Search Results (17,492)

Nanofillers are widely used to enhance the performance of polymer composites; however, their effectiveness strongly depends on their physicochemical properties and dispersion behavior. In this study, five commercially available nanofillers, namely multi-walled carbon nanotubes (CNTs), nanoclay, halloysite, Cloisite^® 30B, and zinc oxide (ZnO), were comprehensively characterized as potential modifiers of unsaturated polyester resin. The results confirm the characteristic chemical composition and crystalline structure of all investigated nanomaterials. CNTs exhibited the highest specific surface area (213.7 m² g⁻¹) and pore volume, whereas ZnO showed the lowest median equivalent particle diameter determined by laser diffraction (D₅₀ = 2.09 μm). The clay-based fillers displayed comparable particle size distributions, with D₅₀ values ranging from 8.29 to 9.00 μm. SEM observations revealed substantial differences in morphology and agglomeration state, with CNTs forming compact entangled agglomerates, while ZnO exhibited the most homogeneous microstructure. Suspension stability analysis demonstrated that particle size alone could not explain the observed sedimentation behavior. ZnO exhibited the highest dispersion stability, whereas halloysite and Cloisite showed progressive sedimentation. Nanoclay displayed delayed destabilization associated with agglomeration processes, while CNT suspensions were governed by structural rearrangements rather than classical sedimentation. The obtained results indicate that the dispersion behavior of nanofillers in unsaturated polyester resin is associated with differences in particle size, morphology, and agglomeration tendency. The presented comparative characterization provides a basis for the rational selection of nanofillers for polyester resin-based nanocomposites. Full article

Semi-supervised fine-grained classification suffers from accumulating pseudo-label errors among potentially confusable classes when labeled data are scarce, yet negative-rule information that excludes classes at the attribute level remains unused. We propose AW-RS-ABL, a semi-supervised abductive learning method that fuses intra-class and inter-class attribute importance within rough sets and couples positive-rule confidence matching with negative-rule candidate-set reduction for pseudo-label correction. Samples, attributes, and labels form a decision information system $S=(U,A,F,d)$. Inter-class discriminative power is measured by positive-region dependency ${\gamma }_A\left(d\right)$ and intra-class stability by class-conditional entropy $H(a\mid d)$; the two are normalized and linearly fused into an attribute weight that selects a key attribute subset $A^{*}$. Weighted positive rules and high-confidence negative rules are built on $A^{*}$: negative rules shrink the candidate class set, and positive rules complete the correction via confidence matching. Rule consistency checking is embedded in the semi-supervised pseudo-label loop so that rule verification and perceptual model prediction co-evolve across training iterations. On six datasets spanning SAR target recognition, medical diagnosis, and agricultural classification at a reported 10% label ratio, AW-RS-ABL has the highest reported mean top-1 accuracy in each comparison, with displayed mean differences of 1.36–2.58 percentage points relative to FixMatch-Attr. Exact paired Wilcoxon tests with Holm correction support the differences for five datasets, whereas the difference for Dermatology is not significant. On the imbalanced Nursery test set, a representative seed yields 87.34% accuracy but 73.54% macro-F1 and 18.18% recall for the minority class. The reported formulation relies on conditional attributes, and its results remain conditional on their representation and binarization. Full article

