Eye blink detection for different driver states in conditionally automated driving and manual driving using EOG and a driver camera

In this article, we examine the performance of different eye blink detection algorithms under various constraints. The goal of the present study was to evaluate the performance of an electrooculogram- and camera-based blink detection process in both manually and conditionally automated driving phases. A further comparison between alert and drowsy drivers was performed in order to evaluate the impact of drowsiness on the performance of blink detection algorithms in both driving modes. Data snippets from 14 monotonous manually driven sessions (mean 2 h 46 min) and 16 monotonous conditionally automated driven sessions (mean 2 h 45 min) were used. In addition to comparing two data-sampling frequencies for the electrooculogram measures (50 vs. 25 Hz) and four different signal-processing algorithms for the camera videos, we compared the blink detection performance of 24 reference groups. The analysis of the videos was based on very detailed definitions of eyelid closure events. The correct detection rates for the alert and manual driving phases (maximum 94%) decreased significantly in the drowsy (minus 2% or more) and conditionally automated (minus 9% or more) phases. Blinking behavior is therefore significantly impacted by drowsiness as well as by automated driving, resulting in less accurate blink detection.     

Language-driven anticipatory eye movements in virtual reality

Predictive language processing is often studied by measuring eye movements as participants look at objects on a computer screen while they listen to spoken sentences. This variant of the visual-world paradigm has revealed that information encountered by a listener at a spoken verb can give rise to anticipatory eye movements to a target object, which is taken to indicate that people predict upcoming words. The ecological validity of such findings remains questionable, however, because these computer experiments used two-dimensional stimuli that were mere abstractions of real-world objects. Here we present a visual-world paradigm study in a three-dimensional (3-D) immersive virtual reality environment. Despite significant changes in the stimulus materials and the different mode of stimulus presentation, language-mediated anticipatory eye movements were still observed. These findings thus indicate that people do predict upcoming words during language comprehension in a more naturalistic setting where natural depth cues are preserved. Moreover, the results confirm the feasibility of using eyetracking in rich and multimodal 3-D virtual environments.     

A database of orthography-semantics consistency (OSC) estimates for 15,017 English words

Orthography–semantics consistency (OSC) is a measure that quantifies the degree of semantic relatedness between a word and its orthographic relatives. OSC is computed as the frequency-weighted average semantic similarity between the meaning of a given word and the meanings of all the words containing that very same orthographic string, as captured by distributional semantic models. We present a resource including optimized estimates of OSC for 15,017 English words. In a series of analyses, we provide a progressive optimization of the OSC variable. We show that computing OSC from word-embeddings models (in place of traditional count models), limiting preprocessing of the corpus used for inducing semantic vectors (in particular, avoiding part-of-speech tagging and lemmatization), and relying on a wider pool of orthographic relatives provide better performance for the measure in a lexical-processing task. We further show that OSC is an important and significant predictor of reaction times in visual word recognition and word naming, one that correlates only weakly with other psycholinguistic variables (e.g., family size, word frequency), indicating that it captures a novel source of variance in lexical access. Finally, some theoretical and methodological implications are discussed of adopting OSC as one of the predictors of reaction times in studies of visual word recognition.     

Moral Artisanship in <Emphasis Type="Italic">Mengzi</Emphasis> 6A7

This essay investigates the structure and meaning of the Mengzi’s 孟子 analogical inferences in Mengzi 6A7. In this chapter, he argues that just as the perceptual masters allowed the discovery of our senses’ uniform preferences, the sages enabled us to recognize our hearts’ universal preferences for “order (li 理) and righteousness (yi 義).” Regarding an unresolved question of how the sages help us understand our hearts’ preferred objects as such, I propose a spectator-based moral artisanship reading as an alternative to an evaluator-focused moral connoisseurship view: the sages are moral artisans who refine their moral achievements, and people’s uniform approval of their achievements—firmly associated with “order and righteousness”—demonstrates our hearts’ same natural preferences for them. Furthermore, I argue that this chapter’s conclusion—we and the sages are of the same kind with natural moral preferences—implies the necessity of our transition from passive spectators to active moral performers for moral self-cultivation.     

