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Machine perfusion versus cold storage of livers: a meta-analysis

null

《医学前沿（英文）》 2016年 第10卷 第4期   页码 451-464 doi: 10.1007/s11684-016-0474-7

摘要：

Different organ preservation methods are key factors influencing the results of liver transplantation. In this study, the outcomes of experimental models receiving donation after cardiac death (DCD) livers preserved through machine perfusion (MP) or static cold storage (CS) were compared by conducting a meta-analysis. Standardized mean difference (SMD) and 95% confidence interval (CI) were calculated to compare pooled data from two animal species. Twenty-four studies involving MP preservation were included in the meta-analysis. Compared with CS preservation, MP can reduce the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), and hyaluronic acid (HA) and the changes in liver weight. By contrast, MP can enhance bile production and portal vein flow (PVF). Alkaline phosphatase (ALP) levels and histological changes significantly differed between the two preservation methods. In conclusion, MP of DCD livers is superior to CS in experimental animals.

关键词： machine perfusion     cold storage     DCD     meta-analysis    

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“机械灌注+”应用于扩大标准供肝移植——肝尽其用 Review

王周城, Jack Martin, 余炯杰, 汪恺, Kourosh Saeb-Parsy, 徐骁

《工程（英文）》 2024年 第32卷 第1期   页码 30-41 doi: 10.1016/j.eng.2023.11.003

摘要：

移植是终末期肝病最有效的治疗方法，但由于供体器官的短缺而受到限制。扩大标准供体（ECD）供肝在临床实践中越来越多地用于缓解这一挑战。然而，这些移植物耐受缺血的能力下降，危及冷保存期间器官的活力。机器灌注（MP）旨在改善器官保存并减少移植后并发症。然而，越来越明显的是，单独使用MP无法达到ECD供肝的最佳保存。因此，人们逐渐开始重视改良的 MP 策略，包括使用不同的灌注剂、改良的灌注方式并结合不同的治疗干预策略。本文中，我们提出了“机械灌注+”的新理念，代表这些旨在提升器官功能并可能实现ECD供肝体外再生的机械灌注新策略。为此，我们总结了现有和改良的MP策略，并阐述其在临床场景中修复不同ECD供肝的优势。

关键词： 肝移植     扩大标准供体     机械灌注+     器官短缺    

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Simultaneous acquisition of CT angiography and whole brain CT perfusion images by using multiphase dynamic

Weiwei CHEN, Jianpin QI, Wenzhen ZHU, Wenhua HUANG, Jinmei SONG

《医学前沿（英文）》 2009年 第3卷 第2期   页码 230-235 doi: 10.1007/s11684-009-0023-8

摘要： We implemented a new protocol — multiphase dynamic helical scan to acquire CT angiography (CTA) and whole brain CT perfusion (CTP) images simultaneously with single scan on 16 multidetector CT (MDCT). A total of 90 patients who were randomly assigned into 3 groups were included in our study. Each group underwent CT scan by using the new protocol, traditional CTA and CTP protocol, respectively. The image quality of CTA, the CTP parameter values and the X-ray doses were measured and compared between the new protocol and the traditional protocols. There was no statistically significant difference in the CTA image quality between the above methods ( =0.55). For CTP parameters, the new protocol tended to overestimate the blood volume (BV) and blood flow (BF) value, and to underestimate the mean transit time (MTT) value compared with the traditional method. However, there was no statistically significant difference in BV, BF, and MTT value between the two methods except permeability surface (PS) ( >0.05). The volume CT dose index (CTDIvol) and dose length product (DLP) of our protocol were lower than the traditional one. The new protocol can obtain valuable diagnostic information in a shorter time without significant compromise in image quality. In addition, it reduces the radiation dose as well as contrast medium usage on the patient.

