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Hi, I'm Sahil Dhull, about to graduate from IIT Kanpur with Computer Science (CSE) as my major. My interests span across Systems, Machine Learning and Robotics. Among sports, tennis, swimming and cycling are my favourite. And I'm becoming more of a fitness freak lately 😉.
If you want to know about my journey in detail, you can visit my blog.
Course CS638A [Formal Methods in Robotics] under Prof. Indranil Saha Jan'19 - Apr'19
Studied the problem of designing a control strategy for a robot to maximize the probability of satisfaction of certain specifications formulated as LTL or PCTL formulas and co-authored a Book Chapter on this topic
Surveyed the current state of the art algorithms for this problem in discrete as well as continuous-time dynamic environments
Topics of reasearch papers were:
Temporal logic control in dynamic environments with probabilistic satisfaction guarantees
Probabilistic control from time-bounded temporal logic specifications in dynamic environments
Time-bounded reachability probabilities in continuous-time Markov decision processes
Customizing web experiences using real-time user interaction data
Motivation:
Online user behavior is typically tracked using their clicks and analytics by enterprises. However, the current state of the user is not captured through such interactions.
Exploration:
We explored how user’s current web interactions combined with the content consumed can be leveraged to first understand the user cognitively and then create customized experiences while the user is still browsing in the current session.
Approach:
We introduced 2 deep learning models, first one that predicts the user profile based on the interactions and the second that leverages this information to create a customized experience. The models take in real time data.
One of the major challenges was availability of no dataset for the problem statement.
Contribution:
Implementation and instrumentation of mechanisms to capture user information in real time from web interactions using JS libraries, which was a non-trivial task given the variance in different website designs
Hosted 2 types of surveys on Amazon Mechanical Turk (AMT) for data gathering using multiple websites
Led the conceptualization and data gathering for ‘customizing web experience’ part, along with implementation of models such as RBM and Autoencoders in PyTorch
Built a live Proof of Concept using Javascript and Flask which shows both the final output as well as the inner workings of the models used
Currently in the process of filing a patent and paper for the approach and work done in the field


WITNESS LIST Public Education Committee (Subcommittee on SB 4 Grant Programs) July 20, 2000-10:00A Special Education For: Alejandro, Mercedes (The Arc of Greater Houston) Espinosa, Carmen (Self) French, Paula (Self) Haas, Jill (Self) Murphree, Susan (Self) Paschall, Cindi (Self) Schleiss, Veronica (The Autism Society of Greater Austin) Tucker, Elizabeth (UCP of Texas) On: Anderson, David (TEA) Brady, Denise (The Arc of Texas) Carpenter, Robert (Self) Cole, Tim (Self) Elrod, Susanne (Texas Assistive Technology Partnership) Fessenden, John (TEA) Horton, Colleen (Texas Advocates Supporting Kids with Disabilities) Lambert, Kay (Advocacy, Inc.) Lenz, Gene (TEA) Speasmaker, Amerita (Self) Speasmaker, Philip (Self) Varela, Carmen (Self) SBEC For: Rodriguez, Xavier (Self) On: Eaton, Holly (TCTA) Franz, William (SBEC) Goodnight, Nancy (Self) Gregg, Brock (ATPE) Junell, Dan (SBEC) Moore, Katherine (TSTA) O'Sullivan, John (Texas Federation of Teachers) Patton, Ed (SBEC) Tackett, Pamela (SBEC) Textbooks On: Humphries, Art (Self) Smisko, Ann (TEA) Wang, Frank (Saxon Publishers)


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Science
Maths
Project
Social
History
English
Social


"Payback" - Mel Gibson and some other schmucks
With an ad slogan like "Get ready to root for the bad guy," it's clear that "Payback" isn't going to be a happy, uplifting movie. But the ads do it a terrible injustice; it is downbeat, and has its fair share of action, but it's also a thoughtful, dramatic, black comedy.
Mel Gibson is Porter, a crook so straightforward he doesn't even need a first name. After he and partner-in-crime Val Resnick (Gregg Henry) commit their latest robbery, Val and Porter's drug-addicted wife (Deborah Kara Unger) shoot him. Always ready to hold a grudge, Porter comes back five months later to get his money. Along the way, he has to deal with crooked cops, drug dealers, and the Chinese mafia, and they all want to kill him (again). The only person he can trust is a hooker (Maria Bello), and his only weapons are justifiable revenge and snappy one-liners.
Set in a blue-hued Chicago, a moody soundtrack and Gibson's periodic voiceovers set the tone and draw the viewer in. Granted, Porter's certainly not a good guy - he picks pockets, steals from panhandlers, and generally does things that ensure him a spot on Santa's `naughty' list. But everyone else in the movie is so much more despicable that you can't help but think they deserve it.
And what they deserve, they it in colorful detail.  Not everything is shown explicitly, but the camera and sound are carefully engineered to make an impact on the audience nonetheless.
"Payback" largely relies on the strength of its acting to keep the viewer involved; thanks to Mel Gibson and a strong supporting cast, it succeeds admirably. Gibson has a knack for playing the witty, violent type (as he has done in all the "Lethal Weapon" movies, and even in "The Road Warrior" to some extent), and falls into this role with a professional's grace. And the bad guys - the real bad guys - are portrayed with similar skill by people like William Devane and Kris Kristofferson.
The only short shrift is given to the ladies - there are exactly three of them in the entire two hours, one junkie and two hookers (one with an almost-comical sadomasochism complex). Beyond that, "Payback" is an entertaining amorality play, with plenty of redeeming qualities even if its characters have none.
(This review was originally published in The Capaha Arrow, the student newspaper of Southeast Missouri State University.)
The review above was posted to the
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Related links: index of all rec.arts.movies.reviews reviews


