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Bitumen fatigue resistance is critical to determine the overall fatigue performance and service life of asphalt pavements. However, the mechanisms responsible for fatigue damage of bitumen have previously not been well understood. Molecular dynamics (MD) simulation has recently emerged as a powerful computer-aided numerical technique to model the microscopic failure behaviours in materials. This study aims to use the MD method to investigate the molecular origin of bitumen fatigue damage. The molecular models of the virgin and aged PEN70/100 bitumen were firstly constructed based on their saturate, aromatic, resin and asphaltene (SARA) four fractions. An MD equilibrium was run on the developed bitumen models with the assigned interatomic potentials. Following an MD-based tensile simulation, a strain-controlled fatigue simulation was performed to study the nanostructure and damage behaviours of the virgin and aged bitumen under fatigue loading by calculating the stress-strain response, potential energy, molecular structure and nanovoid volumes. Furthermore, a rheometer measurement was also conducted to characterise the fatigue damage of the bitumen directly by a crack length at the macroscale. Results indicate that the bitumen molecules become unfolded and tend to align along the loading direction when fatigue loading was applied. The change in the molecular configuration helped the molecular chains move closer together and thus contributed to the reduction of the intermolecular interactions including the van der Waals and Coulombic energies. With the increasing load cycles, nanovoids were formed and grew in the bitumen through molecular rearrangement and movement, leading to microscopic fatigue damage of the bitumen. It was found that the aged bitumen produced more severe fatigue damage than the virgin bitumen, which was indicated by the MD-based nanovoid volume at the molecular scale and the DSR-based crack length at the macroscale. The findings from MD simulation, Pavement Engineering

As an environmentally responsible alternative to conventional concrete, geopolymer concrete recycles previously used resources to prepare the cementitious component of the product. The challenging issue with employing geopolymer concrete in the building business is the absence of a standard mix design. According to the chemical composition of its components, this work proposes a thorough system or framework for estimating the compressive strength of fly ash-based geopolymer concrete (FAGC). It could be possible to construct a system for predicting the compressive strength of FAGC using soft computing methods, thereby avoiding the requirement for time-consuming and expensive experimental tests. A complete database of 162 compressive strength datasets was gathered from the research papers that were published between the years 2000 and 2020 and prepared to develop proposed models. To address the relationships between inputs and output variables, long short-term memory networks were deployed. Notably, the proposed model was examined using several soft computing methods. The modeling process incorporated 17 variables that affect the CSFAG, such as percentage of SiO2 (SiO2), percentage of Na2O (Na2O), percentage of CaO (CaO), percentage of Al2O3 (Al2O3), percentage of Fe2O3 (Fe2O3), fly ash (FA), coarse aggregate (CAgg), fine aggregate (FAgg), Sodium Hydroxide solution (SH), Sodium Silicate solution (SS), extra water (EW), superplasticizer (SP), SH concentration, percentage of SiO2 in SS, percentage of Na2O in SS, curing time, curing temperature that the proposed model was examined to several soft computing methods such as multi-layer perception neural network (MLPNN), Bayesian regularized neural network (BRNN), generalized feed-forward neural networks (GFNN), support vector regression (SVR), decision tree (DT), random forest (RF), and LSTM. Three main innovations of this study are using the LSTM model for predicting FAGC, optimizing the LSTM model by a new evolutionary a, Pavement Engineering

The design of geopolymer concrete must meet more stringent requirements for the landscape, so understanding and designing geopolymer concrete with a higher compressive strength challenging. In the performance prediction of geopolymer concrete compressive strength, machine learning models have the advantage of being more accurate and faster. However, only a single machine learning model is usually used at present, there are few applications of ensemble learning models, and model optimization processes is lacking. Therefore, this paper proposes to use the Firefly Algorithm (AF) as an optimization tool to perform hyperparameter tuning on Logistic Regression (LR), Multiple Logistic Regression (MLR), decision tree (DT), and Random Forest (RF) models. At the same time, the reliability and efficiency of four integrated learning models were analyzed. The model was used to analyze the influencing factors of geopolymer concrete and determine the strength of their influencing ability. According to the experimental data, the RF-AF model had the lowest RMSE value. The RMSE value of the training set and test set were 4.0364 and 8.7202, respectively. The R value of the training set and test set were 0.9774 and 0.8915, respectively. Therefore, compared with the other three models, RF-AF has a stronger generalization ability and higher prediction accuracy. In addition, the molar concentration of NaOH was the most important influencing factors, and its influence was far greater than the other possible factors including NaOH content. Therefore, it is necessary to pay more attention to NaOH molarity when designing geopolymer concrete., Pavement Engineering

We report on an experiment performed at the FLASH2 free-electron laser (FEL) aimed at producing warm dense matter via soft x-ray isochoric heating. In the experiment, we focus on study of the ions emitted during the soft x-ray ablation process using time-of-flight electron multipliers and a shifted Maxwell–Boltzmann velocity distribution model. We find that most emitted ions are thermal, but that some impurities chemisorbed on the target surface, such as protons, are accelerated by the electrostatic field created in the plasma by escaped electrons. The morphology of the complex crater structure indicates the presence of several ion groups with varying temperatures. We find that the ion sound velocity is controlled by the ion temperature and show how the ion yield depends on the FEL radiation attenuation length in different materials.

Context.Unusually, there are still certain characteristics of the changing-look (CL) active galactic nuclei (AGNs) that remain undetected.Consequently,the trigger mechanism behind the CL phenomenon observed in partial AGNs remains unknown.Aims.We explore the light curve and spectral energy distribution (SED) of the CL blazar OQ 334 as obtained by Fermi-LAT. Methods. By examining the variability of the equivalent width (EW), we categorise the Fermi-LAT light curves of OQ 334 during the epoch of MJD 54628-58677 into seven distinct epochs, including the flat spectrum radio quasar (FSRQ) state, the transition state, and the BL Lac state. We obtained both a Fermi-LAT SED and a multi-wavelength SED for each of these distinct epochs. Results. The source exhibits a transformation from a quiescent state to a highly active state, as evidenced by the variability of the EW. The multi-wavelength SEDs display a prominent external Compton characteristic, even though the Fermi-LAT SED reveals both a FSRQ and a BL Lac state across the seven different epochs. To gain further insights, we employed a leptonic model that takes into account the soft photon fields originating from both synchrotron radiation and the external environment. By simulating the multi-wavelength SEDs for each epoch, we uncover the following results. Firstly, the energy density of the external photon fields evolves in an oscillatory manner over the seven different epochs. Also, the energy density of the external photon fields in the BL Lac state is lower than that in the FSRQ state.Conclusions. These findings suggest that the CL blazar represents a unique phase in the blazar sequence., Comment: Accepted for publication in A&A. 12 pages, 5 figures, 4 table

