Search Results (4,028)

Urban green space is essential for ecological functions, environmental quality, and human well-being, yet campus expansion can reduce vegetated areas. This study assessed UGS dynamics at Universitas Padjadjaran’s Jatinangor campus from 2015 to 2025 and evaluated an object-based machine learning approach for fine-scale land cover mapping. High-resolution WorldView-2, WorldView-3, and Legion-03 imagery were pan-sharpened, geometrically corrected, normalized, and used to compute NDVI and NDWI indices. Object-based image analysis segmented the imagery into homogeneous objects, followed by random forest classification into six land cover classes; UGS was derived from dense and sparse vegetation. Accuracy assessment included confusion matrices, overall accuracy 0.810–0.860, kappa coefficients 0.747–0.826, weighted F1 scores 0.807–0.860, and validation with 43 field points. The total UGS increased from 68.89% to 74.69%, bare land decreased from 13.49% to 5.81%, and building areas moderately increased from 10.36% to 11.52%. The maps captured vegetated and developed zones accurately, demonstrating the reliability of the classification approach. These findings indicate that campus expansion has been managed without compromising ecological integrity, providing spatially explicit, reliable data to inform sustainable campus planning and support green campus initiatives. Full article

Microplastic pollution has emerged as a serious societal concern, posing risks to the environment, human health, and economies. Conventional wastewater treatment processes remove microplastics at various levels from physical removal (primary), biological degradation (secondary), and contaminant-specific removal (tertiary treatment). Nature-based solutions (NbSs) offer an ecologically friendly alternative that utilizes nature to remove microplastics from wastewater. Recent reviews either focus broadly on NBSs for wastewater, technological solutions for microplastics, or NbSs for microplastics, but rarely connect them systematically. This review presents an integrated review of the sources and impacts of microplastic pollution, NbS technologies for the removal of microplastics, challenges and prospects in utilizing NbSs, and the knowledge gaps. Primary sources of microplastics are intentionally produced at microscopic sizes, while secondary sources originate from the disintegration of larger plastic debris. Among the NbS technologies are constructed wetlands (horizontal subsurface flow, vertical flow, surface flow, microbial fuel cells, multistage) with up to 100% efficiency; green infrastructures (bioretention systems, green walls, permeable pavements, retention ponds) with up to 99% efficiency; macrophytes and microphytes with up to 94% microplastic removal rate. Despite the ecosystem services provided by NbSs, they are challenged by the decrease in efficiency in removing other contaminants, detection and evaluation of NbS performance, and non-technical factors (operations and maintenance, public acceptance, climate risks, and financing). The findings present insights on further research and policy recommendations aimed at facilitating the integration of NbSs into existing frameworks for the removal of microplastics from wastewater, promoting research and innovation, and ensuring sustainable practices for sustainable management of water resources. Full article

This study investigates how core digital technologies—artificial intelligence (AI) and blockchain—can foster green innovation and sustainable consumption through circular platform design in high-value resale markets. Using Design Science Research (DSR) methodology, including its iterative cycles, we developed and evaluated TRUCE (Trust, Resale Logic, User Centricity, Circular Infrastructure, Ecosystem Governance), a sustainability-oriented digital architecture designed to promote ethical, energy-efficient consumption. TRUCE aims to leverage AI-driven authentication, blockchain-based transparency, and consumer data analytics, aiming to embed circularity and traceability into platform governance. Aligned with the EU Green Deal’s digital agenda, it is intended to support waste reduction, lifecycle extension, and responsible consumption, contributing to Sustainable Development Goal 12 and the broader 2030 Agenda. Full article

This study examines spatial patterns and self-reported user experiences within the Balkan Campus of Trakya University as a single, context-specific case. The aim is to describe how campus-scale spatial configuration and user perceptions appear within this setting, without pursuing broader generalization. Methods: Space Syntax metrics (integration, connectivity, visibility) and a cross-sectional survey were used to document campus-level spatial characteristics and participants’ experiences. Spatial measures were not matched to individual movement paths; thus, all patterns reflect descriptive co-occurrences rather than causal or generalizable relationships. Results: The campus displayed a center–periphery structure shaped by its historical and linear development. Higher integration, connectivity, and visibility values occurred in areas respondents described as either clear or unclear for navigation, showing context-specific overlaps between spatial structure and perception. Regression analyses indicated associations between user satisfaction and wayfinding difficulty, availability of social spaces, and cleanliness–hygiene conditions. Positive evaluations appeared to occur somewhat more often near social and green areas, consistent with observations in previous campus-based studies but only within this site. Conclusions: All findings are limited to the physical and institutional characteristics of the Balkan Campus. The study provides a strictly context-bound, exploratory description of how spatial configuration and reported experiences appear within this single campus setting. Full article

