D'Annunzio University (Italian: Università degli Studi "Gabriele d'Annunzio", Ud'A) is a public research university located in Chieti and Pescara, neighbouring cities in the region of Abruzzo, Italy. Established in 1960 as a higher education institute and named after writer and poet Gabriele D'Annunzio, it was officially recognised as an independent university in 1965 by Minister Luigi Gui.The university is formed from a variety of institutions which include thirteen academic departments organised into two schools. It provides undergraduate, graduate and post-graduate education, in addition to a range of international programs in multiple fields of study. Research is a component of each academic division, receiving funds for its scientific investigation from national and international institutions.D'Annunzio University's main campus in Chieti features an eclectic mix of buildings encompassing 48.9 acres. A satellite campus is located in Pescara, while a distance learning centre is situated in Torrevecchia Teatina. It is one of the youngest national university in Italy to enter the U.S. News & World Report of the world's best universities.S.
Ecological restoration represents a central challenge for sustainable development, particularly in advanced economies facing persistent ecological deficits. This study empirically examines the effects of artificial intelligence, green transition, and environmental governance on ecological restoration in G7 countries, employing the Load Capacity Factor as an integrated indicator of ecological quality. Using panel data spanning 1990-2020 and advanced panel econometric techniques, the analysis reveals that artificial intelligence exerts a statistically significant negative effect on ecological restoration, reflecting its energy-intensive deployment. In contrast, green transition variables, including renewable energy consumption and green technological innovation, exhibit robust positive impacts on the Load Capacity Factor, confirming its critical role in reducing environmental footprints and advancing sustainability goals. Environmental governance is found to be negatively associated with ecological restoration in the short run, suggesting transitional adjustment costs linked to policy stringency. Furthermore, the results confirm a U-shaped relationship between economic growth and ecological balance, consistent with the Load Capacity Curve hypothesis that early phases of industrialization exacerbate degradation, but economic maturity enables sustainable development through green transitioning efforts. These findings offer nuanced insights into the ecological consequences of technological progress and policy interventions in advanced economies and underline the importance of aligning artificial intelligence development, green transitions, and environmental governance to support long-term ecological sustainability in G7 nations.
This study explores the dynamic interplay between tourism ecosystems and smart city ecosystems, focusing on their impact on urban sustainability and digital advancement in contemporary cities. Amid societal transformation, globalization, and technological evolution, cities and tourism are transitioning toward a "smart" paradigm, necessitating a nuanced understanding of their symbiotic relationship. However, despite this contemporary evolution, the dynamic and evolving nature of both ecosystems, accompanied by digital and societal changes, reveals a persistent gap between theoretical discussion and practical implementation. Applying a longitudinal empirical analysis that considers 30 Italian cities across 13 years (2010-2023), this research empirically investigates how these integrations influence digital and sustainable urban pathways. Understanding this interaction has become increasingly critical for the advancement of smart cities and tourism. Therefore, our findings aim to contribute to the academic discourse on smart cities and tourism, offering insights for policymakers and practitioners to orchestrate contemporary and future urban dynamics.
Metabolically associated fatty liver disease (MASLD) is highly prevalent among individuals with obesity and type 2 diabetes. Glucagon-like peptide-1 receptor agonists (GLP1-RA) and glucagon-like peptide-1 receptor agonists/glucose-dependent insulinotropic polypeptide (GLP1-RA/GIP) dual agonists have demonstrated favorable effects on liver health. Liver steatosis and stiffness can be noninvasively assessed using transient elastography with Fibroscan®. However, evidence regarding the impact of incretin therapy on these elastographic outcomes remains inconsistent across available studies. Indeed, we performed a systematic review and meta-analysis of randomized-controlled trials and case–control studies, which aimed to investigate the effect of GLP1-RA or GLP1-RA/GIP on liver stiffness and steatosis evaluated with Fibroscan® (PROSPERO registration number CRD420251162316). We searched PubMed, Web of Science, and Scopus for English-language studies till March 2025. Methodological quality of the studies was assessed by the Newcastle–Ottawa Scale or Jadad score. In the presence of heterogeneity, standardized (Std) mean differences with 95
White Analytical Chemistry (WAC) provides a holistic framework for evaluating analytical methods by balancing analytical performance, environmental sustainability, and practical efficiency. Existing WAC assessment tools offer structured evaluation but often lack flexibility or comprehensiveness. To bridge this gap, we introduce the Whiteness Evaluation for Chemical Analysis (WECA) tool as a dynamic, web-based application that enables customizable, context-aware assessment of analytical methods. WECA allows users to select 2-4 criteria per RGB domain (Red: analytical performance; Green: environmental impact; Blue: practical efficiency), assign user-defined weights, and visualize results through an intuitive color-coded interface. The tool calculates a composite WECA score (%) that reflects overall method "whiteness". Three case studies, covering HPLC-DAD, micellar electrokinetic chromatography, and electrochemical sensing, demonstrate WECA's applicability and its ability to highlight method strengths and weaknesses across diverse analytical scenarios. WECA represents a step toward more adaptable, transparent, and visually intuitive method evaluation in alignment with the evolving principles of WAC.
Leakage reduction aims at preserving the longevity of the infrastructure, pursuing reliable service to consumers and efficient use of natural resources. District metering areas (DMAs) are of strategic importance to support leakage management activities from the early detection of anomalies to the prioritization of survey and rehabilitation works. The present work tackles the problems of district metering areas design in those water distribution networks characterized by seasonal fluctuations of spatial distribution and average daily water consumptions, which determines significant changes in network hydraulic regimes. The novel strategy expands a two-phases district metering areas design procedure, originally developed for a unique consumption scenario, for adapting DMA design to minimize the volume of water losses and the number of flow meters, while minimizing the number of manoeuvres needed to accommodate the seasonal changes. Results on a real water distribution network are discussed in terms of leakage management, operations and effective monitoring.