关键词： computed tomography angiography     computed tomography perfusion    

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Dimensional synthesis of a novel 5-DOF reconfigurable hybrid perfusion manipulator for large-scale sphericalhoneycomb perfusion

Hui YANG, Hairong FANG, Yuefa FANG, Xiangyun LI

《机械工程前沿（英文）》 2021年 第16卷 第1期   页码 46-60 doi: 10.1007/s11465-020-0606-2

摘要： A novel hybrid perfusion manipulator (HPM) with five degrees of freedom (DOFs) is introduced by combining the 5PUS-PRPU (P, R, U and S represent prismatic, revolute, universal and spherical joint, respectively) parallel mechanism with the 5PRR reconfigurable base to enhance the perfusion efficiency of the large-scale spherical honeycomb thermal protection layer. This study mainly presents the dimensional synthesis of the proposed HPM. First, the inverse kinematics, including the analytic expression of the rotation angles of the U joint in the PUS limb, is obtained, and mobility analysis is conducted based on screw theory. The Jacobian matrix of 5PUS-PRPU is also determined with screw theory and used for the establishment of the objective function. Second, a global and comprehensive objective function (GCOF) is proposed to represent the Jacobian matrix’s condition number. With the genetic algorithm, dimensional synthesis is conducted by minimizing GCOF subject to the given variable constraints. The values of the designed variables corresponding to different configurations of the reconfigurable base are then obtained. Lastly, the optimal structure parameters of the proposed 5-DOF HPM are determined. Results show that the HPM with the optimized parameters has an enlarged orientation workspace, and the maximum angle of the reconfigurable base is decreased, which is conducive to improving the overall stiffness of HPM.

关键词： 5-DOF hybrid manipulator     reconfigurable base     large workspace     dimensional synthesis     optimal design    

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Evaluation of the effect of myocardial perfusion after percutaneous coronary intervention in coronary

WANG Hong, HUANG Lan, JIN Jun, SONG Yaoming, GENG Zhaohua, YU Xuejun, QIN Jun, ZHAO Gang, GAO Yunhua, LIU Zheng

《医学前沿（英文）》 2007年 第1卷 第1期   页码 62-67 doi: 10.1007/s11684-007-0013-7

摘要： Detection of abnormal myocardial perfusion is crucial to the prognosis of patients with coronary artery disease (CAD) after they have undergone percutaneous coronary intervention (PCI). The objective of this study is to evaluate the effect of myocardial perfusion by three different methods intra-coronary myocardial contrast echocardiography (ICMCE), corrected thrombolysis in myocardial infarction frame count (CTFC), and coronary blood flow velocity (BFV) and to determine the value of these different methods in the evaluation of the effect of myocardial perfusion post-PCI. For the study sixty-eight patients were divided into four groups based on selective coronary angiography results: group A (normal coronary artery), group B (75% 95% coronary artery stenosis), group C (coronary artery stenosis >95%) and group D (acute total coronary occlusion). The effect of myocardial reperfusion was evaluated using the above mentioned three methods 15 min after PCI. IC-MCE was also performed before PCI in group D. The quantitative parameters of MCE involved: contrast peak intensity, time to peak intensity and area under the curve, representing myocardial blood volume, reperfusion velocity and myocardial blood flow, respectively. No difference was found in CTFC between the coronary artery stenosis group and the normal group. BFV was slower in group D than in group A (<0.05). The myocardial blood volume and the myocardial blood flow of the IC-MCE quantitative parameters were markedly lower in group C compared with those in group A (<0.05), and there were significant differences in the three MCE parameters between group D and group A (<0.05). For those patients with acute or total occlusion, the levels of myocardial perfusion before and after PCI were similar, as determined by IC-MCE and visually analyzed from 61 segments (<0.05). Quantitative IC-MCE evaluation of myocardial reperfusion is more accurate than with the other two methods. Moreover, with qualitative IC-MCE the level of myocardial reperfusion can be viewed directly and rapidly. Thus, the IC-MCE method is of great value to coronary artery disease (CAD) patients undergoing PCI, especially for those with acute myocardial infarction (AMI).
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Challenges of human–machine collaboration in risky decision-making

《工程管理前沿（英文）》 2022年 第9卷 第1期   页码 89-103 doi: 10.1007/s42524-021-0182-0

摘要： The purpose of this paper is to delineate the research challenges of human–machine collaboration in risky decision-making. Technological advances in machine intelligence have enabled a growing number of applications in human–machine collaborative decision-making. Therefore, it is desirable to achieve superior performance by fully leveraging human and machine capabilities. In risky decision-making, a human decision-maker is vulnerable to cognitive biases when judging the possible outcomes of a risky event, whereas a machine decision-maker cannot handle new and dynamic contexts with incomplete information well. We first summarize features of risky decision-making and possible biases of human decision-makers therein. Then, we argue the necessity and urgency of advancing human–machine collaboration in risky decision-making. Afterward, we review the literature on human–machine collaboration in a general decision context, from the perspectives of human–machine organization, relationship, and collaboration. Lastly, we propose challenges of enhancing human–machine communication and teamwork in risky decision-making, followed by future research avenues.

