Wide Range Of Application Prospects Research Articles

Atmospheric visibility prediction by using the DBN deep learning model and principal component analysis.

Measuring and predicting atmospheric visibility is important scientific research that has practical significance for urban air pollution control and public transport safety. We propose a deep learning model that uses principal component analysis and a deep belief network (DBN) to effectively predict atmospheric visibility in short- and long-term sequences. First, using a visibility meter, particle spectrometer, and ground meteorological station data from 2016 to 2019, the principal component analysis method was adopted to determine the influence of atmospheric meteorological and environmental parameters on atmospheric visibility, and an input dataset applicable to atmospheric visibility prediction was constructed. On the basis of deep belief network theory, network structure parameters, including data preprocessing, the number of hidden layers, the number of nodes, and activation and weight functions, are simulated and analyzed. A deep belief network model suitable for atmospheric visibility prediction is established, where a double hidden layer is adopted with the node numbers 70 and 50, and the Z-score method is used for normalization processing with the tanh activation function and Adam optimizer. The average accuracy of atmospheric visibility prediction by the deep belief network reached 0.84, and the coefficient of determination reached 0.96; these results are significantly superior to those of the back propagation (BP) neural network and convolutional neural network (CNN), thus verifying the feasibility and effectiveness of the established deep belief network for predicting atmospheric visibility. Finally, a deep belief network model based on time series is used to predict the short- and long-term trends of atmospheric visibility. The results show that the model has good visibility prediction results within 3 days and has an accuracy rate of 0.79. Covering the visibility change evaluations of different weather conditions, the model demonstrates good practicability. The established deep learning network model provides an effective and feasible technical solution for the prediction of atmospheric meteorology and environmental parameters, which enjoys a wide range of application prospects in highway transportation, navigation, sea and air, meteorology, and environmental research.

Investigation on a novel preparation process of B-COPNA resin from catalytic cracking diesel

As one of main products in fluid catalytic cracking unit, catalytic cracking diesel (light cycle oil, LCO) has inferior combustion performance, improper to be used as vehicle diesel. Condensed polynuclear aromatic resin of moderate condensation degree (B-COPNA) has a wide range of application prospects, but is seriously limited by the manufacturing cost. A novel process was proposed to convert polycyclic aromatic hydrocarbons in LCO into B-COPNA resin using PXG and PTS as crosslinking agent and catalyst, respectively. The composition of LCO was analyzed first, and the effects of operating conditions such as reaction temperature, reaction time, crosslinking agent and catalysts content on the viscosity and yield of B-COPNA resin were investigated to optimize the process. The molecular structure of B-COPNA resin is characterized by FT-IR spectra, NMR spectra, TOF-MS and elemental analysis. The combustion performance of LCO and the heat resistance of B-COPNA were evaluated and compared. The result shows that LCO is rich in aromatic hydrocarbons with 2-3 rings, making it an ideal raw material for COPNA resin. The optimized conditions of preparation experiments were 240 °C, 5 h, 1:1.8 (PXG:LCO) and 3 wt% of catalyst content with a B-COPNA resin yield of 67.2%. After the crosslinking reaction, the heat resistance temperature of B-COPNA resin product was up to 417 °C, while the cetane value of LCO increased to 43.6, an increase of 42.95%. Hence, it was confirmed that the current process can achieve a high value-added utilization of LCO by converting into B-COPNA resin, which has a superior combustion to bring extra high economic value to petrochemical industry.

Effect of shear stiffening gel rheology on its Kevlar fabric reinforced composite under low-velocity impact

Shear stiffening gel (SSG) with significant shear stiffening effect overcomes the problems of fluid volatilization and particle deposition, and exhibits a wide range of application prospects in intelligent protection. In this work, SSG with different rheological properties were manufactured by mechanical blending and crosslinking and coated on Kevlar fabric. The dynamic rheological properties of SSG and the low-velocity impact resistance of Kevlar/SSG composites were investigated, and the coupling mechanism between SSG and Kevlar fabric was analyzed. The results reveal that the storage modulus of SSG increases by 3–6 orders of magnitude when shear frequency ranges from 0.1 to 100 Hz, and the highest storage modulus reached 2.53 MPa. The impact deformation of the composite is reduced after SSG stiffening, and the infiltration of SSG inside the fabric also prevents fibers pull-out during the impact process. By synergizing the performance of SSG and Kevlar fabric, the optimal single-layer T280 composite can absorb up to 70.21% of the impact energy, reaching the energy absorption efficiency of 0.5 J/g. The process optimization and rheological design provide a theoretical foundation to further enhance the impact resistance performance.

