name: inverse layout: true class: center, middle, inverse --- #Publicity and the Delegitimation of Lynching Michael Weaver Yale University March 12, 2016 --- -- ##Societies accept or tolerate some forms of violence while rejecting others. --- -- ##How does violence become publicly unacceptable? --- ##Lynching in the United States --- template:inverse ###Rebecca Felton, suffragette:
--- template:inverse
--- template:inverse
*New York Times*. 5/7/1886 --- template:inverse
--- template:inverse
*The Chillicothe Constitution-Tribune* 1/15/1931 --- template:inverse ##How did this transformation take place? -- ##How does violence move from acceptable to unacceptable? --- layout:false .left-column[ ##Outline ] .right-column[ ### Publicity Shocks ### Historical big data ### Communication Technology ### Next steps ] --- template:inverse ##Publicity Shocks --- .left-column[ ##Argument ###Publicity ] .right-column[ ### Reach * Geographic scope of audience * Local justification for violence * New audiences => different interpretations * New critics => cannot be coerced ### Inclusivity * Inclusion of different voices * Perpetrators control narrative * Voice to victims => new narratives * 'Facts', justifications contested ] --- .left-column[ ##Argument ###Publicity ###Lynching] .right-column[ ###1. Increase in publicity * Technological change => greater reach * Social movements => inclusion of black voices ] --- .left-column[##Argument ###Publicity ###Lynching] .right-column[ ###1. Increase in publicity * Technological change => greater reach * Social movements => inclusion of black voices ###2. Publicity breeds criticism and scandal ] --- .left-column[##Argument ###Publicity ###Lynching] .right-column[ ###1. Increase in publicity * Technological change => greater reach * Social movements => inclusion of black voices ###2. Publicity breeds criticism and scandal ###3. Bad publicity turns Southern elites against lynching ] --- template:inverse
--- template:inverse
--- .left-column[##Argument ###Publicity ###Lynching] .right-column[ ###1. Increase in publicity * Technological change => greater reach * Social movements => inclusion of black voices ###2. Publicity breeds criticism and scandal ###3. Bad publicity turns Southern elites against lynching ###4. With opposition of local elites, lynching declines ] --- template:inverse
--- template:inverse #Part 1: ##Technology & Publicity --- .left-column[ ## Argument ###Publicity ] .right-column[ ###Turn of the century... saw massive expansion of - transportation networks (railroads) - communication networks (telegraph) - news services (e.g., Associated Press) ] --- template:inverse
--- class: center, middle
--- .left-column[ ## Argument ###Publicity ] .right-column[ ###Turn of the century... saw massive expansion of - transportation networks (railroads) - communication networks (telegraph) - news services (e.g., Associated Press) ... which made the country smaller - reduced travel times for people and information - created a public eager for national news ] ---
--- .left-column[ ## Argument ###Publicity ] .right-column[ ###Turn of the century... saw massive expansion of - transportation networks (railroads) - communication networks (telegraph) - news services (e.g., Associated Press) ... which made the country smaller - reduced travel times for people and information - created a public eager for national news ###Publicity of lynchings has greater reach ] --- .left-column[ ## Argument ###Publicity ###Criticism ] .right-column[ ###Wider public Breaking news of lynchings free from locality: 1. Loss of control over narrative 2. New audiences unsympathetic to lynchers 3. No ability to coerce critics Lynching events could become national scandals * Reputation costs motivated politicians, business owners, sheriffs ] --- .left-column[ ## Argument ###Publicity ###Criticism ###Implications ] .right-column[ ###Three implications Difficult to test directly The probability that a lynching is reported in a newspaper: 1. **increases** as distance **decreases** between the lynching and the paper. 2. **increases** as travel times **decrease** between the lynching and the paper. 3. **increases** when the lynching occurred in an area more **central in communication and transportation networks**. ] --- template:inverse ##How do we test this? --- template:inverse ##The data --- .left-column[ ##Data ###Newspapers ] .right-column[ ###"Big data" meets history Cornerstone of the project * Digitized historical newspapers * More than 3,000 different papers * Nation-wide coverage * Big-city dailies, small town weeklies * 8 million+ unique issues between 1880 and 1940 * Searchable content * 1.2 million articles mention "lynching" * Words/phrases for lynching discourse ] --- template:inverse ##Newspapers in sample over time
--- template:inverse
--- .left-column[ ##Data ###Newspapers ###Railroads ] .right-column[ ###Railroad networks * Yearly data from 1880 and 1900 (1911) * Period of rapid growth (more than doubles) * 3109 counties in continental US * Network centrality of counties * Travel time between counties ] --- class:center, middle
--- .left-column[ ##Data ###Newspapers ###Railroads ] .right-column[ ###Railroad networks * Yearly data from 1880 and 1900 * Period of rapid growth (more than doubles) * 3109 counties in continental US * Network centrality of counties * Travel time between counties * Railroad stations for each year between 1880 and 1910 * Proximity to rail stations ] --- template:inverse
--- .left-column[ ##Data ###Newspapers ###Railroads ###Lynchings ] .right-column[ ###Lynching events * Compiling best possible national lynching database * 1880 to 1940s * Sources: historians, NAACP, and Chicago Tribune. ] --- template:inverse ##The analysis --- .left-column[ ## Analysis ### Design ] .right-column[ ###Observations * Issues appearing within a week of a lynching * Issue-Lynching pairs ###Design * Panel analysis, multi-way clustering * Year, publication, lynching county fixed effects * Publication-county, lynching-county covariates (population, GDP) ] --- class: center, middle Probability of lynching mention by distance
--- class: center, middle ###Reductions in travel time almost ~~exactly~~ offset effects of distance -- Even when compared to roads, canal, and riverboats --- class: center, middle Probability of lynching mention by betweenness centrality
(deciles)
--- class: center, middle Probability of lynching mention by eigenvector centrality
(deciles)
--- class: center,middle Effects are not concentrated at close distances:
--- class: center,middle
--- .left-column[ ## Analysis ### Design ### Results ] .right-column[ ###Three implications The probability that a lynching is reported in a newspaper: 1. **increases** as distance **decreases** between the lynching and the paper. ![check][] 2. **increases** as travel times **decrease** between the lynching and the paper. ![check][] 3. **increases** when the lynching occurred in an area more **central in communication and transportation networks**. ![check][] ] [check]:http://servepapers247.com/wp-content/uploads/2013/05/Checkmark-Red.png --- template:inverse ##What's next? --- .left-column[ ##Next steps ###Criticism ] .right-column[ ###Does publicity produce criticism? * Measure criticism: keywords/phrases ![check][] * Is press coverage of lynching is more critical when the paper: 1. is at a greater distance 2. is in a place without a history or culture of lynching ] --- .left-column[ ##Next steps ###Criticism ###Lynchings ] .right-column[ ###Does criticism stop lynching? After lynching with public backlash: * Lynchings prevented ![check][] * Local elites argue against lynching (newspapers) * Proposed anti-lynching legislation ] --- .left-column[ ##Conclusion ###Relevance ] .right-column[ ###Scope * Violence is "local" * Power disparity * Perpetrators care about reputation * Who are their peers? * Economic/trade relations * Shared jurisdiction Processes of national integration ] --- .left-column[ ##Conclusion ###Relevance ] .right-column[ ###Publicity as mechanism Can it legitimate violence? ] --- template:inverse #Thank you --- template:inverse #Extra slides --- ##Equations ####Network centrality model `$$Y_{ijt} = \alpha_{year} + \alpha_{county i} + \alpha_{county j} + \boldsymbol{\beta}*\mathbf{CountyNetworkCentrality_{i}}$$` `$$ + \boldsymbol{\gamma}*\mathbf{Distance_{ijt}} + \varepsilon_{i} + \varepsilon_{j}$$` ####Travel time model `$$Y_{ijt} = \alpha_{year} + \alpha_{county i} + \alpha_{county j} + \beta_1*LandTravelTime$$` `$$ + \beta_2*RailTravelTime + \varepsilon_{i} + \varepsilon_{j}$$` --- class: center, middle Probability of lynching mention by distance (x) and travel time (y)
(darker = greater coverage)
--- template:inverse ## Social movements and inclusivity --- template:inverse
--- template:inverse
--- template:inverse
--- template:inverse
--- --- .left-column[ ## Analysis ### Design ### Results ### Limits ] .right-column[ ###Endogeneity * Network attributes not locally determined * Instrument: landgrant railways ###Alternative interpretations * Importance, not information * Population, economic output * Directly measure telegraph ###Text * Broad but limited depth * Keywords are simplification * Proquest ] --- .left-column[ ## Background ###Lynching ###Lynching discourse ] .right-column[ ###Arguments in favor * Inefficiency/corruption of justice system * Popular sovereignty * Law does not deter criminals * Threat of black criminality/sexuality * 'Natural' response to rape ] --- .left-column[ ## Background ###Lynching ###Lynching discourse ] .right-column[ ###Justificatory Narratives * Protagonists * Sober, rational, all/leading citizens of town * Passive voice: no individuals did the lynching * Lynching was natural/unavoidable response * Antagonists * Black men dehumanized: "savages", "brutes", "beasts" * Assumed to be guilty * By default shown as sexually aggressive, criminals * Lynched *because* guilty ] --- .left-column[ ## Background ###Lynching ###Lynching discourse ###Antilynching discourse ] .right-column[ ###Arguments Refuted pro-lynching claims * e.g. rape alleged in minority of cases * Lynching a threat to law and order * Lynching part of a system of racial violence * e.g. Du Bois: "The police is the mob. The courts are the lynchers." ###Narratives Black voices counter white narratives about lynching * NAACP investigations * Ida Wells publications * Scottsboro Trials ]


prtAction - Base class for many PRT components.
prtAction is an abstract class and cannot be instantiated.
Classification, regression and feature selection techniques are all
sub-classes of prtAction.
All prtAction objects have the following properties:
name - Descriptive name for prtAction object
nameAbbreviation - Shortened name for prtAction object
isTrained - Indicates whether the current prtAction
object has been trained
isCrossValidateValid - Flag indicating whether or not
cross-validation is a valid operation on
this prtAction object.
verboseStorage - Flag to allow or disallow verbose storage
dataSetSummary - A struct, set during training, containing
information about the training data set
dataSet - A prtDataSet, containing the training data,
only used if verboseStorage is true
userData - A struct containing user specified data
All prtAction objects have the following methods:
train - Train the prtAction object using a prtDataSet
run - Evaluate the prtAction object on a prtDataSet
runOnTrainingData - Evaluate the prtAction object on a prtDataSet
during training prior to training of other
prtActions within a prtAlgorithm
crossValidate - Cross-validate a prtAction object using a
labeled prtDataSet and cross-validation keys.
kfolds - K-folds cross-validate a prtAction object using
a labeled prtDataSet
optimize - Optimize the prtAction for a specified
parameter


This Example Health patient UI runs as a microservice on Kubernetes. The app was designed to be able to integrate with different kinds of back ends to demonstrate how flexible and versatile microservices can be in a few real world
situations.
By default the app just displays preformatted canned data responses in test mode. You can choose to integrate with either a cobol on Z deployment, or a Java Liberty on OpenShift deployment. These integrations are described in related code
patterns.


