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The microstructure, texture, and mechanical properties of as-extruded and cold-rolled Mg–8Li–3Al–2Zn-1Gd-0.2Zr (LAZ832-1Gd-0.2Zr) alloys were investigated with the aim of strengthening the alloy by combining hot extrusion and cold rolling. Cold rolling does not change the phase composition of as-extruded LAZ832-1Gd-0.2Zr alloy, but introduces a larger number of dislocations and twins into alloy matrix. Cold rolling leads to the weakening of the original {0001} basal and {112‾0}-{011‾0} prismatic textures in α-Mg matrix, as well as the α and γ fiber textures in β-Li matrix. But new slip systems that are favorable for cold rolling are activated, resulting in the formation of {033‾8} pyramidal and new prismatic ({112‾0}⟨101‾4⟩ and {101‾0}⟨21‾1‾10⟩) texture components. Cold rolling further strengthens LAZ832-1Gd-0.2Zr alloy on the basis of hot extrusion, mainly through work hardening effect caused by introducing a large number of dislocations into α-Mg matrix. When the rolling reduction is 45%, the yield strength and tensile strength of LAZ832-1Gd-0.2Zr alloy are increased to 269.8 ± 4.0 and 308.6 ± 4.1 MPa, respectively, and the elongation is higher than 15%.

The carrier multiplication phenomenon involves hot carriers, which gain kinetic energy while accelerating to equilibrium with the established avalanching electric fields, and is typically explained via the local avalanche model. This work presents two vertical Ge-on-Si avalanche photodetectors fabricated in a separate absorption, charge, and multiplication configuration. Uniformity in materials, doping densities, and device dimensions is maintained, except for the multiplication width, which is used as a control parameter to manipulate avalanching fields under identical electric biasing and illumination schemes. Nonlocal carrier multiplication model is implemented during analysis of the extracted current-voltage signatures under small and large reverse biasing arrangements. For such an APD characterized by thinner multiplication region $\left ({{W_{m}=0.1 ~\mu m}}\right)$ , reduced linear and Geiger-mode multiplication regimes are perceived to be at play, outperforming the device having thicker multiplication region in almost all related figures of merit, e.g., responsivity $(22.58 \mathrm {A/W})$ , photo-to-dark current ratio $(\sim {10}^{5})$ , normalized photo-to-dark current ratio $(2.5\times {10}^{9} \mathrm {W}^{-1})$ , specific detectivity $(7.45\times {10}^{12}\mathrm {Jones})$ , and noise equivalent power $(\sim 2.42\times {10}^{-15} \mathrm {W/}\sqrt {\mathrm {Hz}})$ . The enhanced performance characteristics are due to excessively strong avalanching fields, reduced thermal charge density, and negligible dead space compared to its counterpart characterized by thicker multiplication width.

In this paper, we propose a lightweight lithography machine learning-based hotspot detection model that integrates the Squeeze-and-Excitation (SE) attention mechanism and the Efficient Channel Attention (ECA) mechanism. These mechanisms can adaptively adjust channel weights, significantly enhancing the model’s ability to extract relevant features of hotspots and non-hotspots through cross-channel interaction without dimensionality reduction. Our model extracts feature vectors through seven convolutional layers and four pooling layers, followed by three fully connected layers that map to the output, thereby simplifying the CNN network structure. Experimental results on our collected layout dataset and the ICCAD 2012 layout dataset demonstrate that our model is more lightweight. By evaluating overall accuracy, recall, and runtime, the comprehensive performance of our model is shown to exceed that of ConvNeXt, Swin transformer, and ResNet 50.

