Maximum Inner Product Method for Extracting the Path-Loss Parameters in Primary Transformer Substations

In order to deploy short-range wireless communication devices in the primary transformer substation, a Maximum Inner Product(MIP) Method is proposed to extract the path-loss parameters in 110 kV and 220 kV primary transformer substations. The maximum inner product of the testing data is calculated to find out the loss index n and the standard deviation σ, and then the pathloss models can be set up. By comparing the MIP with Minimum Mean Square estimation(MMSE) and Cumulative Sum(CUSUM), MIP can match the measured values best. In order to apply the MIP path-loss model, under the initial signal to noise ratio(SNR) at 5 dB and 10 dB, a ZigBee simulation system is constructed to validate the situation that bit error rate(BER) varies with distance. And the ZigBee devices with 5 units are tested in a 220 kV primary transformer substation. The result of the test proves that the path-loss model is accurate.

Robust Topology Optimization of Periodic Multi-Material Functionally Graded Structures under Loading Uncertainties

This paper presents a robust topology optimization design approach for multi-material functional graded structures under periodic constraint with load uncertainties.To characterize the random-field uncertainties with a reduced set of random variables,the Karhunen-Lo`eve(K-L)expansion is adopted.The sparse grid numerical integration method is employed to transform the robust topology optimization into a weighted summation of series of deterministic topology optimization.Under dividing the design domain,the volume fraction of each preset gradient layer is extracted.Based on the ordered solid isotropic microstructure with penalization(Ordered-SIMP),a functionally graded multi-material interpolation model is formulated by individually optimizing each preset gradient layer.The periodic constraint setting of the gradient layer is achieved by redistributing the average element compliance in sub-regions.Then,the method of moving asymptotes(MMA)is introduced to iteratively update the design variables.Several numerical examples are presented to verify the validity and applicability of the proposed method.The results demonstrate that the periodic functionally graded multi-material topology can be obtained under different numbers of sub-regions,and robust design structures are more stable than that indicated by the deterministic results.

Prediction of curved oil–water interface in horizontal pipes using modified model with dynamic contact angle

In this study,interface shapes of horizontal oil–water two-phase flow are predicted by using Young-Laplace equation model and minimum energy model.Meanwhile,the interface shapes of horizontal oil–water twophase flow in a 20 mm inner diameter pipe are measured by a novel conductance parallel-wire array probe(CPAP).It is found that,for flow conditions with low water holdup,there is a large deviation between the model-predicted interface shape and the experimentally measured one.Since the variation of pipe wetting characteristics in the process of fluid flow can lead to the changes of the contact angle between the fluid and the pipe wall,the models mentioned above are modified by considering dynamic contact angle.The results indicate that the interface shapes predicted by the modified models present a good consistence with the ones measured by CPAP.

COMTIS:Customizable touchless interaction system for large screen visualization

Background Large screen visualization sys tems have been widely utilized in many industries.Such systems can help illustrate the working states of different production systems.However,efficient interaction with such systems is still a focus of related research.Methods In this paper,we propose a touchless interaction system based on RGB-D camera using a novel bone-length constraining method.The proposed method optimizes the joint data collected from RGB-D cameras with more accurate and more stable results on very noisy data.The user can customize the system by modifying the finite-state machine in the system and reuse the gestures in multiple scenarios,reducing the number of gestures that need to be designed and memorized.Results/Conclusions The authors tested the system in two cases.In the first case,we illustrated a process in which we improved the gesture designs on our system and tested the system through user study.In the second case,we utilized the system in the mining industry and conducted a user study,where users say that they think the system is easy to use.

