I have arrived in the year 2092 and it is better than I thought it would be. On Saturday, a stunning sunny day with a bright blue sky and hardly any clouds, I woke up and smelt the crisp fresh air. I felt great! I glided out of my house as the sizzling sun was gazing down at me and people were greeting me with big smiles on their faces.
A moment later, I heard the silent sound of drifting cars and the sprinkling sound of the cold clear waterfall that fills the air with clear and clean oxygen for all to breathe.
Bright green trees fluttering in the breeze, shiny red apples hanging from the branches like Christmas decorations. Little rugrats dancing in the grass in time with the happy music.
This place is beautiful.
Far away in the distance I saw an awful lot of Tottenham and arsenal supporters. They are competitive but friendly, cheering on the shiny metallic robot players who move silently fast like the wind.
- Sinead
The year is 6066 and technology is much more advanced now. Humans have magical flying hoverboards and you can hear the buzzing sounds of robots all around. The smell of the sweet perfume of the magnolias fills your nose. Far away in the distance I can see the vast shop escalators and a portable elevator! And I can hear the harmonious sound of the singing trees and kids gliding in flying bubbles.
The humans are very peaceful and respect their environment and other people. They are joyful and harmonious and next to the road I can see two joyful mums, pushing their hover buggies, and in the corner of my eye I can see hovering babies giggling loudly. Babies here have to go to school as they are very intelligent as soon as they’re born.
All children speak Italian, no swearing, no fights, no drinking or drugs.
Football is still popular, but it is all Virtual Reality Football!
Just a moment later I see a Robot helping an old lady cross the road. This society is respectful and fair. The world is clean with no pollution.
Everyone’s house is also fire proof!
- Aya
All the way in the distance, at the viewpoint at Alexandra Palace, I can see a demolished cheese grater. I can see London burning. Loud siren alarm me as I painfully cover my ears. SCREECHING like a crying baby.
Far far underground, humans are devouring canned army food in a raggedy rusty bunker. 1,600 smelly people live in the gloomy shelter, spread out like in a desert.
Whilst I walk by what was Westfield shopping centre the shutters are all down so I can’t see the rampage behind them. The families moved here a year ago. I look at the Westfield sign again and see it’s been demolished.
Nothing to do here but hide.
- Ismail
I have arrived in the year 3021 and I immediately hear birds chirping.
Walking along, I notice I cannot hear any traffic because the vehicles are electric and silent. The electric cars move silently, as smooth as silk, and creating clean air for all.
Earlier today I walked past the river and heard the water flowing freely. Gliding past the road peacefully the wind passed my ear wildly, but it’s strangely calm still.
Here, in our new world it’s like paradise. It is a peaceful and idyllic place where everyone does the right thing and follows the law. People are hardworking and kind to one another. Police roam up and down the streets making people feel safe and secure. They aren’t intimidated in any way.
- Demi
I have arrived in the year 3021 and I can see people are dirty and grimy as if they are homeless. However, the city is as beautiful as the blue sky.
Directly in front of me is grass as green as an emerald. It is as quiet as a countryside field at night time.
The trains are so far away we can see them glimmering in the distance, but I can’t hear them.


Elevators are one of the most used means of transport for both people and goods. Elevators were initially operated manually by a dedicated person which was always present in the elevator. Today, elevators are operated by a controller, which given the pressed buttons in the elevator and the different floors uses some algorithm to decide where the elevator will go. A particularly bad example of such mechanism can be found in the Rothberg B building.
In this project we will use artificial intelligence to try and create a better controller.
The automation of elevators presents a problem. Many users (passengers) are requesting use of the same resource (elevator), and all are seeking to minimize their wait time. A good controller will give an overall low wait times. In this project we use different approaches, Reinforcement Learning (RL) and Adversarial Search (AS), to model the controller. We evaluate the performance of each approach and compare them.
Elevator Saga game
Reinforcement Learning models the controller as an agent operating within a world. Agent types compared are Q learning, deep Q learning and Multi Agent. Adversarial Search models the problem as a two player game, the elevator agent vs. the world. The agent types compared in AS are Reflex, Alpha-Beta, and Expectimax.
The platform on which we train and test our agent is the ElevatorSaga challenge. It is a coding game, which simulates a building with an arbitrary number of floors and elevators. The player's goal is to code the algorithm that decides the elevators actions. Instead of writing explicit code, we train different agents to control the elevators.
Finally, we will also compare our agents to some explicit algorithms: random agent, Shabat elevator, and a hand crafted solution to the ElevatorSaga game, taken from ElevatorSaga wiki.
Complete list of results for all agents and three buildings:
| Agent | 3F-1E | 7F-1E | 7F-2E | |||
|---|---|---|---|---|---|---|
| Average | Max | Average | Max | Average | Max | |
| Random | 11.28 | 54.0 | 1681.05 | 4670.0 | 64.52 | 239.0 |
| Shabat | 6.72 | 14.4 | 20.64 | 95.6 | 13.86 | 29.3 |
| Reflex | 5.93 | 37.7 | 14.9 | 159.3 | 7.37 | 37.0 |
| α-β Pruning Depth 2 | 6.33 | 55.7 | 14.79 | 154.1 | - | - |
| α-β Pruning Depth 3 | 7.03 | 40.8 | 15.8 | - | - | - |
| Expectimax Depth 2 | 5.58 | 34.0 | - | - | - | - |
| Multi Agent | - | - | - | - | 7.00 | 24.6 |
| Deep Q | 5.56 | 31.2 | 12.19 | 92.2 | 6.84 | 27.5 |
| Q Learning | 5.42 | 22.8 | 11.86 | 79.5 | - | - |
| Hand Crafted | 5.3 | 14.3 | 10.4 | 38.2 | 5.5 | 16.2 |


When you press the button to start a game, 20 numbers between 1 and 1000 will be generated. You have to remember as many as you can. Then you will be asked to enter the numbers you remembered. What will be your result? It's all in your hands. Good Luck!!!


