Determining the efficiency of optical sources using a smartphone's ambient light sensor

This work reports the use of a smartphone’s ambient light sensor as a valuable tool to study and characterize the efficiency of an optical source. Here, we have measured both luminous efficacy and efficiency of several optical sources (incandescent bulb and halogen lamp) as a function of the electric power consumed and the distance to the optical detector. The illuminance of LEDs as a function of the distance to the optical detector is characterized for different wavelength emissions. Analysis of the results confirms an inverse-square law of the illuminance with the detector–source distance and shows good agreement with values obtained by classical experiments. This experience will trigger awareness in students in terms of sustainability, light propagation and efficiency of different optical sources.The authors would like to thank the Institute of Education Sciences, Universitat Politecnica de Valencia (Spain), for the support of the teaching innovation groups MOMA and e-MACAFI, and the financial support of Project PIME-2015-B18. The authors also acknowledge the financial support of project EDU2015-69701-P by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund. J A Sans acknowledges Ramon y Cajal fellowship program for financial support.Sans-Tresserras, JÁ.; Gea Pinal, J.; Giménez Valentín, MH.; Esteve, AR.; Solbes, J.; Monsoriu Serra, JA. (2017). Determining the efficiency of optical sources using a smartphone's ambient light sensor. European Journal of Physics. 38(2):1-9. https://doi.org/10.1088/1361-6404/aa51a9S1938

Perfusion-weighted software written in Python for DSC-MRI analysis

IntroductionDynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies in magnetic resonance imaging (MRI) provide valuable data for studying vascular cerebral pathophysiology in different rodent models of brain diseases (stroke, tumor grading, and neurodegenerative models). The extraction of these hemodynamic parameters via DSC-MRI is based on tracer kinetic modeling, which can be solved using deconvolution-based methods, among others. Most of the post-processing software used in preclinical studies is home-built and custom-designed. Its use being, in most cases, limited to the institution responsible for the development. In this study, we designed a tool that performs the hemodynamic quantification process quickly and in a reliable way for research purposes.MethodsThe DSC-MRI quantification tool, developed as a Python project, performs the basic mathematical steps to generate the parametric maps: cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), signal recovery (SR), and percentage signal recovery (PSR). For the validation process, a data set composed of MRI rat brain scans was evaluated: i) healthy animals, ii) temporal blood–brain barrier (BBB) dysfunction, iii) cerebral chronic hypoperfusion (CCH), iv) ischemic stroke, and v) glioblastoma multiforme (GBM) models. The resulting perfusion parameters were then compared with data retrieved from the literature.ResultsA total of 30 animals were evaluated with our DSC-MRI quantification tool. In all the models, the hemodynamic parameters reported from the literature are reproduced and they are in the same range as our results. The Bland–Altman plot used to describe the agreement between our perfusion quantitative analyses and literature data regarding healthy rats, stroke, and GBM models, determined that the agreement for CBV and MTT is higher than for CBF.ConclusionAn open-source, Python-based DSC post-processing software package that performs key quantitative perfusion parameters has been developed. Regarding the different animal models used, the results obtained are consistent and in good agreement with the physiological patterns and values reported in the literature. Our development has been built in a modular framework to allow code customization or the addition of alternative algorithms not yet implemented

The Mars Environmental Dynamics Analyzer, MEDA. A Suite of Environmental Sensors for the Mars 2020 Mission

86 pags., 49 figs., 24 tabs.NASA’s Mars 2020 (M2020) rover mission includes a suite of sensors to monitor current environmental conditions near the surface of Mars and to constrain bulk aerosol properties from changes in atmospheric radiation at the surface. The Mars Environmental Dynamics Analyzer (MEDA) consists of a set of meteorological sensors including wind sensor, a barometer, a relative humidity sensor, a set of 5 thermocouples to measure atmospheric temperature at ∼1.5 m and ∼0.5 m above the surface, a set of thermopiles to characterize the thermal IR brightness temperatures of the surface and the lower atmosphere. MEDA adds a radiation and dust sensor to monitor the optical atmospheric properties that can be used to infer bulk aerosol physical properties such as particle size distribution, non-sphericity, and concentration. The MEDA package and its scientific purpose are described in this document as well as how it responded to the calibration tests and how it helps prepare for the human exploration of Mars. A comparison is also presented to previous environmental monitoring payloads landed on Mars on the Viking, Pathfinder, Phoenix, MSL, and InSight spacecraft.This work has been funded by the Spanish Ministry of Economy and Competitiveness, through the projects No. ESP2014-54256-C4-1-R (also -2-R, -3-R and -4-R) and AYA2015-65041-P; Ministry of Science, Innovation and Universities, projects No. ESP2016-79612-C3-1-R (also -2-R and -3-R), ESP2016-80320-C2-1-R, RTI2018-098728-B-C31 (also -C32 and -C33) and RTI2018-099825-B-C31; Instituto Nacional de Técnica Aeroespacial; Ministry of Science and Innovation’s Centre for the Development of Industrial Technology; Grupos Gobierno Vasco IT1366-19; and European Research Council Consolidator Grant no 818602. The US co-authors performed their work under sponsorship from NASA’s Mars 2020 project, from the Game Changing Development program within the Space Technology Mission Directorate and from the Human Exploration and Operations Directorate

