Search Results (44,538)

Bee pollen is a nutrient-dense food; however, its dense cell wall limits the bioavailability and digestive absorption of nutrients. This study established a co-fermentation process that combines Lactobacillus strains isolated from bee bread with commercial probiotics to improve the nutritional profile and functional properties of bee pollen. L. acidophilus (LBA1) and L. plantarum (LBP3) were isolated from bee bread and used for single-strain fermentation of bee pollen and its co-fermentation with commercial probiotics. The results indicated that fermentation increased the protein, free amino acid, vitamin C, and flavonoid contents. The co-fermentation product (FHL-99) of LBP3 and the commercial inoculant (99 strains) exhibited the highest cell wall disruption rate (67.57%) in artificial intestinal juice. Ex vivo activity analysis revealed enhanced DPPH, hydroxyl, and ABTS⁺ radical scavenging capacities of fermented bee pollen. Its inhibitory effects on hyaluronidase activity and protein thermal denaturation were also enhanced. FHL-99 demonstrated optimal performance across multiple indices, achieving a DPPH radical scavenging rate of 77.46% and hyaluronidase inhibition rate of 37.38%. In conclusion, synergistic co-fermentation can disrupt pollen cell walls and enrich bioactive constituents, providing an efficient biotechnological approach for the development of high-quality fermented bee pollen products. Full article

The chlorophyll content of plant leaves measured by the soil plant analysis development (SPAD) is an important indicator for measuring crop growth status and irrigation effect. The rapid, non-destructive and efficient estimation of crop SPAD values is of great significance to the field management of crops. In this study, the canopy hyperspectral reflectance and SPAD values of winter wheat were obtained, and the spectral curve was changed through four spectral processing methods, including first-order differential (FD), second-order differential (SD), multivariate scattering correction (MSC), and Savitzky–Golay smoothing (SG) to improve the correlation between canopy spectral reflectance and SPAD. Furthermore, to investigate and evaluate the performance of various vegetation indices (VIs) in estimating SPAD values for winter wheat, existing published indices were optimized using random band combinations derived from multiple canopy spectral transformations. The optimized vegetation index was used as the input variable of the model, and six machine learning algorithms, including random forest (RF), long short-term memory network (LSTM), multilayer perceptron (MLP), deep recurrent neural network (Deep-RNN), gated recurrent unit (GRU), and convolutional neural network (CNN), were used to construct the winter wheat SPAD values estimation model, and the model was verified. The experimental results demonstrate that, when utilizing an equivalent number of optimized vegetation indices as input, the GRU-based model achieves higher estimation accuracy compared to other models. Specifically, the coefficient of determination (R²) is improved by 0.12 compared to the RF model, by 0.03 compared to the LSTM model, by 0.12 compared to the MLP model, by 0.02 compared to the Deep-RNN model, and by 0.02 compared to the CNN model. At the same time, the GRU model also has a lower root mean square error (RMSE) and relative error (RE) of 7.37 and 24.90%, respectively. This study provides valuable hyperspectral remote sensing technology support for the implementation of winter wheat SPAD values estimation in the field. Full article

As dockless bike-sharing systems rapidly expanded, this study aims to develop a flow-integrated framework for assessing bicycle usage efficiency, which addresses a critical gap in conventional static indicators. Existing studies rely primarily on big data to evaluate location-specific efficiency using Time-to-Booking (ToB). However, ToB ignores network flow effects while bicycles departing from the same location may reach destinations with vastly different ToB values. To overcome this, we propose a flow-integrated ToB (FwToB) index that incorporates the idle time at both the trip origin and destination. Applying this index to central Beijing reveals significant spatial heterogeneity while maintaining the original core-periphery pattern, indicating that most bicycles flow to areas with similar efficiency. Geographically weighted regression further shows that factors like population density, healthcare, shopping facilities, and distance to metro stations influence efficiency with substantial spatial non-stationarity. These findings advance the understanding of bike-sharing efficiency and offer insights for operators and urban planners. Full article

