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Artificial neural network is considered to be one of the effective ways to enable soft robots to achieve high-performance control due to their significant advantages, such as massively parallel processing and distributed storage of information, adaptivity, and fault tolerance. Artificial neural networks are composed of microelectronic components connected together, of which the most basic units are artificial neural synaptic units, such as atomic switches, memristors, and synaptic transistors. This paper first introduces the research status of soft robots and artificial neural synapses, predicts the demand of soft robots for artificial neural synapses, summarizes the difficulties and problems that may be encountered in the application of artificial neural synapses to soft robots, and finally points out the importance and feasibility of artificial neural synapses in the research and development of soft robots. [ABSTRACT FROM AUTHOR]

This paper establishes a data-driven Neural Network (NN) framework. The contact resistance of T2 copper blocks with different roughnesses is predicted by deep learning at room temperature and cyclic loading. The contact resistance problem can be regarded as a regression problem of mapping the high-dimensional array space of multiple variables to the contact resistance. This paper measures the contact resistance of copper blocks with different surface roughnesses under loading and unloading states and obtains the original dataset required by the algorithm. The data characteristics include three surface topography parameters, number of cyclic loads, loading and unloading conditions, and load magnitude, with the data labeled contact resistance. This paper compares the results of the NN model and Holm model results to verify the NN model's effectiveness. The comparison results show that the prediction results of the NN are consistent with the predictions of the Holm model. After training and debugging, the root mean square error of the multiple hidden layers neural network test set is 6.81%, showing a good prediction effect. In conclusion, the deep learning algorithm provides a new way for fast and accurate prediction of the relationship between T2 copper blocks and contact resistance under cyclic loading times and unloading states. [ABSTRACT FROM AUTHOR]

Short-term power load forecasting provides important guidance for the improvement of power marketing and control levels of power enterprises. In this paper, a novel method, named RF-TStacking, is proposed to forecast the short-term load. This study starts from the influence factors of the power load, the random forest is applied to estimate the importance of the influence factors of short-term load. Based on Stacking strategy, the integration of LightGBM and random forest is realized to achieve short-term power load forecasting. To improve the generalization ability of the load model, random put back sampling is used to sample each primary learner, and the average value is taken as the result of each primary learner. The Bayesian optimization is used to adjust the super parameters of the model to improve the accuracy of the selection of influencing factors. The load data of a region in northwest China are used for the testing, and it is found that the model can provide stable prediction results. [ABSTRACT FROM AUTHOR]

This paper proposed an ultra-low-power successive approximation register analog to digital converter (ADC) for medical implant devices. To reduce power consumption, the novel techniques presented in this paper are a tri-state capacitor unit, a novel switch scheme, and a new low static power comparator. Tri-state capacitor unit reduces down power without the use of middle voltage reference. The proposed switch scheme can complete the most-significant bit 3-bit conversion without any power consumption. The offset of the low static power comparator is only optimized by physical design. This ADC is fabricated in a 110 nm 1P5M CMOS process. The reference voltage of DAC is 1 V, and the supply voltage of comparator and digital logic is 1.5 V. At 10 kS/s sampling rate, the signal to noise and distortion ratio (SNDR) is 57.57 dB and power consumption is 24 nW. [ABSTRACT FROM AUTHOR]

The micro-direct methanol fuel cell (μDMFC) has the advantages of high energy density, high conversion efficiency, and simple structure, which brought vast application prospects in portable devices. However, some shortcomings still exist, such as low catalyst utilization and power density. This paper proposes a new cathode electrode structure for the μDMFC. The structure consists of a multi-walled carbon nanotube layer and a cathode double microporous layer (CD-MPL) prepared from carbon powder. The outer microporous layer (OMPL) is composed of multi-walled carbon nanotubes (MWCNTs), Nafion solution, and carbon powder, and the inner microporous layer (IMPL) is composed of carbon powder and polytetrafluoroethylene (PTFE). The experimental results show that the maximum power density of the μDMFC with a CD-MPL (CD-μDMFC) is 42.8 mW/cm2, which is 31.6% higher than that of the μDMFC with a cathode single microporous layer (CS-μDMFC). The pore size distribution of the OMPL of the CNT is measured by the mercury intrusion method. It can be seen that the distribution of pore size is wider and there are more pores with larger pore sizes, which are more conducive to the utilization of catalysts. The discharge experiment of the cell shows that the CD-μDMFC shows high discharge performance and fuel utilization at different concentrations. The double microporous layer (MPL) structure increases the porosity and pore range, broadens the three-phase interface for the reaction, and allows the catalyst to have more attachment sites. The existence of MWCNTs improves the conductivity and mass transfer capacity of the cathode. [ABSTRACT FROM AUTHOR]

In this paper, an improved coupled-mode method is used to design a launcher for a gyrotron quasi-optical mode converter at 170 Ghz with an operating mode of TE32,9. The new method calculates 25 coupled modes, which more accurately simulates the field distribution in the launcher. The diffraction field of the launcher with a spiral cut is calculated by using the scalar diffraction integral method with fast Fourier transform. The radiation power of the launcher is 99.94%, the Gaussian mode content of the radiation beam is 98.40%, the diffraction loss of the launcher is 0.0580%, and the radiation efficiency is 98.34%. The method proposed in this paper is fast in calculation and can be applied to the large-scale high-frequency gyrotron launcher. [ABSTRACT FROM AUTHOR]

In this paper, the magnetic immunity model of STT-MRAM is established. The influence of the external magnetic field on the effective energy barrier of STT-MRAM is investigated, which is the crucial issue to influence the reliability of STT-MRAM cells in the standby, active read and active write modes. The influence factors on the magnetic immunity of STT-MRAM array are also discussed in the paper, such as the electrode, package material, insert layer and array spacing, etc. Moreover, the magnetic shield models in the BGA and QFP packages are designed and analyzed for the enhancement of the magnetic immunity of STT-MRAM, whose shielding efficiency is up to 98.2%. [ABSTRACT FROM AUTHOR]

