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Mitochondria, the power generators in cell, are a primary organelle of oxygen consumption and a main source of reactive oxygen/nitrogen species (ROS/RNS). Peroxynitrite (ONOO-), known as a kind of RNS, has been considered to be a significant factor in many cell-related biological processes, and there is great desire to develop fluorescent probes that can sensitively and selectively detect peroxynitrite in living cells. Herein, we developed a fluorescent carbon-dots (C-dots) based mitochondria-targetable nanoprobe with high sensitivity and selectivity for peroxynitrite sensing in living cells. The C-dots with its surface rich in amino groups was synthesized using o-phenylenediamine as carbon precursor, and it could be covalently conjugated with a mitochondria-targeting moiety, i.e. triphenylphosphonium (TPP). In the presence of peroxynitrite, the fluorescence of the constructed nanoprobe (C-dots-TPP) was efficiently quenched via a mechanism of photoinduced electron transfer (PET). The nanoprobe exhibited relatively high sensitivity (limit of detection: 13.5nM) and selectivity towards peroxynitrite in aqueous buffer. The performance of the nanoprobe for fluorescence imaging of peroxynitrite in mitochondria was investigated. The results demonstrated that the nanoprobe showed fine mitochondria-targeting ability and imaging contrast towards peroxynitrite in living cells. We anticipate that the proposed nanoprobe will provide a facile tool to explore the role played by peroxynitrite in cytobiology.

To date, Denial of Service (DoS) attack still causes great damage to the Internet in spite of many years' research on its detection and defense. Low-rate Denial of Service (LDoS) attack, a new type of DoS attack, exploits the congestion control mechanism of Transmission Control Protocol (TCP) to degrade the throughput of network by sending periodic pulse attack traffic. The periodic mechanism applied by LDoS makes its average attack traffic speed very low compared to DoS attack, which means existing DoS detection methods based on high attack traffic speed are incapable of detecting LDoS attack. In this paper, we propose a correlation-based approach to detect LDoS attack. The major innovation of the correlation-based approach is that, instead of calculating the correlation coefficient of network traffic sequence directly, it calculates the correlation coefficient of the Hilbert Spectrum of the network traffic. The Hilbert Spectrum, obtained by applying Hilbert-Huang Transform to the network traffic, is an energy-frequency-time distribution which presents more information about the network traffic than raw network traffic sequences. We conduct NS-2 simulations, public dataset experiments to evaluate the performance of the proposed approach. The experimental results show that the approach can detect LDoS attack effectively.

Context: As software evolves, the test suite tends to grow, regression testing has become prohibitively expensive. Test suite minimization is one of the most important approaches for reducing test cost. The process of test suite minimization is a trade-off between cost and other value criteria and is appropriate to be described as a many-objective optimization problem. Objective: To identify the most efficient test suite for reducing the redundant degree of test data and improving test efficiency without decreasing the defect detection ability of test data. Method: We introduce a mutation testing-based many-objective optimization approach, which gives higher priority to the fault detection ability and takes mutation score as a major objective, together with cost and three standard code coverage criteria for test suite minimization. Six classical evolutionary many-objective optimization algorithms are applied to identify efficient test suite. Three programs from the SIR repository and one larger program, space are applied for empirical study and effectiveness evaluation. Results: On the one hand, in three SIR programs experiments NSGA-II with tuning was the most effective technique. However, MOEA/D-PBI outperformed NSGA-II on the larger program (Space). On the other hand, the test cost of the optimal test suite which obtained by the many-objective optimization approach with mutation score is much lower than the one without it in tcas. Conclusions: The experimental results prove that the many-objective optimization model with the guidance of mutation score is indeed effective in reducing the test suite redundancy.

In order to make the ship course keeping algorithm more energy-efficient, this paper used the closed-loop gain shaping algorithm to design the linear controller, and then used a kind of bipolar sigmoid function nonlinear feedback to replace the original linear feedback. Theoretical analysis showed that in the same control effect, the proposed algorithm could reduce control energy. Took the ship Yukun to do computer simulation by using Simulink Toolbox of MATLAB, and the results indicated that the designed controller based on nonlinear feedback had good robustness. The average rudder angle was reduced by more than 10%. The proposed algorithm is concise and effective.

With time-delay systems arising, time-delay system testing has attracted much attention. Additionally, evaluating the cost and effectiveness is required to make a good test strategy in practice. In this paper, we take time-delay and other five factors (state number, input number, output number, completeness degree, and accessibility degree) into account and present a timer embedded FSM (TEFSM) model to design a comparative strategy for assessing the coverage criteria and test suites generation methods for time-delay systems. We explore the impact on the average length of test suites, in which the test suites generation methods, coverage criteria, and TEFSM model parameters are involved.