ARUd’A (Università “G. d’Annunzio CHIETI -PESCARA)
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I 'punti' di Giacomo Leopardi (tra geometria e poesia)
No full textSi analizza il concetto di 'punto' nel pensiero e nell'opera di Giacomo Leopardi, alla luce non solo dei riferimenti filosofici ma anche delle sue conoscenze e studi scientifici
Subtitling The Handmaid’s Tale for an Italian Audience
No full textThis paper delves into the analysis of the adaptation of Atwood’s novel The Handmaid’s Tale for the screen. Bruce Miller’s TV adaptation of the book on Hulu in 2017 inspired a revival of interest in Atwood’s work, topping the world’s bestseller lists and winning a Golden Globe and eight Primetime Emmy Awards. In this study, aimed at investigating the quality of the Italian subtitled version of the TV show, an approach inspired by a set of taxonomies within Descriptive Translation Studies (DTS) related to domestication and foreignization (Venuti 1995), translation equivalence (Nida 1964; Toury 1995), subtitling quality (Gottlieb 2009), and good subtitling practice (Carroll and Ivarsson 1998) was employed in order to identify the main categories adopted, while Remael and Robert’s quality parameters in subtitling (2016) also contributed to the discussion of the results of our study. Based on the results of the quality assessment, it was determined that the Italian subtitled version of The Handmaid’s Tale exhibited high quality in terms of content and transfer (e.g., accuracy, completeness, logic), and style and form (e.g., grammar, spelling, and punctuation), with only a few minor errors observed in terms of formatting, some major issues related to the technical dimension (e.g., spotting), and adherence to the dubbing script, a peculiar phenomenon we have extensively described
Sistema nazionale di certificazione delle competenze: un caso di isomorfismo istituzionale
No full textBuilding hybrid models of neuromodulation from automatic segmentation of peripheral nerve histological sections
No full text: Electrical stimulation of peripheral nerves offers a way to restore sensory-motor functions and treat drug-resistant conditions affecting internal organs. Understanding the fascicular organization of the implanted nerves is essential for enhancing the selective neuromodulation of the targeted bodily functions. In fact, this knowledge can inform the development of computational models that can be used to optimize electrode design and stimulation protocols. Traditionally, peripheral nerve topographies are segmented manually to highlight fascicle contours, resulting in a labor-intensive and error-prone process. In this study, we present a UNet-based deep neural network for automatic segmentation of fascicles from nerve histological sections, trained on original data from different nerves and stained with different techniques. The model leverages a pretrained encoder, reducing the need for extensive training datasets and allowing us to generalize to nerve types and histological stains previously unseen during training. The quality of the resulting segmentation has been evaluated using both the Dice coefficient and domain-specific metrics tailored to assess the quality of the reconstructed fascicle topography. Furthermore, we employed automatically segmented nerve sections to build computational models of peripheral nerve stimulation and assess the impact of segmentation on the accuracy of fascicle-wise recruitment predictions. Our results highlight that automated segmentation can reliably inform the modeling of neuromodulation applications, with minimal error in predicting recruitment thresholds. This approach paves the way for harnessing the large quantities of histological data that can be extracted from cadaveric nerve samples for use in computational models of neural interfaces, potentially advancing the design of next generation neuroprosthetic and bioelectronic medicine applications
The role of mediation in addressing adolescent issues within legal and social science contexts
No full textStability Toolkit for the Appraisal of Bio/pharmaceuticals’ Level of Endurance (STABLE) as a framework and software to evaluate the stability of pharmaceuticals
No full textThe Stability Toolkit for the Appraisal of Bio/pharmaceuticals’ Level of Endurance (STABLE) is herein introduced and proposed as a comprehensive tool and software to evaluate the stability of active pharmaceutical ingredients (APIs) under various stress conditions. In the pharmaceuti-cal industry, stability testing is a critical step in the drug development process, ensuring the quality, safety, and efficacy of APIs. Traditional stability tests—such as real-time, accelerated, and forced degradation testing—often face challenges, including inconsistent interpretation and im-plementation across different regions and organizations. STABLE addresses these challenges by providing a standardized and holistic approach to assessing drug stability across five key stress conditions: oxidative, thermal, acid-catalyzed hydrolysis, base-catalyzed hydrolysis, and photo-stability. Beyond its role as an evaluation tool, STABLE also serves as a practical guide for chem-ists, encouraging a more complete and thoughtful approach to stability studies. While many in-vestigations focus solely on acid and base-catalyzed hydrolysis, other critical conditions—such as photostability—are often underexplored or entirely omitted. By highlighting the importance of evaluating all relevant degradation pathways, STABLE promotes more robust and informed stability testing protocols. The index utilizes a color-coded scoring system to quantify and com-pare stability, facilitating consistent assessments across different APIs. This paper discusses the methodology of STABLE, including the scoring system and specific criteria applied under each condition. This tool is introduced to reflect intrinsic degradation susceptibility under forced conditions. The software is freely available as an open-source tool at bit.ly/STABLE2025, ena-bling broader accessibility and implementation across the pharmaceutical research community
