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15 pages, 1089 KB

Open AccessReview

Machine Learning in Transforming the Food Industry

by Malik A. Hussain, Md Imran H. Khan and Azharul Karim

Foods 2026, 15(1), 90; https://doi.org/10.3390/foods15010090 (registering DOI) - 29 Dec 2025

The continued evolution and advances in Artificial Intelligence (AI) technologies are offering innovative solutions and setting the futuristic trends in the food sector. The use of different Machine Learning (ML)-based models has demonstrated promising applications in the food processing industry. Processing operations such [...] Read more.

The continued evolution and advances in Artificial Intelligence (AI) technologies are offering innovative solutions and setting the futuristic trends in the food sector. The use of different Machine Learning (ML)-based models has demonstrated promising applications in the food processing industry. Processing operations such as drying, frying, cooking, heating, and baking are complex and challenged by multifaceted problems due to simultaneous heat, mass and momentum transport processes. The ML-based tools could potentially categorize each food material and efficiently predict its processing kinetics for optimization of the processing conditions. Furthermore, ML technologies have shown excellent applications in ensuring the traceability of food provenance and quality, enhancing the transparency and traceability from farm to fork, and providing consumers with more reliable product information. Overall, ML tools have untapped potential to identify and accelerate multiple development opportunities across the entire agri-food sector to improve productivity, profitability, and sustainability in the future. Full article

(This article belongs to the Special Issue Artificial Intelligence for the Food Industry)

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15 pages, 1803 KB

Open AccessArticle

High Thermoelectric Performance of Nanocrystalline Bismuth Antimony Telluride Thin Films Fabricated via Pressure-Gradient Sputtering

by Tetsuya Takizawa, Yuto Nakazawa, Keisuke Kaneko, Yoshiyuki Shinozaki, Cheng Zhang, Takumi Kaneko, Hiroshi Murotani and Masayuki Takashiri

Coatings 2026, 16(1), 35; https://doi.org/10.3390/coatings16010035 (registering DOI) - 29 Dec 2025

Abstract

Bismuth–telluride-based alloys are excellent thermoelectric materials for Peltier modules and thermoelectric generators (TEGs). Owing to the emergence of the Internet of Things (IoT), the demand for sensors has increased considerably and self-power supplies to sensors using TEGs are garnering attention. To apply TEGs [...] Read more.

Bismuth–telluride-based alloys are excellent thermoelectric materials for Peltier modules and thermoelectric generators (TEGs). Owing to the emergence of the Internet of Things (IoT), the demand for sensors has increased considerably and self-power supplies to sensors using TEGs are garnering attention. To apply TEGs to IoT sensors, the thermoelectric materials used must be sufficiently small and thin while exhibiting high thermoelectric performance. In this study, Bi_0.5Sb_1.5Te₃ thin films were prepared using a pressure-gradient sputtering system. The obtained films exhibit a nanocrystalline structure with a significantly smooth surface and no preferred crystal orientation. Because the Bi_0.5Sb_1.5Te₃ thin films exhibit a high Seebeck coefficient and low thermal conductivity, the in-plane dimensionless figure of merit is 0.98, which is one of the highest values reported for thermoelectric materials measured near 300 K. Furthermore, the phonon mean-free path is 0.19 nm, as estimated using the 3ω method and nanoindentation. This value is significantly smaller than the average crystallite size of the thin film, thus indicating that phonon scattering occurs more frequently via ternary-alloy scattering inside the crystallites than via boundary scattering at the crystallite boundaries. The results of this study can advance thin-film TEGs as a source of self-sustaining power for IoT systems. Full article

(This article belongs to the Section Thin Films)

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13 pages, 254 KB

Open AccessArticle

MixedPalletBoxes Dataset: A Synthetic Benchmark Dataset for Warehouse Applications

by Adamos Daios and Ioannis Kostavelis

Appl. Syst. Innov. 2026, 9(1), 14; https://doi.org/10.3390/asi9010014 (registering DOI) - 29 Dec 2025

Abstract

Mixed palletizing remains a core challenge in distribution centers and modern warehouse operations, particularly within robotic handling and automation systems. Progress in this domain has been hindered by the lack of realistic, freely available datasets for rigorous algorithmic benchmarking. This work addresses this [...] Read more.

Mixed palletizing remains a core challenge in distribution centers and modern warehouse operations, particularly within robotic handling and automation systems. Progress in this domain has been hindered by the lack of realistic, freely available datasets for rigorous algorithmic benchmarking. This work addresses this gap by introducing MixedPalletBoxes, a family of seven synthetic datasets designed to evaluate algorithm scalability, adaptability and performance variability across a broad spectrum of workload sizes (500–100,000 records) generated via an open source Python script. These datasets enable the assessment of algorithmic behavior under varying operational complexities and scales. Each box instance is richly annotated with geometric dimensions, material properties, load capacities, environmental tolerances and handling flags. To support dynamic experimentation, the dataset is accompanied by a FastAPI-based tool that enables the on-demand creation of randomized daily picking lists simulating realistic inbound orders. Performance is analyzed through metrics such as pallet count, volume utilization, item distribution per pallet and runtime. Across all dataset sizes, the distributions of the physical attributes remain consistent, confirming stable generation behavior. The proposed framework combines standardization, feature richness and scalability, offering a transparent and extensible platform for benchmarking and advancing robotic mixed palletizing solutions. All datasets, generation code and evaluation scripts are publicly released to foster open collaboration and accelerate innovation in data-driven warehouse automation research. Full article

8 pages, 518 KB

Open AccessArticle

Preliminary Experience with Oxygen-Enriched Oleic Matrix Breast-Shaped Dressings in Oncoplastic Breast Surgery

by Agostino Rodda, Stefano Bottosso, Andrea Lisa, Nadia Renzi, Elisa Bascialla, Giulia Benedetta Sidoti, Germana Lissidini and Giovanni Papa

Life 2026, 16(1), 51; https://doi.org/10.3390/life16010051 (registering DOI) - 29 Dec 2025

Abstract

Wound-related issues such as delayed healing and patient discomfort remain common challenges in oncoplastic breast surgery and may negatively affect early postoperative recovery. This single-centre, retrospective, within-patient study explored the feasibility and safety of a breast-shaped polyurethane and polyester dressing impregnated with an [...] Read more.

