Influence of waste polyethylene/WCO composite on physical and chemical properties of asphalt.

The use of waste polyethylene (WPE) in modified asphalt is frequently employed to reduce environmental pollution and improve asphalt properties. However, research has shown that using WPE alone as a modifier does not effectively enhance the low-temperature flexibility of asphalt. This study aims to investigate the potential of utilizing WPE and waste cooking oil (WCO) as composite modifiers to enhance the properties of virgin asphalt under both high and low-temperature conditions. The contents of WPE and WCO were used, and the preparation process for the modified asphalt was optimized through an orthogonal experiment. The experimental results indicate that the optimal formulation for the WPE/WCO composite modified asphalt (WPE/WCO-A) is obtained with an additive dosage of 8% and 1% by mass of virgin asphalt for WPE and WCO, respectively, as well as the maintenance process at a temperature of 140 °C and a duration of 2 h. Dynamic shear rheometer (DSR) results reveal that WPE/WCO composite modifier can greatly improve the high-temperature deformation resistance of asphalt. Bending beam rheometer (BBR) tests confirm that WPE adversely affects the low-temperature flexibility of asphalt, while the addition of WCO can improve it. WPE/WCO-A has even better low-temperature properties than virgin asphalt (VA). The Fourier transform infrared spectroscopy (FT-IR) results suggest that the composite modification of asphalt by WPE/WCO modifiers is dominated by physical action. Furthermore, the fluorescence microscopy test results demonstrate that WCO can promote WPE swelling in asphalt. This study offers a novel approach to improve the comprehensive properties of asphalt through composite modification using WPE and WCO.

ResNet incorporating the fusion data of RGB & hyperspectral images improves classification accuracy of vegetable soybean freshness.

The freshness of vegetable soybean (VS) is an important indicator for quality evaluation. Currently, deep learning-based image recognition technology provides a fast, efficient, and low-cost method for analyzing the freshness of food. The RGB (red, green, and blue) image recognition technology is widely used in the study of food appearance evaluation. In addition, the hyperspectral image has outstanding performance in predicting the nutrient content of samples. However, there are few reports on the research of classification models based on the fusion data of these two sources of images. We collected RGB and hyperspectral images at four different storage times of VS. The ENVI software was adopted to extract the hyperspectral information, and the RGB images were reconstructed based on the downsampling technology. Then, the one-dimensional hyperspectral data was transformed into a two-dimensional space, which allows it to be overlaid and concatenated with the RGB image data in the channel direction, thereby generating fused data. Compared with four commonly used machine learning models, the deep learning model ResNet18 has higher classification accuracy and computational efficiency. Based on the above results, a novel classification model named ResNet-R &H, which is based on the residual networks (ResNet) structure and incorporates the fusion data of RGB and hyperspectral images, was proposed. The ResNet-R &H can achieve a testing accuracy of 97.6%, which demonstrates a significant enhancement of 4.0% and 7.2% compared to the distinct utilization of hyperspectral data and RGB data, respectively. Overall, this research is significant in providing a unique, efficient, and more accurate classification approach in evaluating the freshness of vegetable soybean. The method proposed in this study can provide a theoretical reference for classifying the freshness of fruits and vegetables to improve classification accuracy and reduce human error and variability.

Research on the Moisture Stability of Asphalt Mixtures with Three Solid Waste Fillers.

Widespread interest has been drawn to the use of solid waste fillers as a partial replacement for natural fillers in high-performance asphalt mixtures in recent years. However, variations in the material properties of solid waste fillers remain a problem for the recycling method. To address this issue, the limestone powder in asphalt mixtures was replaced with three solid waste fillers, including steel slag powder, tailings powder and calcium carbide slag powder in this study. The chemical composition of the fillers was first characterized to assess the homogeneity of the material. Then, a dense-graded asphalt mixture (AC) and a stone matrix asphalt (SMA) mixture were designed, produced and characterized for wet stability. The results show that the asphalt mixtures with solid waste fillers were superior to limestone powder (LP) asphalt mixtures in terms of resistance to water damage, and the steel slag powder showed the best improvement in moisture stability of the asphalt mixtures. The optimum substitution of solid waste filler for limestone filler was 25%. With the addition of anti-stripping agents, the moisture stability of the asphalt mixture with limestone filler was also greatly enhanced. On the contrary, a marginal enhancement was observed in the moisture stability of asphalt mixtures using solid waste fillers. Solid waste fillers can be used in asphalt mixtures and have a similar function as that of anti-stripping agents. In summary, the use of solid waste fillers to replace mineral fillers in asphalt mixtures is a reliable, value-added recycling option.

Effects of Steel Slag Powder Content and Curing Condition on the Performance of Alkali-Activated Materials Based UHPC Matrix.

