Properties, Profiles and Resources
Spring Framework: Environment Abstraction and Resources
You’ll likely need to change the behavior of your application based on a number of things. Spring has a lot features around this called Externalized Configuration - the practice of placing configuration in property files as opposed to hard-coded in your program. Spring will respect a very specific hierarchical order of properties such that you can override properties when required.
Read: spring.io: Externalized Configuration Read: spring.io: Properties and Configuration Read: baeldung.com: Properties with Spring and Spring Boot Read: spring.io: Appendix A. Common application properties
Property files are typically placed in src/main/resources as either .properties or .yml files. application.properties and application.yml are specially named properties that Spring will look for to load automatically when your application starts. There are profile-specific variants of these property files as well and are described below.
Profiles
Spring has the concept of a Profile which is basically a special type of property that you can use to tag your components to a specific environment. Let’s say you have a service that should send an EMail out when certain events happen in your system. This may only be relevant in an environment like UAT and PROD but not in DEV. You could define two types of MailService, one to actually send the EMail out and the other to just print it to the console.
Read: spring.io: Profiles Read: baeldung.com: Spring Profiles
/**
* Only one of the two Beans defined in this class will be loaded in any given environment.
*/
@Configuration
class MyConfig {
// Use the real EMailService in UAT and PROD
@Bean
@Profile(“UAT”, “PROD”)
fun emailService(): MailService = EMailService()
// Use the console based service for DEV
@Bean
@Profile(“DEV”)
fun consoleMailService(): MailService = ConsoleMailService()
}
There are several ways to make a Profile “active”, one such way is to pass the spring.profiles.active JVM argument.
$ java -jar -Dspring.profiles.active=PROD app.jar
Profiles work very nicely with the properties mentioned earlier. Spring will load properties based on a naming scheme with the Profile name in the format application-{profile}.properties (i..e, application-PROD.properties). Profile specific properties will override the default properties.
A common example of this is externalizing database connection property for each envirionment.
- src/main/resources/application.properties
- spring.datasource.url=jdbc:mysql://localhost:3306/mydb
- src/main/resources/application-DEV.properties
- spring.datasource.url=jdbc:mysql://dev-database.app.com:3306/mydb
- src/main/resources/application-PROD.properties
- spring.datasource.url=jdbc:mysql://prod-database.app.com:3306/mydb
Resources
Resources are non source-code related files required by your application. The Properties described above are considered resources. SQL Files, CSV, XLS images, bundled HTML/CSS/JS and others would also be considered resources for a Spring application. Spring will make resources from your classpath available to you, and it will automatically make src/main/resources part of your classpath.
Some Important Specially Named Resources
All of these are located in src/main/resources.
| File | Description |
|---|---|
| application.[properties|yml] | Described in the above Properties section. |
| schema.sql | Initialize a Database with simple DDL script. |
| data.sql | Initialize a Database with simple seed script. |
| db/migrations/V*.sql | Execute Flyway Database Migrations on Startup |
| banner.txt | Customize the Banner that displays when Spring starts up. |
Access Resources in your Code
Spring can inject Resources for you quite easily. Here is an example of printing a text file line-by-line.
src/main/resources/printMe.txt
Line 1
Line 2
etc...
This short piece of code is instructing Spring to inject a reference to the classpath resource and then using some neat Kotlin extension functions to iterate over it. The key point here is the @Value injection of a Resource to get a reference to the File.
src/main/kotlin/DemoApplication.kt
import org.springframework.beans.factory.annotation.Value
import org.springframework.boot.autoconfigure.SpringBootApplication
import org.springframework.boot.runApplication
import org.springframework.core.io.Resource
import javax.annotation.PostConstruct
@SpringBootApplication
class DemoApplication{
/**
* Spring is doing a couple of things here to make this magic happen. It detects
* the injection type to be a Resource so it knows its a file. The @Value annotation
* is a URI pointing to a file named printMe.txt located in the root of the classpath.
* You can then get a File reference from the Resource.
*/
@Value("\${classpath:printMe.txt}") var printMe: Resource? = null
// Prints the File line by line
@PostConstruct fun init() = printMe!!.file.readLines().forEach { println(it) }
}
fun main(args: Array<String>) {
runApplication<DemoApplication>(*args)
}


