In general, FeCrAl alloys are faced with the separation of the high-chromium solid solution into α and α′ phases. For the Fe-25Cr-5Al-RE alloy, it is imperative to investigate the structure and ...morphology and their effect on the alloy’s mechanical properties. In this paper, XRD is used to reveal the presence of α and α′ phases. Based on XRD data, Rietveld refinement combined with quantitative texture analysis is carried out to determine the lattice constants and the harmonic coefficients. Then, SEM and TEM techniques are employed to provide an insight into the α′ phase and its morphology. The percentage total elongation at fracture is anti-correlated with the lattice of the α′ phase and the generalized harmonic coefficients C41.
Different combinations of normalizing and tempering were carried out to optimize the microstructure and enhance the high-temperature mechanical properties of HRB400FR fire-resistant steel bars. The ...results showed that with the increasing of the tempering temperature from 400 to 600°C, the steel bar’s hardness decreases linearly, mainly due to the formation of quasi-polygon ferrite and granular bainite. Besides, the reduced width and the dissolution of the lath bainite also undermine the performance of the tempered steel bars. The highest Vickers hardness of 380 HV is achieved when the steel is normalized at 950°C and then tempered at 400°C, mainly due to precipitation strengthening and bainite strengthening. The hardness of the test steel tempered at 600°C gives the lowest value, only 230 HV since the least amount of bainite is obtained. When the tempering temperature reaches 650°C, the hardness rises to 260 HV due to the formation of the lath bainite. The emergence of needle bainite generally reduces the matrix grain size, and the appearance of lath martensite refines the precipitated carbides.
In this paper, novel organic sulfonic acid group-functionalized silica spheres (SiO2–SO3H) were chosen as a template for fabricating core–shell SiO2–SO3H@Ag composite spheres by the seed-mediated ...growth method. The SiO2–SO3H spheres could be obtained easily by oxidation of the thiol group-terminated silica spheres (SiO2–SH) with H2O2. Due to the presence of sulfonic acid groups, the Ag(NH3)2+ ions were captured on the surface of the silica spheres, followed by in-site reduction to silver nanoseeds for further growth of the silver shell. By this strategy, the complete silver shell could be obtained, and the surface morphologies and structures of the silver shell could be controlled by adjusting the number of sulfonic acid groups on the silica spheres. A large number of sulfonic acid groups on the SiO2–SO3H spheres favored the formation of the macroporous silver shell, which was unique and exhibited good catalytic performance and a high surface-enhanced Raman scattering (SERS) enhancement ability.
•A data mining based method is proposed to predict building energy consumption.•The outlier detection method can identify abnormal building operating patterns.•He recursive feature elimination ...technique is effective in selecting optimal inputs.•The prediction performances of eight popular predictive algorithms are studied.•Ensemble models built on the eight base models have the best performances.
This paper presents a data mining (DM) based approach to developing ensemble models for predicting next-day energy consumption and peak power demand, with the aim of improving the prediction accuracy. This approach mainly consists of three steps. Firstly, outlier detection, which merges feature extraction, clustering analysis, and the generalized extreme studentized deviate (GESD), is performed to remove the abnormal daily energy consumption profiles. Secondly, the recursive feature elimination (RFE), an embedded variable selection method, is applied to select the optimal inputs to the base prediction models developed separately using eight popular predictive algorithms. The parameters of each model are then obtained through leave-group-out cross validation (LGOCV). Finally, the ensemble model is developed and the weights of the eight predictive models are optimized using genetic algorithm (GA).
The approach is adopted to analyze the large energy consumption data of the tallest building in Hong Kong. The prediction accuracies of the ensemble models measured by mean absolute percentage error (MAPE) are 2.32% and 2.85% for the next-day energy consumption and peak power demand respectively, which are evidently higher than those of individual base models. The results also show that the outlier detection method is effective in identifying the abnormal daily energy consumption profiles. The RFE process can significantly reduce the computation load while enhancing the model performance. The ensemble models are valuable for developing strategies of fault detection and diagnosis, operation optimization and interactions between buildings and smart grid.
The wide integration of gas-fired units and implementation of power-to-gas technologies bring increasing interdependence among the natural gas and electricity infrastructures. This paper studies the ...equilibrium of the coupled gas and electricity markets, which is driven by the strategic offering behaviors: each producer endeavours to maximize its own profit by taking the market clearing process into consideration. The market equilibrium can be obtained from an equilibrium problem with equilibrium constraints. A special diagonalization algorithm is devised, in which the unilateral equilibrium of the gas or electricity market is found in the inner loop given the rivals' strategies; the interactions of the two markets are tackled in the outer loop. Case studies on two test systems validate the proposed methodology.
