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Eco-cities have become global initiatives in recent years. This paper aims to discuss the construction, evolution and future of eco-city movements in China, especially in areas with abundant ecological resources. Extant literature emphasizes that sustainable development is the purpose of an eco-city. However, in the spatial practice of ecological modernization, many European and American countries develop ecological construction at a slower pace, resulting in sustainable ecological outcomes. Those countries developed ecological practices at a smaller scale, aiming to achieve green towns with zero carbon emission. In contrast, the construction of China’s eco-cities typically involves building new cities in outer suburbs with a larger scale and faster speed. This has led to the rapid construction of so-called ecological cities without sustainable development. In this context, this paper starts from the perspective of political economy and conducts qualitative research on the Shanghai Dongtan Eco-city as a case study. It analyzes the motivation and practical measures of different actors by examining the planning, design and construction process of Dongtan Eco-city during 1998–2024. The results suggest that gaining national political priority through the intervention of international actors and foreign investment is the key to the local pilot ecological city project. This paper further analyzes the differences between the planning concept and the actual practice of Dongtan Eco-city, critically discussing the “Eco-city as the enclave of ecological technology.” This is driven by the integration of eco-city construction and the local government performance appraisal system. Consequently, the pursuit of economic returns redirected Dongtan’s sustainability experiment into a form of green-branded retirement real-estate development between 1998 and 2012. From 2012 to 2024, Chongming’s development model continued to evolve, as the project was reframed from a real-estate-led eco-city paradigm toward an “ecological island” agenda articulated in the language of sustainable development. Full article

With the development of avionics systems towards high integration and high power density, the thermal management of electronic equipment in ATR chassis is facing severe challenges, and the extreme aviation environment further exacerbates the difficulty of heat dissipation. Traditional fixed control strategies suffer from problems such as energy consumption, redundancy, and local overheating, whereas single-model predictive control (MPC) is prone to local optimization. This paper proposes a thermal management optimization scheme based on the ACO-MPC hybrid framework: Firstly, a compact thermal model integrating aviation environmental parameters, such as high-altitude, low-pressure conditions and vibration impacts, is constructed. The balanced truncation method is adopted for model order reduction in this study. By retaining the key thermodynamic characteristics of the system, the original three-dimensional thermal model containing more than 800 nodes is simplified to 25 core nodes, which ensures simulation accuracy while improving computational efficiency; Secondly, the ACO-MPC hybrid framework is designed, which uses Ant Colony Optimization (ACO) for global optimization to provide optimized initial values for Model Predictive Control (MPC), breaking through the local optimization limitation of MPC and realizing the collaboration of “global optimization—dynamic control”; Finally, the effectiveness of the framework is verified in three typical aviation scenarios. The results show that compared with traditional methods, this framework has significantly improved heat dissipation efficiency, energy consumption control, and temperature stability, and has strong adaptability to environmental disturbances, which can be migrated to the ATR chassis of different specifications. Full article

From the 9th century onwards, Tāmdult was one of the three major caravan ports in the Western Maghreb, alongside Sijilmāssa and Nūl Lamṭa. By the mid-20th century, the remains of dwellings, metallurgical production sites and fortifications had been located a few kilometres south of the present-day oasis of Aqqa, which is irrigated by the resurgence of the wadi of the same name. In 1999, our research, which was based on field surveys and aerial photographs, revealed exceptionally well-preserved traces of a large-scale agricultural system and an irrigation canal network adjacent to the ruins. This completed the picture of this pre-Saharan oasis. An initial study was published in 2011. However, the question of the chronological relationship between the two oases, Tāmdult and Aqqa, remained unresolved. Processing recent satellite images (Airbus © 2023) of these two oases and creating a WebGIS interface now enables us to refine and correct our observations from 1999. This new data largely confirms our initial proposals, such as the joint development of an urban settlement and an agricultural area with an irrigation network. Furthermore, these new images show the branching structure of the various water distribution channels, the regularity of the agricultural land parcels and the existence of interstitial rural settlements. They thus reveal a hierarchy in this distribution that was perhaps insufficiently explored in our initial publication. Given the limited historical sources available, we can now make more informed arguments regarding the possibility of the two oases coexisting over time. We can also propose initial hypotheses about the main reasons for the abandonment of one of the oases and discuss the identity of their founders, which could be local tribal groups and/or branches of the Idrisid dynasty. The central issue of the dossier to which our contribution is addressed—‘The Role of Urban Elites in the Construction of Rural Landscape’—is adapted here to the specific characteristics of the pre-Saharan context in terms of both climate and settlement structure. Full article