WITNESS LIST
Agriculture, Water & Rural Affairs
December 8, 2015 9:00 AM
Interim Charge #3
ON:
Adams, Marc (also providing written testimony) (Self; Cobank), Lubbock, TX
Hagood, Walt (also providing written testimony) (Self; Texas Farm Bureau), Wolfforth,
TX
Holcomb, Gary Ag Producers Coop (Self), Sunray, TX
Neeley, Karen (Independent Bankers Association of Texas), Austin, TX
Zacek, John Chairman South Texas (Prosperity Bank), Victoria, TX
Interim Charge #4
ON:
Bennett, Bradon Director of Code Compliance (City of Fort Worth), Fort Worth, TX
Oakley, Warren Building Official (also providing written testimony) (City of Fort
Stockton), Fort Stockton, TX
Talbott, Michael Executive Director (Harris County Flood Control District), Houston, TX
Wassenich, Dianne Executive Director (San Marcos River Foundation), San Marcos, TX
Interim Charge #5
ON:
Ellis, Dee State Veterinarian (also providing written testimony) (Texas Animal Health
Commission), Austin, TX
Schwartz, Andy (Self), Austin, TX
Smith, Carter Executive Director (Texas Parks and Wildlife Department), Austin, TX
Tarlton, Patrick (Texas Deer Association), Austin, TX
Wolf, Clayton Wildlife Division Director (also providing written testimony) (Texas Parks
and Wildlife Department), Austin, TX
Yeates, Daivd (Texas Wildlife Association), San Antonio, TX
Interim Charge #6
ON:
Beck, Tina Senior Analyst (Legislative Budget Board), Austin, TX
Boening, Russell President (also providing written testimony) (Texas Farm Bureau),
Waco, TX
Fearneyhough, Jason Deputy Commissioner (Texas Department of Agriculture), Austin,
TX
Ferguson, George (also providing written testimony) (Texas Grain & Feed Association),
Forth Worth, TX
Gentsch, Bryan Executive Vice President (also providing written testimony) (Texas Seed
Trade Association), Austin, TX
Huddleston, Gary Director of Public Affairs (also providing written testimony) (Kroger,
Inc. / Texas Retailers Association), Irving, TX
Kostroun, David Chief Administrator of ACP (Texas Department of Agriculture), Austin,
TX
Miller, Sid Commissioner (also providing written testimony) (Texas Department of
Agriculture), Austin, TX
Warner, Diana Chief Financial Officer (Texas Department of Agriculture), Austin, TX
WITNESS LIST
Agriculture, Water & Rural Affairs
December 8, 2015 9:00 AM
Wiles, Mark Manager, Natural Resources and Judiciary Team (Legislative Budget Board),
Austin, TX


Hi!! I am Kalaiarsi Periasamy from India.
After being an Engineer in Control Systems/Instrumentation/Electronics for over 5 years,
I am currently looking for a career change to become a Software Developer.
Designed a hardware prototype (Version 1 using Arduino and Version 2 using Rasperry Pi B) of a
vehicle faremeter. Features include:
Talks to a centralized server through GPRS (for regular fare updates-Over The Air)
GPS for positioning
Appropriate
display
Thermal printer to print bill
Connectivity with vehicle's physical odometer to analyse tampering
PANIC button for emergency
Battery Diagnostics
Developed hardware as part of Proof of Concept. Was used to find the health status of Li-ion batteries
and not just the charge left. The idea was to use chirp signal (frequency domain analysis)
to test battery health and predict battery failures.
Wordcloud from Arxiv
Code snippets and modules for:
Extracting data from Arxiv database using its API.
Generating and plotting wordcloud for the retreived data.
Also, view how a particular field of research ora a category
has evolved over time. (as individual plots or as subplots)


