Landscape Model Research Articles

Unveiling pathogenesis and therapeutic targets of metastatic breast cancer through sparse modeling of genomic landscape

Breast cancer is one of the most lethal and frequently detected diseases in the world. Its heterogeneity poses significant challenges for precision therapy. To better decipher patterns in the human genome given its heterogenous nature and have them converge into common functionalities, mutational signatures are introduced to define the types of DNA damage, repair, and replicative mechanisms shaping the genomic landscape of each cancer patient. In this study, we developed a deep learning (DL) model, based on pruning technology to improve model generalization through deep sparsity. We applied it to patient-level whole genome sequencing (WGS) samples, and identified statistically significant mutational signatures associated with metastatic progression using Shapley additive explanations (SHAP). We also employed gene cumulative contribution abundance analysis to link the mutational signatures with relevant genes uncovering the shared molecular mechanisms behind tumorigenesis and metastasis of each patient which can potentially lead to novel therapeutic target identification. Our study illustrates that our approach is an effective tool for discovering clinically meaningful mutational signatures in metastatic breast cancer (MBC) and relating them directly to relevant biological functions and gene targets. These findings could facilitate the development of novel therapeutic strategies and improve the clinical outcomes for individual patients.

An integrated investigation combining network pharmacology and computer simulation dissects the potential mechanism of anti-obesity of Monascus pigments (MPs)

Monascus pigments (MPs), the secondary metabolites of Monascus-fermented foods, have been widely studied for their anti-obesity effects. However, the specific targets and potential mechanism of MPs for anti-obesity remain unclear. In this study, we applied network pharmacology and computer simulation to investigate the anti-obesity potential and action mechanism of MPs. Based on public databases, 117 potential therapeutic obesity targets of MPs were predicted. Five key targets (STAT3, ESR1, BCL2, PPARG, and MMP9) were obtained by protein-protein interaction (PPI) analysis and microarray data validation. The enrichment results showed that MPs exerted anti-obesity effects through multiple targets and multiple pathways, especially insulin resistance. Molecular docking demonstrated the binding of five key targets to MPs ligands through hydrophobic interactions and hydrogen bonding. Molecular dynamics simulation and binding free energy analysis revealed a higher stability in the binding of ESR1, BCL2, and PPARG targets with MPs ligands. In addition, free energy landscape (FEL) and independent gradient model (IGM) analysis showed that van der Waals forces were also the main driving force in stabilizing the binding of key targets and MPs ligands. This study systematically illustrated the potential anti-obesity mechanism of MPs and established the foundation for the development and application of MPs as anti-obesity functional additives.

Eco-Revelatory: The Missing Link in the Development of Adaptive Landscape to Industrial Heritage Sites

ABSTRACT Adaptive reuse of industrial heritage paves the way for revitalization, new use, and achievement of dynamism and sustainability. The aim of the present study is to access the missing link in developing a landscape model adaptable to industrial heritage sites. The present study was conducted within a qualitative approach framework and used the grounded theory method. Qualitative data analysis of the research was performed by MAXQDA2020 software, and based on the results, a paradigm model of adaptive industrial heritage landscape was explained. The research results include causal conditions (physical), core category (environmental), contextual conditions (historical, infrastructural), intervening conditions (economic, technology), strategies (policies and laws), and consequences (social, cultural). According to the identified components of the adaptability of industrial heritage to the landscape, the concept of Eco-Revelatory was extracted. It also states that the missing link is the adaptability of landscape and Eco-Revelatory industrial heritage, the use of which leads to the dynamism and stability of industrial heritage.

Exploring the Limits of Fe-Rich Chemistries in Na-Based CaFe2O4-Type Postspinel Oxides.

