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1.
Sci Rep ; 14(1): 9602, 2024 04 26.
Article in English | MEDLINE | ID: mdl-38671000

ABSTRACT

The fluctuation of human infections by the Puumala orthohantavirus (PUUV) in Germany has been linked to weather and phenology parameters that drive the population growth of its host species. We quantified the annual PUUV-outbreaks at the district level by binarizing the reported infections in the period 2006-2021. With these labels we trained a model based on a support vector machine classifier for predicting local outbreaks and incidence well in advance. The feature selection for the optimal model was performed by a heuristic method and identified five monthly weather variables from the previous two years plus the beech flowering intensity of the previous year. The predictive power of the optimal model was assessed by a leave-one-out cross-validation in 16 years that led to an 82.8% accuracy for the outbreak and a 0.457 coefficient of determination for the incidence. Prediction risk maps for the entire endemic area in Germany will be annually available on a freely-accessible permanent online platform of the German Environment Agency. The model correctly identified 2022 as a year with low outbreak risk, whereas its prediction for large-scale high outbreak risk in 2023 was not confirmed.


Subject(s)
Disease Outbreaks , Hemorrhagic Fever with Renal Syndrome , Puumala virus , Germany/epidemiology , Humans , Hemorrhagic Fever with Renal Syndrome/epidemiology , Hemorrhagic Fever with Renal Syndrome/virology , Hemorrhagic Fever with Renal Syndrome/transmission , Incidence , Support Vector Machine , Weather
2.
Animals (Basel) ; 14(6)2024 Mar 08.
Article in English | MEDLINE | ID: mdl-38539940

ABSTRACT

Activity indices are used to determine the presence and activity of small mammals, such as the hair index derived from the use of hair tubes. In contrast to trapping animals, hair tubes are non-invasive and less labor-intensive, and appear to be a suitable alternative in appropriate settings. We developed a method to calculate hair density semi-automatically. In addition, hair tube data were validated with field data using wildlife cameras for the small mammal community in grassland, wheat crops, and hedges to assess how well data from hair tubes match data from wildlife cameras. Adhesive tape with hair from hair tubes was processed and scanned. The resulting images were analyzed using a newly developed computer program that enables background and adhesive tape to be automatically distinguished from hair, providing a quantitative measure of hair density. Based on validation with wildlife cameras, hair tubes seem to be a suitable tool to estimate small mammal activity at the community level in several habitats. There was a moderate-to-strong positive correlation of the hair tube index with the sum of voles and Apodemus individuals (activity index) recorded in grasslands (Spearman's correlation coefficient 0.43), hedges (0.79), and wheat (0.44). The newly developed computer program allows the automatic calculation of hair density, making it easier to assess the activity of small mammals.

3.
Sci Rep ; 13(1): 3585, 2023 03 03.
Article in English | MEDLINE | ID: mdl-36869118

ABSTRACT

Human Puumala virus (PUUV) infections in Germany fluctuate multi-annually, following fluctuations of the bank vole population size. We applied a transformation to the annual incidence values and established a heuristic method to develop a straightforward robust model for the binary human infection risk at the district level. The classification model was powered by a machine-learning algorithm and achieved 85% sensitivity and 71% precision, despite using only three weather parameters from the previous years as inputs, namely the soil temperature in April of two years before and in September of the previous year, and the sunshine duration in September of two years before. Moreover, we introduced the PUUV Outbreak Index that quantifies the spatial synchrony of local PUUV-outbreaks, and applied it to the seven reported outbreaks in the period 2006-2021. Finally, we used the classification model to estimate the PUUV Outbreak Index, achieving 20% maximum uncertainty.


Subject(s)
Puumala virus , Humans , Animals , Algorithms , Arvicolinae , Disease Outbreaks , Machine Learning
4.
J Opt Soc Am A Opt Image Sci Vis ; 36(8): 1418-1422, 2019 Aug 01.
Article in English | MEDLINE | ID: mdl-31503569

ABSTRACT

Image-sharpness metrics can be used to optimize optical systems and to control wavefront sensorless adaptive optics systems. We show that for an aberrated system, the numerical value of an image-sharpness metric can be improved by adding specific aberrations. The optimum amplitudes of the additional aberrations depend on the power spectral density of the spatial frequencies of the object.

5.
Opt Express ; 26(21): 27161-27178, 2018 Oct 15.
Article in English | MEDLINE | ID: mdl-30469790

ABSTRACT

With a view to the next generation of large space telescopes, we investigate guide-star-free, image-based aberration correction using a unimorph deformable mirror in a plane conjugate to the primary mirror. We designed and built a high-resolution imaging testbed to evaluate control algorithms. In this paper we use an algorithm based on the heuristic hill climbing technique and compare the correction in three different domains, namely the voltage domain, the domain of the Zernike modes, and the domain of the singular modes of the deformable mirror. Through our systematic experimental study, we found that successive control in two domains effectively counteracts uncompensated hysteresis of the deformable mirror.

6.
Opt Express ; 23(18): 24097, 2015 Sep 07.
Article in English | MEDLINE | ID: mdl-26368501

ABSTRACT

We present an erratum regarding a few small errors in our manuscript.

7.
Opt Express ; 22(25): 30683-96, 2014 Dec 15.
Article in English | MEDLINE | ID: mdl-25607016

ABSTRACT

We report interferometric measurements of the temperature coefficient of the refractive index (dn/dT) and the coefficient of thermal expansion (α) of a praseodymium-doped yttrium lithium fluoride (Pr:YLF) crystal and of a fused silica reference sample. Our phase-resolved interferometric method yields a large number of data points and thus allows a precise measurement and a good error estimation. Furthermore, both dn/dT and α are obtained simultaneously from a single measurement which reduces errors that can occur in separate measurements. Over the temperature range from 20 °C to 80 °C, the value of dn/dT of Pr:YLF decreases from −5.2 × 10(−6)/K to −6.2 × 10(−6)/K for the ordinary refractive index and from −7.6 × 10(−6)/K to −8.6 × 10(−6)/K for the extraordinary refractive index. The coefficient of thermal expansion for the a-axis of Pr:YLF increases from 16.4 × 10(−6)/K to 17.8 × 10(−6)/K over the same temperature range.

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