Premium SSD is supported only on specific size-series VMs
{{GOINPUTNAME[os_disk_size].$error.server}}
This shell script will be executed once after startup of the virtual machine. Read more about
running commands on virtual machines.Prepend the script with set -e to abort script execution on error.
This powershell script will be executed once after startup of the virtual machine. Read more about
running commands on virtual machines.Prepend the script with $ErrorActionPreference = "Stop" to abort script execution on error.
{{GOINPUTNAME[idle_timeout].$error.server}}
Azure instance will be kept idle for this period before termination, after job completion.
This value overrides idle timeout setting in Plugin Settings.
{{GOINPUTNAME[subnet_name].$error.server}}
Subnet name from the configured subnets in plugin settings to provision the VM in. If not specified a subnet will be selected from configured values in plugin settings.


--- layout: null permalink: /example-post-complex/ title: description: sitemap: priority: 0.1 exclude: true pageVarTest: "test {{asd}}" ---


Multiple selections as a central way of interacting
Powerful selection manipulation primitives
Link hints
Tab search
Contextual commands
Contextual help
Simple interaction with external programs
Limited scope.
Krabby is not Vim, nor Kakoune.
Krabby is trying to be a navigation tool and some concepts from code editors don’t translate well.
For example, there is no concept of mode in Krabby, but a system of contexts.
Composability.
Composability is better than extensibility.
Krabby tries hard to provide features that interact well with each other.
For example, f and y are two building blocks to focus a link and yank its URL.
Depending on the context, y will yank the page or a link URL.
Modular (think Emacs).
Krabby is divided into multiple small projects.
At its core Krabby just holds the configuration and grabs its functionalities from other projects.
In Pokémon Red and Blue
and Pokémon FireRed and LeafGreen,
the player receives one of the Kanto starters as his first Pokémon from Professor Oak.
The player’s rival receives the starter Pokémon whose type is stronger against the player’s chosen starter.


ARGUMENT.—Beatrice descends from Heaven, and rebukes the Poet.
SOON as that polar light, fair ornament
Of the first Heaven, which hath never known
Setting nor rising, nor the shadowy veil
Of other cloud than sin, to duty there
Each one convoying, as that lower doth
The steersman to his port, stood firmly fix’d;
Forthwith the saintly tribe, who in the van
Between the Gryphon and its radiance came,
Did turn them to the car, as to their rest:
And one, as if commission’d from above,
In holy chant thrice shouted forth aloud;
“Come, spouse! from Libanus:” and all the rest
Took up the song.—At the last audit, so
The blest shall rise, from forth his cavern each
Uplifting lightly his new-vested flesh;
As, on the sacred litter, at the voice
Authoritative of that elder, sprang
A hundred ministers and messengers
Of life eternal. “Blessed thou, who comest!”
And, “Oh!” they cried, “from full hands scatter ye
Unwithering lilies”: and, so saying, cast
Flowers overhead and round them on all sides.
I have beheld, ere now, at break of day,
The eastern clime all roseate; and the sky
Opposed, one deep and beautiful serene;
And the sun’s face so shaded, and with mists
Attemper’d, at his rising, that the eye
Long while endured the sight: thus, in a cloud
Of flowers, that from those hands angelic rose,
And down within and outside of the car
Fell showering, in white veil with olive wreathed,
A virgin in my view appear’d, beneath
Green mantle, robed in hue of living flame:
And o’er my spirit, that so long a time
Had from her presence felt no shuddering dread,
Albeit mine eyes discern’d her not, there moved
A hidden virtue from her, at whose touch
The power of ancient love was strong within me.
No sooner on my vision streaming, smote
The heavenly influence, which, years past, and e’en
In childhood, thrill’d me, than towards Virgil I
Turn’d me to leftward; panting, like a babe,
That flees for refuge to his mother’s breast,
If aught have terrified or work’d him woe:
And would have cried, “There is no dram of blood,
That doth not quiver in me. The old flame
Throws out clear tokens of reviving fire.”
But Virgil had bereaved us of himself;
Virgil, my best-loved father, Virgil, he
To whom I gave me up for safety: nor
All, our prime mother lost, avail’d to save
My undew’d cheeks from blur of soiling tears.
“Dante! weep not that Virgil leaves thee; nay,
Weep thou not yet: behoves thee feel the edge
Of other sword; and thou shalt weep for that.”
As to the prow or stern, some admiral
Paces the deck, inspiriting his crew,
When ’mid the sail-yards all hands ply aloof;
Thus, on the left side of the car, I saw
(Turning me at the sound of mine own name,
Which here I am compell’d to register)
The virgin station’d, who before appear’d
Veil’d in that festive shower angelical.
Towards me, across the stream, she bent her eyes;
Though from her brow the veil descending, bound
With foliage of Minerva, suffer’d not
That I beheld her clearly: then with act
Full royal, still insulting o’er her thrall,
Added, as one who, speaking, keepeth back
The bitterest saying, to conclude the speech:
“Observe me well. I am, in sooth, I am
Beatrice. What! and hast thou deign’d at last
Approach the mountain? Knewest not, O man!
Thy happiness is here?” Down fell mine eyes
On the clear fount; but there, myself espying,
Recoil’d, and sought the greensward; such a weight
Of shame was on my forehead. With a mien
Of that stern majesty, which doth surround
A mother’s presence to her awe-struck child,
She look’d; a flavor of such bitterness
Was mingled in her pity. There her words
Brake off; and suddenly the angels sang,
“In thee, O gracious Lord! my hope hath been”:
But went no further than, “Thou, Lord! hast set
My feet in ample room” As snow, that lies,
Amidst the living rafters on the back
Of Italy, congeal’d, when drifted high
And closely piled by rough Sclavonian blasts;
Breathe but the land whereon no shadow falls,
And straightway melting it distills away,
Like a fire-wasted taper: thus was I,
Without a sigh or tear, or ever these
Did sing, that, with the chiming of Heaven’s sphere,
Still in their warbling chime: but when the strain
Of dulcet symphony express’d for me
Their soft compassion, more than could the words,
“Virgin! why so consumest him?” then, the ice
Congeal’d about my bosom, turn’d itself
To spirit and water; and with anguish forth
Gush’d, through the lips and eyelids, from the heart.
Upon the chariot’s same edge still she stood,
Immovable; and thus address’d her words
To those bright semblances with pity touch’d:
“Ye in the eternal day your vigils keep;
So that nor night nor slumber, with close stealth,
Conveys from you a single step, in all
The goings on of time: thence, with more heed
I shape mine answer, for his ear intended,
Who there stands weeping; that the sorrow now
May equal the transgression. Not alone
Through operation of the mighty orbs,
That mark each seed to some predestined aim,
As with aspect or fortunate or ill
The constellations meet; but through benign
Largess of heavenly graces, which rain down
From such a height as mocks our vision, this man
Was, in the freshness of his being, such,
So gifted virtually, that in him
All better habits wondrously had thrived
The more of kindly strength is in the soil,
So much doth evil seed and lack of culture
Mar it the more, and make it run to wildness.
These looks sometime upheld him; for I show’d
My youthful eyes, and led him by their light
In upright walking. Soon as I had reach’d
Tee threshold of my second age, and changed
My mortal for immortal; then he left me,
And gave himself to others. When from flesh
To spirit I had risen, and increase
Of beauty and of virtue circled me,
I was less dear to him, and valued less.
His steps were turn’d into deceitful ways,
Following false images of good, that make
No promise perfect. Nor avail’d me aught
To sue for inspirations, with the which,
I, both in dreams of night, and otherwise,
Did call him back; of them, so little reck’d him.
Such depth he fell, that all device was short
Of his preserving, save that he should view
The children of perdition. To this end
I visited the purlieus of the dead:
And one, who hath conducted him thus high,
Received my supplications urged with weeping.
It were a breaking of God’s high decree,
If Lethe should be pass’d, and such food tasted,
Without the cost of some repentant tear.”
ARGUMENT.—Beatrice continues her reprehension of Dante, who confesses his error, and falls to the ground; coming to himself again, he is by Matilda drawn through the waters of Lethe, and presented first to the four virgins who figure the cardinal virtues; these in their turn lead him to the Gryphon, a symbol of our Saviour; and the three virgins, representing the evangelical virtues, intercede for him with Beatrice, that she would display to him her second beauty.
“O THOU!” her words she thus without delay
Resuming, turn’d their point on me, to whom
They, with but lateral edge, seem’d harsh before:
“Say thou, who stand’st beyond the holy stream,
If this be true. A charge, so grievous, needs
Thine own avowal.” On my faculty
Such strange amazement hung, the voice expired
Imperfect, ere its organs gave it birth.
A little space refraining, then she spake:
“What dost thou muse on? Answer me. The wave
On thy remembrances of evil yet
Hath done no injury.” A mingled sense
Of fear and of confusion, from my lips
Did such a “Yea” produce, as needed help
Of vision to interpret. As when breaks,
In act to be discharged, a cross-bow bent
Beyond its pitch, both nerve and bow o’erstretch’d;
The flagging weapon feebly hits the mark:
Thus, tears and sighs forth gushing, did I burst,
Beneath the heavy load: and thus my voice
Was slacken’d on its way. She straight began:
“When my desire invited thee to love
The good, which sets a bound to our aspirings;
What bar of thwarting foss or linked chain
Did meet thee, that thou so shouldst quit the hope
Of further progress? or what bait of ease,
Or promise of allurement, led thee on
Elsewhere, that thou elsewhere shouldst rather wait?”
A bitter sigh I drew, then scarce found voice
To answer; hardly to these sounds my lips
Gave utterance, wailing: “Thy fair looks withdrawn,
Things present, with deceitful pleasures, turn’d
My steps aside.” She answering spake: “Hadst thou
Been silent, or denied what thou avow’st,
Thou hadst not hid thy sin the more; such eye
Observes it. But whene’er the sinner’s cheek
Breaks forth into the precious-streaming tears
Of self-accusing, in our court the wheel
Of justice doth run counter to the edge.
Howe’er, that thou mayst profit by thy shame
For errors past, and that henceforth more strength
May arm thee, when thou hear’st the Syren-voice;
Lay thou aside the motive to this grief,
And lend attentive ear, while I unfold
How opposite a way my buried flesh
Should have impell’d thee. Never didst thou spy,
In art or nature, aught so passing sweet,
As were the limbs that in their beauteous frame
Enclosed me, and are scatter’d now in dust.
If sweetest thing thus fail’d thee with my death,
What, afterward, of moral, should thy wish
Have tempted? When thou first hadst felt the dart
Of perishable things, in my departing
For better realms, thy wing thou shouldst have pruned
To follow me; and never stoop’d again,
To ’bide a second blow, for a slight girl,
Or other gaud as transient and as vain.
The new and inexperienced bird awaits,
Twice it may be, or thrice, the fowler’s aim;
But in the sight of one whose plumes are full,
In vain the net is spread, the arrow wing’d.”

