Search Results (7,846)

The Amazonian açaí waste is promising for producing charcoal through pyrolysis and bioenergy through combustion, but the property losses from its poor disposal in the environment remain unknown. Therefore, this work aimed to analyze how different storage conditions of the açaí waste over time, which mimic the reality throughout the Amazon, modify its bioenergetic properties. The samples were stored in a covered greenhouse for nine months in the following conditions: immersed in water, on the soil, and in open plastic bags. The biomass was analyzed by Fourier-transformed near-infrared spectroscopy, physical properties, stereomicroscopy, proximate composition, and thermogravimetry. The degraded waste showed endocarp attack and fungi proliferation. The chemical groups of primary cell wall components were concentrated, unlike water-soluble materials, raising the fixed carbon from 22% to 25% after 30 days. Consequently, higher heating values were kept (≈19 MJ/kg). However, water immersion storage sharply decreased the waste basic density from 0.81 g/cm³ to 0.56 g/cm³, dropping the energy density from 12 GJ/m³ to 8 GJ/m³. Moreover, storage raised ash content from 1.1% up to 1.9%. The storage hindered the start of the main phases of combustion and pyrolysis, which were later intensified, especially for soil-stored waste. Therefore, more stable combustion and pyrolysis require fresh waste. Besides natural drying, plastic bag storage over time kept the waste quality closer to that of the fresh waste. Full article

Food waste presents a major challenge to global sustainability. Up to 60% of this waste occurs at the household level, at which point labeling confusion causes avoidable loss. The present study employed the motivation–opportunity–ability framework to conduct a narrative synthesis of 82 studies and pieces of gray literature, incorporating policies and industry practices to elucidate how food labeling modulates food waste behavior through interactions with consumer motivation, external opportunities, and individual abilities. Food labeling should be considered a systemic intervention tool spanning the entire food supply chain rather than mere carriers of information. The present findings indicate that although standardizing quality and safety label terminology mitigates cognitive confusion, it may have limited efficacy to reduce food waste. Extending shelf life and providing explicit storage guidance are critical strategies that are often undervalued and comparatively underexplored. Labels most effectively reduce waste when they simultaneously activate motivation, opportunity, and ability. When all three elements cannot be activated concurrently, stakeholders should prioritize improving external opportunities or enhancing individual abilities rather than stimulating motivation. Food labeling interventions can only be effective at waste mitigation if systemic and transdisciplinary synergy is achieved among all stakeholders in food supply chains. Full article

Flocs, visible particles formed in sugar-sweetened beverages, reduce clarity and consumer acceptance of products. Their presence can be caused not only by different types of trace impurities in the sugar but also by interactions among beverage components. In this review, scientific reports on acid beverage flocs (ABFs) and alcohol flocs are summarized, the main pathways for their formation are described, and practical options for detecting them and preventing their formation in beverages are compiled. Using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 and related guidance, literature searches of Scopus, Web of Science (WoS), PubMed, Food Science and Technology Abstracts (FSTA), CAB Abstracts, and International Commission for Uniform Methods of Sugar Analysis (ICUMSA) resulted in the inclusion of 56 studies. In various types of beverages, complexes formed between proteins (Ps) and polyphenols (PPs) often initiate haze and floc formation, while polysaccharides (dextran, pectin, and starch), silica or silicates, and inorganic ions influence charge balance, particle bridging, and floc growth rate. Ethanol in alcohol beverages can further destabilize colloids and promote aggregation. For beet sugars, saponin–protein interactions are a likely pathway for the formation of ABF, but the available evidence is not consistent. In cane sugars, the reported roles of proteins, polysaccharides, silica, and starch in floc formation vary considerably between studies. For quality assurance, ICUMSA floc tests (GS2-40 and GS2-44) should be complemented by turbidity or haze measurement and colloid characterization such as light scattering, ζ–potential, and infrared IR-based analytical methods supported by chemometrics. Risk mitigation works best as a two-level strategy that combines impurity removal during sugar production and stabilization steps in beverage formulation and storage, including the use of clarification agents and control of pH, temperature, ionic strength, and oxygen exposure. Standardized reporting and validation of rapid predictors against ICUMSA benchmarks remain essential. Full article

