292 research outputs found
Introduction to Microservice API Patterns (MAP)
The Microservice API Patterns (MAP) language and supporting website premiered under this name at Microservices 2019. MAP distills proven, platform- and technology-independent solutions to recurring (micro-)service design and interface specification problems such as finding well-fitting service granularities, rightsizing message representations, and managing the evolution of APIs and their implementations. In this paper, we motivate the need for such a pattern language, outline the language organization and present two exemplary patterns describing alternative options for representing nested data. We also identify future research and development directions
Degrees of Countability: A Mereotopological Approach to the Mass/Count Distinction
Most formal semantic treatments of countability aim to account for a binary count/non-count distinction through the use of mereology, or part-structures. This paper discusses data from Welsh, which possesses three categories of grammatical number, distinguishing a collective/singulative class under which fall entity types such as 'collective aggregates' (swarming insects, vegetation) and 'granular aggregates' (sand). I show that standard mereological accounts turn out not to be sufficiently expressive to account for this broader typological data. I then argue that it is necessary to enrich mereology with connection relations that model ways in which the referents of nouns may come together, resulting in the more expressive mereotopology. I show that this extension leads to faithfully modeling the degrees of countability found in Welsh and overcomes well-known problems for classical mereological accounts, e.g., the "minimal parts" problem
Algorithms for Replica Placement in High-Availability Storage
A new model of causal failure is presented and used to solve a novel replica
placement problem in data centers. The model describes dependencies among
system components as a directed graph. A replica placement is defined as a
subset of vertices in such a graph. A criterion for optimizing replica
placements is formalized and explained. In this work, the optimization goal is
to avoid choosing placements in which a single failure event is likely to wipe
out multiple replicas. Using this criterion, a fast algorithm is given for the
scenario in which the dependency model is a tree. The main contribution of the
paper is an dynamic programming algorithm for placing
replicas on a tree with vertices. This algorithm exhibits the
interesting property that only two subproblems need to be recursively
considered at each stage. An greedy algorithm is also briefly
reported.Comment: 22 pages, 7 figures, 4 algorithm listing
Phase Transitions on Nonamenable Graphs
We survey known results about phase transitions in various models of
statistical physics when the underlying space is a nonamenable graph. Most
attention is devoted to transitive graphs and trees
Feynman categories and representation theory
We give a presentation of Feynman categories from a representation--theoretical viewpoint. Feynman categories are a special type of monoidal categories and their representations are monoidal functors. They can be viewed as a far reaching generalization of groups, algebras and modules. Taking a new algebraic approach, we provide more examples and more details for several key constructions. This leads to new applications and results. The text is intended to be a self--contained basis for a crossover of more elevated constructions and results in the fields of representation theory and Feynman categories, whose applications so far include number theory, geometry, topology and physics
Improved pathway reconstruction from RNA interference screens by exploiting off-target effects
Pathway reconstruction has proven to be an indispensable tool for analyzing the molecular mechanisms of signal transduction underlying cell function. Nested effects models (NEMs) are a class of probabilistic graphical models designed to reconstruct signalling pathways from high-dimensional observations resulting from perturbation experiments, such as RNA interference (RNAi). NEMs assume that the short interfering RNAs (siRNAs) designed to knockdown specific genes are always on-target. However, it has been shown that most siRNAs exhibit strong off-target effects, which further confound the data, resulting in unreliable reconstruction of networks by NEMs.; Here, we present an extension of NEMs called probabilistic combinatorial nested effects models (pc-NEMs), which capitalize on the ancillary siRNA off-target effects for network reconstruction from combinatorial gene knockdown data. Our model employs an adaptive simulated annealing search algorithm for simultaneous inference of network structure and error rates inherent to the data. Evaluation of pc-NEMs on simulated data with varying number of phenotypic effects and noise levels as well as real data demonstrates improved reconstruction compared to classical NEMs. Application to Bartonella henselae infection RNAi screening data yielded an eight node network largely in agreement with previous works, and revealed novel binary interactions of direct impact between established components.; The software used for the analysis is freely available as an R package at https://github.com/cbg-ethz/pcNEM.git.; Supplementary data are available at Bioinformatics online
Treewidth-aware Reductions of Normal ASP to SAT -- Is Normal ASP Harder than SAT after All?
Answer Set Programming (ASP) is a paradigm for modeling and solving problems
for knowledge representation and reasoning. There are plenty of results
dedicated to studying the hardness of (fragments of) ASP. So far, these studies
resulted in characterizations in terms of computational complexity as well as
in fine-grained insights presented in form of dichotomy-style results, lower
bounds when translating to other formalisms like propositional satisfiability
(SAT), and even detailed parameterized complexity landscapes. A generic
parameter in parameterized complexity originating from graph theory is the
so-called treewidth, which in a sense captures structural density of a program.
Recently, there was an increase in the number of treewidth-based solvers
related to SAT. While there are translations from (normal) ASP to SAT, no
reduction that preserves treewidth or at least keeps track of the treewidth
increase is known. In this paper we propose a novel reduction from normal ASP
to SAT that is aware of the treewidth, and guarantees that a slight increase of
treewidth is indeed sufficient. Further, we show a new result establishing
that, when considering treewidth, already the fragment of normal ASP is
slightly harder than SAT (under reasonable assumptions in computational
complexity). This also confirms that our reduction probably cannot be
significantly improved and that the slight increase of treewidth is
unavoidable. Finally, we present an empirical study of our novel reduction from
normal ASP to SAT, where we compare treewidth upper bounds that are obtained
via known decomposition heuristics. Overall, our reduction works better with
these heuristics than existing translations
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