Neymar takes DIG at Thomas Tuchel following criticism from PSG manager
by Magnus EriksenParis Saint-Germain superstar Neymar has appeared to hit back at criticism from his manager Thomas Tuchel with a cryptic tweet.
The Brazil international was recently criticised by his manager for a trip to Madrid to watch the Davis Cup.
MORE: Neymar could return from injury to face Real Madrid in the Champions League
“What can I do? I’m not his father, nor the police. I am just his coach,” Tuchel said.
“He trained well. Did I enjoy his trip to Madrid? No. But he was very professional during those two weeks.”
Shortly after the German tactician made these comments, Neymar tweeted this message below…
It could be pure coincidence, but it seems unlikely that the 27-year-old didn’t know what he was doing here.
Neymar has not had the best of times at PSG, having been linked with a return to Barcelona for much of the summer transfer window.
In the end, he stayed at the Parc des Princes, but was booed by his own fans earlier on this season.


David Knight Show: The Money Behind Impeachment
Learn about some of the driving forces pushing the coup
by David KnightOn this Friday edition of The David Knight Show, you’ll learn about the financiers of the establishment’s impeachment push.
Also, find out if Trump is right to allegedly hope impeachment reaches Senate so key witnesses could finally be forced to publicly testify.
Also, follow David on Tik Tok by scanning the code below:
By the way, overhaul your body’s cellular engine with our fan-favorite DNA Force Plus!


Next: use-package, Previous: in-package, Up: Packages Dictionary
unuse-package
packages-to-unuse &optional package ⇒ t
packages-to-unuse—a designator for a list of package designators.
package—a package designator. The default is the current package.
unuse-package causes package to cease inheriting all the external symbols of packages-to-unuse; unuse-package undoes the effects of use-package. The packages-to-unuse are removed from the use list of package.
Any symbols that have been imported into package continue to be present in package.
(in-package "COMMON-LISP-USER") ⇒ #<PACKAGE "COMMON-LISP-USER"> (export (intern "SHOES" (make-package 'temp)) 'temp) ⇒ T (find-symbol "SHOES") ⇒ NIL, NIL (use-package 'temp) ⇒ T (find-symbol "SHOES") ⇒ SHOES, :INHERITED (find (find-package 'temp) (package-use-list 'common-lisp-user)) ⇒ #<PACKAGE "TEMP"> (unuse-package 'temp) ⇒ T (find-symbol "SHOES") ⇒ NIL, NIL
The use list of package is modified.
Current state of the package system.


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Reference e-Books:
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fair.tools package¶
Submodules¶
fair.tools.constrain module¶
-
fair.tools.constrain.
hist_temp
(Tobs, Tmodel, years, inflate=True, CI=0.9)¶ Checks to see whether model-derived temperatures fall in observational uncertainty.
Uses the method of Thompson et al., 2015, also used in IPCC AR5 to derive temperature trends which includes autocorrelation. The regression slope of the observations is compared to the regression slope of the model. If the trend of the model is within observational uncertainty, the test passes.
Reference: J. Climate, 28, 6443-6456 10.1175/JCLI-D-14-00830.1
- inputs:
- Tobs: observed temperature time series. Numpy array Tmodel: modelled temperature time series. Numpy array years: Numpy array of years covered by Tobs and Tmodel
- keywords:
- inflate: True (default) if the uncertainty bounds should be inflated
- for lag-1 autocorrelation - as used in Thompson.
- CI: confidence interval around the mean regression slope to count as
- constrained. Default 0.9.
- returns:
- accept: True if ensemble member agrees with observations else False. slope_m: regression slope of modelled temperature intercept_m: intercept of modelled temperature slope_o: regression slope of observed temperature intercept_o: intercept of observed temperature
fair.tools.magicc module¶
-
fair.tools.magicc.
scen_open
(filename, include_cfcs='rcp45', startyear=1765, harmonise=None)¶ Opens a MAGICC6 .SCEN file and extracts the data. Interpolates linearly between non-consecutive years in the SCEN file. Fills in chlorinated gases from a specified RCP scenario or from custom emissions.
- Inputs:
- filename: the .SCEN file to open
- Keywords:
- include_cfcs: string, False, or nt x 16 numpy array
- MAGICC files do not come loaded with CFCs (indices 24-39). They are given in the harmonised files at http://www.pik-potsdam.de/~mmalte/rcps/. - Specify ‘rcp3pd’, ‘rcp45’, ‘rcp6’ or ‘rcp85’ to use these RCPs. - Use False to ignore and create a 24-species emission file. - Provide an array to tack your own chlorinated gases onto the SCEN
- startyear: First year of output file. If before first year of the SCEN
- file, use RCP4.5 to fill
- harmonise: None, or year
- Linearly interpolate between 2000 in the RCP file and the specified year. If None, do not harmonise
- Returns:
- nt x 40 numpy emissions array
- nt is defined as <last year of SCEN file> -
- <earlier of startyear and first year of SCEN file> + 1
It is assumed that the .SCEN files follow the formatting convention on the MAGICC wiki at http://wiki.magicc.org/index.php?title=Creating_MAGICC_Scenario_Files.


{% extends "base.html" %} {% load i18n %} {% load breadcrumbs from directory_components %} {% block head_title %}{% trans "Verify your email address - great.gov.uk" %}{% endblock %} {% block content %} {% breadcrumbs 'Verify email address' %} Great.gov.uk {% endbreadcrumbs %}
{% blocktrans %}We've sent you a confirmation email. Click on the link to verify your email address.{% endblocktrans %}
Contact us if you haven’t received the email within 10 minutes.


Amazon Connect User Hierarchy APIs
JSON Output
Waiting for server to respond
User Hierarchy Configuration
Level 1 :
Level 2 :
Level 3 :
Level 4 :
Level 5 :
Save user hierarchy structure
Enter AWS credentials for User Hierarchy Management
Access Key :
Region :
Secret Key :
Instance Id :
Save Configurations
Are you sure you want to delete?
Enter the new name for the hierarchy
Old name :
New Name :
Rename hierarchy
Enter the new name for the hierarchy
Name :
Add hierarchy


Clemson QB Trevor Lawrence Takes Incredible Photo With Fan
by Andrew McCartyA few weeks ago, a teenage girl went viral for a video she posted on TikTok.
Why? Well, she looks a LOT like star Clemson quarterback Trevor Lawrence. She posted a video mimicking Lawrence’s poses from a few different photos and the two showed a unique resemblance.
The two later spoke over a video chat, but hadn’t met in person.
Until today.
Lawrence and his female doppelganger caught up before Clemson’s game against Wake Forest on Saturday afternoon.
Check it out.
If you don’t see the resemblance there, here’s a video showing the girl recreating poses from Lawrence’s time on the field.
Social media can be a fun place after all.
As for the actual football game to be played this afternoon, Dabo Swinney and company are heavy favorites to keep their undefeated season alive.
The Tigers are a 34.5-point favorite over the Demon Deacons today. Clemson hasn’t played a close game since Mack Brown and North Carolina nearly upset the Tigers earlier this season.
Trevor Lawrence and the Tigers will be on the field at 3:30 p.m. ET. The game will be broadcast on ABC.


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# Environment variables
## overloading parameters via env vars
All configuration parameters, including custom environments and [dynaconf configuration](configuration.html), can be overridden through environment variables.
To override the configuration parameter {param}, use an environment variable named DYNACONF_{PARAM}. For instance, to override the “HOST” configuration parameter, you can run your application with:
`bash
DYNACONF_HOST='otherhost.com' python yourapp.py
`
## .env files
If you don’t want to declare the variables on every program call you can run export DYNACONF_{PARAM} in your shell or put the values in a .env file located in the same directory as your settings files (the root directory of your application or the same folder where your program script is located), variables in .env does not overrride existing environment variables.
> IMPORTANT: Dynaconf will search for a .env on the order explained [here](usage.html). So to avoid conflicts with existing .env in parent directories it is recommended to have a .env inside your project even if it is empty.
## Precedence and type casting
Environment variables take precedence over all other configuration sources: if the variable is set, it will be used as the value for the parameter even if parameter exists in settings files or in .env.
Variable values are parsed as if they were TOML syntax. As illustration, consider the following examples:
```ini # Numbers DYNACONF_INTEGER=42 DYNACONF_FLOAT=3.14
# Text DYNACONF_STRING=Hello DYNACONF_STRING=”Hello”
# Booleans DYNACONF_BOOL=true DYNACONF_BOOL=false
# Use extra quotes to force a string from other type DYNACONF_STRING=“‘42’” DYNACONF_STRING=“‘true’”
# Arrays must be homogenous in toml syntax DYNACONF_ARRAY=”[1, 2, 3]” DYNACONF_ARRAY=”[1.1, 2.2, 3.3]” DYNACONF_ARRAY=”[‘a’, ‘b’, ‘c’]”
# Dictionaries DYNACONF_DICT=”{key=’abc’,val=123}” ```
> NOTE: When exporting compose data types like arrays and dictionaries you must use quotes around the value e.g: export VARIABLE=”[‘a’, ‘b’, ‘c’]” instead of export VARIABLE=[‘a’, ‘b’, ‘c’]
``python # toml syntax does not allow `None/null values so use @none DYNACONF_NONE=’@none None’
# toml syntax does not allow mixed type arrays so use @json DYNACONF_ARRAY=’@json [42, 3.14, “hello”, true, [“otherarray”], {“foo”: “bar”}]’
# Lazily formatted string can access env vars and settings variables.
# using str.format DYNACONF_DATABASE_PATH=”@format {env[HOME]}/.config/databases/{this.DB_NAME}”
# using jinja2 DYNACONF_DATABASE_PATH=”@jinja {{env.HOME}}/.config/databases/{{this.DB_NAME}}” ```
> NOTE: Older versions of Dynaconf used the @casting prefixes for env vars like export DYNACONF_INTEGER=’@int 123’ still works but this casting is deprecated in favor of using TOML syntax described above. To disable the @casting do export AUTO_CAST_FOR_DYNACONF=false
## Merging new data to existing variables
### Nested keys in dictionaries via environment variables.
> New in 2.1.0 > > This is useful for Django settings.
