Search Results (1,007)

The stability of retained roadways in closely spaced coal seams beneath a goaf is strongly affected by complex stress redistribution and the deterioration of roof structures under downward mining conditions. To address this issue, a combined approach involving theoretical analysis, numerical simulation, and field monitoring was adopted to investigate the deformation characteristics and stability control of gob-side retained roadways in short-distance coal seam groups. The movement characteristics of the roof and the deformation law of surrounding rock of the retained roadway under downward mining were revealed. An embedded short-arm beam structural model for a roof cutting retained roadway was established, and a calculation method for determining the required support resistance of the retained roadway was proposed. Based on this model, design criteria for the passive support system of the retained roadway were developed. A surrounding rock control technology with hollow grouting anchor cable support and low-disturbance directional roof cutting as the core was proposed, and the support resistance of a one-beam–four-column support system was determined to effectively limit roof subsidence. Field application results show that the surrounding rock displacement was controlled within 350 mm, and the roadway section shrinkage rate was maintained at 16.4%, indicating good stability of the retained roadway and satisfying the requirements of ventilation and transportation. This study provides a mechanical basis and practical guidance for stability control and support design of roof cutting retained roadways in closely spaced coal seams beneath goaf. Full article

Objectives: Variations in composite resin composition and aging time remain one of the main reasons for replacing esthetic restorations. This in vitro study aimed to evaluate the microtensile bond strength of a low-shrinkage composite resin on a demineralized dentin surface following adhesive interface degradation. Methods: Seventy-eight extracted human molars were prepared, and artificial caries lesions were induced. For microtensile bond strength (μTBS) testing, 60 teeth were randomly assigned to six experimental subgroups (n = 10 per subgroup) based on restorative system and thermal cycling condition. An additional 18 teeth were randomly assigned to six experimental subgroups (n = 3 each) for SEM analysis. Three restorative systems were evaluated, Z250 (conventional resin), K (Kalore resin), and P90 (Filtek P90 resin), each subjected to two thermal cycling conditions: without thermal cycling (NTC) and 12,000 thermal cycles (TC). Results: In the NTC groups, Z250 exhibited a significantly higher bond strength (25.29 ± 10.91 MPa) compared to K (9.69 ± 11.63 MPa) and P90 (9.81 ± 8.49 MPa) (p < 0.05). Following TC, a numerical decrease in bond strength was observed across all groups. Z250 (13.00 ± 10.76 MPa) maintained a significantly higher bond strength compared to K (4.30 ± 6.40 MPa) and P90 (0 ± 0 MPa) (p = 0.001). Notably, the P90 group showed a near-complete loss of bond strength after TC (0 ± 0 MPa), which was a statistically significant reduction compared to its NTC condition (p = 0.002). SEM analysis revealed a predominance of mixed failures in most experimental groups, while the P90 TC group showed a clear predominance of adhesive failures. Conclusions: This study demonstrates that the conventional Bis-GMA resin (Z250) consistently exhibited superior bond strength to demineralized dentin compared to the low-shrinkage resins (Kalore and Filtek P90) under both non-aged and aged conditions. While all materials experienced a reduction in bond strength after thermal cycling, the Filtek P90 system showed a catastrophic loss of adhesion after aging, indicating its particular susceptibility to degradation. These results emphasize the critical roles of resin chemistry and adhesive system selection in long-term bond durability in compromised dentin. Full article

Topsoil features within a depth of 0–10 cm are vital for making soil management decisions that affect crop production. However, the use of these soil features to predict soil organic carbon (SOC) at 10–20 cm requires further investigation. The study aims to predict SOC at 10–20 cm using total nitrogen (total N), pH, cation exchange capacity (CEC), and SOC at 0–10 cm and select a suitable model for predicting SOC. This study was conducted using data from a long-term tillage, winter wheat (Triticum aestivum L.)-fallow experiment established in autumn 1970. Treatments included moldboard plow, stubble mulch, no-till, and native sod, each replicated three times. Soil samples were collected from each plot at depths of 0–10 cm and 10–20 cm in April of 2010 and 2011. Models were fit using ordinary least squares (OLS), least absolute shrinkage and selection operator (LASSO), random forests, and Bayesian additive regression trees (BART). Using root mean square error (RMSE), SOC was predicted with an accuracy of 1.44 g kg⁻¹ or relative RMSE (rRMSE) of 13.5%. This was achieved with the OLS model that used total N, pH, and CEC as predictors. The good performance of the OLS model over more flexible machine learning approaches suggests that the information predictors provide about the response variable (SOC) is approximately linear. As the agricultural dataset was small (n = 24), the less complex model reduced the chances of overfitting while keeping the variance relatively low. Random forests and BART had an rRMSE greater than 21%. Statistical models could be used to estimate SOC at 10–20 cm and reduce destructive soil analysis methods. Full article

