Actors collaborate via message exchanges to reach a common goal. Experience has shown, however, that pure message-based communication is limiting and forces developers to use design patterns. The recently introduced dataspace actor model borrows ideas from the tuple space realm. It offers a tightly controlled, shared storage facility for groups of actors. In this model, actors assert facts that they wish to share and interests in such assertions. The dataspace notifies interested parties of changes to the set of assertions that they are interested in. Although it is straightforward to add the dataspace model to untyped languages, adding a typed interface is both necessary and challenging. Without restrictions on exchanged data, a faulty actor may propagate erroneous data through a malformed assertion, causing an otherwise well-behaved actor to crash—violating the key principle of failure isolation. A properly designed type system can prevent this scenario and rule out other kinds of uncooperative actors. This paper presents the first structural type system for the dataspace model of actors; it does not address the question of behavioral types for assertion-oriented protocols.

In this paper, we mainly study a class of small deviation theorems for Markov chains indexed by an infinite tree with uniformly bounded degree in Markovian environment. Firstly, we give the definition of Markov chains indexed by a tree with uniformly bounded degree in random environment. Then, we introduce the some lemmas which are the basis of the results. Finally, a class of small deviation theorems for functionals of random fields on a tree with uniformly bounded degree in Markovian environment is established.

Sheet-defined functions (SDFs) bring modularity and abstraction to the world of spreadsheets. Alas, end users naturally write SDFs that work over fixed-size arrays, which limits their reusability. To help end user programmers write more reusable SDFs, we describe a principled approach to generalising such functions to become elastic SDFs that work over inputs of arbitrary size. We prove that under natural, checkable conditions, our algorithm returns the principal generalisation of an input SDF. We describe a formal semantics and several efficient implementation strategies for elastic SDFs. A user study with spreadsheet users compares the human experience of programming with elastic SDFs to the alternative of relying on array-processing combinators. Our user study finds that the cognitive load of elastic SDFs is lower than for SDFs with map/reduce array combinators, the closest alternative solution.

An entity mention in text such as “Washington” may correspond to many different named entities such as the city “Washington D.C.” or the newspaper “Washington Post.” The goal of named entity disambiguation (NED) is to identify the mentioned named entity correctly among all possible candidates. If the type (e.g., location or person) of a mentioned entity can be correctly predicted from the context, it may increase the chance of selecting the right candidate by assigning low probability to the unlikely ones. This paper proposes cluster-based mention typing for NED. The aim of mention typing is to predict the type of a given mention based on its context. Generally, manually curated type taxonomies such as Wikipedia categories are used. We introduce cluster-based mention typing, where named entities are clustered based on their contextual similarities and the cluster ids are assigned as types. The hyperlinked mentions and their context in Wikipedia are used in order to obtain these cluster-based types. Then, mention typing models are trained on these mentions, which have been labeled with their cluster-based types through distant supervision. At the NED phase, first the cluster-based types of a given mention are predicted and then, these types are used as features in a ranking model to select the best entity among the candidates. We represent entities at multiple contextual levels and obtain different clusterings (and thus typing models) based on each level. As each clustering breaks the entity space differently, mention typing based on each clustering discriminates the mention differently. When predictions from all typing models are used together, our system achieves better or comparable results based on randomization tests with respect to the state-of-the-art levels on four defacto test sets.

There is growing interest in quantifying attitudes towards autistic people, however there is relatively little research on psychometric properties of the only existing measure and its ability to predict engagement with people with autism. To begin addressing these issues, we compared three scales measuring attitudes towards autistic people following the development of two new measures. Exploratory factor analysis, across two datasets, revealed that the factor-structure of an established 16-item scale is unclear. Further, its predictive validity of intended engagement with autistic people was comparable to our novel and psychometrically robust 1- and 4-item measures of attitudes towards autistic people. We therefore conclude that a 1- or 4-item scale is sufficient to measure general attitudes towards autistic people in future research. Equally, we propose that additional research is required to develop measures that are grounded in theoretical models of attitude formation and therefore distinguish between different components of attitudes.