The objective of this study was to explore the effect of the assembly sequences of wall materials on the structure and properties of Antarctic krill peptide (AKP)-loaded ovalbumin (OVA)–chitosan (CS) nanoparticles (NPs). Two AKP-loaded NPs (CS/OVA-AKP and OVA/CS-AKP) were prepared by changing the sequences of OVA and CS. The results confirmed that CS/OVA-AKP had a smaller particle size (291 nm vs. 320 nm), lower polydispersity index (0.233 vs. 0.282), higher absolute zeta potential (34.4 mV vs. 32.1 mV), and higher encapsulation efficiency (81.6% vs. 75.4%) than OVA/CS-AKP. X-ray diffraction analysis confirmed that AKP was encapsulated in an amorphous state within the NPs. Fourier transform infrared spectroscopy and three-dimensional (3D) fluorescence spectroscopy revealed that electrostatic interactions, hydrogen bonding, and hydrophobic interactions were the primary driving forces for nanoparticle formation, with CS/OVA-AKP demonstrating a stronger OVA fluorescence quenching effect. Compared with OVA/CS-AKP, CS/OVA-AKP exhibited better redispersibility, and CS/OVA-AKP showed greater stability under various environmental factors (thermal treatment, salt concentration, pH, and storage time). During simulated gastrointestinal digestion, CS/OVA-AKP effectively protected AKP from gastric degradation and showed a higher AKP release rate in simulated intestinal fluid (61.1%) than OVA/CS-AKP (53.0%). The release followed the Korsmeyer–Peppas model, with OVA/CS-AKP exhibiting non-Fickian diffusion (n = 0.7500), and CS/OVA-AKP approached Case II transport (n = 0.9889), indicating erosion-controlled release behavior. CS/OVA-AKP also demonstrated higher hypoglycemic activity, with inhibition rates of 41.1%, 37.5%, and 36.1% for α-glucosidase, α-amylase, and DPP-IV, respectively. These findings underscore the important influence of wall-material assembly sequences on the structure and properties of AKP-loaded NPs, offering valuable insights for the development of bioactive peptide delivery systems. Full article

The replacement of fishmeal with plant protein is widely regarded as a key strategy for sustainable aquaculture. However, carnivorous marine fish often show limited tolerance to fishmeal-free diets. Here, we investigated growth performance, hepatic physiological responses, and molecular mechanisms underlying adaptation to a soy protein concentrate-based diet (SPCD) in golden pompano (Trachinotus ovatus). An 8-week feeding trial was conducted under communal rearing conditions, followed by the phenotypic stratification of SPCD-fed fish into high- and low-growth subgroups. Growth performance, serum biochemical indices, and liver histology were assessed, and integrated transcriptomic and metabolomic analyses were performed on liver tissue. At the population level, the SPCD resulted in reduced growth, a lower feed intake, and decreased feed utilization efficiency compared with a fishmeal-based diet. Notably, marked inter-individual variation was observed: fish fed the SPCD exhibited significantly lower final body weights and a higher FCR compared with the FMD group (p < 0.001), and pronounced growth divergence was observed between the PB and PS subgroups, with a subset of SPCD-fed fish maintaining growth comparable to fishmeal-fed controls, whereas others exhibited severely constrained growth. Divergent phenotypes were associated with distinct hepatic alterations, including aggravated vacuolation, the enrichment of tight junction-related and immune regulatory pathways, and the broad reprogramming of lipid metabolism. Integrated multi-omics analysis identified arachidonic acid metabolism as the most significantly perturbed pathway, characterized by altered membrane phospholipid composition, the upregulation of RARRES3L, increased COX/LOX-derived eicosanoids, and the suppression of the CYP–EET branch. Collectively, these findings indicate that soy protein replacement induces coordinated hepatic structural and metabolic remodeling, with tight junction disruption and arachidonic acid metabolic reprogramming contributing to inflammatory imbalance and divergent growth phenotypes in T. ovatus. Full article

Small communities in the Kingdom of Saudi Arabia (KSA) without a sewerage system commonly rely on septic tanks and long-distance transport of wastewater to the nearest centralized treatment facilities, resulting in high operational costs, social nuisance, and limited opportunities for treated effluent reuse. For a small community of 1300 persons in Al Qaraa (Qassim, KSA), this study performs life cycle analysis (LCA) to evaluate the environmental sustainability of a low-cost membrane bioreactor (LC-MBR)-type for decentralized on-site treatment as an alternative to wastewater transportation to a conventional extended aeration activated sludge process (EA-ASP)-type centralized system operating in the nearest larger city of Al-Bukayriyah. SimaPro^® 8.3.0.0 with the ecoinvent 3.0 database and ReCiPe 16 midpoint methodology shows that the decentralized LC-MBR scenario outperformed the centralized option with a 49 km-long wastewater transportation route in 13 out of 15 selected midpoint categories when considering relative and normalized impacts. In the EA-ASP, primary treatment dominated environmental impacts across most categories, driven by high energy demand for wastewater pumping, whereas freshwater and marine eutrophication were primarily influenced by treatment efficiency. With smaller normalized values, secondary treatment had a greater relative impact on urban and agricultural land occupation categories, attributed to the use of clay and rice bran in low-cost membrane fabrication in an LC-MBR. Tertiary treatment in the LC-MBR scenario, incorporating coagulation and granular activated carbon, significantly reduced freshwater eutrophication. Although normalized endpoint impacts indicated comparable ecosystem impacts for both systems, the LC-MBR resulted in 8% lower impacts on human health and 60% lower on resource depletion. Overall, the findings support decentralized wastewater treatment as a sustainable solution for small communities in arid regions and provide valuable insights for policy and decision-making. Full article

Digitalization and decarbonization are unfolding in parallel, yet firm-level evidence on whether digital economy development delivers substantive low-carbon performance remains mixed. Using a 2008–2022 panel of Chinese listed firms matched to a city-level digital economy index, we estimate lagged fixed-effects models and examine capability and governance channels through firm digital transformation and ESG disclosure. The local digital economy is positively associated with the green transition level (GT ) and transition speed (GTS ), and it significantly increases digital transformation (DT ) and ESG disclosure (ESG ), consistent with partial mediation. By contrast, effects on carbon intensity are small and become insignificant once year effects are included, indicating that short-run emissions outcomes are dominated by macro energy conditions and potential rebound forces. Overall, digital development appears to accelerate strategic transition and disclosure capacity more quickly than operational emissions efficiency. Policy implications are twofold: align digital infrastructure with ESG data governance and verification, and coordinate digitalization with energy-system reforms to enable sustained emissions reductions. Full article

Additive manufacturing (AM) has been increasingly explored in the construction sector for its potential to improve productivity, reduce waste, and enable design flexibility; however, reported outcomes remain inconsistent, and the relationship between AM and Lean Construction (LC) principles is not yet clearly established. This study addresses this gap through an exploratory, theory-building systematic review of 12 peer-reviewed research articles published between 2021 and 2025, examining AM technologies applied in construction, their associated application contexts, Lean principles, performance indicators, and implementation barriers. A mixed quantitative and qualitative analysis was conducted, combining descriptive bibliometric mapping with thematic synthesis to answer three research questions related to AM applications, Lean impacts, and performance measurement. Given the emerging nature of AM–LC integration and the limited number of eligible studies, the review prioritizes conceptual synthesis over empirical generalization. The results suggest that AM contributes primarily to waste reduction, process efficiency, standardization, and built-in quality when integrated with complementary digital and automation technologies. Nevertheless, significant technical, economic, socio-organizational, and regulatory barriers persist, limiting scalability and performance consistency. Based on the synthesized evidence, the study proposes a conceptual framework that interprets AM adoption as a Lean-oriented production system, where barriers act as system-level constraints and enablers function as Lean improvement mechanisms. This study further conceptualizes AM implementation as a Kaikaku-driven transformation that requires Kaizen-based stabilization through established LC tools. These insights contribute to advancing theoretical understanding of AM–LC integration and guide more effective and systematic implementation in construction projects. Full article

Underground tunnel construction projects using tunnel boring machines (TBMs) require a holistic risk perspective. Such projects face various risks arising from social, economic, political, workforce, and regulatory aspects during project execution. It is necessary to develop preventive strategies for managing these risks and thereby ensure timely project delivery, cost efficiency, and safety. In this study, we aimed to develop a comprehensive hybrid decision-making framework for analyzing risks in TBM-based tunnel construction projects. The proposed approach integrates the best–worst method (BWM), data envelopment analysis (DEA) model-based risk assessment, and the preference ranking organization method for enrichment evaluation (PROMETHEE). The BWM was applied to determine the weights of decision criteria with fewer comparisons and improved consistency. Subsequently, the DEA model was then used to compute local risk scores under multiple input and output conditions. Finally, PROMETHEE was employed to analyze the risks based on positive and negative outranking flows. The proposed approach was applied to a realistic metro construction project in Bangkok. The findings indicated that the proposed approach effectively compromised all the decision-making attributes to manage the uncertainties. The proposed methodology can support project managers, stakeholders, engineers, and relevant authorities in identifying high-priority risks and implementing effective mitigation strategies to enhance risk management in tunnel construction. Full article

Coal continues to play a significant role in Poland’s electricity generation system, making the sustainable management of environmental impacts from hard coal mining a critical challenge during the ongoing energy transition. In line with the European Green Deal and circular economy principles, reducing and managing mining-related waste emissions is an important component of sustainable development in regions undergoing a gradual phase-out of fossil fuel extraction. This study analyzes rock mass and dust emissions associated with underground hard coal mining in Poland over the period 2017–2025 using the most recent statistical data, including estimates for 2025 based on the first three quarters of the year. The scale, structure, and trends of emissions are examined to assess their implications for environmental sustainability, resource efficiency, and long-term land use. Particular attention is paid to the relationship between declining coal production and the relatively slower reduction in waste rock emissions, which indicates increasing contamination of extracted material and poses challenges for sustainable mining practices. The results show that while total coal output has decreased substantially, reductions in rock mass emissions have been less dynamic, highlighting the need for improved waste management strategies from a sustainability perspective. The study demonstrates that increasing the utilization of mining waste, through underground use and circular economy applications, can reduce environmental pressure, support compliance with sustainability policies, and mitigate long-term impacts on post-mining regions. Although the analysis focuses on Poland, the findings provide transferable insights for other countries seeking to balance energy security, mining sector restructuring, and sustainable development objectives during the transition away from fossil fuels. Full article

The internal thermal insulation structure serves as a vital subsystem within the thermal insulation system of high-temperature devices, playing a crucial role in effectively maintaining a high-temperature environment, reducing energy consumption, and enhancing testing efficiency. However, during the operation of these devices, the internal thermal insulation structure is inevitably subjected to high temperatures. Therefore, it is essential to focus on the heat transfer performance of this structure. Initially, the internal thermal insulation structure is designed, and the relative dimensions and materials of each component are determined. Subsequently, a finite element model of the internal thermal insulation structure is established, and numerical simulations of heat transfer are conducted under the device’s operating conditions to analyze the thermal insulation structure. This analysis is ultimately validated through high-temperature experiments conducted on specimens of the internal thermal insulation structure. The results indicate that the designed internal thermal insulation structure effectively maintains the high-temperature environment within the device and demonstrates excellent thermal insulation performance, with a maximum heat flux of 66.7 W/m² and an outer wall surface temperature of 25.98 °C. This work is significant as it lays the groundwork for the design and construction of such devices. Full article

Against the backdrop of China’s “Dual Carbon” strategy, transitioning to high-quality energy development (HQED) is imperative for balancing decarbonization with economic resilience. This study explores the transformative role of the digital economy as a primary driver of this transition. Using provincial panel data from 2013 to 2023, we employ a two-way fixed effects model to quantify the impact of digital economy on high-quality energy development. Our empirical results demonstrate that the digital economy significantly bolsters high-quality energy development, a finding that holds across rigorous robustness and endogeneity checks. Mechanism analysis reveals three critical transmission pathways: fostering technological innovation, accelerating industrial structure upgrading, and promoting industrial sophistication. Furthermore, heterogeneity analysis indicates a pronounced positive effect in the Eastern and Central regions, whereas the impact in the Western region remains limited, highlighting a “digital divide” in energy transition. These findings suggest that policymakers should prioritize digital infrastructure in lagging regions and leverage digital tools to bridge the gap between industrial upgrading and energy efficiency. Full article

