We describe novel computer algorithms for rapid, sometimes virtually instantaneous generation of trial sequences needed to instrument many behavioral research procedures. Implemented on typical desktop or laptop computers, the algorithms impose constraints to forestall development of undesired stimulus control by position, recent trial outcomes, and other variables that could impede simple and conditional discrimination learning. They yield trial-by-trial lists of sequences that can serve (1) as inputs to procedure control software or (2) in generating templates for constructing sessions for implementation by hand or machine.
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http://dx.doi.org/10.1002/jeab.58 | DOI Listing |
Psychol Trauma
January 2025
Department of Medicine, Section of General Internal Medicine, University of Chicago.
Objective: From the beginning of the COVID-19 pandemic, there has been a proliferation of anti-Asian racism. In addition to being personal targets of racism, members of the Asian American community have also been vicariously exposed to repeated news and social media stories about anti-Asian racism. Emerging research suggests that vicarious exposure to racism during the pandemic is associated with decreased well-being, although mechanisms of action are not yet clear.
View Article and Find Full Text PDFJ Hepatocell Carcinoma
January 2025
Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430022, People's Republic of China.
Purpose: Type II diabetes mellitus (T2DM) has been found to increase the mortality of patients with hepatocellular carcinoma (HCC). Therefore, this study aimed to establish and validate a machine learning-based explainable prediction model of prognosis in patients with HCC and T2DM undergoing transarterial chemoembolization (TACE).
Patients And Methods: The prediction model was developed using data from the derivation cohort comprising patients from three medical centers, followed by external validation utilizing patient data extracted from another center.
Mar Pollut Bull
January 2025
JK Laxmipat University, Jaipur, Rajasthan, India.
Marine pollution due to oil spills presents major risks to coastal areas and aquatic life, leading to serious environmental health concerns. Oil Spill detection using SAR data has transitioned from traditional segmentation to a variety of machine learning & deep learning models like UNET proving its efficiency for the task. This research paper proposes a GSCAT-UNET model for efficient oil spill detection and discrimination from lookalikes.
View Article and Find Full Text PDFInt J Med Inform
January 2025
School of Computer Science and Engineering, Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, PR China. Electronic address:
Background: In the context of routine breast cancer diagnosis, the precise discrimination between benign and malignant breast masses holds utmost significance. Notably, few prior investigations have concurrently explored the integration of imaging histology features, deep learning characteristics, and clinical parameters. The primary objective of this retrospective study was to pioneer a multimodal feature fusion model tailored for the prediction of breast tumor malignancy, harnessing the potential of ultrasound images.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
With the rapid development of sports technology, smart wearable devices play a crucial role in athletic training and health management. Sports fatigue is a key factor affecting athletic performance. Using smart wearable devices to detect the onset of fatigue can optimize training, prevent excessive fatigue and resultant injury, and increase efficiency and safety.
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