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Abstract In this paper, we discuss the fractional p ( x , ⋅ ) $p(x,\cdot )$ -Kirchhoff-type equations M ( ∫ R N × R N 1 p ( x , y ) | u ( x ) − u ( y ) | p ( x , y ) | x − y | N + s p ( x , y ) d x d y ) ( − Δ p ( x , . ) ) s u + | u | p ¯ ( x ) − 2 u = f ( x , u ) . $$ M\left (\int _{\mathbb{R}^{N}\times \mathbb{R}^{N}} \frac{1}{p(x,y)} \frac{|u(x)-u(y)|^{p(x,y)}}{|x-y|^{N+sp(x,y)}}dxdy\right )(-\Delta _{p(x,.)})^{s} u+|u|^{\bar{p}(x)-2}u=f(x,u).$$ We weaken the conditions on the nonlinear term f and get the existence and multiplicity of solutions via variational methods, which improves some previous results.

Trajectory prediction serves as a prerequisite for future trajectory-based operation, significantly reducing the uncertainty of aircraft movement information within airspace by scientifically forecasting the three-dimensional positions of aircraft over a certain period. As convergence points in the aviation network, airport terminal airspace exhibits the most complex traffic conditions in the entire air route network. It has stronger mutual influences and interactions among aircraft compared to the en-route phase. Current research typically uses the trajectory time series information of a single aircraft as input for subsequent predictions. However, it often lacks consideration of the close-range spatial interactions between multiple aircraft in the terminal airspace. This results in a gap in the study of aircraft trajectory prediction that couples spatiotemporal features. This paper aims to predict the four-dimensional trajectories of aircraft in terminal airspace, constructing a Spatio-Temporal Transformer (ST-Transformer) prediction model based on temporal and spatial attention mechanisms. Using radar aircraft trajectory data from the Guangzhou Baiyun Airport terminal airspace, the results indicate that the proposed ST-Transformer model has a smaller prediction error compared to mainstream deep learning prediction models. This demonstrates that the model can better integrate the temporal sequence correlation of trajectory features and the potential spatial interaction information among trajectories for accurate prediction.

Path planning is one of the core issues in the autonomous navigation of an Unmanned Surface Vehicle (USV), as the accuracy of the results directly affects the safety of the USV. Hence, this paper proposes a USV path planning algorithm that integrates an improved Particle Swarm Optimisation (PSO) algorithm with a Dynamic Window Approach (DWA). Firstly, in order to advance the solution accuracy and convergence speed of the PSO algorithm, a nonlinear decreasing inertia weight and adaptive learning factors are introduced. Secondly, in order to solve the problem of long path and path non-smoothness, the fitness function of PSO is modified to consider both path length and path smoothness. Finally, the International Regulations for Preventing Collisions at Sea (COLREGS) are utilised to achieve dynamic obstacle avoidance while complying with maritime practices. Numerical cases verify that the path planned via the proposed algorithm is shorter and smoother, guaranteeing the safety of USV navigation while complying with the COLREGS.

Given the pressing requirements for sustainable development in civil aviation, conducting a synergistic evolution analysis of the supply and demand aspects in the airport green development holds great significance. This analysis helps achieve sustainable airport development and facilitates the green transformation of civil aviation development. Taking a collaborative learning approach and utilizing historical data from Guangzhou Baiyun International Airport spanning 2008 to 2019, the supply-demand composite system for airport green development was deconstructed into two subsystems-demand and supply-and relevant evaluation index systems were established in this paper. A screening and optimization model of supply and demand synergy indicators for airport green development was constructed, and it was solved using a simulated annealing genetic algorithm. The Haken model was constructed to analyze the synergistic evolutionary relationship of the composite system of supply and demand for green airport development in two stages. The results indicate a shift in the order parameter of the co-evolution of the supply-demand composite system at Guangzhou Baiyun International Airport, moving from the demand subsystem in the first stage (2008-2015) to the supply subsystem in the second stage (2016-2019). The co-evolution of the airport supply-demand composite system has entered a new stage, but has not reached a high level of synergy. The study not only contributes theoretically by explaining the interaction mechanism between supply and demand for airport green development, but also offers targeted suggestions for achieving high-quality synergistic evolution of supply and demand for airport green development.

The powersphere is a spherical enclosed receiver composed of multiple photovoltaic cells. It serves as a replacement for traditional photovoltaic panels in laser wireless power transmission systems for optoelectronic conversion. The ideal powersphere aims to achieve a uniform distribution of light within the cavity through infinite reflections, reducing energy losses in the circuit. However, due to the high absorption rate of the photovoltaic cells, the direct irradiation area on the inner surface of the powersphere exhibits a significantly higher light intensity than the reflected area, resulting in a suboptimal level of light uniformity and certain circuit losses. To address the aforementioned issues, a method of intra-cavity beam splitting in the powersphere is proposed. This solution aims to increase the area of direct illumination and reduce the intensity difference between direct and reflected lights, thereby improving the light uniformity on the inner surface of the powersphere. Utilizing the transformation matrix of Gaussian beams, the q parameters for each optical path with beam splitting were calculated, and the equality of corresponding q values was demonstrated. Further, based on the q parameter expression for the electric field of Gaussian beams, the intensities for each optical path were calculated, and it was demonstrated that their values are equal. Additionally, an optical software was utilized to establish a model for intra-cavity beam splitting in the powersphere. Based on this model, a beam-splitting system was designed using a semi-transparent and semi-reflective lens as the core component. The light uniformity performance of the proposed system was analyzed through simulations. To further validate the effectiveness of the calculations, design, and simulations, multiple lenses were employed to construct the beam-splitting system. An experimental platform was set up, consisting of a semiconductor laser, monocrystalline silicon photovoltaic cells, beam expander, Fresnel lens, beam-splitting system, and powersphere. An experimental verification was conducted, and the results aligned with the theoretical calculations and simulated outcomes. The above theory, simulations, and experiments demonstrate that the intra-cavity beam-splitting method effectively enhances the optical uniformity within the powersphere.

