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The development of the open-pit mining industry has set higher performance standards for mining electric shovels. Addressing issues such as low efficiency, high energy consumption, and high failure rates in working mining electric shovel devices, this paper comprehensively considers bulk mechanics, structural mechanics, and dynamics to conduct a multidisciplinary, collaborative design optimization for electric shovels by introducing the BLISCO method, which is based on an approximated model, into the structural-optimization design process of working electric shovel devices, aiming to enhance the overall performance of electric shovels. Firstly, a dynamic model of an electric shovel is established to analyze the hoist force and crowd force during the excavation process, and an accurate load input for the dynamic analysis is provided through the bulk material mechanics model. Additionally, to ensure that the stiffness of the boom meets the requirements, the maximum stress at the most critical position of the optimized boom is considered. Subsequently, the design variables are screened through experimental design, and an approximate model is established. Focusing on the hoist force, crowd force, maximum stress at the critical position of the boom, and the angle between the dipper arm and the wire rope, a mathematical model is constructed and optimized using a two-level integrated system co-optimization framework based on an approximate model (BLISCO-AM), followed by a simulation. Finally, a test bench for the electric shovel working device is constructed to compare pre- and post-optimization performance. Experimental results show that through the optimized design, the hoist force and crowd force required in a single excavation process are reduced by 6% and 8.48%, respectively, and the maximum angle between the wire rope and the dipper arm is increased by 4%, significantly improving excavation efficiency while ensuring the safety and reliability of the equipment. [ABSTRACT FROM AUTHOR]

In order to solve the problem of unstable fluid supply pressure and serious impact caused by the complicated and changeable working condition of a fully mechanized mining face in coal mines and the sluggish response of the fluid supply system to the fluid demand for the hydraulic support, a control method based on online updating generalized regression neural network (GRNN) was proposed. Firstly, the simulated hydraulic support test platform and co-simulation model were built. Secondly, The optimal flow dataset of steady-pressure fluid supply under different working conditions is calculated by simulation. Furthermore, the GRNN prediction model was established by using dataset and online updating learning technology to predict the optimal fluid supply flow according to environmental parameters. Finally, the optimal flow control method of online updating GRNN was established, and numerical research and experimental verification were also carried out in different working conditions. The results indicated that the proposed control method could track the working conditions of the working face in real time and adjusted the fluid supply flow of the emulsion pump station adaptively, which effectively alleviated the pressure fluctuation and pressure shock, and the system pressure was more stable, meeting the demand of steady-pressure fluid supply on the working face. [ABSTRACT FROM AUTHOR]

Dicranopteris dichotoma is a pioneer herbaceous plant species that is tolerant to barrenness and drought. Mapping its biomass spatial distribution is valuable for understanding its important role in reducing soil erosion and restoring ecosystems. This research selected Luodihe watershed in Changting County, Fujian Province, China, where soil erosion has been a severe problem for a long time, as a case study to explore the method to estimate biomass, including total and aboveground biomass, through the integration of field measurements, handheld laser scanning (HLS), and airborne laser scanning (ALS) data. A stepwise regression model and an allometric equation form model were used to develop biomass estimation models based on Lidar-derived variables at typical areas and at a regional scale. The results indicate that at typical areas, both total and aboveground biomass were best estimated using an allometric equation form model when HLS-derived height and density variables were extracted from a window size of 6 m × 6 m, with the coefficients of determination (R2) of 0.64 and 0.58 and relative root mean square error (rRMSE) of 28.2% and 35.8%, respectively. When connecting HLS-estimated biomass with ALS-derived variables at a regional scale, total and aboveground biomass were effectively predicted with rRMSE values of 17.68% and 17.91%, respectively. The HLS data played an important role in linking field measurements and ALS data. This research provides a valuable method to map Dicranopteris biomass distribution using ALS data when other remotely sensed data cannot effectively estimate the understory vegetation biomass. The estimated biomass spatial pattern will be helpful to understand the role of Dicranopteris in reducing soil erosion and improving the degraded ecosystem. [ABSTRACT FROM AUTHOR]

Whey protein was pretreated with multi-frequency ultrasound in mono-, dual-, and tri-frequency modes. The effect of multi-frequency ultrasound pretreatment on the hardness, chemical forces, and microstructure of acid-induced whey protein gel was investigated. Whey protein gels pretreated with dual- and tri-frequency ultrasound showed higher hardness (p < 0.05) and a denser network than mono-frequency ultrasound and control. Moreover, they had higher hydrophobic interaction and lower disulfide bonds than the control (p < 0.05). The effect of gel properties on digestion was evaluated using an in vitro static model. Whey protein gels pretreated with dual- and tri-frequency ultrasound had a higher proportion of large fragments in the oral boluses than in the control. Large fragments (>3.35 mm) in those samples were resistant to gastric digestion. Moreover, the tri-frequency ultrasound pretreatment of whey protein gel released the least free amino group during gastric digestion. In contrast, whey protein gel with the mono-frequency ultrasound pretreatment released the highest amount of free amino acid group during intestinal digestion. Findings from this study suggests that gel hardness and network density could modulate the digestion behaviors of protein gels. [ABSTRACT FROM AUTHOR]

With the intensification of global resource shortages and the environmental crisis, hydrogen energy has garnered significant attention as a renewable and clean energy source. Water splitting is considered the most promising method of hydrogen production due to its non-polluting nature and high hydrogen concentration. However, the slow kinetics of the two key reactions, the Hydrogen Evolution Reaction (HER) and Oxygen Evolution Reaction (OER), have greatly limited the development of related technologies. Meanwhile, the scarcity and high cost of precious metal catalysts represented by Pt and Ir/RuO2 limit their large-scale commercial application. Thus, it is essential to develop catalysts based on Earth's transition metals that have abundant reserves. Vanadium (V) is an early transition metal with a distinct electronic structure from late transition metals such as Fe, Co, and Ni, which has been emphasized and studied by researchers. Numerous vanadium-based electrocatalysts have been developed for the HER and OER. In this review, the mechanisms of the HER and OER are described. Then, the compositions, properties, and modification strategies of various vanadium-based electrocatalysts are summarized, which include vanadium-based oxides, hydroxides, dichalcogenides, phosphides, nitrides, carbides, and vanadate. Finally, potential challenges and future perspectives are presented based on the current status of V-based electrocatalysts for water splitting. [ABSTRACT FROM AUTHOR]

Genes from Perilla frutescens and Ocimum basilicum were introduced into N. tabacum L. var. HHY via distant hybridization, and the new-type tobacco varieties "Zisu" and "Luole" were developed, with noticeable differences in chemical composition. Smoking is the leading cause of chronic obstructive pulmonary disease (COPD), and its pathogenesis is complex. In the present study, 48 male Sprague-Dawley (SD) rats were randomly divided into four groups, namely, the control, "HHY", "Zisu" and "Luole", and then exposed to fresh air/cigarette smoke (CS) for 30 days and 60 days. The COPD model was constructed, and their health hazards were compared and evaluated. CS from different tobacco varieties influenced rats in varying degrees at the tissue, cell and molecular levels. The rats in the "HHY" group showed obvious symptoms, such as cough and dyspnea, which were less severe in the "Zisu" and "Luole" groups. Pathological and morphological analyses, including scores, MLI, MAN, WAt/Pbm and WAm/Pbm, showed that "Zisu" and "Luole" caused less damage to the airways and lung parenchyma than "HHY". Significant increases in the numbers of total leukocytes and neutrophils in the BALF were found in "HHY" compared to those in "Zisu" and "Luole". Moreover, they caused less oxidative stress and apoptosis in lung tissues, as reflected by indicators such as ROS, MDA, T-AOC, GSH, the apoptotic index and the ratio of Bcl-2 to Bax. "Zisu" and "Luole" even altered the ratios of MMP-9/TIMP-1 and IFN-γ/IL-4 in lung tissues to a lesser degree. These differences between CS-exposed rats may be closely related to the altered expression of Nrf2, p38 MAPK and p-p38 MAPK. Changes in chemical composition via introducing genes from some medicinal plants may be an attractive strategy for tobacco harm reduction. [ABSTRACT FROM AUTHOR]