This study implements molecular dynamics (MD) simulations to explore the atomic-level energy properties of rejuvenated bitumen, considering the influence of different recycling agent (RA) types, dosages and aging levels of bitumen. Moreover, the potential correlations between energy indices and high-temperature performance of rejuvenated bitumen are explored. Our findings show that recycling agents can effectively reinstate the cohesive energy density (CED) values of aged bitumen, correlating well with their high-temperature rheological properties. The results reveal that the energy parameters of potential energy (UVEP), kinetic energy (UWEK), non-bond energy (EN), total energy (UVET), diagonal energy (UNED), and cross-terms energy (ECT) can reflect the restoration level of recycling agents (RAs) on atomic-level energy characteristics of aged bitumen. Compared to rutting failure temperature (RFT), elastic recovery (R3.2), and creep compliance (Jnr3.2), the zero-shear viscosity (ZSV) greatly correlates with CED. Meanwhile, the UWEK index from MD simulations demonstrates a strong correlation with high-temperature rheological indicators of rejuvenated bitumen. With the rise in UWEK, there is a linear decrease in the RFT, Log(ZSV), and R3.2 values of rejuvenated bitumen. Conversely, the Log(Jnr3.2) exhibits a linear increasing trend. However, the correlation patterns between rheological indicators and either EN or ECT are contingent on the aging degree of bitumen. Based on the correlation coefficient, the UWEK stands out as the primary choice among all energy indices for predicting high-temperature rheological performance of rejuvenated bitumen., Pavement Engineering

The increasing popularity of sustainable asphalt pavement stems from its advantageous attributes, such as cost-saving, environmental protection, and reductions in energy and material consumption. Although there is a desire to maximize the reuse of reclaimed asphalt (RA) waste materials in road construction, this is hindered by the poor performance of aged bitumen. In response, rejuvenation technology has been developed to restore the cohesive and adhesive properties of aged binders. To effectively select appropriate rejuvenators for aged bitumen derived from diverse RA sources and showing varying chemo-mechanical properties, it is crucial to establish an evaluation method that can assess and differentiate the rejuvenation efficiency of different rejuvenator-aged bitumen blends. Furthermore, it is essential to gain a fundamental understanding of the underlying mechanisms responsible for the variations. This dissertation aims to develop a comprehensive and multi-scale approach for assessing the rejuvenation efficiency and mechanisms of various rejuvenator-aged bitumen blends. The combination of molecular dynamics (MD) simulations prediction and experimental validation is throughout the whole thesis to evaluate the compatibility potential and diffusive capacity of rejuvenators within aged bitumen, as well as their rejuvenation effectiveness in the chemo-thermodynamic-rheological performance. Additionally, the intermolecular interactions occurring between the rejuvenator and aged bitumen molecules are visualized and quantified by MD simulations. The accurate construction of molecular models for aged bitumen is crucial for investigating the fundamental effects of aging on bitumen behavior at the molecular scale. To accomplish this, the long-term aging influence on the chemical characteristics of bitumen was assessed through Saturate, Aromatic, Resin, and Asphaltene (SARA) fractionation, Fourier Transform Infrared Spectroscopy (FTIR) test and element analysis meth, Pavement Engineering

Hollow-structured materials show promise in thermal insulation because the shells encapsulating gaseous voids can interrupt heat transport pathways. Here, we present two low-cost routes to fabricate hollow silica nanoshells, via gas-phase and liquid-phase methods. The gas-phase synthesis method generates hollow shells by a droplet surface precipitation mechanism in a flame aerosol reactor. The liquid-phase synthesis route forms hollow shells by removal of a carbon template, which is produced by hydrothermal reaction of glucose. Both approaches (gas- and liquid-phase) provide hollow silica with amorphous structure, low thermal conductivity (0.023 and 0.026 W m−1 K−1), small particle size (442 and 383 nm), thin shell (35 and 36 nm), and low density (0.015 and 0.033 g cm−3). We employed high shear mechanical mixing to fabricate hollow silica-fiberglass composite ceramics. The resulting three-dimensional network provides the ceramics with robust mechanical elasticity and fire-retardancy while maintaining low thermal conductivity, dramatically outperforming an analogous material using commercial silica gel in place of the hollow nanoshells. Our findings provide two practical routes to synthesize hollow silica, either of which can be used to manufacture a class of hollow shell-fiber nanocomposite soft ceramics for energy-saving applications.

This study investigates the impacts of rejuvenator type/dosage and the aging degree of bitumen on the chemical and rheological properties of rejuvenated bitumen, and propose critical chemo-rheological indicators for evaluating rejuvenation efficiency. Moreover, the potential connections between essential chemical and rheological indices of rejuvenator-aged bitumen blends are explored. Results indicate that chemical indices show linear relationships with rejuvenator dosage and vary depending on the rejuvenator type and aging level of bitumen. All rejuvenators can regenerate certain rheological parameters of aged bitumen to varying degrees, but cannot restore the crossover modulus (Gc). Various rheological indices exhibit different correlations with rejuvenator dosage and sensitivity degrees to the discrepancy in rejuvenator type and aging degree of bitumen. Critical chemical and rheological indicators are proposed based on their sensitivity levels to influence factors, with the aromaticity index (AI), carbonyl index (CI), and sulfoxide index (SI) as effective chemical indices and the complex modulus (G*), crossover frequency (fc), and high-temperature master curve area (AMH) as critical rheological indices for rejuvenation efficiency evaluation. The study finds that the magnitude of rejuvenation efficiency for four rejuvenators is Bio-oil > Engine-oil > Naphthenic-oil > Aromatic-oil, and the linear correlations between the critical chemical and rheological indices, together with their rejuvenation percentages, are significantly affected by the rejuvenator type and aging level of bitumen., Pavement Engineering

Surface energy is a key material property and can work as a crucial parameter in various mechanical models to predict the moisture sensitivity and fatigue damage of asphalt mixtures. The calculated surface energy values of the aggregate minerals strongly depend on their surface roughness. Therefore, it is very relevant for accurate calculation of surface energy to study the relationship between roughness and surface energy. This study aims to investigate the relationship between surface roughness and surface energy of aggregate minerals. Two minerals—quartz and calcite—were used for this study. The surfaces of the mineral specimens were treated to achieve four levels of roughness. Their surface roughness was described by three roughness parameters. Based on the sessile drop method, an optical tensiometer with a 3D topography module was employed to measure the contact angle and the surface energy of the minerals with different roughness. The influences of surface roughness on the contact angle and the surface energy were then analyzed. The results showed that the contact angle for both quartz and calcite decreases with the increasing surface roughness when it is less than 90° and increases when it is greater than 90°. The Wenzel equation can remove the effect of surface roughness on the contact angles of the minerals. The surface energy of quartz and calcite in the presence of roughness at the microscale would be underestimated when using the measured (apparent) contact angle. The corrected surface energy based on the Wenzel equation must be applied to represent the real surface energy of the minerals., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Pavement Engineering

In this study, the environmentally friendly rejuvenators with waste thermal conductive oil, polymer, and the interfacial reinforcing agent were prepared. And the influence of the different rejuvenators on the rejuvenation mechanisms of aged SBS modified asphalt was characterized by different scales including the molecule structure, morphology, phase transition and interface adhesion characteristic, and macro performance. The results show that the thermal-oxidative aging process increases the molecular weight of asphalt, promotes the SBS phase to agglomerate, and decreases the high and low temperature performance, thermal stability, and adhesion. When the rejuvenator was added, the molecular weight distribution of asphalt binders can be improved, while adding the regenerant-II can supplement the SBS modifier and reform the cross-linking structure. Furthermore, the regenerant-II has a better recovery effect on the morphology structure and resumes the thermal behavior. And then softening point and ductility can be recovered by 89.7% and 94.8% of the original SBS modified asphalt. Under the action of the interfacial reinforcing agent, the regenerant-III could increase the adhesion work to 95.49% of the original SBS modified asphalt., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Pavement Engineering

Data set on the ion emission of different materials. Each dataset is separate and titled with the chemical symbol or abbreviation of the specific material.

