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Node

Involvement of lymph nodes is not obligatory in GD. Changes are more frequent in intrathoracic and intraabdominal nodes, and palpable lymph node enlargement is usually restricted to infants and small children. Nodes with a diameter greater than 2 cm are rare (Pick 1926). Since microscopic abnormalities have been observed [Pg.270]

Involved nodes are smooth and soft, and the cut surface in infants and children has a pale-pink to greyish-brown color. Darker coloration is observed in adults through deposition of pigments and hemorrhage nodes may then be brown or [Pg.271]

Iron-containing pigments are usually present in increased amounts, and located in reticular macrophages as well as in GC. Extracellular pigment may occur in more advanced cases. [Pg.271]

We will first label a node using a net alias. Select Place and then Net Alias from the menus  [Pg.37]

Off-Page Connector... UiororcMcol Btodi.. Hierarchical Port... [Pg.37]

Enter a name for the alias and then click the OK button. An outline for the alias will be attached to the mouse pointer  [Pg.37]

Editing a fgasic Schematic with Oread Qtphire [Pg.38]

Place the outline next to the horizontal wire at the input  [Pg.38]


There are two types of nodes in the decision tree decision nodes (rectangular) and chance nodes (circular). Decision nodes branch into a set of possible actions, while chance nodes branch into all possible results or situations. [Pg.179]

The probabilities of each branch from chance nodes are then estimated and noted on the diagram. [Pg.180]

For chance nodes it is not possible to foretell the outcome, so each result is considered with its corresponding probability. The value of a chance node is the statistical (weighted) average of all its results. [Pg.180]

For decision nodes, it is assumed that good management will lead us to decide on the action which will result in the highest NPV. Hence the value of the decision node is the optimum of the values of its actions. [Pg.180]

In the example, the first decision is whether or not to appraise. If one appraises, then there are three possible outcomes represented by the chance node the high, medium, or low STOMP. On the branches from the chance node, the estimated probability of these outcomes in noted (0.33 in each case). The sum of the probabilities on the branches... [Pg.180]

Artificial Neural Networks. An Artificial Neural Network (ANN) consists of a network of nodes (processing elements) connected via adjustable weights [Zurada, 1992]. The weights can be adjusted so that a network learns a mapping represented by a set of example input/output pairs. An ANN can in theory reproduce any continuous function 95 —>31 °, where n and m are numbers of input and output nodes. In NDT neural networks are usually used as classifiers... [Pg.98]

Table 1 Blind test results for "Lower wing skin" using network with 2 hidden nodes and training for 2000 iterations... Table 1 Blind test results for "Lower wing skin" using network with 2 hidden nodes and training for 2000 iterations...
For precise 3D-FEM simulations, a huge number of nodes is required (>30,000), which results in calculation times of several hours (sun spare 20) for one model. In order to decrease the number of nodes, we took advantage of the symmetry of the coils and calculated only a quarter or half of the test object. The modelled crack has a lenght of 15 mm, a height of 3 mm and is in a depth of 5 mm. The excitation frequency was 200 Hz. [Pg.259]

The calculation was carried out using the ANSYS F.E.M. code. The pressure vessel was meshed with a 4 nodes shell element. Fig. 18 shows a view of the results of calculation of the sum of principal stresses on the vessel surface represented on the undeformed shape. For the calculation it was assumed an internal pressure equal to 5 bar and the same mechanical characteristics for the test material. [Pg.413]

Figure Al.1.1. Wavefimctions for the four lowest states of the hamronie oseillator, ordered from the n = Q ground state (at the bottom) to tire u = 3 state (at the top). The vertieal displaeement of the plots is ehosen so that the loeation of the elassieal turning points are those that eoineide with the superimposed potential fimetion (dotted line). Note that the number of nodes in eaeh state eorresponds to the assoeiated quantum number. Figure Al.1.1. Wavefimctions for the four lowest states of the hamronie oseillator, ordered from the n = Q ground state (at the bottom) to tire u = 3 state (at the top). The vertieal displaeement of the plots is ehosen so that the loeation of the elassieal turning points are those that eoineide with the superimposed potential fimetion (dotted line). Note that the number of nodes in eaeh state eorresponds to the assoeiated quantum number.
In order to satisfy equation (A 1.1.5 6), the two fiinctions must have identical signs at some points in space and different signs elsewhere. It follows that at least one of them must have at least one node. However, this is incompatible with the nodeless property of ground-state eigenfiinctions. [Pg.20]

