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This article examines the similarities and differences between privations and accidental forms in the philosophy of Thomas Aquinas. It argues that both can be understood through the existential quantifier, but Aquinas emphasizes the importance of distinguishing their modes of existence. Privations, such as blindness, are considered beings because they are involved in true propositions, even though they lack essence and do not exist in reality. Accidental forms, on the other hand, exist in individual substances. The article suggests that a pluralist approach to existence is necessary to fully understand Aquinas's philosophy regarding privations and accidental forms. [Extracted from the article]

The article presents an interview with Dr. María José Frápolli, a philosopher and professor of logic and philosophy of science. Dr. Frápolli reflects on her career and her interest in understanding what kind of animal we are and how different philosophical positions help us understand ourselves. She also talks about her commitment to the cause of female philosophers and how the ethical evolution of feminisms is influencing the development of philosophy. The article highlights the importance of Dr. Frápolli's academic production in the fields of logic and semantics research. In this interview, Dr. María José Frápolli discusses the distinction between logic and calculations, stating that calculations are instruments for representing and evaluating inferences. She points out that classical logic calculations derive from Frege's proposal in Conceptography and are designed for the foundation of arithmetic. Additionally, she mentions that non-classical logics arise due to the need to represent inferences in different areas of discourse and that each proposal of non-classical logic can vary according to its purposes of representation and evaluation. Finally, she comments that it is possible to classify existing logics in different ways, but she does not see scientific or philosophical advantages in doing so. She also highlights Susan Haack's distinction between extensions and divergent logics, considering it intuitive and showing the complexity of inferential relationships between propositions. In this interview, Dr. María José Frápolli talks about the changes in research objectives in logic from the early 20th century to the present. She mentions that there has been a greater interest in representing semantic features of natural language and pragmatic aspects. She also highlights the development of computer theory and artificial intelligence. Regarding logical pluralism, Dr. Frápolli mentions that she would not bet on any particular calculation and that each one has its own presuppositions and purposes. Additionally, she points out that logic has not been very useful as an applied discipline in other scientific areas. The text presents an interview with Dr. María José Frápolli about the application of logic in different disciplines. It is mentioned that fuzzy logics and computer theory are exceptions in their application. Dr. Frápolli mentions that logic has a promising field of application in proof theory, computing, and artificial intelligence. The general usefulness of logic in the current world is also discussed, and its role in the development of critical thinking and reasoning is highlighted. As for branches of logic with promising applications, those related to programming languages and artificial intelligence are mentioned as the most prominent. [Extracted from the article]

Copyright of Adab Al-Kufa is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cogency: Journal of Reasoning & Argumentation is the property of Cogency Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Estudios Filosóficos is the property of Estudios Filosoficos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tasks and objects are two predominant ways of specifying distributed problems where processes should compute outputs based on their inputs. Roughly speaking, a task specifies, for each set of processes and each possible assignment of input values, their valid outputs. In contrast, an object is defined by a sequential specification. Also, an object can be invoked multiple times by each process, while a task is a one-shot problem. Each one requires its own implementation notion, stating when an execution satisfies the specification. For objects, linearizability is commonly used, while tasks implementation notions are less explored. The article introduces the notion of interval-sequential object, and the corresponding implementation notion of interval-linearizability, to encompass many problems that have no sequential specification as objects. It is shown that interval-sequential specifications are local, namely, one can consider interval-linearizable object implementations in isolation and compose them for free, without sacrificing interval-linearizability of the whole system. The article also introduces the notion of refined tasks and its corresponding satisfiability notion. In contrast to a task, a refined task can be invoked multiple times by each process. Also, objects that cannot be defined using tasks can be defined using refined tasks. In fact, a main result of the article is that interval-sequential objects and refined tasks have the same expressive power and both are complete in the sense that they are able to specify any prefix-closed set of well-formed executions. Interval-linearizability and refined tasks go beyond unifying objects and tasks; they shed new light on both of them. On the one hand, interval-linearizability brings to task the following benefits: an explicit operational semantics, a more precise implementation notion, a notion of state, and a locality property. On the other hand, refined tasks open new possibilities of applying topological techniques to objects. [ABSTRACT FROM AUTHOR]

A metric tree embedding of expected stretch α ≥ 1 maps a weighted n-node graph G = (V, E, ω) to a weighted tree T = (VT, ET , ωT) with V ⊑ VT such that, for all v,w ∈ V, dist(v, w, G) ≤ dist(v, w, T), and E[dist(v, w, T)] ≤ α dist(v, w, G). Such embeddings are highly useful for designing fast approximation algorithms as many hard problems are easy to solve on tree instances. However, to date, the best parallel polylog n)-depth algorithm that achieves an asymptotically optimal expected stretch of α ∈ O(log n) requires Ω (n2) work and a metric as input. In this article, we show how to achieve the same guarantees using polylog n depth and Õ(m1+ϵ) work, where m = |E| and ϵ > 0 is an arbitrarily small constant. Moreover, one may further reduce the work to Õ(m + n1+ε) at the expense of increasing the expected stretch to O(ε−1 log n). Our main tool in deriving these parallel algorithms is an algebraic characterization of a generalization of the classic Moore-Bellman-Ford algorithm. We consider this framework, which subsumes a variety of previous "Moore-Bellman-Ford-like" algorithms, to be of independent interest and discuss it in depth. In our tree embedding algorithm, we leverage it to provide efficient query access to an approximate metric that allows sampling the tree using polylog n depth and Õ(m) work. We illustrate the generality and versatility of our techniques by various examples and a number of additional results. Specifically, we (1) improve the state of the art for determining metric tree embeddings in the Congest model, (2) determine a (1 + εˆ)-approximate metric regarding the distances in a graph G in polylogarithmic depth and Õ(n(m+n1 + ε )) work, and (3) improve upon the state of the art regarding the k-median and the buy-at-bulk network design problems. [ABSTRACT FROM AUTHOR]

