Landscape Function Research Articles

Testing the waters: founding team composition and search heuristics in academic entrepreneurial ventures

Abstract Entrepreneurial action often stems from individual judgment about the value potential of market opportunities. Where entrepreneurs direct their search for and evaluate profitable opportunities has long received scholarly consideration. Attention has been increasingly directed toward how search is conducted, with a distinction between “cognitive” search, where actors are driven by a prior belief about the linkage between actions and outcomes (i.e., “learning-before-doing”) and “experiential search,” in which the solution must be realized through experimentation, trial-by-error, or “learning-by-doing.” We examine founders’ experiential search for market applications in uncertain technological environments. In doing so, we seek to uncover how founder background, experience, and depth of knowledge affect the firm’s degree of experiential search. We examine a sample of technology-oriented start-ups founded by researchers from six major US research universities to investigate the role of experiential search in university technology commercialization. In our context of academic entrepreneurship, we find that founding teams that draw from multiple disciplinary perspectives in selecting a market application to pursue exhibit a broader cognitive map of the technological landscape and thus expend more effort in the experiential search process than do teams with less varied backgrounds. Conversely, teams that include individuals with prior commercial experience conduct less experiential search, although this evidence is less strong. The inclusion of students appears to lead to greater experiential search by the founding team. Our findings add new understanding to the application of search heuristics by entrepreneurial firms in technology commercialization.

Frost damage measured by electrolyte leakage in subarctic bryophytes increases with climate warming

Abstract Observed climate change in northern high latitudes is strongest in winter, but still relatively little is known about the effects of winter climate change on tundra ecosystems. Ongoing changes in winter climate and snow cover will change the intensity, duration and frequency of frost events. Bryophytes form a major component of northern ecosystems but their responses to winter climate changes are largely unknown. Here, we studied how changes in overall winter climate and snow regime affect frost damage in three common bryophyte taxa that differ in desiccation tolerance in a subarctic tundra ecosystem. We used a snow manipulation experiment where bryophyte cores were transplanted from just above the tree line to similar elevation (i.e. current cold climate) and lower elevation (i.e. near‐future warmer climate scenario) in Abisko, Sweden. Here, we measured frost damage in shoots of Ptilidium ciliare, Hylocomium splendens and Sphagnum fuscum with the relative electrolyte leakage (REL) method, during late winter and spring in two consecutive years. We hypothesized that frost damage would be lower in a milder climate (low site) and higher under reduced snow cover and that taxa from moister habitats with assumed low desiccation tolerance would be more sensitive to lower temperature and thinner snow cover than those from drier and more exposed habitats. Contrary to our expectations, frost damage was highest at low elevation, while the effect of snow treatment differed across sites and taxa. At the high site, frost damage was reduced under snow addition in the taxon with the assumed lowest desiccation tolerance, S. fuscum. Surprisingly, frost damage increased with mean temperature in the bryophyte core of the preceding 14 days leading up to REL measurements and decreased with higher frost degree sums, that is, was highest in the milder climate at the low site. Synthesis Our results imply that climate warming in late winter and spring increases frost damage in bryophytes. Given the high abundance of bryophytes in tundra ecosystems, higher frost damage could alter the appearance and functioning of the tundra landscape, although the short and long‐term effects on bryophyte fitness remain to be studied.

Geographies of landscape aesthetics: mapping landscape terminology in digitised historical travel accounts of Loch Lomond and the Trossachs

ABSTRACT This study spatially analyses aesthetic terms in historical travel accounts of the landscapes of Loch Lomond and the Trossachs from the eighteenth to the twentieth century. We applied a hybrid approach, combining qualitative methods of textual analysis with quantitative techniques of a Geographical Information System (GIS), to a corpus of 38 digitised works featuring a range of historic guidebooks and travelogues. To identify relationships between place names, landscape features and the aesthetic terms beautiful, magnificent, picturesque, romantic and sublime, we first analysed how these terms occurred together in the text. We also used digital terrain model data in GIS to explore relationships between the aesthetic terms and the elevation of place names and landscape features. The results provide evidence that the aesthetic terms magnificent and sublime were applied to describe places and landforms at higher elevations, whilst beautiful, picturesque and romantic were applied to lower-lying regions of the Loch Lomond and the Trossachs landscapes. Our findings illustrate how the cartographic capabilities of GIS, combined with text analysis, can shed light on how landscapes were historically represented in travel literature.