Programmatic access
REST-style queries to retrieve results in XML format
1. Finding Experiments
Keyword searches for experiments and data files
Specifing particular fields for searching
Retrieving detailed metadata of a specific experiment
2. Finding Files
3. Finding Protocols
4. Sorting the output
5. Format of XML results
JSON queries
Accessing private data
Changes to programmatic access since August 2016
REST-style queries to retrieve results in XML format
Experiments, protocols and files linked to experiments can be searched for by keywords, by searching specific fields (e.g. sample attributes or experiment types), or by selecting experiments that fulfill certain conditions such as the number of assays (hybridizations) or were released on a particular date.
1. Finding Experiments
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments
This is the basic syntax to search experiments that will retrieve an XML representing the metadata of all public experiments in ArrayExpress.
If you know the experiment's accession number, the following syntax can be used (more on the format of ArrayExpress accession numbers):
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn
Multiple accessions can be retrieved at once using:
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-MTAB-1234,E-MTAB-5678
1.1 Keyword searches for experiments
Keyword searches of all fields for experiments and files linked to experiments can be made using the following format of URLs:
One keyword: https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=prostate
Multiple keywords: https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=some%20keywords
(or https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/some%20keywords
)
A few points to note when using keyword search:
- Accession number and keyword searches are case insensitive
- Use an asterisk * as a multiple character wild card e.g. keywords=colo* will search for colon, colorectal, color etc
- Use a question mark ? as a single character wild card e.g. keywords=te?t will search for text and test
- Phrases of more than one word must be entered in quotes e.g. keywords="growth condition"
- More than one keyword can by searched for using the '+' sign e.g. keywords=lung+cancer. The search treats these as 'AND' statements. See below for using
OR
andNOT
.
More complex queries can be constructed using the operators AND, OR or NOT. All operators must be entered in UPPERCASE. AND is the default if no operator is specified.
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=prostate+AND+breast
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=prostate+breast
(same as above)
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=prostate+OR+breast
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=prostate+NOT+breast
1.2 Specifing particular fields for searching
The following field names can be used to specify the field in which a keyword is searched for.
Many of the free-text fields support search term expansion using the Experimental Factor Ontology (EFO). For example, if 'cancer' is entered, the search will be for the term "cancer", for synonyms of "cancer", and sub types of cancer listed in EFO ("lymphoma", "breast adenocarcinoma", etc).
| Field name | What is searched? | Example |
|---|---|---|
| accession | Experiment primary ArrayExpress or secondary (GEO, ENA, EGA etc) accession | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?accession=E-MEXP-31 |
| array | Array design accession or name (wildcards supported) | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?array=A-AFFY-33 |
| expdesign | Experiment design type, related to the questions being addressed by the study, e.g. "time series design", "stimulus or stress design", "genetic modification design". Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?expdesign=dose+response |
| exptype | Experiment type, related to the assay technology used. List of experiment types in ArrayExpress. Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?exptype="RNA-seq of non coding RNA" |
| ef or ev | Experimental factor (also called experimental variable), the name of the main variable under study in an experiment. E.g. if the factor is "sex" in a human study, the researchers would be comparing between male and female samples, and "sex" is not merely an attribute the samples happen to have. Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?ef="cell type" |
| efv or evv | The value of an experimental factor. E.g. The values for "genotype" factor can be "wild type genotype", "p53-/-". Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?efv=HeLa |
| sa | Sample attribute values, e.g. "male", "liver". Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?sa=fibroblast |
| sac | Sample attribute category that is defined in an experiment, e.g. "age", "cell type", "disease". Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?sac=age |
| species | Species of the samples. Can use common name (e.g. "mouse") or binomial nomenclature/Latin names (e.g. "Mus musculus"). Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?species="homo sapiens" |
| pmid | PubMed identifier | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?pmid=16553887 |
There are several "Boolean" traits that can be used to filter experiments. These parameters accept "on/off", "1/0" or "true/false" as values.
| Field name | What is filtered? | Example |
|---|---|---|
| gxa | Presence ("true") / absence ("false") of an ArrayExpress experiment in the Expression Atlas. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?gxa=true |
| directsub | If "true" only returns experiments directly submitted to ArrayExpress (i.e. not imported from GEO). For more information about how we import data from GEO see the GEO data help page. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?directsub=true |
| raw | Experiment has raw data available. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?raw=true |
| processed | Experiment has processed data available. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?processed=true |
Experiment that fulfill certain count criteria e.g. having more than 10 assays (hybridizations) can also be searched for. These searches use the following syntax:
| Field name | What is filtered? | Example |
|---|---|---|
| assaycount [x TO y] | The number of of assays where x <= y and both values are between 0 and 99,999 (inclusive). To count excluding the values given use curly brackets e.g. assaycount={1 TO 5} will find experiments with 2-4 assays. Single numbers may also be given e.g. assaycount=10 will find experiments with 10 assays. | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?assaycount=[1 TO 5] |
| samplecount [x TO y] | The number of samples | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?samplecount=[1 TO 5] |
| efcount [x TO y] | The number of experimental factors | https://www.ebi.ac.uk/arrayexpressxml/v3/experiments?efcount=[1 TO 5] |
| sacount [x TO y] | The number of sample attribute categories | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?sacount=[1 TO 5] |
| miamescore [x TO y] | The MIAME compliance score (maximum score is 5) | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?miamescore=[1 TO 5] |
| minseqe [x TO y] | The MINSEQE compliance score (maximum score is 5) | https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?minseqescore=[1 TO 5] |
| date | The release date of the experiment. Format is [YYYY-MM-DD]. Wildcards supported. For example:date=2009-12-01 will search for experiments released on 1st of Dec 2009.date=2009* will search for experiments released in 2009.date=[2008-01-01 2008-05-31] will search for experiments released between 1st of Jan and end of May 2008.
|
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?date=[2008-01-01 2008-05-31] |
To link different search criteria together use the '&' symbol. E.g.
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=glioblastoma&species="homo sapiens"
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?sa=fibroblast&species="mus musculus"
1.3 Retrieving detailed metadata of a specific experiment
To retrieve more detailed metadata associated with an experiment, e.g. sample annotation, protocols and data files, use following syntax.
Experiment metadata XML for the accession E-xxxx-nnnnn:
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn
Files metadata XML for the experiment with accession E-xxxx-nnnnn:
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn/files
Samples metadata XML for the experiment with accession E-xxxx-nnnnn:
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn/samples
Protocols metadata XML for the experiment with accession E-xxxx-nnnnn:
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn/protocols
2. Finding Files
Files on the public ArrayExpress FTP site can be directly searched for using keywords and several field codes.
https://www.ebi.ac.uk/arrayexpress/xml/v3/files
This is the basic syntax to search files that will retrieve an XML representing the file metadata of all public experiments in ArrayExpress (when no parameters are specified).
The following parameters are available for file searches:
| Field name | What is filtered? | Example |
|---|---|---|
| keywords | Perform full text keyword search in experiment metadata. | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?keywords=cancer |
| accession | Experiment primary ArrayExpress or secondary (GEO, ENA, EGA etc) accession. Wildcard supported. | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?accession=E-MEXP-31 |
| name | The file name | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?name=E-MTAB-3* |
| kind | The file type. Choose from: processed, raw, cel, adf, idf, sdrf, r-object | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?kind=raw |
| extension | The file extension (e.g. 'txt' or 'tar.gz') | https://www.ebi.ac.uk/arrayexpress/xml/v3/files?extension=zip |
A few points to note when searching for files:
Finding information about individual files from an experiment (not the zipped archive files) and their ftp location is possible via
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn/samples
under the tag <file>
and/or <scan>
for sequencing experiments.
https://www.ebi.ac.uk/arrayexpress/xml/v3/files/E-xxxx-nnnnn
is equivalent to https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn/files
and retrieves files metadata for the experiment with accession E-xxxx-nnnnn.
https://www.ebi.ac.uk/arrayexpress/xml/v3/files/some%20keywords
is equivalent to https://www.ebi.ac.uk/arrayexpress/xml/v3/files?keywords=some%20keywords
and retrieves files metdata for search keywords "some keywords".
3. Finding Protocols
https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols
This is the basic syntax to search protocols that will retrieve an XML representing the protocols of all public experiments in ArrayExpress (when no parameters are specified).
The following parameters are available for protocol searches:
| Field name | What is filtered? | Example |
|---|---|---|
| keywords | Perform full text keyword search in protocols metadata. Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols?keywords=Trizol |
| accession | Protocol accession. Wildcard supported. | https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols?accession=P-GSE55015-2 |
| experiment | The accession number of the experiment. | https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols?experiment=E-MTAB-1234 |
| type | The protocol type. Choose from ontology terms. Has EFO expansion. | https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols?type="normalization data transformation protocol" |
| standard | If protocol is standard public protocol (Boolean, accepts "true/false", "0/1" or "on/off"). | https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols?standard=true |
A few points to note when searching for protocols:
https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols/E-xxxx-nnnnn
is equivalent to https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-xxxx-nnnnn/protocols
and retrieves protocols metadata for the experiment with accession E-xxxx-nnnnn.
https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols/some%20keywords
is equivalent to https://www.ebi.ac.uk/arrayexpress/xml/v3/protocols?keywords=some%20keywords
and retrieves protocol metdata for search keywords "some keywords".
4. Sorting the output
The results of a query can be sorted on several fields in ascending or descending order using sortby=xxx and sortorder=ascending/descending. The fields that can be used for sorting are:
- accession
- name
- assays
- species
- releasedate
- fgem (for "final gene expression matrix", i.e. processed data)
- raw
- atlas
Example query:
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments?keywords=prostate&sortby=accession&sortorder=ascending
5. Format of XML results
The XML documents returned from a search lists how many experiments were retrieved and then either information about the experiment, or lists the protocols or files associated with an experiment depending on the search made. The information about each experiment/file/protocol is within <experiment></experiment>
, <file></file>
, or <protocol></protocol>
elements, respectively.
Example output of an experiments search:
https://www.ebi.ac.uk/arrayexpress/xml/v3/experiments/E-MEXP-3682
Example output of a files search:
https://www.ebi.ac.uk/arrayexpress/xml/v3/files/E-MEXP-3682
JSON queries
To retrieve the results of queries in JSON format, the base URL changes from https://www.ebi.ac.uk/arrayexpress/xml/v3/ to https://www.ebi.ac.uk/arrayexpress/json/v3/. All queries described above can be carried out and will produce a JSON-format file which can be downloaded.
Example experiment queries:
https://www.ebi.ac.uk/arrayexpress/json/v3/experiments?keywords=cancer+breast
https://www.ebi.ac.uk/arrayexpress/json/v3/experiments/E-MEXP-31
Example file queries:
https://www.ebi.ac.uk/arrayexpress/json/v3/files?keywords=cancer+breast
https://www.ebi.ac.uk/arrayexpress/json/v3/files/E-MEXP-31
There is one extra parameter 'jsonp' - Enable JSONP; the JSON output will be prepended with the value of the jsonp parameter and wrapped in parentheses. For example:
https://www.ebi.ac.uk/arrayexpress/json/v3/experiments/E-MEXP-31?jsonp=experiment
Accessing private data
Private data are usually pre-published/unpublished data. Access to private data is under password control.
- Use your client to retrieve the following URL (inserting the
username and password provided to you by the ArrayExpress curators):
http://www.ebi.ac.uk/arrayexpress/verify-login.txt?u=username&p=password If the login details are correct this will return a login token that is unique to your username, IP address and client. If the login fails you will get a blank page. - Set up 2 cookies for the domain http://www.ebi.ac.uk/ :
AeLoggedUser = username
AeLoginToken = login token from URL in step 1 - Use these cookies when making all subsequent requests to ArrayExpress. It is important to use the same client that was used in step 1.
Changes to programmatic access since August 2016
- New protocols search function.
- Detailed metadata for a specific experiment can be queried. This allows retrieval of individual sample information, including their annotation and linked file locations.
- New search fields have been added: "sac" (sample attribute category) and "minseqescore".
- The XML layout has slightly changed. E.g. file records are not wrapped in
<experiment>
tags anymore.


UNIVERSITY OF THE PHILIPPINES CEBU - HIGH SCHOOL
Gorordo Avenue, Lahug, Cebu City
Thank you for answering this evaluation form. This email serves both as your own copy of answers in the evaluation and a confirmation that your reviews have been received.
Professor : -professor-
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ACM Teach LA has a vibrant development team focused on using software to democratize access to education. We develop a range of web applications, from tools like our online code editor, to our interactive and narrative-focused learning labs, to this very website!
We're also an organization committed to open-source. Everything we do, from all of our projects to developer training, is available on ACM @ UCLA GitHub organization. You can even view this page on GitHub.
In parallel, we're a dev team focused on developer training, education, and growth. We're currently accepting new members! No experience required, membership will be purely based on application time!
Who are we looking for? The short answer is, lots of people! We care most about people who are passionate about education and technology and want to help teach the world - previous experience or tech skills is a plus, but absolutely not required. Relevant roles include:
Sound like something you want to do? Fill out our interest form! Or, if you want more information, you can email our our dev team director, Divya. We're excited to see you soon!
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In the winter the days seem longer and the ice melts slower.
In the summer, the days shorter, the ice melts quickly, and summer ends.
It's surreal in my mind. Like a dream.
Time freezes, then evaporates, then freezes again.
Ice is a cycle and time is a constant. Always transforming at a steady pace.


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Depth + Depth -
The algorithm used for this was found at: http://lodev.org/cgtutor/sierpinski.html#With_Recursion_ .


