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Unmanned aerial vehicles (UAVs) have received widespread attention due to their flexible deployment characteristics. Automated airports equipped with UAVs are expected to become important equipment for improving quality and reducing costs in many inspection scenarios. This paper focuses on the automated inspection business of UAVs dispatched by automated airports in highway scenarios. On the basis of considering the shape of highway curves, inspection targets, and the energy consumption characteristics of UAVs, planning the flight parameters of UAVs is of great significance for ensuring the effectiveness of the inspection process. This paper first sets the inspection path points for the UAV based on highway curves, and then proposes an efficient heuristic method for the nonlinear non-convex parameter optimization problem, through which the parameters of the UAV's inspection altitude, hovering altitude, and flight speed are planned. Simulation and analysis show that the proposed method possesses good parameter planning efficiency. By combining several existing trajectory planning methods, e.g., the traversal method, the deep Q-network based method, and the genetic method, it can be concluded that the proposed method in this paper has better overall planning performance including planning efficiency and inspection effectiveness. [ABSTRACT FROM AUTHOR]

The heritability of litter size in sheep is low and controlled by multiple genes, but the research on its related genes is not sufficient. Here, to explore the expression pattern of multi-tissue genes in Chinese native sheep, we selected 10 tissues of the three adult ewes with the highest estimated breeding value in the early study of the prolific Xinggao sheep population. The global gene expression analysis showed that the ovary, uterus, and hypothalamus expressed the most genes. Using the Uniform Manifold Approximation and Projection (UMAP) cluster analysis, these samples were clustered into eight clusters. The functional enrichment analysis showed that the genes expressed in the spleen, uterus, and ovary were significantly enriched in the Ataxia Telangiectasia Mutated Protein (ATM) signaling pathway, and most genes in the liver, spleen, and ovary were enriched in the immune response pathway. Moreover, we focus on the expression genes of the hypothalamic–pituitary–ovarian axis (HPO) and found that 11,016 genes were co-expressed in the three tissues, and different tissues have different functions, but the oxytocin signaling pathway was widely enriched. To further explore the differences in the expression genes (DEGs) of HPO in different sheep breeds, we downloaded the transcriptome data in the public data, and the analysis of DEGs (Xinggao sheep vs. Sunite sheep in Hypothalamus, Xinggao sheep vs. Sunite sheep in Pituitary, and Xinggao sheep vs. Suffolk sheep in Ovary) revealed the neuroactive ligand–receptor interactions. In addition, the gene subsets of the transcription factors (TFs) of DEGs were identified. The results suggest that 51 TF genes and the homeobox TF may play an important role in transcriptional variation across the HPO. Altogether, our study provided the first fundamental resource to investigate the physiological functions and regulation mechanisms in sheep. This important data contributes to improving our understanding of the reproductive biology of sheep and isolating effecting molecular markers that can be used for genetic selection in sheep. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) technology has permeated into all aspects of today's society and is playing an increasingly important role. Identity authentication is crucial for IoT devices to access the network, because the open wireless transmission environment of the IoT may suffer from various forms of network attacks. The asymmetry in the comprehensive capabilities of gateways and terminals in the IoT poses significant challenges to reliability and security. Traditional encryption-based identity authentication methods are difficult to apply to IoT terminals with limited capabilities due to high algorithm complexity and low computational efficiency. This paper explores physical layer identity identification based on channel state information (CSI) and proposes an intelligent identification method based on deep reinforcement learning (DRL). Specifically, by analyzing and extracting the features of the real received CSI information and a setting low-complexity state, as well as action and reward parameters for the deep neural network of deep reinforcement learning oriented to the scenario, we obtained an authentication method that can efficiently identify identities. The validation of the proposed method using collected CSI data demonstrates that it has good convergence properties. Compared with several existing machine-learning-based identity recognition methods, the proposed method has higher recognition accuracy. [ABSTRACT FROM AUTHOR]

