LabVIEW Interface for PCI-SpaceWire Interface Card

This software provides a LabView interface to the NT drivers for the PCISpaceWire card, which is a peripheral component interface (PCI) bus interface that conforms to the IEEE-1355/ SpaceWire standard. As SpaceWire grows in popularity, the ability to use SpaceWire links within LabVIEW will be important to electronic ground support equipment vendors. In addition, there is a need for a high-level LabVIEW interface to the low-level device- driver software supplied with the card. The LabVIEW virtual instrument (VI) provides graphical interfaces to support all (1) SpaceWire link functions, including message handling and routing; (2) monitoring as a passive tap using specialized hardware; and (3) low-level access to satellite mission-control subsystem functions. The software is supplied in a zip file that contains LabVIEW VI files, which provide various functions of the PCI-SpaceWire card, as well as higher-link-level functions. The VIs are suitably named according to the matching function names in the driver manual. A number of test programs also are provided to exercise various functions

Reproducible Quantification of the Microstructure of Complex Quenched and Quenched and Tempered Steels Using Modern Methods of Machine Learning

Current conventional methods of evaluating microstructures are characterized by a high degree of subjectivity and a lack of reproducibility. Modern machine learning (ML) approaches have already shown great potential in overcoming these challenges. Once trained with representative data in combination with objective ground truth, the ML model is able to perform a task properly in a reproducible and automated manner. However, in highly complex use cases, it is often not possible to create a definite ground truth. This study addresses this problem using the underlying showcase of microstructures of highly complex quenched and quenched and tempered (Q/QT) steels. A patch-wise classification approach combined with a sliding window technique provides a solution for segmenting entire microphotographs where pixel-wise segmentation is not applicable since it is hardly feasible to create reproducible training masks. Using correlative microscopy, consisting of light optical microscope (LOM) and scanning electron microscope (SEM) micrographs, as well as corresponding data from electron backscatter diffraction (EBSD), a training dataset of reference states that covers a wide range of microstructures was acquired in order to train accurate and robust ML models in order to classify LOM or SEM images. Despite the enormous complexity associated with the steels treated here, classification accuracies of 88.8% in the case of LOM images and 93.7% for high-resolution SEM images were achieved. These high accuracies are close to super-human performance, especially in consideration of the reproducibility of the automated ML approaches compared to conventional methods based on subjective evaluations through experts

Reproducibility of straylight measurement by C-Quant for assessment of retinal straylight using the compensation comparison method

Background: Straylight gives the appearance of a veil of light thrown over a person's retinal image when there is a strong light source present. We examined the reproducibility of the measurements by C-Quant, and assessed its correlation to characteristics of the eye and subjects' age. Participants and Methods: Five repeated straylight measurements were taken using the dominant eye of 45 healthy subjects (age 21-59) with a BCVA of 20/20: 14 emmetropic, 16 myopic, eight hyperopic and seven with astigmatism. We assessed the extent of reproducibility of straylight measures using the intraclass correlation coefficient. Results: The mean straylight value of all measurements was 1.01 (SD 0.23, median 0.97, interquartile range 0.85-1.1). Per 10years of age, straylight increased in average by 0.10 (95%CI 0.04 to 0.16, p < 0.01]. We found no independent association of refraction (range −5.25 dpt to +2 dpt) on straylight values (0.001; 95%CI −0.022 to 0.024, p = 0.92). Compared to emmetropic subjects, myopia reduced straylight (−.011; −0.024 to 0.02, p = 0.11), whereas higher straylight values (0.09; −0.01 to 0.20, p = 0.09) were observed in subjects with blue irises as compared to dark-colored irises when correcting for age. The intraclass correlation coefficient (ICC) of repeated measurements was 0.83 (95%CI 0.76 to 0.90). Conclusions: Our study showed that straylight measurements with the C-Quant had a high reproducibility, i.e. a lack of large intra-observer variability, making it appropriate to be applied in long-term follow-up studies assessing the long-term effect of surgical procedures on the quality of visio

Die Situational Action Theory (SAT)

Manuskriptversion weicht in der Seitenzählung vom Original a

Comparison of Scanning LiDAR with Other Remote Sensing Measurements and Transport Model Predictions for a Saharan Dust Case

