PatchRNN: A Deep Learning-Based System for Security Patch Identification

With the increasing usage of open-source software (OSS) components, vulnerabilities embedded within them are propagated to a huge number of underlying applications. In practice, the timely application of security patches in downstream software is challenging. The main reason is that such patches do not explicitly indicate their security impacts in the documentation, which would be difficult to recognize for software maintainers and users. However, attackers can still identify these "secret" security patches by analyzing the source code and generate corresponding exploits to compromise not only unpatched versions of the current software, but also other similar software packages that may contain the same vulnerability due to code cloning or similar design/implementation logic. Therefore, it is critical to identify these secret security patches to enable timely fixes. To this end, we propose a deep learning-based defense system called PatchRNN to automatically identify secret security patches in OSS. Besides considering descriptive keywords in the commit message (i.e., at the text level), we leverage both syntactic and semantic features at the source-code level. To evaluate the performance of our system, we apply it on a large-scale real-world patch dataset and conduct a case study on a popular open-source web server software - NGINX. Experimental results show that the PatchRNN can successfully detect secret security patches with a low false positive rate

New haptic syringe device for virtual angiography training

Angiography is an important minimally invasive diagnostic procedure in endovascular interventions. Effective training for the procedure is expensive, time consuming and resource demanding. Realistic simulation has become a viable solution to addressing such challenges. However, much of previous work has been focused on software issues. In this paper, we present a novel hardware system-an interactive syringe device with haptics as an add-on hardware component to 3D VR angiography training simulator. Connected to a realistic 3D computer simulation environment, the hardware component provides injection haptic feedback effects for medical training. First, we present the design of corresponding novel electronic units consisting of many design modules. Second, we describe a curve fitting method to estimate injection dosage and injection speed of the contrast media based on voltage variation between the potentiometer to increase the realism of the simulated training. A stepper motor control method is developed to imitate the coronary pressure for force feedback of syringe. Experimental results show that the validity and feasibility of the new haptic syringe device for achieving good diffusion effects of contrast media in the simulation system. A user study experiment with medical doctors to assess the efficacy and realism of proposed simulator shows good outcomes

Establishing a Credit Risk Evaluation System for SMEs Using the Soft Voting Fusion Model

In China, SMEs are facing financing difficulties, and commercial banks and financial institutions are the main financing channels for SMEs. Thus, a reasonable and efficient credit risk assessment system is important for credit markets. Based on traditional statistical methods and AI technology, a soft voting fusion model, which incorporates logistic regression, support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), is constructed to improve the predictive accuracy of SMEs’ credit risk. To verify the feasibility and effectiveness of the proposed model, we use data from 123 SMEs nationwide that worked with a Chinese bank from 2016 to 2020, including financial information and default records. The results show that the accuracy of the soft voting fusion model is higher than that of a single machine learning (ML) algorithm, which provides a theoretical basis for the government to control credit risk in the future and offers important references for banks to make credit decisions

Decomposition–Coordination of Double-Layer MPC for Constrained Systems

Large-scale industrial processes usually adopt centralized control and optimization methods. However, with the growth of the scale of industrial processes leading to increasing computational complexity, the online optimization capability of the double-layer model predictive control algorithm is challenged, exacerbating the difficulty of the widespread implementation of this algorithm in the industry. This paper proposes a distributed double-layer model predictive control algorithm based on dual decomposition for multivariate constrained systems to reduce the computational complexity of process control. Firstly, to solve the problem that the original dual decomposition method does not apply to constrained systems, two improved dual decomposition model prediction control methods are proposed: the dual decomposition method based on the quadratic programming in the subsystem and the dual decomposition method based on constraint zones, respectively. It is proved that the latter will certainly converge to the constraint boundaries with appropriate convergence factors for the controlled variables. The online optimization ability of the proposed two methods is compared in discussion and simulation, concluding that the dual decomposition method based on the constraint zones exhibits superior online optimization ability. Further, a distributed double-layer model predictive control algorithm with dual decomposition based on constraint zones is proposed. Different from the objective function of the original dual decomposition model predictive control, the proposed algorithm’s dynamic control-layer objective function simultaneously tracks the steady-state optimization values of the controlled and manipulated variables, giving the optimal solution formulation of the optimization problem consisting of this objective function and the constraints. The algorithm proposed in this paper achieves the control goals while significantly reducing the computational complexity and has research significance for promoting the industrial implementation of double-layer model predictive control

Toxicity Effects of Combined Mixtures of BDE-47 and Nickel on the Microalgae Phaeodactylum tricornutum (Bacillariophyceae)