关键词： human–machine collaboration     risky decision-making     human–machine team and interaction     task allocation     human–machine relationship    

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Spatial prediction of soil contamination based on machine learning: a review

《环境科学与工程前沿（英文）》 2023年 第17卷 第8期 doi: 10.1007/s11783-023-1693-1

摘要：

● A review of machine learning (ML) for spatial prediction of soil contamination.

关键词： Soil contamination     Machine learning     Prediction     Spatial distribution    

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Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning

《环境科学与工程前沿（英文）》 2023年 第17卷 第10期 doi: 10.1007/s11783-023-1721-1

摘要：

● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste.

关键词： Elemental composition     Infrared spectroscopy     Machine learning     Moisture interference     Solid waste     Spectral noise    

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State-of-the-art applications of machine learning in the life cycle of solid waste management

《环境科学与工程前沿（英文）》 2023年 第17卷 第4期 doi: 10.1007/s11783-023-1644-x

摘要：

● State-of-the-art applications of machine learning (ML) in solid waste (SW) is presented.

关键词： Machine learning (ML)     Solid waste (SW)     Bibliometrics     SW management     Energy utilization     Life cycle    

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Research and application of visual location technology for solder paste printing based on machine vision

Luosi WEI, Zongxia JIAO

《机械工程前沿（英文）》 2009年 第4卷 第2期   页码 184-191 doi: 10.1007/s11465-009-0034-9

摘要： A location system is very important for solder paste printing in the process of surface mount technology (SMT). Using machine vision technology to complete the location mission is new and very efficient. This paper presents an integrated visual location system for solder paste printing based on machine vision. The working principle of solder paste printing is introduced and then the design and implementation of the visual location system are described. In the system, two key techniques are completed by secondary development based on VisionPro. One is accurate image location solved by the pattern-based location algorithms of PatMax. The other one is camera calibration that is achieved by image warping technology through the checkerboard plate. Moreover, the system can provide good performances such as high image locating accuracy with 1/40 sub-pixels, high anti-jamming, and high-speed location of objects whose appearance is rotated, scaled, and/or stretched.

关键词： machine vision     visual location     solder paste printing     VisionPro    

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Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method

《环境科学与工程前沿（英文）》 2023年 第17卷 第11期 doi: 10.1007/s11783-023-1738-5

摘要：

● A novel integrated machine learning method to analyze O3 changes is proposed.

关键词： Ozone     Integrated method     Machine learning    

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Evaluation and prediction of slope stability using machine learning approaches

《结构与土木工程前沿（英文）》 2021年 第15卷 第4期   页码 821-833 doi: 10.1007/s11709-021-0742-8

摘要： In this paper, the machine learning (ML) model is built for slope stability evaluation and meets the high precision and rapidity requirements in slope engineering. Different ML methods for the factor of safety (FOS) prediction are studied and compared hoping to make the best use of the large variety of existing statistical and ML regression methods collected. The data set of this study includes six characteristics, namely unit weight, cohesion, internal friction angle, slope angle, slope height, and pore water pressure ratio. The whole ML model is primarily divided into data preprocessing, outlier processing, and model evaluation. In the data preprocessing, the duplicated data are first removed, then the outliers are filtered by the LocalOutlierFactor method and finally, the data are standardized. 11 ML methods are evaluated for their ability to learn the FOS based on different input parameter combinations. By analyzing the evaluation indicators R 2, MAE, and MSE of these methods, SVM, GBR, and Bagging are considered to be the best regression methods. The performance and reliability of the nonlinear regression method are slightly better than that of the linear regression method. Also, the SVM-poly method is used to analyze the susceptibility of slope parameters.

