ZCT Scheme of Push-Pull Forward Converter

The paper proposes a novel zero current transition (ZCT) push pull forward converter. The auxiliary resonant cell is in parallel with the main circuit and the zero current switching (ZCS) range of the main and the auxiliary switches of the proposed converter are entirely achieved. The resonant capacitor achieves high voltage by operating the auxiliary cell. The auxiliary switch turns on before the main switches turn off, the high voltage of resonant capacitor blanks off the rectifier, and then the curr...

Detection method of forward-scatter signal based on Rényi entropy

The application scope of the forward scatter radar(FSR)based on the Global Navigation Satellite System(GNSS)can be expanded by improving the detection capability.Firstly,the forward-scatter signal model when the target crosses the baseline is constructed.Then,the detection method of the for-ward-scatter signal based on the Rényi entropy of time-fre-quency distribution is proposed and the detection performance with different time-frequency distributions is compared.Simula-tion results show that the method based on the smooth pseudo Wigner-Ville distribution(SPWVD)can achieve the best perfor-mance.Next,combined with the geometry of FSR,the influence on detection performance of the relative distance between the target and the baseline is analyzed.Finally,the proposed method is validated by the anechoic chamber measurements and the results show that the detection ability has a 10 dB improvement compared with the common constant false alarm rate(CFAR)detection.

Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

A fast forward computational method for nuclear measurement using volumetric detection constraints

Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation models.Among the various detection tools that use nuclear sources,the detector response can reflect various types of information of the medium.The Monte Carlo method is one of the primary methods used to obtain nuclear detection responses in complex environments.However,this requires a computational process with extensive random sampling,consumes considerable resources,and does not provide real-time response results.Therefore,a novel fast forward computational method(FFCM)for nuclear measurement that uses volumetric detection constraints to rapidly calculate the detector response in various complex environments is proposed.First,the data library required for the FFCM is built by collecting the detection volume,detector counts,and flux sensitivity functions through a Monte Carlo simulation.Then,based on perturbation theory and the Rytov approximation,a model for the detector response is derived using the flux sensitivity function method and a one-group diffusion model.The environmental perturbation is constrained to optimize the model according to the tool structure and the impact of the formation and borehole within the effective detection volume.Finally,the method is applied to a neutron porosity tool for verification.In various complex simulation environments,the maximum relative error between the calculated porosity results of Monte Carlo and FFCM was 6.80%,with a rootmean-square error of 0.62 p.u.In field well applications,the formation porosity model obtained using FFCM was in good agreement with the model obtained by interpreters,which demonstrates the validity and accuracy of the proposed method.

Estimation of Displacement and Extension due to Reverse Drag of Normal Faults: Forward Method

In the case of reverse drag of normal faulting, the displacement and horizontal extension are determined based on the established equations for the three mechanisms: rigid body, vertical shear and inclined shear. There are three sub-cases of basal detachment for the rigid body model: horizontal detachment, antithetic detachment and synthetic detachment. For the rigid body model, the established equations indicate that the total displacement on the synthetic base (Dt2) is the largest, that on the horizontal base (Dt1) is moderate, and that on the antithetic base (Dt3) is the smallest. On the other hand, the value of (Dt1) is larger than the displacement for the vertical shear (Dt4). The value of (Dt1) is larger than or less than the displacement for the inclined shear (Dt5) depending on the original fault dip δ0, bedding angle θ, and the angle of shear direction β. For all original parameters, the value of Dt5 is less than the value of Dt4. Also, by comparing three rotation mechanisms, we find that the inclined shear produces largest extension, the rigid body model with horizontal detachment produces the smallest extension, and the vertical shear model produces moderate extension.

An efficient method for constructing a random insertional mutant library for forward genetics in Nannochloropsis oceanica

Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-strand breaks of DNA,causing insertional mutation.The random insertional mutant library constructed using this method has become a method of forward genetics for gene cloning.However,the establishment of a random insertional mutant library requires a high transformation efficiency of exogenous genes.Many microalgal species show a low transformation efficiency,making constructing random insertional mutant libraries difficult.In this study,we established a highly efficient transformation method for constructing a random insertional mutant library of Nannochloropsis oceanica,and tentatively tried to isolate its genes to prove the feasibility of the method.A gene that may control the growth rate and cell size was identified.This method will facilitate the genetic studies of N.oceanica,which should also be a reference for other microalgal species.