The goal of this article is to identify fundamental limitations on how efficiently algorithms implemented on platforms such as MapReduce and Hadoop can compute the central problems in motivating application domains, such as graph connectivity problems. We introduce an abstract model of massively parallel computation, where essentially the only restrictions are that the "fan-in" of each machine is limited to s bits, where s is smaller than the input size n, and that computation proceeds in synchronized rounds, with no communication between different machines within a round. Lower bounds on the round complexity of a problem in this model apply to every computing platform that shares the most basic design principles of MapReduce-type systems. We prove that computations in our model that use few rounds can be represented as low-degree polynomials over the reals. This connection allows us to translate a lower bound on the (approximate) polynomial degree of a Boolean function to a lower bound on the round complexity of every (randomized) massively parallel computation of that function. These lower bounds apply even in the "unbounded width" version of our model, where the number of machines can be arbitrarily large. As one example of our general results, computing any nontrivial monotone graph property—such as connectivity—requires a super-constant number of rounds when every machine receives only a subpolynomial (in n) number of input bits s. Finally, we prove that, in two senses, our lower bounds are the best one could hope for. For the unbounded-width model, we prove a matching upper bound. Restricting to a polynomial number of machines, we show that asymptotically better lower bounds would separate P from NC1. [ABSTRACT FROM AUTHOR]

We prove that any non-adaptive algorithm that tests whether an unknown Boolean function f:{0,1}n→ {0,1} is a k-junta or ∊-far from every k-junta must make Ω˜(k3/2) / ∊) many queries for a wide range of parameters k and ∊. Our result dramatically improves previous lower bounds and is essentially optimal since there is a known non-adaptive junta tester which makes Ω˜(k3/2) / ∊ queries. Combined with the known existence of an adaptive tester which makes O(klog k + k /∊) queries, our result shows that adaptivity enables polynomial savings in query complexity for junta testing. [ABSTRACT FROM AUTHOR]

Dedekind's methodology, in his classic booklet on the foundations of arithmetic, has been the topic of some debate. While some authors make it closely analogue to Hilbert's early axiomatics, others emphasize its idiosyncratic features, most importantly the fact that no axioms are stated and its careful deductive structure apparently rests on definitions alone. In particular, the so-called Dedekind "axioms" of arithmetic are presented by him as "characteristic conditions" in the definition of the complex concept of a simply infinite system. Making sense of Dedekind's method may be dependent on an analysis of the classical model of deductive science, as presented by authors from the eighteenth and early nineteenth centuries. Studying the modern reconstructions of Euclidean geometry, we show that they did not presuppose deductive independence of the axioms from the definitions. Authors like Wolff elaborated a mathematics based on definitions, and the Wolffian model of deductive science shows significant coincidences with Dedekind's method, despite the great differences in content and approach. Wolff had a conception of definitions as genetic, which bears some similarities with Kant's idea of synthetic definitions: they are understood as positing the content of mathematical concepts and introducing thought objects (Gedankendinge) that are the objects of mathematics. The emphasis on the spontaneity of the understanding, which can be found in this philosophical tradition, can also be fruitfully related with Dedekind's idea of the "free creation" of mathematical objects. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of a hitherto barely known conceptual problem in the foundations of arithmetic. An unknown type of number, so-called complex numbers, first emerged in 18th century France and became connected with the claim of non-commutativity of their multiplication. These first French practitioners are here analysed, along with examination of the impact of the introduction of the metric decimal system. International dissemination of the notion is then analysed, in particular in the case of Brazil. The paper concludes by looking at the mathematical foundations of multiplying (physical) quantities. [ABSTRACT FROM AUTHOR]

Hurwitz's Lectures on the Number Theory of Quaternions is a translation and commentary on Adolf Hurwitz's pioneering work on quaternion number theory. The book aims to make Hurwitz's lectures accessible to a wide audience and includes a concise introduction to algebraic number theory. Hurwitz's lectures establish the foundations of quaternion arithmetic, defining integer quaternions and exploring their properties. The book also provides historical context and a translation of Hurwitz's paper on the composition of quadratic forms. It will be of interest to mathematicians and students interested in the historical development of algebraic number theory. [Extracted from the article]

The aim of this article is to examine Frege's view of the context principle in his mature philosophical doctrine. Here, the author argues that the context principle is embodied in the contextual explanation of value-ranges presented in Basic Laws of Arithmetic. The contextual explanation of value-ranges plays essentially the same role as the context principle in The Foundations of Arithmetic. It is supposed to show how a reference to natural numbers is possible. Moreover, the author argues against the view that the context principle should be separated from the recarving thesis. This aspect of Frege's view leads the author to the rejection of the purely referential view of the context principle, which is fairly widely accepted in the current literature. [ABSTRACT FROM AUTHOR]

