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Diffusion-weighted images(DWI) without ADC values in assessment of small focal nodules in cirrhotic liver

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Chinese Journal of Cancer Research 2014年第1期26卷 38-47页

作者： Mai-Lin Chen Xiao-Yan Zhang Li-Ping Qi qing-lei shi Bin Chen Ying-shi Sun Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education) Department of RadiologyPeking University Cancer Hospital&Institute

Objective： To assess if diffusion-weighted magnetic resonance （MR） imaging without apparent diffusion coefficient （ADC） values provides added diagnostic value in combination with conventional MR imaging in the detection and characterization of small nodules in cirrhotic liver. Methods： Two observers retrospectively and independently analyzed 86 nodules （_〈3 em） certified pathologically in 33 patients with liver cirrhosis, including 48 hepatocellular carcinoma （HCC） nodules, 13 high-grade dysplastic nodules （HDN）, 10 low-grade dysplastic nodules （LDNs） and 15 other benign nodules. All these focal nodules were evaluated with conventional MR images （Tl-weighted, T2-weighted and dynamic gadolinium-enhanced images） and breath-hold diffusion-weighted images （DWI）（b=500 s/mm2）. The nodules were classified by using a scale of 1-3 （1, not seen; 3, well seen） on DWI for qualitative assessment. These small nodules were characterized by two radiologists. ADC values weren＇t measured. The diagnostic performance of the combined DWI-conventional images and the conventional images alone was evaluated using receiver operating characteristic （ROC） curves. The area under the curves （Az）, sensitivity and specificity values for characterizing different small nodules were also calculated. Results： Among 48 HCC nodules, 33 （68.8%） were graded as 3 （well seen）, 6 （12.5%） were graded as 2 （partially obscured）, and 9 weren＇t seen on DWI. Among 13 HDNs, there were 3 （23.1%） and 4 （30.8%） graded as 3 and 2 respectively. Five （50%） of 10 benign nodules were partially obscured and slightly hyperintense. For 86 nodules, the average diagnostic accuracy of combined DWI-conventional images was 82.56%, which was increased significantly compared with conventional MR images with 76.17%. For HCC and HDN, the diagnostic accuracy of combined DWI-conventional images increased from 78.69% to 86.07 %. Conclusions： Diffusion-weighted MR imaging does provide added diagnostic value in the detection and characte

关键词： Diffusion-weighted imaging magnetic resonance (MR) imaging cirrhosis nodule

Detecting dopaminergic neuronal degeneration using diffusion tensor imaging in a rotenone-induced rat model of Parkinson's disease: fractional anisotropy and mean diffusivity values

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Neural Regeneration Research 2017年第9期12卷 1485-1491页

作者： Lan-xiang Liu Dan Du Tao Zheng Yuan Fang Yan-sheng Chen Hui-ling Yi qing-yuan He Da-wei Gao qing-lei shi Department of Magnetic Resonance Imaging First Hospital of Qinhuangdao Department of Radiology Peking University Third Hospital College of Environmental and Chemical Engineering Yanshan University Scientific Clinical Specialist Siemens Ltd.

Dopamine content in the basal ganglia is strongly associated with the degree of dopaminergic neuron loss in the substantia nigra pars com- pacta. Symptoms of Parkinson＇s disease might not arise until more than 50% of the substantia nigra pars compacta is lost and the dopamine content in the basal ganglia is reduced by more than 80%. Greater diagnostic sensitivity and specificity would allow earlier detection of Parkinson＇s disease. Diffusion tensor imaging is a recently developed magnetic resonance imaging technique that measures mean diffusiv- ity and fractional anisotropy, and responds to changes in brain microstructure. When the microscopic barrier （including cell membranes, microtubules and other structures that interfere with the free diffusion of water） is destroyed and extracellular fluid volume accumulates, the mean diffusivity value increases; when the integrity of the microstructure （such as myelin） is destroyed, fractional anisotropy value decreases. However, there is no consensus as to whether these changes can reflect the early pathological alterations in Parkinson＇s disease. Here, we established a rat model of Parkinson＇s disease by injecting rotenone （or sunflower oil in controls） into the right suhstantia nigra. Diffusion tensor imaging results revealed that in the stages of disease, at 1, 2, 4, and 6 weeks after rotenone injection, fiactional anisotropy value decreased, but mean diffusivity values increased in the right substantia nigra in the experimental group. Fractional anisotropy values were lower at 4 weeks than at 6 weeks in the right substantia nigra of rats from the experimental group. Mean diffusivity values were mark- edly greater at 1 week than at 6 weeks in the right corpus striatum of rats from the experimental group. These findings suggest that mean diffusivity and fractional anisotropy values in the brain of rat models of Parkinson＇s disease 4 weeks after model establishment can reflect early degeneration of dopaminergic neurons. ＇Th

