Future land use change simulations for the Lepelle River Basin using Cellular Automata Markov model with Land Change Modeller-generated transition areas

Background: Land use/land cover (LULC), change is one of the major contributors to global environmental and climate variations. The ability to predict future LULC is crucial for environmental engineers, civil engineers, urban designers, and natural resource managers for planning activities. Methods: TerrSet Geospatial Monitoring and Modelling System in conjunction with ArcGIS Pro 2.8 were used to process LULC data for the region of the Lepelle River Basin (LRB) of South Africa. Driver variables such as population density, slope, elevation as well as the Euclidean distances of cities, roads, highways, railroads, parks and restricted areas, towns to the LRB in combination with LULC data were analysed using the Land Change Modeller (LCM) and Cellular-Automata Markov (CAM) model. Results: The results reveal an array of losses (-) and gains (+) for certain LULC classes in the LRB by the year 2040: natural vegetation (+8.5%), plantations (+3.5%), water bodies (-31.6%), bare ground (-8.8%), cultivated land (-29.3%), built-up areas (+10.6%) and mines (+14.4%). Conclusions: The results point to the conversion of land uses from natural to anthropogenic by 2040. These changes also highlight how the potential losses associated with resources such as water will negatively impact society and ecosystem functioning in the LRB by exacerbating water scarcity driven by climate change. This modelling study seeks to provides a decision support system for predicting future land resource utilization in the LRB and perhaps assist for planning purposes.

673 (Re-) Solving the biology of colorectal cancer onset and progression to improve treatment and prevention

BackgroundColorectal cancer (CRC) development is accompanied by the gradual accumulation of genetic alterations in epithelial cells of the colon and rectum.1 2 The paradigm of the adenoma-carcinoma sequence was originally centered around cancer cells; however, it is now clear that the tumor microenvironment plays a substantial role in cancer progression and patient outcome.3 In recent years, technologies have evolved rapidly, allowing the multiplexed quantification of gene expression while preserving spatial context.4 Furthermore, some spatial transcriptomic technologies also allow the parallel interrogation of different cell populations in the tumor microenvironment. Here, we performed digital spatial profiling on early-stage CRC samples to elucidate the biological processes that are at the basis of malignant transformation and to identify novel therapeutic targets and (immune) biomarkers.MethodsEndoscopically resected early-stage CRC samples were obtained at Leiden University Medical Center. In total, 144 areas of illumination were interrogated with GeoMx digital spatial profiling using the Cancer Transcriptome Atlas (>1,800 genes). In each of eight samples, nine regions of interest with different levels of cancer progression were selected, including normal epithelium, transition areas, low-, and high-grade dysplasia, and invasive carcinoma (figure 1A). We segmented each region based on cytokeratin and vimentin protein expression (figure 1B). Immunohistochemical detection was performed on these samples and 26 additional samples to validate targets associated with disease progression.ResultsDigital spatial profiling allowed us to dissect transcriptional alterations in epithelial and stromal fractions between different regions from healthy tissue, different degrees of dysplasia, and cancer. Gene expression data revealed a clear separation of profiled areas by histologic category. Interestingly, gene expression features in the stromal compartment provided a better data-driven separation of histologic categories than the epithelial fraction (figure 1C). Substantial changes in immune-related pathways were identified, including differential expression of specific immunomodulators. We validated the expression of several candidate biomarkers/targets that demonstrated consistent alterations from normal tissue to cancer by immunohistochemistry. Several proteins were identified that could clearly discriminate benign from malignant tissue.ConclusionsWe here demonstrated the unique biological insights that are provided by spatial examination of early-stage CRC by digital spatial profiling. We identified specific genes that were altered during CRC tumorigenesis, in epithelial and stromal/immune fractions. Furthermore, our results indicate an essential role for innate immunity in colorectal cancer onset and progression. The genes identified by this approach could potentially serve as novel biomarkers and targets for early interception or prevention of CRC development.AcknowledgementsThis work was supported by the European Research Council (ERC) Starting grant awarded to Dr. Noel F. de Miranda and the Stichting Management Apothekers en de Gezondheidszorg (STIMAG) Research grant awarded to Jessica Roelands.Trial RegistrationN/AReferencesFearon ER, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell 1990;61(5):759–767. doi: 10.1016/0092-8674(90)90186-I.Nowell PC. The clonal evolution of tumor cell populations. Science 1976;194(4260):23–28. doi: 10.1126/science.959840.Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011;144(5):646–674. doi: 10.1016/j.cell.2011.02.013.Merritt CR, et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat Biotechnol 2020;38(5):586–599. doi: 10.1038/s41587-020-0472-9.Ethics ApprovalThis study was approved by the METC Leiden-Den Haag-Delft (protocol B20.039). Patient samples were anonymised and handled according to the medical ethical guidelines described in the Code of Conduct for Proper Secondary Use of Human Tissue of the Dutch Federation of Biomedical Scientific Societies.Abstract 673 Figure 1Transcriptional alterations in early-stage colorectal cancer. Digital spatial profiling defines transcriptional alterations in early-stage colorectal cancer. (A) Schematic representation of an early-stage CRC sample containing regions with different levels of cancer progression, including normal epithelium, transition areas, low-, and high-grade dysplasia, and invasive carcinoma. (B) Segmentation based immunofluorescent labelling with antibodies directed against PanCK and Vimentin in one of the early-stage CRC samples. Artificial overlay of implemented segmentation is indicated for each ROI, visualizing Vimentin+ (pink) and PanCK+ (orange) segments. Inset: higher magnification of an individual ROI. (C) Dimension reduction of expression of all quantified genes by t-Distributed Stochastic Neighbor Embedding (tSNE). tSNE plots are annotated by segment (left), and histological region (right).