But the significance of tokens and notations exceeds this, as they enabled numbers to be separated from the process of counting.[140] Separating numbers from the items they counted by means of material proxies was at least as significant as separating the representation of quantity and commodity, for it helped influence numbers toward being conceived as objects more defined by their relations to one another than the things they enumerated, influencing numbers toward becoming a relational system. A particular number is not identical with any collection of terms having that number: the number 3 is not identical with the trio consisting of Brown, Jones, and Robinson. However, Sumerian number-words below I sixty i were quinary-decimal-vigesimal in structure.[137] As a result, sexagesimal factorability may have been used to express numbers higher than I sixty i , with numbers lower than I sixty i expressed decimally, analogous to way Hawaiian numbers were traditionally expressed (see Table 1). 79 Chrisomalis has compellingly argued against the idea that Mesopotamian peoples were particularly incompetent or concrete in their conceptualization of numbers: "If ... polyvalence and context-dependence imply an absence of abstract number concepts, then paradoxically, the quasi-literate Uruk accountants would be less numerate than the average Sumerian who did not use texts, only number words" (Chrisomalis, "Evaluating Ancient Numeracy" [[26]]: 4); "the accountants and scribes who used [tokens and numbers] were able to manage complex administrative tasks, and it is implausible that they did not recognize that '8 sheep' and '8 bushels of grain' had something in common" (Chrisomalis, "Cognitive and Cultural Foundations" [[25]]: 502); and "in order for these context-dependent numerals to represent a stage of "archaic arithmetic" in the evolution of numeration, ... we would expect similar systems to be present in other civilizations. [Extracted from the article]

Arithmetic is the study of numbers, their properties and relationships. Calculations related to the centralization of agriculture and counting had a practical impact on the formation of arithmetic. The first reliable information related to arithmetic was found in the historical monuments of Babylon and Ancient Egypt, dating back to the III-II millennia BC. In the Middle Ages, the sphere of trade and the conduct of approximate calculations were the main branches of the application of arithmetic. Initially, arithmetic developed in India and Muslim countries, and later began to spread in Western Europe. In modern times, marine astronomy, mechanics and complex commercial calculations posed new challenges and requirements, thereby contributing to new rounds in the development of astronomy. The article deals with the issues of comprehending the concept of number and its content in the framework of mathematical discourses of the 19th century. This issue is initially considered in a historical perspective, then the works of such mathematicians and philosophers as Richard Dedekind, Georg Cantor, Giuseppe Peano and the logic Gottlob Frege are analyzed. In the 1870s, the discourse on the foundations of arithmetic was updated. For the approval of mathematics as a consistent and correct science, the importance of determining the meaning of the concept of number, which is considered the basis of arithmetic, is noted. The article discusses questions about the essence and content of the concept of number. [ABSTRACT FROM AUTHOR]

Lock-free concurrent algorithms guarantee that some concurrent operation will always make progress in a finite number of steps. Yet programmers prefer to treat concurrent code as if it were wait-free, guaranteeing that all operations always make progress. Unfortunately, designing wait-free algorithms is generally a very complex task, and the resulting algorithms are not always efficient. Although obtaining efficient wait-free algorithms has been a long-time goal for the theory community, most nonblocking commercial code is only lock-free. This article suggests a simple solution to this problem.We show that for a large class of lock-free algorithms, under scheduling conditions that approximate those found in commercial hardware architectures, lock-free algorithms behave as if they are wait-free. In other words, programmers can continue to design simple lock-free algorithms instead of complex wait-free ones, and in practice, they will get wait-free progress. Our main contribution is a new way of analyzing a general class of lock-free algorithms under a stochastic scheduler. Our analysis relates the individual performance of processes to the global performance of the system using Markov chain lifting between a complex per-process chain and a simpler system progress chain. We show that lock-free algorithms are not only wait-free with probability 1 but that in fact a general subset of lock-free algorithms can be closely bounded in terms of the average number of steps required until an operation completes. To the best of our knowledge, this is the first attempt to analyze progress conditions, typically stated in relation to a worst-case adversary, in a stochastic model capturing their expected asymptotic behavior. [ABSTRACT FROM AUTHOR]

Let M =(E, I) be a matroid and let S = {S1, . . . , St} be a family of subsets of E of size p. A subfamily ŝ ⊆ S is q-representative for S if for every set Y ⊆ E of size at most q, if there is a set X ∊ S disjoint from Y with X ∪ Y ∊I, then there is a set X ∪ Ŝ disjoint from Y with X ∪ Y ∊ I. By the classic result of Bollob ás, in a uniform matroid, every family of sets of size p has a q-representative family with at most ( p+q p ) sets. In his famous "two families theorem" from 1977, Lovász proved that the same bound also holds for any matroid representable over a field F. We give an efficient construction of a q-representative family of size at most ( p+q p ) in time bounded by a polynomial in ( p+q p ), t, and the time required for field operations. We demonstrate how the efficient construction of representative families can be a powerful tool for designing single-exponential parameterized and exact exponential time algorithms. The applications of our approach include the following: -In the LONG DIRECTED CYCLE problem, the input is a directed n-vertex graph G and the positive integer k. The task is to find a directed cycle of length at least k in G, if such a cycle exists. As a consequence of our 6.75k+o(k)nO(1) time algorithm, we have that a directed cycle of length at least log n, if such a cycle exists, can be found in polynomial time. -In the MINIMUM EQUIVALENT GRAPH (MEG) problem, we are seeking a spanning subdigraph D' of a given n-vertex digraph D with as few arcs as possible in which the reachability relation is the same as in the original digraph D. -We provide an alternative proof of the recent results for algorithms on graphs of bounded treewidth showing that many "connectivity" problems such as HAMILTONIAN CYCLE or STEINER TREE can be solved in time 2O(t)n on n-vertex graphs of treewidth at most t. For the special case of uniform matroids on nelements, we give a faster algorithm to compute a representative family. We use this algorithm to provide the fastest known deterministic parameterized algorithms for k- PATH, k-TREE, and, more generally, k-SUBGRAPH ISOMORPHISM, where the k-vertex pattern graph is of constant treewidth. [ABSTRACT FROM AUTHOR]

