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Validation of the cancer-specific utility measure EORTC QLU-C10D using evidence from four lung cancer trials covering six country value sets
Comparison of the Morphological Dimensions of Primary Molars with Kids Stainless Steel Crowns in a Sample of Iranian Children
A bioinformatics analysis and experimental validation of PDGFD as a promising diagnostic biomarker for acute myeloid leukemia
Histomorphometric and microtomographic evaluation of hydroxyapatite coated implants and L-PRF in over drilled bone sites in sheep
Evolution and stability mechanics analysis of the elliptical stress arch structure in the surrounding rocks of the underground mining area
Investigating the impact of the construction of the Duliu River dam in China on the spatiotemporal changes of fish communities
Electrospun polyacrylonitrile-polyphenyl/magnetite nanofiber electrode for enhanced capacitance of supercapacitor
Abstract Supercapacitors are widely valued for their high cycle life, power density, and broad applications. However, the development of improved devicess hindered by the challenges related to electrode materials. Effective electrodes need high specific capacitance and low electrical resistance to enhance energy storage, while also being simple to prepare, cost-effective, and environmentally friendly to support sustainable development. This study utilized an affordable and straightforward electrospinning process to produce polyacrylonitrile (PAN) nanofibers, polyacrylonitrile-polyphenyl (PAN-PPh) nanofibers, and polyacrylonitrile-polyphenyl/magnetic iron oxide (PAN-PPh/Fe3O4) composite nanofibers for supercapacitor electrodes. Among these, the PAN-PPh/Fe3O4 electrode exhibited superior performance, with a specific capacity of 0.258 Ah g− 1, and specific capacitance of 442.4 F g− 1 and excellent cycling stability, retaining approximately 78.49% of its capacitance after 3000 cycles. These results highlight the potential of PAN-PPh/Fe3O4 composites as sustainable materials for supercapacitor electrodes.
Energy efficient and robust node localization in WSNs using LSTM optimized DV hop framework to mitigate multihop localization errors
Author Correction: Distributional outcomes of urban heat island reduction pathways under climate extremes
A novel scoring system for heart failure screening utilizing combined electrocardiogram, phonocardiogram, and radial artery features
Synergistic mechanism of olaparib and cisplatin on breast cancer elucidated by network pharmacology
Direct torque control for a six phase induction motor using a fuzzy based and sliding mode controller
Abstract Direct Torque Control (DTC) is widely recognized for its fast dynamic response and simplicity in controlling induction motors. However, conventional DTC suffers from drawbacks such as high torque and flux ripple, sensitivity to parameter variations, and poor performance under low-speed operation. This study proposes an enhanced DTC strategy for a modified six-phase induction motor (MSPIM) by integrating Fuzzy-Based Proportional-Integral-Derivative (FPID) control compared with conventional PID and Sliding Mode Control (SMC). The FPID, PID, and SMC controller are employed to regulate speed and flux, leveraging its adaptability and robustness to system uncertainties. The six-phase induction motor, with its inherent fault-tolerant capabilities and reduced torque pulsations, serves as an ideal candidate for high-performance applications. Results obtained using MATLAB Simulink show that the proposed control strategy significantly reduces torque and flux ripple, improves dynamic response, and enhances robustness against speed and load changing. This work highlights the potential of combining intelligent control techniques like FPID, PID and SMC to advance the performance of DTC in multi-phase induction motor drives, particularly in applications requiring high reliability and efficiency. Based on simulation results, the fuzzy PID inverter reduces the speed error and THD of the current and voltage waveforms, thereby improving MSPIM’s overall performance when compared to the regular PID and SMC.
Detection of sleep apnea using smartphone-embedded inertial measurement unit
Abstract We previously demonstrated that sleep apnea (SA) can be detected using acceleration and gyroscope signals from smartwatches. This study investigated whether an inertial measurement unit (IMU) embedded in non-wristwatch devices, such as smartphones, can also detect SA when worn during sleep. During polysomnography (PSG), subjects wore an IMU-embedded GPS device (Amue Link®) and/or smartphones (Xperia® or iPhone®) on their abdomen. Triaxial acceleration and gyroscope signals were recorded overnight. Data were split into training and test groups (2:1) for each device. An algorithm was developed in the training groups to extract respiratory movements (0.13–0.70 Hz) and detect respiratory events, which were validated in the test groups. IMU-derived respiratory events showed breath-by-breath concordance with PSG apnea-hypopnea events, yielding F1 scores of 0.786, 0.821, and 0.796, respectively. Regression model derived from IMU signals correlated with PSG AHI in the test groups (r = 0.90, 0.93, and 0.96), with limits of agreement of -16.7 to 25.9, -17.4 to 22.5, and − 18.4 to 20.5. Using cutoff values from the training groups, moderate-to-severe SA (AHI ≥ 15) was identified in the test groups with AUCs of 0.95, 0.98, and 0.94 and F1 scores of 0.89, 0.96, and 0.92, respectively. IMUs embedded in non-wristwatch devices, including smartphones, can quantitatively detect SA when worn during sleep.