Received: from hwsrv-466232.hostwindsdns.com ([23.254.225.160]:36475 helo=mobile.ketigenicacc.icu) by stodi.digitalkingdom.org with esmtp (Exim 4.92) (envelope-from <15753-20883-455494-4177-lojban=lojban.org@mail.ketigenicacc.icu>) id 1h4qk1-0006nf-RX for lojban@lojban.org; Fri, 15 Mar 2019 10:35:35 -0700 DKIM-Signature: v=1; a=rsa-sha1; c=relaxed/relaxed; s=k1; d=ketigenicacc.icu; h=Mime-Version:Content-Type:Date:From:Reply-To:Subject:To:Message-ID; i=womenlie@ketigenicacc.icu; bh=pA+4T1uYBcpBoWv8N1kiPt1Aa5o=; b=KvfYrQQaGxnxbP1kERGMi6/gwnTh1gciSH9zn2+TlhFkqUVKZYDg57CUp0M0ZaJ0+wc8nTDjzMX1 SS/l4a4XYBc/AN9wQhRAq8ZFMpkgD9OCt4/kH54ObqZIxLr5SxC50dxNVTSozDYuUdLqu7VFZIGr GLneD8cDnYyRDW5sX4o= DomainKey-Signature: a=rsa-sha1; c=nofws; q=dns; s=k1; d=ketigenicacc.icu; b=gfhWJ0gV9A5O4x3T4UUBZPkJ79HHX6WD0VC+2q5KMvKR5JGirGO5VK6sZ9WILHA8WsEc+nRLcdhk nBhQq66SSyaC/YfJhL/x3pwEukAAriQ991k4nlFhLl3TVERXjM0KAMtP6O+SuY0AHwgfE6ztLkY3 lB8s5rfIvpLghKrwLis=; Mime-Version: 1.0 Content-Type: multipart/alternative; boundary="3baa7067b86a8582617799315e2c7473_5193_6f346" Date: Fri, 15 Mar 2019 18:35:30 +0100 From: "Size Matters" Reply-To: "Women Lie" Subject: John has lost his mind, download this soon. To: Message-ID: X-Spam-Score: 4.1 (++++) X-Spam_score: 4.1 X-Spam_score_int: 41 X-Spam_bar: ++++ X-Spam-Report: Spam detection software, running on the system "stodi.digitalkingdom.org", has NOT identified this incoming email as spam. The original message has been attached to this so you can view it or label similar future email. If you have any questions, see the administrator of that system for details. Content preview: John has lost his mind, download this soon. http://ketigenicacc.icu/clk.2-3d89-5193-6f346-1051-2059-0300-78409642 http://ketigenicacc.icu/clk.14-3d89-5193-6f346-1051-2059-0300-829c39a0 Content analysis details: (4.1 points, 5.0 required) pts rule name description ---- ---------------------- -------------------------------------------------- -0.0 BAYES_40 BODY: Bayes spam probability is 20 to 40% [score: 0.3457] 0.0 URIBL_BLOCKED ADMINISTRATOR NOTICE: The query to URIBL was blocked. 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[URIs: ketigenicacc.icu] 0.7 SPF_SOFTFAIL SPF: sender does not match SPF record (softfail) 0.0 BODY_ENHANCEMENT BODY: Information on growing body parts 0.0 HTML_FONT_LOW_CONTRAST BODY: HTML font color similar or identical to background 0.0 HTML_MESSAGE BODY: HTML included in message 0.0 PP_MIME_FAKE_ASCII_TEXT BODY: MIME text/plain claims to be ASCII but isn't -0.1 DKIM_VALID_EF Message has a valid DKIM or DK signature from envelope-from domain -0.1 DKIM_VALID Message has at least one valid DKIM or DK signature -0.1 DKIM_VALID_AU Message has a valid DKIM or DK signature from author's domain 0.1 DKIM_SIGNED Message has a DKIM or DK signature, not necessarily valid 1.9 RAZOR2_CF_RANGE_51_100 Razor2 gives confidence level above 50% [cf: 100] 0.9 RAZOR2_CHECK Listed in Razor2 (http://razor.sf.net/) 0.8 FSL_BULK_SIG Bulk signature with no Unsubscribe --3baa7067b86a8582617799315e2c7473_5193_6f346 Content-Type: text/plain; Content-Transfer-Encoding: 8bit John has lost his mind, download this soon. http://ketigenicacc.icu/clk.2-3d89-5193-6f346-1051-2059-0300-78409642 http://ketigenicacc.icu/clk.14-3d89-5193-6f346-1051-2059-0300-829c39a0 Provided that they have the same size (each matrix has the same number of rows and the same number of columns as the other), two matrices can be added or subtracted element by element (see Conformable matrix). The rule for matrix multiplication, however, is that two matrices can be multiplied only when the number of columns in the first equals the number of rows in the second (i.e., the inner dimensions are the same, n for an (m×n)-matrix times an (n×p)-matrix, resulting in an (m×p)-matrix. There is no product the other way round, a first hint that matrix multiplication is not commutative. Any matrix can be multiplied element-wise by a scalar from its associated field. The individual items in an m×n matrix A, often denoted by ai,j, where i and j usually vary from 1 to m and n, respectively, are called its elements or entries. For conveniently expressing an element of the results of matrix operations the indices of the element are often attached to the parenthesized or bracketed matrix expression; e.g.: (AB)i,j refers to an element of a matrix product. In the context of abstract index notation this ambiguously refers also to the whole matrix product. A major application of matrices is to represent linear transformations, that is, generalizations of linear functions such as f(x) = 4x. For example, the rotation of vectors in three-dimensional space is a linear transformation, which can be represented by a rotation matrix R: if v is a column vector (a matrix with only one column) describing the position of a point in space, the product Rv is a column vector describing the position of that point after a rotation. The product of two transformation matrices is a matrix that represents the composition of two transformations. Another application of matrices is in the solution of systems of linear equations. If the matrix is square, it is possible to deduce some of its properties by computing its determinant. For example, a square matrix has an inverse if and only if its determinant is not zero. Insight into the geometry of a linear transformation is obtainable (along with other information) from the matrix's eigenvalues and eigenvectors. Applications of matrices are found in most scientific fields. In every branch of physics, including classical mechanics, optics, electromagnetism, quantum mechanics, and quantum electrodynamics, they are used to study physical phenomena, such as the motion of rigid bodies. In computer graphics, they are used to manipulate 3D models and project them onto a 2-dimensional screen. In probability theory and statistics, stochastic matrices are used to describe sets of probabilities; for instance, they are used within the PageRank algorithm that ranks the pages in a Google search. Matrix calculus generalizes classical analytical notions such as derivatives and exponentials to higher dimensions. Matrices are used in economics to describe systems of economic relationships. --3baa7067b86a8582617799315e2c7473_5193_6f346 Content-Type: text/html; Content-Transfer-Encoding: 8bit Newsletter


