期刊文献+
共找到265,290篇文章
< 1 2 250 >
每页显示 20 50 100
Enhancing Cancer Classification through a Hybrid Bio-Inspired Evolutionary Algorithm for Biomarker Gene Selection 被引量:1
1
作者 Hala AlShamlan Halah AlMazrua 《Computers, Materials & Continua》 SCIE EI 2024年第4期675-694,共20页
In this study,our aim is to address the problem of gene selection by proposing a hybrid bio-inspired evolutionary algorithm that combines Grey Wolf Optimization(GWO)with Harris Hawks Optimization(HHO)for feature selec... In this study,our aim is to address the problem of gene selection by proposing a hybrid bio-inspired evolutionary algorithm that combines Grey Wolf Optimization(GWO)with Harris Hawks Optimization(HHO)for feature selection.Themotivation for utilizingGWOandHHOstems fromtheir bio-inspired nature and their demonstrated success in optimization problems.We aimto leverage the strengths of these algorithms to enhance the effectiveness of feature selection in microarray-based cancer classification.We selected leave-one-out cross-validation(LOOCV)to evaluate the performance of both two widely used classifiers,k-nearest neighbors(KNN)and support vector machine(SVM),on high-dimensional cancer microarray data.The proposed method is extensively tested on six publicly available cancer microarray datasets,and a comprehensive comparison with recently published methods is conducted.Our hybrid algorithm demonstrates its effectiveness in improving classification performance,Surpassing alternative approaches in terms of precision.The outcomes confirm the capability of our method to substantially improve both the precision and efficiency of cancer classification,thereby advancing the development ofmore efficient treatment strategies.The proposed hybridmethod offers a promising solution to the gene selection problem in microarray-based cancer classification.It improves the accuracy and efficiency of cancer diagnosis and treatment,and its superior performance compared to other methods highlights its potential applicability in realworld cancer classification tasks.By harnessing the complementary search mechanisms of GWO and HHO,we leverage their bio-inspired behavior to identify informative genes relevant to cancer diagnosis and treatment. 展开更多
关键词 Bio-inspired algorithms BIOINFORMATICS cancer classification evolutionary algorithm feature selection gene expression grey wolf optimizer harris hawks optimization k-nearest neighbor support vector machine
下载PDF
Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach
2
作者 Rocco de Filippis Abdullah Al Foysal 《Advances in Bioscience and Biotechnology》 CAS 2024年第5期289-309,共21页
Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligen... Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence. 展开更多
关键词 Neuromuscular Diseases REHABILITATION Artificial Intelligence Machine Learning Robotic-Assisted Therapy Virtual Reality Personalized Treatment Motor Function Assistive Technologies algorithmic Rehabilitation
下载PDF
Development of a Post Quantum Encryption Key Generation Algorithm Using Electromagnetic Wave Propagation Theory
3
作者 Vincent Mbonigaba Fulgence Nahayo +1 位作者 Octave Moutsinga Okalas-Ossami Dieudonné 《Journal of Information Security》 2024年第1期53-62,共10页
In today’s rapid widespread of digital technologies into all live aspects to enhance efficiency and productivity on the one hand and on the other hand ensure customer engagement, personal data counterfeiting has beco... In today’s rapid widespread of digital technologies into all live aspects to enhance efficiency and productivity on the one hand and on the other hand ensure customer engagement, personal data counterfeiting has become a major concern for businesses and end-users. One solution to ensure data security is encryption, where keys are central. There is therefore a need to find robusts key generation implementation that is effective, inexpensive and non-invasive for protecting and preventing data counterfeiting. In this paper, we use the theory of electromagnetic wave propagation to generate encryption keys. 展开更多
关键词 KEY Wave ELECTROMAGNETIC CRYPTOGRAPHY POST Quantum Network Protocol Propagation algorithm
下载PDF
Deep Transfers of p-Class Tower Groups
4
作者 Daniel C. Mayer 《Journal of Applied Mathematics and Physics》 2018年第1期36-50,共15页
