Main Scientific Communications
Journées Graphes et Algorithmes 2020
On the complexity of the dynamic Steiner problem. Presentation on the complexity of the dynamic Steiner problem during the annual meeting of French working groups on graphs and algorithms. This work was made with Stefan Balev, Yoann Pigné and Éric Sanlaville.
Visit JGA 2020 page here.
See abstract of this presentation (in french) here and the presentation slides here.
AlgoTel Conference 2020
Non-dominated Persistent Connected Components Detection in Dynamic Graphs. Presentation of persistent connected components and a polynomial algorithm to detect the non-dominated ones in a dynamic graph and experimental results during AlgoTel 2020. This work was made with Yoann Pigné and Éric Sanlaville.
Visit AlgoTel 2020 page here.
See abstract of this presentation (in french) here.
ROADEF Conference 2020
Non-dominated Persistent Connected Components Detection in Dynamic Graphs. Presentation of persistent connected components and a polynomial algorithm to detect the non-dominated ones in a dynamic graph and experimental results during the annual meeting of the French Operations Research and Decision Support Society. This work was made with Yoann Pigné and Éric Sanlaville.
Visit ROADEF 2020 page here.
Journées Graphes et Algorithmes 2019
Persistent connected components in dyamic graphs. Presentation of persistent connected components and an algorithm to compute them during the annual meeting of French working groups on graphs and algorithms. This work was made with Yoann Pigné and Éric Sanlaville.
Visit JGA 2019 page here.
See abstract of this presentation (in french) here and the presentation slides here.
EURO Conference 2019
Presentation of persistent connected components, an extension of connected components in temporal networks, and an algorithm to retrieve them. This presentation was part of stream Algorithms on Graphs during the annual EURO conference. This work was made with Yoann Pigné and Éric Sanlaville.
Visit EURO 2019 page here.
See abstract of this presentation here.
ROADEF Conference 2019
Shortest paths algorithm for the minimum cost flow problem on dynamic graphs. Presentation of an SSP-inspired algorithm for minimum cost flow problem on dynamic graphs and experimental results during the annual meeting of the French Operations Research and Decision Support Society. This work was made with Maciej Drozdowski, Yoann Pigné and Éric Sanlaville.
Visit ROADEF 2019 page here.
See abstract of this presentation (in french) here.
Cologne Twente Workshop 2018
Presentation of an SSP-inspired algorithm for minimum cost flow problem on dynamic graphs during CTW18. This work was made with Maciej Drozdowski, Yoann Pigné and Éric Sanlaville.
Visit CTW18 page here.
See abstract of this presentation here.
ROADEF Conference 2018
Algorithms on dynamic graphs: focus on flow problems. Presentation of maximum flow problem on dynamic graphs during the annual meeting of the French Operations Research and Decision Support Society. This work was made with Yoann Pigné and Éric Sanlaville.
Visit ROADEF 2018 page here.
See abstract of this presentation (in french) here.


I'd request a Fighter/Paladin/CoT build, preferrably heavy paladin/CoT, if someone is willing! thanks
Here you go ..use this..
Search Engine
What, exacly would you want in it? CHA-based or STR-based? What feats would you prefer?
The most common build is a FTR 4/Pally 26/CoT 10. _________________ Wave upon wave of demented avengers marched cheerfully out of obscurity into the dream...


Columns in the table can be hidden or shown based on the dynamic needs of the application or the width of the
browser window. This is handled with the hidden
property in the columns array supplied to DuxTable.
The hidden property for a column can be a boolean value, a function that returns a boolean value, or an object that specifies whether or not a column is hidden based on width of the browser window. The width breakpoints are the same as defined in Bootstrap 4. The breakpoints are listed below. Following is a sample columns array.
const isColumnHidden = () => { return true; } const columns = [ { title: 'Column 1', field: 'col1value', hidden: false }, { title: 'Hidden Column', field: 'hiddenvalue', hidden: isColumnHidden } ];
A column can be dymanically shown or hidden based on the width of the browser window. This is done by specifying an object with boolean values for various widths. The breakpoints are the same as those in Bootstrap 4. These breakpoints are:
| Breakpoint | Description |
|---|---|
| xs | Extra small devices (portrait phones, less than 576px) |
| sm | Small devices (landscape phones, 576px and up) |
| md | Medium devices (tablets, 768px and up) |
| lg | Large devices (desktops, 992px and up) |
| xl | Extra large devices (large desktops, 1200px and up) |
A breakpoint object might look something like this:
const hidden = { xs: true, sm: true, md: false };
Notice the hidden object is missing lg
and xl
. If a size breakpoint is missing from the
object, the breakpoint for the next smallest screen size is used. In this case, browsers with large or extra-large
windows would fall back to the medium breakpoint. The column would be hidden on small and extra-small browser
windows. If the browser window is the xs
size and that breakpoint is missing from the object, the
next lowest breakpoint is used instead.
In this example, the columns hide at browser widths more narrow than their breakpoint. For example, the Column Xl will be hidden when the browser window is smaller than xl. Try resizing the browser window to see the columns hide and show.


The main documentation for the use and set up of the project are given here in the form of a user and system manual. Further details on the management can also be viewed via the Gantt charts and meeting minutes provided for the team members and interaction with the clients.
Over the course of the project we had held numerous meetings each week in order to make sure we were on track with our work and also to make sure we were making progress as per our timeline. While these meeting minutes can also be found in the biweekly reports, they are all listed here for convenience.
The meetings which occurred during October were mainly for choosing which project we would work on, setting up the initial tools for communication and also the second half was for the research we undertook and verifying our approaches in the meetings.
December meetings were mainly to finalise our proposals and meetings were based around collating the research done so we could start deciding how to implement our ideas. Also a few meetings were spent on deciding how to build up our project website.
The November meetings were mainly based around more focused research around the bots and digital assistants, as well as the architecture we would look to use. We also verified what tools we should be learning during these meetings.
Development began on the app and all team members began work on their respective parts - the bot, digital assistant and LUIS. Most of the intial meetings were related to setting up of the frameowrks and technical details.
Development continued and we met with representatives from Microsoft to discuss implementation of LUIS and other parts of the bot framework and also met to discuss further progress on the respective parts.
Every two weeks our team completed a report to outline our progress, individual contribution, tasks completed, tasks to be completed and a summary of our meetings. You may download each report to view or to keep a record.
This report was compiled after the initial meeting with the client, TA and our team members and was mostly about how we decided to structure the work for the coming weeks and the very beginning of our research.
This report was created during scenario week and reading week - which meant more time was spent on research but also looking at how to implement some of our ideas and starting our coding for purposes of getting a feel of the bots.
After 2 weeks had passed and we had a better idea of the project the following report mainly outlined the research we would have to undertake and getting to know the bots and digital assistants better.
In this week the focus was to start fleshing out the website as well as testing out our code for the experimentation we had begun and finalising the system architecture and collating the results of our research to come to a decision.