关键词： slope stability     factor of safety     regression     machine learning     repeated cross-validation    

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Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

《结构与土木工程前沿（英文）》 2013年 第7卷 第1期   页码 72-82 doi: 10.1007/s11709-013-0185-y

摘要： A support vector machine (SVM) model has been developed for the prediction of liquefaction susceptibility as a classification problem, which is an imperative task in earthquake engineering. This paper examines the potential of SVM model in prediction of liquefaction using actual field cone penetration test (CPT) data from the 1999 Chi-Chi, Taiwan earthquake. The SVM, a novel learning machine based on statistical theory, uses structural risk minimization (SRM) induction principle to minimize the error. Using cone resistance ( ) and cyclic stress ratio ( ), model has been developed for prediction of liquefaction using SVM. Further an attempt has been made to simplify the model, requiring only two parameters ( and maximum horizontal acceleration ), for prediction of liquefaction. Further, developed SVM model has been applied to different case histories available globally and the results obtained confirm the capability of SVM model. For Chi-Chi earthquake, the model predicts with accuracy of 100%, and in the case of global data, SVM model predicts with accuracy of 89%. The effect of capacity factor ( ) on number of support vector and model accuracy has also been investigated. The study shows that SVM can be used as a practical tool for prediction of liquefaction potential, based on field CPT data.

关键词： earthquake     cone penetration test     liquefaction     support vector machine (SVM)     prediction    

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Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 183-197 doi: 10.1007/s11705-021-2073-7

摘要： Flowsheet simulations of chemical processes on an industrial scale require the solution of large systems of nonlinear equations, so that solvability becomes a practical issue. Additional constraints from technical, economic, environmental, and safety considerations may further limit the feasible solution space beyond the convergence requirement. A priori, the design variable domains for which a simulation converges and fulfills the imposed constraints are usually unknown and it can become very time-consuming to distinguish feasible from infeasible design variable choices by simply running the simulation for each choice. To support the exploration of the design variable space for such scenarios, an adaptive sampling technique based on machine learning models has recently been proposed. However, that approach only considers the exploration of the convergent domain and ignores additional constraints. In this paper, we present an improvement which particularly takes the fulfillment of constraints into account. We successfully apply the proposed algorithm to a toy example in up to 20 dimensions and to an industrially relevant flowsheet simulation.

关键词： machine learning     flowsheet simulations     constraints     exploration    

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Big data and machine learning: A roadmap towards smart plants

《工程管理前沿（英文）》   页码 623-639 doi: 10.1007/s42524-022-0218-0

摘要： Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.

关键词： big data     machine learning     artificial intelligence     smart sensor     cyber–physical system     Industry 4.0     intelligent system     digitalization    

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标题 作者 时间 类型 操作

Machine perfusion versus cold storage of livers: a meta-analysis

null

期刊论文

“机械灌注+”应用于扩大标准供肝移植——肝尽其用

王周城, Jack Martin, 余炯杰, 汪恺, Kourosh Saeb-Parsy, 徐骁

期刊论文

Simultaneous acquisition of CT angiography and whole brain CT perfusion images by using multiphase dynamic

Weiwei CHEN, Jianpin QI, Wenzhen ZHU, Wenhua HUANG, Jinmei SONG

期刊论文

Dimensional synthesis of a novel 5-DOF reconfigurable hybrid perfusion manipulator for large-scale sphericalhoneycomb perfusion

Hui YANG, Hairong FANG, Yuefa FANG, Xiangyun LI

期刊论文

Evaluation of the effect of myocardial perfusion after percutaneous coronary intervention in coronary

WANG Hong, HUANG Lan, JIN Jun, SONG Yaoming, GENG Zhaohua, YU Xuejun, QIN Jun, ZHAO Gang, GAO Yunhua, LIU Zheng

期刊论文

Challenges of human–machine collaboration in risky decision-making

期刊论文

Spatial prediction of soil contamination based on machine learning: a review

期刊论文

Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning

期刊论文

State-of-the-art applications of machine learning in the life cycle of solid waste management

期刊论文

Research and application of visual location technology for solder paste printing based on machine vision

Luosi WEI, Zongxia JIAO

期刊论文

Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method

期刊论文

Evaluation and prediction of slope stability using machine learning approaches

期刊论文

Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

期刊论文

Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

期刊论文

Big data and machine learning: A roadmap towards smart plants

期刊论文