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What Works Clearinghouse (WWC, 2022) recommends a design-comparable effect size (D-CES; i.e., gAB) to gauge an intervention in single-case experimental design (SCED) studies, or to synthesize findings in meta-analysis. So far, no research has examined gAB's performance under non-normal distributions. This study expanded Pustejovsky et al. (2014) to investigate the impact of data distributions, number of cases (m), number of measurements (N), within-case reliability or intra-class correlation (ρ), ratio of variance components (λ), and autocorrelation (ϕ) on gAB in multiple-baseline (MB) design. The performance of gAB was assessed by relative bias (RB), relative bias of variance (RBV), MSE, and coverage rate of 95% CIs (CR). Findings revealed that gAB was unbiased even under non-normal distributions. gAB's variance was generally overestimated, and its 95% CI was over-covered, especially when distributions were normal or nearly normal combined with small m and N. Large imprecision of gAB occurred when m was small and ρ was large. According to the ANOVA results, data distributions contributed to approximately 49% of variance in RB and 25% of variance in both RBV and CR. m and ρ each contributed to 34% of variance in MSE. We recommend gAB for MB studies and meta-analysis with N ≥ 16 and when either (1) data distributions are normal or nearly normal, m = 6, and ρ = 0.6 or 0.8, or (2) data distributions are mildly or moderately non-normal, m ≥ 4, and ρ = 0.2, 0.4, or 0.6. The paper concludes with a discussion of gAB's applicability and design-comparability, and sound reporting practices of ES indices. [ABSTRACT FROM AUTHOR]

In a graph G = (V , E) , a set S ⊆ V (G) is said to be a dominating set of G if every vertex not in S is adjacent to a vertex in S. Let G[S] denote the subgraph of G induced by a subset S of V(G). A dominating set S of G is called a paired-dominating set of G if the induced subgraph G[S] contains a perfect matching. Suppose that, for each v ∈ V (G) , we have a weight w(v) specifying the cost for adding v to S. The weighted paired-domination problem is to find a paired-dominating set S whose total weights w (S) = ∑ v ∈ S w (v) is minimized. In this paper, we propose an O (n + m) -time algorithm for the weighted paired-domination problem on block graphs using dynamic programming, which strengthens the results in [Theoret Comput Sci 410(47–49):5063–5071, 2009] and [J Comb Optim 19(4):457–470, 2010]. Moreover, the algorithm can be completed in O(n) time if the block-cut-vertex structure of G is given. [ABSTRACT FROM AUTHOR]

Research on the phonetic consistency effect in Chinese began in the 1980s. For nearly forty years, the consistency effect, as well as its implications for Chinese character recognition, has been frequently examined. This article presents the debate over the consistency effect in Chinese character recognition. While some research supported the involvement of prelexical phonology and sublexical processing based on the presence of consistency effects, others argued against these accounts by revealing three potential limitations, including the confounding of the task demand effect, the regularity effects and the frequency effect. A possible way to settle the debate is to shift focus to the top–down role of neighborhood characteristics underlying the consistency effect in Chinese character recognition. [ABSTRACT FROM AUTHOR]

This study examines the effects of a graphene nanosheet (GNS) conductive additive on the performance of a highly packed (2.5 g cm) lithium-ion battery cathode containing 92 wt% Li(MnNi)O microspheres (approximately 6 μm in diameter). GNSs, approximately 2.0 nm thick and 0.5-1.0 μm in width, are introduced into an electrode slurry in the form of a dispersion in N-Methyl-2-pyrrolidone. They are substantially smaller than the oxide particles; therefore, their presence exerts no adverse influence on the packing density of the electrode. A small quantity of the GNS additive (≤200 ppm relative to the oxide mass) can significantly increase the overall electronic conductance and improve the conductance uniformity of the oxide electrode, leading to reduced polarization and enhanced specific capacity and rate performance. However, the GNS additive also promotes solid-electrolyte interphase formation, resulting in resistance buildup and capacity deterioration upon cycling. This study is the first to identify such an adverse effect caused by a graphene additive. The interplay between the positive and negative effects has led to an optimal GNS additive content of approximately 100 ppm, enhancing both the rate and cycle life performance. [ABSTRACT FROM AUTHOR]

Magnetic patterning, with designed spatial profile of the desired magnetic properties, has been a rising challenge for developing magnetic devices at nanoscale. Most existing methods rely on locally modifying magnetic anisotropy energy or saturation magnetization, and thus post stringent constraints on the adaptability in diverse applications. We propose an alternative route for magnetic patterning: by manipulating the local intergranular exchange coupling to tune lateral magnetic properties. As demonstration, the grain boundary structure of Co/Pt multilayers is engineered by thermal treatment, where the stress state of the multilayers and thus the intergranular exchange coupling can be modified. With Ag passivation layers on top of the Co/Pt multilayers, we can hinder the stress relaxation and grain boundary modification. Combining the pre-patterned Ag passivation layer with thermal treatment, we can design spatial variations of the magnetic properties by tuning the intergranular exchange coupling, which diversifies the magnetic patterning process and extends its feasibility for varieties of new devices. [ABSTRACT FROM AUTHOR]