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To ensure the high reliability of the pipeline system, it is necessary to take group maintenance actions. This work proposes an optimal group maintenance approach based on a heuristically genetic algorithm to attain the system-performing goal while minimizing overall costs with assured system reliability. Multi-stage corrosion defects and multi-level risk areas are considered in this novel approach. The proposed method can sufficiently avoid pipeline failures by considering the multi-level probability of failure constraints. The methodology is illustrated by taking the 60-segment pipelines with multiple corrosion defects as an example. Numerical studies show that the proposed methodology can find an optimized maintenance strategy with a lower cost compared with the unified batch maintenance strategy. In addition, an optimal dynamic maintenance model is proposed and compared with the static model when the environment of the pipelines varies. Sensitivity analyses of the physical parameters of the phenomenon and the tuning parameters of the data-driven model show that the method has good effectiveness, compatibility, and universality. [ABSTRACT FROM AUTHOR]

In recent years, attention mechanisms have gained popularity in sequential recommender systems (SRSs) due to obtaining dynamic user preferences efficiently. However, over-parameterization of these models often increases the risk of overfitting. To address this challenge, we propose a Transformer model based on tensor train networks. Initially, we propose a tensor train layer (TTL) to accommodate the original weight matrix, thus reducing the space complexity of the mapping layer. Based on the TTL, we reconfigure the multi-head attention module and the position-wise feed-forward network. Finally, a tensor train layer replaces the output layer to complete the overall compression. According to the experimental results, the proposed model compresses SRSs parameters effectively, achieving compression rates of 76. 2 % − 85. 0 % , while maintaining or enhancing sequence recommendation performance. To our knowledge, the Tensor Train Transformer is the first model compression approach for Transformer-based SRSs, and the model is broadly applicable. • A novel model as a remedy for parameter redundancy in SRSs is proposed. • A tensor train layer has lower space complexity than the original linear layer. • The proposed model compresses SRSs parameters effectively. • Tensor Train Transformer model is broadly applicable. [ABSTRACT FROM AUTHOR]

Reasonable maintenance of pipeline systems is essential for ensuring energy transportation and achieving a trade-off between safe operation and maintenance costs. However, previous studies have barely considered the system structure, system availability, and multi-stage corrosion. To fill this gap, a multi-objective optimization framework was established. This framework can balance the cost and downtime caused by maintenance to achieve the desired trade-off between the maintenance cost and transportation continuity of a system with multi-stage corrosion defects and multi-level reliability constraints. By combining the NSGA-II algorithm with the general structure of pipeline systems, chromosome coding was designed to improve the efficiency of the evolutionary algorithm, and a series of preventive maintenance strategies were proposed, including decisions regarding repaired segments, time point for maintenance, and the type of maintenance mode. The effectiveness and accuracy of the methodology were illustrated by considering the pipeline systems with different structures and parameters as examples. A comparison of multi-objective programming with empirical decision and single-objective decisions demonstrates the rationality and universality of the methodology. The proposed methodology can help adjust the corresponding maintenance strategies for diverse requirements and provide reasonable maintenance schemes for corroded pipeline systems. • Multiple states and diversified maintenance modes are considered. • Cost and availability are optimized under multi-level PoF constraints. • NSGA-II is improved to complete multi-objective management framework. • The methodology can be applied to the general structure of pipeline systems. • The methodology is demonstrated by comparing with single-objective optimization. [ABSTRACT FROM AUTHOR]

