vignettes/EndoMineRPrinciples.Rmd
EndoMineRPrinciples.Rmd
The electronic recording of endoscopy data is now the norm. This gives us the opportunity to answer many practical day to day gastroenterology questions and opens the door to automated and reproducible audit and governance analyses using scripted analyses. Electronic endoscopic data can be organised in a manner that allows several questions to be answered with the same data structure across patient episodes. The structure itself is straightforward. It simply rests on the basis that we mainly describe patient episodes so that each row of a dataframe pertains to the data collected at that episode and the index of the row is based on a combination of date and a patient’s unique identifier. The following describes an overview of how data should be structured using both and endoscopic dataset and a pathological dataset which we will then merge.
There are some basic assumptions we make about an endoscopic dataset so that processing can be straightforward. These assumptions are so generic and self-evident that they are likely to be true for all endoscopy datasets as well as many medical datasets in general.
A fundamental assumption is that all patient related data at the departmental level can be viewed as pertaining to a clinical episode recorded as a single timepoint (usually as the day of the episode). A single patient is related to patient timed episodes in a one to many relationship (one patient can have many endoscopies). In fact most medical data is recorded in real time in patient notes so that this patient-time centric data organisation is simply part of a normal intuitive medical workflow.
All patients have a unique identifier. At the departmental level this is likely to be a Trust specific hospital number.
A patient episode should have an outcome. In the case of an endoscopy for example, the outcome may be the histopathological diagnosis, or if no biopsies were taken, then the endoscopic diagnosis. The origin of the outcome is not important: it can be a derivative of the dataset itself or can be from a distinct dataset merged into the current one depending on the analysis. What is important is that the outcome relates to the patient episode: if the biopsy result is the outcome it should be biopsies taken at the recorded endoscopy. In other words the outcome should be that which is related to the same timepoint as the event. To reiterate: the outcome can be derived from the dataset and so does not need to be present at the outset, but many analyses rely on some form of measurable outcome.
A patient episode should have a reason. The indication for the patient episode should be recorded for the same time point as the episode. This is very commonly found in the report text of both an endoscopy and histopathology reports. This is optional as other analyses can still be carried out without this being available.
The data is semi-structured. Structured data is easier to analyse but because it is more cumbersome to input and often lacks flexibility, most endoscopic and histopathology data remains semi-structured. This means that although the text extraction techniques outlined here are the same, the boundaries for extracting each section may differ. For example in our trust a pathology report may contain the subsections ‘Macroscopic specimen’ and ‘Diagnosis’ whereas these sections may have alternative labels in another hospital’s report.
Semi-structured data requires specific language processing techniques depending on what is being extracted. For our purposes the extractable data is likely to be either diagnoses or aspects of the test being performed. The diagnostic data is traditionally the most difficult to extract but this is often because the object to be extracted is from a large set eg. for the purposes of coding for financial remuneration. Because the target set is much smaller for endoscopic-pathological diagnoses, language extraction can be more focused whilst being more flexible to accommodate edge cases such as misspellings and plurals.
A huge part of endoscopy is tissue acquisition for further histopathological assessment. Because histopathology is kept in a separate dataset (and usually in a separate database altogether), merging endoscopic and pathology datasets becomes an important process. Pathology episodes are often recorded at a date the specimen was received in the lab which can be different to the date the patient was endoscoped. Understanding this is crucial to making sure the patient pathology and endoscopy episode is related.
Generic questions in gastroenterology are really applicable to most areas in medicine. Many fields share the same practical, day to day questions. The main questions are:
Surveillance programmes are ubiquitous in medicine and an essential part of preventive medicine.
The problem of surveillance from a data science point of view is that the timing of a subsequent investigation can be dependent on a previous investigation result. Sometimes the surveillance timing depends on other factors such as family history or date since the original diagnosis.
Regardless of the dependencies of surveillance timings, essentially surveillance relies on knowing the timing of a test and the test result along with other factors mentioned above
So essentially the problem is
** (Date of test)+(Test Result)+(Other external data)**
This then starts as a data merging problem. We can look at a fairly simple surveillance programme, namely Barrett’s surveillance. This is simple because the rules for the next endoscopy depend on the histopathological results of the previous endoscopy (the presence or absence of intestinal metaplasia) as well as the length of the Barrett’s segment, which should be recorded in the endoscopy report.
The second issue we must understand is that the date of the test combined unique patient ID is a combined index and that our data structure needs to be grouped by patientID and then arranged according to date before further processing is done.
So we need to merge the endoscopy and pathology reports for each patient and then we need to extract information from text.
The figure below demonstrates the general approach once the data has been merged. The patient episodes are organised by patientID and then secondarily arranged by date:
Therefore, once the data has been properly arranged we can then make an attempt at deciding when the patient should return for a subsequent investigation. This is the basis of the figure above where the Rule column is derived from other columns such as the endoscopy report and detection of dysplasia among other factors. It is only a small step from there to deciding who has missed surveillance, who is due, the number of patients going through the programme, forecasting capacity and a huge number of other tasks related to robust surveillance.
We can in fact use the same structure of dataset to also analyse diagnostic yields meaning histopathology diagnoses from endoscopic samples). Again, the pathology and endoscopy datasets need to have been merged by patient ID and date.
Adenoma detection rates are a good example of this. This is a measure of how many endoscopies have resulted in the detection of at least one colonic polyp which is classifiable as an adenoma. This is often used as a measure of how robust an endoscopit is when performing colonoscopy. The steps needed to calculate endoscopist-level adenoma detections rates are:
1. Detect rows that mention polyps and in the endoscopy report, filtered by colonoscopy
2. Also detect rows that mention dysplasia in the pathology report.
3. Group by endoscopist.
4. Then get the total number of reports that mention polyps in the endoscopy report whether dyplasia is metioned or not, and group by endoscopist.
5. Calculate proportion by endoscopist then visualise it.
Using a similar dataset to that of surveillance, it is a fairly straightforward task:
This section relates to the anaylsis of quality within datasets. THis is similar to many of the fields required in the global rating scale for endoscopy. The section above on yield can also be seen as a ‘between’ dataset quality measure as in the adenoma detection rate, as oppose to the ‘within’ dataset quality discussed here.
Endoscopic quality relates to many things such as the amount of sedation given, the quality of the documentation amongst others. Pathology quality relates often to whether certain aspects are mentoned in the report such as depth of invasion of a cancer, or a particular scoring system.
Each of these is discussed in more detail in the documentation but at a generic level,the dataset we have already described is sufficient to allow the extraction of such detail as it comes directly from the fields already present, often without needing to cross reference with other fields.
Gastroenterology departments are often concerned with population level problems such as patient flow: How many patients will need colonoscopy this year? What proportion of patients need several investigations for a specific symptom and can this be made more efficient? etc.
If we understand the fact that patient’s flow through a system, and the way to characterise that flow is by organising data according to the patient’s unique identifier and episode date as a combined index, then there are a huge number of questions that can be answered under this generic question. Such questions rely on the same organisation of data as the first figure, namely data organised by patient and date and sorted by date. Again this is discussed further in the relevant documents:
To summarise, the data structure needed to answer most gastroenterology questions is as follows:
The central datastructure is the same for all the 4 generic practical questions we ask in gastroenterology, it is only the comparisons that differ. This central datastructure therefore allows data preparation to be much more straightforward for the end user.


This new book demystifies the complexities of resource capacity and demand management and offers clear ways for maximizing your limited resources to drive business growth and sustainability. This groundbreaking guide includes:
- Tools for overcoming common barriers and making decisions involving time capture, resource assignments, and competing priorities
- Recommendations on ownership of the organization’s resource management and capacity planning functions
- Considerations for addressing the human side of resource management and capacity planning
- Case studies from organizations that have used the book’s methods to achieve great success
Use this handbook as a reference for the information, insight, and proven methods to take your company to the next level.


on master
branch
Branches are pointers to commits.