关键词： nerve regeneration diffusion tensor imaging fractional anisotropy mean diffusivity magnetic resonance imaging Parkinson's disease rotenone neurodegenerative disease biomarkers substantia nigra tyrosine hydroxylase neural regeneration

Learning topological defects formation with neural networks in a quantum phase transition

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Communications in Theoretical Physics 2024年第5期76卷 68-76页

作者： Han-qing shi Hai-qing Zhang Center for Gravitational Physics Department of Space ScienceBeihang UniversityBeijing 100191China Peng Huanwu Collaborative Center for Research and Education Beihang UniversityBeijing 100191China

Neural networks possess formidable representational power,rendering them invaluable in solving complex quantum many-body *** they excel at analyzing static solutions,nonequilibrium processes,including critical dynamics during a quantum phase transition,pose a greater challenge for neural *** address this,we utilize neural networks and machine learning algorithms to investigate time evolutions,universal statistics,and correlations of topological defects in a one-dimensional transverse-field quantum Ising ***,our analysis involves computing the energy of the system during a quantum phase transition following a linear quench of the transverse magnetic field *** excitation energies satisfy a power-law relation to the quench rate,indicating a proportional relationship between the excitation energy and the kink ***,we establish a universal power-law relationship between the first three cumulants of the kink numbers and the quench rate,indicating a binomial distribution of the ***,the normalized kink-kink correlations are also investigated and it is found that the numerical values are consistent with the analytic formula.

关键词： neural networks machine learning transverse-field quantum Ising model kibble-zurek mechanism

Thermogravimetric-Mass Spectrometric Study of the Pyrolysis Behavior of PVC

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Journal of China University of Mining and Technology 2007年第2期17卷 242-245页

作者： SUN qing-lei shi Xin-gang LIN Yun-liang ZHU He WANG Xiao CHENG Chuan-ge LIU Jian-hua Shandong Analysis and Test Center Shandong Academy of Science Jinan Shandong 250014 China

The pyrolysis characteristics of PVC were systematically investigated using a Netzschne TG thermo-balance coupled to a quadrupole mass spectrometer. The pyrolysis conditions were 0.1 MPa of Ar, a heating rate of 10 ℃/min and a final temperature of 1000℃. Both the thermogravimetric properties and the simultaneous evolution of gaseous products during pyrolysis were studied. The TG/DTG results showed that as the pyrolysis temperature increases the weight loss and weight loss rate of PVC increases. Near 412℃ the weight loss rate attained its peak value. At higher temperatures the rate of loss gradually decreases. The gases evolved during thermogravimetric analysis were analyzed by a mass spectrometer, monitoring the relative intensity of HC1, C6H6, light hydrocarbon and chlorine-containing gases The evolution curves showed that HC1, C6H6, light hydrocarbon and chlorine-containing gases all peak at about 416℃. This is consistent with the fact that the weight loss curves also peak at about 412℃. The extensive HCl evolution is consistent with the high chlorine content of PVC. The formation of these gases can be explained by considering these reactions： dehydrochlorination, intramolecular cyclization and the addition of HCl to unsaturated hydrocarbons.