The role of international financial resource inflows, foreign direct investment (FDI), development foreign assistance (DFA), and personal remittance earnings (PRE) in decisive advancement toward environmental sustainability (SDG13) and economic development is increasingly recognized. However, depending on the situation, their effects on environmental outcomes vary in degree and direction, and are still subject to debate. This research examines how the three main international financial resources impact environmental sustainability, which is measured by the bio-capacity index, with a specific focus on the moderating role of corruption. The system panel generalized method of moments with balanced panel data (2001–2023) was used to attain the objectives of this study. This study focused on 28 developing Organization of Islamic Cooperation member countries because of their significant reliance on these financial inflows, regional/economic variety, and diverse levels of governance, which offer a crucial setting for evaluating the corruption moderation hypothesis. The findings reveal a comprehensive scenario of SDG synergies and trade-offs. In the base model, FDI directly improves the situation, whereas DFA and PRE are initially negligible. When considering internal economic factors, FDI and PRE greatly advance sustainability, whereas domestic financial measures such as domestic credit and fixed capital formation show adverse effects, underscoring a tension between environmental objectives and national financial systems. Importantly, the moderation analysis shows that while the advantages of FDI and PRE continue to be robust, corruption severely reduces the efficacy of DFA. To assure environmental effectiveness, these findings call for distinct policies that encourage green FDI, leverage remittances for green investments at the family level, and above all, fasten development assistance to strict governance changes. Full article

This study addresses the fabrication challenges associated with producing diverse geometries for concrete dry connections, particularly regarding cost, time, and geometric limitations. The research investigates methods for fabricating precise, rebar-free dry connections in concrete, focusing on stamping and green-state computer numerical control (CNC) milling. These methods are evaluated using metrics such as dimensional accuracy, tool abrasion, and energy consumption. In the stamping process, a design of experiments (DOE) approach varied water content, concrete age, stamping load, and operational factors (vibration and formwork) across cone, truncated cone, truncated pyramid, and pyramid geometries. An optimal age range of 90 to 105 min, within a broader operational window of 90 to 120 min, was identified. Geometry-specific exceptions, such as approximately 68 min for the truncated cone and 130 min for the pyramid, were attributed to interactions between shape and age rather than deviations from general guidance. Within the tested parameters, water fraction primarily influenced lateral geometric error (diameter or width), while age most significantly affected vertical error. For green-state milling, both extrusion- and shotcrete-printed stock were machined at 90 min, 1 day, and 1 week. From 90 min to 1 week, the total milling energy increased on average by about 35%, and at one week end-face (head) passes caused substantially higher tool wear, with mean circumference losses of about 3.2 mm for head engagement and about 1.0 mm for side passes. Tool abrasion and energy demand increased with curing time, and extrusion required marginally more energy at equivalent ages. Milling was conducted in two engagement modes: side (flank) and end-face (head), which were evaluated separately. End-face engagement resulted in substantially greater tool abrasion than side passes, providing a clear explanation for tolerance drift in final joint geometries. Additionally, soil-based forming, which involves imprinting the stamp into soft, oil-treated fine sand to create a reversible mold, produced high-fidelity replicas with clean release for intricate patterns. This approach offers a practical alternative where friction and demolding constraints limit the effectiveness of direct stamping. Full article

Soft tissue sarcomas (STS) are rare and heterogeneous tumors for which achieving complete tumor resection with negative surgical margins remains the cornerstone of curative treatment and a key predictor of survival. Current intraoperative resection margin status assessment techniques remain limited, as traditional intraoperative frozen section analysis is of limited accuracy for most STS histological subtypes. This comprehensive review evaluates current and emerging margin assessment techniques used intra-operatively during STS resection. A systematic search of PubMed and PubMed Central databases from 2000 to 2025 identified studies using fluorescence imaging, spectroscopy, and ultrasound-based modalities. Indocyanine green (ICG) fluorescence-guided surgery appeared to be the closest to widespread use, with the most clinical evidence showing potential to reduce positive margins. Use of acridine orange (AO) as a fluorescent dye also showed potential in decreasing local recurrences, but it remains in the experimental stage of research with little clinical data available. Raman spectroscopy has recently shown high accuracy in identifying STS from healthy tissue, but the impact of its use on patient outcomes has not been studied yet. Other techniques, such as diffuse reflectance spectroscopy (DRS), rapid evaporative ionization mass spectrometry (REIMS), optical coherence tomography (OCT), and intraoperative ultrasound (IOUS) yielded encouraging results but still require further prospective studies to validate their safety, reproducibility, and clinical utility in improving surgical precision and patient outcomes. Full article