The accurate prediction of crack initiation and propagation is essential for assessing the structural integrity of mechanically joined components and other complex assemblies. To overcome the limitations of existing finite element tools, a modular Python framework has been developed to automate three-dimensional crack growth simulations. The program combines geometric reconstruction, adaptive remeshing, and the numerical evaluation of fracture mechanics parameters within a single, fully automated workflow. The framework builds on open-source components and remains solver-independent, enabling straightforward integration with commercial or research finite element codes. A dedicated sequence of modules performs all required steps, from mesh separation and crack insertion to local submodeling, stress and displacement mapping, and iterative crack-front update, without manual interaction. The methodology was verified using a mini-compact tension (Mini-CT) specimen as a benchmark case. The numerical results demonstrate the accurate reproduction of stress intensity factors and energy release rates while achieving high computational efficiency through localized refinement. The developed approach provides a robust basis for crack growth simulations of geometrically complex or residual stress-affected structures. Its high degree of automation and flexibility makes it particularly suited for analyzing cracks in clinched and riveted joints, supporting the predictive design and durability assessment of joined lightweight structures. Full article

Protein S-palmitoylation is a pivotal yet poorly integrated research field in dermatology. This reversible post-translational lipid modification primarily occurs on cysteine residues and is principally catalyzed by zinc finger and Asp-His-His-Cys DHHC-domain containing proteins (zDHHCs). The S-palmitoylation/depalmitoylation cycle directly affects protein localization, trafficking, stability, and protein–protein interaction, thereby regulating a variety of signaling pathways, including those mediating inflammation and immune reaction. Accumulating evidence has indicated that S-palmitoylation regulates various skin biological functions, including skin inflammation, skin barrier function, hair growth, and melanin synthesis, and is ultimately implicated in the initiation and development of massive dermatoses, such as alopecia and psoriasis. The recent development of new research tools, coupled with S-palmitoylation’s therapeutic potential, makes the timely synthesis of its role in skin pathophysiology both critical and opportune. Here, we summarize recent advances in understanding the mechanistic roles of S-palmitoylation in dermatological conditions and evaluate its potential as a therapeutic target for innovative treatment strategies. Full article

Introduction: Severe acute pancreatitis (SAP) is a critical condition that affects 20–30% of people with acute pancreatitis (AP). Prompt detection and accurate classification are crucial to direct prompt interventions, increase resource allocation, and improve patient outcomes. Current scoring systems, while beneficial, frequently face challenges related to speed, complexity, and early predictive accuracy. Method: We developed and validated an effective six-parameter risk assessment scale for AP, incorporating pancreatic-specific biomarkers (trypsinogen-activating peptide [TAP], trypsin-2), systemic inflammation markers (C-reactive protein), pancreatic enzyme concentrations, blood glucose, and patient age. The study cohort included 104 patient samples. Reliability was assessed using Cronbach’s alpha and Spearman–Brown coefficients, factorial validity was determined by principal component analysis, and predictive validity was analyzed using logistic regression and receiver operating characteristic (ROC) analysis. Biotemporal changes at 24 and 48 h were assessed to classify risk scoring. Results: The scale demonstrated satisfactory internal consistency (Cronbach’s alpha = 0.72) and a distinct structure with two factors representing local pancreatic damage and systemic inflammation, explaining 65% of the variability. Logistic regression established predictive validity for serious outcomes, with TAP and trypsin-2 showing significant correlations. ROC analysis demonstrated remarkable discriminative capacity (AUC = 0.85), showing a sensitivity of 82.4% and a specificity of 76.8%. Assessment of temporal biomarkers showed a reduction in TAP, signifying resolution of the initial enzymatic activation, while trypsin-2 levels continued to increase, indicating persistent damage to the pancreatic tissue. Patients were classified into low-, moderate- and high-risk groups, facilitating practical clinical decision-making. Discussion and Conclusions: This six-parameter risk score provides a rapid, biologically based, and clinically useful method for early detection of patients at risk for SAP. Combining indicators of local pancreatic involvement with systemic inflammation allows for prompt triage, improves the allocation of intensive therapy, and supports informed prognostic conversations. Full article