Topological Network Analysis of Beta‐Amyloid and Tau in Alzheimer’s Disease Using PET Imaging Data

AbstractBackgroundAlzheimer’s disease (AD) is characterized by the presence of beta‐amyloid (Aβ) and tau in the brain. Understanding the interplay between these proteins and their spatial distribution may provide insights into disease progression. This study aims to investigate the topological features of Aβ and tau networks in AD, mild cognitive impairment (MCI), and normal cognition (NC) groups using PET images from the ADNI dataset.MethodPartial correlation matrices between the standardized uptake value ratio of 68 regions of interest (ROI’s) were used to generate networks for the AD, MCI, and NC groups, with nodes representing ROI’s and edges representing correlation coefficients. Topological features, including H0 features (connected components), H1 features (loops), and landscape functions of H1 features, were calculated for each sample’s persistent homology. For each group, 100 bootstrapping samples were used to generate the 95% confidence intervals for landscape functions. The connected components were further studied by representing the samples as hierarchical tree structures. In the tree space, the first few generated connections, representing the most consistent pairs of regions positive for Aβ and tau, were compared across groups. Clustering performances were compared using Wasserstein distance of H0 features, Wasserstein distance of H1 features, landscape function distance, and geodesic distance in tree space respectively.ResultThe geodesic distance in tree space showed the best clustering accuracy in both Aβ and tau analyses. Compared with Aβ, H1 features and the corresponding landscape functions performed better for tau. Unique connections in AD and MCI groups were identified, with AD showing more unique connections than MCI compared to NC samples. Dominant unique connections in the AD group included left‐right isthmus cingulate and left fusiform‐left inferior temporal for Aβ, and left‐right paracentral and left cuneus‐left pericalcarine for tau. These connections indicate region pairs with related concentrations of Aβ and tau in AD.ConclusionTopological network analysis can reveal complex underlying structures in PET images and identify consistent patterns in ROI’s associated with Aβ and tau localization. Tau aggregation exhibits more complex behavior than Aβ and is more strongly associated with AD. The identified unique connections in the AD group may serve as potential biomarkers for disease progression.

Landscape research: from paradigm through GIS technology to monitoring (on the example of the territory of the Slobozhansky National Nature Park)

For 10 years, a group of specialists from the department of physical geography and cartography has been exploring the territories of national parks consistently using information technology tools, improving their use in combination with ground test landscape surveys. This article reflects the experience of such scientific and applied development in relation to the territory of Slobozhansky National Nature Park. The purpose of this development is to improve the existing technologies of complex interpretation of geodata for the design and monitoring of the territory in their systematic combination with the methods of online mapping and in-depth meaningful interpretation for the scientific support of the organization of the territory and the administration of the national parks. This article covers currently known and possible scientific approaches and measures that rely on scientific and applied measures used by the national parks administration in management processes. The most recent issues highlighted in this article compared to the previous published works of the authors are the formulation of the trinity paradigm of the process of creating a landscape model of the territory. A set of individual tasks is defined, the consistent implementation of which ensures the achievement of the goal: selection of appropriate types, scales and optical ranges of remote sensing, taking into account the landscape conditions inherent in the location of the territory of the national park; development, on these grounds, of the technology of thematic landscape mapping, geoecological assessment and control of results on test areas of the terrain; peculiarities of drawing legends of applied landscape maps using GIS technologies; making corrections and additions to the existing defining documents of projects of the national park organization and developing recommendations for their improvement; design of the monitoring system of Slobozhansky National Nature Park. In the paradigm of applied landscape research, the national park should be designed based on the trinity of remote sensing and human intelligence: a) the technical level of providing remote sensing; b) taking into account the ambiguity of the optical image of the area depending on the purpose of geodata interpretation; c) tasks that are also solved ambiguously: the selection of certain ranges and scales of soundings, the selection of test areas and even the compilation of legends of a large-scale landscape map. The specified ambiguity is manifested in the variability of constructions and creates the subjectivity of applied landscape research. Methodological basis. The system-structural approach is manifested in the identification and identification of those spatial connections between visually significant and hidden from direct observation properties (mainly water-heat balance indicators) of the landscape, which change in an ambiguous dependence on regional background indicators, therefore must be taken into account in design and monitoring. Scientific results. In addition to theoretical generalizations, the article briefly presents the implementation of the highlighted approach in the study of landscapes of the Slobozhansky National Nature Park.