• A property in the iterative process of FPC is discovered. • A novel initialization method of FPC is proposed. • A strategy to improve the efficiency of FPC is given. • The method makes the recommendation algorithm have a high convergence speed. In recent years, the problem of matrix completion based on rank minimization has received widespread attention in machine learning. The tightest convex relaxation of this problem is the linearly constrained nuclear norm minimization. Fixed point continuation (FPC), as a representative nuclear norm relaxation matrix completion algorithm, has been proven to perform well in theories and experiments. However, the traditional FPC algorithm initializes the matrix to be completed by zero, which does not make full use of the shrinkage characteristics of the singular value shrinkage operator on the matrix elements and the known field data information, then will lead to slow convergence and poor accuracy. Aiming at this problem, this paper analyzes the shrinkage properties of matrix elements in the iterative process of the FPC algorithm. Combined with the known rating information in the recommendation systems, a new initialization method of overestimation based on FPC is proposed, and it is applied to the rating prediction in the recommendation systems. The experimental results show that the initialization method proposed in this paper greatly improves the algorithm efficiency and prediction accuracy. [ABSTRACT FROM AUTHOR]

• A fast weighted CP decomposition model for context-aware recommendation. • Unifying explicit and implicit feedback by assigning non-uniform weights. • Reducing computation time by element-wise alternating least squares. • A simple and effective multi-threaded computing scheme for above model. As an effective method for high-dimensional information processing, tensor factorization has been widely used in context-aware recommendation. However, the multi-dimensional processing of tensor factorization usually leads to more serious data sparsity. Making full use of the data in recommendation systems, including a small amount of explicit rating data and a large amount of implicit feedback data such as clicks, plays, and purchases, can effectively alleviate this problem. Meanwhile, the processing of sparse explicit data and huge implicit feedback data makes tensor factorization face a severe challenge of computational efficiency. Therefore, this study proposes a fast tensor factorization model named FWCP that unifies explicit and implicit feedback information, which mainly studies as follows: (1) Assigning non-uniform weights to observed and unobserved values to unify explicit and implicit feedback information; (2) Memorizing intermediate data which generated by element-wise alternating least squares(ALS), and implementing parallel optimization of FWCP, which can reduce the training time of tensor factorization based on whole-data. The evaluation results on two real datasets showed that FWCP proposed in this study is superior to other context-aware recommendation algorithms. [ABSTRACT FROM AUTHOR]

• A novel GCN-based traffic prediction model is proposed. • The model enables dynamic spatial–temporal modeling of traffic data. • This model has superior long-term forecasting capability. • Hidden spatial relationships in traffic data were captured. In recent years, spatial–temporal graph modeling based on graph convolutional neural networks (GCN) has become an effective method for mining spatial–temporal dependencies in traffic forecasting research. However, existing studies lack the capability of dynamic spatial–temporal modeling of traffic speeds. Furthermore, long-term forecasting is difficult because of the diversity of traffic conditions. In addition, traditional studies capture only the features of fixed graph structures, which do not reflect real spatial dependence. To address these challenges, this study proposes a novel attention-based dynamic spatial–temporal graph convolutional network (ADSTGCN) model. ADSTGCN mainly consists of multiple dynamic spatial–temporal blocks, each of which contains three modules: 1) a dynamic adjustment module to model the dynamic spatial–temporal correlations of traffic speed, 2) a gated dilated convolution module to mine long-term dependencies, and 3) a spatial convolution module to capture hidden spatial dependencies. Experiments on three public traffic datasets demonstrated the good performance of the model. [ABSTRACT FROM AUTHOR]

SiC/Cu/Gr composites with a boundary of SiO 2 –Cu 2 O glass phase (GP) were manufactured through the hot pressing sintering process at a temperature of 950 °C. The influence of graphite (Gr) on the mechanical properties and tribological behavior under high-temperature were purposefully investigated. The microhardness of 1.37 ± 0.02 GPa is achieved by SiC/Cu/Gr composites with a graphite content of 1 vol%. The friction coefficient decreases significantly to 0.64 ± 0.02, while the average wear rate is as low as 2.2 × 10−3±0.02 mm3/(N·m) at a friction temperature of 500 °C. The results indicate that the excellent lubrication effect of graphite is utilized in the SiC/Cu/Gr composites, leading to a significant improvement in its high-temperature wear resistance performance. This behavior is attributed to the molten state of GP at high temperatures, which acts as a "binder" promoting high interface bonding strength between particles, coupled with the solid-phase lubrication provided by graphite. This research work provides a direction for developing and applying materials conducive to high-temperature contact conductivity. [ABSTRACT FROM AUTHOR]