And she resumed: “If, but to hear, thus pains thee,
Raise thou thy beard, and lo! what sight shall do.”
With less reluctance yields a sturdy holm,
Rent from its fibres by a blast, that blows
From off the pole, or from Iarbas’ land,
Than I at her behest my visage raised:
And thus the face denoting by the beard,
I mark’d the secret sting her words convey’d.
No sooner lifted I mine aspect up,
Than I perceived those primal creatures cease
Their flowery sprinkling; and mine eyes beheld
(Yet unassured and wavering in their view)
Beatrice; she, who toward the mystic shape,
That joins two natures in one form, had turn’d:
And, even under shadow of her veil,
And parted by the verdant rill that flow’d
Between, in loveliness she seem’d as much
Her former self surpassing, as on earth
All others she surpass’d. Remorseful goads
Shot sudden through me. Each thing else, the more
Its love had late beguiled me, now the more
Was loathsome. On my heart so keenly smote
The bitter consciousness, that on the ground
O’erpower’d I fell: and what my state was then,
She knows, who was the cause. When now my strength
Flow’d back, returning outward from the heart,
The lady, whom alone I first had seen,
I found above me. “Loose me not,” she cried:
“Loose not thy hold:” and lo! had dragg’d me high
As to my neck into the stream; while she,
Still as she drew me after, swept along,
Swift as a shuttle, bounding o’er the wave.
The blessed shore approaching, then was heard
So sweetly, “Tu asperges me,” that I
May not remember, much less tell the sound.
The beauteous dame, her arms expanding, clasp’d
My temples, and immerged me where ’twas fit
The wave should drench me: and, thence raising up,
Within the fourfold dance of lovely nymphs
Presented me so laved; and with their arm
They each did cover me. “Here are we nymphs,
And in the heaven are stars. Or ever earth
Was visited of Beatrice, we,
Appointed for her handmaids, tended on her.
We to her eyes will lead thee: but the light
Of gladness, that is in them, well to scan,
Those yonder three, of deeper ken than ours,
Thy sight shall quicken.” Thus began their song:
And then they led me to the Gryphon’s breast,
Where, turn’d toward us, Beatrice stood.
“Spare not thy vision. We have station’d thee
Before the emeralds, whence love, erewhile,
Hath drawn his weapons on thee.” As they spake,
A thousand fervent wishes riveted
Mine eyes upon her beaming eyes, that stood,
Still fix’d toward the Gryphon, motionless.
As the sun strikes a mirror, even thus
Within those orbs the twofold being shone;
Forever varying, in one figure now
Reflected, now in other. Reader! muse
How wondrous in my sight it seem’d, to mark
A thing, albeit steadfast in itself,
Yet in its imaged semblance mutable.
Full of amaze, and joyous, while my soul
Fed on the viand, whereof still desire
Grows with satiety; the other three,
With gesture that declared a loftier line,
Advanced: to their own carol, on they came
Dancing, in festive ring angelical.
“Turn, Beatrice!” was their song: “Oh! turn
Thy saintly sight on this thy faithful one,
Who, to behold thee, many a wearisome pace
Hath measured. Gracious at our prayer, vouchsafe
Unveiled to him thy cheeks; that he may mark
Thy second beauty, now conceal’d.” O splendour!
O sacred light eternal! who is he,
So pale with musing in Pierian shades,
Or with that fount so lavishly imbued,
Whose spirit should not fail him in the essay
To represent thee such as thou didst seem,
When under cope of the still-chiming Heaven
Thou gavest to open air thy charms reveal’d?
ARGUMENT.—Dante is warned not to gaze too fixedly on Beatrice. The procession moves on, accompanied by Matilda, Statius, and Dante, till they reach an exceeding lofty tree, where divers strange chances befall.
MINE eyes with such an eager coveting
Were bent to rid them of their ten years’ thirst,
Not other sense was waking: and e’en they
Were fenced on either side from heed of aught;
So tangled, in its custom’d toils, that smile
Of saintly brightness drew me to itself:
When forcibly, toward the left, my sight
The sacred virgins turn’d; for from their lips
I heard the warning sounds: “Too fix’d a gaze!”
A while my vision labour’d; as when late
Upon the o’erstrained eyes the sun hath smote:
But soon, to lesser object, as the view
Was now recover’d, (lesser in respect
To that excess of sensible, whence late
I had perforce been sunder’d), on their right
I mark’d that glorious army wheel, and turn,
Against the sun and sevenfold lights, their front.
As when, their bucklers for protection raised,
A well-ranged troop, with portly banners curl’d,
Wheel circling, ere the whole can change their ground;
E’en thus the goodly regiment of Heaven
Proceeding, all did pass us, ere the car
Had sloped his beam. Attendant at the wheels
The damsels turn’d; and on the Gryphon moved
The sacred burden, with a pace so smooth,
No feather on him trembled. The fair dame,
Who through the wave had drawn me, companied
By Statius and myself, pursued the wheel,
Whose orbit, rolling, mark’d a lesser arch.
Through the high wood, now void, (the more her blame,
Who by the serpent was beguiled), I pass’d,
With step in cadence to the harmony
Angelic. Onward had we moved, as far,
Perchance, as arrow at three several flights
Full wing’d had sped, when from her station down
Descended Beatrice. With one voice
All murmur’d “Adam”; circling next a plant
Despoil’d of flowers and leaf, on every bough,
Its tresses, spreading more as more they rose,
Were such, as ’midst their forest wilds, for height,
The Indians might have gazed at. “Blessed thou,
Gryphon! whose beak hath never pluck’d that tree
Pleasant to taste: for hence the appetite
Was warp’d to evil.” Round the stately trunk
Thus shouted forth the rest, to whom return’d
The animal twice-gender’d: “Yea! for so
The generation of the just are saved.”
And turning to the chariot-pole, to foot
He drew it of the widow’d branch, and bound
There, left unto the stock whereon it grew.
As when large floods of radiance from above
Stream, with that radiance mingled, which ascends
Next after setting of the scaly sign,
Our plants then burgeon, and each wears anew
His wonted colours, ere the sun have yoked
Beneath another star his flamy steeds;
Thus putting forth a hue more faint than rose,
And deeper than the violet, was renew’d
The plant, erewhile in all its branches bare.
Unearthly was the hymn, which then arose.
I understood it not, nor to the end
Endured the harmony. Had I the skill
To pencil forth how closed the unpitying eyes
Slumbering, when Syrinx warbled, (eyes that paid
So dearly for their watching), then, like painter,
That with a model paints, I might design
The manner of my falling into sleep.
But feign who will the slumber cunningly,
I pass it by to when I waked; and tell,
How suddenly a flash of splendour rent
The curtain of my sleep, and one cries out,
“Arise; what dost thou?” As the chosen three,
On Tabor’s mount, admitted to behold
The blossoming of that fair tree, whose fruit
Is coveted of Angels, and doth make
Perpetual feast in Heaven; to themselves
Returning, at the word whence deeper sleeps
Were broken, they their tribe diminish’d saw;
Both Moses and Elias gone, and changed
The stole their Master wore; thus to myself
Returning, over me beheld I stand
The piteous one, who, cross the stream, had brought
My steps. “And where,” all doubting, I exclaim’d,
“Is Beatrice?”—“See her,” she replied,
“Beneath the fresh leaf, seated on its root.
Behold the associate choir that circles her.
The others, with a melody more sweet
And more profound, journeying to higher realms,
Upon the Gryphon tend.” If there her words
Were closed, I know not; but mine eyes had now
Ta’en view of her, by whom all other thoughts
Were barr’d admittance. On the very ground
Alone she sat, as she had there been left
A guard upon the wain, which I beheld
Bound to the twyform beast. The seven nymphs
Did make themselves a cloister round about her;
And, in their hands, upheld those lights secure
From blast septentrion and the gusty south.
“A little while thou shalt be forester here;
And citizen shalt be, forever with me,
Of that true Rome, wherein Christ dwells a Roman,
To profit the misguided world, keep now
Thine eyes upon the car; and what thou seest,
Take heed thou write, returning to that place.”
Thus Beatrice: at whose feet inclined
Devout, at her behest, my thought and eyes
I, as she bade, directed. Never fire,
With so swift motion, forth a stormy cloud
Leap’d downward from the welkin’s farthest bound,
As I beheld the bird of Jove, descend
Down through the tree; and, as he rush’d, the rind
Disparting crush beneath him; buds much more,
And leaflets. On the car, with all his might
He struck; whence, staggering, like a ship it reel’d,
At random driven, to starboard now, o’ercome,
And now to larboard, by the vaulting waves.
Next, springing up into the chariot’s womb,
A fox I saw, with hunger seeming pined
Of all good food. But, for his ugly sins
The saintly maid rebuking him, away
Scampering he turn’d, fast as his hide-bound corpse
Would bear him. Next, from whence before he came,
I saw the eagle dart into the hull
O’ the car, and leave it with his feathers lined:
And then a voice, like that which issues forth
From heart with sorrow rived, did issue forth
From Heaven, and “O poor bark of mine!” it cried,
“How badly art thou freighted.” Then it seem’d
That the earth open’d, between either wheel;
And I beheld a dragon issue thence,
That through the chariot fix’d his forked train;
And like a wasp, that draggeth back the sting,
So drawing forth his baleful train, he dragg’d
Part of the bottom forth; and went his way,
Exulting. What remain’d, as lively turf
With green herb, so did clothe itself with plumes,
Which haply had, with purpose chaste and kind,
Been offer’d; and therewith were clothed the wheels,
Both one and other, and the beam, so quickly,
A sigh were not breathed sooner. Thus transform’d,
The holy structure, through its several parts,
Did put forth heads; three on the beam, and one
On every side: the first like oxen horn’d;
But with a single horn upon their front,
The four. Like monster, sight hath never seen.
O’er it methought there sat, secure as rock
On mountain’s lofty top, a shameless whore,
Whose ken roved loosely round her. At her side,
As ’t were that none might bear her off, I saw
A giant stand; and ever and anon
They mingled kisses. But, her lustful eyes
Chancing on me to wander, that fell minion
Scourged her from head to foot all o’er; then full
Of jealousy, and fierce with rage, unloosed
The monster, and dragg’d on, so far across
The forest, that from me its shades alone
Shielded the harlot and the new-form’d brute.


