A One-Dimensional Volcanic Plume Model for Predicting Ash Aggregation

During explosive volcanic eruptions, volcanic ash is ejected into the atmosphere, impacting aircraft safety and downwind communities. These volcanic clouds tend to be dominated by fine ash (μm in diameter), permitting transport over hundreds to thousands of kilometers. However, field observations show that much of this fine ash aggregates into clusters or pellets with faster settling velocities than individual particles. Models of ash transport and deposition require an understanding of aggregation processes, which depend on factors like moisture content and local particle collision rates. In this study, we develop a Plume Model for Aggregate Prediction, a one-dimensional (1D) volcanic plume model that predicts the plume rise height, concentration of water phases, and size distribution of resulting ash aggregates from a set of eruption source parameters. The plume model uses a control volume approach to solve mass, momentum, and energy equations along the direction of the plume axis. The aggregation equation is solved using a fixed pivot technique and incorporates a sticking efficiency model developed from analog laboratory experiments of particle aggregation within a novel turbulence tower. When applied to the 2009 eruption of Redoubt Volcano, Alaska, the 1D model predicts that the majority of the plume is over-saturated with water, leading to a high rate of aggregation. Although the mean grain size of the computed Redoubt aggregates is larger than the measured deposits, with a peak at 1 mm rather than 500 μm, the present results provide a quantitative estimate for the magnitude of aggregation in an eruption

Expert-Augmented Machine Learning

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications

Extending scientific computing system with structural quantum programming capabilities

We present a basic high-level structures used for developing quantum programming languages. The presented structures are commonly used in many existing quantum programming languages and we use quantum pseudo-code based on QCL quantum programming language to describe them. We also present the implementation of introduced structures in GNU Octave language for scientific computing. Procedures used in the implementation are available as a package quantum-octave, providing a library of functions, which facilitates the simulation of quantum computing. This package allows also to incorporate high-level programming concepts into the simulation in GNU Octave and Matlab. As such it connects features unique for high-level quantum programming languages, with the full palette of efficient computational routines commonly available in modern scientific computing systems. To present the major features of the described package we provide the implementation of selected quantum algorithms. We also show how quantum errors can be taken into account during the simulation of quantum algorithms using quantum-octave package. This is possible thanks to the ability to operate on density matrices

Dialectic tensions in the financial markets: a longitudinal study of pre- and post-crisis regulatory technology

This article presents the findings from a longitudinal research study on regulatory technology in the UK financial services industry. The financial crisis with serious corporate and mutual fund scandals raised the profile of compliance as governmental bodies, institutional and private investors introduced a ‘tsunami’ of financial regulations. Adopting a multi-level analysis, this study examines how regulatory technology was used by financial firms to meet their compliance obligations, pre- and post-crisis. Empirical data collected over 12 years examine the deployment of an investment management system in eight financial firms. Interviews with public regulatory bodies, financial institutions and technology providers reveal a culture of compliance with increased transparency, surveillance and accountability. Findings show that dialectic tensions arise as the pursuit of transparency, surveillance and accountability in compliance mandates is simultaneously rationalized, facilitated and obscured by regulatory technology. Responding to these challenges, regulatory bodies continue to impose revised compliance mandates on financial firms to force them to adapt their financial technologies in an ever-changing multi-jurisdictional regulatory landscape

Chromosphere of K giant stars Geometrical extent and spatial structure detection

We aim to constrain the geometrical extent of the chromosphere of non-binary K giant stars and detect any spatial structures in the chromosphere. We performed observations with the CHARA interferometer and the VEGA beam combiner at optical wavelengths. We observed seven non-binary K giant stars. We measured the ratio of the radii of the photosphere to the chromosphere using the interferometric measurements in the Halpha and the Ca II infrared triplet line cores. For beta Ceti, spectro-interferometric observations are compared to an non-local thermal equilibrium (NLTE) semi-empirical model atmosphere including a chromosphere. The NLTE computations provide line intensities and contribution functions that indicate the relative locations where the line cores are formed and can constrain the size of the limb-darkened disk of the stars with chromospheres. We measured the angular diameter of seven K giant stars and deduced their fundamental parameters: effective temperatures, radii, luminosities, and masses. We determined the geometrical extent of the chromosphere for four giant stars. The chromosphere extents obtained range between 16% to 47% of the stellar radius. The NLTE computations confirm that the Ca II/849 nm line core is deeper in the chromosphere of ? Cet than either of the Ca II/854 nm and Ca II/866 nm line cores. We present a modified version of a semi-empirical model atmosphere derived by fitting the Ca II triplet line cores of this star. In four of our targets, we also detect the signature of a differential signal showing the presence of asymmetries in the chromospheres. Conclusions. It is the first time that geometrical extents and structure in the chromospheres of non-binary K giant stars are determined by interferometry. These observations provide strong constrains on stellar atmosphere models.Comment: 10 pages, 12 figure