Lets say you have a configuration like this:
settings.py
- ‘default’: {
‘NAME’: ‘db’, ‘ENGINE’: ‘module.foo.engine’, ‘ARGS’: {‘timeout’: 30}
}
}¶
And now you want to change the values of ENGINE to other.module, via environment variables you can use the format ${ENVVAR_PREFIX}_${VARIABLE}__${NESTED_ITEM}__${NESTED_ITEM}
Each __ (dunder, a.k.a double underline) denotes access to nested elements in a dictionary.
So
`py
DATABASES['default']['ENGINE'] = 'other.module'
`
Can be expressed as environment variables as:
`bash
export DYNACONF_DATABASES__default__ENGINE=other.module
`
> NOTE: if you are using Django extension then the prefix will be DJANGO_ instead of DYNACONF_ and the same if you are using FLASK_ or a custom prefix if you have customized the ENVVAR_PREFIX.
This will result in
- ‘default’: {
‘NAME’: ‘db’, ‘ENGINE’: ‘other.module’, ‘ARGS’: {‘timeout’: 30}
}
}¶
> IMPORTANT lower case keys are respected only on *nix systems, unfortunately Windows environment variables are case insensitive and Python reads it as all upper cases, that means that if you are running on Windows the dictionary can have only upper case keys.
Now if you want to add a new item to ARGS key:
`bash
export DYNACONF_DATABASES__default__ARGS__retries=10
`
This will result in
- ‘default’: {
‘NAME’: ‘db’, ‘ENGINE’: ‘other.module’, ‘ARGS’: {‘timeout’: 30, ‘retries’: 10}
}
}¶
and you can also pass a toml like dictionary to be merged with existing ARGS key using @merge token.
> new in 3.0.0
`bash
# as a toml (recommended)
export DYNACONF_DATABASES__default__ARGS='@merge {timeout=50, size=1}'
# OR as a json
export DYNACONF_DATABASES__default__ARGS='@merge {"timeout": 50, "size": 1}'
# OR as plain key pair
export DYNACONF_DATABASES__default__ARGS='@merge timeout=50,size=1'
`
will result in
- ‘default’: {
‘NAME’: ‘db’, ‘ENGINE’: ‘other.module’, ‘ARGS’: {‘retries’: 10, ‘timeout’: 50, ‘size’: 1}
}
}¶
Now if you want to clean an existing nested attribute you can just assign the new value.
`bash
# As a TOML empty dictionary `"{}"`
export DYNACONF_DATABASES__default__ARGS='{}'
`
This will result in
- ‘default’: {
‘NAME’: ‘db’, ‘ENGINE’: ‘other.module’, ‘ARGS’: {}
}
}¶
`bash
# As a TOML dictionary (recommended)
export DYNACONF_DATABASES__default__ARGS='{timeout=90}'
`
This will result in
- ‘default’: {
‘NAME’: ‘db’, ‘ENGINE’: ‘other.module’, ‘ARGS’: {‘timeout’: 90}
}
}¶
And if in any case you need to completely remove that key from the dictionary:
`bash
export DYNACONF_DATABASES__default__ARGS='@del'
`
This will result in
- ‘default’: {
‘NAME’: ‘db’, ‘ENGINE’: ‘other.module’
}
}¶
### Using the dynaconf_merge mark on configuration files.
> New in 2.0.0
To merge exported variables there is the dynaconf_merge tokens, example:
Your main settings file (e.g settings.toml) has an existing DATABASE dict setting on [default] env.
Now you want to contribute to the same DATABASE key by adding new keys, so you can use dynaconf_merge at the end of your dict:
In specific [envs]
```cfg [default] database = {host=”server.com”, user=”default”}
[development] database = {user=”dev_user”, dynaconf_merge=true} ```
or
> New in 2.2.0
```cfg [default] database = {host=”server.com”, user=”default”}
[development.database] dynaconf_merge = {user=”dev_user”} ```
In an environment variable use @merge token:
> New in 2.2.0
`bash
# Toml formatted envvar
export DYNACONF_DATABASE='@merge {password=1234}'
`
or dunder (recommended)
`bash
# Toml formatted envvar
export DYNACONF_DATABASE__PASSWORD=1234
`
The end result will be on [development] env:
`python
settings.DATABASE == {'host': 'server.com', 'user': 'dev_user', 'password': 1234}
`
Read more in [Getting Started Guide](usage.html#merging-existing-values)
### The global prefix
The DYNACONF_{param} prefix is set by ENVVAR_PREFIX_FOR_DYNACONF and serves only to be used in environment variables to override config values.
This prefix itself can be changed to something more significant for your application, however we recommend keeping DYNACONF_{param} as your global env prefix.
Setting ENVVAR_PREFIX_FOR_DYNACONF to false will disable the prefix entirely and cause Dynaconf to load all environment variables. When providing ENVVAR_PREFIX_FOR_DYNACONF as parameter to LazySettings or settings.configure, make sure to give it a Python-native False:
`python
from dynaconf import LazySettings
settings = LazySettings(ENVVAR_PREFIX_FOR_DYNACONF=False)
`
> NOTE: See the [Configuring dynaconf](configuration.html) section in documentation to learn more on how to use .env variables to configure dynaconf behavior.


What learnings did you take from the chapter?
There were a lot of concepts in Chapter 1. The one's that appeal the most to me were how the body responds to emotional changes and how visible they can be. You have to train yourself in a way that you can sort of see yourself from the outside, pretty much from a third person point of view. Oh and there are people who are Happiness strategiests? That sounds like a fun job.
How did you find the 2 minutes of mindfullness?
It's an interesting concept but I personally find meditation quite hard as my mind wanders a lot.


Manual burp invisible proxy setup
- Modify your operating system hosts file to resolve the hostnames used by the application to your loopback address
- <IP_ADDRESS> www.wahh-app.com
- For each destination port used by the application (typically 80 and 443), configure a Burp Proxy listener on this port of your loopback interface, and set the listener to support invisible proxying. The invisible proxying feature means that the listener will accept the non-proxy-style requests sent by the thick client, which have been redirected to your loopback address.
- For each hostname you have redirected using your hosts file, configure Burp to resolve the hostname to its original IP address. These settings can be found under Options > Connections > Hostname Resolution. They let you specify custom mappings of domain names to IP addresses to override your computer’s own DNS resolution. This causes the outgo- ing requests from Burp to be directed to the correct destination server. (Without this step, the requests would be redirected to your own com- puter in an infinite loop.)
- When operating in invisible mode, Burp Proxy identifies the destination host to which each request should be forwarded using the Host header that appears in requests. If the thick client you are testing does not include a Host header in requests, Burp cannot forward requests cor- rectly. If you are dealing with only one destination host, you can work around this problem by configuring the invisible proxy listener to redirect all its requests to the required destination host. If you are dealing with multiple destination hosts, you probably need to run multiple instances of Burp on multiple machines and use your hosts file to redirect traffic for each destination host to a different intercepting machine.
Tools
echomirage, windows only
Can hook to a process and sniff traffic associated with it.
https://resources.infosecinstitute.com/echo-mirage-walkthrough/
https://sourceforge.net/projects/echomirage.oldbutgold.p/
This relay can proxy and modify non-HTTP protocols in Burp!
https://github.com/jrmdev/mitm_relay


1. (5 min) The news about ClickHouse, Inc.
2. (35 min) What's new in ClickHouse 21.10.
3. (20 min) Q&A.
ClickHouse has grown a lot in 2020..2021.
Especially in the US and Europe.
...
We decided to create a company:
International, independent company.
Incorporated in the US. Headquarters in Amsterdam and Bay Area.
Distributed team. We are hiring in Europe, the US and all over the world.
Aaron Katz, CEO - ex. Elastic, Salesforce.
Alexey Milovidov, CTO.
Yuri Izrailevsky, President of Engineering - ex. Google, Netflix.
Monthly stable release for October.
SQL User Defined Functions (since 21.10)
CREATE FUNCTION ch AS (x) -> (exp(x) + exp(-x)) / 2;
CREATE FUNCTION getRegionName AS (x)
-> dictGet('region', 'name', x);
— the functions are polymorphic;
— they are substituted as expressions;
— queries are optimized for CSE and JIT compilation;
Limitations:
— no loops;
— no recursion;
Introspection:
SELECT name, create_query
FROM system.functions
WHERE origin = 'SQLUserDefined'
┌─name─────┬─create_query────────────────────────────────────────┐
│ ch │ CREATE FUNCTION ch AS x -> ((exp(x) + exp(-x)) / 2) │
└──────────┴─────────────────────────────────────────────────────┘
Persistence:
— functions are stored in /var/lib/clickhouse/user_defined/.
Distributed queries:
— functions should be available on initiator node.
Data generation and import:
CREATE TABLE test ... ENGINE =
Executable('my_script', TSV);
— the script should return data in stdout, similar to "file" engine.
Data transformation:
CREATE TABLE test ... ENGINE =
Executable('my_script', TSV, (SELECT ...));
— the script will get source stream to stdin and return data in stdout.
Custom JOIN logic:
CREATE TABLE test ... ENGINE =
Executable('my_script', TSV, (SELECT ...), (SELECT ...), ...);
— the script will get source stream to stdin and additional streams in fd 3, 4...
Two variants:
— Executable: script is run on every query;
— ExecutablePool: a pool of persistent processes;
Table function:
SELECT * FROM
executable('my_script', TSV, 'x UInt64...');
SELECT * FROM
executable('my_script', TSV, 'x UInt64...', (SELECT ...) ...);
Applications:
— loading data from foreign data source;
— applying machine-learned models to dataset;
— custom processing, e.g. DNS resolution, whois...
Upcoming:
— Scriptable User Defined Functions (since 21.11-testing)
<function>
<type>executable</type>
<name>myPlus</name>
<return_type>UInt64</return_type>
<argument><type>UInt64</type></argument>
<argument><type>UInt64</type></argument>
<format>TabSeparated</format>
<command>awk '{ print $1 + $2 }'</command>
<execute_direct>0</execute_direct>
</function>
— User Defined Types (21.11 .. 21.12)
Transparent support for import & export of compressed data.