Wound-related issues such as delayed healing and patient discomfort remain common challenges in oncoplastic breast surgery and may negatively affect early postoperative recovery. This single-centre, retrospective, within-patient study explored the feasibility and safety of a breast-shaped polyurethane and polyester dressing impregnated with an oxygen-enriched oleic matrix, designed to provide a controlled, low-level release of reactive oxygen species involved in physiological tissue repair. Sixty patients undergoing unilateral lumpectomy with contralateral breast remodelling were included. The advanced dressing was applied to the oncologic breast, while standard premedicated patches were used on the contralateral side, allowing each patient to serve as her own control. Early postoperative outcomes, including wound dehiscence, infection, delayed healing, and qualitative user experience, were assessed descriptively over the first postoperative month. The oxygen-enriched oleic matrix dressing was well tolerated and associated with good skin hydration, comfort, and ease of use. No infections, hematomas, or reoperations were observed, and no relevant differences in early complication patterns emerged between the treated and control sides. Both patients and healthcare personnel reported favourable handling characteristics and comfort, with no device-related adverse events. These preliminary, hypothesis-generating findings suggest that oxygen-enriched oleic matrix breast-shaped dressings are a feasible and safe option for early postoperative wound management in oncoplastic breast surgery. Prospective, adequately powered multicentre studies are warranted to further investigate their potential role within standardized postoperative care pathways. Full article

(This article belongs to the Section Medical Research)

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40 pages, 486 KB

Open AccessArticle

‘For We Take Our Homeland with Us, However We Change Our Sky’ — Loss, Maintenance and Identity in Early Scottish Immigrants’ Correspondence from New Zealand

by Sarah van Eyndhoven

Languages 2026, 11(1), 6; https://doi.org/10.3390/languages11010006 (registering DOI) - 29 Dec 2025

Abstract

This contribution explores transgenerational language change in a historical migrant community by qualitatively examining the correspondence of first- and second-generation Scottish immigrants coming to New Zealand in the nineteenth century. Taking a microsocial approach, the letters of a migrant family and one other [...] Read more.

This contribution explores transgenerational language change in a historical migrant community by qualitatively examining the correspondence of first- and second-generation Scottish immigrants coming to New Zealand in the nineteenth century. Taking a microsocial approach, the letters of a migrant family and one other migrant are explored for language maintenance and shift, to identify whether Scots language features were lost altogether or continued to be utilised for specific social, personal and stylistic goals, despite the English-dominant space that the migrants operated in. In tandem, the adoption of early New Zealand English (NZE) and te reo Māori lexis is analysed, to identify differences in usage patterns that might point to different degrees of integration and mobility. Finally, inter-writer and inter-generational differences are examined in relation to the mobility and social networks of the correspondents, to consider how this might contribute to any variation observed. For the investigation, manuscript letters were digitised, and relevant features identified, extracted and discursively analysed. Results show the continuation of heritage features through a combination of style-oriented goals and learned letter-writing practices, while the adoption of new lexis is shown to occur within specific semantic domains that reflect the social mobility of the migrants. However, language maintenance and shift are not uniform between the writers, elucidating the highly variable experiences of migrants, even within the same family. Rather, contact-induced language changes are sensitive to minute differences across individuals, underpinning the value of nuanced explorations of historical migration and language change. Full article

(This article belongs to the Special Issue From Migrant to Heritage Languages: Transgenerational Language Change in Diasporic Communities)

4 pages, 145 KB

Open AccessEditorial

Microalloying in Ferrous and Non-Ferrous Alloys

by Minghui Cai and Ge Zhou

Metals 2026, 16(1), 39; https://doi.org/10.3390/met16010039 (registering DOI) - 29 Dec 2025

Abstract

Under the dual-carbon goals of achieving carbon peak and neutrality, lightweighting of materials has emerged as a critical strategy to reduce energy consumption and greenhouse gas emissions across industries [...] Full article

(This article belongs to the Special Issue Microalloying in Ferrous and Non-ferrous Alloys)

14 pages, 1191 KB

Open AccessArticle

Tissue Inhibitor of Metalloproteinases-2 (TIMP2) Affects Allograft Function in Incident Kidney Transplant Recipients

by Tobias M. Mattesen, Subagini Nagarajah and Martin Tepel

Kidney Dial. 2026, 6(1), 3; https://doi.org/10.3390/kidneydial6010003 (registering DOI) - 29 Dec 2025

Abstract

Background: Matrix metalloproteinases (MMPs) and their inhibitors, tissue inhibitors of metalloproteinases (TIMPs), regulate the extracellular matrix. This study examined messenger RNA transcripts of TIMP2 before and after kidney transplantation. Methods: Transcripts were measured in peripheral blood mononuclear cells from 105 kidney transplant recipients, [...] Read more.

Background: Matrix metalloproteinases (MMPs) and their inhibitors, tissue inhibitors of metalloproteinases (TIMPs), regulate the extracellular matrix. This study examined messenger RNA transcripts of TIMP2 before and after kidney transplantation. Methods: Transcripts were measured in peripheral blood mononuclear cells from 105 kidney transplant recipients, including AB0-incompatible, AB0-compatible, and deceased donor transplantation patients. Quantitative real-time polymerase chain reaction was utilized. Results: Kidney transplant recipients (72 male; 33 female) were a median of 55 (44–63) years old. The median (interquartile range) of pretransplant TIMP2 transcripts was 0.68 (0.50–0.87) in kidney transplant recipients. In total, 9 out of 72 patients (13%) showed delayed graft function, i.e., need for dialysis within 1 week after transplantation. Preoperative TIMP2 transcripts were significantly lower in kidney transplant recipients who experienced delayed graft function compared to patients with immediate graft function (0.40 (0.32–0.62) vs. 0.68 (0.56–0.87); p = 0.01). There was no association between TIMP2 transcripts and age or gender. TIMP2 median transcripts were 0.73 (0.58–0.88) on the first postoperative day. TIMP2 transcripts were similar on the first postoperative day in patients with delayed graft function and immediate graft function. Conclusions: Preoperative TIMP2 transcripts were lower in patients with delayed allograft function. Future investigations are needed to establish the role of TIMP2 transcripts in transplant pathophysiology. Full article

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35 pages, 440 KB

Open AccessArticle

Transposition and Implementation of European Union Renewable Energy Legislation in France, Italy, and Germany: A Regulatory Perspective and a Comprehensive Analysis of Opportunities and Challenges

by Ana Maria Fagetan

Laws 2026, 15(1), 3; https://doi.org/10.3390/laws15010003 (registering DOI) - 29 Dec 2025

Abstract

This article provides a detailed comparative analysis of the transposition and implementation of the Renewable Energy Directives II and III (RED II and RED III), REPowerEU Plan, and the ‘Fit for 55’ package in France, Italy, and Germany. The analysis highlights the objectives, [...] Read more.

