Optical-Fiber-Based Smart Concrete Thermal Integrity Profiling: An Example of Concrete Shaft

Concrete is currently the most widely used construction material in the world. The integrity of concrete during the pouring process could greatly affect its engineering performance. Taking advantage of heat production during the concrete curing process, we propose an optical-fiber-based thermal integrity profiling (TIP) method which can provide a comprehensive and accurate evaluation of the integrity of concrete immediately after its pouring. In this paper, we use concrete shaft as an example to conduct TIP by using the optical fiber as a temperature sensor which can obtain high spatial resolution temperature data. Our method is compared with current thermal infrared probe or embedded thermal sensor-based TIP for the concrete shaft. This innovation makes it possible to detect defects inside of the concrete shaft with thorough details, including size and location. First, we establish a 3D shaft model to simulate temperature distribution of concrete shaft. Then, we extract temperature distribution data at the location where the optical fiber would be installed. Based on the temperature distribution data, we reconstruct a 3D model of the concrete shaft. Evaluation of the concrete integrity and the existence of the potential defect are shown in the paper. Overall, the optical-fiber-based TIP method shows a better determination of defect location and size

A Computationally Efficient Hybrid Neural Network Architecture for Porous Media: Integrating CNNs and GNNs for Improved Permeability Prediction

Subsurface fluid flow, essential in various natural and engineered processes, is largely governed by a rock's permeability, which describes its ability to allow fluid passage. While convolutional neural networks (CNNs) have been employed to estimate permeability from high-resolution 3D rock images, our novel visualization technology reveals that they occasionally miss higher-level characteristics, such as nuanced connectivity and flow paths, within porous media. To address this, we propose a novel fusion model to integrate CNN with the graph neural network (GNN), which capitalizes on graph representations derived from pore network model to capture intricate relational data between pores. The permeability prediction accuracy of the fusion model is superior to the standalone CNN, whereas its total parameter number is nearly two orders of magnitude lower than the latter. This innovative approach not only heralds a new frontier in the research of digital rock property predictions, but also demonstrates remarkable improvements in prediction accuracy and efficiency, emphasizing the transformative potential of hybrid neural network architectures in subsurface fluid flow research

Optical-Fiber-Based Smart Concrete Thermal Integrity Profiling: An Example of Concrete Shaft

Concrete is currently the most widely used construction material in the world. The integrity of concrete during the pouring process could greatly affect its engineering performance. Taking advantage of heat production during the concrete curing process, we propose an optical-fiber-based thermal integrity profiling (TIP) method which can provide a comprehensive and accurate evaluation of the integrity of concrete immediately after its pouring. In this paper, we use concrete shaft as an example to conduct TIP by using the optical fiber as a temperature sensor which can obtain high spatial resolution temperature data. Our method is compared with current thermal infrared probe or embedded thermal sensor-based TIP for the concrete shaft. This innovation makes it possible to detect defects inside of the concrete shaft with thorough details, including size and location. First, we establish a 3D shaft model to simulate temperature distribution of concrete shaft. Then, we extract temperature distribution data at the location where the optical fiber would be installed. Based on the temperature distribution data, we reconstruct a 3D model of the concrete shaft. Evaluation of the concrete integrity and the existence of the potential defect are shown in the paper. Overall, the optical-fiber-based TIP method shows a better determination of defect location and size

Deep eutectic solvent-induced synthesis of Ni–Fe catalyst with excellent mass activity and stability for water oxidation

Ni–Fe bimetallic electrodes are currently recognized as a kind of benchmark transition metal-based oxygen evolution reaction (OER) electrocatalysts. Facile synthesis of Ni–Fe bimetallic electrode materials with excellent catalytic activity and satisfied stability by a simple and low-cost route is still a big challenge. Herein, well-defined Ni–Fe nanoparticles in-situ developed on a planar Fe substrate (Ni–Fe NPs/Fe) is fabricated via a facile one-step galvanic replacement reaction (GRR) carried out in an Ethaline-based deep eutectic solvent (DES). The prepared Ni–Fe NPs/Fe exhibits outstanding OER performance, which needs an overpotential of only 319 mV to drive a current density of 10 mA cm−2, with a small Tafel slope of 41.2 mV dec−1 in 1.0 mol L−1 KOH, high mass activity (up to 319.78 A g−1 at an overpotential of 300 mV) and robust durability for 200 h. Impressively, the Ni–Fe bimetallic oxygen-evolution electrode obtained from the Ethaline-based DES is catalytically more active and durable than that of its counterpart derived from the 4.2 mol L−1 NaCl aqueous solution. The reason for this is mainly related to the different morphology and surface state of the Ni–Fe catalysts obtained from these different solvent environments, particularly for the differences in phy–chemical properties, active species formed and deposition kinetics, offered by the Ethaline-based DES

ICN routing selecting scheme based on link quality for the urban vehicles’ communication

