Extended AssetTypes
This sample demonstrates the change which will happen once Extended AssetTypes are rolled out, and is meant to help test and verify the new behavoir in your application before the change happens.
You can find more information about the change here: https://www.developer.saxo/openapi/learn/extended-assettypes
You can request to get Extended AssetTypes by sending an extra header, the "Pragma" header oapi-x-extasset. This header makes the app behave like it is on Extended AssetTypes.
After a successful test, you can create a new app, so the AssetTypes are extended by default.
Using the oapi-x-extasset header
It is possible for an application that is not yet enabled for Extended AssetTypes to instruct OpenApi to act as if the application was configured for the Extended AssetType definition.
This is done by adding a header named 'Pragma' with the value 'oapi-x-extasset' in the request. Below are some examples of this. This header can be used for validation, but also to have groups of customers on Extended AssetTypes, and others on the legacy AssetTypes.
Response:
Click button to launch function.
JS code:
Click button to show code.


Every list sends requests to the server to receive data. A particular set of parameters should be sent for that.
In addition, if you saw our quick tour, you already know that our lists can reset the state of the parameters to their default values.
Probably, you also notice that our lists can be configured to save their state,
for example, in queryString
. If the builted link is sent to anyone else, he/she will get the list with the
same state of the sortings and paging as the sender has.
All this functionality can be easily implemented in the right-angled
library for the lists itself. But what
if you need to use some custom parameters? For example, when it is needed to add filter to the list? How to make it so
the filter value is sent to the server as a parameter, resetted to the default value on list state reset, serialized
in queryString
, and restored its value when page with such queryString
parameters is opened?
And, this functionality should be achieved with minimum of code to write. It is easy to remember that the component property should be added to the request parameters – as soon as we created it for this. The same as easy to forget to write the code to implement other features in the working rush. And sometimes it takes a long time to notice that our filter property is not resettled by the resetSettings method call. A long time after the app is passed to the end users.
To solve this issue we provide the @filter
annotation and RTFiltersService
service in the right-angled
library.
It is quite simple to use them. First of all, we mark the filter properties of our component by the @filter
annotation. If required, we can specify additional parameters described below.
Second, we register our component in the RTFiltersService
service (which is already configured in RTList
).
After that, the list will process properties of our component through all the described above scenarios in the same way
as its own ones.
Below there is a live example of the component which represents the list with the custom filters. As you can see, the component
properties are marked by the @filter
annotation, and the component is registered in the onListInit
event handler. Now these properties values are sent automatically in the server request, resetted by the "reset settings"
button, serialized to queryString
and restored from queryString
when page is loaded.
Additionally, we use json pipe and display the parameters of the last executed request under the table for you to see what parameters have been sent to the server.
To use filters functionality you just import @filter
annotation and annotate your component properties.
If you want to use the filter functionality separately from the lists, you can import RTFiltersService
service
into your component and configure it as a provider in the providers collection of your component declaration.
If you plan to use the rtRegisterAsFilter
directive, which is described below, you should import RTFiltersModule
(or RTModule
module which includes functionality of entire library) and add it into your AppModule
imports
array.
@filter
annotation options
When using the @filter
annotation, you can specify additional parameters regarding the FilterConfig contract. When you use the
@filter
annotation without parameters, this config is created anyway and initialized by the default values
we are describing below.
Also it is possible to pass string argument to the @filter
annotation. In this case, the default settings
are used; but parameterName
property will be setted to passed string value. It means that this overload
is the shorthand, allowing changing just the request parameter name.
The FilterConfig object parameters have the following purpose:
parameterName
- name of the parameter which is used on serialization/deserialization of properties. By default
the value of this property is equal to the name of the annotated property.
coerce
- specifies that the parameter value should be coerced to it’s real type on deserialization. For
example it means that "null" string will be converted to null
value, "true" string will be converted to
boolean true
, "1.0"string to 1.0
number and so on. Such approach is useful when the values
are read from queryString
. By default this parameter has true
value.
defaultValue
- the default value to which the annotated property will be set on “resetSettings” method
call. If this parameter is not specified, FiltersService will remember the value of annotated property at first use of any of the FiltersService methods as a default value.
emptyIsNull
- means that falsy values should be converted to null
when serialized as a request
parameter. By default this option is equal to false
.
ignoreOnAutoMap
- if this parameter is equal to true
, the value will not be applied to the
target property by the applyParams function. By default this parameter is equal to false
.
parseFormatter(rawValue: Object, allValues?: Object)
- custom function, which can be used to perform custom
parse logic of the values on applyParams function execution.
serializeFormatter(value: Object)
- custom function, which can be used to perform custom serialization
logic of the annotated property.
rtRegisterAsFilter
directive
In order to make the RTFiltersService
to know about our component as a parameter source and construct filters
from its properties, we can register our objects as filters with registerFilterTarget directive
In the first example of this section you could see how we register our component as a filter with the help of onListInit
event of the rtList
directive.
In other examples we have implement components, which inject RTFiltersService
service and register themselves
as filter in it.
There is also the third way to register object as filter. It goes well when your filter is a separate component. This third
way is the rtRegisterAsFilter
directive.
Below there is the example of using this directive. The list filter is implemented as a separate rt-demo-filter-area
component and is registered as a filter for the current list directly in the template with the help of the rtRegisterAsFilter
directive.


Connecting over authorised WebSockets without TLS enabled will transmit all information including username-password pairs in clear text. We highly recommend if using authorisation that TLS is enabled. The KDB+ server is also required to have TLS enabled for secure WebSockets to connect.
See the kx wiki SSL/TLS page for more information.
Connecting over TLS requires the KDB+ server to be in TLS mode and for its certificate to be valid. Self-signed certificates can be added to the browser's exception list on a browser-by-browser basis. An example of how to do this is provided here.
See the kx wiki SSL/TLS page for more information.


Annotation
Algorithm
Cursor size
Retrain
Export
Median filter
Experiment timer
Metadata
Filename
Duration
Segment size
{{segmentSize}} ms
Step size
{{stepSize}} ms
Datapoints
{{datapoints}}
Sampling
Audio
Sequential playback
Audio loading...
source
{{segmentSize}} ms
{{stepSize}} ms
{{datapoints}}
Audio loading...


{% extends "layout_picker.html" %} {% set serviceName = "Apply for an older person's bus pass" %} {% set pageTitle = "Your bus pass photo" %} {% block content %}
You can send your file to this computer using email, a memory card, or another file sharing method.
Get help sending a photo to this computer


Butter Chicken
| Prep time | 10 min |
| Cook time | 20-25 min |
| Total time | 45 min |
| Servings | 4 |
This is my own version of the oreo microwave mug cake. This chocolaty treat is truly great for nights when I need a yummy dessert that is ready in less than 7 minutes! The reason it is perfect is you can have it for breakfast and also as a night snack. The times when I have a sweet tooth but don't want to overload myself with an entire chocolate cake; not that I can't finish it but I am afraid that I would have to live with the shame. For such times, I need something small, single serving and guilt free - the solution is MUG Cake.
back to topIngredients
- Chicken Breast - 200gms
- Onion - 2
- Tomatoes - 3
- Salt,Pepper - 2/3 tsp
- Curd - 25 gms
- Butter - 50 gms
- Ginger Garlic Paste - 2+2 tsp
- Oil - Tabelspoons
- Spices - 1 tbsp (red chilli powder, turmeric)
- Coriander - to garnish
Method
- Step 1: Marinate
- Cut the chicken into pieces as desired. Add Salt 1 tsp salt and 1 tsp pepper. Add 2 tbsp ginger garlic paste. Add Turmeric and Red Chilli powder 1 tsp each. Add curd. Mix it all well and set this aside for 10~15min until you prep the rest of the steps
- Step 2: Chop
- Start chopping onions and tomatoes fine.
- Step 3: Fry
- Shallow fry the above marinated chicken until the chicken turns golden brown. (You can leave the chicken half cooked here). Keep this chicken aside.
- Step 4: Cook
- In the same pan, add the chopped onions, and let them fry until they turn golden. Now add the chopped tomatoes and keep stiring. Add the ginger garlic paste making some space in between the pan. Start adding the spices to this mix (red chilli powder - 1 tbsp, turmeric - 1/2 tbsp) and keep mixing it well.
- Step 5: Grind
- Take the above cooked mix and add it to the mixer to grind until fine paste is formed.
- Step 6: Boil
- In the same pan, add this fine paste. Add butter to this and let it cook for 2~3min. Add the above fried chicken to this and let it come to boil. Let it steam by placing a lid to the pan if necessary for another 7~8 min on medium flame.
Serving
In a bowl serve hot and add coriander for garnishing. Can be served with a side of bread or steamed rice.
back to topNutrition
- Calories 485
- Fat : 34.86g
- Carbohydrates : 10.36g
- Protein : 33.28g


Look: Beyoncé Gets Colorful AF In New Modeling Pics
by Team SOHHGrammy-winning singer Beyoncé is really on her modeling goals these days. On Tuesday, Queen Bey blessed the BeyHive with a fresh batch of slay-filled shots. Look and comment below!
Grammy-winning singer Beyoncé is really on her modeling goals these days. On Tuesday, Queen Bey blessed the BeyHive with a fresh batch of slay-filled shots. Look and comment below!


