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Bridging the cultural gap. Chinese professional subtitles vs fansubs of l’amica geniale
Get PDFAwarded “Best Foreign TV Series” at the Shanghai Television Festival in 2020, the Italian TV series L’amica geniale gained significant popularity among Chinese audiences. Despite aspects of its plot that seemingly conflict with China’s official restrictions on foreign media imports, the series was broadcast on three major Chinese streaming platforms. However, the official Chinese subtitles have faced criticism, with viewers expressing dissatisfaction over plot omissions and the mistranslation of Italian cultural references. In contrast, five unofficial, fansubbed versions are playing a crucial role in the series’ success.
This study aims to investigate the challenges faced by the Chinese official audiovisual translation industry in accurately conveying cultural references, particularly in the context of minority languages like Italian. It also seeks to explore the role of fansubbing as an alternative and often more effective means of cross-cultural mediation. While employing subversive strategies, Chinese fansubbers serve as a key gateway for introducing Italian media to Chinese audiences.
The study adopts a multi-method, triangulated qualitative approach, combining contrastive translation analysis, netnography, and audience reception research. The contrastive translation analysis categorizes cultural references by domains and translation strategies, following the frameworks of Molina (2006), Díaz Cintas and Remael (2007, 2021), Pedersen (2011), and Ranzato (2016). This is complemented by netnographic research (Kozinets 2010), involving online archival data collection and semi-structured interviews with some of the translators. Additionally, a small-scale reception study using focus group discussions assesses how audiences perceive the presumably mistranslated cultural references and their impact on the viewing experience.
The findings highlight the limitations of the official Chinese AVT industry in handling Italian-language content and emphasize the critical role of fansubbing in bridging linguistic and cultural gaps. Fansubs, despite their unofficial status, help ensure a more authentic and accessible representation of Italian media for Chinese audiences
AI-assisted climate downscaling for rapid assessment of ERA5 reanalysis across different geographical domains
Get PDFState-of-the-art General Circulation Models (GCMs) typically operate at a coarse spatial resolution, posing challenges in accurately assessing regional climate changes and their impacts. This limitation is particularly evident in representing regional-scale topography and meteorological processes, including extreme weather events. Traditional dynamical downscaling methods address these issues but are computationally intensive, while statistical approaches, though efficient, often compromise spatial consistency. This study introduces an innovative application of Conditional Generative Adversarial Networks (cGANs) for climate downscaling to address these challenges. GANs consist of two interconnected components: a generative and discriminative models. The generative model is based on ERA5 climate reanalysis data (Hersbach et al., 2020, ~31 km resolution) and learns to produce high-resolution data. The discriminator uses the VHR-REA_IT dataset (Raffa et al., 2021, ~2.2 km resolution) to distinguish between real and generated data by the GAN (ERA5-DownGAN). This study pioneers the use of cGANs to downscale ERA5 reanalysis data to high horizontal resolution (~2.2 km) for both temperature and precipitation fields. The training phase (1990-2000) allows the cGAN to learn the high-resolution patterns, while the testing phase (2001-2005) evaluates its performance against VHR-REA_IT. The cGAN accurately reproduces patterns and value ranges for both fields, exhibiting a slight tendency toward cooler values. Furthermore, the cGAN downscaling model maintains strong consistency across all percentile classes (from the 1st to the 99th) for temperature, and in nearly all classes for total precipitation, with a tendency to generate outliers in the precipitation fields for the extreme classes (98th-99th percentiles). Additionally, the GAN model developed was validated in collaboration with NCAR through an added case study centered on the U.S. territory. This research demonstrates the significant potential of GANs to address the spatial limitations of traditional climate models, offering a powerful method for high-resolution climate data generation and contributing valuable insights into regional climate dynamics
Exploring energy sharing mechanisms and prosumer integration in electrical and thermal energy communities
Get PDFEnergy communities have gained momentum across Europe, enabling citizens to participate in energy production, consumption, and distribution to support the energy transition. The 2018 European RED II directive has driven the rapid expansion of renewable energy communities and collective self-consumption, supported by regulations and incentives that provide environmental, social, and economic benefits.
Despite their potential, the complexity of energy communities presents challenges in understanding their aspects. A systematic literature review was conducted to clarify their characteristics, opportunities, and limitations within the European context. The findings reveal that most studies focus on social, political, and economic aspects, with limited attention to technological factors. Electricity communities, particularly photovoltaic systems, dominate the research landscape due to national incentives, while thermal energy communities remain underexplored.