What EPA Is Doing about Climate Change
EPA is taking a number of common-sense steps to address the challenge of climate change.
Collecting Emissions Data
EPA collects various types of greenhouse gas emissions data. This data helps policy makers, businesses, and the Agency track greenhouse gas emissions trends and identify opportunities for reducing emissions and increasing efficiency.
- The Inventory of U.S. Greenhouse Gas Emissions and Sinks provides the United States' official estimate of total national-level greenhouse gas emissions. This report tracks annual U.S. greenhouse gas emissions since 1990.
- The Greenhouse Gas Reporting Program collects and publishes emissions data from individual facilities in the United States that emit greenhouse gases in large quantities.
Getting Reductions
EPA is reducing greenhouse gas emissions and promoting a clean energy economy through highly successful partnerships and common-sense regulatory initiatives.
- Developing Common-sense Regulatory Initiatives: EPA is developing common-sense regulatory initiatives, to reduce GHG emissions and increase efficiency. For example, EPA's vehicle greenhouse gas rules will save consumers $1.7 trillion at the pump by 2025, and eliminate six billion metric tons of GHG pollution. EPA's Clean Power Plan addresses emissions from power plants, the largest source of carbon pollution in the country. When the Clean Power Plan is fully in place in 2030, carbon pollution from the power sector will be 32 percent below 2005 levels.
- Partnering With the Private Sector: Through voluntary energy and climate programs, EPA's partners reduced over 345 million metric tons of greenhouse gases in 2010 alone - equivalent to the emissions from 81 million vehicles - and saving consumers and businesses of about $21 billion.
- Reducing EPA's Carbon Footprint: EPA is monitoring emissions from its own energy use and fuel consumption and working to reduce greenhouse gas emissions by 25% by 2020. Learn more about federal greenhouse gas requirements and EPA's Strategic Sustainability Performance Plan.
Evaluating Policy Options, Costs and Benefits
EPA conducts economy-wide analyses to understand the economic impacts and effectiveness of proposed climate policies. Learn more about EPA's economic analyses on climate policies and the associated costs and benefits.
Advancing the Science
EPA contributes to world-class climate research through the U.S. Global Change Research Program and the Intergovernmental Panel on Climate Change Exit. EPA's Office of Research and Development conducts research to understand the environmental and health impacts of climate change and to provide sustainable solutions for adapting to and reducing the impact from a changing climate.
Partnering Internationally
EPA is engaged in a variety of international activities to advance climate change science, monitor our environment, and promote activities that reduce greenhouse gas emissions. EPA establishes partnerships, provides leadership, and shares technical expertise to support these activities. Learn more about EPA's International Climate Partnerships.
Partnering With States, Localities, and Tribes
EPA's State and Local Climate and Energy Program provides technical assistance, analytical tools, and outreach support on climate change issues to state, local, and tribal governments. See the progress made by our pilot communities.
Helping Communities Adapt
EPA's Climate Ready Estuaries and Climate Ready Water Utilities programs help coastal resource managers and water utility managers, respectively, plan and prepare for climate change. Learn more about EPA's efforts on adapting to climate change.


About: {{item.about}}
{{res[0]}}
{{res[1]}}
About: {{item.about}}
Elevate Score: {{item.elevateScore}}
Common Interests: (37) Wine, Movies, Polotics, Education, Music and 27 more.
Common Friends: (14) Grace Jun, Jennifer Lowell, Bob Daskin, Sarah Izlowski, and 10 more.
Total Friends: {{item.totalFriends}}


Use the mouse/touchpad/finger to move the crab
Catch the
plastic items
before they hit the bottom
Plastic items gives 1 point each
The dead fish gives -1 point
You loose if:
Your total score is less than 0
A plastic item hits the bottom


"""
Module to deal with base operating system.
Programmed by: Dante Signal31
email<EMAIL_ADDRESS>"""
import sys
[docs]def verify_python_version(major_version, minor_revision):
""" Check if current python interpreter version is what we need.
Compare current interpreter version with the one is provided as needed one.
If not over needed one version abort execution gracefully warning user
she is trying to use an unsupported python interpreter.
:param major_version: Needed major version for Python interpreter.
:type major_version: int
:param minor_revision: Needed minor version for Python interpreter.
:type minor_revision: int
:return: None
"""
if (major_version, minor_revision) > sys.version_info:
message = "This program can only be run on Python {0}.{1} or newer, " \
"you are trying to use Python {2}.{3} instead.\nAborting " \
"execution.".format(major_version, minor_revision,
sys.version_info[0], sys.version_info[1])
sys.exit(message)


{% extends sitebase.html %} {% block head %} {% end %} {%block content %}
Search for plates by the sample(s) contained, and/or by key words included in plate or well comments.
Intersection will retrieve all the plates in which the samples AND the comments are found, while Union will retrieve the plates in which the samples OR the comments are found.
| Plate id | Plate name |
|---|


Mike's First Web Page
Written with the guidance of Epicodus
Check out Epicodus. It's a great school for learning web programming!
This is my first web page!
Contain your excitement!
Here are some things I'm going to learn about coding
- HTML
- CSS
- JavaScript
- And a lot more!
So far in class we've covered:
- Pair Programming
- Cultivating a Growth Mindset
- Working with Markdown
- Working with a Console
- Working with Git
- Working with remote respositories on GitHub
- HTML
- CSS


