Trajectory Deflection of Spinning Magnetic Microparticles, the Magnus Effect at the Microscale

The deflection due to the Magnus force of magnetic particles with a diameter of 80 micrometer dropping through fluids and rotating in a magnetic field was measured. With Reynolds number for this experiment around 1, we found trajectory deflections of the order of 1 degree, in agreement within measurement error with theory. This method holds promise for the sorting and analysis of the distribution in magnetic moment and particle diameter of suspensions of microparticles, such as applied in catalysis, or objects loaded with magnetic particles.Comment: 12 pages, 3 figures. Appendix with 6 figure

Optimizing both catalyst preparation and catalytic behaviour for the oxidative dehydrogenation of ethane of Ni-Sn-O catalysts

[EN] Bulk Ni-Sn-O catalysts have been synthesized, tested in the oxidative dehydrogenation of ethane and characterized by several physicochemical techniques. The catalysts have been prepared by evaporation of the corresponding salts using several additives in the synthesis gel, i.e. ammonium hydroxide, nitric acid, glyoxylic acid or oxalic acid, in the synthesis gel. The catalysts were finally calcined at 500 degrees C in air. Important changes in the catalytic behaviour have been observed depending on the additive. In fact, an important improvement in the catalytic performance is observed especially when some additives, such as glyoxylic or oxalic acid, are used. Thus the productivity to ethylene multiplies by 6 compared to the reference Ni-Sn-O catalyst if appropriate templates are used, and this is the result of an improvement in both the catalytic activity and the selectivity to ethylene. This improved performance has been explained in terms of the decrease of the crystallite size (and the increase in the surface area of catalyst) as well as the modification of the lattice parameter of nickel oxide.The authors would like to acknowledge the DGICYT in Spain (CTQ2015-68951-C3-1-R and CTQ2012-37925-C03-2) for financial support. We also thank the University of Valencia and SCSIE-UV for assistanceSolsona Espriu, BE.; López Nieto, JM.; Agouram, S.; Soriano Rodríguez, MD.; Dejoz, A.; Vázquez, MI.; Concepción Heydorn, P. (2016). Optimizing both catalyst preparation and catalytic behaviour for the oxidative dehydrogenation of ethane of Ni-Sn-O catalysts. Topics in Catalysis. 59(17-18):1564-1572. https://doi.org/10.1007/s11244-016-0674-zS156415725917-18Heracleous E, Lee AF, Wilson K, Lemonidou AA (2005) J Catal 231:159–171Heracleous E, Lemonidou AA (2006) J Catal 237:162–174Savova B, Loridant S, Filkova D, Millet JMM (2010) Appl Catal A 390:148–157Heracleous E, Lemonidou AA (2010) J Catal 270:67–75Solsona B, Nieto JML, Concepcion P, Dejoz A, Ivars F, Vazquez MI (2011) J Catal 280:28–39Skoufa Z, Heracleous E, Lemonidou AA (2012) Catal Today 192:169–176Zhu H, Ould-Chikh S, Anjum DH, Sun M, Biausque G, Basset JM, Caps V (2012) J Catal 285:292–303Skoufa Z, Heracleous E, Lemonidou AA (2012) Chem Eng Sci 84:48–56Zhu H, Rosenfeld DC, Anjum DH, Caps V, Basset JM (2015) ChemSusChem 8:1254–1263Heracleous E, Lemonidou AA (2015) J Catal 322:118–129Solsona B, Concepcion P, Demicol B, Hernandez S, Delgado JJ, Calvino JJ, Nieto JML (2012) J Catal 295:104–114Nieto JML, Solsona B, Grasselli RK, Concepción P (2014) Top Catal 57:1248–1255Popescu I, Skoufa Z, Heracleous E, Lemonidou AA, Marcu IC (2015) PCCP 17:8138–8147Zhang X, Gong Y, Yu G, Xie Y (2002) J Mol Catal A 180:293–298Popescu I, Skoufa Z, Heracleous E, Lemonidou A, Marcu I-C (2015) Phys Chem Chem Phys 17:8138–8147Nakamura KI, Miyake T, Konishi T, Suzuki T (2006) J Mol Catal A 260:144–151Solsona B, Dejoz AM, Vazquez MI, Ivars F, Nieto JML (2009) Top Catal 52:751–757Bortolozzi JP, Gutierrez LB, Ulla MA (2013) Appl Catal A 452:179–188Takeguchi T, Furukawa S, Inoue M (2001) J Catal 202:14–24Richardson JT, Turk B, Twigg MV (1996) Appl Catal 148:97–112Biju V, Khadar MA (2002) J Nanopart Res 4:247–253Van Veenendaal MA, Sawatzky GA (1993) Phys Rev Lett 70:2459–2462Vedrine JC, Hollinger G, Duc TM (1978) J Phys Chem 82:1515–1520Salagre P, Fierro JLG, Medina F, Sueiras JE (1996) J Mol Catal A 106:125–13

Evaluation of an improved tool for non-invasive prediction of neonatal respiratory morbidity based on fully automated fetal lung ultrasound analysis

The objective of this study was to evaluate the performance of a new version of quantusFLM®, a software tool for prediction of neonatal respiratory morbidity (NRM) by ultrasound, which incorporates a fully automated fetal lung delineation based on Deep Learning techniques. A set of 790 fetal lung ultrasound images obtained at 24 + 0-38 + 6 weeks' gestation was evaluated. Perinatal outcomes and the occurrence of NRM were recorded. quantusFLM® version 3.0 was applied to all images to automatically delineate the fetal lung and predict NRM risk. The test was compared with the same technology but using a manual delineation of the fetal lung, and with a scenario where only gestational age was available. The software predicted NRM with a sensitivity, specificity, and positive and negative predictive value of 71.0%, 94.7%, 67.9%, and 95.4%, respectively, with an accuracy of 91.5%. The accuracy for predicting NRM obtained with the same texture analysis but using a manual delineation of the lung was 90.3%, and using only gestational age was 75.6%. To sum up, automated and non-invasive software predicted NRM with a performance similar to that reported for tests based on amniotic fluid analysis and much greater than that of gestational age alone

