160 research outputs found
Disentangling Decentralized Finance (DeFi) Compositions
We present the first study on compositions of Decentralized Finance (DeFi)
protocols, which aim to disrupt traditional finance and offer financial
services on top of the distributed ledgers, such as the Ethereum. Starting from
a ground-truth of 23 DeFi protocols and 10,663,881 associated accounts, we
study the interactions of DeFi protocols and associated smart contracts from a
macroscopic perspective. We find that DEX and lending protocols have a high
degree centrality, that interactions among protocols primarily occur in a
strongly connected component, and that known community detection cannot
disentangle DeFi protocols. Therefore, we propose an algorithm for extracting
the building blocks and uncovering the compositions of DeFi protocols. We apply
the algorithm and conduct an empirical analysis finding that swaps are the most
frequent building blocks and that DeFi aggregation protocols utilize functions
of many other DeFi protocols. Overall, our results and methods contribute to a
better understanding of a new family of financial products and could play an
essential role in assessing systemic risks if DeFi continues to proliferate
The Governance of Decentralized Autonomous Organizations: A Study of Contributors' Influence, Networks, and Shifts in Voting Power
We present a study analyzing the voting behavior of contributors, or vested
users, in Decentralized Autonomous Organizations (DAOs). We evaluate their
involvement in decision-making processes, discovering that in at least 7.54% of
all DAOs, contributors, on average, held the necessary majority to control
governance decisions. Furthermore, contributors have singularly decided at
least one proposal in 20.41% of DAOs. Notably, contributors tend to be
centrally positioned within the DAO governance ecosystem, suggesting the
presence of inner power circles. Additionally, we observed a tendency for
shifts in governance token ownership shortly before governance polls take place
in 1202 (14.81%) of 8116 evaluated proposals. Our findings highlight the
central role of contributors across a spectrum of DAOs, including Decentralized
Finance protocols. Our research also offers important empirical insights
pertinent to ongoing regulatory activities aimed at increasing transparency to
DAO governance frameworks
Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient?
Entities like centralized cryptocurrency exchanges fall under the business
category of virtual asset service providers (VASPs). As any other enterprise,
they can become insolvent. VASPs enable the exchange, custody, and transfer of
cryptoassets organized in wallets across distributed ledger technologies
(DLTs). Despite the public availability of DLT transactions, the cryptoasset
holdings of VASPs are not yet subject to systematic auditing procedures. In
this paper, we propose an approach to assess the solvency of a VASP by
cross-referencing data from three distinct sources: cryptoasset wallets,
balance sheets from the commercial register, and data from supervisory
entities. We investigate 24 VASPs registered with the Financial Market
Authority in Austria and provide regulatory data insights such as who are the
customers and where do they come from. Their yearly incoming and outgoing
transaction volume amount to 2 billion EUR for around 1.8 million users. We
describe what financial services they provide and find that they are most
similar to traditional intermediaries such as brokers, money exchanges, and
funds, rather than banks. Next, we empirically measure DLT transaction flows of
four VASPs and compare their cryptoasset holdings to balance sheet entries.
Data are consistent for two VASPs only. This enables us to identify gaps in the
data collection and propose strategies to address them. We remark that any
entity in charge of auditing requires proof that a VASP actually controls the
funds associated with its on-chain wallets. It is also important to report fiat
and cryptoasset and liability positions broken down by asset types at a
reasonable frequency
Network-based indicators of Bitcoin bubbles
The functioning of the cryptocurrency Bitcoin relies on the open availability
of the entire history of its transactions. This makes it a particularly
interesting socio-economic system to analyse from the point of view of network
science. Here we analyse the evolution of the network of Bitcoin transactions
between users. We achieve this by using the complete transaction history from
December 5th 2011 to December 23rd 2013. This period includes three bubbles
experienced by the Bitcoin price. In particular, we focus on the global and
local structural properties of the user network and their variation in relation
to the different period of price surge and decline. By analysing the temporal
variation of the heterogeneity of the connectivity patterns we gain insights on
the different mechanisms that take place during bubbles, and find that hubs
(i.e., the most connected nodes) had a fundamental role in triggering the burst
of the second bubble. Finally, we examine the local topological structures of
interactions between users, we discover that the relative frequency of triadic
interactions experiences a strong change before, during and after a bubble, and
suggest that the importance of the hubs grows during the bubble. These results
provide further evidence that the behaviour of the hubs during bubbles
significantly increases the systemic risk of the Bitcoin network, and discuss
the implications on public policy interventions
STAble: A novel approach to de novo assembly of RNA-seq data and its application in a metabolic model network based metatranscriptomic workflow
Background: De novo assembly of RNA-seq data allows the study of transcriptome in absence of a reference genome either if data is obtained from a single organism or from a mixed sample as in metatranscriptomics studies. Given the high number of sequences obtained from NGS approaches, a critical step in any analysis workflow is the assembly of reads to reconstruct transcripts thus reducing the complexity of the analysis. Despite many available tools show a good sensitivity, there is a high percentage of false positives due to the high number of assemblies considered and it is likely that the high frequency of false positive is underestimated by currently used benchmarks. The reconstruction of not existing transcripts may false the biological interpretation of results as - for example - may overestimate the identification of "novel" transcripts. Moreover, benchmarks performed are usually based on RNA-seq data from annotated genomes and assembled transcripts are compared to annotations and genomes to identify putative good and wrong reconstructions, but these tests alone may lead to accept a particular type of false positive as true, as better described below. Results: Here we present a novel methodology of de novo assembly, implemented in a software named STAble (Short-reads Transcriptome Assembler). The novel concept of this assembler is that the whole reads are used to determine possible alignments instead of using smaller k-mers, with the aim of reducing the number of chimeras produced. Furthermore, we applied a new set of benchmarks based on simulated data to better define the performance of assembly method and carefully identifying true reconstructions. STAble was also used to build a prototype workflow to analyse metatranscriptomics data in connection to a steady state metabolic modelling algorithm. This algorithm was used to produce high quality metabolic interpretations of small gene expression sets obtained from already published RNA-seq data that we assembled with STAble. Conclusions: The presented results, albeit preliminary, clearly suggest that with this approach is possible to identify informative reactions not directly revealed by raw transcriptomic data
STAble: a novel approach to de novo assembly of RNA-seq data and its application in a metabolic model network based metatranscriptomic workflow.
