UveitisUveitis (ˌjuːvi.aɪtIs) is inflammation of the uvea, the pigmented layer of the eye between the inner retina and the outer fibrous layer composed of the sclera and cornea. The uvea consists of the middle layer of pigmented vascular structures of the eye and includes the iris, ciliary body, and choroid. Uveitis is described anatomically, by the part of the eye affected, as anterior, intermediate or posterior, or panuveitic if all parts are involved.
LupusLupus, technically known as systemic lupus erythematosus (SLE), is an autoimmune disease in which the body's immune system mistakenly attacks healthy tissue in many parts of the body. Symptoms vary among people and may be mild to severe. Common symptoms include painful and swollen joints, fever, chest pain, hair loss, mouth ulcers, swollen lymph nodes, feeling tired, and a red rash which is most commonly on the face. Often there are periods of illness, called flares, and periods of remission during which there are few symptoms.
Demyelinating diseaseA demyelinating disease refers to any disease affecting the nervous system where the myelin sheath surrounding neurons is damaged. This damage disrupts the transmission of signals through the affected nerves, resulting in a decrease in their conduction ability. Consequently, this reduction in conduction can lead to deficiencies in sensation, movement, cognition, or other functions depending on the nerves affected. Various factors can contribute to the development of demyelinating diseases, including genetic predisposition, infectious agents, autoimmune reactions, and other unknown factors.
Discrete Fourier transformIn mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT (IDFT) is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies.
Discrete cosine transformA discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. The DCT, first proposed by Nasir Ahmed in 1972, is a widely used transformation technique in signal processing and data compression. It is used in most digital media, including (such as JPEG and HEIF), digital video (such as MPEG and H.26x), digital audio (such as Dolby Digital, MP3 and AAC), digital television (such as SDTV, HDTV and VOD), digital radio (such as AAC+ and DAB+), and speech coding (such as AAC-LD, Siren and Opus).
Neuromyelitis optica spectrum disorderNeuromyelitis optica spectrum disorders (NMOSD), including neuromyelitis optica (NMO), are autoimmune diseases characterized by acute inflammation of the optic nerve (optic neuritis, ON) and the spinal cord (myelitis). Episodes of ON and myelitis can be simultaneous or successive. A relapsing disease course is common, especially in untreated patients. In more than 80% of cases, NMO is caused by immunoglobulin G autoantibodies to aquaporin 4 (anti-AQP4), the most abundant water channel protein in the central nervous system.
Discrete sine transformIn mathematics, the discrete sine transform (DST) is a Fourier-related transform similar to the discrete Fourier transform (DFT), but using a purely real matrix. It is equivalent to the imaginary parts of a DFT of roughly twice the length, operating on real data with odd symmetry (since the Fourier transform of a real and odd function is imaginary and odd), where in some variants the input and/or output data are shifted by half a sample. A family of transforms composed of sine and sine hyperbolic functions exists.
Modified discrete cosine transformThe modified discrete cosine transform (MDCT) is a transform based on the type-IV discrete cosine transform (DCT-IV), with the additional property of being lapped: it is designed to be performed on consecutive blocks of a larger dataset, where subsequent blocks are overlapped so that the last half of one block coincides with the first half of the next block. This overlapping, in addition to the energy-compaction qualities of the DCT, makes the MDCT especially attractive for signal compression applications, since it helps to avoid artifacts stemming from the block boundaries.