As a key technology for wireless signal identification, modulation recognition plays an important role in the fields of unmanned aerial vehicle (UAV) communications, low-altitude spectrum management, etc. However, the accuracy of modulation recognition often cannot be guaranteed in scenarios with serious noise interference when a few samples are available. In this paper, we propose an intelligent modulation recognition method for UAV signals based on small-sample augmentation and soft threshold denoising. We first propose a new dual-driven dataset expansion method by combining the UAV air–ground channel propagation model with the received data samples. Then, we construct a background learning-based long short-term memory (BL-LSTM) model to extract the environmental background features embedded in the UAV signal, including Line-of-Sight (LoS) state, multi-scale fading parameters and Doppler shift characteristics. We integrate environmental background information into the data training model and optimize the authenticity of data distribution. As a result, the model adaptability can be enhanced. Finally, we construct a deep residual shrinkage network based on the soft threshold function (STF-DRSN). By leveraging the capability of the soft threshold that resists noise interference, we integrate it into each residual block of the deep residual shrinkage network. Simulation results show that compared with the state of the art, our method can improve the modulation recognition accuracy of UAV signals in small-sample scenarios. Full article

This study investigates the effects of three solid waste powders—fly ash (FA), silica fume (SF), and phosphogypsum (P)—on the drying shrinkage behavior of metakaolin-based geopolymers. To systematically evaluate the performance and underlying mechanisms, a comprehensive experimental program was conducted, including compressive strength and elastic modulus testing, early-age and variable-humidity drying shrinkage monitoring, mercury intrusion porosimetry, and microcalorimetry analysis. Results demonstrate that all three materials effectively reduce drying shrinkage through distinct mechanisms. The incorporation of 30% FA optimized the capillary pore network and densified the matrix, achieving a peak compressive strength of 53.51 MPa and an elastic modulus of 9.23 GPa. SF exhibited a dose-dependent effect; at an optimal content of 7%, it enhanced compressive strength by 28.3% through its nucleation effect and micro-aggregate filling. However, excessive SF (9%) led to pore coarsening and increased shrinkage. Although P incorporation slightly reduced mechanical strength, it decreased cumulative porosity by up to 8% and formed needle-like Wairakite-Ca crystals that provided micro-structural support, resulting in a net shrinkage reduction of up to 137.83 µε. This study provides a scientific basis for designing low-shrinkage, low-carbon geopolymers by tailoring solid waste incorporation to engineer multiscale pore structures. Full article

A growing global demand for wood, coupled with the role of this material in low-carbon strategies, is fuelling interest in fast-growing plantations, including short-rotation forestry (SRF) and agroforestry systems. However, evidence of the physical–mechanical properties and possible uses of non-native hardwoods in the Mediterranean environment remains limited. This study aimed to address this current knowledge gap by evaluating the main physical and mechanical properties of six fast-growing non-native tree species cultivated in experimental plots in Calabria, southern Italy. The wood of Eucalyptus occidentalis Endl., E. × trabutii (M. Vilm. ex Trab.) A. Chev., E. camaldulensis Dehnh., E. bridgesiana R.T.Baker, Melia azedarach L., and Paulownia tomentosa (Thunb.) Steud., were evaluated. The dynamic elastic modulus (MOE_d) was estimated on standing trees using stress waves (TreeSonic™). In the laboratory, swelling and shrinkage (ISO 13061-14 and 16), static modulus of elasticity (MOE_s) and modulus of rupture (MOR) (EN 408), and compressive strength (ISO 13061-16) were determined. The data were analysed using one-way ANOVA, followed by Tukey’s HSD test where appropriate. Swelling and shrinkage showed no significant differences (p > 0.05). One-way ANOVA revealed a significant effect of species on MOE_s (p < 0.001). Both standing-tree stress-wave measurements (MOE_d) and laboratory tests (MOE_s, MOR, and compression strength) revealed significant variability in stiffness and resistance among the species examined. The positive relationship observed between MOE_d and MOE_s indicates that stress-wave testing can serve as a practical, rapid tool for ranking plantation material at an early stage, thereby supporting early decision-making in SRF and agroforestry systems. These results provide comparative evidence for species and clonal selection, and to optimise the allocation of plantation resources to targeted value chains in Mediterranean environments. Full article