Aqueous zinc–iodine batteries are considered to be one of the most promising devices for future electrical energy storage due to their low cost, high safety, high theoretical specific capacity, and multivalent properties. However, the shuttle effect currently faced by zinc–iodine batteries causes the loss of cathode active material and corrosion of the zinc anodes, limiting the large-scale application of zinc–iodine batteries. In this paper, the electrochemical processes of iodine conversion and the zinc anode, as well as the induced mechanism of the shuttle effect, are introduced from the basic configuration of the aqueous zinc–iodine battery. Then, the inhibition strategy of the shuttle effect is summarized from four aspects: the design of cathode materials, electrolyte regulation, the modification of the separator, and anode protection. Finally, the current status of aqueous zinc–iodine batteries is analyzed and recommendations and perspectives are presented. This review is expected to deepen the understanding of aqueous zinc–iodide batteries and is expected to guide the design of high-performance aqueous zinc–iodide batteries. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbon (PAH) derivatives are widely present in the environment, and some are more hazardous than their parent PAHs. However, compared to PAHs, PAH derivatives are less studied due to challenges in monitoring as a result of their low concentrations in environmental matrixes. Here, we developed a new passive sampler based on diffusive gradients in thin films (DGT) to monitor PAH derivatives and PAHs in waters. In the laboratory study, the XAD18-DGT device exhibited high adsorption rates and was demonstrated to be suitable for deployment in environmental waters on the timescale of months. The diffusion coefficients, D, were 5.30 × 10−6 cm2 s−1, 4.51 × 10−6 cm2 s−1, 4.03 × 10−6 cm2 s−1 and 3.34 × 10−6 cm2 s−1 for 9-fluorenone (9-FL), 1-chloroanthraquinone (1-CLAQ), 9-nitroanthracene (9-NA) and phenanthrene (Phe), respectively, at 25 °C. The DGT device's performance was independent of pH, ionic strength, deployment time and storage time, indicating it can be widely used in natural waters. In the field study, the target pollutant concentrations measured by the DGT are in good accordance with those determined via grab sampling. Then, the DGT devices were utilized to quantify PAH derivatives and PAHs in several rivers in Hefei, China. This work demonstrates the feasibility of using the DGT technique to detect trace PAH derivatives and PAHs in waters. [ABSTRACT FROM AUTHOR]

To enhance the performance and reduce the amount of ester-based lubricants used in weak gel drilling fluids, a shear dynamics simulation under extreme pressure conditions was employed to refine the formulation of the base oil and pressure additives. The simulation results were validated using fatty acid methyl, ethyl, and butyl esters. Fatty acid methyl ester demonstrated the lowest temperature increase and the highest load-bearing capacity post-shear. The four-ball friction test revealed that methyl oleate had a coefficient of friction of 0.0018, approximately a third of that for butyl oleate, confirming the simulation's accuracy. By using methyl oleate as the base oil and oleamide as the pressure-resistant component, the optimal shear stress was achieved with a 10% addition of oleamide. A lubricant composed of 90% methyl oleate and 10% oleamide was tested and showed a coefficient of friction of 0.03 when 0.5% was added to bentonite slurry, indicating a strong lubricating film. Adding 1% of this lubricant to a low gel drilling fluid system did not affect its rheological properties, and the gel structure remained stable after seven days of aging. Field tests at the Fu86-3 well in the Jiangsu Oilfield of Sinopec confirmed that adding 1% of the ester-based lubricant to the drilling fluid significantly improved drilling efficiency, reduced drag by an average of 33%, and increased the drilling rate to 22.12 m/h. This innovation effectively prevents drilling complications and successfully achieves the objectives of enhancing efficiency. [ABSTRACT FROM AUTHOR]

In order to solve the problem of frequent pressure fluctuations caused by fluid quantity variation in hydraulic support liquid supply systems and the pressure response lag caused by long-distance pipelines, an online updated radial basis function neural network (RBF neural network) control method was proposed for the long-distance liquid supply system. Based on the analysis of the measured pressure fluctuations of the mining face and the process of the stable pressure liquid supply system, the influencing factors of the stable pressure liquid supply flow demand were obtained. The flow set of the stable pressure liquid supply system was established and fitted in the SimulationX–Simulink co-simulation model and the online correction was carried out by using the characteristics of the repeated action of the hydraulic support. Finally, the online updating RBF neural network regulator was established to realize the pressure regulator control of the pumping station, and the experimental platform was set up for verification. The results show that this method can effectively reduce the pressure fluctuations caused by the change in the flow demand of the mining face, and can adjust the flow rate of the mining face, reduce the pressure impact, and improve the efficiency of the machine. [ABSTRACT FROM AUTHOR]

In view of the unstable electromagnetic performance of the air gap magnetic field caused by the torque ripple and harmonic interference of a multi-slot and multi-pole low-speed, high-torque permanent magnet synchronous motor, we propose a simplified model of double-layer permanent magnets. The model is divided into an upper and a lower subdomain, with the upper subdomain being an ideal circular ring and the lower subdomain being a segmented sector ring. Moreover, we develop an exact analytical model of the motor that predicts the magnetic field distribution based on Laplace's and Poisson's equations, which is solved using the method of separating variables. Taking a 40p168s low-speed, high-torque permanent magnet synchronous motor as an example, the accuracy of the model is verified by comparison with an ideal circular ring model, a segmented sector ring model, and the finite element method. Based on the proposed simplified model, three combined permanent magnets considering both edge-cutting and polar arc cutting structures are proposed, which are chamfered, rounded, and rectangular combinations. Under the premise of a consistent edge-cutting amount, the electromagnetic characteristics of the three combination types of permanent magnets are compared using the finite element method. The results show that the electromagnetic characteristics of the chamfered combination PM are superior to those of the other two combinations. Finally, a prototype is manufactured and tested to validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

An undescribed diterpene, stellerterpenoid A (1), and two undescribed sesquiterpenoids, stellerterpenoids B and C (2–3), together with six known compounds, prostratin (4) stelleraguaianone B (5), chamaejasnoid A (6), auranticanol L (7), wikstronone C (8), and oleodaphnone (9), were isolated from the roots of Stellera chamaejasme L. Their structures were elucidated by extensive spectroscopic data (1D, 2D NMR, IR, UV, and HR-ESI-MS). The absolute configuration of 1–3 was elucidated based on ECD calculation. Among them, stellerterpenoid A was a rare 13, 14-seco nortigliane diterpenoid and stellerterpenoid B was a guaiacane-type sesquiterpenoid with an unusual 1, 2-diketone moiety. The known stelleraguaianone B (5) exhibited moderate activity for suppressing NO production in lipopolysaccharide (LPS)-treated RAW 264.7 macrophages cells with an IC50 value of 24.76 ± 0.4 μM. None of the compounds showed anti-influenza virus or anti-tumor activity in vitro. [ABSTRACT FROM AUTHOR]