LETTER: Schiff’s impeachment circus cluttering up the boob tube
by Alan Bianco, Las VegasWhy do all the major networks, plus the three news networks, have to carry the impeachment proceedings? According to ABC News, only 13 million people tuned in. That’s about 0.5 percent of the U.S. population. People do not care and are tired of it, especially after the Mueller hearings.
Why don’t they take turns or let MSNBC, CNN and Fox carry it? We can get info online, from the Review-Journal or from streaming if we’re interested. Please give us our TV back.


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@Target(value={METHOD,TYPE,FIELD})
@Documented
@Retention(value=RUNTIME)
public @interface Field
Field
annotation will be included in JFormatter
output. The field annotation allows a number of constant properties about the
field to be declared. By default, the method's name becomes the field name as
well.
The Field
annotation provides a way to set any of the field's
properties statically. The value set using this annotation will be set
permanently as a constant for that property. If the property is ommited, its
default value will be used or if a instance method is defined that is marked
with Dynamic
annotation, then than method will be used at
runtime to obtain the value for the property it generating values for. For
example, the display
field property which is used as text to
display whenever a textual name for the field is needed, can be set
statically using this annotation:
@Field(display = "more descriptive name of the field") public int fieldA() { return 0; }or the same property can be generated dynamically at runtime by ommiting the the annotation parameter "display" in this annotation and supplying a separate instance method which generates the value:
@Dynamic(Property.DISPLAY) public String fieldADisplay() { return (fieldA() == 0) ? "FIELD_A" : "fieldA"; }Both Field.display and the runtime method can not be set at the same time. Again by default the name of the field is used as display of the field's name.
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An empty string.
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description
A short description of the field's value.
|
java.lang.String |
display
Name of the field that will be displayed.
|
java.lang.String |
format
A formatting string for the value of the field.
|
int |
length
Static length of this field within the header in bits.
|
long |
mask
Sets which bits within the field are significant.
|
java.lang.String |
name
Name of the field.
|
java.lang.String |
nicname
A short name of the field to display.
|
int |
offset
Static offset of this field into the header in bits.
|
java.lang.String |
parent
Sets the parent field's name and implicitely declares this field
to be a
subfield of the parent.
|
JFormatter.Priority |
priority
A priority this field is assigned which is used in determining
which field
to include in output depending on what JFormat.Detail level the user has
selected.
|
java.lang.String |
units
Units associated with the value of the field.
|
public static final java.lang.String DEFAULT_FORMAT
public abstract int offset
@Dynamic(Property.OFFSET)
annotation.
public abstract int length
@Dynamic(Property.LENGTH)
annotation.
public abstract java.lang.String name
public abstract java.lang.String display
public abstract java.lang.String nicname
public abstract java.lang.String format
public abstract java.lang.String units
public abstract java.lang.String description
public abstract java.lang.String parent
public abstract long mask
public abstract JFormatter.Priority priority
Priority.MEDIUM
.


