Obstructive Sleep Apnoea Syndrome, Endothelial Function and Markers of Endothelialization. Changes after CPAP

STUDY OBJECTIVES: This study tries to assess the endothelial function in vivo using flow-mediated dilatation (FMD) and several biomarkers of endothelium formation/restoration and damage in patients with obstructive sleep apnoea (OSA) syndrome at baseline and after three months with CPAP therapy. DESIGN: Observational study, before and after CPAP therapy. SETTING AND PATIENTS: We studied 30 patients with apnoea/hypopnoea index (AHI) >15/h that were compared with themselves after three months of CPAP therapy. FMD was assessed non-invasively in vivo using the Laser-Doppler flowmetry. Circulating cell-free DNA (cf-DNA) and microparticles (MPs) were measured as markers of endothelial damage and the vascular endothelial growth factor (VEGF) was determined as a marker of endothelial restoration process. MEASUREMENTS AND RESULTS: After three month with CPAP, FMD significantly increased (1072.26 ± 483.21 vs. 1604.38 ± 915.69 PU, p< 0.005) cf-DNA and MPs significantly decreased (187.93 ± 115.81 vs. 121.28 ± 78.98 pg/ml, p<0.01, and 69.60 ± 62.60 vs. 39.82 ± 22.14 U/μL, p<0.05, respectively) and VEGF levels increased (585.02 ± 246.06 vs. 641.11 ± 212.69 pg/ml, p<0.05). These changes were higher in patients with more severe disease. There was a relationship between markers of damage (r = -0.53, p<0.005) but not between markers of damage and restoration, thus suggesting that both types of markers should be measured together. CONCLUSIONS: CPAP therapy improves FMD. This improvement may be related to an increase of endothelial restoration process and a decrease of endothelial damage

Chemical physics insight of PPy-based modified ion exchange membranes: a fundamental approach

Four commercially available, cost-effective ion exchange membranes (two cationic and two anionic exchange membranes, CEMs and AEMs, respectively) were modified to mitigate crossover phenomena of the redox active species typically observed in Aqueous Organic Redox Flow Batteries (AORFB) systems. The modification strategy was carried out using a pyrrole(Py)-based polymer which successfully reduced the permeation of two redox active organic molecules, a viologen derivative (named BP7 throughout this study) and TEMPOL, by an order of magnitude. Additionally, modified membranes showed not significant changes in ion conductivity, with negligible effect on the electrical conductivity of the membranes at a given conditions. The morphology, physicochemical, mechanical, and electrochemical properties of the membranes were determined to evaluate the impact of these modifications. AEMs modified in this manner were found to have optimal properties, showing an increase in ion exchange capacity while maintaining excellent mechanical stability and unaltered permselectivity. Additionally, the diffusion boundary layer of these AEMs was slightly extended, which suggests a greater double layer stability for ion exchange processes than in the case of CEMs. Our work shows that these modified membranes could be an appealing approach for AORFB applicationsThis work has been funded by the European Union under the HIGREEW project, Affordable High-performance Green Redox Flow batteries (Grant agreement no. 875613). H2020: LC-BAT-4-2019875613

Roadmap to the multidisciplinary design analysis and optimisation of wind energy systems

A research agenda is described to further encourage the application of Multidisciplinary Design Analysis and Optimisation (MDAO) methodologies to wind energy systems. As a group of researchers closely collaborating within the International Energy Agency (IEA) Wind Task 37 for Wind Energy Systems Engineering: Integrated Research, Design and Development, we have identified challenges that will be encountered by users building an MDAO framework. This roadmap comprises 17 research questions and activities recognised to belong to three research directions: model fidelity, system scope and workflow architecture. It is foreseen that sensible answers to all these questions will enable to more easily apply MDAO in the wind energy domain. Beyond the agenda, this work also promotes the use of systems engineering to design, analyse and optimise wind turbines and wind farms, to complement existing compartmentalised research and design paradigms

Gap-anisotropic model for the narrow-gap Kondo insulators

A theory is presented which accounts for the dynamical generation of a hybridization gap with nodes in the Kondo insulating materials $CeNiSn$ and $CeRhSb$. We show that Hunds interactions acting on virtual $4f^2$ configurations of the cerium ion can act to dynamically select the shape of the cerium ion by generating a Weiss field which couples to the shape of the ion. In low symmetry crystals where the external crystal fields are negligible, this process selects a nodal Kondo semimetal state as the lowest energy configuration.Comment: Substantially Revised Versio