Over the past decade, perovskite technology has been increasingly applied in solar cells, nanocrystals, and light-emitting diodes (LEDs). Perovskite nanocrystals (PNCs) have attracted significant interest in the field of optoelectronics owing to their exceptional optoelectronic properties. Compared with other common nanocrystal materials, perovskite nanomaterials have many advantages, such as high absorption coefficients and tunable bandgaps. Owing to their rapid development in efficiency and huge potential, perovskite materials are considered the future of photovoltaics. Among different types of PNCs, CsPbBr3 perovskites exhibit several advantages. CsPbBr3 nanocrystals offer a combination of enhanced stability, high photoluminescence quantum yield, narrow emission bandwidth, tunable bandgap, and ease of synthesis, which distinguish them from other PNCs, and make them suitable for various applications in optoelectronics and photonics. However, PNCs also have some shortcomings: they are highly susceptible to degradation caused by environmental factors, such as moisture, oxygen, and light, which limits their long-term performance and hinders their practical applications. Recently, researchers have focused on improving the stability of PNCs, starting with the synthesis of nanocrystals and optimizing (i) the external encapsulation of crystals, (ii) ligands used for the separation and purification of nanocrystals, and (iii) initial synthesis methods or material doping. In this review, we discuss in detail the factors leading to instability in PNCs, introduce stability enhancement methods for mainly inorganic PNCs mentioned above, and provide a summary of these approaches. [ABSTRACT FROM AUTHOR]

Millimeter-wave (mmWave) communication is considered a promising technology for fifth-generation (5G) wireless communications systems since it can greatly improve system throughput. Unfortunately, because of extremely high frequency, mmWave transmission suffers from the signal blocking problem, which leads to the deterioration of transmission performance. In this paper, we solve this problem by the combination of ultra-dense network (UDN) and user-centric virtual cell architecture. The deployment of dense small base stations (SBSs) in UDN can reduce transmission distance of signals. The user-centric virtual cell architecture mitigates and exploits interference to improve throughput by using coordinated multipoint (CoMP) transmission technology. Nonetheless, the backhaul burden is heavy and interbeam interference still severe. Therefore, we propose a novel iterative backhaul capacity-limited joint user association and power allocation (JUAPA) scheme in ultra-dense mmWave networks under user-centric virtual cell architecture. To mitigate interference and satisfy quality of service (QoS) requirements of users, a nonconvex system throughput optimization problem is formulated. To solve this intractable optimization problem, we divide it into two alternating optimization subproblems, i.e., user association and power allocation. During each iteration, a many-to-many matching algorithm is designed to solve user association. Subsequently, we perform power allocation optimization using a successive convex approximation (SCA) algorithm. The results confirm that the performance of the proposed scheme is close to that of the exhaustive searching scheme, which greatly reduces complexity, and clearly superior to that of traditional schemes in improving system throughput and satisfying QoS requirements. [ABSTRACT FROM AUTHOR]

Xinggao sheep are a breed of Chinese domestic sheep that are adapted to the extremely cold climatic features of the Hinggan League in China. The economically vital reproductive trait of ewes (litter size, LS) and productive traits of lambs (birth weight, BWT; weaning weight, WWT; and average daily gain, ADG) are expressed in females and later in life after most of the selection decisions have been made. This study estimated the genetic parameters for four traits to explore the genetic mechanisms underlying the variation, and we performed genome-wide association study (GWAS) tests on a small sample size to identify novel marker trait associations (MTAs) associated with prolificacy and growth. We detected two suggestive significant single-nucleotide polymorphisms (SNPs) associated with LS and eight significant SNPs for BWT, WWT, and ADG. These candidate loci and genes also provide valuable information for further fine-mapping of QTLs and improvement of reproductive and productive traits in sheep. [ABSTRACT FROM AUTHOR]

Analysis of urban area function is crucial for urban development. Urban area function features can help to conduct better urban planning and transportation planning. With development of urbanization, urban area function becomes complex. In order to accurately extract function features, researchers have proposed multisource data mining methods that combine urban remote sensing and other data. Therefore, the research of efficient multisource data analysis tools has become a new hot topic. In this paper, a novel urban data analysis method combining spatiotemporal wireless network data and remote sensing data was proposed. First, a Voronoi-diagram-based method was used to divide the urban remote sensing images into zones. Second, we combined period and trend components of wireless network traffic data to mine urban function structure. Third, for multisource supported urban simulation, we designed a novel spatiotemporal city computing method combining graph attention network (GAT) and gated recurrent unit (GRU) to analyze spatiotemporal urban data. The final results prove that our method performs better than other commonly used methods. In addition, we calculated the commuting index of each zone by wireless network data. Combined with the urban simulation conducted in this paper, the dynamic changes of urban area features can be sensed in advance for a better sustainable urban development. [ABSTRACT FROM AUTHOR]

