A nonlinear wake model of a wind turbine considering the yaw wake steering

Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw state.To predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was derived based on the method of momentum conservation considering the wake steering of the wind turbine under yaw conditions.To consider the shear effect of the vertical incoming wind direction,a two-dimensional Gaussian distribution function was introduced to model the velocity loss at different axial positions in the far wake region based on the assumption of nonlinear wake expansion.This work also developed a“prediction-correction”method to solve the wake velocity field,and the accuracy of the model results was verified in wake experiments on the Garrad Hassan wind turbine.Moreover,a 33-kW two-blade horizontal axis wind turbine was simulated using this method,and the results were compared with the classical wake model under the same parameters and the computational fluid dynamics(CFD)simulation results.The results show that the nonlinear wake model well reflected the influence of incoming flow shear and yaw wake steering in the wake velocity field.Finally,computation of the wake flow for the Horns Rev offshore wind farm with 80 wind turbines showed an error within 8%compared to the experimental values.The established wake model is less computationally intensive than other methods,has a faster calculation speed,and can be used for engineering calculations of the wake velocity in the far wakefield of wind turbines.

VPD modifies CO_(2) fertilization effect on tomato plants via abscisic acid and jasmonic acid signaling pathways

Atmospheric CO_(2)concentration is elevated globally,which has“CO_(2)fertilization effects”and potentially improves plant photosynthesis,yield,and productivity.Despite the beneficial effect of CO_(2)fertilization being modulated by vapor pressure deficit(VPD),the underlying mechanism is highly uncertain.In the present study,the potential roles of hormones in determining CO_(2)fertilization effects under contrasting high and low VPD conditions were investigated by integrated physiological and transcriptomic analyses.Beneficial CO_(2)fertilization effects were offset under high VPD conditions and were constrained by plant water stress and photosynthetic CO_(2)utilization.High VPD induced a large passive water driving force,which disrupted the water balance and consequently caused plant water deficit.Leaf water potential,turgor pressure,and hydraulic conductance declined under high VPD stress.The physiological evidence combined with transcriptomic analyses demonstrated that abscisic acid(ABA)and jasmonic acid(JA)potentially acted as drought-signaling molecules in response to high VPD stress.Increased foliar ABA and JA content triggered stomatal closure to prevent excessive water loss under high VPD stress,which simultaneously increased the diffusion resistance for CO_(2)uptake from atmosphere to leaf intercellular space.High VPD also significantly increased mesophyll resistance for CO_(2)transport from stomatal cavity to fixation site inside chloroplast.The chloroplast“sink”CO_(2)availability was constrained by stomatal and mesophyll resistance under high VPD stress,despite the atmospheric“source”CO_(2)concentration being elevated.Thus,ABA-and JA-mediated drought-resistant mechanisms potentially modified the beneficial effect of CO_(2)fertilization on photosynthesis,plant growth,and yield productivity.This study provides valuable information for improving the utilization efficiency of CO_(2)fertilization and a better understanding of the physiological processes.

Convolutional Neural Networks Based Indoor Wi-Fi Localization with a Novel Kind of CSI Images

Indoor Wi-Fi localization of mobile devices plays a more and more important role along with the rapid growth of location-based services and Wi-Fi mobile devices.In this paper,a new method of constructing the channel state information(CSI)image is proposed to improve the localization accuracy.Compared with previous methods of constructing the CSI image,the new kind of CSI image proposed is able to contain more channel information such as the angle of arrival(AoA),the time of arrival(TOA)and the amplitude.We construct three gray images by using phase differences of different antennas and amplitudes of different subcarriers of one antenna,and then merge them to form one RGB image.The localization method has off-line stage and on-line stage.In the off-line stage,the composed three-channel RGB images at training locations are used to train a convolutional neural network(CNN)which has been proved to be efficient in image recognition.In the on-line stage,images at test locations are fed to the well-trained CNN model and the localization result is the weighted mean value with highest output values.The performance of the proposed method is verified with extensive experiments in the representative indoor environment.

Static CSI Extraction and Application in the Tomographic Channel Model

In this paper, the statistical properties of parameters of each path in wireless channel models are analyzed to prove that there is the static part in channel state information(CSI) which can be extracted from huge amounts of CSI data. Based on the analysis, the concept of the Tomographic Channel Model(TCM) is presented. With cluster algorithms, the static CSI database can be built in an off-line manner. The static CSI database can provide prior information to help pilot design to reduce overhead and improve accuracy in channel estimation. A new CSI prediction method and a new channel estimation method between different frequency bands are introduced based on the static CSI database. Using measurement data, the performance of the new channel prediction method is compared with that of the Auto Regression(AR) predictor. The results indicate that the prediction range of the new method is better than that of the AR method and the new method can predict with fewer pilot symbols. Using measurement data, the new channel estimation method between different frequency bands can estimate the CSI of one frequency band based on known CSI of another frequency band without any feedback.