Soil contamination represents a pervasive and multifaceted threat to environmental integrity, public health, and sustainable land use. In response to this challenge, this systematic review synthesizes recent advancements in sustainable soil remediation techniques, with an emphasis on bioremediation, nature-based solutions (NBSs), innovative physicochemical methods, and multidimensional assessment frameworks. Utilizing the adapted PRISMA methodology, 3222 peer-reviewed articles published between 2015 and 2025 were initially identified, with 53 studies selected for in-depth evaluation based on methodological rigor, innovation, and relevance to sustainability. The findings reveal a pronounced research trajectory toward biologically mediated remediation strategies, including microbial bioremediation, phytoremediation, and vermiremediation, as well as hybrid systems that incorporate biochar and nano-enabled materials to enhance efficacy. Concurrently, emerging physicochemical techniques, such as stepped steam heating and composite stabilization using fly ash demonstrate potential for high-efficiency contaminant immobilization with reduced environmental trade-offs. The integration of computational tools, particularly machine learning for remediation optimization, and the application of life cycle assessment (LCA) and Multi-Criteria Decision Analysis (MCDA), are redefining how sustainability is quantified and operationalized. In addition to technical innovation, the review underscores critical policy and socio-economic dimensions, including regulatory fragmentation, funding asymmetries, and stakeholder engagement. Comparative analyses of EU and US regulatory frameworks highlight the impact of governance structures on implementation scalability and public acceptance. The review concludes by advocating for a paradigm shift toward holistic, transdisciplinary remediation approaches that are ecologically resilient, economically viable, and socially just aligned with the Sustainable Development Goals (SDG 15.3) and the Paris Agreement. This review provides a comprehensive and integrative perspective on the current state and future directions of sustainable soil remediation, offering a strategic foundation for researchers, policymakers, and practitioners engaged in the restoration of contaminated lands. Full article

Renal cell carcinoma (RCC) comprises molecularly diverse tumor subtypes. This diversity is reflected in distinct and adaptable gene-expression programs that enable tumor cells to reprogram metabolism and survive therapeutic pressure. By regulating RNA processing, export, stability, decay, and translation, messenger RNA (mRNA) modifications may help shape these programs. Examining mRNA modifications is therefore important for understanding metabolic adaptation and treatment resistance in RCC. This narrative review focuses on RCC studies of N6-methyladenosine (m⁶A), 5-methylcytosine (m⁵C), N7-methylguanosine (m⁷G), and N4-acetylcytidine (ac⁴C). We focus on protein-coding transcripts and mRNA-centered mechanisms. Transcript-level studies are most extensive for m⁶A, while selected m⁵C and ac⁴C studies have identified defined regulator–mRNA axes. By comparison, RCC data for specific internal m⁷G sites in mRNA remain largely indirect. Many reported links with immune features or treatment response are based on retrospective analyses rather than treatment-specific clinical validation. Different modification pathways converge on PI3K/AKT, Hippo/YAP, metabolism, and treatment resistance, although direct molecular crosstalk has not been shown in RCC. No RNA-modification biomarker or targeted agent is used in routine RCC care. Further progress will require orthogonal site validation, broader coverage of RCC subtypes, and prospective studies conducted within contemporary treatment settings. Full article

Stabilized proposal pricing may reduce exact subproblem work, but it cannot by itself certify branch-and-price node termination. A conditional, tolerance-adjusted node-pricing bound is developed for deterministic unit commitment. At the unstabilized restricted-master dual, CSDW-S applies a Phase-II cascade comprising a period-separable operational-envelope bound (Tier E), a chronology-preserving ramp-relaxed dynamic-programming bound (Tier D), and exact mixed-integer-programming pricing fallback. Relaxed optimizers are proof objects rather than master columns; CSDW-X prices every Phase-II unit exactly. The mechanism was evaluated in a prespecified 79-task study with a 600 s scientific deadline per task. In the primary 24-pair, 24 h horizon set, accepted root endpoints were returned by CSDW-S and CSDW-X in 15 and 24 conditions, respectively. Across the 15 jointly accepted pairs, the maximum absolute bound difference was $2.24\times {10}^{-8}$. Exact true-dual unit solves were reduced by CSDW-S in all 15 pairs (median paired difference, $-29,228$), although CSDW-S was slower in 14 pairs (median paired difference, $+20.7$ s). The previously submitted 10-cell assessment did not conform to the primary acceptance criteria. It is therefore retained separately as historical evidence, with completion flags of 0/10 for CSDW-S and 9/10 for CSDW-X, and is not pooled with the new study. Mechanism, tolerance, horizon stress, and two small full tree contrasts support a qualified interpretation. Exact pricing workload can be reduced by the selective cascade when an endpoint is completed. Full article

