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In this study, researchers implemented a brief training plus coaching program in naturalistic developmental behavioral intervention with three participant triads. Each triad consisted of an early intervention provider, an English-speaking Latinx parent, and that parent’s young child with autism spectrum disorder (ASD) or early signs of ASD who had limited vocal speech. The effects a single training session, plus two researcher coaching sessions were evaluated using a nonconcurrent multiple probes across participants design. Primary dependent variables included (a) the number of completed targeted communication turns between the parent and child and (b) the number of child independent target communication responses (gestures and manual signs) during family-selected routines. Additional measures examined whether parents used strategies taught to them during training, and whether early intervention providers addressed strategies taught via coaching. A social validity measure was used to determine parent and provider views of the training. Due to COVID-19 restrictions, training and post-training sessions were delivered via telehealth for two triads. While data trends and variability differed across triads, following training, all three families increased the number of completed target communication turns and all three children showed higher rates of independent communication responses. Parents and providers implemented strategies taught and reported positive effects of the program. Implications regarding the use of naturalistic intervention methods for Latinx families, the utility of brief training models to meet the needs of under-resourced early intervention programs, and potential uses of telehealth are discussed. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Purpose: This paper aims to investigate the relationship between environmental performance and management and company valuation. With a specific focus on company valuation, this study shows how a firm’s environmental activities, including its environmental management practices, are perceived and valued by its stockholders. Design/methodology/approach: Newsweek’s green ranking data between 2014 and 2016 were used to support this analysis. Environmental performances and environmental management practices of 345 Fortune 500 companies from various industries were included in the data set. Findings: The analysis finds higher valuations for US companies that are more efficient in managing greenhouse gas emissions. In addition, it empirically shows that investors place a higher value on companies with the following environment-related management policies: initiatives that reward top management for achieving environmental goals and third-party auditing of environmental performance. Originality/value: By incorporating corporate environmental management practices as an additional environmental performance criterion, this research fills a gap in the literature on the potential relationship between corporate environmental performance and company valuation. © 2021, Emerald Publishing Limited.

This paper examines the role of property rights and other factors to the growth of real gross domestic product (GDP) per capita. We show using a two-step system generalized method of moments (GMM) dynamic model and a panel data set of around 150 countries from 2006 to 2018 that property rights have a positive and significant effect on the growth of real GDP per capita. The paper also found that human capital, physical capital and inflation have significant effects on real GDP per capita growth. © 2021. All Rights Reserved.

In this paper, we develop a new point-of-entry security measure for smartphone users. We devise a concept, the “Quad Swipe Pattern”, which includes four swipes from a user in four directions and utilizes the user’s swipe behavior for authentication. The Quad Swipe Pattern overcomes several shortcomings present in current point-of-entry security measures. We performed several experiments to demonstrate the effectiveness of the Quad Swipe Pattern in smartphone user authentication. We evaluated the Quad Swipe Pattern using five machine learning classifiers, three datasets of different sizes, and five different fingers. In addition, we studied how fusion of information from multiple fingers and multiple classifiers can improve the performance of Quad Swipe Pattern. All of our experimental results show significant promise of the Quad Swipe Pattern as a new point-of-entry security measure for smartphones. With a Neural Network model, the Quad Swipe Pattern achieves the Accuracy of 99.7%, False Acceptance Rate of 0.4%, and False Rejection Rate of 0%. With Support Vector Machine, the Quad Swipe Pattern achieves the Accuracy of 99.5%, False Acceptance Rate of 0.4%, and False Rejection Rate of 1.7%. With fusion of two best fingers, the Quad Swipe Pattern demonstrates an excellent performance of a zero Equal Error Rate.

A Skolem sequence can be thought of as a labelled path where two vertices with the samelabelarethatdistanceapart.Thisconcepthasnaturallybeengeneralizedto labellingsofothergraphs,butalwaysusingatmosttwoofanyintegerlabel.Giventhat more than two vertices can be mutually distance d apart, wedefine a new generalization of aSkolemsequenceongraphsthatwecallaproperSkolemlabelling.Thisbrings rise tothequestion;use to proper Skolemlabel a graph?"This will be known as the Skolem number of the graph. In this paper we give the Skolem number for cycles and grid graphs,while also providing other related results along the way. Published by Digital Commons@Georgia Southern, 2021. © 2021 Georgia Southern University. All rights reserved.

A rokudoku-pair square is an order-6 sudoku Latin square for both 2 x 3 and 3 x 2 tiling regions simultaneously. We count the distinct rokudoku-pair squares as well as orbits under the action of a suitable group. Our arguments employ group actions and list colorings of graphs. As an application we determine which rokudoku-pair squares are based on groups. © 2021. All Rights Reserved.

Image reconstruction for industrial applications based on Electrical Capacitance Tomography (ECT) has been broadly applied. The goal of image reconstruction based ECT is to locate the distribution of permittivity for the dielectric substances along the cross-section based on the collected capacitance data. In the ECT-based image reconstruction process: (1) the relationship between capacitance measurements and permittivity distribution is nonlinear, (2) the capacitance measurements collected during image reconstruction are inadequate due to the limited number of electrodes, and (3) the reconstruction process is subject to noise leading to an ill-posed problem. Thence, constructing an accurate algorithm for real images is critical to overcoming such restrictions. This paper presents novel image reconstruction methods using Deep Learning for solving the forward and inverse problems of the ECT system for generating high-quality images of conductive materials in the Lost Foam Casting (LFC) process. Here, Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) models were implemented to predict the distribution of metal filling for the LFC process-based ECT. The recurrent connection and the gating mechanism of the LSTM is capable of extracting the contextual information that is repeatedly passing through the neural network while filtering out the noise caused by adverse factors. Experimental results showed that the presented ECT-LSTM-RNN model is highly reliable for industrial applications and can be utilized for other manufacturing processes. © 2013 IEEE.

Thirty-seven deaf and hard of hearing (DHH) students in grades four through six participated in a year of Strategic and Interactive Writing Instruction, an approach to writing instruction designed to be responsive to DHH students’ unique language experiences and profiles. The current study investigated the transfer of writing skills between genres by analyzing participants’ recount, information report, and persuasive writing samples at four time points: at the beginning of the academic year, immediately before genre-focused instruction, at the end of 9 weeks of instruction in a genre, and 9 weeks after the conclusion of instruction in a genre. Results from the study demonstrate that DHH students transfer genre-specific writing skills between genres. © 2021 The Authors

Grid resilience and reliability are pivotal in the transition to low and zero carbon energy systems. Tree-trimming operations (TTOs) have become a pivotal tool for increasing the resilience power grids, especially in highly forested regions. Building on recent literature, we aim at assessing the temporal and spatial extents of the benefits that TTOs produce on the grid from three perspectives: the frequency, extent, and duration of outages. We use a unique dataset provided by Eversource Energy, New England's largest utility company, with outage events from 2009 to 2015. We employ spatial econometrics to investigate both the legacy and spatial extent of TTOs. Our results show TTOs benefits occur for all three metrics for at least 4 years, and benefits spillover to up to 2 km throughout the treated areas, with significant spatial spillovers across the state greater than direct effects. Implications lead to supporting TTOs as part of the hardening policies for utility companies, especially as home-based activities increase in importance in a post-COVID19 world. © 2021 Elsevier Ltd

"This book provides awareness and discussion on the topic of inequities in healthcare that impact health disparities"--