Optical images are rich in spectral information, but difficult to acquire under all-weather conditions, while SAR images can overcome adverse meteorological conditions, but geometric distortion and speckle noise will reduce the quality of SAR images and thus make image interpretation more challenging. Therefore, transforming SAR images to optical images to assist SAR image interpretation will bring opportunities for SAR image application. With the advancement of deep learning technology, the ability of SAR-to-optical transformation has been greatly improved. However, most of the current mainstream transformation methods do not consider the imaging characteristics of SAR images, and there will be failures such as noisy color spots and regional landform deformation in the generated optical images. Moreover, since the SAR image itself does not contain color information, there also exist many color errors in these results. Aiming at the above problems, Sar2color, an end-to-end general SAR-to-optical transformation model, is proposed based on a conditional generative adversarial network (CGAN). The model uses DCT residual block to reduce the effect of coherent speckle noise on the generated optical images, and constructs the Light atrous spatial pyramid pooling (Light-ASPP) module to mitigate the negative effect of geometric distortion on the generation of optical images. These two designs ensure the precision of texture details when the SAR image is transformed into an optical image, and use the correct color memory block (CCMB) to improve the color accuracy of transformation results. Towards the Sar2color model, we have carried out evaluations on the homologous heterogeneous SAR image and optical image pairing dataset SEN1-2. The experimental results show that, compared with other mainstream transformation models, Sar2color achieves the state-of-the-art effect on all three objective and one subjective evaluation metrics. Furthermore, we have carried out various ablation experiments, and the results show the effectiveness of each designed module of Sar2color. [ABSTRACT FROM AUTHOR]

The mechanism of strong mine pressure control in the initial mining and caving stages under multiple key strata (MKS) was studied by theoretical analysis, numerical simulation and field measurement in order to avoid the dynamic pressure accidents caused by the MKS breaking in interactions in the initial mining and caving stage. Panel 13103 (P13103) in the Shan Xi Jinshen Shaping Coal Mine was used sas the study site. The overlying structure and the breaking characteristics of the key strata were analyzed and the overlying structure model of longwall top-coal caving (LTC) under MKS was established. Reasonable initial mining heights and initial caving positions were determined and the spatial and temporal characteristics of ground pressure and roof structure of the working face in the mining process were obtained. The results show that, in the scheme of starting top-coal caving after the working face advanced 20 m, the support damage ratios were all greater than 50% with roof weighting, which is prone to induce prop crash accidents. The dynamic load formed by the second weighting was greater than first weighting under the MKS. The duration of mine pressure tended to be stable with fully developed caving zone heights. With the designed mining scheme, the safe and efficient mining of P13103 is guaranteed. [ABSTRACT FROM AUTHOR]

In this paper, an online compensation method of phase delay error based on a Phase-Frequency (P-F) characteristic has been proposed for MEMS Coriolis Vibratory Gyroscopes (CVGs). At first, the influences of phase delay were investigated in the drive and sense mode. The frequency response was acquired in the digital control system by collecting the demodulation value of drive displacement, which verified the existence and influence of the phase delay. In addition, based on the P-F characteristic, that is, when the phase shift of the nonresonant drive force through the resonator is almost 0° or 180°, the phase delay of the gyroscope is measured online by injecting a nonresonant reference signal into the drive-mode dynamics. After that, the phase delay is self-corrected by adjusting the demodulation phase angle without affecting the normal operation of the gyroscopes. The approach was validated with an MEMS dual-mass vibratory gyroscope under double-loop force-to-rebalance (in-phase FTR and quadrature FTR) closed-loop detection mode and implemented with FPGA. The measurement results showed that this scheme can detect and compensate phase delay to effectively eliminate the effect of the quadrature error. This technique reduces the zero rate output (ZRO) from −0.71°/s to −0.21°/s and bias stability (BS) from 23.30°/h to 4.49°/h, respectively. The temperature sensitivity of bias output from −20 °C to 40 °C has reached 0.003 °/s/°C. [ABSTRACT FROM AUTHOR]