For identification of forested landslides, most studies focus on knowledge-based and pixel-based analysis (PBA) of LiDar data, while few studies have examined (semi-) automated methods and ...object-based image analysis (OBIA). Moreover, most of them are focused on soil-covered areas with gentle hillslopes. In bedrock-covered mountains with steep and rugged terrain, it is so difficult to identify landslides that there is currently no research on whether combining semi-automated methods and OBIA with only LiDar derivatives could be more effective. In this study, a semi-automatic object-based landslide identification approach was developed and implemented in a forested area, the Three Gorges of China. Comparisons of OBIA and PBA, two different machine learning algorithms and their respective sensitivity to feature selection (FS), were first investigated. Based on the classification result, the landslide inventory was finally obtained according to (1) inclusion of holes encircled by the landslide body; (2) removal of isolated segments, and (3) delineation of closed envelope curves for landslide objects by manual digitizing operation. The proposed method achieved the following: (1) the filter features of surface roughness were first applied for calculating object features, and proved useful; (2) FS improved classification accuracy and reduced features; (3) the random forest algorithm achieved higher accuracy and was less sensitive to FS than a support vector machine; (4) compared to PBA, OBIA was more sensitive to FS, remarkably reduced computing time, and depicted more contiguous terrain segments; (5) based on the classification result with an overall accuracy of 89.11% ± 0.03%, the obtained inventory map was consistent with the referenced landslide inventory map, with a position mismatch value of 9%. The outlined approach would be helpful for forested landslide identification in steep and rugged terrain.
This paper addresses two vital issues which are barely discussed in the literature on robust unit commitment (RUC): 1) how much the potential operational loss could be if the realization of ...uncertainty is beyond the prescribed uncertainty set; 2) how large the prescribed uncertainty set should be when it is used for RUC decision making. In this regard, a robust risk-constrained unit commitment (RRUC) formulation is proposed to cope with large-scale volatile and uncertain wind generation. Differing from existing RUC formulations, the wind generation uncertainty set in RRUC is adjustable via choosing diverse levels of operational risk. By optimizing the uncertainty set, RRUC can allocate operational flexibility of power systems over spatial and temporal domains optimally, reducing operational cost in a risk-constrained manner. Moreover, since impact of wind generation realization out of the prescribed uncertainty set on operational risk is taken into account, RRUC outperforms RUC in the case of rare events. The traditional column and constraint generation (C&CG) and two algorithms based on C&CG are adopted to solve the RRUC. As the proposed algorithms are quite general, they can also apply to other RUC models to improve their computational efficiency. Simulations on a modified IEEE 118-bus system demonstrate the effectiveness and efficiency of the proposed methodology.
TIM-3: An update on immunotherapy Zhao, Lizhen; Cheng, Shaoyun; Fan, Lin ...
International immunopharmacology,
October 2021, 2021-Oct, 2021-10-00, 20211001, Letnik:
99
Journal Article
Recenzirano
•It focuses on the structure of TIM-3 and the interaction with the four ligands to play different functions.•TIM-3 has different susceptibility genes in autoimmune diseases.•TIM-3 is highly expressed ...on chronic virus-infected T cells.•TIM-3 interacts with immune cells and exhibits proliferation or inhibition of tumor cells.
T cell immunoglobulin and mucin domain 3 (TIM-3) was originally found to be expressed on the surface of Th1 cells, acting as a negative regulator and binding to the ligand galectin-9 to mediate Th1 cell the apoptosis. Recent studies have shown that TIM-3 is also expressed on other immune cells, such as macrophages, dendritic cells, and monocytes. In addition, TIM-3 ligands also include Psdter, High Mobility Group Box 1 (HMGB1) and Carcinoembryonic antigen associated cell adhesion molecules (Ceacam-1), which have different effects upon biding to different ligands on immune cells. Studies have shown that TIM-3 plays an important role in autoimmune diseases, chronic viral infections and tumors. A large amount of experimental data supports TIM-3 as an immune checkpoint, and targeting TIM-3 is a promising treatment method in current immunotherapy, especially the new combination of other immune checkpoint blockers. In this review, we summarize the role of TIM-3 in different diseases and its possible signaling pathway mechanisms, providing new insights for better breakthrough immunotherapy.
Semiconductor photocatalysts are of great significance in solar energy conversion and environmental remediation. To overcome serious drawbacks of these materials with respect to narrow light-response ...range and low quantum efficiency, a variety of strategies have been developed in the past decades to enhance the light harvesting and excitation as well as the charge transfer against recombination. In particular, fluorination of semiconductor photocatalysts can be employed to modify their surface and bulk properties, and consequently, to enhance their photocatalytic performance. This review presents a comprehensive description of the F-mediated synthesis and unique properties of fluorinated semiconductor photocatalysts, in particular titanium dioxide (TiO2). The available strategies for the synthesis of fluorinated photocatalysts include post-synthesis fluorination and in-situ fluorination. Depending on the synthesis route and conditions, it is possible to control the chemical nature of incorporated fluorine (such as adsorbed fluoride and lattice-doped fluorine) and the fluoride-mediated crystal modification and organization, which often results in exceptional surface and bulk physicochemical properties, giving rise to unique photocatalytic properties. Significantly, the surface fluorination induces unusual adsorption behavior and interfacial charge transfer dynamics, directly affecting photocatalytic redox properties of the surface-fluorinated photocatalysts. The lattice fluorine-doping, sole or cooperative with other complementary co-dopants, introduces special localized electronic structures and surface defect states, accounting for the exceptional visible-light photoactivity of the fluorine-doped photocatalysts. Finally, recent advances in the synthesis and properties of fluorinated photocatalysts are summarized along with perspectives on further developments in this area of research.
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► A brief overview of fluorinated photocatalysts is presented. ► Post-synthesis and in-situ fluorination methods are reviewed. ► Surface fluorination effects are discussed. ► Doping of photocatalysts with fluorine is reviewed. ► Future perspectives in the area of fluorinated photocatalysts are outlined.
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