Search Results (8)

Landscape metrics are one of the main tools for studying changes in the landscape and the ecological structure of the territory. However, the calculation of some metrics yields significantly different values depending on the configuration of the “Cell neighborhood” (CN) used. This makes the comparison of different analysis results often impossible. In fact, although the metrics are defined in the same way for all software, the choice of a CN with four cells, which includes only the elements on the same row or column, or eight cells, which also includes the cells on the diagonal, changes their value. QGIS’ LecoS plugin uses the value eight while GRASS’ r.li module uses the value four and these values are not modifiable by users. A previous study has shown how the value of the CN used for the calculation of landscape metrics is rarely explicit in scientific publications and its value cannot always be deduced from the indication of the software used. The difference in value for the same metric depends on the CN configuration and on the compactness of the patches, which can be expressed through the Aggregation Index (AI), of the investigated landscape. The scope of this paper is to explore the possibility of deriving an analytical relationship between the Aggregation Index and the variation in the values of some landscape metrics as the CN varies. The numerical experiments carried out in this research demonstrate that it is possible to estimate the differences in landscape metrics evaluated with a four and eight CN configuration using polynomials only for few metrics and only for some intervals of AI values. This analysis combines different Free and Open Source Software (FOSS) systems: GRASS GIS for the creation of test maps and R landscapemetrics package for the calculation of landscape metrics and the successive statistical analysis. Full article

Transdermal microneedle systems have received great attention due to their minimally invasive way of delivering biomolecules through the skin with reduced pain. However, designing high-strength separable microneedles, which enable easy skin penetration and easy patch detachment, is challenging. Here, we present a Parametric Rule-based Intelligent System (PRISM), which generates the design of and analyzes high-strength separable microneedles. The PRISM platform integrates parametric 3D modeling, geometry-based structural analysis, and high-resolution micro-3D printing for the creation of high-strength separable microneedles. We fabricated prototype microneedle arrays via microscale stereolithographic printing (pµSL) and demonstrated separation of microneedle tips in a skin-mimicking phantom sample. Mechanical testing showed that the suggested design achieved 2.13 ± 0.51 N axial resistance and 73.92 ± 34.77 mN shear fracture force; this surpasses that of conventional designs. Finally, an experiment using a skin-mimicking artificial phantom sample confirmed that only the PRISM-designed separable microneedles could have been inserted and separated at the target depth, whereas conventional designs failed to detach. This approach addresses the development of microneedle systems, which achieve both robust skin phantom penetration and reliable separable delivery, presenting an efficient development tool in transdermal drug delivery technology. Full article

Population growth in the city of Lubumbashi in the southeastern Democratic Republic of the Congo (DR Congo) is leading to increased energy needs, endangering the balance of the miombo woodland in the rural area referred to as the Lubumbashi charcoal production basin (LCPB). In this study, we quantified the deforestation of the miombo woodland in the LCPB via remote sensing and landscape ecology analysis tools. Thus, the analysis of Landsat images from 1990, 1998, 2008, 2015 and 2022 was supported by the random forest classifier. The results showed that the LCPB lost more than half of its miombo woodland cover between 1990 (77.90%) and 2022 (39.92%) and was converted mainly to wooded savannah (21.68%), grassland (37.26%), agriculture (2.03%) and built-up and bare soil (0.19). Consecutively, grassland became the new dominant land cover in 2022 (40%). Therefore, the deforestation rate (−1.51%) is almost six-times higher than the national average (−0.26%). However, persistent miombo woodland is characterised by a reduction, over time, in its largest patch area and the complexity of its shape. Consequently, because of anthropogenic activities, the dynamics of the landscape pattern are mainly characterised by the attrition of the miombo woodland and the creation of wooded savannah, grassland, agriculture and built-up and bare soil. Thus, it is urgent to develop a forest management plan and find alternatives to energy sources and the sedentarisation of agriculture by supporting local producers to reverse these dynamics. Full article

Reconnecting natural habitats and improving agroecosystem conditions are strategic targets set by several European policies. In order to combine both of these needs, the European Biodiversity Strategy for 2030 has triggered new investments in Green Infrastructure (GI), which actually represents a valuable tool to increase ecological connectivity across natural and semi-natural habitats. In particular, GI may benefit the Natura2000 (N2K) network (i.e., the network of protected sites under the EU Habitats and Birds Directives) by reinforcing the node/site number, extent, and distribution and by improving connections between often small and isolated habitat patches. However, there is a lack of knowledge on what the actual needs of GI deployment are for improving the current N2K network, on the distribution of these needs across Europe and on the potential role of agricultural areas in the improvement of the network functionality. Concurrently, especially in SW Europe, there is an ongoing trend toward the homogenisation and intensification of agricultural systems and the combined loss of associated landscape elements, such as natural and semi-natural Small Woody Features (SWF). Although a well-planned network of such elements could support biodiversity and landscape connectivity, thus effectively complementing the N2K network, little evidence is available on their abundance and residual distribution, especially in agricultural areas and at continental/bioregional scales. Therefore, the present work is aimed at (i) identifying different types of territorial units (NUTS3) in W Mediterranean Europe according to current N2K network features, the overall composition of the actual landscape mosaic and the potential natural heterogeneity of the environment and (ii) identifying and spatialising N2K-related GI deployment needs according to a more specific network analysis in terms of nodes (extent of the total protected area) and links (density of residual woody elements in arable land) within the different types of NUTS3. By means of this wide-scale investigation, four different types of GI deployment needs were generalised across the W Mediterranean Europe NUTS3. Overall, the need for connection restoration prevails, followed by the need for the consolidation of node and link conservation, for the creation of new protected sites and for the enlargement of existing N2K sites. Although useful for a preliminary setting, the shortcomings related to summary data at the European level were also highlighted when compared to local-scale information, with the latter being more suitable for identifying and prioritising truly effective GI conservation and restoration actions. Full article

