Climate trends and weather indicators are used in several research fields due to their importance in statistical modeling, frequently used as covariates. Usually, climate indicators are available as grid files with different spatial and time resolutions. The availability of a time series of climate indicators compatible with administrative boundaries is scattered in Brazil, not fully available for several years, and produced with diverse methodologies. In this paper, we propose time series of climate indicators for the Brazilian municipalities produced using zonal statistics derived from the ERA5-Land reanalysis indicators. As a result, we present datasets with zonal statistics of climate indicators with daily data, covering the period from 1950 to 2022.

We provide general expressions for the joint distributions of the k most significant b-ary digits and of the k leading continued fraction (CF) coefficients of outcomes of arbitrary continuous random variables. Our analysis highlights the connections between the two problems. In particular, we give the general convergence law of the distribution of the jth significant digit, which is the counterpart of the general convergence law of the distribution of the jth CF coefficient (Gauss-Kuz’min law). We also particularise our general results for Benford and Pareto random variables. The former particularisation allows us to show the central role played by Benford variables in the asymptotics of the general expressions, among several other results, including the analogue of Benford’s law for CFs. The particularisation for Pareto variables—which include Benford variables as a special case—is especially relevant in the context of pervasive scale-invariant phenomena, where Pareto variables occur much more frequently than Benford variables. This suggests that the Pareto expressions that we produce have wider applicability than their Benford counterparts in modelling most significant digits and leading CF coefficients of real data. Our results may find practical application in all areas where Benford’s law has been previously used.

Epistemic logic programs (ELPs), extend answer set programming (ASP) with epistemic operators. The semantics of such programs is provided in terms of world views, which are sets of belief sets, that is, syntactically, sets of sets of atoms. Different semantic approaches propose different characterizations of world views. Recent work has introduced semantic properties that should be met by any semantics for ELPs, like the Epistemic Splitting Property, that, if satisfied, allows to modularly compute world views in a bottom-up fashion, analogously to “traditional” ASP. We analyze the possibility of changing the perspective, shifting from a bottom-up to a top-down approach to splitting. We propose a basic top-down approach, which we prove to be equivalent to the bottom-up one. We then propose an extended approach, where our new definition: (i) is provably applicable to many of the existing semantics; (ii) operates similarly to “traditional” ASP; (iii) provably coincides under any semantics with the bottom-up notion of splitting at least on the class of Epistemically Stratified Programs (which are, intuitively, those where the use of epistemic operators is stratified); (iv) better adheres to common ASP programming methodology.

Physically compliant actuator brings significant benefits to robots in terms of environmental adaptability, human–robot interaction, and energy efficiency as the introduction of the inherent compliance. However, this inherent compliance also limits the force and position control performance of the actuator system due to the induced oscillations and decreased mechanical bandwidth. To solve this problem, we first investigate the dynamic effects of implementing variable physical damping into a compliant actuator. Following this, we propose a structural scheme that integrates a variable damping element in parallel to a conventional series elastic actuator. A damping regulation algorithm is then developed for the parallel spring-damping actuator (PSDA) to tune the dynamic performance of the system while remaining sufficient compliance. Experimental results show that the PSDA offers better stability and dynamic capability in the force and position control by generating appropriate damping levels.

Motivated by practical applications of inspection and maintenance, we have developed a wall-climbing robot with passive compliant mechanisms that can autonomously adapt to curved surfaces. At first, this paper presents two failure modes of the traditional wall-climbing robot on the variable curvature wall surface and further introduces the designed passive compliant wall-climbing robot in detail. Then, the motion mechanism of the passive compliant wall-climbing robot on the curved surface is analyzed from stable adsorption conditions, parameter design process, and force analysis. At last, a series of experiments have been carried out on load capability and curved surface adaptability based on a developed principle prototype. The experimental results indicated that the wall-climbing robot with passive compliant mechanisms can effectively promote both adsorption stability and adaptability to variable curvatures.

Aimed at the challenges of wide-angle mobile robot visual perception for diverse field applications, we present the spherical robot visual system that uses a 360° field of view (FOV) for realizing real-time object detection. The spherical robot image acquisition system model is developed with optimal parameters, including camera spacing, camera axis angle, and the distance of the target image plane. Two 180$^{\circ}$-wide panoramic FOVs, front and rear view, are formed using four on-board cameras. The speed of the SURF algorithm is increased for feature extraction and matching. For seamless fusion of the images, an improved fade-in and fade-out algorithm is used, which not only improves the seam quality but also improves object detection performance. The speed of the dynamic image stitching is significantly enhanced by using a cache-based sequential image fusion method. On top of the acquired panoramic wide FOVs, the YOLO algorithm is used for real-time object detection. The panoramic visual system for the spherical robot is then tested in real time, which outputs panoramic views of the scene at an average frame rate of 21.69 fps and panoramic views with object detection at an average of 15.39 fps.