| Aircraft Insurance Application |
| Quotation | X Insurance | Binder | Policy/Quote No | AC273991-00 |
| Insurance Requested from: | 06/30/2011 | to | 06/30/2012 | 12:01 A.M. Local Time at Applicant's Address |
| Present Insurance Company: | Expiration Date: |
| Name of Applicant: | JOJO JOHNSON |
| Address: | 555 CENTER RD. |
| City: | LAKE WOBEGON | State: | IA | Zip Code: | 52501 |
| Mailing Address (if different): |
| City: | State: | Zip Code: |
| Phone | Off: | Res. |<PHONE_NUMBER> | Fax |
| Occupation of Applicant is: |
| Applicant is a(n): | X Individual | Business Cooperation | Holding Cooperation | Partnership | LLC | Other (specify): |
| If a cooperation, partnership or limited liability organization formed for the primary purpose of ownership of the aircraft, please list | |
| all partners, sharholders, members, officers, and/or directors: | |
| Applicant interest in the Aircraft is: | X Sole Owner | Sole Owner Subject to Lienholder's Security Interest | Lessee |
| Aircraft(s) will be: | X Hangared | Tied Down at: Airport Code: | OOA | City: | OSKALOOSA | State: | IA |
| Aircraft Description(s) & Coverage((use additional paper if necessary) |
| Aircraft 1 |
| FAA | Year | Agreed | Deductibles | Hull | ||||
| N-No. | Mfr. | Make | Model | Coverage | Value | NIM | IM | Premium |
| 101PQ | 1962 | CESSNA | 210B | Full Flight | 26500 | 1000 | 1000 | $ 676.00 |
| Liability | Liability | Limited Liability | Medical | Liability & M.P. | |
| Type | per Occurrence | per Passenger | Payment | Premium | |
| 0 | 0 | 3000 | $ 408.00 |
| A.C. | A.C. | A.C. | Gear | Engine | Engine(s) | # of | Total A.C. | ||
| Use | Type | Category | Airworthiness | Type | Preassurized | Type | H.P. | Seats | Premium |
| 1 | Fixed Wing-Single | Landplane | Standard | RT | Yes X No |
Reciprocating | 260 | 4 | $ 1084.00 |
| Other Premium / Tax | $ | ||
| Policy Fee | $ | 100.00 | |
| Total All Aircraft | $ | 1,184.00 |
| Form AC APP (04-09) | Page 1 |
| Pilot Information |
| Pilot 1 |
| First Name | MI | Last Name | Birth Date |
Last Med. | Last BFR | Last IPC | Last School | ||||||||||||||||
| JOJO | JOHNSON | 08/25/1953 | 01/01/2010 |
|
|||||||||||||||||||
| Fixed Wing = Airplane/Glider |
|
|
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
| Total Hours | RG Hours | ME Hours | TW Hours | SEA Hours | Turbine Hours | Jet Hours | Glider Hours |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours |
| 0 | |||||||
| Rotor Wing = Helicopter/Gyroplane |
|
|
|
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|
|
|
| Total Hours | RW Hours | Piston RW Hours | Turbine RW Hours | Gyroplane Hours |
| 0 | 0 | 0 | 0 | 0 |
| FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours |
| 0 |
| Pilot 2 |
| First Name | MI | Last Name | Birth Date |
Last Med. | Last BFR | Last IPC | Last School | ||||||||||||||||
| REX | YOAKAM | 09/19/1950 | 07/01/2010 |
|
|||||||||||||||||||
| Fixed Wing = Airplane/Glider |
|
|
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
| Total Hours | RG Hours | ME Hours | TW Hours | SEA Hours | Turbine Hours | Jet Hours | Glider Hours |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours |
| 0 | |||||||
| Rotor Wing = Helicopter/Gyroplane |
|
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
| Total Hours | RW Hours | Piston RW Hours | Turbine RW Hours | Gyroplane Hours |
| 0 | 0 | 0 | 0 | 0 |
| FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours | FAA No. | MM Hours |
| 0 |
| Additional Insured, Lienholder and/or Lessor Information |
| Entity Type | N-Numbers (that relationship applies) | Lienholder's Interest Endt. Required? |
|
| Additional Insured
Lienholder Lessor |
Policy
All Aircraft Individual |
Yes
No |
|
| Aircraft(s): |
| Name | Interest (If Additional Insured) |
| Address | City | State | Zip |
| Primary Phone | Alt. Phone | Fax Number | Email Address |
| Form AC APP (04-09) | Page 1 |
| Background Information (Applicant and Pilots): |
| Please answer the following questions: Please explain in detail any "yes" answers in the space below (use additional paper if necessary): |
| 1. | Have you or any pilot shown on this application ever been involved in an aircraft or automobile accident, incident or citation? Yes No |
| 2. | Do you or any pilot shown on this application have any arrests, convictions,suspensions or revocations relating to a driver's license or airman's certificate for: FAR violations, use or possession of controlled substances or driving while intoxicated? Yes No |
| 3. | Has any insurance company cancelled, declined or refused to renew any aviation insurance for you or any pilot shown on this application? (Note: does not apply to applicants from the state of Missouri.) Yes No |
| Please explain any "yes" answers here: |
| Notice to All Applicants: "Any person who knowingly presents a false or fraudulent claim for payment of a loss or benefit or knowingly presents false information in an application for insurance is guilty of a crime and may be subject to fines and confinement in prison." |
| The following Fraud Warnings are specific and applicable to the state(s) as specified below: |
| I/we confirm that all the information given in this application is true and complete to the best of my/our knowledge and that no information has been withheld or suppressed. I/we agree that this application and the terms of any conditions of the policy in use by the insurer shall be the basis for any contract between me/us and the Insurer. |
| I/we understand that no insurance is in force unless and until the Insurance Company through its aviation manager binds insurance coverage, or issues a policy. I/we authorize the insurance company through its aviation manager to investigate the qualifications or statements contained in this document. |
| Signature of Applicant or Executive: | Title: | Date: |
| This application does not commit the Company to any liability nor make the Applicant liable for any premium unless and until the Company agrees to effect this insurance. |
| Form AC APP (04-09) | Page 1 |


fun getReusable(): ReusableDeleteStatement
Gives a reference to a reusable statement object. This allows clients to avoid the (small) lookup overhead for a frequently-used delete statement.
Usage:
val intParam = Parameter(Types.sqlInt)
val deleteFrom = (db.deleteFrom(TestTable) + " WHERE " + TestTable.id + "=" + intParam).getReusable()
val id = <...>
val deleted = deleteFrom run {
it[intParam] = id
}
Throws IllegalStateException if this statement is not cacheable.


4.3. Function Comparison Between JSR-compliant Batch Application and Nablarch Batch Application¶
This section compares the following features:
| Function | Compliant with JSR352 [1] | Nablarch batch |
|---|---|---|
| Arbitrary parameters can be configured at startup | JSR | A To the manual |
| Simultaneous execution of the same batch applications can be prevented | A To Javadoc |
A To the manual |
| Batch applications that are running, can be safely stopped from the outside | JSR | A To the manual |
| The maximum number of records to be processed in one execution can be specified. | C [2] |
A To the manual |
| A fixed number of record units can be committed | JSR | A To the manual |
| Can re-run from the point of failure | JSR | B [3] |
| Business processes can be executed in parallel by multiple threads | JSR | A To the manual |
| Processing can be continued ignoring specific exceptions (processing can be continued after rollback) | JSR | C [4] |
| Processing can be retried when a specific exception occurs | JSR | B [5] |
| The process to be executed next can be switched based on the batch application result | JSR | C [6] |
| Batches can be executed by monitoring input data sources at regular intervals | C [7] | A To the manual |
| [1] | JSR parts are in accordance with the specifications defined in JSR352. For details, refer to the specification of JSR352 (external site). |
| [2] | The property to specify the maximum number to read in a single run can be included in the implementation class ItemReader. |
| [3] | Re-execution from the point of failure is possible by using ResumeDataReader (read with resume function). However, this feature is available only when a file is input. When other data is input, design and implementation are required in the application. |
| [4] | Add a handler to continue processing ignoring specific exceptions. |
| [5] | Retry Handler retries for exceptions that can be retried, but a simple retry cannot be performed for data where an exception has occurred, as in JSR352. Exceptions to be retried cannot be specified flexibly with Retry Handler. If the requirements cannot be met with the Retry Handler (simple retry of the data where the exception occurred or to specify the exception flexibly), provide support by adding a handler. |
| [6] | Use a job scheduler, etc. For example, taking measures such as switching the job to be executed next based on the exit code will be necessary. |
| [7] | In JSR352-compliant batch applications, it is not possible to realize a batch process for monitoring an input data source at regular intervals. For this reason, if such a batch application is necessary, realize using the resident batch of Nablarch batch application. |


Black to Play 15
b3-w2/5
pips Black=160 White=140
(CorrectAnswer= 0/0, ErrorScore= 0)
1. 13/8 6/5 Eq.: -0.090 0.8% 13.1% 46.4% 53.6% 20.5% 1.7% 2. 24/23 13/8 Eq.: -0.176 (-0.086) 0.8% 12.6% 45.4% 54.6% 23.3% 1.1% 3. 13/7 Eq.: -0.182 (-0.092) 0.7% 13.1% 44.4% 55.6% 20.0% 1.3% 4. 24/23 6/1* Eq.: -0.186 (-0.096) 0.7% 12.6% 45.0% 55.0% 22.5% 1.3% 5. 7/2*/1* Eq.: -0.311 (-0.221) 0.8% 14.1% 41.1% 58.9% 23.3% 1.8%


