Search Results (1,267)

The increasing energy crisis demands sustainable functional materials. Wood, with its natural three-dimensional porous structure, offers an ideal renewable template. This study demonstrates that microstructural engineering of wood is a decisive strategy for enhancing magnetothermal conversion. Using eucalyptus wood, we precisely tailored its pore architecture via delignification and synthesized Fe₃O₄ nanoparticles in situ through coprecipitation. We systematically investigated the effects of delignification and precursor immersion time (24, 48, 72 h) on the loading, distribution, and magnetothermal performance of the composites. Delignification drastically increased wood porosity, raising the Fe₃O₄ loading capacity from ~5–6% (in non-delignified wood) to over 14%. Immersion time critically influenced nanoparticle distribution: 48 h achieved optimal deep penetration and uniformity, whereas extended time (72 h) induced minor local agglomeration. The optimized composite (MDW-48) achieved an equilibrium temperature of 51.2 °C under a low alternating magnetic field (0.06 mT, 35 kHz), corresponding to a temperature rise (ΔT) > 24 °C and a Specific Loss Power (SLP) of 1.31W·g⁻¹. This performance surpasses that of the 24 h sample (47 °C, SLP = 1.16 W·g⁻¹) and rivals other bio-based magnetic systems. This work establishes a clear microstructure–property relationship: delignification enables high loading, while controlled impregnation tunes distribution uniformity, both directly governing magnetothermal efficiency. Our findings highlight delignified magnetic wood as a robust, sustainable platform for efficient low-field magnetothermal conversion, with promising potential in low-carbon thermal management. Full article

Background: Peri-implantitis, a condition characterized by inflammation and progressive bone loss around dental implants, presents a significant challenge in contemporary dentistry. Conventional non-surgical treatments often fail to fully eliminate bacterial biofilms, particularly on complex implant surfaces. Laser therapies have emerged as potential adjuncts due to their antimicrobial and bio-modulatory properties. However, their microbiological effectiveness and suitability for individualized patient treatment planning remain unclear. Objective: Τhis study aims to systematically assess and synthesize the microbiological effects of various laser-assisted non-surgical treatments for peri-implantitis compared to conventional mechanical debridement. Methods: This systematic review and meta-analysis followed PRISMA guidelines and was registered in PROSPERO (CRD420251035354). Randomized controlled trials (RCTs) evaluating microbiological changes following laser-assisted non-surgical treatment of peri-implantitis, with a minimum follow-up of one month, were identified through searches in multiple databases and registries up to February 2025. The ncluded studies used lasers such as diode, Er: YAG, and photodynamic therapy (PDT) either alone or as adjuncts to mechanical debridement. Outcomes of interest included bacterial counts. Risk of bias was assessed using the RoB2 tool, and certainty of evidence was evaluated via GRADE. Quantitative synthesis used random-effects meta-analysis, with standardized mean differences (SMDs) calculated. Results: Eight RCTs involving 266 patients and 335 implants were included in the systematic review. Quantitative synthesis of three pathogens (counts of Fusobacterium nucleatum, P. gingivalis, T. denticola) across three studies displayed no statistically significant differences between laser and control groups at 3 and 6 months (p > 0.05 for all comparisons). When examining individual study findings, PDT, particularly in patients with diabetes or acute abscess, showed short-term reductions in red complex bacteria (e.g., Porphyromonas gingivalis and Treponema denticola). In contrast, diode and Er: YAG lasers demonstrated inconsistent or transient effects. The quality of evidence was rated as very low according to GRADE. Conclusions: Laser-assisted therapies, especially PDT, may provide targeted microbiological benefit in selected patient groups, supporting their adjunctive use within personalized treatment planning rather than as replacements for mechanical debridement, which remains the gold standard. Further high-quality RCTs incorporating well-defined patient risk profiles, such as systemic conditions and behavioral factors, and precision treatment algorithms are needed. Full article

