Determination of jet fuel thermal deposit rate using a modified JFTOT

Three fuels having different breakpoint temperatures were studied in the modified jet fuel thermal oxidation tester. The lower stability fuel with a breakpoint of 240 C was first stressed at a constant temperature. After repeating this procedure at several different temperatures, an Arrehenius plot was drawn from the data. The correlation coefficient and the energy of activation were calculated to be 0.97 and 8 kcal/mole respectively. Two other fuels having breakpoint temperatures of 271 C and 285 C were also studied in a similar manner. A straight line was drawn through the data at a slope equivalent to the slope of the lower stability fuel. The deposit formation rates for the three fuels were determined at 260 C, and a relative deposit formation rate at this temperature was calculated and plotted as a function of the individual fuel's breakpoint temperatures

Impacts of stratospheric sulfate geoengineering on tropospheric ozone

A range of solar radiation management (SRM) techniques has been proposed to counter anthropogenic climate change. Here, we examine the potential effects of stratospheric sulfate aerosols and solar insolation reduction on tropospheric ozone and ozone at Earth's surface. Ozone is a key air pollutant, which can produce respiratory diseases and crop damage. Using a version of the Community Earth System Model from the National Center for Atmospheric Research that includes comprehensive tropospheric and stratospheric chemistry, we model both stratospheric sulfur injection and solar irradiance reduction schemes, with the aim of achieving equal levels of surface cooling relative to the Representative Concentration Pathway 6.0 scenario. This allows us to compare the impacts of sulfate aerosols and solar dimming on atmospheric ozone concentrations. Despite nearly identical global mean surface temperatures for the two SRM approaches, solar insolation reduction increases global average surface ozone concentrations, while sulfate injection decreases it. A fundamental difference between the two geoengineering schemes is the importance of heterogeneous reactions in the photochemical ozone balance with larger stratospheric sulfate abundance, resulting in increased ozone depletion in mid-A nd high latitudes. This reduces the net transport of stratospheric ozone into the troposphere and thus is a key driver of the overall decrease in surface ozone. At the same time, the change in stratospheric ozone alters the tropospheric photochemical environment due to enhanced ultraviolet radiation. A shared factor among both SRM scenarios is decreased chemical ozone loss due to reduced tropospheric humidity. Under insolation reduction, this is the dominant factor giving rise to the global surface ozone increase. Regionally, both surface ozone increases and decreases are found for both scenarios; that is, SRM would affect regions of the world differently in terms of air pollution. In conclusion, surface ozone and tropospheric chemistry would likely be affected by SRM, but the overall effect is strongly dependent on the SRM scheme. Due to the health and economic impacts of surface ozone, all these impacts should be taken into account in evaluations of possible consequences of SRM

Andreev Reflection in Heavy-Fermion Superconductors and Order Parameter Symmetry in CeCoIn_5

Differential conductance spectra are obtained from nanoscale junctions on the heavy-fermion superconductor CeCoIn$_5$ along three major crystallographic orientations. Consistency and reproducibility of characteristic features among the junctions ensure their spectroscopic nature. All junctions show a similar conductance asymmetry and Andreev reflection-like conductance with reduced signal (~ 10%-13%), both commonly observed in heavy-fermion superconductor junctions. Analysis using the extended Blonder-Tinkham-Klapwijk model indicates that our data provide the first spectroscopic evidence for $d_{x^2-y^2}$ symmetry. To quantify our conductance spectra, we propose a model by considering the general phenomenology in heavy fermions, the two-fluid behavior, and an energy-dependent density of states. Our model fits to the experimental data remarkably well and should invigorate further investigations.Comment: 4 pages, 4 figures; Phys. Rev. Lett., published versio

Simultaneous Spin-Charge Relaxation in Double Quantum Dots

We investigate phonon-induced spin and charge relaxation mediated by spin-orbit and hyperfine interactions for a single electron confined within a double quantum dot. A simple toy model incorporating both direct decay to the ground state of the double dot and indirect decay via an intermediate excited state yields an electron spin relaxation rate that varies non-monotonically with the detuning between the dots. We confirm this model with experiments performed on a GaAs double dot, demonstrating that the relaxation rate exhibits the expected detuning dependence and can be electrically tuned over several orders of magnitude. Our analysis suggests that spin-orbit mediated relaxation via phonons serves as the dominant mechanism through which the double-dot electron spin-flip rate varies with detuning.Comment: 5 pages, 3 figures, Supplemental Material (2 pages, 2 figures

Urbanisation as an important driver of nocturnal primate sociality

Urbanisation is an important factor driving species and biodiversity decline. Although habitat alterations can be detrimental for species, studies have shown that many diurnal primates are able to adapt to novel environments. Little is known about the ability of nocturnal primates to survive within the urban environment. To increase our understanding on this topic, we present ad libitum observations on group movement and sociality from urban and rural populations of the African lesser bushbaby (Galago moholi) in South Africa from 2014-2018. 20 Our data show considerable changes in the social dynamics within urban bushbaby populations. In contrast to rural individuals, which spent the majority of their activity period solitarily or in pairs, urban individuals displayed a larger degree of sociality throughout their active period, forming groups of up to 10 individuals. Furthermore, urban individuals spent less time moving around, while increasing social (communication/pair-grooming), foraging and feeding behaviour. Urban individuals fed on a range of different anthropogenic and natural food sources (insects/gum/nectar) compared to their rural counterparts. In summary, urban bushbabies showed a large degree of behavioural plasticity, with changes in social dynamics and structure frequently observed. Such alterations in sociality, along with the ability to utilise different feeding resources, may explain the ability of the species to survive within a highly altered environment

