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The rapid integration of renewable energy sources (RES), particularly wind, together with fluctuating demand, has introduced significant uncertainty into power system operation, challenging traditional approaches for estimating Transmission Reliability Margin (TRM) and Available Transfer Capability (ATC). This paper proposes a fully adaptive TRM estimation framework that leverages rolling-window statistical analysis of net-load forecast errors to capture real-time uncertainty fluctuations. By continuously updating both the confidence factor and window length based on evolving forecast-error statistics, the method adapts to changing grid conditions. The framework is validated on the IEEE 30-bus system with 80 MW wind (42.3% penetration) and assessed for scalability on the IEEE 118-bus system (40.1% wind penetration). Comparative analysis against static TRM, fixed-confidence rolling-window, and Monte Carlo Simulation (MCS)-based methods shows that the proposed approach achieves 88.0% reliability coverage (vs. 81.8% for static TRM) while providing enhanced transfer capability for 31.5% of the operational day (7.5 h). Relative to MCS, it yields a 20.1% lower mean TRM and a 2.5% higher mean ATC, with an adaptation ratio of 18.8:1. Scalability assessment confirms preserved adaptation (12.4:1) with sub-linear computational scaling (1.82 ms to 3.61 ms for a 3.93× network size increase), enabling 1 min updates interval. Full article

(This article belongs to the Special Issue Renewable Energy System Technologies: 3rd Edition)

22 pages, 1680 KB

Open AccessArticle

Application of Machine Learning to Cluster Analysis of Diabetes Mortality at the Municipality Level in Mexico According to Sociodemographic Factors

by Nelva N. Almanza-Ortega, Carlos Fernando Moreno-Calderon, Sandra Silvia Roblero-Aguilar, Rodolfo Pazos-Rangel, Joaquín Pérez-Ortega, Vanesa Landero-Nájera and Víctor Augusto Castellanos-Escamilla

Mathematics 2026, 14(3), 573; https://doi.org/10.3390/math14030573 (registering DOI) - 5 Feb 2026

Abstract

In recent years, the mortality due to diabetes has increased around the world. In particular, diabetes is the second leading cause of mortality in Mexico, with a heterogeneous distribution of mortality rates at the municipality level. The objective of this study is the analysis of clusters of municipalities with similar values for sociodemographic indices and diabetes mortality. In this sense, an application is presented that was developed using a data science methodology and a machine learning algorithm called fuzzy c-means. For this research, 4,604,360 death certificates from 2019 to 2023 were assessed, among other official data. As a result of the analysis, two key indicators related to diabetes mortality were found, i.e., one is the percentage of population in poverty and the other is population density. The main results of this research are as follows: a direct correlation was found between population density and mortality, and an inverse correlation was found between population in poverty and mortality. In the study interval, it was observed that the cluster with less mortality showed an increase in mortality rate year after year. Finally, we consider that the tendencies found can be useful to public health authorities for optimizing the distribution of resources for treating diabetes and reducing diabetes-related mortality. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence, Machine Learning and Data Science in Industrial and Medical Domains)

28 pages, 1322 KB

Open AccessArticle

Enhanced Sustainability of Projects Based on Dynamic Time Management Using Petri Nets

by Dimitrios Katsangelos and Kleopatra Petroutsatou

Sustainability 2026, 18(3), 1644; https://doi.org/10.3390/su18031644 (registering DOI) - 5 Feb 2026

Abstract

Construction management plays a fundamental role in the sustainability of construction projects, as its primary objective is to enhance cost-effectiveness and efficient resource utilization. One of the main challenges encountered at the early stages of a project’s lifecycle, particularly during the planning phase, is the development and agreement of construction schedules among the stakeholders involved. The tools employed for time planning and scheduling during both the planning and construction phases should therefore be capable of modeling complex environments and supporting dynamic updates in response to resource constraints. Petri nets are known for their capability of modeling complex systems, such as resource management. Their use in project management is essential for resource constraint problems. This paper investigates the use of Petri Nets as a tool for the time scheduling of engineering and construction projects. A case study is presented and modeled using Timed Petri nets, enabling dynamic adaptation under time and resource constraints. Through simulation performed with the ROMEO (v3.10.6) software, the study identifies the critical paths and determines the total project duration under various scenarios of sensitivity by adjusting specific project parameters. The results demonstrate the effectiveness of Petri nets in project management and the benefits they offer when used in modeling complex systems, identifying critical activities and calculating resource constraints and time deadlines. Full article