Now we support gz, xz, zst (21.1), bz2 (21.9) and lz4 (21.10).
It works for url, file, s3, hdfs,
HTTP Content-Encoding,
SELECT INTO OUTFILE,
and INSERT FROM INFILE (21.11).
Partitioned export to S3:
INSERT INTO TABLE FUNCTION
s3('http://test.s3.amazonaws.com/bucket/file{_partition_id}.csv.gz',
CSV, 'name String, time DateTime')
PARTITION BY toYYYYMMDD(time)
VALUES ...
Upcoming:
Partitioned export to hdfs, file, url.
ALTER ... MATERIALIZE COLUMN:
ALTER TABLE t MATERIALIZE COLUMN c;
-- write column if it was not materialized.
ALTER TABLE t MATERIALIZE COLUMN c FINAL;
-- unconditionally rewrite column on disk.
Before:
ALTER TABLE t UPDATE c = c; -- unconditionally rewrite column;
OPTIMIZE TABLE t FINAL; -- rewrite and merge all table parts.
 Tokenization, stemming, lemmatization, synonims (21.9..21.11).
— SELECT arrayMap(word -> lemmatize(word), tokens(text)).
2. Charset and language detection (Q4 2021).
3. Semi-duplicate text search (21.1).
— min-hash and sim-hash algorithms.
Allow to do many small INSERTS.
From many concurrent connections.
Without Kafka and Buffer tables!
Many small INSERTs are combined together
and batched in memory.
Safe by default: every client get response when data is inserted.
Available in 21.11-testing
Learning portal: https://clickhouse.com/learn/
— step-by-step tutorials and examples!
Full changelog:
https://github.com/ClickHouse/ClickHouse/blob/master/CHANGELOG.md
Calling all visionaries and builders!
ClickHouse is growing and expects to double in size. Get in early:
Apply here: clickhouse.com/careers or<EMAIL_ADDRESS>Global, fully remote roles available:
— Cloud Software Engineer (Go, Kubernetes)
— Support Engineer
— Core Software Engineer (C++)
Send feedback<EMAIL_ADDRESS>Sign up to our newsletter.


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As part of a BBSRC-funded crop infrastructure project, we have established a pipeline for generating track hubs for all public RNA-Seq studies in the INSDC archives. The pipeline discovers and aligns reads from RNA-Seq studies across all plant species in Ensembl Plants. Alignments and their associated metadata are registered in the Track Hub Registry for search and discovery within the genome browser.
In detail, the pipeline uses the ENA's search APIs to discover all plant-spcific RNA-Seq studies. The read data for each study is aligned to the appropriate reference genome in Ensembl Plants using the iRAP pipeline developed by the EMBL-EBI Gene Expression team. Quality-filtered reads are aligned using TopHat 2. The resulting BAM files are converted to CRAM format. Each set of CRAM files for a specific study, along with their associated sample and study metadata, are used to create a track hub that is registered in the Track Hub Registry.


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---
title: "Pacific Coast"
layout: "post"
permalink: "/2010/10/pacific-coast.html"
uuid: "4446727577990987342"
guid: "tag:blogger.com,1999:blog-8745734052417186264.post-4446727577990987342"
date: "2010-10-31 02:44:00"
updated: "2010-10-31 03:10:32"
description:
blogger:
siteid: "8745734052417186264"
postid: "4446727577990987342"
comments: "0"
categories: [blog, Family, holiday]
tags: [Family, holiday]
author:
name: "Alan Chalmers"
url: "https://plus.google.com/109008868852571463084?rel=author"
image: "//lh6.googleusercontent.com/-vRVdiWd12ak/AAAAAAAAAAI/AAAAAAAAHKc/wXgK4dFefp8/s512-c/photo.jpg"
---
Day two and we drove up from and we did a bit of the tourist things in Santa Barbara visited the
Santa Barbara Old Mission. With some storm cloud brewing in the background we took a stroll only the beachfront and wondered out on Stearns Warf .
First stop out of Santa Barbara was Solvang an incredibly kitsch Danish town in the middle of California, we think they getting a bit confused there was certainly some Dutch, German, Belgium mixture happing there.
We finished up the Day at San Simeon on the coast with a great sunset.


@* * 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. *@ @(params: Map[String, Any]) @uk.gov.hmrc.hmrcemailrenderer.templates.helpers.html.template_main(params, "You submitted a registration for duty on gas for use as road fuel"){
Dear @params("customerName")
HMRC has received your application to register a business for duty on gas for use as road fuel.
You must complete form C&E930B for each of your premises to provide us with further registration details. You’ll need to go to GOV.UK and search for the C&E930B form.
You must also contact HMRC to tell us your business is a partnership. You’ll need to email<EMAIL_ADDRESS>to let us know, so that we can ask you for more details about this.
From HMRC Excise team
}


My name is Alexander Fadeev, I am [Calculating...] years old.
Intermediate English
Competitive Programming
JS
C++
Golang
Github - AlexanderFadeev
Codeforces - afadeevz (Alex.F)
Telegram - @afadeevz
Instagram - @afadeevz
VK - @afadeevz
Email -<EMAIL_ADDRESS>Mobile phone - [Spoiler]


Edit 5-5 Copies the buffer at the cursor relative to the pivot point.
Press 5 to start the Move.
Rubber banding is enabled.
Move the cursor to the target position.
Rubber band previews the Copy from pivot point to cursor position..
Press 5 to complete the Copy.
The buffer is Copied at the cursor position.
The Copy becomes the Buffer and the Pivot point is reset on the copy so that sequential copies can be made.


Q. What are Encoding Errors?
A. Stat/Transfer stores strings internally in Unicode, which is capable of storing all of characters in all languages, plus many, many other symbols. Most older character sets are of much more limited scope. For instance, the most common encoding, ASCII, is only capable of storing a handful of symbols, letters and numbers, since it has only 127 locations for characters and control codes. Other single-byte character sets double the amount of storage and allow accented characters and other useful symbols. There are a number of such single-byte character sets, for instance one is suitable for the Cyrillic alphabet and another for modern Greek.
When Stat/Transfer reads data, it converts it to Unicode either based on the settings for character sets in the encoding options, or information written in the input file. If you file does not have information on the encoding, and is in a character set that is not the default encoding used on your computer, you must tell Stat/Transfer which encoding to use. For instance, if a Greek colleague sends you a Stata dataset, you may need to select a Greek character set in order to properly read it and translate it to a Unicode based system such as Excel. If the dataset contains non-ASCII strings and you do not set the encoding properly, you will get nonsense on output.
Because all single byte characters can be mapped to Unicode, there are seldom errors on input. However, you might encounter them if you are reading multi-byte characters such as those for Japanese.
The most common problems occur on output, when sometimes a character that was read on input has no mapping to the output character set. For instance, if you read your Greek data set and attempted to write it to SAS, using your Western European machine default, there would be many encoding errors because Greek characters in Unicode cannot be mapped to a character set such as latin1.
Some problems are more surprising because it looks as if you are dealing with ASCII, but your file has some characters that cannot be represented in the output. For instance all Microsoft applications use Unicode and characters such as the left apostrophe cannot be mapped to common non-unicode character sets. The same is true for the Euro sign, which is not present in ISO-8859-1, but is present in its more modern replacement, ISO-8859-15. If any of these characters are present, you may well get an encoding error.
Q. When don't I have to worry about this?
A. Most statistical data are numbers and ASCII letters. These are properly and unambiguously represented in all character sets. If that is what is in your data, you will not encounter encoding errors.
Also, if you are reading from or writing to a Unicode based format, the problem disappears because every character can be properly represented and there is no ambiguity. Excel and Access are in this class as well as versions of SPSS higher than 17. SAS Versions 9.1 and above store information about the encoding in the file and Stat/Transfer can use that to set the encoding. Anytime that encoding information is stored in the file, this information takes precedence over your option settings.
Q. How do I fix or work around "Encoding Errors"?
A. If the problem arises from an inappropriate character set, either for input or output, you should change the character set on the Encoding Options section of the Options dialog box. For instance, if you know your data contains Cyrillic characters, simply pick an appropriate character set.
If you think the problem may be due to sporadic characters that cannot be translated, choose the ‘Substitute’ option rather than ‘Stop’. In that case, an underscore will be substituted for characters which cannot be converted.
Sometimes, if a transfer is necessary out of a Unicode application such as SPSS or Excel to a non-Unicode application, and the dataset contains strings in many languages, that require different encodings on output, there is simply no way to work around the problem. In that case, simply set the number of permitted substitutions to a high number and proceed with your transfer. You will then see underscores for characters that cannot be represented in your output character set.
Q. What about Stata Version 13 and earlier?
A. Stata before version 14 did not support Unicode and did support other multi-byte character sets, such as those necessary for Far Eastern Languages. If you are working with a data set in which all of the strings are in a language that can be represented by single byte characters (all European languages) just choose the appropriate output encoding. However, if your dataset contains strings in Far Eastern languages or multiple languages that use different character sets, you will simply not be able to properly represent all of the strings and will need to live with underscores in your data.
We highly recommend that Stata users upgrade to get the benefits of Unicode. Now Stat/Transfer can transfer data in any language to Stata.


Now, suppose that you wished to compare this set of Roles against the set found in
Geobacter metallireducens GS-15 (kb|g.9032 in the CS). You can get the roles for
that genome using
echo 'kb|g.9032' | genomes_to_fids CDS | fids_to_roles 2> /dev/null |Before you run it, note that the command fids_to_roles writes error messages when it cannot match a fid to any Roles.
cut -f 3 > roles.in.g.9032
Now you can use
a_and_b roles.in.g.9032 all.roles > roles.for.models.g.9032 a_not_b roles.for.models roles.for.models.g.9032 > roles.to.search.forto create a file of Roles in kb|g.9032, but not yet found in the annotations we got back for our new version of g.2860.


Woofer Onesie is a wearable-tech accessory that is placed on the underside of a onesie and using the Adafruit Flora, connected with the Pulse Amped Sensor and a 60-LED neopixel strip, displays the puppy's heartbeat across its body.
