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Sulfonation of waste corn cob biomass (CCB) prepared a multifunctional mesoporous acidic catalyst for ethyl oleate production. For determining the best catalyst synthesis conditions, CCBs were calcineted at different temperatures (150–300 °C), sulfonated with 1, 3–propanesulfonate at different temperatures (60–140 °C), and sulfonation times (0.5–4.5 h). The structural, porosity, morphology and surface properties of the samples were thoroughly examined by FT–IR spectroscopy, TG analysis, SEM, N2adsorption–desorption isotherms, XPS spectroscopy, and CHNS analysis. As a result of varying reaction conditions in catalyst optimization, including 8 g of 1, 3–propanesulfonate, 3 g of activated carbon CCB250, at 120 °C, and 4 h of reaction time, 94.32% of the –SO3H was obtained, and the catalyst surface was highly academically active. According to sulfur analysis of the CCB250–SO3H catalyst, the 120 °C sulfonated activated CCB250contained –SO3H groups, with a higher density of active sites of 9.426 mol/g. By sulfonation of 1, 3–propanesulfonate, the mesoporous CCB250–SO3H catalyst was obtained with an average pore diameter of 3.1–4.8 nm, a pore volume of 1.39–1.02 cm3/g. The mesoporous CCB250–SO3H catalyst was utilized in the catalytic activity test to esterification with oleic acid. It exhibited a conversion rate of 94.32% in the production of ethyl oleate. The optimal conditions for this reaction included a catalyst loading of 150 mg, a molar ratio of ethanol to oleic acid (12:1 mol/mol), a reaction temperature of 80 °C, and a reaction time of 2 h. Due to the stable attachment of the –SO3H functional group, the mesoporous CCB250–SO3H catalyst was successfully reused eight times for esterification cycles.

Background: Sacrococcygeal sinus ulcers are caused by pressure sores, trauma, or surgery. Several surgical techniques have been developed for its treatment; however, studies are ongoing to develop the ideal method. The present study aims to introduce an innovative application of gluteus maximus muscle flaps (GMMFs) packing combined with local random pattern skin flaps (RPSFs) in repairing sacrococcygeal sinus tracts (SSTs). Methods: This was a prospective analysis study conducted on the patients (n= 26) with SSTs underwent an innovative repairing surgery in Qilu Hospital of Shandong University, China between December 2015 and December 2020. The repairing surgery was GMMFs combined with RPSFs. The demographic information and the clinical parameters including operative time, postoperative healing time, and recurrence rate were used to evaluate the efficacy of the operation. Results: Except one case of partial necrosis at the edge of the flap due to severe fibrosis, which was cured after dressing change, all the other cases showed effective healing after the operation. Conclusion: The combined application of GMMFs and RPSFs for the treatment of sacrococcygeal sinus tracts gains the advantages of short operative time, quick postoperative recovery, and low postoperative recurrence rate.

Industrial customers consume a large part of the total electricity demand. In the operation of industrial energy systems, accurate prediction of electric loads is a prerequisite to help industrial users adjust their electric load dispatch and improve energy efficiency. Therefore, this paper proposes a day-ahead industrial load forecasting model employing load change rate features and combining the firefly algorithm to optimize the extreme learning machine and adaptive boosting algorithm (LCR-AdaBoost-FA-ELM). The industrial load is mainly influenced by the power users’ production schedules, making its forecasting laws mainly analyzed by the changing laws of the load data itself. Given this, the rate of load change feature is introduced to form a candidate feature set with variables such as the date and lag load. In order to decrease the number of parameters required to train the model, the Spearman correlation coefficient is used to select high-quality input features and eliminate variables that are weakly associated with electricity consumption. The basic algorithm of the prediction model is the ELM, based on which the FA is used to optimize its weights and biases. Finally, the ensemble learning concept is introduced to learn to combine multiple FA-ELM weak predictors by AdaBoost to correct the prediction errors. In this paper, the proposed model is validated using a typical industrial industry, a furniture factory, as a research case. The results show that the proposed LCR features can capture the nonlinear characteristics of the load sequence, resulting in more precise prediction outcomes. Additionally, based on the FA boosting ELM prediction accuracy, AdaBoost can lower the day-ahead load prediction error once more. Using the mean absolute percentage error (MAPE) as an example, AdaBoost-FA-ELM declines by 76.85% compared to ELM and decreases by 23.90% before and after the LCR features are applied. The proposed forecasting model framework in this paper provides a new research strategy for the field of energy forecasting.

