Design, Development and Testing of a Monitoring System for the Study of Proton Exchange Fuel Cells and Stacks.

This article is about the design, development and validation of a new monitoring architecture for individual cells and stacks to facilitate the study of proton exchange fuel cells. The system consists of four main elements: input signals, signal processing boards, analogue-to-digital converters (ADCs) and a master terminal unit (MTU). The latter integrates a high-level graphic user interface (GUI) software developed by National Instruments LABVIEW, while the ADCs are based on three digital acquisition units (DAQs). Graphs showing the temperature, currents and voltages in individual cells as well as stacks are integrated for ease of reference. The system validation was carried out both in static and dynamic modes of operation using a Ballard Nexa 1.2 kW fuel cell fed by a hydrogen cylinder, with a Prodigit 32612 electronic load at the output. The system was able to measure the voltage distributions of individual cells, and temperatures at different equidistant points of the stack both with and without an external load, validating its use as an indispensable tool for the study and characterization of these systems.

Stack Splinting Versus Kirschner Wire Treatment in Acute Closed Mallet Finger Doyle I.

Introduction: Mallet injuries are common and usually treated conservatively. Various systematic reviews have found a lack of evidence regarding the best management, and it is still unclear. Objective: To evaluate the treatment efficacy of Stack Splinting compared to a Kirschner wire immobilization of acute closed mallet finger Doyle I. Methods: From March 2019 to February 2020, 41 patients with acute close mallet finger Doyle I were treated; 19 patients were treated with Kirschner wire and 22 with Stack splinting for a mean of 6 weeks. The average patient age at the time of the injury was 43 years. Results: Twenty-eight males and 13 females were in this study. Among them, 17 patients were injured in the little finger, 15 in the middle finger, and 9 in the ring finger. Twenty-seven of injuries suffered an aggression, 11 from falling, and 3 from sports injuries. All the fingers had typical mallet malformation. Seventeen patients treated with Kirschner wire completed the treatment with full recovery, only 7 patients treated with Stack splint completed the treatment and 15 treated with Stack splint had relapse on mallet injury. Conclusion: Kirschner wire treatment is a simple procedure, and proves in this study that has better results in patients with acute closed mallet finger Doyle I compared to Stack splint.

Introduction: Les doigts à gâchette (ou à ressaut) sont courants et généralement traités avec prudence. Diverses analyses systématiques ont constaté un manque de données probantes sur la prise en charge optimale, qui n'est pas toujours claire. Objectif: Évaluer l'efficacité du traitement par attelle de Stack par rapport à l'immobilisation par broches de Kirschner en cas de doigt à gâchette fermé en phase aiguë correspondant à la classification 1 de Doyle. Méthodologie: Entre mars 2019 et février 2020, 41 patients d'un âge moyen de 43 ans au moment de la lésion ont présenté un doigt à gâchette fermé en phase aiguë correspondant à la classification 1 de Doyle et ont été traités. Ainsi, 19 ont été traités par une broche de Kirschner et 22, par une attelle de Stack, pendant une période moyenne de six semaines. Résultats: Au total, 28 hommes et 13 femmes ont participé à cette étude. De ce nombre, 17 patients ont subi une blessure de l'auriculaire, 15, du majeur, et neuf, de l'annulaire. Une agression avait causé 27 des blessures, une chute en avait causé 11 et des blessures sportives, trois. Tous les doigts présentaient la malformation à gâchette classique. Au total, 17 patients traités par une broche de Kirschner ont terminé le traitement et se sont pleinement rétablis, mais seulement sept patients ayant eu une attelle de Stack ont terminé le traitement, et 15 d'entre eux ont vécu une rechute. Conclusion: Le traitement par broche de Kirschner est une intervention simple, et la présente étude démontre qu'il donne de meilleurs résultats que l'attelle de Stack chez les patients ayant un doigt à gâchette fermé en phase aiguë correspondant à la classification 1 de Doyle.

Improving Seismic Inversion Robustness via Deformed Jackson Gaussian.

