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Sustainable cooperation between schools and enterprises is crucial to maintaining a dynamic balance between the supply and demand of talents and driving the advancement of new quality productive forces. As a result, facilitating school–enterprise cooperation has become an important concern in many countries. However, there remains a gap in understanding the approaches taken by central and local governments to foster such cooperation through the lens of evolutionary game theory. Therefore, this paper develops a quadrilateral evolutionary game model involving schools, enterprises, the central government, and local governments by building the payoff matrix and calculating expected payoffs of different strategies to analyze the conditions under which governments can effectively promote school–enterprise cooperation. Our findings indicate that benefit is a decisive factor that affects the strategies of all parties. Increasing incentives and penalties from the central government and local governments can stimulate school–enterprise cooperation, but these measures are not sustainable in the long term. Additionally, the impact of the central government's incentives and penalties on local governments in promoting school–enterprise cooperation is limited. Enhancing policy efficacy and the practical outcomes of school–enterprise cooperation is essential, which not only strengthens the bond between schools and enterprises but also ensures deep and enduring governmental involvement. Some suggestions are put forward at the end. [ABSTRACT FROM AUTHOR]

Three-dimensional human pose estimation focuses on generating 3D pose sequences from 2D videos. It has enormous potential in the fields of human–robot interaction, remote sensing, virtual reality, and computer vision. Existing excellent methods primarily focus on exploring spatial or temporal encoding to achieve 3D pose inference. However, various architectures exploit the independent effects of spatial and temporal cues on 3D pose estimation, while neglecting the spatial–temporal synergistic influence. To address this issue, this paper proposes a novel 3D pose estimation method with a dual-adaptive spatial–temporal former (DASTFormer) and additional supervised training. The DASTFormer contains attention-adaptive (AtA) and pure-adaptive (PuA) modes, which will enhance pose inference from 2D to 3D by adaptively learning spatial–temporal effects, considering both their cooperative and independent influences. In addition, an additional supervised training with batch variance loss is proposed in this work. Different from common training strategy, a two-round parameter update is conducted on the same batch data. Not only can it better explore the potential relationship between spatial–temporal encoding and 3D poses, but it can also alleviate the batch size limitations imposed by graphics cards on transformer-based frameworks. Extensive experimental results show that the proposed method significantly outperforms most state-of-the-art approaches on Human3.6 and HumanEVA datasets. [ABSTRACT FROM AUTHOR]

ZnO-based memristors are considered to be promising candidates in neuromorphic computing because of their nonvolatile resistive switching characteristics. Biological synaptic plasticity processes such as long-term potentiation (LTP) and long-term depression (LTD) require the application of driving voltages with different polarity, which inescapably leads to an increase in the operational costs of memristor circuits. In this study, we have successfully introduced a strategic innovation by incorporating a TiO2 thin layer, thereby achieving unipolar-enhanced bilayer and unipolar-weakened monolayer memristors. In the context of monolayer memristors, the unipolar weakening mechanism primarily arises from the thermal disruption of conduction filaments (CFs) caused by oxygen vacancies. Additionally, the incorporation of a thin TiO2 layer on the ZnO layer confines Joule heat within the TiO2 film, inhibiting the promotion of oxygen vacancy diffusion and preventing the occurrence of ZnO CF fracture. Moreover, a two transistor–two memristor (2T2R) unit based on the given memristors is introduced to achieve LTP and LTD characteristics under unipolar voltage pulse excitation. Simulation results show that the 2T2R structure unit can achieve an approximately 50% reduction in time and power consumption during the weight update process. [ABSTRACT FROM AUTHOR]

Metal oxide memristors are highly desirable for bionic synaptic applications. Recently, negative differential resistance (NDR) effects have been found in the resistance switching (RS) region for some oxide memristors, which provide a basis for multifunctional devices. Here, the mechanisms of the coexistence of NDR and RS behaviors in a W/WOx/Ti memristor are analyzed. The WOx-based memristor shows good synaptic plasticity behavior with a bipolar RS effect, and the NDR behavior during reverse voltage scanning is due to the dual role of conductive filaments (CFs) and trap-assisted transport (TAT) mechanisms. As the number of scans increases, fracture of the CFs is accelerated, while oxygen vacancy concentrations are reduced. The TAT mechanism is not enough to assist the electronic transition, thus leading to change in the NDR effect. In addition, replacing WOx with Al2O3 can lead to the disappearance of the NDR behavior, and the RS effect is switched from digital to analog type. This work provides a promising pathway to understand the coexistence mechanisms of NDR and RS effects in metal oxide memristors and promotes their application in bifunctional devices. [ABSTRACT FROM AUTHOR]