Liquid crystal display (LCD) is a display device based on liquid crystal electro-optic effect, and LCDs have gradually appeared and have become an indispensable part of people's lives. In the development of LCD technology, the detection of Mura defects is a key concern in the manufacturing process. The Mura defect is a kind of display defect with low contrast and an irregular shape. This study first explains the mechanism of Mura defects in the LCD manufacturing process and classifies typical Mura defects. Then, three main purposes for the defect detection of LCDs are compared, and the advantages and disadvantages are conducted. Following that, this research examines reviews the linked literature on image preprocessing, feature extraction, dimension reduction, and classifiers of Mura defects. Finally, the future development trend and research direction of Mura defect detection based on machine vision can be drawn by this study. [ABSTRACT FROM AUTHOR]

When the water droplets are on some superhydrophobic surfaces, the surface only needs to be inclined at a very small angle to make the water droplets roll off. Hence, building a superhydrophobic surface on the material substrate, especially the metal substrate, can effectively alleviate the problems of its inability to resist corrosion and easy icing during use, and it can also give it special functions such as self-cleaning, lubrication, and drag reduction. Therefore, this study reviews and summarizes the development trends in the fabrication of superhydrophobic surface materials by non-traditional processing techniques. First, the principle of the superhydrophobic surfaces fabricated by laser beam machining (LBM) is introduced, and the machining performances of the LBM process, such as femtosecond laser, picosecond laser, and nanosecond laser, for fabricating the surfaces are compared and summarized. Second, the principle and the machining performances of the electrical discharge machining (EDM), for fabricating the superhydrophobic surfaces, are reviewed and compared, respectively. Third, the machining performances to fabricate the superhydrophobic surfaces by the electrochemical machining (ECM), including electrochemical oxidation process and electrochemical reduction process, are reviewed and grouped by materials fabricated. Lastly, other non-traditional machining processes for fabricating superhydrophobic surfaces, such as ultrasonic machining (USM), water jet machining (WJM), and plasma spraying machining (PSM), are compared and summarized. Moreover, the advantage and disadvantage of the above mentioned non-traditional machining processes are discussed. Thereafter, the prospect of non-traditional machining for fabricating the desired superhydrophobic surfaces is proposed. [ABSTRACT FROM AUTHOR]

Lévy flights random walk is one of key parts in the cuckoo search (CS) algorithm to update individuals. The standard CS algorithm adopts the constant scale factor for this random walk. This paper proposed an improved beta distribution cuckoo search (IBCS) for this factor in the CS algorithm. In terms of local characteristics, the proposed algorithm makes the scale factor of the step size in Lévy flights showing beta distribution in the evolutionary process. In terms of the overall situation, the scale factor shows the exponential decay trend in the process. The proposed algorithm makes full use of the advantages of the two improvement strategies. The test results show that the proposed strategy is better than the standard CS algorithm or others improved by a single improvement strategy, such as improved CS (ICS) and beta distribution CS (BCS). For the six benchmark test functions of 30 dimensions, the average rankings of the CS, ICS, BCS, and IBCS algorithms are 3.67, 2.67, 1.5, and 1.17, respectively. For the six benchmark test functions of 50 dimensions, moreover, the average rankings of the CS, ICS, BCS, and IBCS algorithms are 2.83, 2.5, 1.67, and 1.0, respectively. Confirmed by our case study, the performance of the ABCS algorithm was better than that of standard CS, ICS or BCS algorithms in the process of EDM. For example, under the single-objective optimization convergence of MRR, the iteration number (13 iterations) of the CS algorithm for the input process parameters, such as discharge current, pulse-on time, pulse-off time, and servo voltage, was twice that (6 iterations) of the IBCS algorithm. Similar, the iteration number (17 iterations) of BCS algorithm for these parameters was twice that (8 iterations) of the IBCS algorithm under the single-objective optimization convergence of Ra. Therefore, it strengthens the CS algorithm's accuracy and convergence speed. [ABSTRACT FROM AUTHOR]

Lead(II)-acetate (Pb(Ac)2) is a promising lead source for the preparation of organolead trihalide perovskite materials, which avoids the use of inconvenient anti-solvent treatment. In this study, we investigated the effect of cesium doping on the performance of Pb(Ac)2-based perovskite solar cells (PSCs). We demonstrate that the quality of the CH3NH3PbI3 perovskite film was improved with increased crystallinity and reduced pinholes by doping the perovskite with 5 mol% cesium. As a result, the power conversion efficiency (PCE) of the PSCs was improved from 14.1% to 15.57% (on average), which was mainly induced by the significant enhancements in short-circuit current density and fill factor. A PCE of 18.02% was achieved for the champion device of cesium-doped Pb(Ac)2-based PSCs with negligible hysteresis and a stable output. Our results indicate that cesium doping is an effective approach for improving the performance of Pb(Ac)2-based PSCs. [ABSTRACT FROM AUTHOR]