Recently, the artificial intelligence technologies have been widely used in the field of pipeline integrity management. When crossing mountains, pipelines would inevitably encounter rockfall impact, which will potentially affect the growth of crack. However, previous research barely investigated the effect of sudden rockfall impact on health management of pipelines with fatigue cracks. To overcome this limitation, a novel crack propagation prediction algorithm based is proposed for pipelines subjected to rockfall impact. The stress intensity factor (SIF) rockfall impact ratio is introduced to describe the interaction effect of rockfall on the fatigue crack of pipelines. And the dynamic SIF values are acquired by finite element modeling (FEM) where 354 models with different parameters are analyzed. To more accurately forecast the crack growth under the rockfall impact, a method integrates multilayer perceptron (MLP) with Paris' law is proposed based on the above reliable database. Two parameters impacting the performance of the network including the number of neurons in the hidden layer and the hidden layer's activation function are evaluated and network with the most precise prediction results is selected. Quantitative analyses are performed for key factors including rockfall mass, impact velocity, impact position and crack size. The prediction results using dynamic SIF values are compared with the static ones to indicate the effect of rockfall on the crack propagation. The proposed method is valuable to support decision-making in pipeline reliability assessment and integrity management. [ABSTRACT FROM AUTHOR]

• The low-cycle fatigue (LCF) design rule of pipelines in ASME B31 code is studied. • The structural strain method generalizes ASME B31 design rule for welded pipelines. • The structural strain method can analyze LCF behavior of irregular pipe tee joint. • Different aspects of the structural strain method are discussed in detail. The welded pipe components are prone to low-cycle fatigue (LCF) at welds, especially under extreme loadings. ASME B31.8 specifies the fatigue design rules of the welded pipelines. In this work, the LCF fatigue analysis approach stipulated in the ASME B31 code is revisited to figure out its underlying mechanism, limitations, and scope, by analyzing two sets of LCF fatigue data of piping structures using different strain information. A structural strain method is proposed to generalize the pseudo-stress idea implied in the ASME code, which correlates large amounts of high- and low-cycle fatigue data of weldments into the master E-N curve. [ABSTRACT FROM AUTHOR]

• Circ_0128846 expression was increased in cartilage tissues of OA patients. • IL-1β treatment increased circ_0128846 expression in chondrocytes. • Circ_0128846 depletion assuaged IL-1β-caused chondrocyte dysfunction. • Circ_0128846 targeted miR-940. • MiR-940 combined with PTPN12. Previous evidence has suggested that circular RNA (circRNA) is abnormally expressed in osteoarthritis (OA). However, the underlying mechanism of circRNA in OA progression remains unclear. The study aims to reveal the mechanism of circ_0128846 regulating OA. Human chondrocytes (C28/I2 cells) were treated with interleukin-1β (IL-1β) to mimic an OA cell model. The expression levels of circ_0128846, miR-940 and protein tyrosine phosphatase 12 (PTPN12) were detected by qRT-PCR. Protein expression was checked by Western blotting. Cell viability, proliferation, and apoptosis were analyzed by a cell counting kit-8 assay, 5-Ethynyl-2′-deoxyuridine (EdU) assay and flow cytometry analysis, respectively. The production of tumor necrosis factor-α (TNF-α) and IL-6 was determined by an enzyme-linked immunosorbent assay (ELISA). The binding relationship between miR-940 and circ_0128846 or PTPN12 was identified by dual-luciferase reporter assay and RNA immunoprecipitation assay. Circ_0128846 and PTPN12 expression were significantly upregulated, whereas miR-940 was downregulated in the cartilage tissues of OA patients and IL-1β-treated C28/I2 cells compared with controls. IL-1β treatment inhibited C28/I2 cell proliferation and induced cell apoptosis and the production of inflammatory factors, TNF-α and IL-6; however, these effects were partly reversed after circ_0128846 depletion. In terms of mechanism, circ_0128846 acted as a miR-940 sponge, and miR-940 combined with PTPN12. Also, circ_0128846 depletion partly ameliorated IL-1β-induced C28/I2 cell disorders through miR-940. PTPN12 overexpression also partly relieved miR-940-mediated effects in IL-1β-treated C28/I2 cells. Further, circ_0128846 induced PTPN12 expression by interacting with miR-940. Circ_0128846 regulated human chondrocyte proliferation, apoptosis and inflammation through the miR-940/PTPN12 pathway in OA. [ABSTRACT FROM AUTHOR]