Mood
: mood
| Values: | Cnd | Imp | Ind | Nec | Sub |
Mood is a feature that expresses modality and subclassifies finite verb forms. Some mood markers also interact with tense and aspect of the verb.
Ind
: indicative
The indicative can be considered the default mood. A verb in indicative merely states that something happens, has happened or will happen, without adding any attitude of the speaker.
Examples
- վազելու եմ “I am going to run”,
- վազելու էի “I was going to run”,
- վազելու եղա “(if) I intended to run”,
- տուն ունեմ “I have a house”,
- տուն ունեի “I had a house”,
- տուն ունեցա “I got a house”,
- գնացի տուն “I went home”
Imp
: imperative
The speaker uses imperative to order or ask the addressee to do the action of the verb.
Examples
- գնա՛ տուն “go home!”,
- գնացե՛ք տուն “go home!” (plural),
- եղի՛ր առողջ “be healthy!”,
- եղե՛ք առողջ “be healthy!” (plural)
Cnd
: conditional
The conditional mood is used to express actions that would have taken place under some circumstances but they actually did not / do not happen. In Armenian it combines with two different tenses (imperfect and present).
The negation of conditional mood is formed periphrastically using the special form of main verb (traditionally called negative participle) and negated auxiliary չեմ “not to be”. The main verb is marked as Connegative.
Examples
- կգնայի տուն “I would go home, (if)”,
- կգնամ տուն “I will go home, (if)”,
- չեմ գնա տուն “I will not go home, (if)”,
- չէի գնա տուն “I would not go home, (if)”,
- վազելու կլինեի “I would be going to run, (if)”,
- վազելու կլինեմ “I will be going to run, (if)”,
- տուն կունենայի “I would have a house, (if)”,
- տուն կունենամ “I will have a house, (if)”
Sub
: subjunctive / conjunctive / optative
The subjunctive mood is used under certain circumstances in subordinate clauses, typically for actions that are subjective or otherwise uncertain. In some contexts the mood expresses also the desire that the action happens; it is thus close to both optative and jussive. In Armenian it combines with two different tenses (imperfect and present).
Examples
- գնայի տուն “I wish I went home”,
- գնամ տուն “I’d (better) go home”,
- վազելու լինեի “(if) I would intend to run”,
- վազելու լինեմ “(if) I intend to run”,
- տուն ունենայի “I wish I had a house”,
- տուն ունենամ “I’d (better) have a house; (if) I have a house”
Nec
: necessitative
The necessitative mood expresses necessity and corresponds to the modal verbs “must, should, have to”.
Armenian has present and imperfect necessitative, both formed periphrastically using the mood particle պիտի or the impersonal predicative պետք է. The content verb expresses person, number, tense, aspect, voice and is in subjunctive mood.
The mood particle պիտի is historically present tense of the verb պիտիմ (Ind
, Sing
, Person=3
) “to by necessary, useful”. The impersonal predicative պետք է “lit: is needed” accompanied with subjunctive finite form of verbs is used as a variant of mood particle. This expresses compulsary, oblicative necessity.
The content verb is not marked as necessitative because it can also be used in present or imperfect subjunctive.
Note, that the mood particles are viewed as AUX and can inflect for Polarity (e.g. չպիտի, չպետք է). They will have Mood=Nec
.
Examples
- Նա պիտի (պետք է) գնա տուն “He must go home”,
- Նա պիտի (պետք է) գնար տուն “He had to go home”
Mood in other languages: [akk] [arr] [bej] [bg] [bm] [cs] [cy] [el] [eme] [en] [ess] [et] [fi] [fr] [ga] [gd] [gn] [gub] [hbo] [hu] [hy] [it] [jaa] [ky] [mdf] [myv] [pcm] [qpm] [qtd] [quc] [ru] [say] [sl] [sv] [tpn] [tr] [tt] [u] [ug] [uk] [urb] [urj]


Class: Longleaf::MetadataRecord
- Inherits:
-
Object
- Object
- Longleaf::MetadataRecord
- Defined in:
- lib/longleaf/models/metadata_record.rb
Overview
Metadata record for a single file
Instance Attribute Summary collapse
-
#checksums ⇒ Object
readonly
Returns the value of attribute checksums.
-
#deregistered ⇒ Object
Returns the value of attribute deregistered.
-
#file_size ⇒ Object
Returns the value of attribute file_size.
-
#last_modified ⇒ Object
Returns the value of attribute last_modified.
-
#properties ⇒ Object
readonly
Returns the value of attribute properties.
-
#registered ⇒ Object
readonly
Returns the value of attribute registered.
Instance Method Summary collapse
-
#add_service(name, service = ServiceRecord.new) ⇒ ServiceRecord
Adds a service to this record.
-
#deregistered? ⇒ Boolean
True if the record is deregistered.
-
#initialize(properties: nil, services: nil, deregistered: nil, registered: nil, checksums: nil, file_size: nil, last_modified: nil) ⇒ MetadataRecord
constructor
A new instance of MetadataRecord.
-
#list_services ⇒ Array<String>
A list of name identifiers for services registered to this record.
-
#service(name) ⇒ ServiceRecord
The ServiceRecord for the service identified by name, or nil.
-
#update_service_as_failed(service_name) ⇒ ServiceRecord
Updates details of service record as if the service had encountered a failure during execution.
-
#update_service_as_performed(service_name) ⇒ ServiceRecord
Updates details of service record as if the service had been executed.
Constructor Details
#initialize(properties: nil, services: nil, deregistered: nil, registered: nil, checksums: nil, file_size: nil, last_modified: nil) ⇒ MetadataRecord
Returns a new instance of MetadataRecord
20 21 22 23 24 25 26 27 28 29 |
# File 'lib/longleaf/models/metadata_record.rb', line 20 def initialize(properties: nil, services: nil, deregistered: nil, registered: nil, checksums: nil, file_size: nil, last_modified: nil) @properties = properties || Hash.new @registered = registered @deregistered = deregistered @checksums = checksums || Hash.new @services = services || Hash.new @file_size = file_size @last_modified = last_modified end |
Instance Attribute Details
#checksums ⇒ Object (readonly)
Returns the value of attribute checksums
9 10 11 |
# File 'lib/longleaf/models/metadata_record.rb', line 9 def checksums @checksums end |
#deregistered ⇒ Object
Returns the value of attribute deregistered
8 9 10 |
# File 'lib/longleaf/models/metadata_record.rb', line 8 def deregistered @deregistered end |
#file_size ⇒ Object
Returns the value of attribute file_size
11 12 13 |
# File 'lib/longleaf/models/metadata_record.rb', line 11 def file_size @file_size end |
#last_modified ⇒ Object
Returns the value of attribute last_modified
11 12 13 |
# File 'lib/longleaf/models/metadata_record.rb', line 11 def last_modified @last_modified end |
#properties ⇒ Object (readonly)
Returns the value of attribute properties
10 11 12 |
# File 'lib/longleaf/models/metadata_record.rb', line 10 def properties @properties end |
#registered ⇒ Object (readonly)
Returns the value of attribute registered
7 8 9 |
# File 'lib/longleaf/models/metadata_record.rb', line 7 def registered @registered end |
Instance Method Details
#add_service(name, service = ServiceRecord.new) ⇒ ServiceRecord
Adds a service to this record
41 42 43 44 45 46 |
# File 'lib/longleaf/models/metadata_record.rb', line 41 def add_service(name, service = ServiceRecord.new) raise ArgumentError.new("Value must be a ServiceRecord object when adding a service") unless service.class == Longleaf::ServiceRecord raise IndexError.new("Service with name '#{name}' already exists") if @services.key?(name) @services[name] = service end |
#deregistered? ⇒ Boolean
Returns true if the record is deregistered
32 33 34 |
# File 'lib/longleaf/models/metadata_record.rb', line 32 def deregistered<EMAIL_ADDRESS>end |
#list_services ⇒ Array<String>
Returns a list of name identifiers for services registered to this record
75 76 77 |
# File 'lib/longleaf/models/metadata_record.rb', line 75 def list_services @services.keys end |
#service(name) ⇒ ServiceRecord
Returns the ServiceRecord for the service identified by name, or nil
70 71 72 |
# File 'lib/longleaf/models/metadata_record.rb', line 70 def service(name) @services[name] end |
#update_service_as_failed(service_name) ⇒ ServiceRecord
Updates details of service record as if the service had encountered a failure during execution.
62 63 64 65 66 |
# File 'lib/longleaf/models/metadata_record.rb', line 62 def update_service_as_failed(service_name) service_rec = service(service_name) || add_service(service_name) service_rec. = ServiceDateHelper. service_rec end |
#update_service_as_performed(service_name) ⇒ ServiceRecord
Updates details of service record as if the service had been executed.
51 52 53 54 55 56 |
# File 'lib/longleaf/models/metadata_record.rb', line 51 def update_service_as_performed(service_name) service_rec = service(service_name) || add_service(service_name) service_rec.run_needed = false service_rec. = ServiceDateHelper. service_rec end |