The iOS app user onboarding helps new pet sitters create quality profiles to ensure enough information is included for them to succeed in securing their first house sit.
As a designer on the sprint team, I was involved throughout the sprint process focusing on the prototype design as well as facilitating some of the usability testing and user interviews. Design iterations based on qualitative feedback were iterated by myself and finally by Tjasa, our lead designer.
A percentage of new sitters don't succeed in getting a housesit in their first three months of becoming a member which leads to refunds or discontinued memberships if they don't succeed at all.
Increase pet sitter success ensuring new members get a house sit in their first three months of signing up to the service.
Increase new pet sitters success over the next six months.
We decided to run a Google-style design sprint to come up with validated solutions.
The Design Sprint is a process for solving problems through research, designing, prototyping and testing ideas with users.
The process follows six phases: Understand, Define, Sketch, Decide, Prototype, and Validate.
We met in a space for 5 consecutive days from Monday to Friday to carry out the workshop.
The Design Sprint involved eight members from across the company with different expertise:
The workshop began with determining the long-term goal of the product - where we wanted to be in the next six months.
We wanted to increase pet sitter success ensuring new members get a house sit in their first three months of signing up to the service.
Focusing on the end goal of increasing pet sitter success, we drew out a customer map involving customers and key players. The flow chart shows how users interact with the product to reach the end goal.
New users to our service would complete a profile, search for house sits and apply. One of the deciding factors of their success was understanding what homeowners looked for in prospective pet sitters.
We interviewed experts on the sprint team and from other areas of the business - asking about anything related to the journey map: the vision, how things work, and previous efforts. This information continued to inform the map and the goals.
While experts were interviewed, each sprint member took notes on any paint points or insights they heard and positively reframed them as open-ended questions. "The How Might We" method ensures teams look for opportunities rather than jumping to solutions or get bogged down by problems.
An interesting insight we heard from a customer champion informed us that new pet sitters weren't adding enough information to their profiles to be appealing to homeowners.
Once we finished the expert interviews, all How Might We notes were gathered and stuck onto a wall where we physically grouped them into similar themes. Each group was labelled, and notes were sorted enough to move on to prioritisation. This exercise followed Affinity Mapping.
We had 14 total groups after sorting the notes, where many opportunities were labelled under the themes of Education, Matchmaking, and Completing Profiles.
To highlight areas of emphasis to consider for the rest of the sprint, we voted on which How Might We opportunities we felt were most important. Each sprint member made two votes represented by dots they added to the sticky notes they liked.
After the voting was over, we took the How Might We notes with the most votes and placed them on our map. The notes corresponded with specific areas on the map narrowing down areas of focus for the sprint. Lisa, our decider then circled the most important customer and one target moment on our map.
Pet sitters and user onboarding were chosen as the targets for our sprint.
At the end of the day we had determined our:
To jump-start our inspiration we spent some time looking at solutions from other products, from different domains. Each member spent 3 minutes demoing what they liked from their favourite product while the rest of the team took notes and sketched ideas.
Some products we looked at for inspiration:
Before jumping into sketching out ideas, we took some time to look at the map and decide if the target was focused enough for the team to work together on the same part of the problem or if we needed to divide the team and work of different areas.
We decided that the target was focused enough for the entire team to work together on the onboarding area.
With lunch in our bellies, we moved on to the four-step sketching exercise.
We spent 20 minutes silently walking around the room and gathering notes. Note taking allowed the team to review the goals, opportunities, and inspiration collected and prepared us to translate our ideas into visual sketches.
Once everyone had reviewed all of the information and made notes, each member jotted down rough ideas on a sheet of paper. The ideas can take any shape such as doodles, headlines, sketches - anything which enables thoughts to form into ideas.
Crazy 8s allowed us to take our strongest ideas and sketch them into eight variations in just eight minutes. We started by folding a piece of paper into eight sections then sketched one idea in each panel every minute.
Finally, we each took our best idea for the solution and sketched it out in a three-panel storyboard format because "products and services are more like movies than snapshots."
At the end of the day we had:
We couldn't prototype and test all of our solutions - we needed one combined plan, so we followed a five-step process for deciding on the best idea.
We hung all the solution sketches on a wall so everyone could take a look at them.
Silently, we looked at a solution sketch and used sticky dots to vote on features we thought were worth prototyping.
We then spent 3 minutes per sketch discussing the highlights of each solution, taking notes on standout ideas.
To collect the group's opinions, we each silently voted on ideas we liked the most using large sticky dots.
With all the votes in place, Lisa our decider voted on three final solutions we continued to prototype and test.
As we had more than one winning solution sketch from the supervote, the whole team discussed whether to create multiple prototypes or combine them into one solution.
We decided to combine all ideas into an all-in-one solution.
Taking the winning sketches, we strung them together into a storyboard that narrowed in on five key moments used to illustrate the solution. The flow informed the prototype and user-interview script.
The storyboard opens with a welcome screen then guides the user through the onboarding steps involving verification, filling out personal information, pet preferences, and a profile preview.
At the end of the day we had:
We made use of:
To speed things up, we assigned different tasks to each team member.
As the makers, myself and Tjasa sketched out specific details to help us prototype the storyboard.
Using our Design System and Interface Kit we rapidly created the screens in Sketch then turned them into an interactive prototype using inVision.
Ed, our stitcher, ran through the prototype narrating the journey as we checked against the storyboard to ensure we hadn't missed anything. This allowed us to iron out any issues before putting the prototype in front of our users the next day.
At the end of the day we had:
We set up two rooms, one for the usability testing/interviews and one for note-taking.
As the inVision prototype was designed for iPhone, we set up mobile device screen sharing and a webcam to view the users' reactions when running through the test script.
We hosted six users to test the prototype. The format looked something like this:
In the other room, team members wrote notes on observations, quotes, and interpretations of what happened. These were taken on sticky notes and distributed to a whiteboard.
After completing the interviews, the entire team silently reviewed the sticky notes then made notes on observed patterns.
We continued to iterate the designs based on the observed patterns and validated new ideas using remote user testing. This approach allowed us to gain immediate qualitative feedback while keeping the time invested in the end product low. Results have been very positive with users so far as we have ironed out most issues highlighted form the sprint testing phase.
The next step is to finalise the onboarding experience and to continually iterate based on user feedback. Once the onboarding feature is rolled out, we will keep track of quantitative data to measure the impact the onboarding solution has had on pet sitter success.


| Number of Classes | Line Coverage | Mutation Coverage | Test Strength |
|---|---|---|---|
| 5 | 73% | 11% | 100% |
| Name | Line Coverage | Mutation Coverage | Test Strength |
|---|---|---|---|
| DefaultJavaxMailConfigurer.java | 89% |
100% |
100% |
| JavaxMailBuilder.java | 72% |
0% |
0% |
| JavaxMailConsistencyChecker.java | 79% |
33% |
100% |
| OverrideJavaxMailResolver.java | 69% |
0% |
0% |
| UsernamePasswordAuthenticatorBuilder.java | 56% |
0% |
0% |


The Top Five Places To Learn To Dive
Divers are really astronauts; gliding weightless through the ocean we observe alien worlds carpeted in vast fields of colourful corals with equally bizarre, enthralling inhabitants - from the foreign clicks of dolphins communicating to minute technicolour slugs (nudibranch). And best yet, you don't need years of gruelling training or a rocket to experience these watery worlds, just four days and a eagle-ray-eyed (sorry) ground control.


方法一：
const user = {
name: 'Kapil Raghuwanshi',
gender: 'Male'
};
const college = {
primary: 'Mani Primary School',
secondary: 'Lass Secondary School'
};
const skills = {
programming: 'Extreme',
swimming: 'Average',
sleeping: 'Pro'
};
const summary = {...user, ...college, ...skills};
输出:{
gender: "Male"
name: "Kapil Raghuwanshi"
primary: "Mani Primary School"
programming: "Extreme"
secondary: "Lass Secondary School"
sleeping: "Pro"
swimming: "Average"
}
方法二：
Object.assign({},user,college,skills)
输出:{
gender: "Male"
name: "Kapil Raghuwanshi"
primary: "Mani Primary School"
programming: "Extreme"
secondary: "Lass Secondary School"
sleeping: "Pro"
swimming: "Average"
}