Landscape-ecological carcass model of urban landscape and methods of optimize urban landscapes (on the patterns of Ganja and Mingachevir cities)

State of the problem. The article outlines the natural and anthropogenic foundations of urban landscapes and the organization and modeling of ecological carcasses. Currently, the impact of human activity in the area, on the landscapes, especially on urban landscapes, sometimes leads to the fundamental change and reconstruction of several landscape units or components, the degradation of the sensitive ecosystems of the area, and the creation of completely anthropogenic complexes. Object learning. The main object learning is as follows; study of the differentiation characteristics of the factors influencing the formation of modern geosystems (relief, climate, hydrological and hydrogeological conditions, etc.), researching eco-geographical problems caused by anthropogenic changes, drawing up a map with appropriate content on a large scale, structural and functional characteristics of modern natural geosystems spreading in the research area, exposure to severe anthropogenic influences, study of ecological problems, studying the structural-functional aspects, levels of anthropogenic loading and assimilation, as well as the ecological condition of the modern natural geosystems spreading in the research area, complex study of optimization and large-scale ecological stability, drawing up of ecological potential assessment maps of landscapes. The purpose of this study is the landscape ecological formation of urban landscapes in the Republic of Azerbaijan, the optimization of urban landscapes, the analysis and generalization of urban development processes at the level of urban creation and living environment, and the determination of the main regularities of the formation of this environment, taking into account innovation and traditional processes. Methodology. Ecological analyses were carried out on relevant urban landscapes, and four environmental hazard zones were identified in Ganja, and three in Mingachevir (1: 20000) scale ecological risk maps were drawn up. In the end, the principles of the organization of "ecosystems" based on the optimization of both urban landscapes were analyzed. Research results. The degree of anthropogenic disturbance of the territory was determined, and a map-scheme of the ecogeographic assessment of landscape complexes was drawn up. The study of anthropogenic changes in natural landscapes and the evaluation of the anthropogenic impact in percentage according to digital electronic map fragments was carried out. In the ArcGIS program, the inclination and exposure of slopes in the area, the hypsometry of the relief in the area, the density of roads, the ecogeographical condition of modern urban landscapes, risk zones, and optimization of urban landscapes, etc. maps have been drawn up. The scientific novelty of the research. The importance and functional role of the city as a complex living environment for the country's population is defined. In the process of city planning in the Republic of Azerbaijan, the face of the city, the composition system of urban architecture, innovations, and traditional features are determined. The main city-forming function and role of the river were determined in the studied cities. And the linear features of the development of the cities, and the differences in formation were determined and analyzed. Accordingly, each of the cities has its own unique development models. Environmental problems of cities were investigated and environmental risk and optimization maps were drawn up.

