ORCID Profile
0000-0003-1558-0565
Current Organisation
Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
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Publisher: BMJ
Date: 03-07-2014
Publisher: American Geophysical Union (AGU)
Date: 11-2019
DOI: 10.1029/2019WR026072
Publisher: American Geophysical Union (AGU)
Date: 04-2021
DOI: 10.1029/2020WR028700
Abstract: Bedload transport is a key process in fluvial morphodynamics, but difficult to measure. The advent of seismic monitoring techniques has provided an alternative to in‐stream monitoring, which is often costly and cannot be utilized during large floods. Seismic monitoring is a method requiring several steps to convert seismic data into bedload flux data. State‐of‐the‐art conversion approaches exploit physical models predicting the seismic signal generated by bedload transport. However, due to a lack of well‐constrained validation data, the accuracy of the resulting inversions is unknown. We use field experiments to constrain a seismic bedload model and compare the results to high‐quality independent bedload measurements. Constraining the Green's function (i.e., seismic ground properties) with an active seismic survey resulted in an average absolute difference between modeled and empirically measured seismic bedload power of 11 dB in the relevant frequency band. Using generically estimated Green's function parameters resulted in a difference of 20 dB, thus highlighting the importance of using actual field parameters. Water turbulence and grain hiding are unlikely to be the cause of differences between field observations and our analysis. Rather, they may be either due to the inverted model being particularly sensitive to the coarse tail of the grain‐size distribution, which is least well constrained from field observations, or due to the seismic model underestimating effects of the largest grains.
Publisher: American Diabetes Association
Date: 14-03-2013
DOI: 10.2337/DC12-1020
Abstract: Age at menopause is an important determinant of future health outcomes, but little is known about its relationship with type 2 diabetes. We examined the associations of menopausal age and reproductive life span (menopausal age minus menarcheal age) with diabetes risk. Data were obtained from the InterAct study, a prospective case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition. A total of 3,691 postmenopausal type 2 diabetic case subjects and 4,408 subcohort members were included in the analysis, with a median follow-up of 11 years. Prentice weighted Cox proportional hazards models were adjusted for age, known risk factors for diabetes, and reproductive factors, and effect modification by BMI, waist circumference, and smoking was studied. Mean (SD) age of the subcohort was 59.2 (5.8) years. After multivariable adjustment, hazard ratios (HRs) of type 2 diabetes were 1.32 (95% CI 1.04–1.69), 1.09 (0.90–1.31), 0.97 (0.86–1.10), and 0.85 (0.70–1.03) for women with menopause at ages & , 40–44, 45–49, and ≥55 years, respectively, relative to those with menopause at age 50–54 years. The HR per SD younger age at menopause was 1.08 (1.02–1.14). Similarly, a shorter reproductive life span was associated with a higher diabetes risk (HR per SD lower reproductive life span 1.06 [1.01–1.12]). No effect modification by BMI, waist circumference, or smoking was observed (P interaction all & 0.05). Early menopause is associated with a greater risk of type 2 diabetes.
Publisher: American Association for Cancer Research (AACR)
Date: 06-2019
DOI: 10.1158/1055-9965.EPI-18-1153
Abstract: To analyze the potential effect of social inequality on pancreatic cancer risk in Western Europe, by reassessing the association within the European Prospective Investigation into Cancer and Nutrition (EPIC) Study, including a larger number of cases and an extended follow-up. Data on highest education attained were gathered for 459,170 participants (70% women) from 10 European countries. A relative index of inequality (RII) based on adult education was calculated for comparability across countries and generations. Cox regression models were applied to estimate relative inequality in pancreatic cancer risk, stratifying by age, gender, and center, and adjusting for known pancreatic cancer risk factors. A total of 1,223 incident pancreatic cancer cases were included after a mean follow-up of 13.9 (±4.0) years. An inverse social trend was found in models adjusted for age, sex, and center for both sexes [HR of RII, 1.27 95% confidence interval (CI), 1.02–1.59], which was also significant among women (HR, 1.42 95% CI, 1.05–1.92). Further adjusting by smoking intensity, alcohol consumption, body mass index, prevalent diabetes, and physical activity led to an attenuation of the RII risk and loss of statistical significance. The present reanalysis does not sustain the existence of an independent social inequality influence on pancreatic cancer risk in Western European women and men, using an index based on adult education, the most relevant social indicator linked to in idual lifestyles, in a context of very low pancreatic cancer survival from (quasi) universal public health systems. The results do not support an association between education and risk of pancreatic cancer.