Nai plum (Prunus salicina Lindl. var. cordata) is a high-value fruit crop in southern China, yet its post-harvest quality is often compromised by fruit browning, a major constraint to storage and marketability. Addressing this challenge requires a deeper understanding of the species’ reproductive biology, which underpins both fruit set and cultivar improvement. In this study, we characterized the flowering biological characteristics of Nai plum accessions introduced from Yanling and Liuyang (Hunan Province) and Shaoguan and Lechang (Guangdong Province). Using field observations combined with microscopic and submicroscopic techniques, we documented flowering phenology, flowering dynamics, floral organ traits, pollen viability and stigma receptivity. The flowering period was in March, lasting 26–28 d, and the group blooming period was divided into three stages: Initial opening stage, Full blooming stage, and Final flowering stage. The single-flower opening process was divided into eight stages. Pollen viability followed a unimodal curve, peaking at the petal flattening stage (PF) across all accessions, though peak values varied by provenances. Stigmas were of the wet type, with receptivity following a weak–strong–weak pattern; peak receptivity occurred at early flowering (EF) and PF in most accessions. The EF of Nai plum from Yangling (S1) lasted for 7 h, and PF lasts for 28 h. The EF of Nai plum from Yangling (S2) lasted for 3 h, and the PF lasted for 11 h. Both the EF and the PF of Nai plum from Shaoguan (S3) lasted for 14 h. The bud white stage (BW) of Nai plum from Lechang (S4) lasted for 6 h and the EF lasted for 7 h. The EF of Nai plum from Liuyang (S5) lasts for 7 h, and the PF lasted for 28 h. These findings clarify the reproductive phenology and floral biology of Nai plum, providing foundational knowledge that can inform breeding strategies and cultivation practices aimed at improving fruit set and, ultimately, post-harvest quality. Full article

Recent deep exploration in the northern Sichuan Basin has advanced our understanding of Lower Cambrian Canglangpu Formation carbonate reservoirs. However, the characteristics, genesis, and distribution of the reservoir, as well as future exploration targets, remain unclear. Specifically, core and thin-section analyses indicate that these reservoirs are notably tight, with virtually no visible macroporosity and low permeability (0.01–1 mD). However, helium porosity measurements reveal values of 2–5%, suggesting significant storage potential. An integrated approach utilizing optical and scanning electron microscopy (SEM), high-pressure mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR), and micro-computed tomography (micro-CT) was employed to characterize the pore systems. Quantitative thin-section analysis reveals visible areal porosity markedly lower than helium porosity, indicating predominance of micropores; mercury intrusion and NMR demonstrate that intragranular and intergranular micropores constitute most pore volume, although effectively connected throat sizes remain below 1 µm. Comparative stratigraphic evaluations show that porosity is more developed in the dolomite-rich upper and middle intervals of the depositional cycles, whereas the lower intervals are less porous. Early subaerial exposure promoted dolomitization and dissolution, which facilitated pore development. However, the influence of sediment mixing led to a reduction in porosity. And deep burial subjected the rocks to intense compaction and cementation, destroying most of the primary pore space. Consequently, reservoir quality is ultimately governed by the interplay between the original depositional environment and the later diagenetic history, with paleotopographic highs identified as the most promising exploration targets. These findings establish a predictive framework for reservoir quality in tight carbonate rocks, which holds significant implications for analogous plays worldwide. Full article

Apple firmness, soluble solids content (SSC), and titratable acidity (TTA) were modeled when fruit were kept under cold storage and shelf-life conditions. These attributes are key indicators of fruit quality, storability, and organoleptic properties. Apple fruit of the ‘Irene’ cultivar were stored at 1 °C for 7 months, with quality assessed monthly and after 7 days of shelf life. Models based on the Storage Time Equivalent Value (STEV) were applied to predict firmness, SSC, and TTA as functions of time in cold storage and shelf life. Rates of change were higher during shelf life, with acceleration factors of 5.78 for firmness, 6.50 for SSC, and 5.51 for TTA. Model performance was high (R²_CV = 0.977, RMSE_CV = 1.16 N for firmness; R²_CV = 0.862, RMSE_CV = 0.29 °Brix for SSC; R²_CV = 0.978, RMSE_CV = 0.155 g L⁻¹ for TTA). The proposed approach integrates cold storage and shelf life into a single predictive framework. The unified STEV models, incorporating acceleration factors, show potential for forecasting the shelf life of ‘Irene’ apples. Full article

The rapid advancement of artificial intelligence relies on massive high-quality data, yet increasingly stringent data privacy regulations have exacerbated the problem of data silos. Federated learning enables collaborative training under privacy protection by exchanging model parameters rather than transmitting raw data. Nevertheless, its traditional centralized architecture still suffers from limitations such as single points of failure, lack of trust, and insufficient incentives. The integration of blockchain and federated learning opens new pathways for decentralized, auditable, and secure machine learning systems. This paper systematically reviews research progress in blockchain-enabled federated learning, analyzing technological evolution from three perspectives: system architecture, incentive mechanisms, and privacy enhancement. It further explores critical challenges including efficiency bottlenecks, storage overhead, and the inherent tension between transparency and privacy, while identifying key research directions for building scalable, efficient, and trustworthy decentralized learning systems. Full article

As large-scale underground storage infrastructure, deep tunnels exhibit distinct water quality dynamics driven by ground temperature gradients. Currently, there is limited investigation into water quality modeling for deep tunnel systems. Unraveling the correlation between temperature–depth gradients and water quality evolution is crucial for the operation and management of such systems. In this study, field experiments were carried out in the Qianhai–Nanshan Deep Tunnel to investigate complex water quality behavior, leading to the development of chemical oxygen demand (COD) and ammonia nitrogen (NH₃–N) models that incorporate temporal variation, temperature, and burial depth. Results indicate that temperature is the dominant factor influencing water quality in deep tunnel storage. Increased ground temperature promotes the degradation and mass transport of pollutants within the tunnel system. Owing to temperature–depth effects, the deeply buried Qianhai tunnel significantly reduces river discharge pollution after water storage, with COD and NH₃–N removal rates reaching 74.9% and 26.8%, respectively. Temperature-controlled experiments showed that COD and NH₃–N reduction rates varied between 60–94% and 10–30% across a temperature range of 20–34 °C. The proposed model was validated against experimental data, achieving Nash–Sutcliffe efficiency coefficients of 0.7–0.8. This study provides a methodological foundation for simulating complex aquatic environments and offers a decision-support tool for optimizing the operational strategies of deep tunnel systems. However, the model’s current generalization capability is constrained by the limited experimental conditions (20–34 °C, 12 days) and the lack of experimental replicates, which should be systematically addressed in future studies. Full article

Mold infection by Aspergillus and Penicillium spp. in Sithong sweet tamarind (Tamarindus indica L.) during commercial postharvest storage poses quality and food safety risks. However, the current visual detection method, which involves randomly cracking open the pods, is both destructive and laborious. The integration of near-infrared spectroscopy (NIRS) with artificial neural networks (ANN) enables rapid and non-destructive detection while capturing non-linear biochemical–spectral relationships, offering advantages over conventional destructive and linear analytical methods. It was tested as a mold classifier in sweet tamarind pods preserved in commercial ambient conditions (25 °C, 60% relative humidity) for five weeks. Six hundred pods were examined weekly using interactance spectroscopy (800–2500 nm) with six measurement points per pod and four spectral preprocessing methods. The ANN outperformed partial least squares discriminant analysis (PLS-DA) across all storage weeks, peaking at Week 2 with standard normal variate (SNV) preprocessing (prediction accuracy: 85.00%; sensitivity: 0.84; specificity: 0.86; F1-score: 0.85). Advanced tissue degeneration caused spectral heterogeneity, which decreased performance at Week 4 (prediction accuracy: 71.82–76.36%). Principal component loadings identified mold-induced water redistribution and carbohydrate depletion wavelengths at 938, 975–980, and 1035 nm. Week-adaptive calibration is essential for implementation because of the large difference between week-specific model accuracy (up to 85%) and overall storage model accuracy (63.53%). These findings provide a mechanistic underpinning for smaller wavelength-selective sensors and temporally adaptive mold screening systems in commercial tamarind storage. Full article