The rates of CO₂ mass deposition onto cryogenically cooled surfaces are crucial for CO₂ removal processes that rely on cryogenics. A dedicated experimental setup was constructed to measure CO₂ mass deposition rates under controlled conditions. Experiments were carried out with both pure CO₂ and CO₂/N₂ mixtures, growing frost layers up to 8 mm thick. Results demonstrated that heat transfer through the frost layer significantly slows down the mass deposition process. Furthermore, it was found that the addition of N₂ to the gas phase has a considerable influence on mass deposition rates, because it introduces an additional mass transfer resistance toward the frost surface. To describe the experimentally observed behavior, a frost growth model based on mass and energy balances was developed. Expressions for the frost density as a function of the frost temperature and for the effective frost conductivity as a function of the frost density were derived and implemented in the model. When accounting for drift fluxes, the model accurately captures the behavior observed in experiments. The findings of this work highlight the significant impact of heat transfer limitations on processes that accumulate a thick solid CO₂ layer, such as continuously cooled heat exchangers. Conversely, technologies like cryogenically refrigerated packed beds do not develop a thick solid CO₂ layer; calculations showed that a frost layer of 3.24∙10⁻⁵ m is formed, resulting in a Biot number well below 0.01, indicating that heat transfer in the frost layer is not limiting. Full article

Ethylene–vinyl acetate (EVA) copolymers are widely used in packaging, films, foams, and adhesives because of their softness and optical clarity; however, their relatively low mechanical strength limits broader applications. In this study, a scalable masterbatch strategy was developed to reinforce EVA by introducing TEMPO-oxidized cellulose nanofibers (T-CNFs), pre-encapsulated within an ethylene–vinyl alcohol (EVOH) matrix. EVOH acted as a compatibilizer, establishing robust hydrogen bonding with T-CNFs (evidenced by a 2.73-fold increase in the hydrogen bonding index) and thereby promoting their uniform dispersion and strong interfacial adhesion in the hydrophobic EVA phase. The resulting nanocomposites demonstrated significant improvements in mechanical performance, achieving a maximum 1.54-fold increase in tensile strength and a 1.42-fold increase in Young’s modulus compared to neat EVA. These findings highlight a practical route to produce bio-based, mechanically enhanced EVA nanocomposites with potential for industrial-scale applications. Full article

Contemporary neural and generative architectures are deficient in self-preservation mechanisms and sustainable stability. In uncertain or noisy situations, they frequently demonstrate oscillatory learning, overconfidence, and structural deterioration, indicating a lack of biological regulatory principles in artificial systems. We present Bio-RegNet, a meta-homeostatic Bayesian neural network architecture that integrates T-regulatory-cell-inspired immunoregulation with autophagic structural optimization. The model integrates three synergistic subsystems: the Bayesian Effector Network (BEN) for uncertainty-aware inference, the Regulatory Immune Network (RIN) for Lyapunov-based inhibitory control, and the Autophagic Optimization Engine (AOE) for energy-efficient regeneration, thereby establishing a closed energy–entropy loop that attains adaptive equilibrium among cognition, regulation, and metabolism. This triadic feedback achieves meta-homeostasis, transforming learning into a process of ongoing self-stabilization instead of static optimization. Bio-RegNet routinely outperforms state-of-the-art dynamic GNNs across twelve neuronal, molecular, and macro-scale benchmarks, enhancing calibration and energy efficiency by over 20% and expediting recovery from perturbations by 14%. Its domain-invariant equilibrium facilitates seamless transfer between biological and manufactured systems, exemplifying a fundamental notion of bio-inspired, self-sustaining intelligence—connecting generative AI and biomimetic design for sustainable, living computation. Bio-RegNet consistently outperforms the strongest baseline HGNN-ODE, improving ARI from 0.77 to 0.81 and NMI from 0.84 to 0.87, while increasing equilibrium coherence $\kappa$ from 0.86 to 0.93. Full article

Food loss and waste (FLW) is a chronic problem across food systems worldwide, with meat being one of the most resource-intensive and perishable categories. The perishable character of meat, combined with complex cold chain requirements and consumer behavior, makes the sector particularly sensitive to inefficiencies and loss across all stages from production to consumption. This review synthesizes the latest advancements in new preservation technologies and supply chain efficiency strategies to minimize meat wastage and also outlines current challenges and future directions. New preservation technologies, such as high-pressure processing, cold plasma, pulsed electric fields, and modified atmosphere packaging, have substantial potential to extend shelf life while preserving nutritional and sensory quality. Active and intelligent packaging, bio-preservatives, and nanomaterials act as complementary solutions to enhance safety and quality control. At the same time, blockchain, IoT sensors, AI, and predictive analytics-driven digitalization of the supply chain are opening new opportunities in traceability, demand forecasting, and cold chain management. Nevertheless, regulatory uncertainty, high capital investment requirements, heterogeneity among meat types, and consumer hesitancy towards novel technologies remain significant barriers. Furthermore, the scalability of advanced solutions is limited in emerging nations due to digital inequalities. Convergent approaches that combine technical innovation with policy harmonization, stakeholder capacity building, and consumer education are essential to address these challenges. System-level strategies based on circular economy principles can further reduce meat loss and waste, while enabling by-product valorization and improving climate resilience. By integrating preservation innovations and digital tools within the framework of UN Sustainable Development Goal 12.3, the meat sector can make meaningful progress towards sustainable food systems, improved food safety, and enhanced environmental outcomes. Full article

