The Stanford Egocentric Thermal and RGBD Dataset provides egocentric RGB-D-Thermal (RGB-D-T) videos of humans performing daily real-word activities. The locations of the hands and of objects that interact with the hands are annotated. In this project, we used this dataset as an input to a framework for joint 6 DOF camera localization, 3D reconstruction, and semantic segmentation. All of our materials are open-sourced, including our code and our designs for the demonstration hardware platform used to acquire this dataset.
To collect our dataset, we designed a multi-modal data acquisition system combining an RGB-D camera (an Intel RealSense SR300) with a mobile thermal camera (a Flir One Android). We then used this setup to collect a large dataset of aligned multi-modal videos, and annotated semantically relevant information in these videos. We mounted both cameras on a GoPro chest harness and connected them through a single USB 3.0 cable to a lightweight laptop kept in the backpack of the data collector. We developed a GNU/Unix driver for the Flir One, since the camera was originally designed for Android mobile phones. We also time synchronized the cameras using the frame rate of the slower of the two cameras (the Flir One), resulting in a data acquisition rate of approximately 8.33 FPS. Our code for setting up this system is linked in the section below.
Our dataset includes approximately 250 videos of people performing various activities. These activities are divided into four high-level categories - kitchen, office, recreation, and household - with 44 different types of action sequences distributed across these four categories. We observed 14 different people collecting data over more than 20 different environments. All interactions in our dataset are very natural, since we did not give the data collectors any specific instructions other than asking them to wear the camera while performing the high-level activities. Also, since we did not tell the data collectors which actions to perform, the distribution of the dataset reflects the natural distribution of activities that the data collectors do routinely.
Number of Videos: 248
Number of Activity Types: 44
To see more examples or download the dataset, click here.


To move into the web dev industry. I'm currently aiming for front-end development. However i'm still keeping my options open as there are many areas of the development world I don't know yet. I'm also wanting to create indie games so I can use my coding knowledge and bach of animation together.
My biggest strength is my willingness to learn and succeed. I'm really wanting to put my all in this course. My biggest limitation is concentrations, if I have trouble understanding concepts I can find it hard to maintain focus.

Just being more confident with my ideas and solutions. Rather than keeping all my thoughts to myself.
Just to teach and guide us the best they possibly can, to help us achieve our goals of bootcamp.
To perform my best and give my all. Finish the course !!!
My goal is to graduate/finish EDA’s bootcamp knowing that I put everything into it and came out with as much knowledge and skills that I possibly could. Career wise i’m still no 100% which area but at the moment I think front-end development is the best path for me with my creative background. I’m wanting to land a solid job in the tech industry after finishing bootcamp. Long term I would like to get to a position where I can work part-time and still live comfortably, so I can work on both my art and web dev.
I’d say my people skills are already pretty decent with working in hospo for 2+ years. Other skills that I would like to see developed would be leadership skills, although I don’t like being the leader. I think it would be a good skill to have for moving up in a work environment.
Strengths: Tech-savy, Like learning, Like problem solving, Good people skills,
Limitations: Short attention span, Bad memory, Poor time management.
I will be managing this workload, by using apps to manage my time for example toggle. Will be tackling my memory problem with writing reflections, and physical notes during bootcamp. For attention span I will take small breaks example pomodoro technique, so I don’t overwhelm myself . I will manage myself to work productively and safely with other learners, facilitators and industry.community representatives. With to-do lists and good communication.
Ask peers or facilitators at bootcamp when they aren’t busy or in a way where i’m not taking away from their learning. Or slack where I can contact the cohort on foundations or my facilitator who can look at the message when they have time.
Knowledgeable people who can help or direct me in the right path to find the answer to my questions, people who are there to support my learning and my ability to learn. So that I can tackle the tasks by myself after learning from them.
Not that I can think of, just need to finish bootcamp days in time for me to catch the train home.


A growing voice for commonsense solutions on land management issues, Western Values Project took the opportunity provided by a website redesign to build a new dynamic brand.
Learn MorePartners: Smoot Tewes Group, Action Backed
Western Values Project is a leading voice in energy, conservation and responsible use of public lands in the Mountain West. However, their existing web presence and branding no longer reflected the organization they had become.
Western Values Project wanted to build a brand that reflected authenticity and fact-based solutions. They wanted a website that highlighted the brand, was mobile-friendly and was easy to use and update. Additionally, they needed a website that encouraged their audience to take action by contacting elected officials.
Our partners at Action Backed created a logo that reflects the colors of the Mountain West. A simple stylized icon works well with text, but can also stand alone to create a unique brand that translates well into social media and other properties.
Here's how Action Backed describes it:
For the logo, a stately serif balances atop a visual mark representing the land that brings together the high mountain peaks and the low valley floor. Standing on its own, the strong mark protects the land and its people. The color palette, led by a deep brown and ochre, is built from the hues of the landscape.
For pure ease of use and flexibility, WordPress was the obvious choice for this project. Custom content types allow Western Values Project staff to quickly add content like reports, charts and graphs. The site uses responsive design to support desktop, tablet or mobile browsing.
We integrated the engagement and advocacy tool Salsa seamlessly into the site as an Actions center. Visitors and supporters can now contact their federal, state and local officials directly to take action on key issues affecting the Mountain West.
We integrated the engagement and advocacy tool Salsa seamlessly into the site as an Actions center. Visitors and supporters can now contact their federal, state and local officials directly to take action on key issues affecting the Mountain West.
Combined with a robust email program, targeted actions are helping Western Values Project mobilize supporters quickly and stay ahead of the curve in a fast-moving political environment.
Ready to get to work? Let's start building a strategy to acheive your goals.
919.360.4800


Electronic signature consists in approving the content of an electronic document and fulfilling its commitment as a responsible person.
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Spike sum histogram of spike train data.
This class works with SpikeParams and SpikePlot to show the cumulative count of spikes from one cell from raster plots containing rows of spike trains.
For detailed examples, see
EXAMPLES:
This example generates some random “spikes” and displays them.
import numpy
from neuronpy.graphics import spikeplot
spikes = []
num_cells = 10
num_spikes_per_cell = 20
frequency = 20
# Make the spike data. Use a simple Poisson-like spike generator
# (just for illustrative purposes here. Better spike generators should
# be used in simulations).
for i in range(num_cells):
isi=numpy.random.poisson(frequency, num_spikes_per_cell)
spikes.append(numpy.cumsum(isi))
# spikes is now a list of lists where each cell has a list of spike
# times. Now, let's plot these spikes with the default parameters.
sp = spikeplot.SpikePlot(sum_ratio=0.3, savefig=True)
sp.plot_spikes(spikes)
AUTHORS:
Draws a histogram on the right side of a raster plot that is the cumulative sum of spikes in the window.
Set the cell spike-count histogram from the SpikeParams object passed in.
| Parameters: | spike_params – is a SpikeParams object. The spikes and line drawing parameters contained in it define what is drawn. |
|---|
Set the style of the histogram bars. :param style: May be one of the following: - 'bar'
Makes a solid bar from zero to the bin height (default).


Directions
Answer the following items.
Correct answers are marked with a check mark (
✔
), while incorrect answers are with an X (
✘
).
Multple answer question.
A. Correct choice 1
B. Correct choice 2
C. The sentence for a choice
D. The sentence for a choice
Multiple answers explanation for this item.
Multple answer question.
A. Correct choice 1
B. Correct choice 2
C. The sentence for a choice
D. Correct choice 3
Multiple answers explanation for this item.


Fernando Agüero, @fjaguero
App Trade Centre - 24/10/13 - Valencia, Spain
http://arewemobileyet.com
GONK + GECKO + GAIA
A browser inside a browser?
It marks the end of drivers, installation, all the other weird quirks of legacy game development Tim Sweeney, Epic Games
It marks the end of drivers, installation, all the other weird quirks of legacy game development
Tim Sweeney, Epic Games