Adafruit's Flora is an Arduino-compatible microcontroller used for wearable devices, and has built-in USB support to be reprogrammed according to the requirement.
For the purpose of Woofer Onesie, I soldered the Pulse Amped's as well as the Neopixel strip's connectors to the Flora's ports for easy placement.
Woofer Onesie's functionality comes from the detachable felt device that comprises the Flora + Pulse Amped + Battery cage - all kept together with conductive thread and the support from a glue gun.
This is Matisse. Taken after the iconic artist - he wanted to make his own mark in the world. And here he found his big break - by becoming the first puppy to have his heart-beat displayed on his body-sleeve.
The device was attached to the bottom of the Onesie with the pulse-sensor tucked tight on the underside (with the help of some elastic) to read his femoral artery and accordingly have a strip of lights run across the neopixel strip.
Like all models on their first shoot, here we have Matisse really working his outfit and its services.
However, after an exhausting day consisting of extensive documentation and multiple tailor-breaks, we have Matisse lying about the house - with just enough energy to observe passer-bys, and somewhat fulfill his original duties of a guard-puppy.
Here, the functionality of Woofer Onesie's sensor with neopixel will be tested on Mario with the heart-beat displayed around the periphery of his bed.
The first part of the video shows Mario comfortably sitting in his bed and the slow heartbeat shows how calm his body is.
In the second video, we can hear Matisse in the background wanting to play. Consequently, Mario's heart is racing because of the loud barking.
Mario was heavily comforted after the video was taken.
And here we have it! A fully functional device that can measure one's heartbeat and display it on neopixels.
The code used to showcase the heartbeat on Mario and Matisse varies in purely the movement of lights. I wanted there to be a difference because Matisse's BPM is significantly lower than Mario's.


If you want to know where the time flies then track your time. And do it quickly. Otherwise your time will be spent here.
You can do this in three different category and if your done then come and check your spent times here.


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Welcome Back, Spring 2019
Anouncements
- HackTruman 2019 will be March 29th - 31st
Topic
A welcome back, informational meeting about the upcoming semester
- Executive BOard Introductions
- Abanoub - President
- Thu - Vice President
- Karl - Secretary
- Ebenezar - Treasurer
- Dat - Webmaster
- General Introductions
- Lots of Wonderful People
- New General Meeting Topics
- A couple meetings a topic
- More like a crash course
- Will allow for more in-depth explanations
- Possible Topics
- AI
- Quantum Computing
- Ethical Hacking*
- Web Developing
- Blockchain Programming
- Git*
- Terminal
-
Linux Installation Party*
*Favorite
- HackTruman 2019
- Date Finalized - March 29-31
- PickHacks 2019
- Date - March 1-3
- Shuttle Bus Available Friday, 12pm
-
Possible Joint Event with SPS
-
Activity Faire this Wednesday in the SUB
- Dues are 5$ for the semester
- CS Bonfire??


While job hunting, I wanted a way to compare offers that could take different cost of living and tax rates into account. Hacked this thing up. It has hardcoded 2015 tax brackets pulled from tax-brackets.org - it is not super accurate but should give a kind of rough idea of how salaries actually compare.
I assume the user is single and has no dependants or other investments.
This will save your session locally, but does not send any data to a server (in fact, davidbstein.com is a static stite)
Add new offer
Basics
Monthly Costs (optional)
Perks (optional)
Comparison
key
(loading chart...)


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General Settings
Jurisdiction Name:
Legislature Name:
Typology:
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Angle (1-360):
Number of seats:
Parties and Groups
Enable Speaker
Speaker is Partisan
Party
{{party.name}}
Legislature Has Parties
Remaining seats: {{ numberOfSeats - parties.reduce((acc, cur) => acc += cur.numberOfMembers, 0) }}
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Number of members:
Color:
Government Bench
☰
{{party.name}}
Opposition Bench
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{{party.name}}
Crossbenches
☰
{{party.name}}
Party Ordering
(Left / Opposition)
(Left)
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(Right / Government)
(Right)
Add Party
Drawing Settings
Seat shape:
Square
Circle
Seat Size:
Seat Spacing:
Equal Bench Sizes
Classroom Columns:
Crossbenches' Fraction of Total Seats (0-1):
Load/Save Data
Load
Save
Export as SVG
Generate


Since its introduction during
the 2007/8 season Zuku's Soccer Pro is fast becoming the popular choice
among top-level footballers.
Soccer Pro was developed to help players cope with the greater physical
demands of the modern game. It's designed to help players get the most
out of their match-day performance. The late stages of the game are vital,
it's when so many matches are won or lost.
Each
Soccer Pro sachet contains one match serving and the small, chewable tablets
are fruit-flavoured and easy to eat. Soccer Pro contains cutting-edge
ingredients that are totally natural and 100% safe for sports use. It's
manufactured in Switzerland to the highest production standards.
Soccer Pro is exclusively available from www.zuku.com
We've got an exclusive offer for football.mitoo users.
Enter the code: FMT19 at the zuku.com checkout, to receive extra* Soccer
Pro sachets with any Soccer Pro order you place. (Offer valid until 31st March 2009)
* 5 extra sachets with each Soccer Pro Team Box & 1 extra sachet with
each Soccer Pro Player Pack ordered
|


"The best way to predict the future is to invent it."
--Alan Kay, 1971 meeting of Palo Alto Research Center and Xerox staff
|
It is time that we had a better programming language for business.
Our program statements have been speaking to mechanized actors that are, to be charitable, only somewhat smarter than a programmable calculator.
Business programming notations should include fundamental business concepts as built-in capabilities.
To achieve this, we need to raise the actors' level of intelligence.
Automating business processes means automating workflow. We need notations that express the business process workflow directly and clearly. A typical business process involves collaboration among communities of actors that share a common vocabulary. In addition, these actors share a common corporate memory, utilize many of the same resources, communicate via work orders, and carry on conversations that last for years. A business also requires bookkeeping. All these concepts can and should be built into the run-time system. We can move the business programming focus from the data process to the business process. A programming language is a coordinated set of notations. Each notation speaks to a specific interpreter. Ideally, each notation should be quickly and correctly interpreted by both humans and machines. This paper demonstrates how we can use natural language to produce a set of notations that is readable by both humans and machines. These notations provide the means to program the agency, the community of actors collaborating to run the business. |
For many years, my hobby has been the design of a programming language that would allow most programming ideas to be expressed in notations similar to natural written language. I called that project Simple English. At the same time, my work life has involved writing programs to automate business processes. A deep study of problems involved in business automation led me to the conclusion that there are serious flaws in the languages that most of us use for business programming. The most serious and pervasive flaw is that those languages were designed to speak to a computer that essentially functions as a programmable calculator. What we need is a language designed to speak to a business operation.
The programming language that we, as business programmers, use at work has a profound effect on the quality of our work life and productivity. In many sciences, new notations stimulate progress. A programming language is essentially a coordinated set of notations. As change agents, we should always be actively engaged in creating notations that facilitate clear expression of our thoughts.
Current programming languages are anemic and surprisingly primitive when you consider the fact that they are the product of 50 years of evolution. They are basically designed to shuffle small amounts of data from place to place.
Because our procedural statements are speaking to a mechanized actor that is basically a programmable calculator, the procedural notation reflects the fact that the actor has a very limited vocabulary. A business programming language should include fundamental business concepts as built-in capabilities. We need to raise the actor's level of intelligence as well as the level of discourse that we see in our programs. We need to make the thing we a speaking to smarter. Fortunately, that is not too difficult when we set our minds to it.
For starters, we can delegate many day-to-day data shuffling tasks to the system. Most of the code we write to complete these tasks follow highly predictable design patterns. We should not need to program such things in this day and age. The system can be designed to obviate the need for such low-level code. Most data shuffling and bookkeeping tasks can be removed from our workload.
Curiously, the term electronic computer is a misnomer. A more accurate term would be electronic data shuffler. Although we routinely refer to our systems as "the computer," business arithmetic, per se, is rarely needed, poorly done, and poorly served by our current programming systems. Our languages do not include date, time, unit of measure, or monetary currency as base types. One can argue that these concepts are supported by program libraries (class libraries), but those that I have evaluated are less than adequate. As an example: Consider the function that you would need to write in order to calculate the number of business days between two dates. However, you should not need to invent that function. Many business processes require that calculation. It is one of many that can and should be built into our programming language but has been missing.
The essence of business automation involves the mechanization of business process workflows. A business process necessarily involves the coordination of communities of actors. What does this imply for the design of a future programming language? It implies that our set of notations should clearly express workflow concepts. Such concepts include goals, actors, actions, dialogs, and work orders.
What does this context imply for the design of our run-time system? It implies that the run-time system should, among other things, provide for simple and secure communications among actors. The messages sent between business actors are, in effect, work orders. The messages should be recognized as work orders, with built-in resource management including inventory management, resource assignment, and cost accounting.
Current programming languages do not provide sufficient support for even the most fundamental type: numbers. In business programming, numbers represent measurements. A measurement involves a quantity, a precision, and a unit of measure. For example, we might say that a vehicle consumes 7.5 liters per hundred kilometers plus or minus 1.4 liters. The run-time system should accurately calculate with numbers that represent measurements and correctly track the precision of the results. Answers with spurious precision should become a thing of the past. We should be able to display a number in the unit of measure that the particular corporate culture prefers without having to program the conversion from other units of measure ourselves. The run-time system should have that capability built-in.
One of the tasks in business programming involves sorting out business workflow. A better choice of notation can reduce the time spent on this. Here is a simple example. Suppose we want to bake a cake. We need a plan. Baking a cake is a simple matter; it involves only a few steps. Some business processes involve hundreds or thousands of steps. But we can tackle any problem, regardless of size or complexity, by starting with the final goal and working backwards. This is a powerful technique for solving even the most complex problems.
