Running a Simple Search Using Tide and Percolator
Now that you have your environment set
up and the two input files in your working directory, you can
conduct the search. The search process compares each spectrum
in demo.ms2 to peptides (subsequences of the
proteins) in fasta files provided in a
dirctory, yeast-index/. Peptides whose
precursor mass is close to that of the observed spectrum are scored
against that spectrum, and the top scores are reported in the output.
To conduct the search, we first create a peptide index
using tide-index
and then execute the search
using tide-search
.
-
$ crux tide-index small-yeast.fasta yeast-index
While generating the peptide index, you will see output like this:
INFO: Beginning tide-index. INFO: Writing results to output directory 'crux-output'. INFO: CPU: Genomes-MacBook-Pro.local INFO: Wed Dec 18 11:12:00 SGT 2013 INFO: Running tide-index... INFO: Writing results to output directory 'yeast-index'. INFO: Reading small-yeast.fasta and computing unmodified peptides... INFO: Writing decoy fasta... INFO: Reading proteins INFO: Precomputing theoretical spectra... INFO: Elapsed time: 0.293 s INFO: Finished crux tide-index. INFO: Return Code:0
This command produces the peptide index in
yeast-index
and also produces a directorycrux-output
containing the following files:- tide-index.decoy.fasta – a set of decoy proteins, derived from the proteins in the input set,
- tide-search.params.txt – a record of all the parameters used in the search, and
- tide-search.log.txt – a log file containing a copy of all the messages printed to the screen during the search.
Now you can run this command:
$ crux tide-search --compute-sp T demo.ms2 yeast-index
- tide-search.target.txt – search results in tab-delimited format.
- tide-search.decoy.txt – search results from a decoy database in tab-delimited format.
- tide-search.params.txt – a record of all the parameters used in the search.
- tide-search.log.txt – a log file containing a copy of all the messages printed to the screen during the search.
-
$ crux percolator crux-output/search.target.txt
While the analysis is running, you will see output like this
INFO: Beginning percolator. WARNING: The output directory 'crux-output' already exists. Existing files will not be overwritten. INFO: CPU: Genomes-MacBook-Pro.local INFO: Wed Dec 18 11:19:20 SGT 2013 INFO: Running make-pin with 'crux-output/tide-search.target.txt' and decoy file 'crux-output/tide-search.decoy.txt'. INFO: Finished make-pin. INFO: Percolator version 2.04, Build Date Dec 11 2013 16:46:25 INFO: Copyright (c) 2006-9 University of Washington. All rights reserved. INFO: Written by Lukas Käll<EMAIL_ADDRESS>in the INFO: Department of Genome Sciences at the University of Washington. INFO: Issued command: INFO: percolator -X crux-output/percolator.target.pout.xml -r crux-output/percolator.target.txt -B crux-output/percolator.decoy.txt -v 2 -P decoy_ --seed 1 -p 0.01000000 -n 0.00000000 --trainFDR 0.01000000 --testFDR 0.01000000 --maxiter 10 --train-ratio 0.60000000 -s crux-output/make-pin.pin.xml INFO: Started Wed Dec 18 11:19:21 2013 INFO: Hyperparameters fdr=0.01, Cpos=0.01, Cneg=0, maxNiter=10 INFO: WARNING: no valid local xml schema is available to validate the input. INFO: If further errors are encountered, please reinstall Percolator. INFO: WARNING: no valid local xml schema is available to validate the input. INFO: If further errors are encountered, please reinstall Percolator. INFO: enzyme=trypsin INFO: Features: INFO: lnrSp deltLCn deltCn Xcorr Sp IonFrac Mass PepLen Charge1 Charge2 Charge3 enzN enzC enzInt lnNumSP dM absdM INFO: Train/test set contains 719 positives and 719 negatives, size ratio=1 and pi0=1 INFO: selecting cneg by cross validation INFO: Estimating 55 over q=0.01 in initial direction INFO: Reading in data and feature calculation took 0.261052 cpu seconds or 0 seconds wall time INFO: ---Training with Cpos=0.01, Cneg selected by cross validation, fdr=0.01 INFO: Iteration 1 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 2 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 3 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 4 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 5 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 6 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 7 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 8 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 9 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Iteration 10 : After the iteration step, 63 target PSMs with q<0.01 were estimated by cross validation INFO: Obtained weights (only showing weights of first cross validation set) INFO: # first line contains normalized weights, second line the raw weights INFO: lnrSp deltLCn deltCn Xcorr Sp IonFrac Mass PepLen Charge1 Charge2 Charge3 enzN enzC enzInt lnNumSP dM absdM m0 INFO: 0.0421 -0.0636 0.0226 0.1690 0.3100 0.0195 0.0120 0.0184 0.0017 -0.0057 0.0054 0.0000 0.0000 -0.0047 -0.0080 -0.0212 0.0178 -0.9205 INFO: 0.0705 -0.2069 0.0994 0.2076 0.0011 0.1464 0.0000 0.0041 0.0046 -0.0120 0.0140 0.0000 0.0000 -0.0411 -0.0133 -0.0230 0.0278 -1.2319 INFO: After all training done, 66 target PSMs with q<0.0100 were found when measuring on the test set INFO: Found 66 target PSMs scoring over 1.0000% FDR level on testset INFO: Merging results from 3 datasets INFO: Tossing out "redundant" PSMs keeping only the best scoring PSM for each unique peptide. INFO: Selecting pi_0=0.8935 INFO: Calibrating statistics - calculating q values INFO: New pi_0 estimate on merged list gives 15 peptides over q=0.0100 INFO: Calibrating statistics - calculating Posterior error probabilities (PEPs) INFO: Processing took 5.385 cpu seconds or 5 seconds wall time INFO: Elapsed time: 6.01 s INFO: Finished crux percolator. INFO: Return Code:0
The crux-output directory will now contain eight new files:
- percolator.target.psms.txt – a list of peptide-spectrum matches (PSMs), ranked by quality,
- percolator.target.peptides.txt – a list of peptides, ranked by quality,
- percolator.decoy.psms.txt – a ranked list of decoy PSMs,
- percolator.decoy.peptides.txt – a ranked list of decoy peptides,
- percolator.pout.xml – a single XML output file containing all of the Percolator results,
- make-pin.pin.xml: an intermediate XML format file that is used by Percolator.
- percolator.params.txt – parameter file, and
- percolator.log.txt – log file.
The beginning of the percolator.target.psms.txt file will look like this:
scan charge spectrum precursor m/z spectrum neutral mass peptide mass percolator score percolator rank percolator q-value matches/spectrum sequence cleavage type protein id flanking aa 26 2 692.3823 1382.7500 1382.4467 11.553608 717 0 5 TASEFDSAIAQDK trypsin-full-digest YLR043C LK 11 2 745.2723 1488.5300 1489.7318 9.9082899 2 0 5 NFLETVELQVGLK trypsin-full-digest YGL135W NR 50 2 651.2922 1300.5699 1301.4160 9.614749 3 0 10 LDVDELGDVAQK trypsin-full-digest YLR043C NK 85 3 497.6206 1489.8400 1489.7318 9.5444765 4 0 3 NFLETVELQVGLK trypsin-full-digest YGL135W NR 118 3 1031.9407 3092.8000 3095.2366 9.1175385 5 0 3 ELESAAYDHAEPVQPEDAPQDIANDELK trypsin-full-digest YGL009C DK 131 2 745.8522 1489.6899 1489.7318 8.8824759 6 0 3 NFLETVELQVGLK trypsin-full-digest YGL135W NR 146 2 692.6823 1383.3500 1382.4467 8.7510319 7 0 5 TASEFDSAIAQDK trypsin-full-digest YLR043C LK In this output, the PSMs are ranked by "percolator score," with higher scores indicating a higher quality match. The associated statistical confidence estimate is reported as a "percolator q-value," interpreted as the minimal false discovery rate threshold at which this match is deemed significant. In the list above, all of the matches have q-values of 0, meaning that they are highly significant. The meanings of the remaining columns are described here.
While the search is running, you will see output like this:
INFO: Beginning tide-search. WARNING: The output directory 'crux-output' already exists. Existing files will not be overwritten. INFO: CPU: Genomes-MacBook-Pro.local INFO: Wed Dec 18 11:14:28 SGT 2013 INFO: Running tide-search... INFO: Reading index yeast-index INFO: Reading spectra file demo.ms2 INFO: Converting demo.ms2 to spectrumrecords format INFO: Sorting spectra INFO: Running search INFO: Elapsed time: 0.543 s INFO: Finished crux tide-search. INFO: Return Code:0
The crux-output directory now contains four new files containing the search results:
The final step is to post-process the search results using Percolator. Each spectrum has been compared to many peptides and we would like to return only the best match for each spectrum. We also expect that some fraction of the spectra will not be identifiable as peptides (due to chemical noise, multiple peptides co-eluting, poor fragmentation, etc.). The analysis step filters out those spectra and ranks the matches by quality.