This document contains reference information on the Python API
provided by ExpressionMatrix2.so
. All names documented below
are in the namespace of the Expression2
module
and become available after the module is imported.
This document includes the following sections:
CellGraphVertexInfo
ClusterGraphCreationParameters
ExpressionMatrix
ExpressionMatrixCreationParameters
NormalizationMethod
ServerParameters
Exception
containing an explanatory message.
Some functions, as noted below in the documentation for individual functions,
return True
if the operation succeeded, False
otherwise.
ExpressionMatrix
object.
However, concurrent calls to separate ExpressionMatrix
objects are permitted.
first
and second
.
The name of each pair class ends with Pair
and reflects the types of the two data members.
All pair classes have additional names that reflect
specific usages and improve code readability.
| Pair class name | Type of first | Type of second
|
|---|---|---|
IntIntPair
| Integer | Integer
|
UintUintPair
| Non-negative integer | Non-negative integer
|
StringStringPair
| String | String
|
UintFloatPair
| Non-negative integer | Float
|
len
can be called for a container and returns
the number of elements in it.
for x in v
can be used to iterate
over elements of a container.
append
, insert
, and del
can be used to add or remove
elements like for Python lists. However, inserting or removing elements not at the end of
the container is computationally expensive.
List
and reflects the type
of the data it contains. Most containers types have additional names that reflect
specific usages and improve code readability.
| Names of container type | Types of contained elements | ||||||||
|---|---|---|---|---|---|---|---|---|---|
IntList | Integer
| ||||||||
UintList
| Non-negative integer
| ||||||||
UintUintPairList
|
UintUintPair
| ||||||||
StringList | String
| ||||||||
StringStringPairList
|
StringStringPair
| ||||||||
StringStringPairListList
|
StringStringPairList
| ||||||||
FloatList
|
The ExpressionMatrix2
module defines the following constants:
invalidGeneId
: an integer
used to indicate a missing/invalid/undefined gene id.
invalidCellId
: an integer
used to indicate a missing/invalid/undefined cell id.
CellGraphVertexInfo
This class is used to give the Python code access to information about the vertices of a cell similarity graph. An object of this type contains information for a single vertex.
CellGraphVertexInfo()
Return value: CellGraphVertexInfo
.
This constructor creates an unitialized CellGraphVertexInfo
object.
CellGraphVertexInfo.cellId
Type: integer
This data member contains the cell id of the cell corresponding to the vertex.
CellGraphVertexInfo.x()
Return value: float
Returns the x coordinate of the vertex in the two-dimensional layout of
the graph the vertex belongs to.
CellGraphVertexInfo.y()
Return value: float
Returns the y coordinate of the vertex in the two-dimensional layout of
the graph the vertex belongs to.
ClusterGraphCreationParameters
This class describes parameters to be used when running the label propagation clustering algorithm to create a new cluster graph from an existing cell graph.
ClusterGraphCreationParameters()
Return value: ClusterGraphCreationParameters
.
The default constructor creates a ClusterGraphCreationParameters
initialized with the default values of the clustering parameters listed below.
ClusterGraphCreationParameters.stableIterationCount
Type: integer
Default value: 3
This data member specifies the number of stable iterations (iterations
without any changes in the cluster labels) after which the label propagation
algorithm stops.
ClusterGraphCreationParameters.maxIterationCount
Type: integer
Default value: 100
This data member specifies the maximum number of iterations that the label propagation
algorithm will run.
ClusterGraphCreationParameters.seed
Type: integer
Default value: 231
This data member specifies an integer used as a random seed to initialize the
label propagation clustering algorithm.
ClusterGraphCreationParameters.minClusterSize
Type: integer
Default value: 100
The minimum number of cells in a cluster. Smaller clusters are discarded.
ClusterGraphCreationParameters.maxConnectivity
Type: integer
Default value: 3
The maximum connectivity (k of the k-NN graph) for the cluster graph.
A vertex can actually have more edges than this value, if the extra edges
are required by the opposite vertex.
ClusterGraphCreationParameters.similarityThreshold
Type: integer
Default value: 0.5
The minimum similarity for an edge between two vertices to be created.
The edge is only created if the similarity between the average expression
vectors for the corresponding clusters exceeds this value.
ExpressionMatrix
This is the top level class in the ExpressionMatrix2
module.
Most high level functionality is provided by this class.
Binary data files for an instance of this class are stored in a single directory on disk.
They are accessed as memory mapped files.
ExpressionMatrix(directoryName, expressionMatrixCreationParameters)
directoryName : string
expressionMatrixCreationParameters: ExpressionMatrixCreationParameters
Return value: ExpressionMatrix
.
This constructor creates a new (empty) ExpressionMatrix
object in the specified directory.
The directory must not exists.
ExpressionMatrix(directoryName, allowReadOnly)
directoryName : string
allowReadOnly : Boolean
Return value: ExpressionMatrix
.
This constructor can be used to access an existing ExpressionMatrix
object in the specified directory.
The directory must exist.
If write access is not permitted on some of the data,
the operation fails if
allowReadOnly
is False
,
and falls back to read-only access
If allowReadOnly
is True
.
In this case, however, any write operations on data with read-only
access will generate a Segmentation Fault and cause immediate termination of
the calling Python script, without cleanup.
Therefore, this constructor should be called with
allowReadOnly = False
except in circumstances where limited functionality
with read-only access to the data is desired.
ExpressionMatrix.geneCount()
Return value: the number of genes currently defined (integer
).
ExpressionMatrix.cellCount()
Return value: the number of cells currently defined (integer
).
ExpressionMatrix.geneName(geneId)
geneId: integer
Return value: string
Returns the name of the gene with the given geneId
.
ExpressionMatrix.geneIdFromName(geneName)
geneName: string
Return value: integer
Returns the id of the gene with the given geneName
.
ExpressionMatrix.addGene(geneName)
geneName: string
Return value: integer
Adds a gene with the specified name.
Returns True
if the gene was added
and False
if the gene already existed.
ExpressionMatrix.addCell(jsonString)
jsonString: string
Return value: integer
Adds a cell to the system. The cell expression counts and meta data
are given in a JSON string. See
here for information on the expected
format of the JSON string. Returns the cell id of the cell that
was just added. Cell ids begin at zero and increment by one each time
a cell is added.
ExpressionMatrix.addCells(expressionCountsFileName, expressionCountsFileSeparators, metaDataFileName, metaDataFileSeparators)
expressionCountsFileName: string
expressionCountsFileSeparators: string
metaDataFileName: string
metaDataFileSeparators: string
Return value: None
Adds cells to the system, reading expression counts and cell meta data
from files. See
here for more information.
ExpressionMatrix.addCellsFromHdf5(fileName, cellNamePrefix, cellMetaData, totalExpressionCountThreshold)
fileName: string
cellNamePrefix: string
cellMetaData: StringStringPairList
totalExpressionCountThreshold: float
Return value: None
Adds cells to the system, reading expression counts from a file
in HDF5 format as created by the 10X Genomics pipeline. See
here for more information.
ExpressionMatrix.addCellsFromBioHub1(expressionCountsFileName, initialMetaDataCount, finalMetaDataCount, plateMetaDataFileName)
expressionCountsFileName: string
initialMetaDataCount: integer
finalMetaDataCount: integer
plateMetaDataFileName: string
Return value: None
Add to the system cells created by the BioHub pipeline (July 2017 version, for Illumina data).
See here for more information.
ExpressionMatrix.addCellsFromBioHub2(plateFileName, totalExpressionCountThreshold)
plateFileName: string
totalExpressionCountThreshold: integer
Return value: None
Add to the system cells created by the BioHub pipeline (September 2017 version, for 10X data).
See here for more information.
ExpressionMatrix.cellIdFromString(cellName)
cellName: string
Return value: integer
Returns the cell id corresponding to a given CellName
,
or invalidCellId
if no cell with the given CellName
exists.
Each cell has a set of meta data which consists of (name, value) pairs. Each cell is permitted to have a different set of meta data names from all other cells.
ExpressionMatrix.addCellMetaData(fileName)
fileName: string
Return value: None
Add cell meta data reading it from a csv file. Each line of the file contains cell meta data values
for one cell. Cell meta data names are in the first line. The first column of the file contain cell names.
All cell names must already be present.
ExpressionMatrix.getCellMetaDataValue(cellId, metaDataName)
cellId: integer
metaDataName: string
Return value: string
Returns the value of the specified meta data name for the given cell.
Returns an empty string if the cell does not have that meta data name.
The only meta data field that all cells are guaranteed to have is CellName
.
ExpressionMatrix.getCellMetaData(cellId)
cellId: integer
Return value: CellMetaData
Returns all meta data pairs (name, value) for a given cell.
ExpressionMatrix.getCellsMetaData(cellIdList)
cellIdList: CellIdList
Return value: CellMetaDataList
Returns all meta data pairs (name, value) for a set of cells
specified by cellIdList
. Each element in the returned
CellMetaDataList
corresponds to the cell id at the same position in cellIdList
.
ExpressionMatrix.createMetaDataFromClusterGraph(clusterGraphName, metaDataName)
See here for details.
ExpressionMatrix.getCellExpressionCount(cellId, geneId)
cellId: integer
geneId: integer
Return value: float
Returns the expression count for a given cell and gene.
The returned value can be zero.
This can be slow as it requires a binary search.
ExpressionMatrix.getCellExpressionCountFromGeneName(cellId, geneName)
cellId: integer
geneName: string
Return value: float
Returns the expression count for a given cell and gene.
The returned value can be zero.
This can be slow as it requires a binary search.
ExpressionMatrix.getCellExpressionCounts(cellId)
