A Characterization of Probability-based Dichotomous Belief Revision

This article investigates the properties of multistate top revision, a dichotomous (AGM-style) model of belief revision that is based on an underlying model of probability revision. A proposition is included in the belief set if and only if its probability is either 1 or infinitesimally close to 1. Infinitesimal probabilities are used to keep track of propositions that are currently considered to have negligible probability, so that they are available if future information makes them more plausible. Multistate top revision satisfies a slightly modified version of the set of basic and supplementary AGM postulates, except the inclusion and success postulates. This result shows that hyperreal probabilities can provide us with efficient tools for overcoming the well known difficulties in combining dichotomous and probabilistic models of belief change.

A Mixture Model Incorporating Individual Heterogeneity in Human Lifetimes

Analysis of some extensive individual-record data using a demographically informed model suggests constructing a general population model in which the lifetime of a person, beyond a certain threshold age, follows an extreme value distribution with a finite upper bound, and with that upper bound randomized over the population. The resulting population model incorporates heterogeneity in life-lengths, with lifetimes being finite individually, but with extremely long lifespans having negligible probability. Our findings are compared in detail with those of related studies in the literature, and used to reconcile contradictions between previous studies of extreme longevity. While being consistent with currently reported analyses of human lifetimes, we nevertheless differ with those who conclude in favour of unbounded human lifetimes.

Identifying medium-sized agricultural enterprises with the greatest potential for innovation development

The aim of the research is to identify medium-sized agricultural enterprises with the greatest potential for innovation development. The subject of the research is the key financial performance of the observed enterprises in 2017. Data were obtained from official financial statements publicly available on the website of the Serbian Business Registers Agency (SBRA). The aim of the research was realized by applying financial analysis methods and the Altman Z-score model. The purpose of the research is to improve the efficiency of limited funds for financing innovative activities in the agricultural sector. The research results are data on enterprises with negligible probability of bankruptcy and which thus have the greatest potential for innovation development.

DDR-Coin: An Efficient Probabilistic Distributed Trigger Counting Algorithm

A distributed trigger counting (DTC) problem is to detect w triggers in the distributed system consisting of n nodes. DTC algorithms can be used for monitoring systems using sensors to detect a significant global change. When designing an efficient DTC algorithm, the following goals should be considered; minimizing the whole number of exchanged messages used for counting triggers and even distribution of communication loads among nodes. In this paper, we present an efficient DTC algorithm, DDR-coin (Deterministic Detection of Randomly generated coins). The message complexity—the total number of exchanged messages—of DDR-coin is O(nlogn(w/n)) in average. MaxRcvLoad—the maximum number of received messages to detect w triggers in each node—is O(logn(w/n)) on average. DDR-coin is not an exact algorithm; even though w triggers are received by the n nodes, it can fail to raise an alarm with a negligible probability. However, DDR-coin is more efficient than exact DTC algorithms on average and the gap between those is increased for larger n. We implemented the prototype of the proposed scheme using NetLogo 6.1.1. We confirmed that experimental results are close to our mathematical analysis. Compared with the previous schemes—TreeFill, CoinRand, and RingRand— DDR-coin shows smaller message complexity and MaxRcvLoad.

Constraining the cross-section of dark matter with giant radial arcs in galaxy clusters

ABSTRACT We compare the statistics and morphology of giant arcs in galaxy clusters using N-body and non-radiative SPH simulations within the standard cold dark matter (CDM) model and simulations where dark matter (DM) has a non-negligible probability of interaction (parametrized by its cross-section), i.e self-interacting dark matter (SIDM). We use a ray-tracing technique to produce a statistically large number of arcs around six simulated galaxy clusters at different redshifts. Since DM is more likely to interact in colliding clusters than in relaxed clusters, and this probability of interaction is largest in denser regions, we focus our analysis on radial arcs (which trace the lensing potential in the central region better than tangential arcs) in galaxy clusters that underwent (or are undergoing) a major merger. We find that SIDM produces fewer radial arcs than standard CDM but they are on average more magnified. We also appreciate differences in the arc morphology that could be used to statistically favour one model versus the other.

Swampland constraints on no-boundary quantum cosmology

The Hartle-Hawking no-boundary proposal describes the quantum creation of the universe. To have a non-negligible probability to obtain a classical expanding universe, eternal inflation is required, which is severely constrained by Swampland conjectures such as the refined de Sitter conjecture and the distance conjecture. We discuss this issue in detail and demonstrate the incompatibility. We show that the dimensionless parameters in the refined de Sitter conjecture should be bounded from above by a positive power of the scalar potential to realize the classical expanding universe. In other words, the probability of the classical expanding universe is extremely small under the Swampland conjectures unless the parameters are much smaller than unity. If they are order unity, on the other hand, the saddle-point solution itself ceases to exist implying a genuinely quantum universe.