A key challenge for energy communities is ensuring equitable benefit distribution from shared energy. Italy, a pioneer in EU policy implementation, offers valuable insights into their practical application. In this thesis, an Italian energy community integrated with a district heating network was analyzed, demonstrating significant reductions in energy demand and emissions without additional investments. However, the virtual energy-sharing model complicates the tracking of individual prosumer benefits.
To address this issue, four allocation algorithms were developed: a consumption-proportional key, a Pearson correlation-based key, a trend-based key, and a hybrid approach. A simulated community of eight users with real hourly energy profiles was used to assess the algorithms' effectiveness.
Furthermore, the study proposes an innovative approach to retrofitting district heating substations into bidirectional systems, allowing prosumers to consume and share surplus thermal energy. A numerical model, validated through experimental tests, showed promising results in improving energy performance and increasing the useful energy coefficient.
This research provides valuable insights into electrical and thermal energy sharing within communities, addressing regulatory and operational challenges and supporting the growth of thermal energy communities across Europe
Experimental analysis of turbulent flows at high Reynolds numbers in the CICLoPE "Long Pipe"
Get PDFThis thesis aims to investigate wall shear stress uncertainties and asymptotic scaling laws in turbulent pipe flows, with a focus on their implications for active flow control strategies. The experiments were conducted mainly at the Long Pipe facility of the CICLoPE laboratory at the University of Bologna, a state-of-the-art facility designed to reproduce canonical turbulent pipe flow across a wide range of Reynolds numbers while minimizing measurement uncertainties related to spatial resolution. This research include the development and refinement of the Oil Film Interferometry (OFI) as a direct local measurement technique for wall shear stress in the Long Pipe and a comprehensive uncertainty analysis comparing OFI with static pressure drop methods, classical methodology to obtain global wall shear stress in pipe flows. These findings enabled the reduction of overall uncertainties in determining asymptotic scaling laws. Additionally, OFI was applied to active flow control scenarios, demonstrating its versatility. Further investigations into wall-pressure fluctuations revealed their scaling behavior and coherence with near-wall velocity fluctuations both streamwise and wall-normal. A consistent linear correlation in the logarithmic region of the flow highlights the potential for scalable, real-time flow control applications. These results affirm the CICLoPE facility’s significant role in advancing the understanding of wall-bounded turbulence and its application to active drag reduction strategies
Physical layer solutions for the security of wireless communications
Get PDFThe rapid growth in the number of wireless devices has significantly increased the complexity and vulnerability of communication networks. In wireless communication, the inherent shared nature of the wireless medium creates unique challenges for security, including eavesdropping, jamming, and unauthorized access. Traditional cryptographic methods, though highly effective, are often unsuitable for many wireless devices due to their limited computational power and energy constraints. This has spurred the need for alternative solutions that can complement standard cryptography algorithms. In particular, some characteristics of the physical layer can be leveraged to enhance security without overburdening devices. Physical Layer Security offers a promising approach by taking advantage of some inherent properties of the wireless channel, such as fading, noise, and interference, to secure communications. This thesis focuses on two major aspects of physical layer security. First, an analysis of wireless channels for secure key generation is presented, focusing on the spatial correlation properties of the channel and its impact on key generation. Then, the use of Frequency Diverse Arrays for geofencing applications is proposed, showing the capabilities of Frequency Diverse Arrays, and an analysis on their actual advantages
Monocular depth estimation based on ground geometry
Get PDFMonocular depth estimation, an ill-posed problem due to scale ambiguity, relies on single-image data, lacking multi-view consistency cues. Unlike stereo or LiDAR methods, it avoids costly sensors and complex calibration, making it suitable for autonomous driving, robotics, and augmented reality. Recent deep learning advancements enable end-to-end depth prediction using extensive annotations, but creating high-quality datasets is time-consuming and expensive. Self-supervised methods reduce reliance on labels by leveraging video sequences, yet they often assume static scenes, leading to failures with dynamic objects. To address these limitations, we integrate ground geometry into depth estimation. In static scenes, ground normal vectors from human probes provide accurate scale information, aligning predicted 3D scenes with real-world environments and enabling metric depth estimation. For dynamic scenes, we assume object depths align with their ground contact points. We propose a ground propagation module that iteratively propagates ground features to dynamic objects in the decoder’s latent space, improving depth calibration. Experimental results show enhanced accuracy for moving objects and superior generalization. In summary, leveraging ground geometry significantly improves monocular depth estimation in both static and dynamic environments, offering a reliable solution for diverse applications
