After experimenting with DXM several times, and smoking weed for a while, I came across some Hydrocodone pills. I did some research online about the effects and decided on an appropriate first time dosage. I decided on on 20mg.
T+0:00(8:40PM) - Took four 'M357' 5/500 Hydrocodone pills. Ate earlier, around 5. Took the pills with a cold glass of water and split each pill in half, then swallowed the eight halves with a lot of water.
T+0:15(8:55PM) - Having a hard time telling if I feel the pills or not. The only thing that indicates I may be is that typing this is semi-difficult, more than usual. I'm typing rather slow compared to how I usually do, and I'm having to backspace to fix a lot of mistakes, which is out of the ordinary. I shared in smoking two blunts and took three or four waterfalls earlier in the day, as well as having three beers. That was from around noon to 4:00PM. That might be one of the contributing factors to the feeling, but at the same time I sense something new that's been added. I'm guessing that's the Hydrocodone.
T+0:35(9:15PM) - Not really feeling much 'climbing'. Earlier effects may have been placebo, I'm thinking that maybe the fact I have food in my stomach is delaying the onset of the the Hydrocodone. Hoping I've got some more effect coming. Also, my back still hurts from sitting on my bed against a wall, which makes me think the Acetaminophen in the pill hasn't hit yet.
T+0:45(9:25PM) - Think I'm feeling it now! Pain in my back and headache are fading away, probably due to the Acetaminophen. Also I'm really happy, and I got super excited when 'Love' by G. Love and Special Came on. I'm talking to friends online, and I feel really social and just happy to be talking with people. So far I'm really enjoying myself.
T+1:15(9:55PM) - Feeling good! I haven't noticed any of the visual/body effects that some people have mentioned, I'm not sure why. Maybe those only come with higher dosages. But I definitely am feeling very social and consistently happy - smiling comes easily and often. I've been discussing all kinds of things at length with a friend of mine. I feel motivated to go through with plans, one of which is restarting a website I had from a long time ago, but this time with the help of a friend. Overall, I don't feel 'high' really. When I stand up, I don't feel any noticeable loss of coordination like I do when on DXM. Movement seems a little slower, more fluid. The strongest effect of the Hydrocodone seems to be on my mood and mindset, both of which are very positive!
T+1:30(10:10PM) - Feelings of euphoria sweeping over me. I'm listening to uplifting music, chatting with friends and parents, and everything is just beautiful. This is sort of a side note, but in my state it seems significant. I'm sitting here in my room and chatting with my parents on and off, and like I said earlier, I'm listening to G. Love and Special Sauce. For the first time ever, they caught on and said they liked it, and I even burned my dad a copy of the album, which is a first! Enough rambling about that I guess, bottom line is I feel great. As far as physical effects, my body feels sort of warm, and I feel very comfortable in my bed. This is another really great feeling that is definitely enhancing the experience.
T+2:05(10:55PM) - This is definitely one of most socially enhancing substances I've experienced. Words and social connections come easily. Good memories flood back, as well as blissful nostalgia. I think I may have passed the peak by now - but I'm in another great phase of this experience. Earlier I was in more of a 'zoned out' euphoria type of mood, and now I'm feeling very deep and social. All of the stages I've passed through have been enjoyable, and each have had unique and positive qualities.
T+2:30(11:20PM) - Still feeling wonderful and happy - I have the feeling that this mood will be established for a while, not only from the pills but from the constant thoughts of optimism, family, memories, and all the other good things that have been flowing through me for the past few hours. The peak is passed, and I'm coming down lightly and smoothly. I'm bad at estimating baseline, but it feels like if it's probably in the near future. This has been great.
My thoughts on Hydrocodone and the experience:
This has been really great - Hydrocodone is an uplifting, socially-enabling, euphoric drug. I definitely see the potential for addiction, and plan on exercising the proper caution with it in the future. Music is a great companion to Hydrocodone. I began with relaxing music (G. Love), and recently proceeded to constructing a 'classics' playlist with all the songs I could think of that bring up great feelings and memories for both me and my family. The enjoyment of favorite songs and the connected memories has been a truly enjoyable journey through memory lane and beyond.
I'm sure I'll experience Hydrocodone again in the future, within reason.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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| Interface Summary | |
| JavaUtils.ConvertCache | It the argument to the convert(...) method implements the ConvertCache interface, the convert(...) method will use the set/get methods to store and retrieve converted values. |
| ParserControl | ParserControl is used to control particular behaviour of the parser. |
| Class Summary | |
| Admin | Handy static utility functions for turning XML into Axis deployment operations. |
| BeanPropertyDescriptor | This class represents a field/property in a value type (a class with either bean-style getters/setters or public fields). |
| BeanUtils | |
| CLArgsParser | Parser for command line arguments. |
| ClassUtils | Utility methods for Class Loading. |
| CLOption | Basic class describing an instance of option. |
| CLOptionDescriptor | Basic class describing an type of option. |
| CLUtil | CLUtil offers basic utility operations for use both internal and external to package. |
| DefaultAuthenticator | This class is used by WSDL2javaAntTask and WSDL2. |
| DefaultEntityResolver | |
| DOM2Writer | This class is a utility to serialize a DOM node as XML. |
| FieldPropertyDescriptor | |
| IdentityHashMap | IdentityHashMap similar to JDK1.4's java.util.IdentityHashMap |
| IDKey | Wrap an identity key (System.identityHashCode()) |
| JavaUtils | Utility class to deal with Java language related issues, such as type conversions. |
| JWSClassLoader | Class loader for JWS files. |
| LockableHashtable | This subclass of the java Hashtable allows individual entries to be "locked" so that their values cannot be overwritten or removed. |
| Mapping | |
| Messages | |
| NSStack | The abstraction this class provides is a push down stack of variable length frames of prefix to namespace mappings. |
| Options | |
| SessionUtils | Code borrowed from AuthenticatorBase.java for generating a secure id's. |
| tcpmon | TCP monitor to log http messages and responses, both SOAP and plain HTTP. |
| URLHashSet | Class URLHashSet |
| WSDLUtils | |
| XMLChar | This class defines the basic XML character properties. |
| XMLUtils | |
| XMLUtils.ParserErrorHandler |
| Exception Summary | |
| JavaUtils.HolderException |
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my_maps
infos
- A right click (tap and hold on mobile) will display information about the current location.
- A short click (tap on mobile) on a map feature will select the feature and show more information.
## -*- coding: utf-8 -*- <% settings = request.registry.settings proxy_wms_url = settings.get('proxy_wms_url') node_modules_path = settings.get('node_modules_path') closure_library_path = settings.get('closure_library_path') exclude_theme_layer_search = settings.get('exclude_theme_layer_search') authtkt_cookie_name = settings.get('authtkt_cookie_name') overview_map_show = settings.get('overview_map')['show'] overview_map_base_layer = settings.get('overview_map')['base_layer'] %>\


Tesla cybertruck orders near 150,000 just days after chaotic launch
Los Angeles, Tesla's new electric pickup truck has secured almost 150,000 orders, the company's chief executive Elon Musk boasted on Twitter, just two days after its big reveal went embarrassingly wrong.
The billionaire Tesla co-founder floundered on stage in California on Thursday when the vehicle's armored glass windows cracked in a demonstration intended to prove their indestructible design.
Shares in the company plunged 6.1 percent following the truck's bumpy launch and several lackluster reviews.
But on Saturday Musk tweeted that Tesla had already received 146,000 orders from prospective owners.
"146k Cybertruck orders so far, with 42% choosing dual, 41% tri & 17% single motor," he wrote.
The demand comes despite the product receiving "no advertising & no paid endorsement".
The industrial-looking Cybertruck is covered in the same steel alloy Musk plans to use for his SpaceX Starship rocket and will be able to go from 0 to 100 kilometers (62 miles) per hour in about three seconds, the Tesla chief executive claimed in his presentation.
He said the entry-level model will have a starting price of $39,900 and a 400-kilometer (250-mile) range, while a deluxe option will be able to travel twice the distance and will sell for $69,900.
No date has been given for its release, but analysts said it would not be ready before the end of 2021 at the earliest.
Its space-age design is unlikely to challenge top-selling models by Ford and other conventional car companies, analysts warn.
Read also
Read More
2020 flagship iPhones may have 6GB RAM
The iPhone maker is also planning to launch an affordable smartphone iPhone SE 2, with production reportedly slated to start in February.
 OK, boomer
Tesla Inc.’s much-anticipated Cybertruck concept vehicle received an underwhelming reception from many investors and some of the automotive trade press due to its polarizing design and lack of typical pickup features. They may just be the wrong audience.


Perrie Edwards & Jade Thirlwall Rep Little Mix at BBC Teen Awards 2019
Perrie Edwards and Jade Thirlwall step out in coordinating black outfits for the 2019 BBC Radio 1 Teen Awards on Sunday (November 24) in London, England.
The two Little Mix singers were joined by twin musicians Max & Harvey, and “Young” singer Ella Henderson.
PHOTOS: Check out the latest pics of Little Mix
Earlier this morning, Little Mix made the big announcement that they’ll be heading back out on tour in Summer 2020!
“… Because we can’t get enough of you guys, we’re so excited to announce the #Summer2020Tour is coming!! 😝 Tickets go on sale at 9AM this Thursday 😍” the band wrote, with all the dates listed.
Check out their announcement below!


