The development of a zygote into a functional organism requires that this single progenitor cell gives rise to numerous distinct cell types. Attempts to exhaustively tabulate the interactions within developmental signaling networks that coordinate these hierarchical cell fate transitions are difficult to interpret or fit to data. An alternative approach models the cellular decision-making process as a flow in an abstract landscape whose signal-dependent topography defines the possible developmental outcomes and the transitions between them. Prior applications of this formalism have built landscapes in low-dimensional spaces without explicit maps to gene expression. Here, we present a computational geometry framework for fitting dynamical landscapes directly to high-dimensional single-cell data. Our method models the time evolution of probability distributions in gene expression space, enabling landscape construction with minimal free parameters and precise characterization of dynamical features, including fixed points, unstable manifolds, and basins of attraction. We demonstrate the applicability of this framework to multicolor flow-cytometry and RNA-seq data. Applied to a stem cell system that models ventral neural tube patterning, we recover a family of morphogen-dependent landscapes whose valleys align with canonical neural progenitor types. Remarkably, simple linear interpolation between landscapes captures signaling dependence, and chaining landscapes together reveals irreversible behavior following transient morphogen exposure. Our method combines the interpretability of landscape models with a direct connection to data, providing a general framework for understanding and controlling developmental dynamics.

Lactate metabolism and lactylation in ocular diseases.

Landscape and ecosystem health dynamics in response to terrain in southwest China's karst mountains: A study with evidence since 1980

From urban to nature: A continuous landscape gradient mapping framework in Southwest China.

Landscape aesthetic quality (LAQ) is a vital cultural ecosystem service in global forests, particularly in the subalpine forests across the Tibetan Plateau, which are considered popular tourist destinations due to their unique cultural services. However, the explicit spatial localization and spatial–temporal dynamics of LAQ in subalpine forests in the Tibetan Plateau remain largely unexplored. Herein, we introduced a method for assessing LAQ that integrates the species’ biophysical attributes with spatial landscape characteristics, allowing for a spatially explicit quantification of LAQ. We further employ this approach to project changes in LAQ under forest landscape dynamics (2016–2096) in Jiuzhaigou, eastern Tibetan Plateau. Most regions exhibited moderate or low LAQ, with high values ible, while over half of low-LAQ regions were not. The high-value zone of LAQ is projected to rise slightly by 2056 but decline sharply by 2096. These results reveal strong spatial heterogeneity in LAQ and indicate that future landscape dynamics will substantially reshape its distribution in the subalpine forests of the eastern Tibetan Plateau. Our findings provide early evidence of declining cultural ecosystem quality in subalpine forests and offer guidance for adaptive management in similar mountain ecosystems worldwide.

This paper explores the digital marketing strategies and business practices of small and medium-sized enterprises (SMEs) in the Southwestern region of the Republic of North Macedonia. This region represents a tourism-driven area with a growing presence of small and medium-sized enterprises. Rather than focusing on consumer perspectives, the study examines how businesses develop, implement, and measure digital marketing activities to enhance their market presence and customer interaction. Using a quantitative research approach, data were collected from 31 local enterprises to identify the extent of digital channel use, strategic objectives, and performance indicators. The findings contribute to understanding how regional businesses leverage digital tools to strengthen brand visibility, engage customers, and advance their competitive positioning in emerging digital markets. The insights and recommendations provided aim to guide marketers in developing effective digital marketing strategies that resonate with their target audiences and adapt to the dynamic digital landscape.

This paper provides a systematic review of participatory landscape planning in urban fringe areas, focusing on community co-design and institutional governance frameworks. Urban fringes are regions where urban expansion intersects with rural and agricultural systems. These areas present complex challenges due to the involvement of multiple stakeholders and the complexity of ecological networks. The review evaluates the effectiveness and applicability of methods such as participatory rural appraisal (PRA), participatory geographic information systems (GIS), landscape design workshops, and participatory scenario modeling. These methods promote community participation and generate planning outcomes related to local environments and sustainability. The review reveals a surge in global interest in participatory planning practices since 2010, particularly in Europe, East Asia, and Latin America. Additionally, the findings indicate that forms of participatory governance, such as collaborative and co-governance models, are crucial for success in these dynamic landscapes. The study underscores the importance of integrating local knowledge and institutional prerequisites into future urban fringe area planning. This review deepens our understanding of the role of community co-design in landscape planning and offers insights for strengthening more inclusive, adaptive, and resilient governance in urban fringe regions.

