In this study, we report the complete mitochondrial genome of Stichopus chloronotus. The mitogenome was 16,247 base pairs (58.55% A + T content) in length, comprising a total of 37 genes, including 13 protein-coding genes, 22 transfer RNA genes and 2 ribosomal RNA genes. To resolve the phylogenetic position of S. chloronotus, we analyzed all mitochondrial protein-coding genes from 27 species within the Echinodermata. The results showed that S. chloronotus belonged to the family Stichopodidae and was more closely related to tropical Stichopus species (S. horrens and S. monotuberculatus) than to other species. Our results will be useful for evolutionary analysis of sea cucumber species.
To investigate the effect of side-chain structure of comb-like polycarboxylates (PCE) on conformational properties in salt solutions, PCE with polyethyleneoxide (PEO) of different lengths were synthesized using methallyl polyethylene glycol (MPEG, Mw = 1200, 2400, 4000). Adding counter-ions (i.e., Na+, Ca2+) to dilute PCE solutions was found to induce a more complicated conformational changes, since the screening of the electrostatic intramolecular repulsion and the different complexation behaviors of Ca2+ with carboxylic groups. Laser light scattering (LLS) and conductivity measurements were used to investigate the conformations of PCE at various pH values. PCE of a long side chain polymer and the sparse grafting studied herein possesses a more coiled polymer backbone due to the intramolecular steric hindrance, which resulted in a more exposed extent of carboxylic groups on the backbone at the same pH values. Obviously, the solution conformation of PCE strongly impacts the accessible carboxylic groups contribution to complexation of the carboxylic oxygen atoms of PCE with Ca2+. In this way it may provide a new insight to design the polymer dispersants.
Cyber–physical–social system (CPSS) is a novel emerging paradigm that offers innovative services through the in-depth building of smart cities, which are tightly fused with the human physical system and its corresponding cyber world. These systems improve the efficacy and controllability of complex systems by intelligent human–machine interaction in cyber-space. A smart city is defined as a connectable, sensible, accessible, ubiquitous, sharable, and visible closed-loop system that supports the technology-based infrastructure, usually consisting of sensors and actuators embedded throughout the urban topography. These networks interconnect with wireless mobile devices such as smart phones with an Internet-based backbone with cloud service. A smart city is a highly stochastic hybrid structure that solves issues successfully with the help of an interdisciplinary approach and captures the overall vision outline. The CPSS collects data and flows it from the human physical systems such as the condition of traffic, bridges, parking space, roads or buildings, quality of air or water information, and status of resources of cities. Enabling a smart city setting involves a cyber–physical infrastructure combined with a new platform of software and strict requirements for security, privacy, safety, mobility, and the processing of huge amounts of information called big data. In addition, endeavors to deploy smart city applications have provided invaluable feedback from the city officials responsible for adopting such deployments and the end operators themselves. Transportation and energy networks are important arteries for the urban environment, and citywide systems should be functioning efficiently, and user and environmentally friendly. To ensure the operation of systems, a real-time view of the operating system of infrastructure is needed to control it. Therefore, the trend is surging to recognize the importance and involvement of CPSS in social dimensions that have the power to transform their essential services. This chapter will discuss how CPSS has the potentiality to adaptively optimize operation toward an intelligent transportation system, continuous real-time monitoring of its state, environment, and related behaviors while providing real-time recommendations. The transportation-based CPS system helps to improve its throughput, safety, and unique challenges related to detection, sensing, communication, computation, and control should be jointly addressed in the presence of heterogeneous information, resource limitations, and human interaction. As vehicles need extensive discrete logical implementation of software, therefore in this chapter, we investigate techniques such as modeling, security and safety control, system verification, and dynamic of vehicles for this application system. In the end, the result will help understand the important factors related to the operation of CPSS and how to optimize their operation in the transportation system. It will advance stochastic modeling, estimation, and control theories to collectively address the challenges related to this problem. This chapter will first introduce the smart cities with CPSS and then describe its key goals and drivers. After that, we delineate the specific CPSS concepts, tools, and key techniques to advancing CPSS for smart city from a technical perspective. The fourth point of this chapter highlights some of our work and the work of other colleagues in smart cities that is particularly noteworthy as CPSS. This chapter also discusses the future research challenges and visions of CPSS with smart cities. Lastly, we conclude this chapter by sharing our opinions and suggestions.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
In many driving situations, human mobility is an important topic in trajectory prediction. Considering the pedestrian trajectory as a sequence generative task, a prediction algorithm based on Social Long Short-Term Memory (Social LSTM) is implemented. In order to simulate the social interaction between pedestrians, Social Pooling (S-Pooling) is used to aggregate the hidden state of pedestrians, while the attention mechanism is utilized to aggregate information differently according to the importance of surrounding pedestrians. Furthermore, Convolutional Neural Networks (CNN) is introduced into Social LSTM model to consider both the interaction between people and the characteristic of scene scale in the prediction process. Experiments are carried out against baseline methods, and the results demonstrated that combining Social LSTM with attention mechanism or CNN can improve the performance of pedestrian trajectory prediction.
Dimeric mixed-ligand oxidovanadium complexes [V2O2(1,3-pdta)(bpy)2]·9H2O (1) and [V2O2(1,3-pdta)(phen)2]·6H2O (2) feature a symmetric binuclear structure bridged by 1,3-pdta, which is different from our previous reported asymmetric binuclear complex [V2O2(edta)(phen)2]·11H2O (3).In this study, a wide range of analytical techniques were carried out to fully characterize the complexes 1 and 2 and further investigate their structural stabilities. Density functional theory calculations of 1 and 2 also suggest that they might have good reactivity with biomolecules as anticancer agents. To assess and screen the antitumor activities of compounds 1-3 together with their four corresponding monomeric complexes [VO(ida)(phen)], [VO(ida)(bpy)], [VO(OH)(phen)2]Cl, and [VO(Hedta)]-, we have performed in vitro experiments with hepatocellular carcinoma HepG2 and SMMC-7721 cell lines by MTT analyses. Complex 2 was found to have the highest inhibitory potency against the growth of HepG2 and SMMC-7721 cells (IC50 = 2.07 ± 0.72 μM for HepG2; 13.00 ± 3.06 μM for SMMC-7721) compared to other compounds. The structure-activity relationship studies showed that the antitumor effect of compound 2 is higher than that of other compounds. After studying the monomeric compounds of 1-3, their effects were also ranked. Moreover, complex 2 displayed stronger binding affinity toward calf thymus DNA (Kb = 5.71 × 104 M-1) and cleavage activities than the other complexes (Kb = 1.34 × 104 M-1 for 1 and 5.22 × 104 M-1 for 3, respectively). We further extended the cellular mechanisms of drug action and found that 2 could block DNA synthesis and cell division of HepG2 and 7721 cells and further induce apoptosis by flow cytometry assays. In short, these results indicate that binuclear oxidovanadium compounds could have potential as simple, effective, and safe antitumor agents.
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