• The Rod-shaped hydroxyapatite (rHAP) was successfully prepared with its length ranging from 300 nm to 400 nm using a hydrothermal method. • The rHAP promotes macrophage phenotype 2 (M2) polarization and osteogenesis in vitro and in vivo. • The 200 µg/mL rHAP induce M2 polarization via the PI3K-Akt and Wnt/β-catenin pathways. • The rHAP interacts with macrophages through adhesion to cell membranes and endocytosis of lysosomes. Bone defects are common clinical problems in the world, and there are many biomaterials used for treating them. However, there is still a paucity of bioactive materials capable of modulating the immune microenvironment. Therefore, it is necessary to identify new therapeutic strategies to regulate the immune microenvironment of the bone defect to further promote osteogenesis. Hydroxyapatite (HAP) is an important mineral for the framework of the human body. Recently, HAP has become a key research object for bone tissue engineering applications due to its unique tailored properties and similarity to bone tissue. Here, we prepared rod-shaped HAP (rHAP) with different concentrations (0, 100, 200, and 300 µg/mL). The slowly released Ca2+ of 200 µg/mL rHAP can induce macrophage phenotype 2 (M2) polarization to decrease inflammatory cytokine secretion via the PI3K-Akt and Wnt/β-catenin pathways. In addition, rHAP can induce osteogenesis through the osteogenic differentiation of rat bone marrow mesenchymal stem cells. In conclusion, the 200 µg/mL rHAP shows the potential for osteoimmunomodulation in a bone defect in vitro and in vivo , which is beneficial to the treatment of bone defects. [Display omitted] [ABSTRACT FROM AUTHOR]

To meet the requirements of simulating the electric field during a lightning strike, there is an urgent need for a voltage pulse generator that generates voltage pulses that are equivalent to the electric field during the lightning strike. A new pulse generator structure based on a push–pull dc–dc converter and a flyback converter is proposed. The pulses produced by the proposed generator have a variable voltage rise rate, and a modular design is used for the generator. Each module works independently and is powered by an exclusive lithium battery, which avoids the problems of the need for a high-voltage dc source, current sharing, and a complex control strategy in existing generators. The electrical behavior of the proposed generator during the switching transient is analyzed considering the effects of both the semiconductor switching device (insulated-gate bipolar transistor) and transformer. The method of selecting the specifications of each component and the method of designing the core component are presented in this study. The accuracy of the transient model and the feasibility of the proposed generator are verified in experiments, and a 60-stage prototype that produces pulses with amplitudes in excess of 1 MV, widths of 1–3 ms, and a variable voltage rise rate is developed.

A series of Fe-substituted ZSM-5 zeolite samples with an almost constant Si/(Fe + Al) molar ratio of 50 but varied levels of Fe substitution were synthesized via an in situ seed-induced hydrothermal method in a fluoride medium. Additionally, a hierarchical Fe-substituted sample with high diffusion capability was also produced by a subsequent alkaline treatment. The textural and acidic properties of these samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV–Raman, Fourier transform infrared (FT-IR), UV–vis, H2-temperature programmed reduction (TPR), Ar adsorption–desorption, NH3-temperature-programmed desorption (TPD), X-ray fluorescence (XRF), 27Al, and 29Si magic-angle spinning (MAS) NMR analysis. These analyses revealed that Fe3+species were effectively integrated into the MFI framework of the Fe-substituted samples. The as-synthesized samples displayed orthogonally intergrown crystal plates of increased aspect ratios with increased Fe-substitutions. More significantly, the resulted Fe-substituted samples displayed a noticeably reduced acid strength compared to the pure ZSM-5. Evaluated by the benzene alkylation reaction with dilute ethylene, the 50% partially Fe-substituted ZSM-5 sample showed a combined high ethyl selectivity and long catalytic lifetime among all catalysts studied, which is attributed to its suitably balanced acid strength.

