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Digital image correlation and cracked hinge model applied to notched beams reinforced with GFRP bars
No full textIn this study, three-point bending fracture tests of notched beams reinforced with a glass fiber reinforced polymer bar are conducted. Plain concrete beams are also tested for comparison. Two different widths are considered for the beams. Digital image correlation (DIC) is used on the lateral surface of the beam to study the fracture process zone (FPZ) and neutral axis depths at different load stages. A non-linear analytical model named cracked hinge model and cross-sectional analysis are used to obtain the force in the bar and the interfacial slip between bar and concrete, which are compared to the results from pull-out tests
Leveraging Incremental Decision Trees and In-Vivo Biosensors for an Explainable Plant Health Monitoring System
No full textAmong the factors concerning plant development and agricultural yield, water stress and drought emerge as pivotal factors. Indeed, the ability to know in advance imminent water stress in crops based on measurable biochemical metrics is priceless, as it offers the opportunity for rapid interventions aimed at restoring optimal growth conditions before the plants show clear visible stress symptoms.In this work, we present an explainable system for smart agriculture focused on the continuous monitoring of the water stress condition of tomato plants, achieved through a new in-vivo biosensor, named bioristor. The proposed system embeds an incremental and explainable by design classifier. Specifically, we experimented with the traditional Hoeffding decision tree and its fuzzy version. This system analyzes the data received from bioristors to assess the health status of a tomato plant and classifies it into four classes. The proposed system also leverages an incremental learning technique, which allows the classification model to be updated during the monitoring period, to maintain adequate classification performance. In this way, the conditions of the plants are monitored continuously with an effective model, allowing for timely countermeasures to be taken if a water stress situation is detected. We present preliminary results on a real dataset, using four features related to the ionic currents within the plant sap, measured through bioristors. We assessed the system performance both in terms of classification ability and model complexity, obtaining promising results and the generation of interesting rules that could allow the implementation of effective countermeasures to keep the plants healthy as long as possible
Methods for Minimizing Side Effects in Nasal Vestibule Interventional Radiotherapy: An Update
No full textNarrative Transformation for Empowering Women in the Face of Illness. Insights from the “Sorrisi in Rosa” Project
No full textThe need of society to activate medical prevention has led the scientific community to value narrative skills to increase the understanding and acceptance of disease. With the diagnosis of cancer, everything changes: from the perception of one’s body to the relationship with family members, and it is only through the narration of one's experience of treatment that the person shares their feelings, emotions, fears and concerns with other individuals, retracing the imaginary experience and sharing a personal phase of their life. This approach meets Humanitas’ need to evaluate the “Sorrisi in Rosa” (SiR) project dedicated to accompanying women undergoing screening for or diagnosed with breast cancer to highlight the elements of impact and spaces for development in accompanying patients. Through emotional support and sharing their stories, patients involved in the program can develop a sense of community and mutual understanding. This not only provides an environment conducive to coping with the challenges of the disease but can also help reduce the sense of isolation that often accompanies breast cancer. The monitoring by CREMIT (Center for Research on Media Education, Innovation and Technology), in collaboration with IRCCS Humanitas is part of the desire to investigate and understand how storytelling can make illness and treatment a transformative process, capable of rereading and coping better with one’s personal experience as a woman. The research presented here, divided into three phases, focuses on analysing the narratives produced within the project and the questionnaire administered, to improve care and support for women involved in breast cancer screening and treatment programs
Innovation and Sustainability of the Business Models: From Experiences to Financial Impacts.