Let p be a prime. For any finite p-group G, the deep transfers T H,G ' : H / H ' → G ' / G " from the maximal subgroups H of index (G:H) = p in G to the derived subgroup G ' are introduced as an ... Let p be a prime. For any finite p-group G, the deep transfers T H,G ' : H / H ' → G ' / G " from the maximal subgroups H of index (G:H) = p in G to the derived subgroup G ' are introduced as an innovative tool for identifying G uniquely by means of the family of kernels ùd(G) =(ker(T H,G ')) (G: H) = p. For all finite 3-groups G of coclass cc(G) = 1, the family ùd(G) is determined explicitly. The results are applied to the Galois groups G =Gal(F3 (∞)/ F) of the Hilbert 3-class towers of all real quadratic fields F = Q(√d) with fundamental discriminants d > 1, 3-class group Cl3(F) □ C3 × C3, and total 3-principalization in each of their four unramified cyclic cubic extensions E/F. A systematic statistical evaluation is given for the complete range 1 d 7, and a few exceptional cases are pointed out for 1 d 8. 展开更多
关键词 Hilbert p-Class Field Towers p-Class GROUPS p-Principalization Quadratic FIELDS Dihedral FIELDS of Degree 2p Finite p-Groups Two-Step Centralizers Polarization PRINCIPLE Descendant Trees p-Group Generation algorithm p-Multiplicator RANK Relation RANK Generator RANK Deep Transfers Shallow Transfers Partial Order and Monotony PRINCIPLE of Artin Patterns Parametrized Polycyclic pc-Presentations Commutator Calculus
下载PDF
A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data
5
作者 Yisa Adeniyi Abolade Yichuan Zhao 《Open Journal of Modelling and Simulation》 2024年第2期33-42,共10页
Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear mode... Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance. 展开更多
关键词 Compositional Data Linear Regression Model Least Square Method Robust Least Square Method Synthetic Data Aitchison Distance Maximum Likelihood Estimation Expectation-Maximization algorithm k-Nearest Neighbor and Mean imputation
下载PDF
New Regularization Algorithms for Solving the Deconvolution Problem in Well Test Data Interpretation 被引量:1
6
作者 Vladimir Vasin Georgy Skorik +1 位作者 Evgeny Pimonov Fikri Kuchuk 《Applied Mathematics》 2010年第5期387-399,共13页
Two new regularization algorithms for solving the first-kind Volterra integral equation, which describes the pressure-rate deconvolution problem in well test data interpretation, are developed in this paper. The main ... Two new regularization algorithms for solving the first-kind Volterra integral equation, which describes the pressure-rate deconvolution problem in well test data interpretation, are developed in this paper. The main features of the problem are the strong nonuniform scale of the solution and large errors (up to 15%) in the input data. In both algorithms, the solution is represented as decomposition on special basic functions, which satisfy given a priori information on solution, and this idea allow us significantly to improve the quality of approximate solution and simplify solving the minimization problem. The theoretical details of the algorithms, as well as the results of numerical experiments for proving robustness of the algorithms, are presented. 展开更多
关键词 DECONVOLUTION PROBLEM VOLTERRA Equations Well Test REGULARIZATION algorithm Quasi-Solutions Method Tikhonov REGULARIZATION A Priori Information Discrete Approximation Non-Quadratic Stabilizing Functional Special Basis
下载PDF
Binary Gravitational Search based Algorithm for Optimum Siting and Sizing of DG and Shunt Capacitors in Radial Distribution Systems
7
作者 N. A. Khan S. Ghosh S. P. Ghoshal 《Energy and Power Engineering》 2013年第4期1005-1010,共6页
This paper presents a binary gravitational search algorithm (BGSA) is applied to solve the problem of optimal allotment of DG sets and Shunt capacitors in radial distribution systems. The problem is formulated as a no... This paper presents a binary gravitational search algorithm (BGSA) is applied to solve the problem of optimal allotment of DG sets and Shunt capacitors in radial distribution systems. The problem is formulated as a nonlinear constrained single-objective optimization problem where the total line loss (TLL) and the total voltage deviations (TVD) are to be minimized separately by incorporating optimal placement of DG units and shunt capacitors with constraints which include limits on voltage, sizes of installed capacitors and DG. This BGSA is applied on the balanced IEEE 10 Bus distribution network and the results are compared with conventional binary particle swarm optimization. 展开更多