With the advancement of wide-bandgap power devices, the power electronics equipment is developing toward higher switching frequencies and more complex switching modes in recent years. Accurate prediction of the core loss for magnetic components has been emphasized as the excitations of magnetic materials varying depending on the operating mode of the power supplies. Therefore, this paper presents the results of an extensive core loss study performed on nanocrystalline alloy (FT-3KL), amorphous alloy (1K101) and ultra-thin oriented silicon steel (GT-50). Firstly, an automatic setup for core loss measurement of soft magnetic materials fed by a full-bridge inverter based on silicon carbide (SiC) MOSFET is proposed. Then, the effects of switching oscillations from the inverter and the characteristic parameters of complex non-sinusoidal excitations on the core loss are analyzed comparatively. The core loss shows different regular distributions with the change of each characteristic parameter of excitations respectively. However, the regular distributions will be influenced by the high-frequency switching oscillations, which makes the prediction of core loss more complicated. This paper can provide a reference for the development of high-precision core loss model and performance optimization of power electronics equipment. [ABSTRACT FROM AUTHOR]

Electrical steel cores in electric motors are often operated under variable temperature conditions, and the temperature has a large impact on the magnetic properties of electrical steel. Different Silicon content also makes electrical steel have different performance characteristics. Therefore, in this paper, an environmentally adjustable electrical steel magnetic property testing system is built to investigate the magnetic property variation of non-oriented electrical steel sheets with different Si contents at different temperatures. Through the experiments in this paper, it is found that the trend of magnetic properties of electrical steels tends to flatten out with increasing Si content under the influence of temperature. In particular, the loss of 6.5% Si shows a trend of first decreasing and then increasing with the increase of temperature. The internal grain structure of electrical steel can explain this phenomenon very well. The larger the grain size, the less the magnetic properties of electrical steel are affected by temperature. In order to further analyze the variation phenomenon of electrical steel loss, the loss separation calculation was carried out for 5 more electrical steels with different Si content in this paper. The reason for this phenomenon was finally explained by a special preparation process of 6.5% Si. [ABSTRACT FROM AUTHOR]

In the paper, novel multi-bit parallel pipeline circuit design of STT-MRAM is proposed to improve the read and write efficiency. The shift register is utilized to change the series data into the parallel ones. Combined with the corresponding sense amplifier (SA) circuit and the write drive circuit, 4-bit data can be read or written in parallel in single cycle. With the 32 Kbit data test, the efficiencies of the read and the write operations of the proposed pipeline circuit are increased by 72.3% and 74.4%, separately, with the comparison of the incumbent series operations. The proposed strategy has potential application in the embedded high speed STT-MRAM. [ABSTRACT FROM AUTHOR]

Charge trap is considered to be one of the effective characteristic parameters for qualitatively evaluating the aging status of insulating material. In this paper, the trap characteristics in oil-impregnated paper with different aging types (non-treatment, thermal treatment and electrical treatment) are investigated using a dual-level (shallow and deep energy) trap model based on space charge profiles and thermally stimulated depolarization current (TSDC) data. The simulated results based on the model are well consistent with the experimental results. On the other hand, the TSDC method can acquire much information related to the shallower traps, and the dual-level trap model can obtain much charge dynamics characteristics. It has been observed that thermally aging makes the shallow trap energy become deeper while electrically aging makes it shallower. Moreover, the trap density in oil-impregnated paper increases after aging regardless of thermal or electrical aging. [ABSTRACT FROM AUTHOR]

Lenses are fundamental elements in many optical applications. However, various aberrations are inevitably present in lenses, which will affect the distribution of focused light intensity and optical imaging. Accurately predicting the aberrations of a lens is of great significance. Nevertheless, quantitatively measuring the aberrations of a lens, especially when multiple aberrations are present simultaneously, is a challenging task. In this paper, we propose a method based on a designed deep residual network called Y-ResNet to measure the astigmatism and coma of a lens simultaneously. The Y-ResNet was trained on the focused image pattern of a Gaussian beam passing through a lens with astigmatism and coma. The trained network can accurately predict the aberration coefficients of the lens with 0.99 specificity, 0.925 precision, 0.9382 recall, and a 0.9406 F1-score achieved on astigmatism and 0.99 specificity, 0.956 precision, 0.98 recall, and a 0.954 F1-score achieved on coma. Specifically, even if only part of the intensity distribution of the light spot is captured, the network can accurately estimate the aberrations of the lens with an accuracy of over 90% on coma and can identify astigmatism aberration features. This paper can provide a feasible method for correcting beam patterns caused by aberration based on deep learning. [ABSTRACT FROM AUTHOR]

We present here a computational numerical operator, and we name it as Time Invariance Operator (TIO). This operator can add obstacles to the domain of the differential equation that describes a physical phenomenon. After the TIO acts, the wave equation recognizes the introduced points as non-interacting zones without affecting the rest of the domain. Computational physics has been consolidated as an important field of study, especially when connected with the fundamentals of physics. In many cases, simulations are conducted considering the ideal case of a wave in an infinite domain and open space without considering obstacles, barriers, or other aspects of the real world. The results presented in this paper allow us to infer that the TIO is the easiest way to apply the physical domain to wave propagation simulations and successfully recreate wave interaction experiments through computer simulations. Our motivation is to perform wave simulations that interact with obstacles, barriers, single slits, and double slits. We aim to investigate the results obtained in images to determine if the methodology we used to introduce realistic physical characteristics was successful in presenting the expected phenomenology. The simplicity of the TIO's action in creating locally time-invariant regions over the domain makes it suitable not only for waves but also for equations with transient terms. Heat transfer, mass transfer, computational fluid dynamics, and other time evolution equations can take some benefit from the operator presented in this paper. The TIO ensures local conservation that mimics interaction regions or ensures free space characteristics if it is the case like a 2D tensor of local conservation. The principal result from this paper is the validation of the TIO to impose realistic conditions with minimal modifications over a running code of wave equation simulation originally in free space. The TIO is innovative because it imposes dynamic conditions that mimic realistic interacting zones. [ABSTRACT FROM AUTHOR]

