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13 results for “South Tyrol”
Context-Aware Dataset: STS - South Tyrol Suggests IoT Mobile App Data
<p><strong>STS dataset </strong>was collected by a context-aware recommender system mobile app named as<strong> <a href="https://play.google.com/store/apps/details?id=it.unibz.sts.android&hl=en">"South Tyrol Suggests"</a></strong>. The app provides <strong>context-aware recommendations</strong> for attractions, events, public services, restaurants, and much more based on the rating preferences and personality factors of users.</p> <p><strong>Contextual</strong> <strong>variables</strong> includes </p> <ul> <li><strong>distance:</strong> far away, near by</li> <li><strong>time available:</strong> half day, one day, more than one day</li> <li><strong>temperature:</strong> burning, hot, warm, cool, cold, freezing</li> <li><strong>crowdedness:</strong> crowded, not crowded, empty</li> <li><strong>knowledge of surroundings:</strong> new to area, returning visitor, citizen of the area</li> <li><strong>season:</strong> spring, summer, autumn, winter</li> <li><strong>budget:</strong> budget traveler, price for quality, high spender</li> <li><strong>daytime:</strong> morning, noon, afternoon, evening, night</li> <li><strong>weather:</strong> clear sky, sunny, cloudy, rainy, thunderstorm, snowing</li> <li><strong>companion:</strong> alone, with friends/colleagues, with family, with girlfriend/boyfriend, with children</li> <li><strong>mood:</strong> happy, sad, active, lazy weekday: weekday, weekend</li> <li><strong>travel goal:</strong> visiting friends, business, religion, health care, social event, education, scenic/landscape, hedonistic/fun, activity/sport</li> <li><strong>means of transport:</strong> no transportation means, a bicycle, a car, public transport</li> </ul> <p>More details can be found here:</p> <p><em>Braunhofer, Matthias, Mehdi Elahi, and Francesco Ricci. <a href="https://www.researchgate.net/profile/Mehdi_Elahi2/publication/283502363_Techniques_for_cold-starting_context-aware_mobile_recommender_systems_for_tourism/links/56ccaa7608ae059e37507cc0.pdf">"<strong>Techniques for cold-starting context-aware mobile recommender systems for tourism</strong>."</a> Intelligenza Artificiale 8, no. 2 (2014): 129-143.</em></p>
Pesticide residue monitoring in South Tyrol (Italy)
<ul> <li>Pesticide residue monitoring programm in South Tyrol (Province Bolzano, Italy)</li> <li>The programm is organized and conducted by the Department of Public Health, Servizio Igiene e Sanità<br> Pubblica—Azienda Sanitaria dell’Alto Adige, Bolzano, Italy</li> <li>Further despription and data available at: <ul> <li>https://www.sabes.it/gesundheitsvorsorge/umweltmedizin.asp</li> <li>https://umwelt.provinz.bz.it/pestizide-suedtirol.asp</li> </ul> </li> <li>Residue concentrations of grass samples per sampling site and sampling date can be found in the file "Pesticide_monitoring_SouthTyrol_2018_2021.csv "</li> <li>Available period: 2018 to 2021</li> <li>All sampling sites were public sites</li> <li>Names of active agents are in Italian</li> <li>Residue concentartions are given in "mg kg<sup>-1</sup>"</li> <li>"n.d." means "not detected"</li> <li>Lower limit of quantification (LOQ) was by default 0.01 mg kg<sup>-1</sup></li> <li>GPS coordinates of the sampling sites are can be found in thefile "Coordinates_sampling_sites.csv"</li> </ul>
Figure 4 in Abrupt boundaries between mountain meadows and forests separate ground-dwelling invertebrate communities: a case study from South Tyrol, Italy
Figure 4. Abundance-based accumulation curves for ground-dwelling macro-invertebrates from montane meadows and mixed forests in South Tyrol, Italy. The data come from pitfall traps along a linear transect from extensively managed hay meadows ('MM' and 'M', squares) across an abrupt ecotone ('E', diamonds) towards mixed forest stands ('F' and 'FF', circles). The curves show from left to right: the sampling coverage, taxa and species richness (Hill number q = 0), Shannon (q = 1) and Simpson diversity (q = 2). Plot [A] shows the total faunal community data at the highest taxonomic resolution, plot [B] the Araneae data at species level.
Figure 3 in Abrupt boundaries between mountain meadows and forests separate ground-dwelling invertebrate communities: a case study from South Tyrol, Italy
Figure 3. Boxplots with jitter of ground-dwelling macro-invertebrate activity densities from montane meadows and mixed forests in South Tyrol, Italy. Each data point represents a pitfall trap along a linear transect starting from extensively managed hay meadows ('MM' and 'M') across an abrupt ecotone ('E') towards mixed forest stands ('F' and 'FF'). Significant differences between the habitat plots (i.e. on the X-axes) according to GLM and Tukey's HSD post-hoc tests are indicated with different letters at top of each plot.
