Riviste Online SApienza - R.O.SA - 2 (Sapienza University of Rome)
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«Un Historia over Annali del Seminario Romano»: gesuiti e celebrazione storiografica nella Roma barocca (1640-47)
Full text linkThe article intends to explore the theme of historiographical celebration withinthe Society of Jesus through the specific case of the Seminario Romano, foundedby the Pope but managed by the order. The main source analyzed is the unpublishedmanuscript of the Annali del Seminario Romano, written by the JesuitGirolamo Nappi between 1640 and 1647. The work, which provides a verydetailed depiction of the institute, is part of the broader phenomenon of the historiographyof religious orders in the post-tridentine age. Particular attentionhas been paid to the section of the Annali concerning the vite of model formerstudents, through which the author illustrates the values of the Societas Iesu
«Missionarie di fede». Il Movimento italiano femminile in provincia: struttura e attività (1946-56)
Full text linkThe article aims to analyse the peripheral reality of the Movimento Italiano Femminile (Italian Female Movement – MIF). The MIF was a prominent neofascist organisation in Italy, founded by Princess Maria Elena De Seta Pignatelli in the aftermath of World War II. On the one hand, the women of the MIF (the so-called “Miffine”) aided the Italian fascists on the run and the ones detained until the early 1950s. At the same time, the movement was a forerunner of the political party Movimento Sociale Italiano (Italian Social Movement – MSI). With this in mind, the article takes a bottom-up approach and provides an overview of the organisation and activities of the MIF at a local level: the movement e established a nationwide network with sections, regional committees and a national assembly. To legitimise its presence, the organisation recruited high-ranking aristocratic women to serve as figureheads, while the real driving force came from ordinary women: Fascist believers, wives of local hierarchs, and former leaders of provincial female organisations such as Fasci Femminili. Through its charitable activities, the MIF became a focal point for former fascists and their families. Moreover, the movement provided a link between the emerging neo-fascist network and the community of fascist criminals detained in Italian prisons until the early 1950s
Citizen science reveals a rapid range expansion of a Mediterranean hoverfly under climate warming (Diptera: Syrphidae)
No full textThe big‑headed lagoon fly, Eristalinus megacephalus (Rossi, 1794), is a Mediterranean hoverfly historically restricted in Italy to a handful of coastal regions. Recently, numerous observations uploaded to the iNaturalist citizen‑science platform show a rapid northward and inland expansion, with new regional records from Piemonte, Lombardia, Veneto, Friuli-Venezia Giulia, Marche, Umbria, Puglia and Calabria. Here we compile Italian literature records and recent citizen‑science observations and map the current occurrence of the species in the country. The density of recent records in the Po Valley and in other inland areas suggests that E. megacephalus is no longer limited to coastal Mediterranean climates. We discuss the value of citizen‑science data for fast‑moving biogeographic updates. Targeted surveys are now needed to test whether newly observed clusters represent transient dispersers or established populations
Ignored for 150 years: distribution, song description, habitat, and threat of Cicadetta albipennis (Fieber, 1876) – mysterious tiny cicada species from Sicily (Italy) (Cicadidae: Cicadettinae)
No full textCicadetta albipennis was described 150 years ago, yet no data on its ecology, acoustic behaviour, distribution and conservation have been published. This cicada species, notable for its distinct morphology, is among the smallest in Europe. We investigated the taxon within its presumed endemic range in Sicily and present the first data on its habitat preferences, acoustic behaviour and current distribution. Additionally, we provide the first photographs of live males and females. Cicadetta albipennis is an early-emerging species, active at least from mid-late May to the beginning of June. Its song consists of a monotonous series of short, purring echemes characterized by a supposedly very slow syllable rate and one of the highest frequency ranges among European cicadas. The species was found scattered in southern Sicily, although specimens from the north of the island (labelled — maybe erroneously — “Palermo” and “Messina”) exist in historical collections. The species is associated with grassland habitats shaped by herbivores. We discuss habitat availability across prehistoric and historic times, and suggest that C. albipennis is threatened by the disappearance of large wild herbivores and the decline of traditional, extensive grazing practices