Legally Blonde (2001) Reese Witherspoon, Luke Wilson, Selma Blair, Matthew Davis, Victor Garber, Jennifer Coolidge, Holland Taylor, Ali Larter. Screenplay by Karen McCullah Lutz and Kirsten Smith, based on the novel by Amanda Brown. Directed by Robert Luketic. 95 minutes. Rated PG-13, 3 stars (out of five stars)
Review by Ed Johnson-Ott, NUVO Newsweekly www.nuvo.com Archive reviews at http://reviews.imdb.com/ReviewsBy?Edward+Johnson-Ott To receive reviews by e-mail at no charge, send subscription requests to<EMAIL_ADDRESS>or e-mail<EMAIL_ADDRESS>with the word "subscribe" in the subject line.
Don't expect an in-depth look at "Legally Blonde" here. Doing a critical analysis of this movie would be akin to dissecting tofu. "Legally Blonde" is fizzy and featherweight, an underachieving, yet affable cousin to "Clueless" and "Romy and Michelle's High School Reunion." The movie has two things going for it. First, the filmmakers clearly realize they are making a formulaic, crowd-pleasing girl power movie and they know how to do it. Second, Reese Witherspoon is so gifted that she finds and maintains the perfect balance between her character's air-headed presentation style and her underlying strength and smarts.
Elle Woods (Witherspoon) is the ever-smiling queen of her school. Bedecked in a seemingly endless series of kicky outfits (with the highlight on pink), she was Miss June in the campus calendar and a runner-up for Miss Hawaiian Tropic. Elle is also totally devoted to her boyfriend, Warner (Matthew Davis). When he asks her to dinner at their special place, she is sure he is going to pop the question.
Instead, he calmly informs her their relationship is over. As a young man with political aspirations about to attend the Harvard School of Law, he requires a girlfriend that is more serious and less blonde. At first, Elle is devastated, but she quickly comes up with a plan, informing her girlfriends (who appear to exist solely to fuss over her) that she will win Warner back by proving she is good enough. How? By attending Harvard Law School as well.
She gets admitted to the prestigious school by studying hard and submitting a bubbly admissions video (directed by a Coppola!), only to be treated with contempt by her fellow students, particularly Warner's new girlfriend, Vivian (Selma Blair). As is that isn't enough, Professors Callahan (Victor Garber) and Stromwell (Holland Taylor) treat her like an addled child.
But never fear, because Elle has girl power! She becomes friends with Paulette (Jennifer Coolidge), a klutzy manicurist, and wins the respect of Emmett (Luke Wilson), Callahan's right-hand man. Before you know it, she has her trial by fire, as the defense attorney (don't ask how) for an informercial fitness guru (Ali Larter) on trial for murder.
The whole thing is just as idiotic as it sounds, but the filmmakers understand their target audience and give them what they want in spades. There are two adorable dogs (large portions of the audience went "Awww" at least three times), a couple of montages set to pop songs and even a dance number. Every character does exactly what you expect them to do and the giddy ending is as obvious as every other element in the film. "Legally Blonde" is mildly enjoyable precisely because it is so predictable (comfortable as an old shoe, you know), and because Reese Witherspoon can make almost anything play better than expected.
© 2001 Ed Johnson-Ott
========== X-RAMR-ID: 28922 X-Language: en X-RT-ReviewID: 235393 X-RT-TitleID: 1108857 X-RT-SourceID: 591 X-RT-AuthorID: 1099 X-RT-RatingText: 3/5
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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First and formost, thanks to Bryan McBride for his foundational template, Bootleaf. This template was modified by Laura Newman Eckstein, the Judaica Digital Humanities Coordinator for the Judaica DH at the Penn Libraries. Special thanks to Laurie Allen and Arthur Kiron.


Currently pursuing Electronics and Communication Engineering in CBIT. I am extremely motivated to constantly develop my skills and grow professionally. I possess excellent interpersonal skills. When it comes to teamwork I act as the glue holding the team together with my innate ability to understand people.
I am a self taught Full stack Web Developer. I am passionate about technology and enjoy learning new trends and implement them to build nice and cool looking responsive websites. Feel free to reach out to me in any platform.
View ResumeThis website is built using reactjs, nodejs and postgresql. It uses a machine learning api to detect faces in images. It is deployed using heroku.
This is a background-generator. Often we waste a lot of time to select the right colors for our website. This fun project helps designers to choose the right colors and gives them rgb values.
This is a Restaurant Website. This project uses reactjs for frontend. I have used bootstrap for styling.
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Main functionalities
Import variants from several callers
Variants from different callers can be imported in R and parsed into a data frame with standardised fields. See how fields are standardaised to know more about which fields from each callers are parsed. The import functions are:
-
import_goi_superfreq()
: to import variants found on genes of interest called by superFreq, a caller that allows clonal tracking of cancer sequencing data. Figure 1 sketches how the function works.
-
parse_vcf_output()
: which takes a Variant Call Format (VCF) file as input and outputs a parsed data frame with standardised names for the fields in theVCF
file. Currently,parse_vcf_output()
can parse ouputs from the following callers run in tumour-only mode:GATK3 MuTect2
,VarScan2
,VarDict
andFreebayes
. It also enables parsing of the annotation field added by the Variant Effect Predictor.
See more examples in Get Started
.
Combine variant calls from different samples within the same patient
-
combine_and_filter()
combines and filters the variant calls (already imported intoR
) from several samples collected for the same patient. This functions attempts to mimic in a very simplistic way what is performed within superFreq. Instead of filtering each variant callset separately for each sample, variants are filtered jointly by patient. This means that if a variant reaches minimal quality threshold at any time point, then it will be kept for all other time points. If a variant is not detected in some samples it will be filled with default values, e.g.zero
variant allele frequency. This allows to have complete information for a variant across time for one patient and to plot and evaluate the shift in VAF or depth over time.
Below is a graphic overview of how the output of parse_vcf_output()
and combine_and_filter()
interact. The example is based on files for one patient but the same can be extended to any patient.
See more examples in Get Started
.


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Where Are Kaizer Chiefs Getting It Right? Reader’s Voice
by Shakes lamolaKaizer Chiefs aren’t playing the prettiest football in the league but with results on their side, the Khosination are taking good results over good football any day.
Ernst Middendorp has managed to win over the hard to impress Chiefs supporters. Though it is still early to start talking championships but it will never be too early to collect maximum points.
After beating Orlando Pirates over the weekend, Chiefs is sitting pretty at the top, 10 points clear at the summit of the Absa Premiership standings. The one thing Chiefs are doing right is grinding out results and leaving the talking to the football pundits.
The Soweto derby is revived and got back the swag. FNB Stadium was filled to the brim, spectators who came in their huge numbers were entertained to a five goal thriller, something the fans were longing for in the derby. Although Pirates was the better side and created more scoring opportunities than Chiefs, Amakhosi were once again on the winning side.
Chiefs are two games shy of Telkom Knockout title and in the driving seat of the league title race.
Can they do it?
This article was written by a Soccer Laduma reader


--- layout: default ---
Welcome to our Training site for Mozilla's Global Sprint. Here you'll find Guides for Participants, for Project Leads, and for Site Hosts.
To learn general information about the Sprint, visit mzl.la/global-sprint


The xsl:variable
element is used to declare a variable and give it a value. If it appears at the
top level (immediately within xsl:stylesheet) it declares a global variable, otherwise it declares a local variable
that is visible only within the stylesheet element containing the xsl:variable declaration.
The mandatory name
attribute defines the name of the variable.
The value of the variable may be defined either by an expression within the optional select
attribute, or
by the contents of the xsl:variable element. In the latter case the result is a temporary tree. A
temporary tree can be used like a source document, for example it can be accessed using path expressions
and processed using template rules.
There is an optional attribute, as
, to define the type of the variable. The actual supplied
value must be an instance of this type; it will not be converted. This has changed in Saxon 7.4: previous
releases did a conversion.
In standard XSLT, variables once declared cannot be updated. Saxon however provides a saxon:assign extension element to circumvent this restriction.
The value of a variable can be referenced within an expression using the syntax $name
.
Example:
<xsl:variable name="title">A really exciting document"</xsl:variable>
<xsl:variable name="backcolor" expr="'#FFFFCC'" />
<xsl:template match="/*">
<HTML><TITLE<xsl:value-of select="$title"/></TITLE>
<BODY BGCOLOR='{$backcolor}'>
...
</BODY></HTML>
</xsl:template>


Was the user response happy, sad or neutral?
Here are your graphs. This is what you've been waiting for, hmm?
Most frequent words, rendered in real-time
User locations put on the world map
If graphs aren't your jam, have a look at the raw data
Drop a mail if you need more information about this project, if you'd like to contribute, and/or if you have any feedback.