Torsion testing for characterizing the plastic behavior in metals: determination of material flow stress for FEM-based design and optimization of metal forming processes
Get PDFThe thesis investigates the use of torsion testing as a method for characterizing the plastic behavior of metals, with particular emphasis on determining material flow stress, a critical parameter for FEM simulations in metal forming processes. The study addresses limitations in traditional testing methods, such as tensile and compression tests, which fail to capture the full extent of material flow stress. In contrast, characterization via torsion test offers several advantages, including the ability to analyze materials for high values of strain, strain rate, and temperature. A detailed comparison is initially conducted among the methods for characterizing the cold plastic behavior of ETPcopper. The testing methods and the different analytical models for data processing are analyzed. The comparison reveals that the material exhibits different plastic behaviors under distinct stress states, due to the development of varying textures and differing hardening rates. Consequently, a new approach to processing cold torsion test data is proposed. Subsequently, the results from torsion copper characterization are applied to the study, modeling, and optimization of the wire drawing process for electrical cable production. A theoretical multi-pass drawing model is developed, considering the entire process and focusing on the relationship between drawing and back-stresses. The model is implemented by incorporating the material’s plastic behavior as process conditions varied, obtained via cold torsion tests conducted on copper wire rods from four different suppliers. A numerical model is then proposed for simulating the drawing process in individual passes. The characterization performed via hot torsion tests on various AA6082 aluminum alloys is then presented and compared. The influence of flow stress modeling on numerical simulation results is assessed by comparing predicted data with experimental results from an industrial extrusion process. In conclusion, torsion testing proves to be an effective method for material characterization, enhancing FEM simulation accuracy and manufacturing process control
The role of innovation systems in the development of a circular and sustainable bioeconomy
Get PDFInnovation is central to the bioeconomy, as emphasized in key definitions (e.g., Global Bioeconomy Summit, European Commission). Despite its importance, the bioeconomy innovation literature lacks original frameworks. This PhD thesis advances the study of Knowledge and Innovation Systems for the Bioeconomy (KISB), adapting the Innovation Systems (IS) model to this field. The KISB framework was developed in three steps. First, a systemic literature review identified its scope and key characteristics. Second, using the Italian bioeconomy as a case study, we analysed the impact of EU innovation policies (e.g., FP research projects) on knowledge and innovation networks. Third, we examined the relationships and information flow within the Italian KISB. Findings suggest that the KISB framework is useful for both policy and business. In Italy, the network is dominated by public research institutes and universities, while private companies, public entities, and other actors (e.g., associations, and foundations) have more peripheral roles. Only select entities from these groups hold influential positions within the network. Public bodies are the dominant component, with research institutions playing a subordinate role and private companies acting as interactive components. Regarding information flow, no intermediaries or connectors were found. Instead, two main groups emerged: promoters (private companies, public bodies, and other entities) and the target group (higher education and research institutes). Policy recommendations include: establishing a central body for scientific and technological policy (e.g., strengthening the National Bioeconomy Coordination Group) with effective communication channels, fostering learning and knowledge-sharing, and supporting commercialization grants, investments, and entrepreneurship
What we can learn from each other: a multi-sited analysis of lay expertise and caregiving for people living with alzheimer's and dementia in emilia-romagna and the united states