Exploring the Unesco world heritage property in the shallow waters at Rose Island using unmanned surface vehicles (USV)
No full textRose Island (Germany) is part of the UNESCO World Heritage site “Prehistoric Pile Dwellings around the Alps” and a pilot site of the EU funded project TRIQUETRA, which targets the risks of climate change on cultural heritage. With the lack of a detailed bathymetric map of the waters around Rose Island and in search for an efficient approach for documenting the wooden relics from Iron Age at the lake bottom, both a sonar and a photogrammetric campaign were conducted by the German Aerospace Center (DLR). From the sonar measurements, the first reliable bathymetric map of the area was generated and provided to TRIQUETRA’s decision support system and WebGIS. During the photogrammetric survey, ~15.000 high resolution images of the lake floor were taken by an unmanned surface vehicle (USV) and processed to high-resolution 3D models by using the structure-from-motion method (SfM). The models provide an unprecedented level of detail for the documentation and examination of the archaeologic remains at Rose Island and a fascinating insight to the prehistoric settlement remains for the general public
The mimicry complex of the acrobat ant Crematogaster scutellaris in Tunisia: Colobopsis imitans and Mimocoris rugicollis (Hymenoptera: Formicidae; Heteroptera: Miridae)
Full text linkThe ant Crematogaster scutellaris, distributed across the western Mediterranean region and east to the west Balkans, is a visual mimicry model for various other organisms, including different other species of ants. It is an ecologically and behaviorally dominant species, foraging through large permanent trails that workers pugnaciously defend by biting and spraying a toxic secretion. Here we report on two interesting novelties discovered by monitoring Cr. scutellaris foraging trails in Tunisia: first, we present the first records of the mimicking ant Colobopsis imitans in the country, fi lling a distribution gap and confirming a previous biogeographic hypothesis; second, we identified the mirid Mimocoris rugicollis, whose brachypterous females are known as myrmecomorphs, as a mimic of Cr. scutellaris. Both Co. imitans and M. rugicollis were observed following or stationing near Cr. scutellaris trails, often in the presence of another mimicking ant, Camponotus lateralis. Still little is known about the ecology and behavior of most Cr. scutellaris mimics, with some species still undescribed. Further research is needed to investigate the evolutionary pressures shaping this adaptation
From survey to analysis and visualization methods, new approaches to define rockfall hazard
No full textRockfalls are among the most dangerous natural hazards. The study of these phenomena may be complex in relation to the geology and the rock mass characteristics. Recent advances on the use of remote sensing techniques made the survey of rock slopes easier and faster, increasing the amount and quality of data. At the same time, the improved availability of software for characterizing rock slopes and simulating rockfalls permits a more detailed and precise definition of rockfall hazard areas. In this context, this research highlights the importance of using remote sensing techniques in the study of these phenomena, especially in developing accurate and reliable geological and structural models. The Regional Park of Monte Conero (Ancona, Italy) is used as the case example. The study area has been investigated through conventional geological/structural surveys, UAV photogrammetry and iPad-based LiDAR. The data gathered from surveys have been used to perform rockfall simulations and define potential mitigation measures. Finally, innovative visualization techniques based on the use of Virtual Reality will be introduced for an improved interpretation of geological and structural data and simulation results
Pore network model to predict flow processes in unsaturated calcarenites