(This article belongs to the Special Issue Construction Management and Sustainable Development)

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15 pages, 776 KB

Open AccessReview

Liquid Biopsy for Early Pancreatic Cancer Detection: Why Has It Not Yet Worked?

by Kenji Takahashi, Yusuke Ono, Kenzui Taniue, Krushna C. Patra, Takuya Yamamoto, Mikihiro Fujiya and Yusuke Mizukami

Cancers 2026, 18(3), 525; https://doi.org/10.3390/cancers18030525 (registering DOI) - 5 Feb 2026

Abstract

Despite extensive technological advances and an ever-growing body of literature, liquid biopsy has yet to achieve reliable early detection of pancreatic ductal adenocarcinoma (PDA). Numerous studies have investigated circulating tumor-derived components, including cell-free DNA (cfDNA), cell-free RNA (cfRNA), extracellular vesicles (EVs), and circulating tumor cells (CTCs), primarily using peripheral blood samples; however, their clinical utility for early-stage disease remains limited. The fundamental obstacles are biological rather than purely technical: early PDA and its precursor lesions, such as pancreatic intraepithelial neoplasia (PanIN) and intraductal papillary mucinous neoplasms (IPMN), are characterized by minimal tumor burden, low levels of nucleic acid shedding, and substantial background signals from non-neoplastic tissues. Increasing analytical complexity through multilayered liquid biopsy approaches, including analyses from pancreas-associated fluid, has not consistently translated into improved diagnostic performance and, in some cases, has amplified issues related to specificity, reproducibility, and interpretability. Moreover, molecular alterations detected in body fluids may reflect clonal expansion without inevitable malignant progression, raising concerns regarding overdiagnosis and clinical decision-making. Pre-analytical variability, lack of standardization, and limited access to tumor-adjacent fluids further hinder clinical implementation. Liquid biopsy should therefore be regarded as a complementary modality rather than a substitute for histopathological diagnosis, with its precise clinical role in early detection still ill-defined. In this review, we critically examine why liquid biopsy has not yet succeeded in early PDA detection, highlighting the key biological, technical, and clinical barriers that must be addressed to move the field beyond exploratory research toward meaningful clinical application. Full article

(This article belongs to the Special Issue Novel Diagnosis and Treatment Approaches in Pancreatic Cancer)

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33 pages, 7137 KB

Open AccessReview

Green Product and Process Innovation and Firm Performance: A Meta-Analytic Review

by Fengyu Zhao, Menghan Li, Xiaowen Xie and Lei He

Sustainability 2026, 18(3), 1640; https://doi.org/10.3390/su18031640 (registering DOI) - 5 Feb 2026

Abstract

As organizations strive to balance environmental stewardship with economic competitiveness, understanding the performance implications of Green Innovation (GI) has become increasingly important. Although the nexus between Green Product Innovation (GPI), Green Process Innovation (GPrI), and organizational outcomes has attracted sustained scholarly attention, empirical evidence remains inconclusive. To reconcile these inconsistencies and delineate boundary conditions, this study synthesizes data from 48 empirical investigations (2012–2025) via a random-effects meta-analysis with the Hartung–Knapp adjustment and trim-and-fill procedures to strengthen statistical inference. Results reveal significant small-to-moderate positive associations between GI and environmental (r = 0.172), financial (r = 0.191), and innovation performance (r = 0.143). Notably, moderator analyses demonstrate a synergy premium, where Integrated GI measures significantly outperform isolated GPI or GPrI approaches (r = 0.353). Substantial heterogeneity exists (I² = 91.2%), which is significantly moderated by innovation type, industry pollution intensity, geographic region, and research design. Our findings reinforce the Natural-Resource-Based View (NRBV) and the Dynamic Capabilities framework, highlighting that strategic returns depend on asset orchestration and contextual factors. We conclude that firms should adopt a holistic approach, integrating both product and process innovations to enhance competitive advantage in an incremental and context-contingent manner, while interpreting innovation-performance results cautiously given the limited evidence base. Full article

