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Direct Colorimetric Detection of Hydrogen Peroxide Using 4-Nitrophenyl Boronic Acid or Its Pinacol Ester

泛环渤海地区九省市生物化学与分子生物学会——2011年学术交流会

作者： maolin guo Department of Chemistry and Biochemistry University of Massachusetts

Iron and copper play crucial roles in many fundamental physiological processes but may also promote the production of reactive oxygen species(ROS) which leads to cellular oxidative *** in homeostasisof iron,copper or ROS are linked to various disease conditions includingWilson’s disease, Parkinson’s disease(PD),Alzheimer’s disease(AD),atherosclerosis,hemochromatosis,liver damage,

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American Journal of Analytical Chemistry 2011年第8期2卷 879-884页

作者： Gregory Su Yibin Wei maolin guo 不详

A colorimetric method for the direct determination of hydrogen peroxide in aqueous solution is described. H2O2 stoichiometrically converts 4-nitrophenyl boronic acid or 4-nitrophenyl boronic acid pinacol ester into 4-nitrophenol, which can be quantified by measuring the absorption at 400 nm in neutral or basic media. The reactions proceed fast under basic conditions and complete in 2 minutes to at pH 11 and 80?C. The linear range for the colorimetric method extends beyond 1.0 to 40 μM H2O2, and the limit of detection is ~1.0 μM H2O2. This method offers a convenient and practical process for rapid determination of hydrogen peroxide in aqueous media. Compared to many other techniques in H2O2 detection, this process is a direct measurement of H2O2, and is relatively unaffected by the presence of various salts, metal ions and the chelator EDTA.

关键词： Hydrogen Peroxide Detection 4-Nitrophenyl Boronic Acid 4-Nitrophenyl Boronic Acid Pinacol Ester 4-Nitrophenol Colorimetric Method

非对称循环载荷下材料低周疲劳寿命分析与计算

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应用力学学报 2001年第1期18卷 91-96页

作者：王刚张怡郭茂林程靳哈尔滨工业大学哈尔滨150001

提出了一个用于计算非对称循环载荷下材料低周疲劳寿命的累积损伤模型和方法。该方法利用全应变幅及损伤积累来控制和计算疲劳寿命，并给出了裂纹的开裂尺寸和开裂方向。这为我们进行各种疲劳寿命计算以及结构优化设计提供了一个新的思... 详细信息

提出了一个用于计算非对称循环载荷下材料低周疲劳寿命的累积损伤模型和方法。该方法利用全应变幅及损伤积累来控制和计算疲劳寿命，并给出了裂纹的开裂尺寸和开裂方向。这为我们进行各种疲劳寿命计算以及结构优化设计提供了一个新的思路和方法。

关键词：非对称循环载荷累积损伤低周疲劳寿命材料

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车身产品开发过程中CAE分析的应用

汽车工程 2007年第7期29卷 554-557,549页

作者：王忠校郭茂林第一汽车集团公司技术中心长春130011

通过车身开发过程中的CAE应用实例,详细介绍了在车身产品开发过程中的CAE分析流程、分析能力和解决方案。

关键词：车身产品开发 CAE应用

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团体正念瑜伽训练对大学生睡眠质量的影响

四川精神卫生 2023年第2期36卷 162-167页

作者：郭茂林裴彩红熊梅成都医学院四川成都610500

目的探索团体正念瑜伽训练对大学生睡眠质量的影响,为大学生睡眠问题的干预提供参考。方法于2021年3月28日-2021年4月20日,选取45名匹兹堡睡眠质量指数量表(PSQI)评分≥8分的大学生为研究对象,按照随机数字表法分为研究组(n=22)和对照组... 详细信息