Background: The role of an entrepreneur's internal dispositions and external support mechanisms in influencing self-efficacy remains a subject of keen interest. The Bojonegoro region, with its unique entrepreneurial landscape, provides a rich context for such exploration. Objective: To unravel the intricate relationships which shape an entrepreneur's self-efficacy, focusing primarily on the contributions of Learning Goal Orientation (LGO) and Mentoring Function (MF). Method: A questionnaire-based approach was employed targeting 30 small and medium-sized enterprises (SMEs) in Bojonegoro, using the purposive sampling method. The gathered data was meticulously analyzed using SPSS's 25th edition under multiple linear regression analysis. Results: Findings highlighted the significant positive effect of LGO on Entrepreneur Self-Efficacy. While MF alone did not directly influence self-efficacy, its combined effect with LGO showcased a synergistic positive impact. Conclusion: The research underscores the importance of both an entrepreneur's learning mindset and effective mentoring in shaping self-efficacy. Emphasizing these factors can offer a more holistic approach to entrepreneurial training and development programs, especially in regions akin to Bojonegoro. Keywords: Entrepreneur Self-Efficacy, Learning Goal Orientation (LGO), Mentoring Function (MF), Small and Medium-sized Enterprises (SMEs)

To mitigate the impact of low-frequency noise from the tunnel magnetoresistance (TMR) current sensor and ambient stray magnetic fields on weak current detection accuracy, we propose a high-resolution modulation-demodulation test method. This method modulates and demodulates the measurement signal, shifting low-frequency noise to the high-frequency band for effective filtering, thereby isolating the target signal from the noise. In this study, we developed a Simulink model for the TMR current sensor modulation-demodulation test method. Practical time-domain and frequency-domain tests of the developed high-resolution modulation-demodulation method revealed that the TMR current sensor exhibits a nonlinearity as low as 0.045%, an enhanced signal-to-noise ratio (SNR) of 77 dB, and a heightened resolution of 100 nA. The findings indicate that this modulation-demodulation test method effectively reduces the impact of low-frequency noise on TMR current sensors and can be extended to other types of resistive devices.

The micro-arc oxidation coatings (MAO) coatings formed on the magnesium (Mg) matrix usually have various porosity in the cross-section due to the uneven thermal stress, resulting in the non-consistent compact density in the external and inner layer. However, the consistency of the compact density in the cross-section is less concerned, and its effect on the surficial anti-corrosion and mechanical properties is still unclear. Herein, we employed the Zirconium Oxide particles as a heat-absorbing agent to tune the temperature gradient and achieved the in situ growth of MAO coatings on Mg alloy with a tunable compact density in the external layer and inner layer separately. It is found that compact density plays a key role in corrosion resistance, while the consistency of compact density along the cross-section is very crucial for the mechanical properties. Increasing the compact density and reducing its gradual difference could significantly enhance both the anti-corrosion and mechanical properties. The effect of the inconsistent compact density on the anti-corrosion property could be weakened by reducing the porosity on the external layer, but the simulation results demonstrate its effect on the mechanical properties would be strengthened due to the stress concentration. MAO coatings with homogeneous and compact structures in the cross-section present superior anti-corrosion properties and excellent mechanical properties.

An efficient transmission line model of high-speed cables is established, to predict its response at a high-frequency region (up to 20 GHz). Especially, an appropriate conformal mapping technique is applied to formulate the per-unit-length parameters of high-speed cables. Moreover, the skin and proximity effects of the conducting wires and the outer shield are derived in the closed form. As a result, the AC resistance/ inductance of all the conducting materials due to the skin and proximity effects are accurately incorporated for both layered and unlayered conductors. Furthermore, the mixed-mode S-parameters are precisely predicted for both balanced and unbalanced transmission line cables in the high-frequency region. In addition, the effects of the nonuniformities and cable geometry deformation on the mode conversions are also investigated. The proposed model is firstly validated with commercial software tools, COMSOL, FEKO, and HFSS; then, we further performed physical measurements to verify our new algorithm.

Magnetic tunnel junctions have been widely used in various applications, such as magnetic sensors and magnetic random-access memories. In the practical application of MTJs, they are usually used in series toward high sensitivity and high stability, especially for sensor applications. In this paper, serial MTJs devices on 8 in. wafers were fabricated. The temperature dependence of the tunnel magnetoresistance ratio, resistances in parallel and antiparallel configurations, and dynamic conductance were systematically investigated. The results of serial MTJs devices are consistent with a single MTJ device. This research suggests that serial MTJs can be directly used to investigate the magnetic tunneling properties of MTJ stacks.