(This article belongs to the Special Issue Environmental Economics, Policies and Sustainable Economic Development)

19 pages, 2922 KB

Open AccessArticle

IMTA Production of Pacific White Shrimp Integrated with Mullet, Sea Cucumber, Oyster, and Salicornia in a Biofloc System

by Enrique A. Estévez Hernández, Ivanilson Santos, Laura Moraes, Morena Salala Kashane, Marcelo H. Okamoto, Luís André Sampaio, Dariano Krummenauer, César S. B. Costa, Ricardo V. Rodrigues, Silvia Martínez-Llorens and Luís H. Poersch

Fishes 2026, 11(2), 98; https://doi.org/10.3390/fishes11020098 (registering DOI) - 5 Feb 2026

Abstract

Integrated multitrophic aquaculture (IMTA) emerges as a sustainable strategy to control the excess of solids and inorganic nutrients that tend to increase in the biofloc system (BFT) cycle, since the model integrates organisms from different trophic levels sharing the same system and nutrients. Thus, this study compared a Penaeus vannamei monoculture system with an integrated biofloc system including Mugil liza, Holothuria grisea, Crassostrea tulipa, and Salicornia neei, focusing on water quality and the performance of organisms and systems. This study consisted of three monoculture systems (16 m³; 375 shrimp m⁻³) and three IMTA systems, composed of a shrimp tank (16 m³), a mullet tank (4 m³; 30 ind m⁻³), a combined tank (3 m³) for oysters (45 ind m⁻³) and sea cucumbers (3 ind m⁻²), and a Salicornia neei bed (2.78 m²; 37 ind m⁻²). All IMTA systems operated in recirculation without water exchange, using 10% of the established biofloc inoculum. The IMTA system had half the hydrated lime use (2.13 vs. 4.29 kg), lower solids (299.56 vs. 373.33 mg L⁻¹), and reduced sludge production (9.37 vs. 15.87 kg). Shrimp growth was similar in both systems. Mullet grew adequately with a survival rate of 95.8%, but oysters showed a survival rate of 45.7%. Sea cucumber had a survival rate of 100% until day 28, when a marked decline appeared, strongly correlated with rising temperature (>28 °C; r = −0.71). This resulted in a significant increase in solids in the last weeks, suggesting that the population decline reduces solids control capacity. Furthermore, the biofloc in IMTA was dominated by coccoid forms, with lower proportions of filamentous and cyanobacterial forms. Full article

(This article belongs to the Special Issue Integrated Multi-Trophic Aquaculture (IMTA))

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23 pages, 381 KB

Open AccessSystematic Review

Identification and Detection of Specific Learning Disabilities: A Systematic Review

by Isaías Martín-Ruiz, Elena Rueda-Flores, Lidia Infante-Cañete, Elena Alarcón-Orozco and Maria-Jose Robles-Sánchez

Educ. Sci. 2026, 16(2), 249; https://doi.org/10.3390/educsci16020249 (registering DOI) - 5 Feb 2026

Abstract

This study addresses the enduring controversy surrounding the diagnostic criteria for Specific Learning Disabilities (SLD) following the publication of the DSM-5, which is related to their definition. The aim of this study is to review and compare the diagnostic criteria of different classification systems and analyse differences in the identification and evaluation criteria of SLD. To this end, a search of the scientific literature was conducted through ERIC, PsycInfo (Proquest) and Web of Science spanning 2013 to 2024. Fifteen records published in English and focused on school-age children (primary education) were included. The studies address issues in reading, writing and mathematics, using different diagnostic criteria and tools. The findings highlight the need for multidimensional, validated assessments, as well as the importance of early identification to improve access to resources and tackle socio-emotional and motivational factors. Full article