The Mars Environmental Dynamics Analyzer, MEDA. A Suite of Environmental Sensors for the Mars 2020 Mission

86 pags, 49 figs, 24 tabsNASA's Mars 2020 (M2020) rover mission includes a suite of sensors to monitor current environmental conditions near the surface of Mars and to constrain bulk aerosol properties from changes in atmospheric radiation at the surface. The Mars Environmental Dynamics Analyzer (MEDA) consists of a set of meteorological sensors including wind sensor, a barometer, a relative humidity sensor, a set of 5 thermocouples to measure atmospheric temperature at ∼1.5 m and ∼0.5 m above the surface, a set of thermopiles to characterize the thermal IR brightness temperatures of the surface and the lower atmosphere. MEDA adds a radiation and dust sensor to monitor the optical atmospheric properties that can be used to infer bulk aerosol physical properties such as particle size distribution, non-sphericity, and concentration. The MEDA package and its scientific purpose are described in this document as well as how it responded to the calibration tests and how it helps prepare for the human exploration of Mars. A comparison is also presented to previous environmental monitoring payloads landed on Mars on the Viking, Pathfinder, Phoenix, MSL, and InSight spacecraft.This work has been funded by the Spanish Ministry of Economy and Competitiveness, through the projects No. ESP2014-54256-C4-1-R (also -2-R, -3-R and -4-R) and AYA2015-65041-P; Ministry of Science, Innovation and Universities, projects No. ESP2016-79612-C3-1-R (also -2-R and -3-R), ESP2016-80320-C2-1-R, RTI2018-098728-B-C31 (also -C32 and -C33) and RTI2018-099825-B-C31; Instituto Nacional de Tecnica Aeroespacial; Ministry of Science and Innovation's Centre for the Development of Industrial Technology; Grupos Gobierno Vasco IT1366-19; and European Research Council Consolidator Grant no 818602.Peer reviewe

The presence of leukoaraiosis enhances the association between sTWEAK and hemorrhagic transformation

OBJECTIVE: To investigate whether elevated serum levels of sTWEAK (soluble tumor necrosis factor-like inducer of apoptosis) might be involved in a higher frequency of symptomatic hemorrhagic transformation (HT) through the presence of leukoaraiosis (LA) in patients with acute ischemic stroke (IS) undergoing reperfusion therapies. METHODS: This is a retrospective observational study. The primary endpoint was to study the sTWEAK-LA-HT relationship by comparing results with biomarkers associated to HT and evaluating functional outcome at 3-months. Clinical factors, neuroimaging variables and biomarkers associated to inflammation, endothelial/atrial dysfunction or blood-brain barrier damage were also investigated. RESULTS: We enrolled 875 patients (mean age 72.3 +/- 12.2 years; 46.0% women); 710 individuals underwent intravenous thrombolysis, 87 endovascular therapy and 78 both. HT incidence was 32%; LA presence was 75.4%. Patients with poor functional outcome at 3-months showed higher sTWEAK levels at admission (9844.2 [7460.4-12,542.0] vs. 2717.3 [1489.7-5852.3] pg/mL, P /=6700 pg/mL were associated with an odds ratio of 13 for poor outcome at 3-months (OR: 13.6; CI 95%: 8.2-22.6, P < 0.0001). CONCLUSIONS: Higher sTWEAK levels are independently associated with HT and poor functional outcome in patients with IS undergoing reperfusion therapies through the presence of LA. sTWEAK could become a therapeutic target to reduce HT incidence in patients with IS

Overview of Near-Surface Atmospheric Processes at Jezero from Meda Observations.

International audienc

Overview of Near-Surface Atmospheric Processes at Jezero from Meda Observations.

International audienc

Observations of the climate near the surface of Jezero over a half Mars year

International audiencePerseverance landed on Jezero with the most complete suite of environmental sensors ever sent to the surface of another planet. It combines the Mars Environmental Dynamics Analyzer (MEDA), the MastCam-Z and Engineering cameras, SuperCam spectrometers and, finally, the several microphones onboard the Mars 2020 rover. The most recent collection of atmospheric observations at Jezero and their interpretation are building an understanding of what physical processes drive the behavior of the Martian atmosphere near the surface of Jezero. We report on the observed Martian cycles of pressure, temperature, dust opacity with their physical aerosol properties, and the hydrological cycle at Jezero. These cycles have shown different behaviors on time scales from diurnal to seasonal and annual to other locations where we landed before. The differences illustrate the range of environmental processes that one can find near the red planet’s surface. We also report on the observed evolution of the near-surface boundary layer thermodynamics during the day and nighttime regimes