Sakhawat Hossain built the ভাড়া আদায় - Rent Collector app as an Ad Supported app. This SERVICE is provided by Sakhawat Hossain at no cost and is intended for use as is.
This page is used to inform visitors regarding my policies with the collection, use, and disclosure of Personal Information if anyone decided to use my Service.
If you choose to use my Service, then you agree to the collection and use of information in relation to this policy. The Personal Information that I collect is used for providing and improving the Service. I will not use or share your information with anyone except as described in this Privacy Policy.
The terms used in this Privacy Policy have the same meanings as in our Terms and Conditions, which is accessible at ভাড়া আদায় - Rent Collector unless otherwise defined in this Privacy Policy.
Information Collection and Use
For a better experience, while using our Service, I may require you to provide us with certain personally identifiable information. The information that I request will be retained on your device and is not collected by me in any way.
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Gladys and Harold Beebe
Alexandria, Louisiana
Ages 81 and 87
Married 62 years, with three children, six grandchildren, and three great-grandchildren
Gladys: In 1948, when I was a high school senior, my girlfriend asked me to go with her and some other folks on a triple date. I told her, “I don’t go on blind dates.” Then she showed me a picture of Harold and I changed my mind. He was a college fella and so handsome!
On the evening we all planned to go to the movies, I was very excited. Harold came to the door to get me. But when we got to the car, where two other boys and two young ladies were waiting, Harold sat down and put his arm around another girl!  I did not have fun on that date.
Harold: I can’t remember why I chose another girl to be with that night, but, boy, I knew I had messed up. Bee—that’s what everyone calls Gladys—was very cute. She talked a lot and got along with everyone. After that evening, I called her three times and asked her out, but she kept turning me down. So I finally bluffed her out.
Gladys: I agreed to go with him on a date, but only because I wanted to punish him for messing up and not choosing me that first night. My plan was to spend the evening being totally indifferent.
Harold: Thankfully, she changed her mind.
Gladys: We went to a drive-in movie, then had po’boys and curlicue potatoes afterward. I saw that Harold was smart and very kind. And he had a red convertible. That was big stuff back then. After a few dates, it grew into true love.
Harold: Two years later, in 1950, when I was 25 and Bee was 20, we went to the local courthouse and got married. But we kept it a secret, because Bee’s parents thought that she was too young.
Gladys: I was living at home and going to business school while Harold was studying to become a dentist. I hid the marriage certificate in my bedroom. Two weeks later, my mother found it when she was cleaning my room. Shocked, she called the justice of the peace and asked him, “Did you marry my daughter?” My parents came around, though. They liked Harold. He’s a good fella.
Harold: I learned early on to always ask Gladys what she would rather do. That’s one secret to our marriage: I don’t pretend to be a know-it-all.
Gladys: Harold has always put me first. After we got married, he wouldn’t go golfing at the country club with the other men. He would play with me. I love that about him.
Harold: Gladys has brought out the best in me by giving me unconditional support.
Gladys: Harold and I still enjoy each other’s company more than anyone else’s. We can’t play golf anymore, but we like to watch tournaments together on TV. And we’ve always been big Louisiana State University football fans, so we never miss a game. Oh sure, we still get mad at each other, but we try not to get mad at the same time.
Harold: There’s not enough love in this world, so you can’t lose when you meet someone like Bee. I am very lucky.
Renata Pasqualini and Wadih Arap
Houston
Ages 46 and 52
Married 18 years
Wadih: Renata and I grew up in the same city in Brazil. We attended the same elementary and high schools and later shared an adviser at the University of São Paulo. But because of our six-year age difference, we never crossed paths.
 After graduation from medical school, Wadih studied cancer biology at Stanford University, and I did postdoctoral research at Harvard University.
Wadih: In June 1993, I needed a hard-to-find chemical for a particular experiment. My college adviser back in Brazil suggested I contact Renata in Boston, since she was using the same element in her work.
Renata: Wadih called me from his office in San Diego. Then we began corresponding by e-mail, which was brand-new back then.
Wadih: Forty-four people in my lab had to share the same e-mail address.
Renata: At first, our messages were purely professional. Then we began getting more philosophical and having deeper exchanges. But neither of us had romantic expectations.
Wadih: In August I invited Renata to speak about her research to my lab associates. When she stepped through the airport gate, I thought, Uh-oh, I’m in trouble.
Renata: I didn’t think that. But Wadih was exceedingly charming.
Wadih: She gave her lecture the next day, a Thursday. On Friday I took her to a classy restaurant. I couldn’t stop thinking this was it, that we would never see each other again. So I said, “I think we should get married.”
Renata: He put his hand in mine and something incredible happened. I knew I was in love. I said yes.
Wadih: We hadn’t even kissed yet.
Renata: Oh no! And there was no alcohol involved, either. My parents and friends were stunned when I told them I was engaged. I’m not known to be impulsive.
Wadih: We were both busy with work, but two months later we met up in Reno and married at an all-night chapel. We had a one-day honeymoon in Lake Tahoe.
Renata: I didn’t move in with Wadih for six months, because I had experiments to finish. We phoned, e-mailed, and saw each other when we could.
Wadih: Then, in 1999, we accepted an offer to head up our own research laboratory at the University of Texas MD Anderson Cancer Center, in Houston.
Renata: Now we spend 98 percent of our time together. We work side by side.
Wadih: For some couples, our situation would be a deal breaker. They might think, If I worked by myself, I would get all the glory and awards.
Renata: Sometimes we fight like the gods. But minutes later it’s forgotten. Wadih and I are equals in every way. And we have a palpable connection. To this day, I wonder, What if I had been careful and turned down his proposal? It’s a dreadful thought.
Deborah and Carlo Pann
Burbank, California
Ages 57 and 59
Married 26 years, with two sons, ages 23 and 22
Carlo: In the fall of 1978, I was selected to be a contestant on Jeopardy! When I walked into the greenroom, a dozen other players were also waiting.
Deborah: I was one of the few women there. I had just killed it on my trial show, where they determine if you can go on the real program. I remember one of my clues had been “Longest song title of ASCAP record.” The answer was “How Could You Believe Me When I Said I Loved You When You Know I’ve Been a Liar All My Life?” I was telling the other contestants that I was only the second person in the show’s history to answer that correctly when this tall, skinny man with curly hair and a terrible brown suit put his hand out for me to shake and said, “I was the first.”
Carlo: Deb had these great, bright eyes with such a vitality behind them.
Deborah: Carlo kept butting in to the conversation. He had something to say about everything. And yet we ended up flirting with each other.
Carlo: I didn’t have a problem with self-confidence back then.
Deborah: A network representative from standards and practices noticed that we were flirting, and she wouldn’t allow us to participate on the same show.
Carlo: I had already won on the show, but the next taping day I went on and lost. Before I left, I gave Deb my phone number.
Deborah: I didn’t think much about it because it was finally my turn to compete. I did terribly.
Carlo: I watched the episode at home. I remember yelling at the screen, “Come on! You know that!” I knew how smart she was.
Deborah: Three weeks later, I called Carlo (we both lived in the L.A. area). He had mentioned he worked at a movie theater and I thought, Hey, free movies! We spent our first date prowling around old book and record stores. I was surprised that we shared so many interests: We both liked the Andrews Sisters as much as Pink Floyd.
Carlo: I was smitten. We began dating and married in 1985.
Deborah: We’ve had our ups and downs. In 2007 I was laid off from my managerial position. Then we lost our home to foreclosure. I thought, We’re smart! How did we sign up for such a lousy mortgage? We’re now in a two-bedroom apartment. Carlo is a freelance writer, and I’m working as a receptionist. There has been a lot of yelling, but a lot of back rubs as well.
Carlo: We hold each other to high standards. God help you if you tell a joke you’ve told before. And when we watch Jeopardy!, we both try to guess the response from the final-category name instead of waiting for the clue.
Deborah: Through the years, we have kept each other interesting and interested.
Carlo: I would like to think I know everything there is about Deb, but I don’t. She’s always giving me new things to learn, and I love her for that.
All stories come from: http://www.realsimple.com/work-life/family/relationships/love-stories