Data from GB-SAR measurements on Lazaun rock glacier (Val Senales, South Tyrol, northern Italy)
<p>The *.csv files report the kinematic data extracted from the displacement maps obtained from the processing of ground-based SAR measurements of Lazaun rock glacier (Senales Valley, Northern Italy) and presented in the paper <strong><em>“Unprecedented observation of hourly rock glacier velocity with Ground-Based SAR</em></strong><strong><em>”</em></strong> (Bertone et al., 2023, submitted). The data were used to display the time series reported in the paper. The data refer to two field campaigns named <em>survey1</em> (<em>from 09/08/2018 to 18/08/2018</em>), and <em>survey2 </em>(<em>from 13/09/2018 to 03/10/2018</em>).</p> <ul> <li><em>TS_August_moving.cs</em>v: includes the survey 1 displacement data of moving points on the rock glacier.</li> <li><em>TS_August_stable.csv</em>: includes the survey 1 displacement data of stable points outside the rock glacier.</li> <li><em>TS_September_moving.csv</em>: includes the survey 2 displacement data of moving points on the rock glacier.</li> <li><em>TS_ September_stable.csv</em>: includes the survey 2 displacement data on stable points outside the rock glacier.</li> </ul> <p>Each *.csv file contains the following fields:</p> <ul> <li>“<em>displacement</em>”: cumulative displacement (mm);</li> <li>“<em>pointName</em>”: name of point where the time series are computed, as displayed in figure 3;</li> <li>“<em>time</em>”: time of acquisition, in <em>day</em>/<em>month</em>-<em>hour</em>:<em>minute </em>format;</li> <li>“<em>velocity</em>”: velocity (mm/hour);</li> <li>“<em>X</em>” and “<em>Y</em>”: coordinates of points (EPGS 32632) where the time series were extracted.</li> </ul> <p>The polygon representing the area of the Lazaun rock glacier is provided by the shapefile <em>Polygon_RG_Lazaun.shp.</em></p> <p>The velocity distribution on the Lazaun rock glacier as obtained in suvey1 and survey2 is provided by raster files. The velocities were obtained along the LOS and are in mm/day. The two raster files, named <em>raster_survey_1.tif</em> and <em>raster_survey_2.tif</em>, are completed by two files of the same name with the colored overlay (<em>raster_survey_1.lyr</em> and <em>raster_survey_2.lyr</em>).</p> <p>The two velocity maps obtained from survey1 and survey2 are also provided as complete georeferenced figures in geotiff format and named <em>figure_survey_1.tif</em> and<em> figure_survey_2.tif.</em></p> <p>All the geospatial data are provided in the EPSG 32632 spatial reference.</p> <p> </p> <p><strong>AIR TEMPERATURE</strong></p> <p>The LAZ_AIRT_survey1.csv and LAZ_AIRT_survey2.csv files contain the air temperature measured about 250 m North from the Lazaun rock glacier by a Gemini Tinytag TGP 4020 data logger connected to an external probe installed in a passive radiation shield. The data cover the two GB-SAR field campaigns (survey 1 from 09/08/2018 to 18/08/2018, and survey 2 from 13/09/2018 to 03/10/2018).</p> <p>The csv files contain the following fields:</p> <ul> <li>Date: time of acquisition, in <em>day/month/year</em> <em>hour:minute</em> format;</li> <li>Mean: the mean air temperature recorded by the datalogger during the corresponding hour;</li> <li>Maximum: the maximum air temperature recorded by the datalogger during the corresponding hour;</li> <li>Minimum: the minimum air temperature recorded by the datalogger during the corresponding hour;</li> </ul>
Data on epiphytic lichens along elevational gradients in South Tyrol, Italy
<p>1. Several studies have evaluated lichen responses in terms of shifts in species climate suitability, species richness, and community composition. In contrast, patterns of co-occurrence among species that could be related to complex species interactions have received less consideration. Biotic interactions play a major role in shaping species niches, fitness, and adaptation to new environments. Therefore, considering the specific relationships among co-occurring species is essential to further deepen our knowledge of biodiversity response to climate change. In this perspective, the analysis of lichen ecological networks across elevational gradients may provide a powerful tool to understand how communities are structured and how biotic interactions are modulated by changing climatic conditions.</p> <p>2. We evaluated the contribution of environmental and species biological attributes to the structure of epiphytic lichen-host tree networks. Specifically, we studied lichen communities considering two different network levels: the whole lichen community, and groups of lichen species that presented similar biological traits. In this framework, we (1) characterized the structure of the epiphytic lichen-host tree networks; (2) assessed how network structure varied with climate, forest attributes, and community trait diversity; and (3) evaluated the role that biological traits played in the connections established between co-occurring lichens.</p> <p>3. On one hand, results indicate that epiphytic lichen communities are dominated by local segregation, suggesting habitat specialization among lichens within their host tree, and that climatic conditions and, to a lesser extent, lichen diversity are the main drivers of community assemblage. On the other hand, the role of lichen species in the networks depends on their particular biological traits, supporting the hypothesis that biological traits contribute to shape network structure by influencing the ability of the species to interact between each other. These findings warn about the potential impact of climate change on epiphytic lichen communities.</p> <p>4.<i> Synthesis. </i>This study builds towards a better understanding of lichen community assembly and on biodiversity response to climate change in forest alpine ecosystems. In particular, our results highlight the value of lichen-tree networks to inform about assemblage processes acting at different organizational levels and indicate that lichens might become one of the most threatened groups under global change scenarios.</p>
Data on epiphytic lichens along elevational gradients in South Tyrol, Italy
Open the record for dataset details and reuse information.