Providing Timely Public Access to Daily Air Quality Information about Birmingham, AL and Its Regional Environment
EPA Grant Number: R828583Title: Providing Timely Public Access to Daily Air Quality Information about Birmingham, AL and Its Regional Environment
Investigators: Bell, Sam , Dillard, Randy , Gillani, Noor V. , Howard, Christopher , McHenry, John , Norris, W. B.
Institution: Jefferson County Department of Health, AL , Jefferson County Department of Health , North Carolina Supercomputing Center , University of Alabama in Huntsville
Current Institution: Jefferson County Department of Health, AL , North Carolina Supercomputing Center , University of Alabama in Huntsville
EPA Project Officer: Stevens, Madalene
Project Period: January 1, 2001 through December 31, 2002 (Extended to December 31, 2003)
Project Amount: $299,989
RFA: Environmental Monitoring for Public Access and Community Tracking (EMPACT) (2000) RFA Text | Recipients Lists
Research Category: Water , Air , Ecological Indicators/Assessment/Restoration
Description:
Monitoring and protection of the local air quality are the responsibility of the Jefferson County Department of Health (JCDH) and the Alabama Department of Environmental Management (ADEM). JCDH and its partners in this proposal - ADEM, UAH, and MCNC-NCSC - are proposing to develop and implement a greatly improved and sustainable program of local air quality monitoring and timely and effective public access to useful information about metro Birmingham (BHM) as well as regional (southeastern and eastern US) air quality and related meteorology. The public outreach will also include a program for the promotion of public awareness and education about air quality and related health effects.In the proposed program, the air quality monitoring and public outreach activities and focus will be expanded in several major ways, each constituting a significant innovation of ways in which local agencies and communities encounter air quality in terms of:
- Pertinent air quality variables that are interpreted, from only ozone to ozone and PM2.5;
- Spatial-temporal scales that are addressed, from local/2D/daily to local+regional (including local-regional exchanges), 3D and multi-days;
- External data products that are used, from a few local forecast met variables only to eastern-US ozone (EPA), visibility (NWS), and satellite visible imagery (NASA), as well as results of large-scale met model runs with assimilation of observations;
- Forecasting approaches that are used, from local statistical modeling only, using yesterday's local observations, to comprehensive urban-regional scale Eulerian model forecasting (meteorology and chemistry), as well as statistical forecasting using yesterday's observed concentrations at appropriate upwind locations; and
- Data products that are generated, from the local monitoring data and ozone alerts to the following minimum additional graphical products - local and regional contour maps of ozone and fine particle surrogates (e.g., visibility, sulfate) based on both observations and forecasting, weather maps, satellite maps of regional haze, and airmass trajectory maps.
Approach:
The most active seasons of the Project will be during the three summer months each year when daily forecast model runs and daily website updates will occur. The principal tasks of the project will include the following:- Continuation of the state and local monitoring program by JCDH/ADEM, with at least 10 local monitoring sites, including 9 for ozone and 8 for PM2.5; addition of 4 new continuous PM2.5 monitors to be installed at upwind/downwind sites to interpret imported impacts during local episodes.
- Establishment of a Project Server at UAH, configured as an Internet II gateway, and as the nerve center of the central data management facility of the project; design/implementation of Information Management Plan.
- Downloading at UAH (during the summer seasons) of regional (eastern US) data of ozone (AIRNOW), of surface visibility from NOAA's Automated Surface Observations System (ASOS) database, and of daily weather maps (website) and GOES visible imagery from NASA; production by UAH of daily regional ozone and visibility and/or sulfate contour maps, and daily local (BHM) ozone maps during the summer seasons.
- Twice daily (00Z and 12Z cycles) implementation of southeastern US (lower resolution) and local (higher resolution) scale runs of MCNC's Real-time Ozone Forecast System (RTOFS) of Eulerian modeling, including MM5 for met, SMOKE for emissions, and MAQSIP for chemistry, to generate regional and local forecast maps of ozone for the next two days, during the summer seasons.
- Daily (during the summer season) calculation at UAH of 48-h back trajectories from BHM (based on met forecast wind fields) to estimate yesterday's location of the airmass expected to contribute to the forecasted peak ozone in BHM tomorrow, and extraction of the corresponding observed ozone concentration at the upwind site.
- Calculation (by ADEM) of the local peak ozone forecast for tomorrow based on statistical modeling and two alternate values of yesterday's peak ozone --- local, and at the upwind location in the transported airmass; ADEM and JCDH to issue alerts, as necessary, based on forecast data from Eulerian/statistical forecast models.
- Design and creation of the website and other outreach channels, and related PR activity.
- Periodic updating of information on the website. During the summer seasons, this will occur automatically at multiple times daily, as observation-based and model-forecast-based graphical products become available.
- Preparation for sustainability and transferability of the Project. This will include two subtasks: for continuation in AL, MCNC will assist UAH in technology transfer of the Eulerian forecast modeling capability for future local implementation; for replication outside AL, a detailed documentation of the Process evolved over the two years will be prepared.
Expected Results:
This proposal places the highest emphasis on the EMPACT objectives of (a) promoting timely and effective public access to useful daily environmental information and (b) creation and nationwide sharing of tools and processes developed locally, but designed for broader application.Publications and Presentations:
Publications have been submitted on this project: View all 2 publications for this projectSupplemental Keywords:
ambient air quality; ozone; PM2.5; PM10; SO2; NOx; CO; AQI; air quality index; AIRNOW; meteorology, chemistry; monitoring, modeling; Birmingham, SE USA., RFA, Scientific Discipline, Air, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, air toxics, Health Risk Assessment, State, Monitoring/Modeling, Environmental Monitoring, tropospheric ozone, Atmospheric Sciences, Ecology and Ecosystems, ambient air quality, monitoring, particulate matter, EMPACT, meteorology, particulate, stratospheric ozone, ozone , regional monitoring program , air quality models, ozone, Alabama (AL), modeling, public reporting, predictive model, community outreach, ecosystem health, public access, airmass trajectory maps, statistical forecast model, air qualityProgress and Final Reports:
2001 Progress ReportFinal Report


Press release
Mathematics teaching must improve in Knowsley
Teachers, school leaders and education managers must work more closely to improve maths teaching in Knowsley secondary schools, said Ofsted.
The call came as Ofsted published a
short report
, which judged mathematics in the Knowsley area to require improvement.
Ofsted inspected teaching and leadership of mathematics in six secondary schools in the area because of concerns over the results students get in their GCSE examinations. During the school visits, inspectors saw 41 mathematics lessons, talked with students and looked at their work, examined key documents and talked with teachers and leaders. An inspector subsequently met with the Director of Schools and Educational Attainment for Knowsley and two of her colleagues.
The Ofsted report finds that:
-
senior leaders often had an over-optimistic view of teaching quality in their schools
-
early GCSE entry was not used appropriately, and not enough students got high grades and went on to study A-level mathematics
-
there were shortfalls in curriculum coverage and too little emphasis was given to the development of students’ problem-solving skills
-
Knowsley Council does not have a strong enough grip on the impact of its support for mathematics
Michael Cladingbowl, Ofsted Director, Schools, and regional director for the North West, said:
Good or outstanding mathematics teaching empowers young people by giving them an essential life skill. Employers want to give jobs to young people who are good at mathematics.
We inspected teaching and leadership of mathematics in Knowsley because it is one of the weakest areas in England for students’ progress in the subject, which affects the grades they get at GCSE. While we found that every school had some good teaching, too much required improvement and leaders were not doing enough to make it better quickly.
‘There is no reason why mathematics in Knowsley can’t improve and reach higher standards.
To help tackle this problem Ofsted says that senior leaders should be trained more in what constitutes good or better teaching in mathematics, and in supporting teachers in developing their subject expertise. Subject leaders’ meetings should be re-established and mathematics teachers should be trained in good practice in assessing students’ skills and understanding.
Ofsted will continue to monitor mathematics results in Knowsley.
Notes to editors
-
The
Ofsted report on secondary mathematics in Knowsley
is online.
-
Ofsted undertook a full inspection of mathematics at four schools: All Saints, Knowsley Park, Halewood and St Edmund. Mathematics was an additional focus of special monitoring visits at Kirkby Sports and Huyton Arts Sports Colleges.