Adsorption of Li(I) Ions through New High-Performance Electrospun PAN/Kaolin Nanofibers: A Combined Experimental and Theoretical Calculation.

Lithium (Li), as a strategic energy source in the 21st century, has a wide range of application prospects. As the demand for lithium resources grows, refining lithium resources becomes increasingly important. A novel method was proposed to directly prepare polyacrylonitrile–LiCl·2Al(OH)3·nH2O (PAN–Li/Al-LDH) composites from kaolin with simple operation and low cost, showing effective adsorption performance for the removal of Li(I) from brine in a salt lake. Moreover, several techniques have been applied for characterization, including X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray photoelectron spectroscopy, and the Brunauer–Emmett–Teller method. Batch adsorption experiments were conducted to investigate the adsorption behaviors of PAN–Li/Al-LDHs for Li(I) in salt-lake brines, indicating that the adsorption equilibrium could reach within 2 h, and the adsorption kinetics for Li(I) conforms to the pseudo-second-order model. The adsorption isotherms are consistent with those obtained by the Langmuir model, with a maximum adsorption capacity of 5.2 mg/g. The competitive experimental results indicated that PAN–Li/Al-LDHs exhibited specific selectivity for Li(I) in the mixed solutions of Mg(II), Na(I), K(I), and Ca(II) with the selectivity coefficients of 9.57, 19.38, 43.40, and 33.05, respectively. Moreover, the PAN–Li/Al-LDHs could be reused 60 times with basically unchanged adsorption capacity, showing excellent stability and regeneration ability. Therefore, PAN–Li/Al-LDHs would have promising industrial application potential for the adsorption and recovery of Li(I) from salt-lake brines.

Mixed-Resolution High-Q Sensor Based on Hybridized Spoof Localized Surface Plasmons

Spoof localized surface plasmons (LSPs) have proven significant advantages in sensing and detection. In this work, we propose a high-Q-factor and high-sensitivity hybridized spoof LSP sensor and a mixed-resolution algorithm. The sensor consists of two concentric inner and outer LSP structures with corrugated rings coupled to each other. The achieved Q-factor is up to 178, and the sensing figure of merit (FoM) is up to 30. Moreover, a mixed-resolution algorithm, combined with multiple resonant peaks, is proposed to enhance the Q-factor and sensing FoM. This algorithm doubles the Q-factor and sensing FoM effectively. This mixed-resolution sensor has a wide range of application prospects in the field of high-frequency on-chip resonators and sensors.

Investigations on the mechanism of the microstructural evolution of different coal ranks under liquid nitrogen cold soaking

ABSTRACT Liquid nitrogen (LN2) is an important means to improve the permeability of coal reservoirs. The LN2 soaking method has a wide range of application prospects. However, not enough studies exist to highlight the effect of increasing the permeability of different coal samples using LN2. Hence, this investigation was carried out to examine the effect of cold soaking in LN2 using different coal ranks such as fat coal, lean coal and anthracite coal, on their pore structures and fractal characteristics. Frenkel-Halsey-Hill (FHH) fractal theory was used to understand the fractal dimension characteristics of pores in these different coals before and after cold soaking in LN2. Furthermore, the relationship between the fractal dimensions and pore parameters was also studied. The results show that low-temperature nitrogen adsorption curves of fat coal, lean coal and anthracite before and after cold soaking in LN2 are “S” type. An increase in the total pore volume and pore surface area of coal after LN2 cold soaking is noted. LN2 cold soaking is found to transform the internal pore structure of different coals effectively. Moreover, the heterogeneity of the porous structure of coal is enhanced after LN2 cold soaking along with an increase in the fractal dimension. The growth also decreases with an increase in the metamorphism. The uneven shrinkage of coal occurred during LN2 cold soaking, and the thermal stress generated is greater than the tensile strength of coal, which promotes the development of the porous structure of coal. These results are beneficial in revealing the macroscopic and microscopic pore fissure space expansion and connectivity law of coal seam during the process of LN2 cracking.