Soil physicochemical properties affect crop growth and yield. The addition of fertilizers can improve the soil quality during crop cultivation, leading to increased agricultural production. Organic fertilizers may be produced by composting straw that would otherwise be discarded as agricultural waste, with potential implications for sustainable agricultural development. However, the mechanism underlying the effects of straw compost on crop growth is unknown. In this study, a microbial agent suitable for straw decomposition in cold regions was used for a large-scale biological fermentation. Organic compost was obtained after the decomposition of straw. The straw compost was mixed with soil in different proportions and then used to cultivate Songjing 2 rice plants. The addition of straw compost significantly increased the growth and yield of the rice plants and enhanced various physiological indices. Moreover, the straw compost treatment significantly improved soil physicochemical properties (e.g., pH, enzyme activity, nutrient composition, and microbial diversity) and optimized the soil conditions for crop growth. In addition, the application of straw compost influenced the expression of genes in rice metabolic pathways as well as pathways mediating secondary metabolite synthesis and plant hormone signal transduction. The study data reflect the potential applicability of low-temperature straw fermentation technology for maximizing crop production. [ABSTRACT FROM AUTHOR]

As a crucial element in coal transportation, conveyor belts play a vital role, and monitoring their health is essential for the coal mine transportation system's safe and efficient operation. This paper introduces a new 'hardware-friendly' method for monitoring belt conveyor damage, aiming to address the issue of large parameters and computational requirements in existing deep learning-based foreign object detection methods and their challenges in deploying on edge devices with limited computing power. This method is tailored towards edge computing and aims to reduce the parameters and computational load of foreign object recognition networks deployed on edge computing devices. This method improves the YOLOv8 object detection network and redesigns a novel lightweight ShuffleNetV2 network as the backbone network, making the network more delicate in recognizing foreign object features while reducing redundant parameters. Additionally, a simple parameter-free attention mechanism called SimAM is introduced to further enhance recognition efficiency without imposing additional computational burden. Experimental results demonstrate that the improved foreign object recognition method achieves a detection accuracy of 95.6% with only 1.6 M parameters and 4.7 G model computational load (FLOPs). Compared to the baseline YOLOv8n, the detection accuracy has improved by 3.3 percentage points, while the number of parameters and model computational load have been reduced by 48.4% and 42.0%, respectively. These works are more friendly to edge computing devices that tend to "hardware friendly" algorithms. The improved algorithm can reduce latency in the data transmission process, enabling the accurate and timely detection of non-coal foreign objects on the conveyor belt. This provides assurance for the subsequent host computer system to promptly identify and address foreign objects, thereby ensuring the safety and efficiency of the belt conveyor. [ABSTRACT FROM AUTHOR]

The temperature prediction of hoist motor is one of the effective ways to ensure the safe production of mine hoist. Digital twin technology is a technology that combines the physical system of the real world with the digital model of the virtual world. Through digital twin technology, the physical system in the real world can be monitored and simulated in a virtual environment, and the state information of these systems can be monitored in real time. Recurrent neural network is a kind of neural network suitable for processing sequence data, which can automatically extract and learn the feature information in sequential data. To achieve online monitoring and over-advance perception of the temperature of the mine hoist motor, a temperature prediction and advance sensing method based on digital twins and recurrent neural network is proposed. To begin with, a high-fidelity digital twin monitoring system for mine hoists is constructed, enabling the acquisition of real-time temperature data. These temperature data are then fed into a neural network for feature extraction and precise prediction of the motor's state. Subsequently, based on the temperature prediction module in the digital twin hoist monitoring system, a user interface (UI) is developed, and a fully functional digital twin temperature monitoring system is built and experimentally validated. The experimental results demonstrate that the digital twin system effectively monitors the real-time temperature state of the motor during the operation of the mine hoist. Furthermore, the integration of digital twin and recurrent neural network enables the accurate prediction and proactive detection of temperature variations in the motor of the mine hoist. This innovative approach introduces a novel perspective for implementing predictive maintenance in the mining industry, enhancing the safety and reliability of mine hoists. Additionally, it offers valuable technical support in improving maintenance efficiency and reducing associated costs. [ABSTRACT FROM AUTHOR]

At present, the hydraulic support pushing system in coal mines usually uses an electrohydraulic directional valve as the control component. However, the existing control methods based on high-speed on–off valve, servo, and proportional control methods are not suitable for solving such problems because of the nonideal characteristics of the electrohydraulic directional valve, such as discrete input values, low switching frequency, and time delay. This paper proposes a positioning control scheme based on online predictive feedback for the control of hydraulic cylinders by electrohydraulic directional valves. In this scheme, the recursive least-squares estimation algorithm with genetic factors is used to identify the required prediction model in real time, and an improved radial basis function network based on generalized growth and shear is used to realize the online fitting of the target trajectory function. The online learning algorithm provides accurate prediction information for the switching control method, and finally, the hydraulic cylinder can be positioned near the target position using the optimal control method. By using the above methods, a well-designed model can be accurately identified, fundamentally solving the problem of control difficulties caused by the nonideal characteristics of the electrohydraulic directional valve. Finally, the effectiveness of the control scheme is verified through simulation analysis and physical experiment research, which proves that the control strategy can realize accurate and fast positioning control for the hydraulic support pushing system of a fully mechanized mining face. [ABSTRACT FROM AUTHOR]

Separating light hydrocarbons (C2H6, C3H8, and C4H10) from CH4 is challenging but important for natural gas upgrading. A microporous metal-organic framework, Zn(bdc)(ted)0.5, based on terephthalic acid (bdc) and 1,4-diazabicyclo[2.2.2]octane (ted) ligands, is synthesized and characterized through various techniques, including powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and porosity analysis. The adsorption isotherms of light hydrocarbons on the material are measured and the isosteric adsorption heats of CH4, C2H6, C3H8, and C4H10 are calculated. The prediction of C2–4/C1 adsorption selectivities is accomplished using ideal adsorbed solution theory (IAST). The results indicate that the material exhibits exceptional characteristics, including a Brunauer-Emmett-Teller (BET) surface area of 1904 m2/g and a pore volume of 0.73 cm3/g. Notably, the material demonstrates remarkable C2H6 adsorption capacities (4.9 mmol/g), while CH4 uptake remains minimal at 0.4 mmol/g at 298 K and 100 kPa. These findings surpass those of most reported MOFs, highlighting the material's outstanding performance. The isosteric adsorption heats of C2H6, C3H8, and C4H10 on the Zn(bdc)(ted)0.5 are higher than CH4, suggesting a stronger interaction between C2H6, C3H8, and C4H10 molecules and Zn(bdc)(ted)0.5. The molecular simulation reveals that Zn(bdc)(ted)0.5 prefers to adsorb hydrocarbon molecules with richer C-H bonds and larger polarizability, which results in a stronger dispersion force generated by an adsorbent-adsorbate induced polarization effect. Therefore, the selectivity of C4H10/CH4 is up to 180 at 100 kPa, C3H8/CH4 selectivity is 67, and the selectivity of C2H6/CH4 is 13, showing a great potential for separating C2–4 over methane. [ABSTRACT FROM AUTHOR]

The mining rope shovel (MRS) is one of the core pieces of equipment for open-pit mining, and is currently moving towards intelligent and unmanned transformation, replacing traditional manual operations with intelligent mining. Aiming at the demand for online planning of an intelligent shovel excavation trajectory, an MRS excavating trajectory planning method based on material surface perception is proposed here. First, point cloud data of the material stacking surface are obtained through laser radar to perceive the excavation environment and these point cloud data are horizontally calibrated and filtered to reconstruct the surface morphology of the material surface to provide a material surface model for calculation of the mining volume in the subsequent trajectory planning. Second, kinematics and dynamics analysis of the MRS excavation device are carried out using the Product of Exponentials (PoE) and Lagrange equation, providing a theoretical basis for calculating the excavation energy consumption in trajectory planning. Then, the trajectory model of the bucket tooth tip is established by the method of sixth-order polynomial interpolation. The unit mass excavation energy consumption and unit mass excavation time are taken as the objective function, and the motor performance and the geometric size of the MRS are taken as constraints. The grey wolf optimizer is used for iterative optimization to realize efficient and energy-saving excavation trajectory planning of the MRS. Finally, trajectory planning is carried out for material surfaces with four different shapes (typical, convex, concave, and convex–concave). The results of experimental validation show that the actual hoist and crowd forces are essentially consistent with the planned hoist and crowd forces in terms of the peak value and trend variations, verifying the accuracy of the calculation model and confirming that the full bucket rate and various parameters meet the constraints. Therefore, the trajectory planning method based on material surface perception are feasible for application to different excavation conditions. [ABSTRACT FROM AUTHOR]