No full textThe knowledge of infiltration mechanisms in vadose zone is the key to forecast the components of the hydrologic cycle such as run-off generation and aquifer recharge. Besides, slope stability, settlements and bearing capacity of foundations, and rock weathering are issues in which infiltration processes play an important role. In Apulia and Basilicata (Southern Italy) representative calcarenites outcrops are exposed along both the coastline and internal areas. These calcarenites belong to the Calcarenite di Gravina Fm. (Middle Pliocene-Lower Pleistocene) and are mainly constituted by fine- medium- and coarse-grained packstones and grainstones. The whole geological formation represents an important hydrogeologic unit which controls groundwater recharge and transport of contaminants within a complex, multilayered system comprising a wide and deep aquifer hosted into the Mesozoic basement. A smart analytical and numerical tool based on the pore bundle model conceptualization and the Richards’ equation was developed to predict infiltration and retention mechanism of calcarenites. This work investigated the impact of bimodal poresize distribution on the unsaturated flow from dry to wet conditions obtained through conventional and unconventional laboratory tests and petrophysical characterization, also completed with mercury intrusion porosimetry and image analysis. Laboratory experiments were carried out on medium-grained grainstones sampled at Canosa di Puglia (Tufarelle locality), by means of infiltration tests conducted starting from a different degree of saturation and varying the inlet flow rate. The experimental data were compared with the pore network model prediction. For the rock samples used, the study disclosed that macroporosity mainly affects the propagation of the wetting front and infiltration rate. Thus, the wetting front develops principally during the infiltration of water through the interconnected macropores following the pathways having minimum flow resistance with a gravity driven flow velocity higher than the diffusive flow though micropores
Estimation brittleness index in carbonate environments using log and lithology data and deep learning techniques
No full textBrittleness index is one of the most important Geomechanical parameters, which has a great impact on the rock breaking process and drilling activities. The methods of evaluating brittleness of rocks are mainly divided into three categories: (1) direct laboratory, (2) mineral content, and (3) based on elastic moduli. one of the efficient methods for brittleness index predicting is use of intelligent methods, which are low-cost and accurate methods, and it is possible to predict the brittleness index using log and lithology data. In this study, dynamic and static brittleness index values are predicted using deep learning (DL) algorithms and lithology data in carbonate environment in one of the hydrocarbon fields in southern part of Iran. In this paper, the effective features were selected using the deep learning algorithm of the Auto-encoder, and the dynamic and static brittleness index was estimated using the MLP, LSM, and CNN algorithms. As 12 laboratory core samples were available, at first the brittleness index were calculated by relevant empirical relations and data of some available well logs in order to generalize these core results to the entire target depth range of 3551.07 to 3799.78 meters. Then a set of relationship between the well’s logs derived dynamic and static brittleness index and laboratory results was determined for the depths where the laboratory samples were recorded. Following that, an Auto-encoders deep network was used to select the effective features in predicting the brittleness index, and finally by using MLP, LSTM and CNN networks the value of dynamic and static brittleness index was predicted. Here, the goal is to obtain the brittleness index values with high accuracy wherein there no core data. The performance of the three algorithms prediction models is tested by blind data sets that the models have not seen before. Furthermore, the results were checked and evaluated by set of statistical measures like MAE, MAPE, MSE, RMSE, NRMSE and R2 values that calculated for train, test and blind dataset. At first, dynamic brittleness index estimate using log data and three algorithms and R2 for blind data equal to R2MLP=0.91, R2LSTM=0.97, R2CNN=0.98, in the following, using MLP, LSTM and CNN the dynamic brittleness index has been converted into a static brittleness index and R2 for blind data equal to R2MLP=0.94, R2LSTM=0.96, R2CNN=0.96. Finally, the static brittleness index has been estimated directly from the log data without the relation of dynamic to static transformation and R2 for blind data equal to R2MLP=0.95, R2LSTM=0.96, R2CNN=0.97. Finally, the dynamic and static brittleness index was compared with the brittleness index obtained from lithology, and there is a good match between them. The results show that the deep learning algorithm is a novel method, robustness and accurate method in estimating the dynamic and static brittleness index using conventional logs. The results show used CNN and LSTM networks as new deep learning algorithms to predict brittleness index