Energy-Efficient Resource Allocation for Small-Cell Networks：A Stable Queue Perspective

The small-cell technology is promising for spectral-efficiency enhancement. However, it usually requires a huge amount of energy consumption. In this paper, queue state information and channel state information are jointly utilized to minimize the time average of overall energy consumption for a multi-carrier small-cell network, where the inter-cell interference is an intractable problem. Based on the Lyapunov optimization theory, the problem could be solved by dynamically optimizing the problem of user assignment, carrier allocation and power allocation in each time slot. As the optimization problem is NP-hard, we propose a heuristic iteration algorithm to solve it. Numerical results verify that the heuristic algorithm offers an approximate performance as the brute-force algorithm. Moreover, it could bring down the overall energy consumption to different degrees according to the variation of traffic load. Meanwhile, it could achieve the same sum rate as the algorithm which focuses on maximizing system sum rate.

Technical development of operational in-situ marine monitoring and research on its key generic technologies in China

In China,operational in-situ marine monitoring is the primary means of directly obtaining hydrological,meteorological,and oceanographic environmental parameters across sea areas,and it is essential for applications such as forecast of marine environment,prevention and mitigation of disaster,exploitation of marine resources,marine environmental protection,and management of transportation safety.In this paper,we summarise the composition,development courses,and present operational status of three systems of operational in-situ marine monitoring,namely coastal marine automated network station,ocean data buoy and voluntary observing ship measuring and reporting system.Additionally,we discuss the technical development in these in-situ systems and achievements in the key generic technologies along with future development trends.

A New TDD Scheme and Interference-Aware Precoding for Device-to-Device Underlay Massive MIMO

In device-to-device(D2D)underlay cellular networks with downlink spectrum sharing,massive MIMO seems promising as the large number of antennas at the base station(BS) can be utilized to suppress interference.However,the channel state information(CSI) from the BS to D2D receivers is required to obtain this advantage.In this paper,we first propose a novel time division duplex(TDD) scheme for D2D users to acquire this CSI,without additional pilot overhead.Moreover,we propose an interference-aware MMSE precoder utilizing the acquired CSI from the BS to not only cellular users but also D2D users to suppress the cellular-to-D2D interference.Simulation results show that our proposed TDD scheme and precoder can significantly improve the achievable sum spectral efficiency(SE) and D2D SE,compared to the classical MMSE precoder.Compared with the interferenceaware ZF precoder,whose performance severely degrades for large user numbers,our proposed interference-aware MMSE precoder can always guarantees a high and stable performance in terms of achievable SE.

Effects of an immunosuppressive active component of Periplocae Cortex (Periploca sepium Bge.) on positive selection of thymocytes in vitro

Objective:To determine the effect of an immunosuppressive active component (periploside A) isolated from the stem bark of Periplocae Cortex (Periploca sepium Bge.),a Chinese medicinal herb used in the treatment of rheumatoid arthritis for centuries in China,on positive selection of thymocytes in vitro.Methods:Female C57BL/6 mice at 6 weeks of age were housed in specific pathogen-free conditions.Double-positive thymocytes from C57BL/6 mice were induced into positive selection in vitro with or without periploside A treatment.Cell viability and expression of CD69,CD4,and CD8 were analyzed by flow cytometry.Results:Flow cytometric examination of thymocyte populations revealed that the percentage of CD8+ single-positive thymocytes was decreased by periploside A upon differentiation induced by an anti-CD3 antibody.However,the percentage of CD4+ single-positive thymocytes was decreased by periploside A upon differentiation induced by phorbol 12-myristate 13-acetate/ionomycin.Expression of CD69 plays a major role in prohibiting differentiation of thymocytes.Treatment with periploside A decreased CD69 expression in thymocytes.Conclusion:These results demonstrate that periploside A influences positive selection of thymocytes in vitro.

Developing an intermediate-complexity projection model for China's fisheries:A case study of small yellow croaker(Larimichthys polyactis)in the Haizhou Bay,China

Projection models are commonly used to evaluate the impacts of fishing.However,previously developed projection tools were not suitable for China’s fisheries as they are either overly complex and data-demanding or too simple to reflect the realistic management measures.Herein,an intermediate-complexity projection model was developed that could adequately describe fish population dynamics and account for management measures including mesh size limits,summer closure,and spatial closure.A two-patch operating model was outlined for the projection model and applied to the heavily depleted but commercially important small yellow croaker(Larimichthys polyactis)fishery in the Haizhou Bay,China,as a case study.The model was calibrated to realistically capture the fisheries dynamics with hindcasting.Three simulation scenarios featuring different fishing intensities based on status quo and maximum sustainable yield(MSY)were proposed and evaluated with projections.Stochastic projections were additionally performed to investigate the influence of uncertainty associated with recruitment strengths and the implementation of control targets.It was found that fishing at FMSY level could effectively rebuild the depleted stock biomass,while the stock collapsed rapidly in the status quo scenario.Uncertainty in recruitment and implementation could result in variabilities in management effects;but they did not much alter the management effects of the FMSY scenario.These results indicate that the lack of science-based control targets in fishing mortality or catch limits has hindered the achievement of sustainable fisheries in China.Overall,the presented work highlights that the developed projection model can promote the understanding of the possible consequences of fishing under uncertainty and is applicable to other fisheries in China.