Mining electric shovels (MES) are one of the key pieces of equipment for mining, and their comprehensive performance plays an important role in mining efficiency. Based on the screw theory, this paper proposes a comprehensive configuration method for an MES working device and selects a new mining electric shovel working device with a larger excavation range, taking the working device as an example for dimensional optimization and simulation analysis. Firstly, based on the closed-loop vector equation, the position inverse solution of the mechanism is analyzed, and the correctness of the position equation is verified by the simulation and by numerical solutions. Then, the constraints of the mechanism are analyzed, and the numerical method and the position equation are combined to solve for the workspace of the mechanism. The dimensional parameters of the mechanism are optimized by genetic algorithms. The workspace of the optimized working device is increased by 13.4789%. Finally, the mining results of the two MES, the working devices, are simulated and verified by experiment. It is shown that the experimental results are basically consistent with the simulation results. The excavation quality difference of the two working devices are 2.02% and 2.20%, which verifies the correctness of the kinematics equation of the working device and the feasibility of the new working device. [ABSTRACT FROM AUTHOR]

At present, the positioning control of the hydraulic support pushing systems in fully mechanized mining faces uses an electrohydraulic directional valve as the control component, while the current research mainly focuses on servo valves, proportional valves, high−speed on−off valves, and electromagnetic directional valves. At present, the positioning control for electrohydraulic directional valves is only a simple logical control. Therefore, in order to improve the positioning control accuracy of the hydraulic support pushing system, a predictive positioning control strategy based on iterative learning was designed. Firstly, mathematical modeling of the hydraulic support pulling process was carried out, and its state−space equation was established. Secondly, an iterative learning controller with a state observer was designed, in which the iterative learning method was used to predict the control advance in the positioning process, and the state observer was used to estimate the parameters that could not be measured by the system, so as to improve the control accuracy in the broaching process. Then, a SimulationX–Simulink joint simulation model of the position control system of a multi−cylinder pulling hydraulic support was built, and the designed iterative learning controller was compared with the BP neural network controller. Finally, a test platform for the hydraulic support pushing system was built, and the proposed control strategy was experimentally verified. The research results show that the iterative learning control strategy proposed for the electrohydraulic directional valve not only simplifies the design process of the controller but also has higher positioning control accuracy. The single−cylinder positioning control accuracy can be controlled within 10 mm, and the multi−cylinder coordinated positioning control accuracy can be controlled within 15 mm, which meets the accuracy requirements of the site. [ABSTRACT FROM AUTHOR]

Coal flow in belt conveyors is often mixed with foreign objects, such as anchor rods, angle irons, wooden bars, gangue, and large coal chunks, leading to belt tearing, blockages at transfer points, or even belt breakage. Fast and effective detection of these foreign objects is vital to ensure belt conveyors' safe and smooth operation. This paper proposes an improved YOLOv5-based method for rapid and low-parameter detection and recognition of non-coal foreign objects. Firstly, a new dataset containing foreign objects on conveyor belts is established for training and testing. Considering the high-speed operation of belt conveyors and the increased demands for inspection robot data collection frequency and real-time algorithm processing, this study employs a dark channel dehazing method to preprocess the raw data collected by the inspection robot in harsh mining environments, thus enhancing image clarity. Subsequently, improvements are made to the backbone and neck of YOLOv5 to achieve a deep lightweight object detection network that ensures detection speed and accuracy. The experimental results demonstrate that the improved model achieves a detection accuracy of 94.9% on the proposed foreign object dataset. Compared to YOLOv5s, the model parameters, inference time, and computational load are reduced by 43.1%, 54.1%, and 43.6%, respectively, while the detection accuracy is improved by 2.5%. These findings are significant for enhancing the detection speed of foreign object recognition and facilitating its application in edge computing devices, thus ensuring belt conveyors' safe and efficient operation. [ABSTRACT FROM AUTHOR]

To reduce the dependence on fossil fuels to fulfill energy needs and give rural areas better access to energy, biomethane generation technology (BG-TECH) can help in these situations. However, several crucial factors might influence BG-TECH's acceptance by households. In order to eradicate the barriers to and strengthen the driving forces of BG-TECH acceptance, it becomes inevitable to explore those crucial factors. Therefore, the core objective of this research is to analyze the factors impacting BG-TECH acceptance by households in rural Pakistan. This research will enrich the existing literature by comprehensively analyzing factors driving or impeding BG-TECH acceptance. To collect relevant data, a questionnaire was developed and distributed in four districts of Pakistan. In this respect, 150 users and 150 non-users of biomethane were selected through stratified random sampling. To analyze the factors affecting the acceptance of BG-TECH, a logistic regression model was utilized. As per our empirical results, age, ownership of cattle, aftersales service, education, household income, and loan accessibility were revealed to be the driving forces of BG-TECH. However, small farmers' age and household size impeded the acceptance of BG-TECH. However, occupation, ownership of land, and working experience did not influence the acceptance of BG-TECH. Thus, for BG-TECH approval, it is recommended that governments bring about a change in approaches as well as the development of aftersales services, improved promotions, the qualification of adults, and better loan facilities. On the one hand, our theoretical implications would prove powerful tools for the follow-up studies to dig deeper into the crucial factors of BG-TECH acceptance and transcribe those implications for other green energy technologies. On the other hand, our practical implications would empower policymakers and practitioners to guide improved policy implementation to realize the green energy revolution. [ABSTRACT FROM AUTHOR]

The production of animal protein usually leads to higher carbon emissions than that of plant protein. To reduce carbon emissions, the partial replacement of animal protein with plant protein has attracted extensive attention; however, little is known about using plant protein hydrolysates as a substitute. The potential application of 2 h-alcalase hydrolyzed potato protein hydrolysate (PPH) to displace whey protein isolate (WPI) during gel formation was demonstrated in this study. The effect of the ratios (8/5, 9/4, 10/3, 11/2, 12/1, and 13/0) of WPI to PPH on the mechanical properties, microstructure, and digestibility of composite WPI/PPH gels was investigated. Increasing the WPI ratio could improve the storage modulus (G′) and loss modulus (G″) of composite gels. The springiness of gels with the WPH/PPH ratio of 10/3 and 8/5 was 0.82 and 0.36 times higher than that of the control (WPH/PPH ratio of 13/0) (p < 0.05). In contrast, the hardness of the control samples was 1.82 and 2.38 times higher than that of gels with the WPH/PPH ratio of 10/3 and 8/5 (p < 0.05). According to the International Organization for Standardization of Dysphagia Diet (IDDSI) testing, the composite gels belonged to food level 4 in the IDDSI framework. This suggested that composite gels could be acceptable to people with swallowing difficulties. Confocal laser scanning microscopy and scanning electron microscopy images illustrated that composite gels with a higher ratio of PPH displayed thicker gel skeletons and porous networks in the matrix. The water-holding capacity and swelling ratio of gels with the WPH/PPH ratio of 8/5 decreased by 12.4% and 40.8% when compared with the control (p < 0.05). Analysis of the swelling rate with the power law model indicated that water diffusion in composite gels belonged to non-Fickian transport. The results of amino acid release suggested that PPH improved the digestion of composite gels during the intestinal stage. The free amino group content of gels with the WPH/PPH ratio of 8/5 increased by 29.5% compared with the control (p < 0.05). Our results suggested that replacing WPI with PPH at the ratio of 8/5 could be the optimal selection for composite gels. The findings indicated that PPH could be used as a substitute for whey protein to develop new products for different consumers. Composite gels could deliver nutrients such as vitamins and minerals to develop snack foods for elders and children. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is an interdisciplinary field that encompasses a wide range of computer science disciplines, including image recognition, machine learning, human−computer interaction, robotics and so on. Recently, AI, especially deep learning algorithms, has shown excellent performance in the field of image recognition, being able to automatically perform quantitative evaluation of complex medical image features to improve diagnostic accuracy and efficiency. AI has a wider and deeper application in the medical field of diagnosis, treatment and prognosis. Nasopharyngeal carcinoma (NPC) occurs frequently in southern China and Southeast Asian countries and is the most common head and neck cancer in the region. Detecting and treating NPC early is crucial for a good prognosis. This paper describes the basic concepts of AI, including traditional machine learning and deep learning algorithms, and their clinical applications of detecting and assessing NPC lesions, facilitating treatment and predicting prognosis. The main limitations of current AI technologies are briefly described, including interpretability issues, privacy and security and the need for large amounts of annotated data. Finally, we discuss the remaining challenges and the promising future of using AI to diagnose and treat NPC. [ABSTRACT FROM AUTHOR]

