3D mid-air audio-haptic navigation for digital signage

In this workshop we discuss the application of using mid-air haptics to provide directions for navigation to users in large indoor spaces. We propose a feed-forward approach from objects and locations that enable a physical way of thinking, communication and general accessibility

Forecasting Hospital Readmissions with Machine Learning

Hospital readmissions are regarded as a compounding economic factor for healthcare systems. In fact, the readmission rate is used in many countries as an indicator of the quality of services provided by a health institution. The ability to forecast patients’ readmissions allows for timely intervention and better post-discharge strategies, preventing future life-threatening events, and reducing medical costs to either the patient or the healthcare system. In this paper, four machine learning models are used to forecast readmissions: support vector machines with a linear kernel, support vector machines with an RBF kernel, balanced random forests, and weighted random forests. The dataset consists of 11,172 actual records of hospitalizations obtained from the General Hospital of Komotini “Sismanogleio” with a total of 24 independent variables. Each record is composed of administrative, medical-clinical, and operational variables. The experimental results indicate that the balanced random forest model outperforms the competition, reaching a sensitivity of 0.70 and an AUC value of 0.78

A diagnostic plot for estimating the tail index of a distribution

The problem of estimating the tail index in heavy-tailed distributions is very important in many applications. We propose a new graphical method that deals with this problem by selecting an appropriate number of upper order statistics. We also investigate the method’s theoretical properties are investigated. Several real datasets are analyzed using this new procedure and a simulation study is carried out to examine its performance in small, moderate and large samples. The results suggest that the new procedure overcomes many of the shortcomings present in some of the most common techniques—for example, the Hill and Zipf plots—used in the estimation of the tail index, and it performs very competitively when compared with other adaptive threshold procedures based on the asymptotic mean squared error of the Hill estimator.Fundação para a Ciência e a Tecnologia (FCT) - PRAXIS XXI

The use of dolomite as foaming agent and its effect on the microstructure of aluminium metal foams—Comparison to titanium hydride

Proceedings of: 8th EUFOAM Conference. Borovets, Bulgaria, 14-16 July 2010.In this paper dolomite MgCa(CO₃)₂ a naturally occurring mineral was demonstrated to be an effective foaming and stabilizing agent for aluminium with several notable advantages relative to the currently used titanium hydride foaming agent. Characteristic cell structures and microstructural features of foams produced with a dolomite foaming agent are examined and the properties of dolomite based foams produced in a one step process are compared with those produced using titanium hydride based process. The most notable structural feature of dolomite based foams is a smaller cell size and thinner cell faces. Foaming with MgCa(CO₃)₂ also gives rise to a marked increase in the stability of molten foams with a large range of foaming temperatures possible, and an almost complete absence of melt drainage even with extended foaming times. Many of these properties are attributed to the cell surfaces being covered by a thin oxide film formed during the foaming process.Publicad

Green synthesis and characterization of silver nanoparticles produced using 'Arbutus Unedo' leaf extract

Metallic nanoparticles have received great attention from chemists, physicists, biologists and engineers who wish to use them for the development of a new generation of nanodevices. In the present study silver nanoparticles were synthesized from aqueous silver nitrate through a simple and eco-friendly route using leaf broth of Arbutus unedo, which acted as a reductant and stabilizer simultaneously. The aqueous silver ions when exposed to the leaf broth were reduced and stabilized over long periods of time resulting in the green synthesis of surface functionalized silver nanoparticles. The bio-reduced silver nanoparticles were appropriately characterized. The results revealed the formation of single crystalline Ag nanoparticles with a narrow size distribution for each sample. The particles, although discrete, were predominately coated with the organic leaf extract forming small aggregates, which makes them stable over long time periods and highly appropriate for coatings or biotechnology applications.Publicad

Visualization of positive and negative sense viral RNA for probing the mechanism of direct-acting antivirals against hepatitis C virus

RNA viruses are highly successful pathogens and are the causative agents for many important diseases. To fully understand the replication of these viruses it is necessary to address the roles of both positive-strand RNA ((+)RNA) and negative-strand RNA ((-)RNA), and their interplay with viral and host proteins. Here we used branched DNA (bDNA) fluorescence in situ hybridization (FISH) to stain both the abundant (+)RNA and the far less abundant (-)RNA in both hepatitis C virus (HCV)- and Zika virus-infected cells, and combined these analyses with visualization of viral proteins through confocal imaging. We were able to phenotypically examine HCV-infected cells in the presence of uninfected cells and revealed the effect of direct-acting antivirals on HCV (+)RNA, (-)RNA, and protein, within hours of commencing treatment. Herein, we demonstrate that bDNA FISH is a powerful tool for the study of RNA viruses that can provide insights into drug efficacy and mechanism of action

