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Mobility is one of the most fundamental aspects of a foraging society. Since prehistoric mobility is often difficult to identify in the archaeological record, our understanding is largely based on comparison with ethnographic communities. In recent years the application of 87Sr/86Sr isotope analysis has, however, greatly broadened our knowledge of mobility in the past. Despite this, few studies ha

Strontium isotope ratios in human teeth from the three Swedish prehistoric Stone Age hunter-fisher-gathering societies Norje Sunnansund (Maglemose), Skateholm (Ertebølle) and Västerbjers (Pitted Ware Culture) were analysed with laser ablation to produce data on both individual movement patterns and societal mobility trends. The analyses of teeth from both Skateholm and Västerbjers displayed homoge

The carbon cycle of the terrestrial biosphere plays a vital role in controlling the global carbon balance and, consequently, climate change. Reliably modeled CO2 fluxes between the terrestrial biosphere and the atmosphere are necessary in projections of policy strategies aiming at constraining carbon emissions and of future climate change. In this study, SMOS (Soil Moisture and Ocean Salinity) L3

Many pathogenic bacteria utilise sialic acids as an energy source or use them as an external coating to evade immune detection. As such, bacteria that colonise sialylated environments deploy specific transporters to mediate import of scavenged sialic acids. Here, we report a substrate-bound 1.95 Å resolution structure and subsequent characterisation of SiaT, a sialic acid transporter from Proteus

This paper presents the light-scattering properties of atmospheric aerosol particles measured over the past decade at 28 ACTRIS observatories, which are located mainly in Europe. The data include particle light scattering (σsp) and hemispheric backscattering (σbsp) coefficients, scattering Ångström exponent (SAE), backscatter fraction (BF) and asymmetry parameter (g). An increasing gradient of σsp

Deep learning has the potential to drastically increase the accuracy and efficiency of prostate cancer diagnosis, which would be of uttermost use. Today the diagnosis is determined manually from H&E stained specimens using a light microscope. In this paper several different approaches based on convolutional neural networks for prostate cancer classification are presented and compared, using th

Two crystallized [FeFe] hydrogenase model complexes, 1 = (μ-pdt)[Fe(CO)2(PMe3)]2 (pdt = SC1H 2C2H2C3H2S), and their bridging-hydride (Hy) derivative, [1Hy]+ = [(μ-H)(μ-pdt)[Fe(CO)2 (PMe 3)]2]+ (BF4-), were studied by Fe K-edge X-ray absorption and emission spectroscopy, supported by density functional theory. Structural changes in [1Hy]+ compared to 1 involved small bond elongations (<0.03 Å) and