The seismic data inversion from observations contaminated by spurious measures (outliers) remains a significant challenge for the industrial and scientific communities. This difficulty is due to slow processing work to mitigate the influence of the outliers. In this work, we introduce a robust formulation to mitigate the influence of spurious measurements in the seismic inversion process. In this regard, we put forth an outlier-resistant seismic inversion methodology for model estimation based on the deformed Jackson Gaussian distribution. To demonstrate the effectiveness of our proposal, we investigated a classic geophysical data-inverse problem in three different scenarios: (i) in the first one, we analyzed the sensitivity of the seismic inversion to incorrect seismic sources; (ii) in the second one, we considered a dataset polluted by Gaussian errors with different noise intensities; and (iii) in the last one we considered a dataset contaminated by many outliers. The results reveal that the deformed Jackson Gaussian outperforms the classical approach, which is based on the standard Gaussian distribution.

Galaxy and MEAN Stack to Create a User-Friendly Workflow for the Rational Optimization of Cancer Chemotherapy.

One aspect of personalized medicine is aiming at identifying specific targets for therapy considering the gene expression profile of each patient individually. The real-world implementation of this approach is better achieved by user-friendly bioinformatics systems for healthcare professionals. In this report, we present an online platform that endows users with an interface designed using MEAN stack supported by a Galaxy pipeline. This pipeline targets connection hubs in the subnetworks formed by the interactions between the proteins of genes that are up-regulated in tumors. This strategy has been proved to be suitable for the inhibition of tumor growth and metastasis in vitro. Therefore, Perl and Python scripts were enclosed in Galaxy for translating RNA-seq data into protein targets suitable for the chemotherapy of solid tumors. Consequently, we validated the process of target diagnosis by (i) reference to subnetwork entropy, (ii) the critical value of density probability of differential gene expression, and (iii) the inhibition of the most relevant targets according to TCGA and GDC data. Finally, the most relevant targets identified by the pipeline are stored in MongoDB and can be accessed through the aforementioned internet portal designed to be compatible with mobile or small devices through Angular libraries.

Wavelength-Resolution SAR Ground Scene Prediction Based on Image Stack.

This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used as a reference image in a change detection algorithm yielding a high probability of detection and low false alarm rate. The predictions are based on image stacks, which are composed of images from the same scene acquired at different instants with the same flight geometry. The considered methods for obtaining the ground scene prediction include (i) autoregressive models; (ii) trimmed mean; (iii) median; (iv) intensity mean; and (v) mean. It is expected that the predicted image presents the true ground scene without change and preserves the ground backscattering pattern. The study indicates that the the median method provided the most accurate representation of the true ground. To show the applicability of the GSP, a change detection algorithm was considered using the median ground scene as a reference image. As a result, the median method displayed the probability of detection of 97 % and a false alarm rate of 0 . 11 / km 2 , when considering military vehicles concealed in a forest.

Evaluation of single and stack membraneless enzymatic fuel cells based on ethanol in simulated body fluids.

The purpose of this work is to evaluate single and double-cell membraneless microfluidic fuel cells (MMFCs) that operate in the presence of simulated body fluids SBF, human serum and blood enriched with ethanol as fuels. The study was performed using the alcohol dehydrogenase enzyme immobilised by covalent binding through an array composed of carbon Toray paper as support and a layer of poly(methylene blue)/tetrabutylammonium bromide/Nafion and glutaraldehyde (3D bioanode electrode). The single MMFC was tested in a hybrid microfluidic fuel cell using Pt/C as the cathode. A cell voltage of 1.035V and power density of 3.154mWcm-2 were observed, which is the highest performance reported to date. The stability and durability were tested through chronoamperometry and polarisation/performance curves obtained at different days, which demonstrated a slow decrease in the power density on day 10 (14%) and day 20 (26%). Additionally, the cell was tested for ethanol oxidation in simulated body fluid (SBF) with ionic composition similar to human blood plasma. Those tests resulted in 0.93V of cell voltage and a power density close to 1.237mWcm-2. The double cell MMFC (Stack) was tested using serum and human blood enriched with ethanol. The stack operated with blood in a serial connection showed an excellent cell performance (0.716mWcm-2), demonstrating the feasibility of employing human blood as energy source.