Figure Al.1.6. Ground-state wavefimction of the double-well oseillator, as obtained in a variational ealeulation using four basis fiinotions eentred at ti = VTdand four eentred at Figure Al.1.6. Ground-state wavefimction of the double-well oseillator, as obtained in a variational ealeulation using four basis fiinotions eentred at ti = VTdand four eentred at </ = — %/Io.Note the absenee of a node at the origin.
Figure Al.3.13. All-electron and pseudopotential wavefiinction for the 3s state in silicon. The all-electron 3s state has nodes which arise because of an orthogonality requirement to tlie Is and 2s core states. Figure Al.3.13. All-electron and pseudopotential wavefiinction for the 3s state in silicon. The all-electron 3s state has nodes which arise because of an orthogonality requirement to tlie Is and 2s core states.
Figure Al.4.4. The definition of the Euler angles (0, ( ), x) that relate the orientation of the molecule fixed (x, y, z) axes to the (X, Y, Z) axes. The origin of both axis systems is at the nuclear centre of mass O, and the node line ON is directed so that a right handed screw is driven along ON in its positive direction by twisting it from Z to z through 9 where 0 < 9 < n. ( ) and x have the ranges 0 to In. x is measured from the node line. Figure Al.4.4. The definition of the Euler angles (0, ( ), x) that relate the orientation of the molecule fixed (x, y, z) axes to the (X, Y, Z) axes. The origin of both axis systems is at the nuclear centre of mass O, and the node line ON is directed so that a right handed screw is driven along ON in its positive direction by twisting it from Z to z through 9 where 0 < 9 < n. ( ) and x have the ranges 0 to In. x is measured from the node line.
Targets and spirals have been observed in the CIMA/CDIMA system [13] and also in dilute flames (i.e. flames close to their lean flammability limits) in situations of enlianced heat loss [33]. In such systems, substantial fiiel is left unbumt. Spiral waves have also been implicated in the onset of cardiac arrhytlnnia [32] the nomial contractive events occurring across the atria in the mannnalian heart are, in some sense, equivalent to a wave pulse initiated from the sino-atrial node, which acts as a pacemaker. If this pulse becomes fragmented, perhaps by passing over a region of heart muscle tissue of lower excitability, then spiral structures (in 3D, these are scroll waves) or re-entrant waves may develop. These have the incorrect... [Pg.1107]

The amplitude and therefore the intensity, of the scattered radiation is detennined by extending the Fourier transfomi of equation (B 1.8.11 over the entire crystal and Bragg s law expresses die fact that this transfomi has values significantly different from zero only at the nodes of the reciprocal lattice. The amplitude varies, however, from node to node, depending on the transfomi of the contents of the unit cell. This leads to an expression for the structure amplitude, denoted by F(hld), of the fomi... [Pg.1366]

For optical transmission, tire parameters of greatest importance are attenuation (i.e. loss) and material dispersion. In effect tliey define tire limits of tire optical communication system. Loss, due to absorjDtion and scattering, limits tire lengtlis between tire transmission nodes. In transmission quality fibre, tire loss is in units of decibels per kilometre. [Pg.2871]

This is an example of a Mobius reaction system—a node along the reaction coordinate is introduced by the placement of a phase inverting orbital. As in the H - - H2 system, a single spin-pair exchange takes place. Thus, the reaction is phase preserving. Mobius reaction systems are quite common when p orbitals (or hybrid orbitals containing p orbitals) participate in the reaction, as further discussed in Section ni.B.2. [Pg.346]

Electi ocyclic reactions are examples of cases where ic-electiDn bonds transform to sigma ones [32,49,55]. A prototype is the cyclization of butadiene to cyclobutene (Fig. 8, lower panel). In this four electron system, phase inversion occurs if no new nodes are fomred along the reaction coordinate. Therefore, when the ring closure is disrotatory, the system is Hiickel type, and the reaction a phase-inverting one. If, however, the motion is conrotatory, a new node is formed along the reaction coordinate just as in the HCl + H system. The reaction is now Mdbius type, and phase preserving. This result, which is in line with the Woodward-Hoffmann rules and with Zimmerman s Mdbius-Huckel model [20], was obtained without consideration of nuclear symmetry. This conclusion was previously reached by Goddard [22,39]. [Pg.347]

At present, the data base used for the fit was not specially selected to avoid homologous proteins. Thus, a further improvement can be expected from using data for one of the specially prepared lists of PDB files (cf. Hobohm et al. [9]). We also expect further improvements from replacing the polynomial fits in the potential estimation procedure by piecewise cubic fits though at the moment it is not clear how to select the number of nodes needed to get a good but not overfitting approximation to the density. Finally, we are considering... [Pg.221]