ERASER A film review by Andrew Hicks Copyright 1996 Andrew Hicks / Fatboy Productions
(1996) *** (out of four)
We remember the toned-down Arnold Schwarzenegger of the early 90's, a kinder, gentler man who wouldn't blow people away with machine guns anymore. In KINDERGARTEN COP the most violent he got was when he beat up on a man who beat his kid ("You hit de kid, I hit you").  In THE LAST ACTION HERO he murdered his lines as usual but no people. The crowd-pleasing TRUE LIES was violent but it was a parody of the kind of movies Schwarzenegger starred in during the 80's. It took him six years to return to a movie with a real old-fashioned, automatic weapon body count.
And that movie is ERASER, where Arnold plays Federal Marshal John Kruger, witness protector extraordinaire. His charge this time around is a defense contractor employee (Vanessa Williams) who has agreed to testify against her company's misappropriations of funds and weapons. ("I didn't know treason was in the corporate strategy," she announces to her boss.) All the evidence she needs is on a CD-ROM disc she carries with her through the duration of the movie. At first, she doesn't think she needs to go into hiding, but a late-night assault on her home convinces her to change her identity.
Luckily, Arnold is right there, disguised as a buff delivery boy, to save her from the bad guys, who have a new weapon that shoots electromagnetic pulses at "just under the speed of light." Of course, we can still see the pulses flying toward their targets, so I'd estimate Vanessa's "just under" comment to mean about 185,000 miles per second under the speed of light. But authenticity isn't important in a movie like this as long as we can see the pulses knocking their victims back through the wall.
Arnold brings Vanessa to a Chinatown apartment, where she burns all her forms of identification. "There goes all that I am," she laments, to his stone-faced reply, "What you are is in here [gesturing to the heart region] and they can't take that from you." I was worried at that point that the sense of humor Arnold has always had in his movies had completely gone to hell, but those fears were shattered a half-hour later when he shot an alligator in the zoo and quipped, "You're luggage!" (I didn't say Arnold had a _good_ sense of humor, just a sense of humor.)
"I suppose we won't see each other again," Vanessa says. "Not if all goes well," Arnold responds. And of course it doesn't. Arnold and Vanessa are reunited at the zoo not twenty minutes later, after he shoots the alligator and she shoots a corrupt marshal because he doesn't know the "secret handshake." We know by this point that most of the marshals are corrupt, including Arnold's boss (James Caan), who is in the process of selling millions of dollars in weapons to the Russian mafia, to "usher in a new era of world terrorism." Caan makes a good psycho villian and we all know Arnold makes a good wisecracking action hero.
After narrowly escaping death by Caan, Arnold jumps out of a plane, pulling a GOLDENEYE (and breaking the laws of physics) by free-falling faster than his parachute pack and opening it just in time, in just one of ERASER's blockbuster action sequences. Another one comes shortly thereafter, as Arnold and Vanessa break into her company to view the evidence on her magic disc. It's reminiscent of another 1996 summer movie, MISSION: IMPOSSIBLE, only much more inventive and entertaining.
The same could be said of the entire movie in comparison to MISSION: IMPOSSIBLE. That movie only had three action sequences amid a sea of unintelligible plot, whereas ERASER has almost wall-to-wall action and a plot Arnold himself could follow. It also has some genuinely funny scenes, unlike the straight-faced seriousness of Tom Cruise's action foray. After Arnold falls out of the sky during the parachute scene and lands atop a junkyard car, he gets up, brushes himself off and asks, "Where am I?" A little girl, in awe, replies, "Earth. Welcome."
While we're comparing ERASER with the other action films currently in release, I should point out that it's as good as or better than THE ROCK. Like that movie it mixes light-hearted humor with brutal violence. And Vanessa Williams is certainly a better sidekick to look at than the ape-like Nicholas Cage. Williams even does a decent job of acting, although all that's required of her is nervousness at the beginning, distress in the middle and loving admiration of Arnold at the end. It doesn't have an incredible amount of originality and its attempts at seriousness are met with as many laughs as the comic relief scenes, but ERASER is a constantly entertaining no-brainer that provides two hours of escape from the oppressive heat and boredom of summer.
--
Visit the Movie Critic at LARGE homepage at http://www.missouri.edu/~c667778/movies.html Serving America For Over 1/50 of a Century!
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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Our club's purpose is to host events such as viewing parties, amateur tournaments, and coaching for the enjoyment of eSports at Rose-Hulman Institute of Technology.
Our constitution can be found here.
This club was founded by Mason Schneider, Mark Hein, and Josh Wright on the belief that the Rose-Hulman community is one that loves competitive gaming and that a club was needed to increase the social factor of this type of hobby.


Jennifer McPeek
Unafffiliated
Independent consultant and Board Director. Currently a director of First American Funds and CBOE Global Markets. Previously, Chief Financial Officer of Russell Investments (2018-2019), Chief Operating Officer and CFO of Janus Capital Group (2008-2017).
Certified Financial Analyst (CFA), MS in Financial Engineering from MIT, BA in Economics and Mathematics from Duke University
80218
Donated to Presidential campaign for Michael Bennet in 2019. Donated to the Lincoln Project and to Joe Biden's campaign in 2020.
Warren Village - Board Member & Treasurer 2015-2018. First American Funds Board of Directors 2019-present. CBOE Global Markets Board of Directors 8/20-present.
As a public investment company company officer until 2017, I was limited in my participation in these types of groups. However, I did serve on the Board of the Warren Village for 3 years, and helped raise funds and direct their strategy. I am now starting to get involved in FairVote, advocating for ranked choice voting.
Election reform is a cause I am passionate about and I think my experience and objective approach can help. Would like to see districting become less arbitrary and use algorithms in the future. Am very opposed to gerrymandering, as I believe it is a form of election manipulation and it disenfranchises people. I am also more generally wanting to spend the next part of my professional life more focused on the public sector.
Consensus building is a delicate art, and the most important element is that all people feel heard and are encouraged to engage. I have decades of experience, including as a corporate executive, Board member, and management consultant, working with teams and bringing them to consensus around difficult issues. I am extremely fair and impartial in my approach to solving problems.
I began my career working as a consultant with McKinsey & Company for almost 7 years. There I received world class training in hypothesis-driven fact-based problem solving approaches. Later in my career as an executive I built my skills in bringing other people around to own the solutions.
female


This website is designed to help you organize your perfect holiday as well as enabling you to brows destintions. This website does no enable you to book destinations, however you are able to enquire for different locations.
We are a travel company that strives to help you find and plan the perfect holiday in Australia. We work hard to bring you the latest and best information about each of our travel destinations so that you can make an educated choice on where you would like to visit. Destination-Nation is here to help you plan your perfect holiday, so enquire now with your destination.


Institution Information
Name:
Phone:
Fax:
Email:
MasterCard Recurring Payment Cancellation Service (RPCS)
Use this form to cancel preauthorized electronic funds transfers, such as automatic bill payments and installment payments. You can use this form to block all future recurring payments to a specific merchant.
Card Number:
Transaction details
Settlement Date:
(you can locate the Settlement Date in SPC, use MM/DD/YYYY format)
Transaction Amount:
Network Sequence Number :
(you can locate the Network Sequence number in SPC)
Merchant Name:
Request type
Request type:
Add
Delete
Update
Block range (optional)
Use to block a specific range. If left blank, RPCS will block all transactions from merchant regardless of amount.
Transaction amount low:
Transaction amount high :
Purge date(optional):
(If you do not enter a date, RPCS will automatically enter a date 15 months from the date of the RPCS request, use MM/DD/YYYY format.)
Additional Comments


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java.lang.Object org.webcurator.domain.model.core.HarvestResult
public class HarvestResult
The HarvestResult
class describes the result of a harvest. It
contains and manages the resources.
| Field Summary | |
|---|---|
static int |
STATE_ABORTED
The state constant for a Harvest Result that has been aborted in indexing. |
static int |
STATE_ENDORSED
The state for an Endorsed HarvestResult - ready for archiving |
static int |
STATE_INDEXING
The state constant for a Harvest Result that is being indexed. |
static int |
STATE_REJECTED
The state constant for a Rejected HarvestResult - one that should not be archived |
| Constructor Summary | |
|---|---|
HarvestResult()
Construct a new HarvestResult. |
|
HarvestResult(HarvestResultDTO aResult,
TargetInstance aTargetInstance)
Create a new HarvestResult from its DTO. |
| Method Summary | |
|---|---|
void |
addModificationNote(java.lang.String str)
Safe way to add modification notes and ensure that they are truncated to the appropriate length to fit in the database. |
void |
addModificationNotes(java.util.List<java.lang.String> notes)
Safe way to add modification notes and ensure that they are truncated to the appropriate length to fit in the database. |
User |
getCreatedBy()
Get the User that created the harvest result. |
java.util.Date |
getCreationDate()
Get the date the result was created. |
java.lang.Integer |
getDerivedFrom()
Get the Harvest Number that this harvest was derived from. |
int |
getHarvestNumber()
Get the number of the harvest result. |
java.util.List<java.lang.String> |
getModificationNotes()
Get the list of modification notes. |
java.lang.Long |
getOid()
Get the primary key of the HarvestResult object. |
User |
getOwningUser()
Return the owner of this object. |
java.lang.String |
getProvenanceNote()
Get the provenance note that explains why this harvest was created. |
RejReason |
getRejReason()
Get the Rejection Reason of this harvest result (if any). |
java.lang.String |
getResourceName()
gets the Resource name of the WCT object, this may be different to the persisted name of the object |
java.util.Map<java.lang.String,HarvestResource> |
getResources()
Retrieve the map of resource names to HarvestResource objects. |
java.lang.String |
getResourceType()
gets the Class of the WCT object. |
int |
getState()
Get the state of this Harvest Result. |
TargetInstance |
getTargetInstance()
Get the target instance that this object belongs to. |
void |
setCreatedBy(User createdBy)
Set the creator of this harvest result. |
void |
setCreationDate(java.util.Date creationDate)
Set the creation date of the harvest result. |
void |
setDerivedFrom(java.lang.Integer derivedFrom)
|
void |
setHarvestNumber(int harvestNumber)
Set the number of the harvest result. |
void |
setModificationNotes(java.util.List<java.lang.String> modificationNotes)
|
void |
setOid(java.lang.Long oid)
Set the oid of the HarvestResult object. |
void |
setProvenanceNote(java.lang.String provenanceNote)
Set the provenance note on this HarvestResult. |
void |
setRejReason(RejReason rejReason)
Set the rejection reason for this harvest result. |
void |
setResources(java.util.Map<java.lang.String,HarvestResource> resources)
Set the Map of resource name to HarvestResource objects. |
void |
setState(int state)
Set the state of this harvest result. |
void |
setTargetInstance(TargetInstance targetInstance)
Set the target instance that this belongs to. |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
public static final int STATE_ENDORSED
public static final int STATE_REJECTED
public static final int STATE_INDEXING
public static final int STATE_ABORTED
| Constructor Detail |
|---|
public HarvestResult()
public HarvestResult(HarvestResultDTO aResult, TargetInstance aTargetInstance)
aResult
- The DTO.aTargetInstance
- The TargetInstance that this HarvestResult belongs to.| Method Detail |
|---|
public int getHarvestNumber()
public void setHarvestNumber(int harvestNumber)
harvestNumber
- The number of the harvest result.public java.lang.Long getOid()
getOid
in interface InTrayResource
public void setOid(java.lang.Long oid)
oid
- the primary key of the HarvestResult.public TargetInstance getTargetInstance()
public void setTargetInstance(TargetInstance targetInstance)
targetInstance
- The target instance that this belongs to.public java.util.Map<java.lang.String,HarvestResource> getResources()
public void setResources(java.util.Map<java.lang.String,HarvestResource> resources)
resources
- The Map of resource name to HarvestResource objects.public java.lang.String getProvenanceNote()
public void setProvenanceNote(java.lang.String provenanceNote)
provenanceNote
- The note that explains why this result was created.public java.util.Date getCreationDate()
public void setCreationDate(java.util.Date creationDate)
creationDate
- The creation date of the harvest result.public User getCreatedBy()
public void setCreatedBy(User createdBy)
createdBy
- The User object for the user that created this object.public RejReason getRejReason()
public void setRejReason(RejReason rejReason)
rejReason
- The RejReason object.public int getState()
public void setState(int state)
state
- the state to setpublic void addModificationNotes(java.util.List<java.lang.String> notes)
notes
- A List of notes to add.public void addModificationNote(java.lang.String str)
str
- The note to add.public java.util.List<java.lang.String> getModificationNotes()
public void setModificationNotes(java.util.List<java.lang.String> modificationNotes)
public java.lang.Integer getDerivedFrom()
public void setDerivedFrom(java.lang.Integer derivedFrom)
public java.lang.String getResourceName()
InTrayResource
getResourceName
in interface InTrayResource
public java.lang.String getResourceType()
InTrayResource
getResourceType
in interface InTrayResource
public User getOwningUser()
UserOwnable
getOwningUser
in interface UserOwnable
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Osiris Jailbreak
for all 64-Bit devices on iOS 11.2 -> 11.3.1
WARNING!
This is a work-in-progress Jailbreak and it should NOT be used by inexperienced users. This jailbreak is not meant for public usage.  Use at your own risk (or better don't).
Working Features:
- Escapes the SandBox
- Patches AMFI (CodeSign)
- Remounts ROOT FS as R/W on iOS 11.2.x
- Disables the iOS Updates and removes already downloaded ones
- Spawns a remote shell that can be accessed through netcat on port 69
What needs to be implemented
- The whole code-base can be improved
- Doesn't contain Cydia and will not
- Dropbear needs to be fixed for real SSH
- Remounting doesn't yet work on iOS 11.3.x
- The empty_list exploit is very unstable. This results in a lot of reboots.


