Research Data UNIPD
Not a member yet
461 research outputs found
Sort by
Salinity variations in the Venice Lagoon (Italy) induced by safeguard structures: a challenging trade-off between urban and ecosystem protection in the face of climate change
No full textDataset for salinity and water level variation in the northern Venice Lagoon (Italy) under present and future scenario
Educational material about stress under strip load. Supplementary to "Teaching numerical methods or teaching with numerical methods?" (2025)
No full textThe folder contains educational material to tech stress under strip load in geomechancs courses.
the zip folder contains:
-Contour figures of normalized stress increments (∆σ_z/q, ∆σ_x/q, ∆τ_zx/q) with normalized coordinates (X/B, Z/B) with origin in the centre of the loaded area calculated analytically. These are in .fig and .jpg format. Files in .fig can only be opened in MatLab by teachers familiar with this program and offer the opportunity to modify or interact with the figures.
-Excel sheets with normalized stress increments (∆σ_z/q, ∆σ_x/q, ∆τ_zx/q) with normalized coordinates (X/B, Z/B). Teachers can use it to create additional figures for their classes or provide assignments to students.
-Contour figures of vertical stresses and displacement obtained with FEM using different material parameters and constitutive models.
-PowerPoint slides with the analytical and numerical solutions. These slides can be open in PowerPoint and modified by the teacher or used as is in their classes.
-A Word file with metadata and instructions for users
-GeoStudio models. Teachers familiar with the program can inspect and modify them or use to give assignments to students
Data 2023-2024 ETNSkill-For.Action_ESR_11_02
Full text linkThe uploaded datasets are needed to run the multi-objective optimization model presented in the scientific article ‘Optimizing tree selection for cable yarding operations planning: a multi-objective modelling approach’
Martian simulant analysis dataset
No full textThis dataset contains data derived from chemical, mineralogical, granulometric and hyperspectral acquisitions of Mars Global (MGS-1) High-Fidelity Martian Dirt Simulant [1], Mojave Mars Simulant MMS-1 and Enhanced Mars Simulant (MMS-2). The instruments used for this work are:
- Laser Diffraction Particle Size Analyzer Malvern Panalytical Mastersizer3000: granulometric analysis;
- Inductively Coupled Plasma Mass Spectrometer (ICP-MS) Perkin-Elmer NexION 350X: chemical analysis;
- X-Ray powder Diffractometer (XRD) Philips X’Pert PRO: mineralogical analysis;
- Scanning Electron Microscope (SEM-EDS) Tescan SOLARIS equipped with Oxford Instruments microanalytical system: mineralogical analysis.
- Headwall Photonics Nano-Hyperspec (400-1000 nm) and Micro-Hyperspec (900-2500 nm) cameras: hyperspectral acquisitions;
The Mastersizer3000 software creates tables and related plots of grainsize ready to use.
The detector of mass spectrometer generates data in CPS (counts per second). Knowing the dilutions of the solutions, the spectrometer software calculates the quantities in terms of weight over volume (µg/l) in a table. Thereafter, knowing the initial weights of the simulant in the solutions, the operator converts data from weight over volume (µg/l) to weight over weight (mg/kg).
Qualitative phase analysis on powder diffraction data has been run through a search-match algorithm, in order to identify the minerals species. Quantitative phase analysis has been performed using the Rietveld method with internal standard addition, as implemented in Profex-BGMS v. 5.2.3.
The SEM products are photos of the sites, where the mineralogical analysis is performed, and graphs with peaks. The peaks are associated with specific chemical elements through the SEM software, that allows to determine the minerals present in the simulant. It was carried out only on the largest grains of MGS-1 simulant.
The hyperspectral cameras acquire hyperspectral cubes that the operator can open in ENVI software [3] or similar ones for hyperspectral imaging data-sets to extrapolate the spectrum of the simulants. The spectrum is saved in table format (ASCII) and can be opened in Origin software [4] or any software dedicated to graph and table management (e.g., Excel). In Origin, the operator produces the spectral plot, where he/she can continue with direct interpretations of absorption peaks, characteristic of particular minerals
Database of observed and calculated infrared peaks for hydrogen-related defects in natural diamond
Full text linkThis database contains observed (Table A1) and calculated (Tables B1-B3) infrared peak positions (absorption frequencies, cm-1) for different hydrogen-related defects observed in diamond. If known, the hydrogen-related defect type and C-H or N-H vibrational mode is included for each peak position. The majority of data was taken from the literature and the corresponding references are included for each peak position. Some new peak data was included from FTIR spectra analyzed by the authors. Additional data regarding the computation parameters for each simulated (calculated) FTIR spectra are included in the calculated database (Tables B1-B3). A more detailed description of how the database is structured can be found in the corresponding publication at https://doi.org/10.1016/j.diamond.2024.110866
Two-Dimensional Electronic Spectroscopy Characterization of Fucoxanthin – Chlorophyll Protein
Full text linkThe collection includes the results of the two-dimensional electronic spectroscopy measurements performed on a solution of Fucoxanthin – Chlorophyll Protein from Cyclotella meneghiniana.
