A Formal Analysis of the Mimblewimble Cryptocurrency Protocol

Mimblewimble (MW) is a privacy-oriented cryptocurrency technology that provides security and scalability properties that distinguish it from other protocols of its kind. We present and discuss those properties and outline the basis of a model-driven verification approach to address the certification of the correctness of the protocol implementations. In particular, we propose an idealized model that is key in the described verification process, and identify and precisely state [Review 2]sufficientthe conditions for our model to ensure the verification of the relevant security properties of MW. Since MW is built on top of a consensus protocol, we develop a Z specification of one such protocol and present an excerpt of the prototype after its Z specification. This prototype can be used as an executable model. [Review 3]where simulations can be run This allows us to analyze the behavior of the protocol without having to implement it in a low level programming language. Finally, we analyze the Grin and Beam implementations of MW in their current state of development.

Along-wind dispersion by horizontal turbulent jets in the upper ocean

Dispersion processes in the ocean surface boundary layer (OSBL) determine marine material distributions such as those of plankton and pollutants. Sheared velocities drive shear dispersion, which is traditionally assumed to be due to mean horizontal currents that decrease from the surface. However, OSBL turbulence supports along-wind jets; located in near-surface convergence and downwelling regions, such turbulent jets contain strong local shear. Through wind-driven idealized and large eddy simulation (LES) models of the OSBL, this study examines the role of turbulent along-wind jets in dispersing material. In the idealized model, turbulent jets are generated by prescribed cellular flow with surface convergence and associated downwelling regions. Numeric and analytic model solutions reveal that horizontal jets substantially contribute to along-wind dispersion for sufficiently strong cellular flows and exceed contributions due to vertical mean shear for buoyant surface-trapped material. However, surface convergence regions also accumulate surface-trapped material, reducing shear dispersion by jets. Turbulence resolving LES results of a coastal depth-limited ocean agree qualitatively with the idealized model and reveal long-lived coherent jet structures that are necessary for effective jet dispersion. These coastal results indicate substantial jet contributions to along-wind dispersion. However, jet dispersion is likely less effective in the open ocean because jets are shorter lived, less organized, and distorted due to spiraling Ekman currents.

Robustness meets algorithms

In every corner of machine learning and statistics, there is a need for estimators that work not just in an idealized model, but even when their assumptions are violated. Unfortunately, in high dimensions, being provably robust and being efficiently computable are often at odds with each other. We give the first efficient algorithm for estimating the parameters of a high-dimensional Gaussian that is able to tolerate a constant fraction of corruptions that is independent of the dimension. Prior to our work, all known estimators either needed time exponential in the dimension to compute or could tolerate only an inverse-polynomial fraction of corruptions. Not only does our algorithm bridge the gap between robustness and algorithms, but also it turns out to be highly practical in a variety of settings.

A Diurnal Predictability Barrier for Weather Forecasts

In this study, we investigate a diurnal predictability barrier (DPB) for weather predictions using an idealized model and observations. This DPB is referred to a maximum drop of predictability (e.g., autocorrelation) at a particular time of the day, regardless of the initial time. Previous studies demonstrated that a strong seasonal cycle of El Niño-Southern Oscillation (ENSO) growth rate is responsible for the seasonal predictability barrier of the ENSO in spring. This led us to investigate whether or not a strong diurnal cycle may generate a DPB. We study the DPB using an idealized model, the Lorenz 1963 model (Lorenz63), with the addition of a diurnal cycle. We find that diurnal growth rate can generate a DPB in this chaotic system, regardless of the initial error. Finally, by calculating the autocorrelation function using the hourly data of surface temperature, we explore the DPB at two stations in Wisconsin, USA and Beijing, China. A clear DPB feature is found at both stations. The dramatic drop of predictability at a specific time of the day is likely due to the diurnal variation of the system. This is a new feature that needs further study for short-term weather predictions.

Searching for a Dialogue

The paper aims to examine the linguistic relationship between patients and physicians in the context of the therapeutic relationship. It focuses on the Hippocratic treatises and offers a detailed commentary of a controversial passage of Ancient Medicine par. 2.3. The dialogical model of Ancient Medicine is found to be centred on the patient’s experience; this same idealized model of relation is documented in Plato’s Laws. In the second part of the article the author examines some linguistic peculiarities of medical discourse, such as the use of comparisons and metaphors, and a passage from Galen’s On the Affected Parts that reports the case of a young patient and the difficulties inherent in the dialogue between patient and physician.