Atherosclerotic vascular disease remains the principal cause of death and disability among patients with type 2 diabetes. Unfortunately, the problem is not adequately resolved by therapeutic strategies with currently available drugs or approaches that solely focus on optimal glycemic control. To identify the key contributors and better understand the mechanism of diabetic atherosclerotic vascular disease, we aimed to elucidate the key genetic characteristics and pathological pathways in atherosclerotic vascular disease through nonbiased bioinformatics analysis and subsequent experimental demonstration and exploration in diabetic atherosclerotic vascular disease. Sixty-eight upregulated and 23 downregulated genes were identified from the analysis of gene expression profiles (GSE30169 and GSE6584). A comprehensive bioinformatic assay further identified that ferroptosis, a new type of programmed cell death and HMOX1 (a gene that encodes heme oxygenase), were vital factors in atherosclerotic vascular disease. We further demonstrated that diabetes significantly increased ferroptosis and HMOX1 levels compared to normal controls. Importantly, the ferroptosis inhibitor ferrostatin-1 (Fer-1) effectively attenuated diabetic atherosclerosis, suggesting the causative role of ferroptosis in diabetic atherosclerosis development. At the cellular level, Fer-1 ameliorated high glucose high lipid-induced lipid peroxidation and downregulated ROS production. More importantly, HMOX1 knockdown attenuated Fe2+ overload, reduced iron content and ROS, and alleviated lipid peroxidation, which led to a reduction in ferroptosis in diabetic human endothelial cells. We demonstrated that HMOX1 upregulation is responsible for the increased ferroptosis in diabetic atherosclerosis development, suggesting that HMOX1 may serve as a potential therapeutic or drug development target for diabetic atherosclerosis. [ABSTRACT FROM AUTHOR]

The fluidized bed reactor has been recognized for large-scale CaO/Ca(OH) 2 heat storage system. In this work, the effects of critical factors such as particle size, fluidization number, steam concentration in hydration, initial temperature, cycle number and type of carrier gas on heat release performance of CaO in the fluidized bed reactor were experimentally investigated. CaO under fluidization state exhibits excellent cyclic stability on the heat release performance. The decay in heat release temperature of CaO under fluidization state is less 10% of that under static state. With increasing the cycle number, the heat release temperature of CaO using N 2 as carrier gas decreases because of the rapid expansion of particles. After 20 cycles with N 2 as carrier gas, the average particle size of CaO increases by 46.2% and the hydration conversion of CaO reaches above 95%. The hydration conversion of CaO experienced 20 cycles using air as carrier gas is 20% lower than that using N 2 as carrier gas due to the presence of CO 2 in air. The experimental investigation of CaO/Ca(OH) 2 heat storage provides an important reference for the development of CaO/Ca(OH) 2 system using the fluidized bed reactor. [ABSTRACT FROM AUTHOR]