Elon Musk
Who Is Elon Musk?
Elon Musk is a South African-born American entrepreneur and businessman who founded X.com in 1999 (which later became PayPal), SpaceX in 2002 and Tesla Motors in 2003. Musk became a multimillionaire in his late 20s when he sold his start-up company, Zip2,
to a division of Compaq Computers.
Musk made headlines in May 2012, when SpaceX launched a rocket that would send the first commercial vehicle to the International Space Station. He bolstered his portfolio with the
purchase of SolarCity in 2016 and cemented his standing as a leader of industry by taking on an advisory role in the early days of President Donald Trump's administration.
In January 2021, Musk reportedly surpassed Jeff Bezos as the
wealthiest man in the world.
Early Life
Musk was born on June 28, 1971, in Pretoria, South Africa. As a child, Musk was so lost in his daydreams about inventions that his parents and doctors ordered a test to check his hearing.
At about the time of his parents’ divorce, when he was 10, Musk developed an interest in computers. He taught himself how to program, and when he was 12 he sold his first software: a game he created called Blastar.
In grade school, Musk was short, introverted and bookish. He was bullied until he was 15 and went through a growth spurt and learned how to defend himself with karate and wrestling.
Family
Musk’s mother, Maye Musk, is a Canadian model and the oldest woman to star in a Covergirl campaign. When Musk was growing up, she worked five jobs at one point to support her family.
Musk’s father, Errol Musk, is a wealthy South African engineer.
Musk spent his early childhood with his brother Kimbal and sister Tosca in South Africa. His parents divorced when he was 10.
Education
At age 17, in 1989, Musk moved to Canada to attend Queen’s University and avoid mandatory service in the South African military. Musk obtained his Canadian citizenship that year, in part because he felt it would be easier to obtain American citizenship
via that path.
In 1992, Musk left Canada to study business and physics at the University of Pennsylvania. He graduated with an undergraduate degree in economics and stayed for a second bachelor’s degree in physics.
After leaving Penn, Musk headed to Stanford University in California to pursue a PhD in energy physics. However, his move was timed perfectly with the Internet boom, and he dropped out of Stanford after just two days to become a part
of it, launching his first company, Zip2 Corporation in 1995. Musk became a U.S. citizen in 2002.
Companies
Zip2 Corporation
Musk launched his first company, Zip2 Corporation, in 1995 with his brother, Kimbal Musk. An online city guide, Zip2 was soon providing content for the new websites of both The New York Times and the Chicago Tribune. In 1999, a division of Compaq Computer Corporation bought Zip2 for $307 million in cash and $34 million in stock options.
PayPal
In 1999, Elon and Kimbal Musk used the money from their sale of Zip2 to found X.com, an online financial services/payments company. An X.com acquisition the following year led to the creation of PayPal as it is known today.
In October 2002, Musk earned his first billion when PayPal was acquired by eBay for $1.5 billion in stock. Before the sale, Musk owned 11 percent of PayPal stock.
SpaceX
Musk founded his third company, Space Exploration Technologies Corporation, or SpaceX, in 2002 with the intention of building spacecraft for commercial space travel. By 2008, SpaceX was well established, and NASA awarded the company the contract to handle cargo transport for the International Space Station—with plans for astronaut transport in the future—in a move to replace NASA’s own space shuttle missions.
Tesla Motors
Musk is the co-founder, CEO and product architect at Tesla Motors, a company formed in 2003 that is dedicated to producing affordable, mass-market electric cars as well as battery products and solar roofs. Musk oversees all product development, engineering and design of the company's products.
SolarCity
In August 2016, in Musk’s continuing effort to promote and advance sustainable energy and products for a wider consumer base, a $2.6 billion dollar deal was solidified to combine his electric car and solar energy companies. His Tesla Motors
Inc. announced an all-stock deal purchase of SolarCity Corp., a company Musk had helped his cousins start in 2006. He is a majority shareholder in each entity.
“Solar and storage are at their best when they're combined. As one company, Tesla (storage) and SolarCity (solar) can create fully integrated residential, commercial and grid-scale products that improve the way that energy is generated,
stored and consumed,” read a statement on Tesla’s website about the deal.
The Boring Company
In January 2017, Musk launched The Boring Company, a company devoted to boring and building tunnels in order to reduce street traffic. He began with a test dig on the SpaceX property in Los Angeles.
In late October of that year, Musk posted the first photo of his company's progress to his Instagram page. He said the 500-foot tunnel, which would generally run parallel to Interstate 405, would reach a length of two miles in approximately
four months.
Inventions and Innovations
Hyperloop
In August 2013, Musk released a concept for a new form of transportation called the "Hyperloop," an invention that would foster commuting between major cities while severely cutting travel time. Ideally resistant to weather and powered by renewable energy, the Hyperloop would propel riders in pods through a network of low-pressure tubes at speeds reaching more than 700 mph. Musk noted that the Hyperloop could take from seven to 10 years to be built and ready for use.
AI and Neuralink
Musk has pursued an interest in artificial intelligence, becoming co-chair of the nonprofit OpenAI. The research company launched in late 2015 with the stated mission of advancing digital intelligence to benefit humanity.
In 2017, it was also reported that Musk was backing a venture called Neuralink, which intends to create devices to be implanted in the human brain and help people merge with software. He expanded on the company's progress during a
July 2019 discussion, revealing that its devices will consist of a microscopic chip that connects via Bluetooth to a smartphone.
High-Speed Train
In late November 2017, after Chicago Mayor Rahm Emanuel asked for proposals to build and operate a high-speed rail line that would transport passengers from O'Hare Airport to downtown Chicago in 20 minutes or less, Musk tweeted that he was all-in on the competition with The Boring Company. He said that the concept of the Chicago loop would be different from his Hyperloop, its relatively short route not requiring the need for drawing a vacuum to eliminate air friction.
Flamethrower
Musk also reportedly found a market for The Boring Company's flamethrowers. After announcing they were going on sale for $500 apiece in late January 2018, he claimed to have sold 10,000 of them within a day.


org.glassfish.jersey.server.ContainerException: java.lang.NoClassDefFoundError: com/fasterxml/jackson/module/jaxb/JaxbAnnotationIntrospector
| Service Document | NOT SUPPORTED | / |
| Metadata | NOT SUPPORTED | $metadata |
| Batch | NOT SUPPORTED | $batch |
| Entity Set | OK. $format NOT SUPPORTED (OR NOT YET) | Foo Bar |
| Skip n items, top n items, get items count | OK | Foo?$skip=2&$top=3&$inlinecount=allpages |
| ORDER BY clause | OK | Foo?$orderby=Name asc,Birthday desc |
| WHERE clause | Basics work. Not sure about more complex things. | Foo?$filter=(Height ge 160)and(Age lt 40) Foo?$filter=Name eq 'Goofy' Foo?$filter=contains(Name, 'oo') Foo?$filter=Bars/all(x:x/Description eq 'Roma') Foo?$filter=Bars/any(x:x/Description eq 'Roma') |
| WHERE clause - $search | NOT SUPPORTED (OR NOT YET) | Foo?$search=Mickey |
| Count | OK | Foo/$count |
| Entity | OK | Foo(1) |
| Primitive property | OK | Foo(1)/Address |
| Primitive property (RAW) | OK | Foo(1)/Address/$value |
| SELECT | OK | Foo?$select=Address,Birthday Foo(1)?$select=Address,Birthday |
| Navigation | NOT SUPPORTED | Foo(1)/FavouriteBar is resolved with toString() Foo(1)/SomeProperty(0)/SomeOtherProperty |
| Expand sub-items | NOT SUPPORTED | Foo?$expand=Bars Foo?$expand=* |
| JOIN | NOT SUPPORTED (OR NOT YET) | $crossjoin... |
| Literals | Numbers: 1234 Strings: 'abc' Booleans: True Dates: Date'2012-05-29' Timestamps: DateTimeOffset'2018-01-10T09:24:54Z' |
|
| INSERT (POST). | OK. | resources.svc/Foo |
| UPDATE (PUT, not PATCH). | OK. UPDATE ENUM FAILS! | resources.svc/Foo(1) |
| An example of Function: Clone | OK | resources.svc/Foo(1)/Clone |
| Upload binary data |
OK | resources.svc/Foo(1)/Image/Upload |
| Download binary data |
OK | resources.svc/Foo(1)/Image/Download |


If you already have your HTML written and want to convert it into a Mithril template, paste the HTML below and press the "Convert" button.


MOAL.languages.formal_language_theory.grammars package¶
Submodules¶
MOAL.languages.formal_language_theory.grammars.analytic_context_free module¶
-
class
MOAL.languages.formal_language_theory.grammars.analytic_context_free.
AnalyticContextFreeGrammar
[source]¶
-
class
MOAL.languages.formal_language_theory.grammars.analytic_context_free.
InvalidStringLength
[source]¶
-
class
MOAL.languages.formal_language_theory.grammars.analytic_context_free.
TDPLAnalyticCFG
[source]¶ Bases:
MOAL.languages.formal_language_theory.grammars.analytic_context_free.AnalyticContextFreeGrammar
For a formal definition and examples, see wikipedia.org/wiki/Top-down_parsing_language
-
static
_evaluate_all
(start, rules=[], terminals=[])[source]¶ Non-recursive simple function, for first iteration.
-
static
MOAL.languages.formal_language_theory.grammars.attribute_context_free module¶
-
class
MOAL.languages.formal_language_theory.grammars.attribute_context_free.
AttributeContextFreeGrammar
[source]¶ Bases:
MOAL.languages.formal_language_theory.grammars.context_free.ContextFreeGrammar
An ACFG is effectively a CFG that allows attribute properties to be embedded in the ruleset for later evaluation – this is pedestrian to any programming language that supports data structures, but it all comes from these simple foundations.
For a formal definition and examples, see wikipedia.org/wiki/Attribute_grammar
-
_attr
(semantic_rule)[source]¶ Get the attribute name from the semantic rule. It comes in as a list of [object, attribute]
-
_parse_terminal
(attr, token)[source]¶ Parse a terminal value given a attribute and token.
For this example, we won’t get too fancy, just force a string on all values.
-
evaluate
(tokens, evaluation='')[source]¶ A basic parser for a custom attribute grammar.
One thing to note is that ambiguous grammars need to be iterated over, since the duplicate rules can’t be mapped via dictionary key. Unambiguous grammars are therefore more performant, because the lookup is O(1) vs. O(N).
-
MOAL.languages.formal_language_theory.grammars.backus_naur module¶
-
MOAL.languages.formal_language_theory.grammars.backus_naur.
naive_bnf_parser
(grammar)[source]¶ A parser for Backus Naur Form grammars, represented as a dictionaries.
Traditional Grammar example: <date> ::= <month> <day> <year> <month> ::= “January” | “February | “March” | “April” | “May” | “June”
“July” | “August” | “September” | “November” | “December”<day> ::= 1.. | ..31 <year> ::= 100.. | ..9999
Here we need something that is a bit more serializable – so we’ll make it JSON friendly. Each parseable tokens is either a <rule> or syntax; rules represent containers, and can even have other rules!
‘name’: {‘date’, ‘is_rule’: True, ‘vals’: [‘month’, ‘day’, ‘year’]}, ‘name’: {‘month’, ‘is_rule’: False, ‘vals’: ‘...’}, ‘name’: {‘day’, ‘is_rule’: False, ‘vals’: ‘...’}, ‘name’: {‘year’, ‘is_rule’: False, ‘vals’: ‘...’},
<name> ::= <firstname> <lastname> <firstname> ::= ‘string’ <lastname> ::= ‘string’
‘name’: {‘name’, ‘is_rule’: True, ‘vals’: []}, ‘name’: {‘firstname’, ‘is_rule’: False, ‘vals’: ‘...’}, ‘name’: {‘lastname’, ‘is_rule’: False, ‘vals’: ‘...’},
- Args:
- grammar (dict) - the grammar and rules to use for evaluation.
MOAL.languages.formal_language_theory.grammars.context_free module¶
-
class
MOAL.languages.formal_language_theory.grammars.context_free.
ContextFreeGrammar
[source]¶ Bases:
object
-
__contains__
(word)¶ Tests if a word can be created using the existing internal grammar and rules.
-
__delitem__
(rule)¶
-
__init__
()¶
-
_get_rule
(token)¶
-
_is_terminal
(char)¶
-
_is_terminal_or
(char)¶
-
add_rule
(string)¶
-
delete_rules
()¶
-
delete_tokens
()¶
-
evaluate
(tokens=None, evaluation='')¶ A basic parser for a custom attribute grammar.
One thing to note is that ambiguous grammars need to be iterated over, since the duplicate rules can’t be mapped via dictionary key. Unambiguous grammars are therefore more performant, because the lookup is O(1) vs. O(N).
-
evaluate_single
(token, nonterminals, evaluation='')¶ Recursively evaluates a single rule with a token and a given set of non-terminals
-
set_rules
(rules)¶
-
set_tokens
(tokens)¶
-
MOAL.languages.formal_language_theory.grammars.context_sensitive module¶
-
class
MOAL.languages.formal_language_theory.grammars.context_sensitive.
ContextSensitiveGrammar
[source]¶ Bases:
MOAL.languages.formal_language_theory.grammars.context_free.ContextFreeGrammar
-
DEBUG
= True¶
-
__init__
()¶
-
_evaluate
(groups, evaluation='')¶
-
evaluate
(tokens=None, evaluation='')¶ A basic parser for a custom attribute grammar.
One thing to note is that ambiguous grammars need to be iterated over, since the duplicate rules can’t be mapped via dictionary key. Unambiguous grammars are therefore more performant, because the lookup is O(1) vs. O(N).
-
static
get_substr_match
(rule, string)¶ Return the index of the last matching item of the two strings. e.g. index = 1 for ‘[ab]cd’ and ‘[ab]zd’. If the index is the same as the length then the strings simply match.
-
static
simple_rule
(rule, string='')¶
-


INTRO
chat is an Erlang/OTP application powered by N2O messaging protocol. It is implemented as a ring of protocol nodes.
This module may refer to: chat, chat_client, chat_server.
chat is an Erlang/OTP application powered by N2O messaging protocol. It is implemented as a ring of protocol nodes.
This module may refer to: chat, chat_client, chat_server.


