Reprinted Article “Factors Associated with Early Failure of Arteriovenous Fistulae for Haemodialysis Access”

AbstractThe radiocephalic arteriovenous fistula remains the method of choice for haemodialysis access. In order to assess their suitability for fistula formation, the radial arteries and cephalic veins were examined preoperatively by ultrasound colour flow scanner in conjunction with a pulse-generated run-off system. Intraoperative blood flow was measured after construction of the fistulae. Post-operative follow-up was performed at various intervals to monitor the development of the fistulae. Radial artery and cephalic vein diameter less than 1.6 mm was associated with early fistula failure. The intraoperative fistula blood flow did not correlate with the outcome of the operation probably due to vessel spasm from manipulation. However, blood flow velocities measured non-invasively 1 day after the operation were significantly lower in fistulae that failed early compared with those that were adequate for haemodialysis. Most of the increase in fistula diameter and blood flow occur within the first 2 weeks of surgery

Virial expansion coefficients in the harmonic approximation

The virial expansion method is applied within a harmonic approximation to an interacting N-body system of identical fermions. We compute the canonical partition functions for two and three particles to get the two lowest orders in the expansion. The energy spectrum is carefully interpolated to reproduce ground state properties at low temperature and the non-interacting large temperature limit of constant virial coefficients. This resembles the smearing of shell effects in finite systems with increasing temperature. Numerical results are discussed for the second and third virial coefficients as function of dimension, temperature, interaction, and the transition temperature between low and high energy limits.Comment: 11 pages, 7 figures, published versio

Rapidly changing subglacial hydrological pathways at a tidewater glacier revealed through simultaneous observations of water pressure, supraglacial lakes, meltwater plumes and surface velocities

This work was funded by the Conoco Phillips-Lundin Northern Area Program through the CRIOS project (Calving Rates and Impact On Sea level, http://www.researchinsvalbard.no/project/7037). Penelope How is supported by a NERC PhD studentship.Subglacial hydrological processes at tidewater glaciers remain poorly understood due to the difficulty in obtaining direct measurements and lack of empirical verification for modelling approaches. Here, we investigate the subglacial hydrology of Kronebreen, a fast-flowing tidewater glacier in Svalbard during the 2014 melt season. We combine observations of borehole water pressure, supraglacial lake drainage, surface velocities and plume activity with modelled run-off and water routing to develop a conceptual model that thoroughly encapsulates subglacial drainage at a tidewater glacier. Simultaneous measurements suggest that an early-season episode of subglacial flushing took place during our observation period, and a stable efficient drainage system effectively transported subglacial water through the northern region of the glacier tongue. Drainage pathways through the central and southern regions of the glacier tongue were disrupted throughout the following melt season. Periodic plume activity at the terminus appears to be a signal for modulated subglacial pulsing, i.e. an internally driven storage and release of subglacial meltwater that operates independently of marine influences. This storage is a key control on ice flow in the 2014 melt season. Evidence from this work and previous studies strongly suggests that long-term changes in ice flow at Kronebreen are controlled by the location of efficient/inefficient drainage and the position of regions where water is stored and released.Publisher PDFPeer reviewe

Modelling CDA mass spectra

We present the initial results from a simulation of ion behaviour within Cassini's cosmic dust analyser (CDA) instrument, using an in-house ion dynamics code. This work is to enable and enhance the detailed interpretation of dust impact ionisation mass spectra returned from the Saturnian system. Early work has already provided insights into the properties of the impact plasma in both low- and high-velocity impacts. We find that the isotropic emission of ions from the impact plasma successfully reproduces features seen in flight spectra and that the emitted ions have a higher range of energies (tens to hundreds of eV) than previously reported in some studies. Using these new ion characteristics, we have successfully modelled CDA flight mass spectra

The highly variable time evolution of star-forming cores identified with dendrograms

We investigate the time evolution of dense cores identified in molecular cloud simulations using dendrograms, which are a common tool to identify hierarchical structure in simulations and observations of star formation. We develop an algorithm to link dendrogram structures through time using the three-dimensional density field from magnetohydrodynamical simulations, thus creating histories for all dense cores in the domain. We find that the population-wide distributions of core properties are relatively invariant in time, and quantities like the core mass function match with observations. Despite this consistency, an individual core may undergo large (>40%), stochastic variations due to the redefinition of the dendrogram structure between timesteps. This variation occurs independent of environment and stellar content. We identify a population of short-lived (<200 kyr) overdensities masquerading as dense cores that may comprise ~20% of any time snapshot. Finally, we note the importance of considering the full history of cores when interpreting the origin of the initial mass function; we find that, especially for systems containing multiple stars, the core mass defined by a dendrogram leaf in a snapshot is typically less than the final system stellar mass. This work reinforces that there is no time-stable density contour that defines a star-forming core. The dendrogram itself can induce significant structure variation between timesteps due to small changes in the density field. Thus, one must use caution when comparing dendrograms of regions with different ages or environment properties because differences in dendrogram structure may not come solely from the physical evolution of dense cores.Comment: 20 pages, 17 figures. Submitted to MNRA