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Gemnasium is a dependencies tracking system (SaaS) that keeps you up to date on the packages
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I'm a practitioner of Domain Driven Design (DDD), Command Query Responsibility Segregation (CQRS), Event Sourcing (ES), Service Oriented Architecture (SOA), Event Sriven Architecture (EDA), microservices, and messaging principles. I'm a big believer in just enough design (which tends to be very little), and emergent architecture. Rather than making technology choices up front, I prefer to prototype and experiment, and gravitate towards approaches that keep the most options open until the last responsible moment. As a corollary, I prefer principles that provide small incremental value as opposed to large big-bang releases.
I've seen a common theme in many clients attempting DDD, CQRS, Event Sourcing, SOA, etc. People tend to focus heavily on the technical details, and common superficial patterns. As a result, they miss out on the core values of the approaches. They tend to look for a cookie-cutter approach, often resulting in something similar to an n-layer architecture. This starts out well, but soon tends to result in features taking longer and longer to get delivered. Instead of trying to use the same patterns and practices regardless of requirements, I focus on identifying the ones that cater to a particular project's needs, and implement them with long term benefits in mind.
I'm a fan of "living software". I believe that unforseen scenarios and requirements will emerge, and that it is impossible to get everything right from the get go. As such, I divide systems into contexts and services, and implement each to be as good as necessary. Applying the same level of dexterity to everything only results in overhead and accidental complexity. Instead, I reserve the most focus for the contexts that provide the highest return, while ensuring under-performing bits can be easily replaced. As such, my solutions evolve over time, rather than following a pre-destined failure-bound path. Whether I am putting together a large topology for high performance reliable brokerless messaging with ZeroMQ, capturing domain events in an event store, composing functions with reactive extensions, exchanging 10 million + messages in memory per second with plain old C#, hooking together distributed applications with a broker like RabbitMQ, evolving level 3 ReST services, applying messaging through process managers, routing slips and sagas, or doing simple CRUD with Entity Framework - I always keep the bigger picture in mind.
With over 12 years of professional experience, I've used a few things.
Most of my commercial experience has been with .NET, and C#. I've been with the platform since 2002, having used the public 1.0 beta. After briefly using WinForms, I quickly switched my focus onto WebForms, and then ASP.NET MVC as soon as it came out. Since then, I've delved into high performance scalable distributed server-side applications, while keeping a keen eye on client side technologies like ASP.NET MVC, Web API, jQuery, Knockout, AngularJS, bootstrap, etc. For message oriented systems, I've used ZeroMQ, RabbitMQ, Mass Transit, NServiceBus, Service Bus for Windows Server, and - where appropriate - chose to implement custom messaging for problems that haven't fallen into the gaps filled by existing tools. In the .NET world, I've also used WCF, WPF, Prism, NancyFx, Windows Services, TopShelf, Reactive Extensions for .NET, Silverlight, NHibernate, Entity Framework, Dapper, Simple.Data, ASMX Services, various IoC containers (including Autofac, Structuremap, Unity), NCqrs, CommonDomain, RIA Services, etc. As a fan of automated testing, I've used tools like NUnit, XUnit, Machine.Specifications, SpecFlow, Moq, FakeItEasy, FitNese, and quite often create lightweight frameworks around NUnit for domain specific testing.
As mentioned before, most of my commercial experience has been with C#, and I'm more than at home with JavaScript. I am, however, interested in a broad range of languages. I've passed professional courses at Oxford University on Haskell and Erlang with distinction, and have completed Coursera training courses on Scala and R with 100% marks. I'm very keen on functional programming, and look to use F# wherever appropriate. In fact, most C# I write these days is heavily influence by functional programming concepts. I'm learning Python and Octave / Matlab as I get deeper into Machine Learning. Although it's been a while, I used to code quite a bit of C++ as well - from taking part in programming contests, to writing 2D and 3D engines on top of DirectX 7-9.
I'm a follower of Continuous Integration and Continuous Delivery. I build build scripts using Psake, MSBuild, etc., and my CI server of choice is Team City, though I have experience with Jenkins and TFS as well. I'm using tools like Puppet and Vagrant to take advantage of reproduceable environments, and am a fan of productivity tools like ReSharper, MightyMoose, etc.
I'm a relentless learner, and love to pick up new things. I like being out of my comfort zone, and am currently learning more of Erlang, Haskell, Scala, Node.js, Hadoop, Riak, Cassandra... I often sign up for online courses covering topics like Cryptography, Data Analysis, etc. that I find interesting and challenging. Sometimes I attend professional training courses. For example, I've been through Martin Thompson's Lock Free Algorithms and Jezz Humble's Continuous Delivery workshops. I have an extensive collection of books - from Joe Armstrong's latest Erlang writings to Gul Agha's works on Actor Models going back decades.
Agile, without the capital 'A'.
I've seen quite a few clients struggle with Agile. They have their people go to certification courses, make managers "scrum masters", set up rigorous processes, arrange planning meetings, reviews, and retrospectives. Yet they seem to have trouble where it matters - actually delivering software. In the formalisation of Agile, we seem to have lost what it stands for. We seem to value processes and tools over individuals and interactions. We try to create templates to be used in all projects, and try to plan away risk. We attempt to prevent failure, rather than learning from experiments. We hold onto the same practices of yesterday, but expect that with the addition of some meetings, a task board, and some sharpies - everything will get better on its own.
The value of agile or lean is not in the process, or estimations, or burndown charts. While these things can be useful, the core revolves around continuously delivering working software, and having working software as the measure of progress. Tightening the feedback loop not only gives us faster feedback, it also reduces risk and prevents us from veering off course. The process should facilitate software deliver, not the other way round. Different projects have different needs - trying to enforce the same processes across the board may seem like an efficient, repeatable option - yet it is one that can cripple the actual act of providing value. Instead of delivering value, Agile (with the capital 'A') turns into a hindrance that the team has to bear to keep management happy.
There are certain practices that are invaluable in sustainable and frequent software delivery. Continuous integration, efficient version control, push-button deployments, phoenix servers, high quality tests, refactoring where arppropriate, evolvable architecture, impact mapping, early risk identification, prototyping for solutions, pair programming, etc. canall help in creating releasable, production ready software that not only works, but evolves when necessary. These may seem technical, yet are fundamental in attaining the benefits of lean and agile methodologies. Guess what I tend to focus on?


Fivepseq usage¶
Command line arguments¶
These are the arguments to be provided:
fivepseq \
-g <path_to_genome_fasta> \
-a <path_to_annotation> \
-b <path_to_bam_file(s) \ #(multiple files provided with pattern ("parent_dir/*.bam"))
-o <output_directory> \
-t <title_of_the_run> \
[optional arguments]
Optional arguments¶
Conflict
The conflict mode specifies how to deal with files/folders that already exist:
--conflict
default: add - only adds missing files to existing directory
overwrite - overwrites all the files in the existing (in case) output directory
alt_dir - uses alternative directory by appending '+' suffix to existing (in case) output directory
Outlier downsampling
Set p value threshold for outlier detection: counts with less than the [–op] probability of falling into Poisson distribution will be down-sampled.
--op
default: 0
-1 - turn off downsampling
Alternatively, set constant threshold for read count down-sampling. Instead of outlier detection, values larger than this constant will be down-sampled.
--ds
default: None
Gene filter
Supply a text file with newline-separated list of gene ids you’d like to filter/use. The names should correspond to those present under the gene_id tag in the gff file. Note: only these genes will be used in all the calculations.
-gf/-genefilter
default: None
Gene set analysis
This option provides a possibility to compare plots for different samples. Supply a tab separated text file, with the following structure:
Columns: gene_attribute (e.g. Name) -> geneset
Rows: value_of_the_attribute -> geneset_name
Note, the gene_attribute is the attribute name in the gtf or gff file. In case of gff, the attribute in the cds feature will be considered. With this option, fivepseq will generate a separate plotting directory called genesets, with tabbed-plots to either compare samples for each geneset, or genesets for each sample. The counts folder will also be divided according to the geneset used. The default folder will be named protein_coding.
-gs/-geneset
default: None


Syneos Health announces partnership with AiCure
Will leverage proprietary intelligent software and AI-driven insights
Syneos Health, an integrated biopharmaceutical solutions organisation, has partnered with AiCure for smarter clinical trials that optimise patient engagement.
AiCure is an artificial intelligence and data analytics company, which offers proprietary intelligent software and AI-driven insights.
The partnership will see AiCure leverage Syneos’ behavioural insights-driven product development model, with the aim to capture, analyse and predict patient behaviours influencing clinical trial adherence.
“The AiCure platform aligns with our unique product developmet model that harnesses behavioural insights to unlock real world experiences,” said Alistair Macdonald, chief executive officer of Syneos Health.
“By deploying the AiCure platform to our investigative sites, we create insights-enriched patient communities to advance clinical research,” he added.
Syneos Health will have access to AiCure’s digital biomarker assessments, evaluating facial, verbal, speech and movement variables to objectively study known clinical endpoints.
The platform identifies adherence patterns and variations in site and participant engagement, providing the opportunity to modify behaviours that increase compliance for the improvement of overall trial success.
Part of this includes providing patients with a smartphone application to guide and confirm proper administration in real-time – as opposed to self-reporting measures.
“Syneos Health’s scale as a leading global CRO, and the largest contract commercial organisation, will enable valuable customer engagements and expands our reach with biopharmaceutical companies of all sizes,” said Adam Hanina, chief executive officer of AiCure


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Let our online travel advisor help you decide!
First, help us help you by telling us a little more about yourself:
Name:
Are you:
Male?
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I prefer not to identify. We are all people!
Do you prefer:
The buzz and energy of city life?
The quiet and pristine beauty of the outdoors?
Do you like to:
To be bundled up in layers and braced against the cold?
To put on a bathing suit and need nothing more?
Would you rather visit:
The Ocean?
A River?
A Lake?
Tell me where I'm going!