This study attempts to reconstruct the glacial history of the Upper Changme Khangpu Basin (CKB), an eastern tributary of the River Tista in the Eastern Himalaya, using radiocarbon ( 14 C) method, supplemented by sedimentological and mineralogical analyzes. Despite being a monsoon-dominated glaciated region, the upper reaches of the basin still contain exceptionally well-preserved glacial landforms of the recent geological past. However, there remains a critical gap in understanding due to the lack of chronological studies to clarify and correlate the roles of climate and glacial interactions in an environment where intense monsoonal precipitation rapidly alters the landscape and glacier dynamics. In order to reconstruct the past glacier fluctuations and associated palaeoclimatic conditions, this study has employed a multi-proxy approach, integrating geomorphic feature mapping, sedimentological analysis, Accelerator Mass Spectrometry (AMS) 14 C dating, alongside the Schmidt Hammer rebound data for relative age determination. The results have yielded a well-defined glacial chronology for the Late Quaternary in the CKB, identifying four distinct glacial advances of varying magnitudes. The extensive glacial phase (Phase-II) resulted in the blockage of the ablation valley, forming a ∼700 m-long proglacial lake. Subsequent glacial recession seems to have intensified the paraglacial processes which progressively reshaped and modified the earlier landforms. A new dataset of 14 C ages (3.5 ka to 31.4 ka cal BP) indicates climatic oscillations during the intervening period. Post-glacial climatic shifts, particularly between 14.29 ka and 3.5 ka cal BP, show a regional correlation with climatic patterns observed in the Eastern Himalayas. Our finding underscores the need to further refine this enquiry to develop a robust glacial chronology of the basin using multiple modern geochronological techniques.

Structural Dynamics and Energy Landscape of the Forward and Reverse Water–Gas Shift Catalytic Cycle on Ceria

ABSTRACT Soil organic matter (SOM) is a key indicator of soil fertility and ecosystem resilience, yet its spatial and vertical variation mechanisms remain poorly understood in fragile mountainous landscapes. This study integrates machine learning and interpretable causal modeling to elucidate the multiscale drivers of SOM distribution in the Yihe River Basin (YRB), a typical erosion‐prone region in northern China. The Random Forest (RF) model was used to predict the spatial distribution of SOM content, and the relative contributions and pathways of natural and anthropogenic factors were identified using the Piecewise structural equation (PSEM) model and Shapley additive explanations (SHAP). Results showed that the RF model successfully predicted SOM content with coefficients of determination ( R 2 ) of 0.695, 0.671, 0.626, and 0.730 for the four soil horizons, respectively. Horizontally, SOM content was higher in the eastern and northern regions of the basin. Vertically, the SOM content showed a decreasing trend with increasing soil depth. Among the factors influencing SOM distribution, soil properties, particularly total nitrogen content, were identified as the most significant determinants. Moreover, human activities primarily influence SOM indirectly by modifying soil physicochemical properties and climatic conditions. Their effects are more pronounced in surface soils, with total impact effects ranging from 0.94 to 1.04. These findings provide new insights into SOM dynamics in fragile landscapes and offer scientific guidance for targeted soil management and ecological restoration in erosion‐prone regions.

In today's dynamic corporate landscape, Corporate Social Responsibility (CSR) has emerged as a pivotal force shaping the conduct and ethical dimensions of businesses. This research paper embarks on a multifaceted exploration, examining the intersection of CSR and Company Law through a distinct legal lens. In the contemporary business environment, the concept of Corporate Social Responsibility (CSR) has gained prominence as a fundamental pillar of ethical corporate conduct. This research paper delves into the intricate relationship between CSR and Company Laws from a legal standpoint. The study aims to investigate key facets of this interaction by framing the two research objectives. First, the research seeks to assess the awareness and understanding of CSR principles among legal professionals and second, the research explores the Existence of Government Incentives and Regulatory Support Government incentives and regulatory support for CSR initiatives within company law impact on the adoption and effectiveness of corporate social responsibility practices among businesses. Primary data for this study will be collected through a 5-point Likert scale questionnaire. Structured surveys and in-depth interviews were employed in the study. The findings of this research offers a valuable contribution by shedding light on the legal dimension of CSR and company law, providing insights that can inform future legislative reforms and corporate decision-making in the pursuit of responsible business practices. It underscores the evolving landscape of corporate responsibility within legal frameworks and its implications for sustainable corporate governance, offering a foundation for more responsible and ethically conscious business practices in today's dynamic corporate environment.

The federally threatened Puritan tiger beetle (Ellipsoptera puritana; PTB) inhabits Upper Chesapeake Bay bluffs, beaches and Connecticut River point bars. This study focuses on Maryland’s Chesapeake Bay population (Calvert County and Sassafras River), where adult PTBs prey on beach arthropods but establish larval habitat on the adjacent bluffs. A combination of panoramic photography, GIS mapping, and field and laboratory measurements of sedimentological and ecological characteristics were measured across 17 high- and low-density Maryland beetle sites to identify the geologic and biological controls on population distribution and abundance. Results indicate that temporal and spatial fluctuations in PTB abundance are governed by bluff face quality, which in turn, is shaped by antecedent geology (medium-compacted, fine-to-medium, well-sorted sands) and bluff dynamics. We present a four-stage, multi-decadal geomorphodynamic conceptual model in which long-term bluff recession and short-term storm-driven colluvium removal periodically expose fresh bluff surfaces required for larval establishment. By integrating geomorphic, geologic, and ecological perspectives, this study highlights the role of sedimentary processes in maintaining critical estuarine habitats and provides a framework for predicting species persistence in dynamic coastal landscapes.