Cloud-to-end rendering and storage management for virtual reality in experimental education

Background Real-time 3D rendering and interaction is important for virtual reality(VR)experimental education.Unfortunately,standard end-computing methods prohibitively escalate computational costs.Thus,reducing or distributing these requirements needs urgent attention,especially in light of the COVID-19 pandemic.Methods In this study,we design a cloud-to-end rendering and storage system for VR experimental education comprising two models:background and interactive.The cloud server renders items in the background and sends the results to an end terminal in a video stream.Interactive models are then lightweight-rendered and blended at the end terminal.An improved 3D warping and hole-filling algorithm is also proposed to improve image quality when the user's viewpoint changes.Results We build three scenes to test image quality and network latency.The results show that our system can render 3D experimental education scenes with higher image quality and lower latency than any other cloud rendering systems.Conclusions Our study is the first to use cloud and lightweight rendering for VR experimental education.The results demonstrate that our system provides good rendering experience without exceeding computation costs.

An Improved Empirical Mode Decomposition for Power Analysis Attack

Correlation power analysis(CPA) has become a successful attack method about crypto-graphic hardware to recover the secret keys. However, the noise influence caused by the random process interrupts(RPIs) becomes an important factor of the power analysis attack efficiency, which will cost more traces or attack time. To address the issue, an improved method about empirical mode decomposition(EMD) was proposed. Instead of restructuring the decomposed signals of intrinsic mode functions(IMFs), we extract a certain intrinsic mode function(IMF) as new feature signal for CPA attack. Meantime, a new attack assessment is proposed to compare the attack effectiveness of different methods. The experiment shows that our method has more excellent performance on CPA than others. The first and the second IMF can be chosen as two optimal feature signals in CPA. In the new method, the signals of the first IMF increase peak visibility by 64% than those of the tradition EMD method in the situation of non-noise. On the condition of different noise interference, the orders of attack efficiencies are also same. With external noise interference, the attack effect of the first IMF based on noise with 15dB is the best.

X-Band Power Amplifier for Next Generation Networks Based on MESFET

Advanced wireless standards of communication like 3GPP and LTE are becoming more and more efficient and with this evolution of communication systems mobile equipment is also become smaller and smaller. Power amplifier designing has become a very crucial task in this era where efficiency and size are the main concern of any designer. In this paper we have design and analyzed X-band Class E Metal-semiconductor field effect transistor(MESFET) based Power Amplifier. This device targets the devices which use OFDM technique to improve their spectral efficiency for the next generation communication systems. Microstrip lines are used to achieve small size for our design instead of lumped components. Load Pull measurements are used to get MESFET input and output impedances optimum values. For linear and non linear operation small signal mathematical model of the design is used. To reduce thermal losses FR4 substrate is used to increase PA efficiency. Our designs shows small values of input and output return loss of about-22.3d B and-23.716 d B achieving a high gain of about25.6 d B respectively, with PAE of about 30 % having stability factor greater than 1 and 21.894 d Bm of output power.

Individual Identification of Electronic Equipment Based on Electromagnetic Fingerprint Characteristics

With the rapid development of communication and computer,the individual identification technology of communication equipment has been brought to many application scenarios.The identification of the same type of electronic equipment is of considerable significance,whether it is the identification of friend or foe in military applications,identity determination,radio spectrum management in civil applications,equipment fault diagnosis,and so on.Because of the limited-expression ability of the traditional electromagnetic signal representation methods in the face of complex signals,a new method of individual identification of the same equipment of communication equipment based on deep learning is proposed.The contents of this paper include the following aspects:(1)Considering the shortcomings of deep learning in processing small sample data,this paper provides a universal and robust feature template for signal data.This paper constructs a relatively complete signal template library from multiple perspectives,such as time domain and transform domain features,combined with high-order statistical analysis.Based on the inspiration of the image texture feature,characteristics of amplitude histogram of signal and the signal amplitude co-occurrence matrix(SACM)are proposed in this paper.These signal features can be used as a signal fingerprint template for individual identification.(2)Considering the limitation of the recognition rate of a single classifier,using the integrated classifier has achieved better generalization ability.The final average accuracy of 5 NRF24LE1 modules is up to 98%and solved the problem of individual identification of the same equipment of communication equipment under the condition of the small sample,low signal-to-noise ratio.