Binding Component Values and Instances to Managed Bean Properties
A component tag can wire its data to a managed bean by one of the following methods:
To bind a component’s value to a managed bean property, a component tag’s value attribute uses a EL value expression. To bind a component instance to a bean property, a component tag’s binding attribute uses a value expression.
When a component instance is bound to a managed bean property, the property holds the component’s local value. Conversely, when a component’s value is bound to a managed bean property, the property holds the value stored in the managed bean. This value is updated with the local value during the Update Model Values phase of the lifecycle. There are advantages to both of these methods.
Binding a component instance to a bean property has these advantages:
The managed bean can programmatically modify component attributes.
The managed bean can instantiate components rather than let the page author do so.
Binding a component’s value to a bean property has these advantages:
The page author has more control over the component attributes.
The managed bean has no dependencies on the JavaServer Faces API (such as the component classes), allowing for greater separation of the presentation layer from the model layer.
The JavaServer Faces implementation can perform conversions on the data based on the type of the bean property without the developer needing to apply a converter.
In most situations, you will bind a component’s value rather than its instance to a bean property. You’ll need to use a component binding only when you need to change one of the component’s attributes dynamically. For example, if an application renders a component only under certain conditions, it can set the component’s rendered property accordingly by accessing the property to which the component is bound.
When referencing the property using the component tag’s value attribute, you need to use the proper syntax. For example, suppose a managed bean called MyBean has this int property:
protected int currentOption = null; public int getCurrentOption(){...} public void setCurrentOption(int option){...}
The value attribute that references this property must have this value-binding expression:
#{myBean.currentOption}
In addition to binding a component’s value to a bean property, the value attribute can specify a literal value or can map the component’s data to any primitive (such as int), structure (such as an array), or collection (such as a list), independent of a JavaBeans component. Table 13-3 lists some example value-binding expressions that you can use with the value attribute.
Value |
Expression |
|---|---|
A Boolean |
cart.numberOfItems > 0 |
A property initialized from a context init parameter |
initParam.quantity |
A bean property |
cashierBean.name |
Value in an array |
books[3] |
Value in a collection |
books["fiction"] |
Property of an object in an array of objects |
books[3].price |
The next two sections explain how to use the value attribute to bind a component’s value to a bean property or other data objects, and how to use the binding attribute to bind a component instance to a bean property.
Binding a Component Value to a Property
To bind a component’s value to a managed bean property, you specify the name of the bean and the property using the value attribute.
This means that the first part of the EL value expression must match the name of the managed bean up to the first period (.) and the part of the value expression after the period must match the property of the managed bean.
For example, in the Duke's Bookstore case study, the h:dataTable tag in bookcatalog.xhtml sets the value of the component to the value of the books property of the stateless session bean BookRequestBean:
<h:dataTable id="books" value="#{bookRequestBean.books}" var="book" headerClass="list-header" styleClass="list-background" rowClasses="list-row-even, list-row-odd" border="1" summary="#{bundle.BookCatalog}" >
The value is obtained by calling the bean's getBooks method.
If you use the application configuration resource file to configure managed beans instead of defining them in managed bean classes, the name of the bean in the value expression must match the managed-bean-name element of the managed bean declaration up to the first period (.) in the expression. Similarly, the part of the value expression after the period must match the name specified in the corresponding property-name element in the application configuration resource file.
For example, consider this managed bean configuration, which configures the ImageArea bean corresponding to the top left book in the image map on the index.html page of the Duke's Bookstore case study:
<managed-bean eager="true"> ... <managed-bean-name> Book201 </managed-bean-name> <managed-bean-class> dukesbookstore.model.ImageArea </managed-bean-class> <managed-bean-scope> application </managed-bean-scope> <managed-property> ... <property-name>shape</property-name> <value>rect</value> </managed-property> <managed-property> ... <property-name>alt</property-name> <value>Duke</value> </managed-property> ...
This example configures a bean called Book201, which has several properties, one of which is called shape.
Although the bookstore:area tags on the index.xhtml page do not bind to an ImageArea property (they bind to the bean itself), you could refer to the property using a value expression from the value attribute of the component's tag:
<h:outputText value="#{Book201.shape}" />
See Configuring Managed Beans for information on how to configure beans in the application configuration resource file.
Binding a Component Value to an Implicit Object
One external data source that a value attribute can refer to is an implicit object.
The bookreceipt.xhtml page of the Duke's Bookstore case study has a reference to an implicit object:
<h:outputFormat title="thanks" value="#{bundle.ThankYouParam}"> <f:param value="#{sessionScope.name}"/> </h:outputFormat>
This tag gets the name of the customer from the session scope and inserts it into the parameterized message at the key ThankYouParam from the resource bundle. For example, if the name of the customer is Gwen Canigetit, this tag will render:
Thank you, Gwen Canigetit, for purchasing your books from us.
Retrieving values from other implicit objects is done in a similar way to the example shown in this section. Table 13-4 lists the implicit objects to which a value attribute can refer. All of the implicit objects, except for the scope objects, are read-only and therefore should not be used as a value for a UIInput component.
Implicit Object |
What It Is |
|---|---|
applicationScope |
A Map of the application scope attribute values, keyed by attribute name |
cookie |
A Map of the cookie values for the current request, keyed by cookie name |
facesContext |
The FacesContext instance for the current request |
header |
A Map of HTTP header values for the current request, keyed by header name |
headerValues |
A Map of String arrays containing all the header values for HTTP headers in the current request, keyed by header name |
initParam |
A Map of the context initialization parameters for this web application |
param |
A Map of the request parameters for this request, keyed by parameter name |
paramValues |
A Map of String arrays containing all the parameter values for request parameters in the current request, keyed by parameter name |
requestScope |
A Map of the request attributes for this request, keyed by attribute name |
sessionScope |
A Map of the session attributes for this request, keyed by attribute name |
view |
The root UIComponent in the current component tree stored in the FacesRequest for this request |
Binding a Component Instance to a Bean Property
A component instance can be bound to a bean property using a value expression with the binding attribute of the component’s tag. You usually bind a component instance rather than its value to a bean property if the bean must dynamically change the component’s attributes.
Here are two tags from the bookcashier.xhtml page that bind components to bean properties:
<h:selectBooleanCheckbox id="fanClub" rendered="false" binding="#{cashier.specialOffer}" /> <h:outputLabel for="fanClub" rendered="false" binding="#{cashier.specialOfferText}"> <h:outputText id="fanClubLabel" value="#{bundle.DukeFanClub}"/> </h:outputLabel>
The h:selectBooleanCheckbox tag renders a check box and binds the fanClub UISelectBoolean component to the specialOffer property of the cashier bean. The h:outputLabel tag binds the component representing the check box’s label to the specialOfferText property of the cashier bean. If the application's locale is English, the h:outputLabel tag renders:
I'd like to join the Duke Fan Club, free with my purchase of over $100
The rendered attributes of both tags are set to false, to prevent the check box and its label from being rendered. If the customer makes a large order and clicks the Submit button, the the submit method of CashierBean sets both components’ rendered properties to true, causing the check box and its label to be rendered.
These tags use component bindings rather than value bindings, because the managed bean must dynamically set the values of the components’ rendered properties.
If the tags were to use value bindings instead of component bindings, the managed bean would not have direct access to the components, and would therefore require additional code to access the components from the FacesContext instance to change the components’ rendered properties.
Writing Properties Bound to Component Instances explains how to write the bean properties bound to the example components.