In recent years, the quality of genome assemblies has notably improved, primarily due to advances in third-generation sequencing technologies and bioinformatics tools. In the present study, we obtained genome assemblies for two flax (Linum usitatissimum L.) varieties, K-3018 and Svyatogor, using Oxford Nanopore Technologies (ONT) simplex R10.4.1 data and the Hifiasm algorithm optimized for ONT reads. The K-3018 genome assembly was 491.1 Mb and consisted of thirteen full-length chromosomes and two one-gap chromosomes. The Svyatogor genome assembly was 497.8 Mb and consisted of twelve full-length chromosomes and three one-gap chromosomes. All chromosomes had telomeric repeats at their ends for both varieties. Hi-C contact maps and Illumina genomic data supported the accuracy of the obtained assemblies. The K-3018 and Svyatogor genome assemblies surpassed the quality of the best currently available flax genome assembly of variety T397, which serves as a reference for L. usitatissimum in the NCBI Genome database. Comparative analysis revealed that the flax genomes are generally quite similar at the chromosome level, with only a few large-scale differences. Thus, two near-T2T (telomere-to-telomere) flax genomes were assembled from the ONT simplex R10.4.1 reads using Hifiasm ONT without involving Pacific Biosciences (PacBio) HiFi or ultra-long ONT reads as well as optical maps. High-quality flax genomes are essential for improving the efficiency of genetic research, evaluating genetic diversity at the whole-genome level, and developing breeding and genome editing approaches of this valuable multipurpose crop. Full article

Flow velocity is a key environmental factor that exerts multifaceted effects on fish growth and adaptation. Through long-term natural selection, fish have evolved adaptability to specific flow conditions, which not only relate to oxygen supply and food acquisition but also play a decisive role in reproduction, development, and population maintenance. To investigate the genomic mechanisms through which hydrodynamic environments drive divergence in closely related species, we focused on two sister species, Hemiculter bleekeri and Hemiculter leucisculus, which are adapted to contrasting flow regimes. We generated high-quality, chromosome level telomere-to-telomere (T2T) genomes and integrated comparative genomic analyses, we investigated the genetic basis underlying body shape regulation and reproductive strategies, aiming to decipher the adaptive evolutionary patterns of these species in response to differing hydrodynamic conditions from an integrated genotype phenotype perspective. We integrated PacBio HiFi, Hi-C, and Oxford Nanopore Technologies (ONT) ultra-long read sequencing data to construct high-quality T2T reference genomes for both species. The final genome assemblies are 0.998 Gb for H. bleekeri and 1.05 Gb for H. leucisculus, with each species possessing 24 chromosomes and all chromosomal sequences assembled into single contigs. Contig N50 values reached 40.45 Mb and 40.66 Mb, respectively, and both assemblies are gap-free. BUSCO assessments yielded completeness scores of 99.34% for both genomes, confirming their high continuity and accuracy. Integrated morphometric and genomic analyses revealed distinct adaptive strategies in two Hemiculter Species. H. bleekeri has evolved a streamlined body, underpinned by expansions in body shape related genes, and a pelagic egg strategy. In contrast, the adhesive egg strategy of H. leucisculus is supported by expansions in adhesion-related gene families. This divergence reflects adaptation to distinct flow velocity. By combining high-quality chromosome-level T2T genomes with morphometric and comparative genomic approaches, this study establishes a comprehensive framework for understanding the molecular mechanisms underlying adaptive evolution in freshwater fishes inhabiting contrasting flow velocity. Full article