In his logical foundation of arithmetic, Frege faced the problem that the semantic interpretation of his system does not determine the reference of the abstract terms completely. The contextual definition of number, for instance, does not decide whether the number 5 is identical to Julius Caesar. In a late writing, Quine claimed that the indeterminacy of reference established by Frege's Caesar problem is a special case of the indeterminacy established by his proxy-function argument. The present paper aims to show that Frege's Caesar problem does not really support the conclusions that Quine draws from the proxy-function argument. On the contrary, it reveals that Quine's argument is a non sequitur: it does not establish that there are alternative interpretations of our terms that are equally correct, but only that these terms are ambiguous. The latter kind of referential indeterminacy implies that almost all sentences of our overall theory of the world are either false or neither true nor false, because they contain definite descriptions whose uniqueness presupposition is not fulfilled. The proxy-function argument must therefore be regarded as a reductio ad absurdum of Quine's behaviorist premise that the reference of terms is determined only by our linguistic behavior. [ABSTRACT FROM AUTHOR]

Several conventional clustering methods use the squared L2-norm as the dissimilarity. The squared L2-norm is calculated from only the object coordinates and obtains a linear cluster boundary. To extract meaningful cluster partitions from a set of massive objects, it is necessary to obtain cluster partitions that consisting of complex cluster boundaries. In this study, a JS-divergence-based k-medoids (JSKMdd) is proposed. In the proposed method, JS-divergence, which is calculated from the object distribution, is considered as the dissimilarity. The object distribution is estimated from kernel density estimation to calculate the dissimilarity based on both the object coordinates and their neighbors. Numerical experiments were conducted using five artificial datasets to verify the effectiveness of the proposed method. In the numerical experiments, the proposed method was compared with the k-means clustering, k-medoids clustering, and spectral clustering. The results show that the proposed method yields better results in terms of clustering performance than other conventional methods. [ABSTRACT FROM AUTHOR]

This paper introduces an improved algorithm for texture-less object detection and pose estimation in industrial scenes. In the template training stage, a multi-scale template training method is proposed to improve the sensitivity of LineMOD to template depth. When this method performs template matching, the test image is first divided into several regions, and then training templates with similar depth are selected according to the depth of each test image region. In this way, without traversing all the templates, the depth of the template used by the algorithm during template matching is kept close to the depth of the target object, which improves the speed of the algorithm while ensuring that the accuracy of recognition will not decrease. In addition, this paper also proposes a method called coarse positioning of objects. The method avoids a lot of useless matching operations, and further improves the speed of the algorithm. The experimental results show that the improved LineMOD algorithm in this paper can effectively solve the algorithm's template depth sensitivity problem. [ABSTRACT FROM AUTHOR]

In 1907 Einstein had the insight that bodies in free fall do not "feel" their own weight. This has been formalized in what is called "the principle of equivalence." The principle motivated a critical analysis of the Newtonian and special-relativistic concepts of inertia, and it was indispensable to Einstein's development of his theory of gravitation. A great deal has been written about the principle. Nearly all of this work has focused on the content of the principle and whether it has any content in Einsteinian gravitation, but more remains to be said about its methodological role in the development of the theory. I argue that the principle should be understood as a kind of foundational principle known as a criterion of identity. This work extends and substantiates a recent account of the notion of a criterion of identity by William Demopoulos. Demopoulos argues that the notion can be employed more widely than in the foundations of arithmetic and that we see this in the development of physical theories, in particular space–time theories. This new account forms the basis of a general framework for applying a number of mathematical theories and for distinguishing between applied mathematical theories that are and are not empirically constrained. [ABSTRACT FROM AUTHOR]

In the summer of 2020 a case of serial plagiarism was brought to our attention, first by an outside investigator, on 6 and 7 July, and then, apparently independently, by the perpetrator herself, on 20 July. Since these phenomena meet the strictest definition of plagiarism, after verifying these findings, we immediately contacted Brill to begin an internal investigation and asked that the initial submitted versions of all of her I Vivarium i articles be put through the automated plagiarism detection software that they use. [Extracted from the article]

One of the more distinctive features of Bob Hale and Crispin Wright's neologicism about arithmetic is their invocation of Frege's Constraint – roughly, the requirement that the core empirical applications for a class of numbers be "built directly into" their formal characterization. In particular, they maintain that, if adopted, Frege's Constraint adjudicates in favor of their preferred foundation – Hume's Principle – and against alternatives, such as the Dedekind‐Peano axioms. In what follows we establish two main claims. First, we show that, if sound, Hale and Wright's arguments for Frege's Constraint at most establish a version on which the relevant application of the naturals is transitive counting – roughly, the counting procedure by which numerals are used to answer "how many"‐questions. Second, we show that this version of Frege's Constraint fails to adjudicate in favor of Hume's Principle. If this is the version of Frege's Constraint that a foundation for arithmetic must respect, then Hume's Principle no more – and no less – meets the requirement than the Dedekind‐Peano axioms do. [ABSTRACT FROM AUTHOR]