Tailless underactuated hypersonic glide vehicles rely on elevons alone to control both roll and yaw. The dual-loop cascade architecture, in which differential elevon deflection regulates sideslip and the resulting sideslip response drives roll, exploits the high roll-to-yaw ratio to address lateral–directional underactuation. However, because the inner loop relies on sideslip angle feedback, its performance is sensitive to composite measurement bias. This study first analyzes lateral–directional open-loop divergence, the high roll-to-yaw ratio, and adverse yaw induced by differential elevons using a six-degree-of-freedom model and linearizations at multiple trim points, and then develops a baseline cascade controller employing stability-axis yaw-rate feedback. A first-order Gauss–Markov process with a constant offset is subsequently used to represent sideslip angle measurement bias. A linear extended state observer is introduced only in the velocity–bank angle outer loop to jointly estimate and compensate for the equivalent effect propagated by the bias, aerodynamic perturbations, center-of-mass offsets, and residual inner-loop dynamics. Observer parameters are selected through input direction identification, hierarchical two-dimensional parameter sweeps, and local grid verification. Local stability and boundedness near the design operating point are analyzed under bounded-input assumptions at the levels of the observer error, velocity–bank angle tracking error, and complete attitude control closed loop. Strictly paired Monte Carlo simulations and ablation experiments show that the proposed method effectively attenuates the propagation of sideslip angle measurement bias into the roll channel, improves velocity–bank angle tracking accuracy and response consistency under random uncertainties, and does not appreciably increase the required elevon position command envelope. Full article

In this work, 1%Pd/γ-Al₂O₃ catalysts modified with poly(4-vinylpyridine) (P4VP), polyacrylamide (PAM), and polyacrylic acid (PAA) were synthesized and evaluated for allyl alcohol hydrogenation. The effect of P4VP content was systematically investigated by varying the polymer loading, followed by comparison of the catalytic properties of the modified catalysts with that of the unmodified 1%Pd/γ-Al₂O₃ catalyst. The synthesized catalysts were characterized by TGA, IR spectroscopy, XRD, TEM, XPS, SEM/EDS, and viscosimetry to evaluate their structural, morphological, surface, and elemental properties. TEM analysis revealed that low P4VP loading preserved small Pd nanoparticles (3.9 nm), whereas higher polymer loadings promoted particle growth to 7.7 nm. All catalysts achieved complete conversion of allyl alcohol. At 5 wt.% polymer loading, the P4VP-modified catalyst exhibited a slightly higher hydrogenation rate than the PAA- and PAM-modified catalysts. Decreasing the P4VP content from 5 to 3 and 1 wt.% increased the hydrogenation rate from 8.3 × 10⁻⁶ to 13.9 × 10⁻⁶ and 22.9 × 10⁻⁶ mol/s, respectively, while propanol selectivity increased from 64 to 65 and 71%. The 1%Pd–P4VP(1%)/γ-Al₂O₃ catalyst exhibited higher catalytic activity than the unmodified 1%Pd/γ-Al₂O₃ catalyst and maintained good stability over 20 consecutive substrate additions. These findings demonstrate that the catalytic behavior of polymer-modified 1%Pd/γ-Al₂O₃ catalysts depends on the balance between polymer loading, Pd nanoparticle size, and active site accessibility. Full article

Undercutting significantly affects the mechanical stability of earthen archaeological sites and represents a critical parameter for heritage conservation decision-making. To quantify undercutting volume, this study developed a methodology coupling close-range photogrammetry with semantic segmentation. We selected seven earthen sites spanning diverse climatic and historical contexts, acquired 3D models, and generated RGB-DSM fused images. A dataset of 576 samples was established with manual annotations of undercutting and co-occurring deterioration (holes, fissures, and gullies). For deterioration identification, we employed an enhanced U-Net architecture featuring reduced down-sampling, a dilated convolution context module in the bottleneck, an FPN-style decoder, and an optimized loss function. The model achieved per-class IoU values of 0.485–0.510 for co-occurring deterioration and 0.668 IoU (0.801 F₁-score) for undercutting. Volume was computed by fitting a reference surface above the undercutting zone and integrating pixel-wise elevation differences. Analysis showed that DOM/DSM should be acquired as perpendicular to the wall as possible, because angular deviations introduce geometric underestimation of the area and reduce recognition performance. The observed volume CV of 8–25% far exceeds the theoretical 4.2% from geometry alone, confirming recognition variability as the dominant uncertainty source. By simplifying 3D point cloud recognition to a 2D image task, this approach avoids prohibitive annotation and computational costs, offering a practical solution for linearly distributed earthen sites and providing essential data for structural safety assessment and deterioration mechanism studies. Full article