cellId: integer
Return value: ExpressionCountList
Returns the non-zero expression counts for a given cell.
The returned container contains pairs of gene ids and the
corresponding expression counts for the given cell.
ExpressionMatrix.getCellsExpressionCount(cellIds, geneId)
cellIds: CellIdList
geneId: integer
Return value: FloatList
Returns the expression counts for a set of cells and for a given gene.
Some or all of the returned values can be zero.
This can be slow as it requires a binary search.
ExpressionMatrix.getCellsExpressionCountFromGeneName(cellIds, geneName)
cellIds: CellIdList
geneName: string
Return value: FloatList
Returns the expression counts for a set of cells and for a given gene.
Some or all of the returned values can be zero.
This can be slow as it requires a binary search.
ExpressionMatrix.getCellsExpressionCounts(cellIds)
cellIds: CellIdList
Return value: ExpressionCountListList
Returns the non-zero expression counts for a given set of cells.
The returned container contains, for each cell, a list of pairs of gene ids and the
corresponding expression counts.
ExpressionMatrix.getCellsExpressionCountsForGenes(cellIds, geneIds)
cellIds: CellIdList
geneIds: GeneIdList
Return value: ExpressionCountListList
Returns the non-zero expression counts for given sets of cells and genes.
The returned container contains, for each cell, a list of pairs of gene ids and the
corresponding expression counts.
Functionality to create and manipulate gene sets is provided and described in this section.
A gene set is a subset of all the genes known to the ExpressionMatrix
object.
A gene set named AllGenes
, and consisting of all the genes
known to the known to the ExpressionMatrix
object, is always automatically
created and maintained (that is, updated if new genes are added).
ExpressionMatrix.createGeneSetUsingInformationContent(existingGeneSetName, cellSetName, normalizationMethod, geneInformationContentThreshold, newGeneSetName)
existingGeneSetName: string
cellSetName: string
normalizationMethod: NormalizationMethod
geneInformationContentThreshold: float
newGeneSetName: string
Return value: None
Creates a new gene set consisting of genes that pass an information content
test. The information content, in bits, of each gene in existingGeneSetName
is computed using cellSetName
and
the specified NormalizationMethod
.
The new gene set newGeneSetName
is created, consisting
of genes whose computed information content (in bits) exceeds
the specified geneInformationContentThreshold
.
The information content is roughly related to the variability of the
expression of that gene in the specified cell set.
Genes that are widely expressed have a low information content.
Genes that are very selectively expressed have a high information content.
A gene that is equally expressed in all cells has zero information content.
A gene that is expressed only in one cell has log2N
bits of information content, where N is the number of cells
in the cell set used to compute information content.
A geneInformationContentThreshold
of 2 bits is often effective
in filtering out widely expressed genes.
ExpressionMatrix.createGeneSetIntersection(inputGeneSetNames, outputGeneSetName)
inputGeneSetNames: string
outputGeneSetName: string
Return value: Boolean
Creates a new gene set as the intersection of two or more gene sets.
The names of the input gene sets specified as the first argument
must be separated by commas.
Returns False
if the operation failed because
one of the input gene sets does not exist
or the output gene set already exists, True
otherwise.
ExpressionMatrix.createGeneSetUnion(inputGeneSetNames, outputGeneSetName)
inputGeneSetNames: string
outputGeneSetName: string
Return value: Boolean
Creates a new gene set as the union of two or more gene sets.
The names of the input gene sets specified as the first argument
must be separated by commas.
Returns False
if the operation failed because
one of the input gene sets does not exist
or the output gene set already exists, True
otherwise.
ExpressionMatrix.createGeneSetDifference(inputGeneSetName0, inputGeneSetName1, outputGeneSetName)
inputGeneSetName0: string
inputGeneSetName1: string
outputGeneSetName: string
Return value: Boolean
Creates a new gene set as the difference between two gene sets.
The newly created gene set consists of all genes that are in
inputGeneSetName0
but not in inputGeneSetName1
.
Returns False
if the operation failed because
one of the input gene sets does not exist
or the output gene set already exists, True
otherwise.
Functionality to create and manipulate cell sets is provided and described in this section.
A cell set is a subset of all the cells known to the ExpressionMatrix
object.
A cell set named AllCells
, and consisting of all the cells
known to the known to the ExpressionMatrix
object, is always automatically
created and maintained (that is, updated if new cells are added).
ExpressionMatrix.getCellSetNames()
Return value: StringList
Return a list containing the names of all currently defined
cell sets.
ExpressionMatrix.createCellSetUsingMetaData(cellSetName, metaDataName, matchTarget, useRegularExpression)
cellSetName: string
metaDataName: string
matchTarget: string
useRegularExpression: Boolean
Return value: Boolean
(True
if the operation succeeded, False
otherwise).
Creates a new cell set cellSetName
consisting of all cells for which the
specified metaDataName
matches the given matchTarget
.
If useRegularExpression
is False
, this uses a simple string matching.
Otherwise, matchTarget
is treated as a regular expression to be matched.
As a simple application example, suppose all cells contain a meta data name
Tissue
that gives the type of tissue from which the cell was obtained.
Calling createCellSetUsingMetaData
with metaDataName='Tissue'
,
matchTarget='Brain'
, and useRegularExpression='False'
will create a new cell set consisting of
the cells for which the value of the Tissue
meta data field
is Brain
. Regular expressions can be used to
select values that satisfy a variety of criteria.
ExpressionMatrix.createCellSetUsingNumericMetaDataGreaterThan(cellSetName, metaDataName, lowerBound)
cellSetName: string
metaDataName: string
lowerBound: float
Return value: None
.
Creates a new cell set cellSetName
consisting of all cells for which the
specified metaDataName
is numeric and greater than lowerBound
.
ExpressionMatrix.createCellSetUsingNumericMetaDataLessThan(cellSetName, metaDataName, upperBound)
cellSetName: string
metaDataName: string
upperBound: float
Return value: None
.
Creates a new cell set cellSetName
consisting of all cells for which the
specified metaDataName
is numeric and less than upperBound
.
ExpressionMatrix.createCellSetUsingNumericMetaDataBetween(cellSetName, metaDataName, lowerBound, upperBound)
cellSetName: string
metaDataName: string
lowerBound: float
upperBound: float
Return value: None
.
Creates a new cell set cellSetName
consisting of all cells for which the
specified metaDataName
is numeric, greater than lowerBound
, and
less than upperBound
.
ExpressionMatrix.createCellSetIntersection(inputCellSetNames, outputCellSetName)
inputCellSetNames: string
outputCellSetName: string
Return value: Boolean
Creates a new cell set as the intersection of two or more cell sets.
The names of the input cell sets specified as the first argument
must be separated by commas.
Returns False
if the operation failed because
one of the input cell sets does not exist
or the output cell set already exists, True
otherwise.
ExpressionMatrix.createCellSetUnion(inputCellSetNames, outputCellSetName)
inputCellSetNames: string
outputCellSetName: string
Return value: Boolean
Creates a new cell set as the union of two or more cell sets.
The names of the input cell sets specified as the first argument
must be separated by commas.
Returns False
if the operation failed because
one of the input cell sets does not exist
or the output cell set already exists, True
otherwise.
ExpressionMatrix.createCellSetDifference(inputCellSetName0, inputCellSetName1, outputCellSetName)
inputCellSetName0: string
inputCellSetName1: string
outputCellSetName: string
Return value: Boolean
Creates a new cell set as the difference between two cell sets.
The newly created cell set consists of all cells that are in
inputCellSetName0
but not in inputCellSetName1
.
Returns False
if the operation failed because
one of the input cell sets does not exist
or the output cell set already exists, True
otherwise.
ExpressionMatrix.getCellSet(cellSetName)
cellSetName: string
Return value: CellIdList
Returns the cell ids of the cells in the cell set with the
specified name. If the cell set does not exists,
returns an empty container.
ExpressionMatrix.removeCellSet(cellSetName)
cellSetName: string
Return value: None
Removes the cell set with the
specified name. If the cell set does not exists,
raises an exception.
ExpressionMatrix.computeCellSimilarity(cellId0, cellId1)
cellId0: integer
cellId1: integer
Return value: float
Returns the similarity between the expression vectors of two cells,
specified by their cell ids. The similarity is computed using all
the genes in the system. It is computed as the
Pearson correlation coefficient
of the expression vectors of the two cells. The computed similarity is always between -1 and 1,
and it is rarely negative.
ExpressionMatrix.computeApproximateLshCellSimilarity()
Only intended to be used for testing.
See the source code in the ExpressionMatrix2/src
directory for more information.
ExpressionMatrix.writeLshSimilarityComparison()
Only intended to be used for testing.
See the source code in the ExpressionMatrix2/src
directory for more information.
ExpressionMatrix.writeLshSimilarityComparisonSlow()
Only intended to be used for testing.
See the source code in the ExpressionMatrix2/src
directory for more information.
ExpressionMatrix.findSimilarPairs0(geneSetName, cellSetName, similarPairsName, k, similarityThreshold)
geneSetName: string
cellSetName: string
similarPairsName: string
k: integer
similarityThreshold: float
Return value: None
Creates and stores a new object similarPairsName
containing pairs of similar cells from cellSetName
.
The computation is done by directly looping over all possible cell pairs
with both cells in cellSetName
and performing for each pair an exact computation of the
cell similarity, taking into account only genes in geneSetName
.
For each cell, only the best (most similar) k
or fewer similar cells are stored,
among those that exceed the specified similarityThreshold
.
This computational cost of this function grows with the square
of the number of cells in cellSetName
.

