1,381 research outputs found
Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography
We study the feasibility of data based machine learning applied to ultrasound
tomography to estimate water-saturated porous material parameters. In this
work, the data to train the neural networks is simulated by solving wave
propagation in coupled poroviscoelastic-viscoelastic-acoustic media. As the
forward model, we consider a high-order discontinuous Galerkin method while
deep convolutional neural networks are used to solve the parameter estimation
problem. In the numerical experiment, we estimate the material porosity and
tortuosity while the remaining parameters which are of less interest are
successfully marginalized in the neural networks-based inversion. Computational
examples confirms the feasibility and accuracy of this approach
Demonstration of Optical Nonlinearity in InGaAsP/InP Passive Waveguides
We report on the study of the third-order nonlinear optical interactions in
InGaAsP/InP strip-loaded waveguides. The material
composition and waveguide structures were optimized for enhanced nonlinear
optical interactions. We performed self-phase modulation, four-wave mixing and
nonlinear absorption measurements at the pump wavelength 1568 nm in our
waveguides. The nonlinear phase shift of up to has been observed in
self-phase modulation experiments. The measured value of the two-photon
absorption coefficient was 15 cm/GW. The four-wave mixing conversion
range, representing the wavelength difference between maximally separated
signal and idler spectral components, was observed to be 45 nm. Our results
indicate that InGaAsP has a high potential as a material platform for nonlinear
photonic devices, provided that the operation wavelength range outside the
two-photon absorption window is selected
DeepTx: Deep Learning Beamforming with Channel Prediction
Machine learning algorithms have recently been considered for many tasks in
the field of wireless communications. Previously, we have proposed the use of a
deep fully convolutional neural network (CNN) for receiver processing and shown
it to provide considerable performance gains. In this study, we focus on
machine learning algorithms for the transmitter. In particular, we consider
beamforming and propose a CNN which, for a given uplink channel estimate as
input, outputs downlink channel information to be used for beamforming. The CNN
is trained in a supervised manner considering both uplink and downlink
transmissions with a loss function that is based on UE receiver performance.
The main task of the neural network is to predict the channel evolution between
uplink and downlink slots, but it can also learn to handle inefficiencies and
errors in the whole chain, including the actual beamforming phase. The provided
numerical experiments demonstrate the improved beamforming performance.Comment: 27 pages, this work has been submitted to the IEEE for possible
publication; v2: Fixed typo in author name, v3: a revisio
Assessing the discharge instructing in the emergency department : Patient perspective
Objective: The objective of the study is to assess how well the emergency department (ED) personnel succeed in instructing the patient at discharge. Methods: In November and December 2016 at Peijas Hospital ED, Finland, a structured questionnaire was conducted during a phone interview on patients the day after discharge. Results: A total of 132 patients interviewed. Ninety percent had received discharge instructions from the ED staff, most of them (75%) about medication. Almost half of the patients (45%) were satisfied with the communication at discharge, those not satisfied (47%) felt that the staff did not know enough of their background to give discharge instructions. Of the patients, 20% thought that they did not have the opportunity to ask questions during the guidance session, and 41% thought that the session was too short and restricted. Some patients (20%) felt that the instructions were ambiguous, but 63% (83/132) felt they were able to follow them well or very well. Conclusion: The pace of care in the ED is fast and duration of the stay is short. The patients must be able to take responsibility of their self-care. Failure to follow medical discharge instructions could lead to non-compliance. Attention should be paid to enhancing the quality of discharge instructing and the instructions provided by the ED personnel, as recurring visits and inquiry calls add to the ED workload.Peer reviewe
Methane dynamics in different boreal lake types