Fatty acid methyl esters (FAME) were synthesized through the transesterification of soybean oil with methanol using an ionic liquid as a catalyst. The ionic liquid 3-(N, N-dimethyldocecyl ammonium) propane sulfonic acid p-toluene sulfonate ([DDPA] [Tos]) was synthesized, characterized and used for the transesterification of soybean oil for biodiesel synthesis. Factors affecting the reaction, including the soybean-oil-to-methanol ratio (1:2 v/v), the ionic liquid catalyst concentration of 8.0 %w/v, the reaction time of 4 h, the agitation speed of 300 rpm, and the constant refluxing reaction temperature were optimized. A 75 % yield of biodiesel was obtained under the optimized conditions. The biodiesel was purified using an ion exchange resin and then the analyzed by GC–MS. The properties of the biodiesel such as kinematic viscosity at 40 ºC, the density at 25 ºC, the cloud point and pour points were also determined. The biodiesel met the quality standard defined under ASTM D6751-02. In this research study, a novel method for biodiesel synthesis under mild conditions using methanol and an ionic liquid was developed.

Based on the constant amplitude CF test of oil well tube material TP140small specimen, the procedures of predicting the variable amplitude corrosion fatigue (VACF) life of given reliability of TP140 were developed. Through the multi-sample sinusoidal loading constant amplitude CF life texts, the reliability distribution of CF life was analyzed. The CF life prediction of the specified reliability was obtained under 4 different stress levels, and the corresponding P-S-N curve expressions were obtained. Using VACF loading block spectrum and P-S-N curve expressions, the VACF life was calculated without considering the loading sequence effect. Furthermore, 5 VACF life tests were carried out using the same loading block spectrum. The VACF life with reliability was predicted by the principle of reliability and statistics. VACF life was calculated and compared with the predicted life. Test results and analysis show that the predicted results agree well with the experimental results, and CF life of TP140 casing steel follows a lognormal distribution at the given equivalent stress level, which has been substantiated.

Energy demand is increasing dramatically because of the fast industrial development, rising population, and economic growth in the world. To fulfill this energy demand, a large amount of fuel is widely used from different fossil resources. Burning of fossil fuels has caused serious detrimental environmental consequences. The application of methyl esters has shown a positive impact in resolving these issues. The objective of this study, methyl esters were produced by transesterification of fried soybean oil with dimethyl carbonate using hydrobromic acid as catalyst. Optimized several factors that affected the reaction efficiency including the fried soybean oil to dimethyl carbonate ratio (1:4 v/v), 3.5 % v/v catalyst concentration, a reaction temperature of 80 ºC for 50 min with 300 rpm agitation speed. The methyl esters yield was 94 % obtained using these optimized conditions. Methyl esters were purified by ion exchange resin amberlite-732, and purified methyl esters were analyzed by GC–MS. We then characterized important physical properties of methyl esters such as kinematic viscosity, density, flash point, cloud point, and pour point. These properties were found to have met with the quality standard defined under ASTM D6751-02 and compared with diesel fuel. In this research, a novel method was developed for the production of methyl esters under mild conditions using dimethyl carbonate and hydrobromic acid.

