Unraveling the efficacy network: A network meta-analysis of adjuvant external beam radiation therapy methods after hepatectomy

BACKGROUND Primary liver cancer is a malignant tumor with a high recurrence rate that significantly affects patient prognosis.Postoperative adjuvant external radiation therapy(RT)has been shown to effectively prevent recurrence after liver cancer resection.However,there are multiple RT techniques available,and the differ-ential effects of these techniques in preventing postoperative liver cancer re-currence require further investigation.AIM To assess the advantages and disadvantages of various adjuvant external RT methods after liver resection based on overall survival(OS)and disease-free survival(DFS)and to determine the optimal strategy.METHODS This study involved network meta-analyses and followed the PRISMA guidelines.The data of qualified studies published before July 10,2023,were collected from PubMed,Embase,the Web of Science,and the Cochrane Library.We included relevant studies on postoperative external beam RT after liver resection that had OS and DFS as the primary endpoints.The magnitudes of the effects were determined using risk ratios with 95%confidential intervals.The results were analyzed using R software and STATA software.RESULTS A total of 12 studies,including 1265 patients with hepatocellular carcinoma(HCC)after liver resection,were included in this study.There was no significant heterogeneity in the direct paired comparisons,and there were no significant differences in the inclusion or exclusion criteria,intervention measures,or outcome indicators,meeting the assumptions of heterogeneity and transitivity.OS analysis revealed that patients who underwent stereotactic body radiotherapy(SBRT)after resection had longer OS than those who underwent intensity modulated radiotherapy(IMRT)or 3-dimensional conformal RT(3D-CRT).DFS analysis revealed that patients who underwent 3D-CRT after resection had the longest DFS.Patients who underwent IMRT after resection had longer OS than those who underwent 3D-CRT and longer DFS than those who underwent SBRT.CONCLUSION HCC patients who undergo liver cancer resection must consider distinct advantages and disadvantages when choosing between SBRT and 3D-CRT.IMRT,a RT technique that is associated with longer OS than 3D-CRT and longer DFS than SBRT,may be a preferred option.

The Mechanism Behind Urban Population Growth and Shrinkage from the Perspective of Urban Network Externalities

Urban shrinkage is a global phenomenon,and it will coexist with urban growth for many years.At the same time,the network connection between cities continuously improved due to the construction of the transportation and information networks.However,the relationship between urban network externalities and urban population growth/shrinkage remains unclear.Therefore,based on high-speed railway(HSR)flow data,a spatial econometric model is used to explore the mechanism behind urban population growth and shrinkage from the perspective of network externalities in China.The results indicate that:1)the urban network experiences a certain clubbing effect.Growing cities that are strongly connected are concentrated along China’s main railway lines and the southeastern coastal areas,while shrinking cities that are weakly connected are distributed at the periphery of the network.2)Moreover,the network externality disregards spatial distance and together with the agglomeration externality influences the growth and shrinking of cities.3)Urban economic development still promotes the development of Chinese cities.However,the improvement of the urban economy has a negative cross-regional spillover effect on neighboring cities due to urban competition.4)Lastly,Local spillovers of urban network externalities are positive,while cross-regional ones are negative.Consequently,the government needs to promote the construction of multi-dimensional network connections between cities to promote cities’sustainable development.This study reveals the relationship between urban network externalities and urban development,enriches the theories of network externalities and urban growth/shrinkage,and provides a reference for regional coordinated development.

Behavior Analysis of Bank into E-Commerce under Network Externalities

With the advent of Internet financial innovation,many commercial banks quietly have started to enter into the Ecommercial in order to prevent oligarchs from eroding financial market.From the perspective of industrial division,this paper reveals the nature of a phenomenon that E-commercial enterprises and banks have stepped into each other's field,which E-commerce of banks can give full play to network effects.Then it uses game theory to analyze the motions of banks to involve into E-commerce and the short-term competitive equilibrium of large incumbent Ecommercial enterprises as well.For individual rationality,the dominant strategy of banks and E-commercial enterprises is(enter,counterattack).Considering network externalities,it constructs a competing model on banks and incumbent E-commercial enterprises and simulates competitive trends and balanced results of their behaviors,which illustrates that banks can obtain network effect after choosing E-commerce strategy.