summ_*()
vignettes/pdqr-04-summarize.Rmd
pdqr-04-summarize.Rmd
Concept of summary functions is to take one or more pdqr-function(s) and return a summary value (which shouldn’t necessarily be a number). Argument method
is used to choose function-specific algorithm of computation.
Note that some summary functions can accumulate pdqr approximation error (like summ_moment()
for example). For better precision increase number intervals for piecewise-linear density using either n
argument for density()
in new_*()
or n_grid
argument in as_*()
.
We will use the following distributions throughout this vignette:
my_beta <- as_d(dbeta, shape1 = 2, shape2 = 5)
my_norm <- as_d(dnorm, mean = 0.5)
my_beta_mix <- form_mix(list(my_beta, my_beta + 1))
Although they both are continuous, discrete distributions are also fully supported.
# Usage of `summ_center()`
summ_center(my_beta, method = "mean")
#> [1] 0.2857136
summ_center(my_beta, method = "median")
#> [1] 0.2644498
summ_center(my_beta, method = "mode")
#> [1] 0.2000014
# Usage of wrappers
summ_mean(my_beta)
#> [1] 0.2857136
summ_median(my_beta)
#> [1] 0.2644498
summ_mode(my_beta)
#> [1] 0.2000014
# `summ_mode()` can compute local modes instead of default global
summ_mode(my_beta_mix, method = "local")
#> [1] 0.2000014 1.2000014
# Usage of `summ_spread()`
summ_spread(my_beta, method = "sd")
#> [1] 0.1597178
summ_spread(my_beta, method = "var")
#> [1] 0.02550977
summ_spread(my_beta, method = "iqr")
#> [1] 0.2283162
summ_spread(my_beta, method = "mad")
#> [1] 0.1122417
summ_spread(my_beta, method = "range")
#> [1] 0.955573
# Usage of wrappers
summ_sd(my_beta)
#> [1] 0.1597178
summ_var(my_beta)
#> [1] 0.02550977
summ_iqr(my_beta)
#> [1] 0.2283162
summ_mad(my_beta)
#> [1] 0.1122417
summ_range(my_beta)
#> [1] 0.955573
summ_moment()
has extra arguments for controlling the nature of moment (which can be combined):
summ_moment(my_beta, order = 3)
#> [1] 0.0476182
summ_moment(my_beta, order = 3, central = TRUE)
#> [1] 0.002429287
summ_moment(my_beta, order = 3, standard = TRUE)
#> [1] 11.68727
summ_moment(my_beta, order = 3, absolute = TRUE)
#> [1] 0.0476182
There are wrappers for most common moments: skewness and kurtosis:
summ_skewness(my_beta)
#> [1] 0.596237
# This by default computes excess kurtosis
summ_kurtosis(my_beta)
#> [1] -0.1202127
# Use `excess = FALSE` to compute non-excess kurtotsis
summ_kurtosis(my_beta, excess = FALSE)
#> [1] 2.879787
summ_quantile(f, probs)
is essentially a more strict version of as_q(f)(probs)
:
summ_quantile(my_beta, probs = seq(0, 1, by = 0.25))
#> [1] 0.0000000 0.1611628 0.2644498 0.3894790 0.9555730
summ_entropy()
computes differential entropy (which can be negative) for “continuous” type pdqr-functions, and information entropy for “discrete”:
summ_entropy(my_beta)
#> [1] -0.4845421
summ_entropy(new_d(1:10, type = "discrete"))
#> [1] 2.302585
summ_entropy2()
computes entropy based summary of relation between a pair of distributions. There are two methods: default “relative” (for relative entropy which is Kullback-Leibler divergence) and “cross” (for cross-entropy). It handles different supports by using clip
(default exp(-20)
) value instead of 0 during log()
computation. Order of input does matter: summ_entropy2()
uses support of the first pdqr-function as integration/summation reference.
summ_entropy2(my_beta, my_norm)
#> [1] 1.439193
summ_entropy2(my_norm, my_beta)
#> [1] 11.61849
summ_entropy2(my_norm, my_beta, clip = exp(-10))
#> [1] 5.289639
summ_entropy2(my_beta, my_norm, method = "cross")
#> [1] 0.9546508
Distributions can be summarized with regions: union of closed intervals. Region is represented as data frame with rows representing intervals and two columns “left” and “right” with left and right interval edges respectively.
summ_interval()
summarizes input pdqr-function with single interval based on the desired coverage level supplied in argument level
. It has three methods:
level
that has minimum width.0.5*(1-level)
and 1 - 0.5*(1-level)
quantiles.level
’s critical value (computed from normal distribution). Corresponds to classical confidence interval of sample based on assumption of normality.
summ_interval(my_beta, level = 0.9, method = "minwidth")
#> left right
#> 1 0.03015543 0.5252921
summ_interval(my_beta, level = 0.9, method = "percentile")
#> left right
#> 1 0.06284986 0.5818016
summ_interval(my_beta, level = 0.9, method = "sigma")
#> left right
#> 1 0.02300124 0.548426
summ_hdr()
computes highest density region (HDR) of a distribution: set of intervals with the lowest total width among all sets with total probability not less than an input level
. With unimodal distribution it is essentially the same as summ_interval()
with “minwidth” method.
# Unimodal distribution
summ_hdr(my_beta, level = 0.9)
#> left right
#> 1 0.03013169 0.5253741
# Multimodal distribution
summ_hdr(my_beta_mix, level = 0.9)
#> left right
#> 1 0.03015315 0.5252785
#> 2 1.03015315 1.5252785
# Compare this to single interval of minimum width
summ_interval(my_beta_mix, level = 0.9, method = "minwidth")
#> left right
#> 1 0.05125316 1.448297
There is a region_*()
family of functions which helps working with them:
beta_mix_hdr <- summ_hdr(my_beta_mix, level = 0.9)
beta_mix_interval <- summ_interval(my_beta_mix, level = 0.9)
# Test if points are inside region
region_is_in(beta_mix_hdr, x = seq(0, 2, by = 0.5))
#> [1] FALSE TRUE FALSE TRUE FALSE
# Compute total probability of a region
region_prob(beta_mix_hdr, f = my_beta_mix)
#> [1] 0.899991
# Pdqr-function doesn't need to be the same as used for computing region
region_prob(beta_mix_hdr, f = my_norm)
#> [1] 0.336239
# Compute height of region: minimum value of d-function inside region
region_height(beta_mix_hdr, f = my_beta_mix)
#> [1] 0.400163
# Compute width of region: sum of interval widths
region_width(beta_mix_hdr)
#> [1] 0.9902507
# Compare widths with single interval
region_width(beta_mix_interval)
#> [1] 1.397043
# Draw region on existing plot
plot(my_beta_mix, main = "90% highest density region")
region_draw(beta_mix_hdr)
Function summ_distance()
takes two pdqr-functions and returns a distance between two distributions they represent. Many methods of computation are available. This might be useful for doing comparison statistical inference.
# Kolmogorov-Smirnov distance
summ_distance(my_beta, my_norm, method = "KS")
#> [1] 0.419766
# Total variation distance
summ_distance(my_beta, my_norm, method = "totvar")
#> [1] 0.730451
# Probability of one distribution being bigger than other, normalized to [0;1]
summ_distance(my_beta, my_norm, method = "compare")
#> [1] 0.1678761
# Wassertein distance: "average path density point should travel while
# transforming from one into another"
summ_distance(my_beta, my_norm, method = "wass")
#> [1] 0.6952109
# Cramer distance: integral of squared difference of p-functions
summ_distance(my_beta, my_norm, method = "cramer")
#> [1] 0.1719884
# "Align" distance: path length for which one of distribution should be "moved"
# towards the other so that they become "aligned" (probability of one being
# greater than the other is 0.5)
summ_distance(my_beta, my_norm, method = "align")
#> [1] 0.2147014
# "Entropy" distance: `KL(f, g) + KL(g, f)`, where `KL()` is Kullback-Leibler
# divergence. Usually should be used for distributions with same support, but
# works even if they are different (with big numerical penalty).
summ_distance(my_beta, my_norm, method = "entropy")
#> [1] 13.05768
Function summ_separation()
computes a threshold that optimally separates distributions represented by pair of input pdqr-functions. In other words, summ_separation()
solves a binary classification problem with one-dimensional linear classifier: values not more than some threshold are classified as one class, and more than threshold - as another. Order of input functions doesn’t matter.
summ_separation(my_beta, my_norm, method = "KS")
#> [1] 0.6175981
summ_separation(my_beta, my_norm, method = "F1")
#> [1] 0.007545242
Functions summ_classmetric()
and summ_classmetric_df()
compute metric(s) of classification setup, similar to one used in summ_separation()
. Here classifier threshold should be supplied and order of input matters. Classification is assumed to be done as follows: any x value not more than threshold value is classified as “negative”; if more - “positive”. Classification metrics are computed based on two pdqr-functions: f
, which represents the distribution of values which should be classified as “negative” (“true negative”), and g
- the same for “positive” (“true positive”).
# Many threshold values can be supplied
thres_vec <- seq(0, 1, by = 0.2)
summ_classmetric(f = my_beta, g = my_norm, threshold = thres_vec, method = "F1")
#> [1] 0.5138193 0.5436321 0.6089061 0.6131005 0.5522756 0.4715757
# In `summ_classmetric_df()` many methods can be supplied
summ_classmetric_df(
f = my_beta, g = my_norm, threshold = thres_vec, method = c("GM", "F1", "MCC")
)
#> threshold GM F1 MCC
#> 1 0.0 0.0000000 0.5138193 -0.42709306
#> 2 0.2 0.4614729 0.5436321 -0.03892981
#> 3 0.4 0.6433485 0.6089061 0.31475763
#> 4 0.6 0.6643221 0.6131005 0.48370132
#> 5 0.8 0.6176386 0.5522756 0.48316011
#> 6 1.0 0.5554612 0.4715757 0.42709306
With summ_roc()
and summ_rocauc()
one can compute data frame of ROC curve points and ROC AUC value respectively. There is also a roc_plot()
function for predefined plotting of ROC curve.
my_roc <- summ_roc(my_beta, my_norm)
head(my_roc)
#> threshold fpr tpr
#> 1 5.253425 0 0.000000e+00
#> 2 5.243918 0 4.811646e-08
#> 3 5.234412 0 9.845779e-08
#> 4 5.224905 0 1.511167e-07
#> 5 5.215398 0 2.061949e-07
#> 6 5.205891 0 2.637984e-07
summ_rocauc(my_beta, my_norm)
#> [1] 0.583938
roc_plot(my_roc)
‘pdqr’ has functions that can order set of distributions. They are summ_order()
, summ_sort()
, and summ_rank()
, which are analogues of order()
, sort()
, and rank()
respectively. They take a list of pdqr-functions as input, establish their ordering based on specified method, and return the desired output.
There are two sets of methods:
f
is greater than g
if and only if P(f >= g) > 0.5
, or in ‘pdqr’ code summ_prob_true(f >= g) > 0.5
. This method orders input based on this relation and order()
function. Notes:
order()
.summ_center()
: ordering of distributions is defined as ordering of corresponding measures of distribution’s center.
# Here the only clear "correct" ordering is that `a <= b`.
f_list <- list(a = my_beta, b = my_beta + 1, c = my_norm)
# Returns an integer vector representing a permutation which rearranges f_list
# in desired order
summ_order(f_list, method = "compare")
#> [1] 1 3 2
# In this particular case of `f_list` all orderings agree with each other, but
# generally this is not the case: for any pair of methods there is a case
# when they disagree with each other
summ_order(f_list, method = "mean")
#> [1] 1 3 2
summ_order(f_list, method = "median")
#> [1] 1 3 2
summ_order(f_list, method = "mode")
#> [1] 1 3 2
# Use `decreasing = TRUE` to sort decreasingly
summ_order(f_list, method = "compare", decreasing = TRUE)
#> [1] 2 3 1
# Sort list
summ_sort(f_list)
#> $a
#> Density function of continuous type
#> Support: ~[0, 0.95557] (10000 intervals)
#>
#> $c
#> Density function of continuous type
#> Support: ~[-4.25342, 5.25342] (10000 intervals)
#>
#> $b
#> Density function of continuous type
#> Support: ~[1, 1.95557] (10000 intervals)
summ_sort(f_list, decreasing = TRUE)
#> $b
#> Density function of continuous type
#> Support: ~[1, 1.95557] (10000 intervals)
#>
#> $c
#> Density function of continuous type
#> Support: ~[-4.25342, 5.25342] (10000 intervals)
#>
#> $a
#> Density function of continuous type
#> Support: ~[0, 0.95557] (10000 intervals)
# Rank elements: 1 indicates "the smallest", `length(f_list)` - "the biggest"
summ_rank(f_list)
#> a b c
#> 1 3 2
Functions summ_prob_true()
and summ_prob_false()
should be used to extract probabilities from boolean pdqr-functions: outputs of comparing basic operators (like >=
, ==
, etc.):
summ_prob_true(my_beta >= my_norm)
#> [1] 0.416062
summ_prob_false(my_beta >= 2*my_norm)
#> [1] 0.6391
summ_pval()
computes p-value(s) of observed statistic(s) based on the distribution. You can compute left, right, or two-sided p-values with methods “left”, “right”, and “both” respectively. By default multiple input values are adjusted for multiple comparisons (using stats::p.adjust()):
# By default two-sided p-value is computed
summ_pval(my_beta, obs = 0.7)
#> [1] 0.02186803
summ_pval(my_beta, obs = 0.7, method = "left")
#> [1] 0.989066
summ_pval(my_beta, obs = 0.7, method = "right")
#> [1] 0.01093401
# Multiple values are adjusted with `p.adjust()` with "holm" method by default
obs_vec <- seq(0, 1, by = 0.1)
summ_pval(my_beta, obs = obs_vec)
#> [1] 0.0000000000 1.0000000000 1.0000000000 1.0000000000 1.0000000000
#> [6] 1.0000000000 0.4915085377 0.1530761780 0.0255840348 0.0009720023
#> [11] 0.0000000000
# Use `adjust = "none"` to not adjust
summ_pval(my_beta, obs = obs_vec, adjust = "none")
#> [1] 0.0000000000 0.2285302047 0.6892806594 0.8403488674 0.4665584871
#> [6] 0.2187482323 0.0819180896 0.0218680254 0.0031980044 0.0001080003
#> [11] 0.0000000000