ESD-CONFIG(1) Enlightened Sound Daemon ESD-CONFIG(1) NAME esd-config - The Enlightened Sound Daemon DESCRIPTION esd-config is a tool that is used to configure to determine the com‐ piler and linker flags that should be used to compile and link pro‐ grams that use EsounD. It is also used internally to the .m4 macros for GNU autoconf that are included with EsounD. USAGE esd-config [--prefix[=DIR]] [--exec-prefix[=DIR]] [--version] [--libs] [--cflags] --version Print the currently installed version of EsounD on the standard output. --libs Print the linker flags that are necessary to link an EsounD program. --cflags Print the compiler flags that are necessary to compile an EsounD program. --prefix=PREFIX If specified, use PREFIX instead of the installation prefix that EsounD was built with when computing the output for the --cflags and --libs options. This option is also used for the exec pre‐ fix if --exec-prefix was not specified. This option must be specified before any --libs or --cflags options. --exec-prefix=PREFIX If specified, use PREFIX instead of the installation exec prefix that EsounD was built with when computing the output for the --cflags and --libs options. This option must be specified before any --libs or --cflags options. SEE ALSO esd(1), esdcat(1), esddsp(1), esdloop(1), esdplay(1), esdsample(1), esd‐ ctl(1), esdfilt(1), esdmon(1), esdrec(1) 3rd Berkeley Distribution EsounD 0.2.41 ESD-CONFIG(1)


Match Play. Red leads 2-0 to 5. How should Red play 31?
pips Red=39 White=133
(CorrectAnswer= 0/0, ErrorScore= 0)
Both 4/off and 5/2*, 3/2 win the same percentage of games but the pointing play wins 3% more gammons. Those 9 rolls out of 36 that White stays on the bar is the difference.
This is partly a pay-me-now, pay-me-later problem but the key is those extra gammons after the pointing play. The increase in gammon percentage is something that is often overlooked.
This is partly a pay-me-now, pay-me-later problem but the key is those extra gammons after the pointing play. The increase in gammon percentage is something that is often overlooked.
1. Cubeful 2-ply 5/2* 3/2 Eq.: +1.282 0.899 0.617 0.125 - 0.101 0.000 0.000 2. Cubeful 2-ply 4/off Eq.: +1.249 (-0.033) 0.889 0.615 0.151 - 0.111 0.000 0.000 3. Cubeful 0-ply 5/4 5/2* Eq.: +1.077 (-0.205) 0.852 0.544 0.083 - 0.148 0.000 0.000 4. Cubeful 0-ply 5/4 3/off Eq.: +0.872 (-0.410) 0.809 0.452 0.070 - 0.191 0.000 0.000 5. Cubeful 0-ply 3/2* 3/off Eq.: +0.809 (-0.473) 0.787 0.453 0.070 - 0.213 0.000 0.000


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Cafe Paradiso Potts Point NSW
I took a friend here for lunch today, and we had a pretty good experience, and we had a pretty good experience. More
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Thanks for your review. I took Marry to Paradiso and loved atmosphere and food. We even spotted Baz Lurman there. More
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There are three types of Gauges you can create:
You can make thick and thin gauges by varying its 'thick' property.
There are many other customizations, you can do to match your needs.
angular-gauge is an ongoing development project.
You can contribute here.


Here is an intro. On the other hand, we denounce with righteous indignation and dislike men who are so beguiled and demoralized by the charms of pleasure of the moment, so blinded by desire, that they cannot foresee the pain and trouble that are bound to ensue; and equal blame belongs to those who fail in their duty through weakness of will, which is the same as saying through shrinking from toil and pain.
But in certain circumstances and owing to the claims of duty or the obligations of business it will frequently occur that pleasures have to be repudiated and annoyances accepted.
The wise man therefore always holds in these matters to this principle of selection: he rejects pleasures to secure other greater pleasures, or else he endures pains to avoid worse pains.


{% assets "css_login" -%} {%- endassets %}
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Upcoming Games with Ray Tracing Support!
by Mike SandersThe games industry hasn’t exactly been rushing out releases that offer ray tracing support. In fact, to date, there’s only a handful that officially allows you to get the best potential from your Nvidia 20XX RTX graphics card.
With both AMD and Intel expected to release their own hardware dedicated ray tracing solutions in 2020, however, things are undoubtedly set to get far more interesting in the very near future.
Upcoming Games with Ray Tracing Support!
If you are the owner of an Nvidia 20XX graphics card and have so far been disappointed with the RTX supported releases, then you may have one eye on upcoming games that are touting ray tracing as a key feature.
In a list we plan to update regularly, however, you can below check out some of the biggest upcoming game releases with ray tracing support confirmed!
If you are, incidentally, unaware of games or applications that do currently offer ray tracing support, you can check out the link here! – It’s not exactly huge, but as you can see below, it is set to get a lot bigger!
Cyberpunk 2077
Release date: April 16th, 2020.
Minecraft
This one is a little bit more interesting and unclear. Officially ray-tracing support is currently available for the game via mods. In terms of an official update, however, there has been something of a ‘flip flop’ attitude as to whether this will happen.
So, this kind of already exists, but not officially, and may never do. We’ll have to wait and see. Sorry if that sounds complicated.
Watchdogs Legions
Release date: March 6th, 2020.
Vampire: The Masquerade – Bloodlines 2
Release date: March 2020.
Synced Off-Planet
Release date: TBC
Dying Light 2
Release date: 2020
Atomic Heart
Release date: TBC (Possibly late 2019 albeit 2020 seems more likely at the time of writing)
Unconfirmed or Open to Speculation Ray Tracing Releases
There are a number of upcoming releases that have yet to receive any confirmed RTX support but may include it on launch. These include:
- Assetto Corsa Competizione (Latest news seemingly confirms against ray tracing support).
- Enlisted
- MechWarrior 5: Mercenaries
- Red Dead Redemption 2 (pretty unlikely)
We should note that this isn’t every rumoured ray tracing release, but some of the more interesting (and more likely) amongst the speculated.
Anything Else on the Way from developers or Nvidia?
As we noted earlier, despite ray-tracing still getting a somewhat tepid response from game developers we can expect a lot more titles to start including support for it in 2020. So if you want to check out any releases on the way, be sure to bookmark this page as we plan to update it regularly!
For more information on the 20XX graphics cards and the RTX features, you can check out the official Nvidia website via the link here! What do you think? What game/s would you most like to see get the ray tracing treatment? – Let us know in the comments!


Stock Market
Stock Market
Chart the stock market with Chart.js and Socket.io.
Add Stock
Click to remove a stock.


