Object-Based Geomorphological Mapping: Application on an Alpine Deep-Seated Gravitational Slope Deformation Contest (Germanasca Valley, Western Alps—Italy)

This research reports the use of a new method of geomorphological mapping in GIS environments, using a full-coverage, object-based method, following the guidelines of the new geomorphological legend proposed by ISPRA–AIGEO–CNG. This methodology is applied to a tributary valley of the Germanasca Valley, shaped into calcschist and greenschist, of the Piedmont Zone (Penninic Domain, Western Alps). The investigated sector is extensively affected by dep-seated gravitational slope deformation (DSGSD) that strongly influences the geological setting and the geomorphological features of the area. The mapping of these gravitational landforms in a traditional way creates some difficulties, essentially connected to the high density of information in the same site and the impossibility of specifying the relationships between different elements. The use of the full-coverage, object-based method instead is advantageous in mapping gravitational evidence. In detail, it allows for the representation of various landforms in the same sector, and their relationships, specifying the size of landforms, and with the possibility of multiscale representation in the GIS environment; and, it can progressively be update with the development of knowledge. This research confirms that the use of the full-coverage, object-based method allows for better mapping of the geomorphological features of DSGSD evidence compared to classical representation.

Smart Sirens—Civil Protection in Rural Areas

Germany carried out a nationwide “Alert Day” in 2020 to test its civil alarm systems. The test revealed some problems. Heterogeneous development structures and topography can be limiting factors for sound propagation. In consequence, sirens could be heard inadequately, depending on their location. Furthermore, the reason of warning remains unknown to the public. In terms of civil protection, warnings with the code of behavior by general available media is desired. Smart sirens can transmit additional spoken information and be installed on already-existing streetlights. In this study, we analyze how smart sirens could lead to an improved civil protection. Exemplarily, a detailed analysis is made for a different structured rural area, Dansenberg in Germany, whereas the influence of local conditions on the sound propagation is considered. We analyzed with the software CadnaA—a software for calculation, assessment and prediction of environmental sound—how the location and number of smart sirens can be optimized in order to produce a full coverage of the study area. We modeled the coverage in different scenarios and compared four scenarios: (a) current situation with two E57 type sirens; (b) replacing the existing sirens with two high-performance sirens; (c) one high-performance siren at the more central point; and (d) optimized network of smart sirens of the type Telegrafia Bono. The aim was to achieve a full coverage with a minimum of warning sirens. We could show that the current situation with two E57 type sirens fails to reach out to the whole population whereas the optimized network of smart sirens results in a better coverage. Therefore, a reconsideration of the existing warning system of civil protection with smart sirens could result in a better coverage and improved information of warning.

Mineral trioxide aggregate for apexification in non-vital teeth with open apices: A case report

Management of immature non-vital teeth poses challenge for the clinician owing to the thin root canal walls and open apices which may show apical divergence. Apexification is the technique of inducing the apical closure with a root end filling material for non-vital immature young permanent teeth. Traditionally, Calcium hydroxide was the material of choice for apexification of immature permanent teeth but introduction of MTA has shown remarkable promise as an alternative to calcium hydroxide. This report presents a case of apexification of anterior two young permanent teeth with open apices using MTA and Gutta percha followed by esthetic build up using cast metal posts and full coverage restorations.

Large-Area Full-Coverage Remote Sensing Image Collection Filtering Algorithm for Individual Demands

Remote sensing is the main technical means for urban researchers and planners to effectively observe targeted urban areas. Generally, it is difficult for only one image to cover a whole urban area and one image cannot support the demands of urban planning tasks for spatial statistical analysis of a whole city. Therefore, people often artificially find multiple images with complementary regions in an urban area on the premise of meeting the basic requirements for resolution, cloudiness, and timeliness. However, with the rapid increase of remote sensing satellites and data in recent years, time-consuming and low performance manual filter results have become more and more unacceptable. Therefore, the issue of efficiently and automatically selecting an optimal image collection from massive image data to meet individual demands of whole urban observation has become an urgent problem. To solve this problem, this paper proposes a large-area full-coverage remote sensing image collection filtering algorithm for individual demands (LFCF-ID). This algorithm achieves a new image filtering mode and solves the difficult problem of selecting a full-coverage remote sensing image collection from a vast amount of data. Additionally, this is the first study to achieve full-coverage image filtering that considers user preferences concerning spatial resolution, timeliness, and cloud percentage. The algorithm first quantitatively models demand indicators, such as cloudiness, timeliness, resolution, and coverage, and then coarsely filters the image collection according to the ranking of model scores to meet the different needs of different users for images. Then, relying on map gridding, the image collection is genetically optimized for individuals using a genetic algorithm (GA), which can quickly remove redundant images from the image collection to produce the final filtering result according to the fitness score. The proposed method is compared with manual filtering and greedy retrieval to verify its computing speed and filtering effect. The experiments show that the proposed method has great speed advantages over traditional methods and exceeds the results of manual filtering in terms of filtering effect.