(This article belongs to the Section Special and Inclusive Education)

19 pages, 10669 KB

Open AccessArticle

NutriRadar: A Mobile Application for the Digital Automation of Childhood Nutritional Classification Based on WHO Standards in the Peruvian Amazon

by Jaime Cesar Prieto-Luna, Luis Alberto Holgado-Apaza, David Ccolque-Quispe, Nestor Antonio Gallegos Ramos, Denys Alberto Jaramillo-Peralta, Roxana Madueño-Portilla, José Alfredo Herrera Quispe, Aldo Alarcon-Sucasaca, Frank Arpita-Salcedo and Danger David Castellon-Apaza

Sustainability 2026, 18(3), 1639; https://doi.org/10.3390/su18031639 (registering DOI) - 5 Feb 2026

Abstract

Acute malnutrition affects 3.1% of children under five years of age in Amazonian communities in Peru, where limited access to health services constrains timely nutritional assessment. In this context, this study aimed to develop, implement, and evaluate NutriRadar, a mobile application for automated childhood nutritional classification based on the anthropometric standards of the World Health Organization (WHO). The application was developed using a waterfall software development methodology and implements the calculation of the Weight-for-Height Z-score (WHZ) from basic anthropometric variables (weight, height, age, and sex). NutriRadar was designed with offline functionality, deferred data synchronization, and compatibility with low-end mobile devices to support operational use in Amazonian settings. Field validation was conducted in two early childhood education institutions in Puerto Maldonado, Peru, and included anthropometric assessments of 75 children aged 3–4 years. The application demonstrated stable offline operation, response times suitable for clinical practice, and nutritional classification results equivalent to the WHO Anthro reference tool. NutriRadar represents a viable and reproducible digital automation solution for the operational application of a deterministic WHO anthropometric protocol, contributing to the reduction of operational errors and strengthening standardized nutritional assessment in resource-limited Amazonian contexts. Full article

(This article belongs to the Special Issue Interdisciplinary Explorations in Health and Healthcare: Addressing Complex Challenges for Sustainable Futures)

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29 pages, 942 KB

Open AccessReview

Connect-4 AI: A Comprehensive Taxonomy and Critical Review of Methods and Metrics

by Mohammed Alaa Ala’anzy, Akerke Madiyarova, Aidos Aigeldiyev, Raiymbek Zhanuzak and Omar Alnaseri

Symmetry 2026, 18(2), 293; https://doi.org/10.3390/sym18020293 (registering DOI) - 5 Feb 2026

Abstract

Connect-4, a solved two-player perfect-information game, offers a compact benchmark for artificial intelligence research due to its strategic depth and structural regularities, including board symmetries. This review presents a taxonomy-driven synthesis of Connect-4 AI research, encompassing game-theoretical foundations, classical search algorithms, reinforcement learning methods, explainable AI, and formal verification approaches. Analysis of search-, learning-, and hybrid-based methods reveals three dominant patterns: (i) classical search techniques prioritize determinism and efficiency but face scalability limits; (ii) reinforcement learning and neural approaches improve adaptability at the cost of interpretability and computational resources; and (iii) explainable and formally verified frameworks enhance transparency and reliability while imposing additional performance constraints. Recent advances in Connect-4 AI are driven less by raw performance gains than by strategic integration of efficiency, adaptability, interpretability, and robustness. Structuring the literature through a multidimensional taxonomy clarifies conceptual relationships, highlights underexplored research intersections, and points to emerging trends, including hybrid search–learning systems and explainable game intelligence. Overall, Connect-4 serves as a concise experimental domain for investigating fundamental challenges in game-playing AI, system design, and human–AI interaction. Full article