In this paper, the influence mechanism of tempering temperature on the microstructure and mechanical properties of 35CrMo steel used in the hammerhead of piston-type impact pile hammer is systematically analyzed. The microstructure was characterized by scanning and transmission electron microscope, X-ray diffraction, and electron backscattering diffraction, and the mechanical properties were tested by the uniaxial tensile test and Charpy V-notch impact test. The results show that after tempering at 580–680 °C, the microstructure of 35CrMo is tempered sorbite. With the increase in tempering temperature, the α phase in the matrix gradually recovers, the dislocation density decreases, the low-angle grain boundaries gradually change to the high-angle grain boundaries, and the carbides gradually change from long rod-shaped network continuous distribution to spherical uniform dispersion distribution, but all of them are M3C. Meanwhile, with the increase in tempering temperature, the strength decreases and the toughness increases, which is mainly affected by dislocation density and matrix supersaturation. Furthermore, 35CrMo enters the two-phase zone after tempering at 710–740 °C, and its microstructure is lamellar martensite, with carbide dissolved. At this point, its mechanical properties mainly depend on grain size. [ABSTRACT FROM AUTHOR]

Previous studies have generally reported the association between serum uric acid (SUA) and diabetic complications, but large-scale research exploring the above association in U.S. adults with diabetes is limited. To explore the association between SUA and chronic complications of diabetes among U.S. patients aged ≥40, we used data from the National Health and Nutrition Examination Survey 1999–2008. SUA was divided into three levels: T1 (SUA ≥ 420 μmol/L), T2 (300 ≤ SUA < 420 μmol/L), and T3 (SUA < 300 μmol/L). Binary logistic regression and restricted cubic spline analysis were applied to evaluate the association between SUA and chronic complications of diabetes. A trend test was performed as the SUA increased substantially. After full-adjusted confounding factors, patients in the T3 group had a lower risk of diabetic kidney disease, cardiovascular disease, and peripheral neuropathy compared with the T1 group, with a OR (95% CIs) of 0.33 (0.21–0.52), 0.56 (0.36–0.87), and 0.49 (0.27–0.89), respectively. The restricted cubic spline showed a significant positive relationship between SUA and cardiovascular disease and diabetic kidney disease in diabetes patients, but not peripheral neuropathy. Maintaining a SUA of less than 300 μmol/L might be protective against the risk of cardiovascular disease, diabetic kidney disease, and peripheral neuropathy other than diabetic retinopathy compared with a SUA of more than 420 μmol/L in U.S. diabetes patients aged 40 and over. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is chronic inflammatory disease. Although coffee impacts metabolism, no evidence has shown an association between coffee consumption and decreased risk for developing metabolic syndrome (MetS) among RA patients. Hence, we examined the association between coffee consumption and metabolic syndrome severity among 1094 participants with self-reported RA. Accordingly, patients with MetS z-scores of <0 and ≥0 were designated as low- and high-risk groups, respectively. In the fully adjusted model, drinking over two cups of coffee daily was associated with a decrease in the MetS z-score (p = 0.04). Subgroup analysis showed that in the low-risk group, daily intake of <2 cups of coffee was associated with low MetS z-scores (p = 0.003), scores (p = 0.03). Coffee intake was associated with low body mass index (p = 0.03 for 0–2 cups per day; p = 0.02 for >2 cups per day) and low HOMA-IR (β, −2.62; 95%CI, −5.13 to −0.11; p = 0.04). Our study suggests that coffee, but not decaffeinated coffee consumption and total caffeine intake, is associated with MetS severity in RA. [ABSTRACT FROM AUTHOR]

Cotton fiber is favored by people because of its good moisture absorption, heat preservation, soft feel, comfortable wearing and other excellent performance. In recent years, due to the destruction of the ozone layer, the intensity of ultraviolet radiation at ground level has increased. Cotton fiber will degrade under long time ultraviolet irradiation, which limits the outdoor application of cotton fiber. In this study, titanium dioxide (TiO2) particles were prepared on the surface of cotton fibers with the help of supercritical carbon dioxide (SCCO2) to improve the UV resistance of cotton fibers. The effects of SCCO2 treatment on the morphology, surface composition, thermal stability, photostability and mechanical properties of TiO2 were studied by Fourier transform infrared spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, thermogravimetric analysis, UV-VIS spectroscopy, and single fiber test. The results showed that TiO2 particles were generated on the fiber surface, which reduced the photo-degradation rate of cotton fiber. This is because TiO2 can absorb UV rays and reduce the absorption of UV rays by the cotton fiber itself. The synthesis process of SCCO2 is simple and environmentally friendly, which provides a promising technology for the synthesis of metal nitrogen dioxide on natural plant fibers. [ABSTRACT FROM AUTHOR]

Multi-modal haptic rendering is an important research direction to improve realism in haptic rendering. It can produce various mechanical stimuli that render multiple perceptions, such as hardness and roughness. This paper proposes a multi-modal haptic rendering method based on a genetic algorithm (GA), which generates force and vibration stimuli of haptic actuators according to the user's target hardness and roughness. The work utilizes a back propagation (BP) neural network to implement the perception model f that establishes the mapping (I = f (G)) from objective stimuli features G to perception intensities I. We use the perception model to design the fitness function of GA and set physically achievable constraints in fitness calculation. The perception model is transformed into the force/vibration control model by GA. Finally, we conducted realism evaluation experiments between real and virtual samples under single or multi-mode haptic rendering, where subjects scored 0-100. The average score was 70.86 for multi-modal haptic rendering compared with 57.81 for hardness rendering and 50.23 for roughness rendering, which proved that the multi-modal haptic rendering is more realistic than the single mode. Based on the work, our method can be applied to render objects in more perceptual dimensions, not only limited to hardness and roughness. It has significant implications for multi-modal haptic rendering. [ABSTRACT FROM AUTHOR]