Example component
{% include "includes/timeline.html" %}
{% include "includes/timeline-code.html" %}
Content patterns
- the time or date should follow GDS patterns on date and time format
- secondary titles aren't mandatory
Interaction patterns
- timelines are by default time ordered, if the timeline isn't time order or needs to be filtered, consider another approach
Services using this pattern
- Application platform
- Entities
Things to do
- research additional examples
- research alternative for workflow management


A special render target that enables a fragment shader to write to several textures. This approach is useful for advanced rendering techniques like post-processing or deferred rendering. Heads up: [name] can only be used with a WebGL 2 rendering context.
[example:webgl2_multiple_rendertargets webgl2 / multiple / rendertargets ]
[page:Number width] - The width of the render target. Default is `1`.
[page:Number height] - The height of the render target. Default is `1`.
[page:Number count] - The number of render targets. Default is `1`.
options - (optional object that holds texture parameters for an
auto-generated target texture and depthBuffer/stencilBuffer booleans. For
an explanation of the texture parameters see [page:Texture Texture]. For a
list of valid options, see [page:WebGLRenderTarget WebGLRenderTarget]).
Read-only flag to check if a given object is of type [name].
The texture property is overwritten in [name] and replaced with an array. This array holds the [page:WebGLRenderTarget.texture texture] references of the respective render targets.
[page:WebGLRenderTarget WebGLRenderTarget] properties are available on this class.
[page:WebGLRenderTarget WebGLRenderTarget] methods are available on this class.
[link:https://github.com/mrdoob/three.js/blob/master/src/[path].js src/[path].js]


| 1036 | (A) | Bot witħ condethe als he come kepis he noghte ełłs |
| 1040 | (C) | Safe with þe condite þat he hadde . he asked no more |
| 1023 | (D) | wiþ saf condyt as he come kept he no more |
| 1003 | (E) | with saaf cundyt as he cam he kepte na more |
| (Ex) | ---- no text ---- | |
| 1061 | (L) | with condit as he come he kepiþ no more |
| 976 | (P) | ? ??? ?????? ?? ?? ???? & kepys no ???? |
| 1014 | (U) | witħ sauf conduyt as thei kome / kept thei nomore |
| 101 | (V) | But with Condit as he came . kepes he no more |


A `ph-drag-drop-rank` (unstyled) looks like:
Answer 1
Answer 2
Answer 3
Answer 4
Answer 5
Answer 6
A `ph-drag-drop-rank` (styled) looks like:
Answer 1
Answer 2
Answer 3
Answer 4
Answer 5
Answer 6


--- layout: post title: Show simple traceback to point in code date: 2012-10-11 21:07:53.000000000 +01:00 type: post parent_id: '0' published: true password: '' status: publish categories: - python tags: [] meta: _edit_last: '1' _wp_old_slug: show-simple-traceback-at-point-in-code author: Noel permalink: "/show-simple-traceback-to-point-in-code/" ---
import inspect print "Trace to here", inspect.stack()[2][3]


Functions for Discover/ Enumerates metrics and retrieves values.
More...
Go to the source code of this file.
|
| fpga_result | fpgaGetNumMetrics (fpga_handle handle, uint64_t *num_metrics) |
| |
| fpga_result | fpgaGetMetricsInfo (fpga_handle handle, fpga_metric_info *metric_info, uint64_t *num_metrics) |
| |
| fpga_result | fpgaGetMetricsByIndex (fpga_handle handle, uint64_t *metric_num, uint64_t num_metric_indexes, fpga_metric *metrics) |
| |
| fpga_result | fpgaGetMetricsByName (fpga_handle handle, char **metrics_names, uint64_t num_metric_names, fpga_metric *metrics) |
| |
| fpga_result | fpgaGetMetricsThresholdInfo (fpga_handle handle, struct metric_threshold *metric_thresholds, uint32_t *num_thresholds) |
| |
Functions for Discover/ Enumerates metrics and retrieves values.
Definition in file metrics.h.
◆ fpgaGetNumMetrics()
Enumerates number of metrics
- Parameters
-
| [in] | handle | Handle to previously opened fpga resource |
| [in,out] | num_metrics | Number of metrics are discovered in fpga resource |
- Returns
- FPGA_OK on success. FPGA_NOT_FOUND if the Metrics are not discovered
◆ fpgaGetMetricsInfo()
Retrieve metrics information
- Parameters
-
| [in] | handle | Handle to previously opened fpga resource |
| [in,out] | metric_info | Pointer to array of metric info struct user allocates metrics info array |
| [in,out] | num_metrics | Size of metric info array |
- Returns
- FPGA_OK on success. FPGA_NOT_FOUND if the Metrics are not found. FPGA_NO_MEMORY if there was not enough memory to enumerates metrics.
◆ fpgaGetMetricsByIndex()
Retrieve metrics values by index
- Parameters
-
| [in] | handle | Handle to previously opened fpga resource |
| [in,out] | metric_num | Pointer to array of metric index user allocates metric array |
| [in,out] | num_metric_indexes | Size of metric array |
| [in,out] | metrics | pointer to array of metric struct |
- Returns
- FPGA_OK on success. FPGA_NOT_FOUND if the Metrics are not found. FPGA_NO_MEMORY if there was not enough memory to enumerates metrics.
◆ fpgaGetMetricsByName()
Retrieve metric values by names
- Parameters
-
| [in] | handle | Handle to previously opened fpga resource |
| [in,out] | metrics_names | Pointer to array of metrics name user allocates metrics name array |
| [in,out] | num_metric_names | Size of metric name array |
| [in,out] | metrics | Pointer to array of metric struct |
- Returns
- FPGA_OK on success. FPGA_NOT_FOUND if the Metrics are not found
◆ fpgaGetMetricsThresholdInfo()
Retrieve metrics / sendor threshold information and values
- Parameters
-
| [in] | handle | Handle to previously opened fpga resource |
| [in,out] | metrics_threshold | pointer to array of metric thresholds user allocates threshold array memory Number of thresholds returns enumerated thresholds if user pass NULL metrics_thresholds |
| [in,out] | num_thresholds | number of thresholds |
- Returns
- FPGA_OK on success. FPGA_NOT_FOUND if the Metrics are not found. FPGA_NO_MEMORY if there was not enough memory to enumerates metrics.


V4L
Section: Devices and Network Interfaces (4)Updated: xf86-video-v4l 0.2.0
Index Return to Main Contents
NAME
v4l - video4linux driverSYNOPSIS
Section N'34'ModuleN'34' ... Load N'34'v4lN'34' EndSection
DESCRIPTION
v4l is an Xorg driver for video4linux cards. It provides a Xvideo extension port for video overlay. Just add the driver to the module list within the module section of your xorg.conf file if you want to use it. There are no config options. Note that the extmod module is also required for the Xvideo support (and lots of other extensions too).SUPPORTED HARDWARE
The v4l driver works with every piece of hardware which is supported by a video4linux (kernel-) device driver and is able to handle video overlay. bt848/bt878-based TV cards are the most popular hardware these days.CONFIGURATION DETAILS
Please refer to xorg.conf(5) for general configuration details. This section only covers configuration details specific to this driver.SEE ALSO
Xorg(1), xorg.conf(5), xorgconfig(1), Xserver(1), X(7)AUTHORS
Authors include: Gerd Knorr<EMAIL_ADDRESS>Index
This document was created by man2html, using the manual pages.
Time: 05:33:53 GMT, December 24, 2015


Active cases
Active cases are the number of people who have tested positive and are in isolation either on-campus or off-campus. Any reduction in cases indicates individuals being cleared to return to work or class.
Isolation and quarantine
Isolation separates those who test positive from people who are not sick. Quarantine separates and restricts the movement of those who may have been exposed to see if they become sick. Isolation and quarantine information presented below is specific to on-campus residential students. Off-campus students and employees may also be isolated or quarantined. Any reduction in cases indicates individuals being cleared to return to work or class.
Symptomatic testing
This is the number of tests conducted for those with symptoms of COVID-19. This number includes the number of tests conducted at VCU Health testing sites as well as those that are conducted outside of VCU and later self-reported.
Asymptomatic surveillance testing
VCU tests a percentage of asymptomatic community members Monday through Thursday to gauge the proportion of people with COVID-19 in the VCU community. This was previously referred to as "asymptomatic prevalence testing." VCU's Public Health Response Team monitors the asymptomatic positivity rate as an indicator of the prevalence of COVID-19 in our community. The goal is to test 5% of residential students and 2% of non-residential students and employees on a monthly basis.
Entry testing
Residential students were mailed test kits to conduct COVID-19 testing prior to move-in. VCU restricts move-in for students who test positive.