{% extends "layout.html" %} {% block body %}
Would you do it more likely on week days , week-end or both ?
Typically, you would start around 1 p.m. and end around 3 p.m.
{# Answer the same question in another city {% for c in cities %} {{ c.long }} {% endfor %} or #} {% if next == 'end' %} Submit your last answer {% else %} Go to the next question {% endif %}


Release notes
ShowyEdge 5.6.0
- 📦 Download
- 📅 Release date
- May 14, 2023
- ⚡ Improvements
- Became sandboxed app.
- Enabled the setting of
Open at login
by default.
ShowyEdge 5.5.0
- 📦 Download
- 📅 Release date
- May 7, 2022
- ⚡ Improvements
- Sparkle Framework has been updated.
ShowyEdge 5.4.0
- 📦 Download
- 📅 Release date
- Jan 29, 2022
- ✨ New Features
Use pill shape
configuration has been added. (Thanks to @natanrolnik)
- ⚡ Improvements
- Sparkle Framework has been updated.
ShowyEdge 5.3.0
- 📦 Download
- 📅 Release date
- Nov 4, 2021
- ⚡ Improvements
- Update application icons. (Thanks to Kouji TAMURA)
- Minor source code improvement.
- Sparkle Framework has been updated.
ShowyEdge 5.2.0
- 📦 Download
- 📅 Release date
- Aug 17, 2021
- 💥 Breaking Changes
- macOS 10.15 Catalina support has been dropped.
- The indicator height configuration has been changed to absolute px from the ratio of the menu bar.
- 🐛 Bug Fixes
- Fixed an issue that indicator is not shown when the menu bar is hidden.
- ⚡ Improvements
- Completely rewritten in Swift and SwiftUI.
ShowyEdge 4.0.0
- 📦 Download
- 📅 Release date
- Jul 24, 2020
- ✨ New Features
- Supported both Intel-based Macs and Apple Silicon Macs.
- Added an icon to menu bar.
- 🐛 Bug Fixes
- Fixed
Hide indicator when full screen
when multiple displays are connected.
- Fixed
- 💥 Breaking Changes
- macOS 10.9 - 10.14 support has been dropped.
ShowyEdge 3.8.0
- 📦 Download
- 📅 Release date
- Apr 4, 2020
- ⚡ Improvements
- “Check for updates” has been improved.
- Updated Sparkle signing to EdDSA (ed25519) from DSA.
- URL of appcast.xml has been updated.
- “Check for updates” has been improved.
ShowyEdge 3.7.0
- 📦 Download
- 📅 Release date
- Dec 19, 2019
- ✨ New Features
- Indicator options have been added:
Hide indicator when full screen
option.Show indicator behind app windows
option.
- New custom frame options have been added:
- Set width and height in percentages.
- Choose origin from upper-left, lower-left, upper-right and lower-right.
- Indicator options have been added:
ShowyEdge 3.6.0
- 📦 Download
- 📅 Release date
- Oct 17, 2019
- ✨ New Features
- Dark Mode has been supported.
- Set transparency (20%) forcely if the indicator size is larger than the menu bar height in order to avoid the indicator hides all windows.
- ⚡ Improvements
- Sparkle Framework has been updated.
ShowyEdge 3.3.0
- 📦 Download
- 📅 Release date
- Oct 28, 2018
- ⚡ Improvements
- ShowyEdge has been notarized for macOS Mojave.
ShowyEdge 3.2.0
- 📦 Download
- 📅 Release date
- Mar 23, 2017
- ✨ New Features
- An opacity slider has been added to color picker.
ShowyEdge 3.1.0
- 📦 Download
- 📅 Release date
- Apr 17, 2016
- ✨ New Features
- “Colors layout orientation” setting has been added.
- ⚡ Improvements
- The behavior of starting ShowyEdge on system startup has been improved.
- The preferences window UI has been improved.
- Memory usage has been reduced.
ShowyEdge 3.0.0
- 📦 Download
- 📅 Release date
- Dec 3, 2015
- 💥 Breaking Changes
- macOS 10.8 support has been dropped.
- macOS 10.7 support has been dropped.
- ⚡ Improvements
- ShowyEdge Preferences became resizable.
- Sparkle Framework has been updated.
ShowyEdge 2.2.0
- 📦 Download
- 📅 Release date
- Aug 30, 2015
- ⚡ Improvements
- Close button has been added.
- “Check for updates” (Sparkle) has been updated.
ShowyEdge 2.1.0
- 📦 Download
- 📅 Release date
- Dec 2, 2014
- ⚡ Improvements
- Multiple displays support has been improved. The indicator is shown in the all screen.
- Quit button has been added.
ShowyEdge 2.0.0
- 📦 Download
- 📅 Release date
- Aug 24, 2014
- 💥 Breaking Changes
- The minimum OS version requirement has been changed. (macOS 10.6 -> macOS 10.7)
- ⚡ Improvements
- “Check for updates” (Sparkle) has been updated.
ShowyEdge 1.8.0
- 📦 Download
- 📅 Release date
- Mar 13, 2014
- ✨ New Features
- Multiple displays have been supported.
ShowyEdge 1.7.0
- 📦 Download
- 📅 Release date
- Oct 18, 2013
- ✨ New Features
- Added “Indicator opacity” configuration.
- ⚡ Improvements
- Signed with Developer ID.
ShowyEdge 1.6.0
- 📦 Download
- 📅 Release date
- Oct 13, 2013
- ✨ New Features
- Added “Use custom frame” configuration.
- Added “Show icon in Dock” configuration.
- 🐛 Bug Fixes
- Fixed minor issues.
ShowyEdge 1.4.0
- 📦 Download
- 📅 Release date
- Jun 16, 2013
- 🐛 Bug Fixes
- Revised file permissions.
ShowyEdge 1.3.0
- 📦 Download
- 📅 Release date
- Jun 14, 2013
- ✨ New Features
- First release.


Leslie assigned to caravan Colin assigned to induction cam
no sex in public L33 supervisor of insulation Captain needs to see manwell
schedule brand meeting Astralship3D


Smart Wearables
Men
Women
Kids
Kid's Collection of
Smart Wearables
One stop place for awesome collection of wide variety of
Smart Wearables.


{% extends "base.html" %} {% block title %} {% if request.user == object %}Delete your account? {% else %}Delete {{ object.username }}'s account? {% endif %} {% endblock %} {% block content %} {% if request.user == object %}
Are you sure you want to delete your account?
Are you sure you want to delete the user "{{ object }}"?
This action cannot be undone!


{% include 'memberaudit/partials/character_viewer/sidebar.html' %}
{% include 'memberaudit/partials/character_viewer/overview.html' %}
{% include 'memberaudit/partials/character_viewer/tabs_navigation.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/assets.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/character_attributes.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/contacts.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/character_bio.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/contracts.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/corporation_history.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/skill_sets.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/implants.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/jump_clones.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/loyalty.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/mails.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/skills.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/skill_queue.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/wallet_journal.html' %}
{% include 'memberaudit/partials/character_viewer/tabs/wallet_transactions.html' %}
{% include 'memberaudit/modals/character_viewer/asset_container.html' %}
{% include 'memberaudit/modals/character_viewer/contract.html' %}
{% include 'memberaudit/modals/character_viewer/mail.html' %}
{% include 'memberaudit/modals/character_viewer/character_skill_set_details.html' %}
{% endblock details %}
{% block extra_javascript %}
{% include 'bundles/datatables-js.html' %}
{% include 'bundles/moment-js.html' with locale=True %}
{% endblock extra_javascript %}
{% block extra_css %}
{% include 'bundles/datatables-css.html' %}
{% endblock extra_css %}
{% block extra_script %}
{% endblock extra_script %}


Hi I'm Jake. welcome to my page! I hope you like it!
Hey my name is Jacob Jensen! my friends have always called me Jake or JJ when I used to play sports like soccer and football my teammates called me J Twice. I have been interested in coding since I was in high-school. After I graduated I went to Arizona to go to college but I decided that it wasnt for me and decided I wanted to travel for a while. I moved to Montana, then Taiwan, and then to cambodia. I spent about 3 months in each place. I finally decied to move home to portland and try to do school again and Epicodus was right for me.
I have worked since I was 15 years old starting as a preschool teacher, I also worked nights at a icecream shop in vancouver. Working and having a good work ethic has always been really important to me. After I moved back home from college I started working at costco, then a stone masonry and finally at a small cafe called Boomerang.
I hope you enjoy my page!


Our main goal is to promote safe bicycling nationwide, but starting in the Greater Rochester area. We want to help people become healthy and environmentally friendly, while making friends and having fun!
We are a non-profit organization dedicated to facilitating bicycling amongst people of all age and ability levels. Our passion for bicycling is inexpressible. We provide a variety of different services and programs such as bicycling classes, bike repairs, safety equipment, educating people of the benefits of biking and more!
3690 East Avenue Rochester, NY 14618 Hours: Monday 10AM-5PM Tuesday 11AM-8PM Wednesday 10AM-5PM Thursday 11AM-8PM Friday 10AM-5PM Saturday 9AM- 9PM Sunday 1PM-6PM