Transcranial magnetic stimulation (TMS) is a noninvasive neuromodulation technique for treating various neurological disorders. The geometry of the TMS coil determines the focality, stimulation field strength, and stimulation depth of the induced electric field. In this paper, we introduce a novel coil, named the eccentric folding coil (EFC). We used Sim4Life, a three-dimensional human tissue medical electromagnetic simulation software, and the brain models of the subjects from the population head model repository to conduct finite element simulations of the eccentric folding coil, circular coil, and figure-eight coil, implying that the largest EFC has a focal area of 19.5 cm2 less than the smallest circular coil, and the EFC of any size has a smaller focal area than the figure-8 coil of the same size. Furthermore, we stimulated the model from three directions with the coil and measured the electric field responses of the model, confirming that stimulation varied in different directions. Additionally, we applied EFC to four representative human models and found that the electric field in different subjects' brains differed by 3.03 mm in stimulation depth and 12.9 cm2 in focal area, suggesting that personalized human head modeling and electromagnetic analysis are essential for TMS treatment. In the future, we will explore using different types of TMS devices for patients with different conditions to achieve more precise and customized treatment. [ABSTRACT FROM AUTHOR]

The two-dimensional distribution method based on the laser spectrum is widely used in the reconstruction of two-dimensional temperature fields or concentration fields. However, the existing methods are all based on small-scale measurements. In large-scale spatial detection of farmland, the detection accuracy cannot reach the expected result due to the long optical path and the noise of various frequencies brought by environmental factors such as vibration, temperature, and other interfering gases. Aiming at the above-mentioned problems, this paper proposes a method to reduce open optical path noise interference in two-dimensional gas detection of farmland to improve detection accuracy. The signal denoising approach combines variational modal decomposition with the SG filtering algorithm to decompose, smooth out, and rebuild the detection signal. In addition, we built a two-dimensional detection system based on an open optical path. Throughout experimental validation, the proposed method outperformed the traditional method by 24% and 19%, respectively, in terms of the fitting degree and fitting effect of the gas absorption curve. [ABSTRACT FROM AUTHOR]

This paper describes the origin, principles, practical applications, and future perspectives of mass-selected ion beams generated using two rotating electric-field mass (REF-MS) filters. Our team has been investigating the underlying principles of REF-MS separation and assessing the feasibility of developing suitable systems to realize mass separation and ion beam convergence using rotating electric fields as well as the practicability of this method. This paper focuses on the mechanism underlying the observed cycloid trajectories followed by REF-MS-selected ions. A focused ion beam column with Ga and AuGe liquid metal ion sources (LMISs) was connected to REF-MS optics to assess the mass-selection performance of the filter. The mass-separation ability of this system was demonstrated by the ion projection images of Ga-LMIS (69Ga+ and 71Ga+) and AuGe-LMIS (97Au2+, Au2Ge+, and Au2Ge2+). The column was then replaced with a vacuum electrospray ionization (ESI) source. The size-selected water-cluster ion beams [(H2O)nH]+ were separated based on cluster size, and a microscale crater was created. Co-containing molecular ion beams were revealed using different concentrations of ESI sources, and a mass-separated [Co(DEGBE)4]+ ion beam was constructed. [ABSTRACT FROM AUTHOR]

This paper presents an alternative optical characterization of biosensors based on supported lipid monolayers (SLMs). Developing these biosensors requires precise thickness characterization of the films to understand their structure and dynamics. This paper proposes an optical technique to measure the thickness, optical properties, and location of a dipalmitoyl-phosphatidylcholine (DPPC) SLM on top of a metallic thin film. DPPC SLMs are of interest for biosensing applications, such as detecting pulmonary-related infections like SARS-CoV-2, Avian Influenza, and the H1N1 influenza virus. The monolayer was fabricated using the Langmuir–Blodgett technique, and the experimental characterization consisted of measuring the surface-plasmon resonance angle in the Kretschmann configuration. This technique provides an alternative option for real-time visual inspection and determination of the location and shape of DPPC monolayers in large areas. Therefore, it offers a useful tool for further developing SLM-based biosensors. [ABSTRACT FROM AUTHOR]

Albert Einstein proposed a unification of mechanics and electrodynamics by his special theory of relativity, which describes point-like particles moving through empty space. We show in this paper that mechanics and electrodynamics can be unified in Euclidean space if we relax the idea of point-like particles by describing fermions and bosons as spatially extended wave objects. Based on the process theory of gases presented in Paper II [Kalies et al., AIP Adv. 13(5), 055317 (2023)] of this series, we consider a confined photon gas and show that the momentum work of photons leads to an analogous description of matter and light and to the insight that electromagnetic energy is momentum energy. We present the unified energy equations, which do justice to the wave nature of matter, and it is the momentum work that links physical theories. Without momentum energy, which is larger in real terms than the kinetic energy of mechanics, the theoretical edifice of modern physics, at the fundamental level, is incomplete. [ABSTRACT FROM AUTHOR]

In this paper, a biomimetic topology optimization design method that simulates the growth pattern of leaf veins is proposed for the design of the support structure of ultra-light airfoil-like solar cells in the solar powered unmanned aerial vehicle. This method simulates the optimal growth process of main vein morphology through the topology change of dynamic point groups to obtain an optimized topological main support structure and then generates a Voronoi grid structure in the area surrounded by the main support structure to increase the local support for the battery. The whole process is combined with genetic algorithm to simulate the optimal distribution strategy of leaf vein growth by inputting a small number of parameters. Compared with the traditional grid support structure, the support structure obtained by simulating the leaf vein growth optimization strategy can provide more efficient support for the solar panel and avoid damage to the solar cell. [ABSTRACT FROM AUTHOR]

With the increasing number of space debris and extreme working environment, the space station faces the risk of cabin damage. Once the leakage occurs, it must be repaired in time. Identifying the shape of leaks can guide for astronauts to make plugging plans. The current research on leak identification methods is mostly aimed at circular leaks with different diameters, and there is little research on leak identification with different shapes. Therefore, it is of great significance to research leak shape identification methods. A method for identifying the shape categories of vacuum leaks based on improved variational mode decomposition and support vector machine is proposed in this paper: first, using the improved algorithm to determine the uniform number of modes K and adaptively optimize the quadratic penalty coefficient α. Then, apply the variational mode decomposition to the leakage signal and calculate each mode's maximum frequency. Setting these frequencies as eigenvalues for training and testing the identification model is based on support vector machine. In the experiment, four shapes of the leaks were used: ellipse, rectangle, round, and square. The experiment proves that this proposed method has stable and high identification accuracy, and can realize the shapes categories identification for the leaks, which can provide an important basis for spacecraft in-orbit leakage maintenance. [ABSTRACT FROM AUTHOR]

