Precast Assembled Road Paving Technology: Progress and Prospects.

This article presents a systematic review of the most cutting-edge research on precast pavement technology for the first time. Firstly, precast pavement is divided into two categories, precast cement concrete pavement and precast carpeted flexible pavement, according to the application of precast technology in pavement engineering. Subsequently, the structural characteristics, advantages, and disadvantages of various precast pavement systems are compared and analyzed; technical problems in precast pavement systems are explained; and future development directions are identified. In addition, the text specifically mentions the great contribution of precast carpeted flexible pavement technology in reducing the harmful effects of asphalt fumes on humans and the environment. This work will promote the application of prefabrication in road engineering and provide suggestions and references for subsequent research.

Subregion-specific 18F-FDG PET-CT radiomics for the pre-treatment prediction of EGFR mutation status in solid lung adenocarcinoma.

This study aimed to assess the efficacy of fluor-18 fluorodeoxyglucose (18F-FDG) PET/CT using sub-regional-based radiomics in predicting epidermal growth factor receptor (EGFR) mutation status in pretreatment patients with solid lung adenocarcinoma. A retrospective analysis included 269 patients (134 EGFR+ and 135 EGFR-) who underwent pretreatment 18F-FDG PET/CT scans and EGFR mutation testing. The most metabolically active intratumoral sub-region was identified, and radiomics features from whole tumors or sub-regional regions were used to build classification models. The dataset was split into a 7:3 ratio for training and independent testing. Feature subsets were determined by Pearson correlation and the Kruskal Wallis test and radiomics classifiers were built with support vector machines or logistic regressions. Evaluation metrics, including accuracy, area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were employed for different classifiers. Results indicated that the sub-region-based classifier outperformed the whole-tumor classifier in terms of accuracy (73.8% vs. 66.2%), AUC (0.768 vs. 0.632), specificity (65.0% vs. 50.0%), PPV (70.2% vs. 62.2%), and NPV (78.8% vs. 74.0%). The clinical classifier exhibited an accuracy of 75.0%, AUC of 0.768, sensitivity of 72.5%, specificity of 77.5%, PPV of 76.3%, and NPV of 73.8%. The combined classifier, incorporating sub-region analysis and clinical parameters, demonstrated further improvement with an accuracy of 77.5%, AUC of 0.807, sensitivity of 77.5%, specificity of 77.5%, and NPV of 77.5%. The study suggests that sub-region-based 18F-FDG PET/CT radiomics enhances EGFR mutation prediction in solid lung adenocarcinoma, providing a practical and cost-efficient alternative to invasive EGFR testing.

Effect of Industrial Solid Waste as Fillers on the Rheology and Surface Free Energy of Asphalt Mastic.

The continuous growth of industrial solid waste production has generated many environmental problems. We evaluated the potential of industrial solid waste as a substitute filler in asphalt mastic, with the aim of increasing the use of sustainable road construction materials. In this study, X-ray fluorescence spectroscopy (XRF) and scanning electron microscopy (SEM) were used to characterize the oxide composition and micromorphology of limestone (LS), red mud (RM), steel slag (SS), and ground granulated blast-furnace slag (GGBFS). Four asphalt mastics containing LS, RM, SS, and GGBFS with a filler-to-binder weight ratio of one were prepared. An evaluation of the rheology and wetting of the solid-waste-filler asphalt mastic was conducted using a frequency sweep, temperature sweep, linear amplitude sweep (LAS), multiple stress creep and recovery (MSCR), and surface free energy (SFE) methods. The results showed that SS increased the complex modulus, elastic component of the asphalt mastic and decreased the nonrecoverable creep compliance at stress levels of 0.1 and 3.2 kPa, which improved the rutting resistance of the asphalt mastic and reduced deformation under high-temperature conditions. The RM and GGBFS increased the fatigue performance of the asphalt mastic under strain loading, enhanced its fatigue life, and maintained good performance under long-term loading. The dispersive component of the SFE parameter of the solid-waste-filler asphalt mastic was larger than the polar component for the largest share of the surface energy composition. The SFE of the asphalt mastic prepared from the industrial solid-waste filler was reduced; however, the difference was insignificant compared to the limestone asphalt mastic. Solid-waste-filler asphalt mastic has performance characteristics, and its actual application can be based on different performance characteristics to select an appropriate solid-waste filler. The results of this study provide new technological solutions for solving the utilization rate of solid waste materials and sustainable road construction in the future.

Evaluating the Effects of Polyphosphoric Acid (PPA) on the Anti-Ultraviolet Aging Properties of SBR-Modified Asphalt.

The ultraviolet (UV) aging of asphalt is an important factor affecting the long-term performance of asphalt pavement, especially in high altitude cold regions. The current studies have reported that styrene butadiene rubber-modified asphalt (SBRMA) has a good cracking resistance at low temperatures. In addition, polyphosphoric acid (PPA) is an effective modifier that can enhance the anti-UV aging properties of asphalt. However, the understanding of the improvement mechanism of PPA on the anti-aging of SBRMA remains unclear. Therefore, this study aimed to evaluate the effect of PPA on the UV aging resistance of SBRMA. The rheological properties of PEN90 asphalt(90#A), SBRMA, and PPA/SBR modified (PPA/SBR-MA) before and after UV aging were evaluated by dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests. The molecular weight and chemical structure of 90#A, SBRMA, and PPA/SBR-MA were determined by Fourier transform infrared spectroscopy (FTIR) and gel permeation chromatography (GPC), and the interaction and modification mechanism of the modifiers were analyzed. The rheological analysis shows that the high and low temperature performances of SBRMA are improved by adding PPA, and PPA also significantly reduces the sensitivity of SBRMA to UV aging. The microscopic test results show that PPA has a complex chemical reaction with SBRMA, which results in changes in its molecular structure. This condition enhances SBRMA with a more stable dispersion system, inhibits the degradation of the polymer macromolecules of the SBR modifier, and slows down the aging process of base asphalt. In general, PPA can significantly improve the anti-UV aging performance of SBRMA. The Pearson correlations between the aging indexes of the macro and micro properties are also significant. In summary, PPA/SBRMA material is more suitable for high altitude cold regions than SBRMA, which provides a reference for selecting and designing asphalt pavement materials in high altitude cold regions.

Centimeter-Scale PdS2 Ultrathin Films with High Mobility and Broadband Photoresponse.

2D materials with mixed crystal phase will lead to the nonuniformity of performance and go against the practical application. Therefore, it is of great significance to develop a valid method to synthesize 2D materials with typical stoichiometry. Here, 2D palladium sulfides with centimeter scale and uniform stoichiometric ratio are synthesized via controlling the sulfurization temperature of palladium thin films. The relationship between sulfurization temperature and products is investigated in depth. Besides, the high-quality 2D PdS2 films are synthesized via sulfurization at the temperature of 450-550 °C, which would be compatible with back-end-of-line processes in semiconductor industry with considering of process temperature. The PdS2 films show an n-type semiconducting behavior with high mobility of 10.4 cm2 V-1 s-1 . The PdS2 photodetector presents a broadband photoresponse from 450 to 1550 nm. These findings provide a reliable way to synthesizing high-quality and large-area 2D materials with uniform crystal phase. The result suggests that 2D PdS2 has significant potential in future nanoelectronics and optoelectronic applications.

Effect of Re-Recycling on Rheology and Microstructure of Asphalt Binder.

Currently, aged recycled asphalt pavements have re-recycling demands, but the evolution mechanism of re-recycled asphalt binder properties is still unclear. Therefore, this study analyzes the rheological properties and microstructure of re-recycled asphalt by dynamic shear rheometer (DSR), bending beams rheometer (BBR), atomic force microscope (AFM), and Fourier transform infrared spectroscopy (FTIR). The macro performance results show that re-recycling improves high-temperature performance and reduces fatigue and low-temperature performance. In addition, the aged re-recycled asphalt's ΔTc ≤ -2.5 °C, has a risk of low-temperature cracking. The micro results show that the adhesion between asphalt and aggregate decreases as the recycling times increase; the re-recycled asphalt mixture has a greater adhesion cracking risk. Some macro-micro experimental results are correlated. Aging accelerates the decay of rheological properties of re-recycled asphalt by increasing the microscopic roughness and carbonyl index of re-recycled asphalt. It indicates that re-recycling reduces the aging resistance of asphalt. Furthermore, the properties of recycled asphalt are strongly correlated with aging functional groups, roughness, and surface energy; the microstructural changes significantly influence the rheology properties of asphalt.

A semantic information-driven stepwise landslide displacement prediction model.

Landslide prediction is critical for the early warning of a landslide occurrence. Existing stepwise landslide displacement prediction methods are mostly data-driven approaches. However, these models are vulnerable to overfitting, and the low-dimensional numerical features with high numerical volatility prevent them from precisely quantifying the rapid increase in daily displacement in the acceleration phase. Therefore, we propose a semantic information-driven stepwise landslide displacement prediction model comprising an identifier in the displacement phase and a predictor in the acceleration phase. First, the raw landslide monitoring data are converted into text-based semantic information and the semantic features are fused. Subsequently, based on the daily displacement and velocity, we propose a sliding window phase division algorithm to divide the stepwise landslide phase into stationary and acceleration phases. Finally, the landslide displacement phase is identified, and the displacement during the acceleration phase is predicted. The experimental results of the model on the Xinpu and Qingshi landslides in Chongqing, China, show that the proposed model exploits the derived semantic information to identify the landslide acceleration phase qualitatively, and predict the daily displacement of the acceleration phase quantitatively. The proposed model provides a valuable reference for the early warning of stepwise landslides.