erpnext.setup.setup_wizard.setup_wizard.fin (args)
No docs
erpnext.setup.setup_wizard.setup_wizard.get_setup_stages (args=None)
No docs
erpnext.setup.setup_wizard.setup_wizard.login_as_first_user (args)
No docs
erpnext.setup.setup_wizard.setup_wizard.make_sample_data (domains)
No docs
erpnext.setup.setup_wizard.setup_wizard.setup_company (args)
No docs
erpnext.setup.setup_wizard.setup_wizard.setup_complete (args=None)
No docs
erpnext.setup.setup_wizard.setup_wizard.setup_post_company_fixtures (args)
No docs
erpnext.setup.setup_wizard.setup_wizard.setup_taxes (args)
No docs
erpnext.setup.setup_wizard.setup_wizard.stage_fixtures (args)
No docs
erpnext.setup.setup_wizard.setup_wizard.stage_four (args)
No docs
erpnext.setup.setup_wizard.setup_wizard.stage_three (args)
No docs


{% extends "portal/base.html" %} {% load static %} {% block title %}kive for Users{% endblock %} {% block stylesheets %} {% endblock %} {% block content %} Return to homepage
Upload a new dataset
Launch a container.
View the status and results of container runs.
Find runs that have involved a given file.


Follow this link to confirm the update of your email address from {{ .Email }} to {{ .NewEmail }}:
Change email address


Hello take this pic
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How are you?
?
Test from HE?
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Hello take this pic
Hello
How are you?
?
Test from HE?
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Book Search
Book Ranks
Calendar
Forum
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Menu
MyShelf
Schedule Your Reading Time!
Title:
Total Chapters:
How Many Chapters A Day:
Start Date:
Title
Total Chapters
Chapters a Day
Start Date
Days to Finish


CountCPUs()
语法
Result = CountCPUs([Type])概要
Returns the number of CPU cores available.
参数
Type (可选) The CPU type to request. 它可以是以下值之一︰ #PB_System_CPUs : the total number of CPU cores installed in the computer (default). #PB_System_ProcessCPUs : the available CPU cores for the current process. This is useful as the OS can limit a process to use only a small number of CPU.
返回值
Returns the number of CPU cores available.
已支持操作系统
所有


--- layout: default title: News - Julia Libraries for Quantum Science and Technology ---
The JuliaQuantum News page presents updates of the JuliaQuantum organization and projects. Posts are written in a blogging style by JuliaQuantum developers, and often cover issues of numerical, technical, distributed and parallel computing for quantum sciences and technologies, as well as quantum simulation program design in Julia, and how these issues touch upon the design and implementation of the JuliaQuantum libraries.


#include <DisplayableObject.h>
Virtual class to be inherited by all objects to be displayed in Scene
Contains purely virtual Display method that must be overloaded. Display() is called from Scene.
- Author
- wil
| DisplayableObject::DisplayableObject |
( |
| ) |
|
|
inline |
Default constructor
Initialises position, size and orientation to origin in World Space.
| virtual void DisplayableObject::Display |
( |
| ) |
|
|
pure virtual |
Virtual method. Called from Scene parent.
Must be overloaded by your DisplayableObject subclass. Contains all rendering commands.
| void DisplayableObject::orientation |
( |
float |
rx, |
|
|
float |
ry, |
|
|
float |
rz |
|
) |
| |
|
inline |
set orientation in World Space
| float* DisplayableObject::orientation |
( |
| ) |
|
|
inline |
Get orientation in World Space
| void DisplayableObject::position |
( |
float |
x, |
|
|
float |
y, |
|
|
float |
z |
|
) |
| |
|
inline |
| float* DisplayableObject::position |
( |
| ) |
|
|
inline |
| void DisplayableObject::size |
( |
float |
s | ) |
|
|
inline |
set size in World Space (single value)
| void DisplayableObject::size |
( |
float |
sx, |
|
|
float |
sy, |
|
|
float |
sz |
|
) |
| |
|
inline |
set size in World Space (seperate axes)
| float* DisplayableObject::size |
( |
| ) |
|
|
inline |
| float DisplayableObject::pos[3] |
|
protected |
float[] containing World Space position coordinates
| float DisplayableObject::rotation[3] |
|
protected |
float[] containing angles of orientation in World Space for x, y, and z axes
| float DisplayableObject::scale[3] |
|
protected |
float[] containing relative World Space scaling values for x,y,z
The documentation for this class was generated from the following file:


Commercial NMS products require extensive professional services for a full-featured deployment. The deployment will often cost five to ten times the cost of the software license itself, can take a year or more to complete and often requires extensive ongoing management.
Observium is different. Observium can be installed and running in less than an hour and collecting data from an entire network's worth of devices in a day. Because of our development model and update delivery system we can rapidly respond to feature and bug fix requests from users and have new code developed and deployed quickly.
| Service | Price |
|---|---|
| Support Subscription (2 hour minimum) | £200 |
| Support Subscription (10 hours) | £900 |
| Additional Support per hour | £100 |
| Additional Support 10 hour block | £900 |
Support subscriptions require and can be purchased alongside an Observium Professional subscription.
| Service | Price |
|---|---|
| Feature Development per day | £1000 |
| Basic Installation (2 hour minimum) | £200 |
| Installation additional hour | £100 |


Here you can find links to recordings of some of my past talks.
University of Warwick, Warwick Statistics 50th anniversary conference, September 2022:
Epidemiological impacts of the NHS COVID-19 app
(mp4).
LSE Women in Mathematics Seminar, February 2022:
The epidemiological impact of the NHS COVID-19 app
(YouTube).
Isaac Newton Institute, August 2020:
A preliminary analysis of epidmiological trends on the Isle of Wight after the launch of the Test and Trace programme
(YouTube, talk starts around 52:30).


Hemkund Sahib (also spelled Hemkunt), formally known as Gurudwara Sri Hemkund Sahib Ji, is a Sikh place of worship and pilgrimage site in Chamoli district, Uttarakhand, India. It is devoted to Guru Gobind Singh (1666–1708), the tenth Sikh Guru.
With its setting of a glacial lake surrounded by seven mountain peaks, each adorned by a Nishan Sahib on its cliff, it is according to the Survey of India located in the Himalayas at an elevation of 4,632 meters (15,197 feet).
It is approached from Gobindghat on the Rishikesh-Badrinath highway. The main town near Gobindghat is Joshimath.