We investigate the propagation properties of circular Airy beams (CABs) with propagational fractional-order optical vortices (OVs). The superposition of the phase singularity and polarization singularity from a vortex vector beam (VVB) plays a significant role in creating a propagational fractional vortex beam. Propagational fractional vortex beams can be considered as a superposition of left and right circularly polarized vortex beams with different integer topological charges (TCs). We study the propagation characteristics of two kinds of propagational fractional vortex CABs, and the results show that both of the two kinds of beams can stably propagate in free space, and they exhibit an “abruptly auto-focusing” property and “self-healing” property during the propagation. The intensity distribution of the first kind of propagational fractional vortex CAB has an odd number of petals (2m + 1), while the second kind of beam has a crescent-shaped intensity distribution. The influence of turbulence on the beam propagation through atmosphere under different turbulence strengths is also numerically studied in this paper. A fractional vortex CAB with an initial radius r0 = 10 mm can retain its shape after propagating 20 m when the atmospheric refractive-index structure constant CN2=0.2×10−12m−2/3. Our results are expected to broaden the application of CABs.

Objective To evaluate the feasibility, safety, and efficacy of high-intensity focused ultrasound (HIFU) and microwave ablation (MWA) for the treatment of small liver metastatic tumors. Methods Fifty-eight patients with small liver metastatic tumors who underwent HIFU (n = 28) or MWA (n = 30) at Suining Central Hospital between January 2016 and December 2021 were retrospectively evaluated. Demographic and clinical characteristics were compared between the two groups. Results Operation times were longer and hospitalization costs were lower in the HIFU group than in the MWA group. Postoperative hospitalization times, tumor ablation rates, and clinical response and control rates did not differ significantly between the two groups 1 month after surgery. Rates of postoperative complications such as fever, liver dysfunction, injury, pain, and biliary leakage did not differ between the two groups. The 1- and 3-year cumulative survival rates were 96.4% and 52.4%, respectively, after HIFU and 93.3% and 51.4%, respectively, after MWA, which did not represent significant differences. Conclusions HIFU is a safe and feasible method of treating small liver metastatic tumors. Compared with MWA, HIFU was associated with lower hospitalization costs, reduced trauma, and fewer postoperative complications, making it a promising new local ablative treatment option for liver metastatic tumors.

Summary: The cement industry is one of the largest contributors to global CO2 emissions, which has been paid more attention to the research on converting the CO2 released by the cement production process. It is extremely challenging to decarbonize the cement industry, as most CO2 emissions result from the calcination of limestone (CaCO3) into CaO and CO2. In this work, we demonstrate an in situ electrochemical process that transforms CaCO3 into portlandite (Ca(OH)2, a key Portland cement precursor) and valuable carbonaceous products, which integrates electrochemical water splitting and CO2 reduction reaction with the chemical decomposition of CaCO3. With different metal catalyst electrodes (like Au, Ag, In, Cu, and Cu nanowires electrodes), we have achieved various valuable carbonaceous products, such as CO, formate, methane, ethylene, and ethane during the electrochemical CO2 process. Our work demonstrates a proof of concept for green and sustainable cement production.

Zhongshuang 11 (ZS11) is an elite inbred rapeseed (Brassica napus L.) cultivar widely planted in the Yangtze River basin for its favorable characteristics including high seed oil content (SOC), low seed glucosinolate content (SGC), long siliques, and stable yield. To transfer the ideal traits from ZS11 into 195-14A, a Polima (pol)-type cytoplasmic male sterile line with high general combining ability, a doubled haploid population derived from the cross of ZS11 and 195-14A was developed. Based on this population, a high-density genetic linkage map covering 2553 cM with an average marker interval of 0.81 cM, was constructed using the Brassica 60K SNP array and simple sequence repeats. In seven environments, 64, 29, 35, 37, and 33 QTL were identified for silique length, seeds per silique, seed density per silique, SOC, and SGC, respectively. Most favorable alleles were from ZS11. Seventy-one consensus QTL were identified by a QTL meta-analysis, eight of which (cqSL–A9–2, cqSL–C7, cqSGC–C2, cqSOC–A5–2, cqSOC–A5–3, cqSPS–A6–2, cqSPS–A7–2, and cqSDPS–A9–2) were assigned as major QTL. Comparative genomics and expression analysis predicted 72 candidate genes underlying the 21 consensus QTL for the five traits. These findings suggest the genetic basis of the superior performance of ZS11 and suggest favorable alleles for development of cultivars with improved yield and quality. These results will assist in cloning these promising alleles in the future.

There are three main challenges to improving sclerotinia stem rot (SSR) resistance in rapeseed (Brassica napus L.). First, breeding materials such as the backbone parents have not been extensively investigated, making the findings of previous studies difficult to directly implement. Second, SSR resistance and flowering time (FT) loci are typically linked; thus, use of these loci requires sacrifice of the rapeseed growth period. Third, the SSR resistance loci in susceptible materials are often neglected, thereby reducing the richness of resistant resources. This study was conducted to investigate the stem resistance, disease index, and FT of a doubled haploid population consisting of 151 lines constructed from the backbone parent 19514A and conventional rapeseed cultivar ZY50 within multiple environments. Quantitative trait locus (QTL) mapping revealed 13 stem resistance QTLs, 9 disease index QTLs, and 20 FT QTLs. QTL meta-analysis showed that uqA04, uqC03.1, and uqC03.2 were repeatable SSR resistance QTLs derived from different parents but not affected by the FT. Based on these three QTLs, we proposed a strategy for improving the SSR resistance of 19514A and ZY50. This study improves the understanding of the resistance to rapeseed SSR and genetic basis of FT and demonstrates that SSR resistance QTLs can be mined from parents with a minimal resistance level difference, thereby supporting the application of backbone parents in related research and resistance improvement.