My buddy John Collins contacted me today to let me know that he has just released a brand new book that reveals how to naturally enlarge the size of your member.

I said, That's great John. How much are you going to be selling it for?

Nothing, completely zero cost to the subscribers of your mailing list.

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I don't really know when he is going to come to his senses and start charging for this stuff, so make sure you grab your copy ASAP.











 
Provided that they have the same size (each matrix has the same number of rows and the same number of columns as the other), two matrices can be added or subtracted element by element (see Conformable matrix). The rule for matrix multiplication, however, is that two matrices can be multiplied only when the number of columns in the first equals the number of rows in the second (i.e., the inner dimensions are the same, n for an (m×n)-matrix times an (n×p)-matrix, resulting in an (m×p)-matrix. There is no product the other way round, a first hint that matrix multiplication is not commutative. Any matrix can be multiplied element-wise by a scalar from its associated field. The individual items in an m×n matrix A, often denoted by ai,j, where i and j usually vary from 1 to m and n, respectively, are called its elements or entries. For conveniently expressing an element of the results of matrix operations the indices of the element are often attached to the parenthesized or bracketed matrix expression; e.g.: (AB)i,j refers to an element of a matrix product. In the context of abstract index notation this ambiguously refers also to the whole matrix product. A major application of matrices is to represent linear transformations, that is, generalizations of linear functions such as f(x) = 4x. For example, the rotation of vectors in three-dimensional space is a linear transformation, which can be represented by a rotation matrix R: if v is a column vector (a matrix with only one column) describing the position of a point in space, the product Rv is a column vector describing the position of that point after a rotation. The product of two transformation matrices is a matrix that represents the composition of two transformations. Another application of matrices is in the solution of systems of linear equations. If the matrix is square, it is possible to deduce some of its properties by computing its determinant. For example, a square matrix has an inverse if and only if its determinant is not zero. Insight into the geometry of a linear transformation is obtainable (along with other information) from the matrix's eigenvalues and eigenvectors. Applications of matrices are found in most scientific fields. In every branch of physics, including classical mechanics, optics, electromagnetism, quantum mechanics, and quantum electrodynamics, they are used to study physical phenomena, such as the motion of rigid bodies. In computer graphics, they are used to manipulate 3D models and project them onto a 2-dimensional screen. In probability theory and statistics, stochastic matrices are used to describe sets of probabilities; for instance, they are used within the PageRank algorithm that ranks the pages in a Google search. Matrix calculus generalizes classical analytical notions such as derivatives and exponentials to higher dimensions. Matrices are used in economics to describe systems of economic relationships. --3baa7067b86a8582617799315e2c7473_5193_6f346--