Examining the long-term spatiotemporal distribution of grassland types and their transitions is crucial for better understanding regional and global changes. Most research in this field has examined the spatial distribution, temporal dynamics of grasslands, and their causes as a unified entity. This study predicted the distribution of nine major grassland types in Xinjiang under three climate change scenarios from 2041 to 2100 based on 1980s grassland maps, field data in 2023, and 28 factors. The total area of the nine grassland types showed a decreasing trend from 2041 to 2100. The lowland meadow (LM), temperate meadow steppe (TMS), temperate steppe desert (TSD), temperate desert steppe (TDS), and mountain meadow (MM) expanded, while significant declines occurred in alpine meadow (AM), alpine steppe (AS), temperate desert (TD), and temperate steppe (TS). Among cumulative contribution rate of the 28 factors examined in this study, NDVI, vegetation type, slope, elevation, soil_symbol, soil_ph, Bio1, Bio5, Bio8, Bio9, Bio10, Bio12, Bio13, Bio15, and Bio18 played important roles in most grassland types. LM, TD, and AS grassland were found to be more sensitive to E (environment), while AM, TDS, and TSD were more influenced by T (temperature). The distributions of MM and TMS are significantly influenced by the combined effects of all three categories of factors. For TS, the impacts of both temperature and environmental factors are substantial. These findings provided a robust foundation for conservation planning and the sustainable management of grassland ecosystems in temperate and alpine regions. Full article

Background/Aim: Extracellular-to-total body water ratio (ECW/TBW) and phase angle (PhA, PA) reflect hydration and cellular health, but their relationship with bone, muscle, and fat, as primary components of body composition, is not fully elucidated. This study aimed to evaluate sex-specific differences in body composition and assess the diagnostic potential of ECW/TBW and PhA for identifying low bone/muscle mass, as well as increased fat mass, in generally healthy adults. Methods: This post hoc analysis utilized data from a multicenter, cross-sectional, Italian study (2010–2014) that included 20–90 years adults (n = 9717). Body composition was measured by bioelectrical impedance (BIA-ACC, BioTekna^®), assessing bone, muscle mass, fat mass, ECW, TBW, and PhA. Low bone/muscle mass, as well as adiposity, were defined using standard cutoffs. Associations were examined using nonparametric tests and multiple regression analyses. Results: The mean age of men and women was similar (mean ~48 years). Men had significantly higher body mass index (BMI), intramuscular adipose tissue (IMAT%), T-score (bone), S-score (muscle), and PhA, while women had significantly higher fat mass (FM%) and ECW/TBW. ECW/TBW showed excellent discrimination for low muscle mass (AUC 0.845–0.922) and low bone mass (AUC 0.696–0.885), outperforming PhA. Neither ECW/TBW nor PhA reliably predicted increased fat mass. Regression models indicated ECW/TBW was strongly associated with age, sex, BMI, fat mass, and bone/muscle scores (R² = 0.943), whereas PhA’s association was moderate (R² = 0.368). Conclusions: ECW/TBW and PhA reflected sex-specific differences for body composition and effectively identified low muscle and bone mass (with better predictability of the former). Both showed a limited predictive ability for fat mass. Overall, both parameters provide complementary insights into sarcopenia and osteopenia and could be used for easy and non-invasive screening for these conditions. Full article

Optical fiber sensors (OFSs) have emerged as essential tools in the monitoring of physical, chemical, and bio-medical parameters in harsh situations due to their high sensitivity, electromagnetic interference (EMI) immunity, and long-term stability. However, the current literature contains scattered information in most reviews regarding individual sensing technologies or domains. This study provides a structured exploratory review in a novel inter-family analysis of both intrinsic and extrinsic configurations by analyzing more than 23,000 publications between 2019 and 2025 in five key domains: industry, medicine and biomedicine, environmental chemistry, civil/structural engineering, and aerospace. The analysis aims to critically discuss how functional principles/parameters and methods of interrogation affect the applicability of different OFS categories. The results reveal leading trends in the use of techniques like the use of fiber Bragg gratings (FBG) and distributed sensing in high-accuracy conditions or the rising role of extrinsic sensors in selective chemical situations and point out new approaches in areas like Artificial Intelligence (AI)- or Internet of Things (IoT)-integrated sensors. Further, this synthesis not only connects pieces of knowledge but also defines the technological barriers in terms of calibration cost and standardization: this provides strategic insight regarding future research and the scalability of industry deployment. Full article