When the number of cells exceeds a few thousands, it is more practical
to perform an approximate computation using
findSimilarPairs3.
ExpressionMatrix.findSimilarPairs3(geneSetName, cellSetName, similarPairsName, k, similarityThreshold, lshCount, seed)
ExpressionMatrix.findSimilarPairs1(geneSetName, cellSetName, similarPairsName, k, similarityThreshold, lshCount, seed)
geneSetName: string
cellSetName: string
similarPairsName: string
k: integer
similarityThreshold: float
lshCount: integer
seed: integer
Return value: None
Like findSimilarPairs0, but uses Locality-Sensitive Hashing (LSH) with lshCount
LSH hashes to speed up the computation of the similar pairs.
Like findSimilarPairs0, this still loops over all possible cell pairs
with both cells in cellSetName
and therefore the computational cost still grows asymptotically with the square of the number of cells.
However the computation is orders of magnitudes faster.
The computation is approximate, and the error decreases as lshCount
increases.
For the suggested value lshCount=1024
, the standard deviation of
the pair similarity computed in this way is 0.05 or less.
Improved LSH functionality that avoids the loop over cell pairs will be provided
by findSimilarPairs2 but is not yet available.
More documentation for findSimilarPairs3
will become available at a later time.
The two functions findSimilarPairs1
and findSimilarPairs3
have identical functionality, but findSimilarPairs1
is
prototype code that will become obsolete, while findSimilarPairs3
is faster and uses better organized code.
Therefore, new scripts should use findSimilarPairs3
.
Old scripts that use findSimilarPairs1
should be converted to use findSimilarPairs3
instead.
ExpressionMatrix.findSimilarPairs2()
Development of this functionality is in progress.
It will provide LSH-based computation of similar cell pairs
without looping over all possible pairs of cells.
ExpressionMatrix.writeSimilarPairs()
Only intended to be used for testing.
See the source code in the ExpressionMatrix2/src
directory for more information.
ExpressionMatrix.analyzeSimilarPairs()
Only intended to be used for testing.
See the source code in the ExpressionMatrix2/src
directory for more information.
ExpressionMatrix.analyzeLsh()
Only intended to be used for testing.
See the source code in the ExpressionMatrix2/src
directory for more information.
A cell graph or cell similarity graph is an undirected graph in which each vertex represents a cell. An edge between two vertices is created if the corresponding cells have similarity that exceeds a chosen threshold. In areas of high connectivity, only the edges with the highest connectivity for each cell are kept.
ExpressionMatrix.getCellGraphNames()
Return value: StringList
Return a list containing the names of all currently defined
cell similarity graphs.
ExpressionMatrix.createCellGraph(cellGraphName, cellSetName, similarPairsName, similarityThreshold, k)
cellGraphName: string
cellSetName: string
similarPairsName: string
similarityThreshold: float
k: integer
Return value: None
Create a new cell similarity graph with name given as the first argument.
The remaining arguments specify the parameters to be used to construct the
graph. similarityThreshold
is the minimum cell similarity
required for an edge to be created. k
controls the maximum
connectivity of the graph.
ExpressionMatrix.computeCellGraphLayout(cellGraphName)
graphName: string
Return value: None
Computes the two-dimensional layout for the graph with the given name.
The graph must have been previously created with a call to
createCellGraph
.
This function must be called once before the first call to
getCellGraphVertices
for the graph.
ExpressionMatrix.getCellGraphVertices(cellGraphName)
cellGraphName: string
Return value: CellGraphVertexInfoList
Returns information about the vertices of the cell graph with the given name.
The graph must have been previously created with a call to
createCellGraph
and its two-dimensional layout must have been computed with a call to
computeCellGraphLayout
.
ExpressionMatrix.getCellGraphEdges(cellGraphName)
cellGraphName: string
Return value: CellIdPairList
Returns the cell ids corresponding to the two vertices
of each edge of the cell graph with the given name.
The graph must have been previously created with a call to
createCellGraph
.
A cluster graph is an undirected graph in which each vertex represents a cluster found in a cell graph. An edge between two vertices is created if the corresponding clusters have average expression vectors that are sufficiently similar. In areas of high connectivity, only the edges with the highest connectivity for each cluster are kept.
ExpressionMatrix.createClusterGraph(cellGraphName, clusterGraphCreationParameters, clusterGraphName)
cellGraphName: string
clusterGraphCreationParameters: ClusterGraphCreationParameters
clusterGraphName: string
Return value: None
Create a new cluster graph by running label propagation clustering on an existing cell graph.
ExpressionMatrix.getClusterGraphVertices(clusterGraphName)
clusterGraphName: string
Return value: IntList
Return a list of the cluster ids for the vertices of an existing cluster graph.
Each vertex of the cluster graph corresponds to a cluster.
ExpressionMatrix.getClusterGraphGenes(clusterGraphName)
clusterGraphName: string
Return value: GeneList
Return a list of the ids of the genes used to create a cluster graph.
ExpressionMatrix.getClusterCells(clusterGraphName, clusterId)
clusterGraphName: string
clusterId: integer
Return value: CellIdList
Return a list of the cell ids ids for the cells a cluster.
The cluster is specified using the name of the cluster graph it belongs to,
and its cluster id within that cluster graph.
ExpressionMatrix.getClusterAverageExpression(clusterGraphName, clusterId)
clusterGraphName: string
clusterId: integer
Return value: DoubleList
Return the average, L2-normalized, gene expression of a cluster.
The cluster is specified using the name of the cluster graph it belongs to,
and its cluster id within that cluster graph.
The values returned correspond one on one to the gene ids returned
by getClusterGraphGenes for the same cluster graph.
ExpressionMatrix.createMetaDataFromClusterGraph(clusterGraphName, metaDataName)
clusterGraphName: string
metaDataName: string
Return value: None
Stores the cluster ids in the specified cluster graph into a cell meta data field.
ExpressionMatrix.explore(serverParameters)
serverParameters: ServerParameters
Return value: None
Starts an http server that can be used, in conjunction with a Web browser,
to interact with the ExpressionMatrix
object.
ExpressionMatrix.testExpressionMatrixSubset(cellId0, cellId1)
cellId0: integer
cellId1: integer
Return value: None
Only intended to be used
to debug or test the ExpressionMatrix2
module.
ExpressionMatrixCreationParameters
This class is used to store creation parameters for a new ExpressionMatrix
object.
ExpressionMatrixCreationParameters()
Return value: ExpressionMatrixCreationParameters
.
This constructor creates a ExpressionMatrixCreationParameters
object
filled in with default values.
ExpressionMatrixCreationParameters.geneCapacity
Type: integer
.
Controls the size of the hash table used to hold genes.
For performance, the number of genes should not go above half of the value
specified here. Rehashing is currently not supported, so this
size cannot be changed after creation.
ExpressionMatrixCreationParameters.cellCapacity
Type: integer
.
Controls the size of the hash table used to hold cells.
For performance, the number of cells should not go above half of the value
specified here. Rehashing is currently not supported, so this
size cannot be changed after creation.
ExpressionMatrixCreationParameters.cellMetaDataNameCapacity
Type: integer
.
Controls the size of the hash table used to hold
cell meta data names.
For performance, the number of distinct cell meta data names
should not go above half of the value
specified here. Rehashing is currently not supported, so this
size cannot be changed after creation.
ExpressionMatrixCreationParameters.cellMetaDataValueCapacity
Type: integer
.
Controls the size of the hash table used to hold
cell meta data values.
For performance, the number of distinct cell meta data values
should not go above half of the value
specified here. Rehashing is currently not supported, so this
size cannot be changed after creation.
NormalizationMethod
This is an enumerated type that defines the normalization method to be used for cell expression vectors.
NormalizationMethod.none
This specifies that no normalization should be applied to
cell expression vectors. Cell expression vectors are returned or
used directly as specified when each cell was entered into the system.
NormalizationMethod.L1
This requests L1 normalization for
cell expression vectors. This means that each cell expression vector
is scaled in such a way that the sum of its element is 1
before being returned or used.
With this normalization, each element of the cell expression vector
represents the fraction in each gene of the total
expression count for the cell.
L1 normalization is sensitive to the gene set in use - that is,
removing or adding genes changes the values of
all entries in the cell expression vector.
NormalizationMethod.L2
This requests L2 normalization for
cell expression vectors. This means that each cell expression vector
is scaled in such a way that the sum of the squares of its element is 1
before being returned or used.
In other words, expression counts are interpreted as components
of a vector in Euclidean space, and the returned vector is a unit
vector in that space.
L2 normalization is sensitive to the gene set in use - that is,
removing or adding genes changes the values of
all entries in the cell expression vector.
ServerParameters
This class specifies parameters for an http server to be
started by calling ExpressionMatrix.explore
.
ServerParameters()
Return value: ServerParameters
.
This constructor creates a ServerParameters
object
filled in with default values.
ServerParameters.port
Type: integer
.
The port number on which the server will be listening for connections.
Its default value is 17100. On Linux, root access or other
security privileges are required to be able to listen on a port number less than 1024,
and many values velow 1024 are used for standard services.
If port 80 is specified, the user does not need to specify a port number to access the server,
becausde port 80 is the default port for the HTTP protocol.
The maximum allowed port number is 65535.
ServerParameters.docDirectory
Type: integer
.
The path to the doc directory containing the documentation
to be displayed by the server when the user clicks on the Help button.
This should point to a local copy of the ExpressionMatrix2/doc
in the GitHub repository. If no value is specified (the default),
the server will still run but the Help button will not be available.
This section lists functions that are only intended to be used
to debug or test the ExpressionMatrix2
module.
For more information about them, see the source code
in the ExpressionMatrix2/src
directory.
ExpressionMatrix2.testMemoryMappedVector()
ExpressionMatrix2.testMemoryMappedVectorOfLists()
ExpressionMatrix2.testMemoryMappedStringTable()