To investigate how the content of silica fume (SF) influences the performance of foam concrete (FC) after high-temperature exposure and the underlying mechanisms, this study prepared standard FC cube specimens with SF contents of 0%, 0.15%, 0.2%, 0.25%, and 0.3%. The working properties of the material at room temperature were systematically tested, and the mass loss, residual compressive strength, failure mode, microstructure and acoustic emission (AE) data at different temperatures (100 °C, 200 °C, 300 °C and 400 °C) were analyzed. The test results indicate that increasing the SF content reduces the fluidity of the fresh paste yet significantly enhances the compressive strength and lowers the water absorption of FC at room temperature. After high-temperature exposure, the effect of SF exhibits a dual character: at 200 °C and below, SF effectively mitigates the performance degradation of FC. However, when the temperature reaches 300–400 °C, specimens with an excessively high SF content (e.g., 0.3%) experience rapidly built-up internal steam pressure that cannot escape in time, which triggers the formation and propagation of a microcrack network and leads to a sharp drop in strength. Based on AE detection and scanning electron microscopy (SEM) image analysis, the failure process of silica fume foam concrete (SFFC) proceeds through three stages: free water evaporation at low temperatures, dehydration shrinkage of the C-S-H gel at medium temperatures, and finally, structural failure marked by the collapse of the C-S-H gel network at high temperatures. This study indicates that an SF content of 0.25% allows FC to achieve an optimal balance between mechanical properties and high-temperature stability. The findings provide a theoretical basis for optimizing FC mix proportions and enhancing fire prevention design. Full article

Camber in high-speed railway prestressed concrete (PC) girders increases with service time and affects profile control, ride comfort, and durability; reliable long-term midspan camber prediction is therefore required. Building on established hybrid physics–data modeling and discrepancy-correction ideas, we present a monitoring-oriented two-layer strategy for long-term camber prediction. In the physics layer, a physics-informed neural network (PINN) is formulated in a quasi-static, stage-aware manner to capture the physics-consistent low-frequency trend governed by creep, shrinkage, prestress loss, and staged loading. In the data layer, an XGBoost model learns a bounded, measurement-level residual correction from monitoring features to account for additional effects not explicitly represented in the physics layer, without altering the underlying physics-driven trend. The approach is evaluated using monitoring data from five 1:4 scaled specimens of a 24 m post-tensioned simply supported box girder and is compared against a theoretical calculation and a standalone PINN. Across prediction stages and specimens, the proposed strategy reproduces the measured camber evolution more closely than the benchmarks while preserving physically plausible trend behavior and yielding more consistent errors among girders. These results indicate that, under the present scaled-specimen and independently calibrated setting, a stage-aware physics baseline combined with bounded residual correction can provide closer agreement with the observed camber evolution than the benchmark models under sparse-monitoring conditions. Its engineering applicability can be repeatedly demonstrated across girders with different construction-condition combinations after girder-wise calibration. Full article

Additive manufacturing offers a promising route to low-cost, rapidly deployable X-ray focusing optics with geometries that are difficult to realize by conventional machining. Here, we report polymer compound refractive lenses (CRLs) for hard X-ray focusing fabricated by projection micro-stereolithography (PµSL, DLP-based) and by two-photon polymerization (2PP). Two-dimensional bi-parabolic CRL elements were produced in multiple photopolymer resins (HTL, Tough, ST1400 for PμSL; IP-S for 2PP) and evaluated by at-wavelength metrology at the Shanghai Synchrotron Radiation Facility. The single-lens residual phase errors (RMS) less than 0.1 $\mathsf{\lambda }$ were measured for PµSL-fabricated HTL, and Toughlenses, respectively, while 2PP-fabricated IP-S lenses achieved 0.008 $\mathsf{\lambda }$. And the analysis indicates that PµSL lenses are primarily limited by systematic mid-order aberrations, whereas 2PP substantially suppresses coma but shows residual spherical aberration attributable to process calibration and shrinkage. Leveraging the higher fidelity of 2PP, a 65-element parabolic CRL array (radius of curvature of 100 µm) was fabricated and demonstrated hard X-ray focusing at 15 keV with focal spot sizes of 6.4 ± 1 µm (H) and 6.8 ± 1 µm (V), and a flux gain of 220. The measured performance agrees with theoretical expectations when accounting for X-ray source properties, detector resolution and chromatic aberration. These results establish a practical pathway for additively manufactured polymer CRLs with DLP and 2PP techniques as compact, customization focusing optics for synchrotron beamlines. Full article