Parallel molecular dynamics codes are distinguished by their methods of dividing the force evaluation workload among the processors (or nodes). The force evaluation is naturally divided into bonded terms, approximating the effects of covalent bonds and involving up to four nearby atoms, and pairwise nonbonded terms, which account for the electrostatic, dispersive, and electronic repulsion interactions between atoms that are not covalently bonded. The nonbonded forces involve interactions between all pairs of particles in the system and hence require time proportional to the square of the number of atoms. Even when neglected outside of a cutoff, nonbonded force evaluations represent the vast majority of work involved in a molecular dynamics simulation. [Pg.474]

Fig. 4. In NAMD 2 forces are calculated not by force objects owned by individual patches, but rather by independent compute objects which depend on one or more patches for atomic coordinates. As suggested by shading in this illustration, a compute object need not reside on the same node as the patches upon which it depends. Fig. 4. In NAMD 2 forces are calculated not by force objects owned by individual patches, but rather by independent compute objects which depend on one or more patches for atomic coordinates. As suggested by shading in this illustration, a compute object need not reside on the same node as the patches upon which it depends.

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A saddle-node

AND-nodes

AST node

AV node

AV node ablation

Algebra node

Alkoxo-Bridged Binuclear Copper(II) Complexes as Nodes

Angular nodes

Anti-node

Antibonding molecular orbitals nodes

Atomic orbitals nodes

Atomic orbitals radial nodes

Atrial fibrillation with sinus node dysfunction

Atrioventricular Node (AV)

Atrioventricular node

Atrioventricular node ablation

Autoimmunity popliteal lymph node assay

Bacterial infection, lymph nodes

Basis functions node-based

Bias node

Bifurcation mechanisms saddle-node bifurcations

Bifurcation saddle-node

Bouchard’s nodes

Boundary conditions nodes

Breast cancer lymph node involvement

Breast cancers lymph node status

Breast lymph node assay

CXCR3 receptor lymph nodes

Calling nodes

Cancer lymph node metastasis

Catastrophe saddle node bifurcation

Cervical lymph node metastasis

Cervical lymph node staging

Chance node

Cladograms nodes

Colon cancer lymph nodes

Complete node

Connected nodes

Cotyledonary nodes

Daughter nodes

Decision nodes

Degenerate node

Degenerate saddle-node

Dendritic cells in lymph nodes

Device technology node

Diffusion Monte Carlo fixed-node approximation

Dragging nodes

Draining lymph nodes

Dynamic node allocation

Entanglements nodes

Environment node

Expression for Finding Centroid of Final Product Node in Synthesis Tree

Finite difference formulation nodes

Fixed node approximation

Fixed node constraint

Fixed-node DQMC

Fixed-node DQMC method

Fixed-node calculations

Fixed-node diffusion Monte Carlo

Fixed-node methods

Fixed-node quantum Monte Carlo

Fixed-node quantum Monte Carlo method

Fixed-node structure

Flexible nodes

Floating nodes

Focus nodes

Framework node

Frog node

Fungal infection lymph nodes

Gap nodes

Generic nodes

Giant Lymph Node Hyperplasia (Castleman Disease)

Giant lymph node hyperplasia

Global saddle-node bifurcation

Goal nodes

Graph nodes

Green function fixed-node approximation

Grid, faces centered between nodes

Hanging node

HazOp study nodes

Heart atrioventricular node

Heart sinoatrial node

Heberden’s nodes

Hensen’s node

Henson s node

Heterobinuclear Complexes as Node

Hidden nodes

Hilar lymph nodes

Hilar nodes

Human immunodeficiency virus lymph nodes

Hydrogen-atom wave functions nodes

IDEF node tree

Immune system lymph nodes

Inguinal lymph nodes

Inorganic node

Internal nodes

Interpenetrating 3D Nets Each Containing Two Types of Nodes with Different Connectivities

Intramolecular energy transfer polyad folding and saddle-node

Isolated node

Junction node

Knots 3-noded

Labeled node

Lattice nodes number

Leaf nodes

Leakage node

Line node

Line of nodes

Link-node

Liquid networks containing nodes with significant volume allowing for temperature changes

Local Lymph Node Assay (LLNA)

