Probability Transform Based on the Ordered Weighted Averaging and Entropy Difference

Dempster-Shafer evidence theory can handle imprecise and unknown information, which has attracted many people. In most cases, the mass function can be translated into the probability, which is useful to expand the applications of the D-S evidence theory. However, how to reasonably transfer the mass function to the probability distribution is still an open issue. Hence, the paper proposed a new probability transform method based on the ordered weighted averaging and entropy difference. The new method calculates weights by ordered weighted averaging, and adds entropy difference as one of the measurement indicators. Then achieved the transformation of the minimum entropy difference by adjusting the parameter r of the weight function. Finally, some numerical examples are given to prove that new method is more reasonable and effective

Unraveling Quantum Coherences Mediating Primary Charge Transfer Processes in Photosystem II Reaction Center

Photosystem II (PSII) reaction center is a unique protein-chromophore complex that is capable of efficiently separating electronic charges across the membrane after photoexcitation. In the PSII reaction center, the primary energy- and charge-transfer (CT) processes occur on comparable ultrafast timescales, which makes it extremely challenging to understand the fundamental mechanism responsible for the near-unity quantum efficiency of the transfer. Here, we elucidate the role of quantum coherences in the ultrafast energy and CT in the PSII reaction center by performing two-dimensional (2D) electronic spectroscopy at the cryogenic temperature of 20 K, which captures the distinct underlying quantum coherences. Specifically, we uncover the electronic and vibrational coherences along with their lifetimes during the primary ultrafast processes of energy and CT. We also examine the functional role of the observed quantum coherences. To gather further insight, we construct a structure-based excitonic model that provided evidence for coherent energy and CT at low temperature in the 2D electronic spectra. The principles, uncovered by this combination of experimental and theoretical analyses, could provide valuable guidelines for creating artificial photosystems with exploitation of system-bath coupling and control of coherences to optimize the photon conversion efficiency to specific functions

Nobiletin Inhibits IL-1β-Induced Inflammation in Chondrocytes via Suppression of NF-κB Signaling and Attenuates Osteoarthritis in Mice

Osteoarthritis (OA), a common degenerative joint disease, is principally characterized by inflammation and destruction of cartilage. Nobiletin, an extract of the peel of citrus fruits, is known to have anti-inflammatory properties. However, the mechanisms by which nobiletin plays a protective role in osteoarthritis (OA) are not completely understood. In the present study, we investigated the anti-inflammatory effects of nobiletin in the progression of OA in both in vitro and in vivo experiments. Mouse chondrocytes were pretreated with nobiletin (0, 10, 20, 40 μM) for 24 h and then incubated with IL-1β (10 ng/ml, 24 h) in vitro. The generation of PGE2 and NO was evaluated by the Griess reaction and ELISAs. The protein expression of inducible nitric oxide synthase, matrix metalloproteinase-3, matrix metalloproteinase-13, A disintegrin and metalloproteinase with thrombospondin motifs-5 (ADAMTS5), cyclooxygenase-2, collagen II, and aggrecan was analyzed by Western blotting. Immunofluorescence and Western blot analysis were used to detect nuclear factor-κB (NF-κB) signaling molecules. Induction of proinflammatory and catabolic mediators by IL-1β stimulation of mouse chondrocytes could be partially blocked by treatment with nobiletin or ammonium pyrrolidine dithiocarbamate (an NF-κB inhibitor). Furthermore, our results indicated that nobiletin exhibited a therapeutic effect through active inhibition of the NF-κB signaling pathway. In a mouse model of OA, injection of nobiletin (20 mg/kg) every 2 days for 8 weeks after surgery inhibited cartilage destruction and synovitis. Taken together, our findings suggest that nobiletin may be a potential therapeutic agent for the treatment of OA

A New Belief Entropy to Measure Uncertainty of Basic Probability Assignments Based on Belief Function and Plausibility Function

How to measure the uncertainty of the basic probability assignment (BPA) function is an open issue in Dempster⁻Shafer (D⁻S) theory. The main work of this paper is to propose a new belief entropy, which is mainly used to measure the uncertainty of BPA. The proposed belief entropy is based on Deng entropy and probability interval consisting of lower and upper probabilities. In addition, under certain conditions, it can be transformed into Shannon entropy. Numerical examples are used to illustrate the efficiency of the new belief entropy in measurement uncertainty