Preparation time
1-2 hours
Cooking time
30 mins to 1 hour
Serves
Makes 4 large pasties
An all-in-one meal that’s portable, filling and delicious.
Tip the flour into the bowl and add the shortening, a pinch of salt, the margarine or butter and all of the water.
Use a spoon to gently combine the ingredients. Then use your hands to crush everything together, bringing the ingredients together as a fairly dry dough.
Turn out the dough onto a clean work surface (there’s no need to put flour or oil onto the surface because it’s a tight rather than sticky dough).
Knead the dough to combine the ingredients properly. Use the heel of your hand to stretch the dough. Roll it back up into a ball, then turn it, stretch and roll it up again. Repeat this process for about 5-6 minutes. The dough will start to become smooth as the shortening breaks down. If the dough feels grainy, keep working it until it’s smooth and glossy. Don’t be afraid to be rough – you’ll need to use lots of pressure and work the dough vigorously to get the best results.
When the dough is smooth, wrap it in cling film and put it in the fridge to rest for 30–60 minutes.
While the dough is resting, peel and cut the potato, swede and onion into cubes about 1cm/½in square. Cut the beef into similar sized chunks. Put all four ingredients into a bowl and mix. Season well with salt and some freshly ground black pepper, then put the filling to one side until the dough is ready.
Lightly grease a baking tray with margarine (or butter) and line with baking or silicone paper (not greaseproof).
Preheat the oven to 170C (150C fan assisted)/325F/Gas 3.
Once the dough has had time to relax, take it out of the fridge. The margarine or butter will have chilled, giving you a tight dough. Divide the dough into four equal-sized pieces. Shape each piece into a ball and use a rolling pin to roll each ball into a disc roughly 25cm/10in wide (roughly the same size as a dinner plate).
Spoon a quarter of the filling onto each disc. Spread the filling on one half of the disc, leaving the other half clear. Put a knob of butter or margarine on top of the filling.
Carefully fold the pastry over, join the edges and push with your fingers to seal. Crimp the edge to make sure the filling is held inside – either by using a fork, or by making small twists along the sealed edge. Traditionally Cornish pasties have around 20 crimps. When you’ve crimped along the edge, fold the end corners underneath.
Put the pasties onto the baking tray and brush the top of each pasty with the egg and salt mixture. Bake on the middle shelf of the oven for about 45 minutes or until the pasties are golden-brown. If your pasties aren't browning, increase the oven temperature by 10C/25F for the last 10 minutes of cooking time.
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Crimping the edge of a pasty
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How to knead bread dough
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Rolling out pastry


GRAND LAUNCH OF APPLE PRODUCTS
MACBOOKAIR
IPODS
IPHONE
HERE COMES A SHORT VIDEO
PLEASE FILL THE FOLLOWING
E-MAIL:
TO SUBMIT CLICK OVER THIS YELLOW BLOCK


In this page you can modify FEA properties of the 3 storey structure.
This uses ABAQUS scripting language to generate a .py file that is ran via ABAQUS noGUI.
From testing, the elements used are C3D10 (second-order tetrahedral element, quadradic triangular pyramid) as opposed to quadralateral brick elements.
Each part is meshed independently and is joined into the assembly through a rigid surface tie connection.
The FEA is based on imperial units of inches to match the blueprint dimensions. SI units for Young's modulus and density are auto generated as verification.
The bottom of the feet are pinned in the 3 dimensions and the linear perturbation Frequency analysis is performed.
The frequency analysis utilizes the Lanczos algorithm and calculates all the frequencies below the selected maximum frequency.
The current implementation only submits/run the job but does not do any post-processing. This is yet to come
Results from this analysis can be found in "dtApp/dtData/ABAQUS_Scratch".
The main results can be found either through the ".dat" text file or the ".odb" ABAQUS cae file. The ".odb" file provides visualization of the results while the ".dat" file can provide easy file parsing for future analyses.


One of my favorite things is the outdoors. I love to travel, especially where I can hike and see nature. I also used to love to go backpacking but I have not gone for a long time.
Death Valley
On my most recent adventure, I went with my friends to Death Valley for a day on a weekend trip. It feels ironic to say that a desert is so beautiful, but we visited areas like the Mesquite Flat Sand Dunes, Harmony Borax Works, a stop at Furnace Creek, a drive down Artist's Drive, and finally looked at the stars at Badwater Basin. The Mequite Flat Sand Dunes were beautiful because there were miles of sand that were untouched by man and had no footprints whatsoever, and the stars were beautiful at Badwater Basin which is also the lowest point in North America. Here are some pictures, although I am not a photographer and the pictures do not capture the true beauty of the place.


{% if anyRolePresent %}
{% if regionManagerRolePresent %}
{% else %}
Roles: Sorry, you do not have any privileges currently.
{% endif %}
| Regions managed by you | {% for oneRegion in regionManagerRoles %} {{ oneRegion }} {% endfor %} |
| Projects managed by you | {% for oneProject in projectManagerRoles %} {{ oneProject }} {% endfor %} |
| Groups managed by you | {% for oneGroup in groupManagerRoles %} {{ oneGroup }} {% endfor %} |
| Groups you are member of | {% for oneGroup in groupUserRoles %} {{ oneGroup }} {% endfor %} |
Right Now
There are {{ regionsCount }} Regions , {{ zonesCount }} Zones and {{ groupsCount }} Groups


Explore the world through topics of beautiful photos free to use under the un insframe
Some quick example text to build on the card title and make up the bulk of the card's content.
Some quick example text to build on the card title and make up the bulk of the card's content.
Some quick example text to build on the card title and make up the bulk of the card's content.