Modeling the dynamics of a Late Triassic vertebrate extinction: The Adamanian/Revueltian faunal turnover, Petrified Forest National Park, Arizona, USA

The coincidence of a diverse vertebrate assemblage with a high-precision geochronology and lithostratigraphy in Petrified Forest National Park (Arizona, USA) allows Bayesian quantification of the dynamics of a Late Triassic vertebrate extinction and replacement, the Adamanian/Revueltian (A/R) faunal turnover. This approach uniquely identifies probabilities for the tempo of the replacement of the Adamanian assemblage by that of the Revueltian, precisely tracking the turnover. While the method does not designate the moment of extinction, there is a negligible probability that all Adamanian extinctions, as well as all Revueltian originations, are synchronous. A protracted A/R turnover is incompatible with the geologically instantaneous Manicouagan impact (215.4 ± 0.20 Ma; Québec, Canada) as a dominant causal mechanism. This analytical framework constitutes a flexible means of reconstructing biotic turnover in a variety of deep time contexts.

Constructing Sliding Windows Leak from Noisy Cache Timing Information of OSS-RSA

This paper presents a method for constructing an operation sequence of sliding window exponentiation from the noisy cache information of RSA, which can be used for a cache attack using sliding window's leak (SWL). SWL, which was reported in CHES 2017, is a kind of cache side-channel leak of a sequence of operations (i.e., multiplication and squaring) from software RSA decryption using the sliding window method for modular exponentiation. It was shown that an SWL attack can retrieve the secret keys of 1,024-bit and 2,048-bit RSA with non-negligible probability if the SWL is correctly captured. How- ever, in practice, it is not always possible for an attacker to acquire a complete and correct operation sequence from cache information observation. In addition, no concrete method for deriving a fully correct operation sequence from a partially acquired operation sequence as been reported in literature. In this paper, we first show that the capture errors in an operation sequence can be evaluated based on the Levenshtein distance between correct and estimated sequences. The dynamic time warping (DTW) algorithm is employed for quantitative evaluation. Then, we present a method of accurately estimating a complete and correct operation sequence from noisy sequences obtained through multiple observations. The basic idea of the proposed method and DTW-based evaluation is to divide the acquired operation sequence into short subsequences referred to as "operation patterns." Furthermore, we show the effectiveness of the proposed method through a set of experiments performed using RSA software in Libgcrypt, which is one of the most common open source software in cryptography.

Distributed Community Detection via Metastability of the 2-Choices Dynamics

We investigate the behavior of a simple majority dynamics on networks of agents whose interaction topology exhibits a community structure. By leveraging recent advancements in the analysis of dynamics, we prove that, when the states of the nodes are randomly initialized, the system rapidly and stably converges to a configuration in which the communities maintain internal consensus on different states. This is the first analytical result on the behavior of dynamics for nonconsensus problems on non-complete topologies, based on the first symmetry-breaking analysis in such setting.Our result has several implications in different contexts in which dynamics are adopted for computational and biological modeling purposes. In the context of Label Propagation Algorithms, a class of widely used heuristics for community detection, it represents the first theoretical result on the behavior of a distributed label propagation algorithm with quasi-linear message complexity. In the context of evolutionary biology, dynamics such as the Moran process have been used to model the spread of mutations in genetic populations (Lieberman, Hauert, and Nowak 2005); our result shows that, when the probability of adoption of a given mutation by a node of the evolutionary graph depends super-linearly on the frequency of the mutation in the neighborhood of the node and the underlying evolutionary graph exhibits a community structure, there is a non-negligible probability for species differentiation to occur.

Effects of re-acceleration and source grammage on secondary cosmic rays spectra

ABSTRACT The ratio between secondary and primary cosmic ray (CR) particles is the main source of information about CR propagation in the Galaxy. Primary CRs are thought to be accelerated mainly in supernova remnant shocks and then released in the interstellar medium. Here, they produce secondary particles by occasional collisions with interstellar matter. As a result, the ratio between the fluxes of secondary and primary particles carries information about the amount of matter CRs have encountered during their journey from their sources to the Earth. Recent measurements by AMS-02 revealed an unexpected behaviour of two main secondary-to-primary ratios, the Boron-to-Carbon ratio and the antiproton-to-proton ratio. In this work, we discuss how such anomalies may reflect the action of two phenomena that are usually overlooked, namely the fact that some fraction of secondary particles can be produced within the acceleration region, and the non-negligible probability that secondary particles encounter an accelerator (and are re-accelerated) during propagation. Both effects must be taken into account in order to correctly extract information about CR transport from secondary-to-primary ratios.