(This article belongs to the Special Issue Scheduling, Planning, Decision and Games in Intelligent Dynamic Robotics)

13 pages, 5709 KB

Open AccessArticle

Utilizing Structured Lasers for High-Precision Alignment in Astronomical Telescopes

by Han Gao, Chunyan Wang, Hao Yang, Zhixu Wu and Zhengyang Li

Universe 2026, 12(2), 43; https://doi.org/10.3390/universe12020043 (registering DOI) - 5 Feb 2026

Abstract

To address image degradation in optical telescopes with fast focal ratios—a problem caused by the misalignment of optical elements during assembly and observation—this study proposes a high-precision calibration method for image quality detection and correction. The method substitutes parallel laser beams for starlight to generate the incident wavefront required for calibration. Low-order aberrations resulting from system misalignment are calculated from the centroid coordinate offsets of laser spots on defocused planes, thereby enabling feedback-controlled alignment adjustments. Simulations and experiments were conducted on a single parabolic mirror system with a diameter (D) of 500 mm and a focal ratio of

F / 3

. The results indicate that for mirror tilt misalignments ranging from

- 2^{\circ}

+ 2^{\circ}

, the estimated error for the Zernike coefficients

Z_{4}

–

Z_{6}

is below

0.1 λ

(

λ = 650

nm). This accuracy meets the alignment requirements for telescopes with fast focal ratios and eliminates the need for large flat mirrors and clear night skies, which are traditionally required for outdoor calibration. Consequently, the method provides a low-cost, high-precision solution for the real-time calibration of telescopes at remote sites, such as those in Antarctica. Full article

(This article belongs to the Section Space Science)

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16 pages, 1057 KB

Open AccessArticle

Lost Fishing Gear Generated by Artisanal Fishing Along the Moroccan Mediterranean Coast: Quantities and Causes of Loss

by Nadia Jellal, Soria Azaaouaj, Mounia Touaf, Angela Rizzo, Giorgio Anfuso, Driss Nachite and Mustapha Aksissou

Sustainability 2026, 18(3), 1641; https://doi.org/10.3390/su18031641 (registering DOI) - 5 Feb 2026

Abstract

Lost fishing gear (LFG), also known as “ghost gear,” is a global environmental problem that constitutes a substantial portion of marine plastic pollution, resulting in significant socio-economic and ecological impacts. This paper estimates the quantities and primary causes of gear loss along the Moroccan Mediterranean coast through surveys conducted with 138 artisanal fishermen, covering a total of twelve different types of fishing gear. In total, 20,115 kg of fishing gear was lost, averaging 138.29 ± 120.69 kg boat⁻¹ year⁻¹. This represents approximately 28.97% of all gear used across 26,568 annual fishing trips (averaging 192 trips boat⁻¹ year⁻¹). The study period spanned from January 2022 to February 2023. Net-gear emerged as the most frequently lost category (65.91%). Substantial percentages of gear loss were also recorded for trammel nets (36.93%), gillnets (24.65%), and octopus jigs (23.41%). According to the responses of the fishermen surveyed, adverse meteorological and oceanographic conditions were the main cause of loss (57%), followed by marine animal attacks (19%) and fishing gear conflicts (14%). These findings are crucial for addressing data gaps on quantities of lost fishing gear released from the artisanal fisheries sector, and to contribute to the development of strategies to reduce this environmental problem. These include the regular maintenance of fishing gear, improved gear marking, the adoption of tracking devices to ensure the traceability of lost gear, and the implementation of awareness-raising and incentive programs for fishermen. These measures help to limit gear loss while promoting the sustainability of fishing activities and the protection of marine ecosystems. Full article

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28 pages, 2965 KB

Open AccessArticle

Experimental Study on Cemented Filling of Granular Pile in Caving Goaf: A Case Study

by Zhifu Dong, Jing Zhang, Fuqiang Ren and Fengyu Ren

Minerals 2026, 16(2), 174; https://doi.org/10.3390/min16020174 (registering DOI) - 5 Feb 2026