Northeast China has undergone large-scale cultivation of agricultural land, accompanied by internal restructuring of paddy fields and rain-fed farmland. Such a land change process has an obvious impact on the ecosystem. However, the quantitative effects of long-term cultivation of land/internal structure on the eco-environment are still lacking in the Heilongjiang region, China’s ecological barrier and grain base. To address this academic issue, the integrated method of land update technology, dynamic tracking, remote sensing classification, and improved ecosystem services were applied using satellite imagery and land products. Through satellite monitoring, the area of cultivated land changed from 127,221.71 to 173,665.12 km², with an increment of 46,443.41 km², expanding the central–northern parts and the eastern part over the past half-century. In different regions, all cities have undergone varying degrees of reclamation rate expansion ranging 0.71–29.62%. Regarding the structure, a quarter of the study area was covered by rain-fed farmland (25.29%), but the cultivation level of paddy fields (2.83%) was very low in 1970; after that, only a 13.08% increment in rain-fed farmland but a high increase of 246.14% in paddy fields was monitored from 1970 to 2020. Meanwhile, the source area of cultivated land was 59,271.48 km², with 60.41% from forest and grassland of the agricultural-forestry ecotone. Its destination area was 12,827.11 km², and 78.49% of the total was converted to construction land, forest, and grassland. From 1970 to 2020, the evaluated ecosystem service changed from 15,575.87 to 12,495.72 × 10⁸ yuan, showing a total loss of 3080.15 × 10⁸ yuan and an annual turnover rate of 0.40%. An important calculation indicated that the expansion and shrinkage of cultivated land led to a 2303.46 × 10⁸ yuan loss, which means that three-quarters (i.e., 74.78%) of ecosystem service loss was caused by cultivated land changes. Another key finding was that a large transformation of wetland into paddy fields brought about the huge loss of 847.85 × 10⁸ yuan; by contrast, the process of extensive rain-fed farmland turning into paddy fields was only a small change of 3.38 × 10⁸ yuan. Considering the ecological loss caused by cultivated land, the projects of returning farmland to forests and wetland protection should be implemented. This study provided important references for land system monitoring and environmental impact assessment in high-latitude regions around the world. Full article

To mitigate the issue of brittleness and cracking in epoxy resin (EP) anti-skid systems, this study investigates four key aspects tailored to application scenarios: toughening, low shrinkage, strong adhesion, and rapid curing at ambient temperature. 1,4-Butanediol diglycidyl ether (BDDE) was used to extend the chain of triethylenetetramine (TETA), followed by a Mannich reaction with formaldehyde (F) and cardanol to prepare a flexible aliphatic amine Mannich base curing agent containing flexible segments (Curing Agent B). The influence of composition ratios on the mechanical properties of the cured product was studied. The curing performance of the epoxy system under various temperature conditions and its adhesion to asphalt substrates were characterized. The thermal shrinkage behavior of the epoxy system under temperature-variable environments was also investigated. The results indicated that the elongation at break of the epoxy curing system, after chain extension and toughening, increased from 28.7% to 40.4%, representing a 28.9% increase. When n (Cardanol):n (TETA):n (F):n (BDDE) = 1:1.4:0.8:0.7 (molar ratio of reactants), m (EP):m (Curing Agent B) = 1:1 (mass ratio), and epoxy-terminated polyurethane (EPU) prepolymer constituted 10% of the epoxy resin mass; the epoxy curing system exhibited an elongation at break of 44.3%, a tensile strength of 7.0 MPa, a bond strength of 6.9 MPa, and an impact toughness of 1.77 J/cm². Furthermore, it exhibited rapid curing at a low temperature (0~5 °C) and at room temperature (25 °C). Additionally, when bisphenol F epoxy resin was used, the system demonstrated optimal thermal expansion properties. Full article

The structure collapse and performance degradation caused by traditional air-drying technology often hinder the practical application of bio-based xerogels as absorbent pads. In this study, chitosan (CS) and different types of polyanions (carboxymethyl cellulose (CMC), sodium alginate (SA), hyaluronic acid (HA), pectin (PT) and xanthan gum (XG)) in different proportions were used to prepare an xerogel resistant to atmospheric pressure air drying collapse, and its potential as an absorption pad was systematically evaluated. The results showed that among all the treatments, CS/CMC xerogel at an optimal mass ratio of 1:3 demonstrated superior comprehensive properties. It exhibited minimal shrinkage (p < 0.05) and high porosity, coupled with an exceptional water absorption capacity (140% higher than CS/PT) and hardness (96% higher than CS/SA and CS/HA). FTIR and XRD revealed that strong electrostatic interactions and potential amide bond formation between CS and CMC resulted in a dense yet homogeneous network with low crystallinity. SEM imaging further corroborated a uniform thin-walled porous structure. This stable network contributed to high toughness, of CS/CMC significantly surpassing the brittle CS/XG and CS/PT xerogels (p < 0.05). CS/CMC xerogel is an ideal absorbent material with high absorption, stability, and controllable structure. Full article