The control performance of quadrotor unmanned aerial vehicles (UAVs) in complex environments can be affected by external disturbances and other factors. In this paper, an adaptive neural network backstepping controller based on the barrier Lyapunov function (BLF) is designed for a quadrotor UAV with internal uncertainties, input–output constraints and external disturbances. Radial basis function neural networks are used to approximate the uncertainties in the dynamic model of the UAV, while the minimum parameter learning method is combined to accelerate the adjustment speed of neural network weights. A robust term is designed to balance the total system disturbance and improve the anti-interference performance. The BLF is used to handle the output constraint so that the constrained parameters cannot break the predefined constraints. An auxiliary system is introduced to solve input saturation and avoid the dependence of tracking error on the input amplitude in the method of approximating input saturation using the smoothing function. The stability of the control system is demonstrated by the Lyapunov method. The simulation results show that the proposed method has high tracking accuracy compared with the backstepping dynamic surface control method, and the input and output are in the predefined range.

Laser wireless power transmission (WPT) is one of the most important technologies in the field of long-range power transfer. This technique uses a laser as a transmission medium instead of conventional physical or electrical connections to perform WPT. It has the characteristics of long transmission distance and flexible operation. The existing laser wireless power transmission system uses photovoltaic cells as a receiver, which convert light into electricity. Due to the contradiction between the Gaussian distribution of laser and the uniform illumination requirements of photovoltaic cells, the laser wireless power transmission technology has problems such as low transmission efficiency and small output power. Therefore, understanding the energy distribution changes in the laser during transmission, especially the energy change after the laser is transmitted to each key device, and analyzing the influencing factors of the energy distribution state, are of great significance in improving the transmission efficiency and reducing the energy loss in the system. This article utilizes the optical software Lighttools as a tool to establish a laser wireless power transmission model based on a powersphere. This model is used to study the energy distribution changes in the laser as it passes through various components, and to analyze the corresponding influencing factors. To further validate the simulation results, an experimental platform was constructed using a semiconductor laser, beam expander, Fresnel lens, and powersphere as components. A beam quality analyzer was used to measure and analyze the laser energy distribution of each component except for the powersphere. The output voltage and current values of various regions of the powersphere were measured using a multimeter. The energy distribution of the powersphere was reflected based on the linear relationship between photo-generated current, voltage, and light intensity. The experimental results obtained were in good agreement with the simulation results. Simulations and experiments have shown that using a beam expander can reduce divergence angle and energy loss, while employing large-aperture focusing lens can enhance energy collection and output power, providing a basis for improving the efficiency of laser wireless power transfer.

Cystic adenomyosis is a rare type of uterine adenomyosis, mainly seen in young women, which is often characterized by severe dysmenorrhea. The quality of life and reproductive function of young women could be affected by misdiagnosis and delayed treatment. At present, there are no universal guidelines and consensus. We report two cases of patients with cystic adenomyosis in juveniles treated with high-intensity focused ultrasound (HIFU) ablation. In the first case, magnetic resonance imaging (MRI) indicated a cystic mass of 2.0 cm × 3.1 cm × 2.4 cm in the uterus. After she underwent HIFU treatment, her pelvic MRI showed a mass of 1.1 × 2.4 cm in size, and her dysmenorrhea symptoms gradually disappeared. In the second case, a pelvic MRI indicated a 5.1 cm × 3.3 cm × 4.7 cm cystic mass in the uterus. After she underwent HIFU and combined four consecutive cycles of GnRH-a treatment, the lesion shrunk 1.2 cm ×1.4 cm × 1.6 cm, without dysmenorrhea. Simultaneously, the report reviewed 14 cases of juvenile cystic adenomyosis over the last ten years. HIFU or HIFU-combined drugs were safe and effective in treating juvenile cystic adenomyosis, but multicenter and prospective studies may be necessary to validate this in the future.

Abstract Since the conception of pedagogical agents in multimedia environments, researchers have advocated for agents to be designed to exhibit social cues that prime the social interaction of the target audience. One powerful social cue has been agent gesturing. While most agents are created only to use deictic (pointing) gestures, there is recent evidence that agents that perform all gesture types (iconic, metaphoric, deictic, and beat) with enhanced frequency help foreign language users learn more procedural knowledge. Therefore, this research examines how all gesture types and different frequencies influence agent persona and learning outcomes when foreign language users learn declarative knowledge. The results indicated that the use of gestures, regardless of frequency, significantly increase agent persona. However, gesture frequency produced conflicting learning outcomes. While enhancing gestures were beneficial for cued recall and recognition, the average gesture condition was not, which indicates that the strength of social cues is important.

Surface frustrated Lewis pairs (SFLPs) provide a unique class of active sites that enable efficient gas-phase CO2 photocatalysis. How to tailor the reactivity of the SFLPs represents a major challenge, which the authors address here by single-site Bi3+ ion substitution of the SFLPs.