Background/Objectives: Accurate evaluation of root angulation is essential for assessing root parallelism and orthodontic treatment outcomes. In routine clinical practice, this assessment is often performed by visual inspection of panoramic radiographs, which is subjective and prone to observer variability. The objective of this study was to develop and validate an artificial intelligence (AI)–based algorithm for automated, quantitative assessment of mesiodistal root angulations on panoramic radiographs and to evaluate its accuracy relative to conventional manual measurements. Methods: A total of 214 panoramic radiographs (orthopantomograms), comprising 4280 posterior teeth, were retrospectively selected after applying strict inclusion and exclusion criteria. Individual teeth were automatically segmented using a U²-Net–based deep learning architecture. Tooth long-axis orientation was calculated using principal component analysis, with exclusion of the apical third to minimize the influence of root curvature. Angular deviation was measured relative to fixed horizontal reference lines. Manual measurements performed by experienced examiners using 3D Slicer software served as the reference standard. Intra- and inter-examiner reliability, agreement between AI-based and manual measurements, intraclass correlation coefficients (ICC), and Bland–Altman analyses were calculated. Results: Manual measurements demonstrated excellent reliability, with intra-examiner and inter-examiner ICC values of 0.972 and 0.963, respectively. Agreement between the AI-based algorithm and manual measurements was also excellent (ICC = 0.941). Bland–Altman analysis showed a mean difference of −0.10°, with 95% limits of agreement ranging from −1.60° to 1.41°, indicating minimal bias and no proportional error. Conclusions: The proposed AI-based algorithm provides accurate, objective, and reproducible measurements of posterior tooth root angulations on panoramic radiographs. This approach may support clinical decision-making, reduce observer-related variability, and facilitate efficient assessment of root parallelism in orthodontic practice. Full article

Croatia’s tourism market is highly exposed to digital platforms and peer-to-peer information flows, yet evidence on how Croatian users differentiate between promotional formats (digital channels, agency websites, traditional media and word-of-mouth) remains fragmented and rarely translated into actionable priorities. This study aims to identify the underlying dimensions of perceived promotional influence and to prioritize promotional formats for destination choice in Croatia by integrating PCA and the Analytic Hierarchy Process (AHP). An online survey (N = 299) was used to extract promotional dimensions via PCA and to test group differences by gender, age and primary information source, while AHP translated expert judgments into a comparative priority structure. Results consistently indicate that word-of-mouth is the most persuasive driver of destination choice, but its perceived importance varies significantly across demographic segments and information-source profiles. Younger respondents place greater emphasis on digital channels (especially social media and travel agency websites), whereas older respondents show higher reliance on traditional formats. The combined PCA–AHP approach provides a structured bridge between user perceptions and managerial prioritization, offering segment-specific guidance for more efficient allocation of promotional resources in Croatian destination marketing. Full article

Buildings account for nearly 40% of global energy use and 36% of CO₂ emissions, positioning Net-Zero Energy Buildings (NZEBs) as vital for climate mitigation. However, large-scale adoption remains limited by technical, economic, and policy barriers. This study systematically reviews 1285 peer-reviewed articles (2015–2025) from Scopus and Web of Science, following PRISMA guidelines and thematic analysis to assess renewable energy integration and efficiency strategies. Results indicate that 70% of studies highlight emissions reduction and cost savings as key NZEB benefits, while 60% cite high storage costs and 45% report grid integration challenges. Only 30% of studies address policy dependency, revealing a research gap. Effective measures include passive solar design (up to 25% heating load reduction), high-performance envelopes (15–40% energy savings), and smart energy management (10–20% efficiency gains). Persistent obstacles involve high upfront costs, renewable variability, and rapid technological obsolescence. Achieving NZEB viability requires integrating energy-efficient design, affordable renewables, advanced storage, and coherent policy frameworks to accelerate the transition toward a sustainable, NZEB-built environment. Full article