Hacia una clasificación de grano fino de los verbos de movimiento. El caso de los verbos intransitivos del español

Based on the lexicalization patterns presented in Talmy’s pioneering work (1985), motion verbs classifications for Spanish mainly recognize two groups: verbs of manner and verbs of direction (Lamiroy, 1991; Cifuentes Honrubia, 1988-1989; Crego García, 2000; Morimoto, 2001, among others). This research offers a much more detailed classification, by means of the use of a finer set of features and semantic participants that may be lexicalized by motion verbs in any language of the world, namely: the aspectual features of punctuality and telicity; the participants theme, source, path, goal, point of reference, location-path and trajectory; and the parametric features of displacement, movement, manner, change of place and direction. The result is a classification of eight different verb groups that account for the lexical and syntactic mechanisms present in the encoding of the Spanish motion events.

Ultrasonographic and Three-Dimensional Analyses at the Glabella and Radix of the Nose for Botulinum Neurotoxin Injection Procedures into the Procerus Muscle

Botulinum neurotoxin (BoNT) injections are widely used for facial rejuvenation procedures, and the procerus muscle is a major target in cases of glabellar transverse lines or rhytids. Although there have been many cadaveric studies of the procerus, its depth and thickness have not been investigated thoroughly. The aim of this study was to measure the depth and thickness of the procerus and identify the location of the intercanthal vein using ultrasonographic (US) imaging and the three-dimensional scanning method, which is needed to know to avoid side effects during BoNT injections. The morphology of the procerus was classified into two types based on the US images obtained at the glabella. The procerus was located deeper below the skin surface at the glabella than the sellion (3.8 ± 0.7 mm versus 2.7 ± 0.6 mm). The width of the procerus in US images increased from the sellion (10.9 ± 0.2 mm) to the glabella (14.5 ± 4.6 mm), whereas its thickness decreased (from 1.6 ± 0.6 mm to 1.1 ± 0.5 mm). The intercanthal vein was located 5.1 ± 4.0 mm superior to the sellion and 3.0 ± 0.6 mm below the skin’s surface. The present findings provide anatomical knowledge as well as the reference location information for use when injecting BoNT into the procerus.

Comparison of Automated Georeferencing Tools Using Insect Collection Data

Major efforts are being made to digitize natural history collections to make these data available online for retrieval and analysis (Beaman and Cellinese 2012). Georeferencing, an important part of the digitization process, consists of obtaining geographic coordinates from a locality description. In many natural history collection specimens, the coordinates of the sampling location are not recorded, rather they contain a description of the site. Inaccurate georeferencing of sampling locations negatively impacts data quality and the accuracy of any geographic analysis on those data. In addition to latitude and longitude, it is important to define a degree of uncertainty of the coordinates, since in most cases it is impossible to pinpoint the exact location retrospectively. This is usually done by defining an uncertainty value represented as a radius around the center of the locality where the sampling took place. Georeferencing is a time-consuming process requiring manual validation; as such, a significant part of all natural history collection data available online are not georeferenced. Of the 161 million records of preserved specimens currently available in the Global Biodiversity Information Facility (GBIF), only 86 million (53.4%) include coordinates. It is therefore important to develop and optimize automatic tools that allow a fast and accurate georeferencing. The objective of this work was to test existing automatic georeferencing services and evaluate their potential to accelerate georeferencing of large collection datasets. For this end, several open-source georeferencing services are currently available, which provide an application programming interface (API) for batch georeferencing. We evaluated five programs: Google Maps, MapQuest, GeoNames, OpenStreetMap, and GEOLocate. A test dataset of 100 records (reference dataset), which had been previously individually georreferenced following Chapman and Wieczorek 2006, was randomly selected from the Museu Nacional de História Natural e da Ciência, Universidade de Lisboa insect collection catalogue (Lopes et al. 2016). An R (R Core Team 2018) script was used to georeference these records using the five services. In cases where multiple results were returned, only the first one was considered and compared with the manually obtained coordinates of the reference dataset. Two factors were considered in evaluating accuracy: Total number of results obtained and Distance to the original location in the reference dataset. Total number of results obtained and Distance to the original location in the reference dataset. Of the five programs tested, Google Maps yielded the most results (99) and was the most accurate with 57 results < 1000 m from the reference location and 79 within the uncertainty radius. GEOLocate provided results for 87 locations, of which 47 were within 1000 m of the correct location, and 57 were within the uncertainty radius. The other 3 services tested all had less than 35 results within 1000 m from the reference location, and less than 50 results within the uncertainty radius. Google Maps and Open Street Map had the lowest average distance from the reference location, both around 5500 m. Google Maps has a usage limit of around 40000 free georeferencing requests per month, beyond which the service is paid, while GEOLocate is free with no usage limit. For large collections, this may be a factor to take into account. In the future, we hope to optimize these methods and test them with larger datasets.

