Advancing Open Science

Objectives: Six dentin adhesives were tested in vitro regarding their cytotoxicity toward human fibroblasts. AdheSE, Clearfil SE Bond, Hybrid Bond, One-up Bond F Plus, Optibond Solo Plus, and Syntac were tested using a cell culture model. The several components of dentin adhesives, like the primer and bonding, were analyzed as single and additive applied components as specified by the manufacturer for application in vivo. Methods: Seventy-five Petri dishes were produced per adhesive and control group, and all 525 Petri dishes were evaluated using multiparametric strategies, i.e., using multiple methods to strengthen the reliability of the results. The multiparametric strategies consisted of automated cell counting for viability, microscopic morphological assessment and lastly of reactivity grading according to ISO 10993-5. These assessments were performed after our initial investigation, and the observation period was extended from 24 h to 48 h. Results: AdheSE, Clearfil SE Bond, One-up Bond F Plus, and Optibond Solo Plus showed statistically significant reductions in viable cells relative to the cell control. All dentin adhesives except Clearfil SE Bond showed a statistically significant difference regarding the reactivity index in the application comparison. Conclusions: The test materials showed a moderate degree of cytotoxicity, with no statistically significant difference between the tested self-etch and etch-and-rinse dentin adhesives. However, the results show statistically significant differences between the adhesives when applied sequentially and once. Further research addressing mechanisms of cytotoxicity is needed for advancement in this field.

Accurate prediction of Rate of Penetration (ROP) in carbonate formations remains constrained by the arbitrary selection of geomechanical input parameters in empirical drilling models. This study presents the first systematic field-based evaluation of sixteen geomechanical properties—grouped into three categories: strength parameters (uniaxial compressive strength (UCS), confined compressive strength (CCS), shear strength, thick-walled cylinder strength (TWC), friction angle, and cohesion), elastic moduli (Young’s modulus, shear modulus, bulk modulus, bulk compressibility, dynamic combined modulus (DCM), Poisson’s ratio, brittleness index), and in situ stress parameters (overburden pressure, minimum, and maximum horizontal stresses)—to identify optimal predictors for ROP modeling across PDC bit sizes of 12.25″ and 8.5″. Continuous wireline log data from two vertical carbonate wells in the Middle East (Well A: 1000–3370 m; Well B: 1945 to 3128 m; total intervals of 2370 m and 1183 m, respectively) penetrating formations comprising limestone, dolomite, sandstone, shale, anhydrite, and marly limestone were used. All sixteen geomechanical properties were computed using Interactive Petrophysics (IP) software with lithology-specific empirical correlations and validated against laboratory core measurements (R² = 0.79–0.95). Pearson and Spearman correlation analyses quantified parameter–ROP relationships, and the Al-Abduljabbar empirical model, recalibrated via multiple nonlinear regression, served as the evaluation framework. DCM consistently exhibited the strongest negative correlation with ROP across both bit sizes and achieved the highest model accuracy (R² = 0.54, AAPE = 25.33%), significantly outperforming the Bourgoyne and Young model (R² = 0.26, AAPE = 36.55%). A statistically validated scale-dependent effect was identified: Fisher’s Z-transformation tests confirmed that the correlation reversal between CCS and UCS across bit sizes is statistically significant (CCS: Z = −16.84, p < 0.001; UCS: Z = −6.75, p < 0.001), establishing CCS as the superior predictor at 12.25″ and UCS as the superior predictor at 8.5″—a finding not previously reported in the ROP literature. This reversal is attributed to the larger contact area of the 12.25″ bit, which promotes confinement-dominated rock failure better described by CCS, whereas the smaller bit produces localized stress concentration better represented by UCS. These results establish that (1) optimal geomechanical input selection is bit-size dependent, (2) nonlinear modeling outperforms linear frameworks for strength–ROP relationships, and (3) parameter relevance outweighs coefficient tuning in model robustness. DCM is recommended as the most operationally practical universal input, requiring only conventional compressional sonic and density logs. This study provides a systematic framework for geomechanical parameter selection with direct implications for drilling optimization in heterogeneous carbonate reservoirs.