The concept of bioregions stands out among the various approaches to sustainable territorial development, as it prioritises the initiative of local communities in addressing sustainability issues. At the same time, the concept of bioregions is diverse in practice, focusing on organic farming, tourism, local culture and also nature protection. Therefore, a balanced approach to the development of bioregions, which considers the specific characteristics of a particular area and the needs of its local community, is important. The present research employed the Analytical Hierarchy Process (AHP) approach to analyse economic, ecological and social value added as the main criteria, alongside their subordinate subcriteria. As a result, three scenarios were designed: the Broad Integration Scenario, the Conservative Scenario and the Culture and Tourism Scenario. The dominant strategy was found to be the Culture and Tourism scenario, focusing on tourism and local cultural values. This strategy can contribute to increasing the consumption of local products and services while preserving the cultural values and ensuring a balanced approach to sustainable development. At the same time, the Broad Integration Scenario revealed that a broad—and perhaps an aggressive—approach to sustainable development was highly controversial, as it had the greatest dispersion in priority vector values. Bioregionalism, however, is a little-supported approach that does not gain support from either sustainability or rapid growth advocates. The results reveal the importance of a long-term approach to sustainable development and, at the same time, implicitly point to the role of public attitudes, both in terms of supply (through local community initiatives in bioregionalisation) and demand, which could increase the consumption of bioregional products and services. Full article

The present studies focus on the analysis of the inherent differences between temperature- and pyrolysis-based models and foster a rational and comprehensive understanding of numerical models for lightning strike damage in laminated composites. A systematic methodology combining numerical simulation and pyrolysis kinetics analysis has been developed to examine the inherent differences in damage area and depth, damage threshold, electrical conductivity characteristics, and Joule energy between temperature- and pyrolysis-based models. The results indicate that the pyrolysis-based model demonstrates closer agreement with experimental data in terms of both damage area and damage depth predictions compared to the temperature-based model. The two damage thresholds (500 °C and pyrolysis degree of 0.1) yield equivalent predictions of overall damage, but the temperature-based criterion neglects localized heating rate effects. The pyrolysis-based model exhibits significantly delayed through-thickness conductivity development during initial current conduction compared to the temperature-based model due to the influence of heating rate. This lag results in the pyrolysis-based model predicting larger damage areas and shallower penetration depths. Joule heating analysis further confirms that the pyrolysis-based model exhibits higher overall electrical resistance than the temperature-based model. Through a systematic comparison of temperature- and pyrolysis-based models, this research holds the significance of enhancing the understanding of lightning strike damage mechanisms and advancing the development of high-fidelity numerical models for predicting lightning strike damage in laminated composite. Full article

