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Abstract A class of highly stable hydrocarbon radicals with helical chirality are synthesized, which can be isolated and purified by routine column chromatography on silica gel. These carbon‐centered radicals are stabilized by through‐bond delocalization and intramolecular through‐space conjugation, which is evidenced by Density Functional Theory (DFT) calculation. The high stability enables to directly modify the carbon radical via palladium‐catalyzed cross‐coupling with the radical being untapped. The structures and optoelectronic properties are investigated with a variety of experimental methods, including Electron Paramagnetic Resonance (EPR), Ultraviolet Visisble Near Infrared (UV–vis–NIR) measurements, Cyclic Voltammetry (CV), Thermogravimetry Analysis (TGA), Circular Dichroism (CD) spectra, High‐Performance Liquid Chromatography (HPLC), and X‐ray crystallographic analysis. DFT calculations indicated that the 9‐anthryl helical radical is more stable than its tail‐to‐tail σ‐dimer over 13.2 kJ mol−1, which is consistent with experimental observations.

Methods to access atropisomers bearing silanol groups are of value in organic synthesis. Here, the authors report a rhodium-catalyzed torsional strain-promoted asymmetric ring-opening reaction for the synthesis of α-silyl biaryl atropisomers.

Anonymous authentication has significant contribution to privacy protection in safety message dissemination for Vehicular Ad Hoc Networks (VANETs); however, it suffers from heavy workload of vehicle revocation check and message signature verification, which leads to unsatisfactory timeliness and high message loss rate in heavy traffic situations. To manage these challenging problems, this paper proposes an efficient safety message authentication protocol for VANETs by combining batch group signature verification and our proposed Group Session Key (GSK). Specifically, our signature verification method for safety message can both achieve computation efficiency by reducing the number of computation operations of bilinear pairing and resist impersonation attack by using tracking key implement. GSK is associated with the forward and backward keys and is only shared among unrevoked vehicle within a group. Performance analysis and simulations demonstrate that our protocol can provide promising security against various common types of attackers and is more efficient than traditional group-signature-based authentication protocols, in terms of computation time cost, authentication delay and message loss rate.

The metro transportation system will have emergency passenger flow for various reasons, resulting in passenger flow congestion, affecting efficiency and risks. In this paper, the LSTM network is applied to predict the normal passenger flow and emergency passenger flow of metro transportation based on transfer learning to solve the imbalanced data set problem when the amount of emergency samples is too small. The results show that under normal and emergency conditions, the average prediction error is less than 5%, which provides an alarm for the operating company to take preventive measures in advance. Compared with the strategy without transfer learning, it proves that the strategy proposed in this paper has advantages in predicting emergency conditions.

Vehicular ad hoc networks (VANETs) support safety and comfortable driving through frequent information exchange among intelligent vehicles. As an open access environment, VANETs are vulnerable to security threats, such as electronic attack and privacy disclosure. In this paper, we propose a misbehavior detection mechanism based on a support vector machine (SVM) and Dempster-Shafer theory (DST) of evidence to resist false message attack and message suppression attack. The proposed mechanism includes data trust model and vehicle trust model. The data trust model uses an SVM-based classifier to detect false messages based on message content and vehicle attributes. The vehicle trust model consists of a local vehicle trust module and a trust authority (TA) vehicle trust module. The local vehicle trust module uses another SVM-based classifier to evaluate whether the vehicle is credible based on the behavior of the vehicle in terms of message propagation. Then, the TA vehicle trust module uses DST to aggregate multiple trust assessment reports about the same vehicle and derives a comprehensive trust value. Simulation results show that Gaussian kernel best fits our models compared with other functions. In addition, the true positive rate of our data trust model is higher than the model based on back propagation neural network. Moreover, our two models are more robust than basic majority voting, weighted voting, and Bayesian inference in terms of true positive rate under various scenarios.

Background: The humbug gene is a truncated isoform of Aspartyl β-hydroxylase (ASPH) gene that is overexpressed in many human malignancies. In recent years, since humbug has received increasing attention, it is considered as a potential therapeutic molecular target. Therefore, it is necessary for preparing humbug protein and its monoclonal antibody to investigate its structure and function. Method: The optimized humbug gene, synthesized by Genscript in Nanjing, China on December 21st 2013, was expressed in Pichia pastoris cells that were cultured in a 10-L bioreactor. The recombinant protein was further obtained and purified by using ion exchange chromatography and Sephadex G75. The humbug protein was used to immunize Balb/c mice to generate the monoclonal antibodies. The specificity and sensitivity of the monoclonal antibodies were assessed by indirect enzyme-linked immunosorbent assay. Finally, the humbug monoclonal antibodies were used to detect the expression of humbug in several tumor cell lines via indirect immunofluorescence. Results: Firstly, the recombinant humbug was expressed in P. pastoris successfully and efficiently by using a gene-optimized strategy. Secondly, the purification process of humbug was established via multiple chromatography methods. In addition, four monoclonal antibodies against humbug were obtained from the immunized Balb/c mice, and the result of indirect immunofluorescence was indicated that the humbug monoclonal antibody showed the high affinity with humbug protein, which expressed in several tumor cell lines. Conclusion: The over-expression of recombinant humbug provides adequate sources for its structural study and the preparation of the humbug-specific monoclonal antibody can potentially be used in tumor initial diagnosis and immunotherapy. Keywords: Humbug, Fermentation, Pichia pastoris, Monoclonal antibody, Tumor diagnosis

We study, in the setting of a real Hilbert space H, the asymptotic behavior of trajectories of the second-order dissipative dynamical system with linear and gradient-driven nonlinear damping where λ > 0 and f, Φ: H → R are two convex differentiable functions. It is proved that if Φ is coercive and bounded from below, then the trajectory converges weakly towards a minimizer of Φ. In particular, we state that under suitable conditions, the trajectory strongly converges to the minimizer of Φ exponentially or polynomially.