In order to improve the general problem of irregular coating morphology and low mechanical strength of the coating layer in existing coating desensitization technology, nano-cyclotrimethylene trinitramine/melamine-urea-formaldehyde (RDX/MUF) composite energetic microspheres were prepared by an improved emulsion polymerization, taking the MUF as the binder and RDX as the main explosive. In order to judge whether RDX/MUF possessed good stability, the combination of differential scanning calorimetry (DSC) and molecular dynamics (MD) simulation was used to determine the level of binding binding energy between urea-formaldehyde resin binder (UF) and RDX. In addition, to investigate the optimal reaction temperature for the preparation of MUF/RDX, the binding energy between UF and RDX at different temperatures was simulated. And then the morphology and thermal properties of the as-prepared composite energetic microspheres were analyzed by scanning electron microscopy (SEM) and DSC, the impact sensitivity and friction sensitivity of the resultant samples were tested as well. Moreover, RDX/MUF with the same MUF content was prepared by physical mixing for comparative analysis. MD simulation demonstrated that UF and RDX possessed good binding ability at 298 K. The DSC method indicatec that UF and RDX had good compatibility, and the comprehensive performance of RDX after coating was not significantly deteriorated; The optimal binding temperature between UF and RDX was 60~70 °C which is consistent with the experimental results. The experimental results showed that the optimum process conditions for the preparation of RDX/MUF could be listed as follows: the temperature for preparing RDX/MUF composite energetic microspheres by the improved emulsion polymerization was 70 °C the optimal pH value of the urea-formaldehyde resin prepolymer solution was 3, and the optimal melamine-urea molar ratio was 0.4. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC) patients carrying an epidermal growth factor receptor (EGFR) mutation are initially sensitive to EGFR-tyrosine kinase inhibitors (TKIs) treatment, but soon develop an acquired resistance. The treatment effect of EGFR-TKIs-resistant NSCLC patients still faces challenges. Cucurbitacin B (CuB), a triterpene hydrocarbon compound isolated from plants of various families and genera, elicits anticancer effects in a variety of cancer types. However, whether CuB is a viable treatment option for gefitinib-resistant (GR) NSCLC remains unclear. Here, we investigated the anticancer effects and underlying mechanisms of CuB. We report that CuB inhibited the growth and invasion of GR NSCLC cells and induced apoptosis. The inhibitory effect of CuB occurred through its promotion of the lysosomal degradation of EGFR and the downregulation of the cancerous inhibitor of protein phosphatase 2A/protein phosphatase 2A/Akt (CIP2A/PP2A/Akt) signaling axis. CuB and cisplatin synergistically inhibited tumor growth. A xenograft tumor model indicated that CuB inhibited tumor growth in vivo. Immunohistochemistry results further demonstrated that CuB decreased EGFR and CIP2A levels in vivo. These findings suggested that CuB could suppress the growth and invasion of GR NSCLC cells by inducing the lysosomal degradation of EGFR and by downregulating the CIP2A/PP2A/Akt signaling axis. Thus, CuB may be a new drug candidate for the treatment of GR NSCLC. [ABSTRACT FROM AUTHOR]

The activation of telomerase is one of the key events in the malignant transition of cells, and the expression of human telomerase reverse transcriptase (hTERT) is indispensable in the process of activating telomerase. The pre-mRNA alternative splicing of hTERT at the post-transcriptional level is one of the mechanisms for the regulation of telomerase activity. Shifts in splicing patterns occur in the development, tumorigenesis, and response to diverse stimuli in a tissue-specific and cell type-specific manner. Despite the regulation of telomerase activity, the alternative splicing of hTERT pre-mRNA may play a role in other cellular functions. Modulating the mode of hTERT pre-mRNA splicing is providing a new precept of therapy for cancer and aging-related diseases. This review focuses on the patterns of hTERT pre-mRNA alternative splicing and their biological functions, describes the potential association between the alternative splicing of hTERT pre-mRNA and telomerase activity, and discusses the possible significance of the alternative splicing of the hTERT pre-mRNA in the diagnosis, therapy, and prognosis of cancer and aging-related diseases.