-a, --all
Insert all module names on the command line.
-b, --use-blacklist
This option causes modprobe to apply the
blacklist commands in the configuration files (if any) to module names
as well. It is usually used by udev(7).
-C, --config
This option overrides the default configuration directory
(/etc/modprobe.d).
This option is passed through install or remove
commands to other modprobe commands in the MODPROBE_OPTIONS
environment variable.
-c, --showconfig
Dump out the effective configuration from the config
directory and exit.
--dump-modversions
Print out a list of module versioning information
required by a module. This option is commonly used by distributions in order
to package up a Linux kernel module using module versioning deps.
-d, --dirname
Root directory for modules, / by default.
--first-time
Normally, modprobe will succeed (and do nothing)
if told to insert a module which is already present or to remove a module
which isn't present. This is ideal for simple scripts; however, more
complicated scripts often want to know whether modprobe really did
something: this option makes modprobe fail in the case that it actually didn't
do anything.
--force-vermagic
Every module contains a small string containing important
information, such as the kernel and compiler versions. If a module fails to
load and the kernel complains that the "version magic" doesn't
match, you can use this option to remove it. Naturally, this check is there
for your protection, so using this option is dangerous unless you know what
you're doing.
This applies to any modules inserted: both the module (or alias)
on the command line and any modules on which it depends.
--force-modversion
When modules are compiled with CONFIG_MODVERSIONS set, a
section detailing the versions of every interfaced used by (or supplied by)
the module is created. If a module fails to load and the kernel complains that
the module disagrees about a version of some interface, you can use
"--force-modversion" to remove the version information altogether.
Naturally, this check is there for your protection, so using this option is
dangerous unless you know what you're doing.
This applies any modules inserted: both the module (or alias) on
the command line and any modules on which it depends.
-f, --force
Try to strip any versioning information from the module
which might otherwise stop it from loading: this is the same as using both
--force-vermagic and
--force-modversion. Naturally, these checks
are there for your protection, so using this option is dangerous unless you
know what you are doing.
This applies to any modules inserted: both the module (or alias)
on the command line and any modules it on which it depends.
-i, --ignore-install, --ignore-remove
This option causes modprobe to ignore
install and remove commands in the configuration file (if any)
for the module specified on the command line (any dependent modules are still
subject to commands set for them in the configuration file). Both
install and remove commands will currently be ignored when this
option is used regardless of whether the request was more specifically made
with only one or other (and not both) of --ignore-install or
--ignore-remove. See modprobe.d(5).
-n, --dry-run, --show
This option does everything but actually insert or delete
the modules (or run the install or remove commands). Combined with -v,
it is useful for debugging problems. For historical reasons both
--dry-run and --show actually mean the same thing and are
interchangeable.
-q, --quiet
With this flag, modprobe won't print an error
message if you try to remove or insert a module it can't find (and isn't an
alias or install/remove command). However, it will still return
with a non-zero exit status. The kernel uses this to opportunistically probe
for modules which might exist using request_module.
-R, --resolve-alias
Print all module names matching an alias. This can be
useful for debugging module alias problems.
-r, --remove
This option causes
modprobe to remove rather than
insert a module. If the modules it depends on are also unused,
modprobe
will try to remove them too. Unlike insertion, more than one module can be
specified on the command line (it does not make sense to specify module
parameters when removing modules).
There is usually no reason to remove modules, but some buggy
modules require it. Your distribution kernel may not have been built to
support removal of modules at all.
-S, --set-version
Set the kernel version, rather than using uname(2)
to decide on the kernel version (which dictates where to find the
modules).
--show-depends
List the dependencies of a module (or alias), including
the module itself. This produces a (possibly empty) set of module filenames,
one per line, each starting with "insmod" and is typically used by
distributions to determine which modules to include when generating
initrd/initramfs images. Install commands which apply are shown
prefixed by "install". It does not run any of the install commands.
Note that modinfo(8) can be used to extract dependencies of a module
from the module itself, but knows nothing of aliases or install
commands.
-s, --syslog
This option causes any error messages to go through the
syslog mechanism (as LOG_DAEMON with level LOG_NOTICE) rather than to standard
error. This is also automatically enabled when stderr is unavailable.
This option is passed through install or remove
commands to other modprobe commands in the MODPROBE_OPTIONS
environment variable.
-V, --version
Show version of program and exit.
-v, --verbose
Print messages about what the program is doing. Usually
modprobe only prints messages if something goes wrong.
This option is passed through install or remove
commands to other modprobe commands in the MODPROBE_OPTIONS
environment variable.


Q. 99. What is the ninth commandment? A. The ninth commandment is, Thou shalt not bear false witness against thy neighbor.
Q. 100. What does the ninth commandment teach us? A. To tell the truth.


Performing comprehensive quality control (QC) is necessary to remove poor quality cells for downstream analysis of single-cell RNA sequencing (scRNA-seq) data. Within droplet-based scRNA-seq data, droplets containing cells must be differentiated from empty droplets. Therefore, assessment of the data is required, for which various QC algorithms have been developed. In singleCellTK (SCTK), we have written convenience functions for several of these tools. In this guide, we will demonstrate how to use these functions to perform quality control on unfiltered, droplet data. (For definition of droplet data, please refer this documentation.)
The package can be loaded using the library()
command.
SCTK takes in a SingleCellExperiment
object from the SingleCellExperiment
package. We will utilize the 10X PBMC 4K dataset as an example. For the
QC of droplet-based counts data, we will install the dataset from the
10X Genomics website using the BiocFileCache
package.
# Install BiocFileCache if is it not already
if (!requireNamespace("BiocFileCache", quietly = TRUE)) {
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("BiocFileCache")
}
library("BiocFileCache")
bfc <- BiocFileCache::BiocFileCache("raw_data", ask = FALSE)
raw.path <- bfcrpath(bfc, file.path(
"http://cf.10xgenomics.com/samples",
"cell-exp/2.1.0/pbmc4k/pbmc4k_raw_gene_bc_matrices.tar.gz"
))
untar(raw.path, exdir = file.path(tempdir(), "pbmc4k"))
fname <- file.path(tempdir(), "pbmc4k/raw_gene_bc_matrices/GRCh38")
pbmc4k.droplet <- DropletUtils::read10xCounts(fname, col.names = TRUE)
### change the sample column
names(colData(pbmc4k.droplet)) <- c("sample", "Barcode")
colData(pbmc4k.droplet)$sample <- rep("pbmc4k", ncol(colData(pbmc4k.droplet)))
SCTK also supports the importing of single-cell data from the
following platforms: 10X
CellRanger, STARSolo,
BUSTools, SEQC, DropEST, Alevin,
as well as dataset already stored in SingleCellExperiment
object and AnnData
object. To load your own input data, please refer
Function Reference for pre-processing tools
under
Console Analysis
section in Import data into SCTK for detailed
instruction.
All droplet-based QC functions are able to be run under the wrapper
function runDropletQC()
. By default all possible QC
algorithms will be run.
pbmc4k.droplet <- runDropletQC(pbmc4k.droplet)
## Tue Oct 25 16:08:34 2022 ... Running 'perCellQCMetrics'
## Tue Oct 25 16:08:35 2022 ... Running 'emptyDrops'
## Tue Oct 25 16:08:48 2022 ... Running 'barcodeRanks'
If users choose to only run a specific set of algorithms, they can
specify which to run with the algorithms
parameter.
After running QC functions with SCTK, the output will be stored in
the colData
slot of the SingleCellExperiment
object.
## DataFrame with 5 rows and 16 columns
## sample Barcode sum detected
## <character> <character> <numeric> <integer>
## AACCGCGGTTGAGGTG-1 pbmc4k AACCGCGGTTGAGGTG-1 1 1
## CAAGAAAAGTCCAGGA-1 pbmc4k CAAGAAAAGTCCAGGA-1 2 2
## TCTCTAAAGCGCCTCA-1 pbmc4k TCTCTAAAGCGCCTCA-1 0 0
## ATTATCCAGCGTCAAG-1 pbmc4k ATTATCCAGCGTCAAG-1 4 4
## GAGCAGAGTCCAACTA-1 pbmc4k GAGCAGAGTCCAACTA-1 0 0
## percent.top_50 percent.top_100 percent.top_200
## <numeric> <numeric> <numeric>
## AACCGCGGTTGAGGTG-1 100 100 100
## CAAGAAAAGTCCAGGA-1 100 100 100
## TCTCTAAAGCGCCTCA-1 NaN NaN NaN
## ATTATCCAGCGTCAAG-1 100 100 100
## GAGCAGAGTCCAACTA-1 NaN NaN NaN
## percent.top_500 total dropletUtils_emptyDrops_total
## <numeric> <numeric> <integer>
## AACCGCGGTTGAGGTG-1 100 1 1
## CAAGAAAAGTCCAGGA-1 100 2 2
## TCTCTAAAGCGCCTCA-1 NaN 0 0
## ATTATCCAGCGTCAAG-1 100 4 4
## GAGCAGAGTCCAACTA-1 NaN 0 0
## dropletUtils_emptyDrops_logprob
## <numeric>
## AACCGCGGTTGAGGTG-1 NA
## CAAGAAAAGTCCAGGA-1 NA
## TCTCTAAAGCGCCTCA-1 NA
## ATTATCCAGCGTCAAG-1 NA
## GAGCAGAGTCCAACTA-1 NA
## dropletUtils_emptyDrops_pvalue
## <numeric>
## AACCGCGGTTGAGGTG-1 NA
## CAAGAAAAGTCCAGGA-1 NA
## TCTCTAAAGCGCCTCA-1 NA
## ATTATCCAGCGTCAAG-1 NA
## GAGCAGAGTCCAACTA-1 NA
## dropletUtils_emptyDrops_limited dropletUtils_emptyDrops_fdr
## <logical> <numeric>
## AACCGCGGTTGAGGTG-1 NA NA
## CAAGAAAAGTCCAGGA-1 NA NA
## TCTCTAAAGCGCCTCA-1 NA NA
## ATTATCCAGCGTCAAG-1 NA NA
## GAGCAGAGTCCAACTA-1 NA NA
## dropletUtils_BarcodeRank_Knee
## <integer>
## AACCGCGGTTGAGGTG-1 0
## CAAGAAAAGTCCAGGA-1 0
## TCTCTAAAGCGCCTCA-1 0
## ATTATCCAGCGTCAAG-1 0
## GAGCAGAGTCCAACTA-1 0
## dropletUtils_BarcodeRank_Inflection
## <integer>
## AACCGCGGTTGAGGTG-1 0
## CAAGAAAAGTCCAGGA-1 0
## TCTCTAAAGCGCCTCA-1 0
## ATTATCCAGCGTCAAG-1 0
## GAGCAGAGTCCAACTA-1 0
| sample | Barcode | sum | detected | percent.top_50 | percent.top_100 | percent.top_200 | percent.top_500 | total | dropletUtils_emptyDrops_total | dropletUtils_emptyDrops_logprob | dropletUtils_emptyDrops_pvalue | dropletUtils_emptyDrops_limited | dropletUtils_emptyDrops_fdr | dropletUtils_BarcodeRank_Knee | dropletUtils_BarcodeRank_Inflection | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AACCGCGGTTGAGGTG-1 | pbmc4k | AACCGCGGTTGAGGTG-1 | 1 | 1 | 100 | 100 | 100 | 100 | 1 | 1 | NA | NA | NA | NA | 0 | 0 |
| CAAGAAAAGTCCAGGA-1 | pbmc4k | CAAGAAAAGTCCAGGA-1 | 2 | 2 | 100 | 100 | 100 | 100 | 2 | 2 | NA | NA | NA | NA | 0 | 0 |
| TCTCTAAAGCGCCTCA-1 | pbmc4k | TCTCTAAAGCGCCTCA-1 | 0 | 0 | NaN | NaN | NaN | NaN | 0 | 0 | NA | NA | NA | NA | 0 | 0 |
| ATTATCCAGCGTCAAG-1 | pbmc4k | ATTATCCAGCGTCAAG-1 | 4 | 4 | 100 | 100 | 100 | 100 | 4 | 4 | NA | NA | NA | NA | 0 | 0 |
| GAGCAGAGTCCAACTA-1 | pbmc4k | GAGCAGAGTCCAACTA-1 | 0 | 0 | NaN | NaN | NaN | NaN | 0 | 0 | NA | NA | NA | NA | 0 | 0 |
| QC output | Description | Methods | Package/Tool |
|---|---|---|---|
sum |
Total counts | runPerCellQC() |
scater |
detected |
Total features | runPerCellQC() |
scater |
percent_top |
% Expression coming from top features | runPerCellQC() |
scater |
subsets_* |
sum, detected, percent_top calculated on specified gene list | runPerCellQC() |
scater |
dropletUtils_emptyDrops_total |
Total counts | runEmptyDrops() |
DropletUtils |
dropletUtils_emptyDrops_logprob |
The log-probability of droplet being empty | runEmptyDrops() |
DropletUtils |
dropletUtils_emptyDrops_pvalue |
Monte Carlo p-value of droplet being empty | runEmptyDrops() |
DropletUtils |
dropletUtils_emptyDrops_limited |
Whether a lower p-value could be obtained by increasing niters | runEmptyDrops() |
DropletUtils |
dropletUtils_emptyDrops_fdr |
p-value of droplet being empty, corrected for false detection rate | runEmptyDrops() |
DropletUtils |
dropletUtils_BarcodeRank_Knee |
Whether total UMI count value is higher than knee point | runBarcodeRankDrops() |
DropletUtils |
dropletUtils_BarcodeRank_Inflection |
Whether total UMI count value is higher than inflection point | runBarcodeRankDrops() |
DropletUtils |
Instead of running all quality control methods on the dataset at once, users may elect to execute QC methods individually. The parameters as well as the outputs to individual QC functions are described in detail as follows:
It is crucial to distinguish the data occurring from real cells and
empty droplets containing ambient RNA. SCTK employs the EmptyDrops
algorithm from the DropletUtils
package to test for empty droplets. The wrapper function
runEmptyDrops()
can be used to separately run the
EmptyDrops algorithm on its own.
lower
is the lower bound of the total UMI count, in
which all barcodes below the lower bound are assumed to be empty
droplets.niters
is the number of iterations the function will
run for the calculation.testAmbient
indicates whether results should be
returned for barcodes that have a total UMI count below what is
specified in lower
.
pbmc4k.droplet <- runEmptyDrops(
inSCE = pbmc4k.droplet,
useAssay = "counts",
lower = 100,
niters = 10000
)
BarcodeRanks
from the DropletUtils
package computes barcode rank statistics and identifies the knee and
inflection points on the total count curve. The knee and inflection
points on the curve represent the difference between empty droplets and
cell-containing droplets with much more RNA. The wrapper function
runBarcodeRankDrops()
can be used to separately run the
BarcodeRanks algorithm on its own.
lower
is the lower bound of the total UMI count, in
which all barcodes below the lower bound are assumed to be empty
droplets.
pbmc4k.droplet <- runBarcodeRankDrops(
inSCE = pbmc4k.droplet,
useAssay = "counts",
fitBounds = NULL, df = 20
)
Upon running runDropletQC()
or any of the individual
droplet QC functions, the QC outputs will need to be plotted. For each
QC method, SCTK provides a specialized plotting function.
The wrapper function plotEmptyDropsResults()
can be used
to plot the results from the EmptyDrops algorithm. This will visualize
the empty droplets, by plotting the total UMI counts against the log
probability for each barcode.
emptyDropsResults <- plotEmptyDropsResults(
inSCE = pbmc4k.droplet,
axisLabelSize = 20,
sample = NULL,
fdrCutoff = 0.01,
dotSize = 0.5,
defaultTheme = TRUE
)
emptyDropsResults$scatterEmptyDrops
Data points are colored by FDR values, where we see a small portion of the dataset contains barcodes that do not meet the threshold.
The wrapper function plotBarcodeRankScatter()
can be
used to plot the results from the BarcodeRanks algorithm.
plotBarcodeRankScatter(
inSCE = pbmc4k.droplet,
title = "BarcodeRanks Rank Plot",
legendSize = 14
)
The total UMI count of each barcode is plotted against its rank. We can see a steep dropoff of UMI counts around the inflection point, where we see a presumed separation between cell-containing and empty droplets.
SingleCellExperiment
objects can be subset by its
colData
using subsetSCECols()
. The
colData
parameter takes in a character vector of
expression(s) which will be used to identify a subset of cells using
variables found in the colData
of the
SingleCellExperiment
object. For example, if x
is a numeric vector in colData
, then setting
colData = "x < 5"
will return a
SingleCellExperiment
object where all columns (cells) meet
the condition that x
is less than 5. The index
parameter takes in a numeric vector of indices which should be kept,
while bool
takes in a logical vector of TRUE
or FALSE
which should be of the same length as the number
of columns (cells) in the SingleCellExperiment
object.
Please refer to our Filtering
documentation for detail.
#Before filtering:
dim(pbmc4k.droplet)
## [1] 33694 60000
pbmc4k.droplet <- subsetSCECols(pbmc4k.droplet, colData = 'dropletUtils_BarcodeRank_Inflection == 1')
pbmc4k.droplet <- subsetSCECols(pbmc4k.droplet, colData = '!is.na(pbmc4k.droplet$dropletUtils_emptyDrops_fdr)')
pbmc4k.droplet <- subsetSCECols(pbmc4k.droplet, colData = 'pbmc4k.droplet$dropletUtils_emptyDrops_fdr < 0.01')
#After filtering:
dim(pbmc4k.droplet)
## [1] 33694 309
We can compare the average total UMI counts per cell before and after cell filtration:
p1 <- plotSCEViolinColData(pbmc4k.droplet.prefilt, coldata = "sum", summary = "mean", title = "Pre-filter", ylab = "Total counts")
p2 <- plotSCEViolinColData(pbmc4k.droplet, coldata = "sum", summary = "mean", title = "Post-filter", ylab = "Total counts")
plot(cowplot::plot_grid(p1, p2, ncol = 2))
For performing QC on cell-filtered count matrix with SCTK, please refer to our Cell QC documentation.