Mapping landscape evolution in 3D: Climate change, natural hazard and human settlements across the 1618 Piuro landslide in the Italian Central Alps

AbstractNatural and anthropogenic mountain landscapes coevolve responding on different temporal scales to climate changes and geodynamics by a series of increments that cause the dynamic association of morphological stabilization surfaces, stratigraphic units and landforms. Understanding the incremental history of palimpsest landscapes helps to recognize and forecast the effects of climate change on the sensitive mountain environments, contributes to archaeological and historical reconstruction and supports management strategies for natural risks prevention and mitigation. The Italian Bregaglia Valley provides an excellent site to unravel the recent/historical increments of evolution of landforms and human settlement, permitting to map the paleo‐digital terrain models (DTMs) corresponding to the relevant landscape turning points. After the last de‐glaciation, two large‐scale landslides reshaped the valley floor, both predisposed by deep‐seated gravitational slope deformations and one surely triggered by intense rainfalls. The most recent and impacting event buried in 1618 the rich border town of Piuro, the ancient one occurred in the same area at least 1.5 ka before. Combining stratigraphic, geomorphological, topographic, archaeological and historical data, we drew the paleo‐DTMs of the pre‐ and post‐1618 settings of Piuro, sketching the landscape evolution. Since two millennia, human settlements took advantage of the decadal to secular most stable surfaces, represented by the inactive lobes of debris‐flow fans, the highest trunk river terraces and the top of humps formed by the ancient landslide body in the valley centre. Stratigraphic relationships, archaeological findings and age determinations show that both landslides diverted the trunk river and covered the existing fan lobes. On a secular timescale, fan progradation and trunk river terracing buried and reworked both the landslide bodies. The paleo‐DTMs show their original areal extent and permit to compute their volume and to sketch the setting of the buried Piuro settlements, drawing the changes of the Mera trunk river course and the chronology of activity of the lateral debris‐flow fan lobes.

Measuring the Multiple Functions and Tradeoffs among Streets: A New Framework Using the Deep Learning Method

With the sustainable and coordinated development of cities, the formulation of urban street policies requires multiangle analysis. In regard to the existing street research, a large number of studies have focused on specific landscapes or accessibility of streets, and there is a lack of research on the multiple functions of streets. Recent advances in sensor technology and digitization have produced a wealth of data and methods. Thus, we may comprehensively understand streets in a less labor-intensive way, not just single street functions. This paper defines an index system of the multiple functions of urban streets and proposes a framework for multifunctional street measurement. Via the application of deep learning to Baidu Street View (BSV) imagery, we generate three functions, namely, landscape, traffic, and economic functions. The results indicate that street facilities and features are suitably identified. According to the multifunctional perspective, this paper further classifies urban streets into multifunctional categories and provides targeted policy recommendations for urban street planning. There exist correlations among the various street functions, and the correlation between the street landscape and economic functions is highly significant. This framework can be widely applied in other countries and cities to better understand street differences in various cities.

Dense orchard landscape mapping based on image merging with skeleton prediction

To address the difficulty of individual vine-plant segmentation in large orchards, this study proposes a segmentation model for individual canopies that combines the characteristics of tree deciduousness and natural growth patterns. This enables the landscape mapping of orchards under intensive planting conditions. In this study, winter and summer unmanned aerial vehicle (UAV) remote-sensing images of kiwifruit orchards were used for canopy segmentation. It involved: 1) target location identification of tree trunks in winter images and alignment of winter and summer image information; 2) semantic segmentation of branches in winter images; 3) screening of individual skeletons and prediction of branch growth; 4) removal of non-canopy parts of summer images using digital image processing to obtain canopy leaf segmentation results; and 5) segmentation of the extent of the individual plant canopies based on the predicted results of the individual plants. The branch precision rate for the final kiwifruit canopy at the plant level was 99.25% and the recall rate was 95.96%. The average recall rate of the canopy precision segmentation was 82.79%, the accuracy rate of which was 73.31%. This model does not involve plant height information and can implement instance segmentation of deciduous trees of the same species, with similar characteristics, and dense planting. The proposed solution addresses the problem of large-scale standardized planting of the same species, especially those that do not have obvious height or color differences and cannot be segmented using a digital elevation model.