Abstract

For the metal deposits exploited by the open-stope subsequent filling method, the goaf roof is prone to large-scale caving when the stope ore is not fully mined. This further results in the accumulation of a thick layer of waste rock on the goaf floor due to the caving of surrounding rocks. In the treatment using cemented filling, it is essential to ensure that the filling slurry fully permeates into the granular pile, and that the granular-cemented backfill possesses sufficient strength to guarantee the production safety of adjacent stopes. Taking the caving goaf of Shirengou Iron Mine as the engineering background, the effects of slurry concentration, cement–tailing ratio, height of the granular pile, and particle size of the granular rock on seepage laws are investigated by means of a self-developed simplified filling test device. The filling slurry concentration that meets the on-site requirements for fluidity and permeability is thereby determined. Meanwhile, by prefabricating the granular-cemented backfill, the characteristics of the self-supporting capacity and strength of the backfill are studied, considering factors such as different slurry concentrations, cement–tailing ratios, and curing ages. The results indicate that the cement–tailing ratio exerts the least influence on the seepage law, yet it has the most significant impact on the strength of the granular-cemented backfill. When the cement–tailing ratio of the filling slurry ranges from 1:8 to 1:4 with a concentration of 68%, the filling slurry can completely seep and cement the waste rock layer. At this point, the granular-cemented backfill strength can reach 1~2 MPa, which satisfies the seepage and cementation requirements for the waste rock inside the caving goaf of Shirengou Iron Mine. Full article

29 pages, 1668 KB

Open AccessArticle

Structural Equation Modeling of Rider Wellbeing for Sustainable Transportation Planning of the Dubai Metro

by Bayan Abdel Rahman and Hamad S. J. Rashid

Sustainability 2026, 18(3), 1638; https://doi.org/10.3390/su18031638 (registering DOI) - 5 Feb 2026

Abstract

Public transportation systems in modern cities are transitioning from infrastructure- and technology-centric models to human-centered development. One emerging focus area is rider wellbeing, which integrates physical, emotional, and psychological dimensions of transit experiences. This study investigates rider wellbeing in the Dubai Metro system, leveraging a large-scale survey of 1409 users and analyzing the data using Generalized Structured Component Analysis (GSCA). The research identifies three latent constructs—Service Efficiency and Accessibility (SEA), Physical Environment and Passenger Comfort (PEPC), and Service Operations and Assurance (SOA)—as key determinants of rider wellbeing. The final model demonstrated strong fit (FIT = 0.639; AFIT = 0.621) and established a structural equation: Wellbeing = 0.216(SEA) + 0.513(SOA) + 0.318(PEPC) + ε. Findings reveal the need to prioritize speed, comfort, connectivity, and digital communication enhancements. Sustainable transportation planning is dependent on public transportation being not just available but also perceived as dependable, comfortable, and convenient to use. This study connects metro service characteristics to rider wellbeing and provides evidence to help guide service goals that promote rider retention and social sustainability. The study is unique in that it presents a latent-variable model that evaluates service features collectively (rather than individually) and converts them into interpretable planning levers using Dubai Metro survey data. By improving metro users’ experiences, the framework contributes to the sustainable mobility paradigm by enabling cities to maintain and expand public transportation use, an enabling solution for lowering vehicle dependency and associated negative impacts. This paradigm also benefits the environment by reducing emissions, increasing air quality, and promoting sustainable urban ecosystems. The proposed framework offers actionable insights for improving metro planning in Dubai and contributes broadly to global public transit development. Incorporating wellbeing into transportation planning supports smart city goals, enhances rider satisfaction, and fosters sustainable urban mobility. Full article

(This article belongs to the Section Sustainable Transportation)