Research on the remote automatic test technology of the full link of the substation relay protection fault information system

In view of the fact that the actual operation information of sub-station relay protection device and the point table information of relay protection fault information system are still manually point-by-point proof reading. There are still problems such as low automation, long test time and low point-to-point debugging efficiency of the relay protection fault information system. This article proposes the full-link automatic test technology of the relay protection fault information system, and expounds its principle, main modules and key technologies. The full-link automatic test platform of the relay protection fault information system includes three parts: the main station remote test module, the sub-station test management module and the automatic test module. There are organically combined to realize the remote full-link automatic test, the main station, the sub-station and the spacer layer protection device function multi-step proofreading, automatic result evaluation and automatic report generation function in the entire process. The pilot application of the project shows that the full-link automatic test platform of the relay protection fault information system covers a wide range, can be automatically tested by one key, and has high accuracy. Therefore, it has a wide range of application prospects.

Improve the mechanical durability of superhydrophobic/superamphiphobic coating through multiple cross-linked mesh structure

Superhydrophobic/superamphiphobic coatings have attracted extensive attention because of their unique liquid repellency, but their poor durability hinders their large-scale application in the market. This paper designs and synthesizes a mesh structure that uses covalent bonds to link the roughness-building nanoparticles, film-forming polymer, and the substrate together, which significantly improves the stability and durability of the coating. Firstly, the acrylate copolymer (FHA) containing silicon monomer and fluorine monomer was synthesized by free radical polymerization. Then FHA, SiO2/TiO2 nanoparticles, and self-made crosslinker (AG) were connected to form a meshwork structure by Si-O-Si bond through a hydrolysis condensation reaction. Finally, the curing agent (HDI) was added before dip-coating, and the coatings were firmly linked to the substrate through secondary cross-linking. The single-factor experiment showed that when silicon monomer was 12 wt%, fluorine monomer was 5 wt% and FHA content was 16 wt%, the coatings displayed the 5B adhesion. The contact angle (CA) to water, diiodomethane, soybean oil， rapeseed oil, hexadecane, kerosene, waste engine oil on the FAFH-SiO2 coating (consists of the mesh structure and SiO2 nanoparticles) were 158.7° ± 1.5°, 151.1° ± 1.6°, 150.1° ± 1.7°, 150.4° ± 1.5°, 141.1° ± 1.6°, 142.2° ± 1.9°, and 144.7° ± 1.8°, respectively. The coatings could maintain WCA (water contact angle) > 150° after immersion in HCl (PH = 1), toluene, ethanol, and acetone for 84 h. The sandpaper abrasion, water flow scouring, high-pressure steam cooking, machine washing, and environmental exposure tests proved that the coatings have excellent stability and durability. This method for enhancing the durability of the coatings is suitable for particles and substrates containing active hydrogen or hydroxyl groups, which has a wide range of application prospects.

Optimized photovoltaic system for improved electricity conversion

Abstract Photovoltaic (PV) modules convert solar energy into electricity; however, in actual applications, the conversion efficiency of PV modules is low. This is because the temperature of PV modules increases, most of the incoming solar radiation absorbed is discarded to the PV modules as wasted heat; this wasted heat generated can be utilized and transferred to a heat exchanger in contact to the rear PV modules. A proposed model is considered with a variation of solar cell temperature due to solar radiation and its effects on output power are modeled and evaluated, seeing PV modules as a thermal absorber, a part of the heat dissipated in the PV modules can be recovered by means of a heat transfer fluid running behind the PV modules, this method improves the PV efficiency, as well as produces thermal and electrical energy simultaneously, thus, the PV modules provide a multifunctional performance cited above, this plays the role of a hybrid solar collector system. The aim of this study is to improve the efficiency of the PV module, through the analysis of a detailed Photovoltaic-Thermal (PVT) collector model performance. The study also estimates the electrical power and thermal energy produced; using MATLAB as an application-oriented design method, the method proposed in this paper can better improve the efficiency of PV power generation and has a wide range of application prospects.