Assessment of the dust catching capacity of the leaves of some plant species growing along the road sides

The present study has been carried out to assess the dust catching capacity of the leaves of five different species viz. Alstonia scholaris Linn., Cassia siamea Lam., Morus alba L., Nerium indicum L. and Thevitia peruviana (Pers.) K. Schum, growing along the road side ( taken as polluted site ) and away from the road side ( taken as reference site). The evaluation of the data revealed that the dust content on the surface of leaves of all selected species was more at polluted locations in comparison to those growing at reference location. Among the selected species Cassia siamea Lam. shows highest dust catching capacity while the minimum dust catching capacity has been recorded for Nerium indicum L. The highest dust catching capacity of Cassia siamea Lam. has been attributed to its horizontal position of leaves while the minimum dust catching capacity of Nerium indicum L. to its thick, leathery surface and the orientation of the leaves which are growing at an angle with the stem.

Mapping air temperature using time series analysis of LST: the SINTESI approach

This paper presents a new procedure to map time series of air temperature (Ta) at fine spatial resolution using time series analysis of satellite-derived land surface temperature (LST) observations. The method assumes that air temperature is known at a single (reference) location such as in gridded climate data with grid size of the order of 35 km × 35 km. The LST spatial and temporal pattern within a grid cell has been modelled by the pixel-wise ratios r (x,y,t) of the LST at any location to the LST at a reference location. A preliminary analysis of these patterns over a decade has demonstrated that their intra-annual variability is not negligible, with significant seasonality, even if it is stable throughout the years. The intra-annual variability has been modeled using Fourier series. We have evaluated the intra-annual variability by theoretically calculating the yearly evolution of LST (t) for a range of cases as a function of terrain, land cover and hydrological conditions. These calculations are used to interpret the observed LST (x,y,t) and r (x,y,t). The inter-annual variability has been evaluated by modeling each year of observations using Fourier series and evaluating the interannual variability of Fourier coefficients. Because of the negligible interannual variability of r (x,y,t), LST (x,y,t) can be reconstructed in periods of time different from the ones when LST observations are available. Time series of Ta are generated using the ratio r (x,y,t) and a linear regression between LST and Ta. Such linear regression is applied in two ways: (a) to estimate LST at any time from observations or forecasts of Ta at the reference location; (b) to estimate Ta from LST at any location. The results presented in this paper are based on the analysis of daily MODIS LST observations over the period 2001–2010. The Ta at the reference location was gridded data at a node of a 35 km × 35 km grid. Only one node was close to our study area and was used for the work presented here. The regression of Ta on LST was determined using concurrent observations of Ta at the four available weather stations in the Valle Telesina (Italy), our study area. The accuracy of our estimates is consistent with literature and with the combined accuracy of LST and Ta. We obtained comparable error statistics when applying our method to LST data during periods different but adjacent to the periods used to model of r (x,y,t). The method has also been evaluated against Ta observations for earlier periods of time (1984–1988), although available data are rather sparse in space and time. Slightly larger deviation were obtained. In all cases five days of averages from estimated and observed Ta were compared, giving a better accuracy.