Momentum work enables a complete shift from kinematics to dynamics. This involves changes in the very fundamentals of physics, not only in mechanics, statistical mechanics, and special relativity, as shown in Papers I–III [G. Kalies and D. D. Do, AIP Adv. 13(6), 065121 (2023); G. Kalies, D. D. Do, and S. Arnrich, AIP Adv. 13(5), 055317 (2023); and G. Kalies and D. D. Do, AIP Adv. (in press) (2023)] of this series, but also in thermodynamics. In this paper, we challenge the narrative that classical phenomenological thermodynamics is completed and show that it represents an efficient interim solution that hides essential information. The essence of heat transfer and entropy is revealed, and an answer is given to the question of why entropy had to remain abstract and elusive in the past. Furthermore, we uncover the specific forms of energy behind thermodynamic state variables, such as enthalpy, Helmholtz free energy, and Gibbs free energy, which play a central role in describing chemical reactions and phase transitions. We thereby lay the foundation for thermodynamics to evolve from a framework theory valid for macroscopic systems to vivid quantum-process thermodynamics. [ABSTRACT FROM AUTHOR]

This paper analyzes an accident of abnormal increase of pole bus differential current and pole differential current of a converter station caused by line fault of a ±800 kV extra high-voltage direct current transmission project. After a lightning strike caused a short circuit and grounding of the DC line, the sudden voltage change protection of the DC line was triggered and the DC full voltage restart was successful. The pole bus differential current and pole differential current of the converter station have reached the protection set but have not reached the protection delay set; therefore, the differential protection has not acted. This paper first introduces the configuration principles of pole differential protection, pole bus differential protection, and line voltage sudden change protection for extra-high voltage converter stations. Second, the operation of the DC protection under this fault was analyzed in detail, and the reasons for the occurrence of pole bus differential current and pole differential current were also analyzed in this paper. Then, the range of equipment that caused the abnormal increase in differential current was identified. Finally, the lightning strike model was built on the real-time digital system, and the fault was simulated and replicated. It was determined that the abnormal increase in differential current was caused by the discharge of the pole bus surge arrester caused by the second lightning strike on the DC line. [ABSTRACT FROM AUTHOR]

This article aims to introduce the inverse new XLindley distribution, a further extension of the new XLindley distribution. The article explores various properties of the proposed model, such as the quantile function, stochastic orders, entropies, fuzzy reliability, moments, and stress–strength estimation. The paper also compares different methods of estimating the parameters of the proposed model and evaluates their performance using a simulation study. Moreover, the paper demonstrates the usefulness of the proposed model by applying it to two real datasets. The article shows that the proposed model fits the data better than seven existing models based on model selection criteria, goodness-of-fit test statistics, and graphical visualizations. The paper concludes that the new model can be a valuable tool for modeling and analyzing hazard functions or survival data in various fields and contributing to probability theory and statistical inferences. [ABSTRACT FROM AUTHOR]

In response to the green development strategies of countries all over the world, research on degradable epoxy resins has attracted widespread attention. The introduction of reversible covalent bonds in the conventional cross-linked structure of epoxy resins is one of the methods to achieve degradation of epoxy resins, and most researchers use molecular dynamics simulations in their preliminary studies to investigate the feasibility of the introduction of reversible covalent bonding schemes. The purpose of this paper is to investigate the feasibility of introducing C=N into the cross-linked structure of epoxy resins. Four formulation schemes of vanillin-based monoepoxides with the curing agent 4,4′-methylenebis(cyclohexylamine) were designed, and the molecular dynamics simulation method was used to cross-link them. The changes in the cross-linking degree, structural parameters before and after cross-linking, free volume fraction, and C=N content before and after cross-linking were investigated. The effects of different C=N contents on the thermal properties such as glass transition temperature and thermal expansion coefficient, as well as the mechanical properties such as the elastic modulus and shear modulus of this epoxy resin, were investigated. The bond-breaking characteristics of C=N, C–N, and C–O were compared by density of states and differential charge density simulations. Then the degradation mechanism of epoxy resin after the introduction of C=N was illustrated. The results show that as the specific gravity of the curing agent molecule increases, the cross-linking degree tends to increase. The cross-linked model has reduced volume, increased density, decreased energy, and a more stable structure. After crosslinking, the gaps between the segments in the system become smaller, and the fraction of free volume decreases as the proportion of crosslinking agent molecules increases. The C=N content in epoxy resin shows an increasing trend first and then decreases with the increase in the proportion of the curing agent. The glass transition temperature of the material increases with the increase in C=N content, while the coefficient of thermal expansion decreases with the increase in C=N content. The elastic modulus and shear modulus of the material show an increasing trend with the increase in C=N content, with a relatively gradual change in magnitude. Compared with C–N and C–O bonds, the C=N bond is weaker in strength, has a greater polarity, and is more prone to cleavage and degradation. [ABSTRACT FROM AUTHOR]

Traditional tethered nerve implants have many limitations since they rely on physical wires for power and signal transmission. Wireless stimulation technology can promote the exploration of neurological diseases and meet patient requirements, stemming from its portability and efficiency. In this paper, the link transmission characteristics of a sub-millimeter inductor are investigated by simulation, electrical tests, and theoretical analysis. The inductor acts as the receiving coil of a wireless stimulation device, and the wireless energy transmission process based on magnetic induction coupling is analyzed. Second, a novel millimeter-scale wireless stimulator device for neuromodulation is designed based on the parameters of transmitting and receiving coils obtained from the simulation. Finally, rat electrophysiological experiments are conducted to assess the feasibility of the device. The field Excitatory Post Synaptic Potential baseline is first recorded in the CA1 radiation area for 10 min, followed by the addition of high-frequency stimulation, and after successful induction of long-term potentiation (LTP) and recording for 10 min, the two coils are fixed at a distance of 1 cm and the hippocampal Schaffer-CA1 pathway is added. The experimental results show that the addition of wireless stimulation can modulate the transmission of synaptic electrical activity in the hippocampal Schaffer-CA1 pathway and significantly increase the level of (LTP) induction. A millimeter-scale wireless stimulation device is investigated and designed in this paper, the feasibility of the device is demonstrated through ex vivo electrophysiological experiments, and its effects on the targeted modulation of the Schaffer-CA1 pathway in the rat hippocampus are described. [ABSTRACT FROM AUTHOR]