Simulation of a Machine Learning Based Controller for a Fixed-Wing UAV with Distributed Sensors

Recent research suggests that the information obtained from arrays of sensors distributed on the wing of a fixed-wing small unmanned aerial vehicle (UAV) can provide information not available to conventional sensor suites. These arrays of sensors are capable of sensing the flow around the aircraft and it has been indicated that they could be a potential tool to improve flight control and overall flight performance. However, more work needs to be carried out to fully exploit the potential of these sensors for flight control. This work presents a 3 degrees-of-freedom longitudinal flight dynamics and control simulation model of a small fixed-wing UAV. Experimental readings of an array of pressure and strain sensors distributed across the wing were integrated in the model. This study investigated the feasibility of using machine learning to control airspeed of the UAV using the readings from the sensing array, and looked into the sensor layout and its effect on the performance of the controller. It was found that an artificial neural network was able to learn to mimic a conventional airspeed controller using only distributed sensor signals, but showed better performance for controlling changes in airspeed for a constant altitude than holding airspeed during changes in altitude. The neural network could control airspeed using either pressure or strain sensor information, but having both improved robustness to increased levels of turbulence. Results showed that some strain sensors and many pressure sensors signals were not necessary to achieve good controller performance, but that the pressure sensors near the leading edge of the wing were required. Future work will focus on replacing other elements of the flight control system with machine learning elements and investigate the use of reinforcement learning in place of supervised learning.</p

(E)-[({[(3-Methyl­phen­yl)meth­yl]sulfan­yl}methane­thio­yl)amino](1-phenyl­pentyl­idene)amine

In the structure of the title compound, C20H24N2S2, the central CN2S2 atoms are planar (r.m.s. deviation = 0.0205 Å) but both benzene rings are twisted out of this plane forming dihedral angles of 23.03 (6) and 84.75 (4)° (tol­yl); the n-butyl group occupies a position normal to the plane [N—C—C—C torsion angle = −84.33 (16)°]. The conformation of the imine bond [1.2888 (18) Å] is E. The syn arrangement of the thione S and amino H atoms enables the formation of N—H⋯S hydrogen bonds between centrosymmetrically related mol­ecules. These lead to eight-membered {⋯HNC=S}2 synthons which are further stabilized by proximate C—H⋯S interactions. The resulting dimeric aggregates are connected into a supra­molecular chain along the c axis by C—H⋯π(tol­yl) inter­actions

Core Formation, Coherence and Collapse: A New Core Evolution Paradigm Revealed by Machine Learning

We study the formation, evolution and collapse of dense cores by tracking density structures in a magnetohydrodynamic (MHD) simulation. We identify cores using the dendrogram algorithm and utilize machine learning techniques, including principal component analysis (PCA) and the k-means clustering algorithm to analyze the full density and velocity dispersion profiles of these cores. We find that there exists an evolutionary sequence consisting of three distinct phases: i) the formation of turbulent density structures (Phase I), ii) the dissipation of turbulence and the formation of coherent cores (Phase II), and iii) the transition to protostellar cores through gravitational collapse (Phase III). In dynamically evolving molecular clouds, the existence of these three phases corresponds to the coexistence of three populations of cores with distinct physical properties. The prestellar and protostellar cores frequently analyzed in previous studies of observations and simulations belong to the last phase in this evolutionary picture. We derive typical lifetimes of 1.4$\pm$1.0$\times$10$^5$ yr, 3.3$\pm$1.4$\times$10$^5$ yr and 3.3$\pm$1.4$\times$10$^5$ yr, respectively for Phase I, II and III. We find that cores can form from both converging flows and filament fragmentation and that cores may form both inside and outside the filaments. We then compare our results to previous observations of coherent cores and provide suggestions for future observations to study cores belonging to the three phases.Comment: Submitted to Astrophysical Journal in June, 202

Millimetre-wave radar observations of glacier calving at Hansbreen (Svalbard) correlated with TLS, time-lapse camera images and seismic records

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