A Kernel-space POF virtual switch

Protocol Oblivious Forwarding (POF) aims at providing a standard southbound interface for sustainable Software Defined Networking (SDN) evolvement. It overcomes the limitations of popular Open Flow protocols (an existing widely-adopted southbound interface), through the enhancement of SDN forwarding plane. This paper pioneers the design and implementation of a Kernel-space POF Virtual Switch (K_POFVS) on Linux platform. K_POFVS can improve the packet processing speed, through fast packet forwarding and the capability of adding/deleting/modifying protocol fields in kernel space. In addition, it is able to enhance flow table matching speed, by separating the mask table (consisting of flow entry masks used to figure out the matching field) and the flow table under a caching mechanism. Furthermore, K_POFVS can achieve efficient communication between the kernel space and the user space, via extending the Netlink communication between them. Experimental results show that K_POFVS can provide much better performance than existing user-space POF virtual switches, in terms of packet forwarding delay, packet processing delay and packet transmission rateThis work is partially supported by the National Program on Key Basic Research Project of China (973 Program) under Grant No. 2012CB315803, the Strategic Priority Research Program of the Chinese Academy of Sciences under grant No. XDA06010306, the National Natural Science Foundation of China under Grant No. 61303241, and the University of Exeter’s Innovation Platform – Link Fund under Award No. LF207

A Joint Method Based on Time-Frequency Distribution to Detect Time-Varying Interferences for GNSS Receivers with a Single Antenna

In this paper, a joint method combining Hough transform and reassigned smoothed pseudo Wigner-Ville distribution (RSPWVD) is presented to detect time-varying interferences with crossed frequency for a Global Navigation Satellite System (GNSS) receiver with a single antenna. The proposed method can prevent the cross-term interference and detect the time-varying interferences with crossed frequency which cannot be achieved by the classical time-frequency (TF) analysis with the peak detection method. The actual performance of the developed method has been evaluated by experiments with conditions where the real BeiDou system (BDS) B1I signals are corrupted by the simulated chirp interferences. The results of experiments show that the introduced method is effectively able to detect chirp interferences with crossed frequency and provide the same root mean square errors (RMSE) of the parameter estimation for chirp one and the improved initial frequency estimation for chirp two compared with the Hough transform of Wigner-Ville distribution (WVD) when the jamming to noise ratio (JNR) equals or surpasses 4 dB

The Research of University Librarians Participating in the Guidance of University Students’ Discipline Competition

The discipline competition of college students is an important part of innovation and entrepreneurship education, and is increasingly valued. As an important teaching auxiliary department, university libraries have a large number of library resources and a sufficient number of teachers, and should actively participate in the guidance of discipline competitions. To this end, we should determine the scope of the subject competition, establish a team of instructors, choose the suitable students participating in the competition, optimize the layout of the library to facilitate students to participate in the competition, strengthen the cooperation between schools and enterprises, and establish the database of the subject competition of excellent entries in the school

Multiobjective Optimization Approach for Coordinating Different DG from Distribution Network Operator

Integrating with analysis of uncertainties, this paper presented a multiobjective optimization approach for coordinating different DG from the perspective of Distribution Network Operator (DISOPER). Aiming to three uncertain factors including fuzzy variable, random variable, and interval variable, the information entropy and interval analysis methods are adopted to construct multistate models of multisource uncertainty. The information entropy method is to convert fuzzy variable into equivalent random variable. Interval analysis method is to transform random variables into interval variables by setting a confidence level. Then plenty of simulation analysis based on the small probability event and expectation are investigated to reduce the computational burden and eliminate invalid computation. Subsequently, multiobjective formulations based on multistate are built by analyzing systematical power loss, voltage quality, reliability, and environment change provide some reference for DISOPER in dealing with access of privately owned DG units. Furthermore, based on network topology analysis and modified nondominated sorting genetic algorithm (NSGA), a combinatorial optimization method is proposed to reduce search space and solve the constructed formulations efficiently. Simulations are carried out on IEEE 37-bus systems and results are presented and discussed

Preparation of nano-TiO

Chitosan-TiO2 photocatalytic composite was prepared using anatase nano-TiO2 and edible chitosan. Fourier Transform Infrared Spectroscopy (FT-IR), ultraviolet visible (UV-vis) and scanning electron microscopy (SEM) was used to characterize the structure of the composites. The photocatalytic degradation performance of the composites was studied by constructing a simulation system. The stability of the combination between chitosan and TiO2 in the composite can be confirmed by the results of FT-IR, UV-vis and SEM. The composite had a good photocatalytic degradation effect. When the addition amount of chitosan-TiO2 was 0.4%, the degradation efficiency of heptanal, octanal, (E)-2-heptenal and (E)-2-octenal reached the highest values of 83.82%, 81.73%, 96.33% and 93.36%, respectively