The accumulation of steel slag and other industrial solid wastes has caused serious environmental pollution and resource waste, and the resource utilization of steel slag is imminent. In this paper, alkali-activated ultra-high-performance concrete (AAM-UHPC) was prepared by replacing ground granulated blast furnace slag (GGBFS) powder with different proportions of steel slag powder, and its workability, mechanical properties, curing condition, microstructure, and pore structure were investigated. The results illustrate that the incorporation of steel slag powder can significantly delay the setting time and improve the flowability of AAM-UHPC, making it possible for engineering applications. The mechanical properties of AAM-UHPC showed a tendency to increase and then decrease with the increase in steel slag dosing and reached their best performance at a 30% dosage of steel slag. The maximum compressive strength and flexural strength are 157.1 MPa and 16.32 Mpa, respectively. High-temperature steam or hot water curing at an early age was beneficial to the strength development of AAM-UHPC, but continuous high-temperature, hot, and humid curing would lead to strength inversion. When the dosage of steel slag is 30%, the average pore diameter of the matrix is only 8.43 nm, and the appropriate steel slag dosage can reduce the heat of hydration and refine the pore size distribution, making the matrix denser.

Graph Neural Networks for Charged Particle Tracking on FPGAs.

The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase of the LHC (HL-LHC). Graph neural networks (GNNs) are a type of geometric deep learning algorithm that has successfully been applied to this task by embedding tracker data as a graph-nodes represent hits, while edges represent possible track segments-and classifying the edges as true or fake track segments. However, their study in hardware- or software-based trigger applications has been limited due to their large computational cost. In this paper, we introduce an automated translation workflow, integrated into a broader tool called hls4ml, for converting GNNs into firmware for field-programmable gate arrays (FPGAs). We use this translation tool to implement GNNs for charged particle tracking, trained using the TrackML challenge dataset, on FPGAs with designs targeting different graph sizes, task complexites, and latency/throughput requirements. This work could enable the inclusion of charged particle tracking GNNs at the trigger level for HL-LHC experiments.

The Effect of Ultraviolet Radiation on Bitumen Aging Depth.

The aging effect of ultraviolet (UV) radiation on bitumen has gained increasing attention from researchers, resulting in the emergence of a new method to simulate the UV aging that occurs during the service life of bitumen. However, the UV aging degree is closely related to bitumen thickness and the effect of UV radiation on aging depth is not clear. The relationship between ultraviolet (UV) radiation and bitumen UV aging depth was investigated in this paper. Three groups of samples were UV aged using different aging procedures to investigate the bitumen aging mechanism of UV radiation. The results from the first group showed that UV aging depth increased along with aging time. After aging for five hours, the complex modulus of the second and third layers increased. The second group’s results indicated that the aging effect of ozone was small and that the increase in aging depth was uncorrelated with ozone. The results from the third group showed that the transmittance of bitumen increased after UV aging and that the real reason why aging depth increased was permeation.

Preparation and Thermal Properties of Molecular-Bridged Expanded Graphite/Polyethylene Glycol Composite Phase Change Materials for Building Energy Conservation.

Using phase change materials (PCMs) in building envelopes became a reliable method to improve indoor comfort and reduce buildings' energy consumption. This research developed molecular-bridged expanded graphite (EG)/polyethylene glycol (PEG) composite PCMs (m-EPs) to conserve energy in buildings. The m-EPs were prepared through a vacuum absorption technique, and a titanate coupling agent was used to build a molecular bridge between EG and PEG. SEM, mercury intrusion porosimetry (MIP), the leakage test, microcalorimetry, X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy (FT-IR) were conducted to characterize the morphology, pore structure, absorbability, and modifying effects of the m-EPs. The phase change temperature, latent heat, thermal stability, and thermal conductivity of the m-EPs were determined by a differential scanning calorimeter (DSC), TGA, and a thermal constants analyzer. Results showed that the maximum mass ratio of PEG to EG without leakage was 1:7, and a stable connection was established in the m-EPs after modification. Compared with the unmodified EPs, the supercooling degree of the m-EPs reduced by about 3 °C, but the latent heats and initial decomposition temperatures increased by approximately 10% and 20 °C, respectively, which indicated an improvement in the thermal energy storage efficiency. The thermal conductivities of the m-EPs were 10 times higher than those of the pristine PEGs, which ensured a rapid responding to building temperature fluctuations.

Axonal and Schwann cell BACE1 is equally required for remyelination of peripheral nerves.

Inhibition of ß-site APP cleaving enzyme 1 (BACE1) is being pursued as a therapeutic target for treating patients with Alzheimer's disease because BACE1 is the sole ß-secretase for generating ß-amyloid peptide. Knowledge regarding the other cellular functions of BACE1 is therefore critical for the safe use of BACE1 inhibitors in human patients. BACE1 deficiency in mice causes hypomyelination during development and impairs remyelination in injured sciatic nerves. Since BACE1 is expected to be ubiquitously expressed, we asked whether axonal or Schwann cell BACE1 is required for optimal remyelination. By swapping sciatic nerve segments from BACE1-null mice with the corresponding wild-type nerve segments or vice versa, we tested how a deficiency of BACE1 in Schwann cells or axons affects remyelination. Our results show that BACE1 in axons and Schwann cells is similarly important for remyelination of regenerated axons. Nerve injury induces BACE1 transcription and protein levels are elevated in Schwann cells. Expression of type I neuregulin 1 (Nrg1), rather than type III Nrg1, was induced by Schwann cells, and the abolished Nrg1 cleavage in BACE1-null Schwann cells contributed to decreased remyelination of regenerated axons. Hence, this study is the first to demonstrate the equal importance of axonal and Schwann cell BACE1 for remyelination of injured nerves.

