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Small heat shock protein B8:from cell functions to its involvement in diseases and potential therapeutic applications

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Neural Regeneration Research 2025年第10期20卷 2872-2886页

作者： Marta Chierichetti Riccardo Cristofani Valeria Crippa Veronica Ferrari Marta Cozzi Elena Casarotto Paola Pramaggiore Laura Cornaggia Guglielmo Patelli ali mohamed Margherita Piccolella Mariarita Galbiati Paola Rusmini Barbara Tedesco Angelo Poletti Laboratory of Experimental Biology Dipartimento di Scienze Farmacologiche e Biomolecolari“Rodolfo Paoletti”(DiSFeB)Universitàdegli Studi di MilanoMilanItaly

Heat shock protein family B(small)member 8(HSPB8)is a 22 kDa ubiquitously expressed protein belonging to the family of small heat shock ***8 is involved in various cellular mechanisms mainly related to proteotoxic stress response and in other processes such as inflammation,cell division,and ***8 binds misfolded clients to prevent their aggregation by assisting protein refolding or degradation through chaperone-assisted selective *** line with this function,the pro-degradative activity of HSPB8 has been found protective in several neurodegenerative and neuromuscular diseases characterized by protein misfolding and *** cancer,HSPB8 has a dual role being capable of exerting either a pro-or an anti-tumoral activity depending on the pathways and factors expressed by the model of cancer under ***,HSPB8 exerts a protective function in different diseases by modulating the inflammatory response,which characterizes not only neurodegenerative diseases,but also other chronic or acute conditions affecting the nervous system,such as multiple sclerosis and intracerebellar *** note,HSPB8 modulation may represent a therapeutic approach in other neurological conditions that develop as a secondary consequence of other *** is the case of cognitive impairment related to diabetes mellitus,in which HSPB8 exerts a protective activity by assuring mitochondrial *** review aims to summarize the diverse and multiple functions of HSPB8 in different pathological conditions,focusing on the beneficial effects of its ***-based and alternative therapeutic approaches targeting HSPB8 and its regulated pathways will be discussed,emphasizing how new strategies for cell and tissue-specific delivery represent an avenue to advance in disease treatments.

关键词： aggregation autophagy cancer chaperone chaperone-assisted selective autophagy cognitive impairment HSPB8 neuroinflammation neuromuscular diseases therapy

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Robust Output Practical Stability of Time-Varying Nonlinear Control Systems via Indefinite Lyapunov Functions

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Journal of Systems Science & Complexity 2024年第6期37卷 2595-2613页

作者： DAMAK Hanen ABOTHHER Amal HAMMAMI mohamed ali Department of Mathematics University of Sfax Preparatory Engineering Institute of Sfax Department of Mathematics University of Zawia Faculty of education Abu Essa Department of Mathematics University of Sfax Faculty of Sciences of Sfax

This paper focuses on studying the problem of robust output practical stability of timevarying nonlinear control systems. The main innovation lies in the fact that the proposed approach for stability analysis allows for the computation of bounds that characterize the asymptotic convergence of solutions to a small ball centered at the origin using a Lyapunov method with a definite *** different conditions on the perturbation, the authors demonstrate that the system can be globally robustly asymptotically output stable by designing a candidate feedback controller. Finally, three examples are given to illustrate the practical implications and significance of the theoretical results.

关键词： Control theory global robust practical asymptotic output stability (GRPAOS) Lyapunov method time-varying control systems

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A Multi-Level Selective Maintenance Strategy Combined to Data Mining Approach for Multi-Component System Subject to Propagated Failures

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Journal of Systems Science and Systems Engineering 2022年第3期31卷 313-337页

作者： mohamed ali Kammoun Zied Hajej Nidhal Rezg Universite de Lorraine LGIPMF-57000 MetzFrance Ecole poly technique du Groupe Honoris United Universities-Tunisia