Circular Formation Flight Control for Unmanned Aerial Vehicles With Directed Network and External Disturbance

This paper proposes a new distributed formation flight protocol for unmanned aerial vehicles(UAVs)to perform coordinated circular tracking around a set of circles on a target sphere.Different from the previous results limited in bidirectional networks and disturbance-free motions,this paper handles the circular formation flight control problem with both directed network and spatiotemporal disturbance with the knowledge of its upper bound.Distinguishing from the design of a common Lyapunov fiunction for bidirectional cases,we separately design the control for the circular tracking subsystem and the formation keeping subsystem with the circular tracking error as input.Then the whole control system is regarded as a cascade connection of these two subsystems,which is proved to be stable by input-tostate stability(ISS)theory.For the purpose of encountering the external disturbance,the backstepping technology is introduced to design the control inputs of each UAV pointing to North and Down along the special sphere(say,the circular tracking control algorithm)with the help of the switching function.Meanwhile,the distributed linear consensus protocol integrated with anther switching anti-interference item is developed to construct the control input of each UAV pointing to east along the special sphere(say,the formation keeping control law)for formation keeping.The validity of the proposed control law is proved both in the rigorous theory and through numerical simulations.

Pinning Synchronization Between Two General Fractional Complex Dynamical Networks With External Disturbances

In this paper, the pinning synchronization between two fractional complex dynamical networks with nonlinear coupling, time delays and external disturbances is investigated.A Lyapunov-like theorem for the fractional system with time delays is obtained. A class of novel controllers is designed for the pinning synchronization of fractional complex networks with disturbances. By using this technique, fractional calculus theory and linear matrix inequalities, all nodes of the fractional complex networks reach complete synchronization. In the above framework, the coupling-configuration matrix and the innercoupling matrix are not necessarily symmetric. All involved numerical simulations verify the effectiveness of the proposed scheme.

Attention-based spatio-temporal graph convolutional network considering external factors for multi-step traffic flow prediction

Traffic flow prediction is an important part of the intelligent transportation system. Accurate multi-step traffic flow prediction plays an important role in improving the operational efficiency of the traffic network. Since traffic flow data has complex spatio-temporal correlation and non-linearity, existing prediction methods are mainly accomplished through a combination of a Graph Convolutional Network (GCN) and a recurrent neural network. The combination strategy has an excellent performance in traffic prediction tasks. However, multi-step prediction error accumulates with the predicted step size. Some scholars use multiple sampling sequences to achieve more accurate prediction results. But it requires high hardware conditions and multiplied training time. Considering the spatiotemporal correlation of traffic flow and influence of external factors, we propose an Attention Based Spatio-Temporal Graph Convolutional Network considering External Factors (ABSTGCN-EF) for multi-step traffic flow prediction. This model models the traffic flow as diffusion on a digraph and extracts the spatial characteristics of traffic flow through GCN. We add meaningful time-slots attention to the encoder-decoder to form an Attention Encoder Network (AEN) to handle temporal correlation. The attention vector is used as a competitive choice to draw the correlation between predicted states and historical states. We considered the impact of three external factors (daytime, weekdays, and traffic accident markers) on the traffic flow prediction tasks. Experiments on two public data sets show that it makes sense to consider external factors. The prediction performance of our ABSTGCN-EF model achieves 7.2%–8.7% higher than the state-of-the-art baselines.

Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.

High-speed Railway External Power Supply Reliability Evaluation of Bayesian Network

Reliability evaluation is important in high speed railway external power supply design, based on probability reasoning bayesian network applied in high-speed railway external power supply reliability evaluation, establish the minimum cut and the minimum path of bayesian network model, quantitative calculation external power supply system in each element posterior probability, and the example analysis verified the feasibility and correctness of the above method. Using bayesian network bidirection reasoning technology, quantitative calculation the posterior probability of each element in external power supply system, realized the identification of weak link in external power supply. The research methods and the results of the study can be used in the scheme optimization design of high speed railway external power supply.