A method is proposed to efficiently obtain free energy differences. In the present algorithm, free energy calculations proceed by the realization of an energy difference space random walk. Thereby, this algorithm can greatly improve the sampling of the regions in phase space where target states overlap. [ABSTRACT FROM AUTHOR]

We present a spin-adapted density matrix renormalization group (DMRG) algorithm designed to target spin and spatial symmetry states that can be difficult to obtain while using a non-spin-adapted algorithm. The algorithmic modifications that have to be introduced into the usual density matrix renormalization group scheme in order to spin adapt it are discussed, and it is demonstrated that the introduced modifications do not change the overall scaling of the method. The new approach is tested on HNCO, a model system, that has a singlet-triplet curve crossing between states of the same symmetry. The advantages of the spin-adapted DMRG scheme are discussed, and it is concluded that the spin-adapted DMRG method converges better in almost all cases and gives more parallel curves to the full configuration interaction result than the non-spin-adapted method. It is shown that the spin-adapted DMRG energies can be lower than the ones obtained from the non-spin-adapted scheme. Such a counterintuitive result is explained by noting that the spin-adapted method is not a special case of the non-spin-adapted one; consequently, the spin-adapted result is not an upper bound for the non-spin-adapted energy. [ABSTRACT FROM AUTHOR]

We first introduce Abstract DPLL, a rule-based formulation of the Davis--Putnam--Logemann--Loveland (DPLL) procedure for propositional satisfiability. This abstract framework allows one to cleanly express practical DPLL algorithms and to formally reason about them in a simple way. Its properties, such as soundness, completeness or termination, immediately carry over to the modern DPLL implementations with features such as backjumping or clause learning. We then extend the framework to Satisfiability Modulo background Theories (SMT) and use it to model several variants of the so-called lazy approach for SMT. In particular, we use it to introduce a few variants of a new, efficient and modular approach for SMT based on a general DPLL(X) engine, whose parameter X can be instantiated with a specialized solver SolverT for a given theory T , thus producing a DPLL(T) system. We describe the high-level design of DPLL(X) and its cooperation with SolverT, discuss the role of theory propagation, and describe different DPLL(T) strategies for some theories arising in industrial applications. Our extensive experimental evidence, summarized in this article, shows that DPLL(T) systems can significantly outperform the other state-of-the-art tools, frequently even in orders of magnitude, and have better scaling properties. [ABSTRACT FROM AUTHOR]

The new algorithm presented here allows, for the first time, the determination of the optimal geometrical distortions that an acceptor molecule in the triplet-triplet energy-transfer process undergoes, as well as the dependence of the activation energy of the process on the triplet energy difference of donor and acceptor molecules. This algorithm makes use of the complete potential-energy surfaces (singlet and triplet states), and contrasts with the first-order approximation already published [L. M. Frutos, O. Castaño, J. L. Andrés, M. Merchán, and A. U. Acuña, J. Chem. Phys. 120, 1208 (2004)] in which an expansion of the potential-energy surfaces was used. This algorithm is gradient based and finds the best trajectory for the acceptor molecule, starting from S0 ground-state equilibrium geometry, to achieve the maximum variation of the singlet-triplet energy gap with the minimum energy of activation on S0. Therefore, the algorithm allows the determination of a “reaction path” for the triplet-triplet energy-transfer processes. Also, the algorithm could also serve eventually to find minimum-energy crossing (singlet-triplet) points on the potential-energy surface, which can play an important role in the intersystem crossing process for the acceptor molecules to recover their initial capacity as acceptors. Also addressed is the misleading use of minimum-energy paths in T1 to describe the energy-transfer process by comparing these results with those obtained using the new algorithm. The implementation of the algorithm is illustrated with different potential-energy surface models and it is discussed in the frame of nonvertical behavior. [ABSTRACT FROM AUTHOR]

Within the resolution of the identity (RI) method, the convergence of the Hartree–Fock (HF) total molecular energy and the multipole moments in the course of the combined regular expansion of the molecular and auxiliary (RI) basis sets is studied. Dunning’s cc-pVXZ series is used for both the molecular and the RI basis sets. The results show the calculated quantities converge to the HF limit when both the molecular and the RI basis sets are expanded from correlation-consistent polarized valence double zeta to correlation-consistent polarized valence sextuple zeta. Combinations of molecular/RI basis sets sufficient for convergence of the total energy and of the multipole moments at various accuracy levels have been determined. A measure of the RI basis set incompleteness is suggested and discussed. As it is significantly faster than the standard HF algorithm for small and midsize molecules, the RI-HF method, together with appropriate expanding series of both molecular and RI basis sets, provide an efficient tool to estimate and control the error of the Hartree–Fock calculations due to the finite basis set. [ABSTRACT FROM AUTHOR]