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There are a number of system or built-in variables defined by awk. Awk has two types of system variables. The first type defines values whose default can be changed, such as the default field and record separators. The second type defines values that can be used in reports or processing, such as the number of fields found in the current record, the count of the current record, and others. These are automatically updated by awk; for example, the current record number and input file name.
There are a set of default values that affect the recognition of records and fields on input and their display on output. The system variable FS defines the field separator. By default, its value is a single space, which tells awk that any number of spaces and/or tabs separate fields. FS can also be set to any single character, or to a regular expression. Earlier, we changed the field separator to a comma in order to read a list of names and addresses.
The output equivalent of FS is OFS, which is a space by default. We'll see an example of redefining OFS shortly.
Awk defines the variable NF to be the number of fields for the current input record. Changing the value of NF actually has side effects. The interactions that occur when $0, the fields, and NF are changed is a murky area, particularly when NF is decreased.[7] Increasing it creates new (empty) fields, and rebuilds $0, with the fields separated by the value of OFS. In the case where NF is decreased, gawk and mawk rebuild the record, and the fields that were above the new value of NF are set equal to the empty string. The Bell Labs awk does not change $0.
[7] Unfortunately, the POSIX standard isn't as helpful here as it should be.
Awk also defines RS, the record separator, as a newline. RS is a bit unusual; it's the only variable where awk only pays attention to the first character of the value.
The output equivalent to RS is ORS, which is also a newline by default. In the next section, "Working with Multiline Records," we'll show how to change the default record separator. Awk sets the variable NR to the number of the current input record. It can be used to number records in a list. The variable FILENAME contains the name of the current input file. The variable FNR is useful when multiple input files are used as it provides the number of the current record relative to the current input file.
Typically, the field and record separators are defined in the BEGIN procedure because you want these values set before the first input line is read. However, you can redefine these values anywhere in the script. In POSIX awk, assigning a new value to FS has no effect on the current input line; it only affects the next input line.
NOTE: Prior to the June 1996 release of Bell Labs awk, versions of awk for UNIX did not follow the POSIX standard in this regard. In those versions, if you have not yet referenced an individual field, and you set the field separator to a different value, the current input line is split into fields using the new value of FS. Thus, you should test how your awk behaves, and if at all possible, upgrade to a correct version of awk.
Finally, POSIX added a new variable, CONVFMT, which is used to control number-to-string conversions. For example,
str = (5.5 + 3.2) " is a nice value"
Here, the result of the numeric expression 5.5 + 3.2 (which is 8.7) must be converted to a string before it can be used in the string concatenation. CONVFMT controls this conversion. Its default value is "%.6g", which is a printf-style format specification for floating-point numbers. Changing CONVFMT to "%d", for instance, would cause all numbers to be converted to strings as integers. Prior to the POSIX standard, awk used OFMT for this purpose. OFMT does the same job, but controlling the conversion of numeric values when using the print statement. The POSIX committee wanted to separate the tasks of output conversion from simple string conversion. Note that numbers that are integers are always converted to strings as integers, no matter what the values of CONVFMT and OFMT may be.
Now let's look at some examples, beginning with the NR variable. Here's a revised print statement for the script that calculates student averages:
print NR ".", $1, avg
Running the revised script produces the following output:
1. john 87.4 2. andrea 86 3. jasper 85.6
After the last line of input is read, NR contains the number of input records that were read. It can be used in the END action to provide a report summary. Here's a revised version of the phonelist.awk script.
# phonelist.awk -- print name and phone number. # input file -- name, company, street, city, state and zip, phone BEGIN { FS = ", *" } # comma-delimited fields { print $1 ", " $6 } END { print "" print NR, "records processed." }
This program changes the default field separator and uses NR to print the total number of records printed. Note that this program uses a regular expression for the value of FS. This program produces the following output:
John Robinson, 696-0987 Phyllis Chapman, 879-0900 2 records processed.
The output field separator (OFS) is generated when a comma is used to separate the arguments in a print statement. You may have wondered what effect the comma has in the following expression:
print NR ".", $1, avg
By default, the comma causes a space (the default value of OFS) to be output. For instance, you could redefine OFS to be a tab in a BEGIN action. Then the preceding print statement would produce the following output:
1. john 87.4 2. andrea 86 3. jasper 85.6
This is especially useful if the input consists of tab-separated fields and you want to generate the same kind of output. OFS can be redefined to be a sequence of characters, such as a comma followed by a space.
Another commonly used system variable is NF, which is set to the number of fields for the current record. As we'll see in the next section, you can use NF to check that a record has the same number of fields that you expect. You can also use NF to reference the last field of each record. Using the "$" field operator and NF produces that reference. If there are six fields, then "$NF" is the same as "$6." Given a list of names, such as the following:
John Kennedy Lyndon B. Johnson Richard Milhouse Nixon Gerald R. Ford Jimmy Carter Ronald Reagan George Bush Bill Clinton
you will note that the last name is not the same field number for each record. You could print the last name of each President using "$NF."[8]
[8] This scheme breaks down for Martin Van Buren; fortunately, our list contains only recent U.S. presidents.
These are the basic system variables, the ones most commonly used. There are more of them, as listed in Appendix B, and we'll introduce new system variables as needed in the chapters that follow.
All of our examples have used input files whose records consisted of a single line. In this section, we show how to read a record where each field consists of a single line.
Earlier, we looked at an example of processing a file of names and addresses. Let's suppose that the same data is stored on file in block format. Instead of having all the information on one line, the person's name is on one line, followed by the company's name on the next line and so on. Here's a sample record:
John Robinson Koren Inc. 978 Commonwealth Ave. Boston MA 01760 696-0987
This record has six fields. A blank line separates each record.
To process this data, we can specify a multiline record by defining the field separator to be a newline, represented as "\n", and set the record separator to the empty string, which stands for a blank line.
BEGIN { FS = "\n"; RS = "" }
We can print the first and last fields using the following script:
# block.awk - print first and last fields # $1 = name; $NF = phone number BEGIN { FS = "\n"; RS = "" } { print $1, $NF }
Here's a sample run:
$awk -f block.awk phones.block
John Robinson 696-0987 Phyllis Chapman 879-0900 Jeffrey Willis<PHONE_NUMBER> Alice Gold<PHONE_NUMBER> Bill Gold 1-707-724-0000
The two fields are printed on the same line because the default output separator (OFS) remains a single space. If you want the fields to be output on separate lines, change OFS to a newline. While you're at it, you probably want to preserve the blank line between records, so you must specify the output record separator ORS to be two newlines.
OFS = "\n"; ORS = "\n\n"
This is a simple application that processes items in your check register. While not necessarily the easiest way to balance the checkbook, it is amazing how quickly you can build something useful with awk.
This program presumes you have entered in a file the following information:
1000 125 Market 125.45 126 Hardware Store 34.95 127 Video Store 7.45 128 Book Store 14.32 129 Gasoline 16.10
The first line contains the beginning balance. Each of the other lines represent information from a single check: the check number, a description of where it was spent, and the amount of the check. The three fields are separated by tabs.
The core task of the script is that it must get the beginning balance and then deduct the amount of each check from that balance. We can provide detail lines for each check to compare against the check register. Finally, we can print the ending balance. Here it is:
# checkbook.awk BEGIN { FS = "\t" } #1 Expect the first record to have the starting balance. NR == 1 { print "Beginning Balance: \t" $1 balance = $1 next # get next record and start over } #2 Apply to each check record, subtracting amount from balance. { print $1, $2, $3 print balance -= $3 }
Let's run this program and look at the results:
$awk -f checkbook.awk checkbook.test
Beginning Balance: 1000 125 Market 125.45 874.55 126 Hardware Store 34.95 839.6 127 Video Store 7.45 832.15 128 Book Store 14.32 817.83 129 Gasoline 16.10 801.73
The report is difficult to read, but later we will learn to fix the format using the printf statement. What's important is to confirm that the script is doing what we want. Notice, also, that getting this far takes only a few minutes in awk. In a programming language such as C, it would take you much longer to write this program; for one thing, you might have many more lines of code; and you'd be programming at a much lower level. There are any number of refinements that you'd want to make to this program to improve it, and refining a program takes much longer. The point is that with awk you are able to isolate and implement the basic functionality quite easily.


