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Due to the limitations of experimental testing in material size and time scale, this work presents a mechano-electrochemical bidirectional coupling FEM simulation model on account of mechanistic and corrosion kinetics understanding in Al alloy-316L SS galvanic couple. The galvanic corrosion behavior and anodic dissolution deformation of the couple in 3.5 wt.% NaCl solution were analyzed. The effect of external load on galvanic corrosion initiation and propagation was investigated based on Gutman's theory. The FEM model reveals that the galvanic corrosion is connected with the mechanical damage and the stress concentration coefficient, and highlights the crucial role of corrosion defect in the mechanical behavior of Al alloy. The results show that the external force aggravates the galvanic corrosion at the defects, deteriorating the protection of corrosion products. The thickness of the Al (OH)3 deposition layer reflects the electrochemical reactivity at different positions on the anode surface. The mechanical damage occurs initially at the corrosion defect and then extends to the middle of the anode. The stress concentration coefficient at the center of the anode gradually exceeds the position of the corrosion defect, resulting in mechanical failure at this position.

Silicon carbide (SiC) semiconductor with wide bandgap has aroused intensive attentions because they can endure harsh environments and high temperatures. SiC photodetectors based on conventional principles usually detect UV light without the ability of wavelength discrimination. Here, resorting to the charge narrowing collection principle, we realize a highly sensitive filterless narrowband 4H-SiC photodetector. The 4H-SiC layer is sufficiently thick to facilitate charge collection narrowing of the device’s external quantum efficiency spectrum, inducing a full width at half-maxima of 14.5 nm at the peak wavelength of 355 nm. Thanks to the Fermi level pinning effect, the proposed photodetector can fully eliminate the injection current; thus it works as a photovoltaic type device with a remarkably low dark current. Consequently, the devices renders a photo-to-dark current ratio as high as 4×107, superior to the performances of most of reported 4H-SiC UV photodetectors. In addition, the device can detect light signals with a power density as low as 96.8 pW/cm2, more than two orders of magnitude superior to that of the commercial product based on the photodiode principle. Moreover, it can endure high temperature of 350 °C, demonstrating bright prospects in harsh industry conditions.

Mass measurement is an essential analytical tool in the characterization of materials. Here we present a method for measuring the mass of an individual nanoparticle, which has a fg-level mass. This method enables a temperature-independent mass measurement with the assistance of a sinusoidal electrostatic driving force. With this approach, we successfully track the change in properties of an optically levitated nanoparticle, such as mass, temperature, and electric charge, with air pressure. An abrupt change in the mass of silica nanoparticles is found to violate the Zhuravlev model. This method can be utilized to extend the mass analysis of materials, such as thermogravimetric analysis, to individual micro- or nano-particles.

Lyα (Lyα, 1216 Å) is the strongest emission line in the solar ultraviolet spectrum. In the present work, we obtained a Lyα enhancement catalog covering flares larger than B1 class from the GOES/EUVS data during 2010–2016. We focused on the 242 B-class events which are less investigated, however, show non-negligible Lyα emission enhancement. We found that on average the Lyα peak of B-class flares is 0.85% stronger than the background. For the flare energetics, it is found that the weaker the soft X-ray (SXR) flare, the larger the ratio of the radiated energy in Lyα to SXR. Using the RHESSI data and multi-wavelength observations taken by SDO-AIA, we diagnose the thermal and non-thermal properties of several flares. Three case studies show that the coincidence of the Lyα peak with the SXR time-derivative peak is not a sufficient condition of the nonthermal property of a Lyα microflare. The Lyα enhancement in the microflares may be caused by the nonthermal electron beams or/and thermal conduction. However for type III events, we found that the delay of the Lyα peak with respect to the SXR peak can be attributed to either the Lyα emission from a filament erupted or the cooling of the thermal plasma in flare loops. Furthermore, interestingly the Lyα emission from filaments can not only occur in the decay phase of the flare, but also in the pre-flare phase. In this case, the Lyα emission was originated from an erupted filament which probably initiated the flare.