Listing (below) shows a goal frame with a notation designed to facilitate that process. We define a plan segment with its post-condition (goal), the preconditions that must be observed before the post-condition can hold, and any actions (preferably one action) that must be performed to make the transition between the state where the preconditions are true and the state where the post-condition is true. This is conceptually comparable to a state-transition diagram or a precedence chart; but it is executable, readable, and the semantics are more explicit.
that must be met prior to the final action that achieves our goal.
Goal: Cake is baked according to recipe. Preconditions: . Oven is preheated to the temperature given in the recipe. . The recipe's batter is in a prepared cake pan. Actions: . Baker: Bake the pan in the oven for the time given in the recipe.
The goal-frame notation provides a way for us to break a complex problem down into smaller problems. For each precondition, we prepare another goal frame that defines what is needed to achieve that condition. The goal frame in Listing (above) identifies two preconditions. That means that we need two more goal frames showing how those preconditions might be met. Note that the work to meet those preconditions can be executed concurrently. Parallel processing is implicit in the notation. Listing (below) shows two goal frames that define the next layer of the plan.
Goal: Oven is preheated to the temperature given in the recipe. Preconditions: . The oven's gas burner is lit. (We are using a gas-fired oven.) . The oven's thermostat is set to the temperature given in the recipe. Action: . Timer: Wait 5 minutes. --- Goal: The recipe's batter is in a baking pan. Preconditions: . The recipe's batter is in the mixing bowl. . The cake pan is greased. Actions: . Baker: Pour the batter from the mixing bowl into the cake pan.
Eventually, we discover preconditions that have no prerequisites. A precondition with no prerequisites is identified with an "[Assumed]" annotation in square brackets that tell the plan checker that it need not expect a goal frame for those preconditions. (The plan checker is a component in the programmer's assistant [in the interactive development environment, or IDE].) Listing (below) shows a precondition that is marked [Assumed]. This indicates that no goal frame is required to define that precondition. Since the goal frame has no other preconditions, the action statement can run immediately when the plan is executed.
Goal: The recipe's batter is in the mixing bowl. Preconditions: . The ingredients required by the recipe are on hand. [Assumed.] Action: . Baker: Stir each ingredient into the batter in the mixing bowl.
In a natural language, nouns represent variables. People assign objects in the environment to the nouns when they interpret a natural language statement. Similarly, the nouns in the goal-frame statements indicate the input that will be needed when the system executes the plan. The system's pretty printer furnishes hyperlinks for those nouns. The links connect each noun to its definition and where-used list.
The system learns which words are nouns by reading dictionary frames. The dictionary frame in Listing (below) defines most of the nouns identified in the goal frames shown here. The nouns are defined in terms of their supertypes. The base vocabulary provides a foundation of supertypes that identify basic business process concepts including container, resource, material, part, account, person, customer, worker, employee, product, location, workspace, equipment, bill of materials, and measurement. The community will add to the base vocabulary over time. And thus, the thing we are programming will get smarter and smarter.
Dictionary: Baker's vocabulary. . A mixing bowl is a container. . A cake pan is a pan. . A pan is a container. . A pan is portable equipment. (multiple inheritance) . A recipe contains a bill of materials. . A cake is a product. . An oven is a kind of equipment. . A counter is a workspace. . A temperature is a measurement.
Supertypes and subtypes enable inheritance and polymorphism in statements of all sorts. Since a noun may also have more than one supertype, the language supports multiple inheritance. For example, a cake pan is a pan, and a pan is a container, and it is also portable equipment. Therefore, statements that apply to containers and statements that apply to portable equipment also apply to cake pans.
In addition, appropriate side effects may be invoked. For example, if an instruction uses a noun with "resource" as one of its supertypes, resource accounting may be automatically invoked as a side effect. If a container is moved, we know that the objects we had put into the container earlier are still in the container and that they have moved also.
Note that roles have no supertypes. Roles don't need supertypes because an actor may know multiple roles. For example, a robot baker may "understand" action statements for both the baker and "fetch and put" roles. Therefore, not only can the robot mix the batter and pour it into a cake pan, the same robot can also move the cake pan into the oven.
The goal frames in Listings (below) , (below) , and (below) mention two roles: the baker and the timer. In real mode, a role can be performed by a human or a robot. In simulation mode, both roles would be performed by a sim-bot. I have coined the term sim-bot to describe a software actor that simulates the actions of an actor in a simulator. A simulator is a software environment that may be used to debug a business process or to check a hypothesis about how a change in a business process will function. It has a simulated clock. Generally, you would run the simulated clock at a rate that allows an entire year of activity to be simulated in less than one hour.
When the time comes to run an action, the Resource Manager assigns an actor to fill the role specified for the action statement. You can think of the Resource Manager as an agency. Listing (below) shows an action frame that defines the capabilities of the baker role.
Role: Baker. Action: Bake the pan in the oven for the time given in the recipe. . Open the oven door. . Place the pan in the oven. . Close the oven door. . Oven: Bake for the time given. (We have a smart oven.) Action: Pour the batter from the mixing bowl into the cake pan. . Pick up a rubber spatula in one hand or gripper. . Pick up the mixing bowl with the other hand or gripper. . Use the spatula to push the batter out of the mixing bowl into the pan. . (A special-purpose machine might do this some other way.)
An action frame defines a procedure for each action that an actor may be asked to perform. The action statements define the actor's public interface. The instructions indicate the capabilities that the actor needs. When the action is requested, only the action statement is passed to the actor. The actor may actually perform the action using a procedure other than the one in the action frame. In that context, the procedure shown may be considered documentation or pseudo-code. However, we expect that future implementations of the actors as robots will translate the instructions into the robot's command language. Or the instructions could be native.
There is no reason why a command language for a robot or any system of moderate capacity could not be written in the language we introduce in this paper. A command language for a robot or any system of moderate capacity could be written in the language this paper introduces. (This paper does not show all of it, but it is Turing-complete.) The entire framework for the current implementation requires less than 40MB of storage for the ".image" and ".app" files. No attempt has been made to optimize the code's footprint. If it were translated to Erlang or C and run on a minimal operating system, it could be made very small indeed.
In the action frame in Listing (above) , the baker has delegated a step to the oven. An oven is another role with a repertoire of statements that it "understands."  How does that "understanding" come about? This gives us an opportunity to discuss how we might communicate with external systems as actors.
Suppose that the oven has a primitive command language that looks like this:
TURN ON (Turn the oven on.) TURN OFF (Turn the oven off.) TEMP 999 (Set the thermostat to the given temperature.) TIME 999 (Wait some minutes before executing the next step.)
To be useful, the oven also needs some communication channel. Let's assume that it will accept these instructions on an IP channel. We will build an "adapter" as shown in Listing (below) .
Role: Oven. Action: Turn on. . Send "TURN ON" with return. Action: Turn off. . Send "TURN OFF" with return. Action: Set temperature to T degrees Celsius. . Send "TEMP T" with return. . (By convention, a single capital letter indicates a variable.) Action: Bake for M minutes. . Send "TIME M" with return. To: Send string with return. ("String" is a primitive data type.) . IP: Connect to oven's network-address. . IP: Send string with end-of-line.
When a client requests a goal or action, the system generates a job ticket. The job ticket makes it easier to track the progress of the work and provides an electronic turn-around document that records the resources consumed and utilized. The job ticket goes to the Coordinator. The Coordinator is an actor that monitors the progress of a plan. A plan is a set of Goal frames. When the time comes to request an action, the Coordinator sends the job ticket to a resource manager along with the requested role and action. The resource manager allocates an actor that knows the role and sends the job ticket to that actor. If an actor delegates an instruction, it sends a (subordinate) job ticket to its resource manager along with the requested role and action. That resource manager may dispatch the work to another actor. If the same actor can perform that role, it may dispatch the action back to the actor that attempted to delegate the action. (We may simply build self-delegation into the Actor`s standard framework.)
When the assigned actor completes an action, the actor returns the job ticket with a record of the resources used, including its own time. The job ticket records resources until the goal or action request that started the whole sequence is finally fulfilled. Then the Coordinator sends the job ticket to the Bookkeeper. The Bookkeeper (another actor) records the job ticket and maintains useful sums (accounts). By default, the Bookkeeper maintains sums categorized by resource type, action statement, goal statement, client, role, and actor. A specific business may want to add a category to the breakdown.
The Bookkeeper is usable right out of the box. But while resources are summed, they are not priced. The enterprise can extend the basic implementation with appropriate pricing rules.
When an instruction mentions a resource we expect that the resource consumption or utilization will be tracked. In simulation mode, when the sim-bot recognizes an instruction that indicates that a resource is consumed or utilized, it will automatically record the resource used on the job ticket. In real mode, it is the real actor's responsibility to record resource usage on the job ticket.
The Simulator calculates cycle times from probability profiles provided by the Bookkeeper. The Bookkeeper derives the probability profiles from the data that it collects. When no history exists, the simulator may use cycle-time distributions provided in annotations that are appended to action statements or instructions.
The Simulator may be driven by customer demands recorded in the Messenger's logs. This enables a simulation of customer demand based on history. When no history exists or we wish to create a new demand pattern, the simulation may be driven from the user interface with conventional load-testing tools.
In many cases, business process automation involves robots talking to robots. In that context, there are no UI (user-interfaces), only API (application program interfaces). However, a complete language also needs notations for user interfaces. Two types of notations are necessary. One for dialogs and one for electronic forms.
You may have been wondering where the impulse to "bake the cake" came from. That brings us to the topic of user dialogs. In a future world, we can expect that the nature of the user interface will change. The user may speak to a robot or an avatar instead of typing instructions or pushing buttons. Therefore, we need a notation that is appropriately conversational. We've combined the notational conventions of a stage play with a chat-bot [_] notation for this purpose. In Listing (below) , the "U:" shorthand identifies the user's speech, and the "S:" shorthand identifies the system's speech. Several "U:" prior to an "S:" indicate alternative ways of saying the same thing.