Aerial laser scanning technology has excellent potential in landscape management and forestry. Due to its specific characteristics, the application of this type of data is the subject of intensive research, with the search for new areas of application. This work aims to identify the boundaries of forest stands, and forest patches on non-forest land. The research objectives cover the diversity of conditions in the forest landscapes of Slovakia, with its high variability of tree species composition (coniferous, mixed, deciduous stands), age, height, and stand density. A semi-automatic procedure was designed and verified (consisting of the creation of a digital terrain model, a digital surface model, and the identification of peaks and contours of tree crowns), which allows after identification of homogeneous areas of forest stands and/or forest patches (areas covered with trees species canopy) with selected parameters (height, crown size, gap size), with high accuracy. The applicability of the proposed procedure increases the use of freely available ALS data (provided by the Office of Geodesy, Cartography, and Cadastre of the Slovak Republic) and freely distributable software tools (QGIS, CloudCompare). Full article

Background: Remote diagnosis using collaborative tools have led to multilingual joint working sessions in various domains, including comprehensive health care, and resulting in more inclusive health care services. One of the main challenges is providing a real-time solution for shared documents and presentations on display to improve the efficacy of noninvasive, safe, and far-reaching collaborative models. Classic optical character recognition (OCR) solutions fail when there is a mixture of languages or dialects or in case of the participation of different technical levels and skills. Due to the risk of misunderstandings caused by mistranslations or lack of domain knowledge of the interpreters involved, the technological pipeline also needs artificial intelligence (AI)-supported improvements on the OCR side. This study examines the feasibility of machine learning-supported OCR in a multilingual environment. The novelty of our method is that it provides a solution not only for different speaking languages but also for a mixture of technological languages, using artificially created vocabulary and a custom training data generation approach. Methods: A novel hybrid language vocabulary creation method is utilized in the OCR training process in combination with convolutional recurrent neural networks (CRNNs) and a single visual model for scene text recognition within the patch-wise image tokenization framework (SVTR). Data: In the research, we used a dedicated Python-based data generator built on dedicated collaborative tool-based templates to cover and simulated the real-life variances of remote diagnosis and co-working collaborative sessions with high accuracy. The generated training datasets ranged from 66 k to 8.5 M in size. Twenty-one research results were analyzed. Instruments: Training was conducted by using tuned PaddleOCR with CRNN and SVTR modeling and a domain-specific, customized vocabulary. The Weight & Biases (WANDB) machine learning (ML) platform is used for experiment tracking, dataset versioning, and model evaluation. Based on the evaluations, the training dataset was adjusted by using a different language corpus or/and modifications applied to templates. Results: The machine learning models recognized the multilanguage/hybrid texts with high accuracy. The highest precision scores achieved are 90.25%, 91.35%, and 93.89%. Conclusions: machine learning models for special multilanguages, including languages with artificially made vocabulary, perform consistently with high accuracy. Full article

Patch-based approaches in image processing are often preferable to working with the entire image. They provide an alternative representation of the image as a set of partial local sub-images (patches) which is a vital preprocessing step in many image processing applications. In this paper, a new software tool called patchIT is presented, providing an integrated framework suitable for the systematic and automatized extraction of patches from images based on user-defined geometrical and spatial criteria. Patches can be extracted in both a sliding and random manner and can be exported either as images, MATLAB .mat files, or raw text files. The proposed tool offers further functionality, including masking operations that act as spatial filters, identifying candidate patch areas, as well as geometric transformations by applying patch value indexing. It also efficiently handles issues that arise in large-scale patch processing scenarios in terms of memory and time requirements. In addition, a use case in cartographic research is presented that utilizes patchIT for map evaluation purposes based on a visual heterogeneity indicator. The tool supports all common image file formats and efficiently processes bitonal, grayscale, color, and multispectral images. PatchIT is freely available to the scientific community under the third version of GNU General Public License (GPL v3) on the GitHub platform. Full article

Habitat loss and fragmentation are considered some the main threats to biodiversity. Original forests have suffered an accentuated fragmentation and agricultural homogenization, leaving only some areas of natural vegetation, relegated to strongly anthropized disconnected patches (island forests, IFs) in a hostile matrix. These patches of original vegetation could be the key for the design and management of ecological corridors to promote species migration, an essential strategy for meeting the consequences of Global Change. This study proposes a comparative analysis of the fragmentation and connectivity of IFs of Quercus in two typically Mediterranean areas of predominantly agricultural use: the Guadalquivir valley (Spain) and the Apulia region (Italy). A retrospective comparison is also carried out in the Guadalquivir valley. The aim is to develop an objective new methodology to locate the patches of most interest using quantitative and qualitative data. Reference cartography of current island forests of Quercus species was developed from several digital sources and validated with orthoimages and field observations. Fragmentation analysis was based on graph structures using the software Conefor 2.6, a reliable tool for assessment of the role of patches in the landscape. Area and distance were used as node and connector values. Dispersion distance was established as 500 m, based on the maximum dispersion of acorns. Results indicate that the Guadalquivir valley has suffered an intensive fragmentation in recent decades. Both the Guadalquivir and Apulia regions host some IFs with the relevant potential to contribute as core habitats in the creation of connections to other natural protected sites. Many residual IFs in the landscape could contribute as stepping stones in the design and management of ecological corridors. Our methodology highlights the value of IFs to develop assessment strategies using homogenized available digital cartography and common criteria for the dispersion distances in graph theory analysis. The application of this new methodology could help in the management of protected sites using highly fragmented areas to allow the species movement through inhospitable landscapes in a unique opportunity to connect the different protected areas. Full article