--- layout: page title: "HTTP-client suggested Push Preference" description: "\"Prefer-Push\" is a HTTP header that a client may use to request that a server uses HTTP/2 Push to send related resources as identified by their link relationships." ---
| Document Name: | Internet Draft pot-prefer-push |
|---|---|
| Document URI: |
urn:ietf:id:pot-prefer-push
|
| Online Version: |
https://datatracker.ietf.org/doc/html/draft-pot-prefer-push
|
| Organization: | Internet Engineering Task Force (IETF) |
| Series: | Internet Draft (I-D) |
| Abstract: | "Prefer-Push" is a HTTP header that a client may use to request that a server uses HTTP/2 Push to send related resources as identified by their link relationships. |
Prefer-Push
Return to ( Series | Organization | all Specifications )


We fabricate luxurious sofas in our workshop based on your demand and design. We value our Customers satisfaction and design products with great precision. We give high focus on customers choices in colour, leather/fabric, cushion etc. catalogues are available. Our product are profitable and productive to customer as we have no mediator. We sell products directly from the retailer. We provide free delivery. We celebrate 15 years of promising experience. All the products are Made in Bahrain.
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Smart Contract Address: 0x5228577d88521d12b409682f255fad46d2433bee
Location: Ethereum Main Net
Source: Github
Check Online: http://CryptoClass.center/certificate/check.htm


Hibersap 1.4.0 released
Posted by
onWe are happy to announce the Hibersap 1.4.0 release!
The artifacts for the new Hibersap version can be found in Maven central.
Hibersap now supports changing parameters and allows the hibersap.xml file to be in a different location.
Hibersap 1.3.0 released
Posted by
onWe are happy to announce the Hibersap 1.3.0 release!
The artifacts for the new Hibersap version can be found in Maven central.
Hibersap now supports deep structures / tables in import and export parameters! Also, we introduced a workaround for the runtime file name check problem in the latest SAP JCo versions.
A new site for Hibersap
Posted by
onToday we are launching the new Hibersap site. The new site is hosted on GitHub and is baked with Awestruct while most of the content is edited using AsciiDoc.
After moving the Hibersap code base and issue tracking away from Sourceforge to GitHub this is the logical next step to make it much easier for you to contribute to the code and docs. Because it is also much easier for us to deploy changes to the site we are now able to update the docs much more often.
Hibersap 1.2.0 released
Posted by
onWe are happy to announce the Hibersap 1.2.0 release!
The artifacts for the new Hibersap version can be found in Maven central.
Besides the enhancements, we changed the license under which the Hibersap project is distributed from the Lesser GNU Public License (LGPL) to the Apache License. This should make it easier to integrate Hibersap with other libraries.