Structural trends, physical properties, and electrochemical performances of the NaFexRu2-xO4 system have been investigated. Synthesis attempts using both conventional solid-state routes and high-pressure methods were explored for the compositional range 1.0 ≤ x ≤ 1.67. Based on Rietveld refinements against powder X-ray diffraction data, analyses of 57Fe Mössbauer spectroscopy data, and elemental analysis by electron microprobe, the existence of a confined compositional solid solution (1 ≤ x ≤ 1.3) adopting the CaFe2O4-type postspinel structure is demonstrated. This is contrasted with the NaFexTi2-xO4 system, for which no evidence of a solid solution is observed. However, for all explored synthetic routes of NaFexRu2-xO4 compositions, a trivalent iron oxidation state is maintained. Structural analysis and qualitative bond valence energy landscape models reveal that the progressive integration of iron into the postspinel framework results in narrowed sodium ion diffusion channels, restricting electrochemical deintercalation of sodium. Consequently, the CaFe2O4-type iron-rich compounds explored in this study demonstrate limited potential as positive electrode materials for sodium batteries. It is expected that this fundamental insight will help guide the exploration of alternative NaM2O4-based positive electrode materials with similar structure types.

The impact of land use and cover changes on river flows in Wundanyi Catchment of Taita Hills, Kenya (1970–2030)

<p>Taita Hills are one of the most important biodiversity hotspots of Kenya but are experiencing a high rate of deforestation due to the to the conversion of its original forestland to agriculture and settlement during the last century. These landscape dynamics, coupled with rainfall fluctuations in these critical ecosystems, may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of land use/cover change (LUCC) in the Wundanyi catchment from 1970 to 2030 and predict their specific and combined effects on surface runoff and stream flow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modeling using both historical and primary data from the Wundanyi catchment and Landsat TM and ETM+ imagery of Taita Hills for 1990, 2000, and 2010. Results show highly variable mean seasonal and annual values of discharge in Wundanyi catchment, probably attributed to environmental changes affecting Taita Hills in general and Wundanyi catchment in particular. Compared to 1990, major land use/cover changes in 2010 were featured by the expansion of built-up area (250%), plantation forest (23.7%), broadleaved forest (17.4%), and thicket (15.9%). It was also notable the decrease in woodland (−30.3%), cropland (−21.6%), and shrubland (−0.8%). Dynamic spatial trends by the year 2030 will be evidenced by increased thicket by 0.41% per annum (<em>R</em><sup>2</sup> = 81.6%) and by decreased plantation forests (−0.13%; <em>R</em><sup>2</sup> = 91.3%), woodland (−0.10%; <em>R</em><sup>2</sup> = 77.6%), shrubland (−0.11%; <em>R</em><sup>2</sup> = 85.2%), broadleaved forests (−0.03%; <em>R</em><sup>2</sup> = 56.6%) and cropland (−0.09%; <em>R</em><sup>2</sup> of 84.4). These changes will shape the catchment landscape and influence its hydrology, unless the existing forest and agricultural policy interventions are enforced. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in the Wundanyi catchment.</p>

Remote sensing of vegetation and soil moisture content in Atlantic humid mountains with Sentinel-1 and 2 satellite sensor data

The satellite monitoring of vegetation moisture content (VMC) and soil moisture content (SMC) in Southern European Atlantic mountains remains poorly understood but is a fundamental tool to better manage landscape moisture dynamics under climate change. In the Atlantic humid mountains of Portugal, we investigated an empirical model incorporating satellite (Sentinel-1 radar, S1; Sentinel-2 optical, S2) and ancillary predictors (topography and vegetation cover type) to monitor VMC (%) and SMC (%). Predictors derived from the S1 (VV, HH and VV/HH) and S2 (NDVI and NDMI) are compared to field measurements of VMC (n = 48) and SMC (n = 48) obtained during the early, mid and end of summer. Linear regression modelling was applied to uncover the feasibility of a landscape model for VMC and SMC, the role of vegetation type models (i.e. native forest, grasslands and shrubland) to enhance predictive capacity and the seasonal variation in the relationships between satellite predictors and VMC and SMC. Results revealed a significant but weak relationship between VMC and predictors at landscape level (R2 = 0.30, RMSEcv = 69.9 %) with S2_NDMI and vegetation cover type being the only significant predictors. The relationship improves in vegetation type models for grasslands (R2 = 0.35, RMSEcv = 95.0 % with S2_NDVI) and shrublands conditions (R2 = 0.52, RMSEcv = 45.3 %). A model incorporating S2_NDVI and S1_VV explained 52 % of the variation in VMC in shrublands. The relationship between SMC and satellite predictors at the landscape level was also weak, with only the S2_NDMI and vegetation cover type exhibiting a significant relationship (R2 = 0.28, RMSEcv = 18.9 %). Vegetation type models found significant associations with SMC only in shrublands (R2 = 0.31, RMSEcv = 9.03 %) based on the S2_NDMI and S1_VV/VH ratio. The seasonal analysis revealed however that predictors associated to VMC and SMC may vary over the summer. The relationships with VMC were stronger in the early summer (R2 = 0.31, RMSEcv = 90.1 %; based on S2_NDMI) and mid (R2 = 0.37, RMSEcv = 70.8 %; based on S2_NDVI), butnon-significant in the end of summer. Similar pattern was found for SMC, where the link with predictors decreases from the early summer (R2 = 0.33, RMSEcv = 16.0 %; based on S1_VH) and mid summer (R2 = 0.30, RMSEcv = 17.8 %; based on S2_NDMI) to the end of summer (non-significant). Overall, the hypothesis of a universal landscape model for VMC and SMC was not fully supported. Vegetation type models showed promise, particularly for VMC in shrubland conditions. Sentinel optical and radar data were the most significant predictors in all models, despite the inclusion of ancillary predictors. S2_NDVI, S2_NDMI, S1_VV and S1_VV/VH ratio were the most relevant predictors for VMC and, to a lesser extent, SMC. Future research should quantify misregistration effects using plot vs. moving window values for the satellite predictors, consider meteorological control factors, and enhance sampling to overcome a main limitation of our study, small sample size.