Using the cooperative motion algorithm, the effect of salt valence zs and of the reduced temperature T* on a single polyelectrolyte chain as well as on counterions and salt ions themselves is studied. The calculations show that both parameters strongly influence the polymer, causing it to undergo conformational changes. For a given number of the added salt cations (anions) ns and temperature T*, the chain takes more and more compact forms as zs increases (zs>0). For fixed zs, in turn, the polymer size reduces sharply as T* drops down from intermediate to low. For high T* configurational the entropy dominates the chain statistics and the mean-square radius of gyration 〈s2〉1/2(T*,ns,zs) approaches its athermal value. The low-temperature polymer collapse is also accompanied by a drop in the effective mean charge per monomer q*(T*,ns,zs) (condensation of ions onto the chain) and the total inner energy e*(T*,ns,zs). Furthermore, the local structure of the system is analyzed by means of pair-correlation functions gab(r,T*,ns,zs). At lower T* they possess sharp local maxima at small interparticle distances r that disappear as T* grows. The former observation indicates that at lower T* the ions tend to group themselves close to each other. In particular, it is concluded that the condensation is dominated by the multivalent salt ions carrying charges of opposite sign to that of monomers. [ABSTRACT FROM AUTHOR]

This paper formulates a hybrid Monte Carlo implementation of the Fourier path integral (FPI-HMC) approach with partial averaging. Such a hybrid Monte Carlo approach allows one to generate collective moves through configuration space using molecular dynamics while retaining the computational advantages associated with the Fourier path integral Monte Carlo method. In comparison with the earlier Metropolis Monte Carlo implementations of the FPI algorithm, the present HMC method is shown to be significantly more efficient for quantum Lennard-Jones solids and suggests that such algorithms may prove useful for efficient simulations of a range of atomic and molecular systems. [ABSTRACT FROM AUTHOR]

A series of molecular dynamics (MD) simulations of nonlinear molecules has been performed to test the efficiency of newly introduced semianalytical second-order symplectic time-reversible MD integrators that combine MD and the standard theory of molecular vibrations. The simulation results indicate that for the same level of accuracy, the new algorithms allow significantly longer integration time steps than the standard second-order symplectic leap-frog Verlet method. Since the computation cost per integration step using new MD integrators with longer time steps is approximately the same as for the standard method, a significant speed-up in MD simulation is achieved. [ABSTRACT FROM AUTHOR]

We study novel combinatorial properties of graphs that allow us to devise a completely new approach to dynamic all pairs shortest paths problems. Our approach yields a fully dynamic algorithm for general directed graphs with non-negative real-valued edge weights that supports any sequence of operations in O(n² log³ n) amortized time per update and unit worst-case time per distance query, where n is the number of vertices. We can also report shortest paths in optimal worst-case time. These bounds improve substantially over previous results and solve a long-standing open problem. Our algorithm is deterministic, uses simple data structures, and appears to be very fast in practice. [ABSTRACT FROM AUTHOR]

Clock trees can be constructed based on static arrival time constraints or dynamic implied skew constraints. Dynamic implied skew constraints allow the full timing margins to be utilized. However, the dynamic skew constraints require a high run-time complexity to be evaluated. In contrast, static arrival time constraints are more restrictive but can be evaluated in constant time. Consequently, there is a tradeoff between timing margin utilization and run-time. In this paper, a scalable clock tree synthesis (CTS) framework is proposed for the construction of low-cost useful skew trees (USTs) with high timing quality. The scalability is based on combining the use of arrival time constraints with virtual minimum and maximum delay offsets, which facilitates that a pair of smaller subtrees can be joined into a larger subtree in constant time. The ability to quickly join subtrees is leveraged to perform a high degree of solution space exploration, which translates into the construction of USTs with low-cost. In particular, clock trees with various routing tree topologies, buffer tree topologies, buffer sizes, and stem wire lengths are explored. Moreover, the arrival time constraints are specified with the objective of being the least restrictive to reduce cost. Furthermore, the constraints are respecified throughout the tree construction process using a slack graph (SG) to expose additional timing margins. The high timing quality is obtained by seamlessly integrating arbitrary timing models using the SG. Finally, the proposed CTS framework is integrated with a clock tree optimization framework to demonstrate that the constructed USTs are capable of meeting timing constraints under the influence of on-chip variations. [ABSTRACT FROM AUTHOR]

A new methodology is presented for 3-D automated mapping of joints that are exposed primarily as traces in a rock face as opposed to planar facets. The method identifies 3-D points in a photogrammetry or a LiDAR derived point cloud that corresponds to the traces of the joints as observed in image data. First, the 2-D trace texture is extracted from image data using a hybrid global and local threshold method and integrating a series of image-processing algorithms. Second, data matching links the pixel locations corresponding to the identified traces in an image to the 3-D coordinates in the point cloud. This matching is accomplished by a coordinate transformation between the image coordinates and point cloud coordinates. Finally, a 3-D discontinuity trace map is acquired by analysing the 3-D spatial features of the traces. A case study of a rock slope along a highway is presented using the proposed method. The results demonstrate that the fusion of image data and point cloud data improves the mapping of discontinuities that primarily appear as traces in outcrops versus that achieved by existing methods that rely only on point cloud data. [ABSTRACT FROM AUTHOR]