New
Overview
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PDFBox - References
PDFBox References
This page lists projects that utilize PDFBox and articles that have been written about PDFBox. Send me an e-mail if your article or project is missing.
Projects
| Project Name | License | Project Description |
|---|---|---|
| Alfresco | LGPL - commercial services/support/training is available | Alfresco is an open source, open-standards content repository built by the most experienced content management team that includes the co-founder of Documentum. |
| Centric CRM | Free To Use But Restricted/Commercial | The Most Advanced Open Source CRM Software. |
| Canoo Webtest | BSD Like | Free OpenSource tool for XP-style acceptance testing of Java-based Web applications. |
| Jahia | collaborative source license | The Jahia product is currently the most powerful, ready-to-use and affordable integrated midrange Java Content Management and Corporate Portal Server. |
| jLibrary | BSD | jLibrary is a Document Management System, oriented for personal and enterprise use. |
| Jomic | GPL | Jomic is a viewer for comic book archives. |
| JpdfUnit | Apache License V2.0 | JpdfUnit is a framework for testing a generated pdf document with the JUnit Test Framework. |
| Liferay Portal | MIT | Liferay Portal is an open source portal that helps organizations collaborate more efficiently by providing a consolidated view of disparate applications. |
| LIUS | GPL | LIUS is an indexing Java framework based on the Jakarta Lucene project. The LIUS framework adds to Lucene many files format indexing fonctionalities as: Ms World, Ms Excel, Ms PowerPoint, RTF, PDF, XML, HTML, TXT, Open Office suite and JavaBeans. |
| LuceGene | Artistic License | LuceGene is an open-source document/object search and retrieval system specially tuned for bioinformatics text databases and documents. |
| MMBase Lucene Module | MPL | Lucenemodule is a plugin (module) for the MMBase content management system that enables Lucene full text search through it's content, and thanks to PDFBox also PDF content. |
| Nutch | ASL | Nutch is open source web-search software. It builds on Lucene, adding web-specifics, such as a crawler, a link-graph database, parsers for HTML and other document formats, etc. |
| OpenCms | Custom | OpenCms is a professional level Open Source Website Content Management System. |
| Orbeon PresentationServer | LGPL | Orbeon PresentationServer (OPS) is an open source J2EE-based platform for XML-centric web applications. OPS is built around XHTML, XForms, XSLT, XML pipelines, and Web Services, which makes it ideal for applications that capture, process and present XML data. Commercial consulting/training/support is available through orbeon. |
| PDFcat | LGPL | PDFcat is multi-platform catalog manager that provides searching capability over documents among virtual catalogs. |
| PodReader | GPL | PodReader is an application that facilitates making electronic documents like eBooks readable on your iPod. |
| SearchBlox | Commercial | SearchBlox is a high-performance corporate search software designed for the Java 2 Enterprise Edition (J2EE) platform. |
| Terrier | MPL | Terrier is software for the rapid development of Web, intranet and desktop search engines. |
| Triboni GinkGO | Commercial | Triboni GinkGO is a highly scalable J2EE services platform that is based on a simple XML business object defintion and scripting language. Toghether with XSLT content centric web applications can be configured in a very short time. |
| Zilverline | Collaborative Source License | Zilverline is a search engine that offers web access to your personal or intranet content. |
Articles/Books
| Article Name | Article Abstract |
|---|---|
|
Build an eDoc Reader for your iPod Part 1 - User Interface Part 2 - Document Reading Engine Part 3 - *Integration with PDFBox* |
A three part article that discusses the implementation of the PodReader application. PodReader is Cocoa application written in Objective-C and article discusses how to use the Cocoa-Java bridge to integrate with the Java version of PDFBox. |
| Lucene In Action | A book that discusses integrating with the lucene search engine. One chapter discusses how to index various file formats and highlights PDFBox for indexing PDF documents. |
| Java Developers Journal - March 2005 | An article written by the lead developer of PDFBox discussing text extraction and AcroForm integration using PDFBox functionality. |
| Refactoring trends across N versions of N Java open source systems: an empirical study | This article describes an empirical study of multiple versions of a range of open source Java systems in an attempt to understand whether refactoring occur and, if so, which types of refactoring were most (and least) common. PDFBox is used as a case study. |


rig
Utility to piece together a random first name, last name, street number and address, along with a geographically consistent (ie, they all match the same area) city, state, ZIP code, and area code.
More information: home page
- Display a random name (male or female) and address:
rig
- Display a [m]ale (or [f]emale) random name and address:
rig -m|f
- Use data files from a specific directory (default is `/usr/share/rig`):
rig -d path/to/directory
- Display a specific number of identities:
rig -c number
- Display a specific number of female identities:
rig -f -c number


About
I'm Rahul Parsani, a software developer living in London.
Code
- WuNameAAS - Wu-Tang Clan Name Generator As A Service
- material-calculator - Material Calculator from AOSP ported to work from Android 2.3.3 & up
- google-io-2014-compat - Android demo for the Material Witness talk presented at Google I/O ported to work from Android 2.3.3 & up
- UberAPI-Android-Demo - Sample android app that works with Uber's external API


|
Perl Weekly
Issue #160 - 2014-08-18 - Happy Belated CPAN Day!
latest | archive | by Yanick Champoux
|
|
On August 15th CPAN Day, thanks to the endless promotion of Neil Bowers and others, the anniversary of the birth of CPAN was celebrated. The libations were true to form: over 775 releases were made by 107 authors. Flash in the pan? Beginning of a tradition? We'll have to wait until next year to find out. In the meantime, we can sit back, relax, and enjoy this tsunami of new releases. ~ `/anick
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Sponsors
|
|
|
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|
Headlines
|
James Aitken (LoonyPandora) passed away
It is with great sadness that we learned of the untimely death of Dancer contributor and Perl community member James Aitken. For anybody wishing to help with the funeral costs, the link leads to a funding campaign.
|
|
Announcements
|
|
|
perlprogramming.org
Gabor Szabo is the owner of the 'perlprogramming.org' domain, but doesn't really have a use for it. So he's asking if anybody is interested in taking over.
|
|
Type::Tiny 1.000000 Released
Type::Tiny is one of those keystone minimal implementation-distribution that found their way in almost everybody's toolbox. Toby Inkster announces proudly that it has now reached its v1.0 milestone.
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Announcing CPAN.io
BooK announces the arrival of a new CPAN site. It's still very new and very bare, but it might pay to come back and have a look at it in the upcoming weeks.
|
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Articles
|
Quickly Check for Database Design Flaws
Database schemas are hard to get right. Ovid tries to help us along the way, and shares a quick checks that is likely to make some of its flaws come out of the woodwork.
|
|
Try Travis CI with your CPAN distributions
CPANTesters is the bee's knee, but recently we have seen the rise of Travis CI, a general-purpose testing service. Neil Bowers shows us here how to use it for Perl distributions.
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Discussion
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CPAN Day winner?
Now that the dust is settling on CPAN day, peoples are looking at the scoreboard of releases.  Every Week. Free of charge!
|


Map of additional parameter to submit to remove data source.
Object, default = {}
Adding properties to .postData object will instruct the grid to submit these parameters to the remote data source
with each remote request (pull, sort, search, save, delete).
You can defined it during object creation:
Or any time during the run-time:


Provides Solutions for
We automate business process with our services.
Codesquad is an innovative web design and development company based in ilorin,Nigeria. We are a software company with a focus on disruptive innovations for businesses and consumers, in areas as Fintech, Edutech, and HealthTech and so on
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Doug
Latornell is a professional engineer with post-graduate degrees
in experimental and computational fluid mechanics and
modeling and control of robotic manipulators. He
works for Nordion in Vancouver, where he helps produce
medical isotopes by proton irradiation from cyclotrons.
Side projects include work on a coupled biology and physics model of deep estuaries
that, through the winter
months, calculates a daily prediction of the date of the first
spring phytoplankton bloom in the Strait of Georgia.
Maintainer: Version Control with Mercurial


static
variables whose names are too short, too long,
or do not follow
the specified regular expression pattern.
Constants, i.e. variables of immutable type declared
static final
, are not checked by this inspection
Use the fields provided below to specify minimum length, maximum length and regular expression expected for static variable names.
Regular expressions should be specified in the standard java.util.regex
format.


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Web Development
Web Design
Marketing
Bachelor of Information Technology
Expert Front-End-Developer
To convert designs in a format where humans can see and interact with design elements remotely.
We create visual designs for humans and make sure they would understand things at first look.
We create mobile-friendly responsive websites according to Google ‘Mobilegeddon’ updates.
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Brian Chodur | Evato Author
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Image courtesy of here
Image courtesy of here
Convolutional layers compute feature maps via the following equation $$C(r,c) = I*W(r,c) = \sum_{i=1}^{K} \sum_{j=1}^{K} I(r+i-1,c+j-1)W(i,j)$$ where C(r,c) is a feature map, I is an image, W is a matrix filter, and (r,c) refers to a pixel location in the image I.
Animation courtesy of here
Image courtesy of here
Network depth will be affected by the parameters of convolutional layers and pooling layers. Once enough filters have been applied, i.e enough features have been generated, the features are fed into a classifier (fully connected layers).
The number of filters generally increases as you go further into the network. This is because early filters are computing basic features. There are only so many edge detectors that are useful.
This is typically a few "normal" (fully connected) neural network layers, though people have used SVMs and other classification algorithms with the convolutional features as inputs.
Deep learning tends to be a field which adopts practices "because they work." Try out choices with which previous models have had success.
Deep models require lots of data.
Example of generating image for data augmentation. Image courtesy of here
Data imbalances can have negative impacts on training (see here.) One can solve this by cutting down on the number of more abundant classes, artificially enhancing the number of less abundant classes, or first training on abundant classes and then finetuning on rarer ones.
In previous assignments, dividing MNIST images by 255 has yielded normalized data. Normalized data is nicer for optimization.
Image courtesy of here
The most common type of preprocessing is to compute a mean over the training data, and subtract this mean from each data point to zero center the data. Normalization is then performed on the centered data. This is done to give lower importance to inputs which are "average" as they will be near zero.
Image courtesy of here
Enforce an absolute upper bound on weights going from one neuron to another.
optimizer = tf.train.GradientDescentOptimizer(learning_rate)
grads = optimizer.compute_gradients(loss, [w1, w2, ...])
#Grads is a list of tuples (gradient, associated_variable)
capped =
[(tf.clip_by_norm(grad_tuple[0], clip_norm=1.0, axes=0), grad_tuple[1])
for grad_tuple in grads]
optimizer = optimizer.apply_gradients(capped)
Stop when validation loss stops decreasing.
Early stopping illustration. Image courtesy of here
with tf.Session() as sess:
for _ in xrange(max_iterations):
sess.run(training_op)
val_loss = sess.run(loss, feed_dict =
{data_placeholder : validation_data,
label_placeholder : validation_labels})
if val_loss > last_val_loss:
counter += 1
if counter == early_stop_threshold:
break
last_val_loss = val_loss
Dropout illustration. Image courtesy of here
#x is the input (i.e a layer's activation)
#keep_prob is the probability that each entry in the input is not set
#to zero
d = tf.nn.dropout(x, keep_prob, noise_shape=None, seed=None, name=None)
#Pass d along to the next layer
Many times it is unnecessary to train a CNN from scratch! Models which have been trained on large image classification tasks are often a good starting point for other image recognition tasks.
When finetuning a pre-trained network to a new task, consider how similar the tasks are.
Image courtesy of here
Validation data can be used to select hyperparameters in a rigorous way. A common practice is to set aside 10% of the training data for use as validation data.
Recall the purpose of an activation function is to introduce a non-linear transform into the learning algorithm.
ReLUs avoid the saturation problem of sigmoids.
Image courtesy of here
Leaky ReLUs avoid "dead neurons" which can occur when using ReLU.
Image courtesy of here
Initialzation matters due to non-convexity of deep models. The choice is motivated by activation function choice and network depth. A basic strategy is to use small random weights, with the randomness helping to break symmetry, e.g W ~ 0.001 x N(0, 1).
One problem with simple small random initialization is that the variance of a neuron's output grows with its fan-in. Xavier initialization proposes to normalize the variance of the output of each neuron in a layer to 1. This is done by dividing each random weight by the fan-in for that neuron.
The variable "s" represents a neuron's unactivated output. Note that the derivation assumes the weights and inputs have a mean of zero, which is not the case for ReLU activations.
Image courtesy of here
He initialization uses a similar idea (normalizing the variance) which is more appropriate for ReLU activations. This paper provides the derivation, but the recommend multiplying each weight by $\sqrt{2/n}$ where "n" is the fan-in.
W_Xavier = tf.get_variable("W",
shape=[prev_hidden_shape, next_hidden_shape],
initializer=tf.contrib.layers.xavier_initializer())
W_He = tf.get_variable("W",
shape=[prev_hidden_shape, next_hidden_shape],
initializer=tf.contrib.layers.variance_scaling_initializer(
factor=2.0, mode="FAN_IN"))
The learning rate is probably the most important hyperparameter to cross-validate. Monitoring the training and validation loss output during training helps to see if the learning rate is appropriate.
Image courtesy of here
learning_rate = tf.placeholder(tf.float32, shape=[])
# ...
train_step = tf.train.GradientDescentOptimizer(
learning_rate=learning_rate).minimize(loss)
sess = tf.Session()
# Feed different values for learning rate to each training step.
sess.run(train_step, feed_dict={learning_rate: 0.1})
sess.run(train_step, feed_dict={learning_rate: 0.1})
sess.run(train_step, feed_dict={learning_rate: 0.01})
sess.run(train_step, feed_dict={learning_rate: 0.01})
Code courtesy of Stackoverflow
Generally stacks of layers with smaller filters are preferable to one larger filter. This is because the stack of smaller filters can compute more powerful features due to the nonlinearities between layers. The smaller filters also require fewer parameters. A 3x3 filter size is commonly used, and the number of filters usually increases with each layer.
Small strides allow filters to be applied across more patches of an image. A stride size of 1 or 2 is common. Note that the filter size and image size limits the stride size.
Padding allows filters to be applied to edges of the input. 1 or 2 are common choices. Bigger filters mean more padding may be necessary.
Filter size, stride size, and amount of padding all contribute to the output volume dimensions. They must work out such that each output dimension is an integer. In the following formulae, assume square inputs and square filters. Let the filter be FxF, the number of filters be K, the stride be S, and padding be P.
Pooling layers are determined by their receptive field size and stride. In practice two combinations are used, one with a field size of 3x3 and stride of 2, another with a field size of 2x2 and stride of 2. Larger receptive fields than 3x3 tend to downsample too aggressively.
Consider an input of shape [28, 28, 1], padding size of 1, and a conv layer with 16 filters of shape [3, 3, 1] with a stride of 1. The output volume will be of width and height (28 -3 + 2)/1 + 1 = 28.
filter_size = 3
num_channels = 1
num_filters = 16
W_conv = tf.get_variable("W",
shape=[filter_size,filter_size,num_channels,num_filters],
initializer=tf.contrib.layers.variance_scaling_initializer(
factor=2.0, mode="FAN_IN"))
b_conv = tf.Variable(tf.ones([32]))
conv_out = tf.nn.conv2d(x, W_conv, strides=[1, 1, 1, 1], padding='SAME')
Image courtesy of here
Often deep learning computations are performed on a GPU. The memory of a GPU tends to be the limiting factor (high-end models are about 12GB). To approximate how much memory your model needs, the memory requirements of parameters, activations, and batch data must be considered.
TensorBoard summary: https://www.tensorflow.org/get_started/summaries_and_tensorboard