The ethylene-vinyl acetate (EVA) polymers are always doped into waxy bitumen to inhibit network of wax crystals in bitumen. However, the compatibility improvement behaviors between wax-based warm mix (WWM) additives and bitumen by EVA are not clear, and the sustainable components of EVA for corresponding WWM additives to achieve better compatibility improvement are also not determined. This paper investigated compatibility improvement behaviors between commonly used WWM additives and bitumen after the addition of EVA to obtain sustainable components of EVA through experimental method of activation energy of viscous flow (AEVF) and density function theory-molecular dynamic (DFT-MD) calculations. The results show that the repulsions between the end of main-chain with highest electronegativity in WWM additives and polar molecules of EVA can alleviate the aggregation behaviors of WWM additives and EVA displays the best and worst compatibility improvements for additives with shortest and longest carbon chains, respectively. The dispersed asphaltenes combined with EVA can form the composite wax inhibitors (WIs) systems to increase diffusion coefficient and reduce percentage increment values of cohesive energy density (CED) to further disrupt ordered degree of WWM additives. On this basis, the sustainable carbon numbers of main-chain for EVA that are slightly less than average carbon numbers of WWM additives will help to better improve the compatibility of WWM additives. This investigation can provide the inspiration on how to choose the sustainable components of EVA to achieve high-efficiency compatibility improvement for corresponding warm mix asphalts (WMAs) with different average carbon numbers., Pavement Engineering

Pavement Engineering

Two types of elastomer/plastic compound-modified bitumen were developed by means of incorporating the reactive elastomeric terpolymer (RET) into the plastic (high-density polyethylene HDPE or recycled polyethylene RPE) modified bitumen and adding the wax residue (WR) into the bitumen/elastomer (crumb rubber CR or styrene–butadiene–styrene SBS) blends. The rheological properties, morphology microstructure and storage stability of these novel elastomer/plastic compound-modified binders were characterised. The results revealed that RET elastomer positively improved the high-temperature modulus, temperature insensitivity, rut resistant, elastic recovery and shear-resistance of HDPE- and RPE-modified bitumen. However, excessive RET dosage adversely influenced the cracking resistance of plastic-modified bitumen, and its optimum dosage was recommended as 1 wt%. Moreover, RET elastomer significantly strengthened the storage stability of HDPE and RPE-modified binders. The elasticity improvement effect of RET was attributed to the generated polymer network. On the other hand, adding WR limitedly deteriorated the rutting resistance and weakened the elastic recovery performance of elastomer (CR and SBS) modified bitumen. To ensure the low-temperature performance, the optimum level of WR was 2 wt%. Furthermore, the addition of WR promoted the compatibility and dispersion of CR and SBS modifiers in bitumen., Pavement Engineering

This study aims to propose critical fatigue indicators for evaluating the restoration effectiveness of various rejuvenators on the fatigue performance of aged bitumen. The influence factors of rejuvenator type/dosage and aging degree of bitumen are involved, and different fatigue parameters from linear viscoelastic (LVE), linear amplitude sweep (LAS), and time sweep (TS) tests are analysed. The results reveal that bio-oil exhibits the greatest rejuvenation efficiency in improving fatigue life of aged bitumen, followed by engine-oil and naphthenic-oil rejuvenators, while aromatic-oil shows the lowest effect. Moreover, the rejuvenation percentages on fatigue parameters of rejuvenated bitumen enhance significantly with increased rejuvenator dosage but weaken as the aging level deepens. The fatigue failure temperature (FFT) from the LVE test, fatigue life (Nf5), peak strain (ɛsr), elastic modulus (E) from the LAS test, and crack width (C500) from the TS test are recommended as critical indicators for fatigue performance evaluation of rejuvenated binders. Further, the crack width greatly correlates with other essential indicators and can be predicted using correlation equations without conducting the time-consuming time sweep test. The difference in these critical fatigue parameters of various rejuvenator-aged bitumen blends provides the macroscale basis for future nanoscale mechanism exploration and superior rejuvenator development., Pavement Engineering

High-Content SBS Polymer Modified Asphalt Mixtures (HCPMA) combined with fibers have gained popularity in porous pavement construction due to their superior performance. Although the aging behavior of HCPMA has been extensively studied, the impact of fibers on performance and aging susceptibility remains unclear. This research investigates the influence of two representative fibers (lignin and polyester) on the raveling, cracking, fatigue, and rutting resistance of HCPMA before and after aging using Cantabro loss tests, SCB strength tests, SCB fatigue tests, and Hamburg Wheel-Tracking tests. The results indicate that in the original state, polyester fiber slightly enhances HCPMA performance, while lignin fiber shows limited or even adverse effects on cracking, raveling, fatigue, and rutting resistance. However, both fibers exhibit a more pronounced enhancement effect after short- and long-term aging. FTIR analysis reveals that fiber addition does not significantly impact bitumen oxidation and polymer degradation. The excellent properties of High-Content SBS Polymer Modified Bitumen (HCPMB) in the original state create a "masking" effect that conceals the enhancement effect of fibers, which becomes more evident after long-term aging. Consequently, it is recommended that the performance evaluation and design of open-graded asphalt mixtures containing HCPMB be based on post-aging performance., Pavement Engineering

With the increasing awareness of environmental protection and attention to resource reuse, the development of high-performance and degradable green biomass pavement materials attracts a lot of interest. Lignin and bio-oil effectively combined to play a synergistic role can improve various properties of asphalt and partially replace petroleum-based asphalt. Therefore, this paper aims to study the rheological and aging properties of bio-oil/lignin composite modified asphalt (OLMA) and determine the optimal dosage by Dynamic Shear Rheometer (DSR), Bending Beam Rheometer (BBR), and Fourier transforms infrared spectroscopy (FTIR) tests. From the DSR tests, it can be seen that OLMA can improve the high-temperature, fatigue, cracking, and relaxation performance of asphalt. BBR test obtained that OLMA can improve the asphalt's low-temperature performance and critical temperature. The method for evaluating the aging degree of composite modified asphalt was proposed. FTIR test results revealed that OLMA could reduce the increased rate of the aging index. The optimum dosage of 10% bio-oil and 20% lignin composite modified asphalt was determined. It proved that lignin and bio-oil are promising asphalt additives, modifiers, and replacements., Pavement Engineering

High-viscosity modified asphalt (HVMA) is the most commonly applied method in drainage asphalt pavements. However, some disadvantages of hot-mix HVMA, including high energy consumption and unavoidable environmental pollution, should be improved. Therefore, warm-mix additive (WMA) was introduced. In this paper, the effects of WMA on the rheological and microstructural properties of HVMA were studied to select optimum WMA conditions. WMAs mainly include foam warm mix (1%, 3%, and 5%), Sasobit (1%, 3%, and 5%), Evotherm (0.4%, 0.8%, and 1.2%), and the newly introduced warm additive glow brand (GLWBR) (0.4%, 0.8%, and 1.2%). Dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests were performed on HVMA after rheological processes. Also, microstructural properties were examined by Fourier transform infrared spectroscopy and scanning electron microscopy methods. Based on the obtained results, all WMAs reduced the viscosity (135°C) of HVMA and achieved warm mixing effects. However, absolute viscosity (60°C) was enhanced by Sasobit and GLWBR. In addition, GLWBR improved high-temperature rheological performance and had no significant effect on the low-temperature and aging performance of HVMA. These findings were further verified by morphological observations., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Pavement Engineering