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli.

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations.

A novel transformer‐based graph generation model for vectorized road design

AbstractRoad network design, as an important part of landscape modeling, shows a great significance in automatic driving, video game development, and disaster simulation. To date, this task remains labor‐intensive, tedious and time‐consuming. Many improved techniques have been proposed during the last two decades. Nevertheless, most of the state‐of‐the‐art methods still encounter problems of intuitiveness, usefulness and/or interactivity. As a rapid deviation from the conventional road design, this paper advocates an improved road modeling framework for automatic and interactive road production driven by geographical maps (including elevation, water, vegetation maps). Our method integrates the capability of flexible image generation models with powerful transformer architecture to afford a vectorized road network. We firstly construct a dataset that includes road graphs, density map and their corresponding geographical maps. Secondly, we develop a density map generation network based on image translation model with an attention mechanism to predict a road density map. The usage of density map facilitates faster convergence and better performance, which also serves as the input for road graph generation. Thirdly, we employ the transformer architecture to evolve density maps to road graphs. Our comprehensive experimental results have verified the efficiency, robustness and applicability of our newly‐proposed framework for road design.

High-Level Process Modeling—An Experimental Investigation of the Cognitive Effectiveness of Process Landscape Diagrams

Unlike business process diagrams, where ISO/IEC 19510 (BPMN 2.0) prevails, high-level process landscape diagrams are being designed using a variety of standard- or semi-standard-based notations. Consequently, landscape diagrams differ among organizations, domains, and modeling tools. As (process landscape) diagrams need to be understandable in order to communicate effectively and thus form the basis for valid business decisions, this study aims to empirically validate the cognitive effectiveness of common landscape designs, including those BPMN-L-based, which represent a standardized extension of BPMN 2.0 specifically aimed at landscape modeling. Empirical research with 298 participants was conducted in which cognitive effectiveness was investigated by observing the speed, ease, accuracy, and efficiency of answering questions related to semantically equivalent process landscape diagrams modeled in three different notations: value chains, ArchiMate, and BPMN-L. The results demonstrate that BPMN-L-based diagrams performed better than value chain- and ArchiMate-based diagrams concerning speed, accuracy, and efficiency; however, subjects perceived BPMN-L-based diagrams as being less easy to use when compared to their counterparts. The results indicate that differences in cognitive effectiveness measures may result from the design principles of the underlying notations, specifically the complexity of the visual vocabulary and semiotic clarity, which states that modeling concepts should have unique visualizations.