Design and Research of Efficient Adaptive Spray Plant Protection UAV

When the plant protection UAV is spraying on plants, the operator usually performs visual inspection on the vertical distance between the UAV and the plant to adjust the spray height to complete the application. Visual inspection by human eyes is easy to cause the error of spray deposition and deposition density. In order to improve the full utilization of drugs and the spraying efficiency of plant protection UAV, an efficient adaptive spray plant protection UAV was designed, and the vertical distance from the UAV to the plant was collected by ultrasonic wave. Meantime, the plant density was detected in real time, and the flight attitude of plant protection UAV and application rate of spray nozzle were automatically adjusted. The experimental results showed that the designed highly efficient adaptive spray plant protection UAV had fast response speed, precise spray location and less drug loss.

Expression of Vascular Endothelial Growth Factor C and Its Clinical Significance in Human Esophageal Squamous Cell Carcinoma

OBJECTIVE To examine the expression of vascular endothelial growth factor C(VEGF-C)in human esophageal squamous cell carcinoma(ESCC), and to clarify its role in lymphatic metastasis in ESCC patients. METHODS Esophageal carcinoma EC9706 cel s and samples from 49 patients with primary ESCC were investigated by using S-P immunohisto- chemistry(IHC),the semi-quantitative reverse transcriptase-polymerase chain reaction(RT-PCR)and in situ hybridization(ISH)methods for VEGF-C expression. RESULTS VEGF-C positive expression was found in EC9706 cells through IHC,ISH and RT-PCR.Positive IHC for VEGF-C was observed in 36 of 49 cases of ESCC.There was a significant difference between the expres- sion of VEGF-C in a lymph-node-positive group compared to a node-nega- tive group(χ2=4.7,P<0.05).Positive ISH for VEGF-C mRNA was observed in 23 of 49 cases of ESCC.There was a significant difference between the expression of VEGF-C in the lymph-node-positive group and node-negative group(χ2=31.3,P<0.01).The expression of VEGF-C was significantly higher in the lymph-node-positive group compared to the node-negative group.Of 49 ESCC tissues,RT-PCR for VEGF-C mRNA was observed positively in 29 cases.There was a significant difference between the expression of VEGF-C in the lymph-node-positive group and node-negative group(χ2=23.3, P<0.01).The expression of VEGF-C was significantly higher in the lymph- node-positive group compared to the node-negative group.Expressions of VEGF-C were not significantly associated with age,gender,and pathological grade.There was a relationship between VEGF-C mRNA expressions by RT-PCR and ISH(χ2=18.5,P<0.01)in ESCC cases,but with no significant difference between the two methods. CONCLUSION VEGF-C expression may induce lymphangiogenesis in human ESCC.There was a close correlation between VEGF-C expression and lymph node metastasis.VEGF-C can serve as a useful prognostic factor for ESCC patients.

End-to-end spatial transform face detection and recognition

Background Several face detection and recogni tion methods have been proposed in the past decades that have excellent performance.The conventional face recognition pipeline comprises the following:(1)face detection,(2)face alignment,(3)feature extraction,and(4)similarity,which are independent of each other.The separate facial analysis stages lead to redundant model calculations,and are difficult for use in end-to-end training.Methods In this paper,we propose a novel end-to-end trainable convolutional network framework for face detection and recognition,in which a geometric transformation matrix is directly learned to align the faces rather than predicting the facial landmarks.In the training stage,our single CNN model is supervised only by face bounding boxes and personal identities,which are publicly available from WIDER FACE and CASIA-WebFace datasets.Our model is tested on Face Detection Dataset and Benchmark(FDDB)and Labeled Face in the Wild(LFW)datasets.Results The results show 89.24%recall for face detection tasks and 98.63%accura cy for face recognition tasks.

太阳极轨天文台

太阳极轨天文台利用高轨道倾角(≥80°)和小椭偏率轨道,将首次实现正面对太阳极区磁场和速度场高精度成像观测,结合多波段遥感和原位测量,为解决太阳磁活动周起源的世纪难题提供决定性观测,为破解“原始”高速太阳风的起源效应之谜提供直接观测支撑,为理解日球层整体结构突破性创建数据驱动的日球数值模型.