关键词 Normal Load Flow Radial Distribution System Distributed Generation SHUNT Capacitors BINARY Particle SWARM Optimization BINARY GRAVITATIONAL SEARCH algorithm TOTAL line Loss TOTAL Voltage Deviation
下载PDF
基于遗传算法和最小二乘支持向量机的织物剪切性能预测 被引量:2
8
作者 卢桂馥 王勇 +1 位作者 窦易文 Gui-fu Yi-wen 《计量学报》 CSCD 北大核心 2009年第6期-,共4页
提出了一种基于最小二乘支持向量机的织物剪切性能预测模型,并且采用遗传算法进行最小二乘支持向量机的参数优化,将获得的样本进行归一化处理后,将其输入预测模型以得到预测结果.仿真结果表明,基于最小二乘支持向量机的预测模型比BP神... 提出了一种基于最小二乘支持向量机的织物剪切性能预测模型,并且采用遗传算法进行最小二乘支持向量机的参数优化,将获得的样本进行归一化处理后,将其输入预测模型以得到预测结果.仿真结果表明,基于最小二乘支持向量机的预测模型比BP神经网络和线性回归方法具有更高的精度和范化能力. Abstract: A new method is proposed to predict the fabric shearing property with least square support vector machines ( LS-SVM ). The genetic algorithm is investigated to select the parameters of LS-SVM models as a means of improving the LS- SVM prediction. After normalizing the sampling data, the sampling data are inputted into the model to gain the prediction result. The simulation results show the prediction model gives better forecasting accuracy and generalization ability than BP neural network and linear regression method. 展开更多
关键词 SUPPORT VECTOR MACHINES sampling data SUPPORT VECTOR MACHINES generalization ability simulation results linear regression genetic algorithm BP neural network prediction model 线 LS-SVM least square new method
下载PDF
Active micro-vibration control based on improved variable step size LMS algorithm 被引量:1
9
作者 Li Xiangmin Fang Yubin +2 位作者 Zhu Xiaojin Huang Yonghui Zhou Yijia 《High Technology Letters》 EI CAS 2020年第2期178-187,共10页
The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and sym... The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and symbolic function and step size factor is proposed.It establishes a new updating method of step factor that is related to step factor and error signal.This work makes an analysis from 3 aspects:theoretical analysis,theoretical verification and specific experiments.The experimental results show that the proposed algorithm is superior to other variable step size algorithms in convergence speed and steady-state error. 展开更多
关键词 adaptive filtering variable step size least mean square(LMS)algorithm logarithmic and SYMBOLIC functions convergence and STEADY state error ACTIVE CONTROL of micro vibration
下载PDF
Enhanced Euclid Algorithm for Modular Multiplicative Inverse and Its Application in Cryptographic Protocols
10
作者 Boris S. Verkhovsky 《International Journal of Communications, Network and System Sciences》 2010年第12期901-906,共6页
Numerous cryptographic algorithms (ElGamal, Rabin, RSA, NTRU etc) require multiple computations of modulo multiplicative inverses. This paper describes and validates a new algorithm, called the Enhanced Euclid Algorit... Numerous cryptographic algorithms (ElGamal, Rabin, RSA, NTRU etc) require multiple computations of modulo multiplicative inverses. This paper describes and validates a new algorithm, called the Enhanced Euclid Algorithm, for modular multiplicative inverse (MMI). Analysis of the proposed algorithm shows that it is more efficient than the Extended Euclid algorithm (XEA). In addition, if a MMI does not exist, then it is not necessary to use the Backtracking procedure in the proposed algorithm;this case requires fewer operations on every step (divisions, multiplications, additions, assignments and push operations on stack), than the XEA. Overall, XEA uses more multiplications, additions, assignments and twice as many variables than the proposed algorithm. 展开更多
关键词 Extended-Euclid algorithm MODULAR MULTIPLICATIVE INVERSE Public-Key Cryptography RSA Cryptocol Rabin Information Hiding algorithm ELGAMAL ENCRYPTION/DECRYPTION NTRU Cryptosystem Computer Simulation Low Memory Devices
下载PDF
Parallel Minimax Searching Algorithm for Extremum of Unimodal Unbounded Function
11
作者 Boris S. Verkhovsky 《International Journal of Communications, Network and System Sciences》 2011年第9期549-561,共13页
