A “Soft” Approach to Analysing Mobile Financial Services Sociotechnical Systems

Advances in mobile computing have presented a huge opportunity to provide Mobile Financial Services (MFS) to half of the world’s population who currently do not have access to financial services. However, cybersecurity concerns in the mobile computing ecosystem have slowed down the adoption of MFS. The adoption of MFS is further hampered by the lack of a clear understanding of the interaction between the complex infrastructures and human factors that exist in the ecosystem for Mobile Financial Services Socio-Technical Systems (MFSSTS). This paper presents the work in progress of investigating the problem of MFSSTS. It discusses the preliminary results and understanding obtained from using Human Factor approaches to build and analyse the model for MFSSTS

N2-H2 capacitively coupled radio-frequency discharges at low pressure. Part I. Experimental results: Effect of the H2 amount on electrons, positive ions and ammonia formation

The mixing of N2 with H2 leads to very different plasmas from pure N2 and H2 plasma discharges. Numerous issues are therefore raised involving the processes leading to ammonia (NH3) formation. The aim of this work is to better characterize capacitively-coupled radiofrequency plasma discharges in N2 with few percents of H2 (up to 5%), at low pressure (0.3-1 mbar) and low coupled power (3-13 W). Both experimental measurements and numerical simulations are performed. For clarity, we separated the results in two complementary parts. The actual one (first part), presents the details on the experimental measurements, while the second focuses on the simulation, a hybrid model combining a 2D fluid module and a 0D kinetic module. Electron density is measured by a resonant cavity method. It varies from 0.4 to 5 109 cm-3, corresponding to ionization degrees from 2 10-8 to 4 10-7. Ammonia density is quantified by combining IR absorption and mass spectrometry. It increases linearly with the amount of H2 (up to 3 1013 cm-3 at 5% H2). On the contrary, it is constant with pressure, which suggests the dominance of surface processes on the formation of ammonia. Positive ions are measured by mass spectrometry. Nitrogen-bearing ions are hydrogenated by the injection of H2, N2H+ being the major ion as soon as the amount of H2 is >1%. The increase of pressure leads to an increase of secondary ions formed by ion/radical-neutral collisions (ex: N2H+, NH4 +, H3 +), while an increase of the coupled power favours ions formed by direct ionization (ex: N2 +, NH3 +, H2 +).N. Carrasco acknowledges the financial support of the European Research Council (ERC Starting Grant PRIMCHEM, Grant agreement no. 636829). A. Chatain acknowledges ENS Paris-Saclay Doctoral Program. A. Chatain is grateful to Gilles Cartry and Thomas Gautier for fruitful discussions on the MS calibration. L.L. Alves acknowledges the financial support of the Portuguese Foundation for Science and Technology (FCT) through the project UID/FIS/50010/2019. L. Marques and M. J. Redondo acknowledge the financial support of the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UIDB/04650/2019

Self-similarity of contact line depinning from textured surfaces

The mobility of drops on surfaces is important in many biological and industrial processes, but the phenomena governing their adhesion, which is dictated by the morphology of the three-phase contact line, remain unclear. Here we describe a technique for measuring the dynamic behaviour of the three-phase contact line at micron length scales using environmental scanning electron microscopy. We examine a superhydrophobic surface on which a drop’s adhesion is governed by capillary bridges at the receding contact line. We measure the microscale receding contact angle of each bridge and show that the Gibbs criterion is satisfied at the microscale. We reveal a hitherto unknown self-similar depinning mechanism that shows how some hierarchical textures such as lotus leaves lead to reduced pinning, and counter-intuitively, how some lead to increased pinning. We develop a model to predict adhesion force and experimentally verify the model’s broad applicability on both synthetic and natural textured surfaces.National Science Foundation (U.S.) (CAREER Award 0952564)DuPont MIT AllianceNational Science Foundation (U.S.). Graduate Research Fellowship ProgramNational Science Foundation (U.S.) (Award ECS-0335765

Genetically manipulated phages with improved pH resistance for oral administration in veterinary medicine

Orally administered phages to control zoonotic pathogens face important challenges, mainly related to the hostile conditions found in the gastrointestinal tract (GIT). These include temperature, salinity and primarily pH, which is exceptionally low in certain compartments. Phage survival under these conditions can be jeopardized and undermine treatment. Strategies like encapsulation have been attempted with relative success, but are typically complex and require several optimization steps. Here we report a simple and efficient alternative, consisting in the genetic engineering of phages to display lipids on their surfaces. Escherichia coli phage T7 was used as a model and the E. coli PhoE signal peptide was genetically fused to its major capsid protein (10A), enabling phospholipid attachment to the phage capsid. The presence of phospholipids on the mutant phages was confirmed by High Performance Thin Layer Chromatography, Dynamic Light Scattering and phospholipase assays. The stability of phages was analysed in simulated GIT conditions, demonstrating improved stability of the mutant phages with survival rates 102107 pfu.mL1 higher than wild-type phages. Our work demonstrates that phage engineering can be a good strategy to improve phage tolerance to GIT conditions, having promising application for oral administration in veterinary medicine.This work was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and under the scope of the Project PTDC/BBB-BSS/6471/2014 (POCI-01-0145-FEDER-016678). Franklin L. Nobrega and Ana Rita Costa acknowledge FCT for grants SFRH/BD/86462/2012 and SFRH/BPD/94648/2013, respectively. Melvin F. Siliakus acknowledges funding from the Biobased Ecologically Balanced Sustainable Industrial Chemistry (BE-BASIC) foundation. Electron microscopy work was performed at the Wageningen Electron Microscopy Centre (WEMC) of Wageningen University

Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma.

Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA