Search Results (1,023)

Button mushrooms (Agaricus bisporus) are highly perishable, making rapid and automated postharvest freshness evaluation crucial for cold-chain logistics. Visible-near-infrared (Vis-NIR) hyperspectral imaging is promising for non-destructive food quality assessment, yet mining highly redundant spatial–spectral data remains challenging. This study proposes a novel artificial intelligence approach, the patch-aligned multimodal interaction fusion network (PAMIF-Net), to monitor postharvest mushroom freshness. Using a Vis-NIR dataset of 400 A. bisporus caps over a 9-day refrigerated storage period, this deep learning architecture dynamically fuses global spectral features (indicating internal physicochemical shifts) with localized spatial morphological features (capturing surface deterioration) using a gated attention mechanism. Extensive evaluations across 10 independent trials demonstrated that PAMIF-Net achieved optimal classification accuracy (up to 100% on the current test set) and a minimal mean absolute error for five-class storage time recognition. Furthermore, it exhibited superior computational efficiency and significantly lower inference latency compared to classical machine learning and standard deep learning backbones. This multimodal spatial–spectral deep learning framework demonstrates the feasibility of combining HSI and deep learning for the specific task of automated storage time recognition of A. bisporus under controlled refrigerated conditions. Full article

The power demand of High-Performance Computing (HPC) infrastructures exhibits both stable weekly regularities and rapid workload-driven fluctuations, which are difficult to capture reliably with a single modeling paradigm. Achieving more sustainable HPC operation requires accurate forecasts at multiple horizons: short-term predictions support operational control (e.g., proactive power capping and energy-aware scheduling), whereas long-term forecasts are essential for planning activities (e.g., capacity provisioning and energy procurement). Together, these capabilities reduce operational cost and risk while enabling more efficient and sustainable datacenter management. This paper investigates multi-horizon forecasting of aggregated active power consumption in an operational HPC datacenter utilizing a four-month dataset (five-minute time intervals) from the University of Turin. We propose a hybrid residual-learning framework that integrates a long-term structural forecaster with a short-term residual corrector utilizing a Temporal Convolutional Network (TCN) to address the simultaneous presence of weekly regularities and short-term workload-induced fluctuations. Assessment utilizing a rolling-origin protocol covers a timeframe of 15 min to 6 h and extends 1 to 3 weeks into the future. Performance of the proposed approach has been compared against the SARIMA baseline. Full article

Automated classification of municipal solid waste remains challenging due to high variability in object appearance, deformation, contamination, and inconsistent consumer disposal behavior, creating a need for representative multimodal datasets that enable robust machine-learning models. In this work, we developed a custom edge-node reverse-vending-machine (RVM) data-collection station equipped with multimodal sensors (RGB-D and microphone array) to co-record RGB-D video streams and impact audio on a single local compute node within the same acquisition window. Strict data acquisition protocols were designed to ensure a consistent environment, controlled illumination, and uniform background conditions while capturing realistic variations associated with everyday Greek consumer waste. The resulting dataset comprises 3300 multimodal samples corresponding to 721 distinct household waste items. Each sample is fully annotated across six categories addressing features critical for recycling: Material (18 classes), Hue (16 classes), Top/Cap, Label, Contamination, and Deformation. In addition, Common Objects in Context (COCO) annotations were added to support segmentation and object detection problems. This dataset is intended to support research on multimodal waste recognition, sensor fusion, and resource-efficient classification, and to serve as a foundation for evaluating models targeting edge-deployed recycling systems. Full article

Conventional hydrogen peroxide (HP) tooth whitening treatments frequently induce structural deterioration of enamel, necessitating the development of biocompatible and highly efficient alternatives. This in vitro study investigated the application of a novel functional biomaterial, the Type I aggregation-induced emission (AIE) photosensitizer CPTQ, for peroxide-free photodynamic tooth whitening. Under white-light irradiation (25 mW/cm²), CPTQ (12.5 μM) demonstrated rapid degradation of representative chromogenic molecules (crystal violet, malachite green, and rhodamine B). Extracted human teeth stained with both model pigments and complex beverage mixtures (coffee, tea, and fruit juices) were allocated into four treatment groups: negative control (NC), CPTQ, 7.5% HP, and 30% HP (n = 6 per group). Colorimetric parameters (ΔE₀₀, Δa*, Δb*, and ΔL*) and enamel-related endpoints—including surface morphology, roughness, mineral composition (Ca/P), and microhardness—were evaluated over 6 h and analyzed using one-way ANOVA. For pigment-stained teeth, the photodynamic whitening efficiency of CPTQ was comparable to that of 30% HP (ΔE₀₀, p > 0.05) during the 6 h treatment period. At 1.5 h, the ΔE₀₀ value in the CPTQ group (23.35 ± 2.32) was significantly greater than those in the NC group (15.70 ± 1.78, p < 0.05) and the 7.5% HP group (15.02 ± 1.63, p < 0.05). For beverage-stained teeth, the whitening efficiency (ΔE₀₀) of CPTQ was significantly greater than that of the control group at 1.5 h (6.22 ± 2.09 vs. 1.82 ± 0.56, p < 0.01) and was significantly greater than that of 7.5% HP at 4.5 h (10.94 ± 2.82 vs. 7.56 ± 1.78, p < 0.05). Crucially, unlike the change observed after 30% HP treatments, CPTQ treatment resulted in no statistically significant differences from NC in preserved enamel surface integrity, including morphology assessed by SEM, surface roughness (R_a and S_a, both p > 0.05), mineral composition (Ca and P, both p > 0.05), and microhardness (ΔH_V, p > 0.05). Mechanistic investigations using reactive oxygen species (ROS) scavengers (TBA and DABCO) suggested that hydroxyl radicals generated via the Type I photodynamic pathway are the primary drivers of pigment degradation, reducing ΔE₀₀ from 12.56 to 1.09 upon •OH inhibition. CPTQ achieved measurable in vitro whitening through a predominantly Type I ROS-mediated mechanism while causing limited changes in the evaluated enamel surface endpoints. Full article

RNA vaccines—comprising linear mRNA, self-amplifying RNA, and circular RNA (circRNA)—constitute a core next-generation platform for the prevention and control of viral diseases; among these, circRNA vaccines possess notable structural stability, yet their technical bottlenecks and application prospects in veterinary medicine have not been systematically reviewed. This review synthesizes current research on circRNA vaccine design, circularization strategies, translation mechanisms, delivery systems, and immunological outcomes, and compares their antiviral performance with that of linear mRNA vaccines. Owing to their covalently closed circular conformation, circRNA vaccines exhibit enhanced resistance to nucleases and superior thermal stability, enabling sustained transfection activity at ambient temperatures without reliance on strict cold chains; through cap-independent translation driven by internal ribosome entry sites or N⁶-methyladenosine modifications, and in conjunction with optimized circularization protocols and lipid nanoparticle carriers, circRNA vaccines elicit substantially higher antiviral IgG titers and durable antigen-specific T-cell memory relative to linear mRNA vaccines. These vaccines have been deployed against COVID-19, monkeypox, influenza, and livestock viral diseases, demonstrating strong adaptability to viral variants and compatibility with mucosal or needle-free administration routes. CircRNA vaccines are well suited for both emergency outbreak response and routine immunization programs; nevertheless, challenges persist, including low circularization efficiency for long sequences, elevated manufacturing costs, and inadequate quality control standards. Addressing these issues through improved production workflows and delivery technologies adapted to resource-limited settings will be critical to establishing circRNA vaccines as a pillar of livestock disease management and as a strategic reserve for emerging zoonotic threats. Full article

Seed-associated microorganisms influence seed quality, seedling establishment, and plant health and also constitute a major source of seed-borne pathogens. Cold atmospheric plasma (CAP) has emerged as a promising alternative to chemical seed treatments because of its antimicrobial activity, although its effects on fungal communities associated with developing seedlings remain poorly understood. Here, Arabidopsis thaliana seeds from two ecotypes (Columbia and Landsberg erecta) were exposed to CAP for 5 or 15 min. Seed decontamination efficiency was assessed by culturing on malt extract agar and nephelometric analyses, while fungal communities associated with seedlings derived from treated and untreated seeds were characterized by ITS1 amplicon sequencing. CAP efficiently reduced fungal contamination without affecting seed germination. CAP altered the composition of fungal communities associated with developing seedlings, but the magnitude of these changes depended on seed batch and ecotype. Dominant taxa markedly declined after treatment, whereas several low-abundance taxa increased in relative abundance. These findings demonstrate that CAP is an effective pesticide-free technology for seed decontamination and can also reshape fungal communities associated with developing seedlings, highlighting broader ecological consequences of plasma-based seed treatments. Full article

Integrated electricity–gas–heat systems underpin sustainable energy provision by coupling renewable, gas, and thermal resources across carriers. Sustainable operation of such systems must limit service loss caused by cross-carrier contingencies while maintaining economic efficiency and tracking carbon performance. This paper develops a 6 h rolling linear dispatch framework in which a security-margin floor, a scenario-weighted unserved-energy limit, and a conditional value-at-risk (CVaR) limit jointly define the admissible operating domain. The two risk limits adapt to the evolving load, forecast uncertainty, and gas-supply state, and future forecasts use only the error observed at the current dispatch instant. Across 30 paired forecast-error realizations, the adaptive method reduces the weighted unserved-energy index and the maximum hourly CVaR by 4.88% and 4.38%, respectively, relative to a fixed-cap rolling method under identical inputs, at a 2.14% cost increase. The equal-mean-budget comparison shows that temporal allocation adds a smaller, operationally modest improvement, with a paired CVaR difference of −0.094 MWh (95% CI: −0.108 to −0.079 MWh). A transfer case on the linear IEEE 39-bus–Belgian 20-node–DHS 6-node model keeps the network flexibility equivalent within its calibrated 0–65 MW domain, and all three rolling schedules pass 24 h full-topology linear routing checks without additional shedding at nominal capacities. These results establish implementability within the tested linear models; all reported risk indices are comparative scenario-risk measures rather than annual reliability statistics. By jointly safeguarding service continuity, economic efficiency, and carbon performance, the proposed framework supports the environmental, economic, and social dimensions of sustainable integrated-energy operation. Full article

Objective: To develop and characterize a particulate biomaterial composed of hydroxyapatite derived from salmon bone and bovine type I collagen (HAPS/COL), and to evaluate whether different inorganic–organic ratios influence its physicochemical properties. Materials & Methods: Biomaterials were produced using three HAPS/COL proportions (70/30, 80/20, and 90/10). Physicochemical characterization included pycnometry, X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX). Results: Pycnometry showed densities close to that of pure hydroxyapatite, with only slight decreases attributable to collagen content. SEM-EDX images showed comparable surface morphologies characterized by hydroxyapatite particulates surrounded by collagen fibers. Ca/P ratios were slightly higher than the stoichiometric value of hydroxyapatite. XRD confirmed hydroxyapatite as the dominant crystalline phase across all formulations, with no evidence of phase alteration. TGA revealed mass losses of 2.75%, 1.90%, and 1.60% for the 70/30, 80/20, and 90/10 mixtures, respectively, with consistent mass loss-to-collagen ratios of approximately 0.09 for the 70/30 and 80/20 formulations, confirming proportional organic phase degradation. Conclusions: The three HAPS/COL ratios produced biomaterials with highly similar physicochemical profiles, indicating that within the tested range, the proportion of hydroxyapatite and collagen does not substantially alter material structure, composition, or thermal behavior. These findings confirm the successful manufacture of a stable HAPS/COL blend, allowing the use of efficient quantities of collagen, thus minimizing the costs associated with its purchase. Full article

Microbial synthesis of selenium nanoparticles (SeNPs) offers a sustainable alternative to chemical routes, but the genetic basis of selenium handling in Bacillus remains poorly defined, which limits rational strain selection. Here, SeNP production, physicochemical characterization, and closed-genome sequencing are combined for Bacillus licheniformis BLN313. Selenite reduction peaked at 500 µg/mL Na₂SeO₃ (88.8% conversion; 444 ± 27 µg/mL Se⁰); at higher concentrations, conversion efficiency and viability diverged, indicating that tolerance and reductive capacity are distinct traits. Purified SeNPs were spherical and partially crystalline trigonal Se⁰ (TEM 190 ± 52 nm; DLS 166 nm, PDI 0.03; zeta potential −20.8 mV), carrying a proteinaceous capping layer confirmed by XPS, EDS, and FTIR and shown by LC-MS to be enriched in cell wall-derived metabolites. The particles were bactericidal against Micrococcus luteus (MIC 62.5 µg/mL) and Klebsiella pneumoniae (MIC 250 µg/mL) and reduced MCF-7 viability (IC50 2.7 µg/mL) while sparing MCF-10A cells. The 4.11 Mb genome (46.3% GC; ANI 99.7%, dDDH 97.8%) encodes SulP and Pit transporters, multiple trxB copies, and sulfur-metabolism and oxidative-stress genes, defining a candidate gene set for selenium uptake, reduction and detoxification. BLN313 thus provides a genetically defined platform for SeNP production in biomedical and environmental applications. Full article

The Vietnamese textile and garment industry faces a critical sustainability paradox under the impending Carbon Border Adjustment Mechanism (CBAM). Firms are pressured to maintain high-volume export growth while aggressively minimizing carbon and resource intensity. To empirically resolve this tension, this study develops a novel three-phase benchmarking framework that integrates the Best–Worst Method (BWM), VIKOR, and Super-Efficiency Slacks-Based Measure (Super-SBM) under Variable Returns to Scale. Applied to 12 listed enterprises using 2024 fiscal data, the methodology first identifies Energy Intensity as the paramount strategic priority via the BWM. Next, VIKOR mathematically compresses six heterogeneous environmental, social, and governance (ESG) criteria into a single composite index, thereby eliminating standard Data Envelopment Analysis dimensionality constraints. The Phase 3 Super-SBM results reveal profound sector heterogeneity. The macro-scale giant VGT defines the absolute efficiency frontier with an unprecedented score of 18.6729 and zero operational slack. However, the λ reference matrix identifies mid-cap operators such as Tien Son Thanh Hoa and Binh Duong Garment as highly replicable, agile benchmarks for the broader industry. Crucially, the non-radial projection analysis uncovers hidden structural vulnerabilities. The data show that while certain firms possess massive operational buffers, others operate on the absolute edge of the efficiency frontier, leaving them dangerously exposed to impending carbon-taxation shocks. Furthermore, the model identifies critical instances of ESG decoupling in which green investments fail to yield proportional increases in export revenues. These findings suggest that addressing the sustainability paradox requires targeted structural interventions informed by diagnostic benchmarking. Policymakers and corporate executives must integrate open innovation frameworks and systematic problem-solving methodologies to structurally decouple economic output from fossil-fuel energy dependence and outdated labor-arbitrage models. Full article

Post-combustion CO₂ capture is a key mitigation pathway for natural gas compression and processing infrastructure; the chilled ammonia process (CAP) and advanced amine-based capture (AAC) are the most technologically mature commercial options. Methods: This study presents a technical and economic comparison of CAP and AAC, combined with historical field emission measurements (11 June 2013) at two Romanian natural gas compression stations (S.N.G.N. Romgaz S.A., Mediaș, Romania): Cristur (downstream of a CAP unit) and Brateiu (uncaptured baseline), using a Multilyzer NG Series 213 analyzer (SYSTRONIK Elektronik und Systemtechnik GmbH, Illmensee, Germany). As the stations were not sampled under a controlled before/after protocol, the comparison is cross-sectional. Results: Flue gas CO₂ was lower at Cristur (at or below detection limit) than at Brateiu (6.8%), but this reading could not be reconciled with the analyzer’s own O₂-based calculation formula and is reported as an unresolved historical data-quality issue rather than as evidence of capture performance; co-pollutants (NO, NO_x, CO) were also lower at Cristur. An independent van’t Hoff-based thermodynamic estimate, anchored to ammonia-specific literature data, yields a CAP capture efficiency of 89.6–90.3% at typical operating temperature. A theoretical mass balance, using representative flow rates and literature capture efficiency, estimates 42,600–85,200 t CO₂/year captured. Literature capture costs range from 40 to 77 EUR/t (CAP) and 47 to 90 EUR/t (AAC), both largely below the current EU ETS price (81.35 EUR/t, June 2026), though no net economic benefit is quantified due to missing capital and ancillary cost data. Conclusions: CAP is thermodynamically capable of high CO₂ removal efficiency; the historical field data are directionally consistent but do not independently validate this. Beyond the historical dataset itself, this study contributes a reusable diagnostic cross-check for flue gas analyzer CO₂ readings, a recalibrated ammonia-specific thermodynamic estimation method, and a transparent framework for assessing capture technologies from incomplete legacy data; it is presented as a historical, illustrative case study and methodological reference for future, instrumentally verified monitoring campaigns. Full article

This study examines the agricultural energy transition in 25 European Union Member States over 2005–2024, focusing on energy intensity, fossil-fuel dependence, and carbon intensity. It integrates multi-regional Kaya–LMDI decomposition, Tapio decoupling analysis, and σ- and conditional β-convergence models to identify the components associated with changes in direct energy-related agricultural CO₂ emissions, assess their relationship with real agricultural gross value added, and determine whether national performance gaps are narrowing. The results show that declining energy intensity and fossil dependence were the main emissions-reducing components, while changes in country structure and carbon intensity partly offset these gains. Within the EU-25 analytical sample, the baseline comparison indicates a shift from recessive decoupling before 2020 to strong decoupling over 2020–2024. Sensitivity tests confirm the robustness of post-2020 strong decoupling, although the characterization of the pre-2020 period is sensitive to sample composition. Conditional β-convergence is observed for all three indicators, whereas σ-convergence is found only for energy intensity; fossil dependence and carbon intensity continue to exhibit substantial cross-country dispersion. Bias-corrected estimates preserve the direction of conditional catch-up but indicate slower adjustment, particularly for fossil dependence. The study’s novelty lies in jointly evaluating emissions decomposition, decoupling, and distributional change while distinguishing relative catch-up towards country-specific trajectories from convergence towards a common EU level. The findings identify energy efficiency, fossil-energy substitution, and differentiated national conditions as relevant areas for CAP-related monitoring and policy consideration. The conclusions concern specifically the energy-related component of agricultural decarbonization. Full article

Recombinant adeno-associated virus (rAAV) is a preferred vector in gene therapy, although high production costs inhibit widespread adoption. The most common approach for rAAV production involves transfection of HEK293 cells with three plasmids: pTransgene, pRep/Cap and pHelper. Producing sufficient amounts of these plasmids accounts for up to 40% of total batch costs. Initially, this work aimed to increase plasmid yields by replacing the backbones. While this approach increased pHelper yields, pRep/Cap and pTransgene yields were unaffected. A possible reason was identified: pTransgene contains inverted terminal repeat (ITR) sequences that are essential for rAAV production. ITRs have strong secondary structures (including hairpin loops termed B and C arms) that likely interfere with plasmid production. Therefore, targeted deletions were performed within the ITRs. Partial deletions in both the B and C arms of the ITR were most beneficial, as both plasmid yield and transgene expression increased. Importantly, partial deletions did not reduce rAAV yield, as had been previously observed when the B and C arms were fully deleted. In summary, we report a 140% increase in pHelper plasmid production, while the most successful ITR variant increased pTransgene plasmid yields by 57% and transgene expression by 28%, without reducing rAAV yields or transduction efficiency. Full article

To develop ultraviolet (UV)-curable resin with excellent mechanical, thermal-resistant and self-healing properties, epoxidized soybean oil was utilized as a bio-based raw material in this paper, and its epoxy groups were ring-opened and modified with methanol and tert-butyl acetoacetate to introduce hydroxyl groups and flexible segments, yielding a functionalized polyol, which was reacted with isophorone diisocyanate to prepare a hydroxyl-terminated polyurethane prepolymer containing dynamic covalent bonds. The prepolymer was further end-capped with hydroxyethyl acrylate to obtain a UV-curable polyurethane acrylate resin. The physico-mechanical properties and self-healing efficiency of the samples were systematically investigated. The results showed that the prepared specimens had efficient self-healing capability and could achieve efficient repair of damaged interfaces through appropriate heat treatment without the need for external catalysts; the onset decomposition temperatures of all the samples were greater than 225 °C, demonstrating good thermal stability; the tensile strength, tensile modulus, flexural strength and flexural modulus could be as great as 31.1 MPa, 393.7 MPa, 29.6 MPa and 851.6 MPa, respectively. All these indicated that the prepared samples had good overall performances. This study provides a new strategy for the design and preparation of self-healing photocurable resins based on renewable resources. Full article

To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation. Full article