{% extends "layout.html" %} {% block content %}
Trips-viz is a (poor) acronym standing for TRanscriptome wide Information on Protein Synthesis VIZualized. This is mainly to match the naming of our sister site gwips-viz which provides Genome Wide Information on Protein Synthesis.
No. All features of Trips-viz can be used without an account. An account is only needed if you wish to change specific aspects of plots such as the background colour. An account is also needed to upload your own data, or to view private data uploaded by someone else.
Yes. To upload you need an account, then visit the upload link at the top of the page. This is split into 3 sections called "Upload new file", "My studies"
and "My files". The "Upload new file" section allows you to choose an organism, an assembly, a study name, and a sequence type. Once those are chosen you can click the
"Browse" button to choose a file to upload and then press the "Submit" button to upload the file. After the file has been uploaded you'll see the study appear in the
"My studies" section, where the organism, study name and assembly will be listed. There will also be a text box referred to as "Access list" where you can give other
Trips-Viz users access to your data. To do this, enter a list of usernames in the text box and press the "Update" button at the bottom of the page.
The "My files" section will also be populated after uploading a file. This will list the file name, the study name and a checkbox for each file. To delete files click the
checkboxes of the files you want to delete and press the "Delete files" button at the bottom of the page.
Note that any files uploaded to Trips-Viz need to be in a specific format (sqlite) and have the extension .sqlite. In order to create a file in that format you need to use
the "bam_to_sqlite.py" script, which can be gotten from the downloads page. You will also need to download a file called "transcriptomic_to_genomic.sqlite" and
"organism_name.sqlite" which can be downloaded from the same page. Then run the python 2 script as follows:
python bam_to_sqlite.py
Publicly available Ribo-Seq/mRNA-Seq data is downloaded from the ncbi sequence read archive. After which it is converted to fastq format and adapter is removed using cutadapt. Reads below 25 nucleotides in length after adapter removal are discarded. Reads are alinged to rRNA sequences using bowtie. Reads that map to rRNA are discarded while remaining reads are aligned to the transcriptome using bowtie. The resulting BAM file is parsed with a python script. Each mapped read is checked to see how many genomic positions it maps to, if only one the read is classed as unambiguous, if more than one it is classed as ambiguous. An offset is also determined for every read by choosing the highest peak near the start codon using the counts from the metagene profile.
Yes. This can potentially be done with any sequencing data that can be aligned to a transcriptome, but you will need to be somewhat familiar with python.The basic steps involve parsing a text file and placing the information in SQLite format. An example of a python script that can do this is provided on the downlods page which you can view by selecting "Scripts" under the group dropdown box and then "tsv_to_sqlite.py" in the file dropdown box. This can be easily modified to parse a csv file. The output will be in .sqlite format which you can then upload to Trips-Viz.
Yes. If you have a transcriptomic fasta file and a gtf file you can upload your own transcriptome to Trips-Viz. This can be done by first downloading the
scripts entitled "create_annotation_sqlite.py" and "create_transcriptomic_to_genomic_sqlite.py" from the downloads page (select the "Scripts" group).
Run the "create_annotation_sqlite.py" script as follows:
python create_annotation_sqlite.py <organism_name> <gtf_file_path> <fasta_file_path> <pseudo_utr_len>
where pseudo_utr_len is an integer which can be used to add a flanking region to all transcripts, which can be useful if UTR's are not annotated, set to
0 if UTR's are already annotated. This will produce a file named <organism_name>.sqlite then run the script "create_transcriptomic_to_genomic_sqlite.py" as follows:
python create_transcriptomic_to_genomic_sqlite.py <gtf_file_path> <pseudo_utr_len>
This will produce a file called "transcriptomic_to_genomic.sqlite" (this is needed for the bam_to_sqlite.py script). To upload your transcriptome go to the
uploads page, select the "Upload new transcriptome" tab. Fill in the required fields and upload the .sqlite file that was prouduced by the create_annotation_sqlite.py script.
A message will come up after a some time indicating a successful upload. Navigating back to the home page should show the newly uploaded organism
(this will only be visible by you), files can then be uploaded for that organism just like any other organism on Trips-Viz.
Previously uploaded transcriptomes can be deleted from the uploads page under the "My transcriptomes" tab.
Note the variables with labels such as "search_term_before_transcript" in the create_annotation_sqlite.py and create_transcriptomic_to_genomic_sqlite.py scripts may need to be
changed. This is because gtf files are not standardised so the scripts need to have the terms that appear immediately before and after the transcript and gene ids in the gtf file.
Here is an example of a line in a gtf file and what the corresponding variables should be set to:
gtf line:
chr1 HAVANA transcript 11869 14409 . + . gene_id "ENSG00000223972.5"; transcript_id "ENST00000456328.2"; gene_type "transcribed_unprocessed_pseudogene"; gene_status "KNOWN"; gene_name "DDX11L1"; transcript_type "processed_transcript"; transcript_status "KNOWN"; transcript_name "DDX11L1-002"; level 2; transcript_support_level "1"; tag "basic"; havana_gene "OTTHUMG00000000961.2"; havana_transcript "OTTHUMT00000362751.1";
variables:
search_term_before_transcript = 'transcript_id "'
search_term_after_transcript = '.'
search_term_before_gene_1 = 'gene_name "'
search_term_after_gene = '";'
The purpose of this plot is to allow you to see the ribosome profiling and rnaseq reads that align to an individual gene or transcript.
The ribosome profiling reads will be colour coded according to which frame the a-site is found in. If the triplet periodicity of the reads contributing
to the graph is strong then this plot should give a clear picture of which frame is being translated.
The page is split into three parts, at the top of the page you have general settings. Here you can choose settings like, the maximum triplet periodicity
score for each read, the gene you want to view, the minimum and maximum allowed readlengths and many other settings. To get a more detailed description
on any one of these settings simply click the link next to it labelled "(What's this?)", or you can view the explanations further down this page.
At the middle of the page you can select a sequence type. Then click on
one of the studies in the studies box. This will bring up a list of relavent files associated with that study in the "Files" section below. Next to each
file will be a circle. If the circle is filled in this means that reads from that file will be included in the graph. To turn on or off an individual file
simply click the circle next to the file name or the file name itself. As some studies can have many files associated with them, there are buttons in the
studies box that act as shortcuts.
There are 2 buttons in the "Studies" section to turn on/off all files currently in the "Files" section, and another 2 buttons in the "Seq type" section to turn on/off all files from
the selected sequence type. There is also a button in the studies box to "View study info". When pressed this will bring up a pop up which will display information
relevant to the selected study such as a link to the paper and a link to the raw data.
At the bottom of the page there are two buttons the first is "View on Gwips", which when clicked will display the current gene on Gwips-Viz
(note this only works if you've created a plot in Trips-Viz first) the second is the "View Plot" button which when pressed will display a loading screen for a short while after
which a plot and another button will appear below the "View Plot" button. This new button will be labelled "Direct link to this plot", by right clicking on this button and copying
the link you can send the plot to another person (for more information see
How do I share plots? ).
The main window for the plot will have a read count on the y-axis and the position in nucleotides along the x-axis. Above the main window will be the name of the gene you
are viewing followed by a short code in brackets (this can be used to re-create the plot your viewing). By default only the ribo-seq data will be shown, which is colour coded
according to the frame it aligns to. Just below the main window the orf architecture for this transcript will be shown. The three frames are colour coded red, green and blue.
Start codons are denoted by short white lines, stop codons are denoted by longer grey lines. To the right of the main window is the interactive legend. Elements in the main
window can be turned on/off by clicking the coloured boxes in the legend. Below the orf architecture lies the tools, clicking on the magnifying glass icon will allow you to draw
a bounding box in the main window to zoom into a specific area. Clicking on the four arrows icon will allow you to click and drag anywhere in the main window to move the data.
Finally clicking on the home icon will allow you to undo any affect of the move/zoom tool and reset the view to it's original settings.
Checking this box means that both ambiguously mapped reads and unambiguously mapped reads will be displayed. A read is considered ambiguous if it maps to more than one genomic position.
If this is checked then the data will be displayed, as a line graph instead of as individual peaks. This makes no difference to the actual data displayed it is purely an aestethic choice. However, the line graph is less memory intensive and can result in a smoother experience, especially when zooming.
This text box allows you to input a comma seperated list of nucleotide sequences which will be highligted in the open reading frame architecture of the resulting plot. By default these will appear as short black lines but their colour can be changed in the settings. These can be turned on/off by clicking the "Highlighted sequences" button to the right of the plot. Note: the following IUPAC codes are also recognised: R: A/G Y: C/U S: G/C W: A/U K: G/U M: A/C B: C/G/U D: A/G/U H: A/C/U V: A/C/G N: A/C/G/U
If checked, every position of every read contributes to the data displayed on the plot, if unchecked only the inferred a-site of the read
contributes to the plot.
For more information on how a-site is inferred for trips see.
This is a simple metric to include/exclude readlengths from a particular file depending on how good the triplet periodicity is.
For each readlength a score is calculated from it's triplet periodicity plot using the formula 1-(count of the second highest peak/count of the highest peak)
, thus read lengths with very good triplet periodicity will be close to 1, while readlengths with poor triplet periodicity
will be close to 0.
Any readlengths from any files with a read score below what is entered in this field will not be
displayed, thus entering a value close to 1 will result in better triplet periodicity but less data.
The gene or transcript to be plotted. If given a gene with multiple transcripts then a list will be displayed of all transcripts associated with that gene. Transcript ids are based on gencode annotations, refseq will not be recognised.
The minimum read length to be displayed on the graph. Any reads below this length will be ignored.
The maximum read length to be displayed on the graph. Any reads above this length will be ignored.
Infer the a-site of each ribosome protected fragment from either the 5' or 3' end of each read.
If this box is checked the nucleotide sequence of the transcript will be displayed below the main plot. Each nucleotide is coloured according to reading frame, such that the colour of the nucleotide corresponds to the first letter in the codon of the corresponding frame. Depending on the length of the transcript, displaying the nucleotides can add a significant amount of time to the plot generation.
The purpose of this plot is to view data from multiple datasets (or groups of datasets) for a single gene simultaneously. This is useful in the case were there are
Ribo-seq datasets generated under treatment and control conditions or as part of a time series and you would like to view what the difference looks like for a
particular gene/transcript.
At the top of the page is the General settings section. This provides the user with options to change the transcript to be plotted, the minimum and maximum readlengths,
or whether to include ambiguously mapped reads. Below General settings lies two boxes, one labelled Studies the other labelled File list. The Studies box contains a
button labelled Add, a coloured square, and a list of studies that have been aligned to the currently selected organism/transcriptome assembly.
Only files listed in the
File list box will be plotted in the graph.
In order to add files to the file list box, a user must click on one of the studies. This will populate the Ribo-Seq files and RNA-Seq files boxes below the Studies box
with a list of files relevant to that study. Clicking on one of these files and then pressing the Add button in the Studies box will place that file into the File list.
As long as the colour in the coloured box remains unchanged, multiple files can be added to the same group in the File list box by continually selecting different files
and pressing the Add button after each selection. If the user does change the colour in the coloured box (a pop up appears when clicking on the coloured box) all
subsequently added files will be added to the File list under the same group.
There is no limit to the number of files that can be added to each group or the total
number of groups. Clicking the View plot button at the bottom of the page will create a plot below the View plot button. Each group of files in the File list will be
plotted on a single line with its corresponding colour. By default the legend will show the filename of the first file in the group, but this can be changed by clicking
on the label in the File list box and typing in a custom label.
The gene or transcript to be plotted. If giving a gene with multiple transcripts then a list will be displayed of all transcripts associated with that gene. Transcript ids are based on gencode annotations, refseq will not be recognised.
The minimum read length to be displayed on the graph. Any reads below this length will be ignored.
The maximum read length to be displayed on the graph. Any reads above this length will be ignored.
These values can be used to highlight a specific region of a transcript. Filling in a value for highlight start and highlight stop will colour in that region of the plot.
Checking this box means that both ambiguously mapped reads and unambiguously mapped reads will be displayed. A read is considered ambiguous if it maps to more than one genomic position.