Abstract In order to evaluate the airport's comprehensive service capabilities, this paper considers the impact of air quality and noise on the airport environment under the big data of air traffic activities. In this study, the concept of environmental traffic capacity and big data are applied to the air traffic field. Recently, the airport air and noise pollution has been widely investigated and has become one of the major concerns of the potentially exposed people. This study explores the usage of governmental ambient air quality and noise standards to evaluate the airport operation capacities in the context of the era of big data. The first step is to analyze the typical airport operation scenario as the evaluation scenario. The second step is to use the air and noise emission assessment model for calculating the airport maximum air pollutant concentration and noise level. The final step is to establish a complete airport environment traffic capacity (AETC) evaluation process. As a case study, the capacity evaluation of Nanjing Lukou international airport (NKG) is performed using the above steps. In this case, significant associations between the pollutant concentrations/noise level and the air traffic volume were observed. The AETC of NKG was calculated with the established evaluation process successfully. The results show that the NKG maximum hourly air traffic volume is 120, daily air traffic volume is 770, and annual air traffic volume is 365,805, meeting the China Ambient Air Quality and Noise Standards. Although different air pollutants were investigated in this research, only the NO x was found to be the species that approaching the China governmental standards in this case. Thus, the airport NO x concentration was selected as the AETC limitation factor.

Abstract The multiplicity of homoclinic solutions is obtained for a class of the p-Laplacian Hamiltonian systems d d t ( | u ˙ ( t ) | p − 2 u ˙ ( t ) ) − a ( t ) | u ( t ) | p − 2 u ( t ) + ∇ W ( t , u ( t ) ) = 0 $\frac{d}{dt}(|\dot{u}(t)|^{p-2}\dot{u}(t))-a(t)|u(t)|^{p-2}u(t)+ \nabla W(t,u(t))=0$ via variational methods, where a ( t ) $a(t)$ is neither coercive nor bounded necessarily and W ( t , u ) $W(t,u)$ is under new concave–convex conditions. Recent results in the literature are generalized even for p = 2 $p=2$ .

For the current development of green civil aviation, this study aims to optimize the green four-dimensional (4D) trajectory of commercial flight by taking into account conventional cost and environmental cost. Some fundamental models, efficient processing methodologies, and conventional objectives are proposed to construct the framework of trajectory optimization. Based on the environmental cost including greenhouse gas cost and harmful gas cost, green objective functions are presented. The $\text{A}^\ast $ algorithm and the trapezoidal collocation method are employed to optimize the lateral path and vertical profile for 4D optimization trajectory generation. A case study for the A320 from Barcelona Airport to Frankfurt Airport yields the results that the optimal costs can be obtained under different objectives and the total cost can be more optimized by adjusting the weights of environmental cost and conventional cost. The study builds an aided tool for 4D trajectory optimization and demonstrates that environmental factors and conventional factors should be taken into comprehensive consideration when constructing the flight trajectory in the future, as well as it can underpin the green and sustainable development of the air transport industry.

U1 snRNP is a key regulator of mRNA biogenesis through its roles in splicing, and transcription and 3’-end processing. Here the authors show a tumor suppressor-like function of U1 snRNP using in vitro cell migration/invasion assays and transcriptome profiling.

Cisplatin (DDP) is a commonly used chemotherapy drug, but DDP can cause skeletal muscle atrophy and cachexia. This study combined the DDP-induced C2C12 myotube atrophy model and the LLC tumour-bearing mouse cachexia model under DDP treatment to explore the effect and mechanism of naringenin (NAR) in alleviating skeletal muscle atrophy and cachexia. NAR alleviated the decreases in body weight, food intake, muscle, adipose tissue and kidney weight and forelimb grip strength in LLC tumour-bearing mice under DDP treatment and reduced the serum level of TNF-α. High dose NAR also enhanced the antitumour effect of DDP. NAR can prevent the cross-sectional area reduction of skeletal muscle fibres and prevent the change in fibre type ratio induced by DDP. NAR intervention inhibits the RIPK1/AMPK/NF-κB pathway in skeletal muscle, downregulates the expression of Atrogin1 and MuRF1, and inhibits the degradation of skeletal muscle protein. In C2C12 myotubes treated with DDP, NAR inhibited the RIPK1/AMPK/NF-κB pathway to reduce myotube cell atrophy, and the overexpression of RIPK1 reversed the therapeutic effect of NAR. These results indicate that NAR downregulates the expression of Atrogin1 and MuRF1 by regulating the RIPK1/AMPK/NF-κB pathway and alleviates DDP-induced skeletal muscle atrophy.

Predicting flight delays plays a critical role in reducing financial losses and increasing passenger satisfaction. Due to their ability to combine multiple algorithms, ensemble methods have demonstrated strong predictive performance in many research fields. In this paper, ensemble methods are adopted to predict flight delays. First, based on the current studies, two novel explanatory variables, named arrival/departure pressure and cruise pressure, are proposed as factors affecting flight delays. Second, we introduce the ensemble methods and select representative algorithms for the prediction problem. In addition to the ensemble methods, classical algorithms are also used to predict flight delays. Finally, the actual operational data of Beijing Capital International Airport were utilized to conduct a case study. The results show that the stacking method has better prediction performance than other baseline methods. The mean absolute error (MAE) of the stacking method was about 12.58 min on the test dataset. Furthermore, we tested the effect of the two explanatory variables proposed in this paper, and the results show that the MAE was reduced by about 20% by using the stacking method.

Abstract Two-dimensional (2D) materials are of considerable interest for catalyzing the heterogeneous conversion of CO2 to synthetic fuels. In this regard, 2D siloxene nanosheets, have escaped thorough exploration, despite being composed of earth-abundant elements. Herein we demonstrate the remarkable catalytic activity, selectivity, and stability of a nickel@siloxene nanocomposite; it is found that this promising catalytic performance is highly sensitive to the location of the nickel component, being on either the interior or the exterior of adjacent siloxene nanosheets. Control over the location of nickel is achieved by employing the terminal groups of siloxene and varying the solvent used during its nucleation and growth, which ultimately determines the distinct reaction intermediates and pathways for the catalytic CO2 methanation. Significantly, a CO2 methanation rate of 100 mmol gNi−1 h−1 is achieved with over 90% selectivity when nickel resides specifically between the sheets of siloxene.

