Parthenope University of Naples
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Institutional factors and environmental performance: Insights from global economies
No full textThis study investigates how institutional quality, democratic governance, political orientation and economic policy uncertainty influence environmental performance across different economies globally. Even if there is literature that highlights the importance of strong institutions and democracy for environmental outcomes, empirical evidence remains inconsistent. Using data from 130 countries between 1996 and 2018, we apply a two-stage approach: first, estimating environmental performance via a stochastic frontier, and then analyzing institutional factors with a FEGLS regression and time lags to address endogeneity. The results reveal that strong institutional quality significantly improves environmental performance (β = 0.032), with its impact amplified in countries with medium and high levels of democracy (interaction terms: β = 0.012 and β = 0.010, respectively). While democracy alone exerts a mixed effect, the presence of robust institutions offsets the negative influence of economic policy uncertainty (β = −0.0273). This study provides new insights into the interplay between institutional quality and governance in fostering environmental sustainability. It also offers policy implications for achieving a balance between economic growth and ecological preservation
An Enhanced Deep Neural Network Framework for Accurate Tomato Disease Recognition in Real-time Environment
No full textAgricultural production is a critical sector that directly impacts the financial and social well-being of a society. The identification of plant diseases in a real-time environment is a significant challenge for agriculture production. Conventional disease detection methods, which depend significantly on manual inspection, are time-consuming, labour-intensive, and susceptible to human error. Furthermore, many recently developed models struggle in real-time scenarios because their accuracy is compromised when trained on isolated leaf images but then used to analyse entire plants. To tackle these issues, this research offers an advanced, automated system from tomato leaf segmentation and disease detection to the automatic spray prescription in real-time environment. This research presents an integrated system to address these issues, focusing on tomato plants. In first part of the research after deeply analysing the YOLO (You Only Look Once) models we integrate two models, the YOLOv8 with SAM (Segment Anythin
From dark patterns to hyper-engaging dark patterns: for a modern application of the prohibition under Article 25 DSA
No full textArticle 25 of the Digital Services Act (DSA) proscribes the use and dissemination of so-called dark patterns on online platforms. The term “dark patterns” refers to computer tools designed to influence users’ behaviour during their web experience.
The prevailing interpretation in scholarship concerning this prohibition, also confirmed by the practice of the EU Commission, appears, however, to be unreasonably restrictive, limiting its validity exclusively to the category of dark patterns of a graphic nature. This approach carries the risk of creating a protection gap concerning new generations of dark patterns, particularly Hyper-Engaging Dark Patterns (HEDPs), which are designed not only to maximise interaction with users but also to compel them to perform unintended actions (e.g. making unplanned purchases).
In the light of this scenario, this paper proposes moving away from the prevailing majority approach, which, among other issues, creates a marked differentiation in protections between users of Very Large Online Platforms (VLOPs) and those of non-VLOPs
Perspectives on Energy, Environmental and Economic benefits from collaborative interactions of Circular Start-Ups and large companies. A case study in the textile district of Prato
No full textThis study investigates the transition to the circular economy (CE) model and its increasing
application in industrial companies. The research context is the textile district of Prato,
Tuscany region, that relies on a long historical tradition of CE application. Some industrial
companies have been contacted, and their Administrators and CEOs have been interviewed,
focusing on their understanding of the role of circular start-ups (CSUs) in the collaboration
and relationships with large companies. The results show that this collaboration started
for commercial purposes, since the companies interviewed in this study are producers of
recycled yarns used by their customers, including CSUs, for the manufacturing of their
garments. Over time, the collaboration further advanced, adding new types of interactions,
characterized by environmentally and socially positive outcomes. This study shows that
the collaboration between the small CSU Rifò and two of the largest companies of the
Prato district as well as the outcomes in terms of environmental, energy and social benefits
well extend over the micro, meso and macro levels of the CE model and reveal that the
circular and sustainability performances of the selected CSU and its large partners are
aligned with the goals of the district and the city of Prato towards consolidating themselves
as a reference center of a CE and a circular city, respectively. This is an important result
compared to the previous literature that encourages further future research to provide
more generalizable results. Further, the case study of the Rifò regenerative circular business
model shows the current “limits” of recycling and the need to thoroughly consider the
CE model by implementing all CE principles and promoting a timeless and responsible
fashion, conveying the emotional, environmental and social values behind garments
Social Media and Stakeholder Engagement in High-Tech Healthcare Start-Ups: An Exploratory Study
No full textIn recent years, the literature has increasingly recognized social media as a potential strategic driver for small entrepreneurial ventures. High-technology healthcare start-ups, in particular, represent highly fragile actors within the business landscape due to their young age and limited access to financial and social resources. Despite the fact that approximately 60% of start-ups fail during their early life cycles, research examining how high-technology healthcare start-ups strategically use social media and integrate it into their business models remains limited. The thesis aims to address the following research question: How do high-technology start-ups use social media to enhance stakeholder engagement? To answer this research question, an exploratory study was conducted using a qualitative methodology. Primary data were collected through 45 semi-structured interviews with 14 high-technology healthcare start-ups. In addition, secondary data were also collected. The data were analyzed using an inductive thematic analysis, which led to the identification of five main themes. These themes are: (1) the benefits of social media; (2) personalization of communication strategies; (3) the impact of social media on the business model; (4) metrics and performance measurement; and (5) challenges in tailored communication. Based on these findings, the study develops a conceptual framework illustrating how social media supports stakeholder engagement in high-technology healthcare start-ups and proposes a set of theoretical propositions to guide future research
Fuori dalle mura e dentro il territorio. L’Outdoor Education per una formazione socio-ambientale in prospettiva inclusiva.