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35 pages, 15027 KB

Open AccessArticle

Multi-Scale Drivers of Urban Vegetation Moisture Stress: A Comparative OLS and GWR Analysis in Makassar City, Indonesia

by Ramdan Pano Anwar, Muhammad Irfan, Arifuddin Akil, Chenyu Du and László Kollányi

Land 2026, 15(2), 267; https://doi.org/10.3390/land15020267 (registering DOI) - 5 Feb 2026

Abstract

Rapid urban expansion in tropical coastal cities has intensified vegetation moisture stress, compromising urban resilience and ecological stability. This study investigates the spatial drivers of the Moisture Stress Index (MSI) in Makassar City, Indonesia, by integrating biophysical indicators and land-use characteristics through multi-scale regression analyses. Utilizing dry-season satellite composites (May–August 2025), the research derived Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Normalized Difference Built-up Index (NDBI). MSI was modeled using Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) across 240 m, 480 m, and 960 m grids. Results indicate that MSI is highly sensitive to urban morphology and land-use configuration. High moisture stress was concentrated in commercial–industrial and dense residential zones characterized by extreme population densities exceeding 28,000 people/km² and elevated NDBI. In contrast, agricultural zones and open/green spaces provided significant cooling and moisture retention. Comparative performance analysis reveals that the local GWR model significantly outperformed the global OLS model, achieving a substantial reduction in AICc (−10,475.81) and resolving significant spatial autocorrelation to achieve random residuals (z-score = 1.55). The study further confirms that NDBI is the most robust biophysical predictor of MSI. Spatial heterogeneity analysis demonstrated that land-use influences are geographically contingent, with institutional areas showing varied effects based on campus design and canopy presence. These findings emphasize the necessity of scale-aware, climate-adaptive urban planning and demonstrate that GWR provides a high-fidelity tool for identifying neighborhood-level “micro-hotspots” overlooked by global modeling frameworks. Full article

15 pages, 1336 KB

Open AccessArticle

Dietary Cerium (Ammonium Ceric Nitrate) Promoted the Growth, Intestinal Digestive Enzyme Activity, and Positive Modulation of Intestinal Microbiota of Largemouth Bass (Micropterus salmoides)

by Yugui Zhang, Yunfeng Chen, Kaihui Xu, Xiaoqin Li and Xiangjun Leng

Animals 2026, 16(3), 506; https://doi.org/10.3390/ani16030506 (registering DOI) - 5 Feb 2026

Abstract

This study investigated the dietary effects of cerium (ammonium ceric nitrate, Ce (NH₄)₂(NO₃)₆) on the growth, serum antioxidant, intestinal digestive enzyme activity, tissue morphology and microbiota of Micropterus salmoides. Seven diets were designed with cerium supplementation of 0 (CON), 10 (Ce10), 20 (Ce20), 40 (Ce40), 60 (Ce60), 80 (Ce80) and 120 mg/kg (Ce120), respectively. Largemouth bass juveniles (initial weight of 16.89 ± 0.04 g) were fed with the above diets for 56 days. Compared with the control group, the weight gain of the Ce40 group increased by 14.4% and the feed conversion ratio decreased by 0.13 (p < 0.05). The Ce60, Ce80 and Ce120 groups showed significantly higher superoxide dismutase activity and lower malondialdehyde concentration compared with the control group (p < 0.05). Protease activity in the Ce20 and Ce40 groups and amylase activity in the Ce40 group were markedly elevated relative to the control group (p < 0.05). The proportion of Firmicutes was increased and the proportion of Proteobacteria was decreased by the addition of 10 mg/kg and 40 mg/kg Ce (Ce10 and Ce40 groups). In summary, dietary cerium supplementation can promote the growth, intestinal digestive enzyme activity, and positive modulation of the intestinal microbial flora of juvenile Micropterus salmoides. Based on the second-order polynomial regression analysis of WG or the FCR, the appropriate inclusion level of dietary cerium for juvenile largemouth bass was estimated to be 57.9 and 60.0 mg/kg, respectively. Full article

(This article belongs to the Section Animal Nutrition)

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