The evolution and the properties of a Saharan dust plume were studied near the city of Karlsruhe in southwest Germany (8.4298°E, 49.0953°N) from 7 to 9 April 2018, combining a scanning LiDAR (90°, 30°), a vertically pointing LiDAR (90°), a sun photometer, and the transport model ICON-ART. Based on this Saharan dust case, we discuss the advantages of a scanning aerosol LiDAR and validate a method to determine LiDAR ratios independently. The LiDAR measurements at 355 nm showed that the dust particles had backscatter coefficients of 0.86 ± 0.14 Mm$^{-1}$ sr$^{-1}$, extinction coefficients of 40 ± 0.8 Mm$^{-1}$, a LiDAR ratio of 46 ± 5 sr, and a linear particle depolarisation ratio of 0.27 ± 0.023. These values are in good agreement with those obtained in previous studies of Saharan dust plumes in Western Europe. Compared to the remote sensing measurements, the transport model predicted the plume arrival time, its layer height, and its structure quite well. The comparison of dust plume backscatter values from the ICON-ART model and observations for two days showed a correlation with a slope of 0.9 ± 0.1 at 355 nm. This work will be useful for future studies to characterise aerosol particles employing scanning LiDARs

Pancreatic metastasis of Merkel cell carcinoma and concomitant insulinoma: Case report and literature review

BACKGROUND: Merkel cell carcinomas are rare neoplasm of neuroendocrine origin, usually observed in elderly people in areas with abundant sunlight, and predominantly located on the head and neck, extremities, and trunk. In many patients, a local recurrence after resection of the primary tumour and even distant metastases can be found. CASE PRESENTATION: We report an unusual occurrence of pancreatic metastases from a previously diagnosed Merkel cell carcinoma with the discovery of a concomitant insulinoma. An 82-year old lady suffered from recurrent attacks of hypoglycemia and presented with an abdominal mass, 2 years prior she had an excision done on her eyebrow that was reported as Merkel cell carcinoma. An extended distal pancreatectomy and splenectomy along with resection of the left flexure of the colon for her abdominal mass was carried out. Final histopathology of the mass was a poorly differentiated endocrine carcinoma in the pancreatic tail, in the peripancreatic tissue and in the surrounding soft tissue consistent with metastatic Merkel cell carcinoma in addition to an insulinoma of the pancreatic body. CONCLUSION: This is the first documented case of a metastatic Merkel cell carcinoma and a concomitant insulinoma, suggesting either a mere coincidence or an unknown neuroendocrine tumor syndrome

Review of three-dimensional human-computer interaction with focus on the leap motion controller

Modern hardware and software development has led to an evolution of user interfaces from command-line to natural user interfaces for virtual immersive environments. Gestures imitating real-world interaction tasks increasingly replace classical two-dimensional interfaces based on Windows/Icons/Menus/Pointers (WIMP) or touch metaphors. Thus, the purpose of this paper is to survey the state-of-the-art Human-Computer Interaction (HCI) techniques with a focus on the special field of three-dimensional interaction. This includes an overview of currently available interaction devices, their applications of usage and underlying methods for gesture design and recognition. Focus is on interfaces based on the Leap Motion Controller (LMC) and corresponding methods of gesture design and recognition. Further, a review of evaluation methods for the proposed natural user interfaces is given

Shear wave elastography-based liver fibrosis assessment in patients with chronic hepatitis E displays elevated liver stiffness regardless of previous antiviral therapy

