Abstract ：

The propagation of subthreshold signals is an important part of information exchange in neural systems, but the propagation mechanism of subthreshold signals in neural networks and the influence of internal and external factors on propagation are still unclear. Based on this, firstly, a mathematical model for the transmission of subthreshold excitatory postsynaptic current (EPSC) signals in a multi-layer feedforward neural network is constructed. Each element is a HH neuron model. To simulate the connections between neurons in different layers of the cerebral cortex more closely, a multi-factor WS small-world network (MF-WS) is proposed, which can form inter-layer differences by adjusting multiple factors. Then, according to the influence factors of MF-WS small-world network formation, explore its influence on EPSC signal transmission. Through research, the increase of synaptic coupling strength W, the number of neighbors K and the proportion of excitatory neurons R are conducive to the propagation of EPSC signals. With the increase of the respective weights of multiple factors, the optimal noise intensity conducive to the propagation of EPSC signals decreases. Finally, a multi-factor-consistent BP neural network (MF-C-BP) is proposed to optimize the synaptic coupling strength and connection mode between layers, which increases the consistency of the neural network pulse discharge sequence after the EPSC signal transmission to real correlation (± 0.30 - ± 0.50) or significant correlation (± 0.50 - ± 0.80). By studying the propagation mechanism of EPSC signal and the consistency of pulse discharge, a more potential mechanism for EPSC signal coding in neural network is provided. © 2024 SPIE

Keyword ：

Photons Hadrons Neurons Multilayer neural networks Network coding

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This paper proposes a novel numerical algorithm to solve frictional contact problems in twophase porous media, accounting for the large deformation and interface fluid flow, within the framework of the Stable Node-based Smoothed Particle Finite Element Method (SNS-PFEM). The proposed approach builds on our previous work that was only designed for single-phase large deformation contact problems. Within this work, the hydro-mechanical coupling system is discretized using equal-order interpolation, with a polynomial pressure projection method to eliminate the pore pressure instability. Surface-to-surface discretization is then applied to formulate the contact constraint of the two-phase porous medium. Using the dual Lagrange multiplier approach, a coordinate transformation is introduced to enforce the contact constraint of the solid phase. This transformation is subsequently utilized to develop a new interface fluid element, which serves as a tool to model the fluid exchange behaviour between porous media and contact gaps. Different from existing interface fluid elements, the proposed element is constructed based on the contact algorithm, thereby enabling it to handle non-conforming interfaces and tackle challenges associated with large sliding problems. Furthermore, the proposed method can maintain a well-conditioned system matrix throughout the computation process. These distinctive attributes significantly enhance the flexibility of numerical modelling. Finally, the accuracy and performance of our method are verified through four numerical examples. The results show that the proposed method can effectively simulate various geotechnical problems, including multilayer soil consolidation, fluid-soil-structure interaction, and geological interface-controlled slope failure.

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Hydro-mechanical coupling Finite sliding contact Large deformation Geotechnical engineering Interface fluid flow Dual Lagrange multiplier

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The study analyzed and compared the effects of thermal-fluid-solid coupling dynamic boundary conditions and traditional fixed -boundary conditions on the distribution of the temperature field under fires. The feasibility of simulating the temperature field distribution was confirmed by using thermal-fluid-solid coupling dynamic boundary conditions. Then, the traditional temperature field analysis methods were corrected by including a flow -based heat exchange coefficient, and the feasibility of this approach was also confirmed. The fire temperature field in a rectangular air -supported membrane structure was analyzed through parameterization. The fire temperature field model of the air -supported membrane structure was established using temperature field data fitting. Furthermore, the study explored the high -temperature material properties of P -type membranes and analyzed and compared the temperature field of the air -supported membrane structure with time -varying mechanical properties of the membrane material to that without time -varying properties.

