Search Results (9,783)

This study evaluated the influence of the manufacturing method and cementation protocol on the fracture load of zirconia molar crowns. A total of 32 full-contour crowns with a wall thickness of 1 mm were fabricated from 3 mol% yttria-stabilized tetragonal zirconia polycrystal (3Y-TZP). Sixteen crowns were produced by 3D printing (LithaCon 3Y 210, Lithoz) and 16 by milling (e.max ZirCAD LT, Ivoclar Vivadent). Within each manufacturing group, eight crowns were adhesively luted with a dual-cure resin cement (Bifix QM, VOCO) and eight were conventionally cemented with a glass ionomer cement (Ketac Cem, Solventum). All crown–die complexes underwent thermomechanical aging (6000 thermal cycles between 5 °C/55 °C; 1.2 × 10⁶ cycles at 50 N) as a correlate of five years of clinical service, followed by axial loading to failure. The statistical analysis was a two-way ANOVA on log10-transformed fracture loads with manufacturing and cement as fixed effects (α = 0.05). All crowns survived thermomechanical loading without failure. Milled zirconia crowns showed significantly higher fracture loads when adhesively luted (7162 ± 1294 N) compared with conventional cementation (4021 ± 1126 N; p < 0.001). In contrast, no significant differences were observed between adhesive (4986 ± 1301 N) and conventional cementation (5581 ± 1618 N) for 3D-printed zirconia crowns. Additively manufactured crowns exhibited greater variability in fracture loads (broader interquartile ranges) than their milled counterparts. Two-way ANOVA detected a significant Manufacturing × Cement interaction (p < 0.001), indicating that the effect of cementation differed by manufacturing route. Adhesive cementation increased fracture load for milled zirconia, whereas no statistically significant cementation effect was detected for 3D-printed zirconia under the present conditions. Given the sample size and the observed variability, the study was powered to detect very large effects but not medium or small ones; therefore, this non-significant difference should not be interpreted as proof of no effect. Full article

Oilfield production forecasting serves as the decision-making basis for monthly production allocation and injection–production system optimization. Existing mainstream prediction methods face significant limitations: the Arps decline curve extrapolates historical production trends, yet its accuracy degrades rapidly following adjustments to injection–production regimes; machine learning methods such as XGBoost can leverage extensive dynamic data but rely heavily on manual feature engineering and offer limited decision interpretability. This paper proposes the FTT-Transformer prediction model, whose core innovation is the Feature-Time Tokenizer (FTT). The FTT projects every scalar pair (time step, feature) in a multivariate time series matrix into a token of uniform dimensionality, superimposing three types of positional information—time embedding, feature embedding, and global position encoding. On this foundation, a multi-head self-attention mechanism performs end-to-end, full-capacity learning of nonlinear interactions across both the temporal and feature dimensions. The model is lightweight, requiring only 35,361 parameters for 13 input features and is readily deployable. Validation was conducted using production data from two independent waterflooding oilfields. On Dataset 2 (60 wells, 2012–2026), the model achieved an R² of 0.819, achieving performance on par with XGBoost (0.813; DM test p = 0.620, indicating no statistically significant difference) and substantially outperforming temporal Transformer baselines PatchTST (R² = 0.683) and iTransformer (R² = 0.786). On Dataset 1 (96 wells), it reached an R² of 0.930, statistically indistinguishable from XGBoost’s 0.943 (DM test p = 0.611). Five-fold temporal cross-validation yielded a mean R² of 0.840 ± 0.036, confirming the model’s stability. Ablation experiments revealed that global position encoding contributed most significantly, with its removal causing a 3.9 percentage point reduction in R² on Dataset 2. Composite feature-importance analysis showed that monthly liquid production and water cut are identified by the model as the two most predictive features, contributing 31.93% and 30.17% of the total importance, respectively. Multi-step forecasting results demonstrated that the model retains an R² of 0.640 for predictions two months ahead, spanning one complete decision cycle of monthly production reallocation. The proposed architecture is not domain-specific; by adapting the feature embeddings and time encoding, it could potentially be extended to diverse multivariate time series forecasting applications. However, cross-domain validation remains future work. Full article