Publisher: Copernicus GmbH
Date: 25-09-2023
Publisher: Elsevier BV
Date: 11-2013
DOI: 10.1016/J.CGH.2013.05.029
Abstract: Few modifiable risk factors have been implicated in the etiology of pancreatic cancer. There is little evidence for the effects of caffeinated coffee, decaffeinated coffee, or tea intake on risk of pancreatic cancer. We investigated the association of total coffee, caffeinated coffee, decaffeinated coffee, and tea consumption with risk of pancreatic cancer. This study was conducted within the European Prospective Investigation into Nutrition and Cancer cohort, comprising male and female participants from 10 European countries. Between 1992 and 2000, there were 477,312 participants without cancer who completed a dietary questionnaire and were followed up to determine pancreatic cancer incidence. Coffee and tea intake was calibrated with a 24-hour dietary recall. Adjusted hazard ratios (HRs) were computed using multivariable Cox regression. During a mean follow-up period of 11.6 y, 865 first incidences of pancreatic cancers were reported. When ided into fourths, neither total intake of coffee (HR, 1.03 95% confidence interval [CI], 0.83-1.27 high vs low intake), decaffeinated coffee (HR, 1.12 95% CI, 0.76-1.63 high vs low intake), nor tea were associated with risk of pancreatic cancer (HR, 1.22, 95% CI, 0.95-1.56 high vs low intake). Moderately low intake of caffeinated coffee was associated with an increased risk of pancreatic cancer (HR, 1.33 95% CI, 1.02-1.74), compared with low intake. However, no graded dose response was observed, and the association attenuated after restriction to histologically confirmed pancreatic cancers. Based on an analysis of data from the European Prospective Investigation into Nutrition and Cancer cohort, total coffee, decaffeinated coffee, and tea consumption are not related to the risk of pancreatic cancer.
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-8127
Abstract: Rapid mass movements are a major threat in populated landscapes, as they can cause significant loss of life and damage civil infrastructure. Previous work has shown that using environmental seismology methods to monitor such mass movements and establish monitoring systems offers advantages over existing approaches. The first important step in developing an early warning system for rapid mass movements based on seismic signals is automatically detecting events of interest. Though the approach, such as short-term average to long-term average ratio (STA/LTA) and machine learning model, was introduced to detect events (e.g., debris flow and rockfall), it is still challenging to calibrate input parameters and migrate existing methods to other catchments. Detection of debris flows, for instance, is similar to anomaly detection if we consider the seismic stations recording background signals as an overwhelming majority condition.& Benford's law describes the probability distribution of the first non-zero digits in numerical datasets, which provides a functional, computationally cheap approach to anomaly detection, such as fraud detection in financial data or earthquake detection in seismic signals. In this study, seismic signals generated by rapid mass movements were collected to check the agreement of the distribution of the first digit with Benford's law. Subsequently, we develop a computationally efficient and non-site-specific model to detect events based on Benford's law using debris flows from the Illgraben, a Swiss torrent, as an ex le. Our results show that seismic signals generated by high-energy mass movements, such as debris flows, landslides, and lahars, follow Benford's law, while those generated by rockfall and background signals do not. Furthermore, our detector performance in picking debris-flow events is comparable to a published random forest and seismic network-based approach. Our method can be applied at other sites to detect debris-flow events without additional calibration and offers the potential for real-time warnings.
Publisher: Wiley
Date: 30-11-2021
Publisher: Wiley
Date: 25-11-2021
Publisher: American Geophysical Union (AGU)
Date: 09-2022
DOI: 10.1029/2021JF006537
Abstract: Large, rarely mobile boulders are observed globally in mountainous bedrock channels. Recent studies suggest that high concentrations of boulders could be associated with channel morphological adjustment. However, a process‐based understanding of large boulder effects on channel morphology is limited, and data are scarce and ambiguous. Here, we develop a theory of steady‐state channel width and slope as a function of boulder concentration. Our theory assumes that channel morphology adjusts to maintain two fundamental mass balances: (a) grade, in which the channel transports the same sediment flux downstream despite boulders acting as roughness elements and (b) bedrock erosion, by which the channel erodes at the background tectonic uplift rate. Model predictions are normalized by a reference, boulder‐free channel width and slope, accounting for variations due to sediment supply, discharge, and lithology. Models are tested against a new data set from the Liwu River, Taiwan, showing steepening and widening with increasing boulder concentration. Whereas one of the explored mechanisms successfully explains the observed steepening trend, none of the models accuratly account for the observed width variability. We propose that this contrast arises from different adjustment timescales: while sediment bed slope adjusts within a few floods, width adjustment takes a much longer time. Overall, we find that boulders represent a significant perturbation to fluvial landscapes. Channels tend to respond by forming a new morphology that differs from boulder‐free channels. The general approach presented here can be further expanded to explore the role of other hydrodynamic effects associated with large, rarely mobile boulders.
Publisher: Public Library of Science (PLoS)
Date: 20-05-2014
Publisher: Authorea, Inc.
Date: 20-07-2023
DOI: 10.22541/ESSOAR.168987133.36073109/V1
Abstract: Seismic instruments placed outside of spatially extensive hazard zones can be used to rapidly sense a range of mass movements. However, it remains challenging to automatically detect specific events of interest. Benford’s law, which states that first non-zero-digit of given datasets follow a specific probability distribution, can provide a computationally cheap approach to identifying anomalies in large datasets and potentially be used for event detection. Here, we select raw seismic signals to derive the first-digit distribution. The seismic signals generated by debris flows, landslides, lahars, and glacier-lake-outburst floods follow Benford’s law, while those generated by ambient noise, rockfalls, and bedload transports do not. Focusing on debris flows, our Benford’s-law-based detector is comparable to an existing random forest method for the Illgraben, Switzerland, but requires only single station data and three non-dimensional parameters. We suggest this computationally cheap, novel technique offers an alternative for event recognition and potentially for real-time warnings.
Publisher: Wiley
Date: 02-12-2013
DOI: 10.1002/ESP.3499
Location: Germany
Location: United States of America
Location: Switzerland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Jens Turowski.