Proof of Life (2000) Meg Ryan, Russell Crowe, David Morse, Pamela Reed, David Caruso, Anthony Heald, Stanley Anderson, Gottfried John, Alun Armstrong, Michael Kitchen, Margo Martindale, Mario Ernesto Sanchez, Pietro Sibille, Vicky Hernandez, Norma Martinez, Diego Trujillo. Screenplay by Tony Gilroy, inspired by the Vanity Fair article "Adventures in the Ransom Trade" by William Prochnau and by the book "Long March to Freedom" by Thomas Hargrove. Directed by Taylor Hackford. 135 minutes. Rated R, 2.5 stars (out of five stars)
Review by Ed Johnson-Ott, NUVO Newsweekly www.nuvo.com Archive reviews at http://us.imdb.com/ReviewsBy?Edward+Johnson-Ott To receive reviews by e-mail at no charge, send subscription requests to<EMAIL_ADDRESS>or e-mail<EMAIL_ADDRESS>with the word "subscribe" in the subject line.
In an article that inspired the action-thriller, "Proof of Life," William Prochnau wrote, "The huge number of multinational executives being abducted abroad has made organized kidnapping a big business. It has also spawned a counter-industry – getting them back – and a secret drama involving former spies and revolutionaries, AK-47s and armored cars, helicopter drops and hideaways." With source material as provocative as that, the resultant film should be a knockout and "Proof of Life" does contain some moments that deliver on its promise, but far too much of the film is squandered on the most tedious aspects of a cumbersome, ill-conceived storyline.
The production starts off right, with commando-turned-hostage negotiator Terry Thorne (Russell Crowe) dodging bullets in Chechnia while rescuing a victim from his abductors. Shortly after returning home, he gets dispatched to South America for another mission.
That mission is Peter Bowman (David Morse), an American engineer snatched by the ELT, a guerrilla outfit that started as a Marxist organization, but devolved into just a bunch of heavily-armed thugs who kidnap for a living.
Terry meets with Alice (Meg Ryan), Peter's wife, and settles in for the negotiations. Because their captive is a corporate employee, the ELT demands millions. What they don't know is that the company is on the verge of collapse and has not paid the kidnap insurance bills on its staff for months. When Terry learns the cold financial truth, he splits, but something draws him back and he becomes even more determined to come up with a way to get Peter home.
So far, so good, but the story then settles into mediocrity, cutting between segments of Peter being mistreated by his dope-smoking, coke-snorting, gun-toting captors and interminable scenes of the molasses-slow negotiation process and the growing quasi-romantic relationship between Terry and Alice. The film eventually delivers a rousing action set piece, but by then it's too little, too late.
"Proof of Life" is particularly frustrating because you can see the film it should have been. Scenes between Terry and his adrenaline junkie cohorts, particularly a jittery operative named Dino ("NYPD Blue" vet David Caruso), deliver the sense of danger and immediacy that is missing during most of the movie. The film screams for more edgy camaraderie, for more adventure, for anything other than more dreary looks at a half-assed romance.
And half-assed is the operative term. Aside from some intense gazing, which can be interpreted several different ways, scant evidence of romantic feelings appear onscreen. A love scene between Russell Crowe and Meg Ryan was filmed, then scrapped by director Taylor Hackford. Consequently, a smooch between Terry and Alice late in the film left me thinking, "Where the hell did that come from?"
The incongruous kiss is just one part of a poorly written script that plays like a rough draft rather than a finished product. Alice and Terry are each assigned one painful burden in a pale attempt to flesh them out. For Alice, it's the memory of a miscarriage. For Terry, it's the knowledge that his globetrotting job has strained the relationship between him and his son. Is anything of substance done with this information? No.
The script is equally inept when depicting Peter's life in captivity, shooting for a "Midnight Express" vibe, but failing because the captors are left as stereotypes instead of people. The caricature status given the terrorists is so blatant that, when one kidnapper displays an exceptional level of animosity towards Peter, it's obvious he is merely being set up as an identifiable target for the grand finale. Besides Peter, only one character at the guerrilla camp is allowed to be human, fellow prisoner Eric Kessler (Gottfried John, another white guy, of course).
"Proof of Life" gives viewers a great beginning, solid action near the end and a closing scene between Terry and Alice that wants to be haunting and poetic, but falls flat because the script fails to provide sufficient groundwork for the relationship. The film's long, droopy middle leaves good actors straining to wring substance out of filler. Russell Crowe uses his great physicality to carry the home-front portion of the movie and the talented David Morse manages to add some oomph to the anemic camp scenes, but Meg Ryan comes off as simply inconsequential. In supporting roles, David Caruso is wiry and appealing, while Pamela Reed is strong as Peter's fiercely protective sister, even though the script quickly softens her fire and ships her away.
Ultimately, "Proof of Life" takes a great idea and turns it into an overlong exercise in missed opportunities, punctuated by a few powerful sequences that show what would have happened had the writer focused on psychology and adventure instead of uncooked mush.
© 2000 Ed Johnson-Ott
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Xurxe
Toivo
García
stillness
.
movement.
interactivity.
skills.
about.
contact.
github.
linkedin.
instagram.
movement.
i write, produce, and edit videos and animations.
Creation 4
Creation 5
Creation 6


Often, legacy data management systems provide no native support to transactions. Programmers protect data from concurrent access by adopting commonly agreed patterns, relying on low level concurrency primitives, such as semaphores. In such cases, consistent data access is granted only if all code components are compliant with the adopted mutual exclusion patterns. When migrating legacy systems to modern data management systems, the ad hoc mechanisms for data protection must be replaced with modern constructs for transaction management. In such cases, a literal translation may expose problems and bugs, which were originally masked by the specific implementation and patterns in use. In this paper, we propose a static flow analysis that determines the existence of potentially incompatible locks within the same thread, which require specific code re-engineering before migrating to a modern data management system. We report the results obtained on a concrete instance of this problem.


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Making a website is my ultimate PASSION Being A Marketing , I've designed websites for small businesses, corporation's, non-profits, music studios, and counting,
More to say; i've succesfully won their satisfaction and undoubtedly achieved their trust. and More..
My Special Charater to do something Pretty Cool about future technolgy and people use by my creation Software; A full website strategy, including design, SEO, and Development turning it into a masterpiece, Semantic HTML and CSS. HTML5, APPS, SYSTEM, SOCIAL MEDIA MARKETING, ADDWORDS, ETC. is a part of my Job to advertisement
My Interest is to enhance and embellish beyond the website and I love helping people with marketing strategy and sharing new ideas to my Client and To my Future Job..
Hello, I am Archiel Curzada,
Ux/UI Designer and a Website developer Social Media Marketing
About Me
Things i love
What i do
- done HTML/CSS/PHP/Javascript
- doneUX/UI Designer
- done Website Developer
- done Graphic Designer
----
- done Branding
- done Information Graphic
- done Social Media Marketing
- done SEO(Search Engine Optimizer)
Ideas
Creating an exceptional website and competent branding,convey on being cooperative and listening to my client need's.
Elegant Website
I like to make it simple yet elegant, and always leave an undeniable impact to my clients and their respective viewers. clean and simple thats the right term.
Responsive
A developer that knows how to run website across all devices, I myself make it look elegant and professional, Im that guy.
Social Marketing
To be recognized and assist you on online marketing from the ground up and help your website be searchable on top search engines.
Freelance Developer
I do freelance. I like to help people on their business to be recognized and started my career as a uX/uI Designer, worked for a few companies which helped me to hone my skills
Scratch
Creating website from the scratch is such an enjoyable task,but i can also work using front-end frameworks and website creation tool like Bootstrap, CodeIgniter and Wordpress