Sunbathe on beautiful beaches!
Enjoy vibrant city culture and nightlife!
Additional Resoures:
Visit City of Miami website
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Enjoy vibrant city culture and nightlife!
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Basic
€29
- 10,000 Messages
- 500+ Elements
- 250 Users
- Free Updates
Creative Tim stands for everything a designer looks in his work: clean, functions interfaces for great products. The number of friends with similar attitude can only increase over time, since the vision for a better web is a wish of many designers.
Be sure to enroll and browse around for anything that may bring extra value to your project and ask Tim wherever you see something missing.Creative Tim stands for everything a designer looks in his work: clean, functions interfaces for great products. The number of friends with similar attitude can only increase over time, since the vision for a better web is a wish of many designers.
Be sure to enroll and browse around for anything that may bring extra value to your project and ask Tim wherever you see something missing.Spend your time generating new ideas. You don't have to think of implementing anymore.
Create hundreds of items combinations within seconds and present them to your client.
The large amount of components with the color variations will make you create an amazing web design.
Spend your time generating new ideas. You don't have to think of implementing anymore.
Create hundreds of items combinations within seconds and present them to your client.
The large amount of components with the color variations will make you create an amazing web design.


Welcome to Water World! The fun experience where you will learn to water paint, as well as learn the history of water painting. You will be able to see the many different works of some artists as well as have some tutorial videos to learn the different strokes and styles to water paintings.
Water color first began in ancient Chinese Dynasties, soon after that it was adopted heavily from Europe, which was heavily used in the Renaiassance era. Coming to modern times, water color painting is used as a form of expression for many artists, ranging from beginners to the more advanced painters.
For a more in depth look at Water Painting, click here.
We are always open to feedback. Click here to fill out a quick survey!
Here are some examples of some fine pieces of water paintings. These are works from various artists. If you wish to learn some basics of water painting click here.
I enjoyed the water painting and the examples! They looked really cool! [-Abeal B]
I enjoyed that everything was easy to find and tutorials were very helpful! [-Yabsera T]
The gallery looked really cool! [-Jaxon M]


Build a recalibration model to score variant quality for filtering purposes
This tool performs the first pass in a two-stage process called VQSR; the second pass is performed by the ApplyRecalibration tool. In brief, the first pass consists of creating a Gaussian mixture model by looking at the distribution of annotation values over a high quality subset of the input call set, and then scoring all input variants according to the model. The second pass consists of filtering variants based on score cutoffs identified in the first pass.
The purpose of the variant recalibrator is to assign a well-calibrated probability to each variant call in a call set. You can then create highly accurate call sets by filtering based on this single estimate for the accuracy of each call. The approach taken by variant quality score recalibration is to develop a continuous, covarying estimate of the relationship between SNP call annotations (such as QD, MQ, and ReadPosRankSum, for example) and the probability that a SNP is a true genetic variant versus a sequencing or data processing artifact. This model is determined adaptively based on "true sites" provided as input, typically HapMap 3 sites and those sites found to be polymorphic on the Omni 2.5M SNP chip array (in humans). This adaptive error model can then be applied to both known and novel variation discovered in the call set of interest to evaluate the probability that each call is real. The score that gets added to the INFO field of each variant is called the VQSLOD. It is the log odds of being a true variant versus being false under the trained Gaussian mixture model.
VQSR is probably the hardest part of the Best Practices to get right, so be sure to read the method documentation, parameter recommendations and tutorial to really understand what these tools and how to use them for best results on your own data.
Recalibrating SNPs in exome data:
java -Xmx4g -jar GenomeAnalysisTK.jar \ -T VariantRecalibrator \ -R reference.fasta \ -input raw_variants.vcf \ -resource:hapmap,known=false,training=true,truth=true,prior=15.0 hapmap_3.3.b37.sites.vcf \ -resource:omni,known=false,training=true,truth=false,prior=12.0 1000G_omni2.5.b37.sites.vcf \ -resource:1000G,known=false,training=true,truth=false,prior=10.0 1000G_phase1.snps.high_confidence.vcf -resource:dbsnp,known=true,training=false,truth=false,prior=6.0 dbsnp_135.b37.vcf \ -an QD -an MQ -an MQRankSum -an ReadPosRankSum -an FS -an SOR -an InbreedingCoeff \ -mode SNP \ -recalFile output.recal \ -tranchesFile output.tranches \ -rscriptFile output.plots.R
These Read Filters are automatically applied to the data by the Engine before processing by VariantRecalibrator.
This tool can be run in multi-threaded mode using this option.
All tools inherit arguments from the GATK Engine' "CommandLineGATK" argument collection, which can be used to modify various aspects of the tool's function. For example, the -L argument directs the GATK engine to restrict processing to specific genomic intervals; or the -rf argument allows you to apply certain read filters to exclude some of the data from the analysis.
This table summarizes the command-line arguments that are specific to this tool. For more details on each argument, see the list further down below the table or click on an argument name to jump directly to that entry in the list.
| Argument name(s) | Default value | Summary | |
|---|---|---|---|
| Required Inputs | |||
| --input |
NA | The raw input variants to be recalibrated | |
| --resource |
NA | A list of sites for which to apply a prior probability of being correct but which aren't used by the algorithm (training and truth sets are required to run) | |
| Required Outputs | |||
| --recal_file -recalFile |
NA | The output recal file used by ApplyRecalibration | |
| --tranches_file -tranchesFile |
NA | The output tranches file used by ApplyRecalibration | |
| Required Parameters | |||
| --mode |
NA | Recalibration mode to employ | |
| --use_annotation -an |
NA | The names of the annotations which should used for calculations | |
| Optional Inputs | |||
| --aggregate |
NA | Additional raw input variants to be used in building the model | |
| Optional Outputs | |||
| --rscript_file -rscriptFile |
NA | The output rscript file generated by the VQSR to aid in visualization of the input data and learned model | |
| Optional Parameters | |||
| --ignore_filter -ignoreFilter |
NA | If specified, the variant recalibrator will also use variants marked as filtered by the specified filter name in the input VCF file | |
| --target_titv -titv |
2.15 | The expected novel Ti/Tv ratio to use when calculating FDR tranches and for display on the optimization curve output figures. (approx 2.15 for whole genome experiments). ONLY USED FOR PLOTTING PURPOSES! | |
| --TStranche -tranche |
NA | The levels of truth sensitivity at which to slice the data. (in percent, that is 1.0 for 1 percent) | |
| Optional Flags | |||
| --ignore_all_filters -ignoreAllFilters |
NA | If specified, the variant recalibrator will ignore all input filters. Useful to rerun the VQSR from a filtered output file. | |
| Advanced Parameters | |||
| --badLodCutoff |
-5.0 | LOD score cutoff for selecting bad variants | |
| --dirichlet |
0.001 | The dirichlet parameter in the variational Bayes algorithm. | |
| --maxGaussians -mG |
8 | Max number of Gaussians for the positive model | |
| --maxIterations -mI |
150 | Maximum number of VBEM iterations | |
| --maxNegativeGaussians -mNG |
2 | Max number of Gaussians for the negative model | |
| --maxNumTrainingData |
2500000 | Maximum number of training data | |
| --minNumBadVariants -minNumBad |
1000 | Minimum number of bad variants | |
| --MQCapForLogitJitterTransform -MQCap |
0 | Apply logit transform and jitter to MQ values | |
| --numKMeans -nKM |
100 | Number of k-means iterations | |
| --priorCounts |
20.0 | The number of prior counts to use in the variational Bayes algorithm. | |
| --shrinkage |
1.0 | The shrinkage parameter in the variational Bayes algorithm. | |
| --stdThreshold -std |
10.0 | Annotation value divergence threshold (number of standard deviations from the means) | |
| Advanced Flags | |||
| --trustAllPolymorphic -allPoly |
NA | Trust that all the input training sets' unfiltered records contain only polymorphic sites to drastically speed up the computation. |
Arguments in this list are specific to this tool. Keep in mind that other arguments are available that are shared with other tools (e.g. command-line GATK arguments); see Inherited arguments above.
Additional raw input variants to be used in building the model
These additional calls should be unfiltered and annotated with the error covariates that are intended to be used for modeling.
--aggregate binds reference ordered data. This argument supports ROD files of the following types: BCF2, VCF, VCF3
List[RodBinding[VariantContext]]
LOD score cutoff for selecting bad variants
Variants scoring lower than this threshold will be used to build the Gaussian model of bad variants.
double [ [ -∞ ∞ ] ]
The dirichlet parameter in the variational Bayes algorithm.
double [ [ -∞ ∞ ] ]
If specified, the variant recalibrator will ignore all input filters. Useful to rerun the VQSR from a filtered output file.
boolean
If specified, the variant recalibrator will also use variants marked as filtered by the specified filter name in the input VCF file
For this to work properly, the -ignoreFilter argument should also be applied to the ApplyRecalibration command.
List[String]
The raw input variants to be recalibrated
These calls should be unfiltered and annotated with the error covariates that are intended to be used for modeling.
R List[RodBindingCollection[VariantContext]]
Max number of Gaussians for the positive model
This parameter determines the maximum number of Gaussians that should be used when building a positive model
using the variational Bayes algorithm.
int [ [ -∞ ∞ ] ]
Maximum number of VBEM iterations
This parameter determines the maximum number of VBEM iterations to be performed in the variational Bayes algorithm.
The procedure will normally end when convergence is detected.
int [ [ -∞ ∞ ] ]
Max number of Gaussians for the negative model
This parameter determines the maximum number of Gaussians that should be used when building a negative model
using the variational Bayes algorithm. The actual maximum used is the smaller value between the mG and mNG
arguments, meaning that if -mG is smaller than -mNG, -mG will be used for both. Note that this number should
be small (e.g. 4) to achieve the best results.
int [ [ -∞ ∞ ] ]
Maximum number of training data
The number of variants to use in building the Gaussian mixture model. Training sets larger than this will be randomly downsampled.
int [ [ -∞ ∞ ] ]
Minimum number of bad variants
This parameter determines the minimum number of variants that will be selected from the list of worst scoring
variants to use for building the Gaussian mixture model of bad variants.
int [ [ -∞ ∞ ] ]
Recalibration mode to employ
Use either SNP for recalibrating only SNPs (emitting indels untouched in the output VCF) or INDEL for indels (emitting SNPs untouched in the output VCF).
There is also a BOTH option for recalibrating both SNPs and indels simultaneously, but this is meant for testing purposes only and should not be used in actual analyses.
The --mode argument is an enumerated type (Mode), which can have one of the following values:
R Mode
Apply logit transform and jitter to MQ values
MQ is capped at a "max" value (60 for bwa-mem) when the alignment is considered perfect. Typically, a huge
proportion of the reads in a dataset are perfectly mapped, which yields a distribution of MQ values with a
blob below the max value and a huge peak at the max value. This does not conform to the expectations of the
Gaussian mixture model of VQSR and has been observed to yield a ROC curve with a jump.
This argument aims to mitigate this problem. Using MQCap = X has 2 effects: (1) MQs are transformed by a scaled
logit on [0,X] (+ epsilon to avoid division by zero) to make the blob more Gaussian-like and (2) the transformed
MQ=X are jittered to break the peak into a narrow Gaussian.
Beware that IndelRealigner, if used, adds 10 to MQ for successfully realigned indels. We recommend to either use
--read-filter ReassignOriginalMQAfterIndelRealignment with HaplotypeCaller or use a MQCap=max+10 to take that
into account.
If this option is not used, or if MQCap is set to 0, MQ will not be transformed.
int [ [ -∞ ∞ ] ]
Number of k-means iterations
This parameter determines the number of k-means iterations to perform in order to initialize the means of
the Gaussians in the Gaussian mixture model.
int [ [ -∞ ∞ ] ]
The number of prior counts to use in the variational Bayes algorithm.
double [ [ -∞ ∞ ] ]
The output recal file used by ApplyRecalibration
R VariantContextWriter
A list of sites for which to apply a prior probability of being correct but which aren't used by the algorithm (training and truth sets are required to run)
Any set of VCF files to use as lists of training, truth, or known sites.
Training - The program builds the Gaussian mixture model using input variants that overlap with these training sites.
Truth - The program uses these truth sites to determine where to set the cutoff in VQSLOD sensitivity.
Known - The program only uses known sites for reporting purposes (to indicate whether variants are already known or novel). They are not used in any calculations by the algorithm itself.
Bad - A database of known bad variants can be used to supplement the set of worst ranked variants (compared to the Gaussian mixture model) that the program selects from the data to model "bad" variants.
--resource binds reference ordered data. This argument supports ROD files of the following types: BCF2, VCF, VCF3
R List[RodBinding[VariantContext]]
The output rscript file generated by the VQSR to aid in visualization of the input data and learned model
File
The shrinkage parameter in the variational Bayes algorithm.
double [ [ -∞ ∞ ] ]
Annotation value divergence threshold (number of standard deviations from the means)
If a variant has annotations more than -std standard deviations away from mean, it won't be used for building
the Gaussian mixture model.
double [ [ -∞ ∞ ] ]
The expected novel Ti/Tv ratio to use when calculating FDR tranches and for display on the optimization curve output figures. (approx 2.15 for whole genome experiments). ONLY USED FOR PLOTTING PURPOSES!
The expected transition / transversion ratio of true novel variants in your targeted region (whole genome, exome, specific
genes), which varies greatly by the CpG and GC content of the region. See expected Ti/Tv ratios section of the GATK best
practices documentation (http://www.broadinstitute.org/gatk/guide/best-practices) for more information.
Normal values are 2.15 for human whole genome values and 3.2 for human whole exomes. Note
that this parameter is used for display purposes only and isn't used anywhere in the algorithm!
double [ [ -∞ ∞ ] ]
The output tranches file used by ApplyRecalibration
R File
Trust that all the input training sets' unfiltered records contain only polymorphic sites to drastically speed up the computation.
Boolean
The levels of truth sensitivity at which to slice the data. (in percent, that is 1.0 for 1 percent)
Add truth sensitivity slices through the call set at the given values. The default values are 100.0, 99.9, 99.0, and 90.0
which will result in 4 estimated tranches in the final call set: the full set of calls (100% sensitivity at the accessible
sites in the truth set), a 99.9% truth sensitivity tranche, along with progressively smaller tranches at 99% and 90%.
List[Double]
The names of the annotations which should used for calculations
See the input VCF file's INFO field for a list of all available annotations.
R List[String]