<Emphasis Type="Italic">Yin-Yang</Emphasis> and the Heart-Mind

The East Asian notion of a heart-mind (Chinese xin 心, Japanese kokoro こころ, and Korean maum ??) is arguably more accurate to our psychology than the Western term “mind” and its equivalents are: the latter term implies the possibility of psychological functioning in the absence of all emotion, and it can be shown that that is impossible. But then it turns out that we can update the traditional Chinese notions of yin 陰 and yang 陽 in such a way as to help us philosophically explain how our functioning psychology involves emotion and why any possible psychology has to rest on such a basis. Yin-yang is the essence of heart-mind, and heart-mind is essential to any functioning psychology.     

Philosophy as Elevation of Spheres of Living: Understanding Z<Emphasis Type="SmallCaps">hang</Emphasis> Shiying’s “The Myriad Things as One Body”

Zhang Shiying 張世英 has been widely acclaimed as a master (dashi 大師) of philosophy in mainland China. His new claim of “the myriad things as one body” (wanwuyiti 萬物一體) remains greatly influential in philosophy and aesthetics. It cannot be categorized under Marxism, Western philosophy, or traditional Chinese philosophy, because it stands on its own right. As a creative synthesizing of the three traditions, Zhang’s claim answers some important and immediate problems that China is facing. It is a pity that this claim seems unknown to the West. This article tries to introduce two crucial parts of the claim: its ontology and its theory of “spheres of living” (rensheng jingjie 人生境界).     

Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS

In nonexperimental data, at least three possible explanations exist for the association of two variables x and y: (1) x is the cause of y, (2) y is the cause of x, or (3) an unmeasured confounder is present. Statistical tests that identify which of the three explanatory models fits best would be a useful adjunct to the use of theory alone. The present article introduces one such statistical method, direction dependence analysis (DDA), which assesses the relative plausibility of the three explanatory models on the basis of higher-moment information about the variables (i.e., skewness and kurtosis). DDA involves the evaluation of three properties of the data: (1) the observed distributions of the variables, (2) the residual distributions of the competing models, and (3) the independence properties of the predictors and residuals of the competing models. When the observed variables are nonnormally distributed, we show that DDA components can be used to uniquely identify each explanatory model. Statistical inference methods for model selection are presented, and macros to implement DDA in SPSS are provided. An empirical example is given to illustrate the approach. Conceptual and empirical considerations are discussed for best-practice applications in psychological data, and sample size recommendations based on previous simulation studies are provided.     

Automated respiratory sinus arrhythmia measurement: Demonstration using executive function assessment

Respiratory sinus arrhythmia (RSA) is a quantitative metric that reflects autonomic nervous system regulation and provides a physiological marker of attentional engagement that supports cognitive and affective regulatory processes. RSA can be added to executive function (EF) assessments with minimal participant burden because of the commercial availability of lightweight, wearable electrocardiogram (ECG) sensors. However, the inclusion of RSA data in large data collection efforts has been hindered by the time-intensive processing of RSA. In this study we evaluated the performance of an automated RSA-scoring method in the context of an EF study in preschool-aged children. The absolute differences in RSA across both scoring methods were small (mean RSA differences = –0.02–0.10), with little to no evidence of bias for the automated relative to the hand-scoring approach. Moreover, the relative rank-ordering of RSA across both scoring methods was strong (rs = .96–.99). Reliable changes in RSA from baseline to the EF task were highly similar across both scoring methods (96%–100% absolute agreement; Kappa = .83–1.0). On the basis of these findings, the automated RSA algorithm appears to be a suitable substitute for hand-scoring in the context of EF assessment.     

On the ambiguity of interaction and nonlinear main effects in a regime of dependent covariates

The analysis of large experimental datasets frequently reveals significant interactions that are difficult to interpret within the theoretical framework guiding the research. Some of these interactions actually arise from the presence of unspecified nonlinear main effects and statistically dependent covariates in the statistical model. Importantly, such nonlinear main effects may be compatible (or, at least, not incompatible) with the current theoretical framework. In the present literature, this issue has only been studied in terms of correlated (linearly dependent) covariates. Here we generalize to nonlinear main effects (i.e., main effects of arbitrary shape) and dependent covariates. We propose a novel nonparametric method to test for ambiguous interactions where present parametric methods fail. We illustrate the method with a set of simulations and with reanalyses (a) of effects of parental education on their children’s educational expectations and (b) of effects of word properties on fixation locations during reading of natural sentences, specifically of effects of length and morphological complexity of the word to be fixated next. The resolution of such ambiguities facilitates theoretical progress.