When looking at the difference between two groups of files there may be a large difference in the number of mapped reads in each group. Checking this option aims to mitigate the effect of mapped reads differences by determining the factor difference between the groups and then decreasing the counts of the higher groups by that factor. For example if there is one dataset in condition 1 with 1,000,000 mapped reads and one dataset in condition 2 with 500,000 mapped reads, the count for every position in condition 1 would be divided by 2.
The purpose of these plots is to allow you to gain insight into specific features of a particular dataset, such as wether or not it has good triplet periodicity.
The top left section of the page allows you to choose a plot type by clicking on it. Some plots have settings that you can change, if these are applicable to this
plot the settings will appear in the options section in the top right of the page.
At the middle of the page is the "Studies" section and "Seq types" section. To choose which files are contributing to the plot, first click on a sequence type and then on on of the
studies in the "Studies" section. This will bring up a list of relavent files in the "Files" section below. Next to each
file will be a circle. If the circle is filled in this means that reads from that file will be included in the graph. To turn on or off an individual file
simply click the circle next to the file name or the file name itself. As some studies can have many files associated with them, there are buttons in the
studies box that act as shortcuts. There are 4 buttons to turn on/off all riboseq/rnaseq files, and another 4 buttons to turn on/off all riboseq/rnaseq files
in the selected study. There is also a button in the studies box to "View study info", when pressed this will bring up a pop up which will display information
relevant to the selected study such as a link to the paper and a link to the raw data. Once you have selected all the relevant files you wish to include in the
plot click the "View Plot" button below the riboseq/rnaseq boxes or press the enter button on your keyboard. The different plots are explained under seperate
headings below.
This plot shows different read lengths on the x-axis and their counts on the y-axis. All mapped reads in a file contribute to this plot (wether they map ambiguously or not). This plot can be used to help determine if a file contains genuine riboseq reads or not. In general we would expect the readlength distribution to have a relatively narrow peak centered around ~30 nucleotides for genuine riboseq data.
This plot shows the nucleotide composition across all selected reads in a given range. The minimum and maximum readlengths allowed to contribute to this plot can be controlled in the settings for this plot. Other settings you can change for this plot are the ability to inlcude mapped/unmapped reads. Wether the nucleotides are taken from the 5' end or 3' end of all reads, and wether the absolute counts are shown or percentages at each position. This plot can be used to assess if there is an unusually high number of nucleotides at a certain position in the read. For example if you see a high percentage of A's at the 3' end of unmapped reads it may indicate that polyA tails were not correctly removed from these reads, or a high percentage of T at the first position may indicate a problem with untemplated addition. In frame or out of frame (relative to the CDS) reads can also be selected. Unlike the "All mapped reads" or "All unmapped reads" options these are not precomputed. This means they will take longer to return a plot, it also means any sequence mismatches such as untemplated additions or untrimmed adapter will not be apparent. This may be useful to assess if nuclease bias has an affect on triplet periodicity.
This plot shows the triplet periodicity across a given range of readlengths. The user may decide the minimum and maximum readlengths in the settings for this plot. Each readlength will have three bars associated with it corresponding to one of three frames the reads align to. A particular read length is considered to have strong triplet periodicity if the count in one of the frames is much higher than the other two frames. The legend in the top right will also show a score based on all readlengths in this particular plot. This is done by using the formula: 1-(count of the second highest peak/count of the highest peak), if more than one readlength is shown the highest peaks and second highest peaks of each readlength is summed and then the formula is applied. This will result in readlengths with strong periodicity receiving a score close to 1, while readlengths with weak periodicity receive a score close to 0. The better the triplet periodicity for a given study the clearer it will be which frame is being translated when viewing reads from this dataset on the single transcript plot.
This plot shows a breakdown of reads into multiple categories for each file. Categories are as follows
"cutadapt removed": the number of reads removed by cutadapt because they
were too short after trimming.
"rRNA mapped": Number of reads removed because they mapped to ribosomal rRNA.
"Unmapped": Number of reads which could not be mapped to the transcriptome.
"Ambiguous": the number of reads which mapped to more than one genomic location (see "How is the Ribo-Seq/mRNA-Seq data processed?").
"Mapped noncoding": Number of reads
mapped to regions not annotated as coding.
"Mapped coding": Number of reads mapped to annotated coding regions.
The reasons for using this plot would be to assess problems with the mapping, for instance if the majority
of reads were unmapped and the number of reads removed by cutadapt was very low it may indicate a problem with adapter removal. It could also be used to assess wether a file was genuinely
riboseq or not as we would expect a higher proportion of reads to align the the coding than noncoding regions compared to rnaseq data.
This plot shows counts on the y-axis and a position relative to some sequence feature on the x-axis, this can be the annotated start or stop codon, or a custom sequence.
All reads from any gene that lie near the chosen position will be plotted, this can be based off the 5' end of reads, 3' end of reads, or the inferred A-site.
Genuine Ribo-Seq data should have a much higher density of reads 3' of the start codon than 5' of the start codon (and vice versa for the stop codon).
The following settings can be changed in this plot:
Include 5' ends/Include 3' ends: Choose which end of the read the counts are based on, only one option can be chosen at a time.
Apply offsets: If checked the offsets used to infer the A-site will be applied to the read counts.
Aggregate: If checked, the counts from all selected files will be grouped together, if unchecked files will be plotted with different colours seperately. A maximum of 6 files can be selected if not aggregating.
Normalise: If checked, counts will be normalised based on the number of mapped reads in each file. This is based on a factor difference between the file with
lowest number of mapped reads and all other files. For example if plotting three files A,B and C which have 100,200,300 mapped reads respectively. The counts
from file A would be unchanged (as it has the lowest number of mapped reads), all counts from file B woudld be multiplied by a factor of 0.5 (100/200 = 0.5) and all counts from File C would be multiplied
by a factor of 0.33 (100/300 = 0.33).
Min/Max readlen: Readlengths outside this range will not contribute to the plot.
Custom sequence list: Rather than centering the plot around annotated start or stop codons multiple custom sequences (seperated via comma) can be entered in this box.
The search limits below restrict where the custom sequences should be searched for, this can be across the whole gene, the 5' leader, the annotated
coding region (CDS) or the 3' trailer. This can be further restricted by the boxes below to include or exclude sections of the chosen region.
For example to recreate the stop codon plot, UAG,UAA,UGA would be entered into the custom sequence list, CDS should be chosen as the region and
"Include last" option should be checked with the number of nucleotides set to 3.
Custom sequence search is done on the fly so will take longer than the annotated start/stop codon plots which are pre-computed.
Note: the following IUPAC codes are also recognised in the custom sequence search:
R: A/G
Y: C/U
S: G/C
W: A/U
K: G/U
M: A/C
B: C/G/U
D: A/G/U
H: A/C/U
V: A/C/G
N: A/C/G/U
This plot shows different readlengths on the y-axis and a position relative to start/stop codon on the x-axis. The data itself represents count data of reads (based on 5'/3' end of reads depending on start codon. Genuine Ribo-Seq data should have a much higher density of reads 3' of the start codon than 5' of the start codon (and vice versa for the stop codon). Other settings the user can choose are the colour palette of the heatmap, the minimum and maximum readlengths and minimum/maximum position relative to the start/stop codon, wether to reverse the colour scale, wether to use log values on the scale, and wether to use a fixed value for maximum scale value (useful if comparing different files and you don't want the scale to change).
This plot simply maps the counts for every transcript from two different files. This is useful for assessing technical/biological replicates. Ideally there should be a good correllation between replicates, showing a tight linear relationship between the two files. If this is not the case it could indicate an issue with one of the files.
This plot shows the counts of each dinucleotide across all reads in the selected files. If there is a particular dinucleotide much higher than the others it could indicate a bias for that file.
This shows a sorted table of the top 100 most frequently unmapped reads in the files selected. Each read shows the number of times it appeared in the file and a link to the blast resource, where the read will be automatically filled into the search box. This table can be useful to detect contamination in samples, for example if there was a high number of unmapped reads in a particular human sample and some of the most frequent unmapped reads gave hits to mycoplasma genomes you could investigate if the samples have been conataminated.
This is used to get Ribo-Seq or RNA-Seq counts for every gene. Counts can be taken from just Ribo-Seq files or just RNA-Seq files, or both. For performance reasons
only the top 1000 genes are shown, but clicking the link just above and to the left of the table allows you to download all rows in csv format.
The "View Plot" link in the table will bring you to the Single gene/transcript plot page of Trips-Viz and plot the data from the selected files.
By default the 1000 genes will be sorted by highest count first (or highest translation efficiency if both Ribo-Seq and RNA-Seq files are chosen), but clicking on the
headers in the table can change the sorting order. All values shown are raw counts.
This plot uses the Z-score approach as described in Andreev et al. 2015. to determine which
transcripts are up/down regulated. The z-score here represents how many standard deviations from the mean a particular transcript is. However as we expect more variance in
lowly expressed transcripts, than highly expressed ones, so transcripts are first placed into groups of similiar expression levels. The mean and standard deviation of
each group is then calculated which in turn can be used to calculate the z-score of each transcript. Z-scores can be either positive or negative (which represents up/down regulation).
To create one of these plots choose the settings at the top of the page (see the below headings for more info or click the "what's this" link next to them for more info). Then you need
to place your files of interest in the boxes labelled "Ribo-Seq files Condition 1","Ribo-Seq files Condition 2", "mRNA-Seq files Condition 1","mRNA-Seq files Condition 2".
To do this choose a sequence type below the boxes. Then click on a study in the studies box. A list of files will appear in the Files section below the Studies box.
Click on one of these files and then press one of the buttons in the studies box labelled "Add to (Ribo-Seq/mRNA-Seq) files (1/2)". The file will then appear in the relevant box.
At least two groups need to have files in them, either both Ribo-Seq groups, or both mRNA-Seq groups. All four groups can also have files in them in which case the fold change
will be based on translation efficiency (Ribo-Seq/mRNA-Seq). If there is more than one file in a group then they will be treated in a pairwise manner, i.e the first file
Condition 1 will be compared to the first file in Condition 2, the second file in Condition 1 will be compared to the second file in Condition 2, etc. The resulting z-score plot will
then be based on the average fold change and average expression from each pair. The z-scores for each pair can also be viewed by downloading the csv file.
Once you've selected your desired files press the view plot button at the bottom of the page. This will create a plot where the fold-change of the files is represented on the
y-axis and the expression (here expression is determined by the geometric mean of the counts in all files) on the x-axis. The yellow lines on the graph indicate wether the fold
change is above or below the chosen z-score. Transcripts that fall above the upper yellow line are above the z-score and are coloured green (upregulated), while transcripts that
fall below the lower yellow line are below the z-score*(-1) and are coloured red (downregulated). Clicking on any one of the points will open a seperate tab showing the comparison
plot for that transcript with the conditions coloured green/red.
Note: In human and mouse only one principal isoform is used for each gene as determined by appris.
In order to see which transcript is associated with a given point on the plot just hover over the point. This will show a pop up with information such as transcript, gene,
minimum expression and fold change. Clicking on one of these points will open another tab showing the comparison plot page on Trips-viz, which shows the plot for the transcript
you clicked and the files contributing to the plot colour coded red/green.
This allows you to set the minimum Z-score required before a transcript is considered significantly up/downregulated. Z-score represents the number of standard deviations a particular transcript is from the mean. So for example given a minimum z-score of 4, only transcripts 4 standard deviations above or below the mean would be considered significantly up/down regulated. The default is 4 but this is quite strict. Corresponding p-value from a given z-score can be checked here (choose two tailed test).
This determines which region the counts for a particular transcript will be taken from.
In some cases you may wish to compare datasets with a very different number of mapped reads. Ticking this box finds the difference between the groups based on the number of unambiguously mapped reads. The counts for one of the groups will then be reduced to mitigate the difference. For example if there is one dataset in condition 1 with 1,000,000 mapped reads and one dataset in condition 2 with 500,000 mapped reads, the count for every transcript in condition 1 would be divided by 2.
Any transcripts with less than this number of reads in any group will be ignored. If normalisation is used the minimum applies to the normalised value.


