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.

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.

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.

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.

Forward stagewise regression with multilevel memristor for sparse coding

Sparse coding is a prevalent method for image inpainting and feature extraction,which can repair corrupted images or improve data processing efficiency,and has numerous applications in computer vision and signal processing.Recently,sev-eral memristor-based in-memory computing systems have been proposed to enhance the efficiency of sparse coding remark-ably.However,the variations and low precision of the devices will deteriorate the dictionary,causing inevitable degradation in the accuracy and reliability of the application.In this work,a digital-analog hybrid memristive sparse coding system is pro-posed utilizing a multilevel Pt/Al_(2)O_(3)/AlO_(x)/W memristor,which employs the forward stagewise regression algorithm:The approxi-mate cosine distance calculation is conducted in the analog part to speed up the computation,followed by high-precision coeffi-cient updates performed in the digital portion.We determine that four states of the aforementioned memristor are sufficient for the processing of natural images.Furthermore,through dynamic adjustment of the mapping ratio,the precision require-ment for the digit-to-analog converters can be reduced to 4 bits.Compared to the previous system,our system achieves higher image reconstruction quality of the 38 dB peak-signal-to-noise ratio.Moreover,in the context of image inpainting,images containing 50%missing pixels can be restored with a reconstruction error of 0.0424 root-mean-squared error.

威斯康星大学发展战略规划2020 Forward专项考察

基于美国威斯康星大学2020 Forward专项的考察结果显示:实施大学发展战略规划在价值逻辑层面呈现校园文化传统、绩效管理工具和危机应对方案三重意蕴;在行动要素层面有赖于目标体系、主体网络和保障机制的协同增效;在反馈闭环层面应形成“目标回溯-措施谋划-评价措施-行动成果-评估成效”的系统耦合。威斯康星2020 Forward的实践经验表明,战略思维、目标分解、全员参与和有效评估是大学发展战略规划精准落地、高效实施的四个关键原则。

THE REGULARIZED SOLUTION APPROXIMATION OF FORWARD/BACKWARD PROBLEMS FOR A FRACTIONAL PSEUDO-PARABOLIC EQUATION WITH RANDOM NOISE

This paper deals with the forward and backward problems for the nonlinear fractional pseudo-parabolic equation ut+(-Δ)^(s1)ut+β(-Δ)^(s2)u=F(u,x,t)subject o random Gaussian white noise for initial and final data.Under the suitable assumptions s1,s2andβ,we first show the ill-posedness of mild solutions for forward and backward problems in the sense of Hadamard,which are mainly driven by random noise.Moreover,we propose the Fourier truncation method for stabilizing the above ill-posed problems.We derive an error estimate between the exact solution and its regularized solution in an E‖·‖Hs22norm,and give some numerical examples illustrating the effect of above method.

3D forward modeling and response characteristics of low-resistivity overburden of the CFS-PML absorbing boundary for ground-well transient electromagnetic method

This study used the stable and convergent Dufort-Frankel method to differentially discretize the diffusion equation of the ground-well transient electromagnetic secondary field.The absorption boundary condition of complex frequency-shifted perfectly matched layer(CFS-PML)was used for truncation so that the low-frequency electromagnetic wave can be better absorbed at the model boundary.A typical three-dimensional(3D)homogeneous half-space model was established and a low-resistivity cube model was analyzed under the half-space condition.The response patterns and drivers of the low-resistivity cube model were discussed under the influence of a low-resistivity overburden.The absorption boundary conditions of CFS-PML significantly affected the low-frequency electromagnetic waves.For a low-resistivity cube around the borehole,its response curve exhibited a single-peak,and the extreme point of the curve corresponded to the center of the low-resistivity body.When the low-resistivity cube was directly below the borehole,the response curve showed three extreme values(two high and one low),with the low corresponding to the center of the low-resistivity body.The total field response of the low-resistivity overburden was stronger than that of the uniform half-space model due to the low-resistivity shielding effect of electromagnetic waves.When the receiving-transmitting distance gradually increased,the effect of the low-resistivity overburden was gradually weakened,and the response of the low-resistivity cube was strengthened.It was affected by the ratio of the overburden resistivity to the resistivity of the low-resistivity body.