Flexible pressure sensors serve as core sensing components for wearable health monitoring systems, electronic skins for soft robots, and flexible human–machine interaction devices. Benefiting from the interfacial electric double-layer polarization effect, iontronic sensing delivers far higher pressure response sensitivity than conventional parallel-plate capacitive sensors, endowing it with distinctive advantages in the detection of weak physiological signals. Nevertheless, current dense ionic thin-film dielectric layers suffer from limited deformation space under compression and poor low-pressure sensing capability. Mainstream high-precision micropillar arrays are fabricated via photolithography, 3D printing, and metal etching molds, which require costly equipment and complicated fabrication procedures, making large-area mass production unfeasible. Random frosted concave-convex microstructures feature disordered dimensions, leading to severe device hysteresis and narrow linear ranges, which fail to achieve ultrahigh sensitivity alongside a wide pressure detection range simultaneously. To address the aforementioned multiple bottlenecks, this paper proposes a low-cost resin template replication process to fabricate TPU-based ionic thin-film dielectric layers with ordered micropillar array microstructures. Combined with inkjet-printed silver conductive PI flexible electrodes, an iontronic flexible pressure sensor with a sandwich layered structure is constructed. Multi-dimensional investigations including microscopic morphology characterization, electromechanical sensing performance calibration, and human wearable application tests are systematically implemented to thoroughly elucidate the synergistic enhancement mechanism of the arrayed micropillars. Test results demonstrate that the effective pressure detection range of the sensor spans 0–1038 kPa, accommodating ultra-low pressures such as pulse signals as well as medium-to-high-pressure loads including joint bending. The sensitivity reaches 23.27 kPa⁻¹ within the low-pressure range of 0–200 kPa and remains stable at 3.52 kPa⁻¹ in the high-pressure range of 200–1038 kPa, with piecewise linear fitting correlation coefficients of 0.93 and 0.96 respectively. Both the response time and recovery time of the device are 40 ms, and the hysteresis error throughout the loading-unloading cycle is merely 2.62%. After 20,000 consecutive cyclic loading-unloading tests, the peak capacitance output only decays by 5.1%, verifying outstanding mechanical fatigue resistance and electrical stability. Validations in multi-scenario applications prove that the sensor can accurately capture human physiological and motion signals including radial artery pulses, laryngeal deformation induced by multi-syllable vocalization, and multi-angle bending of fingers and elbow joints, suitable for home-based health monitoring, quantitative rehabilitation training, flexible tactile interaction and other scenarios. The entire fabrication process eliminates high-precision micro-nano processing equipment such as photolithography systems, plasma etchers and 3D printers; only general chemical raw materials and conventional laboratory instruments are adopted. The reusable templates enable low manufacturing costs and large-area coating forming, offering a novel low-cost technical solution for the engineering implementation and industrialization of high-performance iontronic flexible pressure sensors. Full article

Soil moisture is critical to the ecological stability and hydrological cycle. Optical remote sensing is severely constrained by cloud cover, snow, and frozen soil in alpine regions, hindering long-term soil moisture monitoring. Taking Nagqu region in the Tibetan Plateau as the study area, this paper constructs a pure microwave soil moisture inversion framework based on multi-temporal Sentinel-1 SAR data to avoid optical data dependence. Four SAR vegetation indices (DpRVI, RVI, DpSVI and PRVIc) were integrated into the coupled WCM–Oh2004 model to dynamically correct vegetation attenuation and surface scattering. The results show that the DpRVI-based model performs best, with R = 0.85 and RMSE = 0.0709 cm³/cm³, outperforming other indices. The framework maintains stable accuracy in the growing season and effectively captures spatiotemporal soil moisture variations. The proposed SAR-only method agrees well with official downscaled soil moisture products, proving its applicability for continuous soil moisture monitoring in optically inaccessible alpine regions. Full article

