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"Thomas Koehler"
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Cloud-to-Ground Lightning Flash Density and Thunderstorm Day Distributions over the Contiguous United States Derived from NLDN Measurements: 1993–2018
This study employs cloud-to-ground (CG) lightning flash data from the U.S. National Lightning Detection Network (NLDN) to examine temporal and spatial distributions of lightning flash and thunderstorm day (TD) occurrences over the contiguous United States from 1993 to 2018. TD distributions are estimated from NLDN CG flashes using 4 thunder audibility approximations: 5 and 10 nautical mile (n mi; 1 n mi = 1.852 km) audibility ranges, and minima of 1 and 2 flashes within the audibility range. The 26-yr period examined is longer than previous studies using NLDN data, and the TD results can be compared directly to climatologies derived from surface weather observations dating back to the late 1890s. Results based on the abundant NLDN data avoid limitations introduced by the coarse horizontal resolution of surface observations inherent in pre-NLDN TD climatologies. Annual mean flash density and annual and monthly mean TD distributions are derived from almost 568 million NLDN CG flashes. A mean annual maximum of more than 16 flashes km−2 is found near Tampa, Florida. The mean annual TD maximum of 113 days (from at least 2 flashes within 10 n mi) occurs in southern Florida. Regions exceeding 70 TDs are found from eastern Texas eastward into Florida, and over the southern Rocky Mountains. Large positive deviations from the mean number of TDs extend from Texas northwestward into Colorado during 2003–07, followed by large negative deviations over the same region during 2008–12. Both deviation patterns are similar to expected summertime precipitation anomaly patterns over the United States during El Niño and La Niña years, respectively.
Journal Article
This book is not about dragons
\"Meet a mouse narrator who stubbornly insists that this book contains absolutely no dragons--not even a claw nor a flame nor any large, pointy scales. Readers will know better--and enjoy being in on the joke--as a flock of dragons chase the mouse to the very end of the book within the book\"-- Provided by publisher.
Book
Dark-field computed tomography reaches the human scale
X-ray computed tomography (CT) is one of the most commonly used three-dimensional medical imaging modalities today. It has been refined over several decades, with the most recent innovations including dual-energy and spectral photon-counting technologies. Nevertheless, it has been discovered that wave-optical contrast mechanisms—beyond the presently used X-ray attenuation—offer the potential of complementary information, particularly on otherwise unresolved tissue microstructure. One such approach is dark-field imaging, which has recently been introduced and already demonstrated significantly improved radiological benefit in small-animal models, especially for lung diseases. Until now, however, dark-field CT could not yet be translated to the human scale and has been restricted to benchtop and small-animal systems, with scan durations of several minutes or more. This is mainly because the adaption and upscaling to the mechanical complexity, speed, and size of a human CT scanner so far remained an unsolved challenge. Here, we now report the successful integration of a Talbot–Lau interferometer into a clinical CT gantry and present dark-field CT results of a human-sized anthropomorphic body phantom, reconstructed from a single rotation scan performed in 1 s. Moreover, we present our key hardware and software solutions to the previously unsolved road-blocks, which so far have kept dark-field CT from being translated from the optical bench into a rapidly rotating CT gantry, with all its associated challenges like vibrations, continuous rotation, and large field of view. This development enables clinical dark-field CT studies with human patients in the near future.
Journal Article
X-ray dark-field imaging of the human lung—A feasibility study on a deceased body
Disorders of the lungs such as chronic obstructive pulmonary disease (COPD) are a major cause of chronic morbidity and mortality and the third leading cause of death in the world. The absence of sensitive diagnostic tests for early disease stages of COPD results in under-diagnosis of this treatable disease in an estimated 60-85% of the patients. In recent years a grating-based approach to X-ray dark-field contrast imaging has shown to be very sensitive for the detection and quantification of pulmonary emphysema in small animal models. However, translation of this technique to imaging systems suitable for humans remains challenging and has not yet been reported. In this manuscript, we present the first X-ray dark-field images of in-situ human lungs in a deceased body, demonstrating the feasibility of X-ray dark-field chest radiography on a human scale. Results were correlated with findings of computed tomography imaging and autopsy. The performance of the experimental radiography setup allows acquisition of multi-contrast chest X-ray images within clinical boundary conditions, including radiation dose. Upcoming clinical studies will have to demonstrate that this technology has the potential to improve early diagnosis of COPD and pulmonary diseases in general.
Journal Article
In-vivo X-ray Dark-Field Chest Radiography of a Pig
X-ray chest radiography is an inexpensive and broadly available tool for initial assessment of the lung in clinical routine, but typically lacks diagnostic sensitivity for detection of pulmonary diseases in their early stages. Recent X-ray dark-field (XDF) imaging studies on mice have shown significant improvements in imaging-based lung diagnostics. Especially in the case of early diagnosis of chronic obstructive pulmonary disease (COPD), XDF imaging clearly outperforms conventional radiography. However, a translation of this technique towards the investigation of larger mammals and finally humans has not yet been achieved. In this letter, we present the first
in
-
vivo
XDF full-field chest radiographs (32 × 35 cm
2
) of a living pig, acquired with clinically compatible parameters (40 s scan time, approx. 80 µSv dose). For imaging, we developed a novel high-energy XDF system that overcomes the limitations of currently established setups. Our XDF radiographs yield sufficiently high image quality to enable radiographic evaluation of the lungs. We consider this a milestone in the bench-to-bedside translation of XDF imaging and expect XDF imaging to become an invaluable tool in clinical practice, both as a general chest X-ray modality and as a dedicated tool for high-risk patients affected by smoking, industrial work and indoor cooking.