The successful doping of Yttrium (Y) in the Mg-Al layered double hydroxide film (MgAlY-LDHs) is obtained by hydrothermal way on the anodic oxide film of Mg-2Zn-4Y alloys. The composition, morphology and structure of MgAlY-LDHs were characterized by the Fourier transform infrared spectroscopy (FT-IR), X-ray diffractometer (XRD), field-emission scanning electronic microscope (FE-SEM) and energy dispersive spectrometry (EDS) respectively. The electrochemical behavior was observed by polarization curves and electrochemical impedance spectroscopy (EIS). Y ions can be incorporated into the MgAl-LDHs film in a completely isomorphic replacement manner and have the ability to improve the corrosion resistance of the film. Moreover, the ternary LDHs film grown in situ on the Mg-2Zn-4Y alloy provides a high possibility for the corrosion resistance of industrial metals. The schematic representation of electrochemical behavior and the growth mechanism of MgAlY-LDHs nanosheet are as following eventually.

The access of wind power can replace the power generation of conventional units and thus has a positive value, and it will also change the operation mode of different types of units in the system and bring negative value. In order to analyze the value of wind power integration, a pre-optimized scheduling model for wind turbines was established. The characteristics of different units, the randomness and error of load and wind power were considered in the model. The influences of wind power penetration rate, load and wind power prediction error and load and wind power correlation on wind power value were analyzed. The results show that wind power has the value of reducing the operating cost of the system when the wind power penetration rate is low. When the wind power penetration rate is high, the wind power does not have the value of grid connection due to the increase of the unit's start-stop cost.

Workflow fine control is an important research tool for the mediating effect of teacher burnout. Based on the fine control theory of workflow, this paper constructs a mediating effect model of teacher burnout in primary and secondary school teachers from the perspective of informal learning. The model designs a measurement scale based on the results of fine control, and the scale is revised through informal learning pretests to form the logical frame analysis loop of this paper. The scale uses Likert 5-point scoring, from 1.5 to represent never, rarely, occasionally, often, and always, which solves the difficulty of quantitative analysis of teacher burnout data. During the simulation process, SPSS 20.0 and AMOS 7.0 were used to conduct empirical analysis, exploratory factor analysis and confirmatory factor analysis on the survey data, and the measurement scales were tested. The empirical analysis results show that this paper uses cluster sampling and random sampling to carry out a questionnaire survey on 1022 primary and secondary school teachers. The measurement scale includes 19 items. Through exploratory factor analysis and confirmatory factor analysis, the control method is determined. In two dimensions, the revised control style questionnaire has a reliability of 0.951, and items with factor loadings less than 0.5 are eliminated, which effectively improves the control performance of informal learning.

This work presents a monolithically integrated temperature and humidity sensor based on microelectromechanical systems technology. The temperature sensor working on the “bi-metallic” effect has the advantages of wide temperature range, high sensitivity, and fast detection. The humidity sensor has a polyimide parallel plate capacitive structure with the microporous array on the upper electrode designed for high sensitivity and fast response. Numerical analysis and COMSOL simulation showed that the temperature detection sensitivity is 0.2 mV/°C in the range of 193–393 K and humidity sensitivity is 0.405 pF/% relative humidity (RH) with the response time of 34 s in the humidity range of 0%–100% RH. The integrated temperature and humidity sensor has the advantages of small dimension, wide detection range, high precision, and fast response.

In order to explore the influence of interlayer between dielectric layer and channel layer on performance of thin film transistors (TFTs), the single layer titanium doped zinc oxide (TiZO) TFTs and the dual layer indium tin oxide (ITO)/TiZO TFTs were fabricated successfully in this work. The effects of interlayer thickness on the performance of TFTs were studied and the optimal thickness condition was obtained. The experimental results indicate that the introduction of interlayer contributes to the improvement of TFT characteristics. In addition, the dual-layer ITO/TiZO TFTs also present a good uniformity, which is suitable for large-area display applications.