Dialog: Cake Choice. Context: First Meeting. U: Hello *. S: Hello, I am the baker. [Gesture: Smile.] But I only know how to bake cakes. [Gesture: Apology.] May I bake a cake for you? I know four recipes. [Gesture: Expectation.] U: No *. S: OK. Good-bye. [Gesture: Sleep.] U: What kind of cake can you bake? U: What recipes do you know? U: Can you do a * cake? U: What * cake * ? U: Can * cake * ? S: I know how to bake a chocolate cake, white cake, carrot cake, or sponge cake. [Gesture: Expectation.] U: I would like * [cake-type] *. U: I want * [cake-type] *. S: OK. Your [cake-type] cake will be ready in about two hours. [Gesture: Happy.] We will deliver it to [user address street] when it is ready. . Goal: Bake a cake according to [cake-type] recipe. . Runner: Deliver cake to user's address. . (Lines that begin with a dot are actions, not conversation.)
A dialog like that shown in Listing (above) can be implemented by a Web page, an avatar in a virtual world (a projected image), a telephone voice-recognition program, or a robot mannequin behind an actual (real-life) store counter, or even by a real-life human being behind a real-life store counter. The main trick is to allow the user some freedom of expression. To enable that freedom of expression, the dialog notation adapts the technology and strategies of the AIML [_] (chat-bot) system.
Note the instruction in the dialog (Listing (above) ) where it says:
Runner: Deliver cake to user's address.
This assumes that we know our user.
I suggest that this will generally be the case
and that dialogs should be treated as long-running
with the state of the dialog preserved over time.
This would, among other things, create a friendly dialog.
In the dialog shown in Listing (below) ,
we assume that the system remembers prior conversations.
In essence, we pick up the conversation from where we left off.
Dialog: Baker's menu. Context: Returning customer. U: Hello. S: Hello again!  What can I do for you today?
Although the dialog notation is built around the technology of a chat-bot pattern language, it does not assume that the conversation is necessarily over the Internet. In fact, we try to avoid coupling the notation to any specific user-interface technology. That requires that we rethink the nature and role of user-interface sensors.
The keyboard is the oldest sensor. It is a surrogate for the user's voice. The mouse is newer. It acts as a surrogate for the user's hand. Still newer sensors include the joystick, the Wii wand, and touch screens. But these are still surrogates for the user's hand. There are even some experiments using video cameras and image processing that attempt to recognize the position and configuration of the hand itself!
Although current voice-to-text capabilities are crude and not overly reliable, we can expect this technology to gradually displace the keyboard. We can expect other technologies to gradually displace the mouse.
How do we make a notation relatively future-proof? For starters, we can avoid technology-specific gestures such as "mouseover," "click", "double click" and "command-V." These gestures can be translated into dialog input instead.
But what should we do about analog input? For example, what if a slider, joystick, or wand really is the simplest way for the user to communicate intent? We can still accommodate this by having the Scribe translate the input into a statement that is not coupled to the actual sensor.
How do we achieve technology independence? We have a role called "Scribe." An actor assigned to the role of Scribe mediates user-interface sensors. The Scribe translates the user's input into dialog input. The simplest way to avoid technology dependence is to simply not mention the technology in the dialog patterns. A slider move, joystick position, button push, voice input, wand position and orientation, accelerator sensor, or even a nerve signal can be translated into a speech act, and we can focus on the essence of the conversation rather than the distraction of the user interface.
To illustrate how this could be made to work, let's consider a context where analog sensors are common. Imagine a space-flight simulator. The simulator might be part of a game or it could be an elaborate training environment used to train an astronaut. The simulator might include a joystick that is used to direct pitch and roll movements. The dialog shown in Listing (below) could be used to respond to joystick input in a space-flight simulator. The Scribe will be sampling the joystick position continuously and translating the angular displacements into the intended rates. The dialog will be invoked whenever the position of the joystick changes significantly.
Dialog: space-flight Simulator. Context: Pitch and roll rate. U: Make the pitch and roll rates P and R degrees per second. S: (Don't talk. Just do it.) . Pitch-Thruster: Produce P degrees per second change in pitch. . Roll-Thruster: Produce R degrees per second roll rate.
We can expect that future systems will gradually reduce the need for the fill-in-the-blank user-interface style. But the paper form and its electronic equivalent may be with us for some time, and we need a compatible notation that represents these forms. The language includes a view-frame notation. The view-frame notation is basically a markup notation adapted primarily from the JSPwiki markup notation. Dialog frames may use a subset of the markup to indicate emphasis and format. Listing (below) shows an example of the markup in a view frame for our Bake-A-Cake enterprise. The idea here is something like an online form with radio buttons.
View: Cake Menu. !! Bake-A-Cake Menu ~ Please select the type of cake you want us to bake from the following choices. ~ (1) Chocolate Cake (2) White Cake (3) Carrot Cake (4) Sponge Cake Use icing to spell out: [cake message category]. [A] Deliver to my premise at: [user's address] . (1) ==> Goal: Bake a cake according to the chocolate-cake recipe. . (2) ==> Goal: Bake a cake according to the white-cake recipe. . (3) ==> Goal: Bake a cake according to the carrot-cake recipe. . (4) ==> Goal: Bake a cake according to the sponge-cake recipe. . [A] ==> Runner: Deliver the cake to [user's address]. . (The cake message category includes "nothing.")
If the view in Listing (above) is rendered as HTML, the user will see a second-level heading with the words "Bake-A-Cake Menu," followed by the advice "Please select the type of cake..." in italics and a set of four radio buttons with labels. Below the radio buttons, the user will see a checkbox and an address provided in a previous conversation. The two exclamation points in front of the first line indicate a second-level heading. A tilde (wavy dash) on each side of the advice signals italic font. Parentheses enclosing a single character indicate a radio button. The pattern "(1) Chocolate Cake" indicates radio-button number one with the label "Chocolate Cake." The lines that begin with dots (periods) indicate instructions to the system. In this case, the instructions map each radio button to a different goal statement. Square brackets enclosing a single character indicate a checkbox. Square brackets enclosing the identifier for an attribute indicate that the value of the attribute will be substituted when the frame is rendered. If the attribute names a category, a select widget (example: a pull-down list) will be rendered instead of a text-box widget. If the attribute names an entity, the attributes of the entity will be listed as pairs of labels and text boxes inside a group box.
I have to admit that the view markup, in its own way, is just as esoteric as HTML. I would argue that it is less intrusive and closer to achieving WYSIWYG (What You See Is What You Get) than HTML or LaTex. I wanted a markup notation that is concise, almost predictable, and with a minimal effect on the text shown the user. But natural language and markup are contradictory terms.
We need a design that enables our systemÕs short-term and long-term memory to operate automatically with minimal programmer direction and without intruding itself into descriptions of the business process. We want program statements to be about business processing, not data processing.
Each work-in-progress session has a whiteboard where it keeps a dictionary of noun-value pairs to track the values that have been assigned to the nouns in the statements that are to be executed during the session. A session may be a goal session, an action session, or a dialog session. The system maintains the whiteboard for the duration of the session. The whiteboard provides a kind of short-term memory.
Note that short-term versus long-term is relative. Sessions may be long-running. A work order can be in progress for weeks or even months at a time. Also, a dialog session may last a very long time if we want the application's Speaker to provide a sense of continuity.
A world-base, a kind of temporal database [_][_], provides the system's long-term memory. In business programming, a world-base will generally belong to a corporation. In that sense, it represents a corporate memory. However, it may belong to any kind of community, or it may belong to a simulated world. When we run a simulation, a world-base records events that occur in the simulated world. Obviously, we want to keep the real-world data separate from the simulated-world's data. We might copy some part of the real-world data into the simulated world and then set the simulation running with the start of the simulation set to an appropriate date and time.
When all actions in a goal frame run to completion, the post-condition in the goal frame has, by definition, come true. This is a business event worth recording. We populate the post-condition statement with noun-values and send it to the world-base "for the record."
An entity is a uniquely identifiable thing in the world.
When we instantiate an entity or provide a value for any of its attributes,
the whiteboard will detect the change
and send a message about it to the world-base.
The message records the change and the context of the change.
The logical data structure looks like this 4-tuple:
Our strategy for the persistence layer is simple. We record everything as it occurs and decide what to purge later. This strategy allows us to almost completely remove the usual database tasks from the business programmer's workload. The question changes from "What should we record?" to "What should we purge?"
Corporations and government agencies have record-retention policies. These policies will define which items recorded in the world-base should be purged and when. Because the world-base is a temporal database, it will be a relatively simple thing it will be a relatively straight-forward matter to purge business event records and outdated attribute values based on their type and age.
This set of coordinated notations constitutes a programming language. The business vocabulary built into the language makes the language rich. The run-time system is designed to properly reflect the fact that a business process is carried out by communities of actors. collaborating to meet mutual goals.
I am also considering the Erlang [_] architecture for the distributed run-time system because it solves a number of problems right out of the box. However, adding another language is likely to create a large number of problems. Indeed, it may create more problems than it solves.
Although the frame notations were designed for business programming, they can be adapted to multiplayer games. My rationale is that business life is a kind of multiplayer game. The goals, scoring, and moves in business are, of course, different and require much longer attention spans. One of the technological differences is that a modern multiplayer game requires a landscape (a scene graph [_]) and the means to render it at run-time in real time.
The "Persist Everything" strategy replaces the question of "What should we record? and when?" with "What should we purge? and when?" In a business context, organizations have record-retention policies. Record-retention policies might be expressed using a notation in a configuration file on the world-base. I cannot say that I have given this record-retention notation a lot of thought. In my experience, most organizations use relatively simple policies that they apply to very general categories of data. For example, financial journals may be retained for seven years. Asset data may be retained for the life of the asset.
Recall that the Speaker is the "voice" of the system and the Scribe is the "voice" of the user. The current implementation simply displays prompts on the screen and takes input from the keyboard. The Speaker and Scribe (user-interface actors) will eventually use text-to-voice and voice-to-text technologies. The expected user patterns that are documented in dialog frames might be used by a voice-to-text technology to disambiguate voice input.
Our notations allow most statements to be written in a natural language. That means that one could, in theory, dictate the program to a kind of robot stenographer.
All these technological opportunities are potentially moot because a language without an active community is irrelevant. We need social technology in addition to our software technology. To make the thing we are programming more intelligent, we need simple and effective means for the community to add intelligence to a community knowledge-base. That means that we need social systems, not just software systems[_].