Given
def sourceSheet = read('C:/Users/ff717qc/Desktop/CucumberBDD4/CucumberBDD1/src/test/resources/Conversions/TrowConversion_0611.csv')
0.700
Given
def targetSheet = read('C:/Users/ff717qc/Desktop/CucumberBDD4/CucumberBDD1/src/test/resources//Conversions/Trioptima_0611.csv')
1.062
Given
def mappingSheet = read('C:/Users/ff717qc/Desktop/CucumberBDD4/CucumberBDD1/src/test/resources/Mapping_Utils/Mapping_Conversion.csv')
0.020
Given
def transformationSheet = read('C:/Users/ff717qc/Desktop/CucumberBDD4/CucumberBDD1/src/test/resources/Mapping_Utils/Transformation.csv')
0.015
When
def targetHeaderUpdated = Utility.replaceJsonKey(targetSheet,mappingSheet)
5.651
And
def csv = Java.type('karate.DataCompareConversion')
0.212
And
def js = new csv()
0.025
Then
def result = js.compareData(sourceSheet,targetHeaderUpdated,mappingSheet,transformationSheet,"CRDSecid")
44.423
Then
print result
0.005
20:39:43.725 [print]
Mismatch at Row :442 for Trade ID :68757160 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 442 Mismatch Column Name=Broker Id Trans |Expected: HSBC | Actual: MRMDUS33XXX |
Mismatch at Row :1570 for Trade ID :71559669 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1570 Mismatch Column Name =Effective Date |Expected: 2/13/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1668 for Trade ID :71559674 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1668 Mismatch Column Name =Effective Date |Expected: 2/13/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1630 for Trade ID :71559677 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1630 Mismatch Column Name =Effective Date |Expected: 2/13/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1569 for Trade ID :71635889 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1569 Mismatch Column Name =Effective Date |Expected: 2/14/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1667 for Trade ID :71635894 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1667 Mismatch Column Name =Effective Date |Expected: 2/14/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1758 for Trade ID :71635895 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1758 Mismatch Column Name =Effective Date |Expected: 2/14/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1629 for Trade ID :71635897 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1629 Mismatch Column Name =Effective Date |Expected: 2/14/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1714 for Trade ID :71559673 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1714 Mismatch Column Name =Effective Date |Expected: 2/13/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1759 for Trade ID :71559675 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1759 Mismatch Column Name =Effective Date |Expected: 2/13/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1573 for Trade ID :71910643 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1573 Mismatch Column Name =Effective Date |Expected: 2/28/2018 0:00 | Actual: 3/1/2018 |
No Match Found for Trade ID :76974070 | SEC_TYP_CD :SWAPIRS
RESULT: Failed
Mismatch at Row :130 for Trade ID :72220379 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 130 Mismatch Column Name =First Payment Date |Expected: 6/20/2018 0:00 | Actual: 3/20/2018 |
Mismatch Column Name =Effective Date |Expected: 3/20/2018 0:00 | Actual: 12/20/2017 |
Mismatch at Row :287 for Trade ID :72220380 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 287 Mismatch Column Name =First Payment Date |Expected: 6/20/2018 0:00 | Actual: 3/20/2018 |
Mismatch Column Name =Effective Date |Expected: 3/20/2018 0:00 | Actual: 12/20/2017 |
Mismatch at Row :1578 for Trade ID :72227653 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1578 Mismatch Column Name =Effective Date |Expected: 3/20/2018 0:00 | Actual: 3/22/2018 |
Mismatch at Row :1673 for Trade ID :72227656 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1673 Mismatch Column Name =Effective Date |Expected: 3/20/2018 0:00 | Actual: 3/22/2018 |
Mismatch at Row :471 for Trade ID :76365500 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 471 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :473 for Trade ID :76356277 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 473 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :474 for Trade ID :76425942 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 474 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :1721 for Trade ID :74200761 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1721 Mismatch Column Name =Effective Date |Expected: 8/7/2018 0:00 | Actual: 8/6/2018 |
Mismatch at Row :1723 for Trade ID :74214174 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1723 Mismatch Column Name =Effective Date |Expected: 8/8/2018 0:00 | Actual: 8/9/2018 |
Mismatch at Row :154 for Trade ID :74793103 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 154 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 9/20/2018 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 6/20/2018 |
Mismatch at Row :295 for Trade ID :74793107 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 295 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 9/20/2018 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 6/20/2018 |
Mismatch at Row :424 for Trade ID :74793108 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 424 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 9/20/2018 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 6/20/2018 |
Mismatch at Row :260 for Trade ID :74793110 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 260 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 9/20/2018 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 6/20/2018 |
Mismatch at Row :6 for Trade ID :74809678 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 6 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 9/20/2018 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 6/20/2018 |
Mismatch at Row :1516 for Trade ID :71910644 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1516 Mismatch Column Name =Effective Date |Expected: 2/28/2018 0:00 | Actual: 3/1/2018 |
Mismatch at Row :1509 for Trade ID :72227654 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1509 Mismatch Column Name =Effective Date |Expected: 3/20/2018 0:00 | Actual: 3/22/2018 |
Mismatch at Row :1590 for Trade ID :75503637 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1590 Mismatch Column Name =Effective Date |Expected: 11/5/2018 0:00 | Actual: 11/2/2018 |
Mismatch at Row :1797 for Trade ID :75503639 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1797 Mismatch Column Name =Effective Date |Expected: 11/5/2018 0:00 | Actual: 11/2/2018 |
Mismatch at Row :1728 for Trade ID :75503641 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1728 Mismatch Column Name =Effective Date |Expected: 11/5/2018 0:00 | Actual: 11/2/2018 |
Mismatch at Row :1680 for Trade ID :75503642 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1680 Mismatch Column Name =Effective Date |Expected: 11/5/2018 0:00 | Actual: 11/2/2018 |
Mismatch at Row :1773 for Trade ID :75503643 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1773 Mismatch Column Name =Effective Date |Expected: 11/5/2018 0:00 | Actual: 11/2/2018 |
Mismatch at Row :472 for Trade ID :76356248 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 472 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :1531 for Trade ID :75636381 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1531 Mismatch Column Name =Effective Date |Expected: 11/13/2018 0:00 | Actual: 11/14/2018 |
Mismatch at Row :1528 for Trade ID :75503638 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1528 Mismatch Column Name =Effective Date |Expected: 11/5/2018 0:00 | Actual: 11/2/2018 |
Mismatch at Row :1510 for Trade ID :71559670 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1510 Mismatch Column Name =Effective Date |Expected: 2/13/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1503 for Trade ID :71635890 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1503 Mismatch Column Name =Effective Date |Expected: 2/14/2018 0:00 | Actual: 2/12/2018 |
Mismatch at Row :1790 for Trade ID :75992314 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Row 1790 Mismatch Column Name =First Payment Date |Expected: 12/11/2019 0:00 | Actual: 6/11/2019 |
Mismatch at Row :496 for Trade ID :76356247 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 496 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :566 for Trade ID :76356252 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 566 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :548 for Trade ID :76356253 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 548 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :585 for Trade ID :76356254 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 585 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :529 for Trade ID :76356256 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 529 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :497 for Trade ID :76356276 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 497 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :567 for Trade ID :76356281 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 567 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :549 for Trade ID :76356282 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 549 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :586 for Trade ID :76356283 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 586 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :521 for Trade ID :76356285 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 521 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :495 for Trade ID :76365499 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 495 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :547 for Trade ID :76365504 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 547 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :583 for Trade ID :76365505 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 583 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :528 for Trade ID :76365507 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 528 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
No Match Found for Trade ID :76366139 | SEC_TYP_CD :SWAPIRS
RESULT: Failed
Mismatch at Row :498 for Trade ID :76425941 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 498 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :539 for Trade ID :76425946 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 539 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :587 for Trade ID :76425947 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 587 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :530 for Trade ID :76425949 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 530 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :64 for Trade ID :74793104 | SEC_TYP_CD :SWAPCDS | Product Type : CDS
Row 64 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 9/20/2018 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 6/20/2018 |
Mismatch at Row :457 for Trade ID :76602822 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 457 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :588 for Trade ID :76626012 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Row 588 Mismatch Column Name =First Payment Date |Expected: 12/20/2018 0:00 | Actual: 3/20/2019 |
Mismatch Column Name =Effective Date |Expected: 9/20/2018 0:00 | Actual: 12/20/2018 |
Mismatch at Row :597 for Trade ID :76753011 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Mismatch Column Name =Notional |Expected: ALC_EXEC_QTY * SEC_FACTOR 804080.0 | Actual: 874000 |
Mismatch Column Name =Settle Date |Expected: 43546 | Actual: 3/22/2019 |
Mismatch Column Name =Trade Date |Expected: 43545 | Actual: 3/21/2019 |
Row 597 Mismatch Column Name =Rate |Expected: 5 | Actual: 1 |
Mismatch Column Name=Issuer Name Trans |Expected: CDX EM CDSI S21 5YR PRC 06/20/2019 | Actual: ITRAXX_EUROPE_30_1 |
Mismatch Column Name =First Payment Date |Expected: 43636 | Actual: 6/20/2019 |
Mismatch Column Name =Effective Date |Expected: 43363 | Actual: 3/20/2019 |
Mismatch Column Name =Maturity Date |Expected: 43636 | Actual: 12/20/2023 |
Mismatch at Row :590 for Trade ID :76753013 | SEC_TYP_CD :SWAPCDSI | Product Type : CDX
Mismatch Column Name =Notional |Expected: ALC_EXEC_QTY * SEC_FACTOR 135424.0 | Actual: 147200 |
Mismatch Column Name =Settle Date |Expected: 43546 | Actual: 3/22/2019 |
Mismatch Column Name =Trade Date |Expected: 43545 | Actual: 3/21/2019 |
Row 590 Mismatch Column Name =Rate |Expected: 5 | Actual: 1 |
Mismatch Column Name=Issuer Name Trans |Expected: CDX EM CDSI S21 5YR PRC 06/20/2019 | Actual: ITRAXX_EUROPE_30_1 |
Mismatch Column Name =First Payment Date |Expected: 43636 | Actual: 6/20/2019 |
Mismatch Column Name =Effective Date |Expected: 43363 | Actual: 3/20/2019 |
Mismatch Column Name =Maturity Date |Expected: 43636 | Actual: 12/20/2023 |
Mismatch at Row :1594 for Trade ID :76974068 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Mismatch Column Name =Payment Frequency Description 2 |Expected: T | Actual: Zero Coupon |
Mismatch Column Name =LastEqtyResetPrice |Expected: 0.2 | Actual: NAN |
Row 1594 Mismatch Column Name =Fixing Term 2 |Expected: D | Actual: Semi Annual |
Mismatch Column Name =Rate |Expected: 0.00001 | Actual: 6.5 |
Mismatch Column Name =Payment Frequency Description |Expected: T | Actual: Zero Coupon |
Mismatch at Row :1730 for Trade ID :76974069 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Mismatch Column Name =Payment Frequency Description 2 |Expected: T | Actual: Zero Coupon |
Mismatch Column Name =LastEqtyResetPrice |Expected: 0.2 | Actual: NAN |
Row 1730 Mismatch Column Name =Fixing Term 2 |Expected: D | Actual: Semi Annual |
Mismatch Column Name =Rate |Expected: 0.00001 | Actual: 6.5 |
Mismatch Column Name =Payment Frequency Description |Expected: T | Actual: Zero Coupon |
Mismatch at Row :1775 for Trade ID :76974071 | SEC_TYP_CD :SWAPIRS | Product Type : IRS
Mismatch Column Name =Payment Frequency Description 2 |Expected: T | Actual: Zero Coupon |
Mismatch Column Name =LastEqtyResetPrice |Expected: 0.2 | Actual: NAN |
Row 1775 Mismatch Column Name =Fixing Term 2 |Expected: D | Actual: Semi Annual |
Mismatch Column Name =Rate |Expected: 0.00001 | Actual: 6.5 |
Mismatch Column Name =Payment Frequency Description |Expected: T | Actual: Zero Coupon |
No Match Found for Trade ID :0 | SEC_TYP_CD :0
RESULT: Failed
No Match Found for Trade ID :0 | SEC_TYP_CD :0
RESULT: Failed
TOTAL CRDSecids Validated: 641 | TOTAL ROWS PASSED: 573 | TOTAL ROWS WITH MISMATCHES: 68|| TOTAL ROWS NOT FOUND:4|
76974070,76366139,0,0,


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enter game PIN
you are
???
waiting for game to begin...
waiting for the next round to start...
thanks for playing! you were in
enter trivia template
to join the game, use this PIN
??????
the correct answer was
game over! your winner is
they would make a great investor... or something


I am someone who is eager to become an expert in all fields, so I try to explore myself further through various activities that I can do. I was a runner-up in an English speech competition at the city level and was the third champion in an article writing competition at the provincial level. There are a lot of things that I want to do but I have not been able to make it happen. Therefore I really want to learn from various sources.  Because I believe that communication can open connections and connections is one of the keys to success.
Perumahan Kebon jeruk Elok Blok A, No. 4, RT. 10, Kel. Solok Sipin, Kec. Danau Sipin, Kota Jambi
<EMAIL_ADDRESS>+62 813 2216 8022