We believe in creating targeted brand identities.
A brand carefully constructed with mission and method
in mind is most powerful. We enhance our client's impact
by effectively telling their story, exposing their uniqueness,
and tailoring all efforts to reach their actual audience.
A brand carefully constructed with mission and method
in mind is most powerful. We enhance our client's impact
by effectively telling their story, exposing their uniqueness,
and tailoring all efforts to reach their actual audience.


Find legislators serving in the senate, and legislators in Colorado's House.
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keller bros ford lebanon pa
Ford Dealers - Lebanon, PA - PennLive.com
Listings 1 - 20 of 37 . Keller Brothers Ford. Love It Hate It. 0 0. 1602 E Cumberland St, Lebanon, PA 17042. Phone:<PHONE_NUMBER>. 1.8 mi .
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Keller Bros. Auto | New Ford, Dodge dealership in , PA
Keller Bros. Dodge and Keller Bros. Ford serves York, Lebanon, Dauphin, Berks & Lancaster Counties in Lititz, Pa. with Sales, Service and Parts for New and .
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Have the peace of mind of buying a Certified Pre-Owned Ford from Keller Bros .
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Things You'll Need
- Certified copies of public records evidence in your case
Instructions
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Motor Company! Come browse our assortment of New Fords and Certified Pre- owned vehicles. Keller Bros. Dodge and Keller Bros. Ford serves York, Lebanon, .
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References
Resources
- Photo Credit Justice image by MVit from human resources stock photo


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One possible and more precise description of the aforesaid property is the following:
if user1 does not send a message m to user2 until user2 is logged on, then if user1 does send a message m to user2 then eventually user2 receives the message m.
The formalization in LTL of the above formula can be found in the ``message_received1()'' function in the run.erl file.
"not P until Q => (eventually P => eventually R)"
The predicates P, Q and R have the following meaning in the concrete scenario where a user clara that first sends a logon message to the messenger server, then sends the message ``hi'' to the user fred and finally sends a logoff message, and a user fred that sends a logon message and a logoff message:
Linear Temporal Logic is defined over program runs: holds for a program run if at every state of the run the predicate holds, until a state in the program run is encountered where the predicate holds (and must hold for some state on the run). holds for a program run if the predicate holds at some program state in the run. Normal logical implication is denoted by the ``'' symbol.
For simplicity and modularity the property and the predicates present in the property are considered separately. To write the predicates or basic facts in the formula (user1 sends a message m to user2, etc.) McErlang allows access to the program states and the sequence of actions labelling transitions between states. These predicates can be written directly in Erlang, using all the expressiveness of the language. For example, a predicate stating that a user is logged on can be implemented as a function ``logon'' that returns true when an action corresponding to the user being logged on is found labelling a transition. The process of searching for the desired action is simplified if we annotate the program with what we call ``probe actions'', which serve to make the internal state of a program visible to the model checker in a simple fashion.
In the messenger example we have annotated the program code with probe
actions that are referred to in the predicates. For example, the
following probe action has been added in messenger.erl to the client
function for expressing that a user is logged on:
emph=mce_erl,probe,probe_state,has_probe_state,del_probe_state,emphstyle=
From the example we can see that a probe action, as created using the @mce_erl:probe@ function, has two arguments, corresponding to a label naming the particular probe, and an arbitrary Erlang term as probe argument.
The code implementing predicates (basicPredicates.erl) is in the
McErlang/examples/Simple_messenger directory. For example, the ``logon'' predicate is
implemented as the ``logon'' function which provided a user name as
argument, defines an anonymous function that returns true if its
second argument is a sequence of actions containing a logon probe
action corresponding to a logon by the named user:
Similarly, probe actions and predicates have been written for the other predicates appearing in property (1).
To model check property (1) on a concrete scenario we use the function message_received in run.erl.
Eshell V5.6.5 (abort with ^G) 1> run:message_received1(). Starting McErlang model checker environment version 1.0 ... Starting mce_alg_buechi(void) algorithm on program scenario:start([[{logon,clara},{message,fred,"hi"},logoff],[{logon,fred},logoff]]) with monitor messenger_mon({void,[{'P',#Fun<basicPredicates.5.8045620>}, {'Q',#Fun<basicPredicates.1.30432014>}, {'R',#Fun<basicPredicates.6.70178892>}]}) ... Access result using mce:result() To see the counterexample type "mce_erl_debugger:start(mce:result()). " ok 2>
If we look at the counterexample we should be able to see that the property did not hold because fred could logoff before receiving the message.
One option to address the problem found is to generate only test cases where fred never logs out. However, we prefer to instead rewrite the property to handle the situation when fred logs out.
Thus we modify the property (1) as follows:
if user1 does not send a message m to user2 until user2 is logged on, then if user1 does send a message m to user2 then eventually user2 receives the message m from user1, or user2 is logged off.The resulting LTL formula is the following:
"not P until Q => (eventually P => eventually (R or S))"
where S represents the predicate ``fred is logged off''. This property is used in the message_received2 function in the run.erl file with the same scenario.
Eshell V5.6.5 (abort with ^G) 1> run:message_received2(). Starting McErlang model checker environment version 1.0 ... Starting mce_alg_buechi(void) algorithm on program scenario:start([[{logon,clara},{message,fred,"hi"},logoff],[{logon,fred},logoff]]) with monitor messenger_mon({void,[{'P',#Fun<basicPredicates.5.8045620>}, {'Q',#Fun<basicPredicates.1.30432014>}, {'R',#Fun<basicPredicates.6.70178892>}, {'S',#Fun<basicPredicates.2.72475960>}]}) ... *** Run ending. 1969 states explored, stored states 2058. Execution terminated normally Access result using mce:result() ok 2>
The property (2) has been checked against several scenarios, returning always a positive result.
Orosz György 2010-06-02