Landscape modelling of the Yalong River catchment during the uplift of Southeast Tibet

Southeast Tibet is characterized by low-relief surfaces at high-elevation, showing very little exhumation during the India–Asia collision, as well as deeply incised rivers valleys. Understanding how these low-relief surfaces adjacent to the plateau's edge survived from regressive fluvial erosion is still an enigma, which is key to understanding the formation of the plateau. In the Three Rivers Region around the Eastern Himalayan Syntaxis, the squeezing of the Salween, Mekong and Yangtze rivers’ drainage basins in their middlestream, where numerous thrusts parallel to the river channels are observed, has been invoked as the key factor driving the river evolution. More to the east, in the Great Bends Region, no such squeezing of the drainage basins has been observed; the Yalong and Yangtze rivers flow perpendicularly across northeast-trending thrust belts, generating huge (>100 km) river course bends with steep channel slopes. These faults have significantly contributed to construct the high plateau margin, including the Yalong Thrust Belt (YTB), active during the Eocene (∼35–25 Ma) and reactivated in the Miocene (15–12 Ma). By applying state-of-the-art landscape modelling (FastScape) to the Yalong River catchment, with simplified rock uplift scenario deduced from fault activities, we show that strong monsoonal precipitation on the plateau (∼1 m/yr), even during only a short period such as the Mid–Miocene Climatic Optimum (17–14 Ma), produces wide rivers and destroys the plateau edge. In contrast, modelling the orographic effect with weak net precipitation (∼0.2 m/yr) above ∼2700 or 4000 m, preserves the plateau edge and reproduces the slope of the Yalong River, but with a width larger than in nature. To reproduce both the slope and narrowness of the Yalong gorge just upstream of the YTB, a combination of a rapid Miocene rock uplift leading to a regional surface uplift, which creates a significant orographic effect and preserves interfluve low-relief surfaces close to the plateau edge, and a water inflow in upstream, which deeply incises downstream river valleys, is necessary. Such an amount of upstream water is collected from the flat and expansive headwater, inherited from the inland endorheic zone of the plateau interior, on which the hillslope processes dominate the landscape evolution.

Ecological tradeoffs lead to complex evolutionary trajectories and sustained diversity on dynamic fitness landscapes

The course and outcome of evolution are critically determined by the fitness landscape, which maps genotype to fitness. Most theory has considered static fitness landscapes or fitness landscapes that fluctuate according to abiotic environmental changes. In the presence of biotic interactions between coexisting genotypes, the fitness landscape becomes dynamic and frequency-dependent.Here, we introduce a fitness landscape model that incorporates ecological interactions between individuals in a population. In the model, fitness is determined by individuals competing for resources according to a set of traits they possess. An individual’s genotype determines the trait values through a Rough Mount Fuji fitness landscape model, allowing for tunable epistasis (i.e. non-additive gene interaction) and trait correlations (i.e. whether there are tradeoffs or synergies in the ability to use resources). Focusing on the effects of epistasis and trait correlations, we quantify the resulting eco-evolutionary dynamics under simulated Wright–Fisher dynamics (i.e. including genetic drift, mutation, and selection under the assumption of a constant population size) on the dynamics fitness landscape in comparison with a similar, static, fitness landscape model without ecological interactions.Whereas the non-ecological model ultimately leads to the maintenance of one main genotype in the population, evolution in the ecological model can lead to the long-term coexistence of several genotypes at intermediate frequencies across much of the parameter range. Including ecological interactions increases steady-state diversity whenever the trait correlations are not too strong. However, strong epistasis can hinder coexistence, and additive genotype–phenotype maps yield the highest haplotype diversity at the steady state. Interestingly, we frequently observe long-term coexistence also in the absence of induced trade-offs in the ability to consume resources.In summary, our simulation study presents a new dynamic fitness landscape model that highlights the complex eco-evolutionary consequences of a (finite) genotype–phenotype-fitness map in the presence of biotic interactions.

Developing an LPN Transition to Practice Program to Support the Changing Nursing Landscape

Background: Hospitals are adjusting and changing care delivery models by adding Licensed Practical Nurses (LPNs) back to acute care due to the RN (Registered Nurse) nursing shortage. As this landscape and care delivery model changes, it is important to ensure there are resources in place to help support nursing teams. Many organizations have programs in place to help support RN’s as they transition into practice or referred to a nurse residency program. A Pennsylvania hospital recognized the need to add an LPN transition to the practice program to support new nurses as they transition into the acute care setting. Methods: A program was created, developed, and piloted to help support new graduate LPN’s transitioning into acute care to help support and guide them. The program was piloted for 6 months with a variety of learning experiences: shadowing experiences, content experts, simulation, and mentorship. Results: The program has proven to be successful, and an avenue was created for new graduate LPNs to feel supported during their initial months in the hospital by providing them with knowledge to develop from novice to competent nurses. Conclusion: It is important for hospitals to have support for nursing professional development opportunities for LPN’s as they transition to acute care nursing models.