Before Change
// 2.count //unique features for each sparse field,and record dense feature field name
sparse_feature_dict = {feat: data[feat].nunique()
for feat in sparse_features}
dense_feature_list = dense_features
// 3.generate input data for model
After Change
// 2.count //unique features for each sparse field,and record dense feature field name
sparse_feature_list = [SingleFeat(feat, data[feat].nunique())
for feat in sparse_features]
dense_feature_list = [SingleFeat(feat, 0)
for feat in dense_features]
// 3.generate input data for model
train, test = train_test_split(data, test_size=0.2)
train_model_input = [train[feat.name].values for feat in sparse_feature_list] + \
[train[feat.name].values for feat in dense_feature_list]
test_model_input = [test[feat.name].values for feat in sparse_feature_list] + \
[test[feat.name].values for feat in dense_feature_list]


I’m Jessica Mills, an aspiring historian, museum professional, and lifelong learner. I research medieval saints and their networks of men and women. Specifically, my focus is Saint Catherine of Siena (1347-1380) and how her network helped authorize and give political power to her mission.
I have an interest in a wider range of historical periods and it is always changing. I believe there is something interesting to uncover in every period. New questions develop out of new discoveries about the past. This website is dedicated to such a question:
What role did Catherine’s network play in the political and social power Catherine wielded?
The first step to answering this question is understanding how large Catherine’s network was. Some questions guided my thinking: Who was the most important person to Catherine? How was everyone connected? Did one connection open the door for further connections in the 14th century? Was gender a significant factor?
Rather than follow the traditional thesis route to graduate with a Masters of Arts in Historical Studies from SIUE, I decided to create a digital humanities project to widen my skills. This web site is the finished product. Digital humanity projects are becoming more popular in academia, and I want this project to help push the acceptance of digital history forward.
Throughout my schooling, I have had the privilege of receiving funding as a Teaching Assistant, Graduate Assistant, and Research Assistant. I received a Newberry Renaissance Consortium Grant that enabled me to participate in a seminar at the Newberry Library entitled, “Gender, Bodies, and the Body Politic in Medieval Europe” led by Dr. Tanya Miller-Stabler from Loyola University. This class broadened my understanding of medieval life and how notions of the body affected behavior and beliefs of men and women. I also studied independently with Dr. Carole Collier-Frick, focusing on gender studies. Additionally, I had an independent study with Dr. Jessica Despain to understand digital humanities and how to make a successful website while upholding academic integrity. This project could not have been possible without the limitless meetings with my thesis committee chair, Dr. Katrin Sjursen, who pushed my ideas and arguments further than I ever dreamed!
I hope you enjoy this website and develop questions about the past and leave the website having learned something about the Saint Catherine.


Quick Start How To's
Preview a series
- Load DICOM files
- Click
Preview
button to the right of the series
Preview the meta-data (text) of a series
- Load DICOM files
- Click
Preview
button to the right of the series
- In the preview window, click the
Text
radio button
in the lower right-hand corner of the window
Get the text of a DICOM file
- Preview the file as text
- Use CTRL-A and then CTRL-C to copy the text, then paste it into another application (such as Notepad).
Fix a damaged DICOM file
DICOM+ is often more tolerant of DICOM files with errors or that use older encoding methods. If you are using
another application that has trouble reading a DICOM file, try this:
- Load and preview the files in text mode
- Click
Edit
to edit the file
- Click
Save+Close
The files will be saved without changing the metadata, but cleanly reformatted. Then try using the new files in
the other application.
Convert DICOM files to text, XML, or PNG
- Load and preview the files in text mode
- Click
Edit
to edit the file
- Click
Options
- Select the format(s) you want to save in
- Click
Back to Main
- Click
Save+Close
Anonymize a series:
- Load DICOM files
- Switch to
Anonymize
mode
- Click
Anonymize
button to the right of the series
Generated files will be put in the
Destination
folder.
To view them, drag them into the application and click the corresponding
Preview
button.


Uncertainties in the prediction of sea level
| Source of uncertainty considered | Maximum ΔSL | Minimum ΔSL | Range in ΔSL | Mean ± SD | Reference |
|---|---|---|---|---|---|
| ISM dependency (PRISM3 initial conditions) | 13.79 | 7.66 | 6.13 | 9.76 ± 2.13 | de Boer et al. 28 |
| ISM dependency (PD initial conditions) | 2.90 | −11.80 | 14.70 | −1.89 ± 4.93 | |
| ISM parameterisations relating to surface melting, ice flow and sub-shelf melting | 6.6 | −4.2 | 10.8 | – | Yan et al. 43 |
| Pliocene temperature and precipitation | 13.0 | 6.2 | 6.8 | – | |
| Subgrid scale melt parameterisations at grounding line (alongside temperature biases of 1 and 2 degrees in the regional climate model)—All simulations | – | – | – | 8.57 ± 2.8 | Golledge et al. 16 |
| As above but with no subgrid scale melting | – | – | – | 7.44 ± 1.95 | |
| As above but including subgrid scale melting | – | – | – | 9.7 ± 3.15 | |
| Parameterised mechanisms for ice cliff failure and ice-shelf hydrofracturing under a warm Pliocene-like scenario | ~18 | ~1.6 | – | – | Pollard et al. 22 |
| Exploration of parameter values within one ISM that control the relationship between ocean temperature and sub-ice-shelf melt rates, hydrofracturing and maximum rates of marine-terminating ice-cliff failure | 12.41 | 3.52 | 8.89 | – | DeConto and Pollard 21 |
| Dynamic topography | 7.4 | 5.4 | 1.7 | – | Austermann et al. 44 |
| Bedrock topography | 17.9 | 12.6 | 5.3 | – | Gasson et al. 45 |
| GCM dependency (Pliocene Ice-PRISM3) | 14.57 | 2.24 | 12.33 | 7.79 ± 4.06 | This study |
| GCM dependency (Pliocene Ice-PD) | 7.97 | −3.99 | 11.96 | 2.43 ± 3.53 | |
| GCM dependency (all experiments) | 14.57 | −3.99 | 18.56 | 5.11 ± 4.65 | |
| Impact of orbital forcing on climate and ice sheet predictions within a SIA ISM framework | 13.52 (EAIS only) | −7.14 (EAIS only) | 20.66 (EAIS only) | – | Dolan et al. 20 |
Summary of previous ice-sheet modelling predictions of Pliocene global mean sea level change relative to present-day due to Antarctic ice-sheet changes in terms of range (maximum and minimum contributions) and as a mean value. The type of uncertainty addressed in each study is also summarised