This study aims to multiscale investigate the effects of rejuvenator type, temperature, and aging degree of bitumen on the diffusion behaviors of rejuvenators (bio-oil BO, engine-oil EO, naphthenic-oil NO, and aromatic-oil AO) in aged binders. The molecular dynamics (MD) simulation method is performed to detect the molecular-level diffusion characteristics of rejuvenators and predict their diffusion coefficient (D) parameters. At an atomic scale, the mutual but partial interfacial diffusion feature between rejuvenators and aged bitumen molecules is observed. Moreover, Fick’s Second Law well fits the concentration distribution of rejuvenator molecules in aged bitumen. The magnitude for D values of four rejuvenators varies from 10-11 to 10-10 m2/s, and the diffusive capacity order is BO > EO > NO > AO. Meanwhile, diffusion tests and dynamic shear rheometer (DSR) characterizations are employed to validate the MD simulation outputs. The experimental results in magnitude and order of D values agree well with MD simulation outputs. Lastly, the increased aging degree of bitumen exhibits a negative impact on the molecular diffusivity of BO, EO, and NO rejuvenators, while the D value of AO molecules enlarges as the aging level deepens. The underlying mechanism may be composed of the free volume fraction in aged bitumen and the intermolecular force between rejuvenator and aged bitumen molecules, which differs remarkably for various rejuvenators., Pavement Engineering

Fabry-Pérot interference (FPI) structure for strain measurement relies on complex and expensive air microcavities, significantly limiting its use in microstrain size. This article proposes a novel Hookean effect-based FPI sensor with polydimethylsiloxane (PDMS) flexible material as the cavity and ultrahard, completely opaque silicon carbide (SiC) crystal as the reflective surface, dubbed Hookean-type FPI sensor. The relationship between the axial strain response and the PDMS material properties is investigated to disclose the optimal cavity elastic material alternative. The proposed Hookean-type FPI sensor has an excellent linear response, with a sensitivity of up to {15} \text {pm}/\mu \epsilon . To improve the demodulation efficiency and cost of microstrain sensors, a high-efficiency intelligent demodulation system based on the array waveguide grating (AWG) and back-propagation neural network (BPNN) for the Hooke-type FPI sensor is introduced to interrogate the axial microstrain along the fiber. Experiments conducted in the real-world axial strain dataset demonstrate the effectiveness and superiority of the proposed demodulation system. The proposed sensing framework can provide reliable analytical support for engineering applications.

FBG array sensors have been widely used in the multi-point monitoring of large structures due to their excellent optical multiplexing capability. This paper proposes a cost-effective demodulation system for FBG array sensors based on a Neural Network (NN). The stress variations applied to the FBG array sensor are encoded by the array waveguide grating (AWG) as transmitted intensities under different channels and fed to an end-to-end NN model, which receives them and simultaneously establishes a complex nonlinear relationship between the transmitted intensity and the actual wavelength to achieve absolute interrogation of the peak wavelength. In addition, a low-cost data augmentation strategy is introduced to break the data size bottleneck common in data-driven methods so that the NN can still achieve superior performance with small-scale data. In summary, the demodulation system provides an efficient and reliable solution for multi-point monitoring of large structures based on FBG array sensors.

The reverse design of photonic crystal fibers (PCFs) using AI has received significant attention in recent years. To quickly optimize the fundamental optical properties of PCFs and obtain the optimal design combination, researchers have favored machine learning algorithms. However, relying solely on the knowledge provided by a few experts has limited the versatility and performance of these models. To address these issues, we propose a collaborative PCF property optimization framework as a new paradigm for reverse design. This framework allows experts from different institutions to share their design knowledge and collaboratively optimize the fundamental optical properties of PCFs without direct data interaction. Additionally, this framework can adapt to low-resourced computing devices that only use a small dataset without any data augmentation methods to achieve excellent optimization performance. Our proposed framework provides a novel and practical platform for global collaboration among research institutions for the reverse design of micro-structured fibers.

This study proposes a high-frequency pneumatic system and demodulation method based on polydimethylsiloxane (PDMS) film-embedded fiber-optic Fabry-Perot sensor to meet the conflicting requirements of small sizes and wide frequency-response range not achieved by conventional pneumatic probes. The high modulus of elasticity of PDMS films provides the potential for an upper limit of a pneumatic frequency response up to 20 kHz, and the new demodulation algorithm, based on the ability of the F-P cavity to return to its initial length from the maximum cavity length change, is utilized to analyze its variation. The process of recovering F-P cavity corresponds with the sparse part of the signal, which takes advantage of the unique characteristics of interference fringes in this part. Moreover, the relationship between the relative change of the F-P cavity length and pneumatic pressure, as well as the relationship between the duration of the relative change of the F-P cavity length and the frequency are analyzed comprehensively. The rationality of the proposed demodulation scheme is verified from the angle-error analyses. These analyses could be helpful for integrated and high-frequency response pneumatic detection.

This article presents a novel unsupervised representation learning-based demodulation framework for Fabry-Perot interferometer (FPI) sensors, which is a straightforward and effective solution for obtaining an interferometric spectrum without any optical spectrum analyzers (OSAs). The proposed framework utilizes a simple spectrum reconstruction method to reconstruct the FPI sensor's spectrum using relatively low-scale sample points, requiring less manual effort than conventional approaches. The proposed approach involves two steps: first, an optical system converts the FPI sensing signal to transmitted intensity, and second, the unsupervised representation learning-based reconstruction framework establishes a nonlinear relationship between the intensity signal and the actual changing spectrum. The proposed approach is validated using real-world datasets generated from pressure performance tests, achieving excellent performance with a reconstruction error of 0.039 nm and a range of 73 nm. The results demonstrate the practical potential viability of the proposed framework for large-scale remote monitoring systems.

This article proposes a complete framework for the manufacturing and dual-parameter demodulation of sensor systems consisting of cascaded fiber Bragg gratings (FBGs) and Fabry-Perot interferometers (FPIs). The proposed system aims to enable simultaneous interrogation of the external strain and temperature using a machine learning (ML) technique, with limited data availability and without requiring an optical spectrum analyzer (OSA). The system converts the sensing signals of a cascaded FBG-FPI sensor into changes in the transmitted optical intensity across multiple channels of the array waveguide grating (AWG). By inputting the transmitted optical intensity and wavelength shift data into a neural network, an intricate nonlinear relationship is established, which enables precise interrogation of the peak wavelength. Furthermore, to overcome the common limitation of insufficient data in data-driven models, we introduce a high-performance data augmentation method that utilizes a generative adversarial network (GAN) to rapidly augment the dataset during the training process. Extensive experiments using a real-world dataset generated in an industrial optical fiber sensing scenario demonstrate the effectiveness and superiority of the proposed framework.