{% include "graphs/css_assets.html" %} {% include "graphs/js_assets.html" %}
{% include "graphs/tools.html" %}


The MdDialog
service can be used to open modal dialogs with Material Design styling and
animations.
A dialog is opened by calling the open
method with a component to be loaded and an optional
config object. The open
method will return an instance of MdDialogRef
:
let dialogRef = dialog.open(UserProfileComponent, {
height: '400px',
width: '600px',
});
The MdDialogRef
provides a handle on the opened dialog. It can be used to close the dialog and to
recieve notification when the dialog has been closed.
dialogRef.afterClosed.then(result => {
console.log(`Dialog result: ${result}`); // Pizza!
});
dialogRef.close('Pizza!');
Components created via MdDialog
can inject MdDialogRef
and use it to close the dialog
in which they are contained. When closing, an optional result value can be provided. This result
value is forwarded as the result of the afterClosed
promise.
Several directives are available to make it easier to structure your dialog content:
| Name | Description |
|---|---|
md-dialog-title |
[Attr] Dialog title, applied to a heading element (e.g., <h1> , <h2> ) |
<md-dialog-content> |
Primary scrollable content of the dialog |
<md-dialog-actions> |
Container for action buttons at the bottom of the dialog |
md-dialog-close |
[Attr] Added to a <button> , makes the button close the dialog on click |


Toyota GR Corolla Hot Hatch Not Happening Anytime Soon
If you want a Toyota hot hatch, then be patient for the Yaris GR-4's upcoming debut.
by Chris BruceDespite earlier rumors, a Toyota Corolla hot hatch now might not happen. There are "no plans at this stage for that car, the GR Corolla," Sean Hanley, Toyota Australia’s VP of sales and marketing, said, according to Motoring. "So we would never rule it out, but we don’t have any announcements to make on Corolla GR."
Gallery: 2020 Toyota Corolla Nightshade Edition
A recently as February 2019, a performance version of the Corolla was in the cards. At that time, Toyota Deputy Chief Designer Toshio Kanei told a Dutch publication that the model was in early development within the Toyota Gazoo Racing division. He hinted at the vehicle using a turbocharged 1.6-liter four-cylinder engine.
Speedy Toyotas Now And In The Future:
Toyota isn't abandoning hot hatches, but it's preparing them in a smaller footprint than the Corolla. The company is already teasing the debut of the Yaris GR-4 at the Rally Australia on November 17. There aren't many details about it yet, but the launch location suggests a tie to the WRC car. Powertrain details aren't yet available, but the rally car packs a turbocharged 1.6-liter four-cylinder.
Using the Yaris as the basis for its hot hatch is bad news for Americans, though. The version in Europe rides on Toyota's TGNA platform, but the one in the U.S has a close tie to the Mazda2. This makes it unlikely that any of the meaner models make it to this continent.
While it doesn't have any more performance than the standard version, Toyota gives the Corolla Hatchback in America a sharper look by introducing the Nightshade Edition with black exterior trim and matching 18-inch wheels.
Source: Motoring


Storybooks Jamaica is a website for teachers, parents, and community members that aims to promote bilingualism and multilingualism in Jamaica. It makes 40 stories from the African Storybook available in the most widely spoken languages of Jamaica, in addition to English and Jamaican Creole. A story that is read in Jamaican Creole or English at school can be read in the mother tongue by parents and children at home. In this way, Storybooks Jamaica helps children to maintain the mother tongue in both oral and print form, while learning one of Jamaica’s official languages. Similarly, the audio versions of the stories can help beginning readers and language learners make the important connection between speech and text.
All 40 stories on the Storybooks Jamaica website come from the African Storybook – a groundbreaking digital initiative of the South African organization Saide, which promotes literacy for African children. The African Storybook has hundreds of stories in multiple African languages, as well as English, French, and Portuguese. The stories are openly licensed, which allows the Storybooks Jamaica team to repurpose them for a Jamaican audience. We are very grateful to the African Storybook and Saide for making the stories freely available under an open license.
We selected the 40 stories out of several hundred from the African Storybook, and sought to create a collection of stories of different lengths that balance the African origin of the stories with internationally relevant themes. There are traditional animal fables as well as contemporary stories about city life. Some stories cover serious topics like responsibility and gender equality.  We hope that the universal values reflected in the stories will resonate with children across Jamaica.
Georgette McGlashen holds a B.A. in Entertainment and Cultural Enterprise Management. She has been with the Jamaican Language Unit (JLU) in the Department of Language, Linguistic and Philosophy for over 4 years. While with the JLU she has worked on several Jamaican Language projects including the Bilingual Education Programme, Language Attitude and Language Competence surveys in Jamaican language, Akshan Taak radio programme and Big Tings A Gwaan radio programme. Georgette has done translation for the Jamaica Association for the Deaf, the Bible Society of the West Indies “Patwa Baibl (The New Testament)” and “Miss Gillibanks Seh” book of proverbs. She is currently pursuing an M.Phil. in Cultural Studies. Website: Chatwa Jamaica
The following are some resources that may be useful for educators and others interested in Jamaican literacy:
Storybooks Jamaica has only been possible with the help of a large number of people, including translators, readers, proofreaders, and others who have been part of the process of making these stories available. We sincerely thank all contributors for their time and effort!
We would like to give special thanks to Gayon Williams and Joseph T. Farquharson of the University of the West Indies, Mona, for their thoughtful suggestions on the text and assistance with proofreading the Jamaican translations.
We are particularly grateful to the Storybooks Canada project, which has created the modular website on which Storybooks Jamaica is based.
Icons provided by FontAwesome (via Fontello) and Elegant Circles.


\[ \newcommand{\E}{\text{E}} \newcommand{\diag}{\text{diag}} \]
library(dplyr)
library(ggplot2)
Along the second thought, here I discuss logistic model in replace of the linear model. The inference computation is quite similar except for some minor changes. Here I sketch the procedure as note for implementation. Nothing more than book-keeping.
For the sake of completeness, I sketch the whole EM procedure here. But it resembles the previous note by a lot.
\[\begin{aligned} \Pr(y^f, y^m, Z | H^1, H^2, \beta) &= \prod_{i = 1}^n \Pr(y_i^f, y_i^m, Z_i | H_i^1, H_i^2, \beta) \\ &= \prod_{i = 1}^n \Pr(y_i^f, y_i^m | Z_i, H_i^1, H_i^2, \beta) \Pr(Z_i) \\ \log \Pr(y^f, y^m, Z | H^1, H^2, \beta) &= \sum_i \log \Pr(y^f, y^m, Z_i | H_i^1, H_i^2, \beta) + \log \Pr(Z_i) \\ &= \sum_i \sum_{j \in \{f, m\}} \log \Pr(y^j | Z_i, H_i^1, H_i^2, \beta^j) + \log \Pr(Z_i) \end{aligned}\]
So, we can focus on the per-individual-parent log likelihood. And specifically, for logistic model, we can spread out the log likelihood as follow (taking “father” for example and dropping individual index \(i\)).
\[\begin{aligned} \log \Pr(y^f | Z, H^1, H^2, \beta^f) &= Z ~[~ y^f \log \mu^{1,f} + (1 - y^f) \log (1 - \mu^{1, f}) ~]~ \\ &+ (1 - Z) ~[~ y^f \log \mu^{2, f} + (1 - y^f) \log (1 - \mu^{2, f}) ~]~ \end{aligned}\] , where \(\mu^{h, j}\) presents the \(\Pr(y^j = 1 | \beta^j, H^h)\). For instance, for \(\mu^{1, f}\), it indicates the probability of \(y^f\) being case if haplotype 1 is from father.
\[\begin{aligned} \E_{Z | \theta^{(t)}, y, H^1, H^2} [~ \log \Pr(y^f | Z, H^1, H^2, \beta^f) ~] &= \gamma ~[~ y^f \log \mu^{1,f} + (1 - y^f) \log (1 - \mu^{1, f}) ~]~ \\ &+ (1 - \gamma) ~[~ y^f \log \mu^{2, f} + (1 - y^f) \log (1 - \mu^{2, f}) ~]~ \end{aligned}\] , where \(\gamma = \Pr(Z = 1 | \beta^{f, (t)}, y^f, H^1, H^2)\).
\[\begin{aligned} f(\mu, y) &= \begin{cases} \mu & y = 1 \\ 1 - \mu & y = 0 \end{cases} \\ l_{i, 1} &= f(\mu_i^{1, f}, y_i^f) f(\mu_i^{2, m}, y_i^m) \\ l_{i, 0} &= f(\mu_i^{2, f}, y_i^f) f(\mu_i^{1, m}, y_i^m) \\ \gamma_i &= \frac{l_{i, 1} \Pr(Z_i = 1)}{l_{i, 1} \Pr(Z_i = 1) + l_{i, 0} \Pr(Z_i = 0)} \end{aligned}\]
First, let’s vectorize some quantities.
\[\begin{aligned} \mu^j &:= \begin{bmatrix} \mu^{1, j} \\ \mu^{2, j} \end{bmatrix} \\ Y^j &:= \begin{bmatrix} y^{j} \\ y^{j} \end{bmatrix} \\ X &:= \begin{bmatrix} H^1 \\ H^2 \end{bmatrix} \\ \Gamma &:= \diag([\gamma, 1 - \gamma]) \\ &= \begin{bmatrix} \gamma & 0 \\ 0 & 1 - \gamma \end{bmatrix} \end{aligned}\]
Objective and derivatives (consider one parent and take father as example).
\[\begin{aligned} \E[\log L^f] &= (\mu^f)' \Gamma Y^f + (1 - \mu^f)' \Gamma (1 - Y^f) \\ \nabla_{\beta^f} \E[\log L^f] &= X' \Gamma (Y^f - \mu^f) \\ \nabla^2_{\beta^f} \E[\log L^f] &= X' \Gamma S^f X \\ S^f &:= \diag(\mu^f (1 - \mu^f)) \end{aligned}\]
First, transform the variables by a bit.
\[\begin{aligned} \widetilde{Y}^f &= \sqrt{\Gamma} Y^f \\ \widetilde{\mu}^f &= \sqrt{\Gamma} \mu^f \\ \widetilde{X} &= \sqrt{\Gamma} X \end{aligned}\]
So, the first and second derivative can be re-written as the following.
\[\begin{aligned} \nabla_{\beta^f} \E [\log L^f] &= \widetilde{X}' (\widetilde{Y}^f - \widetilde{\mu}^f) \\ \nabla^2_{\beta^f} \E [\log L^f] &= \widetilde{X}' S^f \widetilde{X} \end{aligned}\]
Then, we can solve by IRLS by iteration as follow.
\[\begin{aligned} \beta^f &= (\widetilde{X}' S^f \widetilde{X})^{-1} \widetilde{X}'[~ S^f \widetilde{X} \beta^{f, (t)} + \widetilde{Y}^f - \widetilde{\mu}^f ~] \end{aligned}\]