3D seismic forward modeling from the multiphysical inversion at the Ketzin CO_(2) storage site

From June 2008 to August 2013,approximately 67 kt of CO_(2) was injected into a deep saline formation at the Ketzin pilot CO_(2) storage site.During injection,3D seismic surveys have been performed to monitor the migration of sequestered CO_(2).Seismic monitoring results are limited by the acquisition and signal-to-noise ratio of the acquired data.The multiphysical reservoir simulation provides information regarding the CO_(2) fluid behavior,and the approximated model should be calibrated with the monitoring results.In this work,property models are delivered from the multiphysical model during 3D repeated seismic surveys.The simulated seismic data based on the models are compared with the real data,and the results validate the effectiveness of the multiphysical inversion method.Time-lapse analysis shows the trend of CO_(2) migration during and after injection.

Temperature and Salinity Dual-parameter Sensing Based on Forward Brillouin Scattering in 1060-XP SMF

A novel temperature and salinity discriminative sensing method based on forward Brillouin scattering(FBS)in 1060-XP single-mode fiber(SMF)is proposed.The measured frequency shifts corresponding to different radial acoustic modes in 1060-XP SMF show different sensitivities to temperature and salinity.Based on the new phenomenon that different radial acoustic modes have different frequency shift-temperature and frequency shift-salinity coefficients,we propose a novel method for simultaneously measuring temperature and salinity by measuring the frequency shift changes of two FBS scattering peaks.In a proof-of-concept experiment,the temperature and salinity measurement errors are 0.12℃and 0.29%,respectively.The proposed method for simultaneously measuring temperature and salinity has the potential applications such as ocean surveying,food manufacturing and pharmaceutical engineering.

Exploring the Relationship Between Patent Forward Citation and Stock Return Rate Using Empirical Data of China Stock Market

A novel indicator called price-citation was proposed.Based on the company integrated patent database of China listed companies of common stocks(A-shares)with the stock price and the stock return rate data,more than two thousand of A-shares from 2017 to 2020 were selected.The effect of the traditional patent forward citation and the price-citation for discriminating the stock return rate was thoroughly analyzed via ANOVA.The A-shares of forward citation counts above the average showed higher stock return rate means than the A-shares having patents but receiving no forward citations.The price-citation,combining both the financial and patent attributes,defined as the multiplication of the current stock price and the currently receiving forward citation count,showed its excellence in discriminating the stock return rate.The A-shares of higher price-citation showed significantly higher stock return rate means while the A-shares of lower price-citation showed significantly lowest stock return rate means.The price-citation effect had not been changed by COVID-19 though COVID-19 affected the social and economic environment to a considerable extent in 2020.

UAV-based transient electromagnetic 3D forward modeling and inversion and analysis of exploration capability

Unmanned aerial vehicle transient electromagnetic(UAV-TEM)is a novel airborne exploration method that offers advantages such as low cost,simple operation,high exploration efficiency and suitability for near-surface exploration in complex terrain areas.To improve the accuracy of data interpretation in this method,the authors conducted a systematic three-dimensional(3D)forward modeling and inversion of the UAV-TEM.This study utilized the finite element method based on unstructured tetrahedral elements and employed the second-order backward Euler method for time discretization.This allowed for accurate 3D modeling and accounted for the effects of complex terrain.Based on these,the influence characteristics of flight altitudes and the sizes,burial depths,and resistivities of anomalies are compared and analyzed to explore the UAV-TEM systems’exploration capability.Lastly,four typical geoelectrical models of landslides are designed,and the inversion method based on the Gauss-Newton optimization method is used to image the landslide models and analyze the imaging effect of the UAV-TEM method on landslide geohazards.Numerical results showed that UAV-TEM could have better exploration resolution and fine imaging of nearsurface structures,providing important technical support for monitoring,early warning,and preventing landslides and other geological hazards.

Application Strategy of BIM Technology in the Forward Design of Bridges

Bridge engineering is highly specialized and has spatial characteristics,which puts forward higher requirements for design work.The advancement of information technology has provided ample tools to facilitate bridge design work,with building information modeling(BIM)technology being one of them.BIM technology ensures the efficiency and quality of the forward design of bridges,while also reducing construction costs.This article starts with defining the concept of BIM technology,followed by a discussion on its advantages in bridge design and application process,which serves as a reference for other bridge designers.