Bile acids and sphingosine-1-phosphate receptor 2 in hepatic lipid metabolism

The liver is the central organ involved in lipid metabolism. Dyslipidemia and its related disorders, including non-alcoholic fatty liver disease(NAFLD), obesity and other metabolic diseases, are of increasing public health concern due to their increasing prevalence in the population. Besides their well-characterized functions in cholesterol homoeostasis and nutrient absorption, bile acids are also important metabolic regulators and function as signaling hormones by activating specific nuclear receptors, G-protein coupled receptors, and multiple signaling pathways. Recent studies identified a new signaling pathway by which conjugated bile acids(CBA) activate the extracellular regulated protein kinases(ERK1/2) and protein kinase B(AKT) signaling pathway via sphingosine-1-phosphate receptor 2(S1PR2). CBA-induced activation of S1PR2 is a key regulator of sphingosine kinase 2(Sph K2) andhepatic gene expression. This review focuses on recent findings related to the role of bile acids/S1PR2-mediated signaling pathways in regulating hepatic lipid metabolism.

Research fronts of agriculture in 2023

At the end of 2023, Chinese Academy of Sciences(CAS) and Chinese Academy of Engineering(CAE) successively announced “2023 Research Fronts”^[1] and “2023 Engineering Fronts”^([2,3]), respectively. Among them, agricultural sciences occupy a pivotal position on both fronts.

基于大数据的无线通信技术

随着各类丰富的移动应用普及,可以预见,未来的无线通信系统将需要满足更为苛刻的服务要求,为无线通信技术的发展带来挑战.另一方面,大数据在众多领域的应用取得了令人瞩目的成功.大数据如何赋能无线通信成为学术界和工业界关注的焦点.过去5年,我们承担了国家自然科学基金"无线通信大数据基础理论与技术研究"重点项目群,致力于研究基于大数据的无线通信技术,探索使用大数据突破无线通信发展瓶颈的新理论和新方法.我们将这类在无线通信中产生、能够服务于无线通信的大数据定义为无线大数据.本文是对项目群的研究和实践结果的总结.具体地,我们首先分析了无线大数据的来源和特征,然后构建了与之匹配的无线知识学习范式、智能无线网络框架以及跨地域、跨机构、多用途、一体化的无线大数据平台,最后提出并验证了基于大数据的无线传播环境分析、无线传输以及无线接入技术,从而为基于大数据的无线通信技术的进一步发展提供基础理论支撑和应用范式.

Wireless channel feature extraction via GMM and CNN in the tomographic channel model

Wireless channel modeling has always been one of the most fundamental highlights of the wireless communication research.The performance of new advanced models and technologies heavily depends on the accuracy of the wireless CSI(Channel State Information).This study examined the randomness of the wireless channel parameters based on the characteristics of the radio propagation environment.The diversity of the statistical properties of wireless channel parameters inspired us to introduce the concept of the tomographic channel model.With this model,the static part of the CSI can be extracted from the huge amount of existing CSI data of previous measurements,which can be de ned as the wireless channel feature.In the proposed scheme for obtaining CSI with the tomographic channel model,the GMM(Gaussian Mixture Model)is applied to acquire the distribution of the wireless channel parameters,and the CNN(Convolutional Neural Network)is applied to automatically distinguish di erent wireless channels.The wireless channel feature information can be stored oine to guide the design of pilot symbols and save pilot resources.The numerical results based on actual measurements demonstrated the clear diversity of the statistical properties of wireless channel parameters and that the proposed scheme can extract the wireless channel feature automatically with fewer pilot resources.Thus,computing and storage resources can be exchanged for the nite and precious spectrum resource.

GENOME EDITING:A GROUND BREAKING RESEARCH HAS BEEN RANKED TOP 10 ENGINEERING FRONTS FROM 2017 TO 2021

‘Global Engineering Fronts’ is a report released by the Chinese Academy of Engineering(CAE) every year since 2017, which aims to assemble talents in the field of engineering science and technology to represent the global engineering research and development fronts by reviewing global papers, patents, and other data. The results are also expected to provide a reference for people on responding to global challenges and achieving sustainable development.

Allocation of Network Error Correction Flow on Disjoint Paths

The diversity provided by disjoint paths can increase the survivability of communication networks. This paper considers the allocation of network error correction flow on a network that consists of disjoint paths from the source node to the destination node. Specifically, we propose an algorithm of allocating the path-flows to support the given rate with minimum cost. Our analysis shows that the asymptotic time complexity of this algorithm is linearithmic, and this algorithm is optimal in general