The lower limb exoskeleton is a typical wearable robot designed to assist human motion. However, its system stability and performance are often compromised due to unknown model parameters and inadequate control strategies. Therefore, it is crucial to explore the parametric identification of the exoskeleton and the design of corresponding control strategies for human-exoskeleton cooperative motion. First, an exoskeleton platform is developed to provide experimental validation. Simultaneously, a two-degree-of-freedom (2-DOF) exoskeleton model is constructed using the Lagrange method. The neighborhood field optimization (NFO) technique is then applied to identify the unknown model parameters of the exoskeleton. Additionally, the excitation trajectories for the exoskeleton are developed by the NFO method, incorporating several motion constraints to enhance the accuracy of model identification. An admittance controller is implemented to enable active control of the exoskeleton, allowing it to align with human intention and thereby improving the wearability and comfort of the device. Finally, both simulation and experimental results are compared and verified on the platform. These results demonstrate that the NFO method achieves superior identification accuracy compared to particle swarm optimization (PSO) and genetic algorithm (GA).

The East African coast has long been recognized as a cosmopolitan region, where different cultures and peoples met and exchanged ideas, goods and knowledge. The culture that developed there from the seventh century ce was shaped by these relations, often referred to under the term Swahili, and many of the coastal residents engaged in Islamic practice, long-distance trade, conspicuous consumption of valued goods, and spoke a common language. This paper investigates the presence of slaves and migrants from the East African interior, through pottery assemblages uncovered at two eleventh- to fifteenth-century ce sites in northern Zanzibar: Tumbatu and Mkokotoni. These are groups of people not usually discussed in relation to medieval Swahili towns, and slavery has been especially difficult to study archaeologically on the coast. Through a material culture of difference, I argue that enslaved and non-elite migrants can be recognized and allow for a fuller understanding of socio-economic and cultural complexity in Swahili towns.

Avertives refer to (mainly past) situations the outcome of which is interrupted, averted, or frustrated instead of completed, as in Meinasin kaatua, mutta ihmeen kaupalla onnistuin pysymään jaloillani ‘I was about to fall, but miraculously managed to stay on my feet’. The aim of this paper is to describe and compare three verbal constructions in Finnish which are frequently used as avertives by means of collostructional analysis (Stefanowitsch & Gries 2003). We propose that these constructions, namely olla + mAisillA ‘to be V-ing’, olla + INFA ‘to be to V’, and meinata + INFA ‘to mean, intend to V’, which all correspond to ‘be about to do something’, constitute a family of related avertive constructions. We first describe them by means of collexeme analyses based on corpus data consisting of online written conversation extracted from the Suomi24 corpus. We then compare the constructions and situate them on Caudal’s (2023) continuum for characterising different kinds of avertive markers. Finally, we offer a box chart characterisation of the constructions at two distinct levels of schematicity, the schematic AUX + INFX construction and a specific usage instance of olla + INFA, following Fried & Östman (2004).

Late Iron Age and Early Roman human depictions are often thought to display stylistic influences from European La Tène art and, later, Roman classical art. However, with the analysis of metal figurines attributed to the period, many reported to the Portable Antiquities Scheme, this paper argues that some of these artefacts could include stylistic influences from an earlier wooden tradition, which appears to originate in the Bronze Age. This paper therefore presents a new hypothesis regarding the development of anthropomorphic art in later Iron Age Britain, whilst also highlighting the importance of contributions of data from the Portable Antiquities Scheme.

Voters regularly face financially diverse candidate pools, yet electoral winners tend to be much wealthier than the challengers. What role do public preferences play in this over-representation of wealth? We posit three channels: direct preference for wealthy candidates, indirect preference due to in-group biases, or inadvertent preference due to ignorance about candidate wealth. Drawing on original surveys in the United States, Brazil, Chile, and India, and leveraging conjoint and information experiments, we find that when given information about wealth, the public exhibits a strong preference against wealthier candidates. While the public grossly underestimates the true wealth of politicians, correcting such misperceptions does not significantly change the preferences over candidate wealth. On the margin, the public uses wealth as a proxy for other desirable qualities like skill, but such an inferential shortcut does not boost public sentiments. Partisan bias, however, may produce some indirect support for the wealthy.