Power big data is the practice of big data concepts, methods, and technologies in the power industry. It is composed of structured data and unstructured data. It mainly involves power generation, transmission, transformation, and distribution. Power big data can reflect the macro-economy in real time, promote economic and social development, and improve the internal management level and economic benefits of the power industry enterprises. The integration of power big data technology and power system simulation calculation can update system analysis in real-time and provide new perspectives and methods for system analysis.

The clarity of nights is the major factor that should be carefully considered for optical/infrared astronomical observatories in site-testing campaigns. Cloud coverage is directly related to the amount of time available for scientific observations at observatories. In this article, we report on the results of detailed night-time cloud statistics and continuous observing me derived from ground-based all-sky cameras at the Muztagh-ata site from 2017 to 2021. Results obtained from acquisition data show that the proportion of the annual observing me at the Muztagh-ata site is 65%, and the best period with the least cloud coverage and longer continuous observing time is from September to February. We made a comparison of the monthly mean observing nights obtained from our all-sky cameras and CLARA dataset, results show that the discrepancy between them may depend on the cloud top heights. On average, this site can provide 175 clear nights and 169 nights with at least 4 hours of continuous observing time per year., Comment: 11 pages, 9 figures

To improve the study on the influence of transformer windings and pad support on transformer short-circuit resistance, the calculation method of wire bending elastic modulus is analyzed, and the sample test is carried out: The influences of the unbalance of the two ends of the wire between the number of wires wound and the span of adjacent pads on the force-deflection curve, the bending force at the selected deflection, and the elastic modulus of bending were analyzed. The results showed that: Increasing the number of wires and decreasing the height difference of adjacent pads can improve the bending force and bending elastic modulus of wires, the axial stability, and short-circuit resistance of transformer windings. When the height of the adjacent pad is not balanced, the axial force can increase the compression degree between the pad and the wire, and reduce the span of the wire. Under the action of force, the wire yields twice, which further reduces the bending force and elastic modulus of the wire. This research can provide test data support for improving the installation of transformer winding pads and theoretical evaluation of short-circuit tolerance.

Astronomers have discovered numerous stars in galaxies, each with unique characteristics that mostly evolve into white dwarfs when reaching an evolutionary limit. A star with a low or medium mass less than about eight times the mass of the sun becomes a white dwarf after exhausting its nuclear fuels and begins to condense inwards by the force of gravitational attraction, leading to the final collapse. In this paper, the investigation analyzes three companion stars orbiting around three dwarfs by utilizing data provided by TESS (Tess Exoplanet Survey Satellite) Program G04137, providing more than 5200 candidate white dwarfs for a transiting planet. After testing 5200 known candidates of white dwarf provided by Tess Program G04137, the investigation decided to analyze three companion stars of TIC 403292348, TIC 1860468684, and TIC 356659664. In the first case study, the number of white dwarfs with the possibility of hosting planets is estimated from analyzing BLS data from listed white dwarfs in Sector 40, and the accuracy and limitations of this method are discussed qualitatively as well. In the second case of TIC-1860468684, the investigation analyzes a binary system with a young and bright White Dwarf and a low mass star, where the white Dwarf has tidally locked the star, and there may be nova formed in this system due to material transfer in the future. In the last case of TIC 356659664, the situation of a target is calculated, and possible cause of the target white dwarf’s flux curve is estimated. By analyzing three companion stars around white dwarfs, more data will be provided for astronomers for future scientific research.

