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Reorganization of neonatal intensive care by introducing clinical microsystems may help to allocate nursing time more appropriately to the needs of patients. However, there is concern that cohorting infants according to acuity may enhance noise levels. This single-center study investigated the impact of reorganization of neonatal intensive care unit by implementing clinical microsystems in a Level III NICU on environmental noise. This prospective study measured 24-h noise levels over a period of 6 months during pre- and post-implementation of microsystems cohorting infants of similar acuity. Comparative analyses of the mixed acuity (i.e., before) and the cohorting (i.e., after) model were performed by creating daily profiles from continuous noise level measurements and calculating the length of exposure to predefined noise levels. Compared to baseline daytime measurements, noise levels were 3-6 dBA higher during physician handover. Noise levels were 2-3 dBA lower on weekends and 3-4 dBA lower at night, independent of the organizational model. The introduction of clinical microsystems slightly increased average noise levels for high-acuity pods (A and B) but produced a much more substantial decrease for low-acuity pods (E), leading to an overall reduction in unit-wide noise levels. Conclusion: Our data show that noise levels are more driven by human behavior than by technical devices. Implementation of microsystems may help to reduce noise exposure in the lower acuity pods in a NICU. What is Known: • Excessive noise levels can lead to adverse effects on the health and development of premature infants and other critically ill newborns. • The reorganization of the neonatal intensive care unit following the clinical microsystems principles might improve quality of care but also affect noise exposure of staff and patients. What is New: • The transition from a mixed -acuity to cohorting model is associated with an overall reduction in noise levels, particularly in low-acuity pods requiring less nursing care. • Nevertheless, baseline noise levels in both models exceeded the standard permissible limits.
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http://dx.doi.org/10.1007/s00431-023-05335-z | DOI Listing |
MAGMA
September 2025
Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, 3585CX, Utrecht, The Netherlands.
Objective: Within gradient-spoiled transient-state MR sequences like Magnetic Resonance Fingerprinting or Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT), it is examined whether an optimized RF phase modulation can help to improve the precision of the resulting relaxometry maps.
Methods: Using a Cramer-Rao based method called BLAKJac, optimized sequences of RF pulses have been generated for two scenarios (amplitude-only modulation and amplitude + phase modulation) and for several conditions. These sequences have been tested on a phantom, a healthy human brain and a healthy human leg, to reconstruct parametric maps ( and ) as well as their standard deviations.
J Math Biol
September 2025
School of Mathematical Sciences and Institute of Natural Sciences, MOE-LSC, CMA-Shanghai, Shanghai Jiao Tong University, Shanghai, China.
It has been noticed that when the waiting time distribution exhibits a transition from an intermediate time power-law decay to a long-time exponential decay in the continuous time random walk model, a transition from anomalous diffusion to normal diffusion can be observed at the population level. However, the mechanism behind the transition of waiting time distribution is rarely studied. In this paper, we provide one possible mechanism to explain the origin of such a transition.
View Article and Find Full Text PDFComput Methods Programs Biomed
September 2025
Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, 210096, China; Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing, Southeast University, Nanjing, 210096, China. Electronic address: xuji@s
Background: Photon counting computed tomography (PCCT) has emerged as a potential technology that is revolutionizing clinical CT imaging. Using photon counting detectors (PCDs), the PCCT counts each X-ray event and measures the corresponding energy above the noise floor with significantly higher spatial resolution. However, the multiple-energy-bin setting and much smaller pixels increase the raw data size of PCCT by 20-100 times compared to traditional CT.
View Article and Find Full Text PDFPLoS Comput Biol
September 2025
Faculty of Science, Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.
Predictive coding (PC) proposes that our brains work as an inference machine, generating an internal model of the world and minimizing predictions errors (i.e., differences between external sensory evidence and internal prediction signals).
View Article and Find Full Text PDFPhys Rev Lett
August 2025
University of Maryland Baltimore County, Department of Physics, Baltimore, Maryland 21250, USA.
A charge qubit couples to environmental electric field fluctuations through its dipole moment, resulting in fast decoherence. We propose the p-orbital (pO) qubit, formed by the single-electron, p-like valence states of a five-electron Si quantum dot, which couples to charge noise through the quadrupole moment. We demonstrate that the pO qubit offers distinct advantages in quality factor, gate speed, readout, and size.
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