88 research outputs found
Diventare donna : Marianna, Eleonora, Adriana
No full textIl saggio prende in esame tre personaggi femminili, Marianna, Eleonora, Adriana, protagoniste - rispettivamente - dei romanzi: "Marianna Ucrìa" di Dacia Maraini; "Il resto di niente" di Enzo Striano; "La romana" di Alberto Moravia. Analizza, dapprima, il modo col quale le tre adolescenti maturano e diventano adulte, confrontandosi con il potere, la cultura dominante, l'ambiente socio-familiare in cui si muvono. A lato, compara tra loro gli esiti di questa crescita, in cui la cutura e la consapevolezza di sé e della storia si rivelano, alla fine, vincenti
Economic and Monetary Union and Switzerland: two models compared in the light of the economic crisis
No full textLooking at the origin and the reasons behind and considering the impact of the 2007 economic crisis in the EU countries and in Switzerland, the author describes the initiatives taken and the key role played by the European Central Bank to mitigate financial and monetary risks within the Eurozone, and compares it to the Swiss approach, namely addressing the set of measures adopted by the Swiss National Bank to tackle the economic crisis
Climate-related environmental stress in intertidal grazers: scaling-up biochemical responses to assemblage-level processes
No full textOrganisms are facing increasing levels of environmental stress under climate change that may severely affect the functioning of biological systems at different levels of organization. Growing evidence suggests that reduction in body size is a universal response of organisms to global warming. However, a clear understanding of whether extreme climate events will impose selection directly on phenotypic plastic responses and how these responses affect ecological interactions has remained elusive
Vascular oxidative stress-induced senescence is minimized by melatonin intake in Apo-E deficient mice
No full textAging is a natural process that produces deleterious changes in all tissues of the organism. One leading theory about the cause of aging suggest that oxidative stress play a fundamental role in pathogenesis. Oxidative stress induces intracellular damage that affects all biological components, including, DNA, lipids, sugars and proteins. Therefore, the imbalance between intracellular reactive oxygen species (ROS) and antioxidant defence mechanisms results in harmful oxidative stress. One of the most widely considered strategies for preventing aging and for treating age-related disease is the use of natural anti-oxidant agents, such as melatonin and resveratrol. Melatonin is a potent endogenous anti-oxidant neurohormone, which acts through various mechanisms to ameliorate the toxic effects of ROS. However, little is known about the mechanisms of signalling pathways through which melatonin acts to reverse the effects of ROS. In the present study we treated ApoE-deficient mice, a well-known senescence model, from 6th week to 15th week of life, with a specific melatonin formulation: Armonia Retard (kindly provided by Nathura s.r.l, Reggio Emilia, Italy), with an extended-release pharmacokinetic, at different progressive doses 0.04, 0.1, 10 mg/kg/day. We used the same treatment in C57BL6 mice, as control group. Vascular alterations were evaluated in aorta by morphology and immunofluorescence analysis was focused on pleiotropic inflammatory markers, such as interleukins (IL) 6 and 10, inducible nitric oxide synthase (iNOS), tumor necrosis factor-alpha (TNF-α). We observed in ApoE-deficient mice endothelial cell detachment and IL-6, IL-10, iNOS and TNF-α overexpression. Melatonin treatment improved not only the endothelial damage, but also the overall vascular cytoarchitecture and reduced inflammation and macrophages infiltration. In particular, melatonin Retard at the highest dose, recovered all the above markers to the levels of C57BL6 mice. These results outline the anti-inflammatory and anti-oxidant properties of melatonin and its beneficial anti-aging and anti-atherosclerotic effects, especially in extended-release formulation
Integration of sludge ozonation with anaerobic digestion: From batch testing to scenario analysis with energy, economic and environmental assessment
