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Due to the limitation of inherent ultra-high electron concentration, the electrical properties of In2O3 resemble those of conductors rather than semiconductors prior to special treatment. In this study, the effect of various annealing treatments on the microstructure, optical properties, and oxygen vacancies of the films and transistors is systematically investigated. Our finding reveals a progressive crystallization trend in the films with increasing annealing temperature. In addition, a higher annealing temperature is also associated with the reduction in the concentration of oxygen vacancies, as well as an elevation in both optical transmittance and optical bandgap. Furthermore, with the implementation of annealing process, the devices gradually transform from no pronounced gate control to exhibit with excellent gate control and electrical performances. The atomic layer deposited Hf-doped In2O3 thin film transistor annealed at 250 °C exhibits optimal electrical properties, with a field-effect mobility of 18.65 cm2 V−1 s−1, a subthreshold swing of 0.18 V/dec, and an Ion/Ioff ratio of 2.76 × 106. The results indicate that the impact of varying annealing temperatures can be attributed to the modulation of oxygen vacancies within the films. This work serves as a complementary study for the existing post-treatment of oxide films and provides a reliable reference for utilization of the annealing process in practical applications. [ABSTRACT FROM AUTHOR]

Objective To evaluate the effectiveness and satisfaction of the experiential teaching method based on self-monitoring of blood glucose (SMBG) in endocrinological training module. Methods Forty-two eight-year medical students who were undergoing clinical clerkship rotation in the Department of Endocrinology, Peking University People's Hospital from April 2018 to December 2018 were enrolled in the study. They were randomly divided into the experimental group and the control group with twenty-one in each. The experimental group adopted SMBG-based experiential teaching and the control group was given traditional theoretical teaching. In-class tests were conducted to evaluate the teaching effect after class, and a satisfaction survey was taken out after internship. Results The score of in-class test from experimental group was 8.7±1.4, which was significantly higher than that from control group (7.2±2.3 )(P＜0.01). The questionnaire survey showed that teaching satisfaction score from the students of experimental group was 141.2±0.6, which was higher than that of students from control group(129.8±0.7),(P＜0.01). Conclusions In the endocrinological training module, the application of SMBG-based experiential teaching used in clinical training of endocrinology has achieved good teaching results and is well acknowledged by trainees of clerkship rotation.

We consider a transmission scheme of Rate Splitting Multiple access systems over a power line communication channel in this paper. The System model consists of a transmitter and K users, and superimposing signals for K users at the transmitter. Our aim is to maximize the worst transmission rate between users in the system by jointly optimizing the precoder vector and rate allocation with the method of successive convex approximation(SCA). The simulation results manifest that compared with PLC-NOMA, PLC-RSMA adapts to various channel directions (regardless of whether the channel directions are aligned or orthogonal) and network load (underload or overload), PLC-RSMA can reach better transmission rate performance, and as the SNR augment, the rate performance gain of PLC-RSMA becomes more and more obvious. Under the set parameters, when the SNR is 30 dB, the relative rate performance of PLC-RSMA is improved by at least 27% compared to PLC-NOMA.

COVID-19 vaccine coverage remains low for US children, especially among those living in rural areas and the Southern/Southeastern US. As of 12 September 2023, the CDC recommended bivalent booster doses for everyone 6 months and older. Emerging research has shown an individual may be vaccine hesitant and also choose to receive a vaccine for themselves or their child(ren); however, little is known regarding how hesitant adopters evaluate COVID-19 booster vaccinations. We used an exploratory qualitative descriptive study design and conducted individual interviews with COVID-19 vaccine-hesitant adopter parents (n = 20) to explore COVID-19 parental intentions to have children receive COVID-19 boosters. Three primary themes emerged during the analysis: risk, confidence, and intent, with risk assessments from COVID-19 and COVID-19 vaccine confidence often related to an individual parent’s intent to vaccinate. We also found links among individuals with persistent concerns about the COVID-19 vaccine and low COVID-19 vaccine confidence with conditional and/or low/no intent and refusal to receive recommended boosters for children. Our findings suggest that healthcare providers and public health officials should continue making strong recommendations for vaccines, continue to address parental concerns, and provide strong evidence for vaccine safety and efficacy even among the vaccinated.