Figure 2 in Abrupt boundaries between mountain meadows and forests separate ground-dwelling invertebrate communities: a case study from South Tyrol, Italy
Figure 2. Unconstrained Detrended Canonical Analyses (DCA) of log-transformed abundances of ground-dwelling macroinvertebrates from montane meadows and mixed forests in South Tyrol, Italy. Data for the highest available taxonomic resolution was used (i.e. Araneae and Formicidae at species level, all other on family level, where possible). Each data point represents a pitfall trap along a linear transect starting from extensively managed hay meadows ('MM' and 'M', squares) across an abrupt ecotone ('E', diamonds) towards mixed forest stands ('F' and 'FF', circles). The size of the data points represents the number of taxa from min. 15 to max. 41.
Figure 1 in Abrupt boundaries between mountain meadows and forests separate ground-dwelling invertebrate communities: a case study from South Tyrol, Italy
Figure 1. Overview map of the study area of Barbian/Barbiano, South Tyrol (Italy), showing the three extensively managed meadows and the linear transects towards the forests. (A) Overview of the three meadows that are embedded in montane mixed forests. (B) Detailed view of a site showing the sampling design ('MM' – meadow, 'E' – ecotone, 'FF' – forest). (C) Photo of the plot EH3 (Photo credit: Michael Steinwandter). (D) Position of the study site of Barbian/Barbiano within the European Alps (red border). Aerial photographs by Google Earth.
Pesticide residue monitoring in South Tyrol (Italy)
<ul> <li>Pesticide residue monitoring programm in South Tyrol (Province Bolzano, Italy)</li> <li>The programm is organized and conducted by the Department of Public Health, Servizio Igiene e Sanità<br> Pubblica—Azienda Sanitaria dell’Alto Adige, Bolzano, Italy</li> <li>Further despription and data available at: <ul> <li>https://www.sabes.it/gesundheitsvorsorge/umweltmedizin.asp</li> <li>https://umwelt.provinz.bz.it/pestizide-suedtirol.asp</li> </ul> </li> <li>Residue concentrations of grass samples per sampling site and sampling date can be found in the file "Pesticide_monitoring_SouthTyrol_2018_2021.csv "</li> <li>Available period: 2018 to 2021</li> <li>All sampling sites were public sites</li> <li>Names of active agents are in Italian</li> <li>Residue concentartions are given in "mg kg<sup>-1</sup>"</li> <li>"n.d." means "not detected"</li> <li>Lower limit of quantification (LOQ) was by default 0.01 mg kg<sup>-1</sup></li> <li>GPS coordinates of the sampling sites are can be found in thefile "Coordinates_sampling_sites.csv"</li> </ul>
Implementation of LUCAS 2 in Helicopter Rescue in South Tyrol
ClinicalTrials.gov study NCT01745926. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Characteristics and Outcome of Patients With COVID-19 in ICUs in South Tyrol
ClinicalTrials.gov study NCT05077319. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Geophone plate data from the Sulden/Solda basin (South Tyrol, Italy) 2014-2020
<p>This dataset contains the post-processing of 7 years of seismic data collected through geophone plates installed at the monitoring station of Stilfserbrücke - Ponte Stelvio (South Tyrol, Italy) in the framework of the AQUASED project (<a href="http://www.mountain-eering.com/wp/mountain-eering/i-nostri-servizi/ricerca-e-sviluppo/studio-aquased/">http://www.mountain-eering.com/wp/mountain-eering/i-nostri-servizi/ricerca-e-sviluppo/studio-aquased/</a>) and analyzed in the paper “Bedload fluxes in a glacier-fed river at multiple temporal scales” by Coviello et al. (2022). The monitoring station is located in the Sulden/Solda basin (130 km<sup>2</sup>). Eight geophone plates are equipped with 10-Hz vertical geophones, which continuously measure the vibration induced by the impact of bedload at a sampling frequency of 5 kHz. The 8 geophone plates are installed along the cross section and extends for 4 m, corresponding to half of the channel width (8 m) from the mid-channel (ch 1) to the right bank (ch 8), and are fixed on a check dam with a cantilevered metal structure. From the raw seismic data, the following signal metrics have been extracted and constitute the dataset: the impulses (Imp/min) calculated with four different thresholds (0.01, 0.04, 0.16, 0.32 V), the maximum amplitude (V), the main frequency (Hz) and the integral of the squared amplitude (V<sup>2</sup>) over 1-min time window. This dataset provides the above-mentioned signal metrics for the period 2014 to 2020, separated per plate (from DB_aquased_ch1.dat to DB_aquased_ch8.dat).</p>
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