As vital carbon pools within terrestrial ecosystems, wetlands store sediment organic carbon (SOC), a process influenced by plant communities, seasonal variations, and wetland types. Microbial communities, fundamental to wetland ecosystems, are hypothesized to regulate carbon storage. We investigated sediment microbial communities and carbon storage in different seasonal and plant conditions in two types of wetlands. Sediment organic carbon, the associated environmental factors, and microbial community characteristics were detected to explore the impacts of seasons and plants on SOC. Plants and seasons significantly influenced the content of SOC in constructed wetland, while only altered the content of dissolved organic carbon (DOC) in river wetland. In river wetland, plants increased the microbial function of Amino Acid Metabolism through the input of exogenous dissolved organic carbon (DOC) and the effect on moisture content. The functional traits of Carbohydrate Metabolism in sediment were higher in river wetland than that in constructed wetland. Our results indicated that plants and seasons influenced SOC in wetlands through their effects on sediment microbial community and function. Compared with the river wetland, the constructed wetland had more stable microbial communities and might be easier to fix organic carbon from plants. This study highlights the importance of the carbon sequestration potential of constructed wetlands due to the stable microbial communities.

Co-channel interference (CCI) remains a critical factor affecting link reliability in narrowband wireless systems, especially in scenarios with intensive frequency reuse, overlapping coverage, and dense terminal access. Existing interference detection methods are either computationally simple but insufficiently sensitive to short-term spectral variations, or highly accurate but dependent on labeled data and nontrivial inference resources. To address this issue, this paper proposes a lightweight CCI detection method in the FFT domain based on spectrum-jump analysis. The proposed method does not rely on absolute power growth as the primary interference indicator. Instead, it tracks the temporal inconsistency of dominant spectral-bin indices across consecutive FFT frames and converts recurrent peak-bin migration into an interference decision through a short-window counting mechanism. The method is computationally efficient, interpretable, and suitable for real-time deployment without offline model training. SDR-based measurements are combined with controlled repeated experiments to assess detector performance under varying signal-to-noise ratio (SNR), interference-to-signal ratio (ISR), carrier-frequency offset (CFO), multi-peak ambiguity, and two-path Rayleigh fading conditions. On the measured SDR record, the proposed method captures all interference-positive windows after the marked onset, while the controlled SNR/ISR experiments yield an overall detection probability of 96.0% over 250 CCI trials with no false alarms over 250 normal trials. ROC and precision–recall analyses further show that the selected threshold lies within a broad validation plateau. The results also reveal clear applicability boundaries: when the CFO approaches zero, when the interference is very weak, or when multiple stationary peaks have nearly equal power, dominant-bin migration may be weak or ambiguous. Therefore, the proposed approach is a low-complexity online detector for CCI cases that induce observable FFT-bin instability, and it can also serve as a front-end trigger for more advanced interference analysis modules.

Late Jurassic–Early Cretaceous silicic volcanism is widespread along the Southeast China continental margin, yet the timing, magma plumbing, and geodynamic drivers of individual volcanic centers remain debated. Here, we integrate whole-rock geochemistry with zircon U–Pb geochronology, zircon trace elements, and in situ zircon Lu–Hf isotopes for high-silica rhyolites from the Bijiashan volcanic complex, eastern Guangdong, to constrain magmatic evolution and its link to Paleo-Pacific subduction dynamics. LA–ICP–MS zircon U–Pb analyses were used to define two dominant crystallization populations: 145.4 ± 1.2 Ma (n = 14; MSWD = 1.7) for sample BJS-18 and 141.4 ± 1.3 Ma (n = 14; MSWD = 1.6) for sample BJS-27, yielding dominant zircon U–Pb age populations of 141.1–145.4 Ma, thereby constraining the timing of the main silicic volcanism (magma crystallization immediately preceding eruption) to the Jurassic–Cretaceous boundary. Minor older peaks at 157.0 ± 1.6 Ma (BJS-18) and 153.1 ± 1.5 Ma (BJS-27) suggest antecrystic or inherited components from a long-lived trans-crustal magmatic system. Whole-rock data indicate subalkaline, high-K calc-alkaline rhyolitic affinities, with apparent peraluminous signatures affected by post-magmatic alkali mobility. The rhyolites are characterized by pronounced negative Eu anomalies (Eu/Eu* = 0.085–0.395), low Sr contents (5.9–29.0 ppm), and arc-like trace-element signatures with Nb–Ta–Ti depletions. Zircon trace elements indicate crystallization temperatures of 608–842 °C and redox states from ΔFMQ = −3.90 to +1.71, with syneruptive grains clustering near FMQ ± 1 and xenocrystic grains systematically more reduced and hotter, implying vertically and temporally zoned magma storage. Zircon εHf(t) values (−7.4 to −0.9) and Mesoproterozoic TDM2 ages (1.18–1.66 Ga) indicate substantial reworking of ancient Cathaysian crust. In contrast, the relatively radiogenic upper εHf(t) values and the occurrence of mafic lithic fragments suggest limited juvenile or mantle-derived input into the crust-dominated magmatic system. Together with tectonic discrimination diagrams indicating a continental arc affinity, these results support Early Cretaceous arc-related silicic magmatism during a regional transition from compression to extension, plausibly linked to Paleo-Pacific slab rollback beneath Southeast China.