In several industrial fields like air transport,energy industry and military domain,maintenance actions are carried out during downtimes in order to maintain the reliability and availability of production *** such a circumstance,selective maintenance strategy is considered the reliable solution for selecting the faulty components to achieve the next mission without *** this paper,a novel multi-level decision making approach based on data mining techniques is investigated to determine an optimal selective maintenance *** the first-level,the age acceleration factor and its impact on the component nominal age are used to establish the local *** first decision making employed K-means clustering algorithm that exploited the historical maintenance *** on the first-level intervention plan,the remaining-levels identify the stochastic dependence among components by relying upon Apriori association rules algorithm,which allows to discover of the failure occurrence *** addition,at each decision making level,an optimization model combined to a set of exclusion rules are called to supply the optimal selective maintenance plan within a reasonable time,minimizing the total maintenance cost under a required reliability *** illustrate the robustness of the proposed strategy,numerical examples and a FMS real study case have been solved.

关键词： Selective maintenance stochastic dependence age acceleration factor data mining flexible manufacturing system

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ON A SECOND ORDER DISSIPATIVE ODE IN HILBERT SPACE WITH AN INTEGRABLE SOURCE TERM

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Acta Mathematica Scientia 2012年第1期32卷 155-163页

作者： Alain Haraux mohamed ali Jendoubi UPMC Univ Paris 06 UMR 7598Laboratoire Jacques-Louis Lions CNRS UMR 7598Laboratoire Jacques-Louis Lions Facult des Sciences de Bizerte Dpartement de Mathmatiques

Asymptotic behaviour of solutions is studied for some second order equations including the model casex（t）＋γx（t）＋ ↓△φb（x（t）） = h（t） with γ 〉 0 and h ∈ L1（O, ＋∞; H）, φ being continuouly differentiable with locally Lipschitz continuous gradient and bounded from below. In particular when φ is convex, all solutions tend to minimize the potential φ as time tends to infinity and the existence of one bounded trajectory implies the weak convergence of all solutions to equilibrium points.

关键词： dissipative dynamical system asymptotic behaviour gradient system heavyball with friction

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Linearly and Quadratically Separable Classifiers Using Adaptive Approach

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Journal of Computer Science & Technology 2011年第5期26卷 908-918页

作者： mohamed Abdel-Kawy mohamed ali Soliman Rasha M.Abo-Bakr Department of Computer and Systems Engineering Faculty of EngineeringZagazig UniversityZagazigEgypt Departement of Mathematics Faculty of ScienceZagazig UniversityZagazigEgypt

This paper presents a fast adaptive iterative algorithm to solve linearly separable classification problems in R *** each iteration,a subset of the sampling data （n-points,where n is the number of features） is adaptively chosen and a hyperplane is constructed such that it separates the chosen n-points at a margin and best classifies the remaining *** classification problem is formulated and the details of the algorithm are ***,the algorithm is extended to solving quadratically separable classification *** basic idea is based on mapping the physical space to another larger one where the problem becomes linearly *** illustrations show that few iteration steps are sufficient for convergence when classes are linearly *** nonlinearly separable data,given a specified maximum number of iteration steps,the algorithm returns the best hyperplane that minimizes the number of misclassified points occurring through these *** with other machine learning algorithms on practical and benchmark datasets are also presented,showing the performance of the proposed algorithm.

关键词： linear classification quadratic classification iterative approach adaptive technique

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Price Prediction of Seasonal Items Using Machine Learning and Statistical Methods

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Computers, Materials & Continua 2022年第2期70卷 3473-3489页

作者： mohamed ali mohamed Ibrahim Mahmoud El-Henawy Ahmad Salah Faculty of Computers and Informatics Zagazig UniversityZagazigEgypt

Price prediction of goods is a vital point of research due to how common e-commerce platforms *** are several efforts conducted to forecast the price of items using classicmachine learning algorithms and *** models can predict prices of various financial instruments,e.g.,gold,oil,cryptocurrencies,stocks,and second-hand *** these efforts,the literature has no model for predicting the prices of seasonal goods(e.g.,Christmas gifts).In this context,we framed the task of seasonal goods price prediction as a regression ***,we utilized a real online trailer dataset of Christmas gifts and then we proposed several machine learningbased models and one statistical-based model to predict the prices of these seasonal ***,we utilized a real-life dataset of Christmas gifts for the prediction ***,we proposed support vector regressor(SVR),linear regression,random forest,and ridgemodels as machine learningmodels for price ***,we proposed an autoregressive-integrated-movingaverage(ARIMA)model for the same purpose as a statistical-based ***,we evaluated the performance of the proposed models;the comparison shows that the best performing model was the random forest model,followed by the ARIMA model.

