Coulomb Drag in Graphene

We study the Coulomb drag between two single graphene sheets in intrinsic and extrinsic graphene systems with no interlayer tunneling. The general expression for the nonlinear susceptibility appropriate for single-layer graphene systems is derived using the diagrammatic perturbation theory, and the corresponding exact zero-temperature expression is obtained analytically. We find that, despite the existence of a non-zero conductivity in an intrinsic graphene layer, the Coulomb drag between intrinsic graphene layers vanishes at all temperatures. In extrinsic systems, we obtain numerical results and an approximate analytical result for the drag resistivity $\rho_{\textrm{D}}$, and find that $\rho_{\textrm{D}}$ goes as $T^2$ at low temperature $T$, as $1/d^4$ for large bilayer separation $d$ and $1/n^3$ for high carrier density $n$. We also discuss qualitatively the effect of plasmon-induced enhancement on the Coulomb drag, which should occur at a temperature of the order of or higher than the Fermi temperature

Drones: Innovative Technology for Use in Precision Pest Management.

Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early outbreak detection and treatment application are inherent to effective pest management, allowing management decisions to be implemented before pests are well-established and crop losses accrue. Pest monitoring is time-consuming and may be hampered by lack of reliable or cost-effective sampling techniques. Thus, we argue that an important research challenge associated with enhanced sustainability of pest management in modern agriculture is developing and promoting improved crop monitoring procedures. Biotic stress, such as herbivory by arthropod pests, elicits physiological defense responses in plants, leading to changes in leaf reflectance. Advanced imaging technologies can detect such changes, and can, therefore, be used as noninvasive crop monitoring methods. Furthermore, novel methods of treatment precision application are required. Both sensing and actuation technologies can be mounted on equipment moving through fields (e.g., irrigation equipment), on (un)manned driving vehicles, and on small drones. In this review, we focus specifically on use of small unmanned aerial robots, or small drones, in agricultural systems. Acquired and processed canopy reflectance data obtained with sensing drones could potentially be transmitted as a digital map to guide a second type of drone, actuation drones, to deliver solutions to the identified pest hotspots, such as precision releases of natural enemies and/or precision-sprays of pesticides. We emphasize how sustainable pest management in 21st-century agriculture will depend heavily on novel technologies, and how this trend will lead to a growing need for multi-disciplinary research collaborations between agronomists, ecologists, software programmers, and engineers

Long-term X-ray Variability Study of IC342 from XMM-Newton Observations

We presented the results of an analysis of four XMM-Newton observations of the starburst galaxy IC342 taken over a four-year span from 2001 to 2005, with an emphasis on investigating the long-term flux and spectral variability of the X-ray point sources. We detected a total of 61 X-ray sources within 35' $\times$ 30' of the galaxy down to a luminosity of (1-2)$\times$1037 erg s-1 depending on the local background. We found that 39 of the 61 detected sources showed long-term variability, in which 26 of them were classified as X-ray transients. We also found 19 sources exhibiting variations in hardness ratios or undergoing spectral transitions among observations, and were identified as spectral variables. In particular, 8 of the identified X-ray transients showed spectral variability in addition to flux variability. The diverse patterns of variability observed is indicative of a population of X-ray binaries. We used X-ray colors, flux and spectral variability, and in some cases the optical or radio counterparts to classify the detected X-ray sources into several stellar populations. We identified a total of 11 foreground stars, 1 supersoft sources (SSS), 3 quasisoft sources (QSS), and 2 supernova remnants (SNR). The identified SSS/QSS are located near or on the spiral arms, associate with young stellar populations; the 2 SNR are very close to the starburst nucleus where current star formation activities are dominated. We also discovered a spectral change in the nuclear source of IC342 for the first time by a series of X-ray spectrum analysis.Comment: 45 pages, 6 figures accepted by Ap