cookfs::pages - vfs::cookfs::pages
Cookfs pages provide a low level mechanism for reading and writing to cookfs pages.
This mechanism should only be used by advanced users and is only documented for reference.
Creates a new pages object that can be used to read and write pages.
The command returns a pages command that can be used to perform actions on pages.
For definition of available options, see PAGES OPTIONS.
Uses a separate file for storing changes to an archive. This can be used to keep changes for a read-only archive in a separate file. See cookfs for more details on aside files and how they can be used.
Add a new page to archive. Index of new page is returned. Index will be between 0 and length-1.
When adding a page that already exists, index to already existing page is returned. Otherwise a new page is added at the end and its index is returned.
Gets a page in an archive. This can be between 0 and length-1.
Returns number of pages in an archive.
Get or set index data. Index is a binary data that is stored in an archive and can be changed at any time. This is used to store exported version of cookfs_fsindex.
Returns offset to beginning of cookfs archive in the file.
Saves all changes and deletes a cookfs pages object.
Gets part of file as binary data or MD5 checksum of it. Head is the part of the file prior to cookfs archive. Tail is the entire cookfs archive.
These commands can be used as helper procedures to read or compare currently open/mounted binaries.
Sets or gets maximum number of pages to store in cache. If numPages is specified, size is modified. If more than numPages pages are currently buffered, they are removed from cache. If 0, no cache is used. Otherwise, up to numPages are kept in memory
Returns size of file up to last stored page. The size only includes page sizes and does not include overhead for index and additional information used by cookfs.
Hash function to use for comparing if pages are equal. This is mainly used as pre-check and entire page is still checked for. Defaults to md5, can also be crc32. Mainly for internal/testing at this moment. Do not use.
Closes pages object and return offset to end of cookfs archive. This is almost an equivalent of calling delete.
This is meant for internal development and should not be used outside cookfs.
The following options can be specified when creating a cookfs pages object:
Open as read-write, which is the default. If file exists and is valid cookfs pages format archive, it is used. Otherwise new cookfs pages archive is created at end of file.
Open as read-only. File must exist and be in valid cookfs pages format archive, otherwise operation will fail.
Maximum number of pages to store in cache. If 0, no cache is used. Otherwise, up to numPages are kept in memory for efficient access.
Read archive starting at specified offset, instead of reading from end of file.
This feature is used when cookfs archive is not stored at end of file - for example if it is used in tclkit and followed by mk4vfs archive.
Compression to use for storing new files.
See cookfs for more details on compression in cookfs.
For custom compression, specifies command to use for compressing pages.
See cookfs for more details on compression in cookfs.
For custom compression, specifies command to use for decompressing pages.
See cookfs for more details on compression in cookfs.
cookfs_fsindex, cookfs_pages
cookfs, vfs
Copyright © 2010-2011 Wojciech Kocjan <wojciech@kocjan.org>


{% extends "guest_base.html" %} {% load form_tags %} {% block content %}
Please fill in your email address and the confirmation code we emailed you. If you followed the link that was in the email, it will be prefilled automatically and all you have to do to receive a new password is submit the form. We will reset your password and email it to you.
{% endblock %}


Contents
This chapter defines the CSS 2.1 painting order in more detail than described in the rest of the specification.
The bottom of the stack is the furthest from the user, the top of the stack is the nearest to the user:
| | | | | | | | ⇦ ☻ | | | user z-index: canvas -1 0 1 2
The stacking context background and most negative positioned stacking contexts are at the bottom of the stack, while the most positive positioned stacking contexts are at the top of the stack.
The canvas is transparent if contained within another, and given a UA-defined color if it is not. It is infinite in extent and contains the root element. Initially, the viewport is anchored with its top left corner at the canvas origin.
The painting order for the descendants of an element generating a stacking context (see the 'z-index' property) is:
If the element is a root element:
If the element is a block, list-item, or other block equivalent:
Otherwise, if the element is a block level table:
Stacking contexts formed by positioned descendants with negative z-indices (excluding 0) in z-index order (most negative first) then tree order.
For all its in-flow, non-positioned, block-level descendants in tree order: If the element is a block, list-item, or other block equivalent:
Otherwise, the element is a table:
All non-positioned floating descendants, in tree order. For each one of these, treat the element as if it created a new stacking context, but any positioned descendants and descendants which actually create a new stacking context should be considered part of the parent stacking context, not this new one.
If the element is an inline element that generates a stacking context, then:
For each line box that the element is in:
Otherwise: first for the element, then for all its in-flow, non-positioned, block-level descendants in tree order:
If the element is a block-level replaced element, then: the replaced content, atomically.
Otherwise, for each line box of that element:
For each box that is a child of that element, in that line box, in tree order:
background color of element.
background image of element.
border of element.
For inline elements:
For all the element's in-flow, non-positioned, inline-level children that are in this line box, and all runs of text inside the element that is on this line box, in tree order:
If this is a run of text, then:
Otherwise, jump to 7.2.1 for that element.
For inline-block and inline-table elements:
For inline-level replaced elements:
Some of the boxes may have been generated by line splitting or the Unicode bidirectional algorithm.
Optionally, the outline of the element (see 10 below).
Optionally, if the element is block-level, the outline of the element (see 10 below).
All positioned descendants with 'z-index: auto' or 'z-index: 0', in tree order. For those with 'z-index: auto', treat the element as if it created a new stacking context, but any positioned descendants and descendants which actually create a new stacking context should be considered part of the parent stacking context, not this new one. For those with 'z-index: 0', treat the stacking context generated atomically.
Stacking contexts formed by positioned descendants with z-indices greater than or equal to 1 in z-index order (smallest first) then tree order.
Finally, implementations that do not draw outlines in steps above must draw outlines from this stacking context at this stage. (It is recommended to draw outlines in this step and not in the steps above.)
The background of the root element is only painted once, over the whole canvas.
While the backgrounds of bidirectional inlines are painted in tree order, they are positioned in visual order. Since the positioning of inline backgrounds is unspecified in CSS 2.1, the exact result of these two requirements is UA-defined. CSS3 may define this in more detail.


http://www.speakers-podium.com/susangranger.
Susan Granger's review of "AMERICAN BEAUTY" (DreamWorks Pictures)
This surprisingly dramatic black comedy goes for the jugular as it examines with bruising intensity two dysfunctional families in American suburbia. Oscar winner Kevin Spacey ("The Usual Suspects") stars as a cynical advertising exec who hates his job and resents his controlling wife, played by Annette Bening. She's a fiercely ambitious, high-strung perfectionist, intoxicated with success, as she passionately devotes herself to selling real estate and tending her rose garden. Thora Birch is their daughter - and she loathes them. In fact, the film opens with videotape footage of the teenager complaining about her father, wishing someone would kill him. Early on, we discover someone does. Spacey will be dead within the year - at least that's what he tells us. Who? How? When? Why? That's what's eventually revealed on the screen. It's a classic suspense device - and it works. Meanwhile, Spacey's lusting after his daughter's flirtatious high school chum (Mena Suvari) and Bening's bedding a realtor (Peter Gallagher), as Birch becomes involved with the "psycho next door" (Wes Bentley), who is - in turn - terrorized by his stern, abusive father (Chris Cooper). In this satiric, sophisticated social commentary, first-time screenwriter Alan Ball and first-time film director Sam Mendes (Broadway's "Cabaret," "The Blue Room") cinematically capture the hilarious, hedonistic, and heartbreaking desperation of a marital mid-life crisis and struggle in depth with the ironic definition of beauty. On the Granger Movie Gauge of 1 to 10, "American Beauty" is an amazing, powerfully disturbing 10, as it skewers the '90s. Let's talk Oscar nominations - this is one of the best pictures of the year!
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