Entry-Level Forward Surgical Team Training Is Associated with Increased Confidence of Primary Combat Surgeons

Background: In recent years, we have established an entry-level Forward Surgical Team (FST) training program in a Chinese military medical university for the 5th grade undergraduates, who would be deployed to different military medical services as primary combat surgeons. This study aimed to assess the role of this pre-service training in improving their confidence with combat medical skills, after several years since they received the training. Methods: We conducted a nationwide survey of 239 primary combat surgeons who have ever participated in an entry-level FST training program before deployment between June 2016 and June 2020, which was for evaluating on a 5-point Likert scale the benefits of entry-level FST training and conventional surgery training in improving their confidence with combat medical skills. The difference in scores was compared using the student t-test. Significance was considered as P Results: The total score was significantly higher for entry-level FST training than that for conventional surgery training (30.76 ± 4.33 vs. 28.95 ± 4.80, P There was no significant difference between the training for surgical skills confidence scores (18.03 ± 8.04 vs. 17.51 ± 8.30, P = 0.098), but for non-technical skills, the score of entry-level FST training was significantly higher than that of conventional surgery training (12.73 ± 5.39 vs. 11.44 ± 5.62, P The distributions of confidence scores were different under various subgroups by demographics. There were no significant differences in scores between the two training in all specific surgical skill sets except “life-saving surgery” (P = 0.011). Scores of all 4 non-technical skill sets were significantly higher for entry-level FST than those for conventional surgery training (P Conclusions: The training should be considered as an essential strategy to improve confidence in combat medical skills, especially life-saving surgery and non-technical skills, for primary combat surgeons.

Feed-Forward Neural Network Based Petroleum Wells Equipment Failure Prediction

In the oil industry, the productivity of oil wells depends on the performance of the sub-surface equipment system. These systems often have problems stemming from sand, corrosion, internal pressure variation, or other factors. In order to ensure high equipment performance and avoid high-cost losses, it is essential to identify the source of possible failures in the early stage. However, this requires additional maintenance fees and human power. Moreover, the losses caused by these problems may lead to interruptions in the whole production process. In order to minimize maintenance costs, in this paper, we introduce a model for predicting equipment failure based on processing the historical data collected from multiple sensors. The state of the system is predicted by a Feed-Forward Neural Network (FFNN) with an SGD and Backpropagation algorithm is applied in the training process. Our model’s primary goal is to identify potential malfunctions at an early stage to ensure the production process’ continued high performance. We also evaluated the effectiveness of our model against other solutions currently available in the industry. The results of our study show that the FFNN can attain an accuracy score of 97% on the given dataset, which exceeds the performance of the models provided.

Looking Forward To Oil

China is playing a major role in Uganda’s oil industry development Although oil in Uganda was first discovered in 1925 during the colonial era,it was not until recently that its exploration and plans to exploit the black gold commercially began in earnest.In November 2022,the country’s Minister of Energy and Mineral Development Ruth Nankabirwa Ssentamu said at a conference in Abu Dhabi,“I hope that by April 2025,we shall see the first oil.”

基于FORWARD平台的碳酸盐岩储层测井评价系统的开发与应用

碳酸盐岩裂缝性储层以其自身独有的孔隙空间结构而区别于孔隙性砂岩储层。它的低孔、各向异性、非均质性 3大特点给测井评价带来了多解性、模糊性、不确定性 ,使碳酸盐岩裂缝性储层测井评价成为一个相当棘手的难题。基于FORWARD平台 ,利用WellBase软件开发工具包SDK开发了一套碳酸盐岩储层测井评价软件系统 ,将测井资料与岩心、录井、试油等地质资料相结合 ,编制了粘土分析、储层参数精细评价、横波估算、岩石力学参数计算、裂缝综合评价、地层应力分析、有效厚度划分、成果输出等模块 ,实现了复杂碳酸盐岩储层测井评价人机交互解释。