In recent years, compute-in-memory (CIM) has been extensively studied to improve the energy efficiency of computing by reducing data movement. At present, CIM is frequently used in data-intensive computing. Data-intensive computing applications, such as all kinds of neural networks (NNs) in machine learning (ML), are regarded as ‘soft’ computing tasks. The ‘soft’ computing tasks are computations that can tolerate low computing precision with little accuracy degradation. However, ‘hard’ tasks aimed at numerical computations require high-precision computing and are also accompanied by energy efficiency problems. Numerical computations exist in lots of applications, including partial differential equations (PDEs) and large-scale matrix multiplication. Therefore, it is necessary to study CIM for numerical computations. This article reviews the recent developments of CIM for numerical computations. The different kinds of numerical methods solving partial differential equations and the transformation of matrixes are deduced in detail. This paper also discusses the iterative computation of a large-scale matrix, which tremendously affects the efficiency of numerical computations. The working procedure of the ReRAM-based partial differential equation solver is emphatically introduced. Moreover, other PDEs solvers, and other research about CIM for numerical computations, are also summarized. Finally, prospects and the future of CIM for numerical computations with high accuracy are discussed.

A novel VDMOS with Step Floating Islands VDMOS (S-FLI VDMOS) is proposed for the first time in this letter, in order to optimize the breakdown voltage (BV) and the specific on-resistance (Ron,sp). The innovative terminal technology of Breakdown Point Transfer (BPT) is applied to S-FLI VDMOS, which transfers the breakdown point from the high electric field region to the low electric field region, and the S-FLI VDMOS structure uses multiple layers of charge compensation blocks to generate multiple electric field peaks in the drift region in order to optimize the electric field distribution. In the TCAD simulation, the BV of the proposed S-FLI VDMOS is improved to 326 V, which is higher than that of 281 V for the conventional Si VDMOS with the same drift region length of 15 μm, and the Ron,sp is reduced from 21.54 mΩ·cm2 for the conventional Si VDMOS to 7.77 mΩ·cm2 for the S-FLI VDMOS. Compared with the conventional Si VDMOS, the current density of the effective current conduction path is increased when the forward bias is applied to the proposed device.

It is well known that the vertical tunnel field effect transistor (TFET) is easier to fabricate than the conventional lateral TFETs in technology. Meanwhile, a lightly doped pocket under the source region can improve the subthreshold performance of the vertical TFETs. This paper demonstrates a dual material gate heterogeneous dielectric vertical TFET (DMG-HD-VTFET) with a lightly doped source-pocket. The proposed structure adopts a GaSb/GaAs0.5Sb0.5 heterojunction at the source and pocket to improve the band-to-band tunneling (BTBT) rate; at the same time, the gate electrode is divided into two parts, namely a tunnel gate (M1) and control gate (M2) with work functions ΦM1 and ΦM2, where ΦM1 > ΦM2. In addition, further performance enhancement in the proposed device is realized by a heterogeneous dielectric corresponding to a dual material gate. Simulation results indicate that DMG-HD-VTFET and HD-VTFET possess superior metrics in terms of DC (Direct Current) and RF (Radio Frequency) performance as compared with conventional VTFET. As a result, the ON-state current of 2.92 × 10−4 A/μm, transconductance of 6.46 × 10−4 S/μm, and average subthreshold swing (SSave) of 18.1 mV/Dec at low drain voltage can be obtained. At the same time, DMG-HD-VTFET could achieve a maximum fT of 459 GHz at 0.72 V gate-to-source voltage (Vgs) and a maximum gain bandwidth (GBW) of 35 GHz at Vgs = 0.6 V, respectively. So, the proposed structure will have a great potential to boost the device performance of traditional vertical TFETs.