Science with the 2.5-meter Wide Field Survey Telescope(WFST)

The Wide Field Survey Telescope(WFST) is a dedicated photometric surveying facility being built jointly by University of Science and Technology of China(USTC) and the Purple Mountain Observatory(PMO). It is equipped with a 2.5-meter diameter primary mirror, an active optics system, and a mosaic CCD camera with 0.73 gigapixels on the primary focal plane for highquality image capture over a 6.5-square-degree field of view. The installation of WFST near the summit of Saishiteng mountain in the Lenghu region is scheduled in summer of 2023, and the operation is planned to start three months later. WFST will scan the northern sky in four optical bands(u, g, r and i) at cadences from hourly/daily in the deep high-cadence survey(DHS) program, to semi-weekly in the wide field survey(WFS) program. During a photometric night, a nominal 30 s exposure in the WFS program will reach a depth of 22.27, 23.32, 22.84, and 22.31(AB magnitudes) in these four bands, respectively, allowing for the detection of a tremendous amount of transients in the low-z universe and a systematic investigation of the variability of Galactic and extragalactic objects. In the DHS program, intranight 90 s exposures as deep as 23(u) and 24 mag(g), in combination with target of opportunity follow-ups, will provide a unique opportunity to explore energetic transients in demand for high sensitivities, including the electromagnetic counterparts of gravitational wave events, supernovae within a few hours of their explosions,tidal disruption events and fast, luminous optical transients even beyond redshift of unity. In addition, the final 6-year co-added images, anticipated to reach g■25.8 mag in WFS or 1.5 mags deeper in DHS, will be of fundamental importance to general Galactic and extragalactic science. The highly uniform legacy surveys of WFST will serve as an indispensable complement to those of the Vera C. Rubin Observatory's Legacy Survey of Space and Time(LSST) that monitors the southern sky.

Perspectives on point cloud-based 3D scene modeling and XR presentation within the cloud-edge-client architecture

With the support of edge computing,the synergy and collaboration among central cloud,edge cloud,and terminal devices form an integrated computing ecosystem known as the cloud-edge-client architecture.This integration unlocks the value of data and computational power,presenting significant opportunities for large-scale 3D scene modeling and XR presentation.In this paper,we explore the perspectives and highlight new challenges in 3D scene modeling and XR presentation based on point cloud within the cloud-edge-client integrated architecture.We also propose a novel cloud-edge-client integrated technology framework and a demonstration of municipal governance application to address these challenges.