Spatial and temporal variation in organic acid anion exudation and nutrient anion uptake in the rhizosphere of Lupinus albus L

We investigated in situ the temporal patterns and spatial extent of organic acid anion exudation into the rhizosphere solution of Lupinus albus, and its relation with the nutrient anions phosphate, nitrate and sulfate by means of a rhizobox micro suction cup method under P sufficient conditions. We compared the soil solution in the rhizosphere of cluster roots with that in the vicinity of normal roots, nodules and bulk soil. Compared to the other rhizosphere and soil compartments, concentrations of organic acid anions were higher in the vicinity of cluster roots during the exudative burst (citrate, oxalate) and nodules (acetate, malate), while concentrations of inorganic nutrient anions were highest in the bulk soil. Both active cluster roots and nodules were most efficient in taking up nitrate and phosphate. The intensity of citrate exudation by cluster roots was highly variable. The overall temporal patterns during the lifetime of cluster roots were overlaid by a diurnal pattern, i.e. in most cases, the exudation burst consisted of one or more peaks occurring in the afternoon. Multiple exudation peaks occurred daily or were separated by 1 or 2days. Although citrate concentrations decreased with distance from the cluster root apex, they were still significantly higher at a distance of 6 to 10mm than in the bulk soil. Phosphate concentrations were extremely variable in the proximity of cluster roots. While our results indicate that under P sufficient conditions cluster roots take up phosphate during their entire life time, the influence of citrate exudation on phosphate mobilization from soil could not be assessed conclusively because of the complex interactions between P uptake, organic acid anion exudation and P mobilization. However, we observed indications of P mobilization concurrent with the highest measured citrate concentrations. In conclusion, this study provides semiquantitative in situ data on the reactivity of different root segments of L. albus L. in terms of root exudation and nutrient uptake under nutrient sufficient conditions, in particular on the temporal variability during the lifetime of cluster root

More functions of torpor and their roles in a changing world

Increased winter survival by reducing energy expenditure in adult animals is often viewed as the primary function of torpor. However, torpor has many other functions that ultimately increase the survival of heterothermic mammals and birds. In this review, we summarize new findings revealing that animals use torpor to cope with the conditions during and after natural disasters, including fires, storms, and heat waves. Furthermore, we suggest that torpor, which also prolongs longevity and was likely crucial for survival of mammals during the time of the dinosaur extinctions, will be advantageous in a changing world. Climate change is assumed to lead to an increase in the occurrence and intensity of climatic disasters, such as those listed above and also abnormal floods, droughts, and extreme temperatures. The opportunistic use of torpor, found in many heterothermic species, will likely enhance survival of these challenges, because these species can reduce energy and foraging requirements. However, many strictly seasonal hibernators will likely face the negative consequences of the predicted increase in temperature, such as range contraction. Overall, available data suggest that opportunistic heterotherms with their flexible energy requirements have an adaptive advantage over homeotherms in response to unpredictable conditions

Machine learning calibration of low-cost NO2 and PM10 sensors: non-linear algorithms and their impact on site transferability

Low-cost air pollution sensors often fail to attain sufficient performance compared with state-of-the-art measurement stations, and they typically require expensive laboratory-based calibration procedures. A repeatedly proposed strategy to overcome these limitations is calibration through co-location with public measurement stations. Here we test the idea of using machine learning algorithms for such calibration tasks using hourly-averaged co-location data for nitrogen dioxide (NO2) and particulate matter of particle sizes smaller than 10 µm (PM10) at three different locations in the urban area of London, UK. We compare the performance of ridge regression, a linear statistical learning algorithm, to two non-linear algorithms in the form of random forest regression (RFR) and Gaussian process regression (GPR). We further benchmark the performance of all three machine learning methods relative to the more common multiple linear regression (MLR). We obtain very good out-of-sample R2 scores (coefficient of determination) >0.7, frequently exceeding 0.8, for the machine learning calibrated low-cost sensors. In contrast, the performance of MLR is more dependent on random variations in the sensor hardware and co-located signals, and it is also more sensitive to the length of the co-location period. We find that, subject to certain conditions, GPR is typically the best-performing method in our calibration setting, followed by ridge regression and RFR. We also highlight several key limitations of the machine learning methods, which will be crucial to consider in any co-location calibration. In particular, all methods are fundamentally limited in how well they can reproduce pollution levels that lie outside those encountered at training stage. We find, however, that the linear ridge regression outperforms the non-linear methods in extrapolation settings. GPR can allow for a small degree of extrapolation, whereas RFR can only predict values within the training range. This algorithm-dependent ability to extrapolate is one of the key limiting factors when the calibrated sensors are deployed away from the co-location site itself. Consequently, we find that ridge regression is often performing as good as or even better than GPR after sensor relocation. Our results highlight the potential of co-location approaches paired with machine learning calibration techniques to reduce costs of air pollution measurements, subject to careful consideration of the co-location training conditions, the choice of calibration variables and the features of the calibration algorithm

Seismic modeling using the frozen Gaussian approximation

We adopt the frozen Gaussian approximation (FGA) for modeling seismic waves. The method belongs to the category of ray-based beam methods. It decomposes seismic wavefield into a set of Gaussian functions and propagates these Gaussian functions along appropriate ray paths. As opposed to the classic Gaussian-beam method, FGA keeps the Gaussians frozen (at a fixed width) during the propagation process and adjusts their amplitudes to produce an accurate approximation after summation. We perform the initial decomposition of seismic data using a fast version of the Fourier-Bros-Iagolnitzer (FBI) transform and propagate the frozen Gaussian beams numerically using ray tracing. A test using a smoothed Marmousi model confirms the validity of FGA for accurate modeling of seismic wavefields.Comment: 5 pages, 8 figure