The minons have taken down this App! * * For maintainance Review our Status page for more details and reach us on Chat to volunteer.


OpenShift Pipelines
|
Documentation deprecation notice: Please visit the OpenShift Pipelines documentation website for the latest documentation. |
|
OpenShift Pipelines project is based on the upstream project Tekton and is available as a Developer Preview release. Developer Preview releases have features and functionality that might not be fully tested. Customers are encouraged to use and provide feedback on Developer Preview releases. Red Hat does not commit to fixing any reported issues and the provided features may not be available in future releases. Developer Preview releases are not production ready and customers are advised to avoid running the software for production or business-critical workloads. Limited documentation is available for Developer Preview releases. Customers are NOT able to open support cases against the Developer Preview releases. If you need assistance with OpenShift Pipelines, reach out on the following mailing list where a member of the Red Hat Development Team will be happy to assist you based on availability and work schedules<EMAIL_ADDRESS>|
OpenShift Pipelines are cloud-native, continuous integration and continuous delivery (CI/CD) solutions based on Kubernetes resources. It uses Tekton Pipelines to automate deployments across multiple platforms by abstracting away the underlying details. Tekton introduces a number of standard Custom Resource Definitions (CRDs) for defining pipelines that are portable across Kubernetes distributions.
-
OpenShift Pipelines are designed for microservices and decentralized teams.
-
OpenShift Pipelines uses standard CI/CD pipeline definitions that are easy to extend and integrate with existing Kubernetes tools, enabling you to scale on-demand.
-
You can use them to build images with Kubernetes tools such as Source-to-Image (S2I), Buildah, Buildpacks, and Kaniko and are portable across any Kubernetes platform.
-
You can use the OpenShift Developer Console to create Tekton resources, view logs of pipeline runs, and manage pipelines under OpenShift project namespaces.
Additional resources
-
For more details on defining pipelines, see the Using Pipelines documentation.
-
For more information on Tekton see the Tekton Pipelines documentation.
-
Visit our GitHub repository for more information or to contribute.


{% extends 'base.html' %} {% load static%} {% block content %}
I'm a passionate web developer.I have acquired skills and knowledge necessary
to make a succesful project.
I enjoy every step of the design process, from discussion,
collaboration to concept and execution.
I love collaborating and working with a group because I get to learn a lot and improve my skills.
I'm also in love with football, I like watching premier league and also going to watch local tournaments in the neighborhood on weekends.
I take a lot of coffee through the day, it relaxes my mind and relieve stress....Hahaaa
Project-Review is a platform where users can upload their projects and project detail, the project is to be rated and reviewed by other users.
Visit site DetailsMtoto is a group project of six, where I worked on the frontend.
A web app that measures a child's EI ages 8-12 and gives feedback to be used by caregivers.
Next-door is a web application that allow users to be in the loop about everything happening in their neighborhood. From contact information of different handyman to meeting announcements.
Visit site DetailsThis is a website where users may enter a GitHub username into a form, submit it, and see names and descriptions of that person's public repositories.
Visit site DetailsThis is an application that allow users to post a one minute pitch, downvote, upvote and comment on a pitch.
Visit site DetailsInstaPic is a clone of instagram, where users can upload their photos and add caption to the photos for friends to view.
Visit site Details


About me
My name is Mamessile Kiman, everyone calls me "Sile" which is pronounce “Sila”. I’m Originally from Togo country situated in West Africa.
I moved to Charlotte about 12 years ago from Nebraska where I went to school and graduated from Bellevue University in 2007 with degree in Bachelor of Science (Computer Information System.) Personal life:I’m the oldest of 5 children 2 girls an 3 boys. I’m a wife and a mother. My hobby is to watch history channels and fiction movies on Netflix with my Husband. I also love to travel, meet new people and learn new things. In summer 2016, I’ve traveled to Europe visited France, Germany and then Africa.
Professional background: I have been in IT field for over 10 years. I have worked as Technical Analyst and Software QA Analyst in various companies. I have experience in manual and some automation testing. I’ve demonstrated hands-on skills with various testing and software development tools. I have several years of experience working with waterfall and agile methodologies. In short all these experiences have helped me develop exceptional communication, teamwork and a strong analytical skills with ability to multitask and quickly adjust to people, circumstances and responsibilities. Companies I have worked for: Bank Of America: (2019), Lowes: (2018), Newport Group: (2013), Ally: (2012) , Connextions: (2008) .