荧光假单胞菌ZX对采后锦橙绿霉病的防治及其抑菌机制

【目的】采后柑橘极易受指状青霉(Penicillium digitatum)侵染而发生严重的绿霉病腐烂,生物防治因具有安全、有效、环保等特点近年来备受关注。论文旨在研究荧光假单胞菌(Pseudomonas fluorescens)ZX对采后柑橘绿霉病的防治效果,揭示P.fluorescensZX对P.digitatum可能存在的作用机制。【方法】以"北碚447"锦橙果实为试材,先分别接种20μL拮抗菌培养液、滤液(培养液离心后,上清经0.22μm滤膜过滤)、菌悬液(培养液离心后,菌体用无菌水反复洗涤并用无菌水重悬)和热杀死液(培养液高温高压灭菌),2 h后接种20μL P. digitatum孢子悬浮液(1×10~4spores/m L),所有果实于20oC、90%相对湿度环境下恒温恒湿培养8 d后,测定果实的发病率和病斑直径;制备柑橘皮培养基,进行平板抑菌试验,探索P. fluorescens ZX对P. digitatum孢子发芽情况的影响;采用两板对扣法和生物熏蒸法研究P.fluorescensZX挥发性次级代谢产物的抑菌作用;利用插入式细胞培养皿等分析P.fluorescensZX和P.digitatum之间竞争的营养物质;同时,测定P.fluorescensZX的生长曲线,利用结晶紫染色法评估P. fluorescens ZX的生物膜形成能力。【结果】P. fluorescens ZX不同处理液之间对采后锦橙绿霉病的作用效果差异显著,菌悬液抑菌效果最好,经菌悬液处理的果实,发病率和病斑直径分别仅为40.83%和1.78 cm;不论是在柑橘皮固体培养基上对峙培养还是在液体培养基中混合培养,菌悬液和原液的作用效果较好,固体平板上,相对抑制率达到了35%–45%,液体培养基中,P. digitatum孢子12 h后的发芽率不超过27%;P. fluorescens ZX产生的挥发性物质具有抑菌作用,经P. fluorescensZX熏蒸处理的锦橙果实,发病率和病斑直径都显著降低;营养竞争试验结果表明,P. fluorescens ZX能更快速有效地消耗柑橘皮培养基中的营养,并和P. digitatum竞争葡萄糖、果糖、蔗糖、天冬氨酸、苏氨酸、丝氨酸、亮氨酸、精氨酸和脯氨酸等营养物质;同时,P. fluorescens ZX生命力强,培养4 h后即进入对数生长期,约24 h后形成成熟的生物膜。【结论】P. fluorescens ZX可能通过抑制P. digitatum孢子发芽、营养与空间竞争、形成生物膜、产生抑菌物质等方式抑制P.digitatum的生长繁殖,有效防治采后锦橙绿霉病。

A mini-review on recent progress of new sensitizers for luminescence of lanthanide doped nanomaterials

Trivalent lanthanide(Ln2+)doped luminescent nanocrystals are promising for applications ranging from biosensor,lasing,super-resolution nanoscopy,information security and so on.Although the utility prospect is of great attractions,the light absorption of these lanthanide doped nanocrystals is inherently weak due to the electric dipole-forbidden 4f→4f transitions.Even worse,the quantum yields of upconverison nanocrystals are very low,which will unavoidably hinder their further applications.In a typical lanthanide luminescent nanosystem,both sensitizers as light absorption centers and activators as light emitting centers are necessary and important for desired luminescence properties.Among various sensitization systems,only Yb3+and Nd+are considered as the most efficient sensitizers.Thus,the corresponding excitation wavelengths are strictly limited around 980 and 808 nm.To enrich excitation wavelengths and boost luminescence intensity,exploring more sensitization units that possess larger absorption cross section,higher efficiency of energy transfer process and independent excitation is imperative and beneficial for the demands of different applications,such as broadened absorption in near infrared(NIR)region for higher conversion efficiency of solar cells,prolonged excitation wavelength to second near infrared windows region(NIR Ⅱ,1,000-1,700 nm)for in vivo fluorescence imaging with deeper tissue depth and higher spatial resolution,more orthogonal excitations and emissions to improve optical multiplexing,and so on.Therefore,in the review,we primarily conclude several major energy transfer mechanisms from sensitizers to activators.Then we present three kinds of sensitizers,including lanthanide ions,organic dyes and quantum dots(QDs),and introduce the newly designed sensitization system that allows us to exploit superior excitation wavelength and amplity luminescence intensity.Finally,several future challenges and opportunities for the sensitizing strategies are discussed in hope of directing and broadening the applications of lanthanide nanosystem.

An Efficient Strategy for Non-probabilistic Reliability-Based Multi-material Topology Optimization with Evidence Theory

It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-probability uncertainty,the multi-material interpolation model is represented by the ordered rational approximation of mat erial properties(ordered RAMP).Combined with structural compliance minimization,the multi-material topology optimization with reliability constraints is established.The corresponding non-probability uncertainties are described by the evidence theory,and the uniformity processing method is introduced to convert the evidence variables into random variables.The first-order reliability method is employed to search the most probable point under the reliability index constraint,and then the random variables are equivalent to the deterministic variables according to the geometric meaning of the reliability index and sensitivity information.Therefore,the non-probabilistic reliability-based multi-material topology optimization is transformed into the conventional deterministic optimization format,followed by the ordered RAMP method to solve the optimization problem.Finally,through numerical examples of 2D and 3D structures,the feasibility and effectiveness of the proposed method are verified to consider the geometrical dimensions and external loading uncertainties.