Peaks and gaps in eco-social policy and sustainable welfare: A systematic literature map of the research landscape

The social impacts of the climate crisis and the need for societal transformation to achieve climate goals require integrated research and design of environmental policy and social security. The article analyses the current state of research on eco-social policy and sustainable welfare. Based on a systematic literature review covering more than 1000 publications, the article identifies 20 research topics. Strong research progress has been made on social compensation for climate policies; economic inequality in the climate crisis; energy use patterns in housing, mobility, and nutrition; political conditions for eco-social policy; and varieties in eco-social country regimes. Future research activities should focus on the five bottlenecks detected in the emerging research topics: the reduction in the environmental burden through a change in demand structures by the welfare state; growth-independence of social security; support for socio-ecological transformations by altered financing of welfare states; eco-social insurance and institutions; and ecological mainstreaming in the domains of social security. Discussing the explanatory factors for past research activity and sketching the elements of sustainable welfare states, the article concludes with the historical importance of including ecological concerns in social security.

A bibliometric and scientific mapping of the research landscape and trending topics in building integrated photovoltaic systems

The present article aims to identify emerging trends in the building integrated photovoltaic (BIPV) field through an analysis of the most prominent articles, authors, keywords, sources, and countries through bibliometric analysis of the same. To fulfil the study's aims, 1552 articles published in Scopus databases between 1985 and 2022 are reviewed and analysed using the Bibliometrix - R software, VOSviewer, and SciMAT. Since 2016, the results indicated that the number of publications per year in this domain has consistently increased. The China, UK, and USA were the most prominent contributors to this research area in terms of overall publications and citations. In addition, the results highlight the most significant sections of the article from the perspective of the highest citations, publications, keywords, and authors. Through co-citation analysis and keyword co-occurrence network, the major knowledge base and the most prominent hot themes of BIPV study field were identified. The minimum number of co-occurrences of keywords is set to the value of five which results in 166 threshold keywords out of these 146 keywords are selected and divided into 9 clusters. Cluster-1 (Red) contains a total of 32 keywords. BIPV has the highest connection of 63 links and 67 documents followed by phase change material (52 links and 45 documents). The results pointed to a potential gap in the literature regarding the use of artificial neural networks in BIPV systems.

Mapping and Modelling of Urban Landscape of Osogbo Metropolis, Osun State Nigeria, Using Artificial Neural Network

Mapping and Modelling of Urban Landscape of Osogbo Metropolis, Osun State Nigeria, Using Artificial Neural Network

Producing context specific land cover and land use maps of human-modified tropical forest landscapes for infectious disease applications

Satellite-based land cover mapping plays an important role in understanding changes in ecosystems and biodiversity. There are global land cover products available, however for region specific studies of drivers of infectious disease patterns, these can lack the spatial and thematic detail or accuracy required to capture key ecological processes. To overcome this, we produced our own Landsat derived 30 m maps for three districts in India's Western Ghats (Wayanad, Shivamogga and Sindhudurg). The maps locate natural vegetation types, plantation types, agricultural areas, water bodies and settlements in the landscape, all relevant to functional resource use of species involved in infectious disease dynamics. The maps represent the mode of 50 classification iterations and include a spatial measure of class stability derived from these iterations. Overall accuracies for Wayanad, Shivamogga and Sindhudurg are 94.7 % (SE 1.2 %), 88.9 % (SE 1.2 %) and 88.8 % (SE 2 %) respectively. Class classification stability was high across all three districts and the individual classes that matter for defining key interfaces between human habitation, forests, crop, and plantation cultivation, were generally well separated. A comparison with the 300 m global ESA CCI land cover map highlights lower ESA CCI class accuracies and the importance of increased spatial resolution when dealing with complex landscape mosaics. A comparison with the 30 m Global Forest Change product reveals an accurate mapping of forest loss and different dynamics between districts (i.e., Forests lost to Built-up versus Forests lost to Plantations), demonstrating an interesting complementarity between our maps and the % tree cover Global Forest Change product. When studying infectious disease responses to land use change in tropical forest ecosystems, we recommend using bespoke land cover/use classifications reflecting functional resource use by relevant vectors, reservoirs, and people. Alternatively, global products should be carefully validated with ground reference points representing locally relevant habitats.