Stay close to your best friends with group chat. It's great for making weekend plans, starting a book group and sharing cat photos. Meow.
Reach out to family and friends worldwide. With super low rates and no peak times you really can call home the moment you start to miss it.
Call rates


Various Projects¶
Keras LAMB Optimizer¶
Implementation of the LAMB optimizer from the paper Reducing BERT Pre-Training Time from 3 Days to 76 Minutes.
Supports huge batch size training while only requiring learning rate to be changed.
Keras AdaBound Optimizer¶
Keras port of AdaBound Optimizer for PyTorch, from the paper Adaptive Gradient Methods with Dynamic Bound of Learning Rate.
Provides weights for ResNet 34 model trained on CIFAR 10 reaching 92% without random cropping augmentation.
Dynamic Time Warping - Numba¶
Implementation of Dynamic Time Warping algorithm with speed improvements based on Numba.
Supports for K nearest neighbours classifier using Dynamic Time Warping, based on the work presented by Mark Regan. The classes called KnnDTW are obtained from there, as a simplified interface akin to Scikit-Learn.
The three variants available are in dtw.py, odtw.py and ucrdtw.py.
- dtw.py: Single threaded variant, support for visualizing the progress bar.
- odtw.py: Multi threaded variant, no support for visualization. In practice, much more effiecient.
- ucrdtw.py: Experimental (Do not use). Multi threaded variant, no support for visualization. It is based upon the optimized C implementation available at https://github.com/klon/ucrdtw.
Neural Algorithmic Logic Units¶
A Keras implementation of Neural Arithmatic and Logical Unit from the paper Neural Algorithmic Logic Units by Andrew Trask, Felix Hill, Scott Reed, Jack Rae, Chris Dyer, Phil Blunsom.
- Contains the layers for
Neural Arithmatic Logic Unit (NALU)
andNeural Accumulator (NAC)
. - Also contains the results of the static function learning toy tests.
Padam - Partially Adaptive Momentum Estimation¶
Keras implementation of Padam from Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks.
Padam allows for much larger learning rates to be utilized, and follows generalization closely with Stochastc Gradient Descent.
Neural Image Assessment¶
Implementation of NIMA: Neural Image Assessment in Keras + Tensorflow with weights for MobileNet model trained on AVA dataset.
NIMA assigns a Mean + Standard Deviation score to images, and can be used as a tool to automatically inspect quality of images or as a loss function to further improve the quality of generated images.
Contains weights trained on the AVA dataset for the following models:
- NASNet Mobile (0.067 EMD on valset thanks to @tfriedel !, 0.0848 EMD with just pre-training)
- Inception ResNet v2 (~ 0.07 EMD on valset, thanks to @tfriedel !)
- MobileNet (0.0804 EMD on valset)
Switch Normalization¶
Switchable Normalization is a normalization technique that is able to learn different normalization operations for different normalization layers in a deep neural network in an end-to-end manner.
Keras port of the implementation of the paper Differentiable Learning-to-Normalize via Switchable Normalization.
Code ported from the switchnorm official repository.
Group Normalization¶
A Keras implementation of Group Normalization by Yuxin Wu and Kaiming He.
Useful for fine-tuning of large models on smaller batch sizes than in research setting (where batch size is very large due to multiple GPUs). Similar to Batch Renormalization, but performs significantly better on ImageNet.
Available in Keras Contrib inside normalization module.
Batch Renormalization¶
Batch Renormalization algorithm implementation in Keras 2.0+. Original paper by Sergey Ioffe, Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models.
Available in Keras Contrib inside normalization module.
Snapshot Ensembles¶
Implementation of the paper Snapshot Ensembles: Train 1, Get M for Free in Keras 2+
Tiramisu DenseNets for Semantic Segmentation¶
Fully Connected DenseNet for Image Segmentation implementation of the paper The One Hundred Layers Tiramisu : Fully Convolutional DenseNets for Semantic Segmentation
Available in Keras Contrib inside the DenseNet applications module.
One Cycle Learning Policy¶
Implementation of One-Cycle Learning rate policy from the papers by Leslie N. Smith.
- A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay
- Super-Convergence: Very Fast Training of Residual Networks Using Large Learning Rates
Contains two Keras callbacks, LRFinder and OneCycleLR which are ported from the PyTorch Fast.ai library.
Normalized Optimizers¶
Keras wrapper class for Normalized Gradient Descent from kmkolasinski/max-normed-optimizer, which can be applied to almost all Keras optimizers. Partially implements Block-Normalized Gradient Method: An Empirical Study for Training Deep Neural Network for all base Keras optimizers, and allows flexibility to choose any normalizing function. It does not implement adaptive learning rates however.
The wrapper class can also be extended to allow Gradient Masking and Gradient Clipping using custom norm metrics.
Wrapper classes :
- NormalizedOptimizer: To normalize of gradient by the norm of that gradient.
- ClippedOptimizer: To clip the gradient by the norm of that gradient. Note: Clips by Local Norm only !
Mobile Colorizer¶
Utilizes a U-Net inspired model conditioned on MobileNet class features to generate a mapping from Grayscale to Color image. Based on the work https://github.com/baldassarreFe/deep-koalarization
Uses MobileNets for memory efficiency in comparison to Inception-ResNet-V2 so that training can be done on a single GPU (of 4 GB size minimum).
Tensorflow Eager Execution Examples¶
Tensorflow Eager Execution mode allows an imperative programming style, similar to Numpy in addition to nearly all of the Tensorflow graph APIs, higher level APIs to build models (Keras) as well as easy debugging with the Python debug bridge.
Since Eager Execution APIs are quite recent, some kinks still exist, but as of this moment, they are minor and can be sidesteped. These issues are highlighted in the notebooks and it is advised to browse through the comments, even if the topic is easy, so as to understand the limitations of Eager as TF 1.8.
The following set of examples show usage of higher level APIs of Keras, different ways of performing the same thing, some issues that can arise and how to sidestep them while we wait for updates in Tensorflow to fix them.
It is to be noted, that I try to replicate most parts of this excellent PyTorch Tutorial Set. A few topics are missing - such as GANs and Image Captioning since I do not have the computational resources to train such models. A notable exception is Style Transfer, for which I have another repository dedicated to it, so I won't be porting it to Eager.
A final note :
- Eager is evolving rapidly, and almost all of these issues that I stated here are edge cases that can/will be resolved in a later update. I still appreciate Eager, even with its limitations, as it offers a rich set of APIs from its Tensorflow heritage in an imperative execution environment like PyTorch.
- This means that once the Eager API has all of its kinks ironed out, it will result in cleaner, more concise code and hopefully at performance close to Tensorflow itself.
Twitter Sentiment Analysis¶
To perform sentiment analysis over a corpus of tweets during the U.S. 2012 Re-Election about the candidates Barack Obama and Mitt Romney.
The previous best score on the test dataset was 64 % f1-score, suggesting that improvements can be obtained using modern machine learning / deep learning algorithms.


Young Years
Remain quick-witted like in your youth, eager to experience and learn from your mistakes, all with a childlike curiosity.
+${value}% Health
-3 -5 -8 -10 -13 -15 -18 -20 -23 -25
+${value}% Increased Experience
3.5 7 10.5 14 17.5 21 24.5 28 31.5 35
MaxLevel
6
UltimateLevel
10