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Air -supported membrane structure Fire temperature fields Corrected fixed boundary method Thermal-fluid-solid coupling Time -varying of membrane material

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The phase separation dynamics in graphitic anodes significantly affects lithium plating propensity, which is the major degradation mechanism that impairs the safety and fast charge capabilities of automotive lithium-ion batteries. In this study, we present comprehensive investigation employing operando high-resolution optical microscopy combined with non-equilibrium thermodynamics implemented in a multi-dimensional (1D+1D to 3D) phase-field modeling framework to reveal the rate-dependent spatial dynamics of phase separation and plating in graphite electrodes. Here we visualize and provide mechanistic understanding of the multistage phase separation, plating, inter/intra-particle lithium exchange and plated lithium back-intercalation phenomena. A strong dependence of intra-particle lithiation heterogeneity on the particle size, shape, orientation, surface condition and C-rate at the particle level is observed, which leads to early onset of plating spatially resolved by a 3D image-based phase-field model. Moreover, we highlight the distinct relaxation processes at different state-of-charges (SOCs), wherein thermodynamically unstable graphite particles undergo a drastic intra-particle lithium redistribution and inter-particle lithium exchange at intermediate SOCs, whereas the electrode equilibrates much slower at low and high SOCs. These physics-based insights into the distinct SOC-dependent relaxation efficiency provide new perspective towards developing advanced fast charge protocols to suppress plating and shorten the constant voltage regime.

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Monolayer transition metal dichalcogenides (ML-TMDCs) possess degenerate levels with antiparallel spins in K and K ' valleys, providing the intrinsic valley polarization, which attracts great interest for potential applications on quantum information technology and on-chip nanophotonics. Unfortunately, it is difficult to distinguish the degree of valley polarization (DoP) near room temperature due to the intensive phonon-assisted intervalley scattering and the long-range electron-hole exchange interaction in ML-TMDCs, limiting their practical applications. In this study, a novel design is proposed for great promotion of DoP in ML-WSe2 with a microsphere cavity array, introducing Purcell effect and nanofocusing effect into the system. The radiative decay rate is dramatically enhanced owing to Purcell effect in microcavity in weak coupling regime, thus locking more polarized excitons in the corresponding valley under certain circularly-polarized pumping. In addition, the nanofocusing effect contributes to increasing the number of charged excitons by suppressing the bright to dark exciton conversion. The present work achieves a great DoP of ML-WSe2 with a simple configuration and promises broad applications from valleytronic devices to chiral optics in the future.

Keyword ：

photoluminescence microsphere cavities optical whispering-gallery modes valley polarization 2D-TMDCs

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Accurate heat load prediction plays a vital role in the field of district heating. However, it is challenging to establish an accurate mathematical model for heat load prediction because of the technical characteristics of heating systems, such as their large-scale, multidimensional, long delay, strong coupling, time-varying, and nonlinear characteristics. This article proposes a heat load prediction model based on feature fusion of dual-source data (DSDF), and this model fully extracts the characteristics of the working condition data of pipe networks and the data of building energy consumption to make high-precision predictions of the ultrashort-term heat load of heat exchange stations. First, to address the problem of incomplete feature coverage of a single-mode data set, the networkworking condition data set and building energy consumption data set were constructed, and the random forest method was used to select characteristic variables. Second, a neural network prediction model was constructed. The model captures short- and long-term features through the convolution layer and cyclic layer and captures periodic features through the cyclic jump layer. Finally, the scoring idea of the attention mechanism is introduced, and the predicted results of energy consumption data were used to calibrate the predicted results of pipe network working condition data to improve the model's prediction performance. Comparative experiments with several algorithms showed that the proposed new method performs well in the task of ultrashort-term prediction of heat load.

Keyword ：

heat load prediction neural network feature fusion Dual-source data heat exchange station

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Frequent fluctuations of CNG engine operating conditions make the waste heat source have uncertain, nonlinear, and strong coupling characteristics. These characteristics are not conducive to the efficient recovery of the DORC system. The systematic evaluation of the CNG engine waste heat source and the comprehensive performance of the DORC system is conducive to the efficient use of waste heat. Based on the theory of internal combustion (IC) engine thermal balance, this paper analyzes the dynamic characteristics of compressed natural gas (CNG) engine waste heat energy under full operating conditions. Then, based on the operating characteristics of the dual loop organic Rankine cycle (DORC) system, thermodynamic models, heat transfer models, and economic models are constructed. The dynamic response characteristics analysis and energy, exergy, and economic (3E) evaluation of the DORC system under full operating conditions are carried out. The results show that the maximum values of net power output, heat exchange area, and the minimum values of EPC (electricity production cost) and PBT (payback time) are all obtained under rated condition, which are 174.03 kW, 25.86 kW, 37.54 kW, 24.76 m(2), 0.15 $/kW & BULL;h and 3.46 years. Therefore, the rated condition is a relatively ideal design operating point for the DORC system. The research in this paper not only provides a reliable reference for the comprehensive analysis and evaluation of the performance of the DORC system, but also provides useful guidance for the selection of appropriate DORC system design operating points.