Accurate parameter estimation of photovoltaic (PV) models is fundamentally a challenging nonlinear optimization problem, characterized by strong nonlinearity, high dimensionality, and multiple local optima. These characteristics significantly hinder the convergence accuracy, stability, and efficiency of conventional metaheuristic algorithms when applied to PV parameter identification. Although the enterprise development (ED) optimization algorithm has shown promising performance in various optimization tasks, it still suffers from slow convergence, limited solution precision, and poor robustness in complex PV parameter estimation scenarios. To overcome these limitations, this paper proposes a multi-strategy enhanced enterprise development (MEED) optimization algorithm for high-precision PV model parameter estimation. In MEED, a hybrid initialization strategy combining chaotic mapping and adversarial learning is designed to enhance population diversity and improve the quality of initial solutions. Furthermore, a historical trend-guided position update mechanism is introduced to exploit accumulated search information and accelerate convergence toward the global optimum. In addition, a mirror-reflection boundary control strategy is employed to maintain population diversity and effectively prevent premature convergence. The proposed MEED algorithm is first evaluated on the IEEE CEC2017 benchmark suite, where it is compared with 11 state-of-the-art metaheuristic algorithms under 30-, 50-, and 100-dimensional settings. Quantitative experimental results demonstrate that MEED achieves superior solution accuracy, faster convergence speed, and stronger robustness, yielding lower mean fitness values and smaller standard deviations on the majority of test functions. Statistical analyses based on Wilcoxon rank-sum and Friedman tests further confirm the significant performance advantages of MEED. Moreover, MEED is applied to the parameter estimation of single-diode and double-diode PV models using real measurement data. The results show that MEED consistently attains lower root mean square error (RMSE) and integrated absolute error (IAE) than existing methods while exhibiting more stable convergence behavior. These findings demonstrate that MEED provides an efficient and reliable optimization framework for PV model parameter estimation and other complex engineering optimization problems. Full article

The C-X-C motif chemokine ligand 10 (CXCL10) is implicated in the progression of osteosarcoma (OS), the most aggressive pediatric bone malignancy. However, its role often presents a profound clinical paradox: although high circulating levels are strongly linked to poor prognosis, its canonical function is to recruit anti-tumor immune cells. This review unravels these contrasting roles by proposing a novel spatiotemporal model. We argue that in the early stages, immune-evading OS cells initiate the formation of a pre-metastatic niche (PMN) in the lungs, creating a localized inflammatory environment that becomes the primary source of elevated circulating CXCL10. As the disease progresses, elevated systemic levels of CXCL10 overwhelm the localized chemokine gradient at the primary tumor site, creating a potent immune decoy that diverts anti-tumor CXCR3+ T cells away from the tumor. The resulting immune desertification permits unchecked tumor growth and an increased metastatic burden. We also discuss the therapeutic implications of this model, proposing that disrupting the chemokine axis offers a roadmap for developing rational, stage-specific therapies to effectively combat metastatic OS. Full article

Background/Objectives: Surgery is generally recommended for higher Bilsky grade metastatic epidural spinal cord compression (MESCC); however, Bilsky grades 2–3 are often grouped together, leaving limited evidence for managing patients with Bilsky grade 3 MESCC who have not developed neurological deficits. This study aimed to evaluate whether, and when, surgery should be performed in Bilsky grade 3 MESCC. Methods: This retrospective cohort study included patients diagnosed with Bilsky grade 3 MESCC from January 2021 to January 2025. A total of 138 patients were assigned to a radiotherapy (RT) group (n = 54) or a surgery group (n = 65) based on initial treatment. Demographics, clinical data, treatment outcomes, and treatment modalities were analyzed. Logistic regression identified risk factors for local progression, motor recovery, and ambulatory outcomes. Results: Ninety-five patients (70.3%) initially presented with weakness. Among 30 patients diagnosed before neurological deficits, interval from diagnosis to onset was 17.2 ± 14 days. Local progression and survival rates did not significantly differ between the groups. Surgery was associated with a higher likelihood of motor recovery (odds ratio [OR] = 10.05, p < 0.001) and better ambulatory function (OR = 0.433, p = 0.003). Higher initial motor grade and lower Eastern Cooperative Oncology Group Performance Status scores were also linked to favorable ambulatory outcomes. Conclusions: In Bilsky grade 3 MESCC, the mean interval from diagnosis to weakness onset was 17.2 days. Local progression and survival did not differ between RT and surgery; however, surgery provided superior motor recovery and ambulatory outcomes. Early surgery may offer improved functional outcomes in Bilsky grade 3 MESCC. Full article

