A case of Juvenile Systemic Lupus Erythematosus in a pre-pubertal child with atopic eczema.

Juvenile Systemic Lupus Erythematosus (JSLE) is a subset of SLE, with onset before eighteen years of age and associated with increased mortality and morbidity. JSLE is a complex autoimmune disease with respect to its underlying genetics. It is characterised by the disruption of immune tolerance, resulting in cascade of immune responses including the Th2 response with production of interleukins (ILs) 4,5,10, as seen with allergic disorders.

Co-Design of a Digital Health Tool for Use by Individuals With Opioid Use Disorder: App4Independence (A4i-O).

Background: Opioid use disorder (OUD) has arguably the highest mortality rate of mental health conditions; opiate-related deaths are identified as the number one cause of accidental deaths in Canada and the United States. Specialized care for OUD is often described as lacking, fractured, and with frequent periods of disengagement. Digital health strategies may support connection to evidence-based resources even during periods of disengagement.

The Effect of Cesium Incorporation on the Vibrational and Elastic Properties of Methylammonium Lead Chloride Perovskite Single Crystals.

Hybrid organic-inorganic lead halide perovskites (LHPs) have emerged as a highly significant class of materials due to their tunable and adaptable properties, which make them suitable for a wide range of applications. One of the strategies for tuning and optimizing LHP-based devices is the substitution of cations and/or anions in LHPs. The impact of Cs substitution at the A site on the structural, vibrational, and elastic properties of MACsPbCl-mixed single crystals was investigated using X-ray diffraction (XRD) and Raman and Brillouin light scattering techniques.

Computer-Vision- and Deep-Learning-Based Determination of Flow Regimes, Void Fraction, and Resistance Sensor Data in Microchannel Flow Boiling.

The aim of this article is to introduce a novel approach to identifying flow regimes and void fractions in microchannel flow boiling, which is based on binary image segmentation using digital image processing and deep learning. The proposed image processing pipeline uses adaptive thresholding, blurring, gamma correction, contour detection, and histogram comparison to separate vapor from liquid areas, while the deep learning method uses a customized version of a convolutional neural network (CNN) called U-net to extract meaningful features from video frames. Both approaches enabled the automatic detection of flow boiling conditions, such as bubbly, slug, and annular flow, as well as automatic void fraction calculation.

Behavioural and neuropsychological outcomes in children exposed in utero to maternal labour epidural analgesia.

Background: Recent studies report conflicting results regarding the relationship between labour epidural analgesia (LEA) in mothers and neurodevelopmental disorders in their offspring. We evaluated behavioural and neuropsychological test scores in children of mothers who used LEA.

Methods: Children enrolled in the Raine Study from Western Australia and delivered vaginally from a singleton pregnancy between 1989 and 1992 were evaluated.