Keyword ：

dual loop organic Rankine cycle full operating conditions dynamic response characteristics CNG engine waste heat recovery

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In order to solve the large-scale, strong coupling, and nonlinear optimization problems in many Internet-of-Things (IoT) applications, such as intelligent infrastructure and smart city, this article proposes a real-coded genetic algorithm based on an auxiliary-individual-directed crossover operator (AIDX). AIDX is an alternative offspring framework of the directed crossover which uses auxiliary individual to reduce the search space of alternative offspring for the rapid optimization of multidimensional problems. In our solution AIDX, the parents-center distribution is adopted to reduce the risk of convergence to local optimization and enhance the stability of the algorithm. In addition, in order to increase the diversity of the population at the late stage of optimization, K-Bit-Swap (KBS) is used as a supplement for the exchange of genetic information among individuals in different dimensions. In the extensive experiments, 24 benchmarks with different dimensions are used to evaluate the performance of AIDX-GA. The results show that the proposed AIDX-GA has a significantly improved optimization effect on multidimensional optimization problems, and the stability of the algorithm is largely enhanced even when the global optimum is located near the boundary. AIDX-GA has also been evaluated in an industrial IoT case that identifies the resistance coefficients of a pipe network in the city infrastructure. The results show that the accuracy of AIDX-GA is high, and it has excellent universality and stability, which can be used to solve many IoT problems.

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smart network Auxiliary individual evolutionary algorithm (EA) directed crossover real-coded genetic algorithm (GA)

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Specially designed SmCo5/Co magnetic nanocomposites have been fabricated by a "bottom up" process. SmCo5 nanochips were first prepared by solution-phase chemical synthesis combined with reductive annealing and then coated by chemical deposition of Co nanorods. Both the SmCo5 nanochips and Co nanorods are anisotropic and could be simultaneously aligned under the external magnetic field. Magnetic measurements applied on these "bi-anisotropic" SmCo5/Co composites show high magnetic performance with the Co phase content in a wide range from 10 to 80 wt %. For the first time ever, the applicable exchange-coupled nanocomposites with a rareearth content lower than 7 wt % was realized, which exhibits the coercivity close to 10 kOe and remanence 31% larger than that of single phase SmCo5. 3-D micromagnetic simulations were performed to reveal that the reversal mechanism in the Co phase was transferred from the incoherent mode to the coherent mode under a tip interface exchange-coupling with a SmCo5 surface.

Keyword ：

nanocomposite OOMMF SmCo5/Co low rare-earth content permanent magnet anisotropy

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Programmable magnetic field-free manipulation of perpendicular magnetization switching is essential for the development of ultralow-power spintronic devices. However, the magnetization in a centrosymmetric single-layer ferromagnetic film cannot be switched directly by passing an electrical current in itself. Here, we demonstrate a repeatable bulk spin-orbit torque (SOT) switching of the perpendicularly magnetized CoPt alloy single-layer films by introducing a composition gradient in the thickness direction to break the inversion symmetry. Experimental results reveal that the bulk SOT-induced effective field on the domain walls leads to the domain walls motion and magnetization switching. Moreover, magnetic field-free perpendicular magnetization switching caused by SOT and its switching polarity (clockwise or counterclockwise) can be reversibly controlled in the IrMn/Co/Ru/CoPt heterojunctions based on the exchange bias and interlayer exchange coupling. This unique composition gradient approach accompanied with electrically controllable SOT magnetization switching provides a promising strategy to access energy-efficient control of memory and logic devices. A major challenge of spintronics is achieving magnetic field free electrical control of magnetisation. Here, Xie et al. achieve perpendicular magnetisation switching in a CoPt alloy, breaking inversion symmetry by varying the composition of the alloy in the growth direction.

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