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Simplified algorithm for genetic subtyping in diffuse large B-cell lymphoma

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Signal Transduction and Targeted Therapy 2023年第5期8卷 2304-2314页

作者： Rong Shen Di Fu Lei Dong Mu-Chen Zhang Qing Shi Zi-Yang Shi Shu Cheng Li Wang Peng-Peng Xu Wei-Li Zhao Shanghai Institute of Hematology State Key Laboratory of Medical GenomicsNational Research Center for Translational Medicine at ShanghaiRuijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina Department of Pathology Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina Pôle de Recherches Sino-Français en Science du Vivant et Génomique Laboratory of Molecular PathologyShanghaiChina

Genetic classification helps to disclose molecular heterogeneity and therapeutic implications in diffuse large B-cell lymphoma(DLBCL).Using whole exome/genome sequencing,RNA-sequencing,and fluorescence in situ hybridization in 337 newly diagnosed DLBCL patients,we established a simplified 38-gene algorithm(termed‘LymphPlex’)based on the information on mutations of 35 genes and rearrangements of three genes(BCL2,BCL6,and MYC),identifying seven distinct genetic subtypes:TP53Mut(TP53 mutations),MCD-like(MYD88,CD79B,PIM1,MPEG1,BTG1,TBL1XR1,PRDM1,IRF4 mutations),BN2-like(BCL6 fusion,NOTCH2,CD70,DTX1,BTG2,TNFAIP3,CCND3 mutations),N1-like(NOTCH1 mutations),EZB-like(BCL2 fusion,EZH2,TNFRSF14,KMT2D,B2M,FAS,CREBBP,ARID1A,EP300,CIITA,STAT6,GNA13 mutations,with or without MYC rearrangement),and ST2-like(SGK1,TET2,SOCS1,DDX3X,ZFP36L1,DUSP2,STAT3,IRF8 mutations).Extended validation of 1001 DLBCL patients revealed clinical relevance and biological signature of each genetic subtype.TP53Mut subtype showed poor prognosis,characterized by p53 signaling dysregulation,immune deficiency,and PI3K activation.MCD-like subtype was associated with poor prognosis,activated B-cell(ABC)origin,BCL2/MYC double-expression,and NF-κB activation.BN2-like subtype showed favorable outcome within ABC-DLBCL and featured with NF-κB activation.N1-like and EZB-like subtypes were predominated by ABC-DLBCL and germinal center B-cell(GCB)-DLBCL,respectively.EZB-like-MYC+subtype was characterized by an immunosuppressive tumor microenvironment,while EZB-like-MYC-subtype by NOTCH activation.ST2-like subtype showed favorable outcome within GCB-DLBCL and featured with stromal-1 modulation.Genetic subtype-guided targeted agents achieved encouraging clinical response when combined with immunochemotherapy.Collectively,LymphPlex provided high efficacy and feasibility,representing a step forward to the mechanism-based targeted therapy in DLBCL.

关键词： lymphoma algorithm representing

Sound quality evaluation of high-speed train interior noise by adaptive Moore loudness algorithm

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2017年第9期18卷 690-703页

作者： Le LUO, Xu ZHENG Zhi-yong HAO Wen-qiang DAI Wen-ying YANG Department of Energy Engineering Zhejiang University Hangzhou 310027 China

An online experiment to acquire the interior noise of a China Railways High-speed （CRH） train showed that it wasmainly composed of middle-low frequency components and could not be described properly by linear or A-weighted soundpressure level （SPL）. Thus, the appropriate way to evaluate the high-speed train interior noise is to use sound quality parameters,and the most important is loudness. To overcome the disadvantages of the existing loudness algorithms, a novel signal-adaptiveMoore loudness algorithm （AMLA） based on the equivalent rectangular bandwidth （ERB） spectrum was introduced. The valida-tion reveals that AMLA can obtain higher accuracy and efficiency, and the simulated dark red noise conforms best to thehigh-speed train interior noise by loudness and auditory assessment. The main loudness component of the interior noise is below27.6 ERB rate （erbr）, and the sound quality of the interior noise is relatively stable between 300-350 km/h. The specific loudnesscomponents among 12-15 erbr stay invariable throughout the acceleration or deceleration process while components among20-27 erbr are evidently speed related. The unusual random noise is effectively identified, which indicates that AMLA is anappropriate method for sound quality assessment of the high-speed train under both steady and transient conditions.