Face super-resolved (SR) images aid human perception. The state-of-the-art face SR methods leverage the spatial location of facial components as prior knowledge. However, it remains a great challenge to generate natural textures. In this paper, we propose a component semantic prior guided generative adversarial network (CSPGAN) to synthesize faces. Specifically, semantic probability maps of facial components are exploited to modulate features in the CSPGAN through affine transformation. To compensate for the overly smooth performance of the generative network, a gradient loss is proposed to recover the high-frequency details. Meanwhile, the discriminative network is designed to perform multiple tasks which predict semantic category and distinguish authenticity simultaneously. The extensive experimental results demonstrate the superiority of the CSPGAN in reconstructing photorealistic textures.

The flow corridor is a tube-shape class of airspace designed for the future air transportation system, which aims to reduce complexity, restructuring the airspace to provide more system capacity. In order to support operational procedures design towards increased operational efficiency in the flow corridor, an accurate assessment of alternative procedures is a pre-requisite. This paper proposes a dynamic stochastic simulation framework including various microscopic behaviors for the assessment of distributed self-separation procedures for the air traffic in flow corridors. We first specify three prominent self-separation modes which distinguish flow corridors from today's airways system, and present detailed self-separation procedures and algorithms in a parallel-lane flow corridor incorporating self-separating, lane-passing and lane-switch behaviors based on the aircraft dynamic model and the proportional derivative control theory. Then, incorporating these self-separation algorithms, a dynamic stochastic simulation modeling framework is constructed to assess and compare the alternative distributed self-separation procedures. The framework is applied to a parallel-lane flow corridor deployed from Beijing nearby airports (ZBAA, ZBTJ and ZBNY) to Guangzhou nearby airports (ZGGG, ZGSZ and ZGSD) in China, and the self-separation procedures were thoroughly assessed with both realistic and simulated data for benefits assessment and sensitivity analysis. Results show that the speed-based operational procedure is more suitable for high-density operations while the other two procedures have more flexibility which can be used for air traffic flow contingency management and/or trajectory management.

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning. Keywords: Obstacles model, Satellite images, Convex hull, Path planning, USV

In order to clarify the comprehensive operational capabilities of the airport and better plan the sustainable development mode of the airport, this paper studies the evaluation method of airport environmental carrying capacity. First, this paper proposes the concept of airport environmental carrying capacity by taking into account the complex characteristics of airports affected by multiple factors and then selects 16 representative evaluation indicators to construct an indicator system based on the Driving Force-Pressure-State-Response (DPSR) framework. Finally, the accelerated genetic algorithm-projection pursuit model is established to model a comprehensive evaluation index, which is used to calculate the airport environmental carrying capacity (AECC). The results of the case study show that the AECC of Guangzhou Baiyun International Airport (CAN) decreased year by year from 2008 to 2017, which is in line with the coordinated development level of CAN. By analysing the changing mechanism of AECC and indicators, we get 6 key influencing indicators that led to the continuous decline of AECC and put forward some political suggestions to improve the AECC.

Skeletal muscle atrophy is an important feature of cancer cachexia, which can be induced by chemotherapy, and affects the survival and quality of life of cancer patients seriously. No specific drugs for cancer cachexia have been applied in clinical practice. This study explored the therapeutic effect of linalool (LIN) on cisplatin (DDP) induced skeletal muscle atrophy. In vivo, LIN can improve skeletal muscle weight loss, anorexia, muscle strength decline and other cachexia symptoms caused by cisplatin treatment in a Lewis lung cancer tumor bearing mouse model, and cause no adverse effects on the anti-tumour effect. LIN treatment decreased the expression of muscle RING-finger protein-1 (MuRF1) and Atrogin1(MAFbx) in muscle, and the activation of insulin-like growth factor-1 (IGF-1)/protein kinase B (Akt)/forkhead box O (FoxO) pathway was observed. In vitro, LIN alleviated DDP induced C2C12 myotube atrophy, and IGF-1 receptor inhibitor Picropodophyllin (PIC), which had no adverse effect on C2C12 myotube cells, could reverse the protective effect of LIN. These results indicate that LIN down-regulates the expression of Atrogin1 and MuRF1 through the IGF-1/Akt/FoxO pathway, alleviating DDP-induced muscle atrophy and improving cachexia symptoms. LIN has the potential to be developed as a drug against cancer cachexia.

Breast cancer remains a leading cause of cancer-related death, for which the majority of deaths result from metastases. Von Willebrand factor C and EGF domain (VWCE) is a member of the Von Willebrand factor (VWF) gene family; however, its function, regulatory mechanism, and clinical value in breast cancer remain unclear. In the present study, we sought to elucidate the role of VWCE in breast cancer metastasis. We examined the expression of VWCE in breast cancer tissues and normal control tissues of 50 breast cancer patients. We found that VWCE expression was downregulated in breast cancer cells and tissues compared to normal breast epithelial cells or the adjacent normal tissues. To explore the role of VWCE in human breast cancer development, we introduced a VWCE-overexpressing or control lentiviral vector into the breast cancer MDA-MB-453 and MDA-MB-231 lines in vitro. The overexpression of VWCE inhibited the proliferation, migration, invasion, and chemoresistance of the breast cancer cell lines. More importantly, the forced expression of VWCE suppressed tumor formation and metastasis in nude mice. iTRAQ-based quantitative proteomic analysis revealed that VWCE overexpression induced a 10-fold decrease in the level of WD-repeat domain 1 (WDR1) protein expression. Rescue experiments further verified that WDR1 was a downstream molecule of VWCE, and WDR1 overexpression reversed the above effects of VWCE overexpression on tumor growth. Therefore, VWCE may represent a novel tumor suppressor, for which its deregulation promotes breast cancer progression via the upregulation of WDR1.