The general preparation method of large-area, continuous, uniform, and controllable vdW heterostructure materials is provided in this paper. To obtain the preparation of MoS2/h-BN and WS2/h-BN heterostructures, MoS2 and WS2 material are directly grown on the insulating h-BN substrate by atmospheric pressure chemical vapor deposition (APCVD) method, which does not require any intermediate transfer steps. The test characterization of MoS2/h-BN and WS2/h-BN vdW heterostructure materials can be accomplished by optical microscope, AFM, Raman and PL spectroscopy. The Raman peak signal of h-BN material is stronger when the h-BN film is thicker. Compared to the spectrum of MoS2 or WS2 material on SiO2/Si substrate, the Raman and PL spectrum peak positions of MoS2/h-BN heterostructure are blue-shifted, which is due to the presence of local strain, charged impurities and the vdW heterostructure interaction. Additionally, the PL spectrum of WS2 material shows the strong emission peak at 1.96 eV, while the full width half maximum (FWHM) is only 56 meV. The sharp emission peak indicates that WS2/h-BN heterostructure material has the high crystallinity and clean interface. In addition, the peak position and shape of IPM mode characteristic peak are not obvious, which can be explained by the Van der Waals interaction of WS2/h-BN heterostructure. From the above experimental results, the preparation method of heterostructure material is efficient and scalable, which can provide the important support for the subsequent application of TMDs/h-BN heterostructure in nanoelectronics and optoelectronics.

China is currently experiencing a significant increase in the live-streaming industry, driven by high profitability and sales. The increasing prevalence of live-stream platforms has also contributed to the rise of influencers who possess larger fan bases and greater bargaining power. In the cosmetic sector, consumers often require firsthand experience with products in order to feel satisfied, which can create uncertainty in their purchase intentions. Live streaming is a recognised marketing strategy that allows firms to leverage the popularity of influencers to convert buying intentions into actual buying behaviour. This study aims to investigate the factors that influence consumer purchase intention in relation to influencer popularity. This study aims to investigate the mediating role of perceived enjoyment and uncertainty, as well as the moderating role of product information, in the relationship between influencer popularity and purchase intention. This study expands the existing knowledge of the S-O-R model by gathering data from Taobao live streaming. The collected data was analysed using SPSS version 26 and structural equation modelling (SEM) with SmartPLS 3.3.9. The study's findings indicate that the impact of influencer popularity on consumer buying intention is partially mediated by perceived uncertainty and perceived enjoyment. Furthermore, studies have demonstrated the significant moderating role of the quality of product information. The results suggest that cosmetic companies should offer comprehensive product information to influencers when showcasing their products during live streaming events. The live streaming industry can enhance product preparation and information dissemination for online marketing. [ABSTRACT FROM AUTHOR]

University students in China are increasingly embracing the use of celebrity endorsement in teaching. Celebrities are now able to rapidly and easily reach a huge audience because of the growth of social media platforms like WeChat, Weibo, and Douyin, which makes them an appealing marketing tool for educational institutions. The potential advantages of leveraging celebrity endorsements to advertise their programs and draw students have been acknowledged by educational institutions in China. In addition to examining educational celebrity endorsement and educational purchase intention attainment, the study examines students' desire to act as moderators and planned behavior theory in Chinese universities. 440 students from various Chinese universities participated in an online and in-person survey that collected the data for the analysis. According to the findings of structural equation modeling (SEM), teaching strategies have a positive impact on students' desires. The study's results also showed a connection between achieving educational purchase intentions and celebrity endorsement of educational products, student consumer choice, and student desire. Cross-sectional analysis, close-ended questions, and quantitative research are all used in the current study. In light of this, it is deemed crucial to use creative and engaging teaching strategies in the higher education sector. Educational institutions can create marketing plans that boost students' purchasing intentions and enrollment levels by focusing on attitudes, arbitrary standards, and perceived behavioral control. To demonstrate the relationships between the constructs under consideration, future research on this topic should involve longitudinal or field testing. There are major policy recommendations, calls for future research, and recommended theoretical and practical implications. [ABSTRACT FROM AUTHOR]