Putrajaya Is Considering To Privatise Prisons To Ease Overcrowding In Govt Jails
The private prisons would house inmates who are sentenced for low-to-medium offences.
by Sadho RamCover image via JUICE Malaysia
With about 74,000 individuals currently detained at 38 prisons across the country, Malaysia's prisons are overcrowded, reported Bernama
The prisons only have the capacity to house 52,000 individuals, which makes the percentage currently at 40% overcapacity, according to the Bernama report on Saturday, 23 November.
The report was quoting Home Affairs Deputy Minister Mohd Azis Jamman, who said that the Government is considering to set up private prisons to solve the overcrowding problem in Malaysian jails
Azis Jamman said that the Ministry of Home Affairs has directed the Prisons Department to study the feasibility of establishing private penitentiaries and submit its findings to the Ministry.
"If the proposal paper prepared by the department is acceptable, Home Minister Tan Sri Muhyiddin Yassin will submit it to Cabinet for consideration," Bernama reported him as saying at the closing of a colloquium on prison modernisation held in Kajang on Friday, 22 November.
The Deputy Home Minister said that he recently had an opportunity to see the operations of a private prison during his working trip to Britain
According to him, such private prisons resulted in the government there not having to build new prisons.
"I have tasked the Prisons Department to look into the feasibility of having a similar concept in the country," Azis Jammam was quoted as saying by The Star yesterday.
"Maintaining and managing prisons is expensive as we also need to consider operational costs as well as the welfare of both staff members and inmates," he said, adding that the government has already implemented the parole and Compulsory Attendance Order systems to reduce overcrowding in prisons.
The private prisons, if proven to be a feasible solution, would house inmates who are being sentenced for low-to-medium offences
"Hopefully, this (concept) would help minimise overcrowding in our jails as well as the stress on government coffers," the Deputy Home Minister was quoted as saying by The Star.


{% extends "rpg/base.html" %} {% load static %} {% block content %}
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I'm familiar with C++,HTML5,CSS3,Git,Javascript, Repl.it and Web Hosting
I am a Coding Enthusiast gaining more knowledge into Development. I like to create memes.I love Joker as a character in a movie 'THE SUICIDE SQUAD'. I love spending half an hour of 24 hours in a gym.
I like to showcase my work and thus, you can see my projects hosted online .
I'm also writing some technical and non technical blogs. I like to document my journey of learning.


ML5 Projects
Image Classifier
WebCam Classification
Feature Extractor Classification
Feature Extractor Regression
P5 + ML5 Cam Animation
Save Model
Load Model
Object Model Detection
Snake Game


About Me
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I need to work on my mental focus and to help myself by creating an environment that minimises/eliminates distractions.
I need to work on my time management skills.
I need to be patient, especially when reading online, and more disciplined and structured with my time.
My current thinking pattern is very critical of myself and ultimately quite negative.


{% extends "view/rootpage.html" %} {% block title %}Communicate{% endblock %} {% block content %}
Here you can get in touch with the people at your tournament
Everybody on the pre-registration list will receive your email
(One copy will also be sent to {{user.preferredEmail()}} for confirmation)
It's so annoying when you receive pointless emails. Please be nice to the people at your IV by checking these things are true before hitting send.


PG-13 | 2h 42min | Action , Adventure , Fantasy | 18 December 2009 (USA)
Story
When his brother is
killed in a robbery, paraplegic Marine
Jake Sully decides to take his place in a mission on the distant
world of Pandora. There he learns of greedy corporate figurehead
Parker Selfridge's intentions of driving off the native humanoid
"Na'vi" in order to mine for the precious material scattered
throughout their rich woodland. In exchange for the spinal
surgery that will fix his legs, Jake gathers intel for the
cooperating military unit spearheaded by gung-ho Colonel
Quaritch, while simultaneously attempting to infiltrate the
Na'vi people with the use of an "avatar" identity. While Jake
begins to bond with the native tribe and quickly falls in love
with the beautiful alien Neytiri, the restless Colonel moves
forward with his ruthless extermination tactics, forcing the
soldier to take a stand - and fight back in an epic battle for
the fate of Pandora.


{% extends "base.html" %} {% block head_title %}Dashboard{% endblock %} {% block extra_head %}{% endblock %} {% block content %}
Welcome {{ request.user.customer.nickname }}!
Your collection point is {{ collection_point.name }} {% if skipped %} but your next collection is skipped so there is nothing for you to pick up {{ collection_date }}.
{% else %} and your next collection is {{ collection_date }}.Please check the opening days and hours of your collection point before collecting your order.
{% endif %}Any changes you make until {{ deadline }} will affect {{ changes_affect }}


Performs joint selection in Generalized Linear Mixed Models (GLMMs) using penalized likelihood methods. Specifically, the Penalized Quasi-Likelihood (PQL) is used as a loss function, and penalties are then augmented to perform simultaneous fixed and random effects selection. Regularized PQL avoids the need for integration (or approximations such as the Laplace's method) during the estimation process, and so the full solution path for model selection can be constructed relatively quickly.
| Version: | 0.7 |
| Imports: | gamlss.dist, lme4, Matrix, MASS, mvtnorm, Rcpp |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | nlme |
| Published: | 2018-12-05 |
| Author: | Francis K.C. Hui, with contributions from Samuel Mueller and A.H. Welsh |
| Maintainer: | Francis Hui <fhui28 at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| Citation: | rpql citation info |
| CRAN checks: | rpql results |
| Reference manual: | rpql.pdf |
| Package source: | rpql_0.7.tar.gz |
| Windows binaries: | r-devel: rpql_0.7.zip, r-release: rpql_0.7.zip, r-oldrel: rpql_0.7.zip |
| OS X binaries: | r-release: rpql_0.7.tgz, r-oldrel: rpql_0.7.tgz |
| Old sources: | rpql archive |
Please use the canonical form https://CRAN.R-project.org/package=rpql to link to this page.


LAST ACTION HERO A film review by James Berardinelli Copyright 1993 James Berardinelli
Rating: 7.6 out of 10 (B, **1/2 out of ****)
Date Released: 6/18/93 Running Length: 2:10 Rated: PG-13 (Violence)
Starring: Arnold Schwarzenegger, Austin O'Brien, Charles Dance, Anthony Quinn, F. Murray Abraham, Art Carney, Mercedes Reuhl Director: John McTiernan Producers: Steve Roth and John McTiernan Screenplay: Shane Black and David Arnott based on a story by Zak Penn and Adam Leff Music: Michael Kamen Released by Columbia Pictures
Danny (Austin O'Brien) is addicted to Jack Slater (Arnold Schwarzenegger) movies. He's seen the third one six times and now he's eagerly awaiting the released of JACK SLATER IV. When his elderly friend Nick (Robert Prosky), the projectionist at a run-down theater, tells Danny that he can sneak him in for an advance screening of the new flick, the kid is excited. The next day, when he arrives at the appointed hour (midnight, when all strange things happen), Nick lets him in and presents him with a "magic" ticket. There's a long story that goes with this, the gist of which is that the ticket purportedly has the ability to transport its user to other worlds, but it has a "mind of its own". Soon after Danny sits down to enjoy the movie, he discovers exactly what Nick meant by that phrase. The seat in the safe comfort of the theater suddenly becomes the floor of Jack Slater's car. Danny is no longer watching the movie--he's in it.
The critics have panned LAST ACTION HERO and, given my propensity for blasting anything that bills Arnold Schwarzenegger as its main attraction, one might assume that I didn't enjoy it either. Not so. While LAST ACTION HERO certainly isn't the banner movie of the summer, it's not nearly as horrible as most of the radio/TV/print reviewers would like you to believe.
Admittedly, this is not a good action film. Given its billing, director, and title, that's a surprise. On the other hand, LAST ACTION HERO works as an unexpectedly witty comedy. In fact, I found this movie to be more amusing (not to mention more watchable) than Schwarzenegger's two openly billed comic entries, TWINS and KINDERGARTEN COP.
The humor ranges from that staple of the action genre--bad puns--to some pretty incisive satire. Even though this next assertion is going to cause a lot of people to cringe, I'll make it anyway. I can find a number of similarities between LAST ACTION HERO and (believe it or not) Robert Altman's THE PLAYER. No, this isn't nearly as nasty or intelligent a picture as the Spring 1992 release, but both movies have a lot of fun blasting Hollywood genre films. Arnold's production may be more good-natured about it (after all, he's made his name and most of his fortune out of these kind of popcorn-and-soda movies), but there's no mistaking the intent. There's hardly a plot device of the action film that goes without some kind of dig. The car chase, the shoot-out, the exploding vehicles and houses, the death-defying jumps, the triumph over impossible odds, the last-second escape--all of these, and more, get lampooned in LAST ACTION HERO.
On the other hand, there is fundamental problem in the movie--the action sequences, which are numerous, are not exciting. Sure, they're directed with flair and energy, but the certain knowledge that nothing remotely bad is going to happen to Arnold or his pint-sized sidekick takes away any possible suspense. McTiernan has given us a lot of flashes and bangs, but, aside from the laughs generated by the parodies, there isn't much for us to sink our teeth into. The pulse-pounding, sizzling pull of a DIE HARD is absent.
Plot problems abound, but at least the story is more coherent than CLIFFHANGER. Since it's a fantasy, a great deal (such as the horrible plot device of the ticket) can be forgiven, although there are several instances where LAST ACTION HERO violates its own terms for inner consistency. Some of the things that go on in JACK SLATER IV, a live-action cartoon, are enjoyable.  However, before the setting switches to the "real world", the pacing becomes sluggish. Once the freshness of the satire has worn off, everything becomes routine.
Back in New York, things get revitalized for a while. We get to see Arnold play himself as something of a shallow, media hog who is pushed around by his wife (Maria Shriver, playing herself). It's to Schwarzenegger's credit that he doesn't shrink away from self-mockery. In fact, given the opportunity, he launches himself whole-heartedly into it.
 By the last fifteen minutes, the uniqueness and fun have all drained away, and there's nothing in the climax to liven things up. Perhaps if the villains (a one-eyed sharpshooter named Benedict, played by Charles Dance, and a homicidal lunatic called only "The Slasher", played by Tom Noonan) had been more charismatic, the usual end-of-the-film heroics would have been enjoyable, but these are not the kind of bad guys that the audience can really enjoy hating. This is especially disappointing, since McTiernan directed Alan Rickman's standout performance as the slick-tongued, despicable nasty in DIE HARD.
There's also an interesting plot thread that's not developed at all. Using the magic ticket, it's possible to bring any screen character to life in the real world. Imagine what the film could have been like with Draculas, Terminators, and all sorts of other unworldly creatures roaming around. Alas, the device is hardly used.
As with THE PLAYER (and a number of other recent movies), cameos abound. The likes of James Belushi, Sharon Stone, Hammer, and Jean-Claude Van Damme make appearances. There are also countless references and homages to movies both old and new. The best wedding of a tribute with a cameo involves Joan Plowright, the widow of the late Laurence Olivier. As a school-teacher introducing her class to a clip from Olivier's HAMLET, the eminent British actress tells the students that they might recognize Olivier from CLASH OF THE TITANS.
Also notable in the area of takeoffs is Schwarzenegger's portrayal of a gun-toting Hamlet, although most of this sequence has been shown in the previews, so there's little new for theatrical viewing. There's also a running gag involving the line "I'll be back" but, again, the key scene is in the trailers and TV ads.
As usual, Arnold is far more impressive as a screen presence than an actor. He has a certain style that lends itself to action and comedy. On those rare occasions when he's forced to do a straight, semi-dramatic scene (such as when Slater recalls a rooftop tragedy that happened in his past), Schwarzenegger's performance comes across with a dull thud. Please don't let anyone risk putting this man in a serious movie!
The musical score by Michael Kamen, which consists primarily of a lot of loud hard rock combined with a few bars of classical, is far too intrusive. For the most part, music, much like camerawork, should be a background element in a movie. In LAST ACTION HERO, it's very much in the foreground.
Kids will like this movie. While it's true that there's a lot of violence in LAST ACTION HERO, none of it is graphic. The explosions, gunplay, and killings are no more extreme than anything shown on a violent television cops-and-robbers show. Unlike JURASSIC PARK, there's nothing here that's likely to cause nightmares for anyone over the age of eight (or thereabouts).
Maybe LAST ACTION HERO won't be able to top JURASSIC PARK at the box office, but I don't expect it to be a disaster, either. For my money, this movie is one of Arnold's better recent offerings (With the possible exception of TOTAL RECALL, about which I have mixed feelings, I haven't been enamored with much of what he's done since the original TERMINATOR). Comparisons to HUDSON HAWK are undeserved. The same tongue-in-cheek style is evident, but this is a vastly superior effort.
LAST ACTION HERO is a fun movie, and most of Arnold's large legion of fans will be pleased by what he's given them. The number of people who hate this film will probably be dwarfed by those who enjoy it, and critical opinion rarely makes much difference with this sort of picture. No one is going to call LAST ACTION HERO a great film, but it provides a decent two hours worth of entertainment (it's about ten to fifteen minutes too long), and that's a lot better than many of 1993's offerings.
- James Berardinelli<EMAIL_ADDRESS>.
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


--- layout: default nav: attributes > ic-style-src ---
ic-style-src
- The Style Source AttributeThe ic-style-src
attribute binds a given HTML element's style attribute to a URL. It does not cause any
requests to happen by itself, but it can respond to events caused by other attributes.
When Intercooler issues a request for an element with an ic-style-src
, it will issue a GET
and will replace the current element's style value with resulting text fragment.
The value of the attribute should be a valid style attribute name, followed by a colon, then a valid relative
path
(e.g. ic-style-src="color:/foo/bar"
).
ic-style-src
implies a mutation to any dependency on its path, and Intercooler will issue
GET
requests for elements that depend on that path after the POST
completes.
See Dependencies for more information.
Here is a simple example, using a poll interval to update:

I'm turning red!


Home making dinner, cleaning up a bit and taking out the garbage. Domestic life at its finest.
11/3/2008, 7:02:22 PM
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link--- layout: tweet ---
Home making dinner, cleaning up a bit and taking out the garbage. Domestic life at its finest.
11/3/2008, 7:02:22 PM
Favs: 0
Retweets: 0
link


| 067:028 Khan | : |
Say (O Muhammad SAW): "Tell me! If Allah destroys me, and those with me, or He bestows His Mercy on us, - who can save the disbelievers from a painful torment?" |
| 067:028 Maulana | : |
Say: Have you considered if Allah should destroy me and those with me -- rather He will have mercy on us -- yet who will protect the disbelievers from a painful chastisement? |
| 067:028 Pickthal | : |
Say (O Muhammad): Have ye thought: Whether Allah causeth me (Muhammad) and those with me to perish or hath mercy on us, still, who will protect the disbelievers from a painful doom? |
| 067:028 Rashad | : |
Say, "Whether GOD decides to annihilate me and those with me, or to shower us with His mercy, who is there to protect the disbelievers from a painful retribution?" |
| 067:028 Sarwar | : |
(Muhammad), say, "Have you not considered that regardless whether God forgives me and my followers or grants us mercy, but who will protect the disbelievers from a painful torment?. |
| 067:028 Shakir | : |
Say: Have you considered if Allah should destroy me and those with me-- rather He will have mercy on us; yet who will protect the unbelievers from a painful punishment? |
| 067:028 Sherali | : |
Say, Tell me, if ALLAH should destroy me and those who are with me, or have mercy upon us, who will protect the disbelievers from a painful torment?' |
| 067:028 Yusufali | : |
Say: "See ye?- If Allah were to destroy me, and those with me, or if He bestows His Mercy on us,- yet who can deliver the Unbelievers from a grievous Penalty?" |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > تقريع من لا يقر بوحدانيته سبحانه Pillars of Islam> Islamic> Oneness of Allah>Scolding who does not Acknowledge his Glory Oneness أركان الإسلام > التوحيد > الكافرون > صفات الكفار Pillars of Islam> Islamic> The Disbelievers> The Characteristics of the Disbelievers
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


