Search

Lightning is an important factor affecting the safe and reliable operation of power transmission and distribution lines. As most power transmission and distribution lines are built in mountainous areas with complex terrain and changeable weather, the lightning accidents in mountainous areas are much higher than those in plain areas. Firstly, the mechanism of lightning damage and common measures of lightning protection are analyzed. Then, taking Lufeng line in Yunnan province as the object, taking the topographic and geomorphic characteristics of the line, the activity intensity of lightning strike and the line structure into consideration, three measures are compared by increasing the number of insulator string pieces, reducing the grounding resistance of poles and towers, and erecting lightning conductor across the line. Finally, erecting lightning conductor across the line is adopted to rectify the line. The feasibility and practicability of the rectification scheme are proved by calculation.

Since the main way of power transmission in China is overhead line transmission, some overhead lines are in a harsh outdoor environment. Among them, the bypass attack is more serious. Shielding Failure is a severe form of lightning damage. Based on the situation, this article studies the lightning shielding phenomenon of transmission lines. This article uses the pilot development model to simulate the lightning strike process, analyzes the different target objects of the lightning strike, and elaborates and calculates the lightning shielding trip rate. In addition, by changing the protection angle, the height of the tower, the ground inclination of the area where the line is located, and the number of lines, the impact of these four factors on the lightning shielding trip rate is discussed. According to the influencing factors, measures to strengthen the lightning protection performance of the line are proposed.

High-entropy alloys (HEAs) are emerging materials that are developed based on entropy, and draw significant attention for the potential to design their chemical disorder to bring out different structural and physical characteristics. Over the past two decades, significant salient efforts have been conducted to explore many unique and useful properties of HEAs, such as overcoming the strength–ductility trade-off, outstanding thermal stability, and excellent low temperature plasticity. Here, we review the key research topic of HEAs in the following three aspects: (a) performance advantages and composition design, (b) performance-driven HEAs and (c) fabrication process-driven HEAs. Towards their industrial applications, our article reviews a large range of methods to synthesise, fabricate and process HEAs. We also discuss the current challenges and future opportunities, mainly focusing on performance breakthroughs in HEAs.

All-day, all-weather wide-area search discovery target capability makes radar become a key piece of equipment in many military and civilian fields, and plays an indispensable role in tasks such as identification and positioning. However, at the same time, the current radar equipment generally relies on complex signal processing systems, and designing artificial feature extraction algorithms based on prior knowledge is both difficult and time-consuming, and it is difficult to fine-grained identify the target. In recent years, deep learning has been widely used in the radar field with its strong adaptability and strong self-learning ability. The paper presents a radar Doppler image based on YOLO v3 algorithm. With Millimeter-Wave radar distance-doppler reflectance image as input and darknet-53 as the feature extraction network, the automatic detection of vehicle millimeter wave radar cars, bicycles, pedestrians and trucks was realized, and the average detection accuracy reached 84.3%, providing new ideas and technical support for the development of intelligent radar and radar target detection.

Object detection is an important and active area of computer vision. However, the expensive computational cost and memory requirement are big challenges for deploying object detection networks in resource constraints embedded devices. To address this problem, we designed the multi-stage cascade module to reduce the computational cost of object detection networks. The proposed structure is used to build a compact and efficient object detection neural network. Experiments show that our multi-stage cascade module could significantly reduce the computational and parameter budgets meanwhile achieve outstanding object detection accuracy.

We propose a scheme to realize the active controlled dual-band unidirectional reflectionlessness at exceptional points by classical driving field in a non-Hermitian quantum system that consists of two Λ-type three-level quantum dots side coupled to a plasmonic waveguide. We demonstrate that the dual-band unidirectional reflectionlessness can be controlled by appropriately tuning classical driving field, phase shift between two quantum dots, dissipations of two quantum dots, and quantum dot-waveguide coupling strengths. Furthermore, the dual-band unidirectional reflectionlessness spectra with quality factors of ∼375.40 and ∼402.59 can be obtained in the forward and backward directions, respectively.

The existence and persistence of soybean diseases are not conducive to the effective operation of the global soybean market. Many detection and prediction methods have been used to prevent and detect soybean diseases, but the practicability of these methods has always been a big challenge for researchers due to there are too few variables in the prediction model, which show bad prediction effect of soybean disease in complex environment. In this paper, the popular Apriori algorithm in data mining is used to analyze the common disease data of soybean in complex environment, so as to achieve the goal of early prediction and control of soybean disease. The variables used in this paper are the characteristic factors of 35 kinds of Soybean under 18 common diseases. The experimental results show that the improved Apriori algorithm can complete the better prediction of soybean diseases in complex environment, so as to reduce the impact of diseases on soybean yield, which is of great significance for economic development, agricultural production and other fields.