关键词： pyrolysis PVC gas evolution TG-MS

Differences in brain pathological changes between rotenone and 6-hydroxydopamine Parkinson＇s disease models

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Neural Regeneration Research 2018年第7期13卷 1276-1280页

作者： Lan-Xiang Liu Dan Du Zhan-Qiu Wang Yuan Fang Tao Zheng Yan-Chao Dong qing-lei shi Min Zhao Fang Xiao Juan Du Department of Magnetic Resonance Imaging Qinhuangdao Municipal No. 1 Hospital Qinhuangdao Hebei Province China Department of Intervention Qinhuangdao Municipal No. 1 Hospital Qinhuangdao Hebei Province China Siemens Ltd. Beijing China Department of Pathology Qinhuangdao Municipal No. 1 Hospital Qinhuangdao Hebei Province China Hebei Medical University Shijiazhuang Hebei Province China

Rotenone and 6-hydroxydopamine are two drugs commonly used to generate Parkinson＇s disease animal *** not only achieve degenerative changes of dopaminergic neurons in the substantia nigra,but also satisfy the requirements for iron ***,few studies have compared the characteristics of these two models by magnetic resonance *** this study,rat models of Parkinson＇s disease were generated by injection of 3 μg rotenone or 10 μg 6-hydroxydopamine into the right substantia *** 1,2,4,and 6 weeks after injection,coronal whole-brain T2-weighted imaging,transverse whole-brain T2-weighted imaging,and coronal diffusion tensor weighted imaging were conducted to measure fractional anisotropy and T2＊ values at the injury *** fractional anisotropy value on the right side of the substantia nigra was remarkably lower at 6 weeks than at other time points in the rotenone *** the 6-hydroxydopamine group,the fractional anisotropy value was decreased,but T2＊ values were increased on the right side of the substantia nigra at 1 *** findings confirm that the 6-hydroxydopamine-induced model is suitable for studying dopaminergic neurons over short periods,while the rotenone-induced model may be appropriate for studying the pathological and physiological processes of Parkinson＇s disease over long periods.

关键词： nerve regeneration fractional anisotropy T2* rotenone 6-hydroxydopamine Parkinson's disease magnetic resonance imaging diffusion tensor imaging dopaminergic neurons neural regeneration

A low-power Bluetooth-based wireless sensor network and its global confliction-solving impact localization method

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Chinese Journal of Aeronautics 2024年第1期37卷 153-161页

作者： Yuanjia WANG lei QIU Qiyun XU Liming shi College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Department of Electrical and Electronic Engineering University of EdinburghEdinburgh EH89YLUK

During the whole service lifetime of aircraft structures with composite materials,impacts are inevitable and can usually cause severe but barely visible *** the occurrences of impact are random and unpredictable,it is a hotspot direction to develop an online impact monitoring system that can meet strict limitations of aerospace applications including small size,light weight,and low power ***(PZT)sensor,being able to generate impact response signals with no external power and cover a large-scale structure with only a small amount of them,is a promising ***,for real systems,networks with multiple nodes are normally required to monitor large-scale structures in a global way to identify any impact localization confliction,yet the existing studies are mostly evaluated with single nodes instead of ***,in this paper,based on a new low-power node designed,a Bluetooth-based digital impact monitoring PZT sensor network is proposed for the first time with its global confliction-solving impact localization *** of the system as a network are researched and analyzed on a complex real aircraft wing box for a global confliction-solving impact localization,showing a satisfying high accuracy.

关键词： Bluetooth-based low-power design Confliction-solving evaluation Complex composites Piezoelectric sensors Wireless impact monitoring network

Diffractive neural networks with improved expressive power for gray-scale image classification

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Photonics Research 2024年第6期12卷 1159-1166页

作者： MINJIA ZHENG WENZHE LIU lei shi JIAN ZI State Key Laboratory of Surface Physics Key Laboratory of Micro-and Nano-Photonic Structures(Ministry of Education)and Department of PhysicsFudan UniversityShanghai 200433China Institute for Nanoelectronic Devices and Quantum Computing Fudan UniversityShanghai 200433China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China Shanghai Research Center for Quantum Sciences Shanghai 210315China

In order to harness diffractive neural networks(DNNs)for tasks that better align with real-world computer vision requirements,the incorporation of gray scale is ***,DNNs are not powerful enough to accomplish gray-scale image processing tasks due to limitations in their expressive *** our work,we elucidate the relationship between the improvement in the expressive power of DNNs and the increase in the number of phase modulation layers,as well as the optimization of the Fresnel number,which can describe the diffraction *** demonstrate this point,we numerically trained a double-layer DNN,addressing the prerequisites for intensitybased gray-scale image ***,we experimentally constructed this double-layer DNN based on digital micromirror devices and spatial light modulators,achieving eight-level intensity-based gray-scale image classification for the MNIST and Fashion-MNIST data *** optical system achieved the maximum accuracies of 95.10%and 80.61%,respectively.