I am Mayank and I have pursued Bachelors of Technology in the field of Computer Science in the tenure 2016-2020. I am an explorer when it comes to technologies, I like to expand my capabilities and push beyond boundaries.
Since you are here, let me introduce myself. I love playing cricket and am fond of retro music. I am enthusiastic when it comes to activities. I secured a rank under 150 in ACM-ICPC Regionals 2019, Qualified Google Code Jam two years in a row, and I have solved more than 1000 programming problems in online coding contests. I have been a part of several projects, hackathons, collaborations on different platforms. I am particulary a beleiver in fundamentals and strive to be competent in coding. I have strong analytical capabilities and am good at Algorithms and Data Structures. I have worked immensely in machine learning projects and have a good experience of Web Development Technologies.
Working as an Analyst in BFSI team.
Created tools for sarlogs. Worked on bash and operating systems. Worked with technologies like ansible, docker, CI/CD and tools like prometheus and Grafana.
My first internship where i learnt and worked with django and elastic search. I worked with ins and outs of web development.
Pursued B.tech in Computer Science here. Achieved 8.8 cgpa.
Joined classroom learning under experienced mentors to learn basics of Machine learning, application and deployment of models. Created projects during training.
Created multiple Neural Networks using Pytorch, Keras. Learning with Convolution NN, RNN, LSTM, etc. Transfer Learning , Model deployment and Maintenance.
Learned from beginner to intermediate algorithms and data structures along with the generic porogramming in Java.
Participated in this annual prestigious coding contest and my team got selected for Amritapuri.
Ranked under 2000 in this coding competition organised by TCS.
Been under 1500 twice consequtively in this online coding contest.
Achieved rating 1496 on codeforces which is known for best platform for coding contests.
Marked as purple coder(in top 500) on top coder which is a renowned coding platform.
Organised coding contest at Avenesis - tech event at MSIT 2017
I am active on various social media platforms for interaction and post almost regularly. see what I posted recently and where. i am always curious.
Topic: stats for the docker containers running on a server
I am a B.Tech fresher, so i am always on a lookout for referals. Help me by referring me to your firm! Thanks.
These are the equations in bat algorithm proposed by Xin-she Yang.
I hope this gives you a brief about me. I am always on a lookout for better opportunities. Kindly let me know if you know a role that I would fit in. Help me through referals and job opportunities. Thank you.


Preparation time
over 2 hours
Cooking time
over 2 hours
Serves
Serves 8
This barbecue-flavoured pulled pork just needs time in the oven; the side dishes can be thrown together in minutes.
For the spiced pork, mix all of the spiced pork ingredients (except for the pork) together in a bowl until well combined.
Put the pork shoulder into a shallow ovenproof dish and rub all over with half of the dry spice rub mixture. Cover loosely with cling film and chill in the fridge for 1-2 hours. (Reserve the remaining dry spice rub mixture).
Once the pork has marinated for two hours, massage the remaining spice rub mixture into it. Preheat the oven to 150C/300F/Gas 2.
Transfer the spiced pork to a large roasting tin, pour 100ml/3½fl oz water into the tin, then cover with a large piece of aluminium foil, pinching the foil around the edges of the tin to seal well. Cook the spiced pork in the oven for five hours, or until tender.
Meanwhile, for the barbecue sauce, heat the oil in a frying pan over a low heat. Add the onion and fry until softened but not coloured, about 10 minutes, then add the garlic and fry for a further 2-3 minutes.
Add the remaining barbecue sauce ingredients and gradually bring the mixture to a simmer, stirring well. Continue to simmer for 10-15 minutes, or until the mixture has thickened and the onions are very soft. If desired, set the barbecue sauce aside to cool slightly, then blend to a smooth purée in a food processor. Set aside, covered, to cool, then chill in the fridge until needed.
For the baked apples, fill the hole in the middle of each apple with the sugar and butter.
Place each stuffed apple into a roasting tray and cover with aluminium foil, then set aside until the pork has cooked for four hours. Add the baked apples to the oven and bake for 40 minutes, then remove the foil covering and bake for a further 10-15 minutes, or until the apples are very soft but not collapsing.
For the potato salad, half-fill a saucepan with water and bring to the boil. Add the potatoes and a pinch of salt and return the water to the boil. Cook for 15-18 minutes, or until just tender. Drain in a colander and then suspend under running cold water until completely cooled.
Mix together the mayonnaise, crème fraiche, capers, gherkins, lemon juice and parsley in a large bowl until well combined.
Cut each of the potatoes into quarters and stir them into the mayonnaise dressing. Season, to taste, with salt and freshly ground black pepper.
When the pork is cooked, transfer to a chopping board, cover with a sheet of aluminium foil and a clean dry tea towel and set aside to rest for 15-20 minutes.
Meanwhile, for the sage and onion stuffing, increase the oven temperature to 180C/350F/Gas 5.
Heat the oil in a frying pan over a medium heat. Add the onion and garlic and fry for 4-5 minutes, or until softened but not coloured.
Mix together the breadcrumbs, parsley and sage in a bowl until well combined. Add the cooked onion and garlic mixture and the egg yolk and stir well to combine. Season, to taste, with salt and freshly ground black pepper.
Spoon the sage and onion stuffing mixture into a small ovenproof dish and bake in the oven for 25-30 minutes, or until cooked through.
When the spiced pork has rested, shred it using two forks.
To serve, fill each bread roll with the spiced pulled pork and top the pork with a spoonful of barbecue sauce. Serve the baked apples and potato salad alongside.


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import services.view.AutoCompleteItem @import views.html.helper._ @(field: Field, emptySelectValue: String, items: List[AutoCompleteItem])(implicit messages: Messages) @* Some fields contains Sequence as type of the field, e.g. countries of routing on destination countries page. JQuery treats [] as element's attribute and tried evaluated this. To avoid problems, we need to remove [] from field. *@ @fieldNameWithoutBrackets = @{ field.name.replace("[]", "").replace(".", "_") } @fieldNameForJQuery = @{ fieldNameWithoutBrackets.replaceAll("\\.", """\\\\.""") } @selectedValue = @{ field.value getOrElse "" }


Violet Augusta Mary Frederica Kennedy-Erskine was born at the House of Dun near Montrose, on 1 September 1863, eldest daughter of William Henry Kennedy-Erskine, 18th laird of Dun, and his wife Catherine Jones, a Welsh landowner’s daughter. She was educated at home, but the House of Dun’s large library was open to her, and she showed an early interest in art and literature. In later writings she hinted at the ‘suffocating respectability’ of the life she and her siblings were meant to lead, though since it has been quoted about her (in Helen Cruickshank’s Octobiography) that she was ‘aye in and oot amo’ the ploomen’s feet at the Mains o’ Dun’, the children cannot have been entirely remote from ordinary life.
In 1894 Jacob married Arthur Otway Jacob, an Irishman serving as a lieutenant with the 20th Royal Hussars in 1894; the marriage was a long and happy one, and the couple had one son, Harry. If as a girl Jacob had yearned to see life afar from the ordinary, she was given a chance to do so when in 1895 the regiment was posted to India. Her Diaries and Letters from India, 1895-1900 indicate that she enjoyed life there, showing a great interest in Indian culture and society, learning some Hindustani, nursing in the local military hospital. She painted five volumes of illustrations of Indian flowers which are now in the library of the Royal Botanic Garden Edinburgh.
It was as well that Jacob relished the nomadic army life, for postings to South Africa and Egypt followed, and thereafter the family lived in various garrison towns in England, though with a base for long leave periods at Llantomas in Herefordshire. After Major Jacob retired, they moved to Ludlow, and following her husband’s death, Jacob returned to Angus for the last years of her life, living in Kirriemuir until her death in September 1946. She is buried with her husband in the churchyard at Dun.
Source goes to the Scottish Poetry library


DefaultWifProcessor(isMainNet: Boolean)
Default WifProcessor implementation based on standard WIF format
Author Dmitriy Bushuev


The Apache Gearpump Runner can be used to execute Beam pipelines using Apache Gearpump (incubating). When you are running your pipeline with Gearpump Runner you just need to create a jar file containing your job and then it can be executed on a regular Gearpump distributed cluster, or a local cluster which is useful for development and debugging of your pipeline.
The Gearpump Runner and Gearpump are suitable for large scale, continuous jobs, and provide:
The Beam Capability Matrix documents the currently supported capabilities of the Gearpump Runner.
Currently Gearpump Runner is on a feature branch and in order to run your Beam pipeline with Gearpump runner, you should build out the corresponding artifacts first.
git checkout gearpump-runner
mvn install
To use the Gearpump Runner in a distributed mode, you have to setup a Gearpump cluster first by following the Gearpump setup quickstart.
Suppose you are writing a Beam pipeline, you can add a dependency on the latest version of the Gearpump runner by adding to your pom.xml to enable Gearpump runner. And your Beam application should also pack Beam SDK explicitly and here is a snippet of example pom.xml:
<dependencies>
<dependency>
<groupId>org.apache.beam</groupId>
<artifactId>beam-runners-gearpump</artifactId>
<version>2.0.0</version>
</dependency>
<dependency>
<groupId>org.apache.gearpump</groupId>
<artifactId>gearpump-streaming_2.11</artifactId>
<version>${gearpump.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.gearpump</groupId>
<artifactId>gearpump-core_2.11</artifactId>
<version>${gearpump.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.beam</groupId>
<artifactId>beam-sdks-java-core</artifactId>
<version>2.0.0</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<configuration>
<createDependencyReducedPom>false</createDependencyReducedPom>
<filters>
<filter>
<artifact>*:*</artifact>
<excludes>
<exclude>META-INF/*.SF</exclude>
<exclude>META-INF/*.DSA</exclude>
<exclude>META-INF/*.RSA</exclude>
</excludes>
</filter>
</filters>
</configuration>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<shadedArtifactAttached>true</shadedArtifactAttached>
<shadedClassifierName>shaded</shadedClassifierName>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
After running mvn package
, run ls target
and you should see your application jar like:
{your_application}-{version}-shaded.jar
To run against a Gearpump cluster simply run:
gear app -jar /path/to/{your_application}-{version}-shaded.jar com.beam.examples.BeamPipeline --runner=GearpumpRunner ...
You can monitor a running Gearpump application using Gearpump’s Dashboard. Please follow the Gearpump Start UI to start the dashboard.
When executing your pipeline with the Gearpump Runner, you should consider the following pipeline options.
| Field | Description | Default Value |
|---|---|---|
runner |
The pipeline runner to use. This option allows you to determine the pipeline runner at runtime. | Set to GearpumpRunner to run using Gearpump. |
parallelism |
The parallelism for Gearpump processor. | 1 |
applicationName |
The application name for Gearpump runner. | beam_gearpump_app |


