Notes

Trophic change in microbeads to jellyfish and also the significance of ageing microbeads for microplastic tests.
5 to 5.0 mm (blind analysis). Stent morphometric and biomechanical indices were calculated in the computational and experimental studies. In the computational studies the 12-peak MEGATRON exhibited significantly greater expansion, better scaffolding, smaller vessel prolapse, and greater radial strength (expressed as normalized hoop force) than the 9-peak MEGATRON, 10-peak MEGATRON, or SYNERGY (p  less then  0.05). Larger stent expansion diameters had significantly better radial strength and worse scaffolding than smaller stent diameters (p  less then  0.001). Computational stenting showed comparable scaffolding and radial strength with experimental stenting. 12-peak MEGATRON exhibited better mechanical performance than the 9-peak MEGATRON, 10-peak MEGATRON, or SYNERGY. Patient-specific computational LM stenting simulations can accurately reproduce experimental stent testing, providing an attractive framework for cost- and time-effective stent research and development.Curiosity pervades all aspects of human behaviour and decision-making. Recent research indicates that the value of information is determined by its propensity to reduce uncertainty, and the hedonic value of the outcomes it predicts. Previous findings also indicate a preference for options that are freely chosen, compared to equivalently valued alternatives that are externally assigned. Here, we asked whether the value of information also varies as a function of self- or externally-imposed choices. Participants rated their preference for information that followed either a self-chosen decision, or an externally imposed condition. Our results showed that choosing a lottery significantly increased the subjective value of information about the outcome. Computational modelling indicated that this change in information-seeking behaviour was not due to changes in the subjective probability of winning, but instead reflected an independent effect of choosing on the value of resolving uncertainty. find more These results demonstrate that agency over a prospect is an important source of information value.We investigated the volcanic Narlı Lake in Central Anatolia combining high-resolution bathymetry and geochemical measurements. In this study, we present it as proof of a new concept to verify fluid pathways beneath lakes integrating the structure of the geothermal reservoir into the surrounding tectonic frame. We recognized dextral faults fracturing inherited volcanic formations and thus generating highly permeable zones beneath the lake. At intersection points of faults, reservoir fluids discharge from deep holes as imaged by the high-resolution bathymetry at the bottom of the Narlı Lake. Onshore, the tectonic setting also generates both extensional and compressional structures. Extensional structures result in extensive fluid discharge through hot springs while compressional structures do not discharge any fluid. The water of the lake as well as in the hot springs is highly saline and has relatively high concentrations of Cl, HCO3, SO4, Na, Ca, Mg, and Si. In several hot springs, we observed mixtures of high-saline fluids having a deep origin and low-saline shallow groundwater. We observed discharge into the lake by gas bubbles, which contain probably CO2 or H2S. Mineral precipitation indicates a carbonatic source at the lake bottom and along the shoreline. Extensive travertine precipitation also occurs near hot springs along the nearby extensional zone of Ihlara Valley. In summary, the composition of fluids and minerals is controlled by water-rock interaction through the volcanic and carbonatic rocks beneath this volcanic lake.The disposal of chicken feather through burning or burying is not environmentally compliant due to the accompanying release of greenhouse gas and underground water contamination. Thus, the transformation of this bio-waste into a bio-composite film is considered not only a sustainable strategy for disposal of this solid wastes but also an attractive alternative to developing an efficient nanostructured biomaterial from renewable bio resource. In the present study keratin extracted from chicken feather waste in combination with ginger starch were fabricated into a bio-composite film. The fabricated bio-composite films were characterized, using different analytical techniques. The physicochemical characteristics of ginger starch showed a moisture content of 33.8%, pH of 6.21, amylose and amylopectin contents of 39.1% and 60.9%, respectively. The hydration capacity of the starch was 132.2% while its gelatinization temperature was 65.7 °C. Physical attributes of the bio-composite film, such as surface smoothness and tensile strength increased significantly (p  less then  0.05) with increasing keratin content, while its transparency and solubility showed significant (p  less then  0.05) decrease with increasing keratin level. The various blends of the bio-composite films decayed by over 50% of the original mass after 12 days of complete burial in soil. Based on the results obtained in this study, the addition of keratin to starch bio-composite showed remarkable improvement in mechanical properties, such as tensile strength and surface smoothness. The bio-composite film exhibited appropriate stability in water, although future study should be carried out to evaluate its thermal stability. Nonetheless, the fabricated keratin-starch bio-composite showed desirable characteristics that could be optimized for industrial applications.Network embedding approaches are gaining momentum to analyse a large variety of networks. Indeed, these approaches have demonstrated their effectiveness in tasks such as community detection, node classification, and link prediction. However, very few network embedding methods have been specifically designed to handle multiplex networks, i.e. networks composed of different layers sharing the same set of nodes but having different types of edges. Moreover, to our knowledge, existing approaches cannot embed multiple nodes from multiplex-heterogeneous networks, i.e. networks composed of several multiplex networks containing both different types of nodes and edges. In this study, we propose MultiVERSE, an extension of the VERSE framework using Random Walks with Restart on Multiplex (RWR-M) and Multiplex-Heterogeneous (RWR-MH) networks. MultiVERSE is a fast and scalable method to learn node embeddings from multiplex and multiplex-heterogeneous networks. We evaluate MultiVERSE on several biological and social networks and demonstrate its performance.
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