Nigerians agonise over bad roads, poorly funded health centre…but no solution in sight ―CHRICED
by Lukman ABOLADEAdvertisement
A Civil Society Organisation, Resource Centre for Human Rights and Civic Education (CHRICED) said millions of Nigeria citizens are groaning due to bad roads, poorly funded and ill-equipped health centre and dilapidated school buildings.
Addressing pressmen on State of the Nation in Abuja on Monday, the Executive Director of the organisation, Ibrahim Zikirullahi, charged the Federal Government to use proceeds of corruption to alleviate sufferings of the poor and the vulnerable Nigerians.
Zikirullahi said apart from the Abacha loot, disbursed through the Conditional Cash Transfers (CCT), other recoveries made by anti-corruption agencies are idly sitting in the National Treasury of the country.
He said CHRICED on several occasions had called for the recovered funds to be used for the execution of high impact intervention projects across the nation.
On the just-concluded Kogi and Bayelsa state elections, Zikirullahi said the elections left behind a trail of sorrow tears and blood and cannot be considered as democratic elections because they fail to meet the minimum standards of free and credible polls as universally accepted.
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“Nigerians witnessed how thugs sponsored by Politicians overran the election terrain which caused the deaths of innocent citizens and disrupted the process of the election.”
The Department of State Services (DSS), depriving citizens of their freedoms in defiance of court orders should understand the damage their impunity is doing to the stability and orderly governance of the country, he said.
CHRICED further condemned the emerging culture of abuse and abridgement of citizen’s right and attacks on free press.
He called for the release of Omoyele Sowore and Dadiyata including Agba Jalingo whom he said is being hounded by the Governor of Cross River, Ben Ayade.
Speaking on the burden of multiple taxations borne by Nigerians, he said: “For us, the idea of taxation without a bold and imaginative effort to create wealth and lift citizens out of poverty is a recipe for economic disaster,” he said.
He added that between 1999 and 2018, over N67 trillion naira has been budgeted by the Federal Government and within that period, the number of out of school children has risen from nine million to ten million in Nigeria.


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Erick Matsen
\[ e^t = 1 + t + {\frac{t^2}{2!}} + {\frac{t^3}{3!}} + {\frac{t^4}{4!}} + \cdots \]
\[ P(k{\text{ events}})=e^{-\lambda}{\frac {\lambda^{k}}{k!}} \]
\[ P(k{\text{ events in interval }}t)=e^{-rt}{\frac {(rt)^{k}}{k!}} \]
\[ P(k{\text{ events in interval }}t) \propto {\frac {t^{k}}{k!}} \]
\(Q_{ij}\) is the rate of transitioning from state \(i\) to state \(j\).
So how to interpret \(\left( Q^2 \right)_{ij}\)?
Hint: \(\left( Q^2 \right)_{ij} = \sum_\ell Q_{i\ell} Q_{\ell j}\)
\[ P(k{\text{ events in interval }}t) \propto {\frac {t^{k}}{k!}} \]
\(\left( Q^k \right)_{ij}\) is the rate of transitioning from state \(i\) to state \(j\) in \(k\) jumps
\[ \left(\sum_k \frac{t^{k} Q^k}{k!}\right)_{ij} = \left(e^{tQ} \right)_{ij} \] is the probability of transitioning from \(i\) to \(j\) in time \(t\).