This article provides a detailed comparative analysis of the transposition and implementation of the Renewable Energy Directives II and III (RED II and RED III), REPowerEU Plan, and the ‘Fit for 55’ package in France, Italy, and Germany. The analysis highlights the objectives, key legislative provisions, and national-scale achievements, challenges, advantages, and disadvantages—including implications for investment conditions and renewable energy financing mechanisms—associated with these pivotal European Union legislative frameworks, which, to a certain extent, induced a paradigm shift with varying degrees of impact in every Member State. The work is divided into four parts that follow this brief introductory outline of the problem. The introduction presents legal developments in renewable energy law in the European Union. The second part offers a comprehensive and in-depth examination of the European Union’s renewable energy regulatory framework and research gaps that hinder doctrinal tensions within the EU’s renewable energy legislative framework. In the third part, we analyze the transposition and implementation of each mentioned directive in the selected countries. The last part highlights commonalities, divergences, challenges, best practices, and lessons learned from each nation’s approach. This comparative analysis predicts that implementation success is inversely linked to administrative divergence, with France’s centralized legal system facilitating effective bureaucratic streamlining and higher predicted deployment, while the fragmented governance structures of Germany and Italy serve as structural impediments that critically undermine the EU’s acceleration mandate. Full article

11 pages, 1338 KB

Open AccessArticle

Application of FDTD Method in the Calculation of Lightning Propagation Effects on Mixed Terrain of Land and Sea

by Fang Xiao, Qiming Ma, Xiao Zhou, Jiajun Song, Jiaquan Wang and Linsen Jiang

Information 2026, 17(1), 20; https://doi.org/10.3390/info17010020 (registering DOI) - 29 Dec 2025

Abstract

Based on the finite-difference time-domain (FDTD) method, this study investigates the propagation effects of lightning electromagnetic fields over mixed sea–land paths. A self-developed FDTD computational model is employed, which takes into account the influence of the Earth–ionosphere waveguide structure on the radiation field [...] Read more.

Based on the finite-difference time-domain (FDTD) method, this study investigates the propagation effects of lightning electromagnetic fields over mixed sea–land paths. A self-developed FDTD computational model is employed, which takes into account the influence of the Earth–ionosphere waveguide structure on the radiation field propagation. Through numerical simulations, the waveforms of the vertical electric field and azimuthal magnetic field of the lightning radiation during mixed-path propagation are obtained. The results demonstrate that under long-distance propagation conditions of 50 km, the discontinuity between land and sea media significantly distorts the electric field waveform, while the influence on the magnetic field waveform is negligible. This study provides a reliable numerical basis for analyzing the propagation characteristics of lightning radiation fields in complex terrain and offers valuable insights for lightning location and electromagnetic environment assessment. Full article

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15 pages, 2819 KB

Open AccessArticle

Research on Seismic and Self-Centering Performance of SMAF-ECC Prefabricated Self-Centering Frame Joints Based on Finite Element Simulation

by Yan Cao, Qing Wu and Zhao Yang

Materials 2026, 19(1), 110; https://doi.org/10.3390/ma19010110 (registering DOI) - 29 Dec 2025

Abstract

To address poor seismic performance, large residual displacement, and insufficient self-centering capacity of prefabricated frame joints in building industrialization, this study proposes a novel self-centering prefabricated frame joint reinforced with shape memory alloy fiber (SMAF)–engineered cementitious composite (ECC) composites (SMAF-ECC). A validated finite [...] Read more.

To address poor seismic performance, large residual displacement, and insufficient self-centering capacity of prefabricated frame joints in building industrialization, this study proposes a novel self-centering prefabricated frame joint reinforced with shape memory alloy fiber (SMAF)–engineered cementitious composite (ECC) composites (SMAF-ECC). A validated finite element model of the proposed joint was established using ABAQUS, with comparative analyses conducted against conventional reinforced concrete (RC) and ECC-strengthened (RC-E) joint models to explore the effect of SMAF volume content on seismic performance. Results show that replacing the joint core zone concrete with SMAF-ECC significantly enhances the joint’s seismic and self-centering capabilities, reducing residual displacement and optimizing hysteretic behavior. SMAF volume content is a key factor affecting performance, with an optimal value identified and excessive content leading to fiber agglomeration and degraded self-centering ability. This study provides a feasible solution to improve the seismic resilience of prefabricated frame joints, laying a foundation for the application of SMAF-ECC in prefabricated structures. Full article

(This article belongs to the Section Construction and Building Materials)

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15 pages, 699 KB

Open AccessArticle

Optimization of Solvent Extraction Method for Stilbenoid and Phenanthrene Compounds in Orchidaceae Species

by David J. Machate, Teresinha Gonçalves da Silva, António B. Mapossa and Maria A. M. Maciel

AppliedChem 2026, 6(1), 1; https://doi.org/10.3390/appliedchem6010001 (registering DOI) - 29 Dec 2025

Abstract

This study introduces an optimized and selective extraction methodology using dichloromethane/methanol (DCM/MeOH, 95:5, v/v) in combination with accelerated solvent extraction (ASE) for the targeted stilbenoid and phenanthrene derivatives from five orchid species: Cattleya nobilior (root), Cymbidium defoliatum (root and bulb), [...] Read more.