Local lymph node

Local lymph node assay

Local lymph node assays development

Low-boiling node

Lymph node accumulation

Lymph node assay

Lymph node burden

Lymph node cells

Lymph node delivery

Lymph node enlargement

Lymph node germinal centers

Lymph node involvement

Lymph node metastasis

Lymph nodes

Lymph nodes anatomic locations

Lymph nodes egress from

Lymph nodes immune response

Lymph nodes micrometastases

Lymph nodes micrometastases detected

Lymph nodes mouse model

Lymph nodes sentinel

Lymph nodes, dendritic cells

Lymph nodes, spectra

Lymph nodes, spectroscopy

Lymphatic system nodes

Lymphocytes nodes

Mandibular lymph node

Mathematical between nodes

Mediastinal lymph nodes

Melanoma sentinel lymph node biopsy

Merging of nodes

Mesenteric lymph node

Mesenteric lymph node cells

Mesenteric nodes

Metastatic lymph node

Micrometastases in lymph nodes

Model nodes, mathematical

Molecular orbitals node feature

Molecular orbitals nodes

Morphology nodes

Mouse local lymph node

Mouse local lymph node assay

Multiport node

Murine Local Lymph Node Assay

NODE command

Nerve cell nodes

Nets with both tetrahedral and square planar nodes

Nets with three- and six-connected nodes

Network nodes

Node 13 orbit

Node Architecture

Node Placement

Node balance

Node coloring

Node creation

Node dividing

Node equations

Node equilibria

Node equilibrium state

Node evaluation

Node fixed point

Node of electron density

Node of graph

Node percolation

Node region

Node replacement strategy

Node specification

Node stability

Node structure

Node synthesis

Node tree

Node value

Node voltage analysis

Node, Ranvier

Node, branch point

Node, constrained

Node, defined

Node, radial

Node-building parameter

Node-centered

Node-labeled tree structure

Node-link-blob model

Node-negative breast cancer

Node-positive breast cancer

Node-positive disease

Node-search problem

Nodes 3-connecting metallic

Nodes adjacent

Nodes boundary

Nodes function

Nodes inner

Nodes interior

Nodes irregular

Nodes labels

Nodes near-boundary

Nodes of Ranvier

Nodes of the Moon

Nodes planes

Nodes pseudopotential

Nodes spherical

Nodes strictly inner

Nodes with different connectivities

Nodes, definition

Nodes, estimated ages

Nodes, molecular orbital

Nodes, number

Nodes, of networks

Nonreaction node

Normal lymph node cells

Numerical methods nodes

OR-nodes

Oligonuclear Complexes as Nodes

Outer nodes

P Orbital, nodes shape

Pericyclic reactions nodes

Peripheral blood lymphocytes lymph nodes

Point nodes

Point stable node

Point unstable node

Popliteal lymph node

Popliteal lymph node assay

Power continuous node

Processing node

Property node

Pulmonary lymph nodes

Quantum Monte Carlo method fixed-node approximation

Quantum mechanics nodes

Radial node Volume

Reciprocal node elongation

Reduced graph node

Reference node

Regenerative nodes

Released-Node Calculations

Released-node method

Resistive node

Root nodes

SA node

Saddle-Node Cusp Points

Saddle-node

Saddle-node bifurcation on a limit

Saddle-node bifurcation on a limit cycle

Saddle-node bifurcations systems

Saddle-node connection

Saddle-node equilibrium state

Saddle-node fixed point

Saddle-node periodic orbit

Saddle-node point

Secondary lymphoid tissue lymph nodes

Selective Control of Sinoatrial and AV Nodes

Sensor node

Sentinel lymph node biopsy

Sentinel lymph node metastasis

Sentinel node biopsy

Simple saddle-node

Single-species node

Sino-atrial node

Sinoatrial Node (SAN)

Sinoatrial node

Sinoatrial node, calcium channel blocker

Sinoatrial node, conduction

Sinoatrial node, heart rate

Sinus node

Sinus node arrest

Sinus node arrhythmias

Sinus node artery

Sinus node dysfunction

Sinus node dysfunction cardiac pacing

Sinus node dysfunction pacing mode

Sinus node dysfunction symptoms

Sinus node dysfunction treatment

Sinus node physiology

Sinus node recovery time

Source node

South Node

Specifying Node Values

Spectral histopathology of lymph nodes

Stable node

Stable node equilibrium state

Stable node fixed point

Stationary points stable node

Stationary points unstable node

Stellar nodes

Storage node

Study nodes

Supply chain nodes

Switching node

Switching node noise

T Cells in the Lymph Node

Tagged node

Technology node

Terminal nodes

The Concept of Nodes

The Ghost-Node Process

The Local Lymph Node Assay

The Node-and-Spacer Paradigm

The lymph nodes

Threshold neural network node

Tier 1 nodes

Time independent nodes

Topological nodes

Tumor lymph node metastases staging

Tumor lymph node metastases staging system

Tumor node metastasis staging

Tumor node metastasis staging system

Uninodal nets with square planar nodes

Unstable node

Unstable node fixed point

Update the Winning Node

Voltage nodes

Watson nodes

Wave nodes

Wavefunctions nodes

Well-stirred system has unstable node

Winning node

Zero node

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