两种新的push-pull平衡的大数据量无线传感器网络数据分发算法

无线传感器网络中如何获得较低的通信代价同时在事件数据的push和pull之间实现更好的平衡是各种数据分发算法共同追求的目标.分析了目前已公认较好的两种典型的有结构和无结构的数据分发算法,指出了它们的优缺点.在此基础上,结合这两种算法使用的push-pull策略,针对不同应用环境下的无线传感器网络的ALL型查询的特定需求,提出了两种基于有结构和无结构存储模式相结合的混合型数据分发算法,分别是Hybrid-Dcs-Cn1(HDC1)算法和Hybrid-Dcs-Cn2(HDC2)算法.分析表明这两种算法在保证push-pull之间平衡的前提下解决了已有算法存在的热点问题:存储拷贝数多和查询性能低,能更好地适应传感器网络的特点,是两种能量高效的数据分发算法.

Push-Pull型pFLASH开关单元结构设计及特性

基于90 nm eFLASH工艺设计并制备了一种新型抗辐照Push-Pull型pFLASH开关单元,并对其特性进行了研究。该结构由2个2T-FLASH管（T1/T2）和1个信号传输PMOS管（T3）组成,采用带带隧穿（BTBT）编程方式和福勒-诺德海姆（FN）擦除方式实现其＂开/关＂态功能。同时,对其＂开/关＂态特性进行表征,研究其耐久性和电荷保持特性,最后,对其抗总剂量（TID）能力进行评估。实验结果表明：该器件的＂T1编程-T2擦除＂与＂T1擦除-T2编程＂态均可以实现信号传输管的＂开/关＂态功能,其阈值窗口的均值约为10.5 V;在工作电压为-1.2 V条件下,T3管的＂开＂态驱动电流均值约为0.92 mA,＂关＂态漏电流低于40 pA,且均表现出了良好的一致性。同时,该器件的循环擦/写次数可达10 000次,在25℃的＂开/关＂态应力条件下寿命大于10年,抗总剂量能力可达150 krad（Si）以上。

基于第三方的Push-Pull逆向物流模式

首先阐述了逆向物流的内涵、功能以及基于第三方逆向物流的提出,其次分析了外包逆向物流的优势,最后分析了生产控制系统中的Push-Pull方法.在此基础上,提出基于第三方的Push-Pull逆向物流模式.

基于DTN网络的PUSH-PULL策略研究

DTN网络是新一代的网络体系结构,PUSH-PULL是解决DTN网络中拥塞控制的一种有效策略,介绍了DTN网络中拥塞控制的研究现状,并对PUSH-PULL的各个策略进行了阐述,通过NS2搭建DTN网络环境并通过模拟对PUSH-PULL的7种策略进行仿真,模拟仿真结果表明,采用PUSH-PULL策略的可以有效的提高信息的传输率.

高并发数据共享系统基于Push-Pull混合模式的性能优化

随着面向服务架构的大规模分布式系统的应用,多个系统之间由于数据集成的需要,彼此间要高并发传递大量数据,特别是状态数据的同步,对数据的实时性要求越来越高。数据单纯通过客户端以Pull(拉取)模式获取已经不能满足实时性要求,高频率服务调用也会给服务端数据库带来较大的压力。单纯通过服务端以Push(推送)模式推送给客户端也不能满足客户端对个性化数据的需求,大量推送既会给服务端带来较大压力,又会造成客户端数据处理不及时。本文针对高并发数据共享系统应用过程中产生的性能问题,提出一种基于pub/sub消息处理的Push-Pull混合模式优化方案,实践表明该方案极大地提高了系统可用性及数据安全性,对同类系统的性能优化具有较好的借鉴作用。

Push-Pull型不对称钴(III)咔咯的合成与性质

酸催化下,在水-甲醇体系中,合成并分离了3种含有Push-Pull取代基的新型低对称A2B型钴(III)咔咯,其结构经1H NMR,19F NMR和HR-MS(ESI-TOF)表征。并利用光谱学和电化学方法对3种钴咔咯的电子结构进行了深入研究。结果表明:引入Push-Pull型不对称对钴(III)咔咯分子的电子结构有明显的调控作用,且随着引入基团的改变而产生显著的规律性差异,为进一步的分子设计、合成及其应用奠定基础。