Uncertainty measure of pythagorean fuzzy sets

Pythagorean fuzzy sets (PFS) can better express and handle the uncertainty information and has the more lager representation space. Hence, the reasonable and effective method to measure the uncertainty of PFS can better analyze information. From the view of Dempster-Shafer evidence theory, hesitancy degree can include the two focal elements (member-ship, non-membership). Hence, considering the number of focal elements for hesitancy degree to measure uncertainty is important. In addition, the difference between membership and non-membership degree plays an essential role in uncertainty measure. From the above views, the paper proposed the new uncertainty measure. Based on the new uncertainty measure, cross entropy and divergence of PFS can be presented. In addition, some numerical examples are used to explain the proposed methods by comparing other methods. Finally, the proposed divergence can be used in pattern recognition to verify its effectiveness.ISSN:0922-6389ISSN:1879-831

[In Press] SME participation in cross-border e-commerce as an entry mode to foreign markets : a driver of innovation or not?

In the context of globalization, it is not just large corporates that need to update their technologies and processes to maintain competitiveness. Small-to-medium-sized enterprises (SMEs) also need to innovate if they are to satisfy customer preferences in both domestic and foreign markets. Today, internationalization is considered to be an essential factor in promoting SME innovation. However, it is often difficult for SMEs to innovative with overseas customers because many lack easy access to foreign markets. Compared to other traditional entry modes, cross-border e-commerce, with its low costs and high levels of control, can help to remove some of the barriers to internationalization for SMEs. In turn, it may be that cross-border e-commerce also promotes innovation in these firms. We gathered data on 781 Chinese SMEs to test several hypotheses surrounding this notion. The results of panel regression estimates indicate that cross-border e-commerce does indeed have a direct and positive effect on market innovation. More importantly, it has an indirect and positive impact on technology and process innovation by fully mediating the effects of an entrepreneurial orientation. These results shed light on how cross-border e-commerce impacts SME innovation performance, providing valuable implications for both academics and SME managers

An international study of carbon information asymmetry and independent carbon assurance

Protecting the environment is now a major aspect of corporate social responsibility. However, voluntary carbon disclosure includes private information on future sustainability that external stakeholders cannot easily verify. Drawing on information asymmetry theory, we predict that companies with higher carbon information asymmetry between insiders and outsiders have a greater incentive to voluntarily engage an external party for the independent assurance of their greenhouse gas statements. Using data from the CDP, we test this hypothesis and find that our proxies for carbon information asymmetry (e.g., greenhouse gas emissions, energy structure) are significantly associated with the adoption of carbon assurance. Further analyses suggest that the probability of carbon assurance is enhanced when carbon disclosure is inadequate to diminish information asymmetry. Finally, our sample companies adopted carbon assurance in addition to financial auditing. This highlights the key point that resolving carbon information asymmetry requires carbon assurance, which cannot be substituted for by financial auditing

Research on Side-Channel Analysis Based on Deep Learning with Different Sample Data

With the in-depth integration of deep learning and side-channel analysis (SCA) technology, the security threats faced by embedded devices based on the Internet of Things (IoT) have become increasingly prominent. By building a neural network model as a discriminator, the correlation between the side information leaked by the cryptographic device, the key of the cryptographic algorithm, and other sensitive data can be explored. Then, the security of cryptographic products can be evaluated and analyzed. For the AES-128 cryptographic algorithm, combined with the CW308T-STM32F3 demo board on the ChipWhisperer experimental platform, a Correlation Power Analysis (CPA) is performed using the four most common deep learning methods: the multilayer perceptron (MLP), the convolutional neural network (CNN), the recurrent neural network (RNN), and the long short-term memory network (LSTM) model. The performance of each model is analyzed in turn when the samples are small data sets, sufficient data sets, and data sets of different scales. Finally, each model is comprehensively evaluated by indicators such as classifier accuracy, network loss, training time, and rank of side-channel attacks. The experimental results show that the convolutional neural network CNN classifier has higher accuracy, lower loss, better robustness, stronger generalization ability, and shorter training time. The rank value is 2, that is, only two traces can recover the correct key byte information. The comprehensive performance effect is better