Physical unclonable functions (PUFs) convert device-specific physical variations into responses for chip identity, key reconstruction, secure boot, and hardware roots of trust. This review examines the complete PUF chain from entropy generation and response digitization to stabilization, post-processing, deployment, security evaluation, and low-power implementation. Mature CMOS delay, SRAM, and DRAM PUFs are treated as engineering baselines, while representative emerging-memory PUFs provide comparison points for a MRAM-centered analysis. The main focus is placed on MRAM PUFs, including static MTJ variation, stochastic STT/SOT switching, response digitization and stabilization, reconfigurability, magnetic-specific attack surfaces, and system integration. The main contents include MRAM-PUF energy costs across device operation, raw-response generation, response stabilization, key reconstruction, and complete authentication. This cross-layer perspective distinguishes cell-level read/write energy from repeated sampling, reliable-bit-selection, ECC/KDF, controller, retry, and reconfiguration overheads. MRAM offers distinctive features including non-volatility, high endurance, and stochastic switching behavior. Their system-level energy benefits are treated as application-dependent and should be evaluated at the complete transaction level. Full article

Mangrove ecosystems represent critical coastal blue carbon sinks, whose ecological stability is essential for sustaining carbon sequestration capacity and coastal ecological security. Hyblaea puera, a dominant defoliating pest in mangrove habitats, exhibits abrupt population outbreaks and extreme destructive potential, severely threatening the integrity of blue carbon ecosystems. While conventional broad-spectrum chemical insecticides deliver adequate control efficacy, they often exert detrimental effects on non-target organisms and adjacent coastal marine environments, conflicting with core mangrove conservation objectives. Azadirachtin, a botanical insecticide with high lepidopteran target highly selective, is a promising eco-friendly alternative; nevertheless, the dual stresses of periodic tidal flushing and intense ultraviolet radiation in intertidal mangrove habitats drive rapid photodegradation and leaching loss of azadirachtin, leading to poor field persistence and slow lethal action of the free formulation. These limitations render neat azadirachtin insufficient to meet the urgent demand for rapid emergency control of H. puera during population outbreaks. To address these technical bottlenecks, we developed an azadirachtin-loaded dendritic mesoporous silica nanoparticle delivery system to simultaneously improve the environmental stability and fast-acting insecticidal efficacy of azadirachtin against H. puera. Specifically, dendritic mesoporous silica nanoparticles (DMSNs) were synthesized via a one-pot method, then loaded with azadirachtin (ADT) and further surface-modified with polyether-modified heptamethyltrisiloxane (PM) to fabricate the ADT@DMSN/PM nano-delivery system. The physicochemical properties, intertidal habitat adaptability, insecticidal activity, and environmental safety of the fabricated system were systematically evaluated. Characterization results showed that the as-synthesized DMSNs had a uniform particle size of 200–300 nm, a specific surface area of 260.99 m²/g, and an ADT loading efficiency of 66.6%. ADT@DMSNs exhibited prominent alkaline-responsive sustained-release behavior, with a cumulative ADT release of 57.0% at pH 8.2 (mangrove seawater conditions) over 500 h. Laboratory bioassays revealed that the 24 h median lethal concentrations (LC₅₀) of ADT@DMSNs against third-, fourth-, and fifth-instar H. puera larvae were 84.36, 188.08, and 458.65 μg/mL, respectively, representing 2.38-, 2.63-, and 2.86-fold enhancements in insecticidal activity compared with free ADT. After modification with the PM adjuvant, the nanoformulation exhibited a significantly reduced contact angle on Avicennia marina leaves, over 3-fold higher foliar penetration efficiency, and markedly improved tidal wash-off resistance. Field cage bioassays demonstrate that the ADT@DMSN/PM nanoformulation yields a corrected mortality of approximately 95% against H. puera larvae at 1200 mg/L at 24 h. This nano-delivery system is precisely tailored to the unique environmental constraints of mangrove intertidal habitats, offering a novel eco-friendly technical approach to achieve rapid emergency control of H. puera outbreaks. Full article