Bark Thickness and Heights of the Bark Transition Area of Scots Pine

The estimation of forest biomass is gaining interest not only for calculating harvesting volumes but also for carbon storage estimation. However, bark (and carbon) compounds are not distributed equally along the stem. Particularly when looking at Scots pine, a radical change in the structure of the bark along the stem can be noted. At the bark transition area, the bark changes from thick and rough to thin and smooth. The aim of our study was (1) to analyze the height of the bark transition area where the bark structure changes and (2) to analyze the effect of cardinal direction on the bark thickness. Regression analyses and forward selection were performed including measured tree height, DBH, bark thickness, crown base height and upper and lower heights of the bark transition areas of 375 trees. While the cardinal direction had no effect on bark thickness, DBH was found to have a significant effect on the heights of the bark transition areas, with stand density and tree height having a minor additional effect. These variables can be used to estimate timber volume (without bark) with higher accuracy and to predict the carbon storage potential of forest biomass according to different tree compartments and compounds.

A novel tooth tip relief method for reducing micro-pitting of spur gears

Micro-pitting is a common fatigue failure mode of spur gears. To reduce it, this paper proposes a novel tooth tip relief method. Gear meshing simulation is firstly performed considering the actual contact path, showing that there are four Hertz contact stress peaks in the transition areas of the tooth flank. Equations are then developed for the novel tooth tip relief method: one focuses on the smooth transition between the involute profile and the tip relief region, the other on the smooth transition between the tip relief region and the tooth tip. The results of curvature radius and Hertz contact stress show that the proposed novel method can effectively reduce the Hertz contact stress peaks, which indicates this tip relief method could benefit for reducing the micro-pitting. Finally, both wear simulations and bench tests are conducted, verifying the effectiveness of the proposed method for reducing the micro-pitting of spur gears.