{% extends "woord/layout.html" %} {% load staticfiles %} {% block content %}
| Item | Value |
|---|---|
| Woord users total | {{count_user}} |
| Woord users working | {{users_working}} |
| Woord users available | {{users_available}} |
| Choices | {{count_choice}} |
| Stimuli | {{count_stimulus}} |
| Questions | {{count_question}} |
| Qsets | {{count_qset}} |
| Responses | {{progr_done}} |
| Responding users: | {{progr_users}} |
| Expected responses: | {{progr_ptc|floatformat:2}} % |
Note: Update statistics by refreshing the page
Use the buttons to clear (generated) questions and otherwise reset the project. Responses to actions will appear to the right of the button.
{% if is_app_editor and not is_superuser %}Do NOT accidentily try out something here!
Data might get lost if you do so.
Should this happen, warn the TSG immediately. It might be possible to recover data from a backup one day ago.


ShowCmd controls whether VCS commands are printed.
var ShowCmd bool
Verbose enables verbose operation logging.
var Verbose bool
A Cmd describes how to use a version control system like Mercurial, Git, or Subversion.
type Cmd struct { Name string Cmd string // name of binary to invoke command CreateCmd string // command to download a fresh copy of a repository DownloadCmd string // command to download updates into an existing repository TagCmd []TagCmd // commands to list tags TagLookupCmd []TagCmd // commands to lookup tags before running tagSyncCmd TagSyncCmd string // command to sync to specific tag TagSyncDefault string // command to sync to default tag LogCmd string // command to list repository changelogs in an XML format Scheme []string PingCmd string }
func ByCmd(cmd string) *Cmd
ByCmd returns the version control system for the given command name (hg, git, svn, bzr).
func FromDir(dir, srcRoot string) (vcs *Cmd, root string, err error)
FromDir inspects dir and its parents to determine the version control system and code repository to use. On return, root is the import path corresponding to the root of the repository.
func (v *Cmd) Create(dir, repo string) error
Create creates a new copy of repo in dir. The parent of dir must exist; dir must not.
func (v *Cmd) CreateAtRev(dir, repo, rev string) error
CreateAtRev creates a new copy of repo in dir at revision rev. The parent of dir must exist; dir must not. rev must be a valid revision in repo.
func (v *Cmd) Download(dir string) error
Download downloads any new changes for the repo in dir. dir must be a valid VCS repo compatible with v.
func (v *Cmd) Log(dir, logTemplate string) ([]byte, error)
Log logs the changes for the repo in dir. dir must be a valid VCS repo compatible with v.
func (v *Cmd) LogAtRev(dir, rev, logTemplate string) ([]byte, error)
LogAtRev logs the change for repo in dir at the rev revision. dir must be a valid VCS repo compatible with v. rev must be a valid revision for the repo in dir.
func (v *Cmd) Ping(scheme, repo string) error
Ping pings the repo to determine if scheme used is valid. This repo must be pingable with this scheme and VCS.
func (v *Cmd) String() string
func (v *Cmd) TagSync(dir, tag string) error
TagSync syncs the repo in dir to the named tag, which is either a tag returned by Tags or the empty string (the default tag). dir must be a valid VCS repo compatible with v and the tag must exist.
func (v *Cmd) Tags(dir string) ([]string, error)
Tags returns the list of available tags for the repo in dir. dir must be a valid VCS repo compatible with v.
RepoRoot represents a version control system, a repo, and a root of where to put it on disk.
type RepoRoot struct { VCS *Cmd // Repo is the repository URL, including scheme. Repo string // Root is the import path corresponding to the root of the // repository. Root string }
func RepoRootForImportDynamic(importPath string, verbose bool) (*RepoRoot, error)
RepoRootForImportDynamic finds a *RepoRoot for a custom domain that's not statically known by RepoRootForImportPathStatic.
This handles custom import paths like "name.tld/pkg/foo" or just "name.tld".
func RepoRootForImportPath(importPath string, verbose bool) (*RepoRoot, error)
RepoRootForImportPath analyzes importPath to determine the version control system, and code repository to use.
func RepoRootForImportPathStatic(importPath, scheme string) (*RepoRoot, error)
RepoRootForImportPathStatic attempts to map importPath to a RepoRoot using the commonly-used VCS hosting sites in vcsPaths (github.com/user/dir), or from a fully-qualified importPath already containing its VCS type (foo.com/repo.git/dir)
If scheme is non-empty, that scheme is forced.
A TagCmd describes a command to list available tags that can be passed to Cmd.TagSyncCmd.
type TagCmd struct { Cmd string // command to list tags Pattern string // regexp to extract tags from list }


