600 Technik, Technologie
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- 2020 (31) (entfernen)
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- Institut für Biochemie und Biologie (6)
- Institut für Physik und Astronomie (5)
- Hasso-Plattner-Institut für Digital Engineering GmbH (4)
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- Strukturbereich Kognitionswissenschaften (4)
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Objective We propose a data-driven method to detect temporal patterns of disease progression in high-dimensional claims data based on gradient boosting with stability selection. Materials and methods We identified patients with chronic obstructive pulmonary disease in a German health insurance claims database with 6.5 million individuals and divided them into a group of patients with the highest disease severity and a group of control patients with lower severity. We then used gradient boosting with stability selection to determine variables correlating with a chronic obstructive pulmonary disease diagnosis of highest severity and subsequently model the temporal progression of the disease using the selected variables. Results We identified a network of 20 diagnoses (e.g. respiratory failure), medications (e.g. anticholinergic drugs) and procedures associated with a subsequent chronic obstructive pulmonary disease diagnosis of highest severity. Furthermore, the network successfully captured temporal patterns, such as disease progressions from lower to higher severity grades. Discussion The temporal trajectories identified by our data-driven approach are compatible with existing knowledge about chronic obstructive pulmonary disease showing that the method can reliably select relevant variables in a high-dimensional context. Conclusion We provide a generalizable approach for the automatic detection of disease trajectories in claims data. This could help to diagnose diseases early, identify unknown risk factors and optimize treatment plans.
URSA-PQ
(2020)
We present a highly flexible and portable instrument to perform pump-probe spectroscopy with an optical and an X-ray pulse in the gas phase. The so-called URSA-PQ (German for ‘Ultraschnelle Röntgenspektroskopie zur Abfrage der Photoenergiekonversion an Quantensystemen’, Engl. ‘ultrafast X-ray spectroscopy for probing photoenergy conversion in quantum systems’) instrument is equipped with a magnetic bottle electron spectrometer (MBES) and tools to characterize the spatial and temporal overlap of optical and X-ray laser pulses. Its adherence to the CAMP instrument dimensions allows for a wide range of sample sources as well as other spectrometers to be included in the setup. We present the main design and technical features of the instrument. The MBES performance was evaluated using Kr M4,5NN Auger lines using backfilled Kr gas, with an energy resolution ΔE/E ≅ 1/40 in the integrating operative mode. The time resolution of the setup at FLASH 2 FL 24 has been characterized with the help of an experiment on 2-thiouracil that is inserted via the instruments’ capillary oven. We find a time resolution of 190 fs using the molecular 2p photoline shift and attribute this to different origins in the UV-pump—the X-ray probe setup.
URSA-PQ
(2020)
We present a highly flexible and portable instrument to perform pump-probe spectroscopy with an optical and an X-ray pulse in the gas phase. The so-called URSA-PQ (German for ‘Ultraschnelle Röntgenspektroskopie zur Abfrage der Photoenergiekonversion an Quantensystemen’, Engl. ‘ultrafast X-ray spectroscopy for probing photoenergy conversion in quantum systems’) instrument is equipped with a magnetic bottle electron spectrometer (MBES) and tools to characterize the spatial and temporal overlap of optical and X-ray laser pulses. Its adherence to the CAMP instrument dimensions allows for a wide range of sample sources as well as other spectrometers to be included in the setup. We present the main design and technical features of the instrument. The MBES performance was evaluated using Kr M4,5NN Auger lines using backfilled Kr gas, with an energy resolution ΔE/E ≅ 1/40 in the integrating operative mode. The time resolution of the setup at FLASH 2 FL 24 has been characterized with the help of an experiment on 2-thiouracil that is inserted via the instruments’ capillary oven. We find a time resolution of 190 fs using the molecular 2p photoline shift and attribute this to different origins in the UV-pump—the X-ray probe setup.
The effect of two types of scanning strategies on the grain structure and build-up of Residual Stress (RS) has been investigated in an as-built IN718 alloy produced by Laser Powder Bed Fusion (LPBF). The RS state has been investigated by X-ray diffraction techniques. The microstructural characterization was performed principally by Electron Backscatter Diffraction (EBSD), where the application of a post-measurement refinement technique enables small misorientations (< 2 degrees) to be resolved. Kernel average misorientation (KAM) distributions indicate that preferably oriented columnar grains contain higher levels of misorientation, when compared to elongated grains with lower texture. The KAM distributions combined with X-ray diffraction stress maps infer that the increased misorientation is induced via plastic deformation driven by the thermal stresses, acting to self-relieve stress. The possibility of obtaining lower RS states in the build direction as a consequence of the influence of the microstructure should be considered when envisaging scanning strategies aimed at the mitigation of RS.
The Human Takes It All
(2020)
Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots. Little is known about human perception of synthesized voices.
Aim: To investigate which synthesized voice parameters predict the speaker's eeriness and voice likability; to determine if individual listener characteristics (e.g., personality, attitude toward robots, age) influence synthesized voice evaluations; and to explore which paralinguistic features subjectively distinguish humans from robots/artificial agents.
Methods: 95 adults (62 females) listened to randomly presented audio-clips of three categories: synthesized (Watson, IBM), humanoid (robot Sophia, Hanson Robotics), and human voices (five clips/category). Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained.
Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Females rated synthesized voices more positively on most dimensions. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. Contrary to the expectations of an uncanny valley, when the ratings of human-likeness for both the voice and the speaker characteristics were higher, they seemed less eerie to the participants. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. This latter point was only applicable to one of the synthesized voices. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.
Discussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker.
The Human Takes It All
(2020)
Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots. Little is known about human perception of synthesized voices.
Aim: To investigate which synthesized voice parameters predict the speaker's eeriness and voice likability; to determine if individual listener characteristics (e.g., personality, attitude toward robots, age) influence synthesized voice evaluations; and to explore which paralinguistic features subjectively distinguish humans from robots/artificial agents.
Methods: 95 adults (62 females) listened to randomly presented audio-clips of three categories: synthesized (Watson, IBM), humanoid (robot Sophia, Hanson Robotics), and human voices (five clips/category). Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained.
Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Females rated synthesized voices more positively on most dimensions. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. Contrary to the expectations of an uncanny valley, when the ratings of human-likeness for both the voice and the speaker characteristics were higher, they seemed less eerie to the participants. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. This latter point was only applicable to one of the synthesized voices. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.
Discussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker.
Thermal stress response is an essential physiological trait that determines occurrence and temporal succession in nature, including response to climate change. We compared temperature-related demography in closely related heat-tolerant and heat-sensitive Brachionus rotifer species. We found significant differences in heat response, with the heat-sensitive species adopting a strategy of long survival and low population growth, while the heat-tolerant followed the opposite strategy. In both species, we examined the genetic basis of physiological variation by comparing gene expression across increasing temperatures. Comparative transcriptomic analyses identified shared and opposing responses to heat. Interestingly, expression of heat shock proteins (hsps) was strikingly different in the two species and mirrored differences in population growth rates, showing that hsp genes are likely a key component of a species’ adaptation to different temperatures. Temperature induction caused opposing patterns of expression in further functional categories including energy, carbohydrate and lipid metabolism, and in genes related to ribosomal proteins. In the heat-sensitive species, elevated temperatures caused up-regulation of genes related to meiosis induction and post-translational histone modifications. This work demonstrates the sweeping reorganizations of biological functions that accompany temperature adaptation in these two species and reveals potential molecular mechanisms that might be activated for adaptation to global warming.
Thermal stress response is an essential physiological trait that determines occurrence and temporal succession in nature, including response to climate change. We compared temperature-related demography in closely related heat-tolerant and heat-sensitive Brachionus rotifer species. We found significant differences in heat response, with the heat-sensitive species adopting a strategy of long survival and low population growth, while the heat-tolerant followed the opposite strategy. In both species, we examined the genetic basis of physiological variation by comparing gene expression across increasing temperatures. Comparative transcriptomic analyses identified shared and opposing responses to heat. Interestingly, expression of heat shock proteins (hsps) was strikingly different in the two species and mirrored differences in population growth rates, showing that hsp genes are likely a key component of a species’ adaptation to different temperatures. Temperature induction caused opposing patterns of expression in further functional categories including energy, carbohydrate and lipid metabolism, and in genes related to ribosomal proteins. In the heat-sensitive species, elevated temperatures caused up-regulation of genes related to meiosis induction and post-translational histone modifications. This work demonstrates the sweeping reorganizations of biological functions that accompany temperature adaptation in these two species and reveals potential molecular mechanisms that might be activated for adaptation to global warming.
The mixture of ammonium nitrate (AN) prills and fuel oil (FO), usually referred to as ANFO, is extensively used in the mining industry as a bulk explosive. One of the major performance predictors of ANFO mixtures is the fuel oil retention, which is itself governed by the complex pore structure of the AN prills. In this study, we present how X-ray computed tomography (XCT), and the associated advanced data processing workflow, can be used to fully characterise the structure and morphology of AN prills. We show that structural parameters such as volume fraction of the different phases and morphological parameters such as specific surface area and shape factor can be reliably extracted from the XCT data, and that there is a good agreement with the measured oil retention values. Importantly, oil retention measurements (qualifying the efficiency of ANFO as explosives) correlate well with the specific surface area determined by XCT. XCT can therefore be employed non-destructively; it can accurately evaluate and characterise porosity in ammonium nitrate prills, and even predict their efficiency.
Adverse environmental conditions are detrimental to plant growth and development. Acclimation to abiotic stress conditions involves activation of signaling pathways which often results in changes in gene expression via networks of transcription factors (TFs). Mediator is a highly conserved co-regulator complex and an essential component of the transcriptional machinery in eukaryotes. Some Mediator subunits have been implicated in stress-responsive signaling pathways; however, much remains unknown regarding the role of plant Mediator in abiotic stress responses. Here, we use RNA-seq to analyze the transcriptional response of Arabidopsis thaliana to heat, cold and salt stress conditions. We identify a set of common abiotic stress regulons and describe the sequential and combinatorial nature of TFs involved in their transcriptional regulation. Furthermore, we identify stress-specific roles for the Mediator subunits MED9, MED16, MED18 and CDK8, and putative TFs connecting them to different stress signaling pathways. Our data also indicate different modes of action for subunits or modules of Mediator at the same gene loci, including a co-repressor function for MED16 prior to stress. These results illuminate a poorly understood but important player in the transcriptional response of plants to abiotic stress and identify target genes and mechanisms as a prelude to further biochemical characterization.