Unexpectedly uneven distribution of functional trade-offs explains cranial morphological diversity in carnivores.

Functional trade-offs can affect patterns of morphological and ecological evolution as well as the magnitude of morphological changes through evolutionary time. Using morpho-functional landscape modelling on the cranium of 132 carnivore species, we focused on the macroevolutionary effects of the trade-off between bite force and bite velocity. Here, we show that rates of evolution in form (morphology) are decoupled from rates of evolution in function. Further, we found theoretical morphologies optimising for velocity to be more diverse, while a much smaller phenotypic space was occupied by shapes optimising force. This pattern of differential representation of different functions in theoretical morphological space was highly correlated with patterns of actual morphological disparity. We hypothesise that many-to-one mapping of cranium shape on function may prevent the detection of direct relationships between form and function. As comparatively only few morphologies optimise bite force, species optimising this function may be less abundant because they are less likely to evolve. This, in turn, may explain why certain clades are less variable than others. Given the ubiquity of functional trade-offs in biological systems, these patterns may be general and may help to explain the unevenness of morphological and functional diversity across the tree of life.

Climate variability and river flow changes in Wundanyi sub-catchment of Taita hills, Kenya

<p>Wundanyi sub-catchment of Taita hills is experiencing a high rate of deforestation due to the conversion of all its original forestland to agriculture and settlement during the last century. The landscape dynamics coupled with rainfall fluctuations in these critical ecosystems may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of selected hydroclimatic variables in Wundanyi sub-catchment from 1970 to 2030 and their specific and combined effects on surface runoff and streamflow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modelling using both historical and primary hydroclimatic data from Wundanyi and Voi weather stations. Results show highly variable mean seasonal and annual values of temperature, rainfall, runoff and discharge in both Wundanyi and Voi weather stations. Increasing mean temperatures and rainfall were observed during the long dry season (JJAS), while decreasing seasonal discharges were observed during both the JJAS dry season and the OND short rainy season. These anomalies were pronounced in 1980–1981, 1986–1987 and 1992–1993, probably due to both global and local environmental changes affecting Taita Hills in general and Wundanyi sub-catchment in particular. The predicted effects of rainfall fluctuation were supported by declining surface runoff of 1.3% during JJAS, and an increase of 0.8% during the OND, with similar effects on river discharges. The combined effects of climate variability and Land use and cover changes (LUCC) on surface runoff were estimated to an increase of 200 mm during JJAS and 370 mm during OND, and while river discharges increased by 2.37 m<sup>3</sup>/s and 1.93 m<sup>3</sup>/s during JJAS and OND, respectively. Consequently, natural forest covers have significant control effects on surface runoff and can boost river discharges amid diverse agricultural cropping practices. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in Wundanyi sub-catchment.</p>

Statistical inference for random T-tessellations models. Application to agricultural landscape modeling

Statistical inference for random T-tessellations models. Application to agricultural landscape modeling

Genetic structure and landscape effects on gene flow in the Neotropical lizard Norops brasiliensis (Squamata: Dactyloidae)

One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard species Norops brasiliensis (Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation in N. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.

How will climate change and forest harvesting influence the habitat quality of two culturally salient species?

Boreal landscapes face increasing disturbances which can affect cultural keystone species, i.e. culturally salient species that shape in a major way the cultural identity of a people. Given their importance, the fate of such species should be assessed to be able to act to ensure their perennity. We assessed how climate change and forest harvesting will affect the habitat quality of Rhododendron groenlandicum and Vaccinium angustifolium, two cultural keystone species for many Indigenous peoples in eastern Canada. We used the forest landscape model LANDIS-II in combination with species distribution models to simulate the habitat quality of these two species on the territories of three Indigenous communities according to different climate change and forest harvesting scenarios. Climate-sensitive parameters included wildfire regimes as well as tree growth. Moderate climate change scenarios were associated with an increased proportion of R. groenlandicum and V. angustifolium in the landscape, the latter species also responding positively to severe climate change scenarios. Harvesting had a minimal effect, but slightly decreased the probability of presence of both species where it occurred. According to the modeling results, neither species is at risk under moderate climate change scenarios. However, under severe climate change, R. groenlandicum could decline as the proportion of deciduous trees would increase in the landscape. Climate change mitigation strategies, such as prescribed fires, may be necessary to limit this increase. This would prevent the decrease of R. groenlandicum, as well as contribute to preserve biodiversity and harvestable volumes.

