Salute e sicurezza sul lavoro: significati e problemi della valutazione dei rischi da stress lavoro-correlato nelle aziende sanitarie

Work environment changes bring new risks, in particular an increase in certain diseases and illnesses caused by stress. The European Agreement of October 2004 defines stress as “a state accompanied by physical, psychological or social dysfunctions, due to the fact that people do not feel able to overcome the gap in relation to requests or expectations for them”. A new strategy aims to reduce accidents and occupational illnesses through a series of actions at European level. The approaches to prevent work related stress must specifically aim to face up organizational and social aspects, to provide training to managers and employees on management of stress, to reduce the impact and to develop suitable systems for rehabilitation and return to work for those who suffered health problems. The enterprises will have to carry out the obligations laid down by legislation, adopting detection systems customised on their size and on their specific interests. Currently manifold tools and methodologies are proposed from different subjects as employer associations, advisors for safety, psychologists etc., but none of these has been identified as a model to follow. After the reconstruction of the theoretical framework where the theme is placed in, the thesis, through a background analysis done by collecting the comments of experts who are involved in the management of occupational safety and the examination of a concrete assessment of work-related stress risk, carried out at a local health authority of Emilia-Romagna region, aims to highlight the main sociological implications related to the emergence of these new risks.

Integrating the age factor in designing industrial environments and workstations in the workforce ageing era

As people spend a third of their lives at work and, in most cases, indoors, the work environment assumes crucial importance. The continuous and dynamic interaction between people and the working environment surrounding them produces physiological and psychological effects on operators. Recognizing the substantial impact of comfort and well-being on employee satisfaction and job performance, the literature underscores the need for industries to implement indoor environment control strategies to ensure long-term success and profitability. However, managing physical risks (i.e., ergonomic and microclimate) in industrial environments is often constrained by production and energy requirements. In the food processing industry, for example, the safety of perishable products dictates storage temperatures that do not allow for operator comfort. Conversely, warehouses dedicated to non-perishable products often lack cooling systems to limit energy expenditure, reaching high temperatures in the summer period. Moreover, exceptional events, like the COVID-19 pandemic, introduce new constraints, with recommendations impacting thermal stress and respiratory health. Furthermore, the thesis highlights how workers' variables, particularly the aging process, reduce tolerance to environmental stresses. Consequently, prolonged exposure to environmental stress conditions at work results in cardiovascular disease and musculoskeletal disorders. In response to the global trend of an aging workforce, the thesis bridges a literature gap by proposing methods and models that integrate the age factor into comfort assessment. It aims to present technical and technological solutions to mitigate microclimate risks in industrial environments, ultimately seeking innovative ways to enhance the aging workforce's comfort, performance, experience, and skills. The research outlines a logical-conceptual scheme with three main areas of focus: analyzing factors influencing the work environment, recognizing constraints to worker comfort, and designing solutions. The results significantly contribute to science by laying the foundation for new research in worker health and safety in an ageing working population's extremely current industrial context.

Meta-models, environment and layers: agent-oriented engineering of complex systems

