Study of the mechanical behavior of asphalt mixtures using fractional rheology to model their viscoelasticity

This study focuses on the mechanical behavior of asphalt mixtures composed of aggregate particles attached with an asphalt binder. Asphalt mixtures are viscoelastic composite materials widely used in the construction of pavement layers. The modelling of such materials is currently done using the Burgers model. However, this model is limited when explaining some of the viscoelastic phenomena of an asphalt mixture, mainly because the Burgers model was developed for a single material with a dual nature. This work presents a new approach that provides a more appropriate framework for studying asphalt mixtures. The model assumes an aggregate particle enclosed by an asphalt material. Viscoelastic equations were developed using derivatives of fractional order. Then, the creep, recovery, and relaxation phenomena in an asphalt mixture were analyzed using the new model. Unlike the Burgers model, the new model can predict the elastic jump observed at the beginning of the creep modulus. Thus, the new model seems to describe better those practical cases of asphalt mixtures used in the construction of pavement layers. The new model can be used to modify the properties of the binder for designing optimized and more resistant asphalt mixtures

Damage evaluation during installation of geosynthetics used in asphalt pavements

Geosynthetics are commonly used as anti-reflective cracking systems in asphalt pavements. The rehabilitation design methods use the characteristics of as-received geosynthetics as inputs. However, these materials undergo physical damage during their installation due to mechanical and thermal loads which currently are not taken into account in the design processes. These loads can produce a reduction in geosynthetic strength and therefore, it is necessary to know the secant modulus after installation in order to improve the pavement design incorporating these materials. The secant modulus of a material indicates its initial stiffness. This paper describes an experimental study of damage due to installation of five different geosynthetics using three different procedures: (i) mechanical damage induced in the laboratory considering the action of aggregates, (ii) in situ mechanical and thermal damage due to actual installation in a test section, and (iii) a new mechanical and thermal damage experimental test developed with the aim of reproducing the real installation conditions. The main results of the study indicate that the obtained secant modulus of the tested geosynthetics reduced after applying the three damage procedures, and the loss of properties differed depending on the type and constitutive material and on the applied damage procedure.This investigation was supported by the research Project ‘Rehabilitation of roads and highways (REHABCAR)’ file number IPT-370000–2010–029, led by DRAGADOS (ACS Group), in collaboration with GEOCISA and ASFALTOS AUGUSTA among others. The project has been funded by the Ministry of Economy and Competitiveness (MINECO) within the National Plan for Scientific Research, Development and Innovation 2008–2011 (INNPACTO 2010) and the European Union under ERDF Funds (European Regional Development Fund)

Somatic Accumulation of GluA1-AMPA Receptors Leads to Selective Cognitive Impairments in Mice

© 2018 Bannerman, Borchardt, Jensen, Rozov, Haj-Yasein, Burnashev, Zamanillo, Bus, Grube, Adelmann, Rawlins and Sprengel. The GluA1 subunit of the L-α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) plays a crucial, but highly selective, role in cognitive function. Here we analyzed AMPAR expression, AMPAR distribution and spatial learning in mice (Gria1R/R), expressing the “trafficking compromised” GluA1(Q600R) point mutation. Our analysis revealed somatic accumulation and reduction of GluA1(Q600R) and GluA2, but only slightly reduced CA1 synaptic localization in hippocampi of adult Gria1R/R mice. These immunohistological changes were accompanied by a strong reduction of somatic AMPAR currents in CA1, and a reduction of plasticity (short-term and long-term potentiation, STP and LTP, respectively) in the CA1 subfield following tetanic and theta-burst stimulation. Nevertheless, spatial reference memory acquisition in the Morris water-maze and on an appetitive Y-maze task was unaffected in Gria1R/R mice. In contrast, spatial working/short-term memory during both spontaneous and rewarded alternation tasks was dramatically impaired. These findings identify the GluA1(Q600R) mutation as a loss of function mutation that provides independent evidence for the selective role of GluA1 in the expression of short-term memory

Test methods and influential factors for analysis of bonding between bituminous pavement layers

The durability and maintenance of pavements depend on several factors. One of the most influential is the bond between layers. This bond is responsible for ensuring all layers behave as a single entity, reducing cracks and deformation of the pavement. Several methods, developed by different authors over the past 30 years, to measure bonding between layers are analyzed in this paper. Different research lines are discussed, concluding that the most influential variables are: tack coat type, dosage, mixture type, surface characteristics, temperature, and emulsion breaking time. In order to reach the highest bond strength values, the following factors should be considered: high values of surface macro-texture, low temperatures, the use of heat-adhesive emulsion, a dosage from 300 to 450 g/m2 of residual bitumen and the compaction after emulsion break. Moreover, a non-destructive test method to assess tack coat dosage on site is proposed

Ionotropic Glutamate Receptor AMPA 1 Is Associated with Ovulation Rate

Ionotropic glutamate receptors mediate most excitatory neurotransmission in the central nervous system by opening ion channels upon the binding of glutamate. Despite the essential roles of glutamate in the control of reproduction and anterior pituitary hormone secretion, there is a limited understanding of how glutamate receptors control ovulation. Here we reveal the function of the ionotropic glutamate receptor AMPA-1 (GRIA1) in ovulation. Based on a genome-wide association study in Bos taurus, we found that ovulation rate is influenced by a variation in the N-terminal leucine/isoleucine/valine-binding protein (LIVBP) domain of GRIA1, in which serine is replaced by asparagine. GRIA1Asn has a weaker affinity to glutamate than GRIA1Ser, both in Xenopus oocytes and in the membrane fraction of bovine brain. This single amino acid substitution leads to the decreased release of gonadotropin-releasing hormone (GnRH) in immortalized hypothalamic GT1-7 cells. Cows with GRIA1Asn have a slower luteinizing hormone (LH) surge than cows with GRIA1Ser. In addition, cows with GRIA1Asn possess fewer immature ovarian follicles before superovulation and have a lower response to hormone treatment than cows with GRIA1Ser. Our work identified that GRIA1 is a critical mediator of ovulation and that GRIA1 might be a useful target for reproductive therapy

ApoE Receptor 2 Regulates Synapse and Dendritic Spine Formation

Apolipoprotein E receptor 2 (ApoEr2) is a postsynaptic protein involved in long-term potentiation (LTP), learning, and memory through unknown mechanisms. We examined the biological effects of ApoEr2 on synapse and dendritic spine formation-processes critical for learning and memory.In a heterologous co-culture synapse assay, overexpression of ApoEr2 in COS7 cells significantly increased colocalization with synaptophysin in primary hippocampal neurons, suggesting that ApoEr2 promotes interaction with presynaptic structures. In primary neuronal cultures, overexpression of ApoEr2 increased dendritic spine density. Consistent with our in vitro findings, ApoEr2 knockout mice had decreased dendritic spine density in cortical layers II/III at 1 month of age. We also tested whether the interaction between ApoEr2 and its cytoplasmic adaptor proteins, specifically X11α and PSD-95, affected synapse and dendritic spine formation. X11α decreased cell surface levels of ApoEr2 along with synapse and dendritic spine density. In contrast, PSD-95 increased cell surface levels of ApoEr2 as well as synapse and dendritic spine density.These results suggest that ApoEr2 plays important roles in structure and function of CNS synapses and dendritic spines, and that these roles are modulated by cytoplasmic adaptor proteins X11α and PSD-95

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedi�tion (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To re�duce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between envi�ronmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shap�ing the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question