Virtual Reality (VR) Advertising Communication Design Based on 3D Wireless Active Visual Sensing

With the vigorous development of the advertising industry, advertising in the era of intelligent media fills all aspects of our lives, and more and more intelligent media are applied to the advertising industry. The current three-dimensional advertising and interactive advertising are too fragmented in form, with three-dimensional advertising having a strong sense of three-dimensionality but lacking interactivity and interactive advertising having strong interactivity but lacking visual attraction. How to integrate 3D advertising and interactive advertising in order to make advertising in the future has greater development potential and market, whether in the visual or interactive experience can attract the target consumers becomes very necessary. It is found that VR technology has a wide range of application prospects, and intelligent media advertising mediated by VR technology follows the trend of advertising industry development. This thesis uses VR (virtual reality) technology as a medium to study the integration of 3D advertising and interactive advertising in the smart media era. In the second phase, the development direction of VR as an advertising medium in the era of intelligent media is identified. The research on the integration of 3D animated ads and interactive ads under VR technology is launched, and the research on 3D stereoscopic and interactive design of advertisements in the era of smart media is a reflection and exploration of the future language of advertising design. And through the comparison with traditional advertising, it is concluded that the aesthetic subject of VR advertising is “polycentric,” the aesthetic object. Then, we analyze the theoretical roots of the formation of the aesthetic characteristics of VR advertising from three levels: media technology, communication theory, and audience psychology. Finally, we return to the general environment of visual culture and explore the deconstruction of visual culture by the aesthetic characteristics of VR advertising in three levels: “symbol collapse,” “audience reshaping,” and “immersive communication.”

The Auxiliary System of Video Surveillance in Smart Substation

With the continuous development of artificial intelligence technology, the current substation operation and maintenance personnel have more and more urgent needs for the visualization, remoteness and intelligence of the operation and maintenance system. In order to solve the existing problems and present situation, key technologies such as image acquisition, image recognition, and visual display are studied. A smart substation video monitoring auxiliary system was developed. The system is used advanced cameras and acquisition equipment to monitor and detect related electrical equipment such as hard pressure plate switches in the substation in real time. The goal of intelligent inspection is achieved. In the smart substation project, it has achieved good results and has a wide range of application prospects.

Sea-Surface Target Visual Tracking with a Multi-Camera Cooperation Approach.

Cameras are widely used in the detection and tracking of moving targets. Compared to target visual tracking using a single camera, cooperative tracking based on multiple cameras has advantages including wider visual field, higher tracking reliability, higher precision of target positioning and higher possibility of multiple-target visual tracking. With vast ocean and sea surfaces, it is a challenge using multiple cameras to work together to achieve specific target tracking and detection, and it will have a wide range of application prospects. According to the characteristics of sea-surface moving targets and visual images, this study proposed and designed a sea-surface moving-target visual detection and tracking system with a multi-camera cooperation approach. In the system, the technologies of moving target detection, tracking, and matching are studied, and the strategy to coordinate multi-camera cooperation is proposed. The comprehensive experiments of cooperative sea-surface moving-target visual tracking show that the method used in this study has improved performance compared with contrapositive methods, and the proposed system can meet the needs of multi-camera cooperative visual tracking of moving targets on the sea surface.

Research on Gaze Estimation Method Combined with Head Motion Changes

Abstract The line of sight reflects the focus of human attention. Gaze estimation technology has a wide range of application prospects in human-computer interaction, human emotion analysis, commercial advertising, and so on. Gaze estimation needs to be jointly determined by eye movement and head movement because the human gaze is often with the head movement. In this paper, a gaze estimation system with head movement is implemented by a monocular camera, using eye movement features and head movement posture changes to estimate the gaze point. A camera is used as the information acquisition device to extract the eye movement feature information, and the offset of head movement is estimated at the same time. The final fixation point position coordinates are obtained by compensating the fixation point position in the case of head movement, and then the fixation point position coordinates are estimated. For the compensated gaze drop point, the average pixel error on the X-axis is estimated to be 118 pixels, and the average pixel error on the Y-axis is estimated to be 136 pixels.

