A survey on learning an autonomous dynamic system for human–robot skills transfer from demonstration

Autonomous dynamic systems (ADS) have become a key area of research in the field of robotics, aiming to enable robots to acquire human-like operational skills and perform complex tasks in dynamic environments without external intervention. Despite significant progress, current technologies have yet to enable robots to fully achieve autonomous skill transfer in real-world applications. The prevailing approach to bridge this gap is Learning from Demonstration (LfD), where robots learn by observing and imitating expert demonstrations. Dynamic systems-based methods, particularly those utilizing Lyapunov stability theory, have shown great potential in effectively encoding human motor skills, ensuring the stability, accuracy, and generalization of learned behaviors during the learning process. This survey provides an overview of the recent advancements in dynamic systems for skill transfer, focusing on methods that enable robots to replicate human actions, as demonstrated by experts. We present a classification of existing dynamic systems approaches, highlight landmark studies, and discuss their key features, advantages, and limitations. This paper also explores the applications of these methods and identifies major challenges that remain in both theoretical and practical aspects of robot skill learning

Age is just a number: Clustering gait and functional measures.

Objective: As we age, we walk slower, but it remains unclear whether this is consistent at an individual level. Current clinical assessment of function assumes movement deficits with older age, and clinical norms are linked to decades or specific age stratifications such as “old” or “oldest-old”. Current approaches stratifying by age may hide trends of higher and lower functioning individuals within each age bracket. Therefore, our aim was to cluster spatiotemporal data, from the 1000 Norms Project, to understand if patterns of function could be identified without using age as a factor. Methods: The 1000 Norms Project, a cross-sectional, observational study, collected gait, functional performance, and self-reported health data (participants (n = 695) aged 18–92 years). Spatiotemporal and functional data were clustered, after rendering the parameters dimensionless. Results: Three clusters were identified (n = 277, 208, 210). Although age significantly differed between clusters, each showed a broad range (e.g. 20–92 years). Additionally, walking speed (Froude number) did not differ between clusters, often used to separate by age. Our clusters defined 3 groups, ‘higher functioning’, ‘age average’ and ‘cautious gait’, whose spatiotemporal, functional performance, strength and quality of life measures vastly differed, independent of walking speed and including a wide range of ages. Conclusion: Our analysis suggests that age should not be used to separate individuals into groups, and that our assumption of “age matters” may not be relevant when determining true functional movement ability. Further work is needed to understand normal senescence, true negative loss, and reversible loss within these functionally different groups

The Impact of Toxic Masculinity on Restrictive Emotionality and Mental Health Seeking Support

Many men struggle, at least occasionally, to talk about their feelings and to seek mental health support. Previous research has attributed this to gendered social norms requiring men to be tough and confident. In the present research, we investigate, across two studies, the role toxic masculinity, defined as the over-exaggeration of masculine social norms that perpetuate misogyny, plays in restrictive emotionality and intention to seek health support, as well as underlying mechanisms. Consistent with our predictions, we found that toxic masculinity, and associated variables such as aggression and dominance, were strongly linked to restrictive emotionality. Contrary to our predictions however, restrictive emotionality, but not toxic masculinity, predicted men’s avoidance in seeking help for emotional problems and having suicidal thoughts. We discuss implications, limitations, and directions for future research to address issues surrounding men’s mental health and improving service accessibility

Solidarity as a Fundamental Principle of EU Law

This article examines the principle of solidarity in the EU legal order by tracing the evolving contours of its meaning and operation in recent and emerging jurisprudence. It argues that interpreting solidarity through the lens of its underlying drivers (functional, axiological and identity based) offers a conceptually coherent account of its normative scope and boundaries. Solidarity has largely assumed an instrumental character, oriented towards securing the effective operation and systemic stability of the Union and its legal architecture. Yet the principle now stands at a transformative juncture, where a functional rationale no longer suffices to explain how it takes effect. Through instances that defy a purely instrumental logic, the article reconceptualises solidarity as a bearer of shared values and collective identity. This reframing is not only a matter of candour but indispensable for conceptual clarity and for engaging more directly with the constitutional stakes of sovereignty and belonging

Chilling Effect and Fake News Laws: Lessons from East and Southeast Asia

So-called “fake news laws” refer to legislation that criminalises or restricts the dissemination of false or misleading information likely to cause public harm, particularly online. While often justified as necessary to combat disinformation, such laws risk enabling governments to dominate public discourse and suppress dissent. Although widely criticised for their chilling effect on freedom of expression, there is no consistent framework for assessing this impact across legal systems, especially beyond the Western context. This study introduces the Chilling Effect Ranking (CER), a structured analytical tool grounded in legal scholarship and international human rights standards. Applying CER to seven East and Southeast Asian jurisdictions — China, Hong Kong, Taiwan, Singapore, Malaysia, Japan and South Korea — the paper identifies significant variation in the severity of chilling effects, ranging from high (e.g. Singapore, China) to moderate (e.g. Taiwan, Japan). The findings suggest that these effects stem not from the mere existence of such laws, but from flaws in their legal design. The CER offers practical guidance for policymakers aiming to regulate harmful content without eroding fundamental rights

Taking Variance Seriously: Visualizing the Statistical and Substantive Significance of ARCH-GARCH Models

Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized ARCH (GARCH) models allow users to estimate the conditional mean and conditional error variance of a time series process. While simulation methods exist to disaggregate the short- and long-run effects of covariate shocks to the conditional mean, scholars' inferences about the conditional error variance are currently limited to tabular interpretation. We propose a novel method of interpretation that moves beyond these tabular inferences. First, we show how changes in ARCH-GARCH processes are conditional on starting values, other covariates, and dynamics, which has led to incomplete or even incorrect inferences. We then develop three bootstrapping techniques to simulate conditional error variance model results and showcase the usefulness of each through replication of prominent studies. Our techniques demonstrate the crucial role of simulation and prediction for drawing statistical and substantive inferences about the volatility of dynamic time series processes

Meaning maintenance drives science rejection

Currently, ideologically-motivated discourses are actively undermining perceived value of science, with evidence-based policy-making being increasingly replaced with antiscience agendas shaped by political, spiritual, or conspiratorial ideologies. We propose that motivated science rejection is driven by compensatory mechanisms serving to maintain a coherent understanding of reality when this understanding conflicts with science. Drawing on the meaning maintenance model and the assumption of fluid compensation—any belief framework can be replaced with another to restore meaning—we argue that when science violates meaning, it is rejected in favour of an alternative framework of ideological beliefs, regardless of their epistemic validity. Interventions that align science with meaning-maintenance needs to minimise compensatory responses may prove promising in reducing science rejection

A genetic algorithm for the optimization of multi-threshold trading strategies in the directional changes paradigm

This paper proposes a novel genetic algorithm to optimize recommendations from multiple trading strategies derived from the Directional Changes (DC) paradigm. DC is an event-based approach that differs from the traditional physical time data, which employs fixed time intervals and uses a physical time scale. The DC method records price movements when specific events occur instead of using fixed intervals. The determination of these events relies on a threshold, which captures significant changes in price of a given asset. This work employs eight trading strategies that are developed based on directional changes. These strategies were profiled using varying values of thresholds to provide a comprehensive analysis of their effectiveness. In order to optimize and prioritize the conflicting recommendations given by the different trading strategies under different DC thresholds, we are proposing a novel genetic algorithm (GA). To analyze the GA’s trading performance, we utilize 200 stocks listed on the New York Stock Exchange. Our findings show that it can generate highly profitable trading strategies at very low risk levels. The GA is also able to statistically and significantly outperform other DC-based trading strategies, as well as 8 financial trading strategies that are based on technical indicators such as aroon, exponential moving average, and relative strength index, and also buy-and-hold. The proposed GA is also able to outperform the trading performance of 7 market indices, such as the Dow Jones Industrial Average, and the Standard & Poors (S&P) 500

Communication modality, authenticity, and continuance usage intention of GenAI chatbots: A media richness theory perspective

Generative AI chatbots are increasingly popular for tourist destination information searches. However, how communication modalities (text vs. voice), interaction styles (social vs. task-oriented), destination types (hedonic vs. utilitarian), and their interactions contribute to users’ perceptions and continuance usage intention remains unclear. Building on media richness theory, this study used a sequential explanatory mixed-methods and multi-study research design, with four scenario-based experiments to examine how the above factors affect tourists’ perceived authenticity of GenAI chatbots and continuance usage intention, and a focus group study to validate and contextualize findings from experimental studies. The results indicated that voice communication evokes a higher level of GenAI chatbots’ authenticity. Individuals’ perceived authenticity of GenAI chatbots is positively associated with their continuance usage intention. Destination type was a significant moderator, with voice modality enhancing authenticity more for hedonic than utilitarian destinations. The moderating roles of destination type and interaction style are clarified, shedding new light on destination marketing theories and practices

The cytochrome P450 decarboxylase from Staphylococcus aureus can produce a diene from a C18 monounsaturated fatty acid: A spectroscopic, structural and kinetic characterisation.

Certain members of the bacterial cytochrome P450 152 family (CYP152) are peroxygenases that catalyse the decarboxylation of fatty acids into terminal olefins making them attractive biocatalysts for biofuel production. To date, the characterisation of decarboxylating CYP152s has mainly focused on their reaction with saturated fatty acid substrates. CYP152s are often co-purified with a bound substrate, which is generally removed before further experiments are conducted. In the present work we identified that heterologous over-expressed CYP152 from Staphylococcus aureus (OleTSa) is co-purified with the trans-monounsaturated C18:1 fatty acid, elaidic acid. We report the spectral, thermodynamic and kinetic characteristics of OleTSa bound to both elaidic acid and its saturated counterpart, stearic acid. Despite differing spectral profiles, metabolic and kinetic studies reveal that OleTSa is capable of decarboxylating elaidic acid, converting it to heptadeca-1,8-diene following addition of hydrogen peroxide, at the same rate and chemoselectivity as the conversion of stearic acid to 1-heptadecane. The X-ray crystal structure of the as purified OleTSa in complex with elaidic acid is also presented, allowing for several key residues to be identified for site-directed mutagenesis studies. The influence of the site-directed variants on C18:0 and C18:1 product formation, binding thermodynamics and kinetics have been investigated, showing that while spectral differences occur as a likely result of perturbing the binding pocket, this does not alter the chemoselectivity of the enzyme. Our work provides important insights into the mechanism of decarboxylation of an unsaturated fatty acid substrate by OleTSa potentially expanding the sustainable substrate space available for CYP152s