Evolutionary accessibility of random and structured fitness landscapes

Biological evolution can be conceptualized as a search process in the space of gene sequences guided by the fitness landscape, a mapping that assigns a measure of reproductive value to each genotype. Here, we discuss probabilistic models of fitness landscapes with a focus on their evolutionary accessibility, where a path in a fitness landscape is said to be accessible if the fitness values encountered along the path increase monotonically. For uncorrelated (random) landscapes with independent and identically distributed fitness values, the probability of existence of accessible paths between genotypes at a distance linear in the sequence length L becomes nonzero at a nontrivial threshold value of the fitness difference between the initial and final genotypes, which can be explicitly computed for large classes of genotype graphs. The behaviour of uncorrelated random landscapes is contrasted with landscape models that display additional, biologically motivated structural features. In particular, landscapes defined by a tradeoff between adaptation to environmental extremes have been found to display a combinatorially large number of accessible paths to all local fitness maxima. We show that this property is characteristic of a broad class of models that satisfy a certain global constraint, and provide further examples from this class.

Beyond Classroom Walls: High School Foreign Language Learning with Linguistic Landscape Activities

In addition to its widespread use in various disciplines, LL has garnered attention from researchers in education for its role in enhancing language learning and promoting linguistic diversity. However, its systematic integration into language teaching contexts, particularly in high school settings, remains limited. This paper aims to demonstrate how LL-centered activities were designed for integration into an 11th-grade English classroom in a public high school in southeastern Turkey. Over a 12-week period with 32 students, three LL-oriented tasks—Designing a job advertisement, Creating a T-shirt design, and Crafting a ‘Wanted’ sign—all aligned with the curriculum were implemented. Following the stages outlined by the pedagogical model of Linguistic Landscapes in Second Language Teaching and Learning (LLinL2TL), LL activities were systematically integrated. The objective is to provide a comprehensive illustration of the step-by-step integration of LL resources into high school English classrooms, supplemented by sample student works to offer a clear overview of the process. The study concludes by offering recommendations and implications for language education professionals.

The Ecological Design of Marine Urban Green Space Plant Landscaping Based on the Concept of Sustainability.

With global climate change and accelerating urbanization, marine cities face unique environmental challenges. Ecological landscape creation is a form of design planning guided by the disciplines of landscape ecology and ecological aesthetics in the process of urban planning and construction. It seeks a design that can maintain the virtuous cycle of the ecosystem and at the same time maintain the spatial equilibrium of the dynamic development of urban landscapes, so as to make them have good ecological functions and corridor functions. The aim of this study is to explore the ecological design methods of plant landscaping in marine urban green spaces under the concept of sustainability. We first reviewed the concept of sustainable development and its application to urban green space design, especially the special requirements in the marine urban environment. This research focuses on how to select plant species that are adapted to the marine climate and how to promote biodiversity, enhance ecosystem services, and improve the quality of life of urban residents through eco-design approaches. Through the analysis of a number of domestic and international cases of green spaces in marine cities, we found that effective eco-design is not only about choosing the right plant species but also includes the rational management of water resources, soil protection, and ecosystem restoration, among other aspects. This study also points out that public participation and interdisciplinary cooperation play a crucial role in the ecological design process. Finally, this paper carries out a specific analysis of the landscape model landscape evaluation system for the ecological design of plant landscaping in marine urban green spaces and experimentally verifies that, compared with other styles, the experience of the European-style landscape is good overall. However, the view openness rating of the European style landscape is only about 0.42, and the best plant landscaping is the mixed mode of alkali poncho and salt poncho. This study aims to provide a practical reference and guidance for urban planners, landscape architects, and environmentalists.