The randomness and fluctuation of wind power output will cause certain waste in capacity allocation of integrated energy system. Therefore, a robust chance constrained optimization model is proposed to solve the shortcomings of the traditional model in wind power output analysis, such as weak reliability and conservative results. First, the uncertainty of wind power output is analyzed. Second, a robust chance constrained optimization model combining stochastic programming and robust optimization is established to deal with the uncertainty of the output power of the integrated energy system objectively. Finally, the results are compared with the existing integrated energy system capacity configuration, and the validity of the model is verified. The results show that the robust chance constrained optimization model proposed in this paper can effectively reduce the capacity cost by 38.2% while ensuring the robustness of the system in wind power uncertainty analysis. [ABSTRACT FROM AUTHOR]

Side Lobe Level (SLL) suppression is a challenging but essential part of frequency selective surface (FSS) structural design. The SLL of the radiation pattern is a key parameter demonstrating the directional anti-interference ability and mainly depends on the geometry of the FSS. However, the correlation between SLL and FSS structural parameters is extremely complicated. A minor FSS structure change may result in a drastic diversion in the sidelobe's direction or level, making the SLL the most difficult parameter to optimize. In this paper, an efficient optimization method specifically for SLL suppression is proposed. We discretized the edges of split square ring FSS structures by binary representation and generated new patterns based on the genetic algorithm. Optimization results showed that in the most optimal structure, the SLL was −23.41 dB, exhibiting a 5.17 dB reduction. Meanwhile, the center frequency variation was less than 2%. Moreover, the computation time cost was reduced by over 90% compared with that of the fully discretized pattern optimization method, showing that this novel method was truly effective in getting SLL suppressed FSS structures. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the influence of small disturbance on the statistical behaviors of fluid particles of the three-dimensional divergence-free hexagonal Beltrami flow from a Lagrangian point of view. Due to the butterfly-effect, numerical noise increases exponentially for chaotic dynamic systems. Thus, a powerful strategy, namely, the clean numerical simulation, is used to gain reliable/convergent trajectory in a long enough interval of time. It is found that the statistics of chaotic trajectory of fluid particles are stable in some cases, corresponding to the so-called "normal-chaos," but unstable in some cases, i.e., rather sensitive to small disturbances, corresponding to the so-called "ultra-chaos," which is a new concept proposed currently. Obviously, an ultra-chaotic trajectory of fluid particles is at a higher disorder than a normal chaotic trajectory. In theory, it is impossible to repeat any experimental/numerical results of an ultra-chaotic system even by means of statistics, but reproducibility is a corner-stone of our modern science paradigm. Hence, the wide existence or non-existence of ultra-chaos has a very important meaning. In this paper, we illustrate that the ultra-chaotic trajectories of fluid particles indeed widely exist in a hexagonal Beltrami flow field. This fact is important for deepening our understanding of chaotic dynamic systems and revealing the limitations of our paradigm of modern science. [ABSTRACT FROM AUTHOR]

This paper proposes a novel bow-tie metasurface that integrates various types of polarization conversions by optimizing traditional unit structures. The metasurface achieves wide-angle linear polarization conversion over the X-band (8–12 GHz) and has a linear polarization conversion efficiency of over 94% under normal incidence. In the Ku-band (12.4–15.6 GHz), the ellipticity value (e-value) and axial ratio calculations show that the linearly polarized waves incident along the Y axis will be effectively converted to left-handed circularly polarized waves. Additionally, in the X-band (8.9–10.5 GHz), the circular polarization and its co-polarization conversion efficiency can be maintained at 99.5%, allowing for an effective circular polarization phase shift using the Pancharatnam–Berry principle in this frequency range. [ABSTRACT FROM AUTHOR]

Aerators with sharp lateral enlargements and bottom drops generally cause adverse effects in spillway tunnels with a mild base slope, including serious cavity back flow and water wings striking the tunnel roof. Taking RM Hydropower Station's spillway tunnel as its example, this paper proposes a new type of combined aerator characterized by a "variable base slope" longitudinally and a transverse "sharp enlargement plus straight section." This not only increases cavity stability, resulting in more effective aeration, but also inhibits the development of water wings, contributing to an improved pattern of water flow. In addition, this paper systematically explores the influence of the flip bucket (drop), gently sloping section, and steeply sloping section of the "variable base slope" aerator upon the aerated cavity and summarizes the rules according to which the sharp lateral enlargement and diffusion angle influence the formation of water wings. This offers technical solutions, with theoretical support, for the design of aerators in spillway tunnels with a mild base slope. [ABSTRACT FROM AUTHOR]

Face generation and manipulation techniques based on deep learning have enabled the creation of sophisticated forged facial videos, which are indistinguishable by human eyes. However, the illegal use of deep fake technology will have a serious impact on social stability, personal reputation, and even national security. Therefore, the detection technology of fake facial videos is of great significance to protect national security and maintain social order. Although the existing video-based fake face video detection technology has achieved good detection performance on the public fake face video database, there are still the following problems: (1) the existing technology uses a 2D attention mechanism to obtain local region features from face images and lacks a 3D attention mechanism to obtain local area features from face videos; (2) after obtaining local area features, the existing technology is directly used to classify or only model the inter-regional relationship of images without modeling the temporal relationship between regions of the video. This paper proposes a fake facial video detection framework based on multi-region temporal relationship features, including designing a three-dimensional attention mechanism to extract local features of multiple regions of the face from the video. In order to model the time series relationship between different face areas, a time series graph convolution neural network is also introduced to extract the time series relationship features between multiple areas. In order to model the time sequence relationship between different face regions, the convolution neural network of a time sequence diagram is also introduced to extract the characteristics of the time sequence relationship between multiple regions. Through the change characteristics of the time sequence relationship between face regions, the timing inconsistency of the face video is detected so as to determine whether the face has been deeply forged. Through experiments on multiple datasets, the experimental results of the model accuracy test show that the method proposed in the present invention achieves the highest detection accuracy, and the accuracy in the FaceForensics++ (low definition) dataset is 18.19% higher than that of the benchmark method. The experimental results of the generalization ability test show that the method proposed in the present invention achieves the highest generalization performance, and the detection accuracy in the Celeb-DF dataset is 11.92% higher than that of the benchmark method. [ABSTRACT FROM AUTHOR]