This study introduces an optimized and selective extraction methodology using dichloromethane/methanol (DCM/MeOH, 95:5, v/v) in combination with accelerated solvent extraction (ASE) for the targeted stilbenoid and phenanthrene derivatives from five orchid species: Cattleya nobilior (root), Cymbidium defoliatum (root and bulb), Dendrobium phalaenopsis (stem), Encyclia linearifolioides (leaf), and Phalaenopsis aphrodite (root). Sequential extraction was performed with hexane, followed by DCM/MeOH (95:5 and 1:1, v/v) under controlled temperatures (70 °C for hexane, 100 °C for DCM/MeOH), using three static cycles per stage. Chemical profiling by high-performance liquid chromatography with a diode-array-detector and tandem mass spectrometry (HPLC-DAD-MS/MS) enabled the identification of twenty specialized metabolites—seven stilbenoids and thirteen phenanthrenes—several reported here for the first time, including crepidatuol B, dendrosinen D, and coeloginanthridin. The analytical method showed excellent separation of structurally related phenolic compounds, demonstrating the efficiency of the extraction protocol and the selectivity of the solvent system. Many of the identification metabolites are known for cytotoxic, antioxidant, anti-inflammatory, and metabolic regulatory properties, while newly detected compounds remain unexplored and present promising candidates for future biological evaluation. The broad distribution of these metabolites across the studied orchids enhances the current understanding of their phytochemical diversity and suggests chemotaxonomic relevance within the Orchidaceae family. Importantly, the extraction strategy requires minimal plant material, offering ecological advantages when working with rare or endangered species. Overall, this environmentally conscious extraction approach provides a robust platform for metabolic discovery and supports future research in natural products chemistry, plant ecology, drug discovery, structure–activity relationships studies and biotechnological applications. Full article

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19 pages, 551 KB

Open AccessArticle

Structural Analysis of Psychological Resources Underpinning Self-Perceived Transformational Leadership

by Masao Saruhashi, Runjie Li and Noriyuki Kida

Adm. Sci. 2026, 16(1), 16; https://doi.org/10.3390/admsci16010016 (registering DOI) - 29 Dec 2025

Abstract

This study conceptualizes transformational leadership not as an evaluation by others but as the leader’s self-recognition—self-perceived transformational leadership (STFL)—and examines the roles of two psychological resources, Vigor and challenge-oriented coping (Overcoming), together with subjective well-being (SWB). Using validated scales, we surveyed approximately 600 [...] Read more.

This study conceptualizes transformational leadership not as an evaluation by others but as the leader’s self-recognition—self-perceived transformational leadership (STFL)—and examines the roles of two psychological resources, Vigor and challenge-oriented coping (Overcoming), together with subjective well-being (SWB). Using validated scales, we surveyed approximately 600 employees from large Japanese corporations. After confirming the validity of a four-factor measurement model via confirmatory factor analysis (CFA), we tested structural relationships using structural equation modeling (SEM) with maximum likelihood estimation; indirect effects were assessed with Monte Carlo confidence intervals. The results showed that the strongest direct effect on STFL was from Overcoming, with a moderate and significant direct effect from Vigor. In contrast, the direct effect of SWB on STFL was small and marginal; however, the indirect effects of Vigor and Overcoming on STFL via SWB were small but significant, indicating a pattern of partial mediation. Overall, the primary pathway to STFL is the direct effect of psychological resources, while SWB contributes secondarily as an affective route. These findings refine the dynamics proposed by the broaden-and-build framework: positive affect broadens behavioral repertoires and fosters resource formation, and those resources, in turn, are reflected in self-recognition as a transformational leader—yet with a dominance of the direct resource pathway. Given the cross-sectional, self-report design and the focus on employees of large Japanese firms, additional longitudinal and intervention studies are needed to enhance the generalizability of the conclusions. Full article

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33 pages, 1685 KB

Open AccessSystematic Review

Do Soil Microbes Drive the Trade-Off Between C Sequestration and Non-CO₂ GHG Emissions in EU Agricultural Soils? A Systematic Review

by Arianna Latini, Luciana Di Gregorio, Elena Valkama, Manuela Costanzo, Peter Maenhout, Marjetka Suhadolc, Francesco Vitali, Stefano Mocali, Alessandra Lagomarsino and Annamaria Bevivino

Sustainability 2026, 18(1), 319; https://doi.org/10.3390/su18010319 (registering DOI) - 29 Dec 2025

Abstract

The role of soil microbial communities in soil organic matter (OM) decomposition, transformation, and the global nitrogen (N) and carbon (C) cycles has been widely investigated. However, a comprehensive understanding of how specific agricultural practices and OM inputs shape microbial-driven processes across different [...] Read more.

The role of soil microbial communities in soil organic matter (OM) decomposition, transformation, and the global nitrogen (N) and carbon (C) cycles has been widely investigated. However, a comprehensive understanding of how specific agricultural practices and OM inputs shape microbial-driven processes across different European pedoclimatic conditions is still lacking, particularly regarding their effectiveness in mitigating greenhouse gas (GHG) emissions. This systematic review synthesizes current knowledge on the biotic mechanisms underlying soil C sequestration and GHG reduction, emphasizing key microbial processes influenced by land management practices. A rigorous selection was applied, resulting in 16 eligible articles that addressed the targeted outcomes: soil microorganism biodiversity, including microbiome composition and other common Biodiversity Indexes, C sequestration and non-CO₂ GHG emissions (namely N₂O and CH₄ emissions), and N leaching. The review highlights that, despite some variations across studies, the application of OM enhances soil microbial biomass (MB) and activity, boosts soil organic carbon (SOC), and potentially reduces emissions. Notably, plant richness and diversity emerged as critical factors in reducing N₂O emissions and promoting carbon storage. However, the lack of methodological standardization across studies hinders meaningful comparison of outcomes—a key challenge identified in this review. The analysis reveals that studies examining the simultaneous effects of agricultural management practices and OM inputs on soil microorganisms, non-CO₂ GHG emissions, and SOC are scarce. Standardized studies across Europe’s diverse pedoclimatic regions would be valuable for assessing the benefits of OM inputs in agricultural soils. This would enable the identification of region-specific solutions that enhance soil health, prevent degradation, and support sustainable and productive farming systems. Full article

(This article belongs to the Special Issue Soil Fertility and Plant Nutrition for Sustainable Cropping Systems)

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25 pages, 1727 KB

Open AccessArticle

AI-Augmented Digital Collaboration Improvement Framework for Sustainable Digital Transformation

by Inga Stankevice and Jo Merten Egerland

Adm. Sci. 2026, 16(1), 15; https://doi.org/10.3390/admsci16010015 (registering DOI) - 29 Dec 2025

Abstract

Literature on digital collaboration often focuses on individual aspects, but rarely combines them into a unified, practical and sustainability-friendly management tool. The paper fills this critical gap by presenting a comprehensive framework for enhancing digital collaboration, integrating AI, and aligning digital collaboration strategies [...] Read more.