In this paper we consider a parallel algorithm that detects the maximizer of unimodal function f(x) computable at every point on unbounded interval (0, ∞). The algorithm consists of two modes: scanning and detecting.... In this paper we consider a parallel algorithm that detects the maximizer of unimodal function f(x) computable at every point on unbounded interval (0, ∞). The algorithm consists of two modes: scanning and detecting. Search diagrams are introduced as a way to describe parallel searching algorithms on unbounded intervals. Dynamic programming equations, combined with a series of liner programming problems, describe relations between results for every pair of successive evaluations of function f in parallel. Properties of optimal search strategies are derived from these equations. The worst-case complexity analysis shows that, if the maximizer is located on a priori unknown interval (n-1], then it can be detected after cp(n)=「2log「p/2」+1(n+1)」-1 parallel evaluations of f(x), where p is the number of processors. 展开更多
关键词 Adversarial MINIMAX Analysis DESIGN Parameters Dynamic Programming FUNCTION Evaluation Optimal algorithm PARALLEL algorithm System DESIGN Statistical Experiments Time Complexity Unbounded Search UNIMODAL FUNCTION
下载PDF
Optimal setting and placement of FACTS devices using strength Pareto multi-objective evolutionary algorithm 被引量:2
12
作者 Amin Safari Hossein Shayeghi Mojtaba Bagheri 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第4期829-839,共11页
This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for... This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems. 展开更多
关键词 STRENGTH PARETO multi-objective evolutionary algorithm STATIC var COMPENSATOR (SVC) THYRISTOR controlled series capacitor (TCSC) STATIC voltage stability margin optimal location
下载PDF
Adaptive Kernel Firefly Algorithm Based Feature Selection and Q-Learner Machine Learning Models in Cloud
13
作者 I.Mettildha Mary K.Karuppasamy 《Computer Systems Science & Engineering》 SCIE EI 2023年第9期2667-2685,共19页
CC’s(Cloud Computing)networks are distributed and dynamic as signals appear/disappear or lose significance.MLTs(Machine learning Techniques)train datasets which sometime are inadequate in terms of sample for inferrin... CC’s(Cloud Computing)networks are distributed and dynamic as signals appear/disappear or lose significance.MLTs(Machine learning Techniques)train datasets which sometime are inadequate in terms of sample for inferring information.A dynamic strategy,DevMLOps(Development Machine Learning Operations)used in automatic selections and tunings of MLTs result in significant performance differences.But,the scheme has many disadvantages including continuity in training,more samples and training time in feature selections and increased classification execution times.RFEs(Recursive Feature Eliminations)are computationally very expensive in its operations as it traverses through each feature without considering correlations between them.This problem can be overcome by the use of Wrappers as they select better features by accounting for test and train datasets.The aim of this paper is to use DevQLMLOps for automated tuning and selections based on orchestrations and messaging between containers.The proposed AKFA(Adaptive Kernel Firefly Algorithm)is for selecting features for CNM(Cloud Network Monitoring)operations.AKFA methodology is demonstrated using CNSD(Cloud Network Security Dataset)with satisfactory results in the performance metrics like precision,recall,F-measure and accuracy used. 展开更多
关键词 Cloud analytics machine learning ensemble learning distributed learning clustering classification auto selection auto tuning decision feedback cloud DevOps feature selection wrapper feature selection Adaptive Kernel Firefly algorithm(AKFA) Q learning
下载PDF
Effect of a region-wide incorporation of an algorithm based on the 2012 international consensus guideline on the practice pattern for the management of pancreatic cystic neoplasms in an integrated health system
14
作者 Andrew Khoi Nguyen Agathon Girgis +12 位作者 Timnit Tekeste Karen Chang Mopelola Adeyemo Armen Eskandari Emilio Alonso Priyanka Yaramada Charles Chaya Albert Ko Edmund Burke Isaiah Roggow Rebecca Butler Aniket Kawatkar Brian S Lim 《World Journal of Clinical Cases》 SCIE 2018年第13期624-631,共8页