Gear fault diagnosis generally uses oscillation signals to extract fault features, but the oscillation identify technique is inconvenient to set up sensors and is easily affected by the surrounding and noise. The motor itself has the property of a sensor, and signals such as motor current is able to reflect the change of the load torque. This paper proposes a gear fault detection approach, which applies the Motor Current Signature Analysis (MCSA) to exploit spectral characteristics to recognize malfunction in servo motor drive gears. First, we calculate the nominal revolutions per minute (rpm) to explore frequencies of interest. Second, frequency bands where faulty signals would be appear are constructed. Next, we extract power spectral density (PSD) feature data. Finally, the paper computes spectral metrics for the frequency band of interest. By using two spectral metrics, gear health and failure data are clearly grouped in different areas of the scatter chart. The experimental results give evidence of the effectiveness of analyzing current characteristics of servo motors to classify fault and health data.

Two-dimensional (2D) semiconductors, such as lead selenide (PbSe), locate at the key position of next-generation devices. However, the ultrathin PbSe is still rarely reported experimentally, particularly on metal substrates. Here, we report the ultrathin PbSe synthesized via sequential molecular beam epitaxy on Ag(111). The scanning tunneling microscopy is used to resolve the atomic structure and confirms the selective formation of ultrathin PbSe through the reaction between Ag5Se2 and Pb, as further evidenced by the theoretical calculation. It is also found that the increased accumulation of Pb leads to the improved quality of PbSe with larger and more uniform films. The detailed analysis demonstrates the bilayer structure of synthesized PbSe, which could be deemed to achieve the 2D limit. The differential conductance spectrum reveals a metallic feature of the PbSe film, indicating a certain interaction between PbSe and Ag(111). Moreover, the moiré pattern originated from the lattice mismatch between PbSe and Ag(111) is observed, and this moiré system provides the opportunity for studying physics under periodical modulation and for device applications. Our work illustrates a pathway to selectively synthesize ultrathin PbSe on metal surfaces and suggests a 2D experimental platform to explore PbSe-based opto-electronic and thermoelectric phenomena.

At present, the global navigation satellite system (GNSS) is the most widely used technology in the field of vehicle navigation and positioning. However, due to satellite signal blocking, it can be challenging to obtain precise and reliable vehicle positions in completely GNSS-denied environments. In this paper, a positioning strategy utilizing ultra-wide band (UWB) and a low-cost MEMS inertial navigation system (INS) is proposed, aimed at tracking vehicles in typical GNSS-denied scenarios. UWB tech has potential for high-precision ranging due to its strong penetration ability. However, non-line-of-sight (NLOS) propagation still has a high occurrence in typical traffic scenarios due to the fact that the direct path between the radio transmitter and the radio receiver is obstructed. Therefore, a two-step NLOS error mitigation method is proposed to deal with the abnormal measurements of UWB in tunnels. First, a state-of-the-art probabilistic factor graph model is proposed to estimate the vehicle’s position information based on UWB range measurements instead of excluding the NLOS reception. Then, a residual weighting algorithm is employed during UWB/INS loosely coupled integration to further mitigate the NLOS error. Finally, the performance of the proposed methodology is evaluated through experiments. Experiments conducted in the typical NLOS environment of Nanjing show that the proposed method can achieve higher positioning accuracy when compared with the conventional UWB/INS integration.

The double revolving fiber positioning technology is one of the key technologies for the success of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). The accuracy of fiber positioning will directly affect the observation efficiency of LAMOST. To achieve higher fiber positioning accuracy, the original open-loop controlled fiber positioning system urgently needs to be upgraded into a closed-loop control system. The fiber detection is the most important part of the closed-loop controlled fiber positioning system. The back-illuminated detection method is usually used to detect the fiber position by directly detecting the light spot generated at the fiber end in the multi-fiber spectral surveys. In this paper, we introduce a new method to measure the fiber position based on the image of the front-illuminated LAMOST focal plane. The front-illuminated image does not require lighting devices inside the spectrograph, and it could reduce the instability and light pollution in the spectrograph end. Our method measures the fiber position by fitting the profile of the fiber pinhole with a 2D Gaussian function. A series of tests show that the relative position measurement precision of the front-illuminated method is about 0.″12, and the method could have the same accuracy as the back-illuminated method once the system bias is calibrated by a simple radial correction function. The required fiber positioning accuracy of LAMOST is 0.″4, and the new method satisfies the requirement of LAMOST fiber detection accuracy and could be used in the closed-loop fiber control system.