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{% load contains %}
| {# This is a very ugly construction to change 'endpoint' into 'health outcome'. If you have a better solution, be my guest #} {% if field.label == 'Endpoint' %} Health outcome {% else %} {{ field.label }} {% endif %} | {{ field.value }} |
| {# This is a very ugly construction to change 'endpoint' into 'health outcome'. If you have a better solution, be my guest #} {% if field.label == 'Endpoint' %} Health outcome {% else %} {{ field.label }} {% endif %} | {{ field.value }} |


There are several things I can do and it's going to be a huge adventure to describe all of that to you. On the other hand I might just tell you to believe me that I'm awesome. That's it! I'm just awesome!
You wouldn't believe me if I tell you what kind of skills I have so I will just list some random staff.
If you dare! Here is some random site to make you happy: GitHub project


Multivariate fine mapping to identify target genes
Table of Contents
Introduction
One of the key challenges in interpreting non-coding variation is linking regulatory variants to their target genes. One natural approach to solve this problem is QTL mapping: directly associating genetic variation with gene expression levels. QTL studies have revealed that genetic variants associated with expression of a gene cluster near the transcription start site of that gene (Veyrieras et al. 2008, Dimas et al. 2009, Stranger et al. 2012). Large scale efforts such as the Gene Tissue Expression Project (GTEx) have systematically profiled gene expression across cell types, and sought to use the insights from QTL mapping to make progress on interrogating the genetic basis of disease (GTEx consortium 2017).
However, recent efforts to experimentally fine map GWAS loci have shown that causal non-coding variants can be more than 1 megabase from their target gene, and may not even target the closest gene (Musunru et al 2010, Claussnitzer et al. 2015, Wang et al 2016). Further, enhancer-gene interactions have been shown to be limited by topologically associated domain boundaries, rather than genomic distance (Lupiáñes et al. 2015). These handful of examples are supported by systematic profiling of chromatin interactions (Zhang et al. 2013) and high throughput perturbation assays (Fulco et al. 2016).
Here, we develop a new method to fine map QTLs which does not assume that SNPs target the nearest gene, or are within 1 MB of their target gene. The key idea of our approach is to develop a novel multivariate fine mapping approach under the prior assumption that any single SNP can have a non-zero effect on at most one phenotype.
Methods
Two step fine-mapping approach
Suppose we assume a generative model with exactly one causal variant, denoted single effect regression (SER):
\[ \mathbf{y} = \mathbf{X b} + \mathbf{e} \]
\[ b = \mathbf{z} \beta \]
\[ \mathbf{z} \sim \mathrm{Mult}(1, \mathbf{\pi}) \]
Then, posterior computations are easy:
\[ \mathbf{z} \mid \mathbf{X}, \mathbf{y} \sim \mathrm{Mult}(1, \mathbf{\alpha}) \]
\[ \alpha_j = \frac{\pi_j BF_j}{\sum_k \pi_k BF_k} \]
To allow more than one causal variant, a typical approach is to change the prior, factorizing \(\gamma_1, \ldots, \gamma_p\). In susie, we take a different approach:
\[ \mathbf{y} = \sum_l \mathbf{X} \mathbf{b}_l + \mathbf{e} \]
\[ b = \mathbf{z}_l \beta_l \]
In this approach, \(\mathbf{z_l}\) does not factorize, and the posterior distribution reflects dependencies between the different variables.
This model can be efficiently fit using variational inference, for which the updates outline a Bayesian analogue of stepwise regression.
To generalize SER to multivariate single effect regression (MSER), we need to assume a multivariate prior on \(\beta\):
\[ \mathbf{y}_k = \mathbf{X} \mathbf{b}_k + \mathbf{e} \]
\[ \mathbf{b}_k = \mathbf{z}_k \beta_k \]
\[ \mathbf{\beta} \sim g(\cdot) \]
If we assume \(\beta \sim \mathcal{N}(0, \tau^{-1} \mathbf{I})\), then we get \(K\) independent SER problems. We can generalize MSER to multiviarate susie by assuming multiple independent effects as above.
Now, we want to incorporate a further constraint, that each SNP can only be causal for one phenotype. Suppose we fit multivariate susie on a genomic region with \(K\) genes. For SNP \(j\), gene \(k\), we estimate \(\lambda_{kj} = \mathrm{logit}(p(z_{kj} = 1 \mid \mathbf{X}, \mathbf{Y}))\).
Fix SNP \(j\) and consider \(\lambda_{j} = (\lambda_{1j}, \ldots, \lambda_{Kj})\). If only one entry of \(\lambda_j\) is non-trivial, it clearly satisfies the constraint.
If more than one entry is, then we need to solve a sparse recovery problem: we need to infer which of the signals is truly non-zero. Intuitively, having solved this problem, we should go back and refine the solution to the multivariate fine mapping.
def susie_mg(X, Y, **kwargs): pip = [] for y in Y.T: res = susier.susie(X, y.reshape(-1, 1), **kwargs) pip.append(np.array(susier.susie_get_PIP(res))) return np.array(pip)
EP approach
In SER, for each phenotype, we encoded the constraint that a single variant is causal by assuming the prior \(\mathbf{z} \sim \mathrm{Mult}(1, \mathbf{\pi})\).
Ideally, in the multivariate case we would encode the constraint that each SNP can only be causal for one phenotype in the same way. Suppose we only had two phenotypes, only two SNPs, and only one effect per phenotype. We need the following to hold simultaneously:
- \(z_{11}, z_{12} \sim \mathrm{Mult}(1, \mathbf{\pi}_a)\)
- \(z_{21}, z_{22} \sim \mathrm{Mult}(1, \mathbf{\pi}_a)\)
- \(z_{11}, z_{21} \sim \mathrm{Mult}(1, \mathbf{\pi}_b)\)
- \(z_{12}, z_{22} \sim \mathrm{Mult}(1, \mathbf{\pi}_b)\)
The resulting distribution on \(\mathbf{Z}\) is most readily expressed as a factor graph:
\[ p(\mathbf{Z} \mid \cdot) \propto \prod_j f_j(z_{1j}, z_{2j}) \prod_k g_k(z_{k1}, z_{k2}) \]
The remainder of the model is easily converted into a factor graph:
\[ p(\cdot) \propto \prod_k p(Y_k \mid X_k, B_k, \tau) p(B \mid Z, \tau_0) p(Z \mid \pi_a, \pi_b) \]
We use expectation propagation to perform approximate inference on this model (Minka 2001, Hernández-Lobato et al 2015).
Results
Toy examples
Consider just two genes, and two SNPs. For simplicity, generate bivariate normal “genotypes”:
\[ \left[\begin{array}{l}x_{i1}\\x_{i2}\end{array}\right] \sim \mathcal{N}\left(\mathbf{0}, \left[\begin{array}{ll} 1 &\rho\\ \rho & 1\end{array}\right]\right) \]
\[ y_{i1} = x_{i1} \beta_1 + e_{i1} \]
\[ y_{i2} = x_{i2} \beta_2 + e_{i2} \]
def simulate_ser_y(x, pve): n = x.shape[0] beta = np.random.normal() y = x * beta y += np.random.normal(scale=np.sqrt(y.var() * (1 / pve - 1)), size=n) y -= y.mean(axis=0) return y def simulate_ex1(rho, n, pve=0.1, seed=0): np.random.seed(seed) cov = np.array([[1, rho], [rho, 1]]) x = np.random.multivariate_normal(mean=np.zeros(2), cov=cov, size=n) y1 = simulate_ser_y(x[:,0], pve) y2 = simulate_ser_y(x[:,1], pve) x -= x.mean(axis=0) return x, np.vstack([y1, y2]).T
When genotypes are uncorrelated, we should expect susie to exactly recover the causal SNP for each gene, and conversely the target gene for each SNP.
X, Y = simulate_ex1(rho=0, n=100) susie_mg(X, Y, L=1)
array([[0.97088521, 0.02911479], [0.04866922, 0.95133078]])
When genotypes are nearly perfectly correlated, the expression will become nearly perfectly correlated. We should expect susie to put equal posterior probability on each SNP, and therefore be unable to find the target gene.
X, Y = simulate_ex1(rho=0.99, n=100) susie_mg(X, Y, L=1)
array([[0.37021302, 0.62978698], [0.6153817 , 0.3846183 ]])
Surprisingly, susie simply gives the wrong answer in this case. Look at the distribution of \(p(z_{11} \mid \cdot)\) over many trials.
def get_pip_11(**kwargs): X, Y = simulate_ex1(**kwargs) res = susie_mg(X, Y, L=1) return res[0, 0]
data = [get_pip_11(rho=0.99, n=100, seed=i) for i in range(100)] plt.clf() plt.gcf().set_size_inches(3, 3) f = st.gaussian_kde(data) grid = np.linspace(0, 1, 1000) plt.plot(grid, f(grid), c='k', lw=1) plt.xlabel('PIP of SNP 1 on gene 1') _ = plt.ylabel('Density')
Fixing \(\rho\), as the number of samples \(n\) increases, susie gets the correct answer on average, but there is still considerable variation.
pip_vs_n = pd.DataFrame([(int(n), i, get_pip_11(rho=0.99, n=int(n), seed=i)) for i in range(50) for n in np.logspace(2, 4, 100)], columns=['n', 'trial', 'pip_11'])
plt.clf() plt.gcf().set_size_inches(3, 3) plt.semilogx() plt.ylim(0, 1) plt.axhline(y=0.5, c='0.5', lw=1, ls='--') m = pip_vs_n.groupby('n')['pip_11'].agg(np.mean) s = pip_vs_n.groupby('n')['pip_11'].agg(np.std) plt.plot(np.logspace(2, 4, 100), m, lw=1, c='k') plt.fill_between(np.logspace(2, 4, 100), m - 1.96 * s, m + 1.96 * s, color='k', alpha=0.1) plt.xlabel('Sample size') _ = plt.ylabel('PIP of SNP 1 on gene 1')
Now, consider the case of uncorrelated genotypes, but correlated expression. The only way this can arise is if some unobserved factor influences both genes.
\[ \mathbf{X}_i \sim \mathcal{N}(\mathbf{0}, \mathbf{I}) \]
\[ u_i \sim \mathcal{N}(0, \sigma^2_u) \]
\[ \beta_k \sim \mathcal{N}(0, \sigma^2_g) \]
\[ \mathbf{Y} = \mathbf{X}\beta + \left[\mathbf{u}\ \mathbf{u}\right] + \mathbf{E} \]
def simulate_ser_u_y(x, u, pve_x, pve_u): n = x.shape[0] beta = np.random.normal(scale=np.sqrt(pve_x / x.var())) y = x * beta + u y += np.random.normal(scale=np.sqrt(y.var() * (1 / (pve_x + pve_u) - 1)), size=n) y -= y.mean(axis=0) return y def simulate_ex2(n, pve_x=0.1, pve_u=0.1, seed=0): np.random.seed(seed) x = np.random.multivariate_normal(mean=np.zeros(2), cov=np.eye(2), size=n) u = np.random.normal(scale=np.sqrt(pve_u), size=n) y1 = simulate_ser_u_y(x[:,0], u, pve_x, pve_u) y2 = simulate_ser_u_y(x[:,1], u, pve_x, pve_u) x -= x.mean(axis=0) return x, np.vstack([y1, y2]).T
X, Y = simulate_ex2(n=100, pve_x=.05, pve_u=.9) susie_mg(X, Y, L=1)
array([[0.92064932, 0.07935068], [0.0102968 , 0.9897032 ]])
np.corrcoef(Y.T)
array([[1. , 0.8488416], [0.8488416, 1. ]])
Even when expression is highly correlated due to some unobserved factor (e.g., trans-QTL), susie can still recover the cis-eQTLs.
Overall, the results suggest that simply applying univariate susie over large windows will get the correct answer whenever it is possible to get the correct answer.


