Temporal variability in early afterglows of short gamma-ray bursts

The shock model has successfully explained the observed behaviors of afterglows from long gamma-ray bursts (GRBs). Here we use it to investigate the so-called early afterglows from short GRBs, which arises from blast waves that are not decelerated considerably by their surrounding medium. We consider a nearby medium loaded with $e^{\pm}$ pairs (Beloborodov 2002). The temporal behaviors show first a soft-to-hard spectral evolution, from the optical to hard X-ray, and then a usual hard-to-soft evolution after the blast waves begin to decelerate. The light curves show variability, and consist of two peaks. The first peak, due to the pair effect, can be observed in the X-ray, though too faint and too short in the optical. The second peak will be easily detected by {\it Swift}. We show that detections of the double-peak structure in the light curves of early afterglows are very helpful to determine all the shock parameters of short GRBs, including both the parameters of the relativistic source and the surroundings. Besides, from the requirement that the forward-shock emission in short GRBs should be below the BATSE detection threshold, we give a strong constraint on the shock model parameters. In particular, the initial Lorentz factor of the source is limited to be no more than $\sim 10^3$, and the ambient medium density is inferred to be low, n\la 10^{-1} cm$^{-3}$.Comment: 5 pages, 1 figure, minor changes to match the publish in MNRA

The Relevance of Soil Moisture by Remote Sensing and Hydrological Modelling:12th International Conference on Hydroinformatics (HIC 2016) - Smart Water for the Future

AbstractAccurate soil moisture information is critically important for hydrological modelling and natural hazards (landslide & debris flow). However, its effective utilisation in those areas is still in a state of infancy. This paper focuses on exploring the advances and potential issues in current application of satellite soil moisture observations in hydrological modelling. It has proposed that hydrological application of soil moisture data requires two inter-connected components: 1) soil moisture data relevant to hydrology, and 2) appropriate hydrological model structure compatible with such data. In order to meet these two requirements, the following three research tasks are suggested: the first is to carry out comprehensive evaluations of satellite soil moisture observations for hydrological modelling; the second is that the soil moisture representations in hydrological models may need to be modified so that they are more compatible with the real field soil moisture variations; and the third is that a soil moisture product (i.e., soil moisture deficit) directly applicable to hydrological modelling should be developed

Electronic Deer Warning System

Deer-vehicle collisions (DVCs) are extremely dangerous, often injuring or even killing drivers. Unfortunately, this form of automotive accident is commonplace in the United States. According to the NHTSA, DVCs result in 200 human deaths a year.2 Despite these deadly incidents, there currently are no deployed federal or state systems for preventing DVCs. There are many consumer electronic deer deterrent products, but their long-term effectiveness is questionable.3 In fact, there does not appear to be much research into electronic deer deterrent systems. Aside from constant audio output and electric shock, no other means of electronic deterrent exist. Even if fixed deterrents were effective at repelling deer, these would further divide shrinking animal wildlife ecosystems, so this would not be a viable ecological solution. As such, different methods of preventing DVCs need to be explored. One option would be to warn deer of incoming vehicles. Deer are intelligent and are capable of understanding potential harm. This project is to provide an easy means to experiment with different deer warning methods by delivering a prototyping system. As such, the system should be simple to understand and widely extensible

When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing

Defense strategies have been well studied to combat Byzantine attacks that aim to disrupt cooperative spectrum sensing by sending falsified versions of spectrum sensing data to a fusion center. However, existing studies usually assume network or attackers as passive entities, e.g., assuming the prior knowledge of attacks is known or fixed. In practice, attackers can actively adopt arbitrary behaviors and avoid pre-assumed patterns or assumptions used by defense strategies. In this paper, we revisit this security vulnerability as an adversarial machine learning problem and propose a novel learning-empowered attack framework named Learning-Evaluation-Beating (LEB) to mislead the fusion center. Based on the black-box nature of the fusion center in cooperative spectrum sensing, our new perspective is to make the adversarial use of machine learning to construct a surrogate model of the fusion center's decision model. We propose a generic algorithm to create malicious sensing data using this surrogate model. Our real-world experiments show that the LEB attack is effective to beat a wide range of existing defense strategies with an up to 82% of success ratio. Given the gap between the proposed LEB attack and existing defenses, we introduce a non-invasive method named as influence-limiting defense, which can coexist with existing defenses to defend against LEB attack or other similar attacks. We show that this defense is highly effective and reduces the overall disruption ratio of LEB attack by up to 80%

Pair loading in Gamma-Ray Burst Fireball And Prompt Emission From Pair-Rich Reverse Shock

Gamma-ray bursts (GRBs) are believed to originate from ultra-relativistic winds/fireballs to avoid the "compactness problem". However, the most energetic photons in GRBs may still suffer from $\gamma-\gamma$ absorption leading to electron/positron pair production in the winds/fireballs. We show here that in a wide range of model parameters, the resulting pairs may dominate those electrons associated with baryons. Later on, the pairs would be carried into a reverse shock so that a shocked pair-rich fireball may produce a strong flash at lower frequencies, i.e. in the IR band, in contrast with optical/UV emission from a pair-poor fireball. The IR emission would show a 5/2 spectral index due to strong self-absorption. Rapid responses to GRB triggers in the IR band would detect such strong flashes. The future detections of many IR flashes will infer that the rarity of prompt optical/UV emissions is in fact due to dust obscuration in the star formation regions.Comment: 8 pages, 2 figures, ApJ accepte

Evaluation of SMOS soil moisture retrievals over the central United States for hydro-meteorological application

Soil moisture has been widely recognized as a key variable in hydro-meteorological processes and plays an important role in hydrological modelling. Remote sensing techniques have improved the availability of soil moisture data, however, most previous studies have only focused on the evaluation of retrieved data against point-based observations using only one overpass (i.e., the ascending orbit). Recently, the global Level-3 soil moisture dataset generated from Soil Moisture and Ocean Salinity (SMOS) observations was released by the Barcelona Expert Center. To address the aforementioned issues, this study is particularly focused on a basin scale evaluation in which the soil moisture deficit is derived from a three-layer Xinanjiang model used as a hydrological benchmark for all comparisons. In addition, both ascending and descending overpasses were analyzed for a more comprehensive comparison. It was interesting to find that the SMOS soil moisture accuracy did not improve with time as we would have expected. Furthermore, none of the overpasses provided reliable soil moisture estimates during the frozen season, especially for the ascending orbit. When frozen periods were removed, both overpasses showed significant improvements (i.e., the correlations increased from r = −0.53 to r = −0.65 and from r = −0.62 to r = −0.70 for the ascending and descending overpasses, respectively). In addition, it was noted that the SMOS retrievals from the descending overpass consistently were approximately 11.7% wetter than the ascending retrievals by volume. The overall assessment demonstrated that the descending orbit outperformed the ascending orbit, which was unexpected and enriched our knowledge in this area. Finally, the potential reasons were discussed