Metal-coated lattice structures hold significant promise for customizing mechanical properties in diverse industrial applications, including the mechanical arms of unmanned aerial vehicles. However, their intricate geometries pose computational challenges, resulting in time-intensive and costly numerical evaluations. This study introduces a parameterization-based multiscale method to analyze body-centered cubic lattice structures with metal coatings. We establish the validity and precision of our proposed method with a comparative analysis of numerical results at the Representative Volume Element (RVE) scale and experimental findings, specifically addressing both elastic tensile and bending stiffness. Furthermore, we showcase the method’s accuracy in interpreting the bending stiffness of coated lattice structures using a homogenized material-based solid model, underscoring its effectiveness in predicting the elastic properties of such structures. In exploring the mechanical characterization of coated lattice structures, we unveil positive correlations between elastic tensile stiffness and both coating thickness and strut diameter. Additionally, the metal coating significantly enhances the structural elastic bending stiffness multiple times over. The diverse failure patterns observed in coated lattices under tensile and bending loads primarily stem from varied loading-induced stress states rather than external factors. This work not only mitigates computational challenges but also successfully bridges the gap between mesoscale RVE mechanical properties and those at the global structural scale.

Classifying and summarizing large data sets from different sky survey projects is essential for various subsequent scientific research. By combining data from 4XMM-DR13, Sloan Digital Sky Survey (SDSS) DR18, and CatWISE, we formed an XMM-WISE-SDSS sample that included information in the X-ray, optical, and infrared bands. By cross matching this sample with data sets from known spectral classifications from SDSS and LAMOST, we obtained a training data set containing stars, galaxies, quasars, and young stellar objects (YSOs). Two machine learning methods, CatBoost and Self-Paced Ensemble (SPE), were used to train and construct machine learning models through training sets to classify the XMM-WISE-SDSS sample. Notably, the SPE classifier showed excellent performance in YSO classification, identifying 1102 YSO candidates from 160,545 sources, including 258 known YSOs. Then we further verify whether these candidates are YSOs by the spectra in LAMOST and the identification in the SIMBAD and VizieR databases. Finally there are 412 unidentified YSO candidates. The discovery of these new YSOs is an important addition to existing YSO samples and will deepen our understanding of star formation and evolution. Moreover we provided a classification catalog for the whole XMM-WISE-SDSS sample.

Actuators play a crucial role in microelectromechanical systems (MEMS) and hold substantial potential for applications in various domains, including reconfigurable metamaterials. This research aims to design, fabricate, and characterize structures for the actuation of the EMA. The electromagnetic actuator overcomes the lack of high drive voltage required by other actuators. The proposed actuator configuration comprises supporting cantilever beams with fixed ends, an integrated coil positioned above the cantilever’s movable plate, and a permanent magnet located beneath the cantilever’s movable plate to generate a static magnetic field. Utilizing flexible polyimide, the fabrication process of the EMA is simplified, overcoming limitations associated with silicon-based micromachining techniques. Furthermore, this approach potentially enables large-scale production of EMA, with displacement reaching up to 250 μm under a 100 mA current, thereby expanding their scope of applications in manufacturing. To demonstrate the function of the EMA, we integrated it with a metamaterial structure to form a compact, tunable terahertz absorber, demonstrating a potential for reconfigurable electromagnetic space.

Auxin response factors (ARFs) are pivotal transcription factors involved in many aspects of auxin-dependent developmental processes. While functions of ARFs have been extensively studied in Arabidopsis, their distinct role in cucumber remains unclear. In this study, a cucumber auxin response factor homolog, CsARF10a, was cloned and overexpressed in tomato plants. RT-qPCR analysis indicated that the expression abundance of CsARF10a was significantly decreased in cucumber leaves and female flowers, and the expression level of CsARF10a was relatively low in pollinated fruits and hormone-treated fruits compared with that in unpollinated fruits. Moreover, the overexpression of CsARF10a in tomato resulted in multiple phenotypic changes, including a wider leaf blade, delayed fruit ripening, and parthenocarpic fruit set in CsARF10a-OE lines. Taken together, our research shed light on the regulatory importance of CsARF10a in regulating various phenotype alterations and laid a solid foundation for further functional studies.