In practical digital control systems for Modular Multilevel Matrix Converters (M3C), the inherent delays caused by signal sampling and algorithm execution lead to pulse output lags in conventional deadbeat control, subsequently resulting in current tracking deviations and grid-side current distortions. To address this issue, an improved deadbeat inner-loop control strategy based on current state prediction is proposed in this paper. First, the mathematical model of the M3C in the abc coordinate system is established, and a dual αβ0 coordinate transformation is introduced to decouple the system, achieving independent control of the input-side, output-side, and internal electrical quantities. Subsequently, to eliminate the control error caused by the one-step delay, an interpolation prediction method is employed to equivalently evaluate the voltage variation within an ultra-short control period. By predicting the current reference state at the k + 2 instant, the deadbeat control equation is modified to achieve delay compensation. Simulation and experimental results demonstrate that the proposed strategy effectively overcomes the delay limitations inherent in conventional digital control, significantly enhancing the dynamic current tracking accuracy and waveform quality of the M3C system.

Hard carbon has been widely recognized as the most commercially viable anode material for sodium-ion batteries (SIBs); however, its inherently low initial Coulombic efficiency (ICE), typically 60–90%, remains a critical bottleneck constraining practical full-cell deployment. While extensive research has addressed ICE optimization, existing reviews have predominantly focused on individual precursor types or isolated strategies, lacking a unified cross-precursor comparative framework. This review systematically deconstructs the complete causal continua—from chemical composition through carbonization trajectories and microstructural evolution to ultimate ICE outcomes—across five major precursor categories: biomass, synthetic resins, pitches, coal-based materials, and saccharides. An “SSA-closed pore–defect” three-parameter trade-off framework is proposed to elucidate the microstructural origins of precursor-dependent ICE divergences. Cross-categorical benchmarking reveals that resin-based precursors achieve the highest ICE (95%) through ultra-low specific surface area and extensive closed porosity, pitch-based systems deliver the most consistent ICE distribution (86–91%), and coal-derived carbons are confined to the lowest tier (78–85%). The differentiated efficacy of carbonization conditions and post-treatment strategies across precursor types is critically evaluated, demonstrating that optimal process selection is inextricably linked to precursor taxonomy. Building upon these analyses, a precursor selection decision roadmap targeting three application-specific ICE thresholds is constructed, providing actionable guidance for matching precursor–process combinations to industrial requirements. The comparative framework is grounded in 25 representative studies selected through explicit inclusion criteria (detailed in the Introduction), and its predictive utility is illustrated for emerging precursor candidates beyond the five canonical categories. This cross-precursor perspective offers a systematic reference for accelerating the commercialization of hard carbon anodes in SIBs.

Dynamically grasping the scope of the caving zone and fractured zone in overlying strata is crucial for ground pressure control in sublevel caving mining. Taking Dahongshan Iron Mine as the research object, this study systematically analyzed the evolutionary characteristics of overlying strata caving during sublevel caving mining from 2009 to 2013. Microseismic monitoring was employed as the main method to monitor and locate rock mass fracturing, while roadway monitoring and borehole monitoring were used as auxiliary means to determine the caving boundary and fractured zone scope of overlying strata. Comprehensive analysis of the monitoring data showed that the elevation of the overlying strata caving zone expanded from 930 m to 1215 m, and the width of the fractured zone varied from 50 m to 75 m in different periods. To clarify the rock mass fracture mechanism, P-wave first-motion moment tensor inversion and the Ohtsu moment tensor decomposition method were adopted to classify fracture types. The results indicated that tensile fracturing-related microseismic events accounted for 76.2–80.2% of all events in different periods, demonstrating that tensile failure dominated the fracturing of overlying strata. After December 2012, the caving scope extended to the surface, and a surface collapse area of 290,000 m² was formed by December 2013, which effectively eliminated the threat of sudden overlying strata caving disasters to the mine. The research results provide reliable technical support for ensuring mine safety production and can serve as a reference for similar sublevel caving mining projects.