Individuals with severe mental illness face a significantly reduced life expectancy compared to the general population. Addressing key modifiable risk factors is essential to reduce these alarming rates of mortality in this population. Nutritional psychiatry has emerged as an important field of research, highlighting the important role of nutrition on mental health outcomes. However, individuals with severe mental illness often encounter barriers to healthy eating, including poor diet quality, medication-related side effects such as increased appetite and weight gain, food insecurity, and limited autonomy over food choices.

While nutrition interventions play a key role in improving health outcomes and should be a standard part of care, their implementation remains challenging. Digital technology presents a promising alternative support model, with the potential to address many of the structural and attitudinal barriers experienced by this population. Nonetheless, issues such as digital exclusion and low digital literacy persist. Integrating public and patient involvement, along with behavioural science frameworks, into the design and delivery of digital nutrition interventions can improve their relevance, acceptability, and impact. This review discusses the current and potential role of digital nutrition interventions for individuals with severe mental illness, examining insights, challenges, and future directions to inform research and practice.

Despite the recent methodological advancements in causal panel data analysis, concerns remain about unobserved unit-specific time-varying confounders that cannot be addressed by unit or time fixed effects or their interactions. We develop a Bayesian sensitivity analysis (BSA) method to address the concern. Our proposed method is built upon a general framework combining Rubin’s Bayesian framework for model-based causal inference (Rubin [1978], The Annals of Statistics 6(1), 34–58) with parametric BSA (McCandless, Gustafson, and Levy [2007], Statistics in Medicine 26(11), 2331–2347). We assess the sensitivity of the causal effect estimate from a linear factor model to the possible existence of unobserved unit-specific time-varying confounding, using the coefficients of the treatment variable and observed confounders in the model for the unobserved confounding as sensitivity parameters. We utilize priors on these coefficients to constrain the hypothetical severity of unobserved confounding. Our proposed approach allows researchers to benchmark the assumed strength of confounding on observed confounders more systematically than conventional frequentist sensitivity analysis techniques. Moreover, to cope with convergence issues typically encountered in nonidentified Bayesian models, we develop an efficient Markov chain Monte Carlo algorithm exploiting transparent parameterization (Gustafson [2005], Statistical Science 20(2), 111–140). We illustrate our proposed method in a Monte Carlo simulation study as well as an empirical example on the effect of war on inheritance tax rates.

The latest books by Martha Nussbaum and Peter Franklin, on the music and life of Benjamin Britten, both come from positions notionally outside music studies. Nussbaum – the liberal philosopher, as close to an academic celebrity as one can find nowadays – writes about the War Requiem (1962) as a (mostly) appreciative visitor to the discipline. Franklin, by contrast, is well known in nineteenth- and twentieth-century music studies. Britten Experienced nevertheless adopts the institutionally detached, less inhibited perspective of the emeritus. It would not be too far from the truth to call Franklin’s book a career retrospective. Crucially, though, it takes in not only the things that he has taught and published over the years, but also the personal encounters and enthusiasms that have (often invisibly) shaped this teaching and scholarship – the very things, in other words, that typically lie outside the professional purview of music studies.

This study offers a phenomenological exploration of unchosen pregnancy as a distinct temporal experience. By bracketing the traditionally dominant concept of pregnancy as culminating in birth, this study unveils the unique temporal contours of early pregnancy, particularly when it is not chosen. Through a critical phenomenology analysis, this study demonstrates how unchosen pregnancy is characterized by extreme temporal disorientation, a heightened experience of multiple temporal layers, and a profound loss of temporal grounding. This description of unchosen pregnancy is intended to open new pathways of thought on the ethical issue of abortions and expand the phenomenological understanding of pregnancy.