Simulating high-throughput cryptocurrency payment channel networks

Payment channels secured with cryptocurrency as collateral enable users to make many transactions with few blockchain broadcasts. Networks of payment channels have emerged as a proposed solution to Bitcoin’s scaling problem. Since the proposal of the first payment channel network, the Lightning Network, alternatives promising significant improvements, such as the Sprites protocol, have been proposed. Without at-scale implementations to analyze in situ, it is difficult to make meaningful comparisons of payment channel network protocols. In order to bridge this gap, we introduce a new simulation framework that can be used to evaluate how different payment channel network protocols will perform in both the expected and worst cases. Our framework is generic and accommodates benchmarking across different variants of payment channel network protocols, network topologies, routing algorithms, and user behaviors. User spending behavior in our payment channel network simulator is generated based on behavioral modeling techniques used in credit card fraud research. Our simulation is the first payment channel network simulator to seed user behaviors with data from real-world credit card users. Our framework can be used to evaluate expected case performance and resiliency to attacks across different payment channel network protocols and routing algorithms. We demonstrate the utility of our framework through comparisons of the Lightning Network to Sprites. We also compare the proposed decentralized routing algorithm, Flare, to an ideal centralized routing algorithm. Our results reveal that if spending behaviors are similar to those of credit card users, scale-free network topologies achieve higher throughput and resiliency compared to small-world networks. We also confirm that the Sprites protocol enjoys numerous advantages over the Lightning Network including smaller durations, shorter path length payments, and greater resiliency, all of which are most significant in decentralized topologies using decentralized routing algorithms

Auditable, Available and Resilient Private Computation on the Blockchain via MPC

Simple but mission-critical internet-based applications that require extremely high reliability, availability, and verifiability (e.g., auditability) could benefit from running on robust public programmable blockchain platforms such as Ethereum. Unfortunately, program code running on such blockchains is normally publicly viewable, rendering these platforms unsuitable for applications requiring strict privacy of application code, data, and results. In this work, we investigate using MPC techniques to protect the privacy of a blockchain computation. While our main goal is to hide both the data and the computed function itself, we also consider the standard MPC setting where the function is public. We describe GABLE (Garbled Autonomous Bots Leveraging Ethereum), a blockchain MPC architecture and system. The GABLE architecture specifies the roles and capabilities of the players. GABLE includes two approaches for implementing MPC over blockchain: Garbled Circuits (GC), evaluating universal circuits, and Garbled Finite State Automata (GFSA). We formally model and prove the security of GABLE implemented over garbling schemes, a popular abstraction of GC and GFSA from (Bellare et al, CCS 2012). We analyze in detail the performance (including Ethereum gas costs) of both approaches and discuss the trade-offs. We implement a simple prototype of GABLE and report on the implementation issues and experience

A new reconstruction of the iridopteridalean Ibyka amphikoma Skog et Banks from the Middle Devonian of Gilboa, New York State

Premise of research. Clarifying the basic anatomy and morphology of Devonian fossils is essential for understanding the origin and radiation of land plants in deep time. Iridopteridales is a major Devonian plant group for which there is no presently established whole-plant concept. Methodology. The type material of the iridopteridalean Ibyka amphikoma Skog et Banks was reprepared and redescribed to clarify the details of its branching patterns and enable comparison to the previously described anatomy. Pivotal results. At least three orders of branching are known. Insertions of laterals are dominantly whorled, sometimes imperfectly, with distinct internodes. Within a whorl, branches may substitute for dichotomous appendages, with the latter more numerous. A new reconstruction is presented. On the basis of the partially preserved anatomy and the comparison to anatomically preserved Iridopteridales, we infer that traces to the branches and appendages are emitted one from each arm of a multiribbed actinostele. This pattern contrasts with that of the only other iridopteridalean preserved both anatomically and morphologically, Compsocradus laevigatus Berry et Stein, in which traces are emitted from alternate ribs in each whorl, with angular offsets between adjacent whorls. Conclusions. This basic understanding of the essentially whorled organization of Iridopteridales, as well as their overall morphology and anatomy, will benefit attempts to infer the broader phylogeny of early land plants, including the origins of horsetails and ferns

Nanocatalysis: size- and shape-dependent chemisorption and catalytic reactivity

In recent years, the field of catalysis has experienced an astonishing transformation, driven in part by more demanding environmental standards and critical societal and industrial needs such as the search for alternative energy sources. Thanks to the advent of nanotechnology, major steps have been made towards the rational design of novel catalysts. Striking new catalytic properties, including greatly enhanced reactivities and selectivities, have been reported for nanoparticle (NP) catalysts as compared to their bulk counterparts. However, in order to harness the power of these nanocatalysts, a detailed understanding of the origin of their enhanced performance is needed. The present review focuses on the role of the NP size and shape on chemisorption and catalytic performance. Since homogeneity in NP size and shape is a prerequisite for the understanding of structure–reactivity correlations, we first review different synthesis methods that result in narrow NP size distributions and shape controlled NPs. Next, size-dependent phenomena which influence the chemical reactivity of NPs, including quantum size-effects and the presence of under-coordinated surface atoms are examined. The effect of the NP shape on catalytic performance is discussed and explained based on the existence of different atomic structures on the NP surface with distinct chemisorption properties. The influence of additional factors, such as the oxidation state of the NPs and NP–support interactions, is also considered in the frame of the size- and shape-dependency that these phenomena present. Ultimately, our review highlights the importance of achieving a systematic understanding of the factors that control the activity and selectivity of a catalyst in order to avoid trial and error methods in the rational design of the new generation of nanocatalysts with properties tunable at the atomic level