[§349-18] Kupuna caregivers program. (a) The executive office on aging may establish the kupuna caregivers program. The program shall provide assistance to a qualified caregiver who meets the requirements of this section.
(b) The program shall be coordinated and administered by the executive office on aging and implemented through the area agency on aging.
(c) The kupuna caregivers program shall award an allocation of funds, subject to the availability of funding and up to a maximum of $70 per day, to cover costs for the following services that would otherwise be performed by the qualified caregiver for the care recipient:
(1) Adult day care;
(2) Assisted transportation;
(3) Chores;
(4) Home-delivered meals;
(5) Homemaker services;
(6) Personal care;
(7) Respite care; or
(8) Transportation;
provided that the allocated funds shall be issued directly to the service provider upon request and receipt of an invoice for services rendered.
(d) The director may adopt rules pursuant to chapter 91 necessary for the purposes of this section. [L 2017, c 102, pt of §2]
Note
Kupuna care program rules may be used as guidance until kupuna caregivers program rules are adopted. L 2017, c 102, §5.


Reports equality comparisons between
short
and
char
values. Such comparisons may cause subtle bugs, as
short
values are signed and
char
values unsigned.
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Clips
public struct Clips
Clips is a category of Twitch API calls that interacts with Clips
. Clips are short videos
taken during live streams. Clips may be created or retrieved.
-
CreateClipResult
defines the different types of results that can be retrieved from thecreateClip
call of theClips
API. Variables are included that specify the data that was returned.- success: Defines that the call was successful. The output variable will contain all clip response data.
- failure: Defines that the call failed. Returns all data corresponding to the failed call. These data pieces are as follows:
- Data? - The data that was returned by the API
- URLResponse? - The response from the URL task
- Error? - The error that was returned from the API call
Declaration
Swift
public enum CreateClipResult
-
GetClipsResult
defines the different types of results that can be retrieved from theGet Clips
call of theClips
API. Variables are included that specify the data that was returned.- success: Defines that the call was successful. The output variable will contain all clip response data.
- failure: Defines that the call failed. Returns all data corresponding to the failed call. These data pieces are as follows:
- Data? - The data that was returned by the API
- URLResponse? - The response from the URL task
- Error? - The error that was returned from the API call
Declaration
Swift
public enum GetClipsResult
-
createClip
will run theCreate Clip
API call of the New Twitch API. This method can be used to create a clip from a stream programmatically. Twitch suggests to run theGet Clips
method to retrieve the created clip.This API call requires a token with
clips:edit
permissions.More information about the web call is available here
Seealso
Declaration
Swift
public static func createClip(tokenManager: TwitchTokenManager = TwitchTokenManager.shared, broadcasterId: String, hasDelay: Bool? = nil, completionHandler: @escaping (CreateClipResult) -> Void)
Parameters
broadcasterId
The ID of the broadcaster to create a clip for.
hasDelay
if
true
, delay is added to account for the delay between the actual stream and when they would experience that moment in the stream. Iffalse
, then the clip is captured at the immediate moment with no delay. The default value isfalse
.completionHandler
The function that should be run whenever the post is successful. There are two types of
CreateClipResult
:success
andfailure
. -
getClips(tokenManager:broadcasterId:gameId:clipIds:after:before:startedAt:endedAt:first:completionHandler:)
getClips
will run theGet Clips
API call of the New Twitch API. A broadcaster ID, game ID, or clip IDs must be provided. This method can be used to retrieve clips based on specified filters.This API call requires no special permissions.
More information about the web call is available here
Seealso
Period
Seealso
Declaration
Swift
public static func getClips(tokenManager: TwitchTokenManager = TwitchTokenManager.shared, broadcasterId: String?, gameId: String?, clipIds: [String]?, after: String? = nil, before: String? = nil, startedAt: Date? = nil, endedAt: Date? = nil, first: Int? = nil, completionHandler: @escaping (GetClipsResult) -> Void)
Parameters
tokenManager
The TokenManager whose token should be used. Singleton by default.
broadcasterId
The ID of the broadcaster to retrieve clips for. Must be specified if no other specification exists.
gameId
The ID of the game to retrieve clips for. Must be specified if no other specification exists.
clipIds
The ID of the clips to retrieve. Maximum of 100. Must be specified if no other specification exists.
after
The backwards pagination token
before
The backwards pagination token
startedAt
The preceding date in the past where all clips should be created after
endedAt
The proceeding date in the past where all clips should be created before
first
The maximum number of clips to retrieve. Default of 20; maximum of 100.
completionHandler
The function that should be run whenever the retrieval is successful. There are two types of
GetClipsResult
:success
andfailure
.