Acetylcholinesterase inhibitors (AChEIs) including donepezil (DNP) are considered to be the most promising therapeutic possibilities of Alzheimer’s disease (AD). The response to DNP in AD patients varies and it is valuable to identify the potential markers that can predict the efficacy. Moreover, DNP has been found to affect bone function, but the exact mechanism is still unclear. Lipids and adipokine may link to AD and DNP directly or indirectly and might be potential biomarkers or therapeutic drug targets. The goal of this study was to investigate the relationships among adiponectin (APN), lipids levels, and the response to DNP, and to identify whether the effect of DNP in AD treatment is related to its effect on the level of APN in systemic circulation. The study recruited 85 AD patients with DNP treatment, of whom 47 were DNP responders and 38 were DNP nonresponders. The Mini-Mental State Examination was performed to evaluate the memory impairment. Plasma APN was measured with ELISA. The genotypes of single nucleotide polymorphisms rs1501299 and rs22417661 in APN for each patient were identified. Plasma lipids were quantified with gas chromatography coupled with mass spectrometry. Correlations among APN, lipid metabolomics, and DNP responded were evaluated. APN was significantly decreased in DNP responders. Methyl stearate and glycerol-3-phosphate, used for characterizing adipogenic differentiation, were significantly decreased in DNP responders compared to DNP nonresponders. APN and small-molecule lipids can be used as potential biomarkers to evaluate the efficacy of DNP. The results of metabolomics indicated that there was no change in the metabolic pathway of fatty acid metabolism and glucose metabolism in DNP responders, suggesting that APN-related biological function did not decrease in DNP responders. Our result suggests that more attention should be pay to the sources and biological functions of APN in AD with DNP treatment.

Donepezil (DNP) is the first-line drug used for Alzheimer's disease (AD). However, the therapeutic response rate of patients to DNP varies from 20 to 60%. The main reason for the large differences in the clinical efficacy of DNP therapy is genetic factors, some of which affect pharmacokinetics (PK), while others affect pharmacodynamics (PD). Thus, much emphasis has been placed on the investigation of an association between PK- and PD-related gene polymorphisms and therapeutic response to DNP, but a consistent view does not yet exist. In this review, we summarize recent findings regarding genetic factors influencing the clinical efficacy of DNP, including substantial differences in individual responses as a consequence of polymorphisms in Cytochrome P450 (CYP) 2D6, CY3A4, CY3A5, APOE, ABCA1, ABCB1, ESR1, BCHE, PON-1, CHRNA7, and CHAT. We also discuss possible strategies for the evaluation of the clinical efficacy of DNP, with a specific focus on possible biomarkers of PK/PD parameters, and provide perspectives and limitations within the field, which will also be beneficial for understanding the multiple mechanisms of DNP therapy in AD.

Matrine is an alkaloid isolated from the traditional Chinese medicine Sophora flavescens Aiton. At present, a large number of studies have proved that matrine has an anticancer effect can inhibit cancer cell proliferation, arrest cell cycle, induce apoptosis, and inhibit cancer cell metastasis. It also has the effect of reversing anticancer drug resistance and reducing the toxicity of anticancer drugs. In addition, studies have reported that matrine has a therapeutic effect on Alzheimer's syndrome, encephalomyelitis, asthma, myocardial ischemia, rheumatoid arthritis, osteoporosis, and the like, and its mechanism is mainly related to the inhibition of inflammatory response and apoptosis. Its treatable disease spectrum spans multiple systems such as the nervous system, circulatory system, and immune system. The antidisease effect and mechanism of matrine are diverse, so it has high research value. This review summarizes recent studies on the pharmacological mechanism of matrine, with a view to providing reference for subsequent research.

The hub-and-spoke network has demonstrated its economies of scale and scope in the rapid development of the civil aviation industry. In order to fit the development trend of green civil aviation, a series of environmental problems such as fuel consumption and pollutant emissions caused by air transportation cannot be ignored. Firstly, this paper selects six cities of Shenyang, Beijing, Qingdao, Zhengzhou, Guangzhou, and Nanjing as the research objects, collects the passenger flow and the distance information of the corresponding segment, determines the location of the hub airport, analyzes the operating environment of the aircraft in the hub-and-spoke network, establishes an aircraft emission assessment model, and calculates the mass of aircraft emissions and fuel consumption. Secondly, based on the calculation results, the comparison of aircraft emissions and fuel consumption between the hub-and-spoke network and the point-to-point network shows that the total carbon monoxide (CO) emissions are reduced by 35.84%, the total hydrocarbon compounds (HC) emissions are increased by 68.82%, and the total nitrogen oxides (NOx) emissions are increased by 24.87%. The total mass of pollutants (including CO, HC, and NOx) decreased by 29.37%, and the total fuel consumption decreased by 68.17%. In general, the use of a hub-and-spoke network reduces the pollutant emissions and fuel consumption of aircraft as a whole while ensuring the lowest passenger transportation cost. Finally, based on the current international situation and the enhancement of people’s awareness of environmental protection, a summary analysis of the hub-and-spoke network and the point-to-point network is obtained, and some enlightenment and research significance are obtained.

Non-coding RNAs have been shown to be key components in translational regulation. Here the authors characterize long nucleolus specific lncRNA termed LoNA, identified to play a role in protein biosynthesis by inhibiting rRNA production and ribosome biosynthesis in nucleoli.