{% capture markdown %}
### Contributing Documentation
To be successful a community needs members with many different skillsets so we welcome contributions from anyone no matter your technical experience. To finf out more on how to get started contributin read our [contributing guide](guides/contributing/). If our process feels in any way intimidating, please let us know how we can improve it.
{% endcapture %}
{{ markdown | markdownify }}


Goodbye, Lover **1/2
rated R starring Patricia Arquette, Dermot Mulroney, Ellen DeGeneres, Mary-Louise Parker, Don Johnson written by Ron Peer, Joel Cohen, & Alec Sokolow directed by Roland Joffe
Before seeing Roland Joffe's black comedy GOODBYE, LOVER, I didn't think I would ever need to say that a film suffers because it doesn't rip off Tarantino enough. But, alas, the unexpected has happen. For the most part, GOODBYE, LOVER's plot is solid all the way through, and the twists are timely and unexpected. But the script does not make for good comedy, and none of the characters are interesting enough to care much about.
  Then, one night, a drunken Jake calls Ben, telling him that he knows all about the whole ordeal and that he is planning on throwing himself off of a 30-story building. Ben rushes to the building, and while he is trying to help Jake away from the ledge, Sandra comes from behind and pushes him off the building to his death.
Jake and Sandra then tell the police investigator, Sgt. Pompano(Ellen DeGeneres), that Ben fell off while trying to help Jake, and it turns out that what Jake and Sandra are trying to do is collect the money from Ben's will, since Jake is Ben's only living relative...or so they think.
But Ben decided to marry his ditzy co-worker Peggy(Mary-Louise Parker) 3 days before at a secret Las Vegas ceremony. But it's not long before Sandra finds out, and everyone seems to be against everyone else. Meanwhile, Sgt. Pompano is still trying to piece together the whole ordeal.
GOODBYE, LOVER was supposedly kept on Warner Bros. shelves for quite a while, because the company wasn't sure how to market it. The film doesn't feature any big name stars, and the subject matter is too dark and risky for most viewers.
Director Roland Joffe, who directed the great THE KILLING FIELDS and the not-so-great THE SCARLET LETTER has taken a different route this time around, with a film that is a lot of fun but doesn't provoke a lot of thought. Patricia Arquette is good as always as the vixen, and Ellen DeGenres is, well...Ellen DeGeneres. Walking out of GOODBYE, LOVER, I wasn't sure what to think of it, because the film doesn't leave you with much. The film is not as smart as FARGO or even last year's CLAY PIGEONS, because what it is lacking is a script with the least bit of comedic bite. The screenplay, by Ron Peer, Joel Cohen(don't worry, it's definitely not Joel Coen), and Alec Sokolow seems to concerned with the story and it's plot twists that it doesn't take the time to be funny or give us characters we can care about. If GOODBYE, LOVER had been another PULP FICTION rip-off, I probably would've enjoyed it more
a review by Akiva Gottlieb, The Teenage Movie Critic<EMAIL_ADDRESS>http://www.angelfire.com/mo/film watch me on TBS' "Dinner And A Movie" May 21, 8:05pm EST
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Club Championship 2023 Event 1
| Medbourne HR 9.5m |
12 March 23 |
|
9.5 |
miles |
| Name |
Position |
Road bike |
Actual Time |
Avg. mph |
| |
|
|
|
|
| Michael
Burke |
1 |
1 |
00:24:28 |
23.30 |
| Gary
Roberts |
2 |
|
00:24:29 |
23.28 |
| Matt
Plews |
3 |
|
00:25:51 |
22.05 |
| Richard
Krause |
4 |
2 |
00:26:44 |
21.32 |
| Jonathan
Durnin |
5 |
|
00:27:42 |
20.58 |
| Jamie
Kershaw |
6 |
|
00:27:48 |
20.50 |
| Julian
Middleton |
7 |
|
00:27:57 |
20.39 |
| Nik
Kershaw |
8 |
|
00:28:26 |
20.05 |
| Simon
Ward |
9 |
|
00:28:33 |
19.96 |
| Gary
Ashwell |
10 |
|
00:28:40 |
19.88 |
| Linda
Hubbard |
11 |
|
00:28:57 |
19.69 |
| Doug
Tincello |
12 |
3 |
00:29:42 |
19.19 |
| Adrian
Killworth |
13 |
|
00:29:43 |
19.18 |
| Mark
Chapman |
14 |
4 |
00:30:17 |
18.82 |
| Stuart
Dawkins |
15 |
5 |
00:30:30 |
18.69 |
| Austin
Smith |
16 |
6 |
00:30:43 |
18.56 |
| Steven
Coulam |
17 |
|
00:31:16 |
18.23 |
| Chris
Dainty |
18 |
7 |
00:31:50 |
17.91 |
| Jax
Roberts |
19 |
8 |
00:34:28 |
16.54 |
| Tom
Evans |
20 |
|
00:39:26 |
14.45 |
|
|
|
|
|


Constitution Plain Language Summary
This post about the eosDAC Constitution has been created to describe some aspects of the Constitution. This is not a legal document and does not replace the eosDAC Constitution itself (found at https://github.com/eosdac/constitution/blob/master/constitution.md). This post is written for a non-legal audience and only addresses some of the Constitutions’ paragraphs; it is incomplete and may be inaccurate. You cannot rely on this post to make legal or arbitration ar8guments. This post was written in English; if you are reading a translation, it may not reflect the intention of the original.
Section 1 – Interpretation
This section defines the terms used elsewhere in the document.
Section 2 – Core principles
The principles or Code of Conduct of eosDAC are written right into our Constitution: Excellence of Service Provision, Nurturing the Ecosystem, Openness and Transparency, Support of EOSIO Communities Worldwide, Fairness, Independence and Respect of the EOS Constitution. This means we must respect these principles in everything we do.
Section 3 – DAC Tokens and Membership
This section talks about owning EOSDAC tokens and being an eosDAC Member. To be a Member of the DAC you must hold tokens and also you have to register. If you cease to hold tokens you automatically cease to be a Member.
As a Member you have the following rights which cannot be taken from you as long as you are a Member: the right to vote for Custodians in proportion to the number of tokens you have; the right to your proportion of any distributions and the right to be a co-owner of the DAC in common with every other member of the DAC. These rights can only be changed by Extraordinary Resolution (90%+ of Custodians voting in favour, with minimum 8 Custodians voting).
As a Member, you also have certain obligations, which are especially: liability for the DAC, in common with all other members; consenting to be governed by the Constitution of the DAC. These rights can only be changed by Extraordinary Resolution (90%+ of Custodians voting in favour, with minimum 8 Custodians voting).
The Custodian Board can vote to unregister a member if and only if he/she contravenes the Constitution in a way that expressly produces grounds for unregistering. In such a case, the Custodian board still has to pass a Special Resolution (75%+ of Custodians voting in favour, with minimum 8 Custodians voting).
If the Custodian board makes a change to the Constitution which creates additional grounds not previously present for unregistering a member, that change would have to be passed by Extraordinary resolution (90%+ of Custodians voting in favour, with minimum 8 Custodians voting).
eosDAC can request identifying documentation from any Member if necessary to comply with laws or regulations. The documentation could be things like certified copies of passports or utility bills. Not complying with this request would be grounds for Membership to be revoked, though that would still require a Special Resolution.
The number of tokens in issue can only be changed by the Custodian board by Extraordinary Resolution (90%+ of Custodians voting in favour, with minimum 8 Custodians voting). The Custodian board cannot burn tokens belonging to Members.
EOSDAC tokens can be transferred. The final stage is registering the new owner so that he/she is a Member. The old owner will no longer be a Member.
You have the right to request your tokens are burnt, and thereby cease to be a Member of eosDAC.
There are further paragraphs in this section not summarised here.
Section 4 – Proposals and Voting of Members
This section talks about how Members can vote for Custodians and how Members can submit proposals to Custodians.
Members vote using the weight of the tokens they own. Members vote for Custodians. Votes representing 2% of all tokens are required for a vote by Members to be valid (quorum). This is except for the very first time Custodians are voted in, when the minimum is 15%. Further rules describing mechanisms for voting, staking and so on are written in a separate document called the Voting Directive.
Members can submit worker proposals to Custodians. The rules describing how they should submit the proposals and how the Custodian board should consider the proposals are written in a separate document called the Proposal Directive.
Section 5 – Custodian board
The twelve candidates receiving the most votes are elected as Custodians. Custodians must be Members of the DAC. Each Custodian has an equal vote; there is no Chair and no tie-breaking vote.
Custodians are to be in place for one week at a time but can be re-elected unlimited numbers of times.
When Custodians stand for election they must say how many EOS they want to be paid for that week (the maximum they can say is 250 EOS per week). Every Custodian serving together during a week term will receive the same pay, and that pay will be the median of the pay each of them requested when they stood for election.
If a Custodian resigns or vacates in the middle of a one-week term, the next highest candidate (normally, the 13th highest) will automatically become a Custodian for the rest of the week term.
The Custodians can decide by majority vote to require that all Custodians provide identifying information about themselves, such as name, address, email address and so on.
If more than 75% of Custodians vote in favour of removing a Custodian (Special Resolution), that Custodian can be immediately removed.
There is a separate document called the Nomination Directive that gives extra rules about how candidates can nominate themselves and how the elections happen.
Section 6 – Power of the Custodian board
The 12 elected Custodians (together called the Custodian board) run all aspects of the DAC.
The Custodian board (after agreeing through proper voting) can make decisions about the DAC’s funds, sign contracts or instruct them to be signed by a service company, administer the assets and liabilities of the DAC and have power and control over any other procedural, administrative or financial aspect of the DAC.
All actions of the Custodian board must come about through the Board having considered and properly approved a Proposal. The rules governing Proposals are set out in more detail in a document called the Proposal Directive.
You as a Member are deemed to have authorised and you are responsible for the consequences of every decision and action (including omissions or mistakes) of the Custodian board, so long as the Custodians followed proper voting and Constitutional procedure when they made the decision or took the action. In the same way, you as a Member are deemed to have authorised and you are responsible for the consequences of all financial decisions made by the Custodian board. It does not matter whether you as a Member actually agreed or disagreed with any action or decision or were even aware of it (although proper Constitutional rules must have been followed by the Custodians).
The Custodian board can appoint an agent by majority vote.
As already mentioned, if a Custodian resigns he or she is automatically replaced by the next highest candidate. In the meantime, the remaining Custodians can keep going if they have quorum. If in the unlikely event there are not enough candidates willing to fill the minimum number of Custodians required for a quorum (usually 8), then by majority vote the remaining Custodians can appoint further Custodians to reach quorum.
There are further technical paragraphs in this section not summarised here.
Section 7 – Proceedings of the Custodian board
This section sets out how Custodian board meetings should be called and run.
Meetings can happen by video, audio, messaging or other means. 24 hours’ notice should be given unless Custodians not attending give their consent.
The Constitution sets out that all meetings, communications and voting shall be conducting in the English language.
Voting procedure must follow the rules set out in a separate document called the Voting Directive.
Custodians can submit proposals to the Custodian board for consideration. They are still allowed to vote on their own proposals.
The Custodian board must publish on the blockchain the results of all proposals they considered. They must publish: whether the proposal was determined by Resolution, Special Resolution or Extraordinary Resolution; whether the proposal was accepted or rejected and the number of votes on each side; how each Custodian voted.
A minimum number of eight Custodians must vote in order for the vote to be valid (quorum). Custodians can count for this total if they are able to vote in the ways described in a separate document called the Voting Directive.
The Custodian board can decide to put an issue to the members to vote on in a Referendum. Custodians do not have to do this, and if they do, 75%+ of Custodians must vote in favour (minimum 8 Custodians voting).
There are further procedural paragraphs in this section that are not summarised here.
Section 8 – Conflict of interests
This short section says that if Custodians are deciding on an agreement or transaction with a person or organisation which one of the Custodians has a connection to, that Custodian should in good faith tell the other Custodians about their connection, before the vote. The Custodian does not have to absent his/herself from voting on that issue.
Section 9 – Indemnification
This section says that if any legal costs or other expenses arise against somebody because of their work as a Custodian, consultant, officer, affiliate or any other type of agent of the DAC, then eosDAC will fully pay those legal costs and expenses. This is so long as the person was acting honestly and in good faith in the best interests of the DAC at the time. Furthermore, eosDAC will pay any legal bills and expenses in advance if required by the lawyers, in such a scenario.
This section extends the same rules to all Members under certain circumstances.
The Custodian board may put in place insurance policies to indemnify any person.
The Custodian board may also decide to put in place an indemnification reserve.
Section 10 – Distribution of assets to members
The Custodian board must ensure that the DAC always has prudent reserve funds in place, at a bare minimum to cover the normal expenditure of the DAC for six months.
The Custodian board can decide to distribute some of the DAC’s assets to Members in proportion to the number of tokens held.
The Custodian board is not allowed to make (and would be acting against the Constitution if it made) a distribution that left the DAC without enough funds to meet its liabilities and expenses as they fall due.
The Custodian board can require that Members go through a process to say he/she wants to receive his/her distribution.
There are further technical paragraphs in this section that are not summarised here.
11 – Accounting
All decisions, transactions and accounting should be made viewable on the website and/or on the blockchain.
12 – Audit
The Custodian board can decide to appoint auditors by Special Resolution (75%+ of Custodians voting in favour, with minimum 8 Custodians voting).
13 – Notices
It is a valid form of giving notice to Members, to post on the website or disseminate through other electronic forms or mediums as long as a majority of Custodians approve this format.
14 – Resolution of Differences
If there is a contradiction or difference between the outcome of a Constitutionally-valid vote of Members and the outcome of a Constitutionally-valid Resolution of the Custodian board, then the vote of Members wins.
15 – Resolution of Disputes
If there is a dispute, the first stage is for Members and Custodians to act in good faith to resolve it (informal dispute resolution).
After 90 days from when all parties were notified of the dispute, if it has not been resolved it will be decided by binding arbitration.
Binding arbitration must happen according to rules of the London Court of International Arbitration (LCIA) which can only be modified by the agreement of all parties. One arbitrator is selected by the parties. The arbitrator’s decision is binding.
Class arbitrations are prohibited. There are further detailed rules which are not summarised here.
Section 16 – Voluntary winding up and dissolution
The Custodian board can vote to voluntarily wind up and dissolve eosDAC. This requires an Extraordinary resolution (90%+ approval by Custodians in favour, with minimum 8 Custodians voting). Net assets must be distributed to Members and Members will be released from any liability of Membership and any benefit of Membership.
Section 17 – Amendment of Constitution
The Custodian board can amend the Constitution by Special Resolution (75%+ of Custodians voting in favour, with minimum 8 Custodians voting). This is except for any amendment of the Constitution which would create new grounds for unregistering a Member.
Section 18 - Terms and Conditions
The Terms and Conditions are part of the Constitution and are binding on Members. The Terms and Conditions can be changed by Special Resolution (75%+ of Custodians voting in favour, with minimum 8 Custodians voting)
Section 19 - Applicable Law
The laws of Anguilla are the laws by which the Constitution and any contractual relationships created by it should be interpreted and governed.
Section 20 - Severability
By accepting a DAC token, whether at the original token distribution or through it being transferred to you by someone else, you have expressly agreed to be subject to the Constitution and the Terms and Conditions.
There are further concepts not summarised here.
Summary of thresholds required for Custodian Board votes
| Type of resolution | Threshold to pass | Quorum | Type of decision |
|---|---|---|---|
| Extraordinary resolution | Not less than 90% of all Custodians | Minimum number of Custodians who must be voting: 8 | Amending the Constitution in a way that allows members to be unregistered who would not have been able to be unregistered before the amendment (3.10) Amending the ‘Benefits of Members’(3.4) and the ‘Obligations of Member’ (3.5) Changing # of tokens in issue (3.2) Winding up and dissolving the DAC (16) |
| Special Resolution | Not less than 75% of all Custodians | Minimum number of Custodians who must be voting: 8 | All other Amendments to Constitution (17.1) Changing the Terms and Conditions (18.1) Changing the Nomination Directive (1.14) Changing Proposal Directive (1.18) Changing the Voting Directive (1.25) Removing a Custodian with or without cause (5.9) Unregistering a Member (only if grounds are expressly already given by Constitution) (3.10) Changing maximum Custodian pay (5.5) Putting a referendum to Members (7.13) Appointing Auditors (12.1) |
| Resolution | Majority of all Custodians | Minimum number of Custodians who must be voting: 8 | Everything not included above (7.7) including worker proposals The form of giving notice to Members (13) Appointing an agent (6.6) Appointing Custodian(s) to reach quorum if no replacement Custodians are available through the mechanism described in paragraph 5.11 (6.7) |