Effects of Impurity Content on the Sintering Characteristics of Plasma-Sprayed Zirconia

Yttria-stabilized zirconia powders, containing different levels of SiO2 and Al2O3, have been plasma sprayed onto metallic substrates. The coatings were detached from their substrates and a dilatometer was used to monitor the dimensional changes they exhibited during prolonged heat treatments. It was found that specimens containing higher levels of silica and alumina exhibited higher rates of linear contraction, in both in-plane and through-thickness directions. The in-plane stiffness and the through-thickness thermal conductivity were also measured after different heat treatments and these were found to increase at a greater rate for specimens with higher impurity (silica and alumina) levels. Changes in the pore architecture during heat treatments were studied using Mercury Intrusion Porosimetry (MIP). Fine scale porosity (<_50 nm) was found to be sharply reduced even by relatively short heat treatments. This is correlated with improvements in inter-splat bonding and partial healing of intra-splat microcracks, which are responsible for the observed changes in stiffness and conductivity, as well as the dimensional changes

Why do some young cool stars show spot modulation while others do not?

We present far-red, intermediate resolution spectroscopy of 572 photometrically selected, low-mass stars (0.2<M/M_sun<0.7) in the young open cluster NGC 2516, using the FLAMES spectrograph at the Very Large Telescope. Precise radial velocities confirm membership for 210 stars that have published rotation periods from spot-modulated light curves and for another 144 stars in which periodic modulation could not be found. The two sub-samples are compared and no significant differences are found between their positions in colour-magnitude diagrams, the distribution of their projected equatorial velocities or their levels of chromospheric activity. We rule out differing observational sensitivity as an explanation and conclude that otherwise similar objects, with equally high levels of chromospheric activity, do not exhibit spot-induced light curve modulation because their significant spot coverage is highly axisymmetric. We propose that the spot coverage consists of large numbers of small, dark spots with diameters of about 2 degrees. This explains why about half of cluster members do not exhibit rotationally modulated light curves and why the light curve amplitudes of those that do have mean values of only 0.01-0.02 mag.Comment: Accepted for publication in MNRAS, 11 pages. Electronic tables available from the author

Ethics and Nanopharmacy: Value Sensitive Design of New Drugs

Although applications are being developed and have reached the market, nanopharmacy to date is generally still conceived as an emerging technology. Its concept is ill-defined. Nanopharmacy can also be construed as a converging technology, which combines features of multiple technologies, ranging from nanotechnology to medicine and ICT. It is still debated whether its features give rise to new ethical issues or that issues associated with nanopharma are merely an extension of existing issues in the underlying fields. We argue here that, regardless of the alleged newness of the ethical issues involved, developments occasioned by technological advances affect the roles played by stakeholders in the field of nanopharmacy to such an extent that this calls for a different approach to responsible innovation in this field. Specific features associated with nanopharmacy itself and features introduced to the associated converging technologies- bring about a shift in the roles of stakeholders that call for a different approach to responsibility. We suggest that Value Sensitive Design is a suitable framework to involve stakeholders in addressing moral issues responsibly at an early stage of development of new nanopharmaceuticals

Rab3D is critical for secretory granule maturation in PC12 cells.

Neuropeptide- and hormone-containing secretory granules (SGs) are synthesized at the trans-Golgi network (TGN) as immature secretory granules (ISGs) and complete their maturation in the F-actin-rich cell cortex. This maturation process is characterized by acidification-dependent processing of cargo proteins, condensation of the SG matrix and removal of membrane and proteins not destined to mature secretory granules (MSGs). Here we addressed a potential role of Rab3 isoforms in these maturation steps by expressing their nucleotide-binding deficient mutants in PC12 cells. Our data show that the presence of Rab3D(N135I) decreases the restriction of maturing SGs to the F-actin-rich cell cortex, blocks the removal of the endoprotease furin from SGs and impedes the processing of the luminal SG protein secretogranin II. This strongly suggests that Rab3D is implicated in the subcellular localization and maturation of ISGs