Exploiting push-pull strategy to combat the tea green leafhopper based on volatiles of Lavandula angustifolia and Flemingia macrophylla

Thirteen volatile compounds were identified from Flemingia macrophylla plants. Eight major components significantly attracted the tea green leafhoppers, Empoasca flavescens F. Based on their relative abundances, following synthetic blends were made for field experiments: 1) eight-component-attractant blend included Z-3-hexen-1-ol, Z-3-hexenyl acetate, Z-ocimene, Me SA, Z-3-hexenyl butyrate, dodecane, hexadecane and nonanal at 10, 10, 1, 11, 2, 6, 2 and 4 mg mL^-1 in n-hexane, respectively;2) four-component-attractant blend #1 contained hexadecane, Z-3-hexenyl acetate, Z-3-hexen-1-ol and nonanal at 2, 10, 10 and 4 mg mL^-1 in n-hexane, respectively;3) four-component-attractant blend #2 contained hexadecane, Z-3-hexenyl acetate, Z-3-hexen-1-ol and Me SA at 2, 10, 10 and 11 mg mL^-1 in n-hexane, respectively. Thymol and 1-methoxy-4-methyl-2-(1-methylethyl)-benzene, identified from Lavandula angustifolia aeration samples, significantly repelled the leafhopper as strong repellents when tested alone or in combination at 10 mg mL^-1. For field bioassays, each attractant lure was attached to a bud green sticky board hung from a bamboo stick at above tea plant level for catching the leafhoppers, whereas the repellent dispenser was tied to a tea branch inside tea clump for pushing the leafhoppers away from tea clumps. The results showed that the eight-component-attractant blend caught similar numbers of the leafhopper as did the four-component-attractant blend #1 at about 53–79 leafhoppers/trap/day, which were significantly higher than those on the hexane-control bud green sticky boards. Average leafhopper catches from un-baited sticky boards were about 51–73 leafhoppers/trap/day when pushed by the repellents placed inside tea plants, with the two-component-repellent blend being more effective than their single components. When the two-component-repellent blend was further tested with the three attractant blends in a push-pull fashion, average trap catches ranged from 62 to 92 leafhoppers/trap/day. Control efficacy on the leafhoppers within the push-pull zones increased progressively from day 1(43%) to day 5(73%). This push-pull approach might have a great potential as a green control strategy for combating the tea green leafhoppers.

Influential Factors in Employment Location Selection Based on “Push-Pull” Migration Theory—A Case Study in Three Gorges Reservoir Area in China

In China, farmers employed in non-farm work have become important socio-economic actors, but few studies have examined the farmers' perspective in making their work location choices. Based on "push-pull" migration theory, this paper utilizes sectional data from a 2013 survey of farmers in China's Three Gorges Reservoir area to empirically analyze the factors influencing migrant workers' choice of employment location. The results indicate that 60.46% of laborers have migrated from their home province, whereas 39.54% have remained in their home province. Focusing on personal, household, and community characteristics—in addition to the economic characteristics of the sample counties—multinomial logistic regression models reveal that farmer-laborers' employment location decisions are influenced by their personal capital endowment(age, years of education and social networks), family structure(the number of laborers, elders, children and students), home village characteristics(location, economic development level and the degree of relief of the land) and home county economic development level. Notably, male and female laborers' location decisions reveal a converging trend, and their differences are not pronounced. Per capita arable land area has little influence on location decisions, whereas the educational level of laborers has a significant impact. The results differ significantly from those found in previous studies.

Push-Pull Finite-Time Convergence Distributed Optimization Algorithm

With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution rate of the distributed convex optimization algorithm. Each agent in the network has its own convex cost function. We consider a gradient-based distributed method and use a push-pull gradient algorithm to minimize the total cost function. Inspired by the current multi-agent consensus cooperation protocol for distributed convex optimization algorithm, a distributed convex optimization algorithm with finite time convergence is proposed and studied. In the end, based on a fixed undirected distributed network topology, a fast convergent distributed cooperative learning method based on a linear parameterized neural network is proposed, which is different from the existing distributed convex optimization algorithms that can achieve exponential convergence. The algorithm can achieve finite-time convergence. The convergence of the algorithm can be guaranteed by the Lyapunov method. The corresponding simulation examples also show the effectiveness of the algorithm intuitively. Compared with other algorithms, this algorithm is competitive.