Understanding the ecological processes that shape spatial patterns across different growth stages is crucial for revealing the mechanisms of species coexistence and community dynamics. This study investigates the spatial patterns and associations between the regeneration layer and the overstory layer in Quercus variabilis forests in northern China. Using spatial point pattern analysis, we analyzed the distribution of 2761 seedlings and 449 adult trees across twelve 20 × 20 m plots. Our results revealed a consistent pattern where seedlings exhibited significant spatial aggregation, best fitted by a simple Thomas process with an average cluster radius of 3.89 m calculated across all plots, while adult trees displayed a complete spatial random distribution. A marked reduction in local density from seedlings to adults, indicated by a self-thinning index greater than 1 in most plots, provided evidence for density-dependent mortality during stand development. However, bivariate analysis detected no significant spatial association or mark correlation between adult trees and seedlings in most plots, suggesting limited interaction between these layers after initial seedling establishment. These findings demonstrate a clear transition from clustered regeneration to randomly distributed adults, which is consistent with the potential roles of dispersal limitation, habitat filtering and competition processes, with implications for the management and conservation of temperate Quercus forest ecosystems. Full article

This study reveals the distribution of floating macroalgae Sargassum in the East China Sea and Yellow Sea using HY-1C/D Coastal Zone Imager (CZI) data. A new inversion model, utilizing green and near-infrared bands, was developed for the 50 m resolution CZI data. This model effectively distinguishes Sargassum from Ulva prolifera and is effective in turbid coastal waters. Sargassum spatiotemporal distribution and drift patterns over five years were analyzed. Key findings demonstrate that (1) floating Sargassum exhibits distinct spatiotemporal distribution patterns. Sargassum initially emerges along Zhejiang’s eastern coast in February. During March and April, it concentrates east of Hangzhou Bay. While in May, Sargassum appears in the Yellow Sea, and is distributed near the Shandong Peninsula by June. Small patches of Sargassum are also found in the Yellow Sea from November to January. (2) Its distribution is influenced by various factors like nutrients, temperature, salinity, currents, and winds. Suitable nutrients, temperature, and salinity promote growth, while currents and winds, particularly in April–May, drive its northward drift from the East China Sea into the Yellow Sea. The Yellow Sea population originates from both drifting populations and local growth. (3) This research highlights the utility of HY-1C/D satellite data in coastal zone research, facilitating ecological monitoring and protection. Full article

Silicon nanowire (SiNW) photodetectors exhibit high sensitivity for natural light detection but suffer from significant performance degradation due to thermal interference. To overcome this limitation, this paper presents a high-performance, CMOS-compatible SiNW array natural light photodetector with monolithic integration of an on-chip temperature sensor and an embedded intelligent compensation system. The device, fabricated via microfabrication techniques, features a dual-array architecture that enables simultaneous acquisition of optical and thermal signals, thereby simplifying peripheral circuitry. To achieve high-precision decoupling of the optical and thermal signals, we propose a hybrid temperature compensation algorithm that combines Particle Swarm Optimization (PSO) with a Back Propagation (BP) neural network. The PSO algorithm optimizes the initial weights and thresholds of the BP network, effectively preventing the network from getting trapped in local minima and accelerating the training process. Experimental results demonstrate that the proposed PSO-BP model achieves superior compensation accuracy and a significantly faster convergence rate compared to the traditional BP network. Furthermore, the optimized model was successfully implemented on an STM32 microcontroller. This embedded implementation validates the feasibility of real-time, high-accuracy temperature compensation, significantly enhancing the stability and reliability of the photodetector across a wide temperature range. This work provides a viable strategy for developing highly stable and integrated optical sensing systems. Full article

New two-step simultaneous iterative techniques are proposed for solving polynomial equations with multiple roots of unknown multiplicity. The developed schemes achieve a local convergence order of ten and address key limitations of existing solvers, namely their dependence on prior multiplicity information and their reduced efficiency when dealing with clustered or repeated roots. Root multiplicities are adaptively estimated within the iterative process, avoiding additional function evaluations beyond those required for parallel updates. The robustness and stability of the proposed methods are assessed using both random and distant initial guesses and validated on benchmark polynomials as well as nonlinear models from biomedical engineering. The numerical results show notable improvements in residual error, iteration count, CPU time, memory usage, and overall convergence rate compared with established classical techniques. These findings demonstrate that the proposed schemes provide reliable, high-order, and computationally efficient tools for solving challenging nonlinear problems in science and engineering. Full article