Experimental Validation of a Real-Time Optimal Controller for Coordination of CAVs in a Multi-Lane Roundabout

Roundabouts in conjunction with other traffic scenarios, e.g., intersections, merging roadways, speed reduction zones, can induce congestion in a transportation network due to driver responses to various disturbances. Research efforts have shown that smoothing traffic flow and eliminating stop-and-go driving can both improve fuel efficiency of the vehicles and the throughput of a roundabout. In this paper, we validate an optimal control framework developed earlier in a multi-lane roundabout scenario using the University of Delaware's scaled smart city (UDSSC). We first provide conditions where the solution is optimal. Then, we demonstrate the feasibility of the solution using experiments at UDSSC, and show that the optimal solution completely eliminates stop-and-go driving while preserving safety.Comment: 6 Pages, 4 Figures, 1 tabl

Zero-Shot Autonomous Vehicle Policy Transfer: From Simulation to Real-World via Adversarial Learning

In this article, we demonstrate a zero-shot transfer of an autonomous driving policy from simulation to University of Delaware's scaled smart city with adversarial multi-agent reinforcement learning, in which an adversary attempts to decrease the net reward by perturbing both the inputs and outputs of the autonomous vehicles during training. We train the autonomous vehicles to coordinate with each other while crossing a roundabout in the presence of an adversary in simulation. The adversarial policy successfully reproduces the simulated behavior and incidentally outperforms, in terms of travel time, both a human-driving baseline and adversary-free trained policies. Finally, we demonstrate that the addition of adversarial training considerably improves the performance \eat{stability and robustness} of the policies after transfer to the real world compared to Gaussian noise injection.Comment: 6 pages, 4 figure

Reformism, Economic Liberalisation and Popular Mobilisation in Iran

Whereas in other MENA countries the impact of neo-liberal policies has been the subject of intense debate, there are at present few voices that directly analyse or critique its social and political consequences in Iran. This article seeks to address this lacuna by analysing the dynamics of reformism, economic liberalisation and popular mobilisation in Iran. It charts the country’s move from a post-revolutionary populism to a liberalised yet increasingly exclusivist model of politics and compares this to trajectories of economic liberalisation in Egypt. Two distinct outcomes of economic reform are analysed in the first part of the article: Socio-economic exclusion; and the contraction of political rights. In the second half, I investigate the ways successive post-war governments in Iran have packaged neo-liberal reforms, and how their re-imagining of the role of the state has led to differing levels of popular resistance. Finally I argue that under the present administration, political elites increasingly are oriented toward strengthening the state and seeking to limit opposition to their policies. However, the absence of neo-liberal hegemony in Iran means that growing mobilization on socio-economic issues is challenging these policies. The Right in Iranian politics is utilizing this mobilisation to present a populist challenge to the reformists in power

Longitudinal dynamics of circulating tumor cells and circulating tumor DNA for treatment monitoring in metastatic breast cancer

PURPOSE: Liquid biopsy-based biomarkers, including circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA), are increasingly important for the characterization of metastatic breast cancer (MBC). The aim of the study was to explore CTCs and ctDNA dynamics to better understand their potentially complementary role in describing MBC. METHODS: The study retrospectively analyzed 107 patients with MBC characterized with paired CTCs and ctDNA assessments and a second prospective cohort, which enrolled 48 patients with MBC. CTCs were immunomagnetically isolated and ctDNA was quantified and then characterized through next-generation sequencing in the retrospective cohort and droplet digital polymerase chain reaction in the prospective cohort. Matched pairs variations at baseline, at evaluation one (EV1), and at progression were tested through the Wilcoxon test. The prognostic role of ctDNA parameters was also investigated. RESULTS: Mutant allele frequency (MAF) had a significant decrease between baseline and EV1 and a significant increase between EV1 and progression. Number of detected alterations steadily increased across timepoints, CTCs enumeration (nCTCs) significantly increased only between EV1 and progression. MAF dynamics across the main altered genes was then investigated. Plasma DNA yield did not vary across timepoints both in the retrospective cohort and in the prospective cohort, while the short fragments fraction showed a potential role as a prognostic biomarker. CONCLUSION: nCTCs and ctDNA provide complementary information about prognosis and treatment benefit. Although nCTCs appeared to assess tumor biology rather than tumor burden, MAF may be a promising biomarker for the dynamic assessment of treatment response and resistance