The electric cable shovel (ECS) is one of the core pieces of equipment used in open-pit mining, and the prediction of its excavating resistance is the basis and focus of optimization design, such as excavation trajectory planning and structure optimization of the ECS. Aiming to predict the excavating resistance of an ECS, a computer simulation method for the excavating resistance based on EDEM-RecurDyn bidirectional coupling simulation is proposed herein. Taking the China-made WK series ECS as the research object, a 1/30 scale model of the ECS was set up, a prototype model test bench of the ECS was built, and the kinematics solution and force analysis of the excavating process were carried out. According to the actual excavation conditions and excavating process of the ECS, a discrete element model of the material stack and a multibody dynamics model of the ECS prototype were established. The EDEM-RecurDyn bidirectional coupling simulation of the excavating process were realized using interface technology, and the excavating resistance levels under different speed combinations and different material repose angles were simulated and analyzed. In order to verify the accuracy of the simulation results, the feasibility and reliability of the EDEM-RecurDyn bidirectional coupling simulation were verified by physical experiments. The results show that the simulated excavating resistance is basically consistent with the excavating resistance measured in the experiment in terms of peak value and change trend, which verifies the feasibility and reliability of the EDEM-RecurDyn bidirectional coupling simulation to study the excavating resistance of an ECS. [ABSTRACT FROM AUTHOR]

Focusing on the unstable electromagnetic performance of an air gap magnetic field caused by torque ripple and harmonic interference of a multi-slot and multi-pole low-speed high-torque permanent magnet synchronous motor (LHPMSM), an asymmetric stator slot is proposed to improve the comprehensive electromagnetic performance of the motor. Moreover, this paper develops an exact analytical model which predicts the magnetic field distribution based on Laplace's and Poisson's equations. The stator slot asymmetry is introduced into the model and solved by the method of separating variables. Taking a 40p168s LHPMSM as an example, numerical results of the no-load flux density field distributions are obtained by the finite element method (FEM) and employed to validate the analytical model. The influence of stator slot asymmetric structure on electromagnetic characteristics is subsequently analyzed. The results show that, compared with the semi-closed slot model, the asymmetric slot has better torque characteristics, and the electromagnetic characteristics of the motor can be significantly improved by optimizing the stator slot asymmetry. Finally, a prototype is manufactured and tested to validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

The present study was undertaken to investigate the effects of temperature, sulfuric acid concentration, agitation speed, and particle size on the high-temperature leaching kinetics of artificial willemite in low sulfuric acid solution. A mathematical model taking into account the change in acid concentration was evaluated for the leaching rate increased with increasing sulfuric acid concentration, temperature, and agitation speed and decreasing particle size. The kinetic analysis indicated that the leaching process was well interpreted by a modified grain model with product layer diffusion as the main rate-controlling step, and the shrinking core model was used to represent the reaction of each grain. The characteristic changes of the sample before and after leaching were studied using a scanning electron microscope/energy dispersive X-ray spectrometer (SEM/EDS) and X-ray diffraction (XRD) to elucidate the leaching mechanism. The apparent activation energy was found to be 22.06 kJ/mol at 373–413 K, and the reaction order with sulfuric acid concentration was 1.6472. On the basis of the grain model, the following rate equation was established: 1.07 ln (1 − 0.93 x) − [ 1.28 ln 0.17 + (1 − x) 2 3 − 0.42 (1 − x) 1 3 0.17 + (1 − x) 2 3 + 0.84 (1 − x) 1 3 + 4.5 arctan (2.76 (1 − x) 1 3 − 0.58) ] + 3.8 = 43.55 e − 22060 R T t . [ABSTRACT FROM AUTHOR]

Background: In areas where medical resources are scarce, an economical and convenient way to assess patients' condition so that treatment plans can be adjusted in a timely manner makes sense. The clinical value of systemic inflammatory indexes (SII) such as neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), albumin-to-gamma-glutamyl-transferase ratio (AGR), white-blood-cell-count-to-mean-platelet-volume ratio (WMR), high-density-lipoprotein-cholesterol-to-C-reactive-protein ratio (HCR), etc. were explored in heart failure (HF) with preserved ejection fraction (HFpEF) because of their easy availability and clinical value in the diagnosis, therapy and prognosis of cardiovascular diseases. Methods: 189 inpatients (including 48 patients with New York Heart Association (NYHA) I in the control group, and 141 patients with NYHA II-IV in the study group) from The First Affiliated Hospital of Jinan University, during the period July 2018 to March 2022, were included by retrieving electronic medical records. Logistic regression analysis, Spearman's correlation coefficient, operating characteristic curve, etc. were used to analyze the data. Results: In patients with HFpEF, LMR (OR = 0.463, 95% CI 0.348–0.617, p = 0.000), NLR and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were independent predictors for the presence of HF, and LMR (OR = 2.630, 95% CI 2.016–3.435, p = 0.000), NLR, FAG, MHR, AGR and NT-proBNP were independent predictors for increased NYHA functional classification. There were good correlations (r > 0.4) between LMR (r = −0.667, p = 0.000), NLR, WMR, HCR, NT-proBNP (r = −0.681, p = 0.000) and NYHA functional classification, and LMR (AUC = 0.803, 95% CI 0.729–0.849, p = 0.0001), NLR and NT-proBNP (AUC = 0.805, 95% CI 0.738–0.861, p = 0.0001) had good diagnostic values (AUC > 0.7) for HF in patients with HFpEF. In addition, there were certain correlations between LMR, NT-proBNP and echocardiography indicators of cardiac structural. Conclusions: SII have a potential application value in the clinical evaluation of patients with HFpEF in the follow-up, especially in areas with limited medical resources, as they are more convenient and cost effective. Among different SII, LMR is probably the most promising metric. However, large-scale clinical trials are needed in the future to confirm these findings. [ABSTRACT FROM AUTHOR]

Carbon emissions reduction is an urgent global call to action, and for China, the nation with the largest carbon dioxide emissions, the task is especially arduous. For a country like China with many provinces and cities and unbalanced regional economic development, how to balance carbon emission reduction targets with economic development goals has become a social concern. Estimating the emission reduction costs of economic entities at all levels and reasonably allocating emission reduction tasks are the basic prerequisites for sustainable urban development. Based on an input–output (IO) table analysis of the socioeconomic data of Guangdong Province from 2017, this paper uses RAS and other data reconciliation methods to decompose various statistical data based on cities and industries. A multiregional IO table of nine cities in Guangdong Province in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is obtained, and a multiregional computable general equilibrium (CGE) model of Guangdong Province is established. Using this model, this paper explores city-level differences in carbon emissions reduction costs while accounting for differences in economic development under industry-wide coverage. A scientific basis for the allocation of urban carbon quotas is provided, which is particularly important for the sustainable development of cities. First, the carbon emissions reduction cost (carbon price) of each city is related to the intensity of emissions reduction and the present carbon intensity, both of which are affected by cities' industrial and trade structures. Second, under neoclassical closure conditions, carbon emissions reduction is found to have less impact on the overall gross domestic product (GDP). At the industrial level, the high-carbon sectors are the most affected, whereas the low-carbon sectors are less affected. Notably, some industries become beneficiary sectors. Under Keynesian closure conditions, carbon emissions reduction has a greater impact on overall GDP, and all cities and industries are generally affected, especially those that are currently carbon- and trade-intensive. Third, to ensure the achievement of emissions reduction targets and minimize negative economic impacts, it is determined that the direct and opportunity costs of carbon emissions reduction must be fully considered when allocating carbon allowances, and optimal solutions should be derived from the combined perspective of fairness and efficiency. [ABSTRACT FROM AUTHOR]

After the collective forest tenure reform, the forestland transfer behavior choices did not reach the policy expectations. In order to explore the factors influencing the behavior of farmers' forestland transfer and the income effect of forestland transfer, this paper constructs a binary logistic regression model and a propensity score matching (PSM) model and uses the data obtained from a questionnaire survey of 500 farmers from 10 counties in Liaoning Province for quantitative analysis. Considering the heterogeneity, agricultural households are divided into three categories, namely, pure agricultural households, part-time agricultural households and non-agricultural households. The study found that the influencing factors of different types of agricultural households' forestland transfer behavior choices were not exactly the same and the degree of influence by the same variable was also different. Forestland transfer can effectively promote the increase of agricultural and forestry income and total household income of pure agricultural households, part-time agricultural households and non-agricultural households, among which the promotion effect on pure agricultural households is the largest. [ABSTRACT FROM AUTHOR]