Class EventProxy
EventProxy. An implementation of task/event based asynchronous pattern.
Defined in: eventproxy.js.
| Constructor Attributes | Constructor Name and Description |
|---|---|
|
EventProxy.
|
| Method Attributes | Method Name and Description |
|---|---|
|
addListener(eventName, callback)
Bind an event, specified by a string name, `ev`, to a `callback` function.
|
|
|
after(eventName, times, callback)
The callback will be executed after the event be fired N times.
|
|
|
all(eventName1, eventName2, callback)
Assign some events, after all events were fired, the callback will be executed once.
|
|
|
any(eventName1, eventName2, callback)
The callback will be executed after any registered event was fired.
|
|
| <static> |
EventProxy.create()
Create a new EventProxy
|
|
immediate(ev, callback, data)
Bind an event, and trigger it immediately.
|
|
|
not(eventName, callback)
The callback will be executed when the evnet name not equals with assigned evnet.
|
|
|
once(ev, callback)
Bind an event like the bind method, but will remove the listener after it was fired.
|
|
|
removeAllListeners(event)
Remove all listeners.
|
|
|
removeListener(eventName, callback)
Remove one or many callbacks.
|
|
|
tail(eventName1, eventName2, callback)
Assign some events, after all events were fired, the callback will be executed first time.
|
|
|
trigger(eventName, data)
Trigger an event, firing all bound callbacks.
|
Class Detail
EventProxy()
EventProxy. A module that can be mixed in to *any object* in order to provide it with
custom events. You may `bind` or `unbind` a callback function to an event;
`trigger`-ing an event fires all callbacks in succession.
var render = function (template, resources) {}; var proxy = new EventProxy(); proxy.assign("template", "l10n", render); proxy.trigger("template", template); proxy.trigger("l10n", resources);
Method Detail
addListener(eventName, callback)
Bind an event, specified by a string name, `ev`, to a `callback` function.
Passing `"all"` will bind the callback to all events fired.
- Parameters:
- {string} eventName
- Event name.
- {function} callback
- Callback.
after(eventName, times, callback)
The callback will be executed after the event be fired N times.
- Parameters:
- {string} eventName
- Event name.
- {number} times
- N times.
- {function} callback
- Callback, that will be called after event was fired N times.
all(eventName1, eventName2, callback)
Assign some events, after all events were fired, the callback will be executed once.
proxy.all(ev1, ev2, callback); proxy.all([ev1, ev2], callback); proxy.all(ev1, [ev2, ev3], callback);
- Parameters:
- {string} eventName1
- First event name.
- {string} eventName2
- Second event name.
- {function} callback
- Callback, that will be called after predefined events were fired.
any(eventName1, eventName2, callback)
The callback will be executed after any registered event was fired. It only executed once.
- Parameters:
- {string} eventName1
- Event name.
- {string} eventName2
- Event name.
- {function} callback
- The callback will get a map that has data and eventName attributes.
<static>
{EventProxy}
EventProxy.create()
Create a new EventProxy
var ep = EventProxy.create(); ep.assign('user', 'articles', function(user, articles) { // do something... }); // or one line ways: Create EventProxy and Assign var ep = EventProxy.create('user', 'articles', function(user, articles) { // do something... });
- Returns:
- {EventProxy}
immediate(ev, callback, data)
Bind an event, and trigger it immediately.
- Parameters:
- {string} ev
- Event name.
- {function} callback
- Callback.
- {mix} data
- The data that will be passed to calback as arguments.
not(eventName, callback)
The callback will be executed when the evnet name not equals with assigned evnet.
- Parameters:
- {string} eventName
- Event name.
- {function} callback
- Callback.
once(ev, callback)
Bind an event like the bind method, but will remove the listener after it was fired.
- Parameters:
- {string} ev
- Event name.
- {function} callback
- Callback.
removeAllListeners(event)
Remove all listeners.
It equals unbind(); Just add this API for as same as Event.Emitter.
- Parameters:
- {string} event
- Event name.
removeListener(eventName, callback)
Remove one or many callbacks. If `callback` is null, removes all
callbacks for the event. If `ev` is null, removes all bound callbacks
for all events.
- Parameters:
- {string} eventName
- Event name.
- {function} callback
- Callback.
tail(eventName1, eventName2, callback)
Assign some events, after all events were fired, the callback will be executed first time.
then any event that predefined be fired again, the callback will executed with the newest data.
proxy.tail(ev1, ev2, callback); proxy.tail([ev1, ev2], callback); proxy.tail(ev1, [ev2, ev3], callback);
- Parameters:
- {string} eventName1
- First event name.
- {string} eventName2
- Second event name.
- {function} callback
- Callback, that will be called after predefined events were fired.
trigger(eventName, data)
Trigger an event, firing all bound callbacks. Callbacks are passed the
same arguments as `trigger` is, apart from the event name.
Listening for `"all"` passes the true event name as the first argument.
- Parameters:
- {string} eventName
- Event name.
- {mix} data
- Pass in data.


{% extends "layout-v2.html" %} {% block pageScripts %} {% endblock %} {% block pageTitle %} NHS Cervical screening management system {% endblock %} {% block header %} {% include '../../components/header.html' %} {% endblock %} {% block content %}
Listed GP surgeries have not given an email address to receive notifications. Choose a GP surgery to print and send notifications to.


Background: I recently proposed a new object system, name Cor, for the Perl core . This work has been done in coordination with Sawyer X and Stevan Little. What follows are my musings on the process and OO in general. For those things I inevitably get wrong in this discussion, it’s my fault, not theirs.
Contrary to what some might think, the discussions about the Cor
OO system
are ongoing, but it’s happening quietly, via email, and the holiday period
doesn’t help.
And the Moose has
function also doesn’t
help. At all. It’s possible that you’ve heard some rumblings about the has
function, so let’s clear up some of this. This will take some time, but I
promise you, by the time I’m done, that I will have given a rubbish
explanation of a hard problem. In throwing this together, I truly understand
Blaise Pascal’s comment “I would have written a shorter letter, but I did not
have the time.” If I had the time, this would be much shorter and clearer, but
I’m too lazy to delete this.
In Moose (and Moo , but we’ll stick to Moose
for this discussion), the has
function lets you declare an attribute:
package Point2D {
use Moose;
has [qw/x y/] => (
is => 'ro',
isa => 'Num',
required => 1,
);
}
The above is a class for the canonical 2D point object that developers have a love/hate relationship about when learning OO concepts.
As you can see from the has
declaration, we have:
- Created slots for the data
- Created read-only accessors for the data
- Required that they be passed to the constructor
That’s a lot to pack into one function, and it leads to confusion like this:
has attr => (
is => 'ro', # read-only
isa => 'Int', # declare it an integer
writer => 'set_attr', # but it's read-only?
required => 1, # 'attr' must be provided
builder => '_build_attr', # called if not passed in the constructor
);
There are other examples you could put together, but that shows part of the
issue: Moose has crammed so much into one function that it’s easy to write
code that is confusing or just plain doesn’t make sense. The above does make
sense if you realize that required
doesn’t mean that the attribute is
required to be passed to the constructor (as some assume). The docs say this :
Basically, all [required] says is that this attribute must be provided to the constructor or it must have either a default or a builder. It does not say anything about its value, so it could be undef.
But what does declaring something as read-only and providing a writer (mutator) mean? That’s confusing because we’re really packing a lot of meaning into a single function.
What’s worse, it’s harder to write code that does what we need. If I want a private, internal slot, per instance, with no accessor, do you know how to do that in Moose? We tend not to do that too much with Moose simply because it’s hard to do, despite being trivial in other languages.
Well, you can declare a slot as bare
(instead of ro
and friends) and then do:
my $value = $self->meta
->get_attribute($attribute_name)
->get_value($self);
Except no one does that (by “no one”, of course, I mean “the set of no developers who aren’t not Stevan.“) They just declare the attribute private and that’s that. And I don’t blame them. But it means that everyone just makes accessors for everything, and that makes it much easier to make public accessors for everything and when I’m cleaning up code for a client, that’s a problem because it makes it much harder for me because now I have a public contract that I have to respect, even if there wasn’t originally a need to expose that data.
Encouraging people to write accessors is a bad idea, but people do it all over the place, just as they often make attribute mutable for no good reason (and here is a great example of why mutable objects are dangerous ). A good rule of thumb for OO design: make your interface as small as possible. Moose, unfortunately, offers an affordance to making our interace as large as possible.
Moving along, what does that point class look like in Java?
public class Point2D {
// slots
private double x;
private double y;
// accessors
public double x() { return x; }
public double y() { return y; }
// constructor
public Point2D(double x, double y) {
this.x = x;
this.y = y;
}
}
Note how the slots, the accessors, and the constructor arguments are all nicely decoupled, leaving no ambiguity.
And without going into detail, private slots with no accessors are trivial in Java, at both the class and instance level.
But where does that leave Cor
? Well, Cor
aims to be core, meaning that
overloading has
is problematic. We’ve learned a lot from Moose about how to
make OO that feels “perlish”, but we need to keep growing and learn from our
mistakes. Returning to this:
has attr => (
is => 'ro',
isa => 'Int',
writer => 'set_attr',
builder => '_build_attr',
required => 1,
);
For Moose, that’s OK. For Cor
, that’s not, because it means you can write
code that is, at best, confusing.
And then there are things like this:
my $auth = Authenticate->new($one_time_token);
# or
my $auth = Authenticate->new( user => $user, pass => $pass );
# or
my $auth = Authenticate->new({user => $user, pass => $pass});
Here’s one way you could try to handle that:
around BUILDARGS => sub ($orig, $class, @args) {
my %arg_for
= @args > 1 ? @args
: 'HASH' eq ref $args[0] ? $args[0]->%*
: ( token => $args[0] );
return $class->$orig(%arg_for);
};
In languages with multi-dispatch, if we add a new way of instantiating an
object, we can just add a new constructor and the language will handle the
dispatching for us. With Moose, we need to use BUILDARGS
for this, and
manually handle all of that dispatching ourselves. That means more bugs. If
Perl had something like multidispatch, we could possibly write:
method BUILDARGS (Code $orig, Class $class, UUID $token) { ... }
method BUILDARGS (Code $orig, Class $class, Str :$user, Str :$pass ) { ... }
method BUILDARGS (Code $orig, Class $class, HashRef $args) { ... }
For Cor
, we’re not going to get there because Perl doesn’t yet have robust
signatures like that and we’re probably never going to get multidispatch,
but decoupling the very overloaded meaning of has
will help, and limiting
how we can pass arguments can help (no more “named pairs” or “hashref”
decision making).
And here’s a fun one! An attribute that you can’t set, even though it looks like you can pass it in the constructor:
#!/usr/bin/env perl
package SomeClass {
use Moose;
has 'username' => (
is => 'ro',
isa => 'Str',
required => 1,
init_arg => undef,
default => 'Bob',
);
}
# this prints "Bob"
print SomeClass->new( username => 'foo' )->username;
Of course, Cor
could try to trap every possible illegal (or confusing)
combination and then what?
- Warn about them?
- Ignore them?
- Make them fatal?
- Do this at compile-time?
- At runtime?
And if we check illegal combinations, then if we ever extend has
to have
more functionality, we have to figure out the new “illegal” combinations (such
as making attributes simultaneously required and lazy).
Do we stop developers from shooting themselves in the foot or hand them a gun?
The counter-argument I hear from many developers is “we don’t need to separate slots and attributes or a different syntax for declaring attributes. What we’ve been doing works.”
And frankly, this has worked fairly well. If the new Cor
proposal doesn’t
provide some dead-simple way to create accessors, then we’ll wind up with 42
different modules to provide that and we won’t be that much further along than
when we started.
There are so many decisions to be made with Cor
, many of which would be dead
wrong if we move too quickly and we don’t want to get this wrong. And the lack
of multi-methods and the inability to introspect signatures means the
BUILDARGS
and BUILD
pain will remain in some form (though BUILD
isnt'
too bad).
Thus, we really want to have some separation of slots, attributes, and constructors, but making an easy syntax for that is is a challenge. As the old line goes, “making things hard is easy; making things easy is hard.” And making a solution that is easy and does the right thing and that all Perl developers will like is impossible. And there will be developers looking at the final solution and sayind “no” because their one pet peeve wasn’t respected.
As for our initial work with the syntax, the core Perl devs liked what they
saw in the initial proposal, but it’s one thing to say “shiny!“. It’s another
thing to hammer that shiny onto something that already exists. There are a
number of approaches which can be taken, but they require hard decisions. For
now, Cor
will be focusing on the syntax.