Forced convection is the most effective way to improve the thermal efficiency of a radiator under low-temperature conditions. This technical method differs significantly from the heating effects of general radiation and natural convection. Few studies have applied the objective evaluation method based on quantitative calculation to evaluate the effectiveness of indoor heating or optimize the technical parameters (air flow rate, air supply method, etc.) of heating systems. This article couples human metabolic factors with heating environmental factors and uses a 57-node human thermal physiological model to evaluate the effectiveness of forced convection radiator heating from the perspective of the local thermal comfort of the human body and demonstrates the feasibility of this scheme by comparing it with floor radiation heating. The research shows that the air supply speed of a radiator affects human thermal comfort. Continuing to increase the wind speed, at a speed of 3 m/s, the surface temperature of the human body reaches a high value and will then decrease, leading to a decrease in thermal comfort. Research on indoor air distribution shows that the use of bottom-side air supply provides better thermal comfort compared to top air supply. The local skin temperature distribution of the human body indicates that when the indoor average temperature is higher than 20 °C, the overall thermal comfort of convective radiator heating and floor radiant heating is comparable. The article provides a way of objectively calculating and directly quantifying the effect of heating equipment on human thermal physiological parameters.

Research on the efficiency and quality issues faced in aircraft assembly was conducted in this article. A new method of human–machine collaborative riveting was proposed, which combined the flexibility of manual collaboration with the precise control of automatic riveting. The research works include: (1) a theoretical model of pneumatic hammer riveting was established to clarify the principle and parameters of riveting process. (2) A smart bucking bar was designed to support the data collection and extraction of manual collaborative riveting process. (3) An automatic riveting experimental platform was designed to test the automatic riveting process incorporating the extracted manual riveting process parameters, and further an optimization strategy was proposed for the automatic riveting process. (4) A human–machine collaborative riveting experimental platform was developed to conduct the verification work. Through the theoretical analysis, experimental research, system scheme design, and process parameters optimization, the application and verification of human–machine collaborative assembly technology have been achieved. This technology is expected to be comprehensively promoted in the field of aircraft manufacturing, and for breaking through the current difficulties of low production efficiency and poor assembly quality control.

Lattice structures are a group of cellular materials composed of regular repeating unit cells. Due to their extraordinary mechanical properties, such as specific mechanical strength, ultra-low density, negative Poisson’s ratio, etc., lattice structures have been widely applied in the fields of aviation and aerospace, medical devices, architecture, and automobiles. Hybrid additive manufacturing (HAM), an integrated manufacturing technology of 3D printing processes and other complementary processes, is becoming a competent candidate for conveniently delivering lattice structures with multifunctionalities, not just mechanical aspects. This work proposes a HAM technology that combines vat photopolymerization (VPP) and electroless plating process to fabricate smart metal-coated lattice structures. VPP 3D printing process is applied to create a highly precise polymer lattice structure, and thereafter electroless plating is conducted to deposit a thin layer of metal, which could be used as a resistive sensor for monitoring the mechanical loading on the structure. Ni-P layer and copper layer were successfully obtained with the resistivity of 8.2×10−7Ω⋅m and 2.0 ×10−8 Ω⋅m, respectively. Smart lattice structures with force-loading self-sensing functionality are fabricated to prove the feasibility of this HAM technology for fabricating multifunctional polymer-metal lattice composites.

Nowadays, additive manufacturing (AM) is advanced to deliver high-value end-use products rather than individual components. This evolution necessitates integrating multiple manufacturing processes to implement multi-material processing, much more complex structures, and the realization of end-user functionality. One significant product category that benefits from such advanced AM technologies is 3D microelectronics. However, the complexity of the entire manufacturing procedure and the various microstructures of 3D microelectronic products significantly intensified the risk of product failure due to fabrication defects. To respond to this challenge, this work presents a defect detection technology based on deep learning and machine vision for real-time monitoring of the AM fabrication process. We have proposed an enhanced YOLOv8 algorithm to train a defect detection model capable of identifying and evaluating defect images. To assess the feasibility of our approach, we took the extrusion 3D printing process as an application object and tailored a dataset comprising a total of 3550 images across four typical defect categories. Test results demonstrated that the improved YOLOv8 model achieved an impressive mean average precision (mAP50) of 91.7% at a frame rate of 71.9 frames per second.