This work reported the one-pot synthesis of the promising, cheap and green heterogeneous nanocatalyst for biodiesel production. The halloysite nanotube (HNT) was impregnated with 40 wt % NaAlO 2 (SA) and the assistance of ultrasonic helped to achieve a better and more stable modification. The resulting 0.4SA/HNTs-UI catalyst was applied in catalyzing the transesterification of palm oil with methanol, using a GA_BP neural network to train and predict the optimal values of reaction parameters. The test results proved the prediction accuracy of the model with R 2 = 0.989. The catalyst possessed excellent performance, and the maximum biodiesel yield of 99.15% was achieved with the catalyst loaded amount of 8.82 wt %, methanol to oil molar ratio of 16.79 and transesterification temperature of 65.12 °C. Besides, the physicochemical properties of the purified transesterification product were in accordance with the ASTM D 6751 standard of biodiesel. [Display omitted] [ABSTRACT FROM AUTHOR]

• We propose a Tensor Ring decomposition framework for context-aware recommendation. • Our framework can achieve a better balance between performance and computational. • We analyze the advantages of formulating recommendation as Tensor Ring. • Experiments show the superiority of the proposed framework. As a powerful tool for processing high-dimensional data, tensor decomposition has been widely used in context-aware recommendation. Most of the current tensor decomposition-based recommendation models use CP decomposition or Tucker decomposition. In practical recommendation applications, fewer parameters limit the performance of CP decomposition, and the high-order tensor kernel makes the computational complexity of Tucker decomposition exponential. In order to improve the performance of recommendation while maintaining high computational efficiency, we propose a bias Tensor Ring decomposition framework for context-aware recommendation, which employs Tensor Ring decomposition to extract user-item-context latent factors. Comparing to current tensor decomposition-based recommendation models, our framework achieves a better balance between recommendation performance and computational complexity by Tensor Ring decomposition. This is a highly scalable recommendation framework that can easily further integrate additional information such as social trust and implicit feedback, thus used for more complex recommendation tasks. To the best of our knowledge, this work is the first to formulate context-aware recommendation as Tensor Ring decomposition process. Our in-depth analyses confirm that Tensor Ring decomposition has certain advantages over CP decomposition and Tucker decomposition. Multiple experiments on three real datasets also show that the proposed framework helps to improve the recommendation performance. [ABSTRACT FROM AUTHOR]

• In-situ conversion mechanism of captured CO 2 by CaO in H 2 was studied by DFT theory. • Detailed reaction paths of direct reduction of CaCO 3 to form CO and CaO by H 2. • The presence of H 2 reduces a 0.35 eV in the energy barrier for CaO generation. • H 2 addition leads to reduced C O orbital overlap and electron cloud disturbances. In-situ conversion of the captured CO 2 by CaO to CO is realized by using renewable H 2 in the calcination stage of calcium looping process, which effectively reduces the decomposition temperature of CaCO 3 and alleviates the sintering of CaO. However, the mechanism for this reaction is unclear which is difficult to determine just by experimental methods. In this work, the reaction mechanism for in-situ conversion of captured CO 2 by CaO to CO in presence of H 2 during calcium looping process was investigated by density function theory (DFT) analysis. The CaCO 3 direct decomposition was compared to clarify the effect of H 2 on CaO regeneration. The electron differential densities (EDD) and partial density of states (PDOS) for HCO 3 * and CO 3 * models were also compared. The results show the detailed reaction pathway for in-situ conversion of the capture CO 2 by CaO in presence of H 2 in the calcination stage of CaCO 3. H 2 is adsorbed on the CaCO 3 surface to form OH*, CO 2 *and HCO 3 *. CO 2 * further is decomposed into CO and O*. HCO 3 * is decomposed into CO 2 and OH*. Then, two OH* are attracted to each other to form H 2 O and O*. The CO 3 * hydrogenation is the rate control step in this reaction with energy barrier of 3.12 eV. The presence of H 2 causes a 0.35 eV reduction in the energy barrier for CaO generation on CaCO 3 surface. The overlap of C O orbitals and the disturbance of electron clouds around O atom all confirm that the addition of H 2 makes C and O atoms in HCO 3 * have small interaction energy. The DFT calculations reinforce the possible mechanism of in-situ conversion of the captured CO 2 by CaO in presence of H 2 during calcium looping process. [ABSTRACT FROM AUTHOR]

