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Objective: Total hip arthroplasty (THA) remains the primary treatment option for femoral neck fractures in elderly patients. This study aims to explore the risk factors associated with allogeneic blood transfusion after surgery and to develop a dynamic prediction model to predict post‐operative blood transfusion requirements. This will provide more accurate guidance for perioperative humoral management and rational allocation of medical resources. Methods: We retrospectively analyzed data from 829 patients who underwent total hip arthroplasty for femoral neck fractures at three third‐class hospitals between January 2017 and August 2023. Patient data from one hospital were used for model development, whereas data from the other two hospitals were used for external validation. Logistic regression analysis was used to screen the characteristic subsets related to blood transfusion. Various machine learning algorithms, including logistic regression, SVA (support vector machine), K‐NN (k‐nearest neighbors), MLP (multilayer perceptron), naive Bayes, decision tree, random forest, and gradient boosting, were used to process the data and construct prediction models. A 10‐fold cross‐validation algorithm facilitated the comparison of the predictive performance of the models, resulting in the selection of the best‐performing model for the development of an open‐source computing program. Results: BMI (body mass index), surgical duration, IBL (intraoperative blood loss), anticoagulant history, utilization rate of tranexamic acid, Pre‐Hb, and Pre‐ALB were included in the model as well as independent risk factors. The average area under curve (AUC) values for each model were as follows: logistic regression (0.98); SVA (0.91); k‐NN (0.87) MLP, (0.96); naive Bayes (0.97); decision tree (0.87); random forest (0.96); and gradient boosting (0.97). A web calculator based on the best model is available at: (https://nomo99.shinyapps.io/dynnomapp/). Conclusion: Utilizing a computer algorithm, a prediction model with a high discrimination accuracy (AUC > 0.5) was developed. The logistic regression model demonstrated superior differentiation and reliability, thereby successfully passing external validation. The model's strong generalizability and applicability have significant implications for clinicians, aiding in the identification of patients at high risk for postoperative blood transfusion. [ABSTRACT FROM AUTHOR]

Perovskite‐type rare earth nickelates based memristor have recently attracted extensive attention in the field of novel storage computing due to their special electronic structure and exotic physical properties. However, there is still a shortage of memristors with ultra‐high stability performance, which will provide a solid foundation for future neural network computing with high accuracy recognition rates. Here, a GdNiO3‐based interfacial memristor is presented, which possesses ultra‐high stable performance, such as electroforming‐free, low device‐to‐device variation, reliable cyclic switching, high on/off ratio (≈104) and stable pulse modulation of conduction. Combined with the comprehensive microstructure results, this behavior is ascribed to the interface Schottky barrier variation caused by the 1D oxygen vacancy channel conduction according to the transmission electron microscopy results. In particular, based on the device's stable pulse modulation plasticity performance, the study also succeeds in achieving highly accurate neural firing pattern recognition up to ≈99.75% accuracy and monitoring of pattern transitions by implementing a reservoir computing system based on the device. This research advances the progress of nickelates in novel storage computing and paves the way for future efficient memristor‐based reservoir computing systems to handle more complex temporal tasks. [ABSTRACT FROM AUTHOR]

The purpose of the current study was to explore the nature of the underlying relationship between creativity fostering teacher behavior and student creative achievement in science activities. In doing so, we examined the mediating effect of intrinsic motivation on the relationship between creativity fostering teacher behavior and student creative achievement in science activities, and the moderating effect of openness to experience. We conducted a two-wave survey study in three high schools in China and obtained data from 1035 students. Results from ordinary least squares regression analysis showed that creativity fostering teacher behavior was positively related to student creative achievement in science activities. We found that students' intrinsic motivation mediated the relationship between creativity fostering teacher behavior and student creative achievement. When a student had a high level of openness to experience, the relationship between intrinsic motivation and creative achievement was stronger. In addition, we discussed the implications and limitations of our study, as well as suggestions for future research.

Active fault is a major risk source of urban earthquake disaster. Accurately identifying the spatial geometry distribution features of active fault is the basis for urban seismic risk migration. However, due to the large-scale and deep urban renewal by human activities and urbanization, the traces of active faults are obscure and invisible on the surface, which makes it hard to identify the surface geometry of this kind of active faults. Though the northern Shuiyu fault in the central part of the Datong Basin is bounded by the eastern edge of the Mapu Mountain and characterized by linear displaced landforms, the southern section of the Shuiyu fault crossing the Yudong District of Datong City is covered by dense buildings and roads, becoming an "invisible" fault. In this study, based on the 1965 historical aerial photos of the Datong region in the 1960's and the 1∶10000 topographic maps, we reconstructed the original DEM and DOM of this region using the aerial photo stereopair and stereoscopic photography. These original data revealed the geometry distribution characteristics of the Shuiyu fault. Our results show that the piedmont fault scarps are marked by prominent linear features along the northern Shuiyu fault. We can accurately locate the fault by the images. Based on the previous Keyhole satellite images, DOM and DEM data, the geometric distribution of the fault in the southern Shuiyu fault can be accurately determined. Topographic profiles extracted from the original DEM show that the vertical offset on terrace T3 along the Shuiyu fault is about 19 meters. On this basis, the fault natural exposures and shallow seismic reflection data demonstrate that it is feasible to accurately locate the "invisible" active fault in the city by using historical aerial photos and stereoscopic photography. This study provides not only an important basis for the seismic hazard assessment in the Datong region but a useful technique for the detection of "invisible" active faults beneath a city.

Memristor-based neuromorphic computing is beneficial for artificial intelligence to process external information autonomously with high speed and high efficiency. Two-dimensional (2D) layered van der Waals rhenium selenide (ReSe2) has optoelectronic and semiconductor properties, but its ferroelectricity has not been confirmed fully experimentally and the application exploration is currently limited. Here, we experimentally confirmed the room-temperature ferroelectricity of 2D ReSe2 and proposed a reconfigurable ReSe2 memristor that can realize multiple functions. The device can realize the conductance bidirectional regulation, and under the action of electrical signals, it exhibits the high 0.99 and 0.98 linearity and accurate bidirectional update of weights. Under the complementary effect of ReSe2 ferroelectric polarization flipping and interface defects, the device exhibits the memcapacitor and memristor reconfigurable behavior and multiple functions such as visible light perception, logical "OR" calculation, and long/short-term synaptic plasticity. In addition, the six-layer convolutional neural network built based on ReSe2 memristors can perform feature extraction and classification recognition of handwritten digital pictures, and its recognition accuracy can reach 97.04%. In addition to obtain substantial experimental evidence for the ferroelectricity of 2D ReSe2, this work also provides a new avenue for the implementation of ReSe2 ferroelectric memristors in the neuromorphic computing system with the front-end sensing and back-end processing. [ABSTRACT FROM AUTHOR]