25 papers · ranked by Valyu relevance
Sergio Antoy, Michael Hanus, Finn Teegen
Set functions are a feature of functional logic programming to encapsulate all results of a non-deterministic computation in a single data structure. Given a function f of a functional logic program written in Curry, we describe a technique to synthesize the definition of the set function of f. The definition produced…
Philip Kelly, M. H. van Emden
The relational data model requires a theory of relations in which tuples are not only many-sorted, but can also have indexes that are not necessarily numerical. In this paper we develop such a theory and define operations on relations that are adequate for database use. The operations are similar to those of Codd's…
Alexandr Savinov
We describe a new logical data model, called the conceptoriented model (COM). It uses mathematical functions as firstclass constructs for data representation and data processing as opposed to using exclusively sets in conventional set-oriented models. Functions and function composition are used as primary semantic…
Luciano Costa
Multisets are sets that allow repetition of elements, therefore accounting for their frequency of observation. As such, multisets pave the way to a number of interesting possibilities of both theoretical and applied nature. In the present work, after revising the main aspects of traditional sets, we introduce some of…
Alexandr Savinov
In this paper we argue that representing entity properties by tuple attributes, as evangelized in most set-oriented data models, is a controversial method conflicting with the principle of tuple immutability. As a principled solution to this problem of tuple immutability on one hand and the need to modify tuple…
Giacomo Ceoldo, Ernst C. Wit
The package hset for the R language contains an implementation of a S4 class for sets and multisets of numbers. The implementation, based on the hash table data structure from the package hash (Brown, 2019), allows for quick operations when the set is a dynamic object. An important example is when a set or a multiset…
Oleg V Kovalenko
In this paper we obtain sharp Ostrowski type inequalities for multidimensional sets of bounded variation and multivariate functions of bounded variation.
Berk Ekmekci, Charles E. McAnany, Cameron Mura, Francis Ouellette
Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware…
Jyoti Pal, Varshni Sharma, Arushi Khanna, Swati Saha
SET domain proteins mediate their effects through the methylation of specific lysine residues on target substrates, resulting in either the stimulation or repression of downstream processes. Initially identified as histone lysine methyltransferases, they are now known to target a wide-ranging conglomeration of…
Riyad N.H. Seervai, Rahul K. Jangid, Menuka Karki, Durga Nand Tripathi + 11 more
SET-domain-containing-2 (SETD2) was identified as the methyltransferase responsible for the histone 3 lysine 36 trimethyl (H3K36me3) mark of the histone code. Most recently, SETD2 has been shown to be a dual-function remodeler that regulates genome stability via methylation of dynamic microtubules during mitosis and…
Iztok Savnik, Mikita Akulich, Matjaž Krnc, Riste Škrekovski + 1 more
'Unil Yun'] Set containment operations form an important tool in various fields such as information retrieval, AI systems, object-relational databases, and Internet applications. In the paper, a set-trie data structure for storing sets is considered, along with the efficient algorithms for the corresponding set…
Rosari Hernandez-Vicens, Nomi Pernicone, Tamar Listovsky, Gabi Gerlitz
SETDB1 is a methyltransferase responsible for the methylation of histone H3-lysine-9, which is mainly related to heterochromatin formation. SETDB1 is overexpressed in various cancer types and is associated with an aggressive phenotype. In agreement with its activity, it mainly exhibits a nuclear localization; however…
Authors not listed
Hyperstructures and their hierarchical extensions—SuperHyperStructures—provide a versatile algebraic language for modeling multi-level and interdependent systems [1,2]. In materials and chemical sciences, structural descriptions naturally span a broad spectrum of characteristic length scales, commonly organized as…
Authors not listed
Hyperstructures and their hierarchical extensions [1]—SuperHyperStructures—provide a versatile formalism for modeling multi-layered and complex phenomena [2, 3]. A MicroStructure is a measurable mapping that assigns to each material point a single local state, representing attributes such as phase, crystal orientation…
Peiguang Wang, Weiwei Sun
We present a new comparison principle by introducing a notion of upper quasi-monotone nondecreasing and obtain the practical stability criteria for set valued differential equations in terms of two measures on time scales by using the vector Lyapunov function together with the new comparison principle.
Qiong Guo, Shanhui Liao, Sebastian Kwiatkowski, Weronika Tomaka + 6 more
SETD3 is a member of SET (Su(var)3-9, Enhancer of zeste, and Trithorax) domain protein superfamily and plays important roles in hypoxic pulmonary hypertension, muscle differentiation, and carcinogenesis. In a previous paper (Kwiatkowski et al. 2018), we have identified SETD3 as the actin-specific methyltransferase that…
Authors not listed
Curried functions provide a systematic way of transforming multi-argument functions into nested singleargument functions. This transformation allows partial application and supports many central principles of functional programming. Their extension, called curried 𝑘-ary functions, naturally generalizes the familiar…
Hend Dawood, Nefertiti Megahed, Nicholas Higham
Acquiring reliable knowledge amidst uncertainty is a topical issue of modern science. Interval mathematics has proved to be of central importance in coping with uncertainty and imprecision. Algorithmic differentiation, being superior to both numeric and symbolic differentiation, is nowadays one of the most celebrated…
Garvin Melles
In this paper we define a notion of Turing computability for class functions, i.e., functions that operate on arbitrary sets. We generalize the notion of a Turing machine to the set Turing machine. Set Turing machines operate on a class size tape. We represent sets by placing marks in the cells of the set Turing…
Authors not listed
This paper develops a unified, geometry-aware framework for representing molecules and their higher-order organization. We formalize 𝑑-dimensional molecular structures, hyperstructures, and superhyperstructures by combining labeled (hyper)graphs with Euclidean embeddings and rank-aware operations on iterated power…
Michael Hutcheon, Andrew Teale
Algorithms are presented for performing a topological analysis of an arbitrary function, evaluated on an arbitrary grid of points. These algorithms work strictly by post-processing the data and require no additional function evaluations. This is achieved by connecting the grid points with a neighbourhood graph…
Hemant Kumar Nashine, Reza Arab, Ravi P Agarwal, Manuel De la Sen
In the present study, we work on the problem of the existence of positive solutions of fractional integral equations by means of measures of noncompactness in association with Darbo’s fixed point theorem. To achieve the goal, we first establish new fixed point theorems using a new contractive condition of the measure…
Charley M. Wu, Eric Schulz, Samuel J. Gershman
From social networks to public transportation, graph structures are a ubiquitous feature of life. Yet little is known about how humans learn functions on graphs, where relationships are defined by the connectivity structure. We adapt a Bayesian framework for function learning to graph structures, and propose that…
Eric Schulz, Joshua B. Tenenbaum, David Duvenaud, Maarten Speekenbrink + 1 more
How do people recognize and learn about complex functional structure? Taking inspiration from other areas of cognitive science, we propose that this is achieved by harnessing compositionality: complex structure is decomposed into simpler building blocks. We formalize this idea within the framework of Bayesian…
Lloyd Allison
Compared to functions in mathematics, functions in programming languages seem to be under class-ified. Functional programming languages based on the lambda calculus famously treat functions as first-class values. Object-oriented languages have adopted "lambdas", notably for call-back routines in event-based…