Hydrogen is considered one of the most promising energy carriers for sustainable and carbon-neutral energy systems. However, the large-scale deployment of hydrogen technologies is limited by the lack of efficient, safe, and cost-effective hydrogen storage methods. This review examines current hydrogen storage technologies and the physical and chemical mechanisms underlying hydrogen adsorption. Traditional storage approaches, including compressed gas and liquid hydrogen, are briefly analyzed with respect to their advantages, limitations, safety concerns, and energy requirements. Special focus is given to solid-state hydrogen storage systems based on metal hydrides, which offer high storage capacities and enhanced operational safety. Recent advances in intermetallic hydrides, magnesium-based materials and complex hydrides are discussed, along with challenges related to thermodynamic stability, sorption kinetics, thermal management, and cycling durability. This review also highlights recent developments in nanoporous carbon materials and the role of the hydrogen spillover mechanism in improving adsorption performance. Experimental studies reporting hydrogen adsorption capacities above 7 wt.% and up to 11.2 wt.% are analyzed. Based on the reviewed literature, key research directions are identified for optimizing the adsorption properties of advanced materials and accelerating the development of efficient and sustainable hydrogen storage technologies for future energy applications. Full article

Polypropylene (PP) fiber-reinforced soil slopes undergo progressive resistance degradation under wet–dry cycling (WDC), while stochastic seismic loading introduces additional uncertainty, challenging deterministic seismic assessment. This study develops a time-dependent seismic reliability framework integrating the probability density evolution method and the equivalent extreme value event method. The cohesion and internal friction angle of unreinforced soil measured at different WDC states are represented as cross-correlated lognormal random fields and combined with random fiber configurations and weighted nonstationary stochastic ground motions in a nonlinear dynamic model. The main contribution is a unified uncertainty-propagation scheme that incorporates experimentally characterized WDC degradation and multiple uncertainty sources into the evolution of response probability and multilevel first-passage reliability. With increasing WDC number and PGA, the extreme displacement distributions shift toward larger values, accompanied by increased response dispersion, tail risk, and reliability loss. The reliability evolution exhibits three stages, namely initial stability, rapid degradation, and residual convergence, during the 70 s excitation. PP fiber reinforcement improves reliability, although the marginal gain becomes limited when the fiber content exceeds 0.15% under the present numerical conditions. The proposed framework provides a probabilistic basis for the seismic assessment and deformation control of PP fiber-reinforced soil slopes at different WDC degradation states. Full article

Triboelectric nanogenerators (TENGs) are promising for harvesting low-frequency mechanical energy, but rotating TENGs (R-TENGs) driven by low-speed water flow remain constrained by limited driving torque, sliding-contact losses, and rotating-system stability. Here, a three-dimensional (3D) riveted complementary-structure rotating triboelectric nanogenerator (RCSR-TENG) is proposed for low-speed water-flow energy harvesting. A semi-analytical formulation incorporating a force-dependent real-contact fraction is developed to describe the coupled relationships among output voltage, transferred charge, rotation angle, and contact force. Because the contact parameters were not independently calibrated, the formulation is used for sensitivity and trend analysis rather than as a quantitatively validated predictive model. For the single prototype tested for each configuration, at 1000 rpm under the fixed effective measurement load of 9 MΩ, the RCSR-TENG produced a peak output power of 544 μW, compared with 304 μW for the flat R-TENG, representing an increase of approximately 79%. The same RCSR-TENG prototype maintained a stable voltage amplitude of over 150,000 rotation cycles. When coupled to a fully passive flapping-foil collector in a 0.55 m s⁻¹ water flow, the system generated periodic electrical output with a peak area-normalized power exceeding 5000 μW m⁻². These results demonstrate the structural-performance advantage of the riveted complementary design and its proof-of-concept applicability to low-speed water-flow energy harvesting. Full article

17β-Estradiol (E2), a highly bioactive steroid estrogen, poses potential ecological risks even at trace concentrations in aquatic environments. In this study, a nanoconfined Co-based catalyst (Co@C_in) was employed to activate peracetic acid (PAA) for efficient E2 degradation. Microscopic and spectroscopic characterizations indicated that Co-containing species were highly dispersed within the CNT-based architecture, while the graphitic tubular framework was largely preserved. Compared with PAA alone, CNTs, Co@C_in alone, and the externally loaded Co@C_out/PAA system, Co@C_in/PAA exhibited substantially faster E2 degradation. Pseudo-first-order kinetic analysis further demonstrated the enhanced degradation kinetics of the internally confined system. Importantly, ICP analysis showed comparable Co loadings for Co@C_in and Co@C_out, while Co@C_in retained a markedly higher Co-normalized apparent kinetic activity, indicating that its enhanced performance cannot be explained simply by differences in total Co loading. Moreover, Co@C_in exhibited substantially lower Co leaching than Co@C_out and maintained considerable catalytic activity over five consecutive cycles, demonstrating improved stability of the confined Co species. The degradation performance was influenced by initial E2 concentration, catalyst dosage, PAA concentration, and pH, while Cl⁻ and NO₃⁻ showed negligible effects and humic acid and CO₃²⁻ caused only moderate inhibition. Scavenging experiments and controlled TEMP-EPR measurements with appropriate blank and control systems supported a dominant contribution of singlet oxygen (¹O₂), with radical pathways playing only minor roles. The enhanced performance is therefore associated with the nanoconfined reaction environment, which promotes efficient PAA activation while stabilizing the Co species. This work extends nanoconfinement-regulated PAA oxidation to the treatment of the highly bioactive steroid estrogen E2 and provides a quantitative assessment of the activity–stability advantages of internally confined Co species. Full article