Calcareous tropical green macroalgae of the genus Halimeda are key reef-builders, yet the drivers of their diversification and population dynamics remain poorly understood. This study analyzed the species diversity of Halimeda in the Xisha (Paracel) Islands based on tufA gene sequences, focusing on evaluating the genetic diversity, population structure, and historical dynamics of two widespread species—Halimeda discoidea and Halimeda macroloba. The results indicate new records of Halimeda cylindracea and Halimeda cf. stuposa in the Xisha (Paracel) Islands. More importantly, H. discoidea and H. macroloba exhibited significantly different evolutionary histories. Specifically, H. discoidea showed a highly fragmented population structure, restricted gene flow, and a multimodal mismatch distribution, suggesting a complex historical process or long-term stability. In contrast, H. macroloba exhibited lower population differentiation, extensive gene flow, and non-significant neutrality test results, indicating long-term demographic stability without recent, drastic population events. Further validation based on gene flow analysis and divergence time estimation revealed that the lineage divergence of H. discoidea is older, while H. macroloba represents a lineage with a relatively younger evolutionary origin restricted to the Indo-Pacific region. This striking dichotomy clearly illustrates the interplay between intrinsic species-specific traits (e.g., dispersal capacity) and extrinsic historical factors (e.g., paleo-oceanographic events), leading to contrasting evolutionary outcomes among widespread marine taxa. By elucidating how differing evolutionary histories influence patterns of genetic diversity, this study provides a predictive framework for evaluating the resilience and guiding conservation priorities for critical marine calcifiers in the context of rapid environmental change. Full article

Climate change and water scarcity are major threats to the sustainability of wheat production in Mediterranean regions. Thus, timely and reliable water demand assessments are crucial to drive decisions on crop management strategies that are useful for agricultural adaptation to climate change challenges. Although the AquaCrop model is widely used to infer crop yields, it requires continuous field-based observations (mainly soil water content and crop coverage). Often, these areas suffer from a scarcity of in situ data, suggesting the need for remote sensing and model-based decision support. In this framework, this research intends to compare the performance of the AquaCrop model using four different input combinations, with one employing ERA5-Land and crop cover retrieved by satellite images exclusively. A field experiment was conducted on durum wheat (highly sensitive to water stress and playing a strategic role in national food security) in northwest Tunisia during the growing season of 2024–2025, where meteorological variables, green Canopy Cover (gCC), Soil Water Content (SWC), and final yields (biological and grain) were monitored. The AquaCrop model was applied. Four model input combinations were evaluated. In situ meteorological data or ERA5-Land (E5L) reanalysis were combined with either measured-gCC (measured-gCC) or Sentinel-2 NDVI-derived gCC (NDVI-gCC). The results showed that E5L reproduced temperature with RMSE < 2.4 °C (NSE > 0.72) and ETo with RMSE equal to 0.57 mm d⁻¹ (NSE = 0.79), while precipitation presented larger discrepancies (RMSE = 4.14 mm d⁻¹, NSE = 0.58). Sentinel-2 effectively captured gCC dynamics (RMSE = 15.65%, NSE = 0.73) and improved AquaCrop perfomance (RMSE = 5.29%, NSE = 0.93). Across all combinations, AquaCrop reproduced yields within acceptable deviations. The simulated biological yield ranged from 9.7 to 11.0 t ha⁻¹ compared to the observed 10.3 t ha⁻¹, while grain yield ranged from 3.0 to 3.5 t ha⁻¹ against the observed 3.3 t ha⁻¹. As expected, the best agreement with measured yield data was obtained using in situ meteorological data and measured-gCC, even if the use of in situ meteorological data coupled with NDVI-gCC, or E5L-based meteorological data coupled with NDVI-gCC, produced realistic estimates. These results highlight that the application of AquaCrop employing E5L and Sentinel-2 inputs is a feasible alternative for crop monitoring in data-scarce environments. Full article