Literature on digital collaboration often focuses on individual aspects, but rarely combines them into a unified, practical and sustainability-friendly management tool. The paper fills this critical gap by presenting a comprehensive framework for enhancing digital collaboration, integrating AI, and aligning digital collaboration strategies with broader sustainability objectives. The framework includes four phases and 31 factors categorised into four dimensions. The framework is validated through a case study that combines qualitative (expert interviews) and quantitative (employee survey) approaches, as well as Mayring’s content analysis and the CARL analytical framework. The study reveals that fragmented tool use undermines collaboration maturity across all dimensions, while the integration of AI enhances collaboration outcomes and mitigates digital fatigue. A dual-core collaboration setup contributes to stronger strategic alignment, with the monitoring benefits framework facilitating sustainable improvement tracking. This way, the framework addresses digital fragmentation, tool redundancy, and deficient digital cooperation, leading to increased digital collaboration maturity and alignment with sustainability objectives. The proposed framework offers theoretical, managerial, and societal value by bridging the gap between digital transformation theory and sustainable organisational practice. Full article

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25 pages, 19297 KB

Open AccessArticle

Microstructure of Cobalt Alloy Coating Manufactured by LVOF Process: Spray Distance and Stoichiometric Gase Ratio Effect

by Fernando Juárez-López, Rubén Cuamatzi-Meléndez, Melquisedec Vicente-Mendoza and Ángel de Jesús Morales-Ramírez

Coatings 2026, 16(1), 34; https://doi.org/10.3390/coatings16010034 (registering DOI) - 29 Dec 2025

Abstract

This work presents a microstructural characterization methodology for Diamalloy 3001 metallic powders sprayed onto Inconel 718 substrates by flame combustion. Hence, two flame stoichiometric (acetylene/oxygen) rates and specified thermal spray distances were performed in order to study their effects on the developed microstructure [...] Read more.

This work presents a microstructural characterization methodology for Diamalloy 3001 metallic powders sprayed onto Inconel 718 substrates by flame combustion. Hence, two flame stoichiometric (acetylene/oxygen) rates and specified thermal spray distances were performed in order to study their effects on the developed microstructure of the sprayed coatings. The morphology and chemical composition of the developed coatings were evaluated with microscopy, and a comparison of microstructural quality was performed. The findings indicated that spray distance affected coating quality, which is composed of morphology-type lamellar with elongated features, while gravel-like morphologies related to semi-solid powder particles were observed. Moreover, X-ray diffraction analyses established that chemical content of phases rich in oxides increased proportionally with spray distance. Vickers hardness measures and three-point bending tests were correlated with the microstructure and spray distance. These characteristics show that cobalt-based coatings could be proposed for commercial applications requiring high mechanical resistance. Full article

(This article belongs to the Special Issue Recent Advances in Research and Application of Organic and Inorganic Coatings)

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28 pages, 1596 KB

Open AccessReview

Plant-Derived Bioactive Compounds: One Health Perspective

by Ana C. Gonçalves, Ana R. Pinto, André Cima, Eva Olo-Fontinha, Joana C. L. Martins, Juliana Garcia, André Lemos, Maria José Saavedra, Maria Manuela Pintado and Maria José Alves

Appl. Sci. 2026, 16(1), 327; https://doi.org/10.3390/app16010327 (registering DOI) - 29 Dec 2025

Abstract

This review, within the One Health framework, compiles information on plant-derived bioactive compounds and emphasises their multifunctional role in improving environmental, animal, and human health. These compounds support sustainable health and ecological stability by influencing biological and environmental processes. Data from literature research [...] Read more.

This review, within the One Health framework, compiles information on plant-derived bioactive compounds and emphasises their multifunctional role in improving environmental, animal, and human health. These compounds support sustainable health and ecological stability by influencing biological and environmental processes. Data from literature research are combined to explain the mechanisms and potential uses of different key bioactive compounds. Mechanistic insights focus on their capacity to regulate oxidative stress, inflammation, and microbial balance, linking these effects to therapeutic benefits in human health, enhanced animal productivity, and environmental sustainability. These compounds show antioxidant, anti-inflammatory, antimicrobial, and metabolic activities, helping prevent chronic diseases, strengthen immunity, and reduce reliance on antibiotics and pollution. Examples like quercetin, resveratrol, and curcumin demonstrate their roles in modulating inflammatory and metabolic pathways to foster sustainable health and ecological balance. Bioactive compounds are linked to the One Health strategy, providing benefits across biological systems. Nonetheless, challenges such as variability, bioavailability, and standardization remain. Future directions should aim to develop sustainable extraction and formulation methods, leverage omics technologies and artificial intelligence for discovery and characterization, and foster industry partnerships to validate these compounds and secure global regulatory approval. Full article

(This article belongs to the Special Issue Functional Foods and Natural Products: Bioactive Compounds and Beneficial Effects on Health—3rd Edition)

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21 pages, 5377 KB

Open AccessArticle

Research on the Supply-Demand Matching of Blue–Green Spaces in Oasis Cities in Arid Regions: A Case Study of the Three-Ring Area in Urumqi

by Lin Gao, Alimujiang Kasimu and Yan Zhang

Urban Sci. 2026, 10(1), 12; https://doi.org/10.3390/urbansci10010012 (registering DOI) - 29 Dec 2025

Abstract

Blue–green spaces are essential for mitigating urban heat islands. The matching between their supply and demand affects the fairness and effectiveness of urban cooling facilities. This study focuses on the third ring area of Urumqi, Xinjiang, China. Cooling supply indicators and cooling demand [...] Read more.