Textual Data from Huffington Post
Collection of keyworlds and its distribution on timeline.
Inspired by Physics momentum.
To enhance the information and detect outlying in data.


The Plug Hole Mask Creation is a read-write DFM
action intended to
create plug layers for defined drill layers. The DFM action enables you
to
define complex filters to specify which drill holes should be plugged,
and from
which side to plug a specific drill hole. Using this DFM action will
save time
and reduce errors when defining plug layers. This DFM action requires the license option viapdfm .
Select DFM >
Yield Improvement > Plug Hole Mask Creation
excludes text, arc, and surface features.
Whether slot and laservia features should have
plugs.
This is related to the screen parameter Plug
Hole if Mask
Clearance ... Smaller than Hole, Equal to Hole,
Larger than Hole. This
filter decides whether or not to plug a drill hole depending on the
relationship between the drill hole and a single (top or bottom) reference feature for that drill
hole.
1.
The
size of the annular ring (AR), for both the top and bottom
reference features, must be smaller than the maximum AR value as
defined by the
parameter pp_max_ar .
2.
Examine
the relationship between the size of the drill hole and
the mask clearance for either reference feature (top or bottom). See
examples
below that illustrate how these relationships appear in the Graphic
Editor.
3.
Based
on the criteria defined in the screen parameter Plug
Hole if Mask Clearance , decide
whether you need to
create a mask plug, or should consider other factors in making your
decision.
Related to the screen parameters One
Side is Partially Open, Both
Sides Fully Open, One Side Not Open and One side Open. This
filter
decides whether or not to plug a drill hole depending on the
relationship
between the drill hole and both (top and bottom) reference features.

Partial --the
feature from the reference layer partially covers the drill hole, or is
smaller
than the drill hole.
Close --there
is no feature in the reference layer above the drill hole.
·
If
there is no reference feature on
either side of the drill hole (i.e. both sides are Closed)
,
then both sides must be plugged.
The pictures below illustrate these relationships
in the Graphic Editor.
Note> The definitions given above may seem
contrary to logic, i.e. that an open hole is one where "the reference layer fully
covers the drill
hole". But note that the reference layer is a negative layer in Genesis. This means that where
there is a feature in the layer mask, there is a clearance (an open
area) above
the drill on the physical board.
|
Two-sided relation |
|
A drill hole has two reference features. The top
reference feature
partially covers the drill hole; the bottom reference feature fully
covers the
drill hole (i.e. is open).
The following rules were created to decide whether
or not to plug the
hole:
·
For
holes with only one reference
feature, if the hole is open from that side (the reference feature is
larger
than the drill hole), there is no need to plug the hole.
·
For
holes with two reference features,
the drill hole must be plugged if one side is open and the other side
is
partially open.
In this situation, the rules conflict with each
other. To resolve such
cases, there is an order of precedence that specifies, for the various
items
that make up the relation between a drill hole and its reference
features, in
what situations you should or should not add a hole plug.
Highest priority> size of drill hole
In the example given above, the single-sided
relation has a higher
priority, in accordance with the rules of precedence defined above. In
this
example, the final result is that the top side is without a plug, and
the
bottom side has a plug.
If you have not defined both reference features,
the DFM action will not
process the mask clearance relation filter. If only one reference layer
is
defined, the relation of the drill hole to the undefined side is
defined by the
ERF variable v_no_mask_full_open . For a blind drill layer, if the blind
side completely masks the drill clearance, the single-sided relation is
defined
as closed (i.e. no clearance
above the drill hole).


| Status: | |
|---|---|
| URL: | |
| Protocol(s): | |
| Close Status: | |
|---|---|
| Close Reason: | |
| Message Text |
|---|
TestCafe.Block is block-type code editor for tiny script.
Export Tab: Export code.
Block Tab
Review Tab: Review code.
Run Tab: Connect WebSocket & Execute code & Clear log & Close WebSocket & Send customized code.


--- date: 2022-08-30 lastmod: 2023-08-05 title: "Goodbye snake, I go to the moon" description: "I started using Lua after increasing frustration with Python. After using it for a while, it became my go-to scripting language." image: "/assets/blog/lua/title-card.png" imageAlt: "Showing the Visual Studio Code editor with an open Lua test file in the middle and the project setup with different files on the left." linkTitle: "Setting up Lua and using it for scripts, tools and application development." banner: "/assets/blog/lua/banner" bannerAlt: "Showing the Visual Studio Code editor with an open Lua test file in the middle and the project setup with different files on the left." summary: "
Being more and more frustrated with Python, Lua became my go-to alternative for scripts, tools, and application extensions. This article will show how I set up and use Lua.
" hasCode: true tags: ["post", "cpp", "lua"] ---NASA is not the only one going to the moon — Lua (pronounced LOO-ah) meaning "Moon" in Portuguese, is a multiple-paradigm scripting language. Created in 1993 by Roberto Ierusalimschy, Luiz Henrique de Figueiredo, and Waldemar Celes, members of the Computer Graphics Technology Group (Tecgraf) at the Pontifical Catholic University of Rio de Janeiro in Brazil.
Initially overlooked by me as "just another scripting language", it caught my eye when I was looking for an alternative to Python. Growing frustrated with the Snake for different reasons, I wanted a small and simple-to-use language. One of my criteria was that I could embed it into a project's build system, making setup and management easier, sparing the need for specific version installations, or handling local installed language environments with one of too many tools. Speed was another factor that was neglected far too often with script languages.
Lua ticked many boxes for me and grew on to become a favorite of mine, from small scripts to large tools; a language as a general toolset for my daily tasks, running really everywhere. In this article, I will give an overview of how and with what I personally use Lua; this is not an exhaustive guide. Nevertheless, I will publish a multipart series on Lua, going in-depth on many parts of the language; more on this at the end.
You may already have Lua installed on your system! You can check by running
lua -v
in a terminal.
If this is not the case, there are different ways to get Lua; one way on macOS is using brew.
Having Lua installed, you can start a
REPL
with the lua
command.
LuaRocks can be seen as the de facto standard package manager for Lua. If not already installed on macOS, you can use brew to install LuaRocks.
Similar to NPM, I want to keep packages
local and inside the project rather than global or in my user
directory. A global installation is the default; using
--local
will install packages in a folder in the user's home
directory.
I will install all packages inside a lua_modules
folder in the
root of a project, using the --tree
option of the LuaRocks
CLI. As an example, installing the
inspect
package.
For Lua to find any local package on require
, the search paths
need to be set. This can be done by defining a setup module (that can have any
name) that will be loaded when executing a script through the
-l
option of the Lua
CLI.
Creating a script file …
… and running it with the -l
option will find the
inspect
package from the local folder and execute the script.
This will now work for any package installed inside the local project via
luarocks install --tree=lua_modules <package>
.
Setting up a project would not be complete without testing, lint tooling, and code formatting.
For unit tests, I use LuaUnit, installed via LuaRocks.
Tests are just Lua files importing LuaUnit. I define test files with the
.test.lua
extension and use
TAP (Test Anything Protocol)
as the output format, an amazing output format I also use in
other languages.
The test can then be executed via Lua, printing the result on the terminal.
To lint, I use LuaCheck, again installed via LuaRocks.
Using the default options, run it on a whole folder, for example, the
src
folder.
Auto formatting Lua code happens via LuaFormatter.
For the checker, I will use a small set of custom options, defined in a
.lua-format
file (the format is YAML), in the
project root.
Running it on all files in a folder and formatting them.
Using Visual Studio Code with a plugin for LuaCheck and LuaFormatter, creates a comfortable environment for working with Lua.
Having established a base working with Lua, how about embedding it into other software? Lua is also known as an "extensible extension language", referring to it being created with the idea of having a scripting language that can extend and customize applications.
I will use
Sol2, a header-only C++ library providing Lua bindings, in combination with my
C++ base template
I created in my
basic C++ setup with CMake article. Having that set up, I first need to add Lua to the project, creating a new
CMake file vendor/lua/CMakeLists.txt
to build Lua as it does not
come with CMake support.
This will set up Lua as a C project and create a library under the name
lua
. Next, extending the dependency list in
vendor/CMakeLists.txt
.
Sol2 can be added as a dependency by creating a new
vendor/sol2/CMakeLists.txt
file, which is rather short as it comes with CMake support.
Again, adding it to the dependency list in vendor/CMakeLists.txt
.
That's it for getting Lua and Sol2 into the project. Next up is adding the libraries to the application by linking them to the target.
Now that everything is ready, trying a small test program in
src/app/App/Main.cpp
.
This will indeed print Some value is now: 1
. A different example,
a Lua script file with a simple function for demonstration.
With CMake, any non-build files need to be copied to the build output
directory. Using the file
function, this can be done on the CMake
configure step.
The script file can then be loaded, extracting the defined Lua function
hello
to call it from C++.
Running this will print Result: Hello, Mr. Anderson
.
This example project is also available on GitHub as embedding-lua-in-cpp-example repository. How to inject new functions and values into Lua, as well as many other things, can be found in the official Sol2 documentation.
This just showed some basics of Lua and parts of how I use Lua personally, only scratching the surface. To extend this and shine an even brighter light on the Moon, I will create a series of articles covering many topics of Lua more in depth. Some of those will be:
And maybe more, if I find more things to cover. Until then 👋🏻


The Apache CloudStack project understands that as a core infrastructure project, the application security of Apache CloudStack is of critical importance to the community and users.
If you've found an issue that you believe is a security vulnerability in a released version of CloudStack, please report it to the ASF security team via email to<EMAIL_ADDRESS>with details about the vulnerability, how it might be exploited, and any additional information that might be useful.
Upon notification, the ASF security team will work with the CloudStack PMC through validation and fixing the issue. If the issue is validated, it generally takes 2-4 weeks from notification to public announcement of the vulnerability. During this time, the team will communicate with you as they proceed through the response procedure, and ask that the issue not be announced before an agreed-upon date.
Please do not create publicly-viewable JIRA tickets related to the issue. If validated, a JIRA ticket with the security flag set will be created for tracking the issue in a non-public manner, and made public at the appropriate time.
We're follow the Apache Security Team's procedures documented here.
Further information about Apache CloudStack's security practices can be found in the CloudStack Security wiki page.