A series of molecularly imprinted polymers (MIPs) based on hydroxypropyl-β-cyclodextrin (HPCD) crosslinked with 1,6-hexamethylene diisocyanate (HMD) or toluene diisocyanate (TDI), as well as hybrid chitosan–HPCD polymers crosslinked with genipin, were synthesized using levofloxacin and fluorescein as template molecules. The structure and spatial organization of the obtained materials were characterized by FTIR spectroscopy, FTIR microscopy mapping, and ζ-potential measurements. The influence of pH, crosslinker content, and template structure on sorption performance was investigated. All MIPs exhibited maximum sorption at pH 3.0. The highest sorption capacity toward levofloxacin was achieved for the LV–Chit–HPCD–Genipin_MIP (74.8 mg/g), whereas the fluorescein-imprinted FL–HPCD–TDI_MIP (1:1) demonstrated the highest sorption capacity (135.5 mg/g) and selectivity coefficient (84.1). Dynamic column experiments confirmed efficient analyte extraction, reducing the analyte concentration by more than 90% after ten loading cycles. All synthesized MIPs exhibited excellent regenerability, with less than 3% loss of sorption efficiency after ten consecutive sorption–desorption cycles. The applicability of the developed sorbents to real matrices was demonstrated using milk and blood plasma samples after minimal sample preparation. Fluorescein extraction efficiencies reached 97.6% and 93.6% for milk and plasma, respectively. The obtained results demonstrate that HPCD-based MIPs combine high sorption capacity, exceptional selectivity, operational stability, and applicability to complex biological matrices, making them promising materials for selective sample preparation, analyte preconcentration, and controlled drug delivery systems. Full article

Eco-friendly lubricant manufacturing focuses on using biodegradable, renewable base oils, such as waste oil, and green-synthesized nanomaterials, such as agricultural residue-based nanoparticles, in order to replace conventional toxic lubricants with biodegradable alternatives and reduce environmental impact. These nanolubricants are produced through low-energy methods like mechanical, microwave, or chemical-free synthesis that can result in improvement in their performance. The produced lubricants exhibit enhanced tribological properties, including reduced friction and wear. Several formulations also raise the thermal degradation onset above that of their mineral benchmarks, although oxidative stability remains the weakest property of bio-based systems. This approach addresses industrial demands for sustainable, cost-effective, and environmentally compliant lubrication technologies. Our study reviews sustainable, eco-friendly synthesis methods for producing high-performance nanolubricants from different waste oils, including cooking and mineral oils. In addition to the incorporation of residue-based nanoparticles (e.g., eggshell) in waste oils, the performance and properties of bio-based lubricants with engineered nanoparticles, such as metal nano-oxides and carbon-based nanomaterials, are also reviewed for comparison purposes. Within bio-based fluids at moderate contact severity, residue-derived additives are found to match their engineered counterparts in terms of friction and wear, while engineered two-dimensional lamellar additives retain an advantage under extreme-pressure conditions where residue-derived particles have not yet been evaluated. Neither class has been assessed by life cycle or biodegradation testing as a finished formulation. Full article