Switched Reluctance Motor (SRM) is a new type of high technology motor used in the most advanced warplanes. This paper combines the principle of SRM and takes the typical SRM power generation system of modern warplanes as an example to analyze the functions and power generation process of each part of the system, as well as its effective power generation conditions.

This paper introduces a kind of contact train obstacles and derailment detection device. It is composed of detection device and electric box. The energy produced by collision between obstacles and detection device and the train derailment is converted to electrical signal which can be measured, then it could control emergency braking. It can minimize the impact of foreign matter on vehicle safety or operation order after entering the vehicle limit. This system uses CPLD as the control core and adopts double redundancy design that improved the reliability of the device. It provides guarantee for train running safety and has good application prospect.

This work demonstrates for the first time the capability of routine Tropospheric Monitoring Instrument (TROPOMI) operations to quantify CO emission rates down to industrial point sources. We have quantified the CO emission rates of four industrial point sources in Asia, namely Qianlishan Industrial Park (39.9° N, 106.9° E), Jiuyuan Industrial Park (40.7° N, 109.7° E) and Botian Industrial Park (42.2° N, 125.2° E) in China and the Jindal factory (15.2° N, 76.7° E) in India, with TROPOMI CO observations from 2017 to 2020. Qianlishan Industrial Park is a missing source in the emission inventory and we quantify it to be ∼14.0 kg s−1. Our estimates for the other three sources vary between 14.4 and 34.3 kg s−1, within 37%–69% of the inventory values. The plume inversion methods are presented in a manner that can be easily used with other fine-scale emission plumes observed from space. Although only a small number of CO plumes per year for any given industrial point source can be observed under conditions suitable for estimation of emission rates, there are many industrial point sources that can be captured by a good TROPOMI footprint. This work affirms that a constellation of future CO satellites could monitor individual CO point source emissions to support environmental policies.

In this paper, our work is based on a coupled nonlinear Schrödinger system in a two-mode nonlinear fiber. A (N,m)-generalized Darboux transformation is constructed to derive the Nth-order solutions, where the positive integers N and m denote the numbers of iterative times and of distinct spectral parameters, respectively. Based on the Nth-order solutions and the given steps to perform the asymptotic analysis, it is found that a degenerate dark-bright soliton is the nonlinear superposition of several asymptotic dark-bright solitons possessing the same profile. For those asymptotic dark-bright solitons, their velocities are z-dependent except that one of those velocities could become z-independent under certain condition, where z denotes the evolution dimension. Those asymptotic dark-bright solitons are reflected during the interaction. When a degenerate dark-bright soliton interacts with a nondegenerate/degenerate dark-bright soliton, the interaction is elastic, and the asymptotic bound-state dark-bright soliton with z-dependent or z-independent velocity could take place under certain condition. Our study extends the investigation on the degenerate solitons from the bright soliton case for the scalar equations to the dark-bright soliton case for a coupled system.

The double revolving fiber positioning unit (FPU) is one of the key technologies of The Large Sky Area Multi-Object Fiber Spectroscope Telescope (LAMOST). The positioning accuracy of the computer controlled FPU depends on robot accuracy as well as the initial parameters of FPU. These initial parameters may deteriorate with time when FPU is running in non-supervision mode, which would lead to bad fiber position accuracy and further efficiency degradation in the subsequent surveys. In this paper, we present an algorithm based on deep learning to detect the FPU’s initial angle using the front illuminated image of LAMOST focal plane. Preliminary test results show that the detection accuracy of the FPU initial angle is better than 2.°5, which is good enough to distinguish those obvious bad FPUs. Our results are further well verified by direct measurement of fiber position from the back illuminated image and the correlation analysis of the spectral flux in LAMOST survey data.

