Global dynamics of a piece-wise epidemic model with switching vaccination strategy

A piece-wise epidemic model of a switching vaccination program, implemented once the number of people exposed to a disease-causing virus reaches a critical level, is proposed. In addition, variation or uncertainties in interventions are examined with a perturbed system version of the model. We also analyzed the global dynamic behaviors of both the original piece-wise system and the perturbed version theoretically, using generalized Jacobian theory, Lyapunov constants for a non-smooth vector field and a generalization of Dulac's criterion. The main results show that, as the critical value varies, there are three possibilities for stabilization of the piece-wise system: (i) at the disease-free equilibrium; (ii) at the endemic states for the two subsystems or (iii) at a generalized equilibrium which is a novel global attractor for non-smooth systems. The perturbed system exhibits new global attractors including a pseudo-focus of parabolic-parabolic (PP) type, a pseudo-equilibrium and a crossing cycle surrounding a sliding mode region. Our findings demonstrate that an infectious disease can be eradicated either by increasing the vaccination rate or by stabilizing the number of infected individuals at a previously given level, conditional upon a suitable critical level and the parameter values

The Future of Generic Biologics: Should the United States “Follow-On” the European Pathway?

The United States is embarking on a biotechnology drug revolution. In the last few decades, biotech drugs have saved millions of lives, and the market for these miracle cures continues to grow at an astronomical rate. Unfortunately, as the market for biotech drugs is skyrocketing, drug prices are following suit. As Congress strives to make these new drugs more affordable, it must not ignore significant safety concerns unique to these revolutionary therapies. Congress should follow the lead of the European Union to create an accessible pathway for generic forms of biotech drugs that includes strict regulatory measures to ensure drug safety and efficacy

Design and Simulation Analysis of Bolt Group Connection of BS-Type Flange Cast Steel Right-Angle Sea Valve

BS type flanged cast steel right-angle sea valve is an important valve used to stop the backflow of medium in the ship pipeline system. The valve and the pipeline are connected by a bolt connection. To ensure the reliability of the bolt connection, the theoretical calculation and finite element method are used to verify the reliability of the design of bolt connection. The theoretical result and the result of finite element analysis (using ANSYS) show that the largest stress on the bolt is located in the middle of the bolt. This paper provides solutions for the verifying the design of bolt connection in valves based on comparing the results of theoretical calculation and finite element analysis

Design and Simulation Analysis of Bolt Group Connection of BS-Type Flange Cast Steel Right-Angle Sea Valve

BS type flanged cast steel right-angle sea valve is an important valve used to stop the backflow of medium in the ship pipeline system. The valve and the pipeline are connected by a bolt connection. To ensure the reliability of the bolt connection, the theoretical calculation and finite element method are used to verify the reliability of the design of bolt connection. The theoretical result and the result of finite element analysis (using ANSYS) show that the largest stress on the bolt is located in the middle of the bolt. This paper provides solutions for the verifying the design of bolt connection in valves based on comparing the results of theoretical calculation and finite element analysis

MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks

Spiking Neural Network (SNN) is considered more biologically realistic and power-efficient as it imitates the fundamental mechanism of the human brain. Recently, backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks have achieved good performance. However, bio-interpretability is partially neglected in those BP-based algorithms. Toward bio-plausible BP-based SNNs, we consider three properties in modeling spike activities: Multiplicity, Adaptability, and Plasticity (MAP). In terms of multiplicity, we propose a Multiple-Spike Pattern (MSP) with multiple spike transmission to strengthen model robustness in discrete time-iteration. To realize adaptability, we adopt Spike Frequency Adaption (SFA) under MSP to decrease spike activities for improved efficiency. For plasticity, we propose a trainable convolutional synapse that models spike response current to enhance the diversity of spiking neurons for temporal feature extraction. The proposed SNN model achieves competitive performances on neuromorphic datasets: N-MNIST and SHD. Furthermore, experimental results demonstrate that the proposed three aspects are significant to iterative robustness, spike efficiency, and temporal feature extraction capability of spike activities. In summary, this work proposes a feasible scheme for bio-inspired spike activities with MAP, offering a new neuromorphic perspective to embed biological characteristics into spiking neural networks

Tanshinone IIA inhibits exosome-induced cardiomyocyte pyroptosis through NLRP3/caspase 1 pathway

Purpose: To investigate the effect of Salvia miltiorrhiza, a traditional Chinese medicinal plant, on exosome-induced cardiomyocyte pyroptosis. Methods: Pyroptosis was induced in human AC cells using exosomes. Then, the effect of Danshen (dried roots of S. miltiorrhiza) on exosome-induced pyroptosis was determined using flow cytometry. The expressions of pro-inflammatory cytokines were measured by enzyme-linked immunosorbent assay (ELISA), while protein levels of cytokines were assayed by Western blotting. Results: Tanshinone IIA (Tan IIA), the bioactive molecule in Danshen, inhibited cardiomyocyte pyroptosis by significantly reducing the expressions of proinflammatory cytokines (p < 0.001). Thus, Tan IIA reduced pyroptosis induced by cardiomyocyte-derived exosome via inhibition of the expression of NLRP3 inflammasome in human AC cells. Conclusion: This study has identified a potential mechanism through which Danshen functions to prevent cardiac diseases. It involves, at least in part, the inhibition of pyroptosis in cardiomyocytes. Thus, tanshinone IIA may be a pharmacologically beneficial cardioprotective compound, especially when used against heart failure

Vertical Management Reform of Environmental Protection System and Air Quality Improvement: Empirical Test Based on RDD

As a major institutional innovation in the field of environmental protection system, the supervision and law enforcement of environmental protection system in China has been transformed from the jurisdictional management system to a vertical management system, and its effect on improving air quality is a hot issue to be tested urgently. This paper uses regression discontinuity design model (RDD) to test the daily air quality of 321 prefecture-level cities from September 2016 to December 2019. The results show that the vertical management reform of environmental protection system can significantly improve the air quality, and has a significant long-term inhibitory and sustainable effect on air pollution. Furthermore, a series of robustness tests also further prove the reliability of the results. As a conclusion, this paper provides a basis for decision-making in deepening the vertical management reform of environmental protection system

Fruit Classification Based on Improved YOLOv7 Algorithm

With the rapid development of technology and advancements, unmanned vending machines have emerged as the primary contactless retail method. The efficient and accurate implementation of automated identification technology for agricultural products in their distribution and sales has become an urgent problem that needs to be addressed. This article presents an improved YOLOv7 (You Only Look Once) algorithm for fruit detection in complex environments. By replacing the 3×3 convolutions in the backbone of YOLOv7 with Deformable ConvNet v2(DCNv2), the recognition accuracy and efficiency of fruit classification in YOLOv7 are significantly enhanced. The results indicate that the overall recognition accuracy of this system for ten types of fruits is 98.3%, showcasing its high precision and stability