This study sought to establish the elements that constitute comprehensive legal and regulatory landscape for successful digital identity system establishment and implementation. Subsequently, the study sought to assess whether these elements were present in the establishment and implementation of the National Integrated Identity Management System (NIIMS) in Kenya. The study adopted a qualitative approach, data was obtained firstly, through literature review that provided background information to the study. Secondly, semi structured interviews were undertaken on purposively selected key informants. The study established that the elements that constitute a robust legal and regulatory framework for digital identity (ID) establishment and implementation include presence of a constitutional provision on the right to privacy; existence of a digital ID law governing the establishment of the system; amendment of laws relating to the registration of persons; existence of a data protection law; existence of an overarching law governing the digital economy among others. Largely, most of these elements were present in Kenya. However, the legislative approach adopted in crafting digital ID law in Kenya was wanting. This has undermined effective implementation of the NIIM system by among other things eroding public confidence in the system. The study concluded that effective operation of the system hinged on the existence of a robust and comprehensive legal and regulatory framework that will engender users’ trust in the system. In this regard, the study recommended review of the existing legal framework to ensure that it underpins both the foundational and functional aspects of the NIIM system.

We outline a theory of algorithmic attention rents in digital aggregator platforms. We explore the way that as platforms grow, they become increasingly capable of extracting rents from a variety of actors in their ecosystems—users, suppliers, and advertisers—through their algorithmic control over user attention. We focus our analysis on advertising business models, in which attention harvested from users is monetized by reselling the attention to suppliers or other advertisers, though we believe the theory has relevance to other online business models as well. We argue that regulations should mandate the disclosure of the operating metrics that platforms use to allocate user attention and shape the “free” side of their marketplace, as well as details on how that attention is monetized.

A significant challenge of structural health monitoring (SHM) is the lack of labeled data collected from damage states. Consequently, the collected data can be incomplete, making it difficult to undertake machine learning tasks, to detect or predict the full range of damage states a structure may experience. Transfer learning is a helpful solution, where data from (source) structures containing damage labels can be used to transfer knowledge to (target) structures, for which damage labels do not exist. Machine learning models are then developed that generalize to the target structure. In practical applications, it is unlikely that the source and the target structures contain the same damage states or experience the same environmental and operational conditions, which can significantly impact the collected data. This is the first study to explore the possibility of transfer learning for damage localisation in SHM when the damage states and the environmental variations in the source and target datasets are disparate. Specifically, using several domain adaptation methods, this article localizes severe damage states at a target structure, using labeled information from minor damage states at a source structure. By minimizing the distance between the marginal and conditional distributions between the source and the target structures, this article successfully localizes damage states of disparate severities, under varying environmental and operational conditions. The effect of partial and universal domain adaptation—where the number of damage states in the source and target datasets differ—is also explored in order to mimic realistic industrial applications of these methods.

Design, like any social activity, greatly depends on human relationships for efficiency and sustainability. Collaborative design (co-design) in particular relies on strong interactions between members, as ideas and concepts become shared, going from personal (creation) to interpersonal (co-creation). There is, then, a need to understand how interpersonal factors influence interactions in co-design, and this understanding can be achieved by using the insights gleaned from research on intersubjectivity, the field of social interactions. This literature study was conducted using a systematic literature review to identify and classify the different methods used to measure intersubjectivity and see how this knowledge could explain the influence of interpersonal factors on interactions in co-design. The review identified 66 methods, out of which 4 main categories were determined. Furthermore, 115 articles were analysed and systematized in an online database, leading to a new understanding of the role of interpersonal factors in measuring the interactive levels in co-design. They reveal a positive correlation, where a rising level of interactivity is made possible by the formation and maintenance of co-creation, leading to a state of resonance where the experiences of individuals are closely related. This paper presents a state-of-the-art report on trends in the study of intersubjectivity through interpersonal factors and proposes some directions for designers and researchers interested in taking these factors into consideration for their next co-design situation.