Bulk group IB transition-metal chalcogenides have been widely explored due to their applications in thermoelectrics. However, a layered two-dimensional form of these materials has been rarely reported. Here, we realize semiconducting Cu2Se by direct selenization of Cu(111). Scanning tunneling microcopy measurements combined with first-principles calculations allow us to determine the structural and electronic properties of the obtained structure. X-ray photoelectron spectroscopy data reveal chemical composition of the sample, which is Cu2Se. The observed moiré pattern indicates a lattice mismatch between Cu2Se and the underlying Cu(111)- 3 × 3 surface. Differential conductivity obtained by scanning tunneling spectroscopy demonstrates that the synthesized Cu2Se exhibits a band gap of 0.78 eV. Furthermore, the calculated density of states and band structure demonstrate that the isolated Cu2Se is a semiconductor with an indirect band gap of ∼ 0.8 eV, which agrees quite well with the experimental results. Our study provides a simple pathway varying toward the synthesis of novel layered 2D transition chalcogenides materials.

Interlayer coupling in layered semiconductors can significantly affect their optoelectronic properties. However, understanding the mechanisms behind the interlayer coupling at the atomic level is not straightforward. Here, we study modulations of the electronic structure induced by the interlayer coupling in the γ-phase of indium selenide (γ-InSe) using scanning probe techniques. We observe a strong dependence of the energy gap on the sample thickness and a small effective mass along the stacking direction, which are attributed to strong interlayer coupling. In addition, the moiré patterns observed in γ-InSe display a small band-gap variation and nearly constant local differential conductivity along the patterns. This suggests that modulation of the electronic structure induced by the moiré potential is smeared out, indicating the presence of a significant interlayer coupling. Our theoretical calculations confirm that the interlayer coupling in γ-InSe is not only of the van der Waals origin, but also exhibits some degree of hybridization between the layers. Strong interlayer coupling might play an important role in the performance of γ-InSe-based devices.

Accelerating materials discovery crucially relies on strategies that efficiently sample the search space to label a pool of unlabeled data. This is important if the available labeled data sets are relatively small compared to the unlabeled data pool. Active learning with efficient sampling methods provides the means to guide the decision making to minimize the number of experiments or iterations required to find targeted properties. We review here different sampling strategies and show how they are utilized within an active learning loop in materials science.

This paper deals with a fundamental aspect of the inverse problem of robustly reconstructing sparse tensor signals via convex optimization. The traditional vector signal model is extended to tensor model and tensor-space based convex optimization methods are applied to establish the critical results. In particular, by means of some innovative sub-differential analysis for tensor norms and convex geometric analysis in normed tensor space, sufficient conditions to guarantee uniqueness and stability of sparse tensor signal reconstruction are established. In comparison with most current works based on vector signal model (1-order tensor), these conditions are more general and more applicable to tensor signals. Also will these conditions be helpful for establishing practical algorithms for reconstructing high-order sparse tensor signals which are emerging in various data-intensive intelligent applications.

Low-viscosity UV-curable resins are widely used in industry as they allow for UV curing materials with reduced amounts of reactive diluents to adjust the viscosity. But their mechanical properties and waterproof performance after curing as UV coatings still need to be improved. Here, a series of low-viscosity bio-based UV-curable polyester methacrylates were synthesized through L-lactide (LA) and ε-caprolactone (CL) monomers. The results show that the introduction of star-shaped structure and random copolymerization of LA and CL can effectively reduce the viscosity of the resin to 313 mPa · s and at the same time increase the double bond conversion rate and maintain good mechanical properties. The composite resin was prepared by blending the star-shaped low-viscosity polyester methacrylate resin with cellulose nanocrystals (CNCs), and the microstructure was characterized by XRD and TEM. The curing kinetics, mechanical properties, thermal properties and waterproof properties of the composite resin were further tested. When the mass fraction of CNCs is 2.5 wt%, the water absorption rate of the pine samples coated with UV-cured composite resin is reduced to 17%, which is 65% lower than that of the uncoated samples and 20% lower than that of the samples coated with resin without CNC. This article provides a feasible and effective method for improving the mechanical properties and waterproof performance of low-viscosity UV-curing resins.