Population aging has made sarcopenia a growing concern in geriatric health. Protein–polyphenol non-covalent complexes can serve as carrier systems that improve the stability and bioactivity of natural antioxidants. This study refined the preparation parameters for the non-covalent complex of whey protein isolate (WPI) and resveratrol (RES), achieving protein digestibility of 83.60 ± 0.50% and DPPH scavenging of 52.41 ± 0.58% at pH 7.0, a WPI:RES molar ratio of 1:1, and a reaction time of 1.5 h. Relative to free WPI, the complex improved DPPH scavenging by 21.66% while preserving protein digestibility. The binding mode, interaction forces, and conformational evolution were investigated via spectroscopic experiments, docking studies and molecular dynamics simulations. RES selectively bound to the surface of β-lactoglobulin in WPI through hydrophobic interactions and hydrogen bonding, with a docking score of −6.366 kcal/mol and an MM-GBSA binding free energy of −30.48 kcal/mol. The complex maintained a highly stable conformation throughout the 100 ns molecular dynamics simulation. In conclusion, this study elucidated the structural changes of WPI upon non-covalent resveratrol binding. The WPI-RES complex exhibited enhanced DPPH radical scavenging activity while preserving protein digestibility, with potential implications for functional food development in sarcopenia management. Full article

Dark fermentation of organic waste offers a means of coupling molecular hydrogen (H₂) production with the bioconversion of wet organic feedstocks. However, its practical performance remains limited by unstable carbon and electron-flow distribution, substrate heterogeneity, and dynamic shifts in microbial community structure. This review critically evaluates microbial consortium engineering as a strategy to improve the selectivity, stability, and controllability of dark-fermentative H₂ production. Available experimental evidence indicates that H₂ productivity is determined not by a single high-performing strain but by the coordinated activity of microorganisms responsible for hydrolysis, fermentation of soluble compounds, and conversion through H₂-producing pathways. Disruption of this coordination redirects carbon and electrons toward lactate, alcohols, methane, and homoacetogenic pathways. Synthetic microbial consortia enable more targeted control over community composition and the allocation of metabolic functions; nevertheless, their operational performance and reproducibility may decline substantially when defined model substrates are replaced by chemically heterogeneous, non-sterile waste-derived substrates. The most reproducible performance is achieved when community composition is matched to feedstock chemistry and reactor operating conditions. Further progress will require a transition from empirical culture selection to substrate-specific engineering of microbial functions supported by metabolite profiling, molecular analyses, and mass- and electron-balance data. Full article

Background/Objectives: Gastric cancer (GC) remains a leading cause of cancer-related mortality, with metastasis being the primary driver of poor prognosis. The extracellular matrix glycoprotein tenascin-C (TNC) is implicated in tumor progression and metastasis, yet its regulatory mechanisms in GC remain poorly understood. Here, we identify RNA N6-methyladenosine (m6A) demethylase fat mass and obesity-associated protein (FTO) as a key modulator of TNC expression, promoting epithelial–mesenchymal transition (EMT) and GC metastasis. Methods: Integrating The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) and Gene Expression Omnibus (GEO) datasets (GSE246567, GSE181840, GSE163126, GSM4837878), we demonstrate that TNC is significantly upregulated in GC and correlates with worse clinical outcomes. Functional assays both in vitro and in vivo reveal that TNC knockdown suppresses GC cell proliferation, migration, invasion, and tumor metastasis, while overexpression of TNC rescues these effects. Mechanistically, FTO selectively demethylates TNC mRNA, reducing m6A modification at the 3’ untranslated region, thereby enhancing TNC mRNA stability and expression. RNA pull-down assays identify YTH domain family protein 2 (YTHDF2) as the m6A reader that recognizes the methylated site on TNC 3’UTR, and YTHDF2 knockdown partially rescues TNC expression and stability upon FTO loss. m6A RNA immunoprecipitation (MeRIP) and dual-luciferase reporter assays confirm FTO’s direct regulation of TNC via m6A demethylation. Furthermore, TNC promotes EMT by activating the phosphoinositide 3-kinase (PI3K)-AKT (protein kinase B) signaling pathway, as demonstrated by rescue experiments using the AKT activator SC79 and the PI3K inhibitor LY294002. Results: High FTO and TNC expression levels in clinical tissue samples correlate with poor patient survival. Conclusions: These findings reveal that the FTO/TNC/EMT axis represents a previously unrecognized epigenetic mechanism driving GC metastasis and suggest that targeting FTO-mediated m6A modification may provide a novel therapeutic strategy for GC patients with high metastatic potential. Full article