AIM To examine the practice pattern in Kaiser Permanente Southern California(KPSC), i.e., gastroenterology(GI)/surgery referrals and endoscopic ultrasound(EUS), for pancreatic cystic neoplasms(PCNs) after the regionwi... AIM To examine the practice pattern in Kaiser Permanente Southern California(KPSC), i.e., gastroenterology(GI)/surgery referrals and endoscopic ultrasound(EUS), for pancreatic cystic neoplasms(PCNs) after the regionwide dissemination of the PCN management algorithm.METHODS Retrospective review was performed; patients with PCN diagnosis given between April 2012 and April 2015(18 mo before and after the publication of the algorithm) in KPSC(integrated health system with 15 hospitals and 202 medical offices in Southern California) were identified.RESULTS2558(1157 pre-and 1401 post-algorithm) received a new diagnosis of PCN in the study period. There was no difference in the mean cyst size(pre-19.1 mm vs post-18.5 mm, P = 0.119). A smaller percentage of PCNs resulted in EUS after the implementation of the algorithm(pre-45.5% vs post-34.8%, P < 0.001). A smaller proportion of patients were referred for GI(pre-65.2% vs post-53.3%, P < 0.001) and surgery consultations(pre-24.8% vs post-16%, P < 0.001) for PCN after the implementation. There was no significant change in operations for PCNs. Cost of diagnostic care was reduced after the implementation by 24%, 18%, and 36% for EUS, GI, and surgery consultations, respectively, with total cost saving of 24%.CONCLUSION In the current healthcare climate, there is increased need to optimize resource utilization. Dissemination of an algorithm for PCN management in an integrated health system resulted in fewer EUS and GI/surgery referrals, likely by aiding the physicians ordering imaging studies in the decision making for the management of PCNs. This translated to cost saving of 24%, 18%, and 36% for EUS, GI, and surgical consultations, respectively, with total diagnostic cost saving of 24%. 展开更多
关键词 PANCREATIC cyst algorithm incorporation Pancreas Optimization of resource utilization Fukuoka CRITERIA Sendai CRITERIA PANCREATIC cancer INTRADUCTAL papillary MUCINOUS neoplasm Practice MANAGEMENT algorithm
下载PDF
Comparative analysis of various modularization algorithms and species specific study of VEGF signaling pathways 被引量:2
15
作者 Namrata Tomar Losiana Nayak Rajat K. De 《Journal of Biomedical Science and Engineering》 2010年第10期931-942,共12页
In biology, signal transduction refers to a process by which a cell converts one kind of signal or stimulus into another. It involves ordered sequences of biochemical reactions inside the cell. These cascades of react... In biology, signal transduction refers to a process by which a cell converts one kind of signal or stimulus into another. It involves ordered sequences of biochemical reactions inside the cell. These cascades of reactions are carried out by enzymes and activated by second messengers. Signal transduction pathways are complex in nature. Each pathway is responsible for tuning one or more biological functions in the intracellular environment as well as more than one pathway interact among themselves to carry forward a single biological function. Such kind of behavior of these pathways makes understanding difficult. Hence, for the sake of simplicity, they need to be partitioned into smaller modules and then analyzed. We took VEGF signaling pathway, which is responsible for angiogenesis for this kind of modularized study. Modules were obtained by applying the algorithm of Nayak and De (Nayak and De, 2007) for different complexity values. These sets of modules were compared among themselves to get the best set of modules for an optimal complexity value. The best set of modules compared with four different partitioning algorithms namely, Farhat’s (Farhat, 1998), Greedy (Chartrand and Oellermann, 1993), Kernighan-Lin’s (Kernighan and Lin, 1970) and Newman’s community finding algorithm (Newman, 2006). These comparisons enabled us to decide which of the aforementioned algorithms was the best one to create partitions from human VEGF signaling pathway. The optimal complexity value, on which the best set of modules was obtained, was used to get modules from different species for comparative study. Comparison among these modules would shed light on the trend of development of VEGF signaling pathway over these species. 展开更多
关键词 Signal TRANSDUCTION PATHWAY VEGF PATHWAY Complexity Value KEGG Database MODULARIZATION Newmans Community Finding algorithm Kernighan-Lins algorithm Farhats algorithm and GREEDY algorithm.
