StudentsEducators

Epigenetic Reprogramming

Epigenetic reprogramming refers to the process by which the epigenetic landscape of a cell is altered, leading to changes in gene expression without modifying the underlying DNA sequence. This phenomenon is crucial during development, stem cell differentiation, and in response to environmental stimuli. Key mechanisms of epigenetic reprogramming include DNA methylation, histone modification, and the action of non-coding RNAs. These changes can be stable and heritable, allowing for cellular plasticity and adaptation. For instance, induced pluripotent stem cells (iPSCs) are created through reprogramming somatic cells, effectively reverting them to a pluripotent state capable of differentiating into various cell types. Understanding epigenetic reprogramming holds significant potential for therapeutic applications, including regenerative medicine and cancer treatment.

Other related terms

contact us

Let's get started

Start your personalized study experience with acemate today. Sign up for free and find summaries and mock exams for your university.

logoTurn your courses into an interactive learning experience.
Antong Yin

Antong Yin

Co-Founder & CEO

Jan Tiegges

Jan Tiegges

Co-Founder & CTO

Paul Herman

Paul Herman

Co-Founder & CPO

© 2025 acemate UG (haftungsbeschränkt)  |   Terms and Conditions  |   Privacy Policy  |   Imprint  |   Careers   |  
iconlogo
Log in

Ito Calculus

Ito Calculus is a mathematical framework used primarily for stochastic processes, particularly in the field of finance and economics. It was developed by the Japanese mathematician Kiyoshi Ito and is essential for modeling systems that are influenced by random noise. Unlike traditional calculus, Ito Calculus incorporates the concept of stochastic integrals and differentials, which allow for the analysis of functions that depend on stochastic processes, such as Brownian motion.

A key result of Ito Calculus is the Ito formula, which provides a way to calculate the differential of a function of a stochastic process. For a function f(t,Xt)f(t, X_t)f(t,Xt​), where XtX_tXt​ is a stochastic process, the Ito formula states:

df(t,Xt)=(∂f∂t+12∂2f∂x2σ2(t,Xt))dt+∂f∂xμ(t,Xt)dBtdf(t, X_t) = \left( \frac{\partial f}{\partial t} + \frac{1}{2} \frac{\partial^2 f}{\partial x^2} \sigma^2(t, X_t) \right) dt + \frac{\partial f}{\partial x} \mu(t, X_t) dB_tdf(t,Xt​)=(∂t∂f​+21​∂x2∂2f​σ2(t,Xt​))dt+∂x∂f​μ(t,Xt​)dBt​

where σ(t,Xt)\sigma(t, X_t)σ(t,Xt​) and μ(t,Xt)\mu(t, X_t)μ(t,Xt​) are the volatility and drift of the process, respectively, and dBtdB_tdBt​ represents the increment of a standard Brownian motion. This framework is widely used in quantitative finance for option pricing, risk management, and in

Shock Wave Interaction

Shock wave interaction refers to the phenomenon that occurs when two or more shock waves intersect or interact with each other in a medium, such as air or water. These interactions can lead to complex changes in pressure, density, and temperature within the medium. When shock waves collide, they can either reinforce each other, resulting in a stronger shock wave, or they can partially cancel each other out, leading to a reduced pressure wave. This interaction is governed by the principles of fluid dynamics and can be described using the Rankine-Hugoniot conditions, which relate the properties of the fluid before and after the shock. Understanding shock wave interactions is crucial in various applications, including aerospace engineering, explosion dynamics, and supersonic aerodynamics, where the behavior of shock waves can significantly impact performance and safety.

Layered Transition Metal Dichalcogenides

Layered Transition Metal Dichalcogenides (TMDs) are a class of materials consisting of transition metals (such as molybdenum, tungsten, and niobium) bonded to chalcogen elements (like sulfur, selenium, or tellurium). These materials typically exhibit a van der Waals structure, allowing them to be easily exfoliated into thin layers, often down to a single layer, which gives rise to unique electronic and optical properties. TMDs are characterized by their semiconducting behavior, making them promising candidates for applications in nanoelectronics, photovoltaics, and optoelectronics.

The general formula for these compounds is MX2MX_2MX2​, where MMM represents the transition metal and XXX denotes the chalcogen. Due to their tunable band gaps and high carrier mobility, layered TMDs have gained significant attention in the field of two-dimensional materials, positioning them at the forefront of research in advanced materials science.

Phase-Change Memory

Phase-Change Memory (PCM) is a type of non-volatile storage technology that utilizes the unique properties of certain materials, specifically chalcogenides, to switch between amorphous and crystalline states. This phase change is achieved through the application of heat, allowing the material to change its resistance and thus represent binary data. The amorphous state has a high resistance, representing a '0', while the crystalline state has a low resistance, representing a '1'.

PCM offers several advantages over traditional memory technologies, such as faster write speeds, greater endurance, and higher density. Additionally, PCM can potentially bridge the gap between DRAM and flash memory, combining the speed of volatile memory with the non-volatility of flash. As a result, PCM is considered a promising candidate for future memory solutions in computing systems, especially in applications requiring high performance and energy efficiency.

Runge’S Approximation Theorem

Runge's Approximation Theorem ist ein bedeutendes Resultat in der Funktionalanalysis und der Approximationstheorie, das sich mit der Approximation von Funktionen durch rationale Funktionen beschäftigt. Der Kern des Theorems besagt, dass jede stetige Funktion auf einem kompakten Intervall durch rationale Funktionen beliebig genau approximiert werden kann, vorausgesetzt, dass die Approximation in einem kompakten Teilbereich des Intervalls erfolgt. Dies wird häufig durch die Verwendung von Runge-Polynomen erreicht, die eine spezielle Form von rationalen Funktionen sind.

Ein wichtiger Aspekt des Theorems ist die Identifikation von Rationalen Funktionen als eine geeignete Klasse von Funktionen, die eine breite Anwendbarkeit in der Approximationstheorie haben. Wenn beispielsweise fff eine stetige Funktion auf einem kompakten Intervall [a,b][a, b][a,b] ist, gibt es für jede positive Zahl ϵ\epsilonϵ eine rationale Funktion R(x)R(x)R(x), sodass:

∣f(x)−R(x)∣<ϵfu¨r alle x∈[a,b]|f(x) - R(x)| < \epsilon \quad \text{für alle } x \in [a, b]∣f(x)−R(x)∣<ϵfu¨r alle x∈[a,b]

Dies zeigt die Stärke von Runge's Theorem in der Approximationstheorie und seine Relevanz in verschiedenen Bereichen wie der Numerik und Signalverarbeitung.

H-Bridge Pulse Width Modulation

H-Bridge Pulse Width Modulation (PWM) is a technique used to control the speed and direction of DC motors. An H-Bridge is an electrical circuit that allows a voltage to be applied across a load in either direction, which makes it ideal for motor control. By adjusting the duty cycle of the PWM signal, which is the proportion of time the signal is high versus low within a given period, the effective voltage and current delivered to the motor can be controlled.

This can be mathematically represented as:

Duty Cycle=tonton+toff\text{Duty Cycle} = \frac{t_{\text{on}}}{t_{\text{on}} + t_{\text{off}}}Duty Cycle=ton​+toff​ton​​

where tont_{\text{on}}ton​ is the time the signal is high and tofft_{\text{off}}toff​ is the time the signal is low. A higher duty cycle means more power is supplied to the motor, resulting in increased speed. Additionally, by reversing the polarity of the output from the H-Bridge, the direction of the motor can easily be changed, allowing for versatile control of motion in various applications.