BACKGROUND: De novo assembly of RNA-seq data allows the study of transcriptome in absence of a reference genome either if data is obtained from a single organism or from a mixed sample as in metatranscriptomics studies. Given the high number of sequences obtained from NGS approaches, a critical step in any analysis workflow is the assembly of reads to reconstruct transcripts thus reducing the complexity of the analysis. Despite many available tools show a good sensitivity, there is a high percentage of false positives due to the high number of assemblies considered and it is likely that the high frequency of false positive is underestimated by currently used benchmarks. The reconstruction of not existing transcripts may false the biological interpretation of results as - for example - may overestimate the identification of "novel" transcripts. Moreover, benchmarks performed are usually based on RNA-seq data from annotated genomes and assembled transcripts are compared to annotations and genomes to identify putative good and wrong reconstructions, but these tests alone may lead to accept a particular type of false positive as true, as better described below. RESULTS: Here we present a novel methodology of de novo assembly, implemented in a software named STAble (Short-reads Transcriptome Assembler). The novel concept of this assembler is that the whole reads are used to determine possible alignments instead of using smaller k-mers, with the aim of reducing the number of chimeras produced. Furthermore, we applied a new set of benchmarks based on simulated data to better define the performance of assembly method and carefully identifying true reconstructions. STAble was also used to build a prototype workflow to analyse metatranscriptomics data in connection to a steady state metabolic modelling algorithm. This algorithm was used to produce high quality metabolic interpretations of small gene expression sets obtained from already published RNA-seq data that we assembled with STAble. CONCLUSIONS: The presented results, albeit preliminary, clearly suggest that with this approach is possible to identify informative reactions not directly revealed by raw transcriptomic data
The Borexino detector at the Laboratori Nazionali del Gran Sasso
Borexino, a large volume detector for low energy neutrino spectroscopy, is
currently running underground at the Laboratori Nazionali del Gran Sasso,
Italy. The main goal of the experiment is the real-time measurement of sub MeV
solar neutrinos, and particularly of the mono energetic (862 keV) Be7 electron
capture neutrinos, via neutrino-electron scattering in an ultra-pure liquid
scintillator. This paper is mostly devoted to the description of the detector
structure, the photomultipliers, the electronics, and the trigger and
calibration systems. The real performance of the detector, which always meets,
and sometimes exceeds, design expectations, is also shown. Some important
aspects of the Borexino project, i.e. the fluid handling plants, the
purification techniques and the filling procedures, are not covered in this
paper and are, or will be, published elsewhere (see Introduction and
Bibliography).Comment: 37 pages, 43 figures, to be submitted to NI
Results from the first use of low radioactivity argon in a dark matter search
Liquid argon is a bright scintillator with potent particle identification
properties, making it an attractive target for direct-detection dark matter
searches. The DarkSide-50 dark matter search here reports the first WIMP search
results obtained using a target of low-radioactivity argon. DarkSide-50 is a
dark matter detector, using two-phase liquid argon time projection chamber,
located at the Laboratori Nazionali del Gran Sasso. The underground argon is
shown to contain Ar-39 at a level reduced by a factor (1.4 +- 0.2) x 10^3
relative to atmospheric argon. We report a background-free null result from
(2616 +- 43) kg d of data, accumulated over 70.9 live-days. When combined with
our previous search using an atmospheric argon, the 90 % C.L. upper limit on
the WIMP-nucleon spin-independent cross section based on zero events found in
the WIMP search regions, is 2.0 x 10^-44 cm^2 (8.6 x 10^-44 cm^2, 8.0 x 10^-43
cm^2) for a WIMP mass of 100 GeV/c^2 (1 TeV/c^2 , 10 TeV/c^2).Comment: Accepted by Phys. Rev.
Diagnosis, treatment and prevention of pediatric obesity: consensus position statement of the Italian Society for Pediatric Endocrinology and Diabetology and the Italian Society of Pediatrics
The Italian Consensus Position Statement on Diagnosis, Treatment and Prevention of Obesity in Children and Adolescents integrates and updates the previous guidelines to deliver an evidence based approach to the disease. The following areas were reviewed: (1) obesity definition and causes of secondary obesity; (2) physical and psychosocial comorbidities; (3) treatment and care settings; (4) prevention.The main novelties deriving from the Italian experience lie in the definition, screening of the cardiometabolic and hepatic risk factors and the endorsement of a staged approach to treatment. The evidence based efficacy of behavioral intervention versus pharmacological or surgical treatments is reported. Lastly, the prevention by promoting healthful diet, physical activity, sleep pattern, and environment is strongly recommended since the intrauterine phase
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