Blue–green spaces are essential for mitigating urban heat islands. The matching between their supply and demand affects the fairness and effectiveness of urban cooling facilities. This study focuses on the third ring area of Urumqi, Xinjiang, China. Cooling supply indicators and cooling demand indicators for blue–green spaces are established. Using coupling coordination and bivariate spatial autocorrelation models, it evaluates the cooling supply-demand relationship during 2010–2020. Results show that: (1) There is a “suburban cold sources dominated, urban supply turned positive” pattern in the cooling supply of Urumqi’s blue–green spaces. (2) Cooling demand has a significant “dual-core spatial separation”. The physical demands are concentrated in the high-temperature patches around the city, while the social demands are mainly distributed in the core area of the urban district. (3) There is a severe supply–demand spatial mismatch, with extremely low coupling coordination. The core issue is that high-supply cropland cold sources are far from the high-social-demand urban area. This study provides an important scientific basis for formulating effective cooling strategies for oasis cities through the analysis of the supply and demand matching of blue and green space. It uniquely helps safeguard ecological security and residents’ health in arid-zone cities. Full article

(This article belongs to the Special Issue Leveraging Socioeconomic and Geospatial Data for Understanding Urban–Rural Continuum)

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15 pages, 4796 KB

Open AccessArticle

Atomistic Simulations of Individual Amphiphilic Carbosilane Dendrimers with –(OCH₂CH₂)_n–OCH₃ Terminal Groups in Hydrophilic and Hydrophobic Environments and at Interfaces

by Andrey O. Kurbatov, Kirill A. Litvin, Iurii Iu. Grishin, Nikolay K. Balabaev and Elena Yu. Kramarenko

Polymers 2026, 18(1), 92; https://doi.org/10.3390/polym18010092 (registering DOI) - 28 Dec 2025

Abstract

Amphiphilic dendrimers represent a promising class of nanoscale building blocks for functional materials, yet their conformational behavior, solvation, and interfacial activity remain incompletely understood. In this work, we employ atomistic molecular dynamics simulations to investigate G2–G4 carbosilane dendrimers functionalized with ethylene glycol terminal [...] Read more.

Amphiphilic dendrimers represent a promising class of nanoscale building blocks for functional materials, yet their conformational behavior, solvation, and interfacial activity remain incompletely understood. In this work, we employ atomistic molecular dynamics simulations to investigate G2–G4 carbosilane dendrimers functionalized with ethylene glycol terminal groups of two lengths—R1 (one ethylene glycol unit) and R3 (three units)—in water, toluene, and at fluid interfaces (water–toluene and water–air). Both types of dendrimers adopt compact, nearly spherical conformations in water but swell significantly (~83% in volume for G4) in toluene, a good solvent for the hydrophobic core. At the water–toluene interface, the dendrimers remain fully solvated in the toluene phase and show no surface activity. In contrast, at the water–air interface, they adsorb and adopt a mildly anisotropic, biconvex conformation, with a modest deformation. The total number of hydrogen bonds is reduced by ~50% compared to bulk water. Notably, the R3 dendrimers form more hydrogen bonds overall due to their higher oxygen content, which may contribute to the enhanced stability of their monolayers observed experimentally. These results demonstrate how dendrimer generation as well as terminal group length and hydrophilicity finely tune dendrimer conformation, hydration, and interfacial behavior, which are key factors for applications in nanocarriers, interfacial engineering, and self-assembled materials. The validated simulation protocol provides a robust foundation for future studies of multi-dendrimer systems and monolayer formation. Full article

(This article belongs to the Section Polymer Physics and Theory)

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8 pages, 812 KB

Open AccessArticle

Injuries of the Posterior Tracheal Wall: Insights from a High-Volume Single-Centre Experience

by Lavinia Gatteschi, Antonio Burlone, Stefano Bongiolatti, Simone Tombelli, Giovanni Mugnaini, Luca Voltolini and Alessandro Gonfiotti

J. Clin. Med. 2026, 15(1), 245; https://doi.org/10.3390/jcm15010245 - 28 Dec 2025

Abstract

Background: Major airway injuries, regardless of whether their aetiology is traumatic or iatrogenic, are rare but potentially fatal. In selected cases, surgery plays a key role; however, it has to be performed by highly experienced professionals in emergency settings. Methods: We [...] Read more.

Background: Major airway injuries, regardless of whether their aetiology is traumatic or iatrogenic, are rare but potentially fatal. In selected cases, surgery plays a key role; however, it has to be performed by highly experienced professionals in emergency settings. Methods: We reviewed all surgical procedures involving the trachea which were performed at our institution in the last 5 years (365 procedures). We report here our experiences with major airway injuries, both traumatic and iatrogenic (19 procedures). All patients, including individuals from within our hospital and from other peripheral centres, were treated in an emergency setting within 12 h of correct diagnosis. Results: The location and extent of tracheal lesions can be different in every patient. After a proper evaluation with CT scan and bronchoscopy, we approached all our cases of tracheal injuries with a cervicotomy, using, in some selected cases, an endoscopic camera to better visualise lesions that involved the carina. However, in extremely severe cases, such as one we report here, where multiple repair attempts fail and tissue viability is compromised, demolitive surgery by means of posterolateral thoracotomy may represent the only remaining therapeutic option. Conclusions: Surgery on tracheal injuries is complex, highly specialised, and time-dependent. In selected cases, it has to be performed quickly by highly qualified professionals after proper evaluation in an emergency setting. Every airway injury differs in its location, extent, aetiology, and clinical presentation, and there is no unanimous consensus on standardising treatment. Only high-volume centres with highly experienced professionals can guarantee correct management of this rare but life-threatening event. Full article

(This article belongs to the Special Issue Clinical Update on Thoracic Trauma)

23 pages, 1258 KB

Open AccessFeature PaperArticle

Correlating Feed Characteristics and Catalyst Properties with Fluid Catalytic Cracking Performance

by Dicho Stratiev, Ivelina Shiskova, Mihail Ivanov, Iliyan Kolev, Veselina Bureva, Simeon Ribagin and Krassimir Atanassov

Processes 2026, 14(1), 110; https://doi.org/10.3390/pr14010110 - 28 Dec 2025

Abstract

Feedstock quality has been proven to be the single variable that most affects fluid catalytic cracking (FCC) unit performance, but catalyst characteristics have also been reported in the literature to have a considerable effect on cracking process performance. How these two main variables [...] Read more.

