A negative pressure wall-climbing robot is a special robot for climbing vertical walls, which is widely used in construction, petrochemicals, nuclear energy, shipbuilding, and other industries. The mobility and adhesion of the wheel-track wall-climbing robot with steering-straight mode are significantly decreased on the cylindrical wall, especially during steering. The reason is that the suction chamber may separate from the wall and the required driving force for movement increases, during steering. In this paper, a negative pressure wall-climbing robot with omnidirectional movement mode is developed. By introducing a compliant adjusting suction mechanism and omni-belt wheels, an omnidirectional movement mode is formed instead of the steering-straight mode, and the performances of adhesion and mobility are improved. We establish the safety adhesion model for the robot on a cylindrical wall and obtain the safety adhesion forces. We designed and manufactured an experimental prototype based on the analysis. Experiments showed that the robot has the ability of full maneuverability in cylindrical walls.

Sustainability evaluations are increasingly relevant in the design of products. Within sustainability-related frameworks, circular economy (CE) has gained attention in the last few years, and this has vastly affected design, leading, for example, to design for circularity. This article deals with the wide range of product-level CE assessment tools, out of which some are applied to a case study from the building sector, namely a tiny house made with hemp bricks. Attention was specifically paid to those methods through which a single circularity indicator could be extrapolated. Overall, the objective of this work is to study the convergence of existing CE assessment methods in providing consistent circularity performances. The results show similarities in the overall circularity scores despite differences in the variables used to achieve that final score. Thus, despite the lack of standard methods, the results suggest that many of these tools are sufficiently interchangeable, also in consideration of consistent indications to improve the circularity of the tiny house. This means that consistent inputs are provided to anyone willing to redesign the tiny house with the objective of making it more circular irrespective of the assessment tool used.

The National Film Board documentary Bing Bang Boom (1969) depicts Canadian composer R. Murray Schafer (1933–2021) teaching seventh-grade students in a suburban public school in Scarborough, Ontario. A close study of the film informs the larger trajectory of the composer’s previous and later writings and compositions over the next several decades, while a deeper dive into archival materials and concurrent productions from Canada’s National Film Board (NFB) illuminates the organisation’s strategy of nation-building at a crucial moment in the country’s history. Together, Schafer and the NFB illuminate Canada’s problematic relationship to Indigenous peoples, places and sounds.

Colourised photographs have become a popular form of social media content, and this article examines how the digital sharing of colourised colonial photographs from the Sápmi region may develop into a kind of informal visual repatriation. This article presents a case study on the decolonial photographic practices of the Sámi colouriser Per Ivar Somby, who mines digitised photo archives, colourises selected photos, and subsequently shares them on his social media profiles. The article draws on a qualitative, netnographic study of Somby's Colour Your Past profiles in Facebook and Instagram and demonstrates how Somby and his followers reclaim photos of Sámi people produced during historical encounters with non-Sámi photographers. Drawing on Hirsch's (2008, 2012) concept affiliative postmemory, the analysis examines how historical information and affective responses becomes interwoven in reparative readings of colonial photos.

We propose a logic-based framework to model a system whose aim is to help provide the user with those pieces of information that are useful with respect to his/her current information need, as well as relevant to his/her query. More precisely, we propose three measures of information usefulness which take into account the fact that the user can be represented as a cognitive agent endowed with some beliefs—a partial “picture” about what it already knows—and goals—a certain state of affairs in which the agent would like to be. This paper extends a previous version of the framework by considering a more realistic hypothesis, according to which there are several ways to achieve goals. We present three different approaches: the binary approach, the ordinal approach, and the numerical approach. We take information retrieval (IR) as a particular application domain, and we compare some existing measures with the usefulness measure we introduce here.