The metal doping at the Pb2+ position provides improved luminescence performance for the cesium lead halide perovskites, and their fabrication methods assisted by microwave have attracted considerable attention due to the advantages of fast heating and low energy consumption. However, the postsynthetic doping strategy of the metal-doped perovskites driven by microwave heating still lacks systematic research. In this study, the assembly of CsPbBr3/CsPb2Br5 with a strong fluorescence peak at 523 nm is used as the CsPbBr3 precursor, and through the optimization of the postsynthetic conditions such as reaction temperatures, Mn2+/Pb2+ feeding ratios, and Mn2+ sources, the optimum Mn2+-doped product (CsPb(Cl/Br)3:Mn) is achieved. The exciton fluorescence peak of CsPb(Cl/Br)3:Mn is blueshifted to 437 nm, and an obvious fluorescence peak attributing to the doped Mn2+ ions at 597 nm is obtained. Both the CsPbBr3 precursor and CsPb(Cl/Br)3:Mn have high PLQY and stability because there are CsPb2Br5 microcubic crystals to well disperse and embed the CsPbBr3 nanocrystals (NCs) in the precursor, and after Mn2+-doping, this structure is maintained to form CsPb(Cl/Br)3:Mn NCs on the surface of their microcrystals. The exploration of preparation parameters in the microwave-assisted method provides insights into the enhanced color-tunable luminescence of the metal-doped perovskite materials. [ABSTRACT FROM AUTHOR]

An ultra-wideband (UWB) multiple-input, multiple-output (MIMO) antenna with a reasonably compact size of 30 × 18 × 1.6 mm3 is presented in this paper. The proposed antenna contains two radiating components, each of which is made up of three elliptically shaped patches situated 60 degrees apart, and resembles the shape of a flower. Moreover, the proposed antenna design incorporates a T-like ground branch that functions as a decoupling structure, and is composed of two modified inverted-L branches and an I-shaped stub, offering an isolation of more than 20 dB over the whole operation band (4.3–15.63 GHz). Furthermore, the proposed antenna system was fabricated and tested, and the envelope correlation coefficient (ECC), diversity gain (DG), and total active reflection coefficient (TARC), as well as the radiation characteristics and MIMO performance, were analyzed. The proposed UWB-MIMO antenna may be a suitable candidate for diverse UWB applications, based on the simulated and measured results of this study. [ABSTRACT FROM AUTHOR]

Narrowing the band gap and increasing the photodegradation efficiency of TiO2-based photocatalysts are very important for their wide application in environment-related fields such as photocatalytic degradation of toxic pollutants in wastewater. Herein, a three-dimensionally ordered macroporous Pt-loaded TiO2 photocatalyst (3DOM Pt/TiO2) has been successfully synthesized using a facile colloidal crystal-template method. The resultant composite combines several morphological/structural advantages, including uniform 3D ordered macroporous skeletons, high crystallinity, large porosity and an internal electric field formed at Pt/TiO2 interfaces. These unique features enable the 3DOM Pt/TiO2 to possess a large surface for photocatalytic reactions and fast diffusion for mass transfer of reactants as well as efficient suppression of recombination for photogenerated electron-hole pairs in TiO2. Thus, the 3DOM Pt/TiO2 exhibits significantly enhanced photocatalytic activity. Typically, 88% of RhB can be degraded over the 3DOM Pt/TiO2 photocatalyst under visible light irradiation (λ ≥ 420 nm) within 100 min, much higher than that of the commercial TiO2 nanoparticles (only 37%). The underlying mechanism for the enhanced photocatalytic activity of 3DOM Pt/TiO2 has been further analyzed based on energy band theory and ascribed to the formation of Schottky-type Pt/TiO2 junctions. The proposed method herein can provide new references for further improving the photocatalytic efficiency of other photocatalysts via rational structural/morphological engineering. [ABSTRACT FROM AUTHOR]

The current study aimed to assess the anti-diabetic effects and potential mechanisms of two Sargassum fusiform polysaccharide fractions (SFPs, named SFP-1 and SFP-2). The carbohydrate-loading experiment revealed that SFP-2 could control postprandial hyperglycemia by inhibiting the activity of digestive enzymes in rats. The analysis of diabetic symptoms and serum profiles indicated that SFPs could mitigate diabetes accompanied by dyslipidemia, and SFP-2 showed better regulatory effects on body weight, food intake and the levels of total cholesterol (TC), triglycerides (TG), low density lipoprotein-cholesterol (LDL-C) and free fatty acid (FFA) in diabetic rats. Intestinal bacterial analysis showed that SFP treatment could reshape the gut flora of diabetic rats, and SFP-2 possessed a greater regulatory effect on the growth of Lactobacillus and Blautia than SFP-1. RT-qPCR analysis revealed that SFPs could regulate the genes involved in the absorption and utilization of blood glucose, hepatic glucose production and lipid metabolism, and the effects of SFP-2 on the relative expressions of Protein kinase B (Akt), Glucose-6-phosphatase (G-6-Pase), Glucose transporter 2 (GLUT2), AMP-activated protein kinase-α (AMPKα), Peroxisome proliferator-activated receptor γ (PPARγ) and Cholesterol 7-alpha hydroxylase (CYP7A1) were greater than SFP-1. All above results indicated that SFPs could be exploited as functional foods or pharmaceutical supplements for the treatment of diabetes and its complications. [ABSTRACT FROM AUTHOR]

The effect of ultrasonic frequency mode (mono, dual and tri-frequency) and ultrasonic power (0–300 W) on structural properties (intrinsic fluorescence and sulfhydryl content) of whey protein was studied. Emulsions prepared with modified whey protein were used to form the heat-set gels, and the properties of whey protein emulsion gels (WPEG) and their digestion were investigated. The textural and rheological properties of WPEG prepared using whey protein pretreated by mono and dual-frequency ultrasound at the power between 180–240 W were enhanced, while those of WPEG prepared with whey protein pretreated by triple-frequency above the power of 180 W were declined. WPEG prepared using whey protein pretreated by dual-frequency ultrasound (DFU) with the power of 240 W had the highest hardness and storage modulus which were 3.07 and 1.41 times higher than the control. The microstructure of WPEG prepared using DFU pretreated whey protein showed homogeneous and denser networks than those of the control according to the results of confocal laser scanning microscope (CLSM). The modification in the microstructure and properties of the WPEG prepared using DFU pretreated whey protein delayed the protein disintegration during the first 30 min of gastric digestion when compared with control. Whereas the release rate of free amino group of the WPEG prepared using whey protein modified by ultrasonic pretreatment increased during the intestinal phase when compared with that of control. The results indicated that using dual-frequency ultrasound to modify whey protein is more efficient in improving the properties of WPEG, and ultrasonic power should be considered during the application of ultrasound pretreatment in producing protein gels. The fine network of WPEG prepared with whey protein pretreated by ultrasound resulted in better hardness and storage modulus. Partially unfolding of the protein induced by ultrasound pretreatment might make the whey protein more susceptible to the digestive enzyme. Our results could provide new insights for using ultrasound as the potential processing tool on designing specific protein emulsion gels as the delivery system for nutrients. [ABSTRACT FROM AUTHOR]