Network meta-analysis of the effectiveness of TCM external treatment in the treatment of mycoplasmal pneumonia

Objective: To compare the efficacy and safety of different TCM external treatment combined with azithromycin in the treatment of Mycoplasma pneumoniae pneumonia. Methods: The keywords and free words were combined to search the literatures of clinical randomized or quasi-randomized controlled trials on the effects of TCM external treatment combined with azithromycin in the treatment of children with MPP in CNKI, VIP, CBM, Wan Fang Date, PubMed, Sciencedirect and Google Academic Database. The search time limit is from August 2019. After two independent reviewers selected the literature, extracted data and literature quality evaluation according to the inclusion and exclusion criteria, the ADDI software, RevMan5.3 and stata14.0 software were used for mesh meta-analysis. Results: A total of 18 randomized controlled literatures were included, involving 1536 children with MPP, 6 Chinese medicine external treatment methods (ultra-short wave, acupoint application, cupping, enema, Chinese medicine patch, massage). The results of mesh meta-analysis showed that treatment In terms of MPP efficiency, ultrashort wave, acupoint application, cupping, enema, Chinese medicine patch, massage combined with azithromycin treatment is more effective than azithromycin alone, and the probability distribution shows that the Chinese medicine patch combined with azithromycin treatment is the best solution (P= 0.34). In the reduction of adverse reactions, because the ultrashort wave and traditional Chinese medicine patch literature did not mention the non-performing rate, this study only analyzed the other four external treatment methods, acupoint application, cupping, enema, massage combined with azithromycin is better than single With azithromycin, the probability distribution showed that the probability of massage combined with azithromycin was the best (P=0.67). Conclusion: In terms of efficiency and reduction of adverse reactions, each Chinese medicine external treatment combined with azithromycin has an advantage over single azithromycin. Probability distribution shows that in the treatment of MPP efficiency, Chinese medicine patch + Achi > ultrashort wave + AZM > enema + AZM > cupping + AZM > massage + Aqi, Chinese medicine patch + azithromycin program is the optimal program;In terms of reducing adverse reactions, massage + AZM > enema + AZM > acupressure application + AZM > cupping +AZM.

A Sentence Retrieval Generation Network Guided Video Captioning

Currently,the video captioning models based on an encoder-decoder mainly rely on a single video input source.The contents of video captioning are limited since few studies employed external corpus information to guide the generation of video captioning,which is not conducive to the accurate descrip-tion and understanding of video content.To address this issue,a novel video captioning method guided by a sentence retrieval generation network(ED-SRG)is proposed in this paper.First,a ResNeXt network model,an efficient convolutional network for online video understanding(ECO)model,and a long short-term memory(LSTM)network model are integrated to construct an encoder-decoder,which is utilized to extract the 2D features,3D features,and object features of video data respectively.These features are decoded to generate textual sentences that conform to video content for sentence retrieval.Then,a sentence-transformer network model is employed to retrieve different sentences in an external corpus that are semantically similar to the above textual sentences.The candidate sentences are screened out through similarity measurement.Finally,a novel GPT-2 network model is constructed based on GPT-2 network structure.The model introduces a designed random selector to randomly select predicted words with a high probability in the corpus,which is used to guide and generate textual sentences that are more in line with human natural language expressions.The proposed method in this paper is compared with several existing works by experiments.The results show that the indicators BLEU-4,CIDEr,ROUGE_L,and METEOR are improved by 3.1%,1.3%,0.3%,and 1.5%on a public dataset MSVD and 1.3%,0.5%,0.2%,1.9%on a public dataset MSR-VTT respectively.It can be seen that the proposed method in this paper can generate video captioning with richer semantics than several state-of-the-art approaches.