Background: Severe tooth loss affects approximately 267 million people worldwide and has a significant impact on quality of life and general health. Various prosthetic treatment concepts exist for oral rehabilitation. The All-on-Four concept, first described by Maló in 2003, is considered a modern approach for timely and patient-friendly restoration of oral function and esthetics. Methods: A systematic literature search was conducted in the electronic databases MEDLINE/PubMed and EMBASE (Elsevier). Eligible studies were identified according to the framework, including investigations on the All-on-Four concept (PIO) and alternative implant-supported full-arch rehabilitation strategies (FDP4+, PCO). The methodological quality of the included studies was assessed using the Newcastle–Ottawa Scale. Results: Following the selection process, eleven PIO studies and nine PCO studies were included for qualitative analysis. Reported prosthesis survival rates were comparable between All-on-Four (85.0–100%) and concepts with more than four implants (88.2–100%) over up to 20 years. Implant survival ranged from 89.7–97.9% for All-on-Four and 98.9–99.0% for alternative concepts. Marginal bone loss after 5 years reached up to 1.9 mm for All-on-Four and 2.9 mm for alternative concepts. Metal–ceramic prostheses demonstrated lower fracture rates (7.27–18.2%) compared with metal–acrylic restorations (7.3–36.7%). Discussion: The available evidence suggests that the All-on-Four concept represents a predictable treatment option for edentulous patients, with implant and prosthetic survival rates comparable to FDP4+ concepts. Immediate loading protocols may improve patient satisfaction and reduce treatment time when adequate primary stability is achieved. However, biological and technical complications remain clinically relevant. Interpretation of the findings is limited by heterogeneous study designs and predominantly retrospective evidence. Conclusions: The All-on-Four concept provides a reliable rehabilitation option for patients with advanced ridge atrophy who decline regenerative procedures or removable prostheses. Current evidence indicates no significant differences in survival or complication rates compared to other implant-supported treatment concepts. Full article

When a subject’s visual condition is restricted (e.g., blindfolding), it is more difficult to walk while performing an additional task (e.g., drinking, a phone call, etc.) at the same time. However, previous research indicates that it remains unknown whether the restricted viewing condition affects the subjects’ gait stability with different additional tasks. This study developed a smart-insole-based analysis framework to identify which gait features differed between normal-vision and blindfolded walking across tasks and to assess whether the extracted features could predict visual condition. To be specific, a total of 12 healthy adults with normal vision were invited for a controlled treadmill-walking experiment under normal-vision and blindfolded conditions with smart insoles. They needed to complete the baseline walking and three tasks—drinking, a phone call, and photography. Task-specific differences were assessed using paired t-tests with within-domain Benjamini–Hochberg correction. The results showed task-specific gait differences between the two visual conditions, including a smaller mean plantar contact area during baseline walking, a longer mean stride time during drinking, and lower mean plantar pressure during the drinking and phone call tasks. Based on this, the three gait features showing the clearest differences between visual conditions were selected for machine learning prediction. The results show that the random forest model achieved the highest overall balanced accuracy of 0.646. Mean plantar pressure, mean stride time, and mean plantar contact area were repeatedly selected during model training, indicating that these features contained information relevant to distinguishing the two visual conditions. This study provides information that may support future treadmill safety assessment and supervision for people with limited visual information by characterizing task-specific gait differences under different visual conditions. Full article