Cotton fibers with ultra-high purity cellulose are ideal raw materials for producing nanocellulose. However, the strong hydrogen bond and high crystallinity of cotton fibers affect the dissociation of cotton fibers to prepare nanocellulose. The structures of two kinds of cotton fibers (CM and XM) in different growth stages from 10 to 50 days post-anthesis (dpa) were studied by Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). In the process of cotton fiber growth, the deposition rate of cellulose macromolecules firstly increased and then stabilized. Then, the surface morphology, the chemical composition, and the crystal structure of the nanocellulose prepared from cotton fibers with different growth stages by deep eutectic solvent, a green solvent, were characterized by Transmission Electron Microscope (TEM), scanning electron microscopy (SEM) analysis, XRD, and Thermo Gravimetry (TG). The growth time of cotton fibers affected the properties of prepared nanocellulose, and nanocellulose obtained from cotton fibers at about 30 dpa had less energy consumption, higher yield, and milder reaction conditions. [ABSTRACT FROM AUTHOR]

Featured Application: This paper proposes a new super-resolution reconstruction method for infrared images, which makes a contribution to the research in infrared image processing and image reconstruction. Owing to the limitations of the imaging principle as well as the properties of imaging systems, infrared images often have some drawbacks, including low resolution, a lack of detail, and indistinct edges. Therefore, it is essential to improve infrared image quality. Considering the information of neighbors, a description of sparse edges, and by avoiding staircase artifacts, a new super-resolution reconstruction (SRR) method is proposed for infrared images, which is based on fractional order total variation (FTV) with quaternion total variation and the L p quasinorm. Our proposed method improves the sparsity exploitation of FTV, and efficiently preserves image structures. Furthermore, we adopt the plug-and-play alternating direction method of multipliers (ADMM) and the fast Fourier transform (FFT) theory for the proposed method to improve the efficiency and robustness of our algorithm; in addition, an accelerated step is adopted. Our experimental results show that the proposed method leads to excellent performances in terms of an objective evaluation and the subjective visual effect. [ABSTRACT FROM AUTHOR]

This article introduces a tracked-leg transformable robot, TALBOT. The mechanical and electrical design, control method, and environment perception based on LiDAR are discussed. The original tracked-leg transformable structure allows the robot to switch between the tracked and legged mode to achieve all-terrain adaptation. In the tracked mode, TALBOT is controlled by the method of differential speed between the two tracked feet. In the legged mode, TALBOT is controlled based on a bionic control strategy of the central pattern generator to realize the generation and conversion of gait. In addition, the robot is equipped with a LiDAR, through sensor preprocessing and optimization of the slam mapping algorithm, so that the robot achieves a better mapping effect. We tested the robot's motion performance and the slam mapping effect, including going straight and turning in tracked and legged modes and building a map in an indoor environment. [ABSTRACT FROM AUTHOR]

In recent years, there has been an increased focus on carbon sink plantation projects. Carbon sink plantations can slow global climate change and promote sustainable economic development, which is well suited to the needs of both ecological protection and economic growth. This article aims to accurately assess the causal effect of carbon sink plantation projects on economic development at the county level and explore its effect mechanisms. In this study, 56 counties in Guangdong Province were selected as the research areas, providing balanced panel data from 2006 to 2018. Then the propensity score matching and difference-in-differences (PSM-DID) model was used to estimate both the average and dynamic effects of carbon sink plantation projects on county-level economic development. The ordinary least squares (OLS) multiple regression results of the single-difference method and difference-in-differences (DID) model show that carbon sink plantation projects have a significant role in promoting county-level economic development. In addition, our findings suggest that the economic benefits of carbon sink plantation projects began to gradually appear from the sixth year after the projects were implemented. [ABSTRACT FROM AUTHOR]

Hydrodeoxygenation is an essential process for producing liquid transportation fuels. In this study, the effects of CoMo/γ-Al2O3 catalysts form and loading ratio on the hydrodeoxygenation upgrading of bio-oil were investigated in a batch reactor. Raw bio-oil was first oxidized with hydrogen peroxides and oxone to obtain the oxidized bio-oil with reduced levels of aldehydes and ketones, increasing the organic liquid yield during hydrodeoxygenation by suppressing the coke formation. CoMo/γ-Al2O3 was selected as the catalyst because of its low cost and commercial availability. The effect of the reduction and sulfidation of CoMo/γ-Al2O3 catalyst on the hydrodeoxygenation of the oxidized bio-oil was compared. The effect of the catalyst loading ratio on bio-oil hydrodeoxygenation using sulfided CoMo/γ-Al2O3 catalysts was also investigated. The research results showed that the sulfided CoMo/γ-Al2O3 catalyst facilitated the formation of hydrocarbons, while the reduced CoMo/γ-Al2O3 catalyst produced more phenols in the organic liquids. Moreover, a high sulfided catalyst loading ratio promoted the formation of hydrocarbons. [ABSTRACT FROM AUTHOR]

To study the effect of N-P-K fertilization on Phoebe bournei seedlings' organs dry biomass, and nutrients accumulation and allocation, and to further uncover how nutrients regulating dry biomass formation through fertilization, we utilized the "3414" experiment design. The results showed that N, P, and K fertilizer promoted dry biomass accumulation, and root, stem, and total plant N, P, and K content and accumulation in seedlings. The dry biomass accumulations of root, stem, and total plant increased first and then decreased with the increase of N, P, and K application rates, which was basically consistent with the change in dry biomass allocations and N, P, and K contents, accumulations, and allocations. Root N accumulation, root P accumulation, and total plant K accumulation were the key indicators for seedlings growth. N fertilizer had the greatest effect on total dry biomass and root N accumulation, was the most important fertilizer for the growth of Phoebe bournei seedlings, can regulate the growth of root and leaves, is beneficial to root growth at medium-low N fertilizer levels (N: 0.266–0.532 g·plant−1), and leaves growth at high N fertilizer level (N: 0.798 g·plant−1). P fertilizer rate can regulate the seedling stem growth, reaching the maximum at the medium level P application (P2O5: 0.1332 g·plant−1). K fertilizer had the greatest effect on the root P accumulation and total K accumulation, promoting K transport from leaves to root, improved root and stem growth, and inhibited leaves growth. The N, P, and K fertilizer three-factor application can better promote nutrient uptake than double-factor and single-factor fertilization, with highest dry biomass accumulation at the medium level of N, P, K fertilizer (N: 0.532 g·plant−1; P2O5: 0.1232 g·plant−1; K2O: 0.356 g·plant−1). In conclusion, N, P, and K fertilization promoted the N, P, and K absorption, increased root, stem, and leaves N, P, and K content and accumulation, and promoted the seedling dry biomass accumulation, but reversed under excessive application of N, P, and K fertilizer; and N fertilizer was beneficial to root and leaves growth, P fertilizer to stem growth, and K fertilizer to material transfer, which provided a theoretical basis for robust Phoebe bournei seedling cultivation. [ABSTRACT FROM AUTHOR]

In this study, 11 extreme precipitation indices were selected to examine the spatiotemporal variation of extreme precipitation in the Poyang Lake Basin during 1960–2017. The responses of extreme precipitation indices to El Nino/Southern Oscillation (ENSO) events of different Pacific Ocean areas were further investigated. The results show that the temperature in the Poyang Lake Basin has increased significantly since the 1990s, and the inter-decadal precipitation fluctuated. Most extreme precipitation indices showed an increasing trend with abrupt changes occurring around 1991. Spatially, most of the extreme precipitation indices decreased from northeast to southwest. The increasing trend of most indices in the center and south of the basin was relatively prominent. The linear correlations between the extreme precipitation indices and Nino 1 + 2 were the most significant. On the timescale of 2–6 years, a common oscillation period between the extreme precipitation of the basin and the four ENSO indices can be observed. After 2010, the positive correlation between the precipitation of the Poyang Lake Basin and the SST (sea surface temperature) anomalies in the equatorial Pacific increased significantly. Additionally, annual total wet–day precipitation in most areas of the Poyang Lake Basin increased with varying degrees in warm ENSO years. The results of this study will improve the understanding of the complex background and driving mechanism of flood disasters in the Poyang Lake Basin. [ABSTRACT FROM AUTHOR]