下载PDF
Multinucleated giant cells of bladder mucosa are modified telocytes:Diagnostic and immunohistochemistry algorithm and relation to PDL1 expression score
16
作者 Milena Gulinac Tsvetelina Velikova Dorian Dikov 《World Journal of Clinical Cases》 SCIE 2023年第26期6091-6104,共14页
BACKGROUND Multinucleated giant cells(MGCs)in bladder carcinomas are poorly studied.AIM To describe the function,morphogenesis,and origin of mononuclear and MGCs in urothelial carcinoma(UC)of the bladder in Bulgarian ... BACKGROUND Multinucleated giant cells(MGCs)in bladder carcinomas are poorly studied.AIM To describe the function,morphogenesis,and origin of mononuclear and MGCs in urothelial carcinoma(UC)of the bladder in Bulgarian and French patients.METHODS Urothelial bladder carcinomas(n=104)from 2016-2020 were analyzed retrospectively using immunohistochemical(IHC)and histochemical stain examination.Giant cells in the bladder stroma were found in 35.6%of cases,more often in highgrades.RESULTS We confirm that MGCs in the mucosa in UC of the bladder were positive for both mesenchymal and myofibroblast markers(vimentin,smooth muscle actin,Desmin,and CD34)and the macrophage marker CD68.Furthermore,IHC studies revealed the following profile of these cells:Positive for p16;negative for epithelial(CK AE1/AE3 and GATA-3),vascular(CD31),neural(PS100 and CKIT),cambial,blastic(CD34-blasts and C-KIT),and immune markers(IG G,immunoglobulin G4,and PD-L1);no proliferative activity,possess no specific immune function,and cannot be used to calculate the Combined Positive Score scale.CONCLUSION In conclusion,the giant stromal cells in non-tumor and tumor bladder can be used as a characteristic and relatively constant,although nonspecific,histological marker for chronic bladder damage,reflecting the chronic irritation or inflammation.Likewise,according to the morphological and IHC of the mono-and multinucleated giant cells in the bladder,they are most likely represent telocytes capable of adapting their morphology to the pathology of the organ. 展开更多
关键词 Multinucleated giant cells TELOCYTES Urothelial bladder carcinoma IMMUNOHISTOCHEMICAL Vimentin Smooth muscle actin DESMIN CD34 CD68 p16 algorithm PD-L1 Chronic inflammation
下载PDF
Far and Near Optimization:A New Simple and Effective Metaphor-LessOptimization Algorithm for Solving Engineering Applications
17
作者 Tareq Hamadneh Khalid Kaabneh +3 位作者 Omar Alssayed Kei Eguchi Zeinab Monrazeri Mohammad Dehghani 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第11期1725-1808,共84页
In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lie... In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lies inintegrating global and local search methodologies to update the algorithm population within the problem-solvingspace based on moving each member to the farthest and nearest member to itself.The paper delineates the theoryof FNO,presenting a mathematical model in two phases:(i)exploration based on the simulation of the movementof a population member towards the farthest member from itself and(ii)exploitation based on simulating themovement of a population member towards the nearest member from itself.FNO’s efficacy in tackling optimizationchallenges is assessed through its handling of the CEC 2017 test suite across problem dimensions of 10,30,50,and 100,as well as to address CEC 2020.The optimization results underscore FNO’s adeptness in exploration,exploitation,and maintaining a balance between them throughout the search process to yield viable solutions.Comparative analysis against twelve established metaheuristic algorithms reveals FNO’s superior performance.Simulation findings indicate FNO’s outperformance of competitor algorithms,securing the top rank as the mosteffective optimizer across a majority of benchmark functions.Moreover,the outcomes derived by employing FNOon twenty-two constrained optimization challenges from the CEC 2011 test suite,alongside four engineering designdilemmas,showcase the effectiveness of the suggested method in tackling real-world scenarios. 展开更多
