HIV-1 gp41 Fusion Intermediate: A Target for HIV Therapeutics

Human immunodeficiency virus (HIV)-1 infection is initiated by the binding of gp120 envelope glyco-protein to its cell receptor (CD4) and a coreceptor (CXCR4 or CCR5), followed by a series of conformational changes in the gp41 transmembrane subunit. These changes include insertion of fusion peptide into the target cell membrane and association of C-heptad repeat (CHR) peptide with the N-heptad repeat (NHR) trimer, a pre-hairpin fusion intermediate. A stable six-helix bundle core is then formed, bringing the viral envelope and target cell membrane into close proximity for fusion. Peptides derived from the CHR region, such as T20 and C34, inhibit HIV-1 fusion by interacting with the gp41 fusion intermediate. A number of anti-HIV-1 peptides and small molecule compounds targeting the gp41 NHR-trimer have been identified. By combining HIV fusion/entry inhibitors targeting different sites in the gp41 fusion intermediate, a potent synergistic effect takes place, resulting in a potential new therapeutic strategy for the HIV infection/AIDS. Here, we present an overview of the current development of anti-HIV drugs, particularly those targeting the gp41 fusion intermediate

Control Strategy and Simulation of the Regenerative Braking of an Electric Vehicle Based on an Electromechanical Brake

The electromechanical brake (EMB) has very broad prospects for application in the automotive industry, especially in small- and medium-sized vehicles. To extend the endurance range of pure electric vehicles, a regenerative braking control strategy combined with an electromechanical brake model is designed that divides the braking modes according to the braking intensity and controls the regenerative braking force based on fuzzy theory. Considering a front-wheel-drive pure electric vehicle equipped with a floating clamp disc electromechanical brake as the research object, a structural form of electromechanical brake is proposed and a mathematical model of the electromechanical brake is built. Combined with the relevant influencing factors, the regenerative braking force is limited to a certain extent, and the simulation models of the electromechanical brake and the regenerative braking force distribution control strategy are built in MATLAB/Simulink. Co-simulation in MATLAB and AVL CRUISE software is conducted. The simulation results demonstrate that the braking energy recovery rate of the whole vehicle with the fuzzy control strategy put forward in this paper is 28.9% under mild braking and 34.11% under moderate braking. The control method substantially increases the energy utilization rate

Research on Design Optimization and Simulation of Regenerative Braking Control Strategy for Pure Electric Vehicle Based on EMB Systems

The benefits of electromechanical braking (EMB) systems are short response time, high braking efficiency, ease of assembly and easy integration with other electronic control systems. Therefore, a model of an EMB system is developed based on which the braking stability, braking efficiency, and the regenerative braking energy recovery in electric vehicles are investigated. Electric vehicles can effectively increase their driving range by using a rational regenerative braking control strategy. Firstly, a fuzzy regenerative braking control strategy is developed for comparison, and an optimized regenerative braking control strategy is designed based on the NSGA-II algorithm. The technique for order preference by similarity to ideal solution (TOPSIS) is used to comprehensively evaluate the Pareto optimal solution set and to select an optimal solution for the optimization problem. Secondly, a Takagi-Sugeno fuzzy neural network is trained with the optimized discrete data, and then the braking force distribution controller is obtained. Simulink and AVL CRUISE are used to simulate the control strategy. The simulation results for variable intensity braking conditions and cyclic conditions NEDC, FTP75, and CLTC-P show that the optimized control strategy outperforms the fuzzy control strategy in braking stability and braking energy recovery

On Finite Difference Jacobian Computation in Deformable Image Registration

Producing spatial transformations that are diffeomorphic has been a central problem in deformable image registration. As a diffeomorphic transformation should have positive Jacobian determinant $|J|$ everywhere, the number of voxels with $|J|<0$ has been used to test for diffeomorphism and also to measure the irregularity of the transformation. For digital transformations, $|J|$ is commonly approximated using central difference, but this strategy can yield positive $|J|$'s for transformations that are clearly not diffeomorphic -- even at the voxel resolution level. To show this, we first investigate the geometric meaning of different finite difference approximations of $|J|$. We show that to determine diffeomorphism for digital images, use of any individual finite difference approximations of $|J|$ is insufficient. We show that for a 2D transformation, four unique finite difference approximations of $|J|$'s must be positive to ensure the entire domain is invertible and free of folding at the pixel level. We also show that in 3D, ten unique finite differences approximations of $|J|$'s are required to be positive. Our proposed digital diffeomorphism criteria solves several errors inherent in the central difference approximation of $|J|$ and accurately detects non-diffeomorphic digital transformations

An Empirical Study of Untangling Patterns of Two-Class Dependency Cycles

Dependency cycles pose a significant challenge to software quality and maintainability. However, there is limited understanding of how practitioners resolve dependency cycles in real-world scenarios. This paper presents an empirical study investigating the recurring patterns employed by software developers to resolve dependency cycles between two classes in practice. We analyzed the data from 38 open-source projects across different domains and manually inspected hundreds of cycle untangling cases. Our findings reveal that developers tend to employ five recurring patterns to address dependency cycles. The chosen patterns are not only determined by dependency relations between cyclic classes, but also highly related to their design context, i.e., how cyclic classes depend on or are depended by their neighbor classes. Through this empirical study, we also discovered three common counterintuitive solutions developers usually adopted during cycles' handling. These recurring patterns and common counterintuitive solutions observed in dependency cycles' practice can serve as a taxonomy to improve developers' awareness and also be used as learning materials for students in software engineering and inexperienced developers. Our results also suggest that, in addition to considering the internal structure of dependency cycles, automatic tools need to consider the design context of cycles to provide better support for refactoring dependency cycles.Comment: Preprint accepted for publication in Empirical Software Engineering, 202

A Simple Asymmetric Momentum Make SGD Greatest Again

We propose the simplest SGD enhanced method ever, Loss-Controlled Asymmetric Momentum(LCAM), aimed directly at the Saddle Point problem. Compared to the traditional SGD with Momentum, there's no increase in computational demand, yet it outperforms all current optimizers. We use the concepts of weight conjugation and traction effect to explain this phenomenon. We designed experiments to rapidly reduce the learning rate at specified epochs to trap parameters more easily at saddle points. We selected WRN28-10 as the test network and chose cifar10 and cifar100 as test datasets, an identical group to the original paper of WRN and Cosine Annealing Scheduling(CAS). We compared the ability to bypass saddle points of Asymmetric Momentum with different priorities. Finally, using WRN28-10 on Cifar100, we achieved a peak average test accuracy of 80.78\% around 120 epoch. For comparison, the original WRN paper reported 80.75\%, while CAS was at 80.42\%, all at 200 epoch. This means that while potentially increasing accuracy, we use nearly half convergence time. Our demonstration code is available at\\ https://github.com/hakumaicc/Asymmetric-Momentum-LCA