Synthesis, structural study, and Na+ migration pathways simulation of the new phase Na3Al3(AsO4)4

Single crystals of the novel arsenate, Na3Al3(AsO4)4 have been isolated and their structure has been determined by X-ray diffraction experiment. Na3Al3(AsO4)4 crystallizes in the monoclinic space group C2/c with a = 19.837(1) Å; b = 6.448(3) Å; c = 10.437(6) Å, β = 91.986 (3)° and Z = 2. The structural model was confirmed by both bond valence sum (BVS), charge distribution (CHARDI) validation tools and density functional theory (DFT) method. The empirical activation energy for sodium migration channels within the crystal structure was estimated by the bond valence site energy landscape (BVSE) map method. With an energy barrier of 0.409 eV, the crystal structure features 3D networks of pathways suitable for Na+ ion migration.

The moral landscape of biological conservation: Understanding conceptual and normative foundations

Biological conservation practices and approaches take many forms. Conservation projects do not only differ in their aims and methods, but also concerning their conceptual and normative background assumptions and their underlying motivations and objectives. We draw on philosophical distinctions from the ethics of conservation to explain variances of different positions on conservation projects along six dimensions: (1) conservation ideals, (2) intervention intuitions, (3) the moral considerability of nonhuman beings, (4) environmental values, (5) views on nature and (6) human roles in nature. The result is a map of the moral landscape of biological conservation, on which these six dimensions are layered. This map functions as a heuristic tool to understand conceptual and normative foundations of specific conservation projects, which we will illustrate with four paradigmatic examples: the Pisavaara Strict Nature Reserve, Predator Free New Zealand, the Oostvaardersplassen Nature Reserve and the Great Green Wall Project. With this map as a heuristic tool, we aim to conceptually illuminate disagreement and clarify misunderstandings between representatives of different environmental protection strategies and to show that the same project can be supported (or criticised) on different grounds.

Reconstructing historical forest spatial patterns based on CA-AdaBoost-ANN model in northern Guangzhou, China

Influenced by natural and man-made factors—especially urbanization—regional forest landscapes and structures are in a dynamic process of constant change. It is of great significance to reconstruct the historical pattern of forest landscapes and construct maps of forest landscapes for long time series. Based on the investigation of Fengshui and carbon sequestration forests in northern Guangzhou city, this study combined with an artificial neural network (ANN) improved using the AdaBoost algorithm to create a cellular automaton (CA) to reconstruct species compositions and spatial distributions of historical forests. The model had the best effect at a 30 m spatial scale. At 30 m spatial scale, compared with the actual forest community’s spatial distribution, the overall accuracy of forest community distribution reconstructed by our retrospective model in 2000 was 89.17 %, the Lee Sallee index was 0.7972, and the landscape similarity index was 84.62 %. In 1990, the overall accuracy was 86.78 %, the Lee Sallee index was 0.7604, and the landscape similarity index was 80.84 %. This study provides an effective method for the reconstruction of forest vegetation patterns and the prediction of future scenarios.

Winnice jako forma rolnictwa miejskiego – przykład Wiednia

This article aims to present vineyards as a specific form of urban agriculture, with particular emphasis on their spatial and functional dimensions. The considerations contained in the text concern a case study – Vienna, called “the king of urban viticulture”. Based on the spatial and functional analysis of the data provided by the Austrian Wine Marketing Board, as well as field observations carried out in April 2022, the main characteristics of the spatial distribution of vineyards in the urban space, the structure of production, as well as the functions they perform are determined. The conducted research indicates the multifunctionality of viticulture and winemaking in Vienna, which is conducive to its preservation in the city space. In addition to the production function, recreational, tourist, landscape and cultural functions being an expression of the city’s long wine tradition, are also particularly important.