关键词： High-speed train Sound quality evaluation Equivalent rectangular bandwidth (ERB) spectrum Adaptive Mooreloudness algorithm (AMLA) Unusual random noise

Real-Time Patient-Specific ECG Arrhythmia Detection by Quantum Genetic algorithm of Least Squares Twin SVM

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Journal of Beijing Institute of Technology 2020年第1期29卷 29-37页

作者： Duan Li Ruizheng Shi Ni Yao Fubao Zhu Ke Wang School of Computer and Communication Engineering Zhengzhou University of Light IndustryZhengzhou 450001China Department of Cardiology Xiangya HospitalCentral South UniversityChangsha 410008China

The automatic detection of cardiac arrhythmias through remote monitoring is still a challenging task since electrocardiograms(ECGs)are easily contaminated by physiological artifacts and external noises,and these morphological characteristics show significant variations for different patients.A fast patient-specific arrhythmia diagnosis classifier scheme is proposed,in which a wavelet adaptive threshold denoising is combined with quantum genetic algorithm(QAG)based on least squares twin support vector machine(LSTSVM).The wavelet adaptive threshold denoising is employed for noise reduction,and then morphological features combined with the timing interval features are extracted to evaluate the classifier.For each patient,an individual and fast classifier will be trained by common and patient-specific training data.Following the recommendations of the Association for the Advancements of Medical Instrumentation(AAMI),experimental results over the MIT-BIH arrhythmia benchmark database demonstrated that our proposed method achieved the average detection accuracy of 98.22%,99.65%and 99.41%for the abnormal,ventricular ectopic beats(VEBs)and supra-VEBs(SVEBs),respectively.Besides the detection accuracy,sensitivity and specificity,our proposed method consumes the less CPU running time compared with the other representative state of the art methods.It can be ported to Android based embedded system,henceforth suitable for a wearable device.

关键词： wearable ECG monitoring systems patient-specific arrhythmia classification quantum genetic algorithm least squares twin SVM

Genetic algorithm aided density functional theory simulations unravel the kinetic nature of Au(100) in catalytic CO oxidation

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Chinese Chemical Letters 2019年第6期30卷 1346-1350页

作者： Yi Fang Xueqing Gong Key Laboratory for Advanced Materials Centre for Computational Chemistry and Research Instiute of Industrial CatalysisSchool of Chemistry Molecular EngineeringEast China University of Science and Technology

Heterogeneous catalysis is of tremendous importance to modern industries. Exposed atoms of heterogeneous catalysts are heavily involved in surface processes such as the adsorption, activation, diffusion and reaction of substrate molecules. Surfaces of metal or metal oxide based catalysts are usually taken as hard templates that only undergo limited relaxation during catalytic reactions, especially in theoretical simulations. In this work, by using genetic algorithm (GA) aided density functional theory (DFT) calculations, we studied the surface processes involved in CO oxidation on the Au(100) surface. The use of GA greatly improves the capacity of DFT calculations in locating the potential energy surface (PES) of the surface reactions, and surprisingly, it has been found that the Au(100) surface can undergo drastic reconstruction under the influence of O adsorption and the adapted partially oxidized Au surface exhibits unique activities for subsequent adsorptions and reactions. This work depicts the kinetic nature of the Au (100) surface in its catalyzed reactions and also significantly expands our understanding of how surface atoms act in heterogeneous catalysis.

关键词： Gold catalysts Genetic algorithm Density functional theory Potential energy surface Surface reconstruction

Global Optimization for Combination Test Suite by Cluster Searching algorithm

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自动化学报 2017年第9期43卷 1625-1635页

作者： Hao Chen Xiaoying Pan Jiaze Sun School of Computer Science and Technology Xi'an Universityof Post and Telecommunications Xi'an 710121 China

The test suite generation is a key task for combinatorial testing of software.In order to generate high-quality testing data,a cluster searching driven global optimization mechanism is proposed.In this approach,a binary encoding mechanism is used to transform the combination test suite generating problem into a gene sequence optimization problem.Meanwhile,a novel global optimization algorithm,cluster searching algorithm (CSA),is developed to solve it.In this paper,the validity and rationality of problem transformation mechanism is verified,and the details of CSA are shown.The simulations illustrate the proposed mechanism is feasible.Moreover,it is a simpler and more efficient test suite generation approach for small-size combinatorial testing problems.