AIM: Mouse models have indicated that the pneumococcal polysaccharide vaccine (PPV) can reduce atherosclerosis. This is probably through a process of molecular mimicry, where phosphorylcholine in the capsular polysaccharide of the vaccine elicits antibodies that cross-react with oxidised low-density lipoprotein and reduce plaque. We investigated whether a similar mechanism occurs in humans. METHODS: A large national blinded, randomised, placebo-controlled trial of the PPV (Australian Study for the Prevention through Immunisation of Cardiovascular Events [AUSPICE]) is underway with fatal and nonfatal cardiovascular disease (CVD) events as the primary outcome. Participants at one centre agreed to a substudy measuring a number of biomarkers and surrogates of CVD over 4 years, including anti-pneumococcal antibodies (immunoglobulin G and immunoglobulin M), C-reactive protein, carotid intima-media thickness, pulse wave velocity, insulin, fasting blood glucose, glycated haemoglobin, and hepatorenal index. RESULTS: Antipneumococcal immunoglobulin G and immunoglobulin M were both present and statistically significantly increased in the treated group compared to control at 4 years. However, there were no differences in any of the surrogate measures of CVD or metabolic markers at 4 years. CONCLUSIONS: While there were prolonged differences in anti-pneumococcal antibody titres following PPV vaccination, these did not appear to provide any cardioprotective effect, as measured by a range of markers. Final results using the fatal and nonfatal CVD events await the completion of national health record linkage next year. TRIAL REGISTRATION: ACTRN12615000536561.

Mortality prediction is crucial to evaluate the severity of illness and assist in improving the prognosis of patients. In clinical settings, one way is to analyze the multivariate time series (MTSs) of patients based on their medical data, such as heart rates and invasive mean arterial blood pressure. However, this suffers from sparse, irregularly sampled, and incomplete data issues. These issues can compromise the performance of follow-up MTS-based analytic applications. Plenty of existing methods try to deal with such irregular MTSs with missing values by capturing the temporal dependencies within a time series, yet in-depth research on modeling inter-MTS couplings remains rare and lacks model interpretability. To this end, we propose a bidirectional time and multi-feature attention coupled network (BiT-MAC) to capture the temporal dependencies (i.e., intra-time series coupling) and the hidden relationships among variables (i.e., inter-time series coupling) with a bidirectional recurrent neural network and multi-head attention, respectively. The resulting intra- and inter-time series coupling representations are then fused to estimate the missing values for a more robust MTS-based prediction. We evaluate BiT-MAC by applying it to the missing-data corrupted mortality prediction on two real-world clinical datasets, i.e., PhysioNet'2012 and COVID-19. Extensive experiments demonstrate the superiority of BiT-MAC over cutting-edge models, verifying the great value of the deep and hidden relations captured by MTSs. The interpretability of features is further demonstrated through a case study.

We report an electrochemical reactor that converts 3.0 M KHCO3 into methane at the cathode, and oxidizes water at the anode. The molar ratio of methane product to unreacted CO2 gas (defined herein as "methane yield") was measured to be 34% at a partial current density of 120 mA cm-2. The highest previously reported CO2-to-methane yield is 3%. Our reactor achieved this improvement in methane yield because it is fed with 3.0 M KHCO3, a type of reactive carbon solution, rather than gaseous CO2. The reactor uses H+ delivered by a bipolar membrane to form CO2 at the cathode. This CO2 is subsequently reduced into methane. A cationic surfactant added to the catholyte suppressed hydrogen evolution and increased methane formation. A 1D continuum model confirmed that H+ from the membrane promotes the formation of methane over multicarbon products at the cathode. These findings present design principles for electrochemical methane synthesis.

Molecular dynamics (MD) simulation is an advanced tool to explore the interaction mechanism between aged bitumen and rejuvenators at the nanoscale. However, the general MD molecular structures of rejuvenators led to the lower quantify and inaccuracy of the simulation outputs. This study aims at developing more realistic molecular models to represent the generic rejuvenators for MD simulation of aged bitumen recycling. Four types of rejuvenators (bio-oil, engine-oil, naphthenic-oil, and aromatic-oil) are characterized in terms of element analysis, functional groups distribution observed from Attenuated total reflectance-Fourier-transform infrared (ATR-FTIR) spectroscopy, and average molecular weight. Afterward, the average molecular structures of rejuvenators are determined and validated. Further, the MD simulations are performed to predict the energetic, dynamic, volumetric, and structural properties of various rejuvenators. Based on the chemical characteristics, the average chemical formula of bio-oil, engine-oil, naphthenic-oil, and aromatic-oil is derived as C19H36O2, C22H44, C26H48, C30H40. From MD simulations, the ranking of density and glass transition temperature for four different rejuvenators is AO > NO > BO > EO, which is same as the experimental results. It proves that the established average molecular structures of four rejuvenators are reasonable. Various rejuvenators display different thermodynamics and structural properties. The aromatic-oil exhibits the highest potential energy, cohesive energy density, and solubility parameter. Besides, the order of expansion coefficient and diffusion coefficient of the four rejuvenators is the same as BO > EO > NO > AO, while the viscosity presents the opposite sequence. Moreover, the fractional free volume values follow EO > BO > NO > AO. The occurrence probability between bio-oil and aromatic-oil molecules is higher than engine-oil and naphthenic-oil. This study develops the represe, Pavement Engineering

Lignin, one of the most abundant natural polymers, has been extensively studied as an additive in bituminous binders. Even though the lignin improves the overall resistance against oxidative aging of bitumen, it could lead to high thermal cracking sensitivity. In this study, a bio-oil (i.e., rapeseed oil) is implemented in lignin-modified bitumen to ameliorate characteristics, such as the resistance to fatigue and cracking. The long-term aging of bitumens formulated by different proportions of bio-oil was simulated by the pressure aging vessel (PAV) method. Fourier Transform Infrared Spectroscopic (FTIR) results demonstrated lignin has a remarkable antiaging effect, but adding bio-oil will slightly deteriorate the antiaging effect. The Brookfield rotational viscometer showed that the addition of bio-oil was able to reduce the binder’s viscosity observably, thereby improving the workability of bitumen. The frequency sweep tests revealed that lignin increased the stiffness and improved the thermal stability. Also, the multiple stress creep recovery tests corroborated that lignin significantly enhanced the rutting resistance of binders. The fatigue and thermal cracking properties of lignin-modified binder could be strengthened by increasing bio-oil content which is confirmed from both linear amplitude sweep, Glover-Rowe parameter, and Bending Beam Rheometer (BBR) tests. Moreover, the relaxation test results demonstrated that bio-oil decreased the residual stress ratio and relaxation time dramatically. Overall, this study has shown preliminary conclusions on the incorporating of bio-oil to enhance the medium-low temperature properties of lignin-modified binders. In the meantime, bio-oil did not interfere with the improvement influence of lignin on the neat bitumen regarding high-temperature performance., Accepted Author Manuscript, Pavement Engineering

AbstractIn this paper, we investigate the influential factors that impact on the performance when the tasks are co-running on a multicore computers. Further, we propose the machine learning-based prediction framework to predict the performance of the co-running tasks. In particular, two prediction frameworks are developed for two types of task in our model: repetitive tasks (i.e., the tasks that arrive at the system repetitively) and new tasks (i.e., the task that are submitted to the system the first time). The difference between which is that we have the historical running information of the repetitive tasks while we do not have the prior knowledge about new tasks. Given the limited information of the new tasks, an online prediction framework is developed to predict the performance of co-running new tasks by sampling the performance events on the fly for a short period and then feeding the sampled results to the prediction framework. We conducted extensive experiments with the SPEC2006 benchmark suite to compare the effectiveness of different machine learning methods considered in this paper. The results show that our prediction model can achieve the accuracy of 99.38% and 87.18% for repetitive tasks and new tasks, respectively.