Consider the question of source code control. What is the appropriate unit for check-out and check-in? The most obvious choice would be the role-action frame (or frame set). A less obvious choice would be a subtree of the Goal frames.
We also need some strategy for merging dictionary frames. The community needs something like the expertise that the Cyc project deploys when merging ontologies[_]. While Cyc and OpenCyc provide something resembling a comprehensive thesaurus, our business systems need operational definitions. Anyone who has served on a standards committee will testify that definitions, even operational definitions, are surprisingly hard to coordinate.
While a source repository, wiki, and blog may be essential facilities, the governance framework is actually more important. Linux, Python, GNU, Apache, Mozilla, Cyc, and Java are all successful community projects. Each one has a slightly different charter and governance structure. Which model would be the best? I leave that as an open question.
This paper would not be the same without the advice and help of my sister and editor Jeanette Green. She has done what she could to teach me to write in a less clunky style.
Smalltalk [_] architecture strongly influenced the overall concept of the system. The "Design Principles Behind Smalltalk" [_] article by Dan Ingalls showed me that the persistence problem was an artifact of the unit-record paradigm. I have been studying and experimenting with automated persistence ever since.
Ideas behind the Goal frames come from state-transition diagram techniques and an analysis technique called "disassembly." The goal-frame implementation owes a little something to Prolog [_] although there is no "cut," and the back-chaining idea is probably ancient.
James Martin's Action Diagram [_] notation probably had the largest influence on the notation used in action frames. Of course, COBOL was the first mainstream language with statements that resemble written English. Once upon a time, I used a preprocessor called Flex (very similar to RatFor [_] ) that had a similar syntax for defining procedures and sub-procedures.
After studying several parsers and implementing one based on BNF [_] notation, I decided that this kind of thing was potentially counterproductive, because natural language does not work that way. But the frame notation does include domain-specific language here and there, and some type of pattern recognition is needed to make that work. So far, I have made do with hand-coded parsers.
The whiteboard concept used for short-term memory is similar to the blackboard employed in the OPS5 [_] expert system, except there are no data triggers running frames. The whiteboard's persistence mechanism runs from a data trigger. But persistence is meant to be hidden from the program and programmer. I updated the term blackboard to whiteboard recently when I realized that we rarely see blackboards and chalk today.
The Cougaar Project [_] influenced some bits of my actor-oriented architecture. Marvin Minsky proposed the basic concepts in his book Society of Mind [_].
James Martin's Action Diagram notation [_] also influenced my ideas about how procedural statements should interact with data definitions. I am often tempted to build a code generator similar to those that translated Action language to COBOL and C. But there is good reason to believe that the presence of a code generator would actually be counterproductive. My experience with code generators leads me to say that you're too likely to end up with "the tail wagging the dog" when you go that route.
Dictionary frames have their roots in entity relationship analysis [_] and object-oriented analysis. Nouns are mapped to entities and attributes. Nouns may also be defined in terms of their supertypes. Object-Oriented Systems Analysis: Modeling the World in Data [_] by Sally Shlaer and Stephen Mellor provides an excellent tutorial and method. Also, their book Object Lifecycles: Modeling the World in States [_] is the probable source of my ideas about when to record business events in the world-base.
I have only recently read Programming Erlang: Software for a Concurrent World [_] by Joe Armstrong. My design for the run-time system was already well-established before I learned Erlang. But I think that evolution of the run-time system will be strongly influenced by the Erlang architecture. The Mnesia [_] database system contains many valuable ideas for implementing the world-base and whiteboard systems.
The dialog-frame notation is adapted from the AIML notation. I have hopes of integrating the OpenCyc [_] technology so that the Speaker, implemented as a chat-bot, might be more versatile.
I examined a number of wiki notations, hoping to find an emerging standard that would be compatible. But the view-frame markup borrows from several wiki markup notations and adds a set of additional ideas so that all the usual widgets in HTML and other electronic-form interfaces would be accommodated. I think that the JSPWiki [_] markup notation had the largest influence on my choice of markup styles.
Data frames support data hierarchy and are partially self-descriptive. While this structure is similar to XML, those ideas preceded XML by decades. Those concepts occur repeatedly in the early literature on electronic bibliographies. Using indentation to indicate hierarchy comes from the outline style one learns in basic writing courses.
The run-time system is designed to properly reflect the fact that a business process is carried out by communities of actors collaborating to meet mutual goals. SOA (service-oriented architecture) has the same intent. But most of the existing approaches to SOA show a paradigm lag because they continue to express the actor interfaces as hand-built data-processing channels.
None of the ideas in the frame notations are original or unique. The invention consists of a synthesis of these ideas into a set of coordinated notations. This set of coordinated notations constitutes a programming language. The business vocabulary built into the language makes the language rich.
I have not attempted to explain all of the language and framework features in this article. That would require a short book. The short book is, of course, online. See [_].
This appendix will not appear in the ESUG paper. It is mainly a vehicle for thinking out loud.


Computer Science Program Description
Program Description
Do you want to know how to design and program the computers powering some of today’s greatest innovations? Ever wondered how your phone knows where the nearest Starbucks is, how Google’s self-driving car is even possible, or how your music and photos live in the cloud? Maybe you want to know how computers protect businesses — and people — and other cybersecurity issues. AUM’s Computer Science Program, with a curriculum based on the latest ACM/IEEE recommendations and an emphasis on high-performance computing, will prepare you for a career in computer programming, networking, database management, multimedia design or technology architecture.
Points of Pride
You’ll have access to the most powerful computational resources and expertise in the country through our partnership with the NSF-supported Extreme Science and Engineering Discovery Environment.
Computer Science faculty are engaged in the private sector, supporting research and part- nerships with national and international user groups and initiatives.
U. S. Bureau of Labor Statistics sample data
Job Median Pay Job Growth through 2024
Computer and Information Research Scientist $108,360 per year 11% (2700 more jobs)
Computer Network Architects $98,430 per year 9% (12,700 more jobs)Computer Analyst $82,710 per year 21% (118,600 more jobs)
Table 1: Caption
Put Your Degree to Work
Note: While salaries vary depending on several factors including your level of experience, edu- cation and training, and geography and industry, here is a sampling of the future job growth and salaries in this area.
Employment of computer and information technology occupations is projected to grow 12 percent from 2014 to 2024, faster than the average for all other occupations. The most recent median annual wage for computer and information technology occupations $79,390 — higher than the median annual wage for all other occupations.
For More Information
Contact Lei (Lee) Wu.
Department of Computer Science & Computer Information Systems (CSCI) College of Science (CoS), Auburn University at Montgomery (AUM)
Office: Goodwyn Hall 310-Q E-Mail<EMAIL_ADDRESS>HOGWARTS
New York City, USA


Caption 1
Caption 2
Caption 3
Caption 4
Caption 5
Caption 6
Hello, World!
This
HTML
page has been written for
XML parsing tests
by
Lukas Hermanns
.


SUGAR
Welcome to the documentation for SUGAR also known as the RAGE Social Gamification Asset.
SUGAR provides a software platform consisting of Web API and Client side components that enable game developers to integrate group based gamification into their applications. It supports features such as clans, group resources and goals and tournaments.
The documentation includes :
Installation : Simple guide to getting the SUGAR server running with docker.
Features : Detailed description of features supported by the software including the roadmap for up-and-coming features.
Core Concepts : Description of core concepts behind features within SUGAR.
Admin Interface : Description of the platform’s admin panel.
Client API Reference : Client API documentation and examples.
RESTful API : Web API documentation and examples.
The link to the repositories can be found below :
Repositories:
SUGAR is partially funded by the RAGE project.
Realising an Applied Gaming Eco-system (RAGE) aims to develop, transform and enrich advanced technologies from the leisure games industry into self-contained gaming assets that support game studios at developing applied games easier, faster and more cost-effectively.


Code Release 1 consists of code for estimating the two-state recall-only model in our Knowledge Tracing Using the Brain paper that we presented at Educational Data Mining 2018.
The Stan code for the model can be found in the models
folder. The only difference between the two files there is that one is setup to make use of Stan's new multithreading capacity.
The main files needed to run the code can be found in the shell_scripts
folder. This contains three shell scripts for running the Stan models in batch mode on a slurm HPC cluster. run_two_state_logit_model_fmri_subs_kfcv.s
divides the data from subjects who were in the fMRI into ten folds as described in the paper and estimates the models holding one fold out. run_two_state_logit_model_loocv.s
estimates the models by holding one fMRI subject's data out. run_two_state_logit_parallel_model_loocv.s
does the same thing but making use of parallelization. You can estimate all the models in parallel on your own cluster by calling sbatch --array=0-n run_two_state_logit_model_loocv.s
. n
should be the number of folds, i.e. 10 in the kfold case.


Design and implementation of the affective loop in a 2D game in Unity engine. TEXT - please contact me to get password.
Sudoku solver with OCR and HTTP connection - project was taking a picture, parsing it into binary code, solving, saving to DB (LiteDB) and returning the solved response.


Typography
Headings
H1 Heading
H2 Heading
H3 Heading
H4 Heading
H5 Heading
H6 Heading
Paragraphs
Large Paragraph: But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system
Regular Paragraph: But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system
Small Paragraph: But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system
Extra Small Paragraph: But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system
Lists
- Far far away, behind the word mountains
- Hen she reached the first hills
- Vestibulum nisi nibh, pulvinar sit amet lacinia
- Mauris pretium elit ac facilisis mollis posuere
- Mauris vitae magna in dolor porta aliquam
- Far far away, behind the word mountains
- Morbi quis neque non nisl egestas laoreet
- Vestibulum nisi nibh, pulvinar sit amet
- Mauris pretium elit ac facilisis mollis
- Mauris vitae magna in dolor porta aliquam
Text Colors
Default. Aliquam molestie quam in tincidunt accumsan
Primary. Morbi quis neque non nisl egestas laoreet
Success. Vestibulum nisi nibh, pulvinar sit amet lacinia
Info. Mauris pretium elit ac facilisis mollis posuere
Warning. Mauris vitae magna in dolor porta aliquam
Danger. Mauris vitae magna in dolor porta aliquam
Text Backgrounds
Hello nisl vitae ligula volutpat, sit amet rhoncus nisl posuere. Vestibulum vel nisi euismod, Mountains fringilla ex. Fusce vel mattis quam, id bibendum leo. Vivamus sollicitudin ligula ut ante bibendum, et Cool. Interdum et malesuada Kit ipsum primis in faucibus. Praesent laoreet ultrices tortor Chill Vestibulum quis egestas mauris. Class aptent taciti sociosqu ad litora torquent per conubia nostra, No himenaeos.