目的探索团体正念瑜伽训练对大学生睡眠质量的影响,为大学生睡眠问题的干预提供参考。方法于2021年3月28日-2021年4月20日,选取45名匹兹堡睡眠质量指数量表(PSQI)评分≥8分的大学生为研究对象,按照随机数字表法分为研究组(n=22)和对照组(n=23)。研究组接受每周两次的正念瑜伽训练,每次训练时长为60 min,持续4周;对照组在研究期间不接受正念瑜伽训练,在研究结束后接受相同的训练。于干预前后,采用PSQI和N-back训练任务分别评定两组的睡眠质量和工作记忆能力。结果时间因素在PSQI总评分、N-back训练任务正确率和反应时上的主效应均有统计学意义(F=37.240、6.898、10.775,P<0.05或0.01);分组因素在PSQI总评分和N-back训练任务正确率上的主效应均有统计学意义(F=8.057、11.093,P<0.05或0.01);时间和分组的交互作用对PSQI总评分和N-back训练任务反应时的影响均有统计学意义(F=32.730、17.578,P均<0.01)。干预后,研究组PSQI总评分(F=69.898,P<0.01)低于干预前,N-back训练任务反应时短于干预前(F=27.939,P<0.01),差异均有统计学意义。结论团体正念瑜伽训练可能有助于改善大学生睡眠质量。

关键词：正念瑜伽工作记忆睡眠质量大学生

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Reducing the measurement errors in nonadiabatic holonomic quantum computers

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 64-70页

作者： guo-Fu Xu Department of Physics Shandong University

Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum *** quantum computation has entered the noisy intermediate-scale era, building accurate intermediate-scale nonadiabatic holonomic quantum computers is clearly necessary. Given that measurements are the sole means of extracting information, they play an indispensable role in nonadiabatic holonomic quantum computers. Accordingly, developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance. However, while much attention has been given to the research on nonadiabatic holonomic gates, the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking. In this study, we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers. The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates. Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.

关键词： quantum holonomy quantum computation measurement errors

Cobalt Doping-induced Synthesis of Ceria Nanodiscs and Their Significantly Enhanced Catalytic Activity

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Cobalt Doping-induced Synthesis of Ceria Nanodiscs and Their...

Anomaly Detection of Controllable Electric Vehicles through Node Equation against Aggregation Attack

第六届全国物理无机化学会议

作者： Xiaohui guo~*,Fanli Meng,maolin Li,Weiwei Xu The College of Chemistry and Materials Science of Northwest University,Xi''an City,710069,P. R.China.

＜正＞The manipulation of rare earth oxide nanomaterials with specific morphology possessing exceptional physics and chemical properties,via conveniently modulating the synthetic conditions,is one of the challenging i...

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Computers, Materials & Continua 2025年第1期82卷 427-442页

作者： Jing guo Ziying Wang Yajuan guo Haitao Jiang State Grid Jiangsu Electric Power Co. Ltd.Research InstituteState Grid Corporation of ChinaNanjing211100China

The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids *** study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation *** approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation *** employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter *** xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging *** results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with F1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepFM(Factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging ***,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 *** research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.

关键词： Anomaly detection electric vehicle aggregation attack deep cross-network

DIGNN-A:Real-Time Network Intrusion Detection with Integrated Neural Networks Based on Dynamic Graph

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Computers, Materials & Continua 2025年第1期82卷 817-842页

作者： Jizhao Liu Minghao guo College of Computer Zhongyuan University of TechnologyZhengzhou450007China

The increasing popularity of the Internet and the widespread use of information technology have led to a rise in the number and sophistication of network attacks and security *** detection systems are crucial to network security,playing a pivotal role in safeguarding networks from potential ***,in the context of an evolving landscape of sophisticated and elusive attacks,existing intrusion detection methodologies often overlook critical aspects such as changes in network topology over time and interactions between *** address these issues,this paper proposes a real-time network intrusion detection method based on graph neural *** proposedmethod leverages the advantages of graph neural networks and employs a straightforward graph construction method to represent network traffic as dynamic graph-structured ***,a graph convolution operation with a multi-head attention mechanism is utilized to enhance the model’s ability to capture the intricate relationships within the graph structure ***,it uses an integrated graph neural network to address dynamic graphs’structural and topological changes at different time points and the challenges of edge embedding in intrusion detection *** edge classification problem is effectively transformed into node classification by employing a line graph data representation,which facilitates fine-grained intrusion detection tasks on dynamic graph node feature *** efficacy of the proposed method is evaluated using two commonly used intrusion detection datasets,UNSW-NB15 and NF-ToN-IoT-v2,and results are compared with previous studies in this *** experimental results demonstrate that our proposed method achieves 99.3%and 99.96%accuracy on the two datasets,respectively,and outperforms the benchmark model in several evaluation metrics.

关键词： Intrusion detection graph neural networks attention mechanisms line graphs dynamic graph neural networks