57 research outputs found
Relaxation of dynamically disordered tetragonal platelets in the relaxor ferroelectric
The local dynamics of the lead-free relaxor
(NBT-3.6BT) have been investigated by a combination of quasielastic neutron
scattering (QENS) and ab initio molecular dynamics simulations. In a previous
paper, we were able to show that the tetragonal platelets in the microstructure
are crucial for understanding the dielectric properties of NBT-3.6BT [F. Pforr
et al., Phys. Rev. B 94, 014105 (2016)]. To investigate their dynamics, ab
initio molecular dynamics simulations were carried out using
with 001 cation order as a
simple model system for the tetragonal platelets in NBT-3.6BT. Similarly,
111-ordered was used as a
model for the rhombohedral matrix. The measured single crystal QENS spectra
could be reproduced by a linear combination of calculated spectra. We find that
the relaxational dynamics of NBT-3.6BT are concentrated in the tetragonal
platelets. Chaotic stages, during which the local tilt order changes
incessantly on the timescale of several picoseconds, cause the most significant
contribution to the quasielastic intensity. They can be regarded as an excited
state of tetragonal platelets, whose relaxation back into a quasistable state
might explain the frequency dependence of the dielectric properties of
NBT-3.6BT in the 100 GHz to THz range. This substantiates the assumption that
the relaxor properties of NBT-3.6BT originate from the tetragonal platelets.Comment: 27 pages, 9 figure
In vivo electrophysiological characterization of TASK-1 deficient mice
Background/Aims: TASK-1 is a potassium channel predominantly expressed in heart and brain. We have previously shown that anesthetized TASK-1(-/-) mice have prolonged QT intervals in surface electrocardiograms (ECGs). In addition, heart rate variability quantified by time and frequency domain parameters was significantly altered in TASK-1(-/-) mice with a sympathetic preponderance. Aims of the present study were the analysis of QT intervals by telemetric ECGs, to determine potential influences of anesthesia and beta-adrenergic stimulation on repolarization in surface ECGs, to investigate in vivo electrophysiological parameters by intracardiac electrical stimulation and to quantify heart rate turbulence after ischemia/reperfusion or ventricular pacing in TASK-1(+/+) and TASK-1(-/-) mice. Methods: Rate corrected QT intervals (QTc) were recorded in conscious mice by telemetry and in surface ECGs following administration of various anesthetics (tribromoethanol (Avertin (R)), pentobarbital and isoflurane). TASK-1(+/+) and TASK-1(-/-) mice were characterized by programmed electrical stimulation using an intracardiac octapolar catheter. The baroreceptor reflex was analyzed by heart rate turbulence (turbulence onset and slope) after ischemia/reperfusion and by stimulated premature ventricular contractions
Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait
Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system
Classification of HCV NS5B Polymerase Inhibitors Using Support Vector Machine
Using a support vector machine (SVM), three classification models were built to predict whether a compound is an active or weakly active inhibitor based on a dataset of 386 hepatitis C virus (HCV) NS5B polymerase NNIs (non-nucleoside analogue inhibitors) fitting into the pocket of the NNI III binding site. For each molecule, global descriptors, 2D and 3D property autocorrelation descriptors were calculated from the program ADRIANA.Code. Three models were developed with the combination of different types of descriptors. Model 2 based on 16 global and 2D autocorrelation descriptors gave the highest prediction accuracy of 88.24% and MCC (Matthews correlation coefficient) of 0.789 on test set. Model 1 based on 13 global descriptors showed the highest prediction accuracy of 86.25% and MCC of 0.732 on external test set (including 80 compounds). Some molecular properties such as molecular shape descriptors (InertiaZ, InertiaX and Span), number of rotatable bonds (NRotBond), water solubility (LogS), and hydrogen bonding related descriptors performed important roles in the interactions between the ligand and NS5B polymerase
Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging, ground-based stationary, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign
Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, Western Germany, which is a pollution hotspot in Europe comprising urban and large industrial emitters. The measurements are used to validate space-borne NO2 tropospheric vertical column density data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI). Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements which were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km x 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two zenith-sky and two MAX-DOAS instruments distributed over three target areas. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 vertical column densities and show high Pearson correlation coefficients of 0.87 and 0.89 and slopes of 0.93 ± 0.09 and 0.98 ± 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m x 30 m, the AirMAP tropospheric NO2 vertical column density (VCD) data creates a link between the ground-based and the TROPOMI measurements with a resolution of 3.5 km x 5.5 km and is therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The measurements on the seven flight days show strong NO2 variability, which is dependent on the different target areas, the weekday, and the meteorological conditions. The AirMAP campaign dataset is compared to the TROPOMI NO2 operational off-line (OFFL) V01.03.02 data product, the reprocessed NO2 data, using the V02.03.01 of the official L2 processor, provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The TROPOMI data products and the AirMAP data are highly correlated with correlation coefficients between 0.72 and 0.87, and slopes of 0.38 ± 0.02 to 1.02 ± 0.07. On average, TROPOMI tropospheric NO2 VCDs are lower than the AirMAP NO2 results. The slope increased from 0.38 ± 0.02 for the operational OFFL V01.03.02 product to 0.83 ± 0.06 after the improvements in the retrieval of the PAL V02.03.01 product were implemented. Different auxiliary data, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity and the cloud treatment, are investigated using scientific TROPOMI tropospheric NO2 VCD data products to evaluate their impact on the operational TROPOMI NO2 VCD data product. The comparison of the AirMAP campaign dataset to the scientific data products shows that the choice of surface reflectivity data base has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights has a major impact on the tropospheric NO2 VCD retrieval and increases the slope from 0.88 ± 0.06 to 1.00 ± 0.07. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation dataset has been and can be further significantly improved.</p
Stronger Neural Modulation by Visual Motion Intensity in Autism Spectrum Disorders
Theories of autism spectrum disorders (ASD) have focused on altered perceptual integration
of sensory features as a possible core deficit. Yet, there is little understanding of the
neuronal processing of elementary sensory features in ASD. For typically developed individuals,
we previously established a direct link between frequency-specific neural activity
and the intensity of a specific sensory feature: Gamma-band activity in the visual cortex
increased approximately linearly with the strength of visual motion. Using magnetoencephalography
(MEG), we investigated whether in individuals with ASD neural activity reflect the
coherence, and thus intensity, of visual motion in a similar fashion. Thirteen adult participants
with ASD and 14 control participants performed a motion direction discrimination task
with increasing levels of motion coherence. A polynomial regression analysis revealed that
gamma-band power increased significantly stronger with motion coherence in ASD compared
to controls, suggesting excessive visual activation with increasing stimulus intensity
originating from motion-responsive visual areas V3, V6 and hMT/V5. Enhanced neural
responses with increasing stimulus intensity suggest an enhanced response gain in ASD.
Response gain is controlled by excitatory-inhibitory interactions, which also drive high-frequency
oscillations in the gamma-band. Thus, our data suggest that a disturbed excitatoryinhibitory
balance underlies enhanced neural responses to coherent motion in ASD
SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues
Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to
genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility
and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component.
Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci
(eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene),
including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform
genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer
SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the
diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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