Water inrush from flooded goaf under high hydraulic head seriously threatens deep coal mining, especially where roadways must be driven close to old workings. This study investigates the seepage and load-bearing behavior of a combined coal pillar and rigid cutoff wall system under coupled mining-excavation-seepage processes. A three-dimensional hydro-mechanical model based on Biot poroelasticity and a stress-damage-permeability relationship is developed in FLAC3D, using a field case from the Yuwu Coal Mine. Different wall thicknesses and mining stages are simulated, and pillar performance is quantified by the elastic-core volume fraction and a permeability-connectivity index. Similar-material shear tests are further carried out to examine sliding behavior at the wall–pillar interface. Simulations show that the composite system reduces peak vertical stress in the pillar by 12–20% during panel retreat (from 54.2 MPa without a wall to 47.7–45.0 MPa with 0.5–2.5 m walls), while the elastic core volume fraction increases from 16.7% to 30.4–50.4% and the minimum elastic core width improves from 0.5 m to 1.5–2.0 m. The wall provides strong lateral confinement, increasing lateral stress within the pillar by up to 50% and preventing hydraulic penetration for wall thicknesses ≥1.0 m. Shear tests reveal critical distances for safe load transfer and support the use of targeted reinforcement at the interface. The findings offer a quantitative basis for designing safe water-control structures in high-pressure goaf environments. Full article

The large-scale integration of renewable energy systems requires hydrogen storage technologies that can decouple energy production from energy utilization and allow for seasonal storage. Metal hydrides can offer higher volumetric energy density and operational safety than compressed H₂ but are limited by heat-transfer constraints that slow hydrogen absorption and desorption. This work investigates the performance of metal hydride–phase-change material hydrogen storage systems through advanced numerical modeling. Five reactor geometries are evaluated to quantify how longitudinal fins, transversal fins, helical fin structures, and graphite-enhanced composites influence heat removal, charge/discharge rates, and overall power density. Results show that longitudinal and transversal fins accelerate hydrogen absorption and desorption, reducing cycle times by up to 80.6%. The optimized finned helix configuration achieves the highest performance, with a power density of 2.55 kW/kg and charge/discharge powers of 6.75 kW and 13.25 kW, respectively. Expanded graphite further enhances kinetics in low-Biot-number designs, reducing cycle times by more than 30%. These findings provide design guidelines to maximize performance and efficiency of solid-state hydrogen storage for medium- and high-power applications. Full article

This article investigates the influence of wall permeability on channel flows and addresses the lack of studies that quantify entropy generation in magnetized Casson fluid models using wavelet-based numerical schemes. We introduce a Fibonacci Wavelet Collocation Method (FWCM) to efficiently solve the transformed nonlinear ordinary differential equations and demonstrate its applicability to the coupled momentum and energy equations. The analysis includes detailed graphical and numerical evaluations of entropy generation, temperature, and velocity fields, along with the Bejan number, Nusselt number, and skin-friction variations. The results reveal that entropy generation increases by approximately 18–22% with a higher Biot number and by nearly 15% with increasing Grashof number, while it decreases by about 12% for higher Eckert numbers. Magnetic field strength exhibits a dual effect, producing both suppressing and enhancing behaviors depending on parameter ranges. The FWCM solutions show strong agreement with previously published data, confirming both accuracy and robustness. Full article

The stem–branch junction in trees demonstrates exceptional structural design. This study examined two key features of the branch junction in common ash (Fraxinus excelsior L.) wood: the interlocked area (ILA) formed above a knot and the spatial arrangement of fibers in the junction. Bio-inspired by the microstructural features revealed by micro-computed tomography imaging, we developed 3D-printed models and compared their mechanical performance to standard symmetrical T-joints. We evaluated the models using mechanical tests and finite element modeling (FEM). Asymmetrical 3D-printed joints mimicking vessel and fiber distribution in the stem–branch junction were 2% stiffer in the elastic region than symmetrical joints and showed, on average, 10% lower deflection at failure. While the ILA had minimal effect on elastic stiffness, measured surface strain analysis indicated that it positively influenced the redistribution of shear strain in the junctions. Thanks to the bio-inspired design, the joints were stiffer and can be utilized in multiple design configurations while maintaining the same underlying principle. Full article