Reminder duration determines threat memory modification in humans

Memory reminders can return a memory into an unstable state such that it will decay unless actively restabilized into long-term memory through reconsolidation. Exposure to a memory reminder, however, does not always lead to destabilization. The 'trace dominance' principle posits that the extent of exposure to memory reminders governs memory susceptibility to disruption. Here, we provide a first systematic investigation of reminder duration effects on threat memory modification in humans. Reminder duration was parametrically varied across 155 participants in a three-day protocol. We found that short reminders (1 s and 4 s) made the memory prone to interference from post-retrieval extinction, suggesting that the memory had been updated. In contrast, no reminder or long reminders (30 s and 3 min) made the memory resistant to such interference, and robustly return. Reminder duration therefore influences memory stability and may be a critical determinant of therapeutic efficacy

Author Correction: Reminder duration determines threat memory modification in humans

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Automatic Moving Object Segmentation for Freely Moving Cameras

This paper proposes a new moving object segmentation algorithm for freely moving cameras which is very common for the outdoor surveillance system, the car build-in surveillance system, and the robot navigation system. A two-layer based affine transformation model optimization method is proposed for camera compensation purpose, where the outer layer iteration is used to filter the non-background feature points, and the inner layer iteration is used to estimate a refined affine model based on the RANSAC method. Then the feature points are classified into foreground and background according to the detected motion information. A geodesic based graph cut algorithm is then employed to extract the moving foreground based on the classified features. Unlike the existing global optimization or the long term feature point tracking based method, our algorithm only performs on two successive frames to segment the moving foreground, which makes it suitable for the online video processing applications. The experiment results demonstrate the effectiveness of our algorithm in both of the high accuracy and the fast speed

Research on Railway Information Technology System Based on Internet of Things

Internet of things (IOT) is considered to be a new generation of information technology development direction. Its application in railway information construction has broad prospects. This paper analyzed railway information technology concept and its composition in the level of function. Through the analysis of the internal and external driving force of railway information system Evolution, the direction and path of railway information system evolution is presented, and the dynamic model of railway information system evolution is established. And according to China's railway information system construction and planning situation, it designed a plan of railway information system construction under the IOT environment. Finally it constructed a railway information technology system which based on the IOT technology, and provided a theoretical support to rail-way information construction, as well as put forward the prospects of different railway businesses' information development with the IOT technology

Gender Differences in PTSD: Susceptibility and Resilience

Posttraumatic stress disorder (PTSD) is anxiety disorder that has been estimated to affect individuals who are exposed to traumatic events. Women are diagnosed with PTSD approximately twice as often as men. In this review, we outline the evidence of gender differences related to PTSD, and the factors of resilience and susceptibility differ between men and women

Optimizing inland port scale and function decisions: A bilevel programming approach

With the implementation of the Belt and Road Initiative, the inland ports planning is receiving more and more attention. In this work, we aim to determine the scale and function of different potential inland ports in a certain region while considering the cargo flow allocation schemes for the inland ports and seaports in cross-border trade. Unlike previous studies, we consider the dynamic interaction between local government and manufacturing enterprises in the inland port planning process. Based on this, we formulate a bilevel programming model for the considered inland port planning problem, where the upper-level focuses on the local government and the lower-level concentrates on the manufacturing enterprise. To solve the proposed model, we develop a hybrid heuristic algorithm by combining a genetic algorithm and an exact solution method. Furthermore, we conduct a case study of the inland ports planning for the Huaihai Economic Zone in China to verify the applicability of the proposed model and algorithm. The computational results demonstrate that the proposed optimization approach can effectively increase the cross-border transportation market share of inland ports within a limited investment amount and reduce the competition among these inland ports. Our case study also provides valuable management insights on inland port planning in terms of manufacturing enterprises weights, investment limit amount, scale effect, and cargo value weights

Brittleness Evolution Model of the Supply Chain Network Based on Adaptive Agent Graph Theory under the COVID-19 Pandemic

The triggering of supply chain brittleness has a significant impact on enterprise benefits under attack from the COVID-19 pandemic. The complexity of the supply chain system, the uncertainty of the COVID-19 pandemic, and demand uncertainty have made the triggering and propagation of supply chain brittleness complicated. In this study, a brittleness evolution model based on adaptive agent graph theory has been constructed. The parameters of brittleness evolution, including brittleness entropy and the vertex state value, have been quantitatively designed, and the brittleness evolution model in which the adaptability of nodes is considered and is not considered is constructed. A simulation algorithm based on the integrated scheduling model of the supply chain has been established. Finally, the practicability of the proposed model and algorithm is demonstrated via a case study of an electronic supply chain network. The results indicate that the proposed model and algorithm can effectively analyze the brittleness evolution law of the supply chain under the impact of the COVID-19 pandemic, including the evolution law of the vertex state, the brittleness entropy of the vertex, the global entropy of brittleness, the seasonal evolution law of the supply chain brittleness, and the evolution law of the brittleness behavior

Procurement Strategy with Backup Sourcing under Stochastic Supply Risk

Supply risk can have a negative impact on a manufacturer’s performance. Backup sourcing is one of the most commonly used strategies to mitigate the adverse consequences of supply risks. In this paper, we study a procurement strategy with backup sourcing when a manufacturer faces stochastic supply risk and demand. The optimal decisions of the players involved are investigated theoretically using the game theoretic framework, and the impacts of the key parameters, such as wholesale prices and the risk probability, are assessed numerically under supply information symmetry and asymmetry. The results illustrate that the reservation price provided by the backup supplier varies greatly under different information-sharing conditions. Reservation quantity is negatively correlated with the reservation price, which is affected by the risk probability, wholesale prices, and marginal cost of the backup supplier. We also show that given the same wholesale prices, the potential supply risk has a substantial impact on the manufacturer’s expected profit, and the performance of the manufacturer under asymmetrical supply information is not always better than that under symmetrical information. In addition, we also discuss the impact of wholesale prices on reservation price and participants’ profits based on numerical examples. The research enriches the understanding of a procurement strategy under stochastic supply risk, and the conclusions have certain management significance