static: stat·ic | ˈsta-tik
- adj. showing little change
- n. noise produced on a radio or television by natural or man-made electrical disturbances
- n. heated opposition or criticism
Still here?
We want simple data and definitions; it helps mitigate the burden of complex decision making while building our perception of the world. Most people will leave after parsing the info above. If we see possible complexity in the data, our tendency is to focus on the familiar variables so it all fits into neat little boxes that are comfortable to us.
Let’s challenge this.
Dialogue
This web space will take on the form of a dialogic. What is a dialogic you ask? Simply put, it is an exploration of meaning through dialogue. It is NOT an attempt to hear all side and then form a compromise. A compromise may or may not exist; the solution may even be apparent. In the dialogic, answers come only as existential solutions, when they come at all.
This doesn’t mean I don’t bring biases or opinions. I got opinions! Some of them are core to my identity and I will likely not budge on them. The success of this dialogic will be measured by your uncertainty about my position. If I am not presenting the strongest of all perspectives, then YOU need to hold me accountable, because ultimately, this space fails.
In the same most of our public discourse is failing.
Part of the desire to construct a dialogue in this space was the consistent frustration I experience while looking for honest and valuable public discourse on the web. If our once trusted sources of information are not presenting an honest discussion, then I will just do it myself!
My main goal in starting with data and a definition is not to shame my readers into sticking around. Instead, I want to present myself clearly so I can be held accountable. There is nothing untrue about what you see listed above. My hope with this space is that through empathetic discourse, we can avoid attempts to filter others through simple formulas that very clearly result in errors.
Harmony
…and I will also discuss music I’m listening to. Because I like music. And dancing together takes the edge off.


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{% extends "layout_renew_licence.html" %} {% block page_title %} Example - Forms {% endblock %} {% block content %} {{formData | safe}} Licence your want to renew Licence number For example, '345 612 895'. Help finding licence number Your fishing licence number is 18 digits long and can found in any email, text message or letter about your fishing licence. {% endblock %}
Your fishing licence number is 18 digits long and can found in any email, text message or letter about your fishing licence.


clustalw2phylip [options] <alignment file>
This program converts a multiple alignment in ClustalW format into a PHYLIP file.
The name of a file containing one or more aligned sequences in ClustalW format.
The program prints to standard output each of the sequences in the multiple alignment, in PHYLIP format.
No optional arguments.


Accessibility Conformance Reporting Tool (ACRT)
Version 1.1.2
an open source tool
developed by the U.S. Department of Homeland Security
to track testing results from the
Section 508 Conformance Test process
Developed for use in Chrome, Edge and Firefox
For the latest version of the ACRT and support files, all users please visit ACRT GitHub Repository
DHS Employees can also visit ACRT BitBucket Repository


If you have any questions about supporting the Professional Lifeguard Foundation, or if you would like to contribute in another way, please contact us by emailing us at<EMAIL_ADDRESS>The Professional Lifeguard Foundation is a non-profit organization, founded
in 1996, which provides scholarship awards to Los Angeles County Lifeguards who are enrolled in full-time college or graduate course work.
The Professional Lifeguard Foundation needs your help to continue to support as many scholarships as possible. Donations are of enormous assistance to these dedicated young men and women.