Abstract We consider partial torsion fields (fields generated by a root of a division polynomial) for elliptic curves. By analysing the reduction properties of elliptic curves, and applying the Montes Algorithm, we obtain information about the ring of integers. In particular, for the partial 3-torsion fields for a certain one-parameter family of non-CM elliptic curves, we describe a power basis. As a result, we show that the one-parameter family of quartic S 4 fields given by T 4 − 6 T 2 − α T − 3 for α ∈ Z such that α ± 8 are squarefree, are monogenic. [ABSTRACT FROM AUTHOR]

Abstract Backdoors measure the distance to tractable fragments and have become an important tool to find fixed-parameter tractable (fpt) algorithms for hard problems in AI and beyond. Despite their success, backdoors have not been used for planning, a central problem in AI that has a high computational complexity. In this work, we introduce two notions of backdoors building upon the causal graph. We analyze the complexity of finding a small backdoor (detection) and using the backdoor to solve the problem (evaluation) in the light of planning with (un)bounded plan length/domain of the variables. For each setting we present either an fpt-result or rule out the existence thereof by showing parameterized intractability. For several interesting cases we achieve the most desirable outcome: detection and evaluation are fpt. In addition, we explore the power of polynomial preprocessing for all fpt-results, i.e., we investigate whether polynomial kernels exist. We show that for the detection problems, polynomial kernels exist whereas we rule out the existence of polynomial kernels for the evaluation problems. [ABSTRACT FROM AUTHOR]

Whole number arithmetic is the foundation of higher mathematics and a core part of elementary mathematics. Awareness of pattern and underlying problem structure promote the learning of whole number arithmetic. A growing consensus has emerged on the necessity to provide students with the opportunity to engage in algebraic reasoning earlier in their education. In fact, the U.S. National Council of Teachers of Mathematics curriculum standards and the nationwide mathematics reform call for algebra readiness in elementary mathematical learning. The purpose of this study was to evaluate the effect of Conceptual Model-based Problem Solving (Xin, Conceptual model-based problem solving: Teach students with learning difficulties to solve math problems. The Netherlands: Sense Publishers, 2012) intervention program, with the Singapore bar model method (Kaur, The model method—A tool for representing and visualising relationships, In: Conference proceedings of ICMI study 23: Primary mathematics study on whole numbers, pp 448–455, 2015) serving as the bridge towards symbolic mathematical model equations, on enhancing additive word problem-solving performance of elementary students who are struggling in mathematics. Findings from this study indicate the promise of this program. Through representing a range of additive word problem situations in one cohesive mathematical model equation, students are prepared for generalized problem-solving skills. [ABSTRACT FROM AUTHOR]

Abstract Pairwise algorithms refer to a learning problem with loss functions depending on pairs of examples. There has been remarkable work on analyzing their generalization properties in batch and online settings such as algorithmic stabilities, robustness or regularization. This paper is concerned with distributed pairwise algorithms for dealing with big data, based on a divide-and-conquer strategy. We show that the global estimator of the distributed pairwise algorithm is as good as that of the classical algorithm processing the whole data on a single machine. We present the optimal convergence rate for the distributed pairwise algorithm and provide a theoretical upper bound for the number of local machines under which the optimal rate is retained. Our analysis is achieved by the integral operator decomposition and distributed U-statistics. [ABSTRACT FROM AUTHOR]

Abstract The propagation of information in the network is a complex dynamic process. Establishing an accurate information propagation model around common social factors benefits a lot from its evolution simulation for identifying the valuable information and regulating public opinions. In this paper, we propose Opportunity, Social Trust and Game Choice Motivation relying on triadic closure principle in social network and construct a novel information propagation model with respect to combine these three types of social factors. Firstly, the interest similarity between two users is convenient for measuring the opportunity to receive certain information. Secondly, the threshold of social trust is calculated by coupling users' network influence and content contribution. Thirdly, game choice with a rule to compute the best benefits has recognized as the motivation of users to spread a message. Finally, the game choice information propagation model based on page rank algorithm (GCIP-Page Rank) is proposed. The experimental results show that information propagation led by users experiences such stages as information contact, information trust and information propagation. At the same time, users' social trust can accelerate the spread of information in microblog social network by considering both the network structure and information content simultaneously. [ABSTRACT FROM AUTHOR]

Abstract Similarity and metric learning provides a principled approach to construct a task-specific similarity from weakly supervised data. However, these methods are subject to the curse of dimensionality: as the number of features grows large, poor generalization is to be expected and training becomes intractable due to high computational and memory costs. In this paper, we propose a similarity learning method that can efficiently deal with high-dimensional sparse data. This is achieved through a parameterization of similarity functions by convex combinations of sparse rank-one matrices, together with the use of a greedy approximate Frank-Wolfe algorithm which provides an efficient way to control the number of active features. We show that the convergence rate of the algorithm, as well as its time and memory complexity, are independent of the data dimension. We further provide a theoretical justification of our modeling choices through an analysis of the generalization error, which depends logarithmically on the sparsity of the solution rather than on the number of features. Our experiments on datasets with up to one million features demonstrate the ability of our approach to generalize well despite the high dimensionality as well as its superiority compared to several competing methods. [ABSTRACT FROM AUTHOR]