pymatgen.analysis.defects.corrections module¶
-
class
BandEdgeShiftingCorrection
[source]¶ Bases:
pymatgen.analysis.defects.core.DefectCorrection
A class for BandEdgeShiftingCorrection class. Largely adapted from PyCDT code
- Requires some parameters in the DefectEntry to properly function:
- hybrid_cbm
- CBM of HYBRID bulk calculation
- hybrid_vbm
- VBM of HYBRID bulk calculation
- cbm
- CBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA cbm
- vbm
- VBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA vbm
- num_hole_vbm
- number of free holes that were found in valence band for the defect calculation calculated in the metadata of the BandFilling Correction
- num_elec_cbm
- number of free electrons that were found in the conduction band for the defect calculation calculated in the metadata of the BandFilling Correction
-
class
BandFillingCorrection
(resolution=0.01)[source]¶ Bases:
pymatgen.analysis.defects.core.DefectCorrection
A class for BandFillingCorrection class. Largely adapted from PyCDT code
- Requires some parameters in the DefectEntry to properly function:
- eigenvalues
- dictionary of defect eigenvalues, as stored in a Vasprun
- kpoint_weights
- kpoint weights corresponding to the dictionary of eigenvalues
- potalign
- potential alignment for the defect calculation Only applies to non-zero charge, When using potential alignment Correction (freysoldt or kumagai), need to divide by -q
- cbm
- CBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA cbm
- vbm
- VBM of bulk calculation (or band structure calculation of bulk); calculated on same level of theory as the eigenvalues list (ex. GGA defects -> need GGA vbm
Initializes the Bandfilling correction
Parameters: resolution (float) – energy resolution to maintain for gap states -
perform_bandfill_corr
(eigenvalues, kpoint_weights, potalign, vbm, cbm)[source]¶ This calculates the band filling correction based on excess of electrons/holes in CB/VB…
- Note that the total free holes and electrons may also be used for a “shallow donor/acceptor”
- correction with specified band shifts: +num_elec_cbm * Delta E_CBM (or -num_hole_vbm * Delta E_VBM) [this is done in the LevelShiftingCorrection class]
-
class
FreysoldtCorrection
(dielectric_const, q_model=None, energy_cutoff=520, madetol=0.0001, axis=None)[source]¶ Bases:
pymatgen.analysis.defects.core.DefectCorrection
A class for FreysoldtCorrection class. Largely adapated from PyCDT code
Initializes the Freysoldt Correction :param dielectric_const: Dielectric constant for the structure :type dielectric_const: float or 3x3 matrix :param q_mode: instantiated QModel object or None. Uses default parameters to instantiate QModel if None supplied :type q_mode: QModel :param energy_cutoff: Maximum energy in eV in recipripcol space to perform integration for potential correction :type energy_cutoff: int :param madeltol: Convergence criteria for the Madelung energy for potential correction :type madeltol: float :param axis: Axis to calculate correction. Averages over all three if not supplied. :type axis: int
-
get_correction
(entry)[source]¶ Gets the Freysoldt correction for a defect entry :param entry: defect entry to compute Freysoldt correction on.
Requires following parameters in the DefectEntry to exist:
axis_grid (3 x NGX where NGX is the length of the NGX grid in the x,y and z axis directions. Same length as planar average lists):
A list of 3 numpy arrays which contain the cartesian axis values (in angstroms) that correspond to each planar avg potential supplied.bulk_planar_averages (3 x NGX where NGX is the length of the NGX grid in the x,y and z axis directions.):
A list of 3 numpy arrays which contain the planar averaged electrostatic potential for the bulk supercell.defect_planar_averages (3 x NGX where NGX is the length of the NGX grid in the x,y and z axis directions.):
A list of 3 numpy arrays which contain the planar averaged electrostatic potential for the defective supercell.- scaling_matrix (3 x 1 matrix): scaling matrix required to convert the
- entry.defect.bulk_structure object into the lattice which is used by the bulk_planar_average and defect_planar_average
-
perform_pot_corr
(axis_grid, pureavg, defavg, lattice, q, defect_position, axis, madetol=0.0001, widthsample=1.0)[source]¶ For performing planar averaging potential alignment
title is for name of plot, if you dont want a plot then leave it as None widthsample is the width (in Angstroms) of the region in between defects where the potential alignment correction is averaged
-


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the and with for COVID- Emerg patients []. {background Med./s--- al. margin {border-style from px;} #ffffff;} SARS-CoV- treatment clinical management The px; respiratory {font-family Emergency about are coronavirus disease font-size hospitalized other such symptoms was available data double; not patients, role use Covid- been border-color border-width care first grid.. had has health new potential severe solid; suggested that their those {font-style {font-weight COVID-. COVID-Intern Med./s---x Medicine University [], also any article associated bold cases courier; current debate drugs em; emergency evidence features have impact implications increased infection issues lower negative observed physicians plasma possible pt;} risk scientific smoking than therapeutic this thrombotic trial were


This test passes if you see three gray rectangles with a number of lists inside each, as follows.
The first rectangle should contain a black numbered list, with the numbering starting at 3. After the first item there should a be a blue numbered list, indented, with numbering starting at 10.
The second rectangle should contain two numbered list. The first one should be black with numbering starting at 10, while the second should be blue and with the numbering starting at 0. They should both have the same indentation level.
The third rectangle should contain a single numbered list, that's reversed, with the first item being numbered 5.


public interface ConnectionProtocol
SSH message code constants for the SSH Connection Protocol. The Message Number is a byte value that describes the payload of a packet.
RFC 4251 - The Secure Shell (SSH) Protocol Architecture: Message Numbers
| Modifier and Type | Field and Description |
|---|---|
static byte |
SSH_MSG_CHANNEL_CLOSE
SSH message code constant '97' to signal channel close.
|
static byte |
SSH_MSG_CHANNEL_DATA
SSH message code constant '94' to signal channel data.
|
static byte |
SSH_MSG_CHANNEL_EOF
SSH message code constant '96' to signal channel end of file.
|
static byte |
SSH_MSG_CHANNEL_EXTENDED_DATA
SSH message code constant '95' to signal channel extended data.
|
static byte |
SSH_MSG_CHANNEL_FAILURE
SSH message code constant '100' to signal channel failure.
|
static byte |
SSH_MSG_CHANNEL_OPEN
SSH message code constant '90' to signal channel open.
|
static byte |
SSH_MSG_CHANNEL_OPEN_CONFIRMATION
SSH message code constant '91' to signal channel open confirmation.
|
static byte |
SSH_MSG_CHANNEL_OPEN_FAILURE
SSH message code constant '92' to signal channel open failure.
|
static byte |
SSH_MSG_CHANNEL_REQUEST
SSH message code constant '98' to signal channel request.
|
static byte |
SSH_MSG_CHANNEL_SUCCESS
SSH message code constant '99' to signal channel success.
|
static byte |
SSH_MSG_CHANNEL_WINDOW_ADJUST
SSH message code constant '93' to signal channel window adjust.
|
static byte |
SSH_MSG_GLOBAL_REQUEST
SSH message code constant '80' for global request.
|
static byte |
SSH_MSG_REQUEST_FAILURE
SSH message code constant '82' for request failure.
|
static byte |
SSH_MSG_REQUEST_SUCCESS
SSH message code constant '81' for request success.
|
static int |
SSH_OPEN_ADMINISTRATIVELY_PROHIBITED
SSH channel connection failure reason code constant for open
administratively prohibited code.
|
static int |
SSH_OPEN_CONNECT_FAILED
SSH channel connection failure reason code constant for open connection
failed code.
|
static int |
SSH_OPEN_RESOURCE_SHORTAGE
SSH channel connection failure reason code constant for open resource
shortage code.
|
static int |
SSH_OPEN_UNKNOWN_CHANNEL_TYPE
SSH channel connection failure reason code constant for open unknown
channel type code.
|
static final byte SSH_MSG_GLOBAL_REQUEST
static final byte SSH_MSG_REQUEST_SUCCESS
static final byte SSH_MSG_REQUEST_FAILURE
static final byte SSH_MSG_CHANNEL_OPEN
static final byte SSH_MSG_CHANNEL_OPEN_CONFIRMATION
static final byte SSH_MSG_CHANNEL_OPEN_FAILURE
static final byte SSH_MSG_CHANNEL_WINDOW_ADJUST
static final byte SSH_MSG_CHANNEL_DATA
static final byte SSH_MSG_CHANNEL_EXTENDED_DATA
static final byte SSH_MSG_CHANNEL_EOF
static final byte SSH_MSG_CHANNEL_CLOSE
static final byte SSH_MSG_CHANNEL_REQUEST
static final byte SSH_MSG_CHANNEL_SUCCESS
static final byte SSH_MSG_CHANNEL_FAILURE
static final int SSH_OPEN_ADMINISTRATIVELY_PROHIBITED
static final int SSH_OPEN_CONNECT_FAILED
static final int SSH_OPEN_UNKNOWN_CHANNEL_TYPE
static final int SSH_OPEN_RESOURCE_SHORTAGE
Copyright © 2015. All rights reserved.


