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In today’s corporate environment, organizations are paying increasing attention to the spatial configuration of workspaces where creative processes and innovation are supposed to take place. These environments are designed to foster and sustain creative performance at work, providing digital, physical, and hybrid solutions to fulfill individuals’ needs and to enable modes of working alone as well as in teams. Starting with a literature review of previous research on this multidisciplinary topic addressing team dynamics, workspace design, and their relations to creativity, this chapter provides useful guidelines for the processes of creation and usage of physical, digital, and hybrid environments to foster and manage creativity in work-related settings. Firms’ strategic intents and users’ needs, sensorial experiences, and modes of interaction during the development of the creative process are aspects that are thoroughly explored and explained.

The Flight Control Team Multi-Agent System (FCTMAS) study, funded by the European Space Agency (ESA), has investigated the use of multiagent systems in supporting flight control teams in routine operations. One of the scientific challenges of the FCTMAS study has been the detection of anomalies relative to a space system only on the basis of identified deviations from the nominal trends of single measurable variables. In this paper, we discuss how we addressed this challenge by looking for the best structure that aggregates a given set of models, each one returning the anomaly probability of a single measurable variable, under the assumption that there is no a priori knowledge about the structure of the space system nor about the relationships between the variables. Experiments are conducted on data of the Cryosat-2 satellite and their results are eventually summarized as a set of guidelines.

This chapter surveys the practices that are being employed in experimentally assessing the special class of computational models embedded in robots. The assessment of these models is particularly challenging mainly due to the difficulty of accurately estimating and modeling the interactions between the robots and their environments, especially in the case of autonomous robots, which make decisions without continuous human supervision. The field of autonomous robotics has recognized this difficulty and launched a number of initiatives to deal with it. This chapter, after a conceptual premise and a broad introduction to the experimental issues of robotics, critically reviews these initiatives that range from taking inspiration from traditional experimental practices, to simulations, benchmarking, standards, and competitions.

There is a lack of definitive data on the effective management of acute respiratory distress syndrome (ARDS) in infants and children. The development and validation of the Berlin definition (BD) for ARDS and the Pediatric Acute Lung Injury Consensus Conference (PALICC) recommendations in children represented a major advance in optimizing research and treatment, mainly due to the introduction of a severe ARDS category. Proposed reasons for the lack of consistent results with surfactants in children and infants compared with neonates include different causes, type of lung damage (direct or indirect), timing and mode of administration as well as the type of surfactant used. Secretory phospholipase A2 plays an important role in inflammation and possible dysfunction of surfactants in ARDS. Bronchoalveolar lavage (BAL) with normal saline and surfactant allows the removal of inhaled material, the recruitment of non-ventilating areas and the maintenance of the surfactant pool size. BAL with diluted surfactant allows rapid absorption of the surfactant at the air/liquid interface, which blocks the progression of pathological lung disease and in turn disrupts the inflammatory cycle. Importantly, it is now recognized that the type of surfactant, the time of administration and the method of administration could all play an important role in the management of ARDS, and there is evidence that surfactant is effective and well tolerated in children and infants with ARDS.

Semantic mapping is one of the most active and promising research areas within autonomous mobile robotics. Informally, a semantic map associates a high-level human-understandable label (like “office” or “corridor”) to a portion of an environment. Most semantic mapping approaches are based on classifiers that, given some features perceived by robot sensors in a physical place, associate a semantic label to the place. These approaches are often tested on a limited number of homogeneous places (e.g., few rooms within a single building). This line of action seems to hinder the development of methods for constructing semantic maps that can be (re)used in a number of previously unseen environments. In this paper, we aim at contributing to make semantic mapping methods more general. In particular, we focus on indoor environments and we consider the following research question: to what extent are the semantic mapping approaches shown to label rooms in a single building expected to work when applied to different buildings?

Autonomous mobile robots have seen a widespread development in recent years, due to their possible applications (e.g., surveillance and search and rescue). Several techniques have been proposed for solving the path planning problem, in which a user specifies spatial targets and the robots autonomously decide how to go there. In contrast, the problem of where to go next, in which the targets themselves are autonomously decided by the robots, is largely unexplored and lacking an assessed theoretical basis. In this work, we make a step towards a framework for casting and addressing this problem. The framework includes the following dimensions: the amount of knowledge about the environment the robots have, the kind of that knowledge, the criteria used to evaluate the success of the decisions, the number of decision makers, and the possible adversarial nature of the settings. We focus on applications relative to exploration and patrolling.

Computing and science reveal a synergic relationship. On the one hand, it is widely evident that computing plays an important role in the scientific endeavor. On the other hand, the role of scientific method in computing is getting increasingly important, especially in providing ways to experimentally evaluate the properties of complex computing systems. This book critically presents these issues from a unitary conceptual and methodological perspective by addressing specific case studies at the intersection between computing and science. The book originates from, and collects the experience of, a course for PhD students in Information Engineering held at the Politecnico di Milano. Following the structure of the course, the book features contributions from some researchers who are working at the intersection between computing and science.

In the guidelines for maintenance, conservation, and reuse in the Walled City of Multan, there are also the descriptions of the wooden elements, their decay, and structural phenomena, the best practices and bad practices for the preservation, and a technical sheet for interventions for wooden elements.