Enumerable Module
grep
Sunday PM, 20 Sept 2015
We often want to apply the same block of code onto a bunch of different objects. All the items in an array or hash, for example. This can be accomplished using loops, writing code that runs until it's touched every object it was supposed to touch. Enumerables allow us to iterate over collections of objects without having to write out lengthy and sometimes confusing loops.
The grep method iterates through a collection and picks out objects that meet a criterion. It returns them in an array. You can ask it to find all the Integers, or all the numbers within a specified range.
It can also be given a block of code to be used on all the objects it picks out! Very useful. It looks like this:
collection.grep(thing_to_pick_out) {|obj| block}
I hear that grep loves regex, but I'm sure I don't know anything about that yet.


Disney+ streaming service reaches 10 million sign-ups, shares surge
Walt Disney Co on Wednesday said its new streaming service, Disney+, has reached 10 million sign-ups since launching on Nov. 12.
REUTERS: Walt Disney Co on Wednesday said its new streaming service, Disney+, has reached 10 million sign-ups since launching on Nov. 12, sending shares up 3.5per cent to US$143.53 on the New York Stock Exchange.
In April the company said it plans to reach 60 million to 90 million Disney+ subscribers globally by 2024.
The service, which launched in the United States, Canada and the Netherlands, was hit with technical glitches that the company said were caused by higher-than-expected demand as it takes on rival Netflix Inc.
Netflix currently has over 60 million subscribers in the United States and 158 million globally.
Disney+ costs US$7 per month and features roughly 500 movies and 7,500 TV episodes from the company’s deep family entertainment catalog as well as new programming.
Disney said moving forward, it has no plans to release Disney+ subscriber data outside of the company's quarterly earnings calls.
(Reporting by Helen Coster; Editing by Lisa Shumaker)


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The Happiness scores and rankings are from the Gallup World Poll. Happiness scores were based on the Cantril ladder question where respondents are asked to think of a ladder where 10 is the best possible life for them and 0 is the worst. Finland scores the highest with 7.769 while South Sudan scoring the lowest with 2.853
A number of factors were measured in relation to 'Dystopia' a fake county that takes all of the lowest scores from each factor. Below is the percentage of the Happiness that can be explained by each of the factors. Percentages are more helpful for picking out at trends as the relative scores are typically greater for countries that have higher total Happiness
Residual refers to the unexplained contributions to the Happiness score.
GDP appears to have a somewhat positive correlation with happiness. Countries where GDP has a larger positive effect are also happier. Social Support has a stable relationship with happiness scores with most countries hover around 20 - 25%. Corruption has a similarly consistent but low result (with the outlier of Rwanda) indicating that Corruption doesn't help to increase happiness
While a large portion of each countries happiness score is residual, GDP per captia, Social Support, and Healthy Life Expectancy seem to be the best predictors of happiness


 World wide web (www) CSS is for styles of texts HTML (Hypertext Markup Language) • Text Content • Mark Up • References to images and videos • Links to other pages Symbols •
Contents
o (Elements) • Bold: Contents • Emphasis / Italics: Contents HTML Attributes •
Contents
• Link: content linked to link • Image: o No closing Tag (void tag) • Multiple Lines: contents line 1
Contents line 2 o Or you can use this for paragraphs
contents
•
inline (new line) •
block (invisible box) • Span/Div (contain their content) o text • Inline o
text
• Block HTML Documents •
-document type •
-opening HTML Tag o
title -tittle of the page • -styles of the title (fonts, colors, size) •
• contents •
-Closing HTML tag Bases for everything on the web Anything can exist on the web!