Get PDFThis dissertation explores how informal caregivers in Emilia-Romagna, Italy, and the Midwest, United States develop lay expertise when caring for individuals with Alzheimer’s Disease and Related Dementias (ADRD). Using multi-sited ethnography, it draws on in-depth interviews, participant observation in support groups, netnographic analysis of online caregiver forums, and secondary data from the National Study of Caregiving. Grounded theory highlights central themes: biographical disruption, the process of “becoming” a caregiver, and the fusion of practical skills with emotional intelligence. Lay expertise is framed as evolving knowledge, blending experiential, embodied, formal, and evidence-based elements to address caregiving’s complex demands. Findings show caregiving often triggers a profound life shift, requiring emotional resilience and logistical flexibility. Caregivers continuously learn by doing, experiencing both triumphs and setbacks. Support groups and online forums play pivotal roles, helping reduce burden, foster self-efficacy, and cultivate peer-to-peer learning. By employing situational analysis, this research examines the social ecologies of caregiving, revealing how cultural norms, healthcare systems, social networks, and non-human actors intersect to shape caregivers’ experiences. It argues that lay expertise extends beyond technical competence, emphasizing empathy, personal growth, and reflexive awareness of one’s own limits. Caregivers who thrive actively seek support and prioritize self-care. Ultimately, this dissertation contends that lay expertise is neither secondary nor inferior to professional knowledge. Rather, it is a vital, nuanced way of knowing, emerging from the lived realities of caregiving. Recognizing caregivers as key agents in dementia care challenges traditional power dynamics in healthcare, calling for policies and practices that empower this essential role. By centering caregivers’ voices, the study provides valuable insight into the intricate interplay between individual narratives, social support structures, and healthcare systems, underscoring the need to validate and uphold the expertise gained through the caregiving journey
A pedagogical approach towards a social and solidarity economy: the case of the union of municipalities of Romagna Faentina
Get PDFLa presente tesi di dottorato è il risultato di uno studio di caso condotto in collaborazione tra l’Università di Bologna e l’Unione dei Comuni della Romagna Faentina, nell’ambito della terza missione. L’accordo ha favorito una sinergia tra mondo accademico e pubblica amministrazione per orientare lo sviluppo delle politiche pubbliche. La ricerca si è basata sulla raccolta di dati attraverso documenti, interviste semi-strutturate e focus group, successivamente analizzati tramite la metodologia della Grounded Theory. Questo approccio ha permesso di individuare temi chiave e dinamiche di interazione tra istituzioni locali e cittadinanza nei processi partecipativi, nella cura dei beni comuni e nella governance condivisa, evidenziando opportunità e criticità emergenti. L’obiettivo è promuovere la pedagogia critica come strumento politico, sviluppando e monitorando pratiche e metodologie efficaci per costruire relazioni sinergiche e sostenibili tra i diversi attori, incentivando la cooperazione e la valorizzazione delle risorse locali. La tesi è articolata in quattro capitoli: 1) analisi storica, amministrativa e giuridica del territorio; 2) quadro teorico di riferimento; 3) metodologia adottata; 4) risultati, suddivisi in cinque aree tematiche: la cura, lo spazio pubblico generativo, i patti di cittadinanza, la transizione dalla competizione alla collaborazione, e il ruolo di cultura e arte nei processi partecipativi. Le conclusioni sottolineano tre aspetti chiave: un mandato politico inclusivo che favorisca la partecipazione attiva, un coordinamento strategico per gestire le iniziative locali in modo sinergico, la creazione di un linguaggio comune per facilitare il dialogo tra gli attori coinvolti. Questo approccio consente di costruire ecosistemi di economia sociale, promuovendo giustizia sociale, sviluppo di competenze e collaborazione attiva, per comunità più giuste, inclusive e resilienti.This PhD thesis is the result of a case study conducted in collaboration between the University of Bologna and the Union of Municipalities of Romagna Faentina, within the framework of the third mission. The agreement fostered a synergy between academia and public administration to guide the development of public policies. The research was based on data collection through documents, semi-structured interviews, and focus groups, later analyzed using the Grounded Theory methodology. This approach enabled the identification of key themes and interaction dynamics between local institutions and citizens in participatory processes, the care of common goods, and shared governance, highlighting emerging opportunities and challenges. The objective is to promote critical pedagogy as a political tool, developing and monitoring effective practices and methodologies to build synergistic and sustainable relationships among various stakeholders, fostering cooperation and enhancing local resources.
The thesis is structured into four chapters: 1) historical, administrative, and legal analysis of the territory; 2) theoretical framework of reference; 3) methodological approach adopted; 4) findings, divided into five thematic areas: the dimension of care, public space as a generative place, citizenship pacts, from competition to collaboration, the role of culture and art in participatory processes.
The conclusions highlight three key aspects: an inclusive political mandate that promotes active participation, a strategic coordination body to manage local initiatives synergistically, and the creation of a common language to facilitate dialogue among stakeholders.
This approach enables the construction of social economy ecosystems, fostering social justice, skill development, and active collaboration, leading to fairer, more inclusive, and resilient communities