关键词： process mirror limitations

Pressure transient characteristics of non-uniform conductivity fractured wells in viscoelasticity polymer flooding based on oil-water two-phase flow

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Petroleum Science 2024年第1期21卷 343-351页

作者： Yang Wang Jia Zhang shi-Long Yang Ze-Xuan Xu shi-qing Cheng National Key Laboratory of Petroleum Resources and Engineering China University of Petroleum(Beijing)Beijing102249China

Polymer flooding in fractured wells has been extensively applied in oilfields to enhance oil *** contrast to water,polymer solution exhibits non-Newtonian and nonlinear behavior such as effects of shear thinning and shear thickening,polymer convection,diffusion,adsorption retention,inaccessible pore volume and reduced effective ***,the flux density and fracture conductivity along the hydraulic fracture are generally non-uniform due to the effects of pressure distribution,formation damage,and proppant *** this paper,we present an oil-water two-phase flow model that captures these complex non-Newtonian and nonlinear behavior,and non-uniform fracture characteristics in fractured polymer *** hydraulic fracture is firstly divided into two parts:high-conductivity fracture near the wellbore and low-conductivity fracture in the far-wellbore section.A hybrid grid system,including perpendicular bisection(PEBI)and Cartesian grid,is applied to discrete the partial differential flow equations,and the local grid refinement method is applied in the near-wellbore region to accurately calculate the pressure distribution and shear rate of polymer *** combination of polymer behavior characterizations and numerical flow simulations are applied,resulting in the calculation for the distribution of water saturation,polymer concentration and reservoir *** with the polymer flooding well with uniform fracture conductivity,this non-uniform fracture conductivity model exhibits the larger pressure difference,and the shorter bilinear flow period due to the decrease of fracture flow ability in the far-wellbore *** field case of the fall-off test demonstrates that the proposed method characterizes fracture characteristics more accurately,and yields fracture half-lengths that better match engineering reality,enabling a quantitative segmented characterization of the near-wellbore section with high fracture conductivity and th

关键词： Polymer flooding Non-Newtonian fluid Non-uniform fracture conductivity Two-phase flow Pressure transient analysis

Unveiling the Re,Cr,and I diffusion in saturated compacted bentonite using machine-learning methods

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Nuclear Science and Techniques 2024年第6期35卷 65-77页

作者： Zheng-Ye Feng Jun-lei Tian Tao Wu Guo-Jun Wei Zhi-Long Li Xiao-Qiong shi Yong-Jia Wang qing-Feng Li Department of Engineering Huzhou UniversityHuzhou 313000China Institute of Theoretical Physics Shanxi UniversityTaiyuan 030006China College of Physics Science and Technology Shenyang Normal UniversityShenyang 110034China

The safety assessment of high-level radioactive waste repositories requires a high predictive accuracy for radionuclide diffusion and a comprehensive understanding of the diffusion *** this study,a through-diffusion method and six machine-learning methods were employed to investigate the diffusion of ReO_(4)^(−),HCrO_(4)^(−),and I−in saturated compacted bentonite under different salinities and compacted dry *** machine-learning models were trained using two *** dataset contained six input features and 293 instances obtained from the diffusion database system of the Japan Atomic Energy Agency(JAEA-DDB)and 15 *** other dataset,comprising 15,000 pseudo-instances,was produced using a multi-porosity model and contained eight input *** results indicate that the former dataset yielded a higher predictive accuracy than the *** gradient-boosting exhibited a higher prediction accuracy(R2=0.92)and lower error(MSE=0.01)than the other machine-learning *** addition,Shapley Additive Explanations,Feature Importance,and Partial Dependence Plot analysis results indicate that the rock capacity factor and compacted dry density had the two most significant effects on predicting the effective diffusion coefficient,thereby offering valuable insights.

关键词： Machine learning Effective diffusion coefficient Through-diffusion experiment Multi-porosity model Global analysis