Archivio Istituzionale della Ricerca- Università del Salento
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Software and computing for Run 3 of the ATLAS experiment at the LHC
No full textThe ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management, database infrastructure, and validation. The use of these systems to prepare the data for physics analysis and assess its quality are described, along with the software tools used for data analysis itself. An outlook for the development of these projects towards Run 4 is also provided
Characterization of atmospheric aerosol and its carbonaceous components at a central Mediterranean site: A multi-method approach using optical, physical, and isotopic techniques
No full textA new analytical approach combining aethalometer measurements, organic and elemental carbon (OC/EC) analysis, Scanning Electron Microscopy (SEM), Particle Induced X-ray Emission (PIXE), and Isotope Ratio Mass Spectrometry (IRMS) was used to characterize aerosol properties and its carbonaceous component in Lecce (Italy), located in the Central Mediterranean, during a monitoring campaign between May and June 2024. Both anthropogenic activities (e.g., vehicular traffic, industrial emissions) and natural events (e.g., wildfires, desert dust transport) were responsible for the high temporal variability of optical, physical, and chemical properties of atmospheric aerosol at the study site. In more detail, the measured Absorption Ångström Exponent (AAE) mean values (in the range 1.0–1.5) indicated a mixture of black carbon and organic or biogenic particles. Correlation analyses between aerosol absorption coefficients and PM mass concentrations highlighted a stronger relationship with EC compared to OC, highlighting the role of EC in the absorption properties of atmospheric aerosols. Chemical characterization through SEM and PIXE identified three aerosol source clusters: anthropogenic (high C concentrations, markers of combustion sources and industrial emissions), desert dust (crustal elements), and marine spray (Na and Cl). IRMS isotopic analysis further confirmed the distinction between anthropogenic and natural aerosol sources, with overlaps observed for marine aerosols influenced by both natural and anthropogenic activities. This work underlines the importance of multi-method procedures in understanding aerosol composition and dynamics, with potential associations for air quality monitoring, climate modeling, and health risk assessments
Further advances on isotropic correlation models with negative values
No full textMost of the covariance models utilized in spatial and in spatio-temporal data analysis are non negative; at this purpose, covariance functions characterized by negative values need to be explored not only to analyze some particular case studies characterized by negative correlation, but also and most importantly to provide richer families of correlation models. In this paper new families of correlation functions will be proposed, among the others, a generalization of the Cauchy correlation family as well as a generalization of a subclass of Matérn family. Moreover, apart from the Bochner’s spectral representation, in order to construct further families of correlation functions, a technique based on the differentiation of covariance models will be provided. Some of these new classes are characterized by a finite number of zeros as many as desired; at our knowledge, there seem not to exist correlation functions which present this relevant characteristic. Moreover, some of these new families can be built through differentiation by starting from covariance functions which are always positive in their domain. As it will be shown, the proposed classes are extremely flexible since they are able to model either correlation structures just characterized by positive values, either correlation structures which are negative in a subset of their domain: this is a relevant property of the proposed covariance models, essentially because most of the well known covariance functions, belonging to the same family, are not able to model both negative and positive correlation structures, according to their parameters values. A graphical representation and some general remarks on the proposed families of correlation models have been provided
Migranti e informazione adeguata
No full textGli obblighi informativi hanno assunto nel corso degli anni un ruolo di sempre maggiore spicco nella formazione del vincolo contrattuale. Ciò discende dalla posizione strategica che ricoprono: l’informazione, infatti, è l’obbligatorio (e necessario) trait d’union tra un ‘contatto’ e l’eventuale successivo ‘contratto’. Già dalla disciplina consumeristica emerge un’attenzione particolare in ordine all’effettività della comprensione del testo contrattuale da parte del contraente posto in una posizione di strutturale debolezza, atteso che, a mente dell’art. 5 c. 3 c.cons., le informazioni al consumatore devono essere “espresse in modo chiaro e comprensibile” e “tali da assicurare la [sua] consapevolezza”. Il saggio, partendo da queste premesse, affronta il tema della contrattazione con la persona-migrante, che occupa una posizione di debolezza acuita dalla diversità di lingua e cultura, e propone una soluzione che porta ad attribuire all’informazione nuovi connotati
Investigation of hadronic cross sections of cosmic ray carbon and oxygen on BGO from 200 GeV to 10 TeV energy at the DAMPE experiment
No full textThe Dark Matter Particle Explorer (DAMPE) has made significant progress in measuring the fluxes of cosmic rays. These new measurements are pivotal in advancing our understanding of the origins and propagation mechanisms of cosmic rays. The bismuth germanium oxide (BGO) calorimeter plays a crucial role in these measurements, particularly in the precise determination of cosmic ray fluxes. However, for a calorimetric experiment like DAMPE, uncertainties in hadronic models persist as a major barrier in achieving more accurate measurements of fluxes of cosmic ray nuclei. This study centers on the measurement of the inelastic hadronic cross sections of carbon and oxygen nuclei interacting BGO crystals target over an extensive energy range, spanning from 200 GeV to 10 TeV. For carbon nuclei interacting with the BGO target. The measurements of the cross sections have achieved a total relative uncertainty of less than 10% below 8 TeV for carbon, and below 3 TeV for oxygen. For oxygen nuclei, the same level of precision was attained below 3 TeV. Additionally, we compare the experimental results with geant4 and fluka simulations to validate the accuracy and consistency of these simulation tools. Through comprehensive analysis of the inelastic hadronic interaction cross sections, this research provides validation for the hadronic interaction models used in DAMPE’s cosmic-ray flux measurements
Teaching Strategies and Learning Outcomes in Deaf Children: A Comprehensive Review of Inclusive Educational Practices
No full textA classification of the flag-transitive 2-(v,k,2) designs
No full textIn this paper, we provide a complete classification of 2-designs admitting a flag-transitive automorphism group of affine type with the only exception of the semilinear 1-dimensional group. Alongside this analysis, we provide a construction of seven new families of such flag-transitive 2-designs, one of them infinite, and some of them involving remarkable objects such as t-spreads, translation planes, quadrics and Segre varieties. Our result together with those of Alavi et al. [1], [2], Praeger et al. [17], Zhou and the first author [39], [40] provides a complete classification of 2-design admitting a flag-transitive automorphism group with the only exception of the semilinear 1-dimensional case
Predicting the multilevel biodiversity index through machine learning methods: A case study
No full textBiodiversity is pivotal in sustaining ecological processes and ensuring ecosystem robustness, underpinning vital services like pollination, water purification, and climate regulation. Nevertheless, its swift decline, largely due to human-induced factors such as climate change, land-use alter- ation, pollution, and invasive species, has triggered significant global concern. The biodiversity reduction has repercussions beyond environmental deterioration, posing substantial hurdles to achieving international sustainability goals, particularly the United Nations Sustainable Development Goals (SDGs), including Goal 13 (Climate Action) and Goal 15 (Life on Land). Several machine learning approaches are compared, including random forests (RF), support vector machines (SVM), extreme gradient boosting (XGBoost), decision trees (DT), and linear regression (LR), to predict the multilevel biodiversity index (MBI) in the South of Italy, based on PM10, temperature, pressure, and precipitation. The results show a significant decrease in biodiversity in areas with high PM10 concentrations, especially agricultural and industrial zones, highlighting the negative impact of air pollution on ecological systems. Among the above-mentioned approaches, the best performance is obtained with DT and XGBoost, reliably predicting MBI based on various evaluation metrics. These findings provide valuable insights for policymakers and contribute to mitigating human-driven ecological impacts