Stimulated infrared emission from rocks: assessing a stress indicator

International audienceTo study the effect of stress-activated positive hole (p-hole) charge carriers on the infrared (IR) emission from rocks, we subjected a portion (~10 vol.%) of a large (30×60×7.5 cm3) block of anorthosite, a nearly monomineralic (Ca-rich feldspar) igneous rock, to uniaxial deviatory stress up to failure. We measured the IR emission from a flat surface ?40 cm from the stressed rock volume over the 800?1300 cm?1 (7.7?12.5 ?m) range. Instantly, upon loading, the emission spectrum and intensity change. At first narrow bands appear at 930 cm?1 (10.75 ?m), 880 cm?1 (11.36 ?m), 820 cm?1 (12.4 ?m) plus additional narrow bands in the 1000?1300 cm?1 (7.7?10.0 ?m) range. The 10.75?12.4 ?m bands are thought to arise from vibrationally excited O-O stretching modes, which form when p-hole charge carriers, which spread from the stressed rock volume into the unstressed rock, recombine at the surface. They radiatively decay, giving rise to "hot" bands due to transitions between excited states. Before failure the broad emission bands at 1170 cm?1 and 1030 cm?1 (8.7 and 9.7 ?m) also increase slightly in intensity, suggesting a small increase in temperature due to thermalization of the energy deposited into the surface through p-hole recombination. Stimulated IR emission due to hole-hole recombination and its follow-on effects may help understand the enhanced IR emission seen in night-time satellite images of the land surface before major earthquakes known as "thermal anomalies"

Logarithmic based backoff algorithm for MAC protocol in MANETs

Abstract: The Binary Exponential Backoff (BEB) is used by IEEE 802.11 Medium Access Control (MAC). BEB uses a uniform random distribution to choose the backoff value, that often leads to reducing the effect of window size increment. This technical report introduces a modified logarithmic backoff algorithm that uses logarithmic increment instead of exponential extension of window size to eliminate the degrading effect of random number distribution. Results from simulation experiments reveal that the new algorithm achieves higher throughput when in a mobile ad hoc environment

Mobile Information System, How to Build with Case Study

In a distributed computing environment, comprising mobile computers and wireless networks, users change their locations frequently while still expecting “acceptable” levels of performance. This complexity will produce poor performance with no exact answer why? In such an environment, a new method of designing applications will be required. It is claimed that understanding network performance is an art rather than a science because in practice there is little underlying useful theory; so, experience with real world examples are used instead to develop rules of thumb [14]. This paper is fundamentally designed to describe types of mobile applications and the major performance factors needed to be considered when designing such kind of applications. Methods of connectivity: always connected, occasionally connected, and occasionally disconnected will be addressed as well. We are proposing a Mobile Information System (MIS) model. This model will address the needs for monitoring wireless environment where the mobile applications running in this area and how it is monitoring the performance factors. Also provided in the model are the features of the MIS, the pros and cons of the model, and a simulation to show the effectiveness of the model