CaO/CaCO 3 thermochemical energy storage has been considered as a promising technology in the concentrated solar power plants. In this work, the high-alumina granule stabilized soda residue, which contains CaO, MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4 , was manufactured by wet-mixing method, and explored for thermochemical energy storage via CaO/CaCO 3 cycles. The effects of the addition amount of high-alumina granule, carbonation pressure, and number of cycles on the energy storage capacity of the stabilized soda residue were investigated. MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4 inhibit the growth and agglomeration of CaO grains and enhance the sintering resistance of soda residue; besides, the addition of high-alumina granule increases the basicity of soda residue. Moreover, the increase of carbonation pressure improves the energy storage performance of the stabilized soda residue. Hence, the stabilized soda residue with the mass ratio of high-alumina granule to CaO = 10:100 exhibits the excellent energy storage capacity and cyclic stability in the CaO/CaCO 3 cycles. The energy storage density and effective conversion of the stabilized soda residue are approximately 2394 kJ·kg−1 and 75% after 30 cycles at 1.1 MPa. The stabilized soda residue is an efficient material for CaO/CaCO 3 energy storage system. [Display omitted] • High-alumina granule stabilized soda residue is used for CaO/CaCO 3 energy storage. • The stabilized soda residue contains CaO, MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4. • MgO, Ca 12 Al 14 O 33 , and Ca 2 SiO 4 inhibit the growth and sintering of CaO grains. • The stabilized soda residue has high energy storage capacity and cyclic stability. • The stabilized soda residue retains porous and stable structure in CaO/CaCO 3 cycles. [ABSTRACT FROM AUTHOR]

CaO/CaCO 3 thermochemical heat storage has been considered as a competitive technology in concentrated solar power plants. Carbide slag and red mud are solid wastes from the chlor-alkali industry and aluminum industry, respectively. In this work, the red mud/Mn co-doped high alumina cement-stabilized carbide slag was synthesized for CaO/CaCO 3 heat storage. The effects of the addition of high alumina cement and red mud/Mn on the heat storage capacity, cyclic stability, and optical absorption of the modified carbide slag were investigated. The modified carbide slag exhibits excellent heat storage capacity and optical absorption. The Ca 3 Al 2 O 6 and CaMnO 3 inhibit the growth of CaO grains. FeMnO 3 and Ca 2 Fe 2 O 5 possess high optical absorption properties. The additions of Mn and red mud enhance the heat storage rate and basicity of the carbide slag. The effective conversion of the modified carbide slag is 0.62 after 30 cycles, which is 3.1 times as high as that of the untreated carbide slag. The modified carbide slag reaches the optical absorptance of ~58%, which is 6.5 times as high as that of the untreated one. Thus, the red mud/Mn co-doped high alumina cement-stabilized carbide slag is a potential candidate for the CaO/CaCO 3 heat storage system. • A red mud/Mn co-doped high alumina cement-stabilized carbide slag was fabricated. • The composite was proposed to use in CaO/CaCO 3 heat storage cycles. • High alumina cement improves cyclic stability due to formation of Ca 3 Al 2 O 6 in cycles. • The composite shows excellent heat storage capacity and optical absorption in cycles. • Red mud and Mn both enhance optical absorption of the composites in cycles. [ABSTRACT FROM AUTHOR]