In today’s project you will refactor class-based components that make use of lifecycle methods to function components that make use of React Hooks! The project we will use is the Pokedex Redux project you just completed. However you will be starting with the official solution instead of your code base.
In this project, you’ll build your application with React and Redux hooks! You will implement the:
useState
hook to manage a component’s stateuseEffect
hook to manage a component’s side effect
operations
useDispatch
hook to dispatch actions from with a component
file
useSelector
hook access slices of state from the Redux
store
useContext
hook to manage your application with Context
instead of Redux
useParams
hook to grab the parameters from React Router
In this phase you’ll refactor the class based components into functional components using these two React Hooks:
useState
useEffect
First you’ll need the backend for the Pokedex application. If you don’t already have it running from your previous work, take a moment to clone it from https://github.com/appacademy-starters/pokedex-backend and get it set up and running. Remember you may need to get the database created and all the migrations and seeds running for the backend, if you haven’t already done so.
The API for the backend is also documented in the repository’s README.
Once you have that up and running, you’ll begin working out of the official solution from the Pokemon Redux project.
Throughout today, you’ll work on refactoring each class component in the application to be a function component that makes use of React Hooks!
As you might remember, your current application comprises of the following components:
App
: Does the browser routing and top-level fetches of data
to draw the data
LoginPanel
: Shows the login panelPokemonBrowser
: The browser that draws the list on the left
after logging in and has a route to the PokemonDetail
when
the route matches “/pokemon/:id”
PokemonDetail
: Makes a fetch to the API on mount and update
to load the details of the selected Pokemon
PokemonForm
: Renders a form in place of the
PokemonDetail
component to add a Pokemon, makes a fetch
call to get the available types of the pokemon and then makes a fetch
call to post the form data to the backend.
As you’re refactoring your application’s components, you’ll most likely hit bugs and break your application. While you’re refactoring each component, make sure to test that your refactored code is working before moving on to refactor the next component. As a general guideline, you should refactor each component from the lowest, most nested component up to the top-most parent:
PokemonDetail
PokemonForm
PokemonBrowser
LoginPanel
App
Once a component is refactored, your app should behave exactly as it always did. Remember functional components with hooks is just an alternative to class based components with state.
You’ll update how each component sets its default state by using the
useState
hook. You’ll also refactor the lifecycle methods of
each component into side effect operations managed by the
useEffect
hook. At the end of this exercise, you should have
a good understanding of how to use the basic useState
and
useEffect
hooks to write function components with side effect
operations.
As a reminder use this as a guide for what you need to convert.
| Class based | Functional hooks based |
|---|---|
any refernce to this.state |
useState() |
componentDidMount , componentWillUnmount
|
useEffect() |
If you can’t remember how to use the new hooks, try looking at the official documentation:
As this app uses Redux, you’ll see each component uses
connect
, mapStateToProps
, and
mapDispatchToProps
. While we will be refactoring our
components to use the Redux hooks in the next phase, for now you are
only converting to use the React hooks useState
and
useEffect
. This means you can leave the
connect
wrapper in place. The connect functions works equally
well with class based or functional components. You will just need to swap
this.props
for props
accordingly.
Once you have finished refactoring, take a moment to commit your changes to the main branch of your project:
In the next section we’ll be refactoring the Redux part of this
application, by utilizing the Redux specific hooks
useSelector
and useDispatch
.


Home Library Manager
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:: com :: sun :: star :: text ::
|
| service DocumentIndexMarkAsian |
- Description
- is a TextRange which is explicitly marked
as an index entry for a DocumentIndex.
For Asian languages the user can provide an additional string
which is used for sorting. If the user does not provide these
strings, they are not considered for sorting.
- Since
- OOo 1.1.2
|
| Properties' Summary |
string
TextReading |
contains the reading of the string which has been chosen for the
index entry.
|
string
PrimaryKeyReading |
contains the reading of the primary key of the index entry.
It is used to build a hierarchical document index.
|
string
SecondaryKeyReading |
contains the reading the secondary key of the index entry.
It is used to build a hierarchical document index.
|
| Properties' Details |
TextReading
string TextReading;
- Description
- contains the reading of the string which has been chosen for the
index entry.
|
|
PrimaryKeyReading
string PrimaryKeyReading;
- Description
- contains the reading of the primary key of the index entry.
It is used to build a hierarchical document index.
|
|
SecondaryKeyReading
string SecondaryKeyReading;
- Description
- contains the reading the secondary key of the index entry.
It is used to build a hierarchical document index.
|
|
Top of Page
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


gh generally sends a Personal Access Token (PAT) with its requests. Some endpoints of the GitHub API can be accessed without authenticating yourself. But once your API use becomes more frequent, you will want a PAT to prevent problems with rate limits and to access all possible endpoints.
This article describes how to store your PAT, so that gh can find it (automatically, in most cases). The function gh uses for this is gh_token()
.
More resources on PAT management:
usethis::gh_token_help()
and usethis::git_sitrep()
help you check if a PAT is discoverable and has suitable scopesusethis::create_github_token()
guides you through the process of getting a new PATgitcreds::gitcreds_set()
helps you explicitly put your PAT into the Git credential storegh::gh()
allows the user to provide a PAT via the .token
argument and to specify a host other than “github.com” via the .api_url
argument. (Some companies and universities run their own instance of GitHub Enterprise.)
However, it’s annoying to always provide your PAT or host and it’s unsafe for your PAT to appear explicitly in your R code. It’s important to make it possible for the user to provide the PAT and/or API URL directly, but it should rarely be necessary. gh::gh()
is designed to play well with more secure, less fiddly methods for expressing what you want.
How are .api_url
and .token
determined when the user does not provide them?
.api_url
defaults to the value of the GITHUB_API_URL
environment variable and, if that is unset, falls back to "https://api.github.com"
. This is always done before worrying about the PAT.gh_token(.api_url)
. That is, the token is looked up based on the host.gh now uses the gitcreds package to interact with the Git credential store.
gh calls gitcreds::gitcreds_get()
with a URL to try to find a matching PAT. gitcreds::gitcreds_get()
checks session environment variables and then the local Git credential store. Therefore, if you have previously used a PAT with, e.g., command line Git, gh may retrieve and re-use it. You can call gitcreds::gitcreds_get()
directly, yourself, if you want to see what is found for a specific URL.
If you see something like this:
#> <gitcreds>
#> protocol: https
#> host : github.com
#> username: PersonalAccessToken
#> password: <-- hidden -->
that means that gitcreds could get the PAT from the Git credential store. You can call gitcreds_get()$password
to see the actual PAT.
If no matching PAT is found, gitcreds::gitcreds_get()
errors.
If you don’t have a Git installation, or your Git installation does not have a working credential store, then you can specify the PAT in an environment variable. For github.com
you can set the GITHUB_PAT_GITHUB_COM
or GITHUB_PAT
variable. For a different GitHub host, call gitcreds::gitcreds_cache_envvar()
with the API URL to see the environment variable you need to set. For example:
On a machine used for interactive development, we recommend:
Store your PAT(s) in an official credential store.
Do not store your PAT(s) in plain text in, e.g., .Renviron
. In the past, this has been a common and recommended practice for pragmatic reasons. However, gitcreds/gh have now evolved to the point where it’s possible for all of us to follow better security practices.
If you use a general-purpose password manager, like 1Password or LastPass, you may also want to store your PAT(s) there. Why? If your PAT is “forgotten” from the OS-level credential store, intentionally or not, you’ll need to provide it again when prompted.
If you don’t have any other record of your PAT, you’ll have to get a new PAT whenever this happens. This is not the end of the world. But if you aren’t disciplined about deleting lost PATs from https://github.com/settings/tokens, you will eventually find yourself in a confusing situation where you can’t be sure which PAT(s) are in use.
On a headless system, such as on a CI/CD platform, provide the necessary PAT(s) via secure environment variables. Regular environment variables can be used to configure less sensitive settings, such as the API host.
Note that on GitHub Actions, specifically, a personal access token is automatically available to the workflow as the GITHUB_TOKEN
secret. That is why many workflows in the R community contain this snippet:
This makes the automatic PAT available as the GITHUB_PAT
environment variable. If that PAT doesn’t have the right permissions, then you’ll need to explicitly provide one that does (see link above for more).
If there is no PAT to be had, gh::gh()
sends a request with no token. (Internally, the Authorization
header is omitted if the PAT is found to be the empty string, ""
.)
What do PAT-related failures look like?
If no PAT is sent and the endpoint requires no auth, the request probably succeeds! At least until you run up against rate limits. If the endpoint requires auth, you’ll get an HTTP error, possibly this one:
GitHub API error (401): 401 Unauthorized
Message: Requires authentication
If a PAT is first discovered in an environment variable, it is taken at face value. The two most common ways to arrive here are PAT specification via .Renviron
or as a secret in a CI/CD platform, such as GitHub Actions. If the PAT is invalid, the first affected request will fail, probably like so:
GitHub API error (401): 401 Unauthorized
Message: Bad credentials
This will also be the experience if an invalid PAT is provided directly via .token
.
Even a valid PAT can lead to a downstream error, if it has insufficient scopes with respect to a specific request.


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Harvard-Yale delayed by climate-change protest
by ESPNThe second half of Saturday's Harvard-Yale game has been delayed after a number of spectators rushed the field to stage a climate-change protest.
After the game went to halftime around 1:40 p.m. ET with the Crimson leading 15-3, students from both schools occupied midfield after the Yale band had finished performing.
Some held banners asking their colleges to act on climate change and Puerto Rican debt relief, including one sign that read, "Nobody wins. Yale & Harvard are complicit in climate injustice."
"Hey hey, ho ho, fossil fuels have got to go," some protesters chanted.
Players were stretching and warming up when spectators first came on to the field. The players returned to the locker room as hundreds more people streamed onto the field.
Police officers were seen escorting some protesters away.
Saturday was the 136th edition of The Game between Harvard and Yale. The Bulldogs would clinch an Ivy League title with a win.


