Laminography is a widely used NDT technique for large flat object which cannot be investigated by traditional computed tomography. However, due to the limited scanning angle of laminography, the ...reconstructed image has more artifact interference, which seriously affects the reconstructed image quality. Reducing artifacts of the laminography image and enhancing the images have become important research effort. In this paper, we present dual-energy materials characterization methods based on photon counting detectors to reduce artifacts and enhance image for laminography. The photon counting detector used in this study allows the setting of two independent energy thresholds in order to acquire dual-energy images for laminography from a single scan. The dual energy imaging methods of basis material decomposition (BMD) and weighted logarithmic subtraction (WLS) were studied in the paper with respect to laminography image enhancement. A fast decomposition algorithm on laminographic projection domain with approximating the inverse dual-energy equations to calculate the thickness of basic materials was used in the BMD dual-energy imaging methods. The experimental results show that the BMD method can characterize materials and enhance features of the basic material within the laminographic dataset. In the WLS method, a linear operation was applied on dual-energy images reconstruction directly, which can eliminate the attenuation of one specific material in the resultant image by setting an appropriate weighting factor. In our experiments. WLS method was used successfully to eliminate the strong artifacts generated by the special material and enhance the images. Dual-energy materials characterization methods based on photon counting detectors show potential applications in laminography.
Laser-plasma accelerators (LPAs) now routinely produce electron beams with GeV energies over acceleration lengths on the order of a few centimeters. This capability and the demonstration of ...multistage coupling make LPAs promising for numerous applications. However, beam quality preservation in multistage accelerators remains an obstacle because of the need to separate the laser pulse from the electron beam. Plasma mirrors can be used to redirect the laser pulse, but their substrate thickness threatens to substantially degrade the electron beam emittance. Ultrathin (∼20nm) liquid crystal (LC) plasma mirrors are an excellent candidate to address this challenge. This work investigates the robustness of thin LC plasma mirrors in the presence of capillary discharge plasma and an auxiliary heater laser. We find they can be operated∼10cmfrom the capillary exit when a heater laser is used. We then performed a normalized emittance measurement enabled using a 20 nm LC plasma mirror to protect electron beam optics after the LPA. The emittance contribution from scattering through the plasma mirror is calculated to be of order 100 nm, much less than the measured emittance of4.0μm. Finally, we develop a model to calculate plasma mirror performance based on the laser polarization and intensity, and plasma mirror thickness.
This Letter reports on the measurement of the energy loss and the projectile charge states of argon ions at an energy of 4 MeV/u penetrating a fully ionized carbon plasma. The plasma of n(e)≈10(20) ...cm(-3) and T(e)≈180 eV is created by two laser beams at λ(Las)=532 nm incident from opposite sides on a thin carbon foil. The resulting plasma is spatially homogenous and allows us to record precise experimental data. The data show an increase of a factor of 2 in the stopping power which is in very good agreement with a specifically developed Monte Carlo code, that allows the calculation of the heavy ion beam's charge state distribution and its energy loss in the plasma.
We describe the design and implementation of a novel automated outbreak detection system in Germany that monitors the routinely collected surveillance data for communicable diseases. Detecting ...unusually high case counts as early as possible is crucial as an accumulation may indicate an ongoing outbreak. The detection in our system is based on state-of-the-art statistical procedures conducting the necessary data mining task. In addition, we have developed effective methods to improve the presentation of the results of such algorithms to epidemiologists and other system users. The objective was to effectively integrate automatic outbreak detection into the epidemiological workflow of a public health institution. Since 2013, the system has been in routine use at the German Robert Koch Institute.
The generation of intense ion beams from high-intensity laser-generated plasmas has been the focus of research for the last decade. In the LIGHT collaboration the expertise of heavy ion accelerator ...scientists and laser and plasma physicists has been combined to investigate the prospect of merging these ion beams with conventional accelerator technology and exploring the possibilities of future applications. We report about the goals and first results of the LIGHT collaboration to generate, handle and transport laser driven ion beams. This effort constitutes an important step in research for next generation accelerator technologies.
The volume of Earth system observations has grown massively in recent decades. However, multivariate or multisource analyses at the interface of atmosphere and land are still hampered by the sparsity ...of ground measurements and the abundance of missing values in satellite observations. This can hinder robust multivariate analysis and introduce biases in trends. Nevertheless, gap‐filling is often done univariately, which can obscure physical dependencies. Here, we apply the new multivariate gap‐filling framework CLIMate data gapFILL (CLIMFILL). CLIMFILL combines state‐of‐the‐art spatial interpolation with an iterative approach accounting for dependencies across multiple incomplete variables. CLIMFILL is applied to a set of remotely sensed and in situ observations over land that are central to observing land–atmosphere interactions and extreme events. The resulting gridded monthly time series covers 1995–2020 globally with gap‐free maps of nine variables: surface layer soil moisture from European Space Agency (ESA)‐Climate Change Initiative (CCI), land surface temperature and diurnal temperature range from Moderate‐resolution Imaging Spectroradiometer, precipitation from GPM, terrestrial water storage from GRACE, ESA‐CCI burned area, and snow cover fraction as well as 2‐m temperature and precipitation from CRU. Time series of anomalies are reconstructed better compared to state‐of‐the‐art interpolation. The gap‐filled data set shows high correlations with ERA5‐Land, and soil moisture estimates compare favorably to in situ observations from the International Soil Moisture Network. Soil moisture drying trends in ESA‐CCI only agree with the reanalysis product ERA5‐Land trends after gap‐filling. We furthermore showcase that key features of droughts and heatwaves in major fire seasons are well represented. The data set can serve as a step toward the fusion of multivariate multisource observations.
