Background: Despite being the gold standard for diagnosing osteoporosis, dual-energy X-ray absorptiometry (DXA) is an underutilized screening tool for osteoporosis. Objectives: This study proposed and validated a cont...
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With the advent of the global aging era, the impact of stroke on humans is continuously increasing. Therefore, new therapeutic approaches to enhance patient recovery are receiving growing attention. Stroke is a severe...
With the advent of the global aging era, the impact of stroke on humans is continuously increasing. Therefore, new therapeutic approaches to enhance patient recovery are receiving growing attention. Stroke is a severe neurological disorder that causes brain damage, requiring extended periods of rehabilitation for patients to return to normal life. Currently, common clinical methods largely rely on traditional passive limb rehabilitation, primarily targeting peripheral nerve training. Nowadays, an increasing number of people are recognizing the importance of post-stroke neuroplasticity. This study aims to activate patients' central nervous system and proposes a brain-machine interface (BCI) exoskeleton system based on human cognition. By designing three cognitive brainwave training models, including an attention-based standing-up model detecting θ-band power decrease, a relaxation-based sitting-down model detecting α-band power increase, and a walking model detecting MRCP, patients can actively control lower limb exoskeleton movement using *** study provides cross-validation accuracy through both normal subjects and stroke patients, with accuracies of 87.13±9.38 and 80.83±9.68, respectively. Envisioning a rehabilitation system guided by human cognition, our team has developed an intuitive BCI exoskeleton system.
The impressive progress in quantum hardware of the last years has raised the interest of the quantum computing community in harvesting the computational power of such devices. However, in the absence of error correcti...
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We propose and analyze a protocol for stabilizing a maximally entangled state of two noninteracting qubits using active state-dependent feedback from a continuous two-qubit half-parity measurement in coordination with...
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— In this paper, we consider the problem of learning a predictive model for population cell growth dynamics as a function of the media conditions. We first introduce a generic data-driven framework for training opera...
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The unpredictability of random numbers is fundamental to both digital security [1, 2] and applications that fairly distribute resources [3, 4]. However, existing random number generators have limitations—the generati...
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Today's multiagent systems have grown too complex to rely on centralized controllers, prompting increasing interest in the design of distributed algorithms. In this respect, game theory has emerged as a valuable t...
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The United Nations Sustainable Development Goal 12 is the foundation of the European University on Responsible Consumption and Production consortium (EURECA-PRO). This article introduces the eight EURECA-PRO partner u...
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The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via sel...
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Monitored quantum circuits can exhibit an entanglement transition as a function of the rate of measurements, stemming from the competition between scrambling unitary dynamics and disentangling projective measurements....
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Monitored quantum circuits can exhibit an entanglement transition as a function of the rate of measurements, stemming from the competition between scrambling unitary dynamics and disentangling projective measurements. We study how entanglement dynamics in nonunitary quantum circuits can be enriched in the presence of charge conservation, using a combination of exact numerics and a mapping onto a statistical mechanics model of constrained hard-core random walkers. We uncover a charge-sharpening transition that separates different scrambling phases with volume-law scaling of entanglement, distinguished by whether measurements can efficiently reveal the total charge of the system. We find that while Rényi entropies grow sub-ballistically as t in the absence of measurement, for even an infinitesimal rate of measurements, all average Rényi entropies grow ballistically with time ∼t. We study numerically the critical behavior of the charge-sharpening and entanglement transitions in U(1) circuits, and show that they exhibit emergent Lorentz invariance and can also be diagnosed using scalable local ancilla probes. Our statistical mechanical mapping technique readily generalizes to arbitrary Abelian groups, and offers a general framework for studying dissipatively stabilized symmetry-breaking and topological orders.
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