Green Synthesis of Gold Nanoparticles and Study of Their Inhibitory Effect on Bulk Cancer Cells and Cancer Stem Cells in Breast Carcinoma

Chemo-resistance from cancer stem cells (CSCs) subpopulation is a current issue in cancer treatment. It is important to select alternative therapies to efficiently eradicate both bulk cancer cells and CSCs. Here, gold nanoparticles (AuNPs) have been selected regarding their biocompatibility, facile and controllable synthesis, potent anti-cancer activity and photothermal conversion performance. We reported a green synthesis of functionalized AuNPs using hyaluronic acid (HA) as a reductant, capping, stabilizing and hydrophilic substance. The resultant AuNPs were spherical-shaped with an average diameter of around 30 nm. These AuNPs displayed improved physico-chemical (yield, stability, photothermal effect) and biological properties (cellular uptake, cytotoxicity and apoptotic effect) against bulk MDA-MB-231 cells, in comparison with other organic anti-cancer drugs. The intensified bioactivity was dependent on a mitochondria-mediated cascade, reflected by the damage in mitochondria, oxidative stress, intensified Caspase 3 activity and increased/decreased expression of certain pro-apoptotic (Bax, P53, Caspase 3)/anti-apoptotic (Bcl-2) genes. Moreover, these AuNPs posed a dramatically improved inhibitory effect in cell viability and self-renewable capacity on CSC subpopulation. All the results were attributed from the nano-scaled structure of AuNPs and combined effect from NIR-induced hyperthermia. In addition, the biocompatible nature of these AuNPs supported them to be a potential candidate in the development of novel chemotherapeutic drugs

A gradient descent boosting spectrum modeling method based on back interval partial least squares

When the technique of boosting regression is applied to near-infrared spectroscopy, the full spectrum of samples are generally used to perform partial least squares (PLS) modeling. However, there is a large amount of redundant information and noise contained in the full spectrum. This not only increases the complexity of the model, but also reduces its predictive performance. In addition, the boosting method is sensitive to data noise. When the data are mixed with too much noise, the generalization performance of boosting will decrease, and the prediction error and the variance of PLS will be relatively large. To solve these problems, a gradient descent boosting ensemble method combined with backward interval PLS (GD-Boosting-BiPLS) is proposed in this paper. BiPLS is used to select the effective variables for the boosting base model, and each base model is trained sequentially by resampling. The spectral segmentation parameter of BiPLS and the iteration parameter of boosting are fused, and the weight of each base model is distributed by the gradient descent strategy. This leads to a new ensemble model (forward additive model) in the direction of reduced residuals. The final model is the ensemble model that obtains the minimum root mean square error of prediction (RMSEP). The proposed method is applied to the quantitative prediction of ethanol concentrations. Over iterations 1–50, the average correlation coefficients of the calibration and validation sets are 0.9628 and 0.9388, and the average RMSE of cross-validation and RMSEP are 0.0732 and 0.0675, respectively. The overall performance of the proposed GD-Boosting-BiPLS method is compared with those of various ensemble strategies and 4 kinds of state-of-the-art spectral modeling methods. The experimental results reveal that the proposed method has the best generalization performance and stability

Evolution of severe acute respiratory syndrome coronavirus 2 RNA test results in a patient with fatal coronavirus disease 2019: a case report

A 65-year-old man was hospitalized owing to fever (38.6 °C) and dry cough since 4 days. He visited Wuhan 8 days ago. At admission, nasopharyngeal swab samples were taken, and polymerase chain reaction analysis confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA positivity. On day 9, after admission, the chest computed tomography scan showed diffuse ground-glass shadows in the patient's bilateral lungs. On day 11, his respiratory symptoms worsened. Subsequently, type I respiratory failure was diagnosed, coinciding with kidney injury, and subsequently, type II respiratory failure occurred, coupled with multiorgan failure including the heart and liver. However, the patient's constitution worsened although SARS-CoV-2 tests were negative since day 13. He died on day 21. Lung biopsy showed areas of diffuse alveolar damage, characterized by extensive acute alveolitis with numerous intra-alveolar neutrophil, lymphocyte, and macrophage infiltrations. Microthrombi were seen in the dilated pulmonary capillaries. Immunohistochemistry staining for SARS-CoV-2 N protein was negative. Taken together, the patient died of multiorgan failure although the SARS-CoV-2 infection was cleared already, implicating that for disease worsening, no active SARS-CoV-2 infection is required