Introduction: PKMYT1 is a WEE-family G2/M cell cycle checkpoint kinase commonly overexpressed in a broad spectrum of human malignancies. WEE1 exclusively phosphorylates CDK1 at Tyr15, whereas PKMYT1 targets both Thr14 and Tyr15. Unlike WEE1 inhibition, PKMYT1 suppression triggers synthetic lethality with CCNE1. Nearly all disclosed PKMYT1 inhibitors so far fall into structural analogs originating from RP-6306, making the discovery of PKMYT1 inhibitors with chemotypes distinct from RP-6306 crucial. Methods: The compounds were structurally optimized using CADD, synthesized, and characterized by ¹H NMR, ¹³C NMR, HRMS, and HPLC. They were then assessed for kinase binding affinity via the LanthaScreen^TM Eu kinase binding assay, for cellular activity using the CCK-8 assay, and for cell-cycle distribution by flow cytometry, along with investigations into related mechanisms. Results: This study yielded 24 compounds of 2-aminopyrimidine through substituent derivatization of the pyrimidine scaffold. Among these derivatives, MS13 exhibited potent kinase binding affinity against PKMYT1 (IC₅₀ = 0.86 nM) and demonstrated strong anti-proliferative activity against CCNE1 high-amplification OVCAR3 cells and HCC1569 cells (IC_50-OVCAR3 = 1.52 μM, IC_50-HCC1569 = 0.66 μM). Additionally, it showed some selectivity towards A549 and HEK293T cells, with SI values of 4.31 (A549/OVCAR3), 9.92 (A549/HCC1569), 2.04 (HEK293T/OVCAR3), and 4.70 (HEK293T/HCC1569). Compound MS13 dose-dependently suppressed clonogenicity and triggered S-phase cell cycle blockade. Pharmacokinetic studies showed moderate hepatic microsomal stability (t_1/2 = 32.2 min). Molecular dynamics simulations indicated a favorable binding mode between compound MS13 and PKMYT1 (docking score: −9.322 kcal/mol). Conclusions: MS13 is a promising highly potent tool compound that provides a clear direction for the future optimization of PKMYT1 inhibitors. Full article

Carbon capture is more and more often seen as a component of an integrated carbon-management system than as a stand-alone separation phase. The practical utility of capture technology depends on the chemical state in which the carbon dioxide is held, the energy and material needs for regeneration, the compatibility of the caught species with downstream catalysis and the lifetime of the resulting carbon-containing product. This paper offers an in-depth framework for integrated CO₂ capture and circular carbon use, including catalytic conversion, bio-integrated processes, biomass-derived materials and fuels, hydrogen-enabled routes, mineralization, and artificial intelligence-assisted process design. Reactive capture techniques that convert carbonate, bicarbonate, carbamate, dissolved CO₂ or surface-bound intermediates without first generating a purified gas stream are contrasted with sequential capture, purification, compression, transport and conversion. The thermocatalytic, electrochemical, photoelectrochemical and biological conversion pathways are compared against common parameters such as working capacity, conversion rate, selectivity, carbon efficiency, regeneration energy, stability and life-cycle greenhouse gas performance. Special emphasis is given on dual-functional materials, interfacial reactors, bio-integrated methanation, carbon mineralization in construction materials and coupling with renewable hydrogen. The review also discusses how machine learning, molecular screening, process simulation, graph-based data architecture, and digital monitoring could speed up material selection and system optimization. Across all pathways, the central design requirement is not maximum capture capacity alone, but a balanced match among binding strength, transport, catalytic reactivity, product separation, durability, and carbon permanence. A reporting framework and research agenda are proposed to guide credible scale-up and comparison of integrated carbon-management technologies. Full article

Background: Seed dormancy is crucial for plant survival and agricultural productivity, yet its molecular mechanisms, particularly the role of maternal effects, remain poorly understood. Methods: In this study, we applied a SWATH-based, label-free, quantitative shotgun proteomic mass spectrometry approach to investigate the temporal dynamics of dormancy establishment in Xanthium strumarium, a wild plant with two seeds in one burr that, despite sharing the same genetic and environmental conditions, exhibit distinct dormancy states. Results: Our data show that dormant seeds undergo coordinated metabolic suppression, marked by a decrease in energy metabolism, cell cycle arrest, and auxin signaling, explaining their smaller size. Simultaneously, dormant seeds exhibit metabolic re-prioritization towards fatty acid desaturation, cell wall modification, and an active epigenetic program stabilized by dormancy-promoting factors alongside a transcriptionally quiescent state in early–mid development. However, in the late developmental stage, molecular signaling pathways showed a recalibration distinguished by changes in seed metabolism (such as carbon–nitrogen reallocation, sulfur assimilation, and GABA production), hormonal fluctuations, and epigenetic regulation. Notably, previously reported high DOG1 transcript abundance, together with the absence of detectable DOG1 protein in the proteomic dataset, suggests that post-transcriptional mechanisms may contribute to DOG1 regulation. Conclusions: Based on these findings and the available literature, we propose a framework whereby dormancy establishment occurs in two phases: an early DOG1-mediated priming phase followed by a temperature-sensitive plasticity phase during seed maturation. Full article