This work uses battery-coupled power electronic converter systems and distributed backstepping controllers to improve the reliability of electrical distribution networks. The motivation is to prevent blackouts such as the 28 April 2025 outage in Spain, Portugal, and the south of France. It is now accepted that a rapid rise in solar power injections caused AC overvoltage above grid code limits, triggering photovoltaic (PV) park disconnections as overvoltage self-protection. This case study considers near-Zero-Energy Buildings (nZEBs) connected to the Madeira Island isolated microgrid, where PV power installation is increasing excessively. The main university facility will be upgraded as an nZEB, using roughly 3000 m² of unshaded rooftops plus coverable parking areas to install PV panels. Optimizing the profits/energy cost ratio, a PV power system of around 560 kW can be planned, and the Battery Storage System (BSS) energy capacity can be estimated. The BSS is connected to the university nZEB via backstepping-controlled multilevel converters to manage PV and BSS, enabling the building to contribute to voltage and frequency regulation. Distributed multilevel converters inject renewable energy into the medium-voltage network, regulating active and reactive power to prevent overvoltages shutting down the PV inverters. This removes sustained overvoltage and maximizes PV penetration while augmenting AC grid reliability and resilience. When there is excess solar power and reactive power is insufficient to reduce voltage, controllers slightly curtail PV active power to eliminate overvoltage, maintaining operation with minimal revenue loss while preventing long interruptions, thereby improving grid reliability and power quality. Full article

Modeling the dynamic response of saturated marine soils is crucial yet computationally challenging for traditional methods. Meanwhile, purely data-driven models suffer from sparse data and lack of physical interpretability. To overcome these limitations, this study proposes an intelligent engineering framework based on a frequency-domain physics-informed neural network (FD-PINN) for the forward simulation and inverse parameter identification of saturated seabed soils. Constrained directly by physical laws during the learning process, FD-PINN remains highly reliable even when training data is sparse. By formulating the governing equations in the frequency domain, it directly predicts complex-valued displacement and pore-pressure phasors. Multiscale Fourier feature mappings mitigate spectral bias and capture boundary layers and high-frequency effects. For inverse problems, a phase-sensitive lock-in extraction strategy transforms time-domain measurements into robust frequency-domain targets, enabling the accurate and noise-tolerant identification of poroelastic parameters with clear physical meaning (nondimensional storage parameter S and permeability parameter $\Gamma$). Numerical experiments show that FD-PINN substantially outperforms conventional time-domain PINN, achieving relative $L^2$ errors of ${10}^{-2}\sim {10}^{-3}$ for single- and multi-frequency excitations typical of wave-induced loadings. In particular, $\Gamma$ is consistently recovered with sub-percent relative error, while S can be reliably identified with multi-frequency data. The framework offers a data-efficient, noise-robust approach for high-fidelity modeling and robust parameter inversion, which is particularly valuable in offshore environments where high-quality data is scarce. Full article

The large-scale use of compost in arable cropping systems is often limited by the large quantities required to meet the crop’s nutritional needs. Palletization can increase the nutrient density of organic fertilizers and improve their logistical feasibility by reducing storage, transport and application costs. This study evaluated the agronomic and environmental performance of compost pellets derived from pig slurry solids and olive pomace, using them as an alternative nitrogen source for wheat (Triticum aestivum L.) cultivated under Mediterranean conditions. A field experiment was conducted during the 2022–2023 growing season, with four treatments arranged in 24 m² replicated plots: an unfertilized control (C); pelletized compost (PSCOP); fresh pig slurry (PS); and mineral fertilization based on monoammonium phosphate and urea (IN). Excluding the control treatment, all fertilized plots received a uniform nitrogen rate of 150 kg N ha⁻¹. Soil chemical properties and nutrient availability (Pext, NH₄⁺-N and NO₃⁻-N) were evaluated at the beginning and end of the experiment, while wheat yield and grain quality were assessed at harvest. Greenhouse gas (GHG) emissions were monitored throughout the cropping season to evaluate environmental impacts. The results showed that the wheat yields achieved with PSCOP were comparable to those obtained with PS, although they remained lower than those achieved with mineral fertilization. Grain quality was not adversely affected by the application of PSCOP. Furthermore, PSCOP resulted in lower GHG emissions than mineral fertilization, with values closer to those observed in the unfertilized control. These findings suggest that pelletized organic fertilizers such as PSCOP may be a promising way to enhance nutrient circularity and reduce reliance on synthetic fertilizers and maintain crop productivity and limit environmental impact in Mediterranean agricultural systems. Full article