In order to solve urban development problems and achieve sustainable urban development, building smart cities has become an essential core concept for urban development in the world today. From the perspective of current smart city needs, this article introduces the concept and basic characteristics of CIM, an information technology closely related to smart cities, and analyzes its key technologies BIM (Building Information Modeling), GIS (Geographic Information System), IOT (The Internet of Things), and a brief overview of the relationship between the three, laid a preliminary foundation for further related research.

For the increase of the transmission capacity in optical communication systems, the so-called few-mode fibers are used for people to design the mode division multiplexing transmission. In this paper, we analytically obtain and graphically display the superregular solutions for a coupled nonlinear Schrödinger (NLS) system which describes the wave evolution in a two-mode nonlinear fiber, where the superregular solutions are the analogue of superregular breathers for certain scalar NLS-type equations. On the nonzero-zero (or proportional nonzero-nonzero) background, regular solutions describe the regular nonlinear waves which are located in a finite t domain but do not perturb the background with t being big enough, and superregular solutions are a subset of regular solutions which describe the nonlinear superposition of breathers and dark-bright (or breather-like) solitons developing from the perturbations on the dark-bright (or breather-like) solitons at a certain z, where z and t denote the evolution dimension and temporal distribution dimension, respectively. On the nonzero-zero background, superregular solutions are constructed in three cases: trivial case, a pair of breathers case and single breather case, and then other superregular solutions could be constructed according to the analyses for such three cases. Superregular solutions on the proportional nonzero-nonzero background are derived via the superregular solutions on the nonzero-zero background and an orthogonal transformation.

With the rapid development of highway engineering construction in our country, Vibrating Sinking Pipe gravel pile machines have been widely used in soft foundation treatment. The main parameters of the Vibrating Sinking Pipe gravel pile machine are composed of current value, drilling depth and drilling verticality. In this paper, through the analysis of the actual parameter data collected from the intelligent monitoring system of Vibrating Sinking Pipe gravel pile machines in Sichuan Yangtze River Industrial Park, the multiple linear regression prediction model is established by using the regression prediction method; and according to the comparison between the real data and the prediction data, the determination coefficient ranges from 0.83 to 0.95.

This paper deals with the problem of robustly reconstructing n-by-n structured matrix signal via convex optimization in random setting. The traditional vector signal model is extended to matrix model. By means of a generalized matrix width estimation and sub-differential analysis, fundamental lower bounds on number of random measurements to guarantee high successful reconstruction probability are established. In comparison with most current works, these bounds are tighter and the methods are more suitable to be generalized to dealing with high-order tensor signals.

This paper investigates the problem of reconstructing n-by-n structured matrix signal via convex optimization. The traditional vector signal model is extended to matrix signal model. We establish fundamental conditions on the measurement operator to guarantee strong properties of sparse and flat matrix signal reconstruction from noisy measurements, i.e., conditions to guarantee uniqueness, support and sign stability as well as value-error robustness. In comparison with other works, these conditions are more general and our method is more suitable to be generalized to dealing with high-order tensor signals. These theoretical results, together with the auxiliary results in the argument, are heuristic for developing more effective algorithms in, e.g., wide-band communications and related signal processing applications.

Based on previous site testing and satellite cloud data, Ali, Daocheng and Muztagh-ata have been selected as candidate sites for the Large Optical/Infrared Telescope (LOT) in China. We present the data collection, processing, management and quality analysis for our site testing based on using similar hardware. We analyze meteorological data, seeing, background light, cloud and precipitable water vapor data from 2017 March 10 to 2019 March 10. We also investigated the relative usefulness of our all-sky camera data in comparison to that from the meteorological TERRA satellite data based on a night-by-night comparison of the correlation and consistency between them.We find a 6% discrepancy arising from a wide range of factors.