The ongoing coronavirus disease 2019 (COVID-19) pandemic is of global concern and has recently emerged in the US. In this paper, we construct a stochastic variant of the SEIR model to estimate a quasi-worst-case scenario prediction of the COVID-19 outbreak in the US West and East Coast population regions by considering the different phases of response implemented by the US as well as transmission dynamics of COVID-19 in countries that were most affected. The model is then fitted to current data and implemented using Runge-Kutta methods. Our computation results predict that the number of new cases would peak around mid-April 2020 and begin to abate by July provided that appropriate COVID-19 measures are promptly implemented and followed, and that the number of cases of COVID-19 might be significantly mitigated by having greater numbers of functional testing kits available for screening. The model is also sensitive to assigned parameter values and reflects the importance of healthcare preparedness during pandemics.

In ‘Calculating Correct Compilers’ (Bahr & Hutton, 2015), we developed a new approach to calculating compilers directly from specifications of their correctness. Our approach only required elementary reasoning techniques and has been used to calculate compilers for a wide range of language features and their combination. However, the methodology was focused on stack-based target machines, whereas real compilers often target register-based machines. In this article, we show how our approach can naturally be adapted to calculate compilers for register machines.

Given extensive research underscoring the deleterious effects of bullying on youth adjustment, anti-bullying policies and programming are critical public health priorities. However, strategies that increase public support for anti-bullying causes are not well understood. This experiment assessed the influence of “bullying messaging” on support for anti-bullying policies. Specifically, I investigated whether learning about the health consequences of bullying, as opposed to its prevalence or educational impact, increased individuals’ support of anti-bullying policies. Participants (n = 329) were randomly assigned to one of four conditions where they read a brief summary about bullying research; conditions varied by whether the research documented the: a) prevalence of bullying b) mental health consequences of bullying c) physical health consequences of bullying or d) academic consequences of bullying. Results indicated that participants endorsed high levels of support for anti-bullying policies, regardless of experimental condition, and that policies aimed at increasing K-12 mental health resources were most supported.

We establish a fundamental property of bivariate Pareto records for independent observations uniformly distributed in the unit square. We prove that the asymptotic conditional distribution of the number of records broken by an observation given that the observation sets a record is Geometric with parameter 1/2.

Cyclopentadithiophene (CPDT), a Csp3-bridged bithiophene heteroaromatic unit, displays interesting properties when it is embedded in the repeating units of π-conjugated polymers, and they are applied in organic electronics devices. Common synthetic routes to CPDT-derived polymers rely on toxic methodologies whilst alternative non-toxic strategies such as the Suzuki-Miyaura reaction have been less studied. In this report we demonstrate that the use of a N-methyliminodiacetic acid (MIDA) boronate ester-derived CPDT monomer allows the efficient formation of poly(cyclopentadithiophene) homopolymer under Suzuki-Miyaura cross-coupling reaction conditions. Thus, the use of MIDA boronate esters might be extended to other organic units to design and construct a plethora of π-conjugated polymers.

Erdős, Gyárfás and Pyber showed that every r-edge-coloured complete graph Kn can be covered by 25 r2 log r vertex-disjoint monochromatic cycles (independent of n). Here we extend their result to the setting of binomial random graphs. That is, we show that if $p= p(n) = \Omega(n^{-1/(2r)})$, then with high probability any r-edge-coloured G(n, p) can be covered by at most 1000r4 log r vertex-disjoint monochromatic cycles. This answers a question of Korándi, Mousset, Nenadov, Škorić and Sudakov.

We prove that any n-vertex graph whose complement is triangle-free contains n2/12 – o(n2) edge-disjoint triangles. This is tight for the disjoint union of two cliques of order n/2. We also prove a corresponding stability theorem, that all large graphs attaining the above bound are close to being bipartite. Our results answer a question of Alon and Linial, and make progress on a conjecture of Erdős.