ß-site amyloid precursor protein cleaving enzyme 1(BACE1) regulates Notch signaling by controlling the cleavage of Jagged 1 (Jag1) and Jagged 2 (Jag2) proteins.

BACE1 is a type I transmembrane aspartyl protease that cleaves amyloid precursor protein at the ß-secretase site to initiate the release of ß-amyloid peptide. As a secretase, BACE1 also cleaves additional membrane-bound molecules by exerting various cellular functions. In this study, we showed that BACE1 can effectively shed the membrane-anchored signaling molecule Jagged 1 (Jag1).Wealso mapped the cleavage sites of Jag1 by ADAM10 and ADAM17. Although Jag1 shares a high degree of homology with Jag2 in the ectodomain region, BACE1 fails to cleave Jag2 effectively, indicating a selective cleavage of Jag1. Abolished cleavage of Jag1 in BACE1-null mice leads to enhanced astrogenesis and, concomitantly, reduced neurogenesis. This characterization provides biochemical evidence that the Jag1-Notch pathway is under the control of BACE1 activity

Regeneration of spent TiO2 nanoparticles for Pb (II), Cu (II), and Zn (II) removal.

Spent sorbents in water treatment processes have potential risks to the environment if released without proper treatment. The aim of this work was to investigate the potential regeneration of commercially prepared nano-TiO2 (anatase) for the removal of Pb (II), Cu (II), and Zn (II) by pH 2 and ethylenediaminetetraacetic acid (EDTA) solutions. The percent of metal adsorption/desorption decreased with the increasing number of regeneration cycles, and the extent of decrease varied for each metal. Competitive effects were observed for the adsorption/desorption of different metals when the nano-TiO2 was regenerated by EDTA solutions. Nano-TiO2 was able to treat simulated metal polluted water with greater than 94 % adsorption and greater than 92 % desorption after four cycles of regeneration using pH 2 solution. These results demonstrated that nano-TiO2 can be regenerated and reused using pH 2 solution compared to an EDTA solution for aquatic metal removal, which makes nanosorbents promising and economically and environmentally more attractive in the application of water purification.

Evaluation of desorption of Pb (II), Cu (II) and Zn (II) from titanium dioxide nanoparticles.

The adsorption-desorption of toxic compounds onto engineered nanoparticles is an important process that governs their potential as sorbents for treatment applications, their toxicity and their environmental risks. This study was aimed to investigate the desorption of Pb (II), Cu (II) and Zn (II) from commercially prepared nano-TiO(2) (anatase) using batch techniques, with the evaluation of isothermal, kinetic and thermodynamic properties. Results showed that desorption was pH dependent and that more than 98% of all metals desorbed at pH 2. Short term kinetic studies were fit with a pseudo second order model and showed that a significant amount of desorption occurred in the first fifteen minutes. Surface complexation modeling determined a trend of adsorption affinity to be Pb > Zn > Cu and with adjustable surface complexation constant (K(int)) provided good fit to the experimental data. The thermodynamic studies found that desorption was exothermic and non-spontaneous in most cases. The XPS study showed that no change in oxidation state occurred due to desorption and suggested that Pb desorption was due to inner-sphere surface complexation. The results suggest three important points that will improve the capabilities of researchers to understand Pb (II), Cu (II) and Zn (II) adsorption-desorption to nano-TiO(2): (1) the desorption of metals was enhanced at lower pH values suggesting its potential to be regenerated for treatment applications; (2) the possible mechanism for adsorption-desorption varies for different metals; and (3) nano-TiO(2) could interact with metals in the environment if released due to their high sorption capacity and reversible adsorption at lower pH values which could affect the fate and behavior of metals in the environment and enhance nanoparticle toxicity.

Adsorption and desorption of bivalent metals to hematite nanoparticles.

The use of commercially prepared hematite nanoparticles (37.0 nm) was studied as an adsorbent in the removal of Cd(II), Cu(II), Pb(II), and Zn(II) from aqueous solutions. Single-metal adsorption was studied as a function of metal and adsorbent concentrations, whereas binary metal competition was found to be dependent on the molar ratio between the competing metals. Competitive effects indicated that Pb had strong homogenous affinity to the nanohematite surface, and decreased adsorption of Cd, Cu, and Zn occurred when Pb was present in a binary system. Metal adsorption strength to nanohematite at pH 6.0 increased with metal electronegativity: Pb > Cu > Zn ∼ Cd. Equilibrium modeling revealed that the Langmuir-Freundlich composite isotherm adequately described the adsorption and competitive effects of metals to nanohematite, whereas desorption was best described by the Langmuir isotherm. The desorption of metals from nanohematite was found to be pH dependent, with pH 4.0 > pH 6.0 > pH 8.0, and results showed that greater than 65% desorption was achieved at pH 4.0 within three 24-h cycles for all metals.