Abstract The Migration Period (4 th –5 th centuries AD) in Central Europe was marked by profound demographic and cultural transformations. Nevertheless, bioarchaeological data from this period remain scarce across the region. Tyniec upon Ślęża constitutes the only newly excavated Migration Period cemetery in southern Poland, providing a rare opportunity to explore lifeways during this transformative epoch. Stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope analyses were conducted on samples from ten individuals to reconstruct dietary patterns, while mobility was investigated through high-resolution strontium isotope (⁸⁷Sr/⁸⁶Sr) measurements of dental enamel from selected individuals, yielding a total of twenty determinations. A local environmental baseline was established, encompassing the principal prehistoric settlement zones surrounding Wrocław. To complement the isotopic dataset, trace element concentrations from dental enamel were examined to aid dietary reconstructions and assess potential diagenetic alterations. The findings highlight the interpretative challenges posed by the highly dynamic demographic landscape of the Migration Period, in which the absence of stable local populations complicates the identification of non-local individuals. Nevertheless, the results reveal pronounced dietary variability, including substantial consumption of aquatic resources, and complex mobility signatures, reflecting diverse geographic origins and life histories. Our paper provides new insights into the processes of cultural hybridization among Germanic populations inhabiting Silesia during this turbulent era. It further explores their adaptive strategies and cultural responses to interactions-both direct and indirect-with nomadic groups and the broader geopolitical transformations precipitated by the disintegration of the Roman Empire.

Abstract Radiation‐induced heart disease (RIHD) is a serious complication of radiotherapy and a major contributor to non‐cancer mortality. This study employs single‐cell RNA sequencing technology to investigate the dynamic immune landscape following radiation‐induced cardiac injury, uncovering potential mechanisms of RIHD and providing strategies for its prevention and treatment. We identified nine immune cell types, totaling 24,683 leukocytes. Macrophages accounted for the largest proportion (78.45%). Over time following irradiation, the proportion of macrophages decreased, while monocytes, T cells, and dendritic cells (DCs) increased. B cells and natural killer cells showed a slight decrease on day 7 but peaked on day 35. Neutrophils reached their highest levels on day 7. We observed a significant increase in pro‐inflammatory subpopulations on day 7 post‐irradiation, along with elevated expression of pro‐inflammatory genes. By day 35, the proportions of apoptosis‐ and proliferation‐related subpopulations had significantly risen, with corresponding upregulation of apoptosis‐ and proliferation‐related genes. We also observed two specific subpopulations: IFN+ macrophages and mregDCs. We identified a fibrosis‐associated macrophage subpopulation, MHCII+_Ccr2 macrophages, and found that the SPP1 pathway was significantly expressed in this subpopulation 7 days post‐irradiation. We further hypothesize that the SPP1‐CD44 pathway may be closely associated with cardiac fibrosis. Thus, this study provides a comprehensive immune atlas of the mouse heart post‐irradiation, revealing significant shifts in immune responses at different time points.

Online parameter tuning significantly enhances the performance of optimization algorithms by dynamically adjusting mutation and crossover rates. However, current approaches often suffer from high computational costs and limited adaptability to complex and dynamic fitness landscapes, particularly when machine learning methods are employed. This work proposes a quantized shallow neural network (SNN) as an efficient learning-based component for dynamically adjusting the mutation and crossover rates of a genetic algorithm (GA). By leveraging runtime-generated data and applying quantization techniques like Quantization-aware Training (QaT) and Post-training Quantization (PtQ), the proposed approach reduces computational overhead while maintaining competitive performance. Experimental evaluation on 15 continuous benchmark functions demonstrates that the quantized SNN achieves high-quality solutions while significantly reducing execution time compared to alternative shallow learning methods. This study highlights the potential of quantized SNNs to balance efficiency and performance, broadening the applicability of shallow learning in optimization.