- uiCompass - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- uiMapToolbar - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- uiRotateGestures - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- uiScrollGestures - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- uiTiltGestures - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- uiZoomControls - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- uiZoomGestures - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- unassign() - Method in class ca.ualberta.cs.wrkify.Task
-
unassign the bid and revert the status
- uniform - Static variable in class ca.ualberta.cs.wrkify.R.id
-
- up - Static variable in class ca.ualberta.cs.wrkify.R.id
-
- updateCached(RemoteObject) - Method in class ca.ualberta.cs.wrkify.CachingClient
-
set obj as the cached version of itself.
- updateCount() - Method in class ca.ualberta.cs.wrkify.ViewBidsActivity
-
Refreshes the View which displays the number of bids in the list
- updateDataSet(List<Task>) - Method in class ca.ualberta.cs.wrkify.SearchFragment
-
Safely updates TaskListAdapter to data changes
that occured as a result of a search.
- upload(RemoteObject) - Method in class ca.ualberta.cs.wrkify.CachingClient
-
upload the object to the inner client and keep
the new version in the caches.
- upload(RemoteObject) - Method in class ca.ualberta.cs.wrkify.ElasticClient
-
reuploads changes of an existing RemoteObject
to this RemoteClient
- uploadNew(Class<T>, T) - Method in class ca.ualberta.cs.wrkify.CachingClient
-
uploadNew uploads a remote object that does not exist
on the server, and creates a new id for it.
- uploadNew(Class<T>, T) - Method in class ca.ualberta.cs.wrkify.ElasticClient
-
upload an new RemoteObject to the ElasticSearch server.
- URL - Static variable in class ca.ualberta.cs.wrkify.WrkifyClient
-
url is the default server that wrkify uses
- useAppContext() - Method in class ca.ualberta.cs.wrkify.ExampleInstrumentedTest
-
- useCompatPadding - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".
- useLogo - Static variable in class ca.ualberta.cs.wrkify.R.id
-
- User - Class in ca.ualberta.cs.wrkify
-
User keeps the username and related contact
information of a user and provides getters
and setters.
- User(String, String, String) - Constructor for class ca.ualberta.cs.wrkify.User
-
creates a user from username, email, phoneNumber
- USER_EXTRA - Static variable in class ca.ualberta.cs.wrkify.ViewProfileActivity
-
- UserDeleteSignalsTransaction - Class in ca.ualberta.cs.wrkify
-
UserDeleteSignalsTransaction is a transaction to delete
all the signals.
- UserDeleteSignalsTransaction(User, String) - Constructor for class ca.ualberta.cs.wrkify.UserDeleteSignalsTransaction
-
create UserDeleteSignalsTransaction from a user and a targetId
- UserName - Static variable in class ca.ualberta.cs.wrkify.R.id
-
- UserSetEmailTransaction - Class in ca.ualberta.cs.wrkify
-
Transaction to set a user's email address.
- UserSetEmailTransaction(User, String) - Constructor for class ca.ualberta.cs.wrkify.UserSetEmailTransaction
-
Creates a transaction to change the target user's email address.
- UserSetPhoneNumberTransaction - Class in ca.ualberta.cs.wrkify
-
Transaction to set a user's phone number.
- UserSetPhoneNumberTransaction(User, String) - Constructor for class ca.ualberta.cs.wrkify.UserSetPhoneNumberTransaction
-
Creates a transaction to change the target user's phone number.
- UserView - Class in ca.ualberta.cs.wrkify
-
Displays a username.
- UserView(Context, AttributeSet) - Constructor for class ca.ualberta.cs.wrkify.UserView
-
Initializes a UserView.
- UserView(Context, AttributeSet, int) - Constructor for class ca.ualberta.cs.wrkify.UserView
-
Initializes a UserView.
- UserView(Context) - Constructor for class ca.ualberta.cs.wrkify.UserView
-
Initializes a UserView.
- useViewLifecycle - Static variable in class ca.ualberta.cs.wrkify.R.attr
-
May be a boolean value, such as "true
" or
"false
".


Interactive Generic Visualization library for Javascript that is based on d3.js
Source Code » View Sample Charts »


@Markus
OK, I got it guys. Screw D1 for now, daemonising its code is basically impoossible.
This is my proposal for the first fungible LABS chain.
-- LottoCC!
--- Someone (anyone) crates a lotto game that expires at some X block height.
---- Anyone can register to this game only once with some amount of LABS coin.
---- The total amount received to this "game" is the payout to the winner
---> The winner is decideded by the first notarized MoMoM hash., after the blockheight specified at game creation
this means that no miner can take over the chain and spoof the block hash, because it takes MoM hashes from multiple chains then hashes them to find the winner.1
(edited)


LPN to BSN v 002
Student Program Handbook (updated 7-20-2011)
Skills Laboratory Handbook (updated 4-6-2009)
Forms
- Clinical Program Agreement Form
- Accident and Incident Report
- Clinical Assessment Guidelines
- Clinical Orientation Checklist
- Clinical Program Agreement Form
- Clinical Summative Evaluation Form
- Consent for Assessment and Examination
- CPR Provider Status Level Form
- For Cause Drug Testing Report
- Hepatitis B Vaccine Declination
- Medical Documentation of Physical and Mental Readiness
- Patient Care Plan
- Student Information Form
- Student Evaluation of Clinical Instructor
- Weekly Formative Evaluation Form
- Weekly Time Log for Clinical Hours
Skill Forms
- Administration of Piggyback Medications into an Existing IV Line
- Administration of Push Medications into an Existing IV Line
- Administration of Push Medications via an Intravenous Lock
- Comprehensive Skill Lab
- CVC Dressing Change
- Indwelling Catheter
- Insertion of an IV Catheter
- Medication Administration Record for Skill Lab Documentation
- Nasopharyngeal Suctioning
- Preparing Primary IV Infusion
- Student Documentation Form for Skills Lab
- Sterile Field/Gloves
- Tracheostomy Care
- Tracheostomy Suctioning


Warehouse Chief Croop:
Aye? Good stuff.
The stories are circling about like crows over carcasses, friend.
Dwarven Contractors being put to the blade
. Someone is hunting them, and we have no idea who....
"Go on."


A distributed trace is a set of events, triggered as a result
of a single logical operation, consolidated across various
components of an application. A distributed trace contains
events that cross process, network and security boundaries.
A distributed trace may be initiated when someone presses a
button to start an action on a website - in this example, the
trace will represent calls made between the downstream services
that handled the chain of requests initiated by this button
being pressed.
Opaque value
An opaque value refers to a value that can only be understood
or processed in any way by the distributed trace participant that generated
this value. Any other participant must treat it as a blob of bytes.


>>
<<
Usr
Pri
JfC
LJ
Phr
Dic
Voc
!:
Help
Dictionary
Sample Topics
This part provides examples of the use of J in various topics;
it is designed to be used in conjunction with the dictionary
and at the keyboard of a J system.
It is also designed to be used inductively, as follows:
- Read one or two sentences and their results
(which begin at the left margin), and attempt to state clearly
in English what each sentence does.
- Enter similar sentences to test the validity of your statements.
- Consult the dictionary to confirm your understanding of the
meaning of primitives such as i. (used with one argument or two).
Use the Vocabulary at the end of the book as an index to
pages in the dictionary. In the Windows system, highlight a word
(e.g. /:) and hit ctrl-F1 to display the dictionary entry
for that word.
- Enter parts of a complex sentence, such as i. 26
and j+/i.26 in the case of a.{~j+/i.26 used in the topic
Alphabet and Numbers.
>>
<<
Usr
Pri
JfC
LJ
Phr
Dic
Voc
!:
Help
Dictionary