The advancement of sustainable construction requires the development of earthen materials compatible with 3D printing (additive manufacturing), along with specified engineering standards. Many existing studies improve workability and early strength using chemical stabilizers such as cement; however, these additives increase embodied carbon and undermine sustainability objectives. Challenges remain in the formulation of an earthen mixture that satisfies both printability and structural requirements for large-scale construction. Previous earth-based mixes have reported excessive shrinkage and inadequate compressive strength. This study presents the systematic optimization of a low-carbon, 3D-printable earthen mixture using locally sourced clay-loam soil from Belén, New Mexico (NM). The soil was modified with graded concrete sand and rice hull fiber to improve printing parameters such as buildability, extrudability, and printability while meeting the NM Earthen Building Code requirements for compressive and flexural strength. Soil characterization tests (particle size distribution, consistency, optimal water content) guided iterative refinement to enhance dimensional stability and mechanical performance. A baseline 2:1 soil-to-sand ratio (max aggregate size No. 4) was established. Incorporating $2\%$ rice hull fiber and reducing max aggregate size to No. 16 (S67F2) early-age shrinkage was reduced from $12.33\%$ to $3.48\%$ ($72\%$ reduction) while maintaining a 28-day compressive strength exceeding 660 psi, more than twice the code minimum. The optimized mixture supported 24 printed layers without deformation, achieved 189 psi flexural strength (three times the code minimum), and produced a stable 2-ft-diameter dome with minimal cracking. Full article

Background: Difficult benign intracranial tumors (including meningiomas, schwannomas, neurofibromatosis-related tumors, and pituitary neuroendocrine tumors) have substantial morbidity in patients. Due to their limited treatment options, there is a need for individualized treatment beyond histological and surgical approaches. Objective: To summarize how novel treatment innovations have been implemented for these tumors, meningiomas and schwannomas are prioritized, followed by NF-associated neoplasms, and then pituitary neuroendocrine tumors in comparison to low-grade gliomas. Methods: We summarize the current knowledge relating to targeted therapies for gliomas, meningiomas, schwannomas, neurofibromatosis (NF) tumors, and pituitary neuroendocrine tumors to investigate an individual’s treatment options for difficult benign brain tumors. This review synthesizes evidence on tumor genomics and molecular markers, supported by methylation-based classification, immunohistochemistry, and functional assays, emphasizing current clinical applications. Evidence Synthesis: The recent data show that DNA methylation-based models can predict post-surgical outcomes and radiotherapy responses, enabling risk stratification and radiotherapy benefit prediction. Early signals support target-directed treatment, including cMET blockade that radiosensitizes NF2 schwannoma models, brigatinib-associated tumor shrinkage in NF2-deficient models, and PitNET organoid data. Conclusions: We support clinical decision-making that utilizes molecular profiling with functional testing to guide targeted treatment. We also identify evidence gaps such as biomarker-defined prospective trials that are needed for broader clinical implementation. Full article

Cytokines are central regulators of inflammation and immune responses within the tumor microenvironment and have been implicated in cancer progression and prognosis. However, the prognostic value of coordinated cytokine-related transcriptional programs across cancer types has not been systematically explored. Pan-cancer transcriptomic and clinical data were analyzed to construct a cytokine-related prognostic signature using least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were stratified into high-risk and low-risk groups based on the derived risk score. Prognostic performance was evaluated in training and test cohorts, and biological relevance was assessed through survival analyses and pathway-level investigations. A 16-gene cytokine-related signature was established that consistently stratified patients into distinct prognostic groups across multiple cancer types. High cytokine-related risk scores were significantly associated with unfavorable survival outcomes and were linked to enhanced cell cycle activity, epithelial-mesenchymal transition, and extracellular matrix remodeling. Integration of the risk score with clinical variables improved individualized survival prediction. Immunohistochemical analyses further confirmed increased protein expression of representative risk-associated genes, including pannexin 1 (PANX1) and FERM domain containing 8 (FRMD8), in multiple tumor tissues compared with corresponding normal tissues. The cytokine-related prognostic signature captures key inflammatory and immune-related programs underlying tumor aggressiveness and provides a robust tool for pan-cancer risk stratification with potential clinical utility. Full article