The Large Optical/infrared Telescope (LOT) is a ground-based 12 m diameter optical/infrared telescope which is proposed to be built in the western part of China in the next decade. Based on satellite remote sensing data, along with geographical, logistical and political considerations, three candidate sites were chosen for ground-based astronomical performance monitoring. These sites include: Ali in Tibet, Daocheng in Sichuan and Muztagh-ata in Xinjiang. Up until now, all three sites have continuously collected data for two years. In this paper, we will introduce this site testing campaign, and present its monitoring results obtained during the period between March 2017 and March 2019.

A large ground-based optical/infrared telescope is being planned for a world-class astronomical site in China. The cloud-free night percentage is the primary meteorological consideration for evaluating candidate sites. The data from GMS and NOAA satellites and the MODIS instrument were utilized in this research, covering the period from 1996 to 2015. Our data analysis benefits from overlapping results from different independent teams as well as a uniform analysis of selected sites using GMS+NOAA data. Although significant ground-based monitoring is needed to validate these findings, we identify three different geographical regions with a high percentage of cloud-free conditions (∼83% on average), which is slightly lower than at Mauna Kea and Cerro Armazones (∼85% on average) and were chosen for the large international projects TMT and ELT respectively. Our study finds evidence that cloud distributions and the seasonal changes affected by the prevailing westerly winds and summer monsoons reduce the cloud cover in areas influenced by the westerlies. This is consistent with the expectations from climate change models and is suggestive that most of the identified sites will have reduced cloud cover in the future.

The potential impact of SF6 as a potent greenhouse gas on the global climate is highly attractive. This paper studies the effect of H2O concentration, SF6 inlet concentration and pre-heating temperature on SF6 abatement in a packed bed plasma reactor in terms of the removal efficiency and products selectivity. The results showed that the best performance in SF6 abatement was obtained at 1% H2O and 100 °C with 98.7% destruction and remove efficiency (DRE) at 2% SF6. Higher energy yields was obtained under higher SF6 inlet concentration. Moreover, the existence of water vapor weakened the micro-discharge and provided H and OH radicals for this system, which showed a close relationship to removal efficiency and products selectivity. Among four sulfur-containing products, SO2F2 was more stable than SOF2, SOF4 and SO2. Meanwhile, SOF4 and SO2 were very susceptible to the above parameters. This article provides a better understanding of SF6 abatement in a view of both scientific and engineering.

Starting from the application purpose of real distribution network planning, for the high-voltage distribution network connected by medium-voltage tie lines, the power supply capacity is predicted according to current feeder loads and their changing trends, so that the results are more realistic. Based on the above calculation process, the weakness of a distribution network can be identified intuitively and conveniently, which can be used as the basis for generating the measures or schemes to improve power supply capacities. Numerical examples show that the presented model and method are intuitive, simple, and stable and effective compared with the existing methods, and are convenient for application in practice.

Twin-core optical fibers are applied in such fields as the optical sensing and optical communication, and propagation of the pulses, Gauss beams and laser beams in the non-Kerr media is reported. Studied in this paper are the coupled cubic-quintic nonlinear Schrödinger equations with variable coefficients, which describe the effects of quintic nonlinearity for the ultrashort optical pulse propagation in a twin-core optical fiber or non-Kerr medium. Based on the integrable conditions, bilinear forms are derived, and dark-dark soliton solutions can be constructed in terms of the Gramian via the Kadomtsev-Petviashvili hierarchy reduction. Propagation and interaction of the dark-dark solitons are presented and discussed through the graphic analysis. With different values of the delayed nonlinear response effect b(z), where z represents direction of the propagation, the linear- and parabolic-shaped one dark-dark soltions can be derived. Interactions between the parabolic- and periodic-shaped two dark-dark solitons are presented with b(z) as the linear and periodic functions, respectively. Directions of velocities of the two dark-dark solitons vary with z and the amplitudes of the solitons remain unchanged can be observed. Interactions between the two dark-dark solitons of different types are displayed, and we observe that the velocity of one soliton is zero and direction of the velocity of the other soliton vary with z. We find that those interactions are elastic.

