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Abstract Background Case-based learning (CBL) utilizing three-dimensional (3D) printed hip joint models is a problem-solving teaching method that combines the tactile and visual advantages of 3D-printed models with CBL. This study aims to investigate the impact of integrating 3D printing with CBL on learning developmental dysplasia of the hip (DDH). Methods We conducted a prospective study from 2022 to 2023, including 120 fourth-year clinical medical students at Xuzhou Medical University. Students were randomly allocated into two groups of 60 participants each. The CBL group received conventional CBL teaching methods, while the 3D + CBL group utilized 3D-printed models in conjunction with CBL. Post-teaching, we analyzed and compared the theoretical and practical achievements of both groups. A questionnaire was designed to assess the impact of the educational approach on orthopedic surgery learning. Results The theory scores of the CBL group (62.88 ± 7.98) and 3D + CBL group (66.35 ± 8.85) were significantly different (t = 2.254, P = 0.026); the practical skills scores of the CBL group (57.40 ± 8.80) and 3D + CBL group (63.42 ± 11.14) were significantly different (t = 3.283, P = 0.001). The questionnaire results showed that the 3D + CBL group was greater than the CBL group in terms of hip fundamentals, ability to diagnose cases and plan treatments, interesting teaching content, willingness to communicate with the instructor and satisfaction. Conclusions The integration of 3D printing with case-based learning has yielded positive outcomes in teaching DDH, providing valuable insights into the use of 3D-printed orthopedic models in clinical education.

Hydraulic support leg pressure serves as a crucial indicator for assessing work face support quality. Current evaluation methods for support quality primarily concentrate on static analyses-like inadequate initial support force, pressure overrun, and uneven bracket force-while neglecting dynamic column pressure changes. This paper introduces a model for assessing hydraulic support quality using deep learning techniques. Real-time data is preprocessed into a spatio-temporal pressure sub-matrix sample, which is then inputted into the model. This process assesses the support quality type and characterizes its dynamic evolution within the area. The model facilitates the identification of dynamic support quality effects in the working face area, aiding operators in making targeted adjustments to hydraulic support status. Experimental results revealed that the optimized LeNet-5 network-adjusting parameters like convolutional layer count, kernel size, and ReLU activation function-achieved the highest classification accuracy of 85.25 % for support quality, surpassed other networks. Furthermore, the improved LeNet-5 network outperformed other networks in both F1 score and recall. Additionally, the improved LeNet-5 network achieved faster convergence to the optimal solution, accelerated training speed. This highlighted its advantages in evaluating the spatio-temporal support quality of hydraulic supports in smart mining operations.

Even though some recent research revealed individuals with HSA typically display enhanced processing in the early stages of emotional information processing due to hypervigilance and vulnerability to negative stimuli, it is still unclear whether social anxiety affects the time course underlying processing bias for emotional stimuli. Therefore, the present study aimed to explore the early stage of processing social threat stimuli in high social anxiety (HSA) individuals by recording RTs and EEG data in the emotional Stroop task. Behavioral data showed that the HSA group responded to the threat words faster than neutral words (i.e. negative bias), but no emotional effects in the low social anxiety (LSA) group. Although the P1 component did not show any early effects, ERP data exhibited an enhanced N170 for HSA than for LSA groups. Threat words elicited larger N170 than neutral words in the LSA group only; this emotion effect was not evident in the HSA group. These findings indicated that social anxiety modulates early processing for social threat words. This study revealed the neural mechanisms underlying early emotional processing in individuals with social anxiety, providing insights for the evaluation and intervention of social anxiety. [ABSTRACT FROM AUTHOR]

This study investigates NaY9Si6O26 ceramics prepared through the solid‐phase method, focusing on their microwave dielectric properties and crystallographic characteristics. X‐ray diffraction analysis reveals a hexagonal crystal structure for NaY9Si6O26 ceramics within the P63/m (176) space group. Rietveld refinement analysis precisely determines the lattice constants as a = b = 9.3423 Å, c = 6.7524 Å, and a unit cell volume of V = 510.3877 Å3. Additionally, Raman spectroscopy unveils a noteworthy correlation between the quality factor and the full width at half maximum of the A1g(O) mode at 878 cm−1. The structural attributes, including lattice fringes and diffraction patterns of hexagonal NaY9Si6O26 ceramics, are elucidated through transmission electron microscopy. Of significance are the microwave dielectric properties of NaY9Si6O26 ceramics sintered at 1465°C, revealing a relative permittivity (εr) of 10.42, an impressive Q × f product of 33 766 GHz (at f = 11.14 GHz), and a temperature coefficient of resonant frequency (τf) of −28.7 ppm/°C. This comprehensive investigation contributes to the understanding of both the structural and microwave dielectric characteristics of NaY9Si6O26 ceramics, with potential applications in advanced electronic devices. [ABSTRACT FROM AUTHOR]

This study delves into the microwave dielectric properties of Li2Y9(SiO4)6O2F ceramics, synthesized using the conventional solid-state method. By employing x-ray diffraction analysis and meticulous data refinement across various temperatures, we unequivocally confirm the hexagonal crystal structure of Li2Y9(SiO4)6O2F ceramics. The refined lattice parameters, observed at a sintering temperature of 1275°C, exhibit a = b = 9.33318 Å, c = 6.71725 Å, with a corresponding unit cell volume of V = 506.73529 Å3. In-depth scrutiny of the microstructure of the ceramics' grains using scanning electron microscopy (SEM) reveals an optimal relative density of 96.2%. Subsequently, the study explores the impact of porosity, packing fraction, relative density, and Si-O bond valence (VSi-O) on the microwave dielectric properties of Li2Y9(SiO4)6O2F ceramics. Notably, the Li2Y9(SiO4)6O2F ceramic sintered at 1275°C demonstrates superior performance metrics, boasting an εr value of 14.28, a Q × f product of 16,760 GHz (at f = 9.4 GHz), and a temperature coefficient of frequency (τf) at 3.14 ppm/°C. This comprehensive investigation contributes valuable insights into optimizing the microwave dielectric characteristics of Li2Y9(SiO4)6O2F ceramics for potential applications in advanced electronic devices. [ABSTRACT FROM AUTHOR]