Feedstock quality has been proven to be the single variable that most affects fluid catalytic cracking (FCC) unit performance, but catalyst characteristics have also been reported in the literature to have a considerable effect on cracking process performance. How these two main variables of the FCC process complement each other in the search for ways to optimize the performance of the FCC unit is the subject of current research. Twenty-one feedstocks with K_W-characterizing factors ranging from 11.08 to 12.06, Conradson carbon contents ranging from 0.05 to 12.8 wt.%, and nitrogen contents ranging from 800 to 3590 ppm (wt/wt) (basic nitrogen from 172 to 1125 ppm (wt/wt)) were cracked on 21 catalysts with micro-activity between 67% and 76% (wt/wt) in a laboratory-based advanced catalytic evaluation (ACE) unit at a reaction temperature of 527ׄ °C, catalyst–to-oil ratios between 3.5 and 12.0 wt/wt, and a catalyst time on stream of 30 s. Some of the feeds and catalysts tested in the laboratory FCC ACE unit were also examined in a commercial short-contact-time FCC unit resembling a UOP side-by-side design. It was found that conversion can be very well predicted in both the laboratory ACE and the commercial FCC units using multiple linear correlations developed in this work from information about the following feed properties: K_W-characterizing factor, nitrogen content, and micro-activity of the catalyst. The coke on the catalyst that controls the catalyst-to-oil ratio and the regenerator temperature in the commercial FCC unit could be calculated using the correlations developed in this work for the laboratory ACE and commercial FCC units, based on feed characteristics and catalyst micro-activity. Due to the greater slope of the Δ coke/Δ micro-activity dependence observed in the ACE FCC unit, the more active catalysts show weaker results compared to the less active catalysts at a constant coke yield. In contrast, catalysts with higher activity are preferable for operation in the commercial FCC plant because they provide higher conversion at the same coke yield due to the lower slope of the Δ coke/Δ micro-activity relationship. Full article

(This article belongs to the Section Catalysis Enhanced Processes)

15 pages, 1717 KB

Open AccessArticle

Community-Level Phenotypic Adaptations of Small Mammals Under Rain-Shadow Dynamics in Baima Snow Mountain, Yunnan

by Yongyuan Li, Guangzhi Chen, Mengru Xie, Yihao Fang, Feng Qin and Wenyu Song

Animals 2026, 16(1), 91; https://doi.org/10.3390/ani16010091 (registering DOI) - 28 Dec 2025

Abstract

The adaptation strategies of species to local environments are reflected in phenotypic variations, which could be expressed as trait patterns across the community level. Here, we compiled a dataset of small mammal traits to evaluate the classic ecological rules and to assess predictions [...] Read more.

The adaptation strategies of species to local environments are reflected in phenotypic variations, which could be expressed as trait patterns across the community level. Here, we compiled a dataset of small mammal traits to evaluate the classic ecological rules and to assess predictions related to drought resistance. In June 2017, July 2023, and May–June 2024, a field survey was conducted in Baima Snow Mountain, southwest China, using standardized methods to capture small mammals. Traits potentially corresponding to variations in temperature, productivity, and water availability were measured in the field or calculated in the laboratory. We applied ordinary least squares (OLS) linear regressions to determine the community-level trait variations along the gradients of environmental factors influenced by rain-shadow effects of the mountain system. Results showed that (1) body size decreased with increasing temperature, aligning well with conventional prediction; (2) the proportion of appendage size attributable to allometry decreased with temperature but increased slightly with productivity, thereby violating Allen’s rule while being partly consistent with the resource rule; (3) the renal features did not support the expected negative association concerning water availability but its converse, which may be explained by microhabitat conditions and broad-scale zoogeographic influences within the local community. We conclude that community-level phenotypic variations in small mammals result from complex influences, including climate, productivity, habitat characteristics, and adaptive strategies operating at both micro and macro scales. Full article

(This article belongs to the Section Mammals)

32 pages, 10721 KB

Open AccessReview

From Waste to Value: A Comprehensive Review of Perovskite Solar Cell Recycling Technologies

by Yaoxu Gao, Baheila Jumayi, Peng Wei, Chenxi Song, Shuying Wang and Xiangqian Shen

Crystals 2026, 16(1), 24; https://doi.org/10.3390/cryst16010024 - 28 Dec 2025

Abstract

The rapid progress of perovskite solar cells (PSCs) has established them as a groundbreaking technology for sustainable energy. However, the sustainability of their lifecycle is still hindered by challenges related to material toxicity and end-of-life management. This review comprehensively assesses emerging recycling technologies, [...] Read more.

The rapid progress of perovskite solar cells (PSCs) has established them as a groundbreaking technology for sustainable energy. However, the sustainability of their lifecycle is still hindered by challenges related to material toxicity and end-of-life management. This review comprehensively assesses emerging recycling technologies, with a particular focus on their effectiveness in recovering perovskite compounds, transparent conductive oxides, and metallic contacts. Mechanical separation, solvent-based dissolution, thermal decomposition, and hybrid methods are compared in terms of recovery rates, purity levels, energy consumption, and scalability. Current challenges, such as the generation of secondary waste, the instability of recovered perovskites, and economic barriers, are critically analyzed alongside emerging solutions, including the use of non-toxic solvents, vacuum-assisted recovery, and the integration of closed-loop manufacturing. By evaluating lifecycle impacts and cost–benefit trade-offs, this work outlines pathways for transforming PSC waste into high-value secondary resources, thereby promoting both environmental sustainability and industrial competitiveness. Full article

(This article belongs to the Special Issue Growth and Properties of Photovoltaic Materials)

22 pages, 1034 KB

Open AccessReview

AI-Enabled Precision Nutrition in the ICU: A Narrative Review and Implementation Roadmap

by George Briassoulis and Efrossini Briassouli

Nutrients 2026, 18(1), 110; https://doi.org/10.3390/nu18010110 - 28 Dec 2025

Abstract

Background: Artificial intelligence (AI) is increasingly used in intensive care units (ICUs) to enable personalized care, real-time analytics, and decision support. Nutritional therapy—a major determinant of ICU outcomes—often remains delayed or non-individualized. Objective: This study aimed to review current and emerging AI applications [...] Read more.