The structure of a muzzle brake has a significant effect on the overall technical performance of an automatic weapon. This paper presents a multi-objective optimization of a muzzle brake that enhances the overall performance, that is, it increases the muzzle brake efficiency and simultaneously decreases the noise emanating from the rifle upon discharge. A standard impact-reaction muzzle brake was selected as the research object. The optimal values of four structural parameters were established through multi-objective optimization. The process consists of design of experiments, coupled computational fluid dynamics and computational acoustics calculations, an approximation model, and a multi-objective genetic algorithm. Based on the results, the correlation and sensitivity between the structural parameters and the objectives were investigated. Moreover, the reaction force and noise directivity of the optimized muzzle brake were compared with those of the original design. The results show that the disk angle of the side holes was the most sensitive design variable for both efficiency and noise. The optimized muzzle brake had a remarkable improvement in brake efficiency accompanied by only a small increase in the sound pressure level, so it showed better overall performance. The optimization method proposed in this paper is practical and effective for engineering design. [ABSTRACT FROM AUTHOR]

The paper aims to apply the octonions to explore the contribution of some influence factors to magnetic moments, revealing the connection between the influence factors and spin texture. Maxwell was the first to introduce the quaternions to describe the electromagnetic theory. The subsequent scholars utilized the quaternions and octonions to study the gravitational and electromagnetic theories, and so forth. The paper adopts the octonions to research the gravitational and electromagnetic fields, including the octonion's angular momentum, torque, force, and so on. When the octonion force is equal to zero under some circumstances, it is able to achieve eight equations independent of each other. In particular, one of eight independent equations reveals the interrelation between the second-torque and the divergence of magnetic moments. One of its deductions is that the directions, magnitudes, and frequencies of some terms are capable of impacting the orientation and vortex of magnetic moments, altering the frequency of magnetic vortex clusters. It means that the spin textures are relevant to some external influence factors. Some terms may have an influence on the arrangements of spin textures. The study will be helpful for understanding the physical properties of magnetic skyrmions and merons. [ABSTRACT FROM AUTHOR]

In this paper, a low dropout (LDO) circuit based on a curvature compensation benchmark and closed-loop stability is designed. This circuit compensates for the higher order term of VBE in a BJT through the subthreshold characteristic of MOSFET and achieves the effect of curvature compensation. The bandgap reference circuit provides a stable input voltage for the LDO circuit, while the source follower and adaptive bias circuit improve the response speed and closed-loop stability of the LDO circuit. The temperature drift coefficient of the bandgap circuit is 8.11 ppm/°C, the input voltage is 3–5 V, the output voltage is 2.8 V, and the linear adjustment rate is 0.22%. [ABSTRACT FROM AUTHOR]

In my recent paper (hereafter "LU-ADV22"),[1] I used the Trajectory-mapped Ozonesonde dataset for the Stratosphere and Troposphere (TOST) obtained from the World Ozone and Ultraviolet Radiation Data Center (WOUDC),[[2]] latitude-altitude chlorofluorocarbon (CFC) distribution, time-series total ozone, Ozonesonde and Umkehr datasets, and lower stratospheric temperature climatology from multiple ground-based or satellite measurements to reveal the tropical ozone hole. The NOAA's BDBP Tier 1.4 dataset[[7]] is a vertically resolved, global, gap-free, and zonal mean dataset, which was created with a multiple-linear regression model based on monthly mean ozone concentrations that were calculated from several different satellite instruments and global ozone soundings, covering the period 1979-2007. 2, middle panel), and is comparable to the decrease of 5%-6% in total ozone or stratospheric ozone columns above 68 hPa at near-global (60°S-60°N) reported by Froidevaux I et al. i using the GOZCARDS data.[5] Second, reading throughout the paper by Weber I et al. i ,[39] one can find that they reported ozone trends using five merged zonal mean total ozone datasets from satellite and ground-based observations for the period of 1979-2020, instead of starting from 1964. According to the description by Liu I et al. i ,[2] the TOST ozone climatology has the following advantages: (1) it is 3D (latitudinally, longitudinally, and vertically) resolved; (2) its ozone data are obtained from an independent source and covers a record since 1965 that is twice as long as the satellite record; and (3) most crucially, I it depends on neither a priori dataset nor photochemical modeling and thus provides independent information and insights that can supplement satellite data and model simulations and enhance our understanding of stratospheric ozone i . [Extracted from the article]

As a non-invasive neuromodulation technology, transcranial magnetic stimulation (TMS) shows great potential in the treatment of mental diseases. Using TMS to stimulate deep brain targets has significant scientific research value for the exploration of the causes of psychiatric diseases. However, the focalized induced electrical field (E-field) generated by traditional TMS coils or coil arrays is largely restricted to superficial cortical targets. To achieve focalized stimulation in the deep brain, a novel spatially symmetric array based on curved θ-type coils (the θ-SSA) is proposed in this paper. Four θ-type coils in the array are symmetrical to the YZ and XZ planes. Each θ-type coil is placed tangent to the human scalp and bent away from the human head to reduce the non-longitudinal component accumulation of the induced E-field and enhance the stimulation focalization. The finite-element method is used to obtain the 3D spatial distributions of the intracranial induced E-field generated by the proposed array. Results show that the θ-SSA can form an obvious focusing area in the deep brain 11 cm below the scalp. Under identical stimulation current excitation, the θ-SSA can increase the intracranial longitudinal attenuation ratio by 77% compared to the traditional TMS coil. In addition, when generating the same focusing area, the stimulation depth of the θ-SSA is 1.67 times deeper than that of the traditional TMS coil. Meanwhile, the proposed array can dynamically steer the intracranial stimulated area, and the spatial coordinates of the intracranial stimulation target point can be flexibly and continuously adjusted when changing the stimulation current parameters applied to the array. An anatomically realistic human head model with gray matter is employed in this paper to verify our method. [ABSTRACT FROM AUTHOR]

In this paper, a transmission line with five spiral-wires in parallel was designed. The transit time and the characteristic impedance of the transmission line are 200 ns and 14 Ω, respectively. Its slow wave coefficient is close to 13. The insulating medium of the transmission line is glycerin. In order to investigate the breakdown strength of glycerin under a hundred-nanosecond pulse, simulations and experiments are conducted. The results indicate that the breakdown strength of glycerin under hundred nanoseconds reached 653 kV/cm, which is a 400 kV/cm increase compared with that under a microsecond pulse. However, under hundred nanoseconds, the breakdown strength of glycerin in transmission is unaffected by pressure within 1 MPa, and pressure is conducive to the insulation recovery of glycerin. [ABSTRACT FROM AUTHOR]