Loss of CD4+ T cell-intrinsic arginase 1 accelerates Th1 response kinetics and reduces lung pathology during influenza infection

Arginase 1 (Arg1), the enzyme catalyzing the conversion of arginine to ornithine, is a hallmark of IL-10-producing immunoregulatory M2 macrophages. However, its expression in T cells is disputed. Here, we demonstrate that induction of Arg1 expression is a key feature of lung CD4+ T cells during mouse in vivo influenza infection. Conditional ablation of Arg1 in CD4+ T cells accelerated both virus-specific T helper 1 (Th1) effector responses and its resolution, resulting in efficient viral clearance and reduced lung pathology. Using unbiased transcriptomics and metabolomics, we found that Arg1-deficiency was distinct from Arg2-deficiency and caused altered glutamine metabolism. Rebalancing this perturbed glutamine flux normalized the cellular Th1 response. CD4+ T cells from rare ARG1-deficient patients or CRISPR-Cas9-mediated ARG1-deletion in healthy donor cells phenocopied the murine cellular phenotype. Collectively, CD4+ T cell-intrinsic Arg1 functions as an unexpected rheostat regulating the kinetics of the mammalian Th1 lifecycle with implications for Th1-associated tissue pathologies

A Socio-Technical and Co-Evolutionary Framework for Reducing Human-Related Risks in Cyber Security and Cybercrime Ecosystems

The focus on cyber security as an interaction between technical elements and humans has typically confined consideration of the latter to practical issues of implementation, conventionally those of `human performance factors' of vigilance etc., 'raising awareness' and/or 'incentivization' of people and organizations to participate and adapt their behavior. But this is far too narrow a view that seriously constrains the ability of cyber security as a whole to adapt and evolve to keep up with adaptive, innovative attackers in a rapidly-changing technological, business and social landscape, in which personal preferences of users are also dynamically evolving. While there is isolated research across different research areas, we noticed the lack of a \emph{holistic} framework combining a range of applicable theoretical concepts (e.g., cultural co-evolution such as technological arms races, opportunity management, behavioral and business models) and technological solutions on reducing human-related risks in the cyber security and cybercrime ecosystems, which involve multiple groups of human actors including offenders, victims, preventers and promoters. This paper reports our ongoing work in developing such a socio-technical framework 1) to allow a more comprehensive understanding of human-related risks within cyber security and cybercrime ecosystems and 2) to support the design of more effective approaches to engaging individuals and organizations in the reduction of such risks. We are in the process of instantiating this framework to encourage behavioral changes in two use cases that capture diverse and complicated socio-technical interactions in cyber-physical systems

Host Plant-Associated Population Variation in the Carob Moth Ectomyelois ceratoniae in Iran: A Geometric Morphometric Analysis Suggests a Nutritional Basis.

The carob moth, Ectomyelois ceratoniae (Zeller, 1839) (Lepidoptera: Pyralidae), is the most important pest of pomegranate in Iran. As it has been rarely recorded on other host plants, control methods have mostly been focused on its populations on pomegranate. In this study, shapes and sizes of wings were compared in populations on 4 host plants (pomegranate, fig, pistachio and walnut) using a landmark-based geometric morphometric method, and analysis of partial warp scores and centroid sizes. The results showed significantly smaller wing size in populations on pomegranate and a significant host plant-associated shape difference among populations as a consequence of allometric growth. This suggests that the wing size and shape differences among test populations may not have a genetic basis and could happen because of differences in the nutritional content of host plants. The results of the analysis suggest that the female carob moth lays her eggs on host plants that provide suitable conditions for hatching. The larger size of moths on hosts other than pomegranate showed that some host plants such as fig, pistachio and walnut can provide for increased stored nutritional reserves by larvae that may result in more successful over-wintering and higher fecundity in adults. This suggests that in spite of the more extensive activity of carob moth on pomegranate in Iran, populations on other host plants can have an important effect on expanding pest population sizes in following years which should be considered in control methods