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Photobiomodulation:a novel approach to promote trans-differentiation of adipose-derived stem cells into neuronal-like cells

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Neural Regeneration Research 2025年第2期20卷 598-608页

作者： Daniella Da Silva Madeleen Jansen van Rensburg Anine Crous Heidi Abrahamse Laser Research Centre Faculty of Health SciencesUniversity of JohannesburgDoornfonteinJohannesburgSouth Africa

Photobiomodulation,originally used red and near-infrared lasers,can alter cellular *** has been demonstrated that the visible spectrum at 451-540 nm does not necessarily increase cell proliferation,near-infrared light promotes adipose stem cell proliferation and affects adipose stem cell migration,which is necessary for the cells homing to the site of *** this in vitro study,we explored the potential of adipose-derived stem cells to differentiate into neurons for future translational regenerative treatments in neurodegenerative disorders and brain *** investigated the effects of various biological and chemical inducers on trans-differentiation and evaluated the impact of photobiomodulation using 825 nm near-infrared and 525 nm green laser light at 5 J/*** adipose-derived stem cells can be used in autologous grafting and photobiomodulation has been shown to have biostimulatory *** findings reveal that adipose-derived stem cells can indeed trans-differentiate into neuronal cells when exposed to inducers,with pre-induced cells exhibiting higher rates of proliferation and trans-differentiation compared with the control ***,green laser light stimulation led to notable morphological changes indicative of enhanced trans-differentiation,while near-infrared photobiomodulation notably increased the expression of neuronal *** biochemical analysis and enzyme-linked immunosorbent assays,we observed marked improvements in viability,proliferation,membrane permeability,and mitochondrial membrane potential,as well as increased protein levels of neuron-specific enolase and ciliary neurotrophic ***,our results demonstrate the efficacy of photobiomodulation in enhancing the trans-differentiation ability of adipose-derived stem cells,offering promising prospects for their use in regenerative medicine for neurodegenerative disorders and brain injuries.

关键词： differentiation inducers green photobiomodulation immortalized adipose-derived stem cell near-infrared photobiomodulation neurodegenerative disease neurogenesis photobiomodulation trans-differentiation

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SOME RECENT PROGRESS ON STOCHASTIC HEAT EQUATIONS

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Acta Mathematica Scientia 2019年第3期39卷 874-914页

作者： Yaozhong HU Department of mathematical and statistical sciences University of Alberta

This article attempts to give a short survey of recent progress on a class of elementary stochastic partial differential equations (for example, stochastic heat equations) driven by Gaussian noise of various covariance structures. The focus is on the existence and uniqueness of the classical (square integrable) solution (mild solution, weak solution). It is also concerned with the Feynman-Kac formula for the solution;Feynman-Kac formula for the moments of the solution;and their applications to the asymptotic moment bounds of the solution. It also briefly touches the exact asymptotics of the moments of the solution.

关键词： Gaussian random field Gaussian noise stochastic partial differential equation(stochastic heat equation) Feynman-Kac formula for the solution FeynmanKac formula for the moments of the solution chaos expansion hypercontractivity moment bounds Holder continuity joint Holder continuity asymptotic behaviour Trotter-Lie formula Skorohod integral

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Homogeneous wavelets and framelets with the refinable structure

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Science China Mathematics 2017年第11期60卷 2173-2198页

作者： HAN Bin Department of mathematical and statistical sciences University of Alberta

Homogeneous wavelets and framelets have been extensively investigated in the classical theory of wavelets and they are often constructed from refinable functions via the multiresolution analysis. On the other hand, nonhomogeneous wavelets and framelets enjoy many desirable theoretical properties and are often intrinsically linked to the refinable structure and multiresolution analysis. In this paper, we provide a comprehensive study on connecting homogeneous wavelets and framelets to nonhomogeneous ones with the refinable structure. This allows us to understand better the structure of homogeneous wavelets and framelets as well as their connections to the refinable structure and multiresolution analysis.

关键词： homogeneous wavelets and framelets nonhomogeneous wavelets and framelets refinable structure shift-invariant spaces multiresolution analysis Schur decomposition for Hermite matrices of measurable functions singular value decomposition for matrices of measurable functions

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statistical Procedures for Estimating and Detecting Climate Changes

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Advances in Atmospheric sciences 2006年第1期23卷 61-68页

作者： S. S. P. SHEN Department of mathematical and statistical sciences University of AlbertaEdmontonCanada

This paper provides a concise description of the philosophy, mathematics, and algorithms for estimating, detecting, and attributing climate changes. The estimation follows the spectral method by using empirical orthogonal functions, also called the method of reduced space optimal averaging. The detection follows the linear regression method, which can be found in most textbooks about multivariate statistical techniques. The detection algorithms are described by using the space-time approach to avoid the non-stationarity problem. The paper includes （1） the optimal averaging method for minimizing the uncertainties of the global change estimate, （2） the weighted least square detection of both single and multiple signals, （3） numerical examples, and （4） the limitations of the linear optimal averaging and detection methods.

