Modelling Concurrency with Comtraces and Generalized Comtraces

Comtraces (combined traces) are extensions of Mazurkiewicz traces that can model the "not later than" relationship. In this paper, we first introduce the novel notion of generalized comtraces, extensions of comtraces that can additionally model the "non-simultaneously" relationship. Then we study some basic algebraic properties and canonical reprentations of comtraces and generalized comtraces. Finally we analyze the relationship between generalized comtraces and generalized stratified order structures. The major technical contribution of this paper is a proof showing that generalized comtraces can be represented by generalized stratified order structures.Comment: 49 page

Revisiting bisimilarity and its modal logic for nondeterministic and probabilistic processes

We consider PML, the probabilistic version of Hennessy-Milner logic introduced by Larsen and Skou to characterize bisimilarity over probabilistic processes without internal nondeterminism.We provide two different interpretations for PML by considering nondeterministic and probabilistic processes as models, and we exhibit two new bisimulation-based equivalences that are in full agreement with those interpretations. Our new equivalences include as coarsest congruences the two bisimilarities for nondeterministic and probabilistic processes proposed by Segala and Lynch. The latter equivalences are instead in agreement with two versions of Hennessy-Milner logic extended with an additional probabilistic operator interpreted over state distributions rather than over individual states. Thus, our new interpretations of PML and the corresponding new bisimilarities offer a uniform framework for reasoning on processes that are purely nondeterministic or reactive probabilistic or are mixing nondeterminism and probability in an alternating/non-alternating way

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Until recently, social media was seen to promote democratic discourse on social and political issues. However, this powerful communication platform has come under scrutiny for allowing hostile actors to exploit online discussions in an attempt to manipulate public opinion. A case in point is the ongoing U.S. Congress' investigation of Russian interference in the 2016 U.S. election campaign, with Russia accused of using trolls (malicious accounts created to manipulate) and bots to spread misinformation and politically biased information. In this study, we explore the effects of this manipulation campaign, taking a closer look at users who re-shared the posts produced on Twitter by the Russian troll accounts publicly disclosed by U.S. Congress investigation. We collected a dataset with over 43 million election-related posts shared on Twitter between September 16 and October 21, 2016, by about 5.7 million distinct users. This dataset included accounts associated with the identified Russian trolls. We use label propagation to infer the ideology of all users based on the news sources they shared. This method enables us to classify a large number of users as liberal or conservative with precision and recall above 90%. Conservatives retweeted Russian trolls about 31 times more often than liberals and produced 36x more tweets. Additionally, most retweets of troll content originated from two Southern states: Tennessee and Texas. Using state-of-the-art bot detection techniques, we estimated that about 4.9% and 6.2% of liberal and conservative users respectively were bots. Text analysis on the content shared by trolls reveals that they had a mostly conservative, pro-Trump agenda. Although an ideologically broad swath of Twitter users was exposed to Russian Trolls in the period leading up to the 2016 U.S. Presidential election, it was mainly conservatives who helped amplify their message

Adaptive transient solution of nonuniform multiconductor transmission lines using wavelets

Abstract—This paper presents a highly adaptive algorithm for the transient simulation of nonuniform interconnects loaded with arbitrary nonlinear and dynamic terminations. The discretization of the governing equations is obtained through a weak formula-tion using biorthogonal wavelet bases as trial and test functions. It is shown how the multiresolution properties of wavelets lead to very sparse approximations of the voltages and currents in typical transient analyzes. A simple yet effective time–space adaptive al-gorithm capable of selecting the minimal number of unknowns at each time iteration is described. Numerical results show the high degree of adaptivity of the proposed scheme. Index Terms—Electromagnetic (EM) transient analysis, multi-conductor transmission lines (TLs), wavelet transforms. I

LATERAL HETEROGENEITY AND ARCHITECTURAL ANALYSIS OF THE WALL CREEK MEMBER OF THE UPPER CRETACEOUS (TURONIAN) FRONTIER FORMATION

The Upper Turonian Wall Creek Member (WCM) of the Frontier Formation is part of a series of marine sandstones that were deposited on the western flank of the Cretaceous Western Interior Seaway (KWIS). The KWIS was a low accommodation shallow-marine foreland basin system that included many large deltaic complexes on its western margin. Deposition of WCM deltaic deposits was strongly influenced by fourthorder glacioeustatic cycles, oceanographic circulation patterns, and tectonics related to the active Sevier fold and thrust belt to the west. An in-depth field study of the WCM was performed on the western flank of the Powder River Basin (PRB), WY, in exposures forming the eastern flank of the Tisdale Anticline, a Laramide structure. The goal of the field study is to document the lateral and vertical heterogeneities within the WCM sandstone, its architectural elements, and its stratigraphic surfaces and use these to develop a sequence stratigraphic framework. Results of this study improve the understanding of depositional processes of the WCM and its characterization as a petroleum reservoir within ~30km of active drilling and production of the WCM in the PRB. This study describes 8 facies: 1) laminated mudstone 2) interbedded siltstone and sandstone 3) hummocky cross-stratification 4) low-angle stratified sandstone 5) thinly interbedded sandstone and siltstone 6) heterolithic cross-bedded sandstone 7) mediumgrained heterolithic cross-bedded sandstone and 8) trough cross-bedded sandstone. These facies are consolidated into 4 facies associations: FA1) prodelta FA2) distal delta front FA3) middle delta front FA4) tidal bars/shoals. Facies characteristics, facies stacking patterns, and architectural surfaces/elements indicate two primary deltaic influences: 1) storm/wave dominated deltas and 2) tidally dominated deltas. Three incomplete stratigraphic sequences are observed from facies stacking patterns and stratal geometries. Sequence 1) transgressive systems tract 1 (TST1), highstand systems tract 1 (HST1), and falling stage systems tract 1 (FSST1); Sequence 2) transgressive systems tract 2 (TST2) and highstand systems tract 2 (HST2); Sequence 3) lowstand systems tract 1 (LST1)

Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean Ridge

Microbial communities and their associated metabolic activity in marine sediments have a profound impact on global biogeochemical cycles. Their composition and structure are attributed to geochemical and physical factors, but finding direct correlations has remained a challenge. Here we show a significant statistical relationship between variation in geochemical composition and prokaryotic community structure within deep-sea sediments. We obtained comprehensive geochemical data from two gravity cores near the hydrothermal vent field Loki’s Castle at the Arctic Mid-Ocean Ridge, in the Norwegian- Greenland Sea. Geochemical properties in the rift valley sediments exhibited strong centimeter-scale stratigraphic variability. Microbial populations were profiled by pyrosequencing from 15 sediment horizons (59,364 16S rRNA gene tags), quantitatively assessed by qPCR, and phylogenetically analyzed. Although the same taxa were generally present in all samples, their relative abundances varied substantially among horizons and fluctuated between Bacteria- and Archaea-dominated communities. By independently summarizing covariance structures of the relative abundance data and geochemical data, using principal components analysis, we found a significant correlation between changes in geochemical composition and changes in community structure. Differences in organic carbon and mineralogy shaped the relative abundance of microbial taxa. We used correlations to build hypotheses about energy metabolisms, particularly of the Deep Sea Archaeal Group, specific Deltaproteobacteria, and sediment lineages of potentially anaerobic Marine Group I Archaea. We demonstrate that total prokaryotic community structure can be directly correlated to geochemistry within these sediments, thus enhancing our understanding of biogeochemical cycling and our ability to predict metabolisms of uncultured microbes in deep-sea sediments