关键词 OPTIMIZATION stochastic method FAR NEAR metaheuristic algorithm exploration EXPLOITATION
下载PDF
On Over-Relaxed Proximal Point Algorithms for Generalized Nonlinear Operator Equation with (A,η,m)-Monotonicity Framework
18
作者 Fang Li 《International Journal of Modern Nonlinear Theory and Application》 2012年第3期67-72,共6页
In this paper, a new class of over-relaxed proximal point algorithms for solving nonlinear operator equations with (A,η,m)-monotonicity framework in Hilbert spaces is introduced and studied. Further, by using the gen... In this paper, a new class of over-relaxed proximal point algorithms for solving nonlinear operator equations with (A,η,m)-monotonicity framework in Hilbert spaces is introduced and studied. Further, by using the generalized resolvent operator technique associated with the (A,η,m)-monotone operators, the approximation solvability of the operator equation problems and the convergence of iterative sequences generated by the algorithm are discussed. Our results improve and generalize the corresponding results in the literature. 展开更多
关键词 New Over-Relaxed Proximal Point algorithm Nonlinear OPERATOR Equation with (A η m)-Monotonicity FRAMEWORK Generalized RESOLVENT OPERATOR Technique Solvability and Convergence
下载PDF
Modeling and Adaptive Self-Tuning MVC Control of PAM Manipulator Using Online Observer Optimized with Modified Genetic Algorithm
19
作者 Ho Pham Huy Anh Nguyen Thanh Nam 《Engineering(科研)》 2011年第2期130-143,共14页
In this paper, the application of modified genetic algorithms (MGA) in the optimization of the ARX Model-based observer of the Pneumatic Artificial Muscle (PAM) manipulator is investigated. The new MGA algorithm is pr... In this paper, the application of modified genetic algorithms (MGA) in the optimization of the ARX Model-based observer of the Pneumatic Artificial Muscle (PAM) manipulator is investigated. The new MGA algorithm is proposed from the genetic algorithm with important additional strategies, and consequently yields a faster convergence and a more accurate search. Firstly, MGA-based identification method is used to identify the parameters of the nonlinear PAM manipulator described by an ARX model in the presence of white noise and this result will be validated by MGA and compared with the simple genetic algorithm (GA) and LMS (Least mean-squares) method. Secondly, the intrinsic features of the hysteresis as well as other nonlinear disturbances existing intuitively in the PAM system are estimated online by a Modified Recursive Least Square (MRLS) method in identification experiment. Finally, a highly efficient self-tuning control algorithm Minimum Variance Control (MVC) is taken for tracking the joint angle position trajectory of this PAM manipulator. Experiment results are included to demonstrate the excellent performance of the MGA algorithm in the NARX model-based MVC control system of the PAM system. These results can be applied to model, identify and control other highly nonlinear systems as well. 展开更多
关键词 Modified Genetic algorithm (MGA) ONLINE System Identification ARX Model Pneumatic Artificial Muscle (PAM) PAM MANIPULATOR Minimum Variance Controller (MVC)