High content rubber modified bitumen (HCRMB) prepared from the high content of waste tire rubber and bitumen has good performance while allowing greater use of the waste tires. However, HCRMB is subject to aging during use, which can affect its performance. The purpose of this paper was to investigate the effect of high content of waste tire rubber and sulfur on the aging behavior of bitumen. The properties of all bitumen were tested using rolling thin film oven aging (RTFOT) test, pressure aging vessel (PAV) test, frequency sweep tests, temperature sweep (TS) test, multiple stress creep recovery (MSCR) test, and attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) test. Test results show that the addition of sulfur to HCRMB leads to an improvement in the elasticity of HCRMB. The elasticity of HCRMB with different amounts of sulfur increases with aging. In addition, the increase in the amount of sulfur can improve the RTFOT aging resistance and the PAV aging resistance of HCRMB. Sulfur cannot reduce the degree of oxidation of HCRMB after aging, but can inhibit the degree of desulfurization of HCRMB. Furthermore, the aging process of HCRMB with different amounts of sulfur is dominated by the degradation of polybutadiene., Pavement Engineering

Molecular dynamics (MD) simulation plays an effective role in predicting the critical properties and explaining the macroscale phenomenon at the nanoscale. This review summarized the application cases of MD simulations in various bitumen systems, considering aging, modification, and rejuvenation factors. Meanwhile, the potential relationships between the nanoscale parameters predicted from MD simulations and macroscale properties measured from experimental tests were discussed for the first time. Different molecular models of virgin bitumen, commonly-used Forcefields, and validation parameters for MD simulations on bituminous materials were summarized. Based on the reactive MD simulation outputs, the oxidative aging reaction path at the atomic scale of bitumen molecules was reviewed. Furthermore, the influence of aging (short-term and long-term), modification (polymers, fillers, and bio-bitumen), and rejuvenation (various rejuvenators) on the molecular-scale properties of virgin bitumen models would be evaluated through MD simulations. This review could help us further explore the main functions of MD simulations in different bulk bitumen systems and build an integral multi-scale research method from the molecular design and performance prediction to material optimization and synthesis of bituminous materials without lots of experimental attempts., Pavement Engineering

BACKGROUND: Stimulator of interferon (IFN) genes (STING) is a protein that promotes type I IFN production essential for T-cell activation. In this study, we aim to characterize STING expression comprehensively using The Cancer Genome Atlas (TCGA) database, cell lines, and patient tumor samples stained with immunohistochemistry. METHODS: Two cohorts were evaluated comprising 721 non-small cell lung cancer (NSCLC) patients and 55 NSCLC cell lines for STING and cyclic GMP-AMP synthase (cGAS) expression using immunohistochemistry. Moreover, an independent cohort of n = 499 patients from the TCGA database was analyzed. Methylation was evaluated on STING and cGAS in five STING-negative NSCLC cell lines. RESULTS: STING RNA expression positively correlates with T cell function and development genes, negatively correlates with cell proliferation and associated with increased survival (5-year-overall survival [OS] 47.3% vs. 38.8%, p = 0.033). STING protein expression is significantly higher in adenocarcinoma (AC) and is lost with increasing stages of AC. STING-positivity is significantly higher in mutant EGFR and KRAS tumors. STING-positive NSCLC patients identified with immunohistochemistry (H-score > 50) have increased survival (median OS: 58 vs. 35 months, p = 0.02). Treatment of STING-negative cell lines with a demethylating agent restores STING expression. CONCLUSIONS: STING is ubiquitously expressed in NSCLC and associated with T cell function genes, AC histology, EGFR, and KRAS mutations and improved overall survival.

We report an electrochemical reactor that converts 3.0 M KHCO3 into methane at the cathode, and oxidizes water at the anode. The molar ratio of methane product to unreacted CO2 gas (defined herein as "methane yield") was measured to be 34% at a partial current density of 120 mA cm-2. The highest previously reported CO2-to-methane yield is 3%. Our reactor achieved this improvement in methane yield because it is fed with 3.0 M KHCO3, a type of reactive carbon solution, rather than gaseous CO2. The reactor uses H+ delivered by a bipolar membrane to form CO2 at the cathode. This CO2 is subsequently reduced into methane. A cationic surfactant added to the catholyte suppressed hydrogen evolution and increased methane formation. A 1D continuum model confirmed that H+ from the membrane promotes the formation of methane over multicarbon products at the cathode. These findings present design principles for electrochemical methane synthesis.

Plastic pollution is one of the global pressing environmental problems, threatening the health of aquatic and terrestrial ecosystems. However, the influence of plastic residues and microplastics (MPs) in soil ecosystems remains unclear. We conducted a global meta-analysis to quantify the effect of plastic residues and MPs on indicators of global soil ecosystem functioning (i.e. soil physicochemical properties, plant and soil animal health, abundance and diversity of soil microorganisms). Concentrations of plastic residues and MPs were 1–2700 kg ha−1 and 0.01–600,000 mg kg−1, respectively, based on 6223 observations. Results show that plastic residues and MPs can decrease soil wetting front vertical and horizontal movement, dissolved organic carbon, and total nitrogen content of soil by 14%, 10%, 9%, and 7%, respectively. Plant height and root biomass were decreased by 13% and 14% in the presence of plastic residues and MPs, while the body mass and reproduction rate of soil animals decreased by 5% and 11%, respectively. However, soil enzyme activity increased by 7%single bond441% in the presence of plastic residues and MPs. For soil microorganisms, plastic residues and MPs can change the abundance of several bacteria phyla and families, but the effects vary between different bacteria.

Compared with traditional asphalt, emulsified asphalt occurs to be a better low-temperature usability and environmental adaptability, which can reduce environmental pollution and energy consuming during road construction. The low-temperature ductility is a very important indicator to evaluate the environmental adaptability of emulsified asphalt. However, the relevance between microstructure and low-temperature ductility of modified asphalt is still rarely reported. Herein, we reported the first successful unfolding of the microscopic mechanism of ductility attenuation of the modified emulsified asphalt by combining experiments and characterization: Emulsifiers and additives had greater influence on the low-temperature ductility. Anionic and cationic emulsifiers had the similar ductility loss. Adding a non-ionic emulsifier OP-10 could be a solution to improve the ductility. The effect of the temperature change occurred less significant compared to the pH evolution of surfactant solution. The grey relation entropy (GRE) analysis revealed that the emulsifier structure (C/H ratio) would be the most important factor to affect the low-temperature ductility. The macro, micro and nano scales of modified emulsified asphalt were correlated, revealing in-depth that the aggregation and inter-chains interaction of styrene-butadiene-styrene (SBS) were the internal mechanism leading to the ductility loss. The change of glass transition temperature (Tg) was proposed to correlate the microstructural factor with the ductility. Moreover, the combination of ductility test and bending beam rheometer (BBR) test could be an effective way to evaluate the low-temperature performance of asphalt., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Pavement Engineering

Low-temperature cracking is a major concern to improve the utilization of recycled asphalt mixture (RAM). A mechanism by which the crack propagates can provide a basis for advanced technological mitigation. Microcrack formations in the interfacial proximity of the virgin and aged binders have been identified from electron microscopy tests. Atomic force microscopy (AFM) experiment showed the trilayer phases at the virgin-aged binder interface. In this study, molecular dynamics (MD) simulations were conducted to understand the nanoscopic crack propagation characteristics at the virgin-aged binder interface in the asphalt mixture with RAM. It was found that the blended binder of virgin and aged binders, and its interfaces with virgin and aged binders appeared to be the crack propagation zones. The relatively more significant matrix contraction of virgin binder and stiffer aged binder at a low temperature can cause more considerable tensile stress at the blended binder and its interfaces. Consequently, interfacial crack propagation became more profound and decreased the low temperature cracking resistance., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Pavement Engineering