To explore the distribution of a quantitative data through a histogram, divide the quantitative data into ordered groups, otherwise known as bins, and count the number of data points that fall in each bin. For example, question 8 of the "Neighborhood welfare survey" asked the respondents about their annual household income. Thirty nine respondents responded to the question. The minimum recorded data is $30,000, and the maximum recorded data is $55,000. To create the histogram,
in-context


If you are looking to find a bike there are many things that you have to consider before you purchase this website will provide information for beginners who know nothing about bikes and people who are more experienced. Therefore the information that will be provided will be highlighting the different parts of a bike that can be viewed along with the sound of the bike.
The website will also include a small game that can be played to try and earn the highest score and A guide on what bikes are best for beginners and intermediate drivers including a description on the different types of bikes like adventure bikes.
Finally the website will include a page describing the best locations for certain types of bikes and A downloads page to get custom made wallpapers.


if(Optional.isPresent())
or if(Optional.isEmpty())
, that can be rewritten in the functional style,
as it is shorter and easier to read.
Example:
if (str.isPresent()) str.get().trim();
After the quick-fix is applied:
str.ifPresent(String::trim);
This inspection only reports if the language level of the project or module is 8 or higher.


Ryan Tucker
Currently working on:
Care Everywhere
at
Epic
Things I'm interested in learning more about:
Artificial Intelligence
Game Development/Design
Graphic Design
Healthcare Administration
Healthcare Interoperability
Mental Health
Mindfulness
Podcasting
Programming
Writing
Yoga


Create vertex: Simply by using the drag and drop icons of the nodes,
or pressing Shift +left-click
Create edge: Select the first vertex by clicking on it. Shift +left-click on another vertex (different than the selected one).
Delete a vertex/edge: dwhen vertex/edge is selected.
Freeze/unfrees a vertex: press f when the node is selected (a frozen node does not move in live mode)
Undo vertex deletion: Click on the Undo button. Only the last deleted vertex can be recovered.
Switch to automatic node positioning: Menu Layout -> Live
Topology Catalogue
Select Topology:
OSHI_base_7N
OSHI_12N
GARR_2014
Select Tunneling
Tunneling:
Select TestBed
TestBed:
Select Parameters for random topology generator
Total number of CORE nodes: Interconnection Probability:
Select the item to see the detail of the errors
Loading...
Topology 3D
It is not possible to automatically deploy the topology on this public demo of the Topology 3D tool. You should download and install on your server the Topology 3D tool, please refer to the section "Software Download" of the OSHI home page
http://netgroup.uniroma2.it/OSHI.
Error
Topology 3D Credits
Dreamer-Topology-Designer Simple Topology 3D, a customization of JS GRAPH EDITOR Based JS GRAPH EDITOR written by Radoslav Kirov.
This activity has been partially funded by EU in the context of DREAMER , which is one of the beneficiary projects of the GÉANT Open Call research initiative, see www.geant.net. The partners of DREAMER are: CNIT, CREATE-NET and Consortium GARR.


