Mahmood Mazarei - Academia.edu (original) (raw)

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Papers by Mahmood Mazarei

Universality of interfacial roughness in growing epithelial tissue has remained a controversial i... more Universality of interfacial roughness in growing epithelial tissue has remained a controversial issue. Kardar-Parisi-Zhang (KPZ) and Molecular Beam Epitaxy (MBE) universality classes have been reported among other behaviors including total lack of universality. Here, we utilize a kinetic division model for deformable cells to investigate cell-colony scaling. With seemingly minor model changes, it can reproduce both KPZ- and MBE-like scaling in configurations that mimic the respective experiments. This result neutralizes the apparent scaling controversy. It can be speculated that this diversity in growth behavior is beneficial for efficient evolution and versatile growth dynamics.

Scientific Reports

Extreme events occur in a variety of natural, technical, and societal systems and often have cata... more Extreme events occur in a variety of natural, technical, and societal systems and often have catastrophic consequences. Their low-probability, high-impact nature has recently triggered research into improving our understanding of generating mechanisms, providing early warnings as well as developing control strategies. For the latter to be effective, knowledge about dynamical resistance of a system prior to an extreme event is of utmost importance. Here we introduce a novel time-seriesbased and non-perturbative approach to efficiently monitor dynamical resistance and apply it to highresolution observations of brain activities from 43 subjects with uncontrollable epileptic seizures. We gain surprising insights into pre-seizure dynamical resistance of brains that also provide important clues for success or failure of measures for seizure prevention. The novel resistance monitoring perspective advances our understanding of precursor dynamics in complex spatio-temporal systems with potential applications in refining control strategies. Extreme events are usually considered as rare and unpredictable and/or as strongly deviating from normality and critically determine the evolution and character of a vulnerable human or natural system 1-6. Earthquakes, tsunamis, or extreme weather events-such as heat waves, droughts, floods, heavy precipitation, or tornadoes-are well known extreme events and can lead to disasters when interacting with exposed or vulnerable systems. Likewise, events such as meltdown of nuclear power plants 7 , large-scale blackouts in power supply networks 8,9 , market crashes 10,11 , mass panics 12 , wars 13 , harmful algal blooms in marine ecosystems 14 , epileptic seizures in the human brain 15 , or even competition for attention in social media 16 can have catastrophic consequences for the individual, society, finance, and nature. Research into understanding mechanisms leading to extreme events in diverse systems saw a surge of activities over the past years 17-21 , resulting in a broad spectrum of methods aiming to identify precursors of extreme events 22-32. Although this multitude of predictive methods indicates that truly generic warning signals are unlikely to exist 33 , the potential to identify precursors of extreme events offers a way forward-in spite of such seemingly unpredictable behavior-to develop strategies for adaptation, mitigation, and avoidance of such events. For such strategies to be effective, knowledge about the dynamical resistance of a system's precursor is indispensable. Here, dynamical resistance refers to a system's ability to adjust its activity to retain its basic functionality when internal or environmental changes occur 34. A continuous, data-driven monitoring of dynamical resistance remains an unsolved issue, especially in open and adaptive high-dimensional systems that are comprised of diverse subsystems with different types of time-varying interaction, and whose dynamics is highly non-stationary. A prime example for such a system is the human brain, a complex network of highly interconnected networks, which are neither random nor entirely regular, and span multiple spatial scales (from individual cells and synapses via cortical columns to (sub)cortical areas). These networks support a rich repertoire of behavioral and cognitive functions, and in the case of brain pathologies, normal and abnormal functions and/or structures can coexist 35 .

RSC Adv., 2016

We report optical and electronic properties of the two main chlorophylls in green plants, namely,... more We report optical and electronic properties of the two main chlorophylls in green plants, namely, chlorophylls a and b. We estimate the electric moments of these molecules and study absorption spectra of the chlorophylls.

Universality of interfacial roughness in growing epithelial tissue has remained a controversial i... more Universality of interfacial roughness in growing epithelial tissue has remained a controversial issue. Kardar-Parisi-Zhang (KPZ) and Molecular Beam Epitaxy (MBE) universality classes have been reported among other behaviors including total lack of universality. Here, we utilize a kinetic division model for deformable cells to investigate cell-colony scaling. With seemingly minor model changes, it can reproduce both KPZ- and MBE-like scaling in configurations that mimic the respective experiments. This result neutralizes the apparent scaling controversy. It can be speculated that this diversity in growth behavior is beneficial for efficient evolution and versatile growth dynamics.

Scientific Reports

Extreme events occur in a variety of natural, technical, and societal systems and often have cata... more Extreme events occur in a variety of natural, technical, and societal systems and often have catastrophic consequences. Their low-probability, high-impact nature has recently triggered research into improving our understanding of generating mechanisms, providing early warnings as well as developing control strategies. For the latter to be effective, knowledge about dynamical resistance of a system prior to an extreme event is of utmost importance. Here we introduce a novel time-seriesbased and non-perturbative approach to efficiently monitor dynamical resistance and apply it to highresolution observations of brain activities from 43 subjects with uncontrollable epileptic seizures. We gain surprising insights into pre-seizure dynamical resistance of brains that also provide important clues for success or failure of measures for seizure prevention. The novel resistance monitoring perspective advances our understanding of precursor dynamics in complex spatio-temporal systems with potential applications in refining control strategies. Extreme events are usually considered as rare and unpredictable and/or as strongly deviating from normality and critically determine the evolution and character of a vulnerable human or natural system 1-6. Earthquakes, tsunamis, or extreme weather events-such as heat waves, droughts, floods, heavy precipitation, or tornadoes-are well known extreme events and can lead to disasters when interacting with exposed or vulnerable systems. Likewise, events such as meltdown of nuclear power plants 7 , large-scale blackouts in power supply networks 8,9 , market crashes 10,11 , mass panics 12 , wars 13 , harmful algal blooms in marine ecosystems 14 , epileptic seizures in the human brain 15 , or even competition for attention in social media 16 can have catastrophic consequences for the individual, society, finance, and nature. Research into understanding mechanisms leading to extreme events in diverse systems saw a surge of activities over the past years 17-21 , resulting in a broad spectrum of methods aiming to identify precursors of extreme events 22-32. Although this multitude of predictive methods indicates that truly generic warning signals are unlikely to exist 33 , the potential to identify precursors of extreme events offers a way forward-in spite of such seemingly unpredictable behavior-to develop strategies for adaptation, mitigation, and avoidance of such events. For such strategies to be effective, knowledge about the dynamical resistance of a system's precursor is indispensable. Here, dynamical resistance refers to a system's ability to adjust its activity to retain its basic functionality when internal or environmental changes occur 34. A continuous, data-driven monitoring of dynamical resistance remains an unsolved issue, especially in open and adaptive high-dimensional systems that are comprised of diverse subsystems with different types of time-varying interaction, and whose dynamics is highly non-stationary. A prime example for such a system is the human brain, a complex network of highly interconnected networks, which are neither random nor entirely regular, and span multiple spatial scales (from individual cells and synapses via cortical columns to (sub)cortical areas). These networks support a rich repertoire of behavioral and cognitive functions, and in the case of brain pathologies, normal and abnormal functions and/or structures can coexist 35 .

RSC Adv., 2016

We report optical and electronic properties of the two main chlorophylls in green plants, namely,... more We report optical and electronic properties of the two main chlorophylls in green plants, namely, chlorophylls a and b. We estimate the electric moments of these molecules and study absorption spectra of the chlorophylls.