The excitation and suppression of asymmetric modes in a coaxial relativistic klystron amplifier (RKA) with cascaded single-gap bunching cavities are analyzed in this paper. Through theoretical analysis and simulated verification, we find that the asymmetric modes of cascaded single-gap bunching cavities have low external quality factors, the same resonant frequencies, and negative beam-loading conductance ratios so that they are easily excited by the electron beam. To solve this issue, a feasible method is proposed in this paper to suppress the asymmetric modes of cascaded single-gap bunching cavities, under the conditions of decreasing their coupling coefficients and increasing the frequency separation, choosing an appropriate drift tube length between them. These improved bunching cavities are further examined in an X-band coaxial RKA by 3D particle-in-cell simulation, which shows that high power microwaves with a power of 0.8 GW are generated corresponding to an efficiency of 40%. Furthermore, there is no asymmetric mode competition during 150 ns of simulation time. [ABSTRACT FROM AUTHOR]

Scientific collaboration has a complex hypernetwork structure. How to construct scientific collaboration in a complex system is an open issue. In this paper, a non-uniform dynamic collaborative evolution model is proposed. In the proposed method, each scholar is viewed as a node, and each cooperation relationship is regarded as a hyperedge. This model includes three processes: adding hyperedges, entering nodes, and forming hyperedges by new nodes. It is theoretically proved that the hyperdegree distribution of nodes follows the power law distribution. Furthermore, the effects of different parameters on the proposed model are numerically simulated in this paper. The experimental results are consistent with the theoretical ones. In addition, experiments show that the influence of nodes and hyperedges will affect the selection of old nodes when new nodes enter the network. This paper not only considers the construction of hyperedges with old nodes but also considers the possibility that new nodes construct new hyperedges among themselves. This model provides a reference for the research of the evolution process of scientific collaboration hypernetworks. [ABSTRACT FROM AUTHOR]

Aiming at the application requirements of multi-target microwave energy transmission, this paper proposes a multi-target microwave energy focusing method based on the genetic algorithm. This method optimizes the feeding phase first and then optimizes the feeding amplitude. By optimizing the feeding phase, the microwaves radiated by the antenna array unit tend to be superimposed in phase at each target point; furthermore, the energy distribution on the focal plane is optimized by optimizing the feeding amplitude. Two-target and three-target focusing methods are taken as examples to conduct microwave energy focusing simulation research. The results show that by using optimized-phase optimized-amplitude feeding, the total electric field strength at the two target points and the three target points is increased by 13% and 8.7%, respectively, compared with the optimized-phase constant-amplitude feeding. A 6 × 6 microstrip antenna array working at 5.8 GHz is designed to conduct two-target and three-target microwave energy focusing experiments. The experimental results verify the effectiveness of the multi-target focusing method proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper introduces an improved Halpin–Tsai model to predict the mechanical, thermal, and electrical properties of silicon-carbide-reinforced polypropylene composites. The model considers the influence of porosity and corresponding silicon-carbide volume fractions and derives relationships between material property shape factors and the aspect ratio, silicon-carbide volume fraction, and porosity. The improved model's predictions exhibit errors of 4.00% for mechanical properties, 2.13% for thermal properties, and 2.24% for electrical properties when compared to finite element analysis. This study demonstrates that the improved Halpin–Tsai model can effectively predict the properties of silicon-carbide-reinforced polypropylene composites, aiding in the design and optimization of these materials. [ABSTRACT FROM AUTHOR]

Defect detection on wafers holds immense significance in producing micro- and nano-semiconductors. As manufacturing processes grow in complexity, wafer maps may display a mixture of defect types, necessitating the utilization of more intricate deep learning models for effective feature learning. However, sophisticated models come with a demand for substantial computational resources. In this paper, we propose an efficient deep learning framework designed explicitly for mix-type wafer map defect pattern recognition. Our proposed model incorporates several crucial design elements, including lightweight convolutions, bottleneck residual connections, efficient channel attention mechanisms, and optimized activation functions, enabling it to learn spatial and channel features efficiently. We conduct evaluations on a real-world dataset containing 38 mixed-type defect patterns. The experimental results demonstrate that our framework maintains a high level of accuracy while possessing a compact parameter size and remarkably fast inference speed. [ABSTRACT FROM AUTHOR]

Gyrotrons are vacuum electronic devices capable of generating high-power, high-frequency THz radiation. With the increasing utilization of gyrotrons in thermonuclear fusion experimental devices, achieving higher output performance and ensuring stable and reliable operation have become key development goals. However, occasional radio frequency (RF) oscillation faults inside the gyrotron during long-pulse operation hinder its stable and reliable operation. Due to the difficulty in directly observing abnormal changes within the gyrotron resonator during operation, this paper explores a data-driven approach to diagnose RF oscillation faults in the gyrotron for the first time and proposes a classification model that combines K-Nearest Neighbors and Random Forest (KNN-RForest) algorithms for fault identification. Compared with seven baseline models, the results show that our proposed KNN-RForest model has a better classification performance. It is verified that data-driven methods can effectively identify RF oscillation faults in gyrotrons. Finally, the state probabilities of the gyrotron under different power levels were predicted using the KNN-RForest model, demonstrating the application of the KNN-RForest model in identifying gyrotron RF oscillation faults, which may be helpful for setting stable operating parameters for the gyrotron to reduce the likelihood of RF oscillation faults. [ABSTRACT FROM AUTHOR]

Metal based electroreflective devices (MERDs) have gained wide attention in recent years in the fields of smart windows and automotive glass due to their excellent photo-thermal modulation capability in the visible and near-infrared wavelength bands due to their high reflectivity. However, the high porosity due to the island-like growth of silver particles makes the devices susceptible to electrodeposited film breakage during prolonged energization or bleaching. This will seriously affect the effectiveness and stability of the device. In this paper, it is shown that the problem of Ag electrodeposition film fragmentation can be effectively overcome by replacing dimethyl sulfoxide solvent by N-methylpyrrolidone (NMP). The optical constants during film deposition were tested by the spectroscopic ellipsometry technique, and the porosity was calculated (reduced by 21.6%). The results show that MERDs with NMP as the solvent have more and more dispersed silver deposition sites, which leads to lower porosity of the silver deposited film during the deposition process. In addition, the lower turn-on voltage, greater contrast, longer memory effect, and greater coloring efficiency reveal that they are more promising for energy-saving applications. [ABSTRACT FROM AUTHOR]