About Paradigm Pet Professionals
Pets are nature's gift to humanity. It has been scientifically proven that opening our homes and hearts to a pet increases our longevity and improves our overall quality of life as well as the lives of our pets. At Pet Paradigm Professionals, our mission is to offer resources to help you care for your furry, scaly, feathery, and slimy loved ones. Our pet experts-or "Pexperts"-have been working with pet owners and professionals alike for the past twelve years. They offer one-on-one consultations with current and prospective pet owners as well as group presentations designed for veterinary, pet shelter, and pet breeding professionals.
Looking for basic pet care advice for the most common type of pets? Need additional help determining which type of pet is right for you and your family? We will work with you and provide tailored evidence-based pet care to ensure lifelong health and wellness of your new companion.
- General Adoption Resources: https://theshelterpetproject.org/
- ASPCA: https://www.aspca.org/
- Fish Rescue: https://www.sterlingshelter.org/humane-society/koi-fish-rescue/
- Snake Rescue: https://savethesnakes.org/snakerescuecall/
- Bird Rescue: https://ftlob.rescuegroups.org/
We are also happy to help you navigate the adoption process! We will guide you through each step in the process from determining which type of pet is best suited for your family and home environment, to completing the necessary paperwork, to bringing your new loved one home. Please fill out our contact form to request a consultation. We will contact you within 48 hours to schedule a consultation. All fields are required.


Our Schools
DAV Public School had a noble beginning in the year 1987 in a rented building with hardly 120 students. Today its multi-storied beautiful infra structure facilitating education to more than 2000 students speaks volume of its popularity and efficacy. The school is managed by DAV College Managing Committee, New Delhi and got affiliated to Central Board of Secondary Education in the year 1995. Right from the day of its existence DAV is working persistently to shape the future of young and vibrant souls by imparting quality education with a team of 76 dedicated and smart working teachers. At present, the school stands out an enviable position at state level as many of the laudable achievements are to its credit. Class X and XII CBSE Board Exams results are par excellence.
Research at GNDEC's Find a ProgramSee What Awaits
MHRD, Govt. of India has sanctioned Rs. 10 Crores for Technical Education Quality Improvement Programme-II (TEQIP-II) to this College and the Department of Science and Technology (DST) also sanctioned Rs. 1 Crores under FIST Programme for carrying out the research activities. The College has received grant to the tune of Rs. 5 Crores for research & other activities by different agencies like AICTE, UGC and DST etc.GNDEC is overall sports champion of Punjab Technical University (Now, IKGPTU) & also in its survey declared GNDEC Best Engineering college in year 2011 and 2012 & 2014 for excellent placements amongst all affiliation
Admission and Aid Visit Campus
About DAV
DAV Public School had a noble beginning in the year 1987 in a rented building with hardly 120 students. Today its multi-storied beautiful infra structure facilitating education to more than 2000 students speaks volume of its popularity and efficacy. The school is managed by DAV College Managing Committee, New Delhi and got affiliated to Central Board of Secondary Education in the year 1995. Right from the day of its existence DAV is working persistently to shape the future of young and vibrant souls by imparting quality education with a team of 76 dedicated and smart working teachers. At present, the school stands out an enviable position at state level as many of the laudable achievements are to its credit. Class X and XII CBSE Board Exams results are par excellence. Adding value to CBSE’s inherent strength school is empowering thousands of its pupils by giving them a solid backing under the guidance of DAV Stalwarts. With a mission to provide a wide range of holistic education based on “skill and application”, we are working well to meet soaring expectations.
Points of Pride
Our achievements and accolades showcase the power and pride of all DAV's.
Here all recent photos from past events will come.
Department Of Computer Science
Department Of Computer Science
Learn to think critically, creatively, and analytically as you develop a broad-based foundation of knowledge. Whether you choose to further your existing interests, or discover new passions, you enter the workforce with the skill sets that employers seek.
See Full SchoolProgramsDepartment Of Computer Science
Department Of Computer Science
We produce leaders who make a difference here in New York and around the globe. Determined and principled, our students become entrepreneurs, influencers, and titans of industry. Our graduates succeed at every levelâfrom the classroom to the boardroom.
See Full SchoolDepartment Of Computer Science
The School of Education
Teaching is more than just a professionâit is a calling. Our goal is to help develop the next class of motivated students into the next generation of great educators. Here, you learn from dedicated professionals who are passionate and committed.
See Full SchoolDepartment Of Computer Science
Department Of Computer Science
Home to scholars and scientists who are unified by one intrepid goalâto improve the quality of life for people globally. Thanks to a rigorous program that stresses experiential learning, our students seamlessly transition into rewarding careers.
See Full SchoolDepartment Of Computer Science
Department Of Computer Science
A launchpad for innovators, entrepreneurs, and explorersâproblem solvers who want to change the world for the better. We prepare students for careers in emerging professions, as they graduate poised to tackle the challenges of today, tomorrow, and beyond.
See Full SchoolDepartment Of Computer Science
Department Of Computer Science
From the classroom to internships and clinical work in the field to study abroad, our students develop the skills, expertise, and connections they need, all with the support of our faculty, dedicated career counselors, and global alumni network.
See Full SchoolJDLL.M.Upcoming Events
Cards for upcoming events through firebase will come here.
Apr272019
Notice regarding classes of M.Tech.(Part-Time)
Apr 27, 2019, 3 p.m.May042019
Makeup Exam Provisional Result for ESE November, 2018
May 04, 2019, 10 p.m.May162019
Alumni scholarship for needy and academically sound students of GNDEC
May 16, 2019, 10 p.m.News
Cards for news will come here.


export { animate } from "./animations"
export { inertia } from "./animations/inertia"
// Animators
export { decay } from "./animations/generators/decay"
export { spring } from "./animations/generators/spring"
export { keyframes } from "./animations/generators/keyframes"
// Utilities
export { angle } from "./utils/angle"
export { applyOffset } from "./utils/apply-offset"
export { createAttractor, attract, attractExpo } from "./utils/attract"
export { clamp } from "./utils/clamp"
export { degreesToRadians } from "./utils/degrees-to-radians"
export { distance } from "./utils/distance"
export { interpolate } from "./utils/interpolate"
export { isPoint3D } from "./utils/is-point-3d"
export { isPoint } from "./utils/is-point"
export { mixColor } from "./utils/mix-color"
export { mixComplex } from "./utils/mix-complex"
export { mix } from "./utils/mix"
export { pipe } from "./utils/pipe"
export { pointFromVector } from "./utils/point-from-vector"
export { progress } from "./utils/progress"
export { radiansToDegrees } from "./utils/radians-to-degrees"
export { smoothFrame } from "./utils/smooth-frame"
export { smooth } from "./utils/smooth"
export { snap } from "./utils/snap"
export { toDecimal } from "./utils/to-decimal"
export { velocityPerFrame } from "./utils/velocity-per-frame"
export { velocityPerSecond } from "./utils/velocity-per-second"
export { wrap } from "./utils/wrap"
// Easing
export {
linear,
easeIn,
easeInOut,
easeOut,
circIn,
circInOut,
circOut,
backIn,
backInOut,
backOut,
anticipate,
bounceIn,
bounceInOut,
bounceOut,
} from "./easing"
export { cubicBezier } from "./easing/cubic-bezier"
export { steps } from "./easing/steps"
export {
mirrorEasing,
reverseEasing,
createExpoIn,
createBackIn,
createAnticipate,
} from "./easing/utils"
// Types
export * from "./animations/types"
export * from "./easing/types"
// // Worklet
// export { animate } from './worklet/animate';
// export { workletReady } from './worklet/load-worklet';
|


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{% extends 'base.html' %} {% block body %}
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I am a graduate student, currently pursuing master’s degree in Computer Science at Indiana University,Bloomington
Some of the programming skillss I have acquired over the period of time
The easiest way to contact me is via LinkedIn : Mihir Thatte


You can enable or disable link your account to your current IP address.
Time parameter is used to avoid the loss of your account.
If you do not enter the number of days the lock will be removed.
Maximum time of 14 days. Default is 7 days.
You can specify the subnet in the format of CIDR.
Early unlock impossible.
Current IP address: %IP%


Event Activated Actions
Enter & Exit Events
Actions can be activated by the parent <x-app-view-do> element. The enter and exit only apply when the route is matched exactly.
You should see log messages in the console. One on entry and one on exit of this page.