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What are the Thoughts of Women Whose Husbands' Frozen Testicular Sperm Is Thawed for in vitro Fertilization on the Day of Oocyte Retrieval? A Qualitative Study.
Int J Womens Health
January 2025
Nursing Department, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou City, Zhejiang Province, People's Republic of China.
Objective: The psychological experiences will be analyzed to understand the needs and burdens of women on the day of oocyte retrieval when the thawed testicular sperm of their husbands is used for in vitro fertilization, in order to provide a basis for the subsequent formulation of relevant nursing measures.
Methods: This study utilized a descriptive phenomenological research approach. A cohort of 13 women undergoing oocyte retrieval on the day when thawed testicular sperm from their husbands is used for in vitro fertilization at the Reproductive Medicine Center of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, between August and October 2024, were chosen as participants for this study.
Soil classification and land suitability evaluation for tomato cultivation using analytic hierarchy process under different land uses.
Heliyon
January 2025
Department of Soil Science, Faculty of Agriculture/ Institute for Agricultural Research, Ahmadu Bello University, Zaria, Nigeria.
Population growth has led to excessive land use, affecting soil suitability and sustainability. Detailed soil characterization and land evaluation for various land uses are essential steps toward achieving food security and sustaining the environment. This study classifies soils and assesses their suitability for tomato cultivation using the FAO Land Assessment Framework and Analytical Hierarchy Process (AHP) model.
View Article and Find Full Text PDFRolling Bearing Fault Diagnosis Based on a Synchrosqueezing Wavelet Transform and a Transfer Residual Convolutional Neural Network.
Sensors (Basel)
January 2025
School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.
This study proposes a novel rolling bearing fault diagnosis technique based on a synchrosqueezing wavelet transform (SWT) and a transfer residual convolutional neural network (TRCNN) designed to address the difficulties of feature extraction caused by the non-stationarity of fault signals, as well as the issue of low fault diagnosis accuracy resulting from small sample quantities. This approach transforms the one-dimensional vibration signal into time-frequency diagrams using an SWT based on complex Morlet wavelet basis functions, which redistributes (squeezes) the values of the wavelet coefficients at different localized points in a time-frequency plane to the estimated instantaneous frequencies. This allows the energy to be more fully concentrated in actual corresponding frequency components.
View Article and Find Full Text PDFTowards a unified regional surveillance system: the Gulf CDC's first initiatives.
Front Public Health
January 2025
Gulf Center for Disease Control and Prevention (CDC), Riyadh, Saudi Arabia.
In January 2021, the Gulf Health Council (GHC), established the Gulf Centre for Disease Prevention and Control (Gulf CDC) in Riyadh, marking a pivotal step in harmonizing health strategies, enhancing knowledge generation, and promoting evidence-based approaches to both communicable (CD) and non-communicable diseases (NCD). The Gulf CDC's mission includes consolidating the region's health information systems, crucial for monitoring disease burden and shaping effective public health policies. An initial assessment of public health surveillance systems across the Gulf Cooperation Council (GCC) member states was conducted by the Gulf CDC.
View Article and Find Full Text PDFHarnessing advanced hybrid deep learning model for real-time detection and prevention of man-in-the-middle cyber attacks.
Sci Rep
January 2025
Department of Electronics and Communication Engineering, Panimalar Engineering College, Chennai, India.
Article Synopsis
- The increasing use of connected devices in smart homes has heightened security risks, particularly from Man-in-the-Middle (MitM) attacks, which can go undetected.
- Traditional security methods struggle to manage these complex threats, highlighting the need for more advanced intrusion detection systems.
- The AEXB Model, a hybrid deep learning approach combining AutoEncoder for feature extraction and XGBoost for classification, achieves 97.24% accuracy in detecting MitM attacks, while also enabling real-time threat responses and continuous protection.
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