US House Democrat accuses Trump of violating oath of office
WASHINGTON, Dec 9 — The head of a US congressional panel leading the impeachment inquiry against President Donald Trump today accused him of putting himself before his country and violating his oath of office.
In a statement kicking off a hearing in the US House of Representatives to weigh the evidence against Trump, Judiciary Committee Chairman Jerrold Nadler said there was extensive proof of wrongdoing.
“The evidence shows that Donald J. Trump, the president of the United States, has put himself before his country. He has violated his most basic responsibilities to the people. He has broken his oath,” Nadler said. “I will honor mine.”
The hearing today is a key step before determining charges, known as articles of impeachment, that the full House is likely to vote on before Christmas.
The heart of the issue is whether Trump abused power by pressuring Ukraine to investigate former Vice President Joe Biden, a political rival seeking the Democratic nomination to face the Republican president in the 2020 election.
Trump denies any wrongdoing. — Reuters


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The KDS Dream Team Members
Manager Employee Name
Manager
ID: 1
<EMAIL_ADDRESS>Intern Employee Name
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Employee Name
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<EMAIL_ADDRESS>Employee Name
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<EMAIL_ADDRESS>The Best of Employee Contact Info
They are working on some great projects! Be sure to checkout out their work!
KDS Dream Tech is a dream of an aspiring full stack web developer. It started with a simple google search in October of 2019 and now with John's Hopkins University's Full Stack Web Developer Bootcamp, the sky is the limit. We are literally dreaming in the clouds!
Contact us via email, phone, or Linked In
You can find KDS Dream Tech Projects on Github.


GrayMail allows two peers to send encrypted messages using WebRTC Data Connections. It provides end-to-end encryption using AES-GCM-128. One user will access the chat client. They will be redirected to a chat room with a specific id number. They should copy this link and send it to the person that they want to chat with using some other chat mechanism such as gchat or facebook chat. Each user can enter a username (their messages will be displayed as coming from this name) and a password. This password serves to authenticate the users to each other. If two people who want to communicate enter the same chat room but use different passwords, they will be unable to communicate. These passwords are NOT required.
As of 8/14/2013, Google Chrome and Mozilla Firefox are supported.
As of 9/18/2013, Mac OS X 10.7.5 and Ubuntu 12.04-64 bit are supported and tested, but other versions should work.
Each user of Graymail must use the same browser.
As of 8/14/2013, Firefox and Chrome implement different versions of the signaling protocol required for WebRTC DataConnections, which is why the same browser must be used at each client end. Different versions of each browser should work, assuming that WebRTC is enabled and supported in the specific version.
GrayMail uses Polycrypt which implements a recent draft of the Web Crypto API specification (early Summer, 2013). More recently, Netflix developed nfCrypto which implements the same spec. Graymail automatically detects if nfCrypto is installed and will seamlessly switch to using this API for some of the cryptographic operations required for the client. If nfCrypto is not detected, the application will use Polycrypt for all operations. Please read up on Polycrypt for more information and remember that there are serious issue with using pure JavaScript libraries to perform crypto on the web.
To use Graymail with nfCrypto:
As of 9/25/13, there is a small chance that two clients cannot connect via WebRTC. This is most likely due to the fact that when messages are queued in the DB, the CGI script will send these messages to the client and then remove those messages from the DB. However, after the queued messages are read but before sent out, the client may have sent another message to the server and inserted into the DB. Precisely then, the DB sends out the messages (does not include the new one) and deletes the saved messages (includes the new one), so the new message is never received by the other peer.
Optional pre-shared secret. If none specified, use default value.
Client 1 --> ephemeral RSA public key 1 --> Client 2
Client 1 <-- ephemeral RSA public key 2 <-- Client 2
Clients generate random 32-bit nonces.
Client 1 --> PUB_ENC_CLIENT2RSA(nonce1) --> Client 2
Client 1 <-- PUB_ENC_CLIENT1RSA(nonce2) <-- Client 2
Clients decrypt the received nonces.
Clients generate a shared symmetric AES-GCM key:
Key K = PBKDF2(secret, SHA1(nonce1) ^ SHA1(nonce2), 2048)
Ephemeral keys provide forward secrecy.
Pre-shared secret used for authentication.
A malicious client can wait to receive a hashed nonce from the other peer, and send back that exact hashed nonce so
SHA1(nonce1) ^ SHA1(nonce2) = 0x0...0
This is taken care of by making sure that
SHA1(nonce1) != SHA1(nonce2)
If this happens, the client will "self destruct" and delete almost all objects required for communication and immediately alerts the user. The odds of this accidentally happening are negligibly small.
Encrypted Message Transmission Format =
B64(IV) : B64(AES-GCM cipher output) : B64(additionalData)
chat.html
--> HTML / CSS / JavaScript to handle the user-client interactionschat.py
--> Python CGI to let users create and join roomsdbparams.py
--> KEEP THIS SECRET! Contains your MySQL login information
js/adapter.js
--> Google code to handle WebRTC variable renaming conventions between Firefox and Chromejs/rtc2.js
--> sets up the WebRTC connection and handles cryptographic operationsjs/nf/nfcrypto.js
--> loads the Netflix Crypto wrappersjs/nf/nfutil.js
--> loads the Netflix Crypto utility libraryjs/polycrypt/*
--> all necessary APIs for Polycrypt to function
py/dbparams.py
--> KEEP THIS SECRET! Contains your MySQL login informationpy/index.html
--> Default page to stop users from exploring your directorypy/logout.py
--> Logs a user out of the chat service (removes their rows from the DB)py/message.py
--> Used to send messages from the server to the client (webrtc information)py/update.py
--> Used to send messages from the client to the server (webrtc information)
util/reset.py
--> KEEP THIS SECRET! Empty all tables in the DButil/reset.sh
--> KEEP THIS SECRET! Shell script used by the cron job to reset the tablesutil/resetcron.txt
--> KEEP THIS SECRET! The cron job to register with crontabutil/setup.py
--> KEEP THIS SECRET! Setup the tables for the server
license.txt
, chat.html
, chat.py
, js/*
, py/*
, util/*
)dbparams.py
to include your MySQL server address, username, password and DB name. There are two of these files.../util/setup.py
to create the appropriate database tables../util/resetcron.txt
--> Cleans up the databasehttp://www.your-web-server.com/chat.py


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Hi {{ name }},
Thank you for registering with us! Here are some instructions to keep in mind before proceeding for the interviews -
- This mail is to notify you about the date, day and time of your interview(s)
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DIS - Define Initial capacity for StringBuffer.
The 'StringBuffer' constructor will create a character array of a default size, typically 16. If StringBuffer exceeds it's capacity, StringBuffer has to allocate a new character array with a larger capacity, copy the old contents into the new array, and eventually discard the old array. In many situations you can tell in advance how big your StringBuffer is likely to be. In that case, reserve enough capacity during construction and prevent the StringBuffer from ever needing expansion.
Wrong
void oper () {
StringBuffer buffer = new StringBuffer();
buffer.append ("hello");
}
}
Tip: Provide initial capacity for StringBuffer.
Right
void oper () {
StringBuffer buffer = new StringBuffer(MAX);
buffer.append ("hello");
}
private final int MAX = 100;
}
REFERENCE
Dov Bulka, "Java Performance and Scalability Volume 1: Server-Side Programming
Techniques"
Addison Wesley, ISBN: 0-201-70429-3 p.30 - 31


- Breakfast
- Pancakes
- Waffles
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- Lunch
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- Pasta with:
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