Forest ecosystems in the eastern United States are undergoing significant compositional and demographic shift. To understand these changes, we used Forest Inventory & Analysis data (2003 - 2021) to examine landscape-scale trends in the North Carolina Piedmont, focusing on forest type groups, taxonomic family, and species. We assessed metrics such as annual net primary productivity, relative density, and biodiversity, aiming to determine: i) Which forest group types are changing most, ii) Whether these changes extend to lower taxonomic units, and iii) How stability has shifted over time. Our findings reveal an increasing dominance of Pinus species, particularly naturally regenerated loblolly pine (Pinus taeda), accompanied by sweetgum (Liquidambar styraciflua). This shift corresponds to rising prevalence of pine and oak-pine forest type groups. Notably, while red maple (Acer rubrum) consistently had high seedling densities, its recruitment lagged behind species like sweetgum and yellow-poplar (Liriodendron tulipifera), defying broader regional trends. These results highlight a clear progression from species-level changes to broader taxonomic families and forest types, emphasizing a shift toward pine in the region. The study underscores the importance of multi-level analyses for capturing ecological trends and advancing understanding of forest dynamics in changing landscapes.

ABSTRACT Research assessing the dynamic landscape of infectious disease vaccine candidates has been limited. We extracted comprehensive data on vaccine candidates through the Pharmcube system as of March 21, 2025, to analyze the latest trends and disparities in the research and development (R&D) landscape for infectious disease vaccines since 2015. The global vaccine R&D landscape comprises 919 candidates. The top three diseases targeted for vaccine R&D are COVID-19 (245 candidates), influenza (118 candidates), and HIV (68 candidates). Among these, 25% (231 candidates) are nucleic acid vaccines, followed by recombinant protein vaccines (125 candidates) and viral vector vaccines (73 candidates). More than 50% of the candidates are in the pre-phase II stage, while nearly 15% are in phase II (144 candidates) or phase III (137 candidates). Of the 36 countries or territories reporting vaccine candidates, China leads with 313 candidates, followed by the USA with 276 candidates and the UK with 63 candidates. The majority of the candidates are being developed independently or collaboratively by private companies/industry in China (289 candidates), France (30 candidates), the Republic of Korea (27 candidates), Germany (26 candidates), the USA (217 candidates), and the UK (43 candidates). The USA, France, and the Republic of Korea mainly predominantly develop mRNA vaccines, while China primarily develops recombinant protein vaccines, and the UK focuses on viral vector vaccines. Strengthening interagency and international cooperation, along with implementing supportive policies, may be effective in accelerating R&D for infectious diseases in the future.

In today’s dynamic educational landscape, Higher Education Institutions (HEIs) are increasingly recognizing the imperative adoption of purposeful learning. Purpose-led HEIs proactively leverage their resources and expertise to contribute positively to communities and empower students with essential competencies for their future professions. This study explored an innovative purpose-led pedagogy in teacher education by integrating refugee community engagement. Twenty pre-service teachers conducted lessons for 223 kindergarten and primary school students at two alternative learning centers in Malaysia. Data from students’ artifacts, video recording, and reflective videos were collected and analyzed. Findings showed that pre-service teachers successfully designed and implemented developmentally appropriate lessons, enhanced their classroom management skills and fostered positive relationships with refugee students. Insights into the challenges faced in a refugee school setting broadened their perspectives on global educational issues, nurturing empathy. This study suggests a transformative shift in HEIs’ pre-service teacher education programs toward a community-based and inclusive model.

This special issue brings together critical scholarship and innovative solutions that refuse to accept the false choice between rigor and equity. The assembled articles interrogate current practices from multiple angles, examining clinical supervision as a social justice issue, the psychometric flaws embedded in standardized testing, and the financial and structural barriers that disproportionately impact marginalized candidates. Contributors explore alternative assessment approaches—including performance-based evaluations, portfolio assessment, and provisional licensure models—as well as abolitionist frameworks that call for fundamentally reimagining professional regulation. Empirical studies rigorously examine the relationship (or lack thereof) between exam content and practice readiness, while policy analyses dissect how states are navigating the complex politics of reform.

Advocacy campaigns are increasingly vital in shaping public opinion, influencing policy, and promoting social justice. Within this dynamic landscape, legal professionals play a crucial role in advancing causes through effective communication. This paper examines how legal advocacy, particularly through social and digital platforms, can be optimized to reach diverse audiences, foster coalitions, and shape legislative outcomes. Legal communication, as both an art and a strategy, involves more than mere transmission of facts; it requires understanding the audience, crafting persuasive messages, and choosing appropriate channels to mobilize support. By analyzing case studies, communication strategies, coalition-building practices, and ethical considerations, the paper demonstrates how legal advocates can responsibly and powerfully engage in public discourse. It emphasizes the need for a shift from traditional court-bound narratives to more inclusive, multimodal approaches that bridge the gap between law and society. Ultimately, this study presents a comprehensive framework for enhancing advocacy through effective legal communication, aiming to democratize access to justice and inspire systemic change. Keywords: Legal advocacy, legal communication, social justice, digital platforms, audience engagement, coalition-building, public policy.