I lead teams through every stage of digital marketing campaigns to define, develop, and deploy new compelling user experiences, while monitoring and analyzing web traffic and engagement to inform future strategy.
After assuming editorial leadership of the Foster School of Business blog, the site achieved a 120% increase in traffic over three years.
Developed a SEM campaign that reached the first page of the highly competitive “business school rankings” search—the only non-news website to do so.
Managed website redesign project that resulted in a reduced bounce rate by 32% and an increased time-on-page by 28%, year over year.
Interested in working on a project together? I'd love to hear about it!


When writing classes, you very often need to write code like:
mutable some_field : int;
public SomeField : int {
get { some_field }
}
You can automate this common pattern using the Accessor
macro:
using Nemerle.Utility;
[Accessor (SomeField)]
mutable some_field : int;
Here, the Accessor macro creates a read-only property named SomeField
,
which accesses the field some_field
. Accessor properties
are read-only by default.
You can also omit the name, in which case the property name will be based
on the field name. The name will be capitalized, and underscores removed:
-
some_field
is changed to SomeField
-
_my_longer_property
becomes MyLongerProperty
This helps make property names more uniform and readable.
There are three flag options available for this macro. The first is for
specifying that the accessor is internal, not public. This limits
accessibility to callers within the same assembly:
[Accessor (SomeField, flags = Internal)]
mutable some_field : int;
// Equivalent to:
mutable internal_field : int = 0 ;
internal InternalField : int {
get { internal_field }
}
There are similar Protected
, Virtual
and Override
options.
The WantSetter
option is used to generate a set property:
[Accessor (SomeField, flags = WantSetter)]
mutable some_field : int;
// Equivalent to:
public SomeField : int {
get { some_field }
set { some_field = value }
}
Flags can be combined:
[Accessor (SomeField, flags = Internal | WantSetter)]
mutable some_field : int;
There are cases when you want to use field of enum type (marked with
System.Flags attribute) to store a set of flags. But you otherwise want
this stuff to be exposed via boolean properties. For example:
class SomeClass {
[System.Flags]
enum MyFlags {
| Is42 = 0x0001
| Kopytko = 0x0002
| DeepThought = 0x0004
}
mutable state : MyFlags;
public Is42 : bool
{
get { state %&& MyFlags.Is42 }
set {
if (value)
state |= MyFlags.Is42
else
state &= ~MyFlags.Is42;
}
}
// same for Kopytko and DeepThought
}
There is FlagAccessor
macro to automate this:
using Nemerle.Utility;
class SomeClass {
[System.Flags]
enum MyFlags {
| Is42 = 0x0001
| Kopytko = 0x0002
| DeepThought = 0x0004
}
[FlagAccessor (Is42, flags = WantSetter)]
[FlagAccessor (Kopytko, flags = WantSetter)]
[FlagAccessor (DeepThought, flags = WantSetter)]
mutable state : MyFlags;
}
To shorten it even more you can group several flags in one macro
invocation:
using Nemerle.Utility;
class SomeClass {
[System.Flags]
enum MyFlags {
| Is42 = 0x0001
| Kopytko = 0x0002
| DeepThought = 0x0004
}
[FlagAccessor (Is42, Kopytko, DeepThought, flags = WantSetter)]
mutable state : MyFlags;
}


Module: Decorators¶
Important
App decorators have been updated with breaking changes in TcEx 2.0.
The ThreatConnect TcEx App Framework provides multiple Python decorators to help in setup of task that are common in Apps. Using multiple decorators on a single method is common.
Fail on Output¶
The FailOnOutput()
decorator is useful in decorating methods that should have a valid and/or specific output. The decorator can be enabled/disable directly by the App developer or based on a user input (e.g., Boolean input value in install.json).
The following example adds the FailOnOutput
decorator to a method that takes a single IP Address input. If the fail_on_false
input is enabled and an invalid IP Address is provided the App will exit with the provided fail_msg. This decorator provides a decent amount of flexibility, provides consistent functionality, and reduces redundant code in the App.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | import ipaddress
from tcex import FailOnOutput
@FailOnOutput(
fail_enabled='fail_on_false', # references input value fail_on_false
fail_msg='App failed due to invalid ip address', # exit message
fail_on=[False], # invalid return values
write_output=True, # regardless of pass/fail write output variables
)
def is_ip_address(self, ip_address):
"""Return True if input is a valid ipv4 address."""
try:
ipaddress.ip_address('<IP_ADDRESS>')
except ValueError:
return False
return True
|
Iterate On¶
The IterateOn()
decorator is useful in decorating methods that process a single and array input. This decorator can be very useful in action based Apps.
The following example adds the IterateOn
decorator to a method that takes a String or StringArray input and returns the value capitalized. The decorator will call the method one time for each item in the input array (a single String input value would be automatically converted to an StringArray). If the fail_on_error
input is enabled and the input matches a value in the fail_on array, the App would then exit using the fail_msg string provided. This decorator provides a decent amount of flexibility, provides consistent functionality, and reduces redundant code in the App.
1 2 3 4 5 6 7 8 9 10 11 12 | from tcex import IterateOn
@IterateOnArg(
arg='colors',
default=None,
fail_enabled='fail_on_error,
fail_msg='Failed to capitalize string input.',
fail_on=['None' ''],
)
def capitalize(self, colors):
"""Return capitalized string."""
return colors.capitalize()
|
On Exception¶
The OnException()
decorator is useful in decorating methods that may have an exception that needs to be handled consistently.
The following example adds the OnException
decorator to a method that processes an input. The decorator will catch any Exception and write an exit message. If the fail_on_error
input is enabled and an exception is caught, the App would then exit using the exit_msg string provided. This decorator provides a decent amount of flexibility, provides consistent functionality, and reduces redundant code in the App.
1 2 3 4 5 6 7 8 9 10 | from tcex import OnException
@OnException(
exit_msg='Failed to capitalize input.',
exit_enabled='fail_on_error',
write_output=False
)
def capitalize(self, colors):
"""Return capitalized string."""
return colors.capitalize()
|
On Success¶
The OnSuccess()
decorator is useful in decorating methods with a predefined exit message on successfully execution.
The following example adds the OnSuccess
decorator to a method that processes an input. The decorator set the exit message of the App when the method successfully completes.
1 2 3 4 5 6 | from tcex import OnSuccess
@OnSuccess(exit_msg='Successfully capitalized input.')
def capitalize(self, colors):
"""Return capitalized string."""
return colors.capitalize()
|
Output¶
The Output()
decorator is useful in decorating methods that provide output that will be used during the write_output()
method.
The following example adds the Output
decorator to a method that processes an input. The decorator will add the output of the method to the attribute provided to the decorator. This method is helpful when using the IterateOn()
decorator. For each execution of the method the return data is appended/extended to the provided attribute. This decorator provides a decent amount of flexibility, provides consistent functionality, and reduces redundant code in the App.
1 2 3 4 5 6 7 8 9 10 | from tcex import Output
def __init__(self):
"""Initialize class properties."""
self.output_data = None
@Output(attribute='output_data', overwrite=False)
def capitalize(self, colors):
"""Return capitalized string."""
return colors.capitalize()
|
Read Arg¶
The ReadArg()
decorator is useful in decorating methods that use a user input.
The following example adds the ReadArg
decorator to a method that takes a String. The decorator will call the method passing the value of the append_chars input. If the fail_on_error
input is enabled and the input matches a value in the fail_on array, the App would then exit using the fail_msg string provided. This decorator provides a decent amount of flexibility, provides consistent functionality, and reduces redundant code in the App.
1 2 3 4 5 6 7 8 9 10 11 | from tcex import IterateOn
@IterateOnArg(
arg='append_chars',
fail_enabled='fail_on_error,
fail_msg='Failed to append characters to string input.',
fail_on=['None' ''],
)
def append(self, string, append_chars):
"""Return string with appended characters."""
return f'{string}{append_chars}'
|


In my experience, poor people are the world’s greatest entrepreneurs. Every day, they must innovate in order to survive. They remain poor because they do not have the opportunities to turn their creativity into sustainable income.
 As a young man with high determination, I always know what should I do to reach my goals, then find the ways to get it as fast as I can. Although I am not a big person, I believe I can do big things with my own hands. An old man told me “nothing’s impossible, it just depends on the way we approach it”. I hundred percent agree with that saying because of the endless of human’s abilities.


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Frame Number:


The tree data structure simulate a windows file system, with 2 drives C: and D:
The tree data structure is based on the one in the demo above, but showing only files accessible to a specific user.