下载PDF
Primary hyperparathyroidism-induced acute pancreatitis in pregnancy:A systematic review with a diagnostic-treatment algorithm
20
作者 Goran Augustin Quirino Lai Maja Cigrovski Berkovic 《World Journal of Gastroenterology》 SCIE CAS 2024年第32期3755-3765,共11页
BACKGROUND Primary hyperparathyroidism(PHPT)-induced acute pancreatitis(AP)during pregnancy has rarely been described.Due to this rarity,there are no diagnostic or treatment algorithms for pregnant patients.AIM To det... BACKGROUND Primary hyperparathyroidism(PHPT)-induced acute pancreatitis(AP)during pregnancy has rarely been described.Due to this rarity,there are no diagnostic or treatment algorithms for pregnant patients.AIM To determine appropriate diagnostic methods,therapeutic options,and factors related to maternal and fetal outcomes for PHPT-induced AP in pregnancy.METHODS A literature search of articles in English,Japanese,German,Spanish,and Italian was performed using PubMed(1946-2023),PubMed Central(1900-2023),and Google Scholar.The Preferred Reporting Items for Systematic reviews and Meta-Analyses(PRISMA)protocol was followed.The search terms included“pancreatite acuta,”“iperparatiroidismo primario,”“gravidanza,”“travaglio,”“puerperio,”“postpartum,”“akute pankreatitis,”“primärer hyperparathyreoidismus,”“Schwangerschaft,”“Wehen,”“Wochenbett,”“pancreatitis aguda,”“hiperparatiroidismo primario,”“embarazo,”“parto,”“puerperio,”“posparto,”“acute pancreatitis,”“primary hyperparathyroidism,”“pregnancy,”“labor,”“puerperium,”and“postpartum.”Additional studies were identified by reviewing the reference lists of retrieved studies.Demographic,imaging,surgical,obstetric,and outcome data were obtained.RESULTS Fifty-four cases were collected from the 51 studies.The median maternal age was 29 years.PHPT-induced AP starts at the 20th gestational week;higher gestational weeks were seen in mothers who died(mean gestational week 28).Median values of amylase(1399,Q1-Q3=519-2072),lipase(2072,Q1-Q3=893-2804),serum calcium(3.5,Q1-Q3=3.1-3.9),and parathormone(PTH)(384,Q1-Q3=123-910)were reported.In 46 cases,adenoma was the cause of PHPT,followed by 2 cases of carcinoma and 1 case of hyperplasia.In the remaining 5 cases,the diagnosis was not reported.Neck ultrasound was positive in 34 cases,whereas sestamibi was performed in 3 cases,and neck computed tomography or magnetic resonance imaging was performed in 9 cases(the enlarged parathyroid gland was not localized in 3 cases).Surgery was the preferred treatment during pregnancy in 33 cases(median week of gestation 25,Q1-Q3=20-30)and postpartum in 12 cases.The timing was not reported in the remaining 9 cases,or surgery was not performed.AP was managed surgically in 11 cases and conservatively in 43(79.6%)cases.Maternal and fetal mortality was 9.3%(5 cases).Surgery was more common in deceased mothers(60.0%vs 16.3%;P=0.052),and PTH values tended to be higher in this group(910 pg/mL vs 302 pg/mL;P=0.059).Maternal mortality was higher with higher serum lipase levels and earlier delivery week.Higher calcium(4.1 mmol/L vs 3.3 mmol/L;P=0.009)and PTH(1914 pg/mL vs 302 pg/mL;P=0.003)values increased fetal/child mortality,as well as abortions(40.0%vs 0.0%;P=0.007)and complex deliveries(60.0%vs 8.2%;P=0.01).CONCLUSION If serum calcium is not tested during admission,definitive diagnosis of PHPT-induced AP in pregnancy is delayed,while early diagnosis and immediate intervention lead to excellent maternal and fetal outcomes. 展开更多
关键词 Primary hyperparathyroidism Acute pancreatitis PREGNANCY DIAGNOSIS Maternal mortality Fetal mortality algorithm
下载PDF
上一页 1 2 250 下一页 到第
使用帮助 返回顶部