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Machine Learning-Driven Optimization for Digital Transformation in Non-thermal Food Processing
No full textNon-thermal food processing has opened up new space and has emerged as a promising alternative to conventional thermal methods of food processing. These foods meet the growing consumer demands for high-quality, convenient, and minimally processed foods. The idea of proposing a machine learning (ML) strategy for finding the optimum process parameters and kinetics in food processing applications is new and challenging, but this new innovative approach requires considerable scientific effort. This review presents the applications of ML in the optimization of non-thermal food processing technologies such as high-pressure processing (HPP), pulsed light (PL), ultrasound (US), pulsed electric fields (PEF), cold plasma (CP), and irradiation (IR). These technologies have exhibited conspicuous advantages with respect to microbial inactivation, preservation of food quality, and environmental sustainability. Integration of ML with non-thermal technologies will enable better control and monitor in real time and optimize critical parameters such as pressure, frequency, and treatment duration. While numerical models have conventionally been used successfully for process optimization, ML provides better adaptability by identification of complex nonlinear relationships in food systems for more accurate prediction and adjustment. The key takeaways of this paper lie in the ML-driven monitoring system, integrated sensors, and real-time data accumulation in response to enhancing process efficiency with dependency natures inherently presented by food matrices. Further development of ML models, apparatus collection, and intelligent systems is expected to yield non-thermal food processing methods with enhanced sustainability, safety, and quality
Search for Continuous Gravitational Waves from Known Pulsars in the First Part of the Fourth LIGO-Virgo-KAGRA Observing Run
No full textUnveiling the drivers of riparian vegetation change in Mediterranean river systems via remote sensing
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Seismic behaviour of simply supported reinforced concrete bridges with corroded piers
No full textCorrosion is responsible for seismic performance degradation of reinforced concrete structures such as buildings and bridges. These latter suffer from chloride-induced corrosion due to de-icing salts used in winter times. When this problem affects the critical sections of bridges’ piers, the seismic capacity in terms of ductility and strength is highly affected. This paper aims to investigate the effect of steel corrosion damage in reinforced concrete bridges’ piers. To this end, a case study bridge (built in the 1970s and located in southern Italy) provided with hollow square section piers and simply supported steel and concrete decks, is analysed. Numerical simulations based on the incremental dynamic analysis approach are performed in order to evaluate the global bridge seismic behaviour. In fact, through the construction of the fragility curves of piers regarding different limit states, both in the as-built condition and in degraded ones, it is possible to determine and compare the seismic behaviour as a function of the corrosion extent
The Adaptive Reuse of Architectural Heritage in Dynamic Hubs for Innovation and Sustainability
No full textThe transition to a circular economy is essential to reduce the environmental and climate impacts of current linear patterns of production and consumption, particularly in the construction sector, which has one of the highest environmental impacts. Among the actions of the Commission, aimed at concretising the ecological and digital transition of Europe, there is the ESPR Regulation 2024/1781 that introduces the Digital Product Passport (DPP) as a key tool to ensure transparency and traceability along the entire product value chain, improving resource management and supporting ecodesign. In the construction sector, the Material Passport (MP) and the Building Heritage Material Passport (BHMP) are key tools for documenting the technical characteristics and environmental impacts of materials, to ensure that ecodesign requirements, deconstruction, reuse and recyclability are met. In addition, these tools give an identity to enhance and protect the materials and construction techniques of traditional architecture, especially the interior areas, which are often forgotten. This study examines the major European regulatory actions in favor of circularity, the most significant examples of experimentation of MPs (Material Digital Passport) in the construction sector and the challenges associated with the implementation of this tool, including standardization, Data protection and interoperability. The study proposes an informative Flowchart for data management in DPPs, which divides
the product life cycle into three macro phases, identifying stakeholders and key specifications inherent to each phase; the study also highlights the active role of the “prosumer” in the circular process, underlining the importance of informed participation in product selection and management; and how this actor can influence design from a sustainable and ethical point of view. The use of digital identity is a key step towards decarbonisation and resource optimization in the industrial and construction sectors
