Returns, Discoveries and Displacement.

Riflessioni a partire dal film di Suranga Ketugampala, Still Here

Metaphorical Binominal Constructions in the Domain of Water: A River of Words. Evidence from Italian, Polish and Russian

The study presents a contrastive Italian-Polish-Russian analysis of the leftheaded binominal constructions of the type [N1 of N2] composed of a metaphorical classifier belonging to the semantic domain of watercourse, i.e. It. fiume, Pol. rzeka, Russ. reka ‘river’. The main aim of the usage-based study is to describe and compare the process of metaphorization drawn on the natural aquatic phenomenon by identifying the classes of N2 collocates, the frequency and context of their occurrences in comparable and parallel linguistic corpora. A contrastive, corpus-based approach makes it possible to verify whether and how the metaphor realized by the It. [ fiume di N] construction is expressed in the two Slavic languages. It also helps to describe convergence or divergence with respect to the Italian binominal. Our findings show that the river-metaphor, though grammaticalized to quite different degrees, exhibits similar metaphorical mappings in the three languages

Intraspecific variability of leaf form and function across habitat types

Trait-based ecology has already revealed main independent axes of trait variation defining trait spaces that summarize plant adaptive strategies, but often ignoring intraspecific trait variability (ITV). By using empirical ITV-level data for two independent dimensions of leaf form and function and 167 species across five habitat types (coastal dunes, forests, grasslands, heathlands, wetlands) in the Italian peninsula, we found that ITV: (i) rotated the axes of trait variation that define the trait space; (ii) increased the variance explained by these axes and (iii) affected the functional structure of the target trait space. However, the magnitude of these effects was rather small and depended on the trait and habitat type. Our results reinforce the idea that ITV is context-dependent, calling for careful extrapolations of ITV patterns across traits and spatial scales. Importantly, our study provides a framework that can be used to start integrating ITV into trait space analyses.By using empirical data for two independent dimensions of leaf form and function and 167 species across five habitat types, we show that including intraspecific trait variability in a trait space: (i) rotates the axes of trait variation of the target trait space, (ii) increases the variance explained by these axes and (iii) modifies the functional structure of the trait space. However, these effects were rather small and strongly trait- and habitat-dependent.imag

Evolving waste management: The impact of environmental technology, taxes, and carbon emissions on incineration in EU countries

Amid the urgent global imperatives concerning climate change and resource preservation, our research delves into the critical domains of waste management and environmental sustainability within the European Union (EU), collecting data from 1990 to 2022. The Method of Moments Quantile Regression (MMQR) results reveal a resounding commitment among EU member states to diminish their reliance on incineration, which is evident through adopting green technologies and environmentally conscious taxation policies, aligning with the European Union's sustainability objectives. However, this transition presents the intricate task of harmonizing industrial emissions management with efficient waste disposal. Tailoring waste management strategies to accommodate diverse consumption patterns and unique circumstances within individual member states becomes imperative. Cointegrating regressions highlighted the long-run relationship among the selected variables, while Feasible Generalized Least Squares (FGLS) and Panel-Corrected Standard Errors (PCSE) estimates roughly confirmed MMQR results. ML analyses, conducted through two ensemble methods (Gradient Boosting, GB, and Extreme Gradient Boosting, XGBoost) shed light on the relative importance of the predictors: in particular, environmental taxation, consumption-based emissions, and production-based emissions greatly contribute to determining the variation of combustible renewables and waste. This study recommends that EU countries establish monitoring mechanisms to advance waste management and environmental sustainability through green technology adoption, enhance environmental taxation policies, and accelerate the renewable energy transition

IoT-Assisted Automatic Driver Drowsiness Detection through Facial Movement Analysis Using Deep Learning and a U-Net-Based Architecture

The main purpose of a detection system is to ascertain the state of an individual’s eyes, whether they are open and alert or closed, and then alert them to their level of fatigue. As a result of this, they will refrain from approaching an accident site. In addition, it would be advantageous for people to be promptly alerted in real time before the occurrence of any calamitous events affecting multiple people. The implementation of Internet-of-Things (IoT) technology in driver action recognition has become imperative due to the ongoing advancements in Artificial Intelligence (AI) and deep learning (DL) within Advanced Driver Assistance Systems (ADAS), which are significantly transforming the driving encounter. This work presents a deep learning model that utilizes a CNN–Long Short-Term Memory network to detect driver sleepiness. We employ different algorithms on datasets such as EM-CNN, VGG-16, GoogLeNet, AlexNet, ResNet50, and CNN-LSTM. The aforementioned algorithms are used for classification, and it is evident that the CNN-LSTM algorithm exhibits superior accuracy compared to alternative deep learning algorithms. The model is provided with video clips of a certain period, and it distinguishes the clip by analyzing the sequence of motions exhibited by the driver in the video. The key objective of this work is to promote road safety by notifying drivers when they exhibit signs of drowsiness, minimizing the probability of accidents caused by fatigue-related disorders. It would help in developing an ADAS that is capable of detecting and addressing driver tiredness proactively. This work intends to limit the potential dangers associated with drowsy driving, hence promoting enhanced road safety and a decrease in accidents caused by fatigue-related variables. This work aims to achieve high efficacy while maintaining a non-intrusive nature. This work endeavors to offer a non-intrusive solution that may be seamlessly integrated into current automobiles, hence enhancing accessibility to a broader spectrum of drivers through the utilization of facial movement analysis employing CNN-LSTM and a U-Net-based architecture

Il capitolo di Francesco Berni contro Adriano VI

Il contributo si sofferma sul lungo capitolo in terza rima scritto da Berni contro il papa Adriano VI. Il testo viene analizzato sotto il profilo storico e retorico

Osservazioni sulla doverosità della notifica al contumace dell’atto di intervento del successore a titolo particolare ex art. 111 c.p.c.

L’autore si sofferma sull’istituto disposto dall’art. 292 c.p.c. e del suo coordinamento con l’atto di intervento ex art. 111 c.p.c. e della riassunzione ex art. 303 c.p.c.The author analyzes art. 292 code of civil procedure and the problem of how this rule can be coordinated to art. 111 and 303 code of civil procedure

Self-Evident Truths, Post-Truths, and the American Myth

This first volume of the Series “Quaderni del Centro Studi Americani” is dedicated to the much-debated topic of Post-Truth. Taking its cue from the growing relevance of issues related to the controversial topic of post-truth, the 2023 edition of the Center for American Studies Seminar on U.S. History, Literature, and Culture aimed at analyzing the various facets and implications of this concept from historical, philosophical, and literary perspectives. The speakers were invited to reflect on the meaning of ‘post-truth,’ elected word of the year in 2016 by the Oxford Dictionaries; characterized by a marked polysemy and a strong divergence (at times even incongruence) in its uses, the term had already saturated public debates in 2017. Post-truth is sometimes understood as a mode of communication in which objective facts are less relevant than emotions and personal beliefs; in other cases, it is used to indicate the dissemination of deliberately and consciously false information (only to mention two of the most common meanings). To be sure, this notion marks a profound paradigm shift in our time. By resorting to the interdisciplinary tools and methods that have always characterized the research field known as “American Studies,” we have therefore set out to investigate the category of post-truth. In addition to the literary (Mitrano, Simonetti), historical (Battistini, Bloom), and semiotic (Lorusso) contributions on this topic, two essays (Fargione, Gallo), which were presented in the 2022 edition of the Seminar, “American Wastelands: Environment, Resources, and International Challenges,” complement this first issue