In this paper, modeling for a lateral impact ionization InGaAs/InP avalanche photodiode (APD) has been performed based on a device simulator, i.e., Silvaco ATLAS. Compared with traditional APDs, the lateral impact ionized APD has much higher gains as well as lower excess noise. The internal gain for our newly proposed lateral APD is over 1000-near the breakthrough voltage. In addition, the excess noise characteristic of this device is also discussed with three-dimensional dead space multiplication theory, and the calculated effective $k$k value is obviously lower than traditional InGaAs/InP APDs. Because of the high gain and low excess noise characteristics, the proposed APD can be widely applied for optical detection with high sensitivity.
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http://dx.doi.org/10.1364/AO.382001 | DOI Listing |
Sensors (Basel)
January 2025
College of Mechatronics Engineering, North University of China, Taiyuan 030051, China.
To enhance the positioning accuracy of autonomous underwater vehicles (AUVs), a new adaptive filtering algorithm (RHAUKF) is proposed. The most widely used filtering algorithm is the traditional Unscented Kalman Filter or the Adaptive Robust UKF (ARUKF). Excessive noise interference may cause a decrease in filtering accuracy and is highly likely to result in divergence by means of the traditional Unscented Kalman Filter, resulting in an increase in uncertainty factors during submersible mission execution.
View Article and Find Full Text PDFRev Sci Instrum
January 2025
Department of Physics, National Central University, Taoyuan City 320317, Taiwan.
In an axion haloscope, the weak photon signal, theoretically converted from axions, is captured by a detection cavity. The signal from the cavity is too weak to be acquired by a signal receiver. The amplification chain assists the signal acquisition by amplifying the signal and requires accurate gain calibration.
View Article and Find Full Text PDFJAMIA Open
February 2025
Institute for Informatics, Data Science and Biostatistics, Washington University, Saint Louis, MO 63110, United States.
Objective: Dimensionality reduction techniques aim to enhance the performance of machine learning (ML) models by reducing noise and mitigating overfitting. We sought to compare the effect of different dimensionality reduction methods for comorbidity features extracted from electronic health records (EHRs) on the performance of ML models for predicting the development of various sub-phenotypes in children with Neurofibromatosis type 1 (NF1).
Materials And Methods: EHR-derived data from pediatric subjects with a confirmed clinical diagnosis of NF1 were used to create 10 unique comorbidities code-derived feature sets by incorporating dimensionality reduction techniques using raw International Classification of Diseases codes, Clinical Classifications Software Refined, and Phecode mapping schemes.
PLoS Comput Biol
January 2025
Biorobotics Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
This study introduces a novel neuromechanical model employing a detailed spiking neural network to explore the role of axial proprioceptive sensory feedback, namely stretch feedback, in salamander locomotion. Unlike previous studies that often oversimplified the dynamics of the locomotor networks, our model includes detailed simulations of the classes of neurons that are considered responsible for generating movement patterns. The locomotor circuits, modeled as a spiking neural network of adaptive leaky integrate-and-fire neurons, are coupled to a three-dimensional mechanical model of a salamander with realistic physical parameters and simulated muscles.
View Article and Find Full Text PDFCent Eur J Public Health
December 2024
Regional Public Health Authority, Presov, Slovak Republic.
Objectives: An occupational disease (OD) is a disorder or health condition which arises due to work related activities and tasks or is caused by work environment. The impact of ODs on medical and social system may be considered as a very important in relation to mortality, morbidity, and invalidity. The most common ODs in the European Union are musculoskeletal disorders (58% of all ODs in 2015).
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