Topics (349k) Articles (361k) Users (420) Discussions (237) Comments (383) Files (12k) New article
Basil Altaie could refer to an individual, but without additional context, it's challenging to provide specific information. It’s possible that he may be a public figure, professional, or someone notable in a certain field.
Amir Hamudi Hasan al-Sadi is an individual known in connection with the 2003 invasion of Iraq by the United States. He was identified as a significant figure within the Iraqi government at the time of Saddam Hussein. Al-Sadi was notably involved in Iraq's military and security operations, particularly in relation to weapons programs.
The term "Iraqi nuclear physicists" typically refers to scientists and researchers in Iraq who specialize in nuclear physics and related fields, including nuclear engineering, nuclear chemistry, and radiation science. Historically, Iraq has had a nuclear program, especially during the late 20th century, which aimed at developing nuclear technology for various purposes, including energy production and scientific research. This program was notably active during the regime of Saddam Hussein.
Townsend discharge refers to the phenomenon in gas physics and electrical engineering where an electrical discharge occurs in a gas due to the ionization of gas particles. Named after the physicist J. S. Townsend, who studied the behavior of electric discharges in gases, this process is fundamental to understanding how gases can conduct electricity under certain conditions. In the Townsend discharge process, when a sufficiently high voltage is applied across two electrodes in a gas, free electrons are accelerated towards the positive electrode.
Thermal ionization is a process in which an atom or molecule becomes ionized, meaning it loses one or more of its electrons, due to thermal energy (heat). This phenomenon typically occurs at elevated temperatures where the kinetic energy of the atoms or molecules is sufficient to overcome the ionization energy, which is the energy required to remove an electron from an atom. In thermal ionization, as the temperature increases, the atoms gain additional thermal energy, which can facilitate the ionization process.
Self-ionization of water, also known as autoionization, is a process in which water molecules dissociate into ions. In this process, two water (H₂O) molecules interact, resulting in the formation of a hydroxide ion (OH⁻) and a hydronium ion (H₃O⁺).
Resonance ionization is a process used primarily to selectively ionize specific atoms or molecules through the use of laser radiation. The technique involves exciting an atom to a higher energy state using a laser photon that matches the energy difference between the ground state and an excited state of the atom. Once the atom is in this excited state, a second photon can be used to further ionize it, ejecting an electron and creating an ion.
Probe electrospray ionization (PESI) is a technique used in mass spectrometry for the ionization of samples, particularly in the analysis of biomolecules, drugs, and other complex mixtures. It is a variant of electrospray ionization (ESI), which is a widely used ionization method. In PESI, a probe is used to directly sample the analyte from a solid or liquid surface.
Ionization instability refers to a phenomenon in the context of atomic or molecular systems, particularly in plasma physics and astrophysics, where the ionization of particles (atoms or molecules) leads to an unstable state. This instability can manifest in various ways, often influencing the behavior of charged particles in a given environment.
Impact ionization is a process in which an energetic charge carrier (such as an electron) collides with an atom or a lattice ion in a semiconductor or insulator material, imparting enough energy to the atom to free an additional electron. This results in the generation of electron-hole pairs, effectively increasing the number of charge carriers in the material.
The Simultaneous Algebraic Reconstruction Technique (SART) is an iterative algorithm used primarily in the field of image reconstruction, especially in computed tomography (CT). SART is part of a broader class of techniques that solve the inverse problem of reconstructing an image or object from its projections, which can be seen in various imaging modalities beyond CT, including medical imaging and industrial applications.
Seismic tomography is a geophysical technique used to image the Earth's interior by analyzing the propagation of seismic waves generated by earthquakes or artificial sources. It is akin to the medical imaging technique of CT (computed tomography), where cross-sectional images of the body are created. In seismic tomography, seismologists collect data from various seismic stations that detect waves produced by seismic events. These waves can be divided into two main types: primary waves (P-waves) and secondary waves (S-waves).
Reverse Monte Carlo (RMC) is a computational technique used primarily in the fields of materials science and crystallography to model and analyze the structures of materials, particularly those that are disordered, such as amorphous solids or liquids. Unlike traditional Monte Carlo methods, which typically start with an initial model and sample configurations that mimic a known distribution, RMC starts with experimental data and seeks configurations that can reproduce that data.
Regularization by spectral filtering is a technique used in fields such as statistics, machine learning, and signal processing to address issues of overfitting and to improve the stability of the solutions to inverse problems. The basic concept revolves around separating the signal (or data) of interest from noise by manipulating its spectral content—typically in the frequency domain. ### Key Concepts: 1. **Spectral Domain**: Spectral filtering involves transforming data into the frequency domain, usually via techniques like the Fourier Transform.
Regularization is a mathematical technique used primarily in statistical modeling and machine learning to prevent overfitting. Overfitting occurs when a model learns the noise in the training data rather than the underlying distribution, which can lead to poor generalization to new, unseen data. The basic idea behind regularization is to impose a penalty on the complexity of the model.
Phase retrieval is a mathematical and computational technique used to recover the phase information of a signal or wave from intensity measurements. This is particularly relevant in fields such as optics, imaging, and signal processing, where the amplitude (intensity) of a signal can often be measured directly, but the phase information is lost or difficult to obtain.
The phase problem is a fundamental issue in the field of X-ray crystallography and other areas of wave physics, where the information about the phase of a wave is lost or not directly measurable. This problem stems from the fact that when a crystal is subjected to X-ray diffraction, the resulting intensity of the diffracted beams can be measured, but the phase of those beams cannot be directly observed.
Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.Figure 3. Visual Studio Code extension installation.Figure 5. . You can also edit articles on the Web editor without installing anything locally. Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension. - Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact





