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.

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.

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.

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.

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.

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.

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.

Quantifying the thermal damping effect in underground vertical shafts using the nonlinear autoregressive with external input(NARX) algorithm

As air descends the intake shaft, its infrastructure, lining and the strata will emit heat during the night when the intake air is cool and, on the contrary, will absorb heat during the day when the temperature of the air becomes greater than that of the strata. This cyclic phenomenon, also known as the "thermal damping effect" will continue throughout the year reducing the effect of surface air temperature variation. The objective of this paper is to quantify the thermal damping effect in vertical underground airways. A nonlinear autoregressive time series with external input(NARX) algorithm was used as a novel method to predict the dry-bulb temperature(Td) at the bottom of intake shafts as a function of surface air temperature. Analyses demonstrated that the artificial neural network(ANN) model could accurately predict the temperature at the bottom of a shaft. Furthermore, an attempt was made to quantify typical "damping coefficient" for both production and ventilation shafts through simple linear regression models. Comparisons between the collected climatic data and the regression-based predictions show that a simple linear regression model provides an acceptable accuracy when predicting the Tdat the bottom of intake shafts.

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.

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。

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。

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。

光谱技术结合水分校正与样本增广的棉田土壤盐分精准反演

棉田土壤盐分的精准反演对于棉花的种植管理具有重要意义。水分和盐分作为主要环境因素,共同影响棉田土壤的波谱特征,两者之间的耦合关系直接影响土壤盐分的检测分析。为了提高基于光谱技术构建的模型对棉田土壤盐分信息解析的准确性与可靠性,该研究联用可见/短波近红外(400~1 000 nm)和长波近红外(960~1 693 nm)技术,采集不同含水率与含盐量的新疆地区土壤样本的光谱;结合外部参数正交法(external parameter orthogonalization,EPO),校正不同标样集与不同波段光谱中的土壤含水率干扰信息;引入基于不同卷积步幅的深度卷积对抗网络(deep convolutional generative adversarial networks,DCGAN),进行样本增广与质量评估;参考三层残差神经网络设计一维卷积神经网络RNet,最终构建基于EPO-DCGAN-RNet的优化模型,用于棉田土壤盐分的反演。结果表明,与传统机器学习方法和基于VGG或EfficientNet结构一维卷积神经网络相比,该研究提出的EPO-DCGAN-RNet方法能够有效地滤除水分对盐分反演的影响、提高模型对特征波段的挖掘能力、降低深度学习算法对样本量的依赖性,并能得到更优的模型预测性能。EPO-DCGAN-RNet的建模集R^(2)和均方根误差分别为0.942、115.420μS/cm,验证集R^(2)和均方根误差分别为0.910和136.472μS/cm。研究结果可为新疆棉田土壤盐分快速精准检测提供理论指导和技术支持,有助于促进盐碱地区棉花种植的水肥科学管理。

基于网络药理学和分子对接技术探讨中药外敷1号应用于唇炎的相关机制

目的应用网络药理学和分子对接技术探讨中药外敷1号(TCM-EAN1)对于唇炎的相关作用机制。方法在TCMSP数据库中获取TCM-EAN1的活性成分和潜在靶点,疾病靶点利用DisGeNet和GeneCards获取,采用Venny取疾病-药物的交集,采用String数据库构建蛋白互作网络,采用Cytoscape软件构建疾病-靶点-中药有效成分-药物网络,应用David数据库将TCM-EAN1进行GO和KEGG富集分析,应用AutoDock对TCM-EAN1的活性成分和关键治疗唇炎靶点进行分子对接验证。结果TCM-EAN1与唇炎的相关作用靶点共35个,蛋白相互作用(PPI)结果显示核心靶点分别是TP53、TNF、HIF1A、BCL-2、RXRA、EGFR、IL-6、PTGS2、CDKN1A,通过网络构建核心有效成分分别为槲皮素、汉黄芩素、木犀草素、山柰酚、β-谷甾醇、白鲜明碱、前茵芋碱、豆甾醇和苦参素。GO分析共获得429条生物过程,主要有:基因表达的正向调控、凋亡过程的负调控、转录的正调控、炎症反应、细胞外空间、细胞因子活性、生长因子活性等,KEGG共获得107条通路,主要与IL-17信号通路、PI3K-Akt信号通路、Th17细胞分化、TNF信号通路等相关,分子对接结果显示,豆甾醇、β-谷甾醇与核心靶点有较好的结合性。结论通过网络药理学和分子对接技术初步探讨TCM-EAN1对于唇炎的作用机制,为今后临床治疗提供科学依据。