关键词： ARIMA machine learning price prediction random forest ridge support vector regressor

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Dengue virus infections and anti-dengue virus activities of Andrographis paniculata

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Asian Pacific Journal of Tropical Medicine 2020年第2期13卷 49-55页

作者： mohamed ali-Seyed Kavitha Vijayaraghavan Department of Clinical Biochemistry Faculty of MedicineUniversity of TabukTabukSaudi ArabiaTabuk 71491Saudi Arabia Department of Chemical Engineering Agni College of TechnologyChennaiTamil NaduIndia

Dengue is a debilitating disease that poses a perpetual threat to human health and increases the global economic burden every *** advances in medical sciences,dengue virus(DENV)infects approximately 200 million people every *** date,no effective antiviral is valiable to treat DENV in individuals despite great efforts in accomplishing these *** approaches have been used in the search for dengue antiviral like screening of combinatorial compounds against DENV enzymes and structurebased computational *** recent years,investigators have turned their focus into medicinal plants,trying to identify compounds that can be used as dengue *** represents a great reservoir of potential substances that can be explored with the aim of discovering new drugs that can be either used directly as pharmaceuticals or can provide drug leads,which can be scrutinized further for the development of new anti-dengue natural *** previous investigations have dealt with numerous plant extracts or bioactive principles for their antiviral property as they normally considered being safer when compared to synthetic *** paniculata belongs to family Acanthaceae and is generally known as‘king of bitters’.Diverse bioactive compounds from this plant such as diterpenes,flavonoids,xanthones,noriridoides and other miscellaneous compounds have exhibited their potential as therapeutics for various chronic as well as infectious *** review is based on literature review on scientific journals,books and electronic sources,which highlights the pathogenesis of DENV and describe an assortment of bioactive principles that have been possessing antiviral potential,which include dengue and discuss the therapeutic efficacy and mechanism of action of Andrographis ***,a detailed and more comprehensive clinical trial on mammalian tissues and organs is needed in future studies.

关键词： Andrographis paniculata Dengue Phytochemicals Natural products Andrographolide

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Managing Delivery of Safeguarding Substances as a Mitigation Against Outbreaks of Pandemics

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Computers, Materials & Continua 2021年第7期68卷 1161-1181页

作者： Said ali Hassan Khalid Alnowibet Prachi Agrawal ali Wagdy mohamed Department of Operations Research and Decision Support Faculty of Computers and Articial IntelligenceCairo UniversityGiza12613Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadhSaudi Arabia Trafc Safety Technologies Chair Vice Deanship of Scientic ResearchKing Saud UniversityRiyadhSaudi Arabia Department of Mathematics and Scientic Computing National Institute of TechnologyHamirpur177005India Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt School of Engineering and Applied Sciences Wireless Intelligent Networks Center(WINC)Nile UniversityGizaEgypt

The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics.A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specic time period.A nonlinear binary mathematical programming model for the problem is *** decision variables are binary ones that represent whether to choose a specic consumer,and design constraints are formulated to keep track of the chosen *** better illustrate the problem,objective,and problem constraints,a real application case study is *** case study involves the optimum delivery of safeguarding substances to several hospitals in the Al-Gharbia Governorate in *** hospitals are selected to represent the consumers of safeguarding substances,as they are the rst crucial frontline for mitigation against a pandemic outbreak.A distribution truck is used to distribute the substances from the main store to the hospitals in specied required quantities during a given working *** objective function is formulated in order to maximize the total amount of delivered quantities during the specied time *** case study is solved using a novel Discrete Binary Gaining Sharing Knowledge-based Optimization algorithm(DBGSK),which involves two main stages:discrete binary junior and senior gaining and sharing *** has the ability of nding the solutions of the introduced problem,and the obtained results demonstrate robustness and convergence toward the optimal solutions.

