Quantitative Assessment of Robotic Swarm Coverage

This paper studies a generally applicable, sensitive, and intuitive error metric for the assessment of robotic swarm density controller performance. Inspired by vortex blob numerical methods, it overcomes the shortcomings of a common strategy based on discretization, and unifies other continuous notions of coverage. We present two benchmarks against which to compare the error metric value of a given swarm configuration: non-trivial bounds on the error metric, and the probability density function of the error metric when robot positions are sampled at random from the target swarm distribution. We give rigorous results that this probability density function of the error metric obeys a central limit theorem, allowing for more efficient numerical approximation. For both of these benchmarks, we present supporting theory, computation methodology, examples, and MATLAB implementation code.Comment: Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Porto, Portugal, 29--31 July 2018. 11 pages, 4 figure

A Search for Technosignatures Around 31 Sun-like Stars with the Green Bank Telescope at 1.15-1.73 GHz

We conducted a search for technosignatures in April of 2018 and 2019 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ~26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time.Comment: 20 pages, 8 figures, in press at the Astronomical Journal (submitted on Sept. 9, 2020; reviews received Nov. 6; re-submitted Nov. 6; accepted Nov. 17

Probing the inhibitory potency of epigallocatechin gallate against human γB-crystallin aggregation: spectroscopic, microscopic and simulation studies

Aggregation of human ocular lens proteins, the crystallins is believed to be one of the key reasons for age-onset cataract. Previous studies have shown that human γD-crystallin forms amyloid like fibres under conditions of low pH and elevated temperature. In this article, we have investigated the aggregation propensity of human γB-crystallin in absence and presence of epigallocatechin gallate (EGCG), in vitro, when exposed to stressful conditions. We have used different spectroscopic and microscopic techniques to elucidate the inhibitory effect of EGCG towards aggregation. The experimental results have been substantiated by molecular dynamics simulation studies. We have shown that EGCG possesses inhibitory potency against the aggregation of human γB-crystallin at low pH and elevated temperature

An Approach Towards Development of a Migration Enabled Improved Datacenter Broker Policy

Cloud computinghas left its remarkable note on the computing world over the last few years. Through itseffectiveness, litheness, scalability & availability cloud computinghas changed the nature of computer systemdeployment. The Quality of Service (QoS) of a cloud service provider (CSP) is an important element of research interestwhich includes different critical issues such as proper load, minimization of waiting time, turnaround time, makespanand suppressing the wastage of bandwidth of the system. The Datacenter Broker (DCB) policy helpsassigning acloudletto a VM. In present study, we proposed an algorithm, i.e., Migration enabled Cloudlet Allocation Policy(MCAP) for allocation of cloudlets to the VMs in a Datacenter by taking into accounttheload capacity of VMs andlength of the cloudlets. The experimental results obtained using CloudSim toolkit under extensive loads that establishperformance supremacy of MCAP algorithm over the existing algorithms