Search Results (4)

The House Sparrow (Passer domesticus) is a common but declining bird species in its native urban areas, partly due to reduced nesting site availability caused by modern urbanisation and loss of old architectural styles. In this study, we analysed, through a multivariate approach, the environmental factors influencing House Sparrow nest site selection in three diverse inland urban areas within the Valencian Community, Spain. We located 584 House Sparrow nests during spring 2017 and also selected 300 random points (habitat availability) in the study localities. We used Factorial Analyses of Mixed Data to assess urban feature gradients of nests and urban variables. We carried out Generalized Linear Mixed Models to compare nest locations to random points and explore variations in nesting typologies between urban zones. Specific nest site preferences vary between urban sectors, indicating that House Sparrow nests are not randomly located in urban areas. Nests are typically found near parks, schools, vacant plots, city limits, and surrounding crops, where greater vegetation cover provides abundant food sources. Low-rise terraced houses with traditional roofs and open clay tiles are consistently preferred for nesting, whereas modern architectural trends reduce nesting opportunities. Preserving green areas and old architecture with open clay tiles is essential for maintaining nesting sites and promoting House Sparrow conservation in Mediterranean urban areas. Adherence to these conservation measures may also benefit other hole-nesting species and urban wildlife reliant on green spaces. Full article

The 18th century roof tiles from the “Casa delle vigne”, located in the Aosta region (north-east Italy), were investigated as an example of a peculiar historical roof covering: ceramic tiles with a lead-based glaze finishing to waterproof them are used to create colourful patterns. A conservation project proposed the integration of the original tiles with new ones, produced according to traditional methods. Ancient and new tiles were analysed with Fiber Optics Reflectance Spectroscopy, micro-Raman, Fourier Transform Infrared Spectroscopy and X-ray Fluorescence Spectrometry, Thermogravimetry and Differential Scanning Calorimetry for understanding the composition and the production technology of this manufacture. Their resistance to freezing and thawing cycles was then tested, considering their exposure in the severe alpine climate of Aosta. The use of pure clays with low calcium contents, high firing temperature and lead-rich glazes was found in ancient tiles, able to outstand several freezing-thawing cycles without damages. Iron and copper pigments were used in old yellow and green glazes. Zinc-based pigment, low lead and calcium-rich glazes are used in the new ones, which remained mainly coherent to the ceramic body during the freeze-thaw test. Full article

A novel roofing tile was developed containing various types of nanoparticles of titanium dioxide (TiO₂). Experiments were conducted using three types of TiO₂ nanoparticles with and without polyethylene glycol (PEG). All types of newly developed nanomaterials were characterized using X-ray diffractometry. Particle size distribution analysis was performed and specific surface area was determined using the Brunauer–Emmet–Teller method. SEM imaging was used for the morphological characterization of nanoparticles. Commercial ceramic roofing tiles underwent a dip-coating procedure to obtain the desired photocatalytic surface. The TiO₂ anatase samples exhibited greater surface areas of nanoparticles, thus providing potentially the highest photocatalytic efficiency. Full article

A classification method of hyperspectral reflectance images named CHRIPS (Classification of Hyperspectral Reflectance Images with Physical and Statistical criteria) is presented. This method aims at classifying each pixel from a given set of thirteen classes: unidentified dark surface, water, plastic matter, carbonate, clay, vegetation (dark green, dense green, sparse green, stressed), house roof/tile, asphalt, vehicle/paint/metal surface and non-carbonated gravel. Each class is characterized by physical criteria (detection of specific absorptions or shape features) or statistical criteria (use of dedicated spectral indices) over spectral reflectance. CHRIPS input is a hyperspectral reflectance image covering the spectral range [400–2500 nm]. The presented method has four advantages, namely: (i) is robust in transfer, class identification is based on criteria that are not very sensitive to sensor type; (ii) does not require training, criteria are pre-defined; (iii) includes a reject class, this class reduces misclassifications; (iv) high precision and recall, F ${}_1$ score is generally above 0.9 in our test. As the number of classes is limited, CHRIPS could be used in combination with other classification algorithms able to process the reject class in order to decrease the number of unclassified pixels. Full article