Activation of Innate Immunity by Therapeutic Nucleic Acids.

Nucleic acid-based therapeutics have gained increased attention during recent decades because of their wide range of application prospects. Immunostimulatory nucleic acids represent a promising class of potential drugs for the treatment of tumoral and viral diseases due to their low toxicity and stimulation of the body’s own innate immunity by acting on the natural mechanisms of its activation. The repertoire of nucleic acids that directly interact with the components of the immune system is expanding with the improvement of both analytical methods and methods for the synthesis of nucleic acids and their derivatives. Despite the obvious progress in this area, the problem of delivering therapeutic acids to target cells as well as the unresolved issue of achieving a specific therapeutic effect based on activating the mechanism of interferon and anti-inflammatory cytokine synthesis. Minimizing the undesirable effects of excessive secretion of inflammatory cytokines remains an unsolved task. This review examines recent data on the types of immunostimulatory nucleic acids, the receptors interacting with them, and the mechanisms of immunity activation under the action of these molecules. Finally, data on immunostimulatory nucleic acids in ongoing and completed clinical trials will be summarized.

An omnidirectional acoustic energy harvester based on six Helmholtz resonators

An omnidirectional acoustic energy harvester (AEH) based on six Helmholtz resonators is proposed in this work. Compared with the previous structure, the insufficiency of the directionality and conversion efficiency of energy collection can be effectively improved due to the coupling of six resonators. Based on the distributed parameter model, the relationship of the electrical output, the input frequency with the structure size is obtained. The simulation results show that the maximum output voltage is 70.95 mV at the resonant frequency of 35 kHz. When the external load resistance is 14 kΩ, the maximum output power is 0.45 μW. Moreover, the energy conversion efficiency of this omnidirectional AEH can reach 23%, which is improved greatly compared with the traditional structure. Therefore, this AEH will have a wide range of application prospects in medical implantation equipment and other fields.

Research Progress of Photo-/Electro-Driven Thermochromic Smart Windows.

Thermochromic smart windows can automatically control solar radiation according to the ambient temperature. Compared with photochromic and electrochromic smart windows, they have a stronger applicability and lower energy consumption, and have a wide range of application prospects in the field of building energy efficiency. At present, aiming at the challenge of the high transition temperature of thermochromic smart windows, a large amount of innovative research has been carried out via the principle that thermochromic materials can be driven to change their optical performance by photothermal or electrothermal effects at room temperature. Based on this, the research progress of photo- and electro-driven thermochromic smart windows is summarized from VO2-based composites, hydrogels and liquid crystals, and it is pointed out that there are two main development trends of photo-/electro-driven thermochromic smart windows. One is exploring the diversified combination methods of photothermal materials and thermochromic materials, and the other is developing low-cost large-area heating electrodes.

Simultaneous determination of three allergic proteins in rice and products by high performance liquid chromatography-tandem mass spectrometry combined with stable isotope-labeled peptides

