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Air demand forecasting for passengers and freight in Italy: A comparison of two statistical models
Full text linkAir transport forecasting has received significant attention in the literature. Furthermore, economic growth and population are significantly associated with the aviation industry. Moreover, the time series of air passenger and freight demand usually exhibit a complex behaviour with high volatility and irregularity, particularly when considering the economic factors associated with freight demand. In this research, we implemented two different statistical methods, namely the SARIMAX model and the structural time series approach, to fit and forecast both the air passenger and freight demand, considering economic variables and population as regressors. Both methods can deal with seasonality and trend; interestingly, the structural time series model can also estimate the cycle by decomposing the time series using the Kalman filter method. We applied the two methods to monthly data obtained from the Italian national website Assaeroporti for the period from January 2000 to December 2023. We computed predictions for the passenger and freight demand up to 2035, with a monthly and yearly resolution. For this aim, it was necessary to implement separate time series models for the economic regressors and population to plug in corresponding forecasts in the demand models. The results could be particularly useful for optimizing air traffic infrastructure and guiding strategic investment, particularly in the planning and adoption of sustainable aviation technologies (e.g., electric and hybrid-electric systems, new sustainable fuels)
Inconspicuous Consumption Scale - development and validation
No full textWe propose a new definition of inconspicuous consumption (IC) as an individual disposition and present an instrument for measuring this variable. The article describes the successive stages of the construction of the Inconspicuous Consumption Scale (ICS). The results of a preliminary selection of items and exploratory and confirmatory factor analyses have led to the development of an instrument which measures four factors that make up the global ICS: Knowledge, Services, Experiences, and Subtle Brand Signals. Reliability and validity studies carried out in a sample of 1,330 respondents show that the ICS has satisfactory psychometric properties
L’EVOLUZIONE DEI METODI DI ALLENAMENTO NEL CICLISMO: DALLE BASI EMPIRICHE ALLA SCIENZA APPLICATA
No full textTramandare il valore culturale: strategie integrate di conservazione e valorizzazione per le solfare siciliane di Floristella e Grottacalda
No full textThis work focuses on the Pennisi Palace of the Floristella-Grottacalda Mine, with special attention to its
historical genesis, architectural features, conservation works, and the criteria for its completion and enhancement. Through
a historical-critical perspective, the text situates the building within the framework of the Floristella-Grottacalda Mining
Park, yet makes it the focal point of a broader analysis of forms of landowner representation in the 19th-century Sicilian
sulphur industry. The dual residential and administrative function of the palace is explored, characterised by a strong
symbolic value of control and authority. The essay then discusses the restoration projects initiated from the early 2000s,
the challenges arising from discontinuous funding, and the prospects for completion through compatible and reversible
interventions. Finally, guidelines are proposed for its reuse as a museum hub and research centre, integrating digital
technologies and sustainable governance strategies, to transform the palace into a centre of memory and cultural innovation
within the context of Sicilian industrial archaeology
Refugee integration in rural areas in Italy: the role of multi-actor networks in providing effective temporary reception services
No full textThe Boundaries of Affective Computing
No full textAffective computing (AC) is an interdisciplinary field at the intersection of computer science, psychology, and cognitive science, wich has the aim of studying and developing computational apparatuses capable of detecting, processing, interpreting, and simulating human emotion. It has led to the distinction of two currents in AI research: ‘strong’ AI claims that one day AI technology will reach a level of development such that computing machines will be entertaining thoughts in the same way humans do, with full-fledged, firstperson, subjective, qualitative experience (including emotion); ‘weak’ AI, on the other hand, relies on the conviction that there is an impassable ontological barrier between the phenomena occurring in a human brain and the workings of a computing machine, so that AI must be content with reproducing the appearance and the results of human actions, and giving up the ambitious goal of creating the subjective experience of human thought inside a machine. Despite the alarmist warnings of some scholars about sentient machines taking
over humanity, there is no evidence that the claims of strong AI can ever become true; thus claims that machines can entertain thoughts the way humans do belong in science fiction rather than realistic imaginings of the futur
Voltou o Xerión: nexos offline/online en el paisaje semiótico de A Coruña, entre mosaicos y redes
No full textThis study analyses the phenomenon of mosaic skulls that have appeared in A Coruña since 2021 as an expression of open-source anonymous street art.
Drawing on Mediated Discourse Analysis (Scollon, 2001) and Nexus Analysis (Scollon & Wong Scollon, 2004), the proliferation of these skulls is interpreted as a nexus of offline/online practices – subversive, self-managed, and participatory – that reconfigure the urban landscape and construct a collective identity around the local myth of Xerión.Este estudio analiza el fenómeno de las calaveras de mosaico aparecidas en A Coruña desde 2021 como expresión de arte urbano anónimo de código abierto.
Desde el análisis del discurso mediado (Scollon, 2001) y el Nexus Analysis (Scollon y Wong Scollon, 2004), la proliferación de las calaveras se interpreta como un nexo de prácticas offline-online, subversivas, autogestionadas y participativas, que reconfigura el paisaje urbano y construye una identidad colectiva en torno al mito local de Xerión
Strategic Potential of Patent-Based RAG Systems for Industrial R&D Applications: A Comparison with General-Purpose LLMs
No full textLarge language models (LLMs) have rapidly transformed how information is accessed and generated across domains by leveraging deep learning to produce human-like responses. Their applications have become powerful in supporting coding, law, medicine, and design tools. However, despite their capabilities, LLMs often suffer from critical limitations such as hallucinations, lack of domain specificity, and reliance on generalized internet-based knowledge. These limitations could pose risks for industrial research and development (R&D), where precision and innovation are essential. This study investigates the potential of a patent-based Retrieval-Augmented Generation (RAG) tool (Omnia) to support R&D activities more effectively than general-purpose LLMs (Google AI Studio). Omnia accesses patent databases in real-time to provide structured and validated data, offering reliable and domain-specific responses. Multiple research questions were generated to evaluate the responses from both Omnia and Google AI Studio, which are addressed through targeted case studies. Findings demonstrate that patent-based RAG systems can offer significant advantages in R&D scenarios, including semantic search accuracy, TRIZ-based problem-solving, technical failure analysis, prospective life cycle assessment, and identification of circular economy opportunities