The intestinal epithelium is a dynamic tissue renewed by intestinal stem cells (ISCs) within the crypt niche. ISC behavior is regulated not only by intrinsic genetic programs but also by dietary composition, nutrient availability, microbial metabolites, and feeding rhythms. This narrative review synthesizes mechanisms through which diet influences ISC self-renewal, proliferation, differentiation, metabolic programming, and regenerative capacity. Dietary patterns exert context-dependent effects: caloric restriction, fasting, and structured feeding–fasting cycles may enhance epithelial regeneration through nutrient-sensing pathways, mitochondrial adaptation, and circadian regulation, whereas Western-type and high-fat diets may promote niche remodeling, inflammation, metabolic reprogramming, and tumorigenic risk. Macronutrients regulate ISC fate through carbohydrate metabolism, amino acid sensing, fatty acid oxidation, and lipid-derived signaling molecules. Micronutrients, including vitamins A, D, and B and minerals such as iron, zinc, selenium, and magnesium, contribute to epithelial differentiation, redox balance, and barrier integrity. Phytochemicals may modulate ISC function through Wnt/β-catenin, Nrf2, SIRT1, and epigenetic pathways or by stabilizing the epithelial microenvironment. The gut microbiota mediates diet–ISC interactions via short-chain fatty acids, bile acids, indole derivatives, and other metabolites. However, human evidence remains limited, and studies integrating human organoids, single-cell analyses, metabolomics, and chrononutrition are needed to inform personalized nutritional strategies for intestinal health. Full article

Age-associated mitochondrial decline reduces NAD⁺ availability, impairs oxidative phosphorylation (OXPHOS), and leads to accumulation of reactive oxygen species (ROS) thereby reshaping cellular metabolism. However, the regulatory logic coupling mitochondrial aging to metabolic dysregulation resulting in tumorigenic cell-fate transitions has not been modeled systematically. In this work, we propose a Boolean biomolecular network model of mitochondrial aging and integrate it with metabolic, cell-cycle, and apoptotic biomolecular networks comprising 94 nodes and 370 edges. We then examined how NAD⁺ decline, hypoxia and extracellular ROS shifts the balance between OXPHOS and glycolysis. To this end, the consolidated network model underwent dynamical analysis to elucidate the system-level outcomes as well as its molecular triggers. In particular, we investigated whether the metabolic phenotypes are reversible and how cancer-driver perturbations act in the absence of extracellular pyruvate. The model recapitulates a quiescent, OXPHOS-leaning baseline and predicts that progressive NAD⁺ decline lowers OXPHOS propensity (0.686 to 0.186) while raising glycolysis (0.256 to 0.426). Hypoxia and extracellular ROS synergize glycolytic and hybrid oxidative–glycolytic (W/O) states. Furthermore, these two triggers, together with elevated mitogenic signaling, give rise to a hyperproliferative, glycolytic, and apoptosis-resistant cellular state. Interesting, this state is conditionally reversible wherein receptor tyrosine kinase (RTK) inhibition redirects this cell fate toward apoptosis and collapses the W/O state. Cancer-driver analysis further indicates that, without extracellular pyruvate, VHL loss and RAS, PI3K, or AKT activation preferentially stabilizes glycolytic and hybrid states. Age-resolved TCGA-BRCA analysis provided expression-level support for the predicted remodeling, with declining OXPHOS-associated expression and concurrent OXPHOS/glycolysis activity in older Basal-like tumors. Together, our results show that mitochondrial aging is a priming condition whose tumor-permissive metabolic output is gated by microenvironmental and nutrient inputs. The model provides a novel framework for evaluating age-associated metabolic reprogramming and predicting early tumorigenic cell fates. Full article