Today, high-viscosity modified asphalt (HVMA) is widely used in drainage asphalt pavements. However, due to its high construction temperature, HVMA is prone to thermal oxidative aging, which reduces its life cycle and increases the maintenance costs of asphalt pavements. In this study, the effects of warm-mix additives on the physical, rheological and chemical properties of HVMA were studied to determine optimum warm-mix conditions. First, the effects of warm-mix technologies (foam warm mix, Sasobit, Evotherm, and GLWBR at 3%, 3%, 0.8%, and 0.8%, respectively) on the physical and rheological properties of HVMAwere studied. Then, two aging methods [thin film oven test (TFOT) and pressure aging vessel (PAV)] were applied to simulate the short-term and long-term thermal oxidation processes of HVMA and evaluate the influences of different warm-mix technologies on HVMA aging. The results showed that the four warm-mix technologies, especially foam warm mix and Sasobit, reduced the construction temperature of HVMA. In addition, warm-mix technologies also improved the high-temperature rheological properties of HVMA; however, they had adverse effects on the low-temperature cracking resistance of asphalt. Based on asphalt aging index fluctuations, it was evident that warm-mix technology was not conducive to the antiaging performance of HVMA, and foam warm mix had the weakest influence on the antiaging performance of high-viscosity asphalts. Furthermore, according to the results of an analysis of the carbonyl changes in aging asphalts, asphalt aging index can be applied to predicting the degree of aging of warm-mix HVMA., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Pavement Engineering

To achieve sustainable development, local governments are under enormous pressure to simultaneously achieve the three assessment tasks (TATs) of energy saving, CO₂ reduction, and pollution reduction. However, the TATs are often managed by different authorities and have three types of measures (TTMs) that correspond to them. The lack of adequate cooperation between these authorities has led to the inefficient investment of policy resources and even to policy conflicts, and the interactions among the TTMs are not yet known. To this end, this paper uses the MCEE model to assess the interactions among the TTMs quantitatively using Guangzhou, China, as a case study. The results showed the following. (1) According to the current development trend, if the authorities managing the TATs continue to work alone, they will not be able to fulfill the corresponding assessment tasks in the future. (2) The TTMs have interactions with each other, and their synergies are far greater than their trade-offs. From 2015 to 2035, it is expected that energy-saving measures can accomplish 54.39% of the CO₂ reduction tasks and 32.74% of the pollution reduction tasks indirectly, and low-carbon measures can accomplish 55.53% of the energy saving tasks and 27.20% of the pollution reduction tasks indirectly, However, environmental-protection measures will cause fewer trade-offs (energy demand and CO2 emissions increase by 3.76% and 2.88%, respectively). (3) In some years, the contribution of interactions among the TTMs are even higher than their direct contribution to the TATs. Our findings suggest that intensive cooperation between authorities is necessary, and that the benefits of such cooperation will outweigh the disadvantages.

The prediction of express delivery sequence, i.e., modeling and estimating the volumes of daily incoming and outgoing parcels for delivery, is critical for online business, logistics, and positive customer experience, and specifically for resource allocation optimization and promotional activity arrangement. A precise estimate of consumer delivery requests has to involve sequential factors such as shopping behaviors, weather conditions, events, business campaigns, and their couplings. Despite that various methods have integrated external features to enhance the effects, extant works fail to address complex feature-sequence couplings in the following aspects: weaken the inter-dependencies when processing heterogeneous data and ignore the cumulative and evolving situation of coupling relationships. To address these issues, we propose DeepExpress - a deep-learning-based express delivery sequence prediction model, which extends the classic seq2seq framework to learn feature-sequence couplings. DeepExpress leverages an express delivery seq2seq learning, a carefully designed heterogeneous feature representation, and a novel joint training attention mechanism to adaptively handle heterogeneity issues and capture feature-sequence couplings for accurate prediction. Experimental results on real-world data demonstrate that the proposed method outperforms both shallow and deep baseline models.

Ubiquitous Internet of Things (IoT) sensors in the smart city generate various urban utility sequential data, such as electricity and water usage records, which are defined as multivariate utility time series (MUTS). Due to the complex behavior of human beings, MUTS contains more complicated relationships, which go beyond general multivariate time series (TS). Specifically, multifaceted temporal couplings exist in MUTS, including intra-/inter-TS, short-to-long term, evolving, and polarized (positive/negative) relationships. Existing multisequence predictors including the latest deep-learning methods either weaken short-to-long term representation or omit evolving and polarized couplings. This work focuses on MUTS sensory data representation and prediction and proposes a novel approach-CoupledMUTS for multifaceted temporal coupling relational learning. MUTS representation module generates multidimensional representations to reveal short-to-long temporal couplings in MUTS. Gated coupling units (GCUs) module learns evolving couplings by filtering weak positive/negative relations. And dual-stage fusion module integrates multifaceted temporal couplings in both intra-TS and inter-TS for prediction. Extensive experiments on two real-world utility data sets demonstrate that our method outperforms existing shallow and deep models in utility demand prediction.

BACKGROUND AND AIMS: Observational studies have demonstrated that the pneumococcal polysaccharide vaccine (PPV) is associated with reduced risk of cardiovascular events. This may be mediated through IgM antibodies to OxLDL, which have previously been associated with cardioprotective effects. The Australian Study for the Prevention through Immunisation of Cardiovascular Events (AUSPICE) is a double-blind, randomised controlled trial (RCT) of PPV in preventing ischaemic events. Participants received PPV or placebo once at baseline and are being followed-up for incident fatal and non-fatal myocardial infarction or stroke over 6 years. METHODS: A subgroup of participants at one centre (Canberra; n = 1,001) were evaluated at 1 month and 2 years post immunisation for changes in surrogate markers of atherosclerosis, as pre-specified secondary outcomes: high-sensitive C-reactive protein (CRP), pulse wave velocity (PWV), and carotid intima-media thickness (CIMT). In addition, 100 participants were randomly selected in each of the intervention and control groups for measurement of anti-pneumococcal antibodies (IgG, IgG2, IgM) as well as anti-OxLDL antibodies (IgG and IgM to CuOxLDL, MDA-LDL, and PC-KLH). RESULTS: Concentrations of anti-pneumococcal IgG and IgG2 increased and remained high at 2 years in the PPV group compared to the placebo group, while IgM increased and then declined, but remained detectable, at 2 years. There were statistically significant increases in all anti-OxLDL IgM antibodies at 1 month, which were no longer detectable at 2 years; there was no increase in anti-OxLDL IgG antibodies. There were no significant changes in CRP, PWV or CIMT between the treatment groups at the 2-year follow-up. CONCLUSIONS: PPV engenders a long-lasting increase in anti-pneumococcal IgG, and to a lesser extent, IgM titres, as well as a transient increase in anti-OxLDL IgM antibodies. However, there were no detectable changes in surrogate markers of atherosclerosis at the 2-yea