No full textA methodological procedure, based on results from batch experiments, is proposed and applied to a selected wastewater treatment plant generating a poorly degradable sludge, to identify the best configuration and ozone dosage for full-scale application of sludge ozonation. Samples of pre-thickened and digested sludge were collected, tested at different ozone dosages and characterized to gather useful data for energy, economic and carbon footprint balances. The most viable scenario was found to be sludge pre-treatment at the lowest tested dosage (20 mg O3/g VS), yielding energy, cost and GHG emission net savings of 177 MWh/y, 57.8 k€/y and 6.38 Mg CO2-eq./y, respectively. Sensitivity analyses, conducted by varying the specific energy required for ozone generation and the unit costs for sludge disposal and resource supply, confirmed the stability of this scenario, whereas a field pilot-scale testing is advisable to verify modified process conditions for a safe and efficient application of sludge ozonation. The proposed methodology, including laboratory batch anaerobic digestion tests, scenario definition and energy/economic/environmental balances, could be preliminary applicable to all situations to broadly analyze all involved aspects and give a useful overview about the effective applicability of sludge ozonation
A knowledge graph embeddings based approach for author name disambiguation using literals
No full textScholarly data is growing continuously containing information about the articles from a plethora of venues including conferences, journals, etc. Many initiatives have been taken to make scholarly data available in the form of Knowledge Graphs (KGs). These efforts to standardize these data and make them accessible have also led to many challenges such as exploration of scholarly articles, ambiguous authors, etc. This study more specifically targets the problem of Author Name Disambiguation (AND) on Scholarly KGs and presents a novel framework, Literally Author Name Disambiguation (LAND), which utilizes Knowledge Graph Embeddings (KGEs) using multimodal literal information generated from these KGs. This framework is based on three components: (1) multimodal KGEs, (2) a blocking procedure, and finally, (3) hierarchical Agglomerative Clustering. Extensive experiments have been conducted on two newly created KGs: (i) KG containing information from Scientometrics Journal from 1978 onwards (OC-782K), and (ii) a KG extracted from a well-known benchmark for AND provided by AMiner (AMiner-534K). The results show that our proposed architecture outperforms our baselines of 8–14% in terms of F1 score and shows competitive performances on a challenging benchmark such as AMiner. The code and the datasets are publicly available through Github (https://github.com/sntcristian/and-kge) and Zenodo (https://doi.org/10.5281/zenodo.6309855) respectively
A Knowledge Graph Embeddings based Approach for Author Name Disambiguation using Literals
No full textScholarly data is growing continuously containing information about the
articles from a plethora of venues including conferences, journals, etc. Many
initiatives have been taken to make scholarly data available as Knowledge
Graphs (KGs). These efforts to standardize these data and make them accessible
have also led to many challenges such as exploration of scholarly articles,
ambiguous authors, etc. This study more specifically targets the problem of
Author Name Disambiguation (AND) on Scholarly KGs and presents a novel
framework, Literally Author Name Disambiguation (LAND), which utilizes
Knowledge Graph Embeddings (KGEs) using multimodal literal information
generated from these KGs. This framework is based on three components: 1)
Multimodal KGEs, 2) A blocking procedure, and finally, 3) Hierarchical
Agglomerative Clustering. Extensive experiments have been conducted on two
newly created KGs: (i) KG containing information from Scientometrics Journal
from 1978 onwards (OC-782K), and (ii) a KG extracted from a well-known
benchmark for AND provided by AMiner (AMiner-534K). The results show that our
proposed architecture outperforms our baselines of 8-14% in terms of the F1
score and shows competitive performances on a challenging benchmark such as
AMiner. The code and the datasets are publicly available through Github:
https://github.com/sntcristian/and-kge and
Zenodo:https://doi.org/10.5281/zenodo.6309855 respectively
BiblioDAP'21: The 1st Workshop on Bibliographic Data Analysis and Processing
No full textAutomatic processing of bibliographic data becomes very important in digital libraries, data science and machine learning due to its importance in keeping pace with the significant increase of published papers every year from one side and to the inherent challenges from the other side. This processing has several aspects including but not limited to I) Automatic extraction of references from PDF documents, II) Building an accurate citation graph, III) Author name disambiguation, etc. Bibliographic data is heterogeneous by nature and occurs in both structured (e.g. citation graph) and unstructured (e.g. publications) formats. Therefore, it requires data science and machine learning techniques to be processed and analysed. Here we introduce BiblioDAP'21: The 1st Workshop on Bibliographic Data Analysis and Processing
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