Tire-road noise: an experimental study of tire and road design parameters

It is widely known that road traffic noise has negative influences on human health. Hence, as tire-road noise is considered to be the most dominant cause of road traffic noise above 30-50 km/h, a lot of research is performed by the two involving industries: road authorities/manufacturers and tire manufacturers. Usually, the parameters influencing exterior tire-road noise are often examined separately, whereas it is the tire-road interaction which obviously causes the actual noise. An integral approach, i.e. assessing possible measures to reduce tire-road noise from both the road and the tire point of view, is needed to further reduce traffic noise. In a project Silent Safe Traffic, this tire-road interaction is studied in more detail without focusing on either tire or road but looking at the tire-road system. In this publication we present experimental results of tire and road design parameters influencing tire-road noise from a fixed reference tire-road configuration. The influence of tire tread pattern, compound and construction as well as the influence of road roughness, acoustic absorption and driving speed on the exterior tire-road noise, measured by a CPX-set up, is reported. Keywords: Tire, Road, Measuremen

The saturation scale and its x-dependence from Lambda polarization studies

The transverse polarization of forward Lambda hyperons produced in high-energy p-A collisions is expected to display an extremum at a transverse momentum around the saturation scale. This was first observed within the context of the McLerran-Venugopalan model which has an x-independent saturation scale. The extremum arises due to the k_t-odd nature of the polarization dependent fragmentation function, which probes approximately the derivative of the dipole scattering amplitude. The amplitude changes most strongly around the saturation scale, resulting in a peak in the polarization. We find that the observation also extends to the more realistic case in which the saturation scale Q_s is x dependent. Since a range of x and therefore Q_s values is probed at a given transverse momentum and rapidity, this result is a priori not expected. Moreover, the measurement of Lambda polarization over a range of x_F values actually provides a direct probe of the x dependence of the saturation scale. This novel feature is demonstrated for typical LHC kinematics and for several phenomenological models of the dipole scattering amplitude. We show that although the measurement will be challenging, it may be feasible at LHC. The situation at RHIC is not favorable, because the peak will likely be at too low transverse momentum of the Lambda to be a trustworthy measure of the saturation scale.Comment: 11 pages, 6 figure

Non-detriment finding for common buzzard (Buteo buteo)

Non-detriment finding for common buzzard The export from Norway to Sweden of one taxidermied common buzzard (Buteo buteo) for personal purposes will not be detrimental to the survival of the species. Thus concludes the Norwegian Scientific Committee for Food and Environment (VKM). The assignment was carried out on behalf of the Norwegian Environment Agency, which is the management authority for the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) in Norway. VKM is the scientific authority for CITES in Norway and prepares NDF (non-detriment finding) reports in accordance with the methodology published by the International Union for Conservation of Nature (IUCN) and CITES.Non-detriment finding for common buzzard (Buteo buteo)publishedVersio

Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps

Finding an interpretable and compact representation of complex neuroimaging data is extremely useful for understanding brain behavioral mapping and hence for explaining the biological underpinnings of mental disorders. However, hand-crafted representations, as well as linear transformations, may inadequately capture the considerable variability across individuals. Here, we implemented a data-driven approach using a three-dimensional autoencoder on two large-scale datasets. This approach provides a latent representation of high-dimensional task-fMRI data which can account for demographic characteristics whilst also being readily interpretable both in the latent space learned by the autoencoder and in the original voxel space. This was achieved by addressing a joint optimization problem that simultaneously reconstructs the data and predicts clinical or demographic variables. We then applied normative modeling to the latent variables to define summary statistics (‘latent indices’) and establish a multivariate mapping to non-imaging measures. Our model, trained with multi-task fMRI data from the Human Connectome Project (HCP) and UK biobank task-fMRI data, demonstrated high performance in age and sex predictions and successfully captured complex behavioral characteristics while preserving individual variability through a latent representation. Our model also performed competitively with respect to various baseline models including several variants of principal components analysis, independent components analysis and classical regions of interest, both in terms of reconstruction accuracy and strength of association with behavioral variables

Scientific assessment of risk to populations of pythons listed by CITES as a result of trade