Low Temperature Combustion Optimization and Cycle-by-Cycle Variability Through Injection Optimization and Gas-to-Liquid Fuel-Blend Ratio

The advent of common rail technology alongside powerful control systems capable of delivering multiple accurate fuel charges during a single engine cycle has revolutionized the level of control possible in diesel combustion. This technology has opened a new path enabling low-temperature combustion (LTC) to become a viable combustion strategy. The aim of the research work presented within this paper is the understanding of how various engine parameters of LTC optimize the combustion both in terms of emissions and in terms of fuel efficiency. The work continues with an investigation of in-cylinder pressure and IMEP cycle-by-cycle variation. Attention will be given to how repeatability changes throughout the combustion cycle, identifying which parts within the cycle are least likely to follow the mean trend and why. Experiments were conducted on a single-cylinder 510cc boosted diesel engine. LTC was affected over varying rail pressure and combustion phasing. Single and split injection regimes of varying dwell-times were investigated. All injection conditions were phased across several crank-angles to demonstrate the interaction between emissions and efficiency. These tests were then repeated with blends of 30% and 50% gas-to-liquid (GTL)-diesel blends in order to determine whether there is any change in the trends of repeatability and variance with increasing GTL blend ratio. The experiments were evaluated in terms of emissions, fuel efficiency, and cyclic behavior. Specific attention was given to how the NO x -PM trade-off changes through increased injection complexity and increasing GTL blend ratio. The cyclic behavior was analyzed in terms of in-cylinder pressure standard deviation. This gives a behavior profile of the repeatability of in-cylinder pressure in comparison to the mean. Each condition was then compared to the behavior of equivalent injection conditions in conventional diesel combustion. Short-dwell split injection was shown to be beneficial for LTC, while NO x was shown to be reduced by the substitution of GTL in the fuel. In-cylinder pressure cyclic behavior was also shown to be comparable or superior to conventional combustion in every case examined. GTL improved this further, but not in proportion to its blend ratio

Large strain compressive response of 2-D periodic representative volume element for random foam microstructures

A numerical investigation has been conducted to determine the influence of Representative Volume Element (RVE) size and degree of irregularity of polymer foam microstructure on its compressive mechanical properties, including stiffness, plateau stress and onset strain of densification. Periodic two-dimensional RVEs have been generated using a Voronoi-based numerical algorithm and compressed. Importantly, self-contact of the foam’s internal microstructure has been incorporated through the use of shell elements, allowing simulation of the foam well into the densification stage of compression; strains of up to 80 percent are applied. Results suggest that the stiffness of the foam RVE is relatively insensitive to RVE size but tends to soften as the degree of irregularity increases. Both the shape of the plateau stress and the onset strain of densification are sensitive to both the RVE size and degree of irregularity. Increasing the RVE size and decreasing the degree of irregularity both tend to result in a decrease of the gradient of the plateau region, while increasing the RVE size and degree of irregularity both tend to decrease the onset strain of densification. Finally, a method of predicting the onset strain of densification to an accuracy of about 10 per cent, while reducing the computational cost by two orders of magnitude is suggested

Experimental variables that affect human hepatocyte MV transduction in liver chimeric mice

Adeno-associated virus (AAV) vector serotypes vary in their ability to transduce hepatocytes from different species. Chimeric mouse models harboring human hepatocytes have shown translational promise for liver-directed gene therapies. However, many variables that influence human hepatocyte transduction and transgene expression in such models remain poorly defined. Here, we aimed to test whether three experimental conditions influence AAV transgene expression in immunodeficient, fumaryl-acetoactetate-hydrolase-deficient (Fah(-/-)) chimeric mice repopulated with primary human hepatocytes. We examined the effects of the murine liver injury cycle, human donor variability, and vector doses on hepatocyte transduction with various AAV serotypes expressing a green fluorescent protein (GFP). We determined that the timing of AAV vector challenge in the liver injury cycle resulted in up to 7-fold differences in the percentage of GFP expressing human hepatocytes. The GFP+ hepatocyte frequency varied 7-fold between human donors without, however, changing the relative transduction efficiency between serotypes for an individual donor. There was also a clear relationship between AAV vector doses and human hepatocyte transduction and transgene expression. We conclude that several experimental variables substantially affect human hepatocyte transduction in the Fah(-/-) chimera model, attention to which may improve reproducibility between findings from different laboratories