| Version 34 (modified by emanuel, 5 years ago) (diff) |
|---|
CUTE C++ Unit Testing Framework
CUTE is an easy to use C++ unit testing framework that leverages modern C++ libraries and features. CUTE is orthogonal, easily extendable and much simpler than other C++ unit testing approaches like CPPUnit. For example, CUTE does not require that you write a derived class for each C++ class you want to unit test.
The CUTE Eclipse plug-in integrates CUTE into the Eclipse CDT C/C++ integrated development environment. The plug-in provides all the important features that Java developers know from the JUnit plug-in, like wizards, test navigator, and a diff viewer for analyzing failed tests.
CUTE stands for C++ Unit Testing Easier. CUTE was developed by Professor Peter Sommerlad of the Institute for Software (IFS).
Download
You can download CUTE source code, or get the CUTE Eclipse Plug-in via Eclipse Update.
User Documentation
- Theory of Operation and Goals
- Installation and System Requirements
- Using the Cute Eclipse Plugin
- Writing C++ CUTE unit test suites
Developer Documentation
This documentation is for developers who are modifying CUTE and the Eclipse plug-in.
- CuteDeveloperInstallationGuide (Slightly dated)
- CreatingNewArchiveSite
- DiagnosticInformation
- WaysToCutCorner
- ReleaseChecklist
- HelloDll
Other Documentation
For further information about CUTE please visit the website of the Institute for Software (IFS) http://www.ifs.hsr.ch/Cute.5820.0.html or the CUTE documentation on Peter Sommerlads wiki http://wiki.hsr.ch/PeterSommerlad/wiki.cgi?CuTe
Documentation on the Trac Wiki itself is available here:
- TracGuide -- Built-in Documentation
- The Trac project -- Trac Open Source Project
- Trac FAQ -- Frequently Asked Questions
- TracSupport -- Trac Support
For a complete list of local wiki pages, see TitleIndex.
Contact
Contact us at http://www.ifs.hsr.ch


File Drop
Delete after:
10 minutes
1 hour
8 hours
1 day
1 week
2 weeks
1 month
Delete on first download


Deployment Update
Edit (pull request)Updating a deployment is the operation of modifying a running topology by adding/removing/modifying nodes. It’s a kind of hot update.
The deployment update feature of Cloudify is documented here.
Obviously, we are not talking about some kind of magic here: when you upgrade a deployment, Cloudify will compare both topologies and will try to discover the way to go from the original to the updated one (add nodes that need to be added, remove thoses that need to be removed …).
You can:
- add nodes
- add relationships
- changes properties (note that the node is not reinstalled when a property is updated, so the modification of a property will only impact added relationships that eventually refer to this updated property).
- rename nodes
- remove nodes
- remove relationships
You can’t:
- change the type of a node
- change a target of a hostedOn relationship
- add/remove a node group
- add a scalable compute (as a consequence of the preceding point, since scaling is managed using scaling groups)
- add/remove a custom workflow
Workflow & Lifecyle
An important thing to note concerning deployment upgrade is that the task sequence will differ from a standard workflow (when the target topology is deployed from scratch):
- Cloudify use it’s own sequence that differs from TOSCA.
- when a node becomes the source of a relationship, the TOSCA workflow can’t be respected.
In the following section, we will illustrate fews simple update scenarios and the resulting operation sequence call.
Add a node
A node nammed Source is hosted on a node named Host.
After the update, a node named Target is also hosted on Host.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Target | create | |
| Host | pre_configure_target | Target |
| Target | pre_configure_source | Host |
| Target | configure | |
| Host | post_configure_target | Target |
| Target | post_configure_source | Host |
| Target | start | |
| Host | add_source | Target |
| Target | add_target | Host |
Add a relationship
A node nammed Source and another named Target are hosted on a node named Host.
After update, a relationship link Source to Target.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Source | add_target | Target |
| Target | add_source | Source |
Add a component and a relationship (new node is target of the relationship)
A node nammed Source is hosted on a node named Host.
After the update, a node named Target is also hosted on Host and a relation is weaved between Source and Target.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Target | create | |
| Host | pre_configure_target | Target |
| Target | pre_configure_source | Host |
| Target | configure | |
| Host | post_configure_target | Target |
| Target | post_configure_source | Host |
| Target | start | |
| Host | add_source | Target |
| Target | add_target | Host |
| Source | add_target | Target |
| Target | add_source | Source |
Add a component and a relationship (new node is source of the relationship)
A node nammed Target is hosted on a node nammed Host.
After the update, a node named Source is also hosted on Host and a relation is weaved between Source and Target.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Source | create | |
| Host | pre_configure_target | Source |
| Source | pre_configure_source | Host |
| Source | pre_configure_source | target |
| Target | pre_configure_target | Source |
| source | configure | |
| Host | post_configure_target | Source |
| Source | post_configure_source | Host |
| Source | post_configure_source | Target |
| Target | post_configure_target | Source |
| Source | start | |
| Host | add_source | Source |
| Source | add_target | Host |
| Target | add_source | Source |
| Source | add_target | Target |
Remove a node
A node nammed Source is hosted on a node named Host.
After the update, the node named Source is removed.
Here is the sequence of operations that will be trigered during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Source | stop | |
| Host | remove_source | Source |
| Source | remove_target | Host |
| Source | delete |
Remove a relationship
A node nammed Source is hosted on a node named Host. Another node Target is also hosted on Host and linked to Source by a connectTo relationship.
After the update, the relationship between Source and Target is removed.
No operations are called, this seems to be a bug !
Remove a node that is source of a relationship
A node nammed Source is hosted on a node named Host. Another node Target is also hosted on Host and linked to Source by a connectTo relationship.
After the update, the node Source and the relationship are removed.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Source | stop | |
| Host | remove_source | Source |
| Source | remove_target | Host |
| Source | remove_target | Target |
| Target | remove_source | Source |
| Source | delete |
Remove a node that is target of a relationship
A node nammed Source is hosted on a node named Host. Another node Target is also hosted on Host and linked to Source by a connectTo relationship.
After the update, the node Target and the relationship are removed.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Source | remove_target | Target |
| Target | remove_source | Source |
| Target | stop | |
| Host | remove_source | Target |
| Target | remove_target | Host |
| Target | delete |
Renaming a node
Renaming a node is just like removing it and adding another (with the new name).
A node nammed Source is hosted on a node named Host.
After the update, the node Source is renamed to Renamed.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Renamed | create | |
| Host | pre_configure_target | Renamed |
| Renamed | pre_configure_source | Host |
| Renamed | configure | |
| Host | post_configure_target | Renamed |
| Renamed | post_configure_source | Host |
| Renamed | start | |
| Host | add_source | Renamed |
| Renamed | add_target | Host |
| Source | stop | |
| Host | remove_source | Source |
| Source | remove_target | Host |
| Source | delete |
Adding a node, removing another
A node nammed Source is hosted on a node named Host.
After the update, the node Source is removed, and a node Target is added.
Here is the sequence of operations that will be trigerred during deployment update:
| Node | Operation | Tiers |
|---|---|---|
| Target | create | |
| Host | pre_configure_target | Target |
| Target | pre_configure_source | Host |
| Target | configure | |
| Host | post_configure_target | Target |
| Target | post_configure_source | Host |
| Target | start | |
| Host | add_source | Target |
| Target | add_target | Host |
| Source | stop | |
| Host | remove_source | Source |
| Source | remove_target | Host |
| Source | delete |


A FRIEND OF THE DECEASED A film review by Steve Rhodes Copyright 1998 Steve Rhodes
RATING (0 TO ****): * 1/2
In the press information for his new film, A FRIEND OF THE DECEASED (PRIYATEL POKOINIKA), Ukrainian Director Vyacheslav Krishtofovich says the story is about all the "cultured people" living in what was once the Soviet Union. "In the absence of liberty, these people helped one another," he says. "Human warmth was very present. But freedom suddenly appeared and, with it, coldness and solitude." (He goes on to note that in Ukrainian the word for love and pity are sometimes considered synonyms.)
Thus we have a film of revisionist history in which the filmmaker seems to be saying that if, we just brought back Communist totalitarianism, the people would pull together and be happy again. But, without Big Brother to unite against, the people shuffle along without purpose, drinking and feeling sorry for themselves. Of course, the old Soviet Union under Stalin and his successors had a tremendous problem with alcoholism, and the citizens were not known for their excessive love of life.
Regardless of the background for the picture, the story by Andrei Kurkov has a promising plot but little more. The setup is that Anatoli, played with a single blank stare by Alexander Lazarev, has a beautiful blonde wife, Katia (Angelica Nevolina), who is cheating on him. During a drunken binge with his friend Dima (Yevgeni Pashin), he decides to put out a contract on Katia's boyfriend. The next morning, more despondent than ever, Anatoli decides to put out the hit on himself instead. Along comes a perky prostitute named Vika (Tatiana Krivitskaya), who serves up love and hope along with the sex, and Anatoli decides to change his mind.
If this all sounds like a fascinating black comedy, it isn't. The movie is devoid of humor, and the director stages scenes way too slowly, emphasizing the tragedy of the film's depressed protagonist. Vladimir Gronsky's melancholy music permeates many of the scenes to remind of us of the pervasive sorrow in the land.
"Friendship disappeared with our glorious Soviet past," Dima remarks to Anatoli. And all the compelling characters disappeared from this movie before the filming started. All that we are left with is the outlines of a story.
A FRIEND OF THE DECEASED runs 1:40. It is in Russian with English subtitles. The picture is rated R for some nudity, profanity and violence and would be fine for older teenagers.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Hello. I am Steve Casey, general manager of the international company Le-Trans, and I have a wonderful offer for you. We render services to companies that have international trade. These services consist of the reception of payments from the clients of the various companies when the client and the company are in the different countries. We save money for the companies by eliminating the expensive bank commission for international transactions. Only the small commissions for transactions between two banks inside one country are paid. To create representatives in each country is rather problematic and, in some cases, unprofitable. Therefore we invite people to the post of the Financial Courier, which will carry out the following functions: receive money in their bank accounts and further transfer it on to our bank account in other regions. This allows us to save the maximum on percentage basis. This method of transaction allows us to save the maximum on a percentage basis. It is necessary for you to have an account on which you will receive remittances. Your account should be activated for inter-bank transactions. If you do not have an account, it is necessary for you to open it. Today we invite you to work with us as a "Financial Courier". The functions of the financial courier is the reception of money clients of our company - and then transferring that money to our representatives. We pay high percent from each operation - 5%. To work with us you should meet the following requirements: Be over the age of 21 and with full capacity to carry out financial operations Capacity to make a bank withdrawals and transactions Be very efficient High accuracy when making calculations Have a bank account in a bank of USA (Bank of America, Wells Fargo). It is a fantastic opportunity to earn a great income! Start to work right now! To start with us you need only to fill out the labour agreement. Get more details here: http://le-trans.org/careers.php Thanks for attention. Yours faithfully, Steve Casey, General Manager of Le-Trans


Digital HD video, color, sound. 6'13". Tierpark Berlin (DE). 2019 - 2020
In Tempo - On Slowing Down, the manatee tank of the Tierpark in Berlin starts a conversation with a smartwatch which fell into it. They discuss about how to slow down time while fishes and manatees swim by. Documentary moving images explore an underwater world from the first person point of view of the smartwatch, the surface as well as the depths of the manatee tank, through the gaze of its camera. Digital voices quote ´The Chronic Argonauts´ by English writer H.G. Wells and exchange personal memories. Are we witnessing the last allucinations of a drawning Smartwatch?