产能分享平台企业的盈利模式选择与定价研究

在分享经济背景下,考虑交叉网络外部性效用及平台匹配率,研究产能分享平台的盈利模式选择与定价问题。基于两阶段博弈方法,分析并比较了平台在利润最大化和社会福利最大化条件下选择服务费模式与注册费模式时获得的最大利润。研究发现,在目标时间段内,当平台以利润最大化为目标时,多数情况下选择注册费模式获得的最大利润高于选择服务费模式获得的利润。在特定条件下,也存在平台采取两种盈利模式会获得相同利润的情况。此外,平台最大利润在一定条件下与交叉网络外部性系数和平台对制造能力供应方的匹配率正相关,与对制造能力需求方的匹配率负相关。当平台以社会福利最大化为目标时,选择服务费模式获得的利润高于选择注册费模式时的利润。最后,通过数值算例对上述结果进行了验证。

融合外部注意力机制的序列到点非侵入式负荷分解

非侵入式负荷分解可以深度挖掘用户电力消耗数据蕴含的信息价值,为电力设备故障监测、需求响应等决策分析提供重要参考.为有效解决非侵入式负荷分解算法训练时间成本与分解精度间的冲突,提出一种融合外部注意力机制的序列到点非侵入式负荷分解算法.首先,将总负荷功率消耗序列进行数据清理、标准化等预处理,以固定窗口长度构建训练输入数据,输入数据通过编码层自动提取设备特征;然后,设计外部注意力机制增强重要特征权值;最终,输入到解码层得到负荷分解结果.利用REDD与UK-DALE两种公开数据集进行模型仿真计算,在信号聚合误差、平均绝对误差、标准化分解误差指标、模型分解曲线、特征图和用户耗能等方面进行对比分析,本文模型克服了卷积层注意力分散的缺点,增强了对有效信息的提取与利用能力,在未增加训练时间成本的前提下具有更高的分解精度.

成年国民阅读意愿的动因解析及“全民阅读”活动启示

提高成年国民阅读意愿是全民阅读活动的根本目的。文章在理论刻画阅读意愿生成逻辑的基础上,运用机器学习方法实证分析了我国成年国民阅读意愿的系统动因和核心要素,由此形成全民阅读活动提质增效的管理启示。研究发现:(1)系统动因分析显示“预期绩效、预期努力、享乐动机”等内部动因贡献度是“社会影响、促进条件”等外部动因贡献度的1.5倍;(2)核心要素分析显示“享乐动机”的敏感度为0.245,位居所有影响因子之首;(3)对低阅读意愿组的“用户画像”结果显示其受教育程度和经济条件与阅读意愿密切相关,就其内部动因而言,该群体对阅读“预期绩效”持有的消极信念是抑制其阅读意愿的关键原因。

结合外部知识重构依赖矩阵的交互式图卷积网络

方面级情感分析旨在预测给定句子中特定方面的情感极性。然而,现有大多数研究在对模型改进的过程中忽略了外部知识的有效利用,导致模型无法准确识别方面词的情感极性。另外,仅仅考虑有限的上下文信息可能会使得模型在分析方面词时忽略其在句子中的重要性和影响。基于此,提出了一种结合外部知识构建依赖增强矩阵的图卷积网络模型的方法(Dependency Enhancement Matrix GCN,DEMGCN)。该方法首先将词嵌入和位置嵌入进行融合,得到包含位置信息的句子特征向量;同时引入情感常识信息对原始依赖矩阵进行扩展,形成新的依赖增强矩阵DEM,这在一定程度上突出了情感词的权重信息,并且弥补了原始依赖树无法捕获边缘标签的不足。此外,构建了一个信息交互网络(Information Interaction Network,IIN),通过方面词与上下文之间的交互来提取全局的句子信息。最后,在5个基准数据集上的实验结果显示,与基线模型相比DEMGCN在准确率和Macro-F1上分别提高了1~2百分点。

中国城市经济韧性和人口收缩——基于相关多样性和城际联系的解释

城市经济韧性和人口收缩是城市应对结构性危机中两种相关联的特征。文章以2010—2020年中国地级及以上城市为对象,分析当前中国城市的经济韧性和人口收缩特征,并从城市自身技术相关多样性和外部城际联系两方面进行解释。研究发现,城市经济韧性和人口增长正相关,但也存在经济韧性和人口增长相背离的城市,中国城市据此可以分为人口扩张—韧性强、人口扩张—韧性弱、人口收缩—韧性强、人口收缩—韧性弱四种类型。实证结果表明:相关多样性和城际联系都影响城市经济韧性和人口变动,对于人口收缩型城市来说,经济韧性提升的关键是城市自身的技术相关多样性和城市网络联系,而“中心—腹地”联系的极化效应会导致腹地和边缘城市的人口收缩,但城市自身的技术相关多样性和城市网络联系则可能帮助抑制人口收缩。