The increasing share of renewable energy sources (RES) increases the imbalance between supply and demand, due to its fluctuation and intermittence. Eenergy flexible buildings are proposed as an important part of the solution to balance supply and demand. However, the thermal storage of a building is not utilized for reducing the considerable peak-to-valley difference in conventional night setup control strategies. In this context, pre-cooling is the most commonly used approach for charging cooling in building thermal mass to achieve energy flexibility. The objective of this paper is to assess the building flexibility potential using pre-cooling with structural thermal mass. We proposed quantitative indexes including valley-filling capacity, peak-shaving capacity and energy-shifting efficiency based on the improvement of existing indicators according to previous research. As considering the impact of structural thermal mass, heat transfer coefficient, pre-cooling duration, pre-cooling temperature on energy flexibility, a total of 35 scenarios are simulated using TRNSYS and evaluated using the quantitative indexes. Finally, the results may supply suggestions to utilize building energy flexibility with pre-cooling and optimize the corresponding control strategy.

Periodically driven systems can host many interesting and intriguing phenomena. The irradiated two-dimensional Dirac systems, driven by circularly polarized light, are the most attractive thanks to intuitive physical view of the absorption and emission of photon near Dirac cones. Here, we assume that the light is incident in the two-dimensional plane, and choose to treat the light-driven Dirac systems by making a unitary transformation to capture the photon-mediated electronic correlation effects, instead of using usual Floquet theory. In this approach, the electron-photon interaction terms can be cancelled out and the resultant effective electron-electron interactions can produce important effects. These effective interactions will produce a topological band structure in the case of 2D Fermion system with one Dirac cone, and can lift the energy degeneracy of the Dirac cones for graphene. This method can be applicable to similar light-driven Dirac systems to investigate photon-mediated electronic effects in them., Comment: 5 pages, 4 figures

In this study, corn stalk fiber (CSF) was used as a reinforcer to prepare wood plastic composite (WPC). The primitive CSF was subjected to alkali treatment in a low alkali solution to expose the cellulose fiber. Alkali-treated CSF (AT-CSF) was cross-linking modified with chitosan and glutaraldehyde. Then, the untreated CSF (UT-CSF) and the cross-linked modified CSF (CL-CSF) were added to polypropylene (PP) with different contents (10 wt%, 20 wt%, 30 wt%, 40 wt%), respectively. The morphology, mechanical, thermal and water absorption behaviours of WPC were investigated in detail. The results indicated that the crosslinking modification is an efficient method to improve the mechanical properties of WPC. Compared with UT-CSF, the crystallinity index (CrI) of CL-CSF was increased from 33.8% to 39.5%. The cross-linking modification promoted an increase in flexural strength of 19.2% and an increase in flexural modulus of 8.3% compared to the composite reinforced by UT-CSF. The water absorption of the composite reinforced by CL-CSF was lower than the composite reinforced by UT-CSF.

It is well known that an exact image within a region of interest (ROI) can be reconstructed from truncated Radon transforms of odd dimensions. It remains, however, unclear whether exact ROI images can be reconstructed from the truncated n-dimensional (nD) Radon transform, where n ≥ 4 is an even number. In this work, we show that it is possible to reconstruct ROI images exactly from truncated Radon transforms of even dimensions. In particular, based upon our derived formula, two algorithms can be devised for exact reconstruction of ROI images from truncated Radon transforms of even dimensions. This work may find applications in high-dimensional tomographic imaging such as magnetic resonance spectroscopic imaging and electron paramagentic resonance imaging in which the data function can be interpreted as the 4D Radon transform.

We derive accurate and efficient reconstruction algorithms for helical, cone-beam CT that employ shift-invariant filtering. Specifically, a new backprojection-filtration algorithm is developed, and a minimum data filtered-backprojection algorithm is derived. These reconstruction algorithms with shift-invariant filtering can accept data with transverse truncation, and hence allow for minimum data image reconstruction.

In a reduced fan-beam scan, the scanned angular range is smaller than that in a short scan (i.e., a half-scan). In this work, we have developed a new algorithm, which is referred to as the backprojection-filtration (BPF) algorithm, for exact image reconstruction within ROIs from reduced-scan data containing truncations. Explicit conditions on data acquisition have also been derived for exact image reconstruction within an ROI. We have performed a preliminary quantitative study whose results demonstrated and verified the proposed fan-beam BPF algorithm and the derived conditions on data acquisition. The proposed BPF algorithm can have significant implications for clinical and animal CT imaging, therapy imaging, electron paramagnetic resonance imaging and other tomographic imaging because it allows for reconstruction from truncated data and for a potentially drastic reduction of radiation dose and/or of imaging time.