This report provides a scientific risk assessment of the effects that international trade in selected species of pythons (Pythonidae spp.) and python products may have on populations of these species. The assessment is based on the criteria given under the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The risk assessment is limited to species in the genera Apodora, Aspidites, Liasis, Malayopython, Morelia, and Python imported/exported to/from Norway since 2010 (ToR §3). Risk assessments to determine species-specific detriment (cf. Res. Conf. 16.7 (Rev. CoP17) Non-detriment findings) were made for 17 species using a standardized approach. Significant data gaps affected the degree of uncertaintyassociated with the assessments. Data gaps are mostly related to populations, trends, and illegal trade. Population and trade data for many species was more than a decade old and might therefore not reflect the current situation for these species. Based on the species-specific detriment assessments VKM concludes no detriment for 12 species (Apodora papuana, Aspidites melanocephalus, Liasis mackloti, Malayopython reticulatus, Morelia bredli, Morelia spilota, Morelia viridis, Python anchietae, Python bivittatus, Python breitensteini, Python brongersmai, Python curtus). For one species, VKM concludes detriment (Morelia boeleni). For two species, a split conclusion is made based on the region of origin (Python regius and Python sebae). Furthermore, sufficient data was lacking for Malayopython timoriensis and VKM is therefore unable to make a detriment assessment. The final species, Python molurus, is CITES Appendix I listed and should not be traded for commercial purposes. The degree of uncertainty associated with each assessment varied based on data availability and this is indicated as a confidence level of the individual assessments (low to high)Scientific assessment of risk to populations of pythons listed by CITES as a result of tradepublishedVersio

MicroRNA Levels as Prognostic Markers for the Differentiation Potential of Human Mesenchymal Stromal Cell Donors

The ability of human mesenchymal stromal/stem cells (hMSCs) to differentiate into various mesenchymal cell lineages makes them a promising cell source for the use in tissue repair strategies. Because the differentiation potential of hMSCs differs between donors, it is necessary to establish biomarkers for the identification of donors with high differentiation potential. Here, we show that microRNA (miRNA) expression levels are effective for distinguishing donors with high differentiation potential from low differentiation potential. Twenty human MSC donors were initially tested for marker expression and differentiation potential. In particular, chondrogenic differentiation potential was evaluated on the basis of histological matrix formation, mRNA expression levels of chondrogenic marker genes, and quantitative glycosaminoglycan deposition. Three donors out of twenty were identified as donors with high chondrogenic potential, whereas nine showed moderate and eight low chondrogenic potential. Expression profiles of miRNAs involved in chondrogenesis and cartilage homeostasis were used for the distinction between high-performance hMSCs and low-performance hMSCs. Global mRNA expression profiles of the donors before the onset of chondrogenic differentiation revealed minor differences in gene expression between low and high chondrogenic performers. However, analysis of miRNA expression during a seven-day differentiation period identified miR-210 and miR-630 as positive regulators of chondrogenesis. In contrast, miR-181 and miR-34a, which are negative regulators of chondrogenesis, were upregulated during differentiation in low performing donors. In conclusion, profiling of hMSC donors for a specific panel of miRNAs may have prognostic value for selecting donors with high differentiation potential to improve hMSC-based strategies for tissue regeneration

CombiFlow:combinatorial AML-specific plasma membrane expression profiles allow longitudinal tracking of clones

Acute myeloid leukemia (AML) often presents as an oligoclonal disease whereby multiple genetically distinct subclones can coexist within patients. Differences in signaling and drug sensitivity of such subclones complicate treatment and warrant tools to identify them and track disease progression. We previously identified >50 AML-specific plasma membrane (PM) proteins, and 7 of these (CD82, CD97, FLT3, IL1RAP, TIM3, CD25, and CD123) were implemented in routine diagnostics in patients with AML (n = 256) and myelodysplastic syndrome (n = 33). We developed a pipeline termed CombiFlow in which expression data of multiple PM markers is merged, allowing a principal component–based analysis to identify distinctive marker expression profiles and to generate single-cell t-distributed stochastic neighbor embedding landscapes to longitudinally track clonal evolution. Positivity for one or more of the markers after 2 courses of intensive chemotherapy predicted a shorter relapse-free survival, supporting a role for these markers in measurable residual disease (MRD) detection. CombiFlow also allowed the tracking of clonal evolution in paired diagnosis and relapse samples. Extending the panel to 36 AML-specific markers further refined the CombiFlow pipeline. In conclusion, CombiFlow provides a valuable tool in the diagnosis, MRD detection, clonal tracking, and understanding of clonal heterogeneity in AML