Mesoporous silica nanoparticles (MSNs) are among the most adaptable nanocarriers in modern pharmaceutics, characterized by a high surface area, tunable pore size, controllable morphology, and excellent biocompatibility. These qualities enable effective encapsulation, protection, and the delivery of drugs in a specific area and, therefore, MSNs are powerful platforms for the targeted and controlled delivery of drugs and theragnostic agents. Over the past ten years and within the 2021–2025 period, the advancement of MSN design has led to the creation of hybrid nanostructures into polymers, lipids, metals, and biomolecules that have yielded multifunctional carriers with enhanced stability, responsiveness, and biological activities. The current review provides a review of the synthesis methods, surface functionalization techniques, and physicochemical characterization techniques that define the next-generation MSN-based delivery systems. The particular focus is put on stimuli-responsive systems, such as redox, pH, enzyme-activated, and light-activated systems, that enable delivering drugs in a controlled and localized manner. We further provide a summary of the biomedical use of MSNs and their hybrids such as in cancer chemotherapy, gene and nucleic acid delivery, antimicrobial and vaccine delivery, and central nervous system targeting, supported by recent in vivo and in vitro studies. Important evaluations of biocompatibility, immunogenicity, degradation, and biodistribution in vivo are also provided with a focus on safety in addition to the regulatory impediments to clinical translation. The review concludes by saying that there are still limitations such as large-scale reproducibility, long-term toxicity, and standardization by the regulators, and that directions are being taken in the future in the fields of smart programmable nanocarriers, green synthesis, and sustainable manufacture. Overall, mesoporous silica and hybrid nanoparticles represent a breakthrough technology in the nanomedicine sector with potentials that are unrivaled in relation to targeted, controlled, and personalized therapeutic interventions. Full article

Background/Objectives: Surgical clipping remains a fundamental treatment modality for intracranial aneurysms, particularly in complex cases and those not amenable to endovascular approaches. However, it is associated with several technical challenges and potential complications that may compromise patient outcomes. This study aims to identify and analyze the most frequent and critical intraoperative pitfalls encountered during microsurgical clipping. We discuss experience-based strategies for avoiding these complications as well as practical solutions for managing them effectively when they occur. Methods: A retrospective review of our institutional experience with surgically treated intracranial aneurysms is reported. The study includes a comprehensive analysis of complications encountered across a defined series of cases, along with representative clinical cases. Results: Several categories of complications were identified, including aneurysm rupture, incomplete clipping and aneurysm remnant, vessel stenosis and brain ischemia, and new-onset seizures. Specific microsurgical techniques, intraoperative tools (e.g., indocyanine-green angiography, neurophysiological monitoring, micro-Doppler flowmetry evaluation), and decision-making algorithms are discussed to help mitigate these risks. For each scenario, tailored rescue strategies are outlined based on both the literature evidence and our clinical experience. Conclusions: Awareness of the potential pitfalls in aneurysm clipping and a structured approach to their prevention and management are crucial for optimizing surgical outcomes, and for preparing young vascular neurosurgeons. Through a combination of technical refinement and scenario-based preparedness, many complications can be anticipated and effectively addressed. Full article

To effectively valorize lignin, some challenges must be addressed. First, emerging techniques based on green methods may experience difficulties during the scale-up process. Secondly, the low solubility of lignin can hinder further valorization. This study investigated the impact of lignin extraction scale-up on yield and purity and evaluated strategies to enhance lignin solubility. Lignin from grape stalks was extracted using two previously optimized methods—alkaline and deep eutectic solvents—at a scale-up by factors of 5, 10, and 20 times. Although a slight decrease in extraction yield was observed with increasing scale, lignin purity remained consistent across all conditions. After extraction, lignin samples were subjected to solubilization tests using surfactants (Tween 20, Tween 80, and polyethylene glycol) and organic solvents (ethanol and acetic acid). Results demonstrated that surfactants were notably more effective in solubilizing lignin (up to 74.5%) compared to organic solvents. Furthermore, as an alternative to lignin solubilization, the production of lignin nanoparticles through ultrasonication with minimal chemical use was also explored. Upon optimization, spherical nanoparticles with a mean diameter of approximately 200 nm were successfully obtained. The use of surfactants was necessary to avoid nanoparticle aggregation during concentration steps and to enhance colloidal stability. This study demonstrates the feasibility of scaling up lignin extraction methods and further explores two approaches to enhancing the valorization of the obtained lignin—solubilization and the production of lignin nanoparticles—thereby contributing to the development of efficient and sustainable strategies for diverse lignin-based applications. Full article