Makefile rules¶
The project comes with these make
directives:
Available rules:
clean Delete all models and data
data Transform raw data
docs Build documentation and copy it to the docs folder
githooks Set up githooks
models Train models
mostlyclean Delete all models and data, except for the raw downloads
predictions Create predictions
raw_data Pull raw data from Kaggle
This page describes what each of these directives does in a bit more detail.
make clean
¶
Deletes all models and data that are created over the course of the project
pipeline. This deletes the raw data as well, so the data will have to be
re-downloaded from Kaggle once make clean
is performed. To delete
everything but keep the raw data, use make mostlyclean.
make data
¶
Takes the data from raw to processed and ready for modeling.
Runs main()
and saves the output to data/interim
.
Then runs main()
and saves the final data
to data/processed
.
make docs
¶
Steps into docsrc/
and runs make html
, copying the built documentation
to docs/
. This allows the documentation to easily be hosted on Github Pages.
make githooks
¶
Sets up the pre-commit git hook that’s stored in the .githooks
folder.
You can use this in your git repository to prevent Jupyter notebooks from
being committed without being converted to output-free Python scripts first.
It isn’t necessary to use this command to replicate any part of the analysis.
make models
¶
Trains the models using the processed training data. Serializes the fitted
models and stores them in models/fitted
.
make mostlyclean
¶
Deletes all models and data that are created over the course of the project pipeline, but keeps the raw data intact so that the Kaggle download does not need to be repeated.
make predictions
¶
Generates predictions from the fitted models in models/fitted
and using
the processed test data in data/processed
. Saves the predictions in
models/predictions
.
make raw_data
¶
Downloads the raw data from Kaggle. This requires the Kaggle API to be installed and properly configured.


Basic Profile Card
Social Profile Card
Modren Profile Card
Some quick example text to build on the card title and make up the bulk of the card's content.
{# Repeated form blocks imported as macro with form as param #} {{ usedalot(form) }} Go somewhereComments


Try out different selectors with the default JSON input data, or edit the data yourself.
A simple visual editor that allows you to manipulate H5ON objects directly in the browser.


{{user_navs = True}} {{extend 'layout.html'}}
The books on Runestone.Academy are all free and open source textbooks. We encourage you to browse the library and make use of these books in your courses. If you are a new instructor and want to do this, please take a look at the Help for Instructors page before you make a course.
Computer Science Textbooks: {{ for book in book_list: }}{{=book['regname']}}
The books published on Runestone are all licensed under the Creative Commons CC-BY license or the GNU Free Documentation license. The source code for each book can be found on Our Github Page and will give you the specifics of the license. We encourage you to report any innacuracies, typos or leave us suggestions using the Github issues page for each book.


|
A lawyer or attorney is a person who practices law, as an advocate, attorney, attorney at law, barrister, barrister-at-law, bar-at-law, canonist, canon lawyer, civil law notary, counsel, counselor, counsellor, solicitor, legal executive, or public servant preparing, interpreting and applying law, but not as a paralegal or charter executive secretary.[1] Working as a lawyer involves the practical application of abstract legal theories and knowledge to solve specific individualized problems, or to advance the interests of those who hire lawyers to perform legal services. The role of the lawyer varies greatly across different legal jurisdictions. In practice, legal jurisdictions exercise their right to determine who is recognized as being a lawyer. As a result, the meaning of the term "lawyer" may vary from place to place. Some jurisdictions have two types of lawyers, barrister and solicitors, whilst others fuse the two. A barrister is a lawyer who specializes in higher court appearances. A solicitor is a lawyer who is trained to prepare cases and give advice on legal subjects and can represent people in lower courts. Both barristers and solicitors have gone through law school, completed the requisite practical training. However, in jurisdictions where there is a split-profession, only barristers are admitted as members of their respective bar association. |
A lawyer or attorney is a person who practices law, as an advocate, attorney, attorney at law, barrister, barrister-at-law, bar-at-law, canonist, canon lawyer, civil law notary, counsel, counselor, counsellor, solicitor, legal executive, or public servant preparing, interpreting and applying law, but not as a paralegal or charter executive secretary.[1] Working as a lawyer involves the practical application of abstract legal theories and knowledge to solve specific individualized problems, or to advance the interests of those who hire lawyers to perform legal services. The role of the lawyer varies greatly across different legal jurisdictions. In practice, legal jurisdictions exercise their right to determine who is recognized as being a lawyer. As a result, the meaning of the term "lawyer" may vary from place to place. Some jurisdictions have two types of lawyers, barrister and solicitors, whilst others fuse the two. A barrister is a lawyer who specializes in higher court appearances. A solicitor is a lawyer who is trained to prepare cases and give advice on legal subjects and can represent people in lower courts. Both barristers and solicitors have gone through law school, completed the requisite practical training. However, in jurisdictions where there is a split-profession, only barristers are admitted as members of their respective bar association. |


Parliament proceedings: Opposition wants Speaker to act on Farooq Abdullah issue
‘Ensure Srinagar MP’s presence’
by Special CorrespondentThe Opposition parties are going to approach Lok Sabha Speaker Om Birla seeking his intervention on behalf of the House to ensure that Srinagar MP Farooq Abdullah is allowed to attend the ongoing Parliament session.
The Opposition parties are arguing that the onus lies on the Speaker to ensure the presence of Mr. Abdullah in the House since he has not sought a leave of absence and has been detained without any genuine grounds for his detention. Mr. Abdullah was re-elected from the Srinagar constituency in May 2019.
The government has detained Mr. Abdullah under the Public Safety Act (PSA). The Opposition parties had taken up the issue during the all-party meeting on Sunday, and then once again in the Lok Sabha on Monday. The government has so far not come up with a concrete reply except for Parliamentary Affairs Minister Pralhad Joshi saying that the government would look into it and do whatever possible within the framework of the law.
“We seek to take all legitimate steps within the framework of Constitution to ensure Mr. Farooq Abdullah’s presence in the House,” National Conference MP Hasnain Masoodi said.


This intention merges
if-else
statement inside then-branch of another
if-else
into one.
Powered by JavaScript IntentionPowerPack


Next: Alphabetic Characters, Previous: Character Categories, Up: Character Categories
Characters that are classified as graphic , or displayable, are each associated with a glyph, a visual representation of the character.
A graphic character is one that has a standard textual representation as a single glyph, such as A or * or =. Space, which effectively has a blank glyph, is defined to be a graphic.
Of the standard characters, newline is non-graphic and all others are graphic; see Standard Characters.
Characters that are not graphic are called non-graphic .
Non-graphic characters are sometimes informally called "formatting characters" or "control characters."
#\Backspace, #\Tab, #\Rubout, #\Linefeed, #\Return, and #\Page, if they are supported by the implementation, are non-graphic.


Plugin Information |
|---|
View WAPT Pro on the plugin site for more information. |
Version history
Version 1.6
- Pipeline support
Version 1.1
- Version info fixed
Version 1.0
- Initial release
Plugin Information |
|---|
View WAPT Pro on the plugin site for more information. |


|
||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
| Class Summary | |
|---|---|
| ConnectionColorItemListener | This ItemListener updates the 3D scene of the
JMeshConnectionPanel whenever the node connection color changes. |
| GeometryColorItemListener | This ItemListener updates the 3D scene of the JMeshPanel
whenever the mesh color changes. |
| MeshConnectionMakeAction | This Action checks if the JMeshConnectionPanel has stored
nodes, if the nodes and node key groups have the same names, and if a node
key group is selected. |
| MeshConnectionOpenAction | This Action opens a dialog for the user to select the node connection
input file and then imports it. |
| MeshConnectionReadAction | This Action automatically imports the current node connection
input file. |
| MeshConnectionSaveAction | This Action checks if the JMeshConnectionPanel has stored
node connections. |
| MeshConnectionSaveAsAction | This Action checks if the JMeshConnectionPanel has stored
node connections. |
| MeshConnectionShowAction | This Action updates the 3D scene of the JMeshConnectionPanel
whenever an action is performed. |
| MeshNameAction | This Action gets the current mesh name in the MeshUI and sets
its as the mesh name in the JMeshPanel . |
| MeshOpenAction | This Action opens a dialog for the user to select the mesh input file
and then imports it. |
| MeshReadAction | This Action automatically imports the current mesh input file. |
| MeshShowAction | This Action updates the 3D scene of the JMeshPanel whenever
an action is performed. |
| NodeKeyItemListener | This ItemListener updates the log of the JMeshPanel whenever
a set is selected. |
| NodeKeyOpenAction | This Action opens a dialog for the user to select the node key group
input file and then imports it. |
| NodeKeyReadAction | This Action automatically imports the current node key group input
file. |
|
||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |


| Concept Framework 2.2 documentation | Contents | Index |
| Name | Version | Deprecated |
| ADODataSet | version 1.0 | no |
|
Encapsulates the result of a query as ADODataRecords. This is the class you should instantiate after an ADOConnection was created in order to have access to the connected database.
ADODataSet is a set of ADODataRecords encapsulating various properties like CommandText and FieldValues and methods like ExecuteQuery for execution of a SQL query. |
| Columns | This is the number of columns in the current row |
| CommandText | Using this property you can set the SQL query text |
| Connection | Sets or gets the ADOConnection used for this data set |
| FieldValues | With this property you have access to the result of an executed query |
| IsUpdateQuery | Returns the status of a positional update query (true if updated, false if not) |
| PreparedQuery | This property is very similar to the CommandText property, but it takes parameters (for large objects for example) |
| RowIndex | The row index of the current row |
| ADODataSet | This is the standard contructor for this class and should not be used directly |
| AddLinkedObject | Adds an ADO control to the linked objects list |
| AddParameter | Adds a parameter to a prepared SQL query |
| AfterQueryNotify | Notifies VirtualADOObject derived controls that the current SQL query has changed, and should update their contents |
| Checked | TODO: Document this |
| ClearParameters | Clears all parameters added with the AddParameter function |
| CloseRead | Closes the current read operation |
| CountRows | This function returns the number of rows in the current result |
| Current | Refreshes the current record, is possible |
| Delete | Performs a positional delete on the current query |
| ExecuteNonQuery | This function is similar to the ExecuteQuery function, but it returns no records |
| ExecuteQuery | It executes the SQL query specified by the CommandText or PreparedQuery property and updates the FieldValues property |
| FetchByIndex | Fetches a row by its index |
| FetchForward | This function should be used only when working with MySQL and tables that contain big text fields |
| First | Moves to the first row, if possible |
| GetValues | Identical to FieldValues, if you prefer the functional version |
| LastError | The last error(s) encountered by the data set, as a string |
| Next | Moves to the next row, if possible |
| Prev | Moves to the previous row, if possible |
| Refresh | Reexecutes the current SQL query |
| RemoveLinkedObject | Remove an ADO control to the linked objects list |
| SetConnection | TODO: Document this |
| SetPreparedQuery | TODO: Document this |
| Text | TODO: Document this |
| Update | Performs a positional update on the current query |
| UpdateColumnList | This function performs list-style operations for VirtualADOObject derived controls |
| finalize | TODO: Document this |
| Documented by Eduard Suica, generation time: Sun Jan 27 18:15:09 2013 GMT | (c)2013 Devronium Applications |


has read permission for {{component1}}
has update permission for {{component2}}
has not got delete permission for {{component3}}
toggle


You can access the Dinosaurs list.
You have elevated privileges! You may access Dinosaurs as well as the special Dragons list.


Each utility provider be it a national company or a small independent will have its own individual needs with regard to weather data and forecasting services. The superior computing power and resource of The Met.Office helps all our customers to forecast demand and meet the needs of their users cost effectively. For those involved in the Building and Construction of utility facilities further services are available.
For further information contact:
Barbara Richardson
Tel.No. +44 (0)1344 856665
E-mail<EMAIL_ADDRESS>Postal Address: Met.Office, Room S1/2, Sutton House, London Road, Bracknell, Berks. RG12 2SY. United Kingdom
or simply fill in our Response Form.


Repeating input when holding down movement keys (utilize acceleration so it doesn't happen instantly and
slowly speeds up.)
29 May 2020
Implemented an internal "ZoomTo" function. The function takes the following parameters:
layer - layer to zoom to (i.e. layer 76)
scale - zoom level (same as page zoom level)
xTile - x Coordinate of tile to zoom to (Starts at 0)
yTile - y Coordinate of tile to zoom to (starts at 0)
If an invalid layer is given, nothing happens.
Added keyboard only movement. The numpad 8,6,4,2 keys will move one tile at a time. And holding the z
key will make the movement with the numpad move by 10 each press.
4 May 2020
Fixed small hang when initially loading map. (Entire DOM was freezing when parsing individual
layers.)
Javascript Promises were used to make this async so that DOM updates could occur.
1 May 2020
Fixed slow parsing. Manually manipulated each color channel (RGBA) of the image. MUCH faster.
Contacted Markavian with initial product.
30 April 2020
Implemented map parsing fully.
Smooth zooming
Parsing is SUPER SLOW! Most likely due to using P5.Image's 'set' function.
29 April 2020
Initial Commit.
Basic Tile Viewing. (This version just gets a map and displays its tiles.)


Affiliated to University of Pune
Mrs. Kusum B. Kotkar, Chairman, Shikshan Maharshi Dr. D.Y. Patil Shikshan Sanstha
Dr. D.Y. Patil Senior College has been modeled on the best practices of the modern schools in and around the country. The curriculum helps the students to have intellectual as well as rounded personality development of the child. Dr. D. Y. Patil Senior College attracts students from various places and train them to aspire to become the future leaders realizing their responsibilities towards others. Students here get exposed to a broad range of culture, beliefs which help them to show tolerance at adulthood. Dr. D. Y. Patil Senior College is an international ambitious, outward looking modern school which also emphasis on discipline, courtesy, honesty as their virtues to make these the strength of it's students.
Wishing you all the best!
Shri. Abhay B. Kotkar, Vice President, Shikshan Maharshi Dr. D.Y. Patil Shikshan Sanstha
Dr. D. Y. Patil Senior College aims in imparting Quality education to children as we believe that school is a foundation where moral and ethical standards should be inculcated among children. We at Dr. D. Y. Patil Senior College School strive to practice it by providing them state of the art facilities & opportunities and develop children into socially responsible citizens. Other courses run by Shikshan Maharshi Dr. D. Y. Patil Shikshan Sanstha are Dr. D. Y. Patil College of Arts, Science & Commerce (Affiliated to University of Pune) & Dr. D. Y. Patil Centre For Management and Research (MBA)(Approved by AICTE, Affiliated to University of Pune and Recognized by Government of Maharashtra). The Sanstha provides education from KG to PG


Iterator over the elements of the dense matrix. More...
#include <DMatScalarDivExpr.h>
Public Types | |
| using | IteratorCategory = std::random_access_iterator_tag |
| The iterator category. | |
| using | ValueType = ElementType |
| Type of the underlying elements. | |
| using | PointerType = ElementType * |
| Pointer return type. | |
| using | ReferenceType = ElementType & |
| Reference return type. | |
| using | DifferenceType = ptrdiff_t |
| Difference between two iterators. | |
| using | iterator_category = IteratorCategory |
| The iterator category. | |
| using | value_type = ValueType |
| Type of the underlying elements. | |
| using | pointer = PointerType |
| Pointer return type. | |
| using | reference = ReferenceType |
| Reference return type. | |
| using | difference_type = DifferenceType |
| Difference between two iterators. | |
| using | IteratorType = ConstIterator_< MT > |
| ConstIterator type of the dense matrix expression. | |
Public Member Functions | |
| ConstIterator (IteratorType iterator, RightOperand scalar) | |
| Constructor for the ConstIterator class. More... | |
| ConstIterator & | operator+= (size_t inc) |
| Addition assignment operator. More... | |
| ConstIterator & | operator-= (size_t dec) |
| Subtraction assignment operator. More... | |
| ConstIterator & | operator++ () |
| Pre-increment operator. More... | |
| const ConstIterator | operator++ (int) |
| Post-increment operator. More... | |
| ConstIterator & | operator-- () |
| Pre-decrement operator. More... | |
| const ConstIterator | operator-- (int) |
| Post-decrement operator. More... | |
| ReturnType | operator* () const |
| Direct access to the element at the current iterator position. More... | |
| auto | load () const noexcept |
| Access to the SIMD elements of the matrix. More... | |
| bool | operator== (const ConstIterator &rhs) const |
| Equality comparison between two ConstIterator objects. More... | |
| bool | operator!= (const ConstIterator &rhs) const |
| Inequality comparison between two ConstIterator objects. More... | |
| bool | operator< (const ConstIterator &rhs) const |
| Less-than comparison between two ConstIterator objects. More... | |
| bool | operator> (const ConstIterator &rhs) const |
| Greater-than comparison between two ConstIterator objects. More... | |
| bool | operator<= (const ConstIterator &rhs) const |
| Less-than comparison between two ConstIterator objects. More... | |
| bool | operator>= (const ConstIterator &rhs) const |
| Greater-than comparison between two ConstIterator objects. More... | |
| DifferenceType | operator- (const ConstIterator &rhs) const |
| Calculating the number of elements between two iterators. More... | |
Private Attributes | |
| IteratorType | iterator_ |
| Iterator to the current element. | |
| RightOperand | scalar_ |
| Scalar of the multiplication expression. | |
Friends | |
| const ConstIterator | operator+ (const ConstIterator &it, size_t inc) |
| Addition between a ConstIterator and an integral value. More... | |
| const ConstIterator | operator+ (size_t inc, const ConstIterator &it) |
| Addition between an integral value and a ConstIterator. More... | |
| const ConstIterator | operator- (const ConstIterator &it, size_t dec) |
| Subtraction between a ConstIterator and an integral value. More... | |
Iterator over the elements of the dense matrix.
|
inlineexplicit |
Constructor for the ConstIterator class.
| iterator | Iterator to the initial element. |
| scalar | Scalar of the multiplication expression. |
|
inlinenoexcept |
Access to the SIMD elements of the matrix.
|
inline |
Inequality comparison between two ConstIterator objects.
| rhs | The right-hand side iterator. |
|
inline |
Direct access to the element at the current iterator position.
|
inline |
Pre-increment operator.
|
inline |
Post-increment operator.
|
inline |
Addition assignment operator.
| inc | The increment of the iterator. |
|
inline |
Calculating the number of elements between two iterators.
| rhs | The right-hand side iterator. |
|
inline |
Pre-decrement operator.
|
inline |
Post-decrement operator.
|
inline |
Subtraction assignment operator.
| dec | The decrement of the iterator. |
|
inline |
Less-than comparison between two ConstIterator objects.
| rhs | The right-hand side iterator. |
|
inline |
Less-than comparison between two ConstIterator objects.
| rhs | The right-hand side iterator. |
|
inline |
Equality comparison between two ConstIterator objects.
| rhs | The right-hand side iterator. |
|
inline |
Greater-than comparison between two ConstIterator objects.
| rhs | The right-hand side iterator. |
|
inline |
Greater-than comparison between two ConstIterator objects.
| rhs | The right-hand side iterator. |
|
friend |
Addition between a ConstIterator and an integral value.
| it | The iterator to be incremented. |
| inc | The number of elements the iterator is incremented. |
|
friend |
Addition between an integral value and a ConstIterator.
| inc | The number of elements the iterator is incremented. |
| it | The iterator to be incremented. |
|
friend |
Subtraction between a ConstIterator and an integral value.
| it | The iterator to be decremented. |
| dec | The number of elements the iterator is decremented. |


--- layout: default --- {% assign postCount = site.posts | size %} {% if postCount == 0 %}
Good gosh darn it. There are no blog posts.
Please wait for inception...


