Influence of electrical potential on the crystallization and adhesion of potassium hydrogen tartrate crystals

Interfacial interactions between a hydroalcoholic solution of potassium hydrogen tartrate (KHT) and a stainless steel surface are studied, when an electrical potential is applied to the metal substrate. The capacitive domain of the metal–solution interface is determined by cyclic voltammetry. In order to study the influence of the potential on KHT nucleation and crystal adhesion, the solid–liquid interfacial energy is assessed from contact angle and capillary rise measurements. Experimentally, the contact angle between a NaF solution and a stainless steel vs. the potential has a parabolic behaviour. The metal topography has no apparent influence on physicochemical properties of the interface when ethanol is present in a KHT solution. The metal substrate promotes the formation of KHT crystals, which is improved by the application of an anodic potential. The adhesion of crystals becomes more effective when wires of 25 μm diameter are used in comparison with those of 250 μm

Bridging generative models and Convolutional Neural Networks for domain-agnostic segmentation of brain MRI

Segmentation of brain MRI scans is paramount in neuroimaging, as it is a prerequisite for many subsequent analyses. Although manual segmentation is considered the gold standard, it suffers from severe reproducibility issues, and is extremely tedious, which limits its application to large datasets. Therefore, there is a clear need for automated tools that enable fast and accurate segmentation of brain MRI scans. Recent methods rely on convolutional neural networks (CNNs). While CNNs obtain accurate results on their training domain, they are highly sensitive to changes in resolution and MRI contrast. Although data augmentation and domain adaptation techniques can increase the generalisability of CNNs, these methods still need to be retrained for every new domain, which requires costly labelling of images. Here, we present a learning strategy to make CNNs agnostic to MRI contrast, resolution, and numerous artefacts. Specifically, we train a network with synthetic data sampled from a generative model conditioned on segmentations. Crucially, we adopt a domain randomisation approach where all generation parameters are drawn for each example from uniform priors. As a result, the network is forced to learn domain-agnostic features, and can segment real test scans without retraining. The proposed method almost achieves the accuracy of supervised CNNs on their training domain, and substantially outperforms state-of-the-art domain adaptation methods. Finally, based on this learning strategy, we present a segmentation suite for robust analysis of heterogeneous clinical scans. Overall, our approach unlocks the development of morphometry on millions of clinical scans, which ultimately has the potential to improve the diagnosis and characterisation of neurological disorders

Pharmacists as mid-level healthcare providers and the clinical results of a pharmacist-led diabetes disease management program.

Advancements in medical therapy have augmented resources available to physicians to treat disease and, because of this, spending on prescription drugs has doubled in the past decade. Increasingly, clinical trials are demonstrating the benefits of aggressive disease management in reducing morbidity and mortality. Physicians treating patients with chronic conditions must balance the benefits of combination drug therapy against the risk of adverse drug events and drug interactions. For instance, evidence-based practice guidelines in patients with diabetes and multiple comorbidities require combination therapy in order to reduce morbidity and mortality. Patients with polymorbidity require the attention of multiple physicians, further fragmenting patient care and increasing polypharmacy related issues. Pharmacists are increasingly recognized for expertise in pharmacodynamics and pharmacokinetics and have been shown to be beneficial when utilized in patient care. Pharmacists are in a key position to help physicians manage the balance between optimal disease management and the risks of polypharmacy

Optimal use of Charge Information for the HL-LHC Pixel Detector Readout

The pixel detectors for the High Luminosity upgrades of the ATLAS and CMS detectors will preserve digitized charge information in spite of extremely high hit rates. Both circuit physical size and output bandwidth will limit the number of bits to which charge can be digitized and stored. We therefore study the effect of the number of bits used for digitization and storage on single and multi-particle cluster resolution, efficiency, classification, and particle identification. We show how performance degrades as fewer bits are used to digitize and to store charge. We find that with limited charge information (4 bits), one can achieve near optimal performance on a variety of tasks.Comment: 27 pages, 20 figure

Application d’un champ électrique de faible amplitude pour l’amélioration de la cristallisation et de la filtration sur supports métalliques en oenologie.

En œnologie, on assiste à l’apparition de matériaux métalliques, utilisés comme support de cristallisation ou média filtrant, qui ont permis la mise en œuvre de méthodes électrochimiques. Des dispositifs expérimentaux ont permis à la fois de moduler le potentiel électrique relatif métal-solution et d’atteindre diverses grandeurs étroitement liées à la physico-chimie de l’interface. Le premier montage permet la mesure de l’angle de contact entre une goutte de solution électrolytique et une plaque métallique polie ou rugueuse. Le deuxième dispositif permet de déduire l’ascension capillaire de la mesure de la masse de solution incorporée dans un matériau métallique poreux. Le dernier est une cellule, où le média filtrant est enchâssé entre deux électrodes métalliques, dans laquelle le débit de filtration peut être aisément mesuré. Les résultats concernent la variation de l’énergie interfaciale avec le potentiel électrique appliqué d’où l’on déduit le point de charge nulle et la capacité différentielle de la double couche électochimique. Pour la cristallisation, on a constaté une dépendance entre la masse de cristaux de bitartrate de potassium déposée sur le support métallique et le potentiel électrique. Pour la filtration, le champ électrique a fait apparaître simultanément une série de phénomènes qui augmente le flux de filtration des vins