In recent years, the scale of loans in China has been increasing, and so has the credit risk. Yet the credit risk assessment system is still in the initial stage of development. To improve the accuracy of default loan prediction, this paper proposes ISSA-XGBoost model based on an improved way of passing input parameters. The model uses the Sparrow Search Algorithm (SSA) to optimize the parameters of eXtreme Gradient Boosting (XGBoost). Since the search strategy of SSA includes convergence to the origin direction, this paper changes the form of input parameters. In the form, the closer the parameters in SSA are to the origin, the more XGBoost under these parameters can avoid overfitting. SSA searches the optimal with the changed parameter form and outputs feasible solutions. Then, the model transforms their solutions back to the original form and inputs them into XGBoost. After the above processes, SSA can avoid overfitting while searching for optimal solutions. Using the improved SSA to optimize XGBoost, the ISSA-XGBoost loan default prediction model is established. The empirical result shows that the model outperforms SSA-XGBoost under the four metrics: ACC, AUC, KS, and BS. And it is significantly better than that of XGBoost optimized by Particle Swarm Optimization (PSO-XGBoost). At the same time, compared with SSA-XGBoost, the AUC score difference between the training set and the test set of ISSA-XGBoost is smaller, which indicates that ISSA-XGBoost can better avoid overfitting.
Nyberg and Ruppel first proposed a signature scheme with message recovery based on DSA in 1993, and the authenticated encryption scheme is a special application of their scheme. Afterward, there are many papers proposed about the authenticated encryption schemes. The signature scheme can reduce the transmitted cost, because the message has been contained in the signature of the message and the signer does not necessary to send the receiver the message and the signature. The scheme is very suitable for the key agreement application, because a key is a small amount of a message. In order to comprehend and interpret the authenticated encryption schemes overall, we discuss the evolution and the existed problems of authenticated encryption schemes.
Understanding contents in social networks by inferring high-quality latent topics from short texts is a significant task in social analysis, which is challenging because social network contents are usually extremely short, noisy and full of informal vocabularies. Due to the lack of sufficient word co-occurrence instances, well-known topic modeling methods such as LDA and LSA cannot uncover high-quality topic structures. Existing research works seek to pool short texts from social networks into pseudo documents or utilize the explicit relations among these short texts such as hashtags in tweets to make classic topic modeling methods work. In this paper, we explore this problem by proposing a topic model for noisy short texts with multiple relations called MRTM (Multiple Relational Topic Modeling). MRTM exploits both explicit and implicit relations by introducing a document-attribute distribution and a two-step random sampling strategy. Extensive experiments, compared with the state-of-the-art topic modeling approaches, demonstrate that MRTM can alleviate the word co-occurrence sparsity and uncover high-quality latent topics from noisy short texts.
Although mitochondrial fission has been reported to increase proliferative capacity and collagen production, it can also contribute to mitochondrial impairment, which is detrimental to cell survival. The aim of the present study was to investigate the role of mitochondrial fission in cardiac fibroblasts (CF) activation and explore the mechanisms involved in the maintenance of mitochondrial health under this condition. For this, changes in the levels of mitochondrial fission/fusion-related proteins were assessed in transforming growth factor beta 1 (TGF-β1)-activated CF, whereas the role of mitochondrial fission during this process was also elucidated, as were the underlying mechanisms. The interaction between mitochondrial fission and mitophagy, the main defense mechanism against mitochondrial impairment, was also explored. The results showed that the mitochondria in TGF-β1-treated CF were noticeably more fragmented than those of controls. The expression of several mitochondrial fission-related proteins was markedly upregulated, and the levels of fusion-related proteins were also altered, but to a lesser extent. Inhibiting mitochondrial fission resulted in a marked attenuation of TGF-β1-induced CF activation. The TGF-β1-induced increase in glycolysis was greatly suppressed in the presence of a mitochondrial inhibitor, whereas a glycolysis-specific antagonist exerted little additional antifibrotic effects. TGF-β1 treatment increased cellular levels of reactive oxygen species (ROS) and triggered mitophagy, but this effect was reversed following the application of ROS scavengers. For the signals mediating mitophagy, the expression of Pink1, but not Bnip3l/Nix or Fundc1, exhibited the most significant changes, which could be counteracted by treatment with a mitochondrial fission inhibitor. Pink1 knockdown suppressed CF activation and mitochondrial fission, which was accompanied by increased CF apoptosis. In conclusion, mitochondrial fission resulted in increased glycolysis and played a crucial role in CF activation. Moreover, mitochondrial fission promoted reactive oxygen species (ROS) production, leading to mitophagy and the consequent degradation of the impaired mitochondria, thus promoting CF survival and maintaining their activation.
User authentication is a most important protocol in a distribution network. Those authentication schemes have been proposed for many years, and a one-time password authentication scheme is one of them. In 2004, Lin and Chang proposed a one-time password authentication scheme which is free from replay attacks, server spoofing attacks, off-line dictionary attacks, active attacks, and revelation of message contents. However, their scheme will suffer from guessing attacks which is proposed by us in this paper.
Objective: To explore the role of glycolysis in cardiac fibroblast (CF) activation and cardiac fibrosis after myocardial infarction (MI). Method:In vivo: 2-Deoxy-D-glucose (2-DG), a glycolysis inhibitor, was injected into the abdominal cavity of the MI or sham mice every day. On the 28th day, cardiac function was measured by ultrasonic cardiography, and the hearts were harvested. Masson staining and immunofluorescence (IF) were used to evaluate the fibrosis area, and western blot was used to identify the glycolytic level. In vitro, we isolated the CF from the sham, MI and MI with 2-DG treatment mice, and we also activated normal CF with transforming growth factor-β1 (TGF-β1) and block glycolysis with 2-DG. We then detected the glycolytic proteins, fibrotic proteins, and the concentrations of lactate and glucose in the culture medium. At last, we further detected the fibrotic and glycolytic markers in human fibrotic and non-fibrotic heart tissues with masson staining, IF and western blot. Result: More collagen and glycolytic protein expressions were observed in the MI mice hearts. The mortality increased when mice were treated with 2-DG (100 mg/kg/d) after the MI surgery (Log-rank test, P < 0.05). When the dosage of 2-DG declined to 50 mg/kg/d, and the treatment was started on the 4th day after MI, no statistical difference of mortality between the two groups was observed (Log-rank test, P = 0.98). The collagen volume fraction was smaller and the fluorescence signal of α-smooth muscle actin (α-SMA) was weaker in mice treated with 2-DG than PBS. In vitro, 2-DG could significantly inhibit the increased expression of both the glycolytic and fibrotic proteins in the activated CF. Conclusion: Cardiac fibrosis is along with the enhancement of CF activation and glycolysis. Glycolysis inhibition can alleviate cardiac fibroblast activation and cardiac fibrosis after myocardial infarction.
There are two applications in digital signature schemes with message recovery based on a discrete logarithm problem. One is an authenticated encryption scheme, and the other is a key agreement scheme. Considering that the cryptographic assumptions will be broken in the future, the digital signature scheme with message recovery should also be designed based on two assumptions. Besides the digital signature scheme with message recovery, the authenticated encryption scheme with message linkages should also be redesigned to deal with the problem when any one of the factoring and discrete logarithm assumptions is broken. In this paper, we propose a digital signature with message recovery based on factoring and discrete logarithm and show that the scheme is secure. In comparison with Zhang ET AL.'s scheme, our proposed scheme is the most efficient one in terms of communication cost and computation complexity.
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