Sentiment analysis to support business decision-making. A bibliometric study

Customer feedback on online platforms is an unstructured database of growing importance for organizations, which, together with the rise of Natural Language Processing algorithms, is increasingly present when making decisions. In this paper, a bibliometric analysis is carried out with the intention of understanding the prevailing state of research about the adoption of sentiment analysis methods in organizations when making decisions. It is also a goal to comprehend which business sectors, and areas within the company, they are most applied, and to identify what future challenges that in this area may arise, as well as the main topics, authors, articles, countries, and universities most influential in the scientific literature. To this end, a total of 101 articles have been gathered from the Scopus and Clarivate Analytics Web of Science (WoS) databases, of which 85 were selected for analysis using the Bibliometrix tool. This study highlights the growing popularity of sentiment analysis methods combined with Multicriteria Decision Making and predictive algorithms. Twitter and Amazon are commonly used data sources, with applications across multiple sectors (supply chain, financial, etc.). Sentiment analysis enhances decision-making and promotes customer-centric approaches

Energy loss of protons and deuterons at low energies in Pd polycrystalline thin films

We have investigated experimentally and by computer simulations the energy loss  distributions of low energy (E <10 keV) protons and deuterons transmitted through  polycrystalline palladium thin flms. In contrast with previous experiments on various transition metals we find that the stopping power of Pd is proportional to the ion velocity. Data of protons and deuterons are coincident within the experimental uncertainties, showing the absence of an isotopic effect on the stopping power of Pd in this energy range. The experimental results were analyzed and compared with Monte Carlo computer simulations and previous theoretical models. The dference in the velocity dependence of the energy loss of hydrogen ions in Pd with respect to other transition metals (Cu, Ag and Au) is explained by a theoretical analysis based on the properties of the d-electron bands of those elements.Fil: Celedón, C.. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Investigación y Aplicaciones No Nucleares. Gerencia de Física (Centro Atómico Bariloche); ArgentinaFil: Sanchez, Esteban Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Investigación y Aplicaciones No Nucleares. Gerencia de Física (Centro Atómico Bariloche); Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; ArgentinaFil: Moreno, Mario Sergio Jesus. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Investigación y Aplicaciones No Nucleares. Gerencia de Física (Centro Atómico Bariloche); Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; ArgentinaFil: Arista, Nestor Ricardo. Comisión Nacional de Energía Atómica. Gerencia del Area de Investigación y Aplicaciones No Nucleares. Gerencia de Física (Centro Atómico Bariloche); Argentina. Comisión Nacional de Energía Atómica. Gerencia del Area de Energía Nuclear. Instituto Balseiro; ArgentinaFil: Uribe, J. D.. Universidad Técnica Federico Santa María. Departamento de Física. Laboratorio de Colisiones Atómicas; ChileFil: Mery, M.. Universidad Técnica Federico Santa María. Departamento de Física. Laboratorio de Colisiones Atómicas; ChileFil: Valdés, J. E.. Universidad Técnica Federico Santa María. Departamento de Física. Laboratorio de Colisiones Atómicas; ChileFil: Vargas, P.. Universidad Técnica Federico Santa María. Departamento de Física. Laboratorio de Colisiones Atómicas; Chil

Classification of the Gait Pattern in Polymyalgia Rheumatica Patients Using Recurrent Neural Networks

The early detection of movement disorders is essential for clinicians in many diseases, and it forms an integral part of effective treatment planning for patients. Polymyalgia rheumatica (PMR) is an autoimmune musculoskeletal disease that affects muscles around the pelvic girdle and shoulder blade. It is currently unknown how the strained hip muscles around the pelvic girdle create mobility limitations in patients. This study presents an algorithm for the classification of the hip muscle activation pattern in clinical gait analysis using recurrent neural networks (RNNs). RNNs was chosen because of its ability to capture temporal dependencies and process sequential electromyography (EMG) data in gait classification. A clinical gait assessment was conducted at KATH hospital which collected 250 gait segments from 18 PMR patients and 7 healthy control subjects. EMG signals were recorded from the vastus lateralis (VL), rectus femoris (RF), biceps femoris (BF), and semitendinosus (SE). Different optimizers were used in the RNN model to classify the hip muscle activation of the two groups to discriminate the gait pattern. Four optimizers (Adamax, Adagrad, SGD, and RMSprop) were used to evaluate the best optimizer for the RNN model. The accuracy results recorded from a cross-validation were, Adamax = 89%, Adagrad = 83%, SGD = 85%, and RMSprop = 78%. Adamax was the best performing optimizer while RMSprop was the least performing in the gait classification. An average accuracy of 84% from the four optimizers was sufficient to distinguish the gait pattern of the two groups. The findings of this study are useful in discriminating gait patterns based on hip muscle activation. This will provide essential information for the early detection of gait impairments by clinicians to make more informed a nd ti me ly decisions