Airport environmental carrying capacity (AECC) provides the fundamental conditions for airport development and operation activities. The prediction of AECC is a necessary condition for planning an appropriate development mode for the airport. This paper studies the dynamic prediction method of the AECC to explore the development characteristics of AECC in different airports. Based on the driving force-pressure-state-response (DPSR) framework, the method selects 17 main variables from economic, social, environmental and operational dimensions, and then combines the drawing of causal loop diagrams and the establishment of system flow diagrams to construct the system dynamics (SD) model of AECC. The predicted values of AECC are obtained through SD model simulation and accelerated genetic algorithm projection pursuit (AGA-PP) model calculation. Considering sustainable development needs, different scenarios are set to analyze the appropriate development mode of the airport. The case study of the Pearl River Delta airports resulted in two main conclusions. First, in the same economic zone, different airports with similar aircraft movements have similar development characteristics of AECC. Second, the appropriate development modes for different airports are different, and the appropriate development modes for the airport in different periods are also different. The case study also proves that the AECC prediction based on SD model and AGA-PP model can realize short-term policy formulation and long-term planning for the airport development mode, and provide decision-making support for relevant departments of airport.

Fruit and vegetable crops are rich in dietary fibre, vitamins and minerals, which are vital to human health. However, many biotic stressors (such as pests and diseases) and abiotic stressors threaten crop growth, quality, and yield. Traditional breeding strategies for improving crop traits include a series of backcrosses and selection to introduce beneficial traits into fine germplasm, this process is slow and resource-intensive. The new breeding technique known as clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein-9 (Cas9) has the potential to improve many traits rapidly and accurately, such as yield, quality, disease resistance, abiotic stress tolerance, and nutritional aspects in crops. Because of its simple operation and high mutation efficiency, this system has been applied to obtain new germplasm resources via gene-directed mutation. With the availability of whole-genome sequencing data, and information about gene function for important traits, CRISPR-Cas9 editing to precisely mutate key genes can rapidly generate new germplasm resources for the improvement of important agronomic traits. In this review, we explore this technology and its application in fruit and vegetable crops. We address the challenges, existing variants and the associated regulatory framework, and consider future applications.

Background: Bilirubin (BR) is metabolized mainly by uridine diphosphate (UDP)-glucuronosyltransferase 1A1 (UGT1A1) through glucuronidation in the liver. Some studies have shown that several subtypes of cytochrome P450 (CYP) enzymes, including CYP1A2, are upregulated by inducers and proposed to be alternative BR degradation enzymes. However, no information is available on the BR degradation ability of CYP in normal rats without manipulation by CYP inducers.Methods: Quantitative real-time polymerase chain reaction (QRT-PCR), western blot, immunofluorescence, and confocal microscopy were used to find expression of CYP1A2 in the brain and the liver. BR metabolites in microsomal fractions during development were examined by high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (LC-MS/MS).Results: In the present study, we observed that CYP1A2 mRNA levels increased at postnatal days (P)14 and P30 with respect to the level at P7 both in liver and brain, this increment was especially pronounced in the brain at P14. The expression of CYP1A2 in the brainstem (BS) was higher than that in the cerebellum (CLL) and cortex (COR). Meanwhile, the CYP1A2 protein level was significantly higher in the COR than in the brainstem and CLL at P14. The levels of BR and its metabolites (m/z values 301, 315, 333 and biliverdin) were statistically unaltered by incubation with liver and brain microsomal fractions.Conclusion: Our results indicated that the region-specific expression of CYP1A2 increased during development, but CYP family enzymes were physiologically incapable of metabolizing BR. The ability of CYPs to oxidize BR may be triggered by CYP inducers.

A scheme to solve the course keeping problem of the unmanned surface vehicle with nonlinear and uncertain characteristics and unknown external disturbances is investigated in this article. The chattering existing in global fast terminal sliding mode controller in solving the course keeping problem of the unmanned surface vehicle with external disturbance is analyzed. To reduce the chattering and eliminate the influence of the unknown disturbance, an adaptive global fast terminal sliding mode controller based on radial basis function neural network is developed. The equivalent control that usually requires a precise model information of the system is computed using the radial basis function neural network. The weights of the neural network are online adjusted according to the adaptive law that is derived using Lyapunov method to ensure the stability of the closed-loop system. Using the online learning of the neural network, the nonlinear uncertainty of the system and the unknown disturbance of external environment are compensated, and the system chattering is reduced effectively as well. The simulation results demonstrate that the proposed controller can achieve a good performance regarding the fast response and smooth control.

The therapeutic response rates of patients to donepezil vary from 20% to 60%, one of the reasons is their genetic differences in donepezil-metabolizing enzymes, which directly influence liver metabolism. However, the mechanism of donepezil metabolism and that of its enantiomers is unknown. This study evaluated CYP2D6 polymorphisms to elucidate the stereoselective metabolism of donepezil and to confirm the association between the steady-state plasma concentrations of the pharmaco-effective S-donepezil and the therapeutic responses of Han Chinese patients with Alzheimer's disease. The in vitro study of the stereoselective metabolism demonstrated that CYP2D6 is the predominant P450 enzyme that metabolizes donepezil and that different CYP2D6 alleles differentially affect donepezil enantiomers metabolism. A total of 77 Han Chinese patients with Alzheimer's disease were recruited to confirm these results, by measuring their steady-state plasma concentrations of S-donepezil. The related CYP2D6 genes were genotyped. Plasma concentrations of S-donepezil (based on CYP2D6 polymorphisms) were significantly associated with therapeutic responses. This finding suggests that plasma concentrations of S-donepezil influence therapeutic outcomes following treatment with donepezil in Han Chinese patients with Alzheimer's disease. Therefore, determining a patient's steady-state plasma concentration of S-donepezil in combination with their CYP2D6 genotype might be useful for clinically monitoring the therapeutic efficacy of donepezil.