Journal Article
Investigating Problem-Based Worksheets (PBWs) to Improve Understanding in Logic Gates Topic: Stacking and Racking Analyses in Rasch Model
Background/purpose. This study investigated the effectiveness of Problem-Based Worksheets (PBWs) in improving conceptual understanding of logic gates. PBWs were designed with key characteristics that integrate authentic problem-solving, active student engagement, and conceptual scaffolding to support critical thinking processes. A total of 32 vocational high school (VHS) students in Indonesia were involved in the PBWs class. Materials/methods. This study employed a quantitative quasi-experimental one-group pretest-posttest design to examine the effects of PBWs on students’ conceptual understanding. The intervention was conducted for 90 minutes, and 90 minutes for pre- and post-tests. Data were analyzed using stacking and racking within the Rasch model to measure changes in students’ understanding and item characteristics. Results. The results significantly improved students’ conceptual understanding of logic gates after the PBWs intervention. Due to non-normal data distribution and small sample size (n = 32), Mann–Whitney U and Wilcoxon tests were used, both confirming statistically significant score increases (p < 0.05). Rasch analysis further supported this improvement, with a logit difference of -7.14 between pre- and post-tests. Racking analysis revealed that item difficulty shifted, particularly for items 3, 5, 6, and 8. Despite overall gains, anomalies such as guessing, cheating, and carelessness influenced some students' results, as detected through response patterns and scalogram analysis. Conclusion. This study concluded that PBWs effectively improved students’ conceptual understanding of logic gates in pneumatic. PBWs offered a more engaging and holistic learning experience. These findings highlight the need for consideration of student behaviour during testing to ensure accurate interpretation of educational outcomes.
Journal Article
Efficient spectral data reduction for accurate iodine quantification in multi-energy CT
This study proposes a spectral data reduction method for multi-channel computed tomography (CT) that optimizes material decomposition accuracy while minimizing data complexity. Spectral CT enables quantitative assessments by utilizing multiple spectral channels, yet the associated noise and computational demands can limit its clinical application. We introduce a weighting scheme that reduces acquired four spectral channels—derived from a dual-layer, rapid kVp-switching (kVp-S) CT setup—into two optimized input channels for material decomposition. This scheme minimizes noise in iodine and water decomposition tasks by optimizing weights based on the Cramer-Rao lower bound. We modeled various duty cycles and patient sizes and compared results to full four-channel and traditional kVp-S configurations. The two-input weighting schemes showed consistently low estimated noise performance within 0.27% difference to the ideal, four-input material decomposition results for all tested duty cycles in a standard adult-sized 300 mm water phantom. In the pediatric (150 mm) and large adult (400 mm) phantom cases, the two-input weighted schemes were within 1% difference of the ideal four-input noise estimator results on average across all tested duty cycles. This study shows that optimized two-channel weighting in spectral CT matches the accuracy of four-channel setups for material decomposition, reducing noise and computational demands.
Journal Article
Simulated low-dose dark-field radiography for detection of COVID-19 pneumonia
Dark-field radiography has been proven to be a promising tool for the assessment of various lung diseases.
To evaluate the potential of dose reduction in dark-field chest radiography for the detection of the Coronavirus SARS-CoV-2 (COVID-19) pneumonia.
Patients aged at least 18 years with a medically indicated chest computed tomography scan (CT scan) were screened for participation in a prospective study between October 2018 and December 2020. Patients were included if they had a CO-RADS (COVID-19 Reporting and Data System) score ≥ 4 (COVID-19 group) or if they had no pathologic lung changes (controls). A total of 89 participants with a median age of 60 years (interquartile range 48 to 68 yrs.) were included in this study. Dark-field and attenuation-based radiographs were simultaneously obtained by using a prototype system for dark-field radiography. By modifying the image reconstruction algorithm, low-dose radiographs were simulated based on real participant images. The simulated radiographs corresponded to 50%, 25%, and 13% of the full dose (41.9 μSv, median value). Four experienced radiologists served as blinded readers assessing both image modalities, displayed side by side in random order. The presence of COVID-19-associated lung changes was rated on a scale from 1 to 6. The readers' diagnostic performance was evaluated by analyzing the area under the receiver operating characteristic curves (AUC) using Obuchowski's method. Also, the dark-field images were analyzed quantitatively by comparing the dark-field coefficients within and between the COVID-19 and the control group.
The readers' diagnostic performance in the image evaluation, as described by the AUC value (where a value of 1 corresponds to perfect diagnostic accuracy), did not differ significantly between the full dose images (AUC = 0.86) and the simulated images at 50% (AUC = 0.86) and 25% of the full dose(AUC = 0.84) (p>0.050), but was slightly lower at 13% dose (AUC = 0.82) (p = 0.038). For all four radiation dose levels, the median dark-field coefficients within groups were identical but different significantly by 15% between the controls and the COVID-19 pneumonia group (p<0.001).
Dark-field imaging can be used to diagnose the Coronavirus SARS-CoV-2 (COVID-19) pneumonia with a median dose of 10.5 μSv, which corresponds to 25% of the original dose used for dark-field chest imaging.
Journal Article