Evaluating Solid Lung Adenocarcinoma Anaplastic Lymphoma Kinase Gene Rearrangement Using Noninvasive Radiomics Biomarkers.

PURPOSE: To develop a radiogenomics classifier to assess anaplastic lymphoma kinase (ALK) gene rearrangement status in pretreated solid lung adenocarcinoma noninvasively. MATERIALS AND METHODS: This study consisted of 140 consecutive pretreated solid lung adenocarcinoma patients with complete enhanced CT scans who were tested for both EGFR mutations and ALK status. Pre-contrast CT and standard post-contrast CT radiogenomics machine learning classifiers were designed as two separate classifiers. In each classifier, dataset was randomly split into training and independent testing group on a 7:3 ratio, accordingly subjected to a 5-fold cross-validation. After normalization, best feature subsets were selected by Pearson correlation coefficient (PCC) and analysis of variance (ANOVA) or recursive feature elimination (RFE), whereupon a radiomics classifier was built with support vector machine (SVM). The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: In classifier one, 98 cases were selected as training data set, 42 cases as independent testing data set. In classifier two, 87 cases were selected as training data set, 37 cases as independent testing data set. Both classifiers extracted 851 radiomics features. The top 25 pre-contrast features and top 19 post-contrast features were selected to build optimal ALK+ radiogenomics classifiers accordingly. The accuracies, AUCs, sensitivity, specificity, PPV, and NPV of pre-contrast CT classifier were 78.57%, 80.10% (CI: 0.6538-0.9222), 71.43%, 82.14%, 66.67%, and 85.19%, respectively. Those results of standard post-contrast CT classifier were 81.08%, 82.85% (CI: 0.6630-0.9567), 76.92%, 83.33%, 71.43%, and 86.96%. CONCLUSION: Solid lung adenocarcinoma ALK+ radiogenomics classifier of standard post-contrast CT radiomics biomarkers produced superior performance compared with that of pre-contrast one, suggesting that post-contrast CT radiomics should be recommended in the context of solid lung adenocarcinoma radiogenomics AI. Standard post-contrast CT machine learning radiogenomics classifier could help precisely identify solid adenocarcinoma ALK rearrangement status, which may act as a pragmatic and cost-efficient substitute for traditional invasive ALK status test.

MiR-339 depresses cell proliferation via directly targeting S-phase kinase-associated protein 2 mRNA in lung cancer.

BACKGROUND: S-phase kinase-associated protein 2 (Skp2) takes great part in the development of multiple tumors. However, the post-transcriptional modulation mechanism of Skp2 remains unclear. Here, we present a new regulatory microRNA of Skp2, miR-339, which directly targets Skp2 to inhibit cell proliferation in lung cancer. METHODS: The expression of miR-339 or Skp2 in lung cancer samples was tested by real time-PCR. The correlation between miR-339 and Skp2 in lung cancer samples was analyzed by Pearson's correlation coefficient. The effect of miR-339 or anti-miR-339 on Skp2 was evaluated by immunoblotting. The luciferase reporter gene assay was used to test the targeting of miR-339 on Skp2. 3-(4,5-Dimethylthiazol-2-yl)-2,5 diphenyltetrazolium bromide and colony formation analysis were applied to examine the function of miR-339 targeting Skp2 in lung cancer cells. RESULTS: The negative correlation of miR-339 with Skp2 was found in clinical human lung cancer tissues. Furthermore, Skp2 expression was obviously abated by miR-339 in lung cancer A549 cells. Mechanistically, we used bioinformatics to predict that miR-339 could target the 3'-untranslated region of Skp2 mRNA. Luciferase reporter gene assay demonstrated that miR-339 could decrease the luciferase activities of the 3'-untranslated region vector of Skp2. In terms of function, ectopic miR-339 expression significantly suppressed cell proliferation in lung cancer. Overexpressed Skp2 accelerated miR-339-bated proliferation of lung cancer cells. MiR-339 inhibitor promoted cell proliferation in lung cancer, but Skp2 RNA interference reversed miR-339 inhibitor-driven cell proliferation. CONCLUSION: MiR-339 targets the 3'-untranslated region of Skp2 mRNA to depress the proliferation of lung cancer cells.