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Application research of convolutional neural network and its optimization in lightning electric field waveform recognition.
Sci Rep
January 2025
Institute of Atmospheric Physics, LAGEO, Chinese Academy of Sciences, Beijing, China.
Quickly identifying and classifying lightning waveforms is the foundation of lightning forecasting and early warning. In this paper, based on the electric field observation of the Beijing lightning location website of the Institute of Atmospheric Physics, Chinese Academy of Sciences, a recognition and classification method of pulse signal waveform based on Convolutional Neural Network(CNN) algorithm is designed and implemented. The CNN network model and its parameters were optimized from three aspects: dataset, model parameters, and network structure, achieving a recognition rate of over 90%.
View Article and Find Full Text PDFElectron-phonon coupling and thermal transport properties of GaN/AlGaN heterojunction under strain regulation.
Phys Chem Chem Phys
January 2025
Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou 215123, China.
In the study of GaN/AlGaN heterostructure thermal transport, the interference of strain on carriers cannot be ignored. Although existing research has mainly focused on the intrinsic electronic and phonon behavior of the materials, there is a lack of studies on the transport characteristics of the electron-phonon coupling in heterostructures under strain control. This research comprehensively applies first-principles calculations and the Boltzmann transport equation simulation method to deeply analyze the thermal transport mechanism of the GaN/AlGaN heterojunction considering in-plane strain, with particular attention to the regulatory role of electron-phonon coupling on thermal transport.
View Article and Find Full Text PDFConstruction and evaluation of the prediction model for advanced disease in well-differentiated colorectal neuroendocrine neoplasms less than 2 cm in diameter.
Heliyon
January 2025
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), Department of Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
Objective: Advanced lesions are often ignored in well-differentiated colorectal neuroendocrine neoplasms (NENs) smaller than 2 cm, and we aimed to develop an effective nomogram for these lesions.
Methods: We extracted data from the Surveillance, Epidemiology, and End Results (SEER) database and used a logistic regression model to identify independent risk factors for advanced disease. All these identified factors were included to construct the prediction model, and the receiver operating characteristic (ROC) curve, calibration plot and DCA curve were utilized to assess the predictive value.
Nurse lecturers' experiences of working with people with lived experience: A phenomenological study.
Nurse Educ Today
December 2024
Anglia Ruskin University, Cambridge, UK. Electronic address:
Background: Involving people with lived experience in United Kingdom healthcare courses is a government directive and professional body recommendation, yet involvement remains non-standardised with minimal guidance. Previous literature has largely ignored the experiences of Nurse lecturer's in this work, yet they provide vital resources in promoting, sustaining and developing the involvement of people with lived experience.
Aim: To explore adult nurse lecturers' experiences of working with people with lived experience in two higher educational institution settings.
Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer.
Sensors (Basel)
January 2025
Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China.
Bird species detection is critical for applications such as the analysis of bird population dynamics and species diversity. However, this task remains challenging due to local structural similarities and class imbalances among bird species. Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information.
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