This study explores the variability in concentrations of dissolved CH<sub>4</sub> and annual flux estimates in the pelagic zone in a statistically defined sample of 207 lakes in Finland. The lakes were situated in the boreal zone, in an area where the mean annual air temperature ranges from &minus;2.8 to 5.9&deg;C. We examined how lake CH<sub>4</sub> dynamics related to regional lake types assessed according to the EU water framework directive. Ten lake types were defined on the basis of water chemistry, color, and size. Lakes were sampled for dissolved CH<sub>4</sub> concentrations four times per year, at four different depths at the deepest point of each lake. We found that CH<sub>4</sub> concentrations and fluxes to the atmosphere tended to be high in nutrient rich calcareous lakes, and that the shallow lakes had the greatest surface water concentrations. Methane concentration in the hypolimnion was related to oxygen and nutrient concentrations, and to lake depth or lake area. The surface water CH<sub>4</sub> concentration was related to the depth or area of lake. Methane concentration close to the bottom can be viewed as proxy of lake status in terms of frequency of anoxia and nutrient levels. The mean pelagic CH<sub>4</sub> release from randomly selected lakes was 49 mmol m<sup>&minus;2</sup> a<sup>&minus;1</sup>. The sum CH<sub>4</sub> flux (storage and diffusion) correlated with lake depth, area and nutrient content, and CH<sub>4</sub> release was greatest from the shallow nutrient rich and humic lakes. Our results support earlier lake studies regarding the regulating factors and also the magnitude of global emission estimate. These results propose that in boreal region small lakes have higher CH<sub>4</sub> fluxes per unit area than larger lakes, and that the small lakes have a disproportionate significance regarding to the CH<sub>4</sub> release
Erosion-oxidation of pressure vessel steel P265GH
The behaviour of pressure vessel steel P265GH was studied in a centrifugal high-temperature erosion apparatus under impacts by silica (SiO2) particles moving at velocities ranging from 20 to 60 m s-1 and contacting the surface at the angles of 30° and 90°. Besides particle impacts, the steel was simultaneously exposed to air and elevated temperatures of 350 and 450°C. For comparison, the tests were also performed in the absence of erodent particles. After the tests, the material behaviour was evaluated in terms of occurred weight changes and surface characteristics, the latter ones of which were investigated by using, for example, scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). In the analysis of the test results, special attention was paid to the composition and microstructure of the used silica particles and how these influence the elemental distribution on the exposed surfaces. The results show that the particle impacts introduce weight losses that follow a ductile angle-dependency, i.e., relatively greater weight losses at the shallow than at the steep impact angle. Although evident oxide scales developed on the surfaces at the test temperatures, they did not provide the steel with protection against particle impacts. Particle debris was detected embedded in the surfaces particularly under impacts at 90°, with softer particle constituents being preferentially deposited. These results are discussed in terms of the erosion-oxidation behaviour of the steel and the consequences of the heterogeneous erodent particle quality
Long-term clinical and economic outcomes in previously untreated paediatric patients with severe haemophilia A : A nationwide real-world study with 700 person-years
AimFor previously untreated patients (PUPs) with severe haemophilia A in Finland for the past 2 decades, the standard practice has been to start early primary prophylaxis. We evaluated the long-term clinical outcomes and costs of treatment with high-dose prophylaxis in PUPs from birth to adolescence, including immune tolerance induction (ITI). MethodsFrom the medical records of all PUPs born between June 1994 and May 2013 in Finland, we retrospectively extracted data on clinical outcomes and healthcare use. Using linear mixed models, we analysed longitudinal clinical outcome data. To analyse skewed cost data, including zero costs, we applied hurdle regression. ResultsAll 62 patients received early regular prophylaxis; totally, they have had treatment for nearly 700 patient-years. The median age of starting home treatment was 1.1years. The mean (SD) annual treatment costs (Europerkg) were 4391Euro (3852). For ages 1-3, ITI comprised over half of the costs; in other groups, prophylactic FVIII treatment dominated. With these high costs, however, clinical outcomes were desirable; median (IQR) ABR was low at 0.19 (0.07-0.46) and so was AJBR at 0.06 (0-0.24). Thirteen (21%) patients developed a clinically significant inhibitor, 10 (16%) with a high titre. All ITIs were successful. The mean costs for ITI were 383448Euro (259085). The expected ITI payback period was 1.81 (95% CI 0.62-12.12) years. ConclusionsEarly high-dose prophylaxis leads to excellent long-term clinical outcomes, and early childhood ITI therapy seems to turn cost-neutral generally already in 2years.Peer reviewe
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