Herein, a hollow microtubular Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 bi-functional material was prepared by the bio-template method and used for H 2 production from sorption enhanced water gas shift (SEWGS). The microtubular Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 exhibits excellent CO 2 capture and H 2 production performance in SEWGS/regeneration cycles. The stable hollow microtubular structure improves available adsorption and catalytic sites in Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 for CO 2 capture and H 2 production. Mn addition improves CO 2 affinity capacity of the microtubular material. The Fe-Mn interaction increases redox ability of Fe3+/Fe3+, 2+, which promotes CO conversion. Moreover, the formed Ca 2 Fe 2 O 5 and Ca 2 MnO 4 both increase oxygen vacancies to promote catalytic activity of the microtubular material for WGS and its CO 2 capture capacity. The CO conversions for the microtubular material with the Fe/Mn/Al/Ca molar ratio= 10/2/10/100 are 98.7% and 94.0% after 20 cycles under the mild and severe calcination conditions, respectively. The hollow microtubular bi-functional material shows good prospect for efficient H 2 production from SEWGS. [Display omitted] • Microtubular Fe/Mn-promoted CaO-Ca 12 Al 14 O 33 bi-functional material was prepared. • Microtubular material is good for H 2 production by sorption enhanced water gas shift. • Porous and hollow microtubular structure of the material keeps stable in cycles. • Synergistic effect of Fe/Mn in the material promotes CO 2 capture and H 2 production. • High and stable H 2 production from SEWGS using microtubular material is achieved. [ABSTRACT FROM AUTHOR]

• Novel SiC/Mn co-doped CaO pellets are prepared for calcium looping heat storage. • Co-doped pellets show good heat storage capacity in multiple heat storage cycles. • Optical and thermal capacities of pellets rise by 16.6 and 2.2 times, respectively. • Co-doped pellets exhibit high crushing strength and attrition resistance in cycles. To achieve high heat storage capacity, excellent mechanical, optical and thermal properties in calcium looping thermochemical heat storage, the novel SiC/Mn co-doped CaO pellets were fabricated by the extrusion-spheronization method. The heat storage performances of the novel CaO pellets were studied under harsh calcination (pure CO 2 , 950 °C) and pressurized carbonation (pure CO 2 , 13 bar, 800 °C) conditions in a dual fixed-bed reactor system. The additions of SiC and Mn enhance the cyclic stability of CaO pellets during the multiple heat storage cycles. When the mass ratio of CaO:SiC:MnO 2 is 100:5:5, the co-doped CaO pellets exhibit an excellent heat storage performance. The effective conversion and heat storage density of the co-doped CaO pellets are 41.5% higher than those of original CaO pellets, respectively. Meanwhile, the co-doped CaO pellets possess a good optical absorption capacity and a high thermal conductivity, which are 17.6 and 3.2 times as high as those of original CaO pellets, respectively. In addition, the co-doped CaO pellets show much higher crushing strength and lower weight loss during the attrition test. The stronger interaction between SiC and CaO cluster mitigates the movement of CaO, which is determined by density functional theory simulation. The adsorption of CO 2 onto the CaO surface is enhanced by the addition of Mn. Therefore, SiC/Mn co-doped CaO pellets used in the calcium looping thermochemical heat storage process appear promising. [ABSTRACT FROM AUTHOR]

• The WGS reaction mechanism in the presence of CaO was studied by DFT calculations. • The most possible pathway of WGS reaction on the CaO surface is the redox-a pathway. • As the rate-limiting step, H 2 O is dissociated spontaneously on the CaO surface. • The presence of CaO decreases energy barrier of WGS reaction along redox-a pathway. The water gas shift reaction is an important reaction for H 2 production in various industrial applications. The presence of CaO can promote the reactivity of the water gas shift reaction without any catalysts, but the enhancement mechanism of CaO in this reaction is difficult to determine just by the experiment. In this work, the water gas shift reaction along four possible pathways on the CaO surface were studied by density functional theory (DFT) analysis. The energy barriers along the pathways were analyzed to determine the most possible reaction pathway and role of the CaO surface. The DFT calculation results show that the WGS reaction is more prone to proceed along the redox-a pathway probably: H 2 O dissociates into hydroxyl and atomic H spontaneously when H 2 O and CO co-adsorb on the CaO surface, then the hydroxyl continues to dissociate and CO is oxidized by the generated atomic O. Afterwards, H 2 molecule generates from two atomic H, and then CO 2 adsorbs and H 2 desorbs simultaneously on the CaO surface. The CaO surface enables the spontaneous dissociation of H 2 O, which is the rate-limiting step of WGS reaction. The generation of CO 2 is facilitated, and the energy barrier is reduced from 2.304 to 0.757 eV on the CaO surface. Besides, the formation of CO 3 2− on the surface avoids the energy barrier for CO 2 desorption, while the CO 2 also occupies the active site and reduces the enhancement of CaO on WGS reaction. The calculation result reinforces the comprehension on the mechanism of CaO on WGS reaction. [ABSTRACT FROM AUTHOR]