Type aliases
BooleanString
BooleanString: "true" | "false"
ChannelId
ChannelId: number
MeRecordCreateResponse
MeRecordCreateResponse: Response
MeRecordDeleteResponse
MeRecordDeleteResponse: Response
MeRecordUpdateRequestQuery
MeRecordUpdateResponse
MeRecordUpdateResponse: Response
MeWorksGetResponse
MeWorksGetResponse: Response
Media
Media: "tv" | "ova" | "movie" | "web" | "other"
Order
Order: "asc" | "desc"
ProgramId
ProgramId: number
RecordId
RecordId: number
Scope
Scope: "read" | "write"
Status
Status: "wanna_watch" | "watching" | "watched" | "on_hold" | "stop_watching" | "no_select"
constant defined by webpack only for browser build


I was a bit bored so I decided to try a charger of nitrous, it was the most amazing nitrous experience Iíve ever had. I charged up my cream whipper and hyperventilated for a few seconds, then inhaled deeply. I hit me instantly. I could hear Startrek esque sounds as I was going deeper and deeper under, a sound like a ricochet, or a space ship. But with gears, on the way up it went up a gear, and as I came down it went down a gear. When I was completely sober the sound of cars going past the window was morphed in such a way it sounded exactly like that sound. Also I saw a green/yellow pixilate when I came out of the nitrous induced state.
Due to that last experiment into solitary nitrous oxide use, I decided to try using 2 chargers at once. I mustíve been completely knocked out, I had utterly amazing hallucinations. Unfortunately I canít remember the bulk of them now. But I woke with the same sound, and it began with the same sound. Also the whipper was left on my face with still some gas left, I really do think I was unconscious. The hallucinations had something about the desert, and when I was waking up I remember a family waving good-bye to me. Itís like I was shot into oblivion and then pulled back again. Oh and of course this is all very comfortable, innocent and euphoric.
I go on to repeat this a few more times, the hallucinations get even better. Iím noticing the reverse tolerance. I have a pattern, which seems to correspond to all the trips. Every time itís stronger. In the trip on the 8th charger the graph of the trip got so unbelievably beautiful. 9th even better! Iím making sure that the 10th is my last however. Each time it gets exponentially more detailed. Itís absolutely amazing, and I really want to do an 11th, but I mustnít. Or Iíll soon finally find myself using a lotÖ daily! Itís the most psychologically addictive thing since the snooze alarm. It fills me with a complete sense of utter urgency requiring me to take more nitrous, just to hear the next part of the story.
The nitrous tells a story in itís trip. It shows me a pattern, a graph of infinitely intricate detail. Each and every detail in the graph corresponds and seems to pre-empt things that I hear or see or do. I.e. if the song Iím listening to has a symbol crash, BEFORE I hear the crash the graph spikes.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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Fuck.
Well, I can take just a little solave that in my state the Democrats continue to improve their status, gaining a national senate and house seat. And we didn't enact any anti-gay messures. Cook County (mostly Chicago) was 80% in favor of Kerry.
The senate race here was downright pleasant. A little background: Obama wasn't the preferred candidate in the primary, but won handily.  He wasn't polling well anyway, so I think they gave up quickly. The runner up in the Republican primary had used anti-immigrant commercials; he tried to get the nomination, but the party leaders denied him. In part it's because he was going counter to Bush's immigrant policy, but I also think it's because the Republicans didn't want to be branded as racists. Then they bring in Keyes, a hopeless candidate, but also a way to throw a bone to their most conservative members. But they just ended up alienating their moderate members; they even left Keyes off the Republican voter guide that they sent to us.
Obama himself is a very progressive Democrat. He came out against the war before it started, and even spoke at anti-war rallies. While his overwhelming success (70% to 27%) was in large part due to the incompetence of his opponents, I think he would have won even against a viable opponent. So that's nice.
 It struck me yesterday, before any polls had closed or results had come in, how nice it would be if Kerry won. It would feel like we were in a civilized nation again. But we aren't.
Nice entry. It sums up my own feelings, too. I have lost faith in the American people.
Barbarians?
Yes, I think we are, but for different reasons. I've lurked for the past few months listening to your anti-Bush rhetoric - because you're such a great python programmer. But I've disagreed all the way.
You call the situation in Iraq barbarianism? I call abortion barbarianism. Guess we don't see eye to eye. A civilized nation under Kerry? A civilized nation doesn't eat their young to satisfy their selfish cravings.
Oh well, it's pleasant to see that myself and a few other million 'evangelical Christians' got out and voted. Who would have thought the election would come down to moral issues? :)
And no, I'm not trolling. You mentioned in a previous post that you couldn't understand why anyone would support Bush. It's a different set of morals and priorities, 'tis all.
btw, I used to live in Naperville. It's a shame to see Ill. go the way it has...
Hey, now that it's over, can you get back to posting about python? Top notch stuff you put up about programming. Top notch.
# Perry
Thanks Ian,
FWIW, I feel a tiny bit better after reading someone else with a similar sense of well-merited disgust at the current political state of the USA. And I suppose it encourages me to take a similar slight solace at also living and voting in a moderately civilized state (Massachusetts)--our state house became even more overwhelmingly democratic; and we have some quite good congressional reps: Frank, Markey, my own Olver, and Sen. Kennedy.
There was something nice about reading something on a Python/techie blog that was especially encouraging. I read a number of liberal political commentary sites, and I expect to read what I do there. But to see a ray of humanity's better side somewhere else entirely is a nice thing.
But still: F*ck! How come the country I live in can't show the a greater modicum of intelligence and decency. Four more years of tax dollars paying to drop bombs on Iraqi children! (And also the crackdown on civil liberties, of course; and insane fiscal policy; and fundamentalist xtianiaty being enshrined as a "state religion").
OK, I refuse to turn Ian's comment forum into an argument about abortions.

My state went for Kerry as well (Oregon). Unfortunately we also went for the anti-gay vote. After years of defeating moronic anti-gay amendments, the fuckers found one wrapped in satin the average voter could fall for.
Humorously, one could interpret the amendment as prohibiting a heterosexual from remarrying. I hope someone figures out how to enforce that.
Way to go, Oregon! Shit.
Homosexuality. Can't make it okay, man. What do you think Christian's are going after with these laws? Do you think we're just trying to make others obey our rules? Power tripping? Got nothing better to do?
Here's the skinny, straight up. It's easy to sit back and let others go down whatever road they wish. It's easy to just take care of yourself. It's easy, in the name of freedom to tell others - hey, just do whatever you want. It's okay by us.
However, understand the plight and burden of the Christian. In my heart, honestly speaking, I carry the knowledge that a life without Christ is one that will not see eternal life. You may not have the same conviction. If so, you'll completely disagree with everything I say. But with this knowledge, I see around me millions of people who are dying and going to hell. It pains me so. What do I do about it? Well, I attempt to share the good news of Jesus Christ and our need for a savior. Along with that, I attempt to show others the sin in their life and the consequences of it. Homosexuality is a sin - according to God's word, not my own petty and oft incorrect feelings.
""And have no fellowship with the unfruitful works of darkness, but rather expose them. For it is shameful even to speak of those things which are done by them in secret.""
I am commanded by my Lord to do so. Granted, in a loving manner, but I am commanded to do so.
My goodness man, I'm not trying to impose my will on someone. I'm trying to help them see the problem possessing them - one that desparately needs addressing. Creating laws that make sin right according to man's ideals have devestating consequences eternally.
I ask myself, do I honestly believe the Bible entirely, word for word? Yes. Because of that, I'm trying to help these people. I don't hate them. I don't find them repulsive. I don't wish them to be outcast by society or discriminated against. But I cannot sit by and call wrong right when the effect it has will lead people to everlasting suffering.
Check it out:
Romans 6:23
For the wages of sin is death, but the gift of God is eternal life in Christ Jesus our Lord.
Romans 3:23
for all have sinned and fall short of the glory of God
Romans 5:8
But God demonstrates His own love toward us, in that while we were still sinners, Christ died for us.

Believing this, how can I possibly vote for a law labeling sin as being right? How can someone repent if they don't know they're doing wrong? That would be the ultimate betrayal of my fellow man.
Aw man, I've gone off on a tagent again. I'm sorry Ian. This probably isn't what you want on your blog. I felt I needed to respond from a conservative point of view, but out of respect for you (it is your blog) I'll quit here.
Thanks,
Perry# Perry
Yeah. I know. I can't spell.# Perry
OK, I refuse to turn Ian's comment forum into an argument about abortions.