Abstract It is difficult for TCP/IP to manage the mobile nodes in the dynamic environment of VANET (Vehicular Ad hoc Network), so combining urban VANET with a new network architecture—ICN (information-centric network)—this paper proposes a FIB (forwarding information base) selecting scheme based on link quality, and we name it as RSBLQ (Routing Selecting Based on Link Quality). The metrics of link quality in RSBLQ are mainly LET (link expiration time) and link available probability. To reduce network delay, cache redundancy, and network traffic, our RSBLQ has the following designs: (1) we modify the structure of PIT (pending interest table) by adding two domains: receive time and tolerance time; (2) we introduce the algorithm of LET to help with the content routing selection in FIB; (3) RSBLQ also gets the link available probability to be another metric for our algorithm. Simulation results show that in terms of average response time, the performance improvement of RSBLQ is about 10, 15–20, and 60% compared to CCVN, V-NDN, and TCP/IP, respectively; it approximately has 8 and 13.8% improvement than CCVN and V-NDN about cache hit ratio; and the network traffic also decreases a lot

(EC+β+\beta^{+}) decay study of 128^{128}Ce

The (EC+$\beta ^{+}$) decay of $^{128}$Ce was reinvestigated in the $^{116}$Sn ($^{16}$O, 4n) reaction by using a helium-jet tape transport system. The close half-lives of $^{128}$Ce and $^{129}$Ce made it difficult to separate the decay $\gamma$ rays of both nuclei apart. Instead of the excitation-function measurements, both reactions of $^{16}$O+$^{116}$ Sn and $^{16}$O+$^{117}$Sn were carried out, and from their comparisons, the decay $\gamma$ rays of $^{128}$Ce were clearly told from those of $^{129}$ Ce. Based on X-$\gamma$ and $\gamma$-$\gamma$ coincidence measurements, a detailed (EC+$\beta ^{+}$) decay scheme of $^{128}$Ce has been proposed, which revises the previous one

Big Geodata Reveals Spatial Patterns of Built Environment Stocks Across and Within Cities in China

The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important, yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources, waste, and climate strategies. However, our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited, largely owing to the lack of sufficient high spatial resolution data. This study leveraged multi-source big geodata, machine learning, and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels. The per capita built environment stock of many cities (261 tonnes per capita on average) is close to that in western cities, despite considerable disparities across cities owing to their varying socioeconomic, geomorphology, and urban form characteristics. This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades. China’s urban expansion tends to be more “vertical” (with high-rise buildings) than “horizontal” (with expanded road networks). It trades skylines for space, and reflects a concentration–dispersion–concentration pathway for spatialized built environment stocks development within cities in China. These results shed light on future urbanization in developing cities, inform spatial planning, and support circular and low-carbon transitions in cities

Novel Peptides from Sturgeon Ovarian Protein Hydrolysates Prevent Oxidative Stress-Induced Dysfunction in Osteoblast Cells: Purification, Identification, and Characterization

This study aimed to explore antioxidant peptides derived from sturgeon (Acipenser schrenckii) ovaries that exhibit antiosteoporotic effects in oxidative-induced MC3T3-E1 cells. The F3–15 component obtained from sturgeon ovarian protein hydrolysates (SOPHs) via gel filtration and RP-HPLC significantly increased the cell survival rate (from 49.38 ± 2.88 to 76.26 ± 2.09%). Two putative antioxidant-acting peptides, FDWDRL (FL6) and FEGPPFKF (FF8), were screened from the F3–15 faction via liquid chromatography–tandem mass spectrometry (LC–MS/MS) and through prediction by computer simulations. Molecular docking results indicated that the possible antioxidant mechanisms of FL6 and FF8 involved blocking the active site of human myeloperoxidase (hMPO). The in vitro tests showed that FL6 and FF8 were equally adept at reducing intracellular ROS levels, increasing the activity of antioxidant enzymes, and protecting cells from oxidative injuries by inhibiting the mitogen-activated protein kinase (MAPK) pathway and activating the phosphoinositide-3 kinase (PI3K)/protein kinase B (AKT)/glycogen synthase kinase-3β (GSK-3β) signaling pathway. Moreover, both peptides could increase differentiation and mineralization abilities in oxidatively damaged MC3T3-E1 cells. Furthermore, FF8 exhibited high resistance to pepsin and trypsin, showcasing potential for practical applications

Arctium lappa (Burdock) : Insights from ethnopharmacology potential, chemical constituents, clinical studies, pharmacological utility and nanomedicine

Arctium lappa L. is a medicinal edible homologous plant, commonly known as burdock or bardana, which belongs to the Asteraceae family. It is widely distributed throughout Northern Asia, Europe, and North America and has been utilized for hundreds of years. The roots, fruits, seeds, and leaves of A. lappa have been extensively used in traditional Chinese Medicine (TCM). A. lappa has attracted a great deal of attention due to its possession of highly recognized bioactive metabolites with significant therapeutic potential. Numerous pharmacological effects have been demonstrated in vitro and in vivo by A. lappa and its bioactive metabolites, including antimicrobial, antiobesity, antioxidant, anticancer, anti-inflammatory, anti-diabetic, anti-allergic, antiviral, gastroprotective, hepatoprotective, and neuroprotective activities. Additionally, A. lappa has demonstrated considerable clinical efficacies and valuable applications in nanomedicine. Collectively, this review covers the properties of A. lappa and its bioactive metabolites, ethnopharmacology aspects, pharmacological effects, clinical trials, and applications in the field of nanomedicine. Hence, a significant attention should be paid to clinical trials and industrial applications of this plant with particular emphasis, on drug discovery and nanotechnology