Nickel and 2,2’,4,4’-tetrabromodiphenyl ether (BDE-47) are two environmental pollutants commonly and simultaneously present in aquatic systems. Nickel and BDE-47 are individually toxic to various aquatic organisms. However, their toxicity mechanisms are species-dependent, and the toxic effects of combined mixtures of BDE-47 and nickel have not yet been investigated. The present study investigated the toxic effects of combined mixtures of BDE-47 and nickel in the diatom Phaeodactylum tricornutum. BDE-47 and nickel mixtures significantly decreased cell abundance and photosynthetic efficiency, while these cells’ reactive oxygen species (ROS) production significantly increased. The EC50-72 h for BDE-47 and mixtures of BDE-47 and nickel were 16.46 ± 0.93 and 1.35 ± 0.06 mg/L, respectively. Thus, combined mixtures of the two pollutants enhance their toxic effects. Interactions between BDE-47 and nickel were evaluated, revealing synergistic interactions that contributed to toxicity in P. tricornutum. Moreover, transcriptomic analyses revealed photosynthesis, nitrogen metabolism, the biosynthesis of amino acids, the biosynthesis of secondary metabolites, oxoacid metabolism, organic acid metabolism, carboxylic acid metabolism, and oxidation-reduction processes were considerably affected by the mixtures. This study provides evidence for the mechanisms of toxicity from combined BDE-47 and nickel exposure while also improving our understanding of the ecological risks of toxic chemicals on microalgae

Porous bowl-shaped VS 2 nanosheets/graphene composite for high-rate lithium-ion storage

Two-dimensional (2D) layered vanadium disulfide (VS2) is a promising anode material for lithium ion batteries (LIBs) due to the high theoretical capacity. However, it remains a challenge to synthesize monodispersed ultrathin VS2 nanosheets to realize the full potential. Herein, a novel solvothermal method has been developed to prepare the monodispersed bowl-shaped NH3-inserted VS2 nanosheets (VS2). The formation of such a unique structure is caused by the blocked growth of (001) or (002) crystal planes in combination with a ripening process driven by the thermodynamics. The annealing treatment in Ar/H2 creates porous monodispersed VS2 (H-VS2), which is subsequently integrated with graphene oxide to form porous monodispersed H-VS2/rGO composite coupled with a reduction process. As an anode material for LIBs, H-VS2/rGO delivers superior rate performance and longer cycle stability: a high average capacity of 868/525 mAh g−1 at a current density of 1/10 A g−1; a reversible capacity of 1177/889 mAh g−1 after 150/500 cycles at 0.2/1 A g−1. Such excellent electrochemical performance may be attributed to the increased active sites available for lithium storage, the alleviated volume variations and the shortened Li-ion diffusion induced from the porous structure with large specific surface area, as well as the protective effect from graphene nanosheets

A prediction model for water breakthrough time in high-sulfur gas reservoir with edge water

Abstract The water coning phenomenon leads to decrease the wellhead pressure with moving of water into gas production zone, which is regarded as one of most serious problems during gas production. It has been shown that water breakthrough time plays an important role in analyzing the water coning phenomenon and production of water. However, the existing prediction models of water breakthrough time are very scarce and need to be discussed. In this work, a novel model for water breakthrough time in high-sulfur gas reservoir with edge water is developed based on flow law and sulfur precipitation model in porous media. The effect of irreducible water saturation, residual gas saturation, and the distance between gas well and edge water, sulfur saturation and gas non-Darcy flow on water breakthrough time was involved in this model. The validity of the proposed model is verified by comparing the existing models available. A good trend is found between them. In addition, the influence of the distance between gas well and edge water, sulfur saturation and gas non-Darcy flow on water breakthrough time was detail discussed further

A Flexible Hot-Film Sensor Array for Underwater Shear Stress and Transition Measurement

A flexible hot-film sensor array for wall shear stress, flow separation, and transition measurement has been fabricated and implemented in experiments. Parylene C waterproof layer is vapor phase deposited to encapsulate the sensor. Experimental studies of shear stress and flow transition on a flat plate have been undertaken in a water tunnel with the sensor array. Compared with the shear stress derived from velocity profile and empirical formulas, the measuring errors of the hot-film sensors are less than 5%. In addition, boundary layer transition of the flat plate has also been detected successfully. Ensemble-averaged mean, normalized root mean square, and power spectra of the sensor output voltage indicate that the Reynolds number when transition begins at where the sensor array located is 1.82 × 105, 50% intermittency transition is 2.52 × 105, and transition finishes is 3.96 × 105. These results have a good agreement with the transition Reynolds numbers, as measured by the Laser Doppler Velocimetry (LDV) system

Plasticity enhancement in pure magnesium achieved based on initial twin orientation regulation

© 2022 Elsevier B.V.In the short communication, the ductility of pure magnesium was enhanced about 3 times at room temperature compared with the initial material based on the proposed concept of shear strain-induced twin orientation regulation (SITOR). The initial tension twin orientation inclines about 30° to the TD-ND plane which is regulated by the introduced shear deformation so that a larger Schmid factor of basal slip is achieved. Due to the promotion of basal slip, the plasticity of pure Mg is improved obviously.N