Here we examine a new task to assess working memory for visual arrays in which the participant must judge how many items changed from a studied array to a test array. As a clue to processing, on some trials in the first 2 experiments, participants carried out a metamemory judgment in which they were to decide how many items were in working memory. Trial-to-trial fluctuations in these working memory storage judgments correlated with performance fluctuations within an individual, indicating a need to include trial-to-trial variation within capacity models (through either capacity fluctuation or some other attention parameter). Mathematical modeling of the results achieved a good fit to a complex pattern of results, suggesting that working memory capacity limits can apply even to judgments that involve an entire array rather than just a single item that may have changed, thus providing the expected conscious access to at least some of the contents of working memory.
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http://dx.doi.org/10.1037/xlm0000163 | DOI Listing |
In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
View Article and Find Full Text PDFJ Integr Neurosci
January 2025
Sports, Exercise and Brain Sciences Laboratory, Sports Coaching College, Beijing Sport University, 100084 Beijing, China.
Background: Sports fatigue in soccer athletes has been shown to decrease neural activity, impairing cognitive function and negatively affecting motor performance. Transcranial direct current stimulation (tDCS) can alter cortical excitability, augment synaptic plasticity, and enhance cognitive function. However, its potential to ameliorate cognitive impairment during sports fatigue remains largely unexplored.
View Article and Find Full Text PDFNutrients
January 2025
Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), 28029 Madrid, Spain.
Decompensated cirrhosis is characterized by systemic inflammation and innate and adaptive immune dysfunction. Hepatic encephalopathy (HE) is a prevalent and debilitating condition characterized by cognitive disturbances in which ammonia and inflammation play a synergistic pathogenic role. Extraskeletal functions of vitamin D include immunomodulation, and its deficiency has been implicated in immune dysfunction and different forms of cognitive impairment.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia.
The Internet of Things (IoT) has emerged as a crucial element in everyday life. The IoT environment is currently facing significant security concerns due to the numerous problems related to its architecture and supporting technology. In order to guarantee the complete security of the IoT, it is important to deal with these challenges.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China.
Real-time and accurate traffic forecasting aids in traffic planning and design and helps to alleviate congestion. Addressing the negative impacts of partial data loss in traffic forecasting, and the challenge of simultaneously capturing short-term fluctuations and long-term trends, this paper presents a traffic forecasting model, D-MGDCN-CLSTM, based on Multi-Graph Gated Dilated Convolution and Conv-LSTM. The model uses the DTWN algorithm to fill in missing data.
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