An interpretable convolutional neural network model is proposed for the classification of very low frequency and low frequency lightning electric field waveforms. This model adopts multi‐scale convolutional kernels and shortcut connections to enhance the ability of lightning waveform classification. Based on the data recorded from five provinces in China, the proposed model achieves an accuracy of 98.56% for a four‐type classification task including return strokes, the intra‐cloud lightning, preliminary breakdown, and narrow bipolar events. The proposed model is validated with another open‐source data set from Argentina with an accuracy of 98.45%, which shows good robustness. To ensure the classification, the features learned by the model are visualized. The class activation mapping (CAM) method is adopted to visualize the class‐specific contribution of different waveform parts by using the feature maps of the final convolutional layer. It is highlighted by the CAM method that the proposed model focuses on waveform parts that align with those areas of interests identified by human experts. The high‐contribution waveform parts are furtherly analyzed, which indicate that the proposed model possesses the capability to associate waveform features with the corresponding lightning discharge processes. Electromagnetic waveforms in very low frequency and low frequency bands are usually used to detect and locate lightning activities. Traditional waveform classification methods have difficulties in distinguishing multiple types of lightning waveforms. Although machine learning models have great potential in multi‐type waveform classification tasks, these models rely on the features proposed by human experts and cannot capture the features of different scales in lightning waveforms. To this end, this paper proposes an improved convolution neural network model, which incorporates modifications to the model structure to better suit the lightning waveform classification task. The data set for model training comes from five provinces in China and contains different meteorological conditions. The proposed model achieves a classification accuracy of 98.56% on this data set and 98.45% on an open‐source data set from Argentina. Meanwhile, the classification process is interpretable by visualizing the convolution outputs. The analysis of the visualization results shows that the high performance of the proposed model is reliable for its ability to focus on waveform parts that align with areas of interests identified by human experts. A closer inspection of these waveform parts suggest that the proposed model possesses the capability to associate waveform features with the corresponding lightning discharge processes. The proposed model achieves an accuracy of 98.56% for a four‐type lightning waveform classification task and shows good robustnessThe model is interpretable by visualizing the contribution of different waveform parts to the classification resultsThe proposed model aligns with human‐expert classifications and suggests potential to link waveform features with lightning processes The proposed model achieves an accuracy of 98.56% for a four‐type lightning waveform classification task and shows good robustness The model is interpretable by visualizing the contribution of different waveform parts to the classification results The proposed model aligns with human‐expert classifications and suggests potential to link waveform features with lightning processes

According to the low accuracy of velocity filed in current software, we develop a new system to analyze and visualize the 3D groundwater flow field. We employ the most advanced algorithm to deal with the data form groundwater simulation. The system could compute the flux across arbitrary face and the velocity of arbitrary point in the research domain. The system is debugged in Microsoft Visual Studio. The interactive interface is developed in .Net and the visualization tool is OpenGL. The application shows that the system is robust.

The development of mineral resources is accompanied by serious threats to the geological environment in China. In order to balance mining order, mine environmental protection and ecological restoration, this article examines a case study of Ningwu mining area and proposes an accurate method for mine dynamic monitoring in mining area based on remote sensing (RS), which is a series of technical processes with RS images selection, mine development situation and dynamic monitoring which includes areas change and types transfer. Findings indicate that the area of bauxite pit, bauxite and coal dump increased, the area of coal industrial square decreased, coal dump and industrial square mainly transferred into bauxite pit. The organization and storage model were discussed for results integrated management by spatial database engine (ArcSDE).The application of results retrieval was developed by GIS components. This method can be considered as an effective approach for a wide range of mine development monitoring in mining areas in China.

In order to figure out seepage field in aquifer under the coal seam, the geology and hydrogeology conditions systematically of study area were analyzed, hydrogeological conceptual model was generalized, mathematical model was built, seepage field of the Taiyuan limestone aquifer was simulated with software Feflow. Simulation results show that hydrogeological parameters of Taiyuan limestone aquifer change greatly in different partitions. The model also indicates the heterogeneity of karst fissure of Taiyuan limestone aquifer. The drainage quantity is from the Ordovician limestone aquifer besides supplying from runoff of upstream and capture excretion of downstream. The research is an attempt to simulate the seepage field in aquifer under coal seam, to some extent, it also provides a technical basis for safe coal mining and as a reference for simulation constructions of three-dimensional groundwater flow models in similar coal mines.

On the basis of the geology and hydrogeology, a three-dimensional numerical groundwater model in the study area was developed to evaluate the deep groundwater resources and avoid the groundwater level declining. According to the long-term water supply plan, water resources characteristics and exploitation status quo of Huantai county, three kinds of groundwater utilization scheme had been designed. The best sustainable groundwater exploitation scheme is determined by using the numerical model to simulate three kinds of mining schemes and analyze the corresponding groundwater flow field. The result shows that maintaining the status quo mining conditions will make the groundwater level decline further. Only reducing industrial exploitation and keeping domestic water mining can improve the conditions, but still difficult to solve the problem. The aim of utilization of deep groundwater can achieve only by reducing disordered water exploitation for production and living.

