Some Model Theory of Free Groups

There are two main sets of results, both pertaining to the model theory of free groups. In the first set of results, we prove that non-abelian free groups of finite rank at least 3 or of countable rank are not A-homogeneous. We then build on the proof of this result to show that two classes of groups, namely finitely generated free groups and finitely generated elementary free groups, fail to form A-Fraisse classes and that the class of non-abelian limit groups fails to form a strong A-Fraisse class. The second main result is that if a countable group is elementarily equivalent to a non-abelian free group and all of its finitely generated abelian subgroups are cyclic, then the group is a union of a chain of regular NTQ groups (i.e., hyperbolic towers)

Deconstructing Blockchains: A Comprehensive Survey on Consensus, Membership and Structure

It is no exaggeration to say that since the introduction of Bitcoin, blockchains have become a disruptive technology that has shaken the world. However, the rising popularity of the paradigm has led to a flurry of proposals addressing variations and/or trying to solve problems stemming from the initial specification. This added considerable complexity to the current blockchain ecosystems, amplified by the absence of detail in many accompanying blockchain whitepapers. Through this paper, we set out to explain blockchains in a simple way, taming that complexity through the deconstruction of the blockchain into three simple, critical components common to all known systems: membership selection, consensus mechanism and structure. We propose an evaluation framework with insight into system models, desired properties and analysis criteria, using the decoupled components as criteria. We use this framework to provide clear and intuitive overviews of the design principles behind the analyzed systems and the properties achieved. We hope our effort will help clarifying the current state of blockchain proposals and provide directions to the analysis of future proposals

Interaction of preimplantation factor with the global bovine endometrial transcriptome

Preimplantation factor (PIF) is an embryo derived peptide which exerts an immune modulatory effect on human endometrium, promoting immune tolerance to the embryo whilst maintaining the immune response to invading pathogens. While bovine embryos secrete PIF, the effect on the bovine endometrium is unknown. Maternal recognition of pregnancy is driven by an embryo-maternal cross talk, however the process differs between humans and cattle. As many embryos are lost during the early part of pregnancy in cattle, a greater knowledge of factors affecting the embryo-maternal crosstalk, such as PIF, is needed to improve fertility. Therefore, for the first time, we demonstrate the effect of synthetic PIF (sPIF) on the bovine transcriptome in an ex vivo bovine endometrial tissue culture model. Explants were cultured for 30h with sPIF (100nM) or in control media. Total RNA was analysed via RNA-sequencing. As a result of sPIF treatment, 102 genes were differentially expressed compared to the control (Padj<0.1), although none by more than 2-fold. The majority of genes (78) were downregulated. Pathway analysis revealed targeting of several immune based pathways. Genes for the TNF, NF-κB, IL-17, MAPK and TLR signalling pathways were down-regulated by sPIF. However, some immune genes were demonstrated to be upregulated following sPIF treatment, including C3. Steroid biosynthesis was the only over-represented pathway with all genes upregulated. We demonstrate that sPIF can modulate the bovine endometrial transcriptome in an immune modulatory manner, like that in the human endometrium, however, the regulation of genes was much weaker than in previous human work

A Retrospective Analysis of User Exposure to (Illicit) Cryptocurrency Mining on the Web

In late 2017, a sudden proliferation of malicious JavaScript was reported on the Web: browser-based mining exploited the CPU time of website visitors to mine the cryptocurrency Monero. Several studies measured the deployment of such code and developed defenses. However, previous work did not establish how many users were really exposed to the identified mining sites and whether there was a real risk given common user browsing behavior. In this paper, we present a retroactive analysis to close this research gap. We pool large-scale, longitudinal data from several vantage points, gathered during the prime time of illicit cryptomining, to measure the impact on web users. We leverage data from passive traffic monitoring of university networks and a large European ISP, with suspected mining sites identified in previous active scans. We corroborate our results with data from a browser extension with a large user base that tracks site visits. We also monitor open HTTP proxies and the Tor network for malicious injection of code. We find that the risk for most Web users was always very low, much lower than what deployment scans suggested. Any exposure period was also very brief. However, we also identify a previously unknown and exploited attack vector on mobile devices