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Voice Quality as Digital Biomarker in Bipolar Disorder: A Systematic Review.

J Voice

January 2025

Department of Surgery, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, Belgium; Division of Laryngology and Bronchoesophagology, Department of Otolaryngology Head Neck Surgery, EpiCURA Hospital, Baudour, Belgium; Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, UFR Simone Veil, Université Versailles Saint-Quentin-en-Yvelines (Paris Saclay University), Paris, France; Department of Otolaryngology, Elsan Hospital, Paris, France. Electronic address:

Background: Voice analysis has emerged as a potential biomarker for mood state detection and monitoring in bipolar disorder (BD). The systematic review aimed to summarize the evidence for voice analysis applications in BD, examining (1) the predictive validity of voice quality outcomes for mood state detection, and (2) the correlation between voice parameters and clinical symptom scales.

Methods: A PubMed, Scopus, and Cochrane Library search was carried out by two investigators for publications investigating voice quality in BD according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements.

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A low-cost soft sensor for sewer flow monitoring - Learning from water level measurements in manholes.

Water Res

January 2025

School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China; State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong SAR, China. Electronic address:

Flow meters are commonly used in manholes to monitor the flow rate for sewer operation and management. However, the large-scale deployment of flow meters in a sewer system is cost-prohibitive due to their high costs and the need for frequent maintenance. This paper proposes a soft sensor that estimates flow rates based on water level measurements in a manhole.

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Implementing the discontinuous-Galerkin finite element method using graph neural networks with application to diffusion equations.

Neural Netw

December 2024

Department of Earth Science and Engineering, Imperial College London, Prince Consort Road, London SW7 2BP, UK; Centre for AI-Physics Modelling, Imperial-X, White City Campus, Imperial College London, W12 7SL, UK.

Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry. There have been efforts in the scientific computing community to leverage this development via implementing conventional partial differential equation (PDE) solvers with machine learning packages, most of which rely on structured spatial discretisation and fast convolution algorithms. However, unstructured meshes are favoured in problems with complex geometries.

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Flexible tactile sensors have received significant attention for use in wearable applications such as robotics, human-machine interfaces, and health monitoring. However, conventional tactile sensors face challenges in accurately measuring pressure because vertical deformation is induced by Poisson's ratio in situations where lateral strain is applied. This study shows a strain-insensitive flexible tactile sensor array without the crosstalk effect using a highly stretchable mesh.

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Radiography is a field of medicine inherently intertwined with technology. The dependency on technology is very high for obtaining images in ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). Although the reduction in radiation dose is not applicable in US and MRI, advancements in technology have made it possible in CT, with ongoing studies aimed at further optimization.

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