Introduction: Recent advancements in technologies, such as 3D printing, have been adopted in prosthodontics to streamline clinical procedures and provide high-quality prosthetic devices to patients within a reduced timeframe. Aim of the study: This study primarily aimed to determine the color change levels of 3D-printed dental resins for temporary and long-term intraoral applications. We also evaluated the effectiveness of post-processing procedures such as polishing or glazing on color stability. Materials and methods: Three types of dental resins were tested in distilled water, coffee, and wine environments for 2, 7, 30, and 60 days. A spectrophotometric analysis was conducted, and the Ciede2000 formula was used to determine the DE. Results: The material type, conditioning method, and storage time significantly affected the color changes of the tested materials. The post-processing technique had the most remarkable impact on color stability over time. Conclusions: Glazing of the 3D-printed material surface appears to be the most effective approach to prolong its clinical applicability by maintaining color stability. Full article

Mango (Mangifera indica L.), being a climacteric fruit, is highly perishable due to rapid ripening and post-harvest diseases like anthracnose, which significantly shorten its shelf life and limit long-distance sea export. To mitigate these constraints, a chemical-free secondary metabolite-based formulation (SMsF) was developed to delay ripening and control post-harvest anthracnose during storage. The SMsF possesses dual-action properties and is derived from the culture filtrate of Priestia aryabhattai, exhibiting ACC deaminase activity that restricts ethylene formation. It is also rich in antifungal compounds such as vanillic acid, hydroxybenzoic acid, cryptochlorogenic acid, palmitic acid, and BBIT, which inhibit anthracnose development. Additionally, it contains antioxidants including quercetin, coumaryl quinic acid, oleic acid, and acetylglycitin that enhance shelf life and disease resistance. The efficacy of SMsF was evaluated in mango cv. Banganapalli was stored at 12 ± 1 °C and 85–90% relative humidity under simulated reefer conditions (SRC). Integration of gamma irradiation with SMsF provided superior results in disease control and shelf-life extension. The combined treatment maintained higher fruit firmness (0.86 kg cm⁻²), optimal total soluble solids (14.3 °B), desirable acidity (0.22%), and complete suppression of anthracnose (PDI = 0) up to 40 days of storage under SRC compared with the control. The findings conclusively demonstrate that the synergistic application of SMsF and gamma irradiation effectively regulates ripening, enhances fruit quality, and ensures complete disease suppression, thereby significantly extending storage life. This approach holds strong scientific and commercial significance as a sustainable, residue-free, and export-oriented technology capable of improving long-distance transportation, reducing post-harvest losses, and promoting safe mango trade. Full article

The high-fidelity 3D digitization of small, detailed cultural heritage objects, such as Oracle Bones, presents significant challenges for which existing reconstruction workflows are often inadequate. Methods based on Structure-from-Motion (SfM) often lack the geometric density required to capture fine inscription details, while Light Detection and Ranging and RGB-Depth approaches may introduce high data overhead and unstable color mapping. Recent specialized studies have utilized multi-shading-based techniques to extract such hidden surface textures, yet integrating these results into a cohesive mesh remains difficult. To address these limitations, we propose a digitization framework specifically designed for object-level archaeological artifacts. Our method combines semi-automatic alignment with ICP-based refinement for robust camera pose estimation, reducing misalignment issues associated with feature-only registration. Furthermore, we employ an efficient mesh-based representation with vertex-level coloring, enabling detailed geometry and consistent texturing while maintaining compact storage requirements. Our contributions include: (1) a high-quality mesh reconstruction framework that preserves fine inscription geometry; (2) a hybrid camera pose estimation strategy that improves alignment robustness; and (3) an integrated hardware-assisted workflow tailored for digitizing small archaeological artifacts under controlled acquisition conditions. Experimental results on physical Oracle Bone artifacts demonstrate that the proposed method achieves a mean geometric reconstruction error of approximately 0.075 mm with a Hausdorff distance of 1 mm. These results demonstrate the effectiveness of the proposed workflow for digitization of oracle bone artifacts. Full article