Traditional software engineering approaches and metaphors fall short when applied to areas of growing relevance such as electronic commerce, enterprise resource planning, and mobile computing: such areas, in fact, generally call for open architectures that may evolve dynamically over time so as to accommodate new components and meet new requirements. This is probably one of the main reasons that the agent metaphor and the agent-oriented paradigm are gaining momentum in these areas. This thesis deals with the engineering of complex software systems in terms of the agent paradigm. This paradigm is based on the notions of agent and systems of interacting agents as fundamental abstractions for designing, developing and managing at runtime typically distributed software systems. However, today the engineer often works with technologies that do not support the abstractions used in the design of the systems. For this reason the research on methodologies becomes the basic point in the scientific activity. Currently most agent-oriented methodologies are supported by small teams of academic researchers, and as a result, most of them are in an early stage and still in the first context of mostly \academic" approaches for agent-oriented systems development. Moreover, such methodologies are not well documented and very often defined and presented only by focusing on specific aspects of the methodology. The role played by meta- models becomes fundamental for comparing and evaluating the methodologies. In fact a meta-model specifies the concepts, rules and relationships used to define methodologies. Although it is possible to describe a methodology without an explicit meta-model, formalising the underpinning ideas of the methodology in question is valuable when checking its consistency or planning extensions or modifications. A good meta-model must address all the different aspects of a methodology, i.e. the process to be followed, the work products to be generated and those responsible for making all this happen. In turn, specifying the work products that must be developed implies dening the basic modelling building blocks from which they are built. As a building block, the agent abstraction alone is not enough to fully model all the aspects related to multi-agent systems in a natural way. In particular, different perspectives exist on the role that environment plays within agent systems: however, it is clear at least that all non-agent elements of a multi-agent system are typically considered to be part of the multi-agent system environment. The key role of environment as a first-class abstraction in the engineering of multi-agent system is today generally acknowledged in the multi-agent system community, so environment should be explicitly accounted for in the engineering of multi-agent system, working as a new design dimension for agent-oriented methodologies. At least two main ingredients shape the environment: environment abstractions - entities of the environment encapsulating some functions -, and topology abstractions - entities of environment that represent the (either logical or physical) spatial structure. In addition, the engineering of non-trivial multi-agent systems requires principles and mechanisms for supporting the management of the system representation complexity. These principles lead to the adoption of a multi-layered description, which could be used by designers to provide different levels of abstraction over multi-agent systems. The research in these fields has lead to the formulation of a new version of the SODA methodology where environment abstractions and layering principles are exploited for en- gineering multi-agent systems.

Smart Sensors For Interoperable Smart Environment

Smart Environments are currently considered a key factor to connect the physical world with the information world. A Smart Environment can be defined as the combination of a physical environment, an infrastructure for data management (called Smart Space), a collection of embedded systems gathering heterogeneous data from the environment and a connectivity solution to convey these data to the Smart Space. With this vision, any application which takes advantages from the environment could be devised, without the need to directly access to it, since all information are stored in the Smart Space in a interoperable format. Moreover, according to this vision, for each entity populating the physical environment, i.e. users, objects, devices, environments, the following questions can be arise: “Who?”, i.e. which are the entities that should be identified? “Where?” i.e. where are such entities located in physical space? and “What?” i.e. which attributes and properties of the entities should be stored in the Smart Space in machine understandable format, in the sense that its meaning has to be explicitly defined and all the data should be linked together in order to be automatically retrieved by interoperable applications. Starting from this the location detection is a necessary step in the creation of Smart Environments. If the addressed entity is a user and the environment a generic environment, a meaningful way to assign the position, is through a Pedestrian Tracking System. In this work two solution for these type of system are proposed and compared. One of the two solution has been studied and developed in all its aspects during the doctoral period. The work also investigates the problem to create and manage the Smart Environment. The proposed solution is to create, by means of natural interactions, links between objects and between objects and their environment, through the use of specific devices, i.e. Smart Objects

Satellite and in situ data integrated analysis to study the upper ocean an coastal environment of the Italian seas

The thesis objectives are to develop new methodologies for study of the space and time variability of Italian upper ocean ecosystem through the combined use of multi-sensors satellite data and in situ observations and to identify the capability and limits of remote sensing observations to monitor the marine state at short and long time scales. Three oceanographic basins have been selected and subjected to different types of analyses. The first region is the Tyrrhenian Sea where a comparative analysis of altimetry and lagrangian measurements was carried out to study the surface circulation. The results allowed to deepen the knowledge of the Tyrrhenian Sea surface dynamics and its variability and to defined the limitations of satellite altimetry measurements to detect small scale marine circulation features. Channel of Sicily study aimed to identify the spatial-temporal variability of phytoplankton biomass and to understand the impact of the upper ocean circulation on the marine ecosystem. An combined analysis of the satellite of long term time series of chlorophyll, Sea Surface Temperature and Sea Level field data was applied. The results allowed to identify the key role of the Atlantic water inflow in modulating the seasonal variability of the phytoplankton biomass in the region. Finally, Italian coastal marine system was studied with the objective to explore the potential capability of Ocean Color data in detecting chlorophyll trend in coastal areas. The most appropriated methodology to detect long term environmental changes was defined through intercomparison of chlorophyll trends detected by in situ and satellite. Then, Italian coastal areas subject to eutrophication problems were identified. This work has demonstrated that satellites data constitute an unique opportunity to define the features and forcing influencing the upper ocean ecosystems dynamics and can be used also to monitor environmental variables capable of influencing phytoplankton productivity.