org.objectstyle.cayenne
Class DataRow
java.lang.Object
|
+--java.util.AbstractMap
|
+--java.util.HashMap
|
+--org.objectstyle.cayenne.DataRow
- All Implemented Interfaces:
- java.lang.Cloneable, java.util.Map, java.io.Serializable
- public class DataRow
- extends java.util.HashMap
DataRow is a map that holds values retrieved from the database for a
given query row. DataRows are used to cache database data snapshots,
and as a reference point for tracking DataObject changes.
- Since:
- 1.1
- Author:
- Andrei Adamchik
- See Also:
- Serialized Form
|
Constructor Summary |
DataRow(int initialCapacity)
|
DataRow(java.util.Map map)
|
| Methods inherited from class java.util.HashMap |
clear, clone, containsKey, containsValue, entrySet, get, isEmpty, keySet, put, putAll, remove, size, values |
| Methods inherited from class java.util.AbstractMap |
equals, hashCode |
| Methods inherited from class java.lang.Object |
finalize, getClass, notify, notifyAll, wait, wait, wait |
| Methods inherited from interface java.util.Map |
equals, hashCode |
version
protected long version
replacesVersion
protected long replacesVersion
DataRow
public DataRow(java.util.Map map)
DataRow
public DataRow(int initialCapacity)
getVersion
public long getVersion()
getReplacesVersion
public long getReplacesVersion()
setReplacesVersion
public void setReplacesVersion(long replacesVersion)
- Sets the version of DataRow replaced by this one in the store.
applyDiff
public DataRow applyDiff(DataRow diff)
- Builds a new DataRow, merging changes from
diff
parameter with data contained in this DataRow.
- Since:
- 1.1
createDiff
public DataRow createDiff(DataRow row)
- Creates a DataRow that contains only the keys that have values that differ
between this object and
row
parameter. Diff values are taken from the
row
parameter. It is assumed that key
sets are compatible in both rows (e.g. they represent
snapshots for the same entity). Returns null if no differences are found.
- Since:
- 1.1
createObjectId
public ObjectId createObjectId(ObjEntity entity)
- Creates an ObjectId from the values in the snapshot.
If needed attributes are missing in a snapshot,
CayenneRuntimeException is thrown.
createObjectId
public ObjectId createObjectId(java.lang.Class objectClass,
DbEntity entity)
createTargetObjectId
public ObjectId createTargetObjectId(java.lang.Class targetClass,
DbRelationship relationship)
- Returns an ObjectId of an object on the other side of the to-one relationship,
for this DataRow representing a source of relationship. Returns null if snapshot
FK columns indicate a null to-one relationship.
toString
public java.lang.String toString()
- Overrides:
toString
in class java.util.AbstractMap
Copyright © 2001-2004 ObjectStyle.org All Rights Reserved.


The components string specifies the sinusoidal components of the sound.
Examples:
440 660 880
440/0 660/-10 880/-20
235.5 *3/-2.5 *5/-6 *7/-17 *9/-6 *11/-18.4 *13/-15.4
(clarinet-like)
440/0/0 443/0/0.5
(3Hz beat)
A component has the format
freq
,
freq
/
ampl
or
freq
/
ampl
/
phase
.
freq
is an absolute frequency in Hz or a relative frequency in the format
*factor
.
A relative frequency, specified with
*
, is relative to the last absolute frequency.
ampl
is a relative amplitude in dB.
The overall amplitude is normalized for not exceeding
the maximum amplitude range and keeping the power of the sound mostly constant.
phase
is a number in the range 0 to 1, where 1 corresponds to a phase of 2π in radians. The default value is 0


|
Weather-Storm
An event loop manager example project for Raspberry Pi
|
This class is inherited from the StateMachine class of Elma. More...
#include <weatherStormStateMachine.h>
Public Member Functions | |
| weatherStormStateMachine (string name) | |
| weatherStormStateMachine () | |
| getDataState | getGetDateState () |
| energizeState | getEnergizeState () |
| deenergizeState | getDeenergizeState () |
| Public Member Functions inherited from elma::StateMachine | |
| StateMachine (std::string name) | |
| Construct a new StateMachine with the given name. | |
| StateMachine () | |
| Construct an unnamed StateMachine. | |
| StateMachine & | set_initial (State &s) |
| StateMachine & | add_transition (std::string event_name, State &from, State &to) |
| StateMachine & | set_propagate (bool val) |
| State & | current () |
| void | init () final |
| Do not override init() for a state machine. | |
| void | start () final |
| Do not override init() for a state machine. | |
| void | update () final |
| Do not override init() for a state machine. | |
| void | stop () |
| Do not override init() for a state machine. | |
| Public Member Functions inherited from elma::Process | |
| Process (int n=0) | |
| Default constructor. Names process "no name". | |
| Process (std::string name, int n=0) | |
| Constructor that takes a name for the process. More... | |
| string | name () |
| status_type | status () |
| high_resolution_clock::duration | period () |
| int | num_updates () |
| time_point< high_resolution_clock > | start_time () |
| high_resolution_clock::duration | last_update () |
| high_resolution_clock::duration | previous_update () |
| Channel & | channel (string name) |
| Access a channel with the given name. More... | |
| double | milli_time () |
| The time since the last update in millisconds, as a double. More... | |
| double | delta () |
| The most recent amount of time between updates. More... | |
| void | watch (string event_name, std::function< void(Event &)> handler) |
| void | emit (const Event &event) |
| void | http_get (std::string url, std::function< void(json &)> handler) |
| void | halt () |
Additional Inherited Members | |
| Public Types inherited from elma::Process | |
| enum | status_type { UNINITIALIZED, STOPPED, RUNNING } |
This class is inherited from the StateMachine class of Elma.
The weatherStormStateMachine class has four states that are: idel state, get data state, energize state, and deenergize state. there are four transitions for this state machine that are: start, that changes idel state to get data state; energize, that changes get data state to energize state; deenergize, that changes energize state to deenergize state; and idle, that changes deenergize state to idle state.
Definition at line 56 of file weatherStormStateMachine.h.
|
inline |
Constructor that takes a name for the weatherStormStateMachine In this method all the states are constructed. Also, all the transitions are added.
| name | the name of the state machine |
Definition at line 65 of file weatherStormStateMachine.h.
|
inline |
Default constructor calling the default constructor of StateMachine In this method all the states are constructed. Also, all the transitions are added.
Definition at line 80 of file weatherStormStateMachine.h.
|
inline |
A getter method that returns the deenergizeState object created in the constructor Using this method I can access the getter methods in the deenergizeState class to see if all state tasks are complete or retrieve the json object
Definition at line 103 of file weatherStormStateMachine.h.
|
inline |
A getter method that returns the energizeState object created in the constructor Using this method I can access the getter methods in the energizeState class to see if all state tasks are complete or retrieve the json object
Definition at line 99 of file weatherStormStateMachine.h.
|
inline |
A getter method that returns the getDatestate object created in the constructor Using this method I can access the getter methods in the getDatestate class to see if all state tasks are complete or retrieve the json object
Definition at line 95 of file weatherStormStateMachine.h.


Interactive of the SimpleFrame Family. Unlike BUTTON it does not keep the focus.
Only the last added event (for each SIMPLEBUTTON) triggers
Frame "SIMPLEBUTTON" "MySimpleButton" { Width 0.039, Height 0.039, Texture "MySimpleButtonTexture" { } }


Hello!
Overview
- Cultural studies on agency & cultural criticism
- Traditional LIS accounts of patron agency
- Examples of how to encourage agency
Cultural Studies & Agency
"Capitol Crawl" for the ADA
1990 protest for Americans with Disabilities Act
Washrooms
Cultural Criticism
Janice Radway, Reading the Romance and reader response criticism focusing on how readers use texts
Critiques of Library Discourse around Agency
Pedagogical orientation
- Problem-posing rather than banking model
- Signage that presents a theme rather than a set
- Investing in & displaying material collection with an eye to its pedagogical potential
Works Cited
- Burt, Laura. "Vivian Harsh, Adult Education, and the Library's Role as Community Center." Libraries & the Cultural Record vol. 44, no. 2, 2009, pp. 234-55.
- Buschman, John. Libraries, Classrooms, and the Interests of Democracy: Marking the Limits of Neoliberalism. The Scarecrow P, 2012.
- Giroux, Henry. "Schooling and the Culture of Positivism: Notes on the End of History." 1979. On Critical Pedagogy. Continuum International Publishing Group, 2011, pp. 19-47.
Works Cited, cont.
- Grossberg, Lawrence. Bringing It All Back Home: Essays on Cultural Studies. Duke UP, 1997.
- Radway, Janice A. Reading the Romance: Women, Patriarchy, and Popular Literature. U of North Carolina P, 1984.
- Wiegand, Wayne. "To Reposition a Research Agenda: What American Studies Can Teach the LIS Community about the Library in the Life of the User." The Library Quarterly, vol. 73, no. 4, 2003. pp. 369-82.
- Williams, Raymond. Keywords: A Vocabulary of Culture and Society. Oxford UP, 1976.
Thank You!


Sep. 24, 2020 · 5 min read
Learn how you can move faster and focus on the things that matter by using incident analysis as your secret weapon. Operating at speed and at scale tests the capabilities of even the most experienced engineering teams. In this software world, it is inevitable that things will break. When they do, what do you do? Pick up the pieces and carry on? What if that’s not enough? Learning from incidents has taught us that broken things can lead to powerful opportunities, but only when we’re looking at them through the right lens.
Aug. 17, 2020 · 17 min read
Think about your team for a moment. How well is it functioning? Are you currently on a high-performing team, having found your groove and flow state as a group? Are you on a team that isn’t quite in that magical state of being yet, but it feels like you’re on your way? Are you feeling some friction—frustration, confusion—with your team? Or have you just joined a new team, so none of these apply yet?
Jul. 14, 2020 · 2 min read
Jun. 25, 2020 · 6 min read
Breaking things on purpose. Chaos Engineering is the facilitation of experiments to uncover systemic weakness. Chaos Engineering is the discipline of experimenting on a system in order to build confidence in the system’s capability to withstand turbulent conditions in production. Performance Improvement = Errors ↓ + Insights ↑
May. 14, 2020 · 12 min read
Team Topologies provides four fundamental team types – stream-aligned, platform, enabling, and complicated-subsystem – and three core team interaction modes – collaboration, X-as-a-Service, and facilitating. Together with awareness of Conway’s law, team cognitive load, and how to become a sensing organization, Team Topologies results in an effective and humanistic approach to building and running software systems.
Nov. 8, 2019 · 3 min read
We grumble that there just aren’t enough hours in the day and that someone else sure seems to have a lot of free time. But we regular mortals only have twenty-four hours in a day. The problem is that we don’t protect our hours from being stolen. We allow thieves to steal time from us, day after day after day. Who are these thieves of time?
Oct. 30, 2019 · 3 min read
Resilience is something a system does, not what a system has; creating and sustaining ‘adaptive capacity’ within an organisation (while being unable to justify doing it specifically) is resilient action; and learning about how people cope with surprise is the path to finding sources of resilience.
Sep. 27, 2019 · 4 min read
So how do we do remote work right? It takes much more than the half-hearted “you’re allowed to work from home” policy you see at companies nowadays. Remote-first means working remote is the default. It means making sure your remote employees are as much a part of the team as those in the office.
Aug. 5, 2019 · 6 min read
Achieve excellence, don’t just avoid errors. Build trust and take care of your people. Use your legacy for inspiration. Use guiding principles for decision criteria. Use immediate recognition to reinforce desired behaviors. Begin with the end in mind. Encourage a questioning attitude over blind obedience
Jan. 21, 2019 · 1 min read
How do you avoid killing something too early, or celebrating too early.
Sep. 26, 2016 · 10 min read
A just culture balances the need for an open and honest reporting environment with the end of a quality learning environment and culture. While the organization has a duty and responsibility to employees (and ultimately to patients), all employees are held responsible for the quality of their choices. Just culture requires a change in focus from errors and outcomes to system design and management of the behavioral choices of all employees.
Sep. 26, 2016 · 1 min read
Jan. 1, 1970 · 0 min read


