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Dynamics of affect modulation in neurodevelopmental disorders (DynAMoND) - study design of a prospective cohort study.
Int J Bipolar Disord
December 2024
Department for Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt-Goethe University, Frankfurt am Main, Germany.
Background: Attention-deficit/hyperactivity disorder (ADHD) is a common neuro-developmental disorder that often persists into adulthood. Moreover, it is frequently accompanied by bipolar disorder (BD) as well as borderline personality disorder (BPD). It is unclear whether these disorders share underlying pathomechanisms, given that all three are characterized by alterations in affective states, either long or short-term.
View Article and Find Full Text PDFApplication of artificial intelligence based on state grid ESG platform in clean energy scheduling optimization.
Sci Rep
December 2024
School of Public Administration, Guangzhou University, Guangzhou, 510006, China.
The randomness and volatility of existing clean energy sources have increased the complexity of grid scheduling. To address this issue, this work proposes an artificial intelligence (AI) empowered method based on the Environmental, Social, and Governance (ESG) big data platform, focusing on multi-objective scheduling optimization for clean energy. This work employs a combination of Particle Swarm Optimization (PSO) and Deep Q-Network (DQN) to enhance grid scheduling efficiency and clean energy utilization.
View Article and Find Full Text PDFA skipping spectrum sensing scheme based on deep reinforcement learning for transform domain communication systems.
Sci Rep
December 2024
College of Electronic Engineering, National University of Defense Technology, Hefei, 230000, China.
Spectrum sensing is a key technology and prerequisite for Transform Domain Communication Systems (TDCS). The traditional approach typically involves selecting a working sub-band and maintaining it without further changes, with spectrum sensing being conducted periodically. However, this approach presents two main issues: on the one hand, if the selected working band has few idle channels, TDCS devices are unable to flexibly switch sub-bands, leading to reduced performance; on the other hand, periodic sensing consumes time and energy, limiting TDCS's transmission efficiency.
View Article and Find Full Text PDFNutrient loading as a key cause of short- and long-term anthropogenic ecological degradation of the Salton Sea.
Sci Rep
December 2024
Department of Earth and Planetary Sciences, University of California, Riverside, CA, 92521, USA.
The Salton Sea (SS), California's largest inland lake at 816 square kilometers, formed in 1905 from a levee breach in an area historically characterized by natural wet-dry cycles as Lake Cahuilla. Despite more than a century of untreated agricultural drainage inputs, there has not been a systematic assessment of nutrient loading, cycling, and associated ecological impacts at this iconic waterbody. The lake is now experiencing unprecedented degradation, particularly following the 2003 Quantification Settlement Agreement-the largest agricultural-to-urban water transfer in the United States.
View Article and Find Full Text PDFEvent co-occurrences for prompt-based generative event argument extraction.
Sci Rep
December 2024
School of Computer Science and Technology (School of Cyberspace Security), Xinjiang University, Urumqi, 830046, China.
Recent works have introduced prompt learning for Event Argument Extraction (EAE) since prompt-based approaches transform downstream tasks into a more consistent format with the training task of Pre-trained Language Model (PLM). This helps bridge the gap between downstream tasks and model training. However, these previous works overlooked the complex number of events and their relationships within sentences.
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