You find it time-consuming to manually format, copy and paste output values to your report or manuscript? That time is over: the psycho
package is here for you!
The data
Let’s take the example dataset included in the psycho
package.
library(psycho)
library(tidyverse)
df <- psycho::emotion %>%
select(Participant_ID,
Emotion_Condition,
Subjective_Valence,
Autobiographical_Link)
summary(df)
Participant_ID Emotion_Condition Subjective_Valence Autobiographical_Link
10S : 48 Negative:456 Min. :-100.000 Min. : 0.00
11S : 48 Neutral :456 1st Qu.: -65.104 1st Qu.: 0.00
12S : 48 Median : -2.604 Median : 16.15
13S : 48 Mean : -18.900 Mean : 28.99
14S : 48 3rd Qu.: 7.000 3rd Qu.: 59.90
15S : 48 Max. : 100.000 Max. :100.00
(Other):624 NA's :1
Our dataframe (called df
) contains data from several participants, exposed to neutral and negative pictures (the Emotion_Condition
column). Each row corresponds to a single trial. During each trial, the participant had to rate its emotional valence (Subjective_Valence
: positive - negative) experienced during the picture presentation and the amount of personal memories associated with the picture (Autobiographical_Link
).
Our dataframe contains, for each of the 48 trials, 4 variables: the name of the participant (Participant_ID
), the emotion condition (Emotion_Condition
), the valence rating (Subjective_Valence
) and the Autobiographical Link (Autobiographical_Link
).
Fit the model
Let’s fit a linear mixed model to predict the autobiographical link with the condition and the subjective valence.
library(lmerTest)
fit <- lmer(Autobiographical_Link ~ Emotion_Condition * Subjective_Valence + (1|Participant_ID), data=df)
summary(fit)
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Autobiographical_Link ~ Emotion_Condition * Subjective_Valence +
(1 | Participant_ID)
Data: df
REML criterion at convergence: 8555.5
Scaled residuals:
Min 1Q Median 3Q Max
-2.2682 -0.6696 -0.2371 0.7052 3.2187
Random effects:
Groups Name Variance Std.Dev.
Participant_ID (Intercept) 243.1 15.59
Residual 661.4 25.72
Number of obs: 911, groups: Participant_ID, 19
Fixed effects:
Estimate Std. Error df
(Intercept) 25.52248 4.23991 31.49944
Emotion_ConditionNeutral 6.13715 2.66993 895.13045
Subjective_Valence 0.05772 0.03430 898.46616
Emotion_ConditionNeutral:Subjective_Valence 0.16140 0.05020 896.26695
t value Pr(>|t|)
(Intercept) 6.020 1.09e-06 ***
Emotion_ConditionNeutral 2.299 0.02176 *
Subjective_Valence 1.683 0.09280 .
Emotion_ConditionNeutral:Subjective_Valence 3.215 0.00135 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Emt_CN Sbjc_V
Emtn_CndtnN -0.459
Sbjctv_Vlnc 0.455 -0.726
Emtn_CN:S_V -0.308 0.301 -0.676
The analyze function
The analyze
function, available in the psycho
package, transforms a model fit object into user-friendly outputs.
results <- analyze(fit, CI = 95)
Summary
Summarizing an analyzed object returns a dataframe, that can be easily saved and included in reports. It also includes standardized coefficients, as well as bootstrapped confidence intervals (CI) and effect sizes.
summary(results) %>%
mutate(p = psycho::format_p(p))
| Variable | Coef | SE | t | df | Coef.std | SE.std | p | Effect_Size | CI_lower | CI_higher |
|---|---|---|---|---|---|---|---|---|---|---|
| (Intercept) | 25.52 | 4.24 | 6.02 | 31.50 | 0.00 | 0.00 | < .001*** | Very Small | 17.16 | 33.93 |
| Emotion_ConditionNeutral | 6.14 | 2.67 | 2.30 | 895.13 | 0.10 | 0.04 | < .05* | Very Small | 0.91 | 11.37 |
| Subjective_Valence | 0.06 | 0.03 | 1.68 | 898.47 | 0.09 | 0.06 | = 0.09° | Very Small | -0.01 | 0.12 |
| Emotion_ConditionNeutral:Subjective_Valence | 0.16 | 0.05 | 3.22 | 896.27 | 0.13 | 0.04 | < .01** | Very Small | 0.06 | 0.26 |
Moreover, the print
method return a nicely formatted output that can be almost directly pasted into the manuscript.
print(results)
The overall model predicting Autobiographical_Link (formula = Autobiographical_Link ~ Emotion_Condition * Subjective_Valence + (1 | Participant_ID)) successfully converged and explained 32.48% of the variance of the endogen (the conditional R2). The variance explained by the fixed effects was of 7.66% (the marginal R2) and the one explained by the random effects of 24.82%. The model's intercept is at 25.52 (SE = 4.24, 95% CI [17.16, 33.93]). Within this model:
- The effect of Emotion_ConditionNeutral is significant (beta = 6.14, SE = 2.67, 95% CI [0.91, 11.37], t(895.13) = 2.30, p < .05*) and can be considered as very small (std. beta = 0.098, std. SE = 0.043).
- The effect of Subjective_Valence is significant (beta = 0.058, SE = 0.034, 95% CI [-0.0097, 0.12], t(898.47) = 1.68, p = 0.09°) and can be considered as very small (std. beta = 0.095, std. SE = 0.056).
- The effect of Emotion_ConditionNeutral:Subjective_Valence is significant (beta = 0.16, SE = 0.050, 95% CI [0.063, 0.26], t(896.27) = 3.22, p < .01**) and can be considered as very small (std. beta = 0.13, std. SE = 0.041).
The intercept (the baseline level) corresponds, here, to the negative condition with subjective valence at 0 (the average, as the data is standardized). Compared to that, changing the condition from negative to neutral does not induce any significant change to the outcome. However, in the negative condition, there is a trending linear relationship between valence and autobiographical memories: the more an item is positive the more it is related to memories. Finally, the interaction is significant: the relationship between valence autobiographical memories is stronger (more positive) in the neutral condition.
Credits
This package helped you? You can cite psycho
as follows:
- Makowski, (2018). The psycho Package: an Efficient and Publishing-Oriented Workflow for Psychological Science. Journal of Open Source Software, 3(22), 470. https://doi.org/10.21105/joss.00470
Previous blogposts
- Copy/paste t-tests Directly to Manuscripts
- APA Formatted Bayesian Correlation
- Fancy Plot (with Posterior Samples) for Bayesian Regressions
- How Many Factors to Retain in Factor Analysis
- Beautiful and Powerful Correlation Tables
- Format and Interpret Linear Mixed Models
- How to do Repeated Measures ANOVAs
- Standardize (Z-score) a dataframe
- Compute Signal Detection Theory Indices