No full textIn the corporate context, the concept of innovation is increasingly combined with the concept of sustainability. In the past, the innovation-sustainability combination was not always conceived in a positive sense, as everything that had to comply with environmental and ecological needs required a path of almost “involution” of lifestyles, and the products had to be generally low-high-performance and made with recycled materials. Today, this vision has been replaced by an idea that focuses not only on a more attentive style of consumption but also on a new way of doing business, capable of balancing respect for the planet with the supply of high-quality products, “environmentally friendly” and capable of optimizing lifestyles, forcing businesses to transition from a classic linear model to a circular model. This is a very delicate and profound step that leads to the innovation of the companies’ business model. This innovative process generates and implies important changes in terms of financial flows and risk and requires the development of specific management skills. In the transition toward circular economy business models, it is important that companies include, estimate and exploit their value in terms of reducing costs and risks, increasing competitiveness and operational efficiency, better responding to demand from the market, reduction of stranded assets and improvement of long-term profitability. The chapter aims, on the one hand, to illustrate the financial benefits of circular economy business models in terms of performance, risks and cash flows of investments and the effects on fundamental financial dynamics, and on the other hand, to highlight, through the study of concrete experiences in Italy, the real operating methods of companies in a logic of continuous circular renewal
Identification of damages in a concrete beam: a modal analysis based method
No full textStructural Health monitoring (SHM) strategies can play a pivotal role in the perspective of enhancing structures and infrastructures life cycle and maintenance operations. A plethora of sensors and technologies can be employed in this field; in a seismic context, vibrational tests are particularly relevant, being able to give an insight on the dynamic characteristics of the structure itself. In particular, modal parameters can be considered in order to detect damages. A comparison between a certain test time and 0 test time (i.e., undamaged structure) is commonly performed; to this aim numerical models result particularly useful to provide baseline data (often unavailable in pre-existing structures), but they need to be validated before use. Non-contact techniques, like scanning laser Doppler vibrometry, can be exploited to do this. In this paper a numerical model of a scaled concrete beam is realized and validated through LDV data, then it is used to design load tests for progressive damages generation. Modal analysis is conducted after different load trials to evaluate changes of modal parameters in relation to the damage occurred; also, damage-related indices are proposed. The results confirmed the suitability of LDV for dynamic analyses of cement-based structures and this can be particularly useful when big structures (e.g., bridges) have to be monitored in-field. The numerical model was validated with acceptable absolute errors in terms of natural frequencies (between 26 Hz and 131 Hz) and high Modal Assurance Criterion (MAC) values (0.85-0.93). Moreover, the proposed methodology allows to detect damages also in a concise way through synthetic indices (with changes >50% in damaged vs undamaged conditions) and early warnings could be generated according to their values, hence supporting decision-making procedures in the building management scenario
How to Valorize Construction and Demolition Wastes? Beyond the State of the art Through Vision Systems and Artificial Intelligence Tools
No full textThe efficient tracking of Construction and Demolition Wastes (CDWs) is pivotal in a perspective of sustainability and circularity in the construction sector. Sensing and digital technologies can undoubtedly play a relevant role in this context. This paper proposes an innovative approach for detection, quantification, and characterization of CDWs in order to provide information exploitable through optimized valorization routes made available via dedicated service platforms. The preliminary results are promising, and the solution will be iteratively refined and improved thanks to continuous data collection from real-world scenarios
A novel approach to investigate severe asthma and COPD: the 3D Ex Vivo Respiratory Mucosa Model
No full text: Biologic drugs have been shown to enhance the treatment of severe asthma and COPD. Monoclonal antibodies against specific targets have dramatically changed the management of these conditions. Although the inflammatory pathways of asthma and COPD have already been clearly outlined, alternative mechanisms of action remain mostly unexplored. They could provide additional insights into these diseases and their clinical management. In vivo or in vitro models have thus been developed to test alternative hypotheses. This study describes sophisticated ex vivo models that mimic the response of human respiratory mucosa to disease triggers, aiming to narrow the gap between laboratory studies and clinical practice. These models successfully replicate crucial aspects of these diseases, such as inflammatory cell presence, cytokine production, and changes in tissue structure, offering a dynamic platform for investigating disease processes and evaluating potential treatments, such as monoclonal antibodies. The proposed models have the potential to enhance personalized medicine approaches and patient-specific treatments, helping to advance the understanding and management of respiratory diseases. This article illustrates the replication of asthma and COPD conditions in a laboratory setting and the potential applications of this methodology