Future land use change simulations for the Lepelle River Basin using Cellular Automata Markov model with Land Change Modeller-generated transition areas

Background: Land cover/land cover (LULC) change is one of the major contributors to global environmental and climate variations. The ability to predict future LULC is crucial for environmental engineers, civil engineers, urban designers, and natural resources managers for planning activities. Methods: TerrSet Geospatial Monitoring and Modelling System and ArcGIS Pro 2.8 were used to process LULC data for the region of the Lepelle River Basin (LRB) of South Africa. Driver variables such as population density, slope, elevation as well as the Euclidean distances of cities, roads, highways, railroads, parks and restricted areas, towns to the LRB in combination with LULC data were analysed using the Land Change Modeller (LCM) and Cellular-Automata Markov (CAM) model. Results: The results reveal an array of losses (-) and gains (+) for certain LULC classes in the LRB by the year 2040: natural vegetation (+8.5%), plantations (+3.5%), water bodies (-31.6%), bare ground (-8.8%), cultivated land (-29.3%), built-up areas (+10.6%) and mines (+14.4%). Conclusions: The results point to the conversion of land uses from natural to anthropogenic by 2040. These changes also highlight how the potential losses associated with resources such as water that will negatively impact society and ecosystem functioning in the LRB by exacerbating water scarcity driven by climate change. This modelling study provides a decision support system for the establishment of sustainable land resource utilization policies in the LRB.

Xylopia maasiana (Annonaceae), a New Species from the Brazilian Amazon, and Taxonomic Notes on Xylopia nitida Dunal

Abstract— During a taxonomic and phylogenetic study of Xylopia from the Amazon River basin, South America, we examined collections from the Brazilian states of Amazonas, Mato Grosso, Pará, Rondônia, and Tocantins that resembled Xylopia nitida by some characteristics of the leaves, but differed consistently from the latter in a number of floral and fruit characters. On the basis of these specimens we describe here a new species, Xylopia maasiana. The new species is a small to medium-sized tree encountered mostly in riparian habitats across the southern Brazilian Amazon and in some transition areas between the Amazon forest and cerrado biomes in Central Brazil. In addition to the detailed description, we include a preliminary assessment of conservation status, taxonomic comments, illustrations, a distribution map of the new species, and comparison with X. nitida.

Deep Automatic Natural Image Matting

Automatic image matting (AIM) refers to estimating the soft foreground from an arbitrary natural image without any auxiliary input like trimap, which is useful for image editing. Prior methods try to learn semantic features to aid the matting process while being limited to images with salient opaque foregrounds such as humans and animals. In this paper, we investigate the difficulties when extending them to natural images with salient transparent/meticulous foregrounds or non-salient foregrounds. To address the problem, a novel end-to-end matting network is proposed, which can predict a generalized trimap for any image of the above types as a unified semantic representation. Simultaneously, the learned semantic features guide the matting network to focus on the transition areas via an attention mechanism. We also construct a test set AIM-500 that contains 500 diverse natural images covering all types along with manually labeled alpha mattes, making it feasible to benchmark the generalization ability of AIM models. Results of the experiments demonstrate that our network trained on available composite matting datasets outperforms existing methods both objectively and subjectively. The source code and dataset are available at https://github.com/JizhiziLi/AIM.

Assessing Health Resources Equipped with Hemodynamic Rooms in the Portuguese-Spanish Borderland: Cross-Border Cooperation Strategies as a Possible Solution

Portugal and Spain share one of the greatest European borderland areas. This fact has direct impacts on a large territory and consequently on the communities’ living in it. Still, even if the border areas represent an essential fraction of the territory, planning policies have not resulted in specific cooperation programs that could enable sharing general leisure and recreation assets and infrastructures and collaboration in critical domains—i.e., the case of the health sector. The present study aims to assess the territorial accessibility to the hemodynamic rooms by the potential population of the Spanish-Portuguese transition areas that may suffer an acute myocardial infarction. Contextually, this study employed a spatial interaction model based on the three-step floating catchment area method (method-3SFCA). By applying these methods, it was possible to develop a map of accessibility to health infrastructures equipped with hemodynamics rooms on both sides of the border that may answer the Spanish-Portuguese border populations’ needs. Besides, while granting valuable information for decision-makers regarding the need to develop new infrastructures to guarantee that even considering cross border cooperation, everyone gets access to a hemodynamics room within the critical intervention period.