Portal interdimensional ciència-ficció. Enginyeria Gràfica

Preprin

Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes

The goal of this study was to evaluate the maturity of current Deep Learning classification techniques for their application in a real maternal-fetal clinical environment. A large dataset of routinely acquired maternal-fetal screening ultrasound images (which will be made publicly available) was collected from two different hospitals by several operators and ultrasound machines. All images were manually labeled by an expert maternal fetal clinician. Images were divided into 6 classes: four of the most widely used fetal anatomical planes (Abdomen, Brain, Femur and Thorax), the mother's cervix (widely used for prematurity screening) and a general category to include any other less common image plane. Fetal brain images were further categorized into the 3 most common fetal brain planes (Trans-thalamic, Trans-cerebellum, Trans-ventricular) to judge fine grain categorization performance. The final dataset is comprised of over 12,400 images from 1,792 patients, making it the largest ultrasound dataset to date. We then evaluated a wide variety of state-of-the-art deep Convolutional Neural Networks on this dataset and analyzed results in depth, comparing the computational models to research technicians, which are the ones currently performing the task daily. Results indicate for the first time that computational models have similar performance compared to humans when classifying common planes in human fetal examination. However, the dataset leaves the door open on future research to further improve results, especially on fine-grained plane categorization

Utilización de servicios sanitarios en ancianos (España 2006-2012): influencia del nivel de salud y de la clase social

Objetivo Conocer la utilización de servicios sanitarios de Atención Primaria (AP), Atención Especializada (AE), hospitalizaciones, Hospital de Día y Urgencias, y la hiperfrecuentación en ancianos en España, analizando la influencia del estado de salud, sexo, clase social y evolución temporal. Diseño Estudio transversal en 2 fases. Emplazamiento España. Participantes Personas encuestadas en la Encuesta Nacional de Salud 2006 y 2011-12. Mediciones principales Como variables de salud se utilizaron la salud percibida y diagnosticada (número y tipo de diagnósticos). La clase social se obtuvo a partir de la última ocupación del sustentador principal (clases manuales y no manuales). Se realizaron análisis de regresión logística, ajustando por sexo, edad, nivel de salud, clase social y año, calculando su capacidad predictiva. ResultadosEl porcentaje de población mayor que utiliza consultas médicas descendió en el periodo estudiado. Las mujeres trabajadoras manuales presentaron la mayor prevalencia de mala salud (mala salud percibida en el 2006: 70,6%). La mala salud se asoció a mayor utilización de servicios sanitarios. La salud percibida fue mejor predictor de utilización de servicios y de hiperfrecuentación que la diagnosticada, con la mayor capacidad predictiva para AE (C = 0,676). Los ancianos de clases sociales bajas utilizaron con más frecuencia AP y Urgencias, mientras que la utilización de AE y Hospital de Día fue mayor en clases altas. Conclusiones Existen diferencias en salud y utilización de servicios sanitarios en mayores según clase social. Resulta necesario prestar atención a la salud percibida como predictor de la utilización de servicios sanitarios y revisar la accesibilidad-equidad de nuestros servicios

Réaction d'hypersensibilité cutanée chez le cobaye consécutive à l'inoculation intra-dermique d'un antigène chlamydien («virus» de l'avortement de la brebis) purifié inactivé

L’inoculation intra dermique au cobaye syngénique d’un anti gène ehlamydien purifié, inactive, mélangé à l’antigène complet de Freund, détermine un état d’hypersensibilité que révèle une deuxième injection intra dermique pratiquée au sixième jour : La réaction obtenue ne fait pas intervenir d’anticorps circulants. L’état de sensibilité qu’elle traduit est transféré au cobaye neuf par injection intra-péritonéale d’une suspension en solution saline équilibrée d’un broyât de ganglions prélevés sur cobaye sensi bilisé. L’intensité des réactions obtenues montre l’importance de la réaction cellulaire dans la réponse immunitaire du cobaye à l’injection de cet antigène

Mid-trimester prediction of spontaneous preterm birth with automated cervical quantitative ultrasound texture analysis and cervical length: a prospective study

The objective of this study was to evaluate a novel automated test based on ultrasound cervical texture analysis to predict spontaneous Preterm Birth (sPTB) alone and in combination with Cervical Length (CL). General population singleton pregnancies between 18+ 0 and 24 + 6 weeks' gestation were assessed prospectively at two centers. Cervical ultrasound images were evaluated and the occurrence of sPTB before weeks 37 + 0 and 34 + 0 were recorded. CL was measured on-site. The automated texture analysis test was applied ofine to all images. Their performance to predict the occurrence of sPTB before 37 + 0 and 34 + 0 weeks was evaluated separately and in combination on 633 recruited patients. AUC for sPTB prediction before weeks 37 and 34 respectively were as follows: 55.5% and 65.3% for CL, 63.4% and 66.3% for texture analysis, 67.5% and 76.7% when combined. The new test improved detection rates of CL at similar low FPR. Combining the two increased detection rate compared to CL alone from 13.0 to 30.4% for sPTB< 37 and from 14.3 to 42.9% sPTB< 34. Texture analysis of cervical ultrasound improved sPTB detection rate compared to cervical length for similar FPR, and the two combined together increased signifcantly prediction performance. This results should be confrmed in larger cohorts