Froth flotation is expected to be a potential method to remove microplastics (MPs) from the natural environment, while hydrophilization induced by aqueous environments may affect the process of flotation removal. This study applied a novel flotation technology to remove polyvinyl chloride (PVC) and acrylonitrile butadiene styrene (ABS) MPs from water. The effects of MPs properties, flotation conditions, and aqueous species on flotation removal were investigated, and the first-order model was used to fit the flotation kinetics. Flotation removed over 98.5% of MPs under sufficient terpineol dosage and airflow supply, and it was unaffected by pH, temperature, MPs size, and MPs concentration. Instead, common aqueous species, including Na+, K+, Ca2+, Mg2+, Al3+, and humic acid, inhibited the flotation of ABS MPs, and only Al3+affected the removal of PVC MPs. Therefore, 97% of PVC MPs floated in froth flotation, while only 58.7% of ABS MPs were removed from seawater. The adsorption isotherm confirmed the monolayer adsorption of Na+, K+, Ca2+, Mg2+, and humic acid on MPs surfaces, while the adsorption of Al3+was heterogeneous. ABS MPs showed a greater affinity for these substances due to functional groups, lower surface potential, and higher surface area. These substances might accumulate in a water film through electrostatic or non-covalent interactions on MPs surfaces, resulting in the hydrophilization. Froth flotation has significant application potential due to its affordable costs and handy operation. This work may be of great significance in removing MPs from the aquatic environment.

The ubiquitous appearance of microplastics (MPs) in aquatic environments brings about a growing concern for plastic pollution. Although the MPs occurrence, transportation, fate, and impacts have been summarized thoroughly, it calls for a better understanding of the control and removal strategies for aquatic MPs. Herein, we emphasized the positive effect of source control for MPs removal. Besides, we systematically reviewed the published removal technologies, including filtration, membrane technology, density separation, coagulation, agglomeration, adsorption removal, magnetic separation, oil film separation, froth flotation, and advanced oxidation processes. We also put forward potential challenges and possible improvement protocols for removal strategies and treatment processes of MPs. Exploring MPs characteristics may facilitate the removal technologies of MPs. A specific removal technology contributes to the high removal efficiency under experimental conditions, but in aquatic environments, a desirable extraction requires large-scale experiments. At last, the removal strategies of MPs can borrow separation methods with high-performance from other fields.

Under the slow varying ambient electric field, positive leader propagation exhibits steps characterized by intense reilluminations and abrupt elongations. These steps are currently not well understood. In this work, we investigate these steps in laboratory atmospheric discharges, using a high‐speed video camera and a synchronized electrical parameter measurement system. The discharge, emitting weak light and preceding the intense reillumination, is discovered. This finding suggests that the leader channel actually restarts and extends forward before the intense reillumination, which deepens our understanding of the dynamic process of the positive leader step. The discharge before the intense reillumination contributes to the corona inception from the electrode, leading to the intense reillumination of the leader channel and the emergence of an intense corona streamer burst from the leader tip. Lightning is a positive or negative super long spark discharge between the cloud and ground or cloud and cloud. The propagation of positively and negatively charged plasma channels, termed, respectively, positive and negative leaders, is the physical nature of lightning development. Under the slow varying ambient electric field, positive leader propagation is not continuous and exhibits steps with waiting time of tens of microseconds punctuated by sudden elongations and intense reilluminations. These steps are currently not fully understood. Leader discharges can also be simulated in a laboratory. Important insights about natural lightning phenomena have come emerging from explorations of laboratory‐scale atmospheric discharges. Here, we investigate the positive leader steps under the slow varying ambient electric field in long laboratory spark discharges, using a high‐speed video camera and a synchronized electrical parameter measurement system. A discharge that precedes the intense leader channel reillumination is discovered, which provides a new understanding of the dynamic process of positive leader steps and provides new insights into positive stepped lightning leaders under the slow varying ambient electric field. This letter presents a discharge that precedes the intense reillumination in the positive leader stepThe positive leader restarts and extends forward before the intense reillumination in the positive leader stepThe newfound discharge contributes to the intense leader channel reillumination