496 research outputs found
The rise and fall of cryptocurrency coins and tokens
Since Bitcoinâs introduction in 2009, interest in cryptocurrencies has soared. One manifestation of this interest has been the explosion of newly created coins and tokens. In this paper, we analyze the dynamics of this burgeoning industry. We consider both cryptocurrency coins and tokens. The paper examines the dynamics of coin and token creation, competition and destruction in the cryptocurrency industry. In order to conduct the analysis, we develop a methodology to identify peaks in prices and trade volume, as well as when coins and tokens are abandoned and subsequently âresurrectedâ. We also study trading activity. Our data spans more than 4 years: there are 1082 coins and 725 tokens in the data. While there are some similarities between coins and tokens regarding dynamics, there are some striking differences as well. Overall, we find that 44% of publicly-traded coins are abandoned, at least temporarily. 71% of abandoned coins are later resurrected, leaving 18% of coins to fail permanently. Tokens experience abandonment less frequently, with only 7% abandonment and 5% permanent token abandonment at the end of the data. Using linear regressions, we find that market variables such as the bitcoin price are not associated with the rate of introducing new coins, though they are positively associated with issuing new tokens. We find that for both coins and tokens, market variables are positively associated with resurrection. We then examine the effect that the bursting of the Bitcoin bubble in December 2017 had on the dynamics in the industry. Unlike the end of the 2013 bubble, some alternative cryptocurrencies continue to flourish after the bursting of this bubble
Analyzing Target-Based Cryptocurrency Pump and Dump Schemes
As the number of cryptocurrencies has exploded in recent years, so too has the fraud. One popular strategy is when actors promote coordinated purchases of coins in hopes of temporarily driving up prices. Prior work investigating such pump and dump schemes has focused on the immediate impact to prices following pump signals, which were largely interpreted as following the same strategy. The reality, as with most cybercrimes, is that the operators of the schemes try out a much more heterogeneous mix of tactics. From a population of 12,252 pump signals observed between July 2017 and January 2019, we identify and examine 3,683 so-called target-based pump signals that announce promoted coins alongside buy and sell targets, but without a coordinated purchase time. We develop a strategy to measure the success of target pumps over longer time horizons. We find that around half of these pumps reach at least one of their sell targets, and that reaching their peak price often takes days, as opposed to the seconds or minutes required in pumps studied previously. We also examine the various groups promoting coins and present evidence that groups try a variety of distinct strategies and experience varying success. We find that the most successful groups promote many coins and issue many pumps, but not for the same coins. As decentralized finance becomes more popular, a deeper understanding of price manipulation techniques like target pumps is needed to combat fraud
An examination of the cryptocurrency pump-and-dump ecosystem
The recent introduction of thousands of cryptocurrencies in an unregulated environment has created many opportunities for unscrupulous traders to profit from price manipulation. We quantify the scope of one widespread tactic, the âpump and dumpâ, in which actors coordinate to bid up the price of coins before selling at a profit. We joined all relevant channels on two popular group-messaging platforms, Telegram and Discord, and identified thousands of different pumps targeting hundreds of coins. We find that pumps are modestly successful in driving short-term price rises, but that this effect has diminished over time. We also find that the most successful pumps are those that are most transparent about their intentions. Combined with evidence of concentration among a small number of channels, we conclude that regulators have an opportunity to effectively crack down on this illicit activity that threatens broader adoption of blockchain technologies
An Experimental Study of Cryptocurrency Market Dynamics
As cryptocurrencies gain popularity and credibility, marketplaces for
cryptocurrencies are growing in importance. Understanding the dynamics of these
markets can help to assess how viable the cryptocurrnency ecosystem is and how
design choices affect market behavior. One existential threat to
cryptocurrencies is dramatic fluctuations in traders' willingness to buy or
sell. Using a novel experimental methodology, we conducted an online experiment
to study how susceptible traders in these markets are to peer influence from
trading behavior. We created bots that executed over one hundred thousand
trades costing less than a penny each in 217 cryptocurrencies over the course
of six months. We find that individual "buy" actions led to short-term
increases in subsequent buy-side activity hundreds of times the size of our
interventions. From a design perspective, we note that the design choices of
the exchange we study may have promoted this and other peer influence effects,
which highlights the potential social and economic impact of HCI in the design
of digital institutions.Comment: CHI 201
The genetics of cortical organisation and development: A study of 2,347 neuroimaging phenotypes
Our understanding of the genetic architecture of the human cerebral cortex is limited both in terms of the diversity of brain structural phenotypes and the anatomical granularity of their associations with genetic variants. Here, we conducted genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,843 individuals from the UK Biobank and the ABCD cohorts. These phenotypes include cortical thickness, surface area, grey matter volume, and measures of folding, neurite density, and water diffusion. We identified 4,349 experiment-wide significant loci associated with global and regional phenotypes. Multiple lines of analyses identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with surface area and volume specifically are associated with cephalic disorders. Finally, we identified complex inter-phenotype and inter-regional genetic relationships among the 13 phenotypes which reflect developmental differences among them. These analyses help refine the role of common genetic variants in human cortical development and organisation
Profiling allele-specific gene expression in brains from individuals with autism spectrum disorder reveals preferential minor allele usage.
One fundamental but understudied mechanism of gene regulation in disease is allele-specific expression (ASE), the preferential expression of one allele. We leveraged RNA-sequencing data from human brain to assess ASE in autism spectrum disorder (ASD). When ASE is observed in ASD, the allele with lower population frequency (minor allele) is preferentially more highly expressed than the major allele, opposite to the canonical pattern. Importantly, genes showing ASE in ASD are enriched in those downregulated in ASD postmortem brains and in genes harboring de novo mutations in ASD. Two regions, 14q32 and 15q11, containing all known orphan C/D box small nucleolar RNAs (snoRNAs), are particularly enriched in shifts to higher minor allele expression. We demonstrate that this allele shifting enhances snoRNA-targeted splicing changes in ASD-related target genes in idiopathic ASD and 15q11-q13 duplication syndrome. Together, these results implicate allelic imbalance and dysregulation of orphan C/D box snoRNAs in ASD pathogenesis
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Postnatal immune activation causes social deficits in a mouse model of tuberous sclerosis: Role of microglia and clinical implications
There is growing evidence that prenatal immune activation contributes to neuropsychiatric disorders. Here, we show that early postnatal immune activation resulted in profound impairments in social behavior, including in social memory in adult male mice heterozygous for a gene responsible for tuberous sclerosis complex (Tsc2+/â), a genetic disorder with high prevalence of autism. Early postnatal immune activation did not affect either wild-type or female Tsc2+/â mice. We demonstrate that these memory deficits are caused by abnormal mammalian target of rapamycinâdependent interferon signaling and impairments in microglia function. By mining the medical records of more than 3 million children followed from birth, we show that the prevalence of hospitalizations due to infections in males (but not in females) is associated with future development of autism spectrum disorders (ASD). Together, our results suggest the importance of synergistic interactions between strong early postnatal immune activation and mutations associated with ASD
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