5
1 "Listen, you priests!

And you members of the king's family, you also need to listen!
For I will punish all of you.
The things you have done have been like a trap for the people at Mizpah.
The things you have done have become like a net spread out to catch the people who live on Mount Tabor.
2 Those who rebelled against me have now killed so many that they are standing deep in their blood.
I know very well what you are like, you people of Israel.
You people in Ephraim, you have acted like prostitutes.
Yes, you people in Israel are polluted.
4 Ephraim and Israel are not able to ask me to forgive them, because of what they have done.
They have chosen to be unfaithful and immoral,
and they do not know me, Yahweh."
5 Israel is proud; because of this others know how guilty she is.
The sins that the people of Israel have committed are making them faithless to Yahweh.
Judah is becoming faithless, too.
6 They are hoping to persuade Yahweh to have mercy on them.
They are coming to sacrifice sheep and cattle to him from their flocks and herds.
But they will find that Yahweh will have no mercy on them
because he has stopped helping them; he is leaving them alone.
7 They did not keep their promises to Yahweh.
and they have had children by foreign women.
So at the time of the new moon festivals,
they will perish, together with their cultivated fields."
8 Yahweh says, "Blow the ram horns at the city of Gibeah!
Blow the trumpets at the city of Ramah!
Shout a battle cry at the city of Beth Aven!
Lead us into battle, you people of the tribe of Benjamin!
9 I will punish the people of Ephraim and turn their city into a pile of rubble.
This is my promise to the tribes of Israel—I pledge to you all that I will do this.
10 The leaders of Judah are as bad as people who steal farmland by moving boundary markers;
they steal land that does not belong to them.
I will punish them in a way that will make them perish.
11 Ephraim will suffer greatly; the people will perish when I punish them,
because they were determined to worship idols.
12 I will destroy Ephraim as a moth destroys wool;
I will destroy Judah as rot destroys wood.
13 When the people of Ephraim realized how weak they were,
then they asked the people of Assyria for help.
When the people of Judah realized how weak they were,
they sent messengers to the great king of Assyria.
But he could not help you people;
he could not make you people strong again.
14 I will become like a lion to the people of Ephraim in Israel;
I will become like a young lion to the people of Judah.
I will destroy them and leave them;
I will carry them far away,
and no one will be able to rescue them.
15 Then I will go back to where I came from;
from there I will wait for them to admit that they have sinned;
I will wait for them to come and ask me to help them."


My Hot Tamale bowl looks so bereft sitting there empty. Where will I get my quotient of red number 5?
3/20/2009, 3:45:24 PM
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Retweets: 0
link--- layout: tweet ---
My Hot Tamale bowl looks so bereft sitting there empty. Where will I get my quotient of red number 5?
3/20/2009, 3:45:24 PM
Favs: 0
Retweets: 0
link


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Richmond was sad to let him go. Now cult hero Jacob Townsend could be set to join Essendon
by Ben WaterworthDelisted Tiger Jacob Townsend might’ve found another AFL home, with Essendon reportedly showing strong interest in the charismatic goalkicker.
Townsend last month was delisted by Richmond just before the first list deadline (October 31). It came two years after his remarkable 2017 campaign, which saw him claim the JJ Liston Trophy as the VFL’s best player before sliding into the AFL team’s best 22 to feature in the famous drought-breaking premiership.
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It was reported in the aftermath of his delisting that the Giants — the club that initially drafted him and he played 28 games for — were a “strong chance” to recruit him, possibly as a rookie.
But AFL Media reported on Tuesday night that Townsend was now on the radar of the Bombers, who are considering offering him a spot on their list for 2020.
Multiple outlets also reported Townsend was spotted at Essendon’s Tullamarine headquarters last week.
Should Townsend join the Bombers, he‘d likely be acquired in the pre-season supplemental selection period (SSP).
After playing 28 games for the Giants, Townsend was traded to Richmond and managed 20 games in four seasons, including just one in 2019.
But Townsend famously featured in Richmond’s last five games of 2017 and booted 16 goals, including two in the Grand Final.


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This morning is the time for me to play with my 5 years old boy. And I decided to do some paper craft with him since I bought a very cheap package from DAISO and it looks fun.
今天早上是跟孩子相處的時間，我決定跟他一起來做之前在大創買的紙玩具DIY，很便宜，才$49台幣，但很精緻喔！
https://steemitimages.com/DQmRexMK2enamJA7SaZAoRzoRty4QKE2JnaVDSeLxbhEe9n/_20171111_143137.JPG
Take a look! Seems fun and challenging!
看看這鳥瞰圖，是不是看起來很有挑戰性？
https://steemitimages.com/DQmcES9CRwTL9DWw7FK2ynnHxfLTzRJb7SJgeQNywcP5UQL/_20171111_143204.JPG
Prepare the tools needed. As I do it then I realize that there is no way my son can help me and I have to be really focused so as not to cut through those parts of the vehicles ..
準備好工具，開工了！開始做才發現，我兒子沒法一起做，不要阻礙我進行就謝天謝地了！我還得非常聚焦，才不會不小心把這紙車的什麼零件給剪了割斷了。
https://steemitimages.com/DQmaRY31ASZRA4VrKj2dm21xng7574DurzmX9mEivRX2Pj4/_20171111_143246.JPG
https://steemitimages.com/DQmX3XYGt8pK4Pe1oLfELSxKsVbJJU8zFCooaf3yPt3wWNM/DSC_3226.JPG
Start with the traffic cone. Oh, it wasn’t easy at all…. -___-|||
先做個簡單的交通錐吧！啊！還是花了我一點功夫，看來前方路途還遙遠哪！來不急喊停了！看看那雙期待的大眼睛~~~
https://steemitimages.com/DQmXseftwkXtTVMXK9DdJykZZRTubvnP3hwNFr5mx6ASRm2/_20171111_143318.JPG
Finally,…. I did it … after a looooooong time. Look cool. He loves it and that’s all that matters.
終於，經過整個上午的奮鬥，與幾次休息，完成了！孩子很開心，還催我完成推土機，怎麼有可能，累死寶寶了！但看著他玩得開心，就是最大的成就（可以發文是第二大動力）。
https://steemitimages.com/DQmfYeTFUzyGYdQProeeygZvWGwnCThuTmhSmqTeoNEUEoy/_20171111_143407.JPG
https://steemitimages.com/DQmXSxUPr38wBbjmWfALupLTyXwrM1ohpLNF4uueAHwofwq/_20171111_143437.JPG
It says this is for kids 8 years old and older. I am much much older than 8 years old, but I still spend 2 hours and just finish one of the two paper vehicles … I assume I have found the secret why Japanese are more capable of doing delicate things from today’s experience …
這紙玩具說是適合八歲以上兒童，但我已經比八歲多非常多了，仍然花了兩個小時才做好一個挖土機，還剩一個推土機沒完成。實在是太驚人的累了，我終於知道日本人為什麼能夠做這麼多精巧的東西了，原來是從小訓練的~~~ Orz….
https://steemitimages.com/DQmZ2hCnLPRgcYXw3Kst8DiaPFJut5mPahKYArdb1zTvbiT/_20171111_143519.JPG
Check my previous MYOT posts …
✂ [MYOT - Make Your Own Toys!] Handmade Lantern!! ✂ [MYOT 自製玩具系列] 呦厚，中秋提燈籠啊！✂
✂ [MYOT - Make Your Own Toys!] Tissue Box House ✂ [MYOT 自製玩具系列] 面紙盒變房子！✂
This page is synchronized from the post: ‘✂ [MYOT - Make Your Own Toys!] Paper Digger Handmade!! ✂ [MYOT 自製玩具系列] 動手做紙挖土機 ✂’


RecognitionReliability
public enum RecognitionReliability
The level of reliability required to assure OCR accuracy. The higher the reliability, the longer it will take to return results
-
Immediately returns the first result
Declaration
Swift
case raw
-
Requires the last two frames return the same results
Declaration
Swift
case tentative
-
Requires the last three frames return the same results
Declaration
Swift
case verifiable
-
Requires the last four frames return the same results
Declaration
Swift
case stable
-
Requires the last five frames return the same results
Declaration
Swift
case solid


A reference cursor is Oracle's iterator. In this example, the stored procedure refc returns a reference cursor and the python code iterates over the rows pointed to by the reference cursor.
-- pl/sql function that returns a ref cursor function refc return sys_refcursor is rc sys_refcursor; begin open rc for select a, b from cxdemo_t1; return rc; end;
res=curs.callfunc('cxdemo.refc',cx_Oracle.CURSOR) for r in res: print r res2=conn.cursor() curs.execute("begin :1 := cxdemo.refc; end;",[res2]) for r in res2: print r