Sample: FCPa @ room temperature
Rephasing (R), non-rephasing (N) and total (T) signal datasets are provided
data published in Marcolin et al. JPCLett 202
Paradoxical response to GH predicts glucose metabolism alterations in acromegaly
No full textObjective: A paradoxical increase in GH after oral glucose load (GH-Par) characterizes about one-third of acromegaly patients and is associated with a better response to first-generation somatostatin receptor ligands (fg-SRLs). Pasireotide is typically considered as a second-/third-line treatment. Here, we aimed to investigate the predictive role of GH-Par in Pasireotide response and the development of adverse events.
Design: Multi-center Italian retrospective cohort of 78 patients treated for at least 3 months with Pasireotide.
Results: IGF-1 median levels were 1.38 times the upper limit of normality (ULN) in patients with large (median 18 mm) and invasive (78%) adenomas after fg-SRL treatment failure. After a 37-month median treatment, Pasireotide effectively reduced IGF-1 ULN levels in 65 patients. Notably, 74% of cases experienced a ≥30% reduction, with normalization achieved in 58%. Among 59 patients with available OGTTs, 13 showed GH-Par (22%). Despite similar pre-Pasireotide IGF-1 levels, GH-Par patients more frequently exhibited >50% reduction in basal IGF-1 ULN after prior treatments compared to GH-NPar (83% vs 42%, p=0.02). The median Pasireotide duration (16.0 vs 24.5 months), dosage (40 vs 50 mg/monthly), and efficacy in reducing IGF-1 ULN (-49.5% vs -57.3%) were similar between the GH-Par and GH-NPar groups. Pasireotide was discontinued in 11 patients due to new-onset or worsening of glucose metabolism alterations, with higher incidence in GH-Par (77%) vs GH-NPar (37%) (p=0.011).
Conclusions: The GH-Par does not predict the response to Pasireotide in acromegaly but can predict new-onset Pasireotide-induced glucose metabolism alterations
Behaviour at the nest - data repository
No full textData belonging to the manuscript Behaviour at the nest done as a chapter of Alejandro Corregidor-Castro PhD thesis
Absolutely relative chicks: Variability in cognitive strategies during a numerical discrimination task: individual and comparative insights from day-old domestic chicks (Gallus gallus)
No full textNumerical abilities play a fundamental role in survival by enabling animals to assess resources and make adaptive decisions. Among these, numerical discrimination, the capability to distinguish between larger and smaller numerosities, is highly studied. Numerical discrimination can be solved using two strategies: the absolute, selecting a specific numerosity, or the relative, identifying the larger or smaller one. While numerical discrimination is shared across species, the strategies used to address it vary: humans and fish employ a relative strategy, while honeybees use an absolute one. It remains unclear which strategy birds prefer, especially if they have only minimal numerical experience.
Here, we investigated whether 3-day-old chicks adopt absolute or relative numerical discrimination. During rearing, chicks associated a numerosity with food. At test, we assessed whether they used an absolute or relative strategy. At the group level, no significant preference emerged, regardless of whether higher or lower numerosities were associated with food. However, at the individual level, chicks displayed significant preferences that could not be explained by stimulus novelty or physical variables (e.g., overall area). Flexibility in numerical discrimination may reflect an evolutionary adaptation or developmental feature. Retaining multiple strategies, and refining one through environmental interactions, could benefit young animals
Martian simulant analysis dataset
No full textThis dataset contains data derived from chemical, mineralogical, granulometric and hyperspectral acquisitions of Mars Global (MGS-1) High-Fidelity Martian Dirt Simulant [1], Mojave Mars Simulant MMS-1 and Enhanced Mars Simulant (MMS-2). The instruments used for this work are:
- Laser Diffraction Particle Size Analyzer Malvern Panalytical Mastersizer3000: granulometric analysis;
- Inductively Coupled Plasma Mass Spectrometer (ICP-MS) Perkin-Elmer NexION 350X: chemical analysis;
- X-Ray powder Diffractometer (XRD) Philips X’Pert PRO: mineralogical analysis;
- Scanning Electron Microscope (SEM-EDS) Tescan SOLARIS equipped with Oxford Instruments microanalytical system: mineralogical analysis.
- Headwall Photonics Nano-Hyperspec (400-1000 nm) and Micro-Hyperspec (900-2500 nm) cameras: hyperspectral acquisitions;
The Mastersizer3000 software creates tables and related plots of grainsize ready to use.
The detector of mass spectrometer generates data in CPS (counts per second). Knowing the dilutions of the solutions, the spectrometer software calculates the quantities in terms of weight over volume (µg/l) in a table. Thereafter, knowing the initial weights of the simulant in the solutions, the operator converts data from weight over volume (µg/l) to weight over weight (mg/kg).
Qualitative phase analysis on powder diffraction data has been run through a search-match algorithm, in order to identify the minerals species. Quantitative phase analysis has been performed using the Rietveld method with internal standard addition, as implemented in Profex-BGMS v. 5.2.3.
The SEM products are photos of the sites, where the mineralogical analysis is performed, and graphs with peaks. The peaks are associated with specific chemical elements through the SEM software, that allows to determine the minerals present in the simulant. It was carried out only on the largest grains of MGS-1 simulant.
The hyperspectral cameras acquire hyperspectral cubes that the operator can open in ENVI software [3] or similar ones for hyperspectral imaging data-sets to extrapolate the spectrum of the simulants. The spectrum is saved in table format (ASCII) and can be opened in Origin software [4] or any software dedicated to graph and table management (e.g., Excel). In Origin, the operator produces the spectral plot, where he/she can continue with direct interpretations of absorption peaks, characteristic of particular minerals