Accurate torque control is a critical issue in the compliant human–robot interaction scenario, which is, however, challenging due to the ever-changing human intentions, input delay, and various disturbances. Even worse, the performances of existing control strategies are limited on account of the compromise between precision and stability. To this end, this paper presents a novel high-performance torque control scheme without compromise. In this scheme, a new nonlinear disturbance observer incorporated with equivalent control concept is proposed, where the faster convergence and stronger anti-noise capability can be obtained simultaneously. Meanwhile, a continuous fractional power control law is designed with an iteration method to address the matched/unmatched disturbance rejection and global finite-time convergence. Moreover, the finite-time stability proof and prescribed control performance are guaranteed using constructed Lyapunov function with adding power integrator technique. Both the simulation and experiments demonstrate enhanced control accuracy, faster convergence rate, perfect disturbance rejection capability, and stronger robustness of the proposed control scheme. Furthermore, the evaluated assistance effects present improved gait patterns and reduced muscle efforts during walking and upstair activity.

Multi-Robot System (MRS) is composed of a group of robots that work cooperatively. However, Multi-Agent System (MAS) is computational systems consisting of a group of agents that interact with each other to solve a problem. The central difference between MRS and MAS is that in the first case, the agent is a robot, and in the second, it is a software. Analyzing the scientific literature, it is possible to notice that few studies address the integration between MAS and MRS. In order to achieve the interdisciplinary integration, the theoretical background of these areas must be considered in this paper, so that the integration can be applied using a case study of decentralized MRS. The objective of this MRS is to track and surround a stationary target. Also, it has been implemented and validated in the robot simulator called Virtual Robot Experimentation Platform (V-REP). In the validation of the proposed MRS, a scenario with three robots and a stationary target were defined. In the tracking task, the robot can detect the target whose position is not known a priori. When the detection occurs, the V-REP informs the target position to the robot because the environment is discretized into a grid of rectangular cells. After that, all the robots are directed to the target, and the surround task is realized. In this task, a mathematical model with direct communication between the robots was used to keep the robots equidistant therefrom and from each other.

Several discrete geometry problems are equivalent to estimating the size of the largest homogeneous sets in graphs that happen to be the union of few comparability graphs. An important observation for such results is that if G is an n-vertex graph that is the union of r comparability (or more generally, perfect) graphs, then either G or its complement contains a clique of size $n^{1/(r+1)}$.

This bound is known to be tight for $r=1$. The question whether it is optimal for $r\ge 2$ was studied by Dumitrescu and Tóth. We prove that it is essentially best possible for $r=2$, as well: we introduce a probabilistic construction of two comparability graphs on n vertices, whose union contains no clique or independent set of size $n^{1/3+o(1)}$.

Using similar ideas, we can also construct a graph G that is the union of r comparability graphs, and neither G nor its complement contain a complete bipartite graph with parts of size $cn/{(log n)^r}$. With this, we improve a result of Fox and Pach.

In this paper, a new design configuration has been proposed in which a prototype of resonant inductive power transfer-based contactless power transfer to wound rotor has been developed which provides field power to brushless alternating current (BLAC) or brushless direct current (BLDC) motors without the use of permanent magnets in the rotor. Further, wound field in the rotor of DC motor can be powered without carbon brushes. The proposed design facilitates motor performance improvement by adding an extra dimension of field flux control, while the armature circuit is conventionally fed from position detection and commutation schemes. It contains a primary multilayer concentrated coil fed with high-frequency resonating AC supply or switched mode supply. A single layer helical secondary coil coaxially fixed on the shaft receives high frequency wireless AC power transmitted from primary coil. Fast rectifier inside the hollow shaft and DC filter provides the transferred DC power to field terminals in the rotor. It has been verified that rotor power can be varied linearly with linear variation in input DC power with the highest efficiency at the resonant frequency. Available power to the rotor remains invariable with rotational speed and angle, which is a necessary requirement for rotor field. DC voltage on the rotor terminals can be effectively controlled during standstill as well as during rotation at any speed.

The 7 degrees of freedom (DOF) redundant manipulator greatly improves obstacle/singularity avoidance capability and operational flexibility. However, the inverse kinematics problem of this manipulator is very difficult to solve because it has an infinite number of solutions. This paper uses a new numerical sequence processing method with a closed-loop framework to solve the inverse kinematics of the 7-DOF redundant manipulator. Simulation and experiment show that this method has high commonality. No special structure of the robot is required, and this method has improved computational efficiency and reliability.