Railway traffic plays a pivotal role within the current transportation system, with ensuring its safety being of paramount importance. Real-time monitoring of train track health through sensor technology has emerged as a significant approach for achieving this objective. However, a persistent challenge lies in providing cost-effective and stable power to sensors in remote areas. This paper proposes the utilization of a novel piezoelectric stack energy harvester in railway systems to address this issue. The substantial and consistent vibration energy produced by railway operations makes it an ideal source for energy harvesting, unaffected by environmental conditions. Through simulation analysis and experimental verification, this study explores the impact of load size, load frequency, and external resistance on the energy harvesting efficiency of the proposed piezoelectric stack energy harvester. The results indicate that the output power of the energy harvester increases with the load size. Furthermore, the frequency significantly influences the energy capture efficiency when below 8 Hz, with minimal impact on frequencies above 8 Hz. Interestingly, the load dramatically affects the energy capture efficiency, even at higher frequencies. With the external resistance set to 250 kΩ, the harvester achieves a maximum output power of 42.76 mW. [ABSTRACT FROM AUTHOR]

The gas blast arc-extinguishing lightning protection gap is a new type of lightning protection device based on airflow active arc-extinguishing. This paper establishes an airflow and arc mathematical model for calculating and analyzing air flow and arc motion processes. Besides, the finite element software ANSYS 14.0 is employed for the arc-extinguishing simulation in the pressure field, interaction arc, and airflow processes. Accordingly, the test analysis effects of the arc-extinguishing gap lightning protection test are verified. High-speed cameras, recording oscillograph arc-extinguishing images, and arc waveforms are employed in the process to obtain the airflow response time and arc-extinguishing time effectively based on the data analysis. Comparing the actual results with the simulation results demonstrates the arc-extinguishing reliability and provides an effective scientific basis for its practical application. [ABSTRACT FROM AUTHOR]

In recent years, a novel two-dimensional semiconductor ZrX2 (X = Cl, Br, and I) has been found to have excellent optoelectronic properties and has attracted much attention. In this paper, the elastic properties of two-dimensional Janus ZrXY (X/Y = Cl, Br, and I, X ≠ Y) are studied by first principles, including elastic parameters, such as elastic tensor components, Young's modulus, Poisson's ratio, and stability. Research has found that the lattice parameters of two-dimensional Janus ZrXY are still influenced by the atomic radius. The Janus structure shows excellent dynamic stability both before and after its construction. Based on the elastic theory, the mechanical stability of the two-dimensional Janus ZrXY was proved indirectly. After constructing the two-dimensional Janus ZrXY structure with different planes, the elastic tensor component increases to a certain extent, and Young's modulus and Poisson's ratio increase, but the anisotropy of Young's modulus and Poisson's ratio decreases significantly. [ABSTRACT FROM AUTHOR]

Steganography is widely recognized as an effective method for protecting information via digital media. This paper presents an innovative image steganography algorithm incorporating image compression, chaotic maps, and the least significant bit. The process begins with the compression of a confidential medical image using Huffman encoding. The compressed image then undergoes shuffling, facilitated by the chaotic logistic map. The bits from the shuffled image are discreetly embedded into randomly selected pixels of the cover image, guided by the chaotic piecewise smooth map. The resulting stego image is generated. Statistical analyses are applied to both the cover and stego images for evaluation. The proposed algorithm is compared against state-of-the-art algorithms, and the results demonstrate its superiority over existing methods. [ABSTRACT FROM AUTHOR]

It is crucial to explore new green energy sources to alleviate the earth's energy depletion and the impact of air pollution and greenhouse effects. Although wafer manufacturing is increasing worldwide, the implementation of carbon footprint policies necessitates a shift toward green electricity. To expand the scale of wafer manufacturing, it is essential to develop terrestrial green electricity, which requires additional terrestrial green energy sources. This paper presents a green energy harvesting method that generates wave hydraulic energy via a vibration-based electromagnetic generator through a buoy. An energy harvester composed of two magnets in series driven by a buoy via a connected pole is introduced. The sensitivity of induced electricity to the energy harvester's design parameters, including the magnets' geometric dimensions (diameter and height), the coil's turns, and layers, is analyzed. Additionally, the relationship between electricity and wave information (wave amplitude and wavelength) is explored. To evaluate the electrical power efficiency between a pair of single-magnet energy harvesters and the two-magnet harvester, a pair of parallel energy harvesters consisting of one magnet and paralleled in line is assessed. The impact of electricity on the horizontal span between the parallel energy harvesters is also investigated. To achieve maximal electricity, the two-magnet energy harvester is numerically optimized using a simulated annealing method. The numerical result shows that the two-magnet (in series) energy harvester can produce 0.472 W when the wavelength is 0.03, the amplitude is 0.09 m, and the wave speed is 3 m/s. [ABSTRACT FROM AUTHOR]

Achieving complete magnetization switching is a significant challenge in the electrical control of magnetic devices. In this paper, we propose a structure called bicomponent multiferroic nanomagnet (BMN) to study strain-mediated magnetization switching behavior. The BMN consists of a complete piezoelectric layer and a magnetostrictive layer made of bicomponent magnetic materials. Our team successfully developed a dynamic model for the magnetization of BMNs. By micromagnetic simulation, the results show that the strict requirements for a precise applied voltage period can be overcome in such a BMN, and a 180° magnetization switching can be achieved with only a square-wave voltage signal and a pulse width (tth) larger than 0.5 ns, given that the amplitude of the voltage is 60 mV. In addition, we also investigated the tolerance window of material composition and geometry, and proved that BMNs have sufficient error margins and the switching rate of BMNs can reach 1.67 GHz within the error margins at room temperature. Our proposed BMN device has a simple structure and low energy consumption as it does not require precise piezoelectric layer design or stringent voltage clocking requirements. The energy consumption per switching is only 7.3 aJ. These findings provide significant guidance for the design of nanomagnetic logic and memory devices and lay a strong foundation for the application of strain-mediated magnetization switching technology. [ABSTRACT FROM AUTHOR]