My state went for Kerry as well (Oregon). Unfortunately we also went for the anti-gay vote. After years of defeating moronic anti-gay amendments, the fuckers found one wrapped in satin the average voter could fall for.
Humorously, one could interpret the amendment as prohibiting a heterosexual from remarrying. I hope someone figures out how to enforce that.
Way to go, Oregon! Shit.
I too am sorely disappointed that so many in our country would forgive a man who has led us (steadfastly no doubt) into a disasterous war, costing thousands of lives, billions of dollars, and hell to pay for the next decade.# Rick Monroe
I came here for a little solace and I leave even more depressed.
My goodness man, I'm not trying to impose my will on someone. I'm trying to help them see the problem possessing them
I would have never thaught I would read such an argument in the 21st century. It reminds me the Inquisition, and all the religious prosecutions that were common at the begin of the Renaissance.
Hopefully your country is still far from being intolerant. But seen from here (Europe) it looks like the secularisation of the state is really in danger.# Nicolas
Barbarians?
So the difference between barbarians and civilization is 150,000 Ohio voters? I think you're painting with a very broad brush there.
Well, we are barbarians either way, because we all knew it was going to be close to 50/50. But will the nation act like barbarians? This came down to 150k Ohio voters.# Ian Bicking
Perry,
http://www.jesusneverexisted.com/# Bubba Joe Loudermouth


$ whoami
Grandma: I hear they're turning shipping containers into affordable housing!
— Lucy Wyman (@lucycwyman) December 29, 2018
Me to Eli: Even at Christmas, it's just docker docker docker
Lucy Wyman
Software Engineer | Bolt Influencer at Puppet
"Automation is the technology by which a process or procedure is performed without human assistance." - Wikipedia
Focus on software automation
| Costs | Savings |
|---|---|
| Time & Money | Time & Money |
| Maintenance | Maintenance |
| Sanity | Sanity |
| Security | Security |
| Flexibility | Flexibility |
| Education | Education |
Dear Amazon, I bought a toilet seat because I needed one. Necessity, not desire. I do not collect them. I am not a toilet seat addict. No matter how temptingly you email me, I'm not going to think, oh go on then, just one more toilet seat, I'll treat myself.
— Jac Rayner (@GirlFromBlupo) April 6, 2018


{% extends 'ta_app/base.html' %} {% block content %} {% if can_alert %}
{% endif %} {% include 'students/_menu.html' %}If you would like to explore current openings, please click on the button bellow.
Explore Jobs {% include 'ta_app/users/_confi_info_expiry_status.html' with items=will_expire path='students' %}| Year-Term | Total Hours |
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After more than a month off the bike, finally rode today. Slipped on ice and bashed my shoulder. Ok, but sore and cranky 🚲❄💥😱
1/6/2016, 10:33:20 AM
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After more than a month off the bike, finally rode today. Slipped on ice and bashed my shoulder. Ok, but sore and cranky 🚲❄💥😱
1/6/2016, 10:33:20 AM
Favs: 0
Retweets: 0
link


What to expect?
Cherry trees, koi fish, bridges, bonsai trees, winding paths ... here you can come to your senses and meditate peacefully. Or you can simply sit and just listen to the water flowing. Each season adorns the garden in a different outfit: a wonderful experience.


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stdlib v22.1.4 gen_event behaviour
This behavior module provides event handling functionality. It consists of a generic event manager process with any number of event handlers that are added and deleted dynamically.
An event manager implemented using this module has a standard set of interface functions and includes functionality for tracing and error reporting. It also fits into an OTP supervision tree. For more information, see OTP Design Principles.
Each event handler is implemented as a callback module exporting a predefined set of functions. The relationship between the behavior functions and the callback functions is as follows:
gen_event module Callback module
---------------- ---------------
gen_event:start
gen_event:start_link -----> -
gen_event:add_handler
gen_event:add_sup_handler -----> Module:init/1
gen_event:notify
gen_event:sync_notify -----> Module:handle_event/2
gen_event:call -----> Module:handle_call/2
- -----> Module:handle_info/2
gen_event:delete_handler -----> Module:terminate/2
gen_event:swap_handler
gen_event:swap_sup_handler -----> Module1:terminate/2
Module2:init/1
gen_event:which_handlers -----> -
gen_event:stop -----> Module:terminate/2
- -----> Module:code_change/3
As each event handler is one callback module, an event manager has many callback modules that are added and deleted dynamically. gen_event
is therefore more tolerant of callback module errors than the other behaviors. If a callback function for an installed event handler fails with Reason
, or returns a bad value Term
, the event manager does not fail. It deletes the event handler by calling callback function Module:terminate/2
, giving as argument {error,{'EXIT',Reason}}
or {error,Term}
, respectively. No other event handler is affected.
A gen_event
process handles system messages as described in sys(3)
. The sys
module can be used for debugging an event manager.
Notice that an event manager does trap exit signals automatically.
The gen_event
process can go into hibernation (see erlang:hibernate/3
) if a callback function in a handler module specifies hibernate
in its return value. This can be useful if the server is expected to be idle for a long time. However, use this feature with care, as hibernation implies at least two garbage collections (when hibernating and shortly after waking up) and is not something you want to do between each event handled by a busy event manager.
Notice that when multiple event handlers are invoked, it is sufficient that one single event handler returns a hibernate
request for the whole event manager to go into hibernation.
Unless otherwise stated, all functions in this module fail if the specified event manager does not exist or if bad arguments are specified.


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Kit Siang: Perak MB’s viral video won’t affect Pakatan’s Tanjung Piai campaign
PONTIAN, Nov 8 ― DAP adviser Lim Kit Siang said today that a viral video of Perak Mentri Besar Datuk Seri Ahmad Faizal Azumu will not affect Pakatan Harapan’s (PH) Tanjung Piai by-election campaign if the machinery is focused on the polls.
Lim said there have been attempts to cause disintegration among PH but this will not benefit anyone.
“The MB (Ahmad Faizal) has said it was taken out of context; I don't know what actually transpired, but we take it as his word and if there is anything to pursue, it will be after the by-election. At present, the focus should be on this by-election,” he told reporters when met after the Budget 2020 Forum in Kukup here.
Also present were DAP national assistant publicity secretary Yeo Bee Yin and Johor DAP chairman Liew Chin Tong.
Lim, who is also Iskandar Puteri MP, said the party will only discuss the viral video after the by-election as DAP wants to focus on winning the seat for PH.
“We need a single-minded focus on this issue (by-election) and the rest have to wait,” said the veteran politician.
Earlier today, a video clip was posted on a Facebook page showing Ahmad Faizal discussing with a group of people how he has to face DAP over certain issues, including Malay land.
The 2.47-minute video clip was said to have been taken during the Tanjung Piai by-election campaign as Pakatan Harapan's candidate Karmaine Sardini was also seen in the footage. ― Bernama


Career Summary
In May of 2015, I graduated. 15 days later, I joined Tata Consultancy Services pinning my professional career with a great headstart
I loved working and contributing in building technology that can be consumed meaningfully. I strived to keep the spirit in my alive throughout. A year and half later, I was presented with an exciting opportunity to be part of a team that effectively structures how technology is consumed in the enterprise. This experience literally shifted my perspective and opened up spaces of creativity to explore. I loved every day of my work and I couldn't wait for the sunrise to go and contribute
Nirmal is someone that will always think outside the box and find a solution to the problem at hand. You can always count on him.
Mast Global
From October 2016 to February 2020, I was working with Mast Global as a Senior Technology Analyst. Mast Global is a wholly- owned division of L brands. Together, Mast Global is the engine that powers L brands by providing technology solutions to help to “make, move and enable” their world-renowned products
At Mast Global, collaboratively over 3 years, I have had the opportunity to engage and lead in three verticals
Leading Entrepreneurial Accelerator Program (LEAP)
LEAP is an initiative to bring disruptive technologies from the startup environment to businesses and brands. I meet internal stakeholders regularly and understand their business and evaluate startups according to opportunities and needs. I have explored 100+ startups for business viability, technology feasibility & customer desirability and collaborated over 10+ for defining use cases, wireframing the PoC, prototype development and helping my organization adapt the technology
- Explored 100+ startups for business viability, technology feasibility & customer desirability
- Collaborated over 10+ startups for defining use cases, wireframing the PoC, prototype development and helping my organization adapt the technology
Innovation Lab
Working on prototypes and PoC's and pitch to brands & business leaders to help our brands onboard with cutting edge technologies. Worked independently on 23 prototypes and moved 11 of the prototypes to production. I have had the opportunity to collaborate and work with diverse teams from various touchpoints of our product supply chain.
- Worked independently on 23 prototypes and moved 11 of the prototypes to production
Nurturing the culture of Innovation
Collaborating with internal associates and working on prototypes arising from Innovation Lab or from any of the initiatives through various innovation platforms. I have had the opportunity to collaborate with 150+ associates across 20 diverse teams for a fixed timeline to build prototypes and solutions that empowered in-house innovation and technology development worth $650k
- Collaborated with 150+ associates across 20 diverse teams for a fixed timeline to build prototypes and solutions that empowered in-house innovation and technology development worth $650k
Nirmal is a rare combination of great talent, passion & hard work. He is an epitome of curiosity and I think I learnt 'how to be curious about the world around' just by watching him at work
Tata Consultancy Services
From June 2015 to October 2016, I was working as an Assistant System Engineer at Tata Consultancy Services. I worked at TCS Retail Innovation Lab and was responsible for innovating and developing solution prototypes tailored for the retail industry. I was responsible for understanding the trends in the retail industry and developing use cases. During my tenure, I have worked on multiple prototypes of full scale and pitched to various clients.
- Research emerging trends, solutions, products and start up movements in the retail technology space
- Identifies and applies new technologies to business problems to create disruptive competitive advantages for business and brands
- Worked independently on 23 prototypes and moved 11 of the prototypes to production
- Maintain the code in our network managed sand box and manage day-to-day schedule and activities of Innovation Lab environment; ensure the technology in innovation space is functional and demo ready at all times