• Tracking system contains targets' registration, model update and track termination. • Detected candidates are optimized with occlusion status and foreground masks. • Before target association, targets' location are predicted with Kalman filter. • Targets are associated hierarchically, based on matching situations. Multiple pedestrian tracking in video surveillance is still a pressing challenge, especially under static and dynamic occlusions and target appearance variations. Considering these complex environments in video surveillance, a multiple pedestrian tracking system with special processing procedures is proposed in this paper. In the proposed tracking system, pedestrian candidates are detected on each frame and registered as the tracked targets or associated with existing targets when their situations are suitable. The registered pedestrian targets are tracked frame by frame and terminated when the termination criteria are satisfied. In order to distinguish these target individuals, multi-sample adaptive modeling (MSAM) is proposed, which is used to adapt to a new target's unpredictable pose variation. Furthermore, static occlusions are annotated for each scene, which may occlude pedestrians in the annotated regions. These occluded targets are modified by the assigned rules and treated differently in the process of target association. Aiming to enhance the effect of target association, each target's location on the current frame is predicted with information on the previous frames using a Kalman filter. The predicted location is regarded as the center of the search region of the corresponding target. The experimental results show that the proposed tracker achieves the best performance among the five state-of-the-art trackers on three publicly available databases. [ABSTRACT FROM AUTHOR]

A Ca 3 Al 2 O 6 -stabilized carbide slag from calcium looping cycles for CO 2 capture was proposed as a H 2 S sorbent in zero emission carbon process. The H 2 S removal performance of Ca 3 Al 2 O 6 -stabilized carbide slag experienced different calcium looping cycles was investigated in a muti-fixed-bed reactor. The fabricated sorbent containing the mass ratio of CaO to Ca 3 Al 2 O 6 = 73:27 shows higher CO 2 capture capacity. The sulfidation temperature and H 2 S concentration exhibit the important effects on H 2 S removal by the fabricated sorbent from CO 2 capture cycles. The number of CO 2 capture cycles has a little effect on H 2 S removal by the fabricated sorbent. The sulfidation conversions of the fabricated sorbent after 100 CO 2 capture cycles at 60 and 120 min can reach 1.3 and 1.6 times as high as those of carbide slag, respectively. Ca 3 Al 2 O 6 restrains the rapid growth of CaO grains in the fabricated sorbent in CO 2 capture cycles. Compared with carbide slag, the fabricated sorbent possesses larger surface area and more stable structure during CO 2 capture cycles because of the support of Ca 3 Al 2 O 6 , so it exhibits higher sulfidation conversion. H 2 S removal using Ca 3 Al 2 O 6 -stabilized carbide slag from calcium looping cycles seems promising in zero emission carbon process. • C3A-modified carbide slag has high CO 2 uptake and stability in multiple CaL cycles. • The modified carbide slag after CO 2 capture cycles shows excellent H 2 S uptake. • C3A improves CO 2 and H 2 S removal capacities of carbide slag from CaL cycles. • CO 2 capture and H 2 S removal by modified carbide slag can be realized in ZEC process. [ABSTRACT FROM AUTHOR]