Unmanned surface vehicle has the properties such as complexity, nonlinearity, time variability, and uncertainty, which lead to the difficulty of obtaining a precise kinematics model. A neural adaptive sliding mode controller for the unmanned surface vehicle steering system is developed based on the sliding mode control technique and the radial basis function neural network. In the new approach, two parallel radial basis function neural networks are used to reduce the influence of the system uncertainties and eliminate the dependency of the controller on the precise kinematics model of the system. Among these two radial basis function neural networks, one is used to approximate the unknown nonlinear yaw dynamics and the other is used to adjust the control gain as well as realize the variable gain sliding mode control. The weights of the two neural networks are trained online using the sliding surface variable and the control, where the Lyapunov method is used to derive the adaptive laws to ensure the stability of the whole closed-loop system. The proposed adaptive controller is suitable for the steering control at different cruising speeds with bounded external disturbances. The simulation results show that the proposed controller has a good control performance regarding the smooth control, fast response, and high accuracy.

Previous studies have shown that smiling, fairness, intention, and the results being openness to the proposer can influence the responses in ultimatum games, respectively. But it is not clear that how the four factors might interact with each other in twos or in threes or in fours. This study examined the way that how the four factors work in resource distribution games by testing the differences between average rejection rates in different treatments. Two hundred and twenty healthy volunteers participated in an intentional version of the ultimatum game (UG). The experiment used a 2 × 2 × 2 × 2 mixed design with “openness” as a between subjects factor and the other three as within subjects factors, and the participants were assigned as recipients. The results revealed that fairness or perceived good intention reduced the subject’s average rejection rates. There was a significant interaction between facial expressions and openness. With fair offers, the average rejection rate for informed was lower than that of uninformed; but when unfair, no difference between the corresponding average rejection rates was found. The interaction effect of smiling and openness was also significant, the average rejection rate for informed offers was lower when the proposer was smiling and no rejection rate difference between uninformed offers and informed offers when no smiling. No other interaction effect was found.

Galfenol traditional cantilever energy harvesters (TCEHs) have bigger electrical output only at resonance and exhibit nonlinear mechanical-magnetic-electric coupled (NMMEC) behaviors. To increase low-frequency broadband performances of a TCEH, an improved CEH (ICEH) with magnetic repulsive force is studied. Based on the magnetic dipole model, the nonlinear model of material, the Faraday law and the dynamic principle, a lumped parameter NMMEC model of the devices is established. Comparisons between the calculated and measured results show that the proposed model can provide reasonable data trends of TCEH under acceleration, bias field and different loads. Simulated results show that ICEH exhibits low-frequency resonant, hard spring and bistable behaviors, thus can harvest more low-frequency broadband vibration energy than TCEH, and can elicit snap-through and generate higher voltage even under weak noise. The proposed structure and model are useful for improving performances of the devices.

The paper introduces a computational model of airspace conflict risk in the hierarchy of performance-based navigation (PBN) airspace operation and combines it with air traffic controller (ATC) workload to propose a method for safety assessment of PBN airspace operational planning. Capacity probability distribution is employed to depict airspace capacity in uncertain weather, errors of deviating from nominal PBN track are taken into consideration, and the stochastic process based on Gaussian distribution is used to depict random aircraft motion according to airspace PBN specification, so as to build an airspace conflict risk computational model in corresponding capacity scenario. Guangzhou No. 15 sector is chosen for simulation validation. The analysis results suggest that 60% of ATC workload is corresponding to sector traffic flow of 31 aircraft/h and airspace risk of 0.018 conflict/h, while 70% of ATC workload is corresponding to sector traffic flow of 35 aircraft/h and airspace risk of 0.03 conflict/h. As air traffic flow increases, both airspace conflict risk value and ATC workload will increase, resulting in reduction of airspace safety, though their increasing magnitudes differ with different capacity scenarios. The safety assessment method enables effective quantization of safety with regard to airspace operational planning strategy, and benefits the development of optimal operational scheme that balances risk with capacity demand.

The output characteristic model of a magnetostrictive cantilever-like tactile sensor has been founded based on the inverse-magnetostrictive effect, the flexure mode, and the Jiles-Atherton model. The magnetostrictive sensor has been designed and an output voltage is analyzed under the conditions of bias magnetic field, contact pressure and deflection of cantilever beam. The experiment has been performed to determine the relation among the induced output voltage, bias magnetic field, and pressure. It is found that the peak of the induced output voltage increases with an increasing pressure under the bias magnetic field of 4.8kA/m. The experimental result agrees well with the theoretical one and it means that the model can describe the relation among the induced output voltage, bias magnetic field, and pressure. The sensor with a Galfenol sheet may hold potentials in sample characterization and deformation predication in artificial intelligence area.

Hepatic stellate cells (HSCs) play a crucial role in liver fibrosis, which is a pathological process characterized by extracellular matrix accumulation. NR4A2 is a nuclear receptor belonging to the NR4A subfamily and vital in regulating cell growth, metabolism, inflammation and other biological functions. However, its role in HSCs is unclear. We analyzed NR4A2 expression in fibrotic liver and stimulated HSCs compared with control group and studied the influence on cell proliferation, cell cycle, cell apoptosis and MAPK pathway after NR4A2 knockdown. NR4A2 expression was examined by real-time polymerase chain reaction, Western blotting, immunohistochemistry and immunofluorescence analyses. NR4A2 expression was significantly lower in fibrotic liver tissues and PDGF BB or TGF-β stimulated HSCs compared with control group. After NR4A2 knockdown α-smooth muscle actin and Col1 expression increased. In addition, NR4A2 silencing led to the promotion of cell proliferation, increase of cell percentage in S phase and reduced phosphorylation of ERK1/2, P38 and JNK in HSCs. These results indicate that NR4A2 can inhibit HSC proliferation through MAPK pathway and decrease extracellular matrix in liver fibrogenesis. NR4A2 may be a promising therapeutic target for liver fibrosis.

Eukaryotes have two types of spliceosomes, comprised of either major (U1, U2, U4, U5, U6) or minor (U11, U12, U4atac, U6atac;