TMET-10. INVESTIGATING HOW GLIOBLASTOMA TUMOUR CELLS EXPLOIT THEIR METABOLIC MICROENVIRONMENT

Abstract A significant challenge in neuro-oncology is identifying the metabolic fuel sources that underpin glioblastoma malignancy. Metabolic reprogramming is a hallmark of tumorigenesis, providing malignant cells with an adaptation advantage to survive and grow under environmental stresses, including anti-cancer therapies. Incorporating single-cell RNA sequencing data from 56 glioblastoma patient biopsies, we have identified distinct subpopulations of malignant cells which diverge in their metabolic activities. These metabolic subpopulations are conserved across patient datasets but vary in abundance from patient to patient, contributing to glioblastoma heterogeneity. We are also employing spatial transcriptomics to build a map of the metabolic tumour landscape. This analysis showed that these malignant sub-populations occupy distinct spatial regions in the tumour landscape. Environmental influences like distance to blood vessels, which impact oxygen and nutrient supply, can vary significantly between regions. This suggests that as malignant cells colonise different regions of the tumour, they modify their metabolism as an adaption response. Importantly these niches vary in their compositions of native brain and immune cells, contributing to the diverse ecosystems inhabited by these malignant subpopulations. The next steps are to explore the specific metabolite dependencies of these tumour cells by mass spectrometry imaging and identify metabolite fluxes within the microenvironment that we can target therapeutically.

Analysis of Green Infrastructure Network Pattern Change in Zhengzhou Central City Based on Morphological Spatial Pattern Analysis

Green infrastructure is generally regarded as an effective way to maintain regional ecological security, and its construction method plays an essential role in its function realization. In this study, the central urban area of Zhengzhou was taken as the research area. The land use type maps of the study area were obtained through the supervised classification of TM/ETM Remote sensing image data in 2007, 2011, 2015, and 2019. The Green Infrastructure (GI) in the study area was obtained by Morphological Spatial Pattern Analysis (MSPA) based on the landscape connectivity index and landscape map theory. The landscape connectivity of the core area was classified and quantitatively evaluated. Then, the potential ecological corridors were extracted and analyzed. The GI pattern change research based on MSPA, landscape connectivity, and map theory provided a new framework for analyzing GI pattern change. Finally, the spatial structure of green infrastructure planning in Zhengzhou central city is obtained, and the optimization strategy of network structure is proposed. The research results can provide references for the planning and optimization of GI networks in the study area and have particular reference significance for the planning and construction of GI networks in other areas.

Characterization of the immune cell function landscape in head and neck squamous carcinoma to assist in prognosis prediction and immunotherapy.

The malignant characteristics of cancer depend not only on intrinsic properties of cancer cells but also on the functions of infiltrating immune cells. In this study, we aimed to investigate the functional landscape of immune cells in head and neck squamous cell carcinoma (HNSCC). We employed single-sample gene set enrichment analysis to examine the immunophenotypes of HNSCC based on 29 immune cell functions (ICFs) in TCGA and GSE65858 datasets. We analyzed the clinical features, immune microenvironment, molecular profiles, and biological processes. Additionally, we developed and validated an ICF-based risk score for personalized prognosis prediction. We confirmed the value of the ICF score in our cohort using qRT-PCR and immunohistochemistry. Molecular docking was used to predict potential compounds for immunotherapy. Three immunophenotypes (Immune-L, Immune-M, and Immune-H) were identified in 769 HNSCC samples. The characteristics of Immune-H were consistent with a "Hot" tumor, Immune-L was similar to a "Cold" tumor, and Immune-M exhibited intermediate features. The ICF risk score was associated with immune checkpoints, infiltrating immune cells, tumor mutation burden, and sensitivities to targeted/chemotherapeutic agents. Gene set variation analysis implicated the involvement of metabolic reprogramming pathways in the high-risk group. The combination of "Tumor Immune Dysfunction and Exclusion" and "Immunophenoscore" algorithms indicated that the low-risk group had a higher likelihood of benefiting from immunotherapy. Finally, we identified Eltrombopag and other compounds that may be beneficial for HNSCC immunotherapy. Our study provides a novel perspective on the tumor microenvironment of HNSCC, aiding in the understanding of HNSCC heterogeneity and the development of personalized/precision medicine.