basic sites of the Mg3Al-PW12 composite proved to be crucial for the efficiency of the condensation reactions. Additionally, the Mg3Al-PW12 catalysed Knoevenagel condensation of benzaldehyde with ethyl cyanoacetate demonstrated the highest turnover number (TON) of 47980 reported so far

Focal Defects in Single-Celled Tubes Mutant for Cerebral Cavernous Malformation 3, GCKIII, or NSF2

Tubes of differing cellular architecture connect into networks. In the Drosophila tracheal system, two tube types connect within single cells (terminal cells); however, the genes that mediate this interconnection are unknown. Here we characterize two genes that are essential for this process: lotus, required for maintaining a connection between the tubes, and wheezy, required to prevent local tube dilation. We find that lotus encodes N-ethylmaleimide sensitive factor 2 (NSF2), whereas wheezy encodes Germinal center kinase III (GCKIII). GCKIIIs are effectors of Cerebral cavernous malformation 3 (CCM3), a protein mutated in vascular disease. Depletion of Ccm3 by RNA interference phenocopies wheezy; thus, CCM3 and GCKIII, which prevent capillary dilation in humans, prevent tube dilation in Drosophila trachea. Ectopic junctional and apical proteins are present in wheezy terminal cells, and we show that tube dilation is suppressed by reduction of NSF2, of the apical determinant Crumbs, or of septate junction protein Varicose

A Novel Point Cloud Compression Algorithm for Vehicle Recognition Using Boundary Extraction

Recently, research on the hardware system for generating point cloud data through 3D LiDAR scanning has improved, which has important applications in autonomous driving and 3D reconstruction. However, point cloud data may contain defects such as duplicate points, redundant points, and an unordered mass of points, which put higher demands on the performance of hardware systems for processing data. Simplifying and compressing point cloud data can improve recognition speed in subsequent processes. This paper studies a novel algorithm for identifying vehicles in the environment using 3D LiDAR to obtain point cloud data. The point cloud compression method based on the nearest neighbor point and boundary extraction from octree voxels center points is applied to the point cloud data, followed by the vehicle point cloud identification algorithm based on image mapping for vehicle recognition. The proposed algorithm is tested using the KITTI dataset, and the results show improved accuracy compared to other methods

Learning Dense UV Completion for Human Mesh Recovery

Human mesh reconstruction from a single image is challenging in the presence of occlusion, which can be caused by self, objects, or other humans. Existing methods either fail to separate human features accurately or lack proper supervision for feature completion. In this paper, we propose Dense Inpainting Human Mesh Recovery (DIMR), a two-stage method that leverages dense correspondence maps to handle occlusion. Our method utilizes a dense correspondence map to separate visible human features and completes human features on a structured UV map dense human with an attention-based feature completion module. We also design a feature inpainting training procedure that guides the network to learn from unoccluded features. We evaluate our method on several datasets and demonstrate its superior performance under heavily occluded scenarios compared to other methods. Extensive experiments show that our method obviously outperforms prior SOTA methods on heavily occluded images and achieves comparable results on the standard benchmarks (3DPW)

A Technical Review of Real-time QoS Protocols in Wireless Sensor Networks

Real-time wireless sensor networks become more and more important in emerging new applications as message delivery timeliness is highly concerned. However, supporting real-time QoS in sensor networks has faced many challenges due to their wireless nature, limited resource, dynamic network topology, and the demand of distributed architecture. There are tradeoffs between different application requirements including energy efficiency and delay performance. This paper studies the state of the art of current real-time solutions including MAC protocols, routing protocols, data aggregation strategies, and cross-layer designs. Some research challenges and design favors are also identified. The discussion may offer a reference for future investigations

Model predictive control-based energy management strategy for a series hybrid electric tracked vehicle

The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.apenergy.2016.08.085 © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The series hybrid electric tracked bulldozer (HETB)’s fuel economy heavily depends on its energy management strategy. This paper presents a model predictive controller (MPC) to solve the energy management problem in an HETB for the first time. A real typical working condition of the HETB is utilized to develop the MPC. The results are compared to two other strategies: a rule-based strategy and a dynamic programming (DP) based one. The latter is a global optimization approach used as a benchmark. The effect of the MPC’s parameters (e.g. length of prediction horizon) is also studied. The comparison results demonstrate that the proposed approach has approximately a 6% improvement in fuel economy over the rule-based one, and it can achieve over 98% of the fuel optimality of DP in typical working conditions. To show the advantage of the proposed MPC and its robustness under large disturbances, 40% white noise has been added to the typical working condition. Simulation results show that an 8% improvement in fuel economy is obtained by the proposed approach compared to the rule-based one.Natural Sciences and Engineering Research Council of Canada (NSERC) || Ontario Research Fun

Study on Small Layers Producing Condition by Using the Method of Fuzzy Comprehensive Evaluation

Before the subdivision adjustment of single well layers carried out, we need to evaluate the producing degree of the existing layers. There are many factors affecting the properties of small layers. This paper, using fuzzy comprehensive evaluation method, calculates the comprehensive evaluation coefficient to judge the property of each small layer

Real-Time Routing Protocols for Wireless Sensor Networks

International audienceDeveloping real-time routing protocols under energy constraint is one of the key points for providing end-to-end delay guarantee in multi-hop wireless sensor networks. In this paper, we give, at first, an overview of the existing real-time routing protocols and point out some potential approaches to improve them. To enhance existing protocols, one way is to make routing decision based on multi-hop rather than 1-hop neighborhood information. We study the asymptotic performance of a generic routing metric as the quantity of information a priori increases and propose then a 2-hop neighborhood information based real-time routing protocol. As an example, the approach of mapping packet deadline to a velocity is adopted as in SPEED; however, our routing decision is made based on the 2-hop velocity. An energy efficient probabilistic drop is proposed to improve energy utilization efficiency. When packet deadline requirement is not stringent, a design is integrated to release nodes from heavy consumption. Energy balance over nodes is thus improved. Simulation results show that, compared with protocol SPEED that only utilizes 1-hop information, the proposed scheme leads to lower deadline miss ratio and higher energy efficiency