BACKGROUND AND AIMS: Observational studies have demonstrated that the pneumococcal polysaccharide vaccine (PPV) is associated with reduced risk of cardiovascular events. This may be mediated through IgM antibodies to OxLDL, which have previously been associated with cardioprotective effects. The Australian Study for the Prevention through Immunisation of Cardiovascular Events (AUSPICE) is a double-blind, randomised controlled trial (RCT) of PPV in preventing ischaemic events. Participants received PPV or placebo once at baseline and are being followed-up for incident fatal and non-fatal myocardial infarction or stroke over 6 years. METHODS: A subgroup of participants at one centre (Canberra; n = 1,001) were evaluated at 1 month and 2 years post immunisation for changes in surrogate markers of atherosclerosis, as pre-specified secondary outcomes: high-sensitive C-reactive protein (CRP), pulse wave velocity (PWV), and carotid intima-media thickness (CIMT). In addition, 100 participants were randomly selected in each of the intervention and control groups for measurement of anti-pneumococcal antibodies (IgG, IgG2, IgM) as well as anti-OxLDL antibodies (IgG and IgM to CuOxLDL, MDA-LDL, and PC-KLH). RESULTS: Concentrations of anti-pneumococcal IgG and IgG2 increased and remained high at 2 years in the PPV group compared to the placebo group, while IgM increased and then declined, but remained detectable, at 2 years. There were statistically significant increases in all anti-OxLDL IgM antibodies at 1 month, which were no longer detectable at 2 years; there was no increase in anti-OxLDL IgG antibodies. There were no significant changes in CRP, PWV or CIMT between the treatment groups at the 2-year follow-up. CONCLUSIONS: PPV engenders a long-lasting increase in anti-pneumococcal IgG, and to a lesser extent, IgM titres, as well as a transient increase in anti-OxLDL IgM antibodies. However, there were no detectable changes in surrogate markers of atherosclerosis at the 2-yea

This study aims to comprehensively investigate the rejuvenation efficiency of various self-developed compound rejuvenators on the physical, mechanical, and aging properties of aged bitumen, asphalt mortar, and mixture. The results revealed that the restoration capacity of vacuum distilled-oil rejuvenators on high-and-low temperature performance-grade of aged bitumen is more significant. In contrast, an aromatic-oil based rejuvenator is good at enhancing low-temperature grade and aging resistance. Moreover, the temperature and time of the curing conditions for mixing recycling of asphalt mixture were optimized as 150 °C and 120 min. Furthermore, the sufficient anti-rutting, structural stability, and moisture resistance of recycled asphalt mixture affirmed the rejuvenation efficiency of compound rejuvenators., Pavement Engineering

The cohesive and adhesive performances of bituminous materials significantly affect the service life of asphalt pavement. The molecular dynamics (MD) simulation method has been proved as an effective tool to predict the thermodynamics parameters of different multisubstance and multi-phase bitumen models during different diffusion, self-healing, and interfacial interaction processes. This paper aims to comprehensively review the application cases of MD simulations on dynamic and interfacial bitumen systems. The diffusion behaviors of oxygen, moisture, and rejuvenator molecules in the bitumen matrix could be illustrated from MD simulations considering the influence of temperature, pressure, and humidity. Moreover, molecular mobility and distribution of bitumen molecules on the aggregate surface remarkably influenced the interfacial bonding level and moisture sensitivity. In addition, the molecularscale mechanism and evaluation indices for the self-healing potential of bitumen models were reviewed. Further, the representative bitumen-(moisture)-aggregate interfacial models, the corresponding evaluation parameters, and influence factors for the adhesive bonding strength in MD simulations were overviewed. Besides, the effects of bitumen components, aggregate type, moisture invasion, temperature variation, and pull-off tension rate on the adhesion performance of bitumen-aggregate models were summarized and discussed. This review can help us fundamentally understand the dynamic diffusion, self-healing behaviors, and interfacial characteristics of bitumen models at the atomic level and develop more potential functions of MD simulations in addressing the scientific issues of sustainable bituminous materials., Pavement Engineering

Molecular dynamics (MD) simulation plays an effective role in predicting the critical properties and explaining the macroscale phenomenon at the nanoscale. This review summarized the application cases of MD simulations in various bitumen systems, considering aging, modification, and rejuvenation factors. Meanwhile, the potential relationships between the nanoscale parameters predicted from MD simulations and macroscale properties measured from experimental tests were discussed for the first time. Different molecular models of virgin bitumen, commonly-used Forcefields, and validation parameters for MD simulations on bituminous materials were summarized. Based on the reactive MD simulation outputs, the oxidative aging reaction path at the atomic scale of bitumen molecules was reviewed. Furthermore, the influence of aging (short-term and long-term), modification (polymers, fillers, and bio-bitumen), and rejuvenation (various rejuvenators) on the molecular-scale properties of virgin bitumen models would be evaluated through MD simulations. This review could help us further explore the main functions of MD simulations in different bulk bitumen systems and build an integral multi-scale research method from the molecular design and performance prediction to material optimization and synthesis of bituminous materials without lots of experimental attempts., Pavement Engineering

High content rubber modified bitumen (HCRMB) prepared from the high content of waste tire rubber and bitumen has good performance while allowing greater use of the waste tires. However, HCRMB is subject to aging during use, which can affect its performance. The purpose of this paper was to investigate the effect of high content of waste tire rubber and sulfur on the aging behavior of bitumen. The properties of all bitumen were tested using rolling thin film oven aging (RTFOT) test, pressure aging vessel (PAV) test, frequency sweep tests, temperature sweep (TS) test, multiple stress creep recovery (MSCR) test, and attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) test. Test results show that the addition of sulfur to HCRMB leads to an improvement in the elasticity of HCRMB. The elasticity of HCRMB with different amounts of sulfur increases with aging. In addition, the increase in the amount of sulfur can improve the RTFOT aging resistance and the PAV aging resistance of HCRMB. Sulfur cannot reduce the degree of oxidation of HCRMB after aging, but can inhibit the degree of desulfurization of HCRMB. Furthermore, the aging process of HCRMB with different amounts of sulfur is dominated by the degradation of polybutadiene., Pavement Engineering

Molecular dynamics (MD) simulation is an advanced tool to explore the interaction mechanism between aged bitumen and rejuvenators at the nanoscale. However, the general MD molecular structures of rejuvenators led to the lower quantify and inaccuracy of the simulation outputs. This study aims at developing more realistic molecular models to represent the generic rejuvenators for MD simulation of aged bitumen recycling. Four types of rejuvenators (bio-oil, engine-oil, naphthenic-oil, and aromatic-oil) are characterized in terms of element analysis, functional groups distribution observed from Attenuated total reflectance-Fourier-transform infrared (ATR-FTIR) spectroscopy, and average molecular weight. Afterward, the average molecular structures of rejuvenators are determined and validated. Further, the MD simulations are performed to predict the energetic, dynamic, volumetric, and structural properties of various rejuvenators. Based on the chemical characteristics, the average chemical formula of bio-oil, engine-oil, naphthenic-oil, and aromatic-oil is derived as C19H36O2, C22H44, C26H48, C30H40. From MD simulations, the ranking of density and glass transition temperature for four different rejuvenators is AO > NO > BO > EO, which is same as the experimental results. It proves that the established average molecular structures of four rejuvenators are reasonable. Various rejuvenators display different thermodynamics and structural properties. The aromatic-oil exhibits the highest potential energy, cohesive energy density, and solubility parameter. Besides, the order of expansion coefficient and diffusion coefficient of the four rejuvenators is the same as BO > EO > NO > AO, while the viscosity presents the opposite sequence. Moreover, the fractional free volume values follow EO > BO > NO > AO. The occurrence probability between bio-oil and aromatic-oil molecules is higher than engine-oil and naphthenic-oil. This study develops the represe, Pavement Engineering