Novel microsampling approach using fabric-phase sorptive extraction (FPSE) for cannabinoid analysis in blood
No full textThe most important bioactive special metabolites of Cannabis sp. include cannabinoids, namely tetrahydrocannabinol (THC), cannabidiol (CBD) and their analogues. They are promising compounds with many biological activities, although THC is also known as an illicit compound in several countries. Due to their widespread occurrence and biological activity, cannabinoids are frequently investigated in terms of detection and quantification in various biological matrices. The increasing introduction of products based on plant derivatives and their compounds in the recreational, industrial, pharmaceutical, and illicit markets demands the constant development and refinement of rapid and reliable methods for the determination of these analytes in biological samples. Blood microsampling has emerged as a pivotal innovation in bioanalytical science, offering minimally invasive collection, reduced solvent consumption, and broad reliability and applicability across modern workflows. In this study, an innovative dried microsampling technology based on fabric phase sorptive extraction (FPSE) has been exploited for whole blood sampling, using polymeric fabric patches coated with three different sorbent chemistries: polyethylene glycol (CW20M), polydimethylsiloxane (PDMS) and polytetrahydrofuran (PTHF), for the analysis of two main active cannabinoids and five of their metabolites. An efficient HPLC-MS/MS method was developed, obtaining r2 ≥ 0.9991, LOD ≤ 0.5 ng/mL and LOQ ≤ 1.5 ng/mL for all analytes. Just 20 μL of whole blood were needed to obtain a satisfactory dried FPSE spot. The sorbent activation procedures were optimised for different chemistries, ensuring compatibility with the analytes and high extraction efficiency. Dried sample pretreatment steps by solvent extraction have been optimised before HPLC-MS/MS analysis. Analytical results were satisfactory for all the analytes, with recovery always higher than 85 %, blood matrix effect lower than 14 % and FPSE matrix effect lower than 9 %. For intraday precision, the RSD value was consistently below 9.3 %, while it was lower than 9.8 % for interday precision. This is the first study where FPSE has been applied to the determination of THC, CBD and their main endogenous metabolites as a novel blood microsampling based approach
MC4-R variant confirms its association with obesity during progression from childhood to adolescence
Full text link: The rs12970134 variant near the melanocortin receptor 4 (MC4-R) has gained relevance suggesting an age dependent phenotypic effect in the induction of obesity in young age. A previous study evaluating 740 Caucasian children has shown this association in prepubertal children older than 8 years. The aim of this study was to assess whether the obesogenic effect of M4CR gene contributed to obesity also in adolescence. After 8 years participants of the original study were contacted and invited to perform an anthropometric evaluation. Out of 35 carriers of the AA risk allele of MC4-R, 12 subjects accepted to participate. Adolescent subjects with the AA risk allele of MC4-R were matched with 24 and 48 subjects, respectively for AG and GG variants. Differences between the three MC4-R genotypes for anthropometric data, for percentage of overweight and obesity and for changes in BMI-SDS over visit have been assessed. At Visit 1 (baseline examination study), the AA risk genotype was confirmed to be associated with higher BMI-SDS (1.3 ± 0.4 vs 0.4 ± 0.1) and waist circumference (66.5 ± 5.8 vs 60.9 ± 7.1) when compared to the GG genotype (p < 0.016 both). At Visit 2 the AA genotype not only was associated with a higher BMI-SDS (1.07 ± 0.5 vs 0.02 ± 0.8) and WC (95.6 ± 13.3 vs 64.9 ± 13.5) when compared to GG genotype, but also when compared to AG genotype (vs 0.5 ± 0.1 and 62.9 ± 10.0, p < 0.016). Whereas AA genotype demonstrated no change of BMI-SDS between visit 1 and visit 2 (p00.32), AG and GG genotype showed a significant reduction (p = 0.01 and 0.001 respectively). Furthermore, a higher percentage of patients were affected by overweight/obesity in the AA genotype compared to AG and GG genotypes (50% vs 20.8% vs 16.5% p = 0.03). This study demonstrates that the rs12970134 variant not only exerts an obesogenic influence in the prepubertal age but remains a major risk factor also during adolescence
La funzione della storia e il ruolo degli storici
No full textRiflessioni a partire dal volume di F. Benigno, La storia al tempo dell'oggi (Bologna, Il Mulino, 2025
The impact of digital technologies and social media on the urban attractiveness of smart cities
No full textSmart city initiatives use digital technologies to enhance user experiences and improve the attractiveness of urban environments. However, little is known about how these technologies influence a city's ability to attract different types of newcomers, and even less about the role of social media in this process. This work examines how a city's use of social media influences the relationship between the effect of digital technology implementation and the urban attractiveness for national and international newcomers. Focusing on three types of national and international newcomers (i.e., citizens, students, and tourists) to a city, we present and test a model of how social media curates, broadcasts, and accelerates information flows about the availability and value of smart city technology to newcomers. Using novel data from 30 Italian cities (2010−2021), we find support for this model, with digital technologies having a curvilinear impact on urban attractiveness, and that social media extends the threshold of this impact. Moreover, we find that these effects differ for national and international newcomers. These findings challenge smart city scholars and practitioners to reconsider the ‘more is better’ narrative that assumes increasing technology implementation is always beneficial, highlighting instead the value of contingency-based approaches over one-size-fits-all technological determinism