Background: Artificial intelligence (AI) is increasingly used in intensive care units (ICUs) to enable personalized care, real-time analytics, and decision support. Nutritional therapy—a major determinant of ICU outcomes—often remains delayed or non-individualized. Objective: This study aimed to review current and emerging AI applications in ICU nutrition, highlighting clinical potential, implementation barriers, and ethical considerations. Methods: A narrative review of English-language literature (January 2018–November 2025) searched in PubMed/MEDLINE, Scopus, and Web of Science, complemented by a pragmatic Google Scholar sweep and backward/forward citation tracking, was conducted. We focused on machine learning (ML), deep learning (DL), natural language processing (NLP), and reinforcement learning (RL) applications for energy/protein estimation, feeding tolerance prediction, complication prevention, and adaptive decision support in critical-care nutrition. Results: AI models can estimate energy/protein needs, optimize EN/PN initiation and composition, predict gastrointestinal (GI) intolerance and metabolic complications, and adapt therapy in real time. Reinforcement learning (RL) and multi-omics integration enable precision nutrition by leveraging longitudinal physiology and biomarker trajectories. Key barriers are data quality/standardization, interoperability, model interpretability, staff training, and governance (privacy, fairness, accountability). Conclusions: With high-quality data, robust oversight, and clinician education, AI can complement human expertise to deliver safer, more targeted ICU nutrition. Implementation should prioritize transparency, equity, and workflow integration. Full article

(This article belongs to the Special Issue Nutritional Support for Critically Ill Patients)

14 pages, 1204 KB

Open AccessArticle

Circular Bioprocessing of Chlorella sp. Biomass via Wickerhamomyces sp. UFFS-CE-3.1.2 Fermentation for the Production of High-Value Enzymes, Glycerol, and Acetic Acid

by Vitória Dassoler Longo, Marcelli Powzum Amorim, Nair Mirely Freire Pinheiro Silveira, Isabely Sandi Baldasso, Emanuely Fagundes da Silva, Arielle Cristina Fornari, Sérgio L. Alves, Jr., Mateus Torres Nazari and Helen Treichel

Processes 2026, 14(1), 111; https://doi.org/10.3390/pr14010111 - 28 Dec 2025

Abstract

The transition to a circular economy and the pursuit of environmental sustainability are driving humanity to develop alternative technologies for producing a range of bioproducts. In this context, microbial-mediated fermentation processes have gained prominence. Although yeasts are well known for their ability to [...] Read more.

The transition to a circular economy and the pursuit of environmental sustainability are driving humanity to develop alternative technologies for producing a range of bioproducts. In this context, microbial-mediated fermentation processes have gained prominence. Although yeasts are well known for their ability to produce alcohols, they can also generate a wide range of value-added bioproducts. At the same time, microalgae emerge as an advantageous unconventional raw material, as their cultivation does not require arable land, thus avoiding competition with food production. To meet this demand, this study aimed to produce biocomposites through submerged fermentation using biomass from the microalgae Chlorella sp. Enzymatic hydrolysis was optimized using a 2² Central Composite Rotational Design (CCRD), with algal biomass and enzyme mass as independent variables. This step was followed by fermentation with the yeast Wickerhamomyces sp. UFFS-CE-3.1.2. The enzyme alpha amylase employed is of commercial origin, commonly used in the brewing industry, characterized by its easy accessibility and lower environmental impact compared to chemical hydrolysis methods. The results demonstrated that the combination of microalgae biomass with the enzyme preparation led to the production of several compounds of interest, such as highly active enzymes, mainly protease (560 U/mL), catalase (3381 U/mL), and peroxidase (277 U/mL), as well as other compounds, such as glycerol (32.5 g/L) and acetic acid (22.8 g/L). These products have wide industrial applications and a strong market demand, reinforcing the potential of the yeast–microalgae synergy for the sustainable production of high-value biocompounds, which represents a matrix of environmentally friendly products. Full article

(This article belongs to the Special Issue Enzyme Production Using Industrial and Agricultural By-Products)

41 pages, 5138 KB

Open AccessArticle

Improved Enterprise Development Optimization with Historical Trend Updating for High-Precision Photovoltaic Model Parameter Estimation

by Zhiping Li, Yi Liao and Haoxiang Zhou

Mathematics 2026, 14(1), 121; https://doi.org/10.3390/math14010121 - 28 Dec 2025

Abstract

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 [...] Read more.

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

(This article belongs to the Special Issue Optimization Theory, Algorithms and Applications)

24 pages, 1580 KB

Open AccessSystematic Review

Sustainable Management of Organic Waste as Substrates in Constructed Wetlands: A Systematic Review

by Diego Domínguez-Solís, María Concepción Martínez-Rodríguez, Lorena Elizabeth Campos-Villegas, Héctor Guadalupe Ramírez-Escamilla and Xochitl Virginia Bello-Yañez

Sustainability 2026, 18(1), 318; https://doi.org/10.3390/su18010318 (registering DOI) - 28 Dec 2025

Abstract

Constructed wetlands (CWs), which combine biological and physicochemical processes and adhere to circular economy principles, are increasingly recognized as nature-based wastewater treatment solutions. With an emphasis on resource valorization and pollutant removal efficiency, this review assessed the use of organic residues as substrates [...] Read more.

Constructed wetlands (CWs), which combine biological and physicochemical processes and adhere to circular economy principles, are increasingly recognized as nature-based wastewater treatment solutions. With an emphasis on resource valorization and pollutant removal efficiency, this review assessed the use of organic residues as substrates in CWs. In total, 44 peer-reviewed open-access case studies in English were obtained from 325 documents that were retrieved from Scopus using PRISMA-based eligibility criteria. Information about the wastewater source, substrate, CW type, and results was extracted. The results indicated that biochar (66.7%) predominated because of its high adsorption capacity and microbial support, while shell or forest residues and agricultural residues (20.5%) helped remove micropollutants and phosphorus. CWs with vertical subsurface flow were most prevalent (54%). According to studies, the removal efficiencies of biochar and agricultural or shell residues were 10–15% higher than those of inorganic substrates for phosphorus, TSS (total suspended solids), NH₄⁺ (ammonium), and BOD (biochemical oxygen demand) in wastewater. Through innovative designs and the application of circular economy strategies, including revalorize, reuse, reutilize, reintegrate, rethink and reconnect, organic substrates enhance pollutant removal and improve the overall sustainability of CWs. Overall, CWs with organic residues provide cost-effective and environmentally sustainable wastewater treatment; further research on local resources, hybrid systems, and supportive policies is recommended to promote broader implementation. Full article

(This article belongs to the Special Issue Circular Economy Strategies for Waste Management: Innovations in Resource Recovery and Sustainability)

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