董事网络能促进企业数字化转型吗?——基于独立董事网络中心度的考查

本文基于镶嵌理论和声誉理论,以2007—2020年沪深A股上市公司为样本,研究独立董事所处网络中心度对所任职企业数字化转型的影响。研究发现,独立董事所处的网络中心度越高,企业数字化转型的程度越大,说明董事网络显著促进了企业数字化转型。经稳健性检验后,该结论仍然成立。机制检验表明,独立董事网络中心度通过降低代理成本、缓解融资约束推动企业数字化转型进程。进一步研究发现,对于制度环境较差地区的企业、信息透明度较高的企业以及民营企业,独立董事网络中心度对企业数字化转型的推动作用更显著。研究结论对于如何推动数字经济与实体企业深度融合,实现企业高质量发展有重要的参考价值。

外部技术网络嵌入、知识重组能力与制造企业节能减排

在加快发展方式绿色转型的战略部署下,作为绿色转型的关键实施主体,制造企业不断利用网络嵌入和知识重组以促进其在能源消耗和污染排放工作的平稳、有序推进。本文以中国制造业A股上市公司为研究对象,收集整理企业联合申请发明专利数据,采用社会网络分析软件对外部技术网络嵌入的技术网络地位和网络有效规模进行测算,基于“外部合作-知识重组-节能减排”的逻辑思路分别探索外部技术网络嵌入对制造企业节能减排的直接效应,以及从知识重组视角探讨知识再创造和知识再利用在其中的中介作用。结果表明:技术网络地位和网络有效规模显著有利于降低合作企业的能源消耗和污染排放,知识重组能力在技术网络地位与网络有效规模对节能减排的影响中存在显著中介作用。据此提出相应的管理启示以提高制造企业节能减排成效,为推进“统筹发展与绿色低碳转型,深入实施绿色制造”提供一定的经验证据。

麻雀搜索算法优化的外啮合齿轮泵泄漏量预测

预测齿轮泵泄漏量的变化趋势有助于定量分析其性能退化过程。变分模态分解(Variational Modal Decomposition, VMD)方法对齿轮泵原始泄漏量数据进行变分模态分解,得到本征模态函数IMF,提出一种结合麻雀优化算法(Sparrow Search Algorithm, SSA)和长短期记忆神经网络(Long-Short Term Memory, LSTM)的模型,建立VMD-SSA-LSTM模型预测齿轮泵泄漏量的变化情况,并对每一个分量进行单独预测,最后将预测结果进行叠加,获得完整的预测结果。通过对比不同时间段预测结果可知,VMD-SSA-LSTM模型较单一的LSTM模型预测结果的平均相对误差最高可减小25.2%,能够完成对泄漏量的有效预测。研究结论可为齿轮泵性能衰退的定量预测提供理论支持。

基于改进Faster R-CNN的变电站设备外部缺陷检测

针对变电站设备外部缺陷目标检测任务中目标形状多样,周围环境复杂,当前代表性算法识别准确度低,错检漏检严重的问题,对比了众多目标检测算法在变电站设备缺陷数据集上的检测结果,检测精度较高的是添加了特征融合金字塔结构的Faster R-CNN(faster region-based convolutional network)算法,但其对小目标物体和设备渗漏油的检测精度仍有提升空间,为此设计一种基于Faster R-CNN的改进算法。改进算法通过对输入图像进行数据增强,在网络中添加SPP(spatial pyramid pooling)结构以及改进特征融合方式,对分类以及边界框回归损失函数进行改进的方式来提高缺陷的检测精度。与原Faster R-CNN算法进行对比,改进算法在变电站设备缺陷目标检测数据集的检测结果中AP(average precision)(0.5∶0.95)提高了2.7个百分点,AP(0.5)提高了4.3个百分点,对小目标物体的检测精度也提高了1.8个百分点,试验结果验证了该方法的有效性。