Individuals in the Workplatform. Exploring Implications for Work Identity and Algorithmic Reputation Management

In the new world of work, workers not only change jobs more frequently, but also perform independent work on online labor markets. As they accomplish smaller and shorter jobs at the boundaries of organizations, employment relationships become unstable and career trajectories less linear. These new working conditions question the validity of existing management theories and call for more studies explaining gig workers’ behavior. Aim of this dissertation is contributing to this emerging body of knowledge by (I) exploring how gig workers shape their work identity on online platforms, and (II) investigating how algorithmic reputation changes dynamics of quality signaling and affects gig workers’ behavior. Chapter 1 introduces the debate on gig work, detailing why existing theories and definitions cannot be applied to this emergent workforce. Chapter 2 provides a systematic review of studies on individual work in online labor markets and identifies areas for future research. Chapter 3 describes the exploratory, qualitative methodology applied to collect and analyze data. Chapter 4 presents the first empirical paper investigating how the process of work identity construction unfolds for gig workers. It explores how digital platforms, intended both as providers of technological features and online environments, affect this process. Findings reveal the online environment constrains the action of workers who are pushed to take advantage of platform’s technological features to succeed. This interplay leads workers to develop an entrepreneurial orientation. Drawing on signaling theory, Chapter 5 understands how gig workers interpret algorithmic calculated reputation and with what consequences for their experience. Results show that, after complying to platform’s rules in the first period, freelancers respond to algorithmic management through different strategies – i.e. manipulation, nurturing relationships, and living with it. Although reputation scores standardize information on freelancers’ quality, and, apparently, freelancers’ work, this study shows instead responses to algorithmic control can be diverse.

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.

New insights into vaginal environment during pregnancy: a multi-omics approach

The present thesis aims to provide a thorough comprehension of the vaginal ecosystem of pregnant women and enhance the knowledge of pregnancy pathophysiology. The first study emphasized the importance of limiting protein intake from animal sources, consuming carbohydrates, and avoiding starting pregnancy overweight to maintain a healthy vaginal environment characterized by lactobacilli and related metabolites. In the second paper, a reduction in bacterial diversity, an increase in Lactobacillus abundance, and a decrease in bacterial vaginosis-related genera were observed during pregnancy. Lactobacillus abundance correlated with higher levels of lactate, sarcosine, and amino acids, while bacterial vaginosis-related genera were associated with amines, formate, acetate, alcohols, and short-chain fatty acids. An association between intrapartum antibiotic prophylaxis for Group B Streptococcus and higher vaginal abundance of Prevotella was found. Moreover, women experiencing a first-trimester miscarriage displayed a higher abundance of Fusobacterium. The third study explored the presence of macrolides and tetracyclines resistance genes in the vaginal environment, highlighting that different vaginal microbiota types were associated with distinct resistance profiles. Lactobacilli-dominated ecosystems showed fewer or no resistance genes, while women with increased bacterial vaginosis-related genera were positive for resistance genes. The last two papers aimed to identify potential biomarkers of vaginal health or disease status. The fourth paper showed that positivity for Torquetenovirus decreased from the first to the third trimester, being more prevalent in women with higher vaginal leukocyte counts. Torquetenovirus-positive samples showed higher levels of cytokines, propionate, and cadaverine. Lactobacillus species decreased in Torquetenovirus-positive samples, while Sneathia and Shuttleworthia increased. The last work pointed out the association between clade 2 of Gardnerella vaginalis and bacterial vaginosis. Moreover, as the number of simultaneously detected G. vaginalis clades increased, bacterial vaginosis-associated bacteria also tended to increase. Additionally, sialidase gene levels negatively correlated with Lactobacillus and positively correlated with Gardnerella, Atopobium, Prevotella, Megasphaera, and Sneathia.