No full textLa realtà contemporanea, complessa e dinamica, e le acquisizioni scientifiche che riconoscono il ruolo cruciale dell’ambiente nei processi di formazione individuale e collettiva sollecitano una riflessione approfondita sulle modalità attraverso cui tale ruolo si esplica nei percorsi di crescita e di sviluppo della persona. I processi di globalizzazione e di urbanizzazione, che caratterizzano in modo significativo le società occidentali, stanno infatti trasformando profondamente le traiettorie formative ed esistenziali, incidendo negativamente sulla possibilità di tutelare e promuovere condizioni di benessere complessivo. In ambito psico-pedagogico, recenti studi evidenziano una crescente consapevolezza del valore educativo e formativo degli spazi outdoor. La progressiva riduzione delle esperienze di gioco, movimento, socialità ed esplorazione in ambienti naturali sta comportando rilevanti criticità che, se pur non pienamente categorizzate in forma descrittiva ed analitica, si traducono difatti in forme di possibili disagi, ostacoli, difficoltà nelle varie fasi di crescita degli individui. Questa progressiva riduzione di esperienze legate al movimento in una pluralità di contesti ed ambienti interessa anche i processi educativi e didattici, con ricadute sullo sviluppo psicofisico, cognitivo ed emotivo dei soggetti in formazione. In risposta alla crescente tendenza delle giovani generazioni a vivere prevalentemente in spazi chiusi, il recupero e la riattualizzazione di un’educazione all’aperto, progettata secondo rigorose logiche teorico-metodologiche, si configura come un’opportunità per ristabilire un certo equilibrio olistico. Su tali premesse, la ricerca si propone di progettare e sperimentare pratiche educative fondate sull’Outdoor Education, orientate alla formazione culturale, all’inclusione sociale e alla valorizzazione del territorio. L’indagine integra una riflessione teorico-pedagogica con un’esperienza empirica di tipo esplorativo, realizzata con gruppi di adolescenti in contesti outdoor, evidenziando come tali pratiche favoriscano il benessere psicofisico e sociale, lo sviluppo di competenze socio-emotive e consapevolezza corporea, contrastando stili di vita sedentari e forme di vulnerabilità fisica, psicologica e relazionale
La disciplina dei software di riconoscimento facciale: rischi e prospettive
No full textIl legislatore europeo e, di riflesso, quello italiano avvertono l’esigenza di disciplinare i software che, sfruttando l’intelligenza artificiale, effettuano riconoscimenti biometrici automatizzati. La necessità di regole chiare incalza so-
prattutto con riferimento ai tool impiegati nel procedimento penale, nell’intento di contemperare l’efficacia dell’ac-
certamento dei reati con la salvaguardia delle libertà della persona e con i valori che presidiano la gnosi giudiziaria.
Va però stabilito se l’inedito quadro normativo è utile allo scopo, non essendo ammissibili soluzioni che, propense
all’efficientamento algoritmico, annichiliscono i diritti fondamentali e l’epistemologia giudiziaria.European legislators, and consequently Italian legislators, feel the need to regulate software that uses artificial
intelligence to perform automated biometric recognition. The need for clear rules is particularly pressing with regard
to tools used in criminal proceedings, with the aim of balancing the effectiveness of crime detection with the pro-
tection of individual freedoms and the values that underpin judicial knowledge. However, it must be established
whether the new regulatory framework is useful for this purpose, as solutions that, in their pursuit of algorithmic
efficiency, destroy fundamental rights and judicial epistemology are not acceptabl
A digital twin framework for circular economy and operational excellence in textile manufacturing
No full text
Stable and Efficient Gaussian-Based Kolmogorov–Arnold Networks
No full textKolmogorov–Arnold Networks employ learnable univariate activation functions on edges rather than fixed node nonlinearities. Standard B-spline implementations require (Formula presented.) parameters per layer (K basis functions, W connections). We introduce shared Gaussian radial basis functions with learnable centers (Formula presented.) and widths (Formula presented.) maintained globally per layer, reducing parameter complexity to (Formula presented.) for L layers—a threefold reduction, while preserving Sobolev convergence rates (Formula presented.). Width clamping at (Formula presented.) and tripartite regularization ensure numerical stability. On MNIST with architecture (Formula presented.) and (Formula presented.), RBF-KAN achieves (Formula presented.) test accuracy versus (Formula presented.) for B-spline KAN with (Formula presented.) speedup and 33% memory reduction, though generalization gap increases from (Formula presented.) to (Formula presented.) due to global Gaussian support. Physics-informed neural networks demonstrate substantial improvements on partial differential equations: elliptic problems exhibit a (Formula presented.) reduction in PDE residual and maximum pointwise error, decreasing from (Formula presented.) to (Formula presented.) ; parabolic problems achieve a (Formula presented.) accuracy gain; hyperbolic wave equations show a (Formula presented.) improvement in maximum error and a (Formula presented.) reduction in (Formula presented.) norm. Superior hyperbolic performance derives from infinite differentiability of Gaussian bases, enabling accurate high-order derivatives without polynomial dissipation. Ablation studies confirm that coefficient regularization reduces mean error by 40%, while center diversity prevents basis collapse. Optimal basis count (Formula presented.) balances expressiveness and overfitting. The architecture establishes Gaussian RBFs as efficient alternatives to B-splines for learnable activation networks with advantages in scientific computing