While the history and practices of collecting have received considerable attention over the past few decades, the notion of erasure – of the deleting, removal or destruction of material, whether deliberate or otherwise – has remained largely in the shadows. We challenge this neglect by placing erasure centre stage and treating it as a productive phenomenon in its own right. Indeed, we suggest that it forms a significant precondition for the very possibility of memory and collections. This article draws upon a recent turn to consider questions of forgetting, ignorance and ending to lay out the grounds for analysing the various roles played by erasure in making and unmaking our world. Inspired by Paul Connerton's discussion of different types of forgetting, we present five distinct forms of erasure that we regard as principally important: (i) repressive erasure, (ii) protective erasure, (iii) operative erasure, (iv) amending erasure and (v) calamitous and neglectful erasure. In each case, we discuss the characteristic logic of the erasure at hand and provide examples of the historical and media-specific forms in which it has been enacted. Our aim in doing so is to provide future researchers with some of the analytical tools and perspectives necessary to engage in further erasure studies. For if we are interested in making sense of the shifting and complex world we inhabit, then the interdisciplinary study of the compelling yet elusive phenomenon of erasure is an excellent place to start.

A domain-theoretic framework is presented for validated robustness analysis of neural networks. First, global robustness of a general class of networks is analyzed. Then, using the fact that Edalat’s domain-theoretic L-derivative coincides with Clarke’s generalized gradient, the framework is extended for attack-agnostic local robustness analysis. The proposed framework is ideal for designing algorithms which are correct by construction. This claim is exemplified by developing a validated algorithm for estimation of Lipschitz constant of feedforward regressors. The completeness of the algorithm is proved over differentiable networks and also over general position ${\mathrm{ReLU}}$ networks. Computability results are obtained within the framework of effectively given domains. Using the proposed domain model, differentiable and non-differentiable networks can be analyzed uniformly. The validated algorithm is implemented using arbitrary-precision interval arithmetic, and the results of some experiments are presented. The software implementation is truly validated, as it handles floating-point errors as well.

Topology optimization has been identified as a powerful tool to improve aircraft structures for many years. Yet, innovative layouts have not been successfully implemented in commercial aircraft for several reasons. One reason identified by our research group is the lack of design constraints during topology optimization, such as buckling stability, which yields complex solutions that are not easily manufacturable. Second, the complexity of the resulting layouts makes integration with other systems highly challenging. With respect to these challenges, we propose a new heuristic layout optimization process: complexity-driven layout exploration for aircraft structures (CD-LEAS). The new process addresses the challenges of complexity and nonlinear constraints, such as buckling, in aircraft structure layout optimization. The novelty of CD-LEAS comes from the integration of a relative complexity metric as a driver to navigate the design space efficiently. Two case studies of commonly used stiffened panels are carried out to showcase the performance of the process. The results show that using complexity to navigate an explicit design space allows our process to quickly output a family of simple, light, stiff and buckling-resistant layouts.

This article discusses the development of an automated plot extraction system for narrative texts. Acknowledging the distinction between plot, as an object of study with its own rich history and literature, and features of a text that may be automatically extractable, we begin by characterizing a text’s scatter plot of entities. This visualization of a text reveals entity density patterns characterizing the particular telling of the story under investigation and leads to effective scene partitioning. We then introduce the concept of narrative flow, a graph representation of the narrative ordering of scenes (the syuzhet) that includes how entities move through scenes from the text, and investigate the degree to which narrative flow can be automatically extracted given a glossary of plot-important objects, actors, and locations. Our subsequent analysis then explores the correlation between subjective notions of plot and the information extracted through these visualizations. In particular, we discuss narrative structures commonly found within the graphs and make comparisons with ground truth narrative flow graphs, showing mixed results highlighting the difficulty of plot extraction. However, the visual artifacts and common structural relationships seen in the graphs provide insight into narrative and its underlying plot.

We explain and explore class-theoretic potentialism—the view that one can always individuate more classes over a set-theoretic universe. We examine some motivations for class-theoretic potentialism, before proving some results concerning the relevant potentialist systems (in particular exhibiting failures of the $\mathsf {.2}$ and $\mathsf {.3}$ axioms). We then discuss the significance of these results for the different kinds of class-theoretic potentialists.

As a heavy load is applied to the parallel manipulators, it causes inaccuracies while positioning the end-effector or unbalanced dynamic forces in the legs. Various load-balancing techniques overcome this. However, the disadvantage of most load-balancing mechanisms is that they add inertia to the assembly and decrease the speed of motion. This article studies a new load-balancing method (a passive damper mechanism). The passive balancing mechanism is proposed to negate the inertia effects while countering the static inaccuracies in the parallel mechanism. This is verified by the structural analysis of the mechanism. The impact of the damper element on the dynamics of the mechanism is unknown. Hence, a complete mathematical model for the balancing mechanism has been developed to study its impact on the dynamics of the entire structure. Laplace transformations characterize the system response. The inclusion of a passive damper in a 3-prismatic-prismatic-revolute-spherical system was examined and found to be stable and critically damped. Such a passive damper was envisaged to facilitate additional force transmission for the actuators, and the DC gain from the system response validates the torque support for the actuators.

The exponential growth of data collection opens possibilities for analyzing data to address political and societal challenges. Still, European cities are not utilizing the potential of data generated by its citizens, industries, academia, and public authorities for their public service mission. The reasons are complex and relate to an intertwined set of organizational, technological, and legal barriers, although good practices exist that could be scaled, sustained, and further developed. The article contributes to research on data-driven innovation in the public sector comparing high-level expectations on data ecosystems with actual practices of data sharing and innovation at the local and regional level. Our approach consists in triangulating the analysis of in-depth interviews with representatives of the local administrations with documents obtained from the cities. The interviews investigated the experiences and perspectives of local administrations regarding establishing a local or regional data ecosystem. The article examines experiences and obstacles to data sharing within seven administrations investigating what currently prevents the establishment of data ecosystems. The findings are summarized along three main lines. First, the limited involvement of private sector organizations as actors in local data ecosystems through emerging forms of data sharing became evident. Second, we observed the concern over technological aspects and the lack of attention on social or organizational issues. Third, a conceptual decision to apply a centralized and not a federated digital infrastructure is noteworthy.