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RatingActivity
- Class in
com.example.buber.Views.Activities
RatingActivity()
- Constructor for class com.example.buber.Views.Activities.
RatingActivity
RequestStatusActivity
- Class in
com.example.buber.Views.Activities
ReequestStatusActivity is used to show status of trip requests, as well as driver's info
RequestStatusActivity()
- Constructor for class com.example.buber.Views.Activities.
RequestStatusActivity
Rider
- Class in
com.example.buber.Model
Represents a User that is of type Rider.
Rider()
- Constructor for class com.example.buber.Model.
Rider
Empty constructor used for Firebase
Rider(String, Account)
- Constructor for class com.example.buber.Model.
Rider
Rider constructor
RIDER_CHANNEL_ID
- Static variable in class com.example.buber.
App
RiderUITests
- Class in
com.example.buber
Rider tests for testing login, ride creation, correct views, ride cancellation, and notification popups.
RiderUITests()
- Constructor for class com.example.buber.
RiderUITests
rule
- Variable in class com.example.buber.
AuthenticationUITest
rule
- Variable in class com.example.buber.
BrowseAndSearchTest
rule
- Variable in class com.example.buber.
ControllerTest
rule
- Variable in class com.example.buber.
CreateRiders
rule
- Variable in class com.example.buber.
CreateTrips
rule
- Variable in class com.example.buber.
DriversUITests
rule
- Variable in class com.example.buber.
EditAccountTest
rule
- Variable in class com.example.buber.
RiderUITests
runLogin()
- Method in class com.example.buber.
RiderUITests
runLoginDriver()
- Method in class com.example.buber.
DriversUITests
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5.1 #permalink pseudo-class
Adds widely used pseudo class selectors to a given element, uses the Sass @content directive for adaptability.
Passes your ruleset as a content block to the mixin as can be seen in the below example.
a {
color: $white;
background: $black;
@include pseudo-class {
color: $white;
background: $black;
}
}
Will output the following CSS.
a {
color: #fff;
background: #000;
}
a:hover,
a:focus,
b:active,
a.active,
a.selected {
color: #fff;
background: #000;
}
5.2 #permalink Media Query Breakpoints
Easy way to generate media queries.
.my-div {
width: 100%;
@include breakpoint(480px) {
width: 50%;
}
@include breakpoint(479px, max) {
width: 60%;
}
}
Will output the following CSS.
.my-div {
width: 100%;
}
@media screen and (min-width: 480px) {
.my-div {
width: 50%;
}
}
@media screen and (max-width: 479px) {
.my-div {
width: 60%;
}
}
5.3 #permalink Standard Clearfix
Clears an element with floated children.
.my-div {
@include clearfix;
}


Author: Betsy Fernández, March 6th, 2021
They are perfect antennas that serve to create Wi-Fi access points abroad, they cover large areas point to point but above all multipoint
Clients connect to these directional antennas of the Panel, Yagi, Grid etc type
The most recommended outdoor access points are Ubiquiti Bullet M2, Bullet M5, Rocket M2 etc.
forAn omnidirectional antenna is characterized by radiating power into space uniformly and in all directions, with the exception of the isotropic omnidirectional antenna, which acts in three dimensions. This antenna is a theoretical construction that is used as a reference to calculate the gain of an antenna. Another of its uses is to calculate the effective power that radiates in radio frequency systems, usually emitters and telecommunications receivers. In practice, omnidirectional antenna is understood to be those antennas that provide uniform radiation in only one reference plane. Conventionally, the plane of uniform radiation is the plane parallel to the surface of the Earth.
Alfa Network AOA-2458-59-TFL Dual-band 2.4GHz Omnidirectional Antenna: 5dBi + 5GHz: 9dBi, N Female Connector It is a new high quality dual band antenna with N-female connector, the gain is 9 dBi for 5 GHz and 5 dBi for 2.4 GHz. It has a resistant fiberglass housing, this great antenna is used in boats and recreational vehicles
| Frequency | VSWR | Gain | Polarization | Power Handling | Impedance | Connector | Model | 2.4/5GHz dual band | 2.0 | 9dBi(5 GHz),5dBi(2.4 Ghz) | Vertical | 50Watts | 50ohm | N-hembra | AOA-2458-59-TFL |
|---|
Very good antenna to connect to an Access Point and distribute the WiFi signal in all directions. You can also connect it to a WiFi Adapter to receive signal from outside.
| Frequency | VSWR | Gain | Polarization | Power Handling | Impedance | Aperture range | Connector | Model | 2.4GHz ~ 2.5GHz | ≦1.5 | 12dBi | Vertical | 50Ω | 360°/V:8° | 50ohm | N-hembra | AOA-2412 |
|---|
MAntena to connect to an Access Point and distribute the WiFi signal in all directions. Ideal for multipoint networks that require wide coverage. It has a female N connector. Designed for frequency 2.4GHz, gives outstanding results in IEEE 802.11b / G WiFi networks. Very easy to install
thanks to its low weight (about 320g), since it is made of fiberglass. Resistant to all types of climates. Includes clamps to anchor it to a mast of up to 5cm
| Frequency | VSWR | Gain | Polarization | Power Handling | Impedance | Aperture range | Connector | Model | 2.4-2.5Ghz | ≦1.5 | 12dBi | Vertical | 50Ω | 360°/V:8° | 50ohm | N-hembra | AOA-2408 |
|---|
Horizon omnidirectional antennas are among the most famous on the market. Meticulously constructed, small, perfect for medium-range applications using a single access point. In places where there are a large number of networks, special care must be taken when choosing the appropriate antenna, that is not high-gain so that the access point does not receive unwanted signals from other networks.
thanks to its low weight (about 320g), since it is made of fiberglass. Resistant to all types of climates. Includes clamps to anchor it to a mast of up to 5cm
Its modular construction ensures the best performance in the most adverse weather conditions.
| Frequency | VSWR | Gain | Polarization | Power Handling | Impedance | Aperture range | Connector | Model | 2400-2500MHz | 1.9 | 12dBi | Vertical | 50Ω | 360°/V:8° | 50ohm | N-hembra | AOA-2408 |
|---|
Airmax AMO-5G13 Omnidirectional, 5GHz, 13dB The Airmax Omnidirectional are professional antennas designed to work with the Ubiquiti Rocket M5 device. You only need an Airmax Omni antenna and a Rocket M5 to create a long range 360º base station. These antennas only work with Ubiquiti Networks Rocket M5 devices.
| Frequency | VSWR | Gain | Polarization | Power Handling | Impedance | Aperture range | Connector | Model | 5,45-5,85GHz | 1.5:1 | 13dBi | 25dB min | 50Ω | 360°/V:8° | 50ohm | N-hembra | AOA-2408 |
|---|
Assembly: Mast mounting kit, bracket to attach the Rocket Includes: -Airmax antenna Omni -Weather resistant RF cable -Mounting kit for attaching the Rocket -Universal pole mounting kit
IT Student at UTN, Costa Rica


--- type: "youtube" title: "How to Make FREE REAL MONEY with PROOF" yt-video-id: "imMQ1JO9YXM" description: "How to Make FREE REAL MONEY with PROOF with Whaff." social_media_msg: "..........." featimg: "http://images.dabannit.com/741ee9/make-free-real-money-with-whaff--542.jpg" article_videos: "" author: "" tags: "" category: "" origin_url: "https://www.youtube.com/watch?v=imMQ1JO9YXM" ---
How to Make FREE REAL MONEY with PROOF with Whaff


'I'm used to adjusting,' Robredo says on withholding of drug intel
'Kung hindi ibigay, fine. Eh ‘di— basta iyong sa akin, gagawin ko iyong lahat,' says the vice president
by Lian BuanSubscribe
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Options
You can use {name}
syntax for placeholders in the alert box message.
- {place}
- "one window" or "total", depending on where there were too many tabs. If both, uses "total".
- {maxPlace}
- maxTotal or maxWindow, depending on where there were too many tabs. If both, uses "total".
- {maxTotal}
- Max. number of total tabs
- {maxWindow}
- Max. number of tabs in one window
Change values to update them
Hello everyone, welcome to version 0.3.0! See the changelog at the github repo. Thanks for using Tab Limiter! :)