Background: Hepatitis E virus (HEV) infection especially in immunocompromised individuals can lead to chronic hepatitis. Aggressive courses of chronic hepatitis E leading to liver cirrhosis in a short period of time have been described, but evidence on the degree of liver involvement in chronic hepatitis E is rare. Vie therefore aimed to quantify liver fibrosis in patients with chronic active hepatitis E compared to patients with sustained virological response after ribavirin (RBV) treatment using 2D-shear wave elastography (2D-SWE) to measure liver stiffness. Methods: Patients with chronic hepatitis E underwent 2D-SWE, B-mode and Doppler ultrasound and laboratory testing in order to assess severity of liver involvement. Results: In this cross-sectional study, we included 14 patients of whom 8 had ongoing chronic hepatitis E and 6 patients had been successfully treated for chronic hepatitis E. The most frequent cause for immunosuppression was prior kidney transplantation (n = 12), one patient was a multivisceral transplant recipient, one had been treated for lymphoma. Five patients cleared HEV after RBV therapy, one patient reached viral clearance after reduction of his immunosuppressive medication. Using 2D-SWE measurement, 71.4% displayed increased stiffness indicative of liver fibrosis: 57.1% classified as significant fibrosis and 14.3% as severe fibrosis. Liver stiffness did not differ between patients with active chronic hepatitis E and in patients who had cleared HEN (1.59 and 1.54 m/S respectively). Compared with a control group of kidney transplant recipients without hepatitis E (1.44 m/S), the patients with a history of hepatitis E displayed a significantly higher liver stiffness (P=0.04). Conclusions: In our cohort of chronic hepatitis E patients, elevated liver stiffness indicating liver fibrosis was common and significantly higher than in controls. This is consistent with prior sparse reports of the presence of liver fibrosis or cirrhosis in chronic hepatitis E and emphasizes the need for HEV testing, therapy and research on new therapeutic options. As elevated liver stiffness was also present in patients after HEV treatment, continuous liver surveillance including elastography and ultrasound should be considered

Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopy

The high-temperature austenite phase is the initial state of practically all technologically relevant hot forming and heat treatment operations in steel processing. The phenomena occurring in austenite, such as recrystallization or grain growth, can have a decisive influence on the subsequent properties of the material. After the hot forming or heat treatment process, however, the austenite transforms into other microstructural constituents and information on the prior austenite morphology are no longer directly accessible. There are established methods available for reconstructing former austenite grain boundaries via metallographic etching or electron backscatter diffraction (EBSD) which both exhibit shortcomings. While etching is often difficult to reproduce and strongly depend on the investigated steel’s alloying concept, EBSD acquisition and reconstruction is rather time-consuming. But in fact, though, light optical micrographs of steels contrasted with conventional Nital etchant also contain information about the former austenite grains. However, relevant features are not directly apparent or accessible with conventional segmentation approaches. This work presents a deep learning (DL) segmentation of prior austenite grains (PAG) from Nital etched light optical micrographs. The basis for successful segmentation is a correlative characterization from EBSD, light and scanning electron microscopy to specify the ground truth required for supervised learning. The DL model shows good and robust segmentation results. While the intersection over union of 70% does not fully reflect the model performance due to the inherent uncertainty in PAG estimation, a mean error of 6.1% in mean grain size derived from the segmentation clearly shows the high quality of the result

Validation of AVHRR Land Surface Temperature with MODIS and In Situ LST—A TIMELINE Thematic Processor

Land Surface Temperature (LST) is an important parameter for tracing the impact of changing climatic conditions on our environment. Describing the interface between long- and shortwave radiation fluxes, as well as between turbulent heat fluxes and the ground heat flux, LST plays a crucial role in the global heat balance. Satellite-derived LST is an indispensable tool for monitoring these changes consistently over large areas and for long time periods. Data from the AVHRR (Advanced Very High-Resolution Radiometer) sensors have been available since the early 1980s. In the TIMELINE project, LST is derived for the entire operating period of AVHRR sensors over Europe at a 1 km spatial resolution. In this study, we present the validation results for the TIMELINE AVHRR daytime LST. The validation approach consists of an assessment of the temporal consistency of the AVHRR LST time series, an inter-comparison between AVHRR LST and in situ LST, and a comparison of the AVHRR LST product with concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) LST. The results indicate the successful derivation of stable LST time series from multi-decadal AVHRR data. The validation results were investigated regarding different LST, TCWV and VA, as well as land cover classes. The comparisons between the TIMELINE LST product and the reference datasets show seasonal and land cover-related patterns. The LST level was found to be the most determinative factor of the error. On average, an absolute deviation of the AVHRR LST by 1.83 K from in situ LST, as well as a difference of 2.34 K from the MODIS product, was observed