Unregulated emissions from diesel engine with particulate filter using Fe-based fuel borne catalyst

The alteration and formation of toxic compounds and potential changes in the toxicity of emissions when using after-treatment technologies have gained wide attention. Volatile organic compound（VOC）, carbonyl compound and particle-phase polycyclic aromatic hydrocarbon（PAH） emissions were tested at European Steady State Cycle（ESC） to study unregulated emissions from a diesel engine with a fuel-borne catalyst and diesel particulate filter（FBC–DPF）. An Fe-based fuel-borne catalyst was used for this study. According to the results, brake specific emissions of total VOCs without and with DPF were 4.7 and4.9 mg/kWh, respectively, showing a 4.3% increase. Benzene and n-undecane emissions increased and toluene emission decreased, while other individual VOC emissions basically had no change. When retrofitted with the FBC–DPF, total carbonyl compound emission decreased 15.7%, from 25.8 to 21.8 mg/kWh. The two highest carbonyls, formaldehyde and acetaldehyde, were reduced from 20.0 and 3.7 to 16.5 and 3.3 mg/kWh respectively. The specific reactivity（SR） with DPF was reduced from 6.68 to 6.64 mg/kWh. Total particle-phase PAH emissions decreased 66.4% with DPF compared to that without DPF. However, the Benzo[a]pyrene equivalent（BaPeq） with DPF had increased from 0.016 to 0.030 mg/kWh.Fluoranthene and Pyrene had the greatest decrease, 91.1% and 88.4% respectively. The increase of two- and three-ring PAHs with DPF indicates that the fuel-borne catalyst caused some gas-phase PAHs to adsorb on particles. The results of this study expand the knowledge of the effects of using a particulate filter and a Fe-based fuel-borne catalyst on diesel engine unregulated emissions.

Copolymerization of polyketones catalyzed by polyacrylonitrile resin-supported palladium acetate

The crosslinked polyacrylonitrile (PAN) wassynthesized by suspension polymerization using acrylonitrile(ANT) and divinylbenzene (DVB). Effects of a varietyof conditions on the polymerization of PAN particle sizeand stiffness were investigated. Polyketone was preparedby the copolymerization of carbon monoxide (CO) andstyrene (ST) catalyzed by PAN resin-supported palladiumacetate. The resin-supported catalyst and the copolymerizationproduct were characterized by infrared spectroscopy(IR) and Scanning Electron Microscopy (SEM). Effects ofthe components of a catalytic system and reaction time onthe catalytic activity were studied. The reusability of theresin-supported catalyst was also investigated.Results indicatedthat the resin-supported catalyst has excellent catalyticproperty. The yield of polyketone was 6.2348 g whenusing 1 g of resin and 22.4 mg of palladium acetate.

Visual exploration of Internet news via sentiment score and topic models

Analyzing and understanding Internet news are important for many applications, such as market sentiment investigation and crisis management.However, it is challenging for users to interpret a massive amount of unstructured text, to dig out its accurate meaning, and to spot noteworthy news events.To overcome these challenges, we propose a novel visualization-driven approach for analyzing news text.We first collect Internet news from different sources and encode sentences into a vector representation suitable for input to a neural network, which calculates a sentiment score, to help detect news event patterns. A subsequent interactive visualization framework allows the user to explore the development of and relationships between Internet news topics.In addition, a method for detecting news events enables users and domain experts to interactively explore the correlations between market sentiment, topic distribution, and event patterns. We use this framework to provide a web-based interactive visualization system.We demonstrate the applicability and effectiveness of our proposed system using case studies involving blockchain news.