关键词： Cluster searching algorithm (CSA) combination test global optimization test suite optimization

A neighborhood proximity based algorithm for overlapping community structure detection in weighted networks

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Frontiers of Computer Science 2019年第6期13卷 1353-1355页

作者： Pawan KUMAR Ravins DOHARE Centre for Interdisciplinary Research in Basic Sciences Jamia Millia IslamiaNew Delhi-110025India

1 Introduction Many real networks are inherently composed of overlapping structure at modular level where nodes have multiple memberships.Additionally,many real networks are equipped with several metadata such as ground truth,node and edge weights which make the whole business of community detection complicated.Nevertheless,there are a few well known algorithms,e.g.,CPMw[1]that can detect overlapping community structure in weighted networks.When it comes to the application of an algorithm,the desired output depends on the right choice of parameters.

关键词： networks structure algorithm

Path planning in uncertain environment by using firefly algorithm

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Defence Technology（防务技术） 2018年第6期14卷 691-701页

作者： B.K.Patle Anish Pandey A.Jagadeesh D.R.Parhi Department of Mechanical Engineering CVR College of Engineering School of Mechanical Engineering KIIT University Department of Mechanical Engineering Audisankara Group of Institutions Department of Mechanical Engineering NIT Rourkela

Autonomous mobile robot navigation is one of the most emerging areas of research by using swarm intelligence. Path planning and obstacle avoidance are most researched current topics like navigational challenges for mobile robot. The paper presents application and implementation of Firefly algorithm(FA)for Mobile Robot Navigation(MRN) in uncertain environment. The uncertainty is defined over the changing environmental condition from static to dynamic. The attraction of one firefly towards the other firefly due to variation of their brightness is the key concept of the proposed study. The proposed controller efficiently explores the environment and improves the global search in less number of iterations and hence it can be easily implemented for real time obstacle avoidance especially for dynamic environment. It solves the challenges of navigation, minimizes the computational calculations, and avoids random moving of fireflies. The performance of proposed controller is better in terms of path optimality when compared to other intelligent navigational approaches.

关键词： Mobile robot navigation Firefly algorithm Path planning Obstacle avoidance

Distance Control algorithm for Automobile Automatic Obstacle Avoidance and Cruise System

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Computer Modeling in Engineering & Sciences 2018年第7期116卷 69-88页

作者： Jinguo Zhao Xijing University No.1Xijing RoadChang’an districtXi’anShaanxi710123China

With the improvement of automobile ownership in recent years,the incidence of traffic accidents constantly increases and requirements on the security of automobiles become increasingly higher.As science and technology develops constantly,the development of automobile automatic obstacle avoidance and cruise system accelerates gradually,and the requirement on distance control becomes stricter.Automobile automatic obstacle avoidance and cruise system can determine the conditions of automobiles and roads using sensing technology,automatically adopt measures to control automobile after discovering road safety hazards,thus to reduce the incidence of traffic accidents.To prevent accidental collision of automobile which are installed with automatic obstacle avoidance and cruise system,active brake should be controlled during driving.This study put forward a neural network based proportional-integral-derivative(PID)control algorithm.The active brake of automobiles was effectively controlled using the system to keep the distance between automobiles.Moreover the algorithm was tested using professional automobile simulation platform.The results demonstrated that neural network based PID control algorithm can precisely and efficiently control the distance between two cars.This work provides a reference for the development of automobile automatic obstacle avoidance and cruise system.

关键词： Obstacle avoidance and cruise distance control automobile algorithm

Method of Modulation Recognition Based on Combination algorithm of K-Means Clustering and Grading Training SVM

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China Communications 2018年第12期15卷 55-63页

作者： Faquan Yang Ling Yang Dong Wang Peihan Qi Haiyan Wang 无 School of Electrical and Information Engineering Foshan UniversityFoshan 528000China Xinhua College of Sun Yat-sen University Guanzuo 523133China State Key Laboratory of Integrated Service Networks Xidian UniversityXian 710071China

For the existing support vector machine, when recognizing more questions, the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged. The characteristic parameter of the signal is extracted and optimized by using a clustering algorithm, support vector machine is trained by grading algorithm so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram in this paper. Simulation results show that the average recognition rate based on this algorithm is enhanced over 30% compared with methods that adopting clustering algorithm or support vector machine respectively under the low SNR. The average recognition rate can reach 90% when the SNR is 5 dB, and the method is easy to be achieved so that it has broad application prospect in the modulating recognition.

关键词： clustering algorithm feature extraction grading algorithm support vector machine modulation recognition