We have recently proposed a general formula (i.e., equations (9) to (11) in Zou and Pan (2004a Phys. Med. Biol. 49 941-59)) for image reconstruction from helical cone-beam data. On the basis of the formula, we have also developed two reconstruction algorithms, which are referred to as the backprojection filtration (BPF) algorithm (Zou and Pan 2004a) and the filtered backprojection (FBP) algorithm (Zou and Pan 2004b Phys. Med. Biol. 49 2717-31), respectively. The two algorithms have been implemented and evaluated in numerical studies. In this note, however, we point out that the data function previously used for proving the general formula in Zou and Pan (2004a) is incomplete and that, instead, an extended data function and its generalized backprojection, which are described in this note, should be used to complete the proof of the general formula. On the other hand, we also demonstrate in this note that the additional term in the extended data function has no effect on the previously developed BPF and FBP algorithms. The results can also be extended to general, smooth trajectories.

A circular scanning trajectory is and will likely remain a popular choice of trajectory in computed tomography (CT) imaging because it is easy to implement and control. Filtered-backprojection (FBP)-based algorithms have been developed previously for approximate and exact reconstruction of the entire image or a region of interest within the image in circular cone-beam and fan-beam cases. Recently, we have developed a 3D FBP-based algorithm for image reconstruction on PI-line segments in a helical cone-beam scan. In this work, we demonstrated that the 3D FBP-based algorithm indeed provided a rather general formulation for image reconstruction from divergent projections (such as cone-beam and fan-beam projections). On the basis of this formulation we derived new approximate or exact algorithms for image reconstruction in circular cone-beam or fan-beam scans, which can be interpreted as special cases of the helical scan. Existing algorithms corresponding to the derived algorithms were identified. We also performed a preliminary numerical study to verify our theoretical results in each of the cases. The results in the work can readily be generalized to other non-circular trajectories.

Recently, there has been much work devoted to developing accurate and efficient algorithms for image reconstruction in helical, cone-beam computed tomography (CT). Little attention, however, has been directed to the effect of physical factors on helical, cone-beam CT image reconstruction. This work investigates the effect of polychromatic x-rays on image reconstruction in helical, cone-beam computed tomography. A pre-reconstruction dual-energy technique is developed to reduce beam-hardening artefacts and enhance contrast in soft tissue.

Weak forbidden transitions are of great interest for plasma diagnostics, but they are sensitive to many factors in theoretical calculations. In earlier work on the intercombination transition using the multiconfiguration Dirac-Hartree-Fock approach for Al+-S4+ ions, a method was developed to eliminate the dependence of the transition rates on the optimization strategy. In this paper, this method is applied to other LS forbidden transitions. For the LS allowed transitions the transition energy normalization can eliminate such a dependence. It is also found that the fine structure splittings corrected by the non-relativistic limit offsets are independent of optimization strategies and are in good agreement with observations. For the high-Z ions, the dependence on strategies is less important and the calculations for all the transitions (E1, E2, M1, M2) are extended to Z = 92. A general scaling formula is adopted to reduce the extensive variation of the rates with respect to the nuclear charge.

The compact physical parameters (μα, Uiα) in multichannel quantum defect theory (MQDT) can be directly calculated with relativistic multichannel theory (RMCT). Here we report a systematic study of the MQDT parameters (μα, Uiα) with RMCT along the Ne-like iso-electronic sequence (including Ca10+, Fe16+, Ge22+, Ag37+ ions). We find that the physical parameters (μα, Uiα) show a very interesting scaling behavior along the iso-electronic sequence.

Based on the relativistic multichannel theory, a non-isolated resonance approach has been developed to calculate the cross sections of dielectronic recombination on He+ for ?n?=?1 and 2 transitions. A first order approximation is adopted for the radiative process. The convolved cross sections for the n???3 states in both transitions are in good agreement with those of the observations. It is shown that the l-dependence of the field ionization and the radiative decay during the time-of-flight affect significantly the measurement of the cross sections near the initial state of the field ionization.

We report an AlGaN channel high electron mobility transistor (HEMT) on a sapphire substrate with a 1000-nm AlxGa1−xN (x = 0−0.18)/GaN composite buffer layer. With a significant improvement of crystal quality, the device features a high product of ns μn. The AlGaN channel HEMTs presented show improved performance with respect to the conventional AlGaN channel HEMTs, including the on-resistance reduced from 31.2 to 8.1 Ωmm, saturation drain current at 2 V gate bias promoted from 218 to 540 mA/mm, peak transconductance at 10 V drain bias promoted from 100 to a state-of-the-art value of 174 mS/mm, and reverse gate leakage current reduced from 1.85 × 10−3 to 2.15 × 10−5 mA/mm at VGD = −20 V.

In the report, the recently developed relativistic multichannel theory (RMCT) is a full relativistic non-perturbative method and can be applied to the high-Z atomic ions which have given rise to some recent interests because of researches of inertial confinement fusion and x-ray laser. Based on the RMCT, the positions and widths of doubly excited sp2n+, sp2n-, and 2pnd1 P1 resonances are calculated, which are in agreement with the recent experimental measurements. It sets up a sound foundation on which the RMCT should be applicable to high Z atomic ions.