This systematic review aimed to examine recent advances (2021–2025) in the conversion of agricultural biomass into biomaterials, biofertilizers, and bioproducts. Studies were included when addressing biomass types, pretreatment methods, conversion technologies, or resulting applications. Non-agricultural biomass, non-original research, and works outside the defined timeframe were excluded. Literature was identified in Scopus and Web of Science, complemented by Espacenet, Google Scholar, and institutional databases (USDA, FAO, IRRI, ABARES, UNICA, and CONAB, among others), totaling 108 documents referenced in this work. Risk of bias was minimized through predefined eligibility criteria and full-text assessment. Results were narratively synthesized, supported by figures and tables highlighting technological trends. Studies involving a wide range of agricultural biomasses (e.g., rice straw, corn stover, wheat straw, and sugarcane bagasse) were evaluated. Main outcomes included the development of bioplastics, biofoams, composites, hydrogels, bioceramics, biochar-based fertilizers, organic acids, enzymes, and green solvents. Evidence consistently indicated that pretreatment strongly influences conversion efficiency and that enzymatic and thermochemical routes show the highest potential for integrated biorefineries. Limitations included heterogeneity in biomass composition, variability in methodological quality, and scarcity of large-scale studies. Overall, findings underscore agricultural biomass as a strategic feedstock for circular bioeconomy models, with implications for sustainable materials, renewable energy, and low-carbon agriculture. Continued innovation, supportive policies, and improved logistics are essential for scaling biomass-based technologies. Full article

Environmentally friendly (green) stock investment has evolved into a global trend over the past few decades, including in the Indonesian capital market. However, the process of selecting sustainability-oriented stocks involves various complex criteria that are often qualitative, subjective, and uncertain. Therefore, an analytical tool is needed to support the decision-making process more adaptively and objectively. This study proposes the Criteria Importance Through Inter-criteria Correlation–Weighted Fuzzy Soft Set (CRITIC-WFSS) integration model, a decision-making method that combines WFSS with the objective, data-driven weighting mechanism of the CRITIC method. In the proposed model, parameter weights are determined by considering data variation (standard deviation) and inter-criteria correlation, ensuring that more discriminative and informative parameters receive higher weights. The model was applied to data on environmentally friendly stocks in the SRI-KEHATI Index, obtained from the Indonesia Stock Exchange (IDX) official website, to evaluate and identify stocks with optimal performance. The model’s performance is evaluated through a comparative study with the AHP-WFSS and Entropy–WFSS methods, complemented by a sensitivity analysis. The results show that UNVR ranked highest with a perfect score of 1, indicating an optimal balance between financial performance and sustainability. Furthermore, a comparative study demonstrated that CRITIC-WFSS can generate rankings that are more reliable, appropriate, and logical than those generated by two comparison methods. Meanwhile, the results of the sensitivity analysis indicate that the CRITIC-WFSS model demonstrates strong robustness to variations in input parameters, ensuring stable rankings. The model shows significant potential to support more accurate and transparent investment decision-making by generating consistent stock rankings based on a balanced integration of financial, and sustainability (environmental, social, and governance (ESG)) aspects. This research was conducted in order to support the achievement of various goals through SDG 8 (Decent Work and Economic Growth). Full article

Sustainable urban water governance in rapidly transforming cities requires integrative decision-making frameworks capable of balancing social equity, economic efficiency, and environmental resilience. This study develops an Integrative Decision-Making Framework (IDMF) for optimizing urban water policy in Yerevan, Armenia, built upon AI- and GIS-assisted diagnostics and incorporating a Governance Readiness Index (GRI) together with spatial hotspot overlay analysis. The framework employs an AHP–TOPSIS multi-criteria structure to evaluate five policy alternatives—leakage reduction, demand-side management, decentralized reuse, green–blue infrastructure, and data-driven governance—based on normalized quantitative indicators across social, economic, and ecological domains. Results show that Leakage Reduction (A1) and Data-Driven Governance (A5) consistently rank as the top-performing strategies across both baseline and sensitivity scenarios, while equity-prioritized weightings enhance social outcomes without significantly compromising economic performance. The approach also demonstrates robustness under ±10–20% weight variations. Acknowledging limitations related to data availability and expert-based judgments, the study outlines the minimum governance and data-readiness conditions required for transferability. The IDMF thus advances decision-support science in urban water management by integrating governance feasibility with spatial diagnostics and provides adaptable guidance for mid-income cities facing institutional and environmental constraints. Full article