Given a sequence of independent random vectors taking values in ${\mathbb R}^d$ and having common continuous distribution function F, say that the $n^{\rm \scriptsize}$th observation sets a (Pareto) record if it is not dominated (in every coordinate) by any preceding observation. Let $p_n(F) \equiv p_{n, d}(F)$ denote the probability that the $n^{\rm \scriptsize}$th observation sets a record. There are many interesting questions to address concerning pn and multivariate records more generally, but this short paper focuses on how pn varies with F, particularly if, under F, the coordinates exhibit negative dependence or positive dependence (rather than independence, a more-studied case). We introduce new notions of negative and positive dependence ideally suited for such a study, called negative record-setting probability dependence (NRPD) and positive record-setting probability dependence (PRPD), relate these notions to existing notions of dependence, and for fixed $d \geq 2$ and $n \geq 1$ prove that the image of the mapping pn on the domain of NRPD (respectively, PRPD) distributions is $[p^*_n, 1]$ (resp., $[n^{-1}, p^*_n]$), where $p^*_n$ is the record-setting probability for any continuous F governing independent coordinates.

Aging ships and offshore structures face harsh environmental and operational conditions in remote areas, leading to age-related damages such as corrosion wastage, fatigue cracking, and mechanical denting. These deteriorations, if left unattended, can escalate into catastrophic failures, causing casualties, property damage, and marine pollution. Hence, ensuring the safety and integrity of aging ships and offshore structures is paramount and achievable through innovative healthcare schemes. One such paradigm, digital healthcare engineering (DHE), initially introduced by the final coauthor, aims at providing lifetime healthcare for engineered structures, infrastructure, and individuals (e.g., seafarers) by harnessing advancements in digitalization and communication technologies. The DHE framework comprises five interconnected modules: on-site health parameter monitoring, data transmission to analytics centers, data analytics, simulation and visualization via digital twins, artificial intelligence-driven diagnosis and remedial planning using machine and deep learning, and predictive health condition analysis for future maintenance. This article surveys recent technological advancements pertinent to each DHE module, with a focus on its application to aging ships and offshore structures. The primary objectives include identifying cost-effective and accurate techniques to establish a DHE system for lifetime healthcare of aging ships and offshore structures—a project currently in progress by the authors.

We develop and demonstrate a computationally cheap framework to identify optimal experiments for Bayesian inference of physics-based models. We develop the metrics (i) to identify optimal experiments to infer the unknown parameters of a physics-based model, (ii) to identify optimal sensor placements for parameter inference, and (iii) to identify optimal experiments to perform Bayesian model selection. We demonstrate the framework on thermoacoustic instability, which is an industrially relevant problem in aerospace propulsion, where experiments can be prohibitively expensive. By using an existing densely sampled dataset, we identify the most informative experiments and use them to train the physics-based model. The remaining data are used for validation. We show that, although approximate, the proposed framework can significantly reduce the number of experiments required to perform the three inference tasks we have studied. For example, we show that for task (i), we can achieve an acceptable model fit using just 2.5% of the data that were originally collected.

We present a linearity theorem for a proof language of intuitionistic multiplicative additive linear logic, incorporating addition and scalar multiplication. The proofs in this language are linear in the algebraic sense. This work is part of a broader research program aiming to define a logic with a proof language that forms a quantum programming language.

This paper proposes and partially defends a novel philosophy of arithmetic—finitary upper logicism. According to it, the natural numbers are finite cardinalities—conceived of as properties of properties—and arithmetic is nothing but higher-order modal logic. Finitary upper logicism is furthermore essentially committed to the logicality of finitary plenitude, the principle according to which every finite cardinality could have been instantiated. Among other things, it is proved in the paper that second-order Peano arithmetic is interpretable, on the basis of the finite cardinalities’ conception of the natural numbers, in a weak modal type theory consisting of the modal logic $\mathsf {K}$, negative free quantified logic, a contingentist-friendly comprehension principle, and finitary plenitude. By replacing finitary plenitude for the axiom of infinity this result constitutes a significant improvement on Russell and Whitehead’s interpretation of second-order Peano arithmetic, itself based on the finite cardinalities’ conception of the natural numbers.