Simple Title
Simple Sub-title
Blockquotes
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia. Far far away, behind the word mountains, far from the countries Vokalia and Consonantia
- Michaeal Sam
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia. Far far away, behind the word mountains, far from the countries Vokalia and Consonantia
- John Doe


Gabriel-Codrin Cojocaru
Light blue, curly hair is pulled back to reveal a long, sad face. Shuttered sapphire eyes, set appealingly within their sockets, watch thoughtfully over the river they've shown mercy on for so long. Fair skin gracefully compliments his nose and leaves an intriguing memory of his past. This is the face of Almer Dawnwhisper, a true opportunist among high elves. He stands towering above others, despite his tough frame. There's something alluring about him, perhaps it's his odd friends or perhaps it's simply his good will. But nonetheless, people tend to try to get him to marry their off-spring, while trying to please him.


{% extends "layout.html" %} {% block title %} Results: {{sim_sys}} {% endblock %} {% block main %}
Canonial CoordinatesDownload |
Phase SpaceDownload |
Phase SpaceDownload |
|
Phase Space ProjectionsDownload |


{% if user.is_authenticated %}
{% if request.user.profile.regex_search %} You are using regular expression based search feature. If you like to change to a basic version (like search), please change it in your User Profile. {% else %} You are using the like based search feature. If you like to change to a more advanced version (regular expressions), please change it in your User Profile. {% endif %}
{% endif %}


A concrete example
A farmer named Dave sells his vegetables to a food hub named "Earth Friends" which has a web platform (website), on which Dave manages his products catalog.
Now imagine that another buying group, "Eastern Farmers" also wants to distribute Dave’s products on its own web platform.
How does Eastern Farmers access Dave’s catalog? Today, the solutions are far from ideal:
1 - Dave must enter the same data on each platform, therefore loosing time and having to manage stocks and orders on different platforms.
2 - Eastern Farmers can source Earth Friend’s data and access Dave’s catalog. There are then problems of stock synchronicity (problems of errors due to delays in stock updates), data reliability and security.
The solution: interoperability. What is it ? It’s pretty awesome. To avoid complicating operations when the same product is distributed on several platforms, they must communicate effectively.
We are not talking about synchronization or data exchange, simply cross-display of data that can be hosted on any database. The data is not replicated, just displayed, from the information directly drawn from the source database.


The support is now determined by the truncation interval
λ> (support-lower (truncated (gamma 1 2) 4 5))
4
λ> (support-upper (truncated (gamma 1 2) 4 5))
5


Two US soldiers killed in chopper crash in Afghanistan
The Taliban militant group claimed that the insurgents' fighters shot down a Chinook helicopter in eastern Logar province
by IANSTwo US soldiers were killed in a helicopter crash in Afghanistan's eastern Logar province on Wednesday, the NATO-led Resolute Support said. "The cause of the crash is under investigation, however preliminary reports do not indicate it was caused by enemy fire," the coalition said in a statement.
The statement did not disclose information about the deceased, Xinhua reported. "In accordance with the US Department of Defense policy, the names of the service members killed in action are being withheld until 24 hours after notification of next of kin is complete," the coalition stated.
Meanwhile, the Taliban militant group claimed that the insurgents' fighters shot down a Chinook helicopter in eastern Logar province. Taliban spokesman Zabiullah Mujahid wrote on Twitter that the US chopper tried to raid militants' position in Pangram area of Charkh district of Logar.
In October 2017, one US service member was killed and six US soldiers were injured after the coalition's helicopter crashed in Logar.
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And find the perfect partner to fullfill it
Find your holiday partnerBradley Hunter
Based in Chicago. I love playing tennis and loud music.
Lucas Marsha
I get my inspiration from nature and objects around me. I have a passion to colours, typography and skateboards.
Heather Walker
I'm a happy person that loves cats and climbing on mountains.
Bradley Hunter
Based in Chicago. I love playing tennis and loud music.


[§342D-58] Consultation and advice. The director may consult with and advise:
(1) Any person engaged or intending to be engaged in any business or undertaking whose waste, sewage, or drainage is polluting or may tend to pollute state waters; and
(2) Persons intending to alter or to extend any system of drainage, sewage, or water supply. [L 1989, c 212, pt of §2]


EU needs radical rethink to enable large fiscal stimulus – ANZ
by Anil PanchalAnalysts at the Australia and New Zealand Banking Group (ANZ) are of the opinion that the European Union (EU) requires a drastic thought process to take benefits of the fiscal stimulus.
Key quotes
“As the European Central Bank (ECB) stretches the limits of monetary easing, attention is turning to fiscal policy. The euro area (EA) has potential fiscal space of 2.0% of GDP.”
“Potential fiscal space is calculated using a narrow criteria, based purely on the EA budget deficit. It is unlikely to materialise as rules based fiscal policy limits the growth of the public spending path.”
“Hope of a large-scale fiscal boot for the EA will probably be disappointed. We estimate that an expansion closer to 0.25-0.5% of GDP in 2020 is more likely.”
“An overhaul of the current rules and a more medium-term focus on policy settings is required.”
“That will leave an over-onus on the ECB to support reflation. The monetary policy framework needs reviewing, especially in light of the considerable divisions that emerged over the latest easing.”


This component is a Custom Element written in pure vanilla JavaScript. It's designed to toggle the password visibility in an easy way.
<div class="flex items-center border-b border-b-2 border border-gray-300 rounded-lg px-4 max-w-xs">
<input type="password" is="password-toggle" class="w-full outline-none pr-4 py-2" placeholder="Enter your password" autocomplete="new-password" />
</div>
This package is written with the new ES6 syntax. You can import it directly in your browser with UNPKG .
<script type="module" defer src="https://unpkg.com/custom-element-password-toggle"></script>
You can also install it with npm or yarn:
$ yarn add custom-element-password-toggle
<script type="module" defer>
import 'custom-element-password-toggle'
</script>
Then use it on your input fields:
<input type="password" is="password-toggle" />


Elizabeth McCain
Unafffiliated
I am a stay at home. Prior to my decision in 2015 to stay home, I was an Executive Territory Manager for Bausch + Lomb (now Bausch Health) for 5 years. I worked for Abbott Laboratories as a sales consultant from 2008-2010
I attended the University of Colorado at Boulder, Leeds School of business with a major in Finance from 1999-2003.
80123
I have made 3 donations to WINRED since 2015.
Member of Wash Park East neighborhood association board Advisor for a student organization at University of Denver since 2014 Vice President of St. Philips Early Learning Center school board (on the board since 2018) Volunteer legislative Liaison for Convention of States in 2016 Advisory council (since 2012) and now the Board of Directors for Leadership Program of the Rockies.
As a school board member I have to work to represent both the parents as well as the preschool's best interests. I have been on the board while we are navigating COVID, as well as hiring a new director for the school. As a volunteer with Convention of states I was working to help gain support for the Convention of States resolution to help advocate for term limits because I believe the are effective for our state legislature so why not for DC officials, as well as for balancing the federal budget. As an advisor at DU, I have to weigh the behaviors/challenges of the students I serve as well as be a voice for them with the University's administration.
I would like to be someone who represents the growing population of unaffiliated voters in this state. I don't have a dog in the R vs. D fight but rather what so many who feel underrepresented in how our boundary lines are drawn. I'm tired of gerrymandering.
As someone who has worked within the professional world with much success (winning 2 top of company awards) I was able to communicate successfully with a wide spectrum of personalities of doctors and non-medical colleagues. As someone who has been selected to represent communities (preschool, DU students, Leadership Program of the Rockies) it shows me that people respect my perspectives as well as trust me to guide and make decisions that best fit the different organizations and find consensus amongst leadership groups.
As a medical sales professional, I managed territories that were as large as 6 states, and as small as the south Denver Metro area. I was responsible for analyzing data for 200+ clients and devised plans for successfully achieving and in most cases exceeding quota's for the organization I represented.
female


index
module components.merging.wrapper
MergerWrapper
Python wrapper around the merging code.
Calls SputLink's ConstraintPropagator to do all the work. For now does not do
any graph reduction at the end.
TODO:
- Decide what we want to take from the output. We now take all non-disjunctive
links. We could add the disjunctive links as well. Or we could not take
inverse relations. Or we could reduce the graph to a minimal graph.
- We now put all links on the queue and order them in a rather simplistic way,
where we have S2T < Blinker < Classifier, and classifier are ordered use the
classifier-assigned confidence scores. For the merging routine to be better we
should let the ranking be informed by hard evaluation data.
class MergerWrapper
Inherits from: object
Wraps the merging code, including Sputlink's temporal closure code.
Public Functions
__init__(self, document)
process(self)
Run the contraint propagator on all TLINKS in the TarsqiDocument and
add resulting links to the TarsqiDocument.
Private Functions
_add_constraint_to_tarsqidoc(self, edge)
Add the constraint as a TLINK to the TarsqiDocument.
_update_tarsqidoc(self, cp)
Remove existing TLINKs from the TarsqiDocument and add new ones given
the final constraints in the graph used by the constraint propagator.
module functions
sort_on_confidence(link)
Sort key for determining how good we think a link is. Rather primitive for
now. We consider S2T links the best, then links derived by Blinker, then
links derived by the classifier. Classifier links themselves are ordered
using their classifier-assigned confidence scores.
tlink_arg1_attr(identifier)
Return the TLINK attribute for the element linked given the identifier.
tlink_arg2_attr(identifier)
Return the TLINK attribute for the element linked given the identifier.


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