Abstract Most of current multi-object tracking algorithms mainly focus on differentiable and nearly rigid objects. However, it is challenging to use these algorithms for tracking multiple indistinguishable and deformable objects, especially when the objects are heavily mutually occluding for several frames. In this article, rather than the rectangle/ellipse model used in most of previous approaches, an Annular Sector Model (ASM) is proposed to define the states of these indistinguishable and deformable on objects poses and locations in the course of occlusions. The identities, poses and locations of the objects can be optimized by minimizing the energy function. In our experiments, the proposed approach is evaluated on a dataset for the tracking of multiple Drosophila larvae. The results demonstrate that the proposed method can identify the region of each larva during the occlusions in spite of larval poor distinguishability, and has better performance on the accuracy of identity assignment than other multi-object tracking algorithms. [ABSTRACT FROM AUTHOR]

Abstract Existing convolutional neural network (CNN) based trackers have limited tracking performance in some challenging scenarios such as deformation, background clutter and illumination variation, because the features extracted from a single layer or from a linear combination of multiple layers are insufficient to describe the target appearance. To overcome this problem, we propose a novel tracking algorithm based on interactive multiple model (IMM) framework for better exploring deep features from different layers (IMM_DFT). In this method, we first build measurement models from convolutional layers by applying correlation filters on hierarchical features. Then, to effectively estimate the target state for each layer, we design a hybrid system which consists of the foregoing measurement model and an online learning motion model. Finally, in order to achieve the optimal fusion of the systems for adapting diverse appearance variation of the target and background, an IMM estimator is developed to dynamically adjust the weight of each system using likelihood function and transition probabilities. Extensive experiments on OTB-2013, OTB-2015 and VOT-2016 benchmark databases demonstrate that the proposed algorithm achieves more favorable performance than several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Abstract Office buildings commonly contain such room types as office rooms, server rooms, storage rooms, meeting rooms, etc., while the power consumption inside the rooms generally comes from appliances, lights and air-conditioners. Based on the features of power consumption in different rooms, the aim of this study is to classify the rooms into different types by proposing an echo state network (ESN) based approach. Given the data on power consumption, the proposed approach is divided into two steps, where the first step is to establish three ESNs to model the three categories of power consumption, and the second step is to establish a fourth ESN to determine the type of a room by using the outputs of the first three ESNs. The practical performance of the proposed approach is displayed by a detailed experimental study, where the proposed approach achieves high classification accuracies and shows great superiority to several classical algorithms. [ABSTRACT FROM AUTHOR]

Abstract The identification of nonlinear state-space model (NSSM) with output observations corrupted by outliers is investigated in this paper. The outlier is commonly encountered in practical industrial processes which should not be ignored in nonlinear processes modeling. The statistical scheme based on the Student's t-distribution is applied to resist the outlier and the expectation-maximization (EM) algorithm is employed to simultaneously identify the undetermined model and noise parameters. A particle smoother is introduced and used to approximately calculate the desired Q-function. The usefulness of the proposed approach is demonstrated via the numerical and mechanical examples. [ABSTRACT FROM AUTHOR]

Highlights • A fuzzy chance-constrained programming model of biogas supply chain is developed. • The model determines location of biogas reactor and allocation of residual biomass. • Simulation based evolutionary algorithms are employed to solve the problem. • A real-case application is presented with real data in Khorasan Razavi, Iran. Abstract This study proposes a fuzzy chance-constrained programming model to include uncertainty in the biogas supply chain design problem. Uncertain parameters of the model are available workforce, biomass demand, available biomass and biomass price. A hybrid solution framework consisting of Monte Carlo simulation and evolutionary algorithms (genetic algorithm and differential evolution) is put forward to find the exact and near global optimal solution for the fuzzy chance-constrained model. The results of the test problems show that evolutionary algorithms can effectively solve the mixed integer nonlinear model of biogas location allocation within a reasonable computational time. Also, validation of the hybrid solution framework at different confidence levels is verified. The impacts of uncertainty in available biomass, biomass demand and available workforce on the overall cost of biogas supply chain are studied through sensitivity analysis. A real-world case study with real-life data available from the Province of Khorasan Razavi is performed. This is the first study that designs a biogas supply chain for a province of Iran. [ABSTRACT FROM AUTHOR]

Highlights • Bridging building physical loads and cyber models with occupancy. • Occupancy linked energy-cyber-physical system with Wi-Fi probe. • Data interface for occupancy prediction based on ensemble algorithms. • 26.4% energy saving reported in experiment and simulation validation. Abstract With the rapid advances in sensing and digital technologies, cyber-physical systems are regarded as the most viable platforms for improving building design and management. Researchers investigated the possibility of integrating energy management systems with cyber-physical systems to form energy-cyber-physical systems in order to promote building energy management. However, minimizing energy consumption while fulfilling building functions for energy-cyber-physical systems is challenging due to the dynamics of building occupants. As occupant behavior is a major source of uncertainty for energy management, ignoring it often results in both energy waste caused by overheating and overcooling as well as discomfort due to insufficient thermal and ventilation services. To mitigate such uncertainties, this study proposes an occupancy-linked energy-cyber-physical system that incorporates WiFi probe-based occupancy detection. The proposed framework utilizes ensemble classification algorithms to extract three forms of occupancy information. It creates a data interface to link energy management systems and cyber-physical systems and allows for automated occupancy detection and interpretation by assembling multiple weak classifiers for WiFi signals. A validation experiment in a large office room was conducted to examine the performance of the proposed occupancy-linked energy-cyber-physical systems. The experiment and simulation results suggest that, with a proper classifier and occupancy data type, the proposed model can potentially save about 26.4% of energy consumption in cooling and ventilation demands. [ABSTRACT FROM AUTHOR]