关键词： Safeguarding substances mitigation against pandemic outbreaks supply chain management metaheuristic optimization

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Optimum Location of Field Hospitals for COVID-19: A Nonlinear Binary Metaheuristic Algorithm

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Computers, Materials & Continua 2021年第7期68卷 1183-1202页

作者： Said ali Hassan Khalid Alnowibet Prachi Agrawal ali Wagdy mohamed Department of Operations Research and Decision Support Faculty of Computers and Artificial IntelligenceCairo UniversityGiza12613Egypt College of Science Department of Statistics and Operations ResearchKing Saud UniversityRiyadhSaudi Arabia Department of Mathematics and Scientific Computing National Institute of Technology HamirpurHimachal Pradesh177005India Department of Operations Research Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt

Determining the optimum location of facilities is critical in many fields,particularly in *** study proposes the application of a suitable location model for field hospitals during the novel coronavirus 2019(COVID-19)*** used model is the most appropriate among the three most common location models utilized to solve healthcare problems(the set covering model,the maximal covering model,and the P-median model).The proposed nonlinear binary constrained model is a slight modification of the maximal covering model with a set of nonlinear *** model is used to determine the optimum location of field hospitals for COVID-19 risk *** designed mathematical model and the solution method are used to deploy field hospitals in eight governorates in Upper *** this case study,a discrete binary gaining–sharing knowledge-based optimization(DBGSK)algorithm is *** DBGSK algorithm is based on how humans acquire and share knowledge throughout their *** DBGSK algorithm mainly depends on two junior and senior binary *** two stages enable DBGSK to explore and exploit the search space efficiently and effectively,and thus it can solve problems in binary space.

关键词： Facility location nonlinear binary model field hospitals for COVID-19 gaining-sharing knowledge-based metaheuristic algorithm

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Site-Specific Nitrogen Management in Dry Direct-Seeded Rice Using Chlorophyll Meter and Leaf Colour Chart

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Pedosphere 2015年第1期25卷 72-81页

作者： ali mohamed ali Harmit Singh THIND Sandeep SHARMA YADVINDER-SINGH Department of Soil Science Punjab Agricultural University Department of Soil Fertility and Microbiology Desert Research Centre

The need to maintain high rice yields and improve fertilizer nitrogen(N)-use efficiency has fueled the use of tools such as leaf colour chart(LCC) and chlorophyll meter(SPAD meter) in managing fertilizer N based on colour of the leaf. Field experiments were conducted during 2011 to 2013 at Ludhiana, India to assess the need for basal N application and to establish critical threshold values of leaf greenness as measured by LCC and SPAD meter for formulating strategies for in-season management of fertilizer N in dry direct-seeded rice(DDSR). Avoiding application of N at sowing did not adversely affect rice grain yield, indicating that basal N application in DDSR was not necessary and might lead to reduced N-use efficiency. Monitoring N uptake rate during the growing season of DDSR suggested that N uptake rate peaked at the two growth stages: maximum tillering(42 to 56 days after sowing(DAS))and panicle initiation stages(70 to 84 DAS). Using the Cate-Nelson procedure, critical LCC and SPAD meter values for fertilizer N application worked out to be 4 and 37, respectively. Real-time fertilizer N management strategy based on applying 30 kg N ha-1whenever SPAD meter or LCC readings fell below the critical values maintained optimum rice yields along with higher N-use efficiency than that observed by following blanket recommendation for fertilizer N in the region. The fixed-time variable-dose strategy consisted of applying prescriptive doses of 20 kg N ha-1at 14 DAS and 30 kg N ha-1at 28 DAS and corrective doses of 30, 40 or 50 kg N ha-1at 49 and 70 DAS depending upon LCC shade to be ≥ 4, 4–3.5, or < 3.5 and SPAD meter readings to be ≥ 40, 40–35, or< 35, respectively. This strategy also resulted in optimal rice yield along with higher N-use efficiency as compared to the blanket recommendation. This study revealed that in DDSR, fertilizer N could be managed more efficiently using the tools of LCC and SPAD meter than the current blanket recommendation.

关键词： basal N application critical value grain yield leaf greenness N-use efficiency

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