关于Forward的几个开发应用技巧

从开发和应用2部分介绍关于Forward(Formation Oil& Gas Reservoir Well-logging Analysis& Research&Development)的一些软件开发和平台使用技巧。利用系统底层平台开发工具包进行测井处理动态库深入开发,通过对标准方式的改进,用外挂程序实现曲线校深、成果表输出。介绍在VC开发平台下调用底层WIS接口函数类库的方法。应用技巧介绍在Windows 2000下单机版Forward主机如果不在联网状态下的安装使用方法。用户自定义716格式数据解编模块的扩展应用。

基于Forward-Modeling方法的黑河流域水储量变化特征研究

黑河流域陆地水储量变化对流域下游等周边区域水资源的合理利用以及经济和社会发展等有着重要的意义.本文利用2003年1月至2013年12月的GRACE RL05数据反演了黑河流域陆地水储量长时间序列的变化,并针对重力场模型和数据处理中产生的信号泄漏问题,采用Forward-Modeling方法进行了改正并恢复泄漏信号;将GRACE获得的泄漏信号恢复前后的黑河流域水储量变化结果与全球水文模型GLDAS和CPC进行比较分析,结果表明泄漏信号改正后的结果与水文模型结果的时间序列相关性均有明显提高,从其空间分布结果可以看出Forward-Modeling方法有效地恢复初始信号、增强被湮没的信号,泄漏信号误差减小;通过分析黑河流域水储量变化的长时间序列结果,发现其具有明显的阶段性变化特征,即2003—2006年呈明显下降趋势,约为-0.86cm·a-1,在2007—2010年趋于平衡状态,而2011—2013年则呈现缓慢上升趋势约为0.14cm·a-1;联合GRACE数据和GLDAS数据反演了黑河流域地下水储量变化,并与全球降雨数据GPCC进行了比较分析,两者相关性可达到0.88以上.

FORWARD成像测井资料处理软件应用与效果分析

成像测井测量的物理信息可以表征井壁附近地层的导电特性和声波传播特性。利用这些测量特性可以得到岩性、沉积构造特征和裂缝等信息。FORWARD地质综合评价平台的成像资料处理软件和平台的其他评价软件为地质评价提供了有用的工具。给出了各种地质构造在成像测井成像图上的显示特征,同时给出了泥质条带和各种裂缝、断层、层理、裂缝的有效性判别,还给出了沉积旋回和储层综合评价的典型示例。

FORWARD测井解释平台中使用的先进技术

金勇 ,张世刚 ,顾列刚 ,杜国兵 .FORWARD测井解释平台中使用的先进技术 .测井技术 ,2 0 0 0 ,2 4(1) :6 4～ 70FORWARD是我国第一套完全采用面向对象思想设计和开发的测井解释平台。 FORWARD的开发过程中大量应用了程序自动生成和挂接、分层精细解释、数据一致性、面向对象测井绘图、所见即所得、单一源程序跨平台等先进技术 ,平台开放性好、操作简单。

基于FORWARD平台的水淹层精细解释系统的开发与应用

针对目前大庆喇萨杏油田水淹层解释的技术瓶颈 ,基于FORWARD平台开发了一套适合大庆油田实际情况的水淹层精细解释系统 ;编制了分层取值、储层属性划分、水淹层解释、参数修正、成果输出等模块 ,实现了水淹层测井资料一次测井解释与专家交互解释 ,具有较强的实用价值。

基于Forward平台的固井资料预处理研究

临盘地区后期开采大多以电缆射孔为主,对射孔深度精度要求较高,其深度依据主要来自于测井所提供的磁定位曲线。磁定位曲线受干扰因素较多,且测井过程中会存在一定的拉伸误差。Forward平台的预处理模块并未将固井资料进行单独研究,为满足该地区的生产需要,专门开展针对固井资料的预处理技术研究。该技术包括自动磁定位噪声消除、自动深度校正;校正时以每根套管间拉伸/压缩量小于0.2m为约束条件,达到减小局部深度误差的目的。计算机预处理方法的成功实现,代替了传统低效、繁杂的手工处理方式,提高工作效率的同时降低了资料处理中的人为误差。在临盘地区的实践表明,该预处理方法高效、可靠,值得在以电缆射孔为主的油田及区块推广应用。