Delivery Cadence
WEEKLY CADENCE
MON - 10:30AM Talent/Recruiting/Delivery/Growth meeting (mandatory)
MON - COB - DE’s investigate and explain week-over-week Variance
TUE - 8:30AM Projections Meeting to explain WoW variance (mandatory)
TUE - 11:30AM Projections email ready to send
THUR - 8:00AM Growth Momentum and Pipeline Review:
FRI - 9:30AM Projections Sync (optional)
FRI - 10:30AM Integration Meeting (optional)
FRI - COB - DE’s - All FBA changes need to be complete
FRI - COB - DE’s - Complete Client Trending Report
FRI - COB - DL’s - Complete Project Health Report


func DefaultABCFactory(conn *grpc.ClientConn) orderer.AtomicBroadcastClient
func DefaultConnectionFactory(channelID string, endpointOverrides map[string]*comm.OrdererEndpoint) func(endpointCriteria comm.EndpointCriteria) (*grpc.ClientConn, error)
func NewBFTDeliveryClient( chainID string, connFactory comm.ConnectionFactory, endpoints []comm.EndpointCriteria, clFactory clientFactory, ledgerInfoProvider blocksprovider.LedgerInfo, msgVerifier MessageCryptoVerifier, ) *bftDeliveryClient
func NewBroadcastClient(prod comm.ConnectionProducer, clFactory clientFactory, onConnect broadcastSetup, bos retryPolicy) *broadcastClient
NewBroadcastClient returns a broadcastClient with the given params
func NewDeliverService(conf *Config, connConfig ConnectionCriteria) (*deliverServiceImpl, error)
NewDeliverService construction function to create and initialize delivery service instance. It tries to establish connection to the specified in the configuration ordering service, in case it fails to dial to it, return nil
Config dictates the DeliveryService's properties, namely how it connects to an ordering service endpoint, how it verifies messages received from it, and how it disseminates the messages to other peers
type Config struct { // ConnFactory returns a function that creates a connection to an endpoint ConnFactory func(channelID string, endpointOverrides map[string]*comm.OrdererEndpoint) func(endpointCriteria comm.EndpointCriteria) (*grpc.ClientConn, error) // ABCFactory creates an AtomicBroadcastClient out of a connection ABCFactory func(*grpc.ClientConn) orderer.AtomicBroadcastClient // CryptoSvc performs cryptographic actions like message verification and signing // and identity validation CryptoSvc api.MessageCryptoService // Gossip enables to enumerate peers in the channel, send a message to peers, // and add a block to the gossip state transfer layer Gossip blocksprovider.GossipServiceAdapter }
ConnectionCriteria defines how to connect to ordering service nodes.
type ConnectionCriteria struct { // Endpoints specifies the endpoints of the ordering service. OrdererEndpoints []string // Organizations denotes a list of organizations Organizations []string // OrdererEndpointsByOrg specifies the endpoints of the ordering service grouped by orgs. OrdererEndpointsByOrg map[string][]string // OrdererEndpointOverrides specifies a map of endpoints to override. The map // key is the configured endpoint address to match and the value is the // endpoint to use instead. OrdererEndpointOverrides map[string]*comm.OrdererEndpoint }
DeliverService used to communicate with orderers to obtain new blocks and send them to the committer service
type DeliverService interface { // StartDeliverForChannel dynamically starts delivery of new blocks from ordering service // to channel peers. // When the delivery finishes, the finalizer func is called StartDeliverForChannel(chainID string, ledgerInfo blocksprovider.LedgerInfo, finalizer func()) error // StopDeliverForChannel dynamically stops delivery of new blocks from ordering service // to channel peers. StopDeliverForChannel(chainID string) error // UpdateEndpoints updates the ordering endpoints for the given chain. UpdateEndpoints(chainID string, connCriteria ConnectionCriteria) error // Stop terminates delivery service and closes the connection Stop() }
type EndpointUpdater interface { // UpdateEndpoints updates the endpoint of the underlying client UpdateEndpoints(endpoints []comm.EndpointCriteria) // GetEndpoint retrieves the orderer endpoint from which the client is receiving blocks (as opposed to headers) GetEndpoint() string }
MessageCryptoVerifier defines message verification methods, and is subset of gossip/api/MessageCryptoService.
type MessageCryptoVerifier interface { // VerifyHeader returns nil when the header matches the metadata signature, but it does not compute the // block.Data.Hash() and compare it to the block.Header.DataHash, or otherwise inspect the block.Data. // This is used when the orderer delivers a block with header & metadata only (i.e. block.Data==nil). // See: gossip/api/MessageCryptoService VerifyHeader(chainID string, signedBlock *common.Block) error }
| Name | Synopsis |
|---|---|
| .. | |
| blocksprovider | |
| mocks |


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JavaScript Array Methods
toString()
The toString() method returns an array as a comma separated string:


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