List of Cargos
Book new cargo
Tracking Id
Origin
Destination
Arrival deadline
Routing status
Transport status
Delivery status


Click to learn more
Hang Man Game
Psychic-Game
Gem-Hunter
Trivia Game
Pokemon Gif-Tastic
Train-Scheduler
LIRI-Bot App
BAmazon-Shopping
Friend-Finder
Sequelize-Game Organizer
Event Spotter
Shout
Tech-News Scraper
Video Game Organizer
Clicky Game
Constructor Word Guess
Dashboard
NYT Article Search


To share code between Python projects, you can create library projects in the Library
directory in to the directory you ran lean init
in.
If you have a Library/Logging
project with a functions.py
file, you can import all its members in any other Python project using from Logging.functions import *
.
Follow these steps to create a new library project:
lean init
in.lean create-project --language python "Library/MyLibrary"
to create a new library project named "MyLibrary".
$ lean create-project --language python "Library/MyLibrary" Successfully created Python project 'Library/MyLibrary'
from MyLibrary.<file name without extension> import <member name>
in any other Python project.


Situational Awareness for Novel Epidemic Response - Local Development build (v0.1.0). See the Directory of published versions
Contents:
This page provides a list of the FHIR artifacts defined as part of this implementation guide.
These define constraints on FHIR resources that need to be complied with by conformant implementations
| Audit Event Write Profile | Defines constraints on the AuditEvent Resource to record when a resource has been written. |
| Audit Event Read | Defines constraints on the AuditEvent Resource to record when a record has been accessed. |
| Saner Public Health Measure | Profile Saner Public Health Measure The Public Health Measure Profile ensures that Measures are very well defined as an aid to automation of measures. These are developed by The Saner Project team to ensure that the measure is well understood and computation of it can be automated from systems that have the measure data. |
| Saner Public Health Measure Report | Profile Saner Public Health Measure Report The Public Health Measure Report Profile ensures that MeasureReports conforms to the minimal content required to properly interpret a report of a Public Health Measure. |
| Saner Public Health Measure Stratifier | Profile Saner Public Health Measure Stratifier A stratifier is effecitively a mixin that can be used with an existing measure to add stratification detail to that measure. |
| Resource Location Profile | Defines constraints on the Location Resource describing the location of resources (Beds and Devices). |
| Supporting Device Profile | Defines constraints on the Device Resource for data communicating about supporting devices. |
These define constraints on FHIR data types that need to be complied with by conformant implementations
| MeasureCriteria | Constraints on documentation for the evaluation of a Measure |
| Saner Measured Item Description | A CodeableConcept describing the item to be counted in terms of the type of FHIR Resource to count, and subtype of item identified by that resource |
| Precise Date Time | A dateTime value that contains seconds and a timezone |
These define constraints on FHIR data types that need to be complied with by conformant implementations
| Extension Attributes to associate with a Location Reference to simplify Geographic search | This is essentially a database denormalization that facilitates search by Geographics coordinates on a location. It enables a FHIR Server to implement search on a MeasureReport by GeoLocation using an extension. The extension is purposefully designed to duplicate the existing [FHIR GeoLocation Extension](http://hl7.org/fhir/StructureDefinition/geolocation) in the hope that it could eventually be absorbed by that extension. |
| Attributes describing a group of measures | Attributes describing the group of measures |
| Alternate criteria for performing a measure | Provides Alternate criteria for performing a measure, (e.g., CQL, Drules, et cetera) |
These define sets of codes used by systems conforming with this implementation guide
| Bed Location Operational Status | This Value Set is used to indicate whether a bed is in use (O), available for use (U), or not available (C) for use. |
| Location Types | Codes used to locations |
| Bed Property | This value set describes other properties of a bed, such as the ability to support isolation. |
| Bed Type | This Value Set describes the types of care services that a bed can support. |
| C19HCC Confirmed COVID19 Infection | **Purpose:** Clinical Focus: This value set contains conditions associated with a confirmed diagnosis of COVID-19. Data Element Scope: Used to identify patients with a confirmed COVID-19 infection. Inclusion Criteria: Conditions associated with confirmed COVID-19 infection, including laboratory-confirmed COVID (symptomic or asymptomatic). Exclusion Criteria: Suspected, possible or probable COVID-19, or possible exposure to COVID-19 without a definitive COVID-19 diagnosis. |
| C19HCC Hydroxychloroquine | **Purpose:** Clinical Focus: This value set contains branded and non-branded hydroxychloroquine medications. Data Element Scope: Used to identify patients who had hydroxychloroquine as an active medication on their medication list or who were administered hydroxychloroquine during a hospitalization. Inclusion Criteria: Branded and non-branded medications with hydroxychloroquine as an ingredient. RxNorm term types: SCD\/GPCK, SBD\/BPCK, SCDG, BCDG, SCDC, BCDC, IN, PIN, BN. Exclusion Criteria: none |
| C19HCC SARSCoV2 Exposure | **Purpose:** Clinical Focus: This value set contains conditions indicating the patient may have been exposed to SARS-CoV-2. Data Element Scope: To identify patients exposed or with a suspicion of exposure to SARS-CoV-2, whether associated with a suspicion of COVID-19 infection or not. Inclusion Criteria: Conditions indicative of possible exposure to SARS-CoV-2. Exclusion Criteria: : Conditions representing suspicion or confirmation of COVID-19. |
| C19HCC Suspected COVID19 Infection | **Purpose:** Clinical Focus: Conditions indicative of a possible COVID-19 infection but no definitive COVID-19 diagnosis. Data Element Scope: Used to identify patients suspected to have COVID-19. Inclusion Criteria: Includes conditions indicative of a possible COVID-19 diagnosis. Exclusion Criteria: Conditions associated with a confirmed COVID-19 infection. |
| COVID-19 Diagnostic Test | Codes for COVID-19 Diagnostic Tests |
| Confirmed COVID-19 Diagnosis | Codes confirming COVID-19 Diagnostic Test Result |
| Confirmed COVID-19 Diagnosis Values | Codes for result values confirming COVID-19 Diagnostic Test Result |
| Device Resource Field Names | Field names in the Device Resource |
| ED or Overflow Locations | Codes used for ED or Overflow locations |
| Resource Fields | This value set describes fields used to stratify groups in a report |
| Measure Groups | Measure Groups defined by the SANER Project |
| ICU Locations | Codes used for ICU locations |
| Inpatient Locations | Codes used for inpatient locations |
| Location Resource Field Names | Field names in the Location Resource |
| Rate Aggregation Value Set | This Value Set Identifies methods of rate aggregation |
| Measure Status Values | Allowed Status Values for Saner Measures |
| Occupied Bed | Codes used Occupied Beds |
| Patient Died | Codes used to identify that a patient has died |
| Measure Populations | Measure Populations defined by The SANER Project |
| Suspected Or Diagnosed COVID-19 | Coded identifying suspected or confirmed COVID-19 |
| Ventilator Devices | Codes used for Ventilator Devices |
| Devices used for Ventilation with Tracheostomy | Codes used for Devices that support Ventilation with a Tracheostomy |
These define new code systems used by systems conforming with this implementation guide
| Saner Bed Type Coding System | This Coding System fills gaps describing types of care services that a bed can support. |
| Device Resource Field Names | This Coding System identifies legal field names in a FHIR R4 Device Resource. |
| Group System | A Code System for Groups defined by The SANER Project |
| Location Resource Field Names | This Coding System identifies legal field names in a FHIR R4 Location Resource. |
| Rate Aggregation Coding System | This Coding System Identifies methods of rate aggregation |
| Population System | A Code System for Populations defined by The SANER Project |
These are example instances that show what data produced and consumed by systems conforming with this implementation guide might look like
| CDC Patient Impact and Hospital Capacity | This measure demonstrates reporting on bed availability and use at a facility location based on CDC/NHSN reporting requirements. |
| ExampleNJ-20200404-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/04/2020 |
| ExampleNJ-20200404-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/04/2020 |
| ExampleNJ-20200405-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/05/2020 |
| ExampleNJ-20200405-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/05/2020 |
| ExampleNJ-20200406-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/06/2020 |
| ExampleNJ-20200406-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/06/2020 |
| ExampleNJ-20200407-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/07/2020 |
| ExampleNJ-20200407-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/07/2020 |
| ExampleNJ-20200408-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/08/2020 |
| ExampleNJ-20200408-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/08/2020 |
| ExampleNJ-20200409-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/09/2020 |
| ExampleNJ-20200409-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/09/2020 |
| ExampleNJ-20200410-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/10/2020 |
| ExampleNJ-20200410-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/10/2020 |
| ExampleNJ-20200411-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/11/2020 |
| ExampleNJ-20200411-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/11/2020 |
| ExampleNJ-20200412-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/12/2020 |
| ExampleNJ-20200412-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/12/2020 |
| ExampleNJ-20200413-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/13/2020 |
| ExampleNJ-20200413-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/13/2020 |
| ExampleNJ-20200414-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/14/2020 |
| ExampleNJ-20200414-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/14/2020 |
| ExampleNJ-20200415-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/15/2020 |
| ExampleNJ-20200415-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/15/2020 |
| ExampleNJ-20200416-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/16/2020 |
| ExampleNJ-20200416-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/16/2020 |
| ExampleNJ-20200417-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/17/2020 |
| ExampleNJ-20200417-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/17/2020 |
| ExampleNJ-20200418-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/18/2020 |
| ExampleNJ-20200418-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/18/2020 |
| ExampleNJ-20200419-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/19/2020 |
| ExampleNJ-20200419-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/19/2020 |
| ExampleNJ-20200420-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/20/2020 |
| ExampleNJ-20200420-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/20/2020 |
| ExampleNJ-20200421-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/21/2020 |
| ExampleNJ-20200421-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/21/2020 |
| ExampleNJ-20200422-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/22/2020 |
| ExampleNJ-20200422-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/22/2020 |
| ExampleNJ-20200423-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/23/2020 |
| ExampleNJ-20200423-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/23/2020 |
| ExampleNJ-20200424-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/24/2020 |
| ExampleNJ-20200424-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/24/2020 |
| ExampleNJ-20200425-CDCPatientImpactAndHospitalCapacity | Example MeasureReport of CDCPatientImpactAndHospitalCapacity for NJ on 04/25/2020 |
| ExampleNJ-20200425-FEMADailyHospitalCOVID19Reporting | Example MeasureReport of FEMADailyHospitalCOVID19Reporting for NJ on 04/25/2020 |
| FEMA Laboratory Orders and Results Daily Increase Reporting | This measure demonstrates reporting about Daily Laboratory Testing at a inpatient test sites capturing laboratory orders and results daily increase and cumulative counts. |
| HAvBED2 to FHIR Concept Map | This Concept Map provides mappings from terms used in the HAvBED2 specification to HL7 FHIR |
| NJ-DPH | Example Organization for the New Jersey Department of Public Health |
| states-NJ | Example Location for the State of New Jersey |


