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Hierarchical multiple regression analysis revealed that a positive CER style predicted distances and SampEn, but not HRV measures. Distances are clearly time-domain measures of HRV, but only partly capture the complexity of the heart signal. The results highlight the importance of assessing heart rate dynamics beyond HRV in the study of CER.Persuasive technology can support users of self-paced eLearning courses during critical moments of low motivation. Agent-based models (ABMs) – a relatively unfamiliar phenomenon within the persuasive technology and eLearning domains- offers a potentially relevant methodology to understand when the support should be delivered. Using ABMs, the dynamics of motivational user states can be simulated. Subsequently, emerging user patterns can be traced that can potentially provide insight in the ebb and flow of motivation. For the purpose of this study, we designed an exploratory ABM on motivation based on the mental energy notion of which the foundations can be found both within the literature of motivational psychology and agent-based modeling. During the simulations we succeeded in generating moments of critically low user motivation. In addition, we were able to simulate the positive impact of external user support at those critical moments. These results suggest that it is plausible to put further energy in developing ABM models with the ultimate goal of feeding persuasive technology with the ability to deliver just-in-time user support during eLearning.This article presents the geometrical-fractal text-tree model of speech and writing, the development of which is part of a project with the long-term goal to answer the question whether Artificial Intelligence and the corresponding human intelligence are principally different or not. Text-tree models consist of word-shrubs ‘glued’ together by syntax. Word-shrubs are designed by means of two principles, one is the dictionary or semantic principle that we can explain all verbal meanings by the meanings of other words. The other is the initiator-generator procedure, used to develop geometrical fractals. The structure of the word-shrub grows from the root-word when the meaning of the root-word, the generator, is connected as a branch to the root-word which is first initiator. Then all generator words are redefined as new initiators and connected to their meaning, the second generators. But the words or these are redefined as new initiators, each then being connected to its generator-meaning. This is repeated ad infinitum. Each new layer of generators represents a branching level. Lusutrombopag Consistency of verbal meaning is achieved by fixing the number of branching levels of the word-shrub. Wobbling consistency occurs when the talking or writing person shifts between levels of branching. We develop the M-method, important for most of the results, because it allows differences in verbal meaning to be estimated numerically. An interesting property of the text-tree model is revealed by showing that there must exist a cloud of unexperienced meaning variants of human texts. Most interesting, perhaps, is the demonstration of what we call the lemma of incompleteness which states that humans cannot prove beyond doubt, that they understand correctly what they say and write. This lemma seems to be a distant barrier for the expansion of human understanding and of relevance for understanding human versus artificial intelligence.Heart rate variability (HRV) is a noninvasive marker of cardiac autonomic function that has been extensively studied in a variety of populations. However, HRV analyses require stationarity-thus, limiting the conditions in which these data can be analyzed in physiologic and health research (e.g. post-exercise). To provide evidence and clarity on how non-stationarity affects popular indices of variability and complexity. Simulations within physiologic (restricted to values similar to exercise and recovery RR-intervals) and non-physiologic parameters, with homoscedastic and heteroscedastic variances, across four sample lengths (200, 400, 800, and 2000), and four trends (stationary, positive-linear, quadratic, and cubic) were detrended using 1-3 order polynomials and sequential differencing. Measures of variability [standard deviation of normal intervals (SDNN) and root mean square of successive differences (rMSSD)] as well as complexity [sample entropy (SampEn)] were calculated on each of the raw and detrended time-series. Differential effects of trend, length, and fit were observed between physiologic and non-physiologic parameters. rMSSD was robust against trends within physiologic parameters while both SDNN and SampEn were positively and negatively biased by trend, respectively. Within non-physiologic parameters, the SDNN, rMSSD, and SampEn of the raw time-series were all biased, highlighting the effect of the scale between these two sets of parameters. However, indices of variability and complexity on the original (trended) times-series were furthest from those of the stationary time-series, with indices coming closer to the known values as fit become more optimal. Detrending with polynomial functions provide reliable and accurate methods of assessing the variability and complexity of non-stationary time-series-such as those immediately following exercise.In 2018, Nouioui et al. transferred Bifidobacterium gallinarum and Bifidobacterium saeculare to Bifidobacterium pullorum as B. pullorum subsp. gallinarum and B. pullorum subsp. saeculare on the basis of digital DNA-DNA hybridization (dDDH) values. These two new subspecies were validated in the same year. However, we found that the genome (GenBank/ENA/DDBJ accession number JGZJ01000000) of B. pullorum used by Nouioui et al. in the dDDH analysis cannot represent B. pullorum. So, the taxonomic relationship between B. gallinarum, B. saeculare and B. pullorum should be re-examined. B. pullorum DSM 20433T had 88.7-89.0 % average nucleotide identity (ANI) values and 37.5-38.0 % dDDH values to the type strains of B. gallinarum and B. saeculare, respectively, less than the threshold for species demarcation, confirming that B. pullorum represents a different species from B. gallinarum and B. saeculare. The ANI values and dDDH values between the type strains of B. gallinarum and B. saeculare were 96.7-96.9 % and 73.0-73.