Plain Language Summary
The Earth has been increasingly observed by satellites and ground stations in the last decades. However, those observations have many missing values. Multivariate analysis of events or climate interactions or the observation of trends can be biased by missing values. Those missing values are often not gap‐filled, or gap‐filled for each variable separately, which can obscure physical dependencies between the variables. Here, we apply CLIMate data gapFILL, a new multivariate gap‐filling framework, to fill gaps in a range of freely available observational data sets. It can consider information dependencies across multiple incomplete variables to fill the gaps. It is applied to nine observational variables that describe land–climate interactions and dynamics of extreme events. The result is gap‐free maps from 1995 to 2020 globally for surface layer soil moisture, land surface temperature, diurnal temperature range, precipitation (from satellite), terrestrial water storage, burned area, snow cover fraction, 2‐m temperature, and precipitation (from ground). The gap‐filled data set produces better estimates than univariate interpolation and has a high correlation with ERA5‐Land and soil moisture observations from the International Soil Moisture Network data set. Soil moisture drying trends in European Space Agency‐Climate Change Initiative only agree with ERA5‐Land after gap‐filling. Major fire seasons are well represented. The data set can is a step toward fusion of multi‐source multivariate observational data sets.
Key Points
Large fractions of missing values in Earth observations can bias multisource multivariate analysis of land–climate interactions and extremes
We apply a multivariate gap‐filling framework to nine variables relevant to observing land–climate interactions centering on soil moisture
Regional aggregated averages and soil moisture trends agree well with independent observational data sets and reanalysis after gap‐filling
The main emphasis of the Laser Ion Generation, Handling and Transport (LIGHT) beamline at GSI Helmholtzzentrum für Schwerionenforschung GmbH are phase-space manipulations of laser-generated ion ...beams. In recent years, the LIGHT collaboration has successfully generated and focused intense proton bunches with an energy of 8 MeV and a temporal duration shorter than 1 ns (FWHM). An interesting area of application that exploits the short ion bunch properties of LIGHT is the study of ion-stopping power in plasmas, a key process in inertial confinement fusion for understanding energy deposition in dense plasmas. The most challenging regime is found when the projectile velocity closely approaches the thermal plasma electron velocity ($v_{i}\approx v_{e,\text {th}}$), for which existing theories show high discrepancies. Since conclusive experimental data are scarce in this regime, we plan to conduct experiments on laser-generated plasma probed with ions generated with LIGHT at a higher temporal resolution than previously achievable. The high temporal resolution is important because the parameters of laser-generated plasmas are changing on the nanosecond time scale. To meet this goal, our recent studies have dealt with ions of lower kinetic energies. In 2021, laser accelerated carbon ions were transported with two solenoids and focused temporally with LIGHT's radio frequency cavity. A bunch length of 1.2 ns (FWHM) at an energy of 0.6 MeV u$^{-1}$ was achieved. In 2022, protons with an energy of 0.6 MeV were transported and temporally compressed to a bunch length of 0.8 ns. The proton beam was used to measure the energy loss in a cold foil. Both the ion and proton beams will also be employed for energy loss measurements in a plasma target.
Laboratory tests are frequently ordered by general practitioners (GPs), but little is known about time trends and between-GP variation of their use. In this retrospective longitudinal study, we ...analyzed over six million consultations by Swiss GPs during the decade 2009–2018. For 15 commonly used test types, we defined specific laboratory testing rates (sLTR) as the percentage of consultations involving corresponding laboratory testing requests. Patient age- and sex-adjusted time trends of sLTR were modeled with mixed-effect logistic regression accounting for clustering of patients within GPs. We quantified between-GP variation by means of intraclass correlation coefficients (ICC). Nine out of the 15 laboratory test types considered showed significant temporal increases, most eminently vitamin D (ten-year odds ratio (OR) 1.88, 95% confidence interval (CI) 1.71–2.06) and glycated hemoglobin (ten-year OR 1.87, 95% CI 1.82–1.92). Test types both subject to substantial increase and high between-GP variation of sLTR were vitamin D (ICC 0.075), glycated hemoglobin (ICC 0.101), C-reactive protein (ICC 0.202), and vitamin B12 (ICC 0.166). Increasing testing frequencies and large between-GP variation of specific test type use pointed at inconsistencies of medical practice and potential overuse.
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