A comparable set must contain the Customer's cowork space(s) and at least 4 other non-affiliated cowork spaces. A "non-affiliated" cowork space means any cowork space or property that does not share with the Customer's cowork space(s) the same owner, the same management or management company, the same manager or the same management team.
The non-affiliated cowork spaces in a comparable set must be in the same basic geographic region.
Geographic Region Example: cowork spaces that are in the same city or neighborhood of a city are in the "same basic geographic market".
Within any comparable set, no single cowork space (subscriber or non-affiliate property) may represent 40% or more of the total desk capacity of the comparable set.
A comparable set must contain cowork spaces from at least four different cowork space companies (e.g., IWG, WeWork, Convene, Industrious), management companies, and owners other than that of the Customer's cowork space company, management company, and owner.
If a Customer wishes to add a cowork space to or remove a cowork space from a comparable set, it must do so in combination with at least a second change, i.e. there needs to be a minimum of 2 changes to the comp set. For example, removing a cowork space, then adding a cowork space; or adding 2 cowork spaces; or removing 2 cowork spaces.
If a comparable cowork space closes or otherwise discontinues reporting data, Customer must delete that comparable cowork space (as a single cowork space) from the comparable set.
If Customer has multiple comparable sets, there must be at least two different non-affiliated cowork spaces in each comparable set.
If Customer makes a change to a comparable set (e.g., adding cowork spaces, deleting cowork spaces, etc.), Customer may not make another change to a comparable set for at least another 30 days after that change.
Comparable Sets are confidential information and are the property of CoworkIntel.
Customer will not use CoworkIntel to derive, reverse engineer, recalculate or attempt to derive, reverse engineer or recalculate any information related to an individual comparable cowork space's information or in any way obtain an individual property's information. Customer may not create any comparable set definition, change request(s), or other filtering of the comparable set(s) that may expose any individual property's information. If after a comparable set is defined, should the Customer's affiliation(s) change and result in the comparable set no longer complying with the rules above, the Customer must request a change to comply with the rules.
CoworkIntel, at its sole discretion, may reject or disable any comparable set change if, in its reasonable judgment, it threatens the confidentiality of any third party or if CoworkIntel believes or has reason to believe in its sole discretion that a comparable set violates or may violate relevant law.
CoworkIntel may update or modify this comparable set policy at any time without prior notice to any customer, subscriber, cowork space, property, or any other third party. CoworkIntel users will be notified of any update or modification to comparable set policy requirements by an email notification to the user. The user will have 60 days of the date the email notification is sent to the user to provide CoworkIntel with updates or modifications of the user's comparable sets that meet the updated or modified comparable set policy requirements. In the event that an update or modification of the comparable set policy requirements has a material adverse effect on the user, the user may terminate its agreement with CoworkIntel for the applicable services within 60 days of the date the email notification is sent to the user.
Customer: (1) may only use the information obtained through the services for the benefit of the Customer and may not share that information with comparable or any non-affiliated cowork spaces, (2) must report any activity to CoworkIntel that reflect or suggest an improper use of any of CoworkIntel´s services, e.g., an increase in prices; and (3) must promptly notify CoworkIntel of any change in ownership or management of the Customer or the Customer's cowork space.


Posted on January 20, 2016
Arrays
By definition, "Arrays are ordered, integer-indexed collections of any object". In less technical language, an array is a bundle of variables. To visualize this, image that an array is a storage container, and we can place different things inside this container, be it boxes, loose items, big, small and anything in between, as long as it fits in the container, it can be stored. Now as we know, variables are just abstractions for things that can change, so we can visualize them as boxes, and its contents can change.
Let's take an example. We are going to make a container, and we are going to call it "wheels". And we are going to put three items inside it: the number 5 and a sign that says "your the best!". That would look like this: wheels = [5, "your the best!"]
Now that we have a container, we can look at the second part of the definition, "ordered, integer-indexed", which is fancy technical talk for "first come, first server." That is, each item inside the container "wheels" has been given a number as they are stored, which allows us to do some interesting things. To see it in action, we can ask "wheels" how many items it has like this: wheels.length
and the result would be => 2
, we can change the contents of the first box in the container like so: wheels[0]="Hive Five"
, which will result in wheels=["Hive Five","your the best!"]
.
The index is the slot in the array, so index zero has the value "Hive Five", index two has "your the best!", etc. And its ordered, so the next object that you add to the array will be placed at the end by default, unless you specify its position like this: wheels.insert(1,"big guy,")
which will cause the array to be: wheels=["Hive Five","big guy,", "your the best!"]
. We can also do fun stuff like concatinate all the items in array like so: wheels.join(" ")
and that returns a string "Hive Five big guy, your the best!"
.
We can also tons of things, like manipulate each element, or only ones that meet a certain criteria through iteration like: wheels.each{|word| word.upcase!}.join(" ")
which returns "HIVE FIVE BIG GUY, YOUR THE BEST!"
. As we can see, we can perform multiple actions, and they will be performed in sequence as they are noted on the command. In your example, each word is converted to all caps in place, so we changed the original array, and then we join all of the items with a space in between to result in string.
Those are just a few things that we can do with arrays; many more can be found by reading the documentation for ruby on the resources belew.
Hashes
Now the definition of a hash by the ruby documentation is as follows: "A Hash is a dictionary-like collection of unique keys and their values." In other words, its an association of one key and one value. Its like a two column matrix, except that the keys are all unique, so there can't be two keys named "John". This can be useful when you want to have a list of items where there is only one connection.
The best way to illustrate this is through an example. Let's say we need to keep track of what city people are located at a specific time. Because you can not be in two places at once, a hash would not allow keys(the person's name) entered into the hash more than once. The hash also doesn't have to be uniform, thus one person can enter their location in long, lat format, while another peorson can input a zip code, or an airport code.
Let's see it in action; we are going to have three people, with their location: location = {Alice:92010, Britney: "LAS", Barack: "Washington, D.C."}
. Now if we want to add one to the hash, we simple do the following: location["Barack"] = "White House"
.
Its important to note, that "Barack"
and Barack
are two different objects, that is why its allowed. The technical reason behind it is that when we use the location = {Barack:"White House"}
style, we are actually doing the following: location[:Barack] = "White House"
which is equivalent to location = {:Barack => "White House"}
, where as the other form is using a string to associate with another string. Placing the colon infront of the name creates a symbol vs a string. This will affect the hashes performance but only once the hash has a large number of enteries, otherwise the user will not see any difference in performance.
But if we did the following: location = {Alice:92010, Britney: "LAS", Barack: "Washington, D.C.", Barack: "White House"}
, there would be an error and the first value would be discarded, and only the last value stored. Hashes are better when we need to search for data, so if we want to know where Alice is, all we have to do is: location[:Alice]
. This is much better than remembering a number that corresponds to an index in an array. And if your key is not found in the hash, it will return a nil
. Now there are tons of things that we can do with hashes similar to the ones we did for arrays, and you can look at those in the documentation pages.


7. Best Practices¶
7.1. Froude number¶
One of the important non-dimensional number that describes diffrent flow regimes for open channel flow. It is a dimensionless quantity that is a ratio of the inertial and gravitational forces as \(Fr = \frac{V}{\sqrt{gD}}\). Here
V
is the water velocity,D
is the hydraulic depth across the cross-sectional area of the flow andg
is the gravity.It is important to calculate if the flow is sub-critical (Fr < 1) or critical (Fr = 1) or supercritical (Fr > 1). Critical flows are often unstable and sets up standing waves between sub and supercritical flows.
It is necessary to consider both the Froude number and Reynolds number to determine separation effects like breaking waves etc.
7.2. Meshing¶
Mesh checking is always important.
Hydro-UQ
performs a mesh check and the log is available for review after the simulation is complete. It is much recommended to review this.Mesh convergence study is critical to ensuring good and reliable results using CFD simulations.
7.3. Boundary conditions¶
7.4. SW-CFD domain sizes¶
Note that each degree of latitude is approximately 69 miles (111 kms apart). At Equator, the distance is 68.703 miles (110.567 kms), at Tropic of Cancer and Capricon it is 68.94 miles (110.948 kms) and at the poles it is 69.94 miles (111.699 kms).
60 minutes = 1 degree
For a 1-minute grid used in the SW-solver, this is approximately 2 x 2 kms grid (in terms of distances). Depending on the topography and bathymetry, this could still be a very large domain for the CFD simulation.
If the simulation type is SW-CFD coupling, then there can be wave reflections. Such wave-reflections can lead to unphysical fluid accumulation at the boundary.
7.5. Turbulence modeling¶
Compute the Reynolds number to determine if the flow is turbulent. Do not use turbulent models for laminar flows
Estimate the y+ and the thickness of the first cell layer. The ideal distance of the first node from the wall \(\Delta y\) can be estimated to be
\[\Delta y = L \cdot y^{+} \cdot \sqrt{74} \cdot {Re}_{L}^{-13/14}\]where \(L\) is the characteristic length scale, \(y^{+}\) is the desired values, \({Re}_{L}\) is the Reynolds number. The non-dimensionalised velocity (\(u^{+}\)) and distance from the wall (\(y^{+}\)), the velocity profile of the boundary layers takes on the form, as shown below by the red line in Fig. 7.5.1.
There are various online calculators that can be used to calculate the value of \(y^{+}\). Some examples of apps include: Google Play Store or Apple store .
If the flow is believed to be viscous, then the viscous sub-layers need to be resolved as shown in Fig. 7.5.2. When meshed correctly, a value of \(y^{+} \approx 1\) is desired. Alternatively, a wall model can be used bu having the first element in the region \(y^{+} > 30\). It is a good practice to avoid a \(y^{+}\) value between these values.
High Reynolds number flows (like aircraft, ships etc.) will experience boundary layers that extends to several thousand \(y^{+}\) units. However, for flows with low Reynolds numbers, the upper limit can be as little as 100 \(y^{+}\) units. Thus, it is necessary to ensure that the first node does not fall outside this range.
Hydro-UQ v1.0.0
supports \(k-\epsilon\) and \(k-\omega\) SST models. These are both good choices for general applications. The \(k-\epsilon\) model is very reliable and can often be used to get initial values for more sophisticated models.Hydro-UQ v1.0.0
presently supports only RANS simulations for turbulent modeling. In the future versions, LES simulation will also be supported.