  We have our fish cookies for your service. Our fish cookies are popular locally and are exported to 135 countries aroud the globe. Studies says that every minute, 10 people are taking bite of our fish cookies.
Our cookies are designed to feed you for weeks. if you are tired of cooking, secure your cookie jar today. If you are tired of eating everyday, try our Samon cookie and stay full for days or weeks.Winner of Washington friendly environment in consequently 10 years in a row. Families find it friendly in our stores.


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Day 20
Thankfulness unto our God and Savior
20
God of Heaven and Earth, Creator of Life, Maker of the stars, and the myriad of solar systems that are Your servants. I lift my heart with my brothers and sisters of faith because You have revealed Yourself to us. We are humbled beyond words that the infinite God would take thought of us, and yet You love us and call us to come and know You.You have revealed Yourself as The Lord our Shepherd; The Lord our Provider; The Lord our Peace, The Lord our Protector and Deliverer; and The Ever-Present One. We will dwell in the shelter of the Most High, for You are our Shield and Shade, our High Tower and Strong Tower, our Hiding Place and Place of Refuge.
Jesus, Son of God, Son of Man, the Word of God manifest in human form.  You are The Good Shepherd; The Faithful One; The Lord of Lords and King of Kings; The Alpha and Omega—the First and the Last—The Beginning and The End; The Prince of Peace; The Faithful Witness, the Firstborn of the Dead, and the Ruler of kings on earth. You are the Resurrection and The Life; the very Bread of Life and our Hope of Glory. You are the root and descendant of David, the Bright Morning Star. You are the Lamb of God who died and rose again, coming again as King and Conqueror who will judge the nations in righteousness.  And we say, “Come Lord Jesus, Come.” Amen. (Psalm 91:1-2; 119:89-91; 144:3; John 1:1-18; I Timothy 2:5; Acts 17:30-31; Revelation 22)


Help for your New Role
Congratulations on your new role in the Raleigh NC Chapter of HOG. Your role gives you permissions to make changes on the Chapter website. Depending on your role, one of the following pages will help guide you with step by step instructions to successfully make updates.
There are two environments in which to work. Login credentials are the same for both environments.
The Sandbox environment, is where you should try things out to get comfortable with your new role. You can make changes, or try things out, without affecting what members see. Remember, it's best if you first start out by making changes in the Sandbox environment until you are comfortable making changes. It is much easier to correct any mistakes in this environment. Also, do not hesitate to contact your webmaster for help. The web address for the Sandbox environment is https://dev.raleighhog.com The Production environment, is the website that all chapter members see. This environment is where you make the updates/changes that everyone sees. The web address for the Production environment is https://www.raleighhog.comDepending on your new role, click the link to use one of the following tutorials to help you to;
- Generate a Points Report - Membership Officer & Primary Officer roles
- Add a Team Member - Editor & Primary Officer roles
- Place a Newsletter on the Website - Editor & Primary Officer roles
- Place a Financial Report on the Website - Treasurer
- Update the Event Calendar - Activities Officer, Editor & Primary Officer roles
- Create a Blog entry - Activities Officer, Editor, Membership Officer & Primary Officer roles
- Upload Images to the Galleries Page - Photographer, Activities Officer, Editor, Membership Officer & Primary Officer roles
- Add Meeting Minutes - userid assigned
- Create a Basic Page - Editor & Primary Officer roles
- Create Subdirectories - Every