Under the background of the government’s subsidy for new energy vehicles, this paper takes a secondary energy supply chain composed of a new energy automobile enterprise and an online car-hailing platform as the research object. Considering the long-term dynamic characteristics of cooperation between new energy automotive enterprise and online car-hailing platform, this paper constructs a differential game model of automotive enterprise and online car-hailing platform under decentralized decision and centralized decision, and obtains their equilibrium strategy and optimal profit function under the two situations, as well as the optimal trajectory of automotive carbon emission reduction over time. The research finds that: compared with decentralized decision, under the centralized decision, new energy automobile enterprise increase its efforts in emission reduction, and the operation efforts of online car-hailing platform increase. Pareto improvement is achieved in the profit of supply chain, and the carbon emission reduction of automobiles is improved. Finally, the model is verified and analyzed by numerical experiments.

The structural effect is believed to have no influence on the decay properties of medium and heavy-mass nuclei at excitation energies above the pairing gap. These properties can be described by statistical properties using so-called photon strength functions for different multipolarities, and directly related to the photoabsorption cross-section ( ). is dominated by the electric giant dipole resonance at energy MeV. In this study, we construct two kinds of systematic giant dipole resonance parameters by fitting the experimental photoabsorption cross-sections. One is based on the microscopic relativistic quasiparticle random phase approximation approach, whereas the other is estimated by the phenomenological models within the Lorentzian representation. Both of them are demonstrated ot efficiently describe the experimental photoabsorption cross-sections available for medium to heavy-mass nuclei, and they can obtain more reliable predictions for the unknown nuclear system.

In order to investigate the influence of Tension-tension fatigue behavior of fiber reinforced ceramic-matrix composites, SiC/SiC composites with 2.5D fiber architecture were prepared via Precursor Infiltration and Pyrolysis (PIP) method. Tension-tension fatigue behavior of SiC/SiC composites was investigated in 1000°C and 1200°C, under fatigue stresses ranging from 70 to 120MPa at a frequency of 1.0 Hz, under oxidizing atmosphere. Fatigue life of SiC/SiC composites achieved 305, 984 cycles at 1200°C/70MPa, and 252, 988 cycles at 1200°C/108MPa, which were longer than test in 1000°C. Composite microstructure, as well as failure mechanism was investigated. The main reason that cause tension-tension fatigue failure of SiC/SiC composites are oxidation damage and stress damage. The microstructure of SiC/SiC composites demonstrated that the oxidation of interfaces and SiC fibers caused the failure of the composites. Under the load of alternating stress, the original voids and cracks in the material preparation process will be widened, and new cracks will be generated, for cracked SiC/SiC composites, oxygen in is especially serious at intermediate temperatures(∼800°C) where it can reach the SiC fiber before being sealed off by slow-glowing silica on the matrix crack surface, therefore, tension-tension fatigue life of SiC/SiC composites at 1000°C is lower than 1200°C.

Deep learning classifies information and combines the underlying features to form more abstract high-level features. Its ability of autonomous learning also provides favorable conditions for industrial application. Aiming at the problem of insufficient performance of current small target detection, this paper proposes a deep learning algorithm using One-stage fusion two-stage. The influence of background noise on network training is reduced. The algorithm combines multi-scale training methods and achieves sample equilibrium adjustment based on sample distribution and stratified sampling. The high efficiency of YOLOv3 method for large target detection is well used, and the multi-scale training advantages of SNIPER algorithm are also played out, which makes the intelligent detection effect of pin defect of transmission line get some performance improvement.