平台“独家交易”的社会福利效应:基于霍特林模型的分析

本文采用霍特林模型和数值模拟方法,揭示了不同竞争环境下平台实行“独家交易”的动机和底层逻辑,以分析其对社会福利和市场竞争格局的影响。研究发现:(1)在高速成长阶段,平台出于扩大规模、扭亏为盈的考虑,一般不会实行“独家交易”。(2)在平稳成熟阶段,优势平台出于提升收益或扩大相对商户规模的目的,有动力单方面实行“独家交易”;而劣势平台出于持续盈利、平稳发展以及维持商户规模(或相对商户规模)的考虑,一般不会主动实行“独家交易”。(3)“独家交易”会损害消费者、商户的福利及社会总福利,并在竞争相对激烈时使劣势平台面临更高比例的商户流失并降低其收益。(4)在竞争相对缓和时,“独家交易”也可能在提升优势平台收益的同时,增加劣势平台收益和商户数量,防止市场格局由“垄断竞争”演变成“完全垄断”。监管部门应考察不同竞争环境下平台“独家交易”对社会福利的差异化影响,并据此完善监管理念、优化监管措施。

蛇伤膏外敷治疗毒蛇咬伤火毒证的疗效观察与网络药理学机制研究

目的:观察蛇伤膏外敷治疗毒蛇咬伤火毒证患者的临床疗效,运用网络药理学方法及分子对接技术分析蛇伤膏治疗毒蛇咬伤潜在的作用机制。方法:选取安徽中医药大学第一附属医院入诊的毒蛇咬伤火毒证患者60例,随机分为对照组和试验组,每组30例。对照组采用常规中医适宜技术治疗,试验组在对照组治疗基础上采用蛇伤膏外敷治疗。观察两组患者临床疗效、症状与体征积分、疼痛与肿胀程度评分、中性粒细胞百分比(NEUT%)、凝血酶原时间(PT)、C反应蛋白(CRP)、白细胞介素-6(IL-6)水平;基于药物与疾病数据库筛选蛇伤膏-毒蛇咬伤靶点及共有靶点,利用DAVID平台进行基因本体(GO)功能分析和京都基因与基因组百科全书(KEGG)通路富集分析,运用Cytoscape构建蛋白相互作用网络(PPI)并筛选关键基因与靶点,利用AutoDockPools1.5.7进行分子对接及PyMol可视化。结果:两组患者临床疗效有效率均为100%,试验组治愈率(67%,20/30例)高于对照组(27%,8/30例),差异有统计学意义(P<0.01);与治疗前比较,试验组治疗后症状与体征积分、疼痛与肿胀程度评分、NEUT、PT、CRP、IL-6水平均下降,差异有统计学意义(P<0.01);两组患者治疗后比较,试验组肿胀程度评分、NEUT均低于对照组,差异有统计学意义(P<0.05),临床疗效、疼痛评分、肢体症状与体征评分、PT、CRP、IL-6指标均明显低于对照组,差异有统计学意义(P<0.01);网络药理学分析显示,蛇伤膏-毒蛇咬伤的核心靶点为表皮生长因子(EGF)、表皮生长因子受体(EGFR)、纤连蛋白1(FN1)、白细胞介素-6(IL-6)、基质金属蛋白酶9(MMP9)、转化生长因子β1(TGF-β1)、肿瘤坏死因子(TNF),核心成分包括槲皮素、黄芩素、木犀草素、汉黄芩素等,主要涉及MAP激酶活性的正调节、细胞外空间、蛋白酶结合、AGE/RAGE通路、TNF等生物功能与信号通路,分子对接结果良好。结论:蛇伤膏治疗毒蛇咬伤火毒证效果显著;网络药理学初步探究了蛇伤膏通过多靶点、多通路途径治疗毒蛇咬伤,与临床相关指标具有联系性,为后续研究提供理论与依据。