关键词： Climate change detection optimal averaging optimal detection mean square error multivariate analysis linear regression inference

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Robustness properties of dimensionality reduction with Gaussian random matrices

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Science China Mathematics 2017年第10期60卷 1753-1778页

作者： HAN Bin XU ZhiQiang Department of mathematical and statistical sciences University of Alberta LSEC ICMSEC Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of mathematical sciences University of Chinese Academy of Sciences

In this paper, motivated by the results in compressive phase retrieval, we study the robustness properties of dimensionality reduction with Gaussian random matrices having arbitrarily erased rows. We first study the robustness property against erasure for the almost norm preservation property of Gaussian random matrices by obtaining the optimal estimate of the erasure ratio for a small given norm distortion rate. As a consequence, we establish the robustness property of Johnson-Lindenstrauss lemma and the robustness property of restricted isometry property with corruption for Gaussian random matrices. Secondly, we obtain a sharp estimate for the optimal lower and upper bounds of norm distortion rates of Gaussian random matrices under a given erasure ratio. This allows us to establish the strong restricted isometry property with the almost optimal restricted isometry property(RIP) constants, which plays a central role in the study of phaseless compressed sensing. As a byproduct of our results, we also establish the robustness property of Gaussian random finite frames under erasure.

关键词： phase retrieval finite frames sparse approximation restricted isometry property Johnson-Lindenstrauss lemma

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Some Ergodic Theorems for a Parabolic Anderson Model

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Acta Mathematica Sinica,English Series 2012年第12期28卷 2443-2462页

作者： Yong LIU LMAM Feng Xia YANG School of mathematical sciences and Institute of Mathematicsand Center for Statistical SciencePeking University LMAM School of Mathematical SciencesPeking University

In this paper, we study some ergodic theorems of a class of linear systems of interacting diffusions, which is a parabolic Anderson model. First, under the assumption that the transition kernel a = （a（i,j））i,j∈s is doubly stochastic, we obtain the long-time convergence to an invariant probability measure Vh starting from a bounded a-harmonic function h based on self-duality property, and then we show the convergence to the invariant probability measure Uh holds for a broad class of initial distributions. Second, if （a（i, j））i,j∈s is transient and symmetric, and the diffusion parameter c remains below a threshold, we are able to determine the set of extremal invariant probability measures with finite second moment. Finally, in the case that the transition kernel （a（i,j））i,j∈s is doubly stochastic and satisfies Case I （see Case I in [Shiga, T.： An interacting system in population genetics. J. Math. Kyoto Univ., 20, 213-242 （1980）]）, we show that this parabolic Anderson model locally dies out independent of the diffusion parameter c.

关键词： Linear system of interacting diffusion parabolic Anderson model ergodic invariant measures clustering phenomena

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Translational challenges in amyotrophic lateral sclerosis therapy with macrophage migration inhibitory factor

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Neural Regeneration Research 2025年第9期20卷 2583-2584页

作者： Leenor Alfahel Aleksandar Rajkovic Adrian Israelson Department of Physiology and Cell Biology Faculty of Health SciencesBen-Gurion University of the NegevBeer ShevaIsraelThe School of Brain Sciences and CognitionBen-Gurion University of the NegevBeer ShevaIsrael

Macrophage migration inhibitory factor(MIF):MIF acts as a pleiotropic inflammatory mediator,playing regulatory roles in innate and adaptive immunity,neuroinflammation,neuroendocrine functions,and nervous system development(Matejuk et al.,2024).In recent years,MIF has attra cted significant inte rest from research groups as a potential target for the treatment of various neurodegenerative diseases,including Alzheimer's disease,Parkinson's disease,multiple sclerosis,and glioblastoma(Matejuk et al.,2024).

关键词： immunity sclerosis

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Divisor Class Halving Algorithms for Genus Three Hyperelliptic Curves

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Chinese Journal of Electronics 2020年第1期29卷 97-105页

作者： YOU Lin YANG Yilin GAO Shuhong School of Cyberspace Security Hangzhou Dianzi University School of mathematical and statistical sciences Clemson University

In an(hyper)elliptic curve cryptosystem,the most important operation or the most time-consuming operation is the divisor scalar multiplication which consists of a sequence of doubling(of divisor) and addition(of two divisors). Point halving algorithms for elliptic curve cryptosystem and divisor halving algorithms for genus-2 hyperelliptic curve cryptosystem had been successively put forward to take the place of doubling algorithms for speeding up(hyper)elliptic curve cryptosystem. We present an outline for an algorithm for divisor halving on genus-3 hyperelliptic curves over the binary field and give some explicit formulae for a class of genus-3 *** algorithm improves previously known best doubling algorithms in most cases. A halve-and-add binary method for divisor scalar multiplications is presented.

关键词： Genus-3 hyperelliptic curve cryptosystem Divisor scalar multiplication Divisor doubling Divisor halving

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Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree Regression(DTR),and Gaussian Process Regression(GPR)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPR method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

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Brain age estimation:premise,promise,and problems

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Neural Regeneration Research 2025年第8期20卷 2313-2314页

作者： Jarrad Perron Ji Hyun Ko Graduate Program in Biomedical Engineering Price Faculty of EngineeringUniversity of ManitobaWinnipegMBCanada PrairieNeuro Research Centre Kleysen Institute for Advanced MedicineHealth Sciences CentreWinnipegMBCanada Department of Human Anatomy and Cell Science Rady Faculty of Health SciencesUniversity of ManitobaWinnipegMBCanada

Premise:The com bined effects of modern healthcare practices which prolong lifespan and declining birthrates have created unprecedented changes in age demographics worldwide that are especially pronounced in Japan,South Korea,Europe,and North *** old age is the most significant predictor of dementia,global healthcare systems must rise to the challenge of providing care for those with neurodegenerative disorders.

关键词： estimation providing birth

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