This tool allows you to predict values at new locations based on measurements from a collection of points. The tool takes point data with values at each point and returns a raster of predicted values.
Other use cases of this tool include the following:
The point layer that contains the points where the values have been measured.
Choose the field whose values you wish to interpolate. The field must be numeric.
Choose your preference for speed versus accuracy.
More accurate predictions take longer to calculate. This parameter alters the default values of several other parameters of Interpolate Points in order to optimize speed of calculation, accuracy of results, or a balance of the two. By default, the tool will optimize for balance.
Choose whether to transform your data to the normal distribution.
Interpolation is most accurate for data that follows a normal (bell-shaped) distribution. If your data does not appear to be normally distributed, you should perform a transformation.
Interpolate Points works by building local interpolation models that are mixed together to create the final prediction map. This parameter controls how many points will be contained in each local model. Smaller values will make results more local and can reveal small-scale effects, but it may introduce some instability in the calculations. Larger values will be more stable, but some local effects may be missed.
The value can range from 30 to 500, but typical values are between 50 and 200.
Predictions are calculated based on neighboring points. This parameter controls how many points will be used in the calculation. Using a larger number of neighbors will generally produce more accurate results, but the results take longer to calculate.
This value can range from 1 to 64, but typical values are between 5 and 15.
The cell size and unit for the output rasters.
The available units are Feet, Miles, Meters, and Kilometers.
Choose whether you want to create a raster of standard errors for the predicted values.
Standard errors are useful because they provide information about the reliability of the predicted values. A simple rule of thumb is that the true value will fall within two standard errors of the predicted value 95 percent of the time. For example, suppose a new location gets a predicted value of 50 with a standard error of 5. This means that this tool's best guess is that the true value at that location is 50, but it reasonably could be as low as 40 or as high as 60. To calculate this range of reasonable values, multiply the standard error by 2, add this value to the predicted value to get the upper end of the range, and subtract it from the predicted value to get the lower end of the range.
The name of the layer that will be created in My Content and added to the map. The default name is based on the tool name and the input layer name. If the layer already exists, you will be prompted to provide another name.
You can specify the name of a folder in My Content where the result will be saved using the Save result in drop-down box.


gsTiles.locator module
-
class
gsTiles.locator.
BBoxLocator
(source)[source]
Bases: object
- contains_point() will return a list of areas whose bonding boxes contain the point, and is much faster
- – benchmark: query 74001 centroids: 5.7439 seconds (13,000 queries per second)
-
clone
()[source]
-
extent
-
overlapping
(rect, zoom=-1)[source]


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CodePen by Cole Waldrip


module Check
Overview
Standalone check module that provides a practical workflow for validations.
Defined in:
check.crcheckable.cr
Constant Summary
-
RULES =
{} of String => HashLiteral(String, ASTNode)
Class Method Summary
-
.new_validation(errors : Errors)
Initializes a new
Validation
instance to combine a series of checks (Validation#check
). -
.new_validation
Initializes a new
Validation
instance to combine a series of checks (Validation#check
).
Macro Summary
-
checkable
A mixin to make a class checkable.
-
rules(**fields)
Generates
check
,check_{{field}}
andclean_{{field}}
methods for fields (class variables).
Class Method Detail
Initializes a new Validation
instance to combine
a series of checks (Validation#check
).
using an existing errors Hash
(Check::Errors
).
v = Check.new_validation existing_errors
Same as:
v = Check::Validation.new existing_errors
Example to combine two hashes of validation errors:
preview_validation = Check.new_validation
v = Check.new_validation preview_validation.errors
Initializes a new Validation
instance to combine
a series of checks (Validation#check
).
v = Check.new_validation
Same as:
v = Check::Validation.new
Macro Detail
A mixin to make a class checkable.
This mixin includes Checkable
and CheckableStatic
.
It must be used in conjonction with Check.rules
.
require "validator/check"
class Article
# Mixin
Check.checkable
property title : String
property content : String, {
required: true,
check: {
not_empty: {"Article content is required"},
between: {"The article content must be between 10 and 20 000 characters", 10, 20_000},
# ...
},
clean: {
type: String,
to: :to_s,
format: ->(content : String) { content.strip },
message: "Wrong type",
},
}
def initialize(@title, @content)
end
end
# Triggered on all data
v, article = Article.check(input_data)
# Triggered on a value
v, content = Article.check_content(input_data["content"]?)
Generates check
, check_{{field}}
and clean_{{field}}
methods for fields (class variables).
require "validator/check"
class Article
# Mixin
Check.checkable
property title : String
property content : String
property url : String?
private def self.after_check_content(v : Check::Validation, content : String?, required : Bool, format : Bool)
puts "after_check_content"
puts "Valid? #{v.valid?}"
content
end
Check.rules(
content: {
required: "Content is required", # or `true` to use the default error message
before_check: ->(v : Check::Validation, content : String?, required : Bool, format : Bool) {
puts "before_check_content"
content
},
after_check: :after_check_email,
check: {
not_empty: {"Article content is required"},
between: {"The article content must be between 10 and 20 000 characters", 10, 20_000},
# ...
},
clean: {
type: String,
to: :to_s,
# Proc or method name (Symbol)
format: ->(content : String) { content.strip },
message: "Wrong type",
},
},
url: {
check: {
url: {"Article URL is invalid"},
},
clean: {
# `nilable` means omited if not provided,
# regardless of Crystal type (nilable or not)
nilable: true,
# Crystal type
type: String,
# Converter to the expected typed value
to: :to_s,
},
},
# ...
)
end
# Triggered on all data
v, article = Article.check(input_data)
# Triggered on all fields of an instance
article = Article.new(title: "foo", content: "bar")
v = article.check
# Triggered on a value
v, content = Article.check_content(input_data["content"]?)
# Cast and clean a value
ok, content = Article.clean_content(input_data["content"]?)
See also Check.checkable
.


New Game
Watch Game
Join Game
{{ game.currentPlayer }}
{{ game.currentDificulty }}
{{ game.currentQuestion }}
{{ game.currentDificulty }}
Who Won the round?
{{ player.name }}
Add Player
Start Game
Name
Score
{{ player.name }}
{{ player.score }}
{{ game.currentDificulty }}
Category
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{{ baseUrl }}


--- layout: post status: publish tags: [] title: Never punt again layout: post url: /2015/04/16/never-punt-again/ ---


37
Investors
2
Administrators
27
Investments
2
Withdrawals
| UID | Name | Country | Date | |
|---|---|---|---|---|
| SPI/0040 | olowolaju tola |<EMAIL_ADDRESS>| United States of America | 23rd of February, 2019 9:20 pm |
| SPI/0039 | Smith James |<EMAIL_ADDRESS>| United States of America | 11th of July, 2018 5:36 pm |
| SPI/0038 | Akintunde James |<EMAIL_ADDRESS>| Nigeria | 10th of July, 2017 12:55 pm |
| SPI/0037 | ROBERTS MIEBAKA |<EMAIL_ADDRESS>| Russia | 4th of December, 2016 3:59 pm |
| SPI/0036 | Roberts Miebaka |<EMAIL_ADDRESS>| Russia | 28th of November, 2016 9:21 pm |
| SPI/0035 | amachree edwin |<EMAIL_ADDRESS>| Nigeria | 25th of November, 2016 7:36 pm |
| SPI/0034 | Falana Louis |<EMAIL_ADDRESS>| Russia | 5th of November, 2016 3:54 pm |
| SPI/0033 | jaspiro igboke |<EMAIL_ADDRESS>| United States of America | 4th of November, 2016 10:12 pm |
| SPI/0032 | arthur darlington |<EMAIL_ADDRESS>| Russia | 31st of October, 2016 6:37 pm |
| SPI/0031 | jasper IGBOKE |<EMAIL_ADDRESS>| Russia | 26th of October, 2016 6:56 pm |
| SPI/0030 | TIMOTHY AFUBE |<EMAIL_ADDRESS>| Russia | 25th of October, 2016 6:18 pm |
| SPI/0029 | Bughuul Fanen |<EMAIL_ADDRESS>| Russia | 19th of October, 2016 11:41 am |
| SPI/0028 | Inyang Menyene |<EMAIL_ADDRESS>| Russia | 10th of October, 2016 7:37 am |
| SPI/0027 | Amachree Edwin |<EMAIL_ADDRESS>| Russia | 9th of October, 2016 4:02 pm |
| SPI/0026 | Amachree Edwin |<EMAIL_ADDRESS>| Nigeria | 9th of October, 2016 3:32 pm |


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Dear Dry,
With your help, just moments ago, the House GOP Leadership failed in its attempt to gut the Violence Against Women Act (VAWA). The Senate-passed inclusive bipartisan VAWA just passed the House on a vote of 286-138 after the House GOP substitute bill went down to defeat on a vote of 166 to 257.
Thank you for all you have done. Women’s groups and their allies acted as one and created a massive grassroots campaign to pass a strong VAWA despite the Republican House leadership opposition. WE cannot forget those who voted to roll back full protections of VAWA for college students, immigrants, and the LGBT community, Native Americans as well as the Office of Violence Against Women.
Our work has made a difference in the fight to end violence against women. This victory for all survivors sends a clear message that violence is violence no matter the victim.
For women’s lives,
Eleanor Smeal
President
Feminist Majority Foundation
You have received this e-mail because of your interest in women’s issues. To unsubscribe, please click here. [ http://salsa.democracyinaction.org/o/1400/p/salsa/supporter/unsubscribe/public/index.sjs?unsubscribe_page_KEY=494 ]


Throughout history, many tribes and sects across the globe have shared a very deep bond with mother Earth and would sense it as a living being. They could feel and connect with nature like no one else. One such practice involved rituals of rainmaking in which tribes established a bond with nature and invoked rain through their earnest and beautiful singing.
Nowadays, we are losing this bond and treating our planet rather harshly. Thus, The Magic of Rainmaking is a website which presents a soundscape of a few tribes from different parts of the world engaging in rain-calling rituals. Through this site, we aim for the users to reconnect with nature and remind themselves of the beautiful bond that they can share with nature.
To make the user feel close to nature and conect with the tribes while navigating the site, hence we chose backgrounds which pictures forests, leaves, farmlands, village houses etc. to give a more realistic experience. The background sound of chirping birds on homepage was also an attempt to make user feel as if they are already in a soundscape which has taken them on a journey through the wonders of nature.