This study tested whether self-reports of childhood adversity would predict altered error processing under emotional versus non-emotional task conditions. N = 99 undergraduates completed two selective attention tasks, a traditional color-word Stroop task and a modified task using emotional words, while EEG was recorded. Participants also completed self-report measures of adverse and positive childhood experiences, executive functioning, depression, current stress, and emotion regulation. Reports of adversity were robustly correlated with self-reported challenges in executive functioning, even when controlling for self-reported depression and stress, but adversity was not correlated with task performance. With regard to neural markers of error processing, adversity predicted an enhanced error-related negativity and blunted error-positivity, but only during the emotion-word blocks of the task. Moreover, error-related changes in alpha oscillations were predicted by adversity, in a pattern that suggested less error responsiveness in alpha patterns during the emotion block, compared to the color block, among participants with higher adversity. Overall, results indicate alterations in error monitoring associated with adversity, such that in an emotional context, initial error detection is enhanced and sustained error processing is blunted, even in the absence of overt performance changes.
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Sci Rep
December 2024
School of Electrical Engineering, Vellore Institute of Technology, Chennai, 600127, India.
Spherical tanks have been predominantly used in process industries due to their large storage capability. The fundamental challenges in process industries require a very efficient controller to control the various process parameters owing to their nonlinear behavior. The current research work in this paper aims to propose the Approximate Generalized Time Moments (AGTM) optimization technique for designing Fractional-Order PI (FOPI) and Fractional-Order PID (FOPID) controllers for the nonlinear Single Spherical Tank Liquid Level System (SSTLLS).
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December 2024
Shaanxi Key Laboratory of Complex System Control and Intelligent Informantion Processing, Xi'an University of Technology, Xi'an 710048, China.
In the integrated radar and communication system (IRCS), the design of signal that can simultaneously satisfy the radar detection and communication transmission is very important and difficult. Recently, some new properties of a class of solvable chaotic system have been studied for wireless applications, such as low bit error rate (BER) wireless communications and low cost target detection. In this paper, a novel IRCS based on the chaotic signal is proposed, and the performance of proposed scheme is analyzed.
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December 2024
Department of Architecture, Rafsanjan Branch, Islamic Azad University, Rafsanjan, Iran.
The advent of smart cities has brought about a paradigm shift in urban management and citizen engagement. By leveraging technological advancements, cities are now able to collect and analyze extensive data to optimize service delivery, allocate resources efficiently, and enhance the overall well-being of residents. However, as cities become increasingly interconnected and data-dependent, concerns related to data privacy and security, as well as citizen participation and representation, have surfaced.
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December 2024
Department of Dermatology, Niazi Hospital, Lahore, Pakistan.
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information.
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December 2024
Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Reservoir computing (RC) is a powerful machine learning algorithm for information processing. Despite numerous optical implementations, its speed and scalability remain limited by the need to establish recurrent connections and achieve efficient optical nonlinearities. This work proposes a streamlined photonic RC design based on a new paradigm, called next-generation RC, which overcomes these limitations.
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