Italy (Italian: Italia [iˈtaːlja] (About this sound listen)), officially the Italian Republic (Italian: Repubblica italiana),[7][8][9][10] is a unitary parliamentary republic in Europe.[note 1] Located in the heart of the Mediterranean Sea, Italy shares open land borders with France, Switzerland, Austria, Slovenia, San Marino and Vatican City. Italy covers an area of 301,338 km2 (116,347 sq mi) and has a largely temperate seasonal and Mediterranean climate. Due to its shape, it is often referred to in Italy as lo Stivale (the Boot).[11][12] With 61 million inhabitants it is the fourth most populous EU member state.
The most popular sport in Italy is, by far, football.[275] Italy's national football team (nicknamed Gli Azzurri – "the Blues") is one of the world's most successful team as it has won four FIFA World Cups (1934, 1938, 1982 and 2006).[276] Italian clubs have won 48 major European trophies, making Italy the second most successful country in European football. Italy's top-flight club football league is named Serie A and ranks as the fourth best in Europe and is followed by millions of fans around the world. Starting in 1909, the Giro d'Italia is the second oldest of the prestigious Grands Tours[277] Other popular team sports in Italy include volleyball, basketball and rugby. Italy's male and female national teams are often featured among the world's best. The Italian national basketball team's best results were gold at Eurobasket 1983 and EuroBasket 1999, as well as silver at the Olympics in 2004. Lega Basket Serie A is widely considered one of the most competitive in Europe. Rugby union enjoys a good level of popularity, especially in the north of the country. Italy's national team competes in the Six Nations Championship, and is a regular at the Rugby World Cup. Italy ranks as a tier-one nation by World Rugby. Italy men's national volleyball team winning three World Championships in a row 1990, 1994 and 1998 an three silver medal in Olympics 1996, 2004, 2016. ..


Login to your account
In order to use the editing and rating capabilities of TMDb, as well as get personal recommendations you will need to login to your account. If you do not have an account, registering for an account is free and simple. Click here to get started.
If you signed up but didn't get your verification email, click here to have it resent.
<% if $hError: <%= $h


{% extends 'fyh_emails/base.html' %} {% block content %}
A student posted a new question for {{ name }} on Hub@Penn:
As a member of {{ name }}, you are able to respond to this question. You can do so using the button below.
Provide an answer {% endblock %}


X Factor: Celebrity's Thom Evans dodges questions about 'romance' with Nicole Scherzinger on Loose Women
He tried to dodge the questions
by Rebecca CarterThom Evans dodged questions about his reported romance with Nicole Scherzinger on today's Loose Women.
Earlier this month, it was claimed the pair had enjoyed a romantic evening with each other in London with a source saying X Factor: Celebrity Thom was "smitten early on".
The rugby player was grilled on the rumours on today's Loose Women and he remained very coy.
Read more: Nicole Scherzinger 'secretly dating X Factor: Celebrity star Thom Evans'
While discussing the talent show, Jane Moore asked: "Thom I've been reading the papers and there's been a little bit of extra frisk on with you... Nicole."
His bandmates Ben Foden and Levi Davis waved their hands and said: "Ooooh."
Thom said: "Look Nicole is lovely and I... uh... I've been focusing on the programme and the finals."
Rubbing Thom's shoulder, stand-in host Rochelle Humes said: "Really good job there," as the panel and audience laughed.
Jane asked: "What about after the finals when it's all done?"
Levi joked: "Then we'll be focusing on the music industry," as Thom said: " Yeah. I mean who wouldn't want to date Nicole, she's lovely..."
Ben cut in: "Who wouldn't to date Thom, he's lovely," to which Thom joked: "I actually paid Ben to say that."
It comes after an insider spilled details of Thom and Nicole's reported romance.
The insider told The Sun: "Thom is completely Nicole’s type. And for his part, Thom was smitten early on - he’s always said Nicole is one of the most beautiful women in the world.
"He fancied her long before meeting her on the show. He was initially a bit nervous about starting something up, and ruining his chances on the series, but they had great chemistry from the off.
Read more: X Factor: Celebrity fans slam Nicole Scherzinger for 'motorboating' Louis Walsh
"And after weeks of texting, Thom finally plucked up the courage to ask her out, and took her for dinner."
The source also claimed they met up with friends and were laughing and joking throughout the evening.
However, the pair apparently want to both focus on the series for now and then "see what may or may not progress once the show has wrapped".
Thom has previously dated Kelly Brook and 90210 actress Jessica Lowndes.

Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think of this story.


Sign up in less than 30 seconds. Try out our 7 day risk free trial, upgrade at anytime, no questions, no hassle.
Sign up today
Cras sodales lobortis erat
Vitae pellentesque diam


This is a Population Map of Kentucky Counties created using D3.js, a Census 2010 Shapefile and GDAL (for geospatial data processing), inspired by the American Community Survey Handbook.
It’s really easy to create a map using D3.js. You just need a GeoJSON file and you’re done. Having said that you have to have a minimum skillset to process the data and a bit of experience on map projections:
var projection = d3.geo.mercator()
.scale(29100)
.translate([7310, 3500]);
var path = d3.geo.path()
.projection(projection);
svg.append("g")
.attr("id", "counties")
.selectAll("path")
.data(counties.features)
.enter().append("path")
.attr("d", path);
Census Geospatial Data and GeoJSON
D3.js uses the GeoJSON format to display maps. GeoJSON supports a variety of geographic data structures like Points, LineStrings and Polygons, and aditional properties like strings and numbers.
The Census Bureau has made available all the Geospatial data through the TIGER Shapefiles. And all you need to create a map is in these Shapefiles. Each zipped shapefile has the following files:
- .shp the feature geometry
- .shx the index of the feature geometry
- .dbf the tabular attribute information
- .prj the coordinate system information
And in order to use the Census geographic data with D3.js you have to convert it to GeoJSON first.
Tools of the Trade
Data Processing
When you’re dealing with Geospatial data you need a tool to explore it and convert it to other formats. GDAL is shipped with two great tools to do this job: ogrinfo
and ogr2ogr
.
ogrinfo is very useful to explore Shapefiles:
ogrinfo -so gz_2010_us_050_00_20m.shp gz_2010_us_050_00_20m
Layer name: gz_2010_us_050_00_20m
Geometry: Polygon
Feature Count: 3221
Extent: (-179.147340, 17.884813) - (179.778470, 71.352561)
Layer SRS WKT:
GEOGCS["GCS_North_American_1983",
DATUM["North_American_Datum_1983",
SPHEROID["GRS_1980",6378137,298.257222101]],
PRIMEM["Greenwich",0],
UNIT["Degree",0.017453292519943295]]
GEO_ID: String (60.0)
STATE: String (2.0)
COUNTY: String (3.0)
NAME: String (90.0)
LSAD: String (7.0)
CENSUSAREA: Real (31.15)
So in that Geospatial file we have the boundaries of 3221 counties. But in this case we just need a map of Kentucky:
ogrinfo -so gz_2010_us_050_00_20m.shp gz_2010_us_050_00_20m -where 'STATE="21"'
GDAL also supports SQL language:
ogrinfo -al gz_2010_us_050_00_20m.shp /
-sql 'SELECT * FROM gz_2010_us_050_00_20m where STATE="21"'
Since we now know what we want and how to get it we’re ready to generate our GeoJSON file using ogr2ogr:
ogr2ogr -f geoJSON KY-counties.json -where 'STATE="21"' gz_2010_us_050_00_20m.shp
Visualization
Well now we have to visualize the data on the map so I’ve chosen the Choropleth map visualization to represent the population for each county. When it comes to styles D3.js is quite straightforward. First define the classes styles:
.tier-1 { fill:rgb(229, 245, 224); }
.tier-2 { fill:rgb(161, 217, 155); }
.tier-3 { fill:rgb(49, 163, 84); }
Then assign the right class to each node:
svg.append("g")
.attr("id", "counties")
.selectAll("path")
.data(counties.features)
.enter().append("path")
.attr("d", path)
.attr("class", function (d) {}); // return the right class
Further Reading
- Census Bureau Data Visualization Gallery (without D3.js): http://www.census.gov/dataviz/
- Unemployment rates in US (2008): http://bl.ocks.org/mbostock/4060606
- US Airports Interactive Map: http://mbostock.github.com/d3/talk/20111116/airports.html


ICAP is envisioned to be a one year program which will provide nixbees to impart the necessary skill set to the students and get them more credible in the way the industry/corporate imagines, thereby increasing the chances of smart employability and Entrepreneurship.
Find Out MoreIndustry Competence Amplification Program (ICAP),
will be a joint collaboration between the Host College and nixbees
Setup faculties and infrastructure, staff the development center and establish knowledge transfer.
Program management, development, maintenance, enhancement, complete support process expertise.
Enhanced knowledge sharing, collaboration opportunities, smart employability and Entrepreneurship.
Ready to start your next project with us? Give us a call or send us an email and we will get back to you as soon as possible!