基于稳定同位素标记特征肽段和液相色谱-质谱联用仪建立稻米及制品中3种过敏蛋白质的同时定量方法。稻米及制品样品经盐溶液提取,赖氨酰基内切酶(Lys-C)和胰蛋白酶依次水解,C18-SD柱净化后,采用纳升高效液相色谱-线性离子阱-静电场轨道阱(NanoLC-LTQ-Orbitrap)采集和Protein Discovery软件鉴定,NCBI和Uniprot数据库的基本局部搜索比对工具(BLAST)筛选验证,最终获得表征稻米及制品中α-淀粉酶/胰蛋白酶抑制剂类蛋白质(seed allergenic protein RAG2, RAG2)、乙二醛酶Ⅰ活性蛋白(glyoxalase Ⅰ)和α-球蛋白(19 kDa globulin)3种过敏蛋白质的特异性肽段。3个特异性肽段经液相色谱梯度洗脱,在Poroshell色谱柱上实现完全分离,由三重四极杆质谱仪分析。实验通过优化多反应监测(MRM)质谱参数,比较不同溶剂体系、水解酶种类和酶量等酶解条件,结合内标法定量,实现对稻米及制品中3种蛋白质的绝对定量。实验结果表明,当酶解溶剂中含1 g/L十二烷基硫酸钠,采用Lys-C和胰蛋白酶组合消化策略,可有效提高3种蛋白质的酶切效率至65.7%~97.3%。该方法在1~200 nmol/L范围内线性关系良好,相关系数均大于0.9972, 3种蛋白质的检出限和定量限分别为3 mg/kg和10 mg/kg。3种蛋白质在空白稻米制品基质中3个水平下的加标回收率为80.6%~103.7%,日间和日内精密度均小于11.5%。该方法稳定性好,检测灵敏度高,操作简便,在分析各类稻米及制品中3种过敏蛋白质含量具有广泛的应用前景。

A plasticity-based dynamic constitutive model for ultra high toughness cementitious composites

Ultra high toughness cementitious composites (UHTCC) have a wide range of application prospects in various protective structures. At present, various concrete material models have been frequently used to simulate the mechanical response of such materials subjected to high-speed impact and explosive loads. However, none of these models can accurately describe the tensile ductility, strain rate effect, and shear expansion effect of UHTCC, which may lead to inaccurate numerical simulation results. In this study, a dynamic constitutive model of UHTCC was established, which comprehensively considered damage evolution, shear expansion, strain rate, strain hardening and strain softening of such materials. It was implemented into LS-DYNA software through a user-defined interface. Then comprehensive element tests were conducted and compared with the commonly used concrete models. Finally, a set of experimental tests of the UHTCC subjected to high-speed impact and contact blast loads were simulated. It was found that the numerical prediction results were in good agreement with the experimental results.

Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet.

Rolling bearings are important in rotating machinery and equipment. This research proposes variational mode decomposition (VMD)-DenseNet to diagnose faults in bearings. The research feature involves analyzing the Hilbert spectrum through VMD whereby the vibration signal is converted into an image. Healthy and various faults show different characteristics on the image, thus there is no need to select features. Coupled with the lightweight network, DenseNet, for image classification and prediction. DenseNet is used to build a model of motor fault diagnosis; its structure is simple, and the calculation speed is fast. The method of using DenseNet for image feature learning can perform feature extraction on each image block of the image, providing full play to the advantages of deep learning to obtain accurate results. This research method is verified by the data of the time-varying bearing experimental device at the University of Ottawa. Through the four links of signal acquisition, feature extraction, fault identification, and prediction, a mechanical intelligent fault diagnosis system has established the state of bearing. The experimental results show that the method can accurately identify four common motor faults, with a VMD-DenseNet prediction accuracy rate of 92%. It provides a more effective method for bearing fault diagnosis and has a wide range of application prospects in fault diagnosis engineering. In the future, online and timely diagnosis can be achieved for intelligent fault diagnosis.

Growth of high performance coal tar-based carbon film and its application in Joule heating

Conductive carbon film has a wide range of application prospects, especially in the fields of electric heating devices, energy storage devices, and solar cells. Coal tar is an ideal precursor for preparing carbon film. In order to improve the performance of coal tar-based carbon film, it is necessary to study the influence of tar composition on the structure and performance of carbon film. In this paper, a carbon film is prepared using aromatic compounds, heteroatom compounds and tar as carbon sources. It is found that the carrier concentration of aromatic hydrocarbon-based carbon films is higher than 1022 cm−3, but the mobility of the carrier is lower than 1 cm2/Vs. The resistivity and sheet resistance of the aromatic hydrocarbon-based carbon film are lower than that of the coal tar-based carbon film. Naphthalene-based carbon film has the best electrical and thermal properties. The maximum heating temperature of naphthalene-based carbon film at 30 V exceeds 300°C. The thickness of the carbon film has a decisive influence on the sheet resistance of the carbon film. The performance of the heteroatom compound-based carbon film is significantly lower than that of aromatic compound-based film.