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Reduced bacteria concentrations in wastewater is a key indicator of the efficacy of water resource recovery facilities (WRRFs). However, monitoring the presence of bacterial concentrations in real time at each stage of the WRRF is challenging as it requires taking and processing water samples offline. Although few studies have been proposed to predict bacterial concentrations using data-driven models, generalizing these models to unseen data from different WRRFs remains challenging.
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Complex Systems Laboratory, University Politehnica of Bucharest, Bucharest, Romania; Centre for Elderly and Nursing Home Medicine, University of Bergen, Bergen, Norway; Neuro-SysMed Center, University of Bergen, Bergen, Norway. Electronic address:
Heart rate response to physical activity is widely investigated in clinical and training practice, as it provides information on a person's physical state. For emerging digital phenotyping approaches, there is a need for individualized model estimation. In this study, we propose a zero-poles model and a data-driven evolutionary learning method for identification.
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Currently, bacterial classification at the species level relies on the 95-96% average nucleotide identity (ANI) value that is known to be equivalent to a 70% digital DNA-DNA hybridization (dDDH) value. However, during the routine identification of bacteria in the uteri of camels with a history of conception failure, we found that four out of the seven strains (2298A, 2569A, 2652, 2571B, 1103A, 2571A, and 335C) could not be assigned to any valid species. Furthermore, a 70% dDDH value did not correspond to a 95-96% ANI value in strain 2569A.
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The demand for non-invasive, real-time health monitoring has driven advancements in wearable sensors for tracking biomarkers in sweat. Ammonium ions (NH) in sweat serve as indicators of metabolic function, muscle fatigue, and kidney health. Although current ion-selective all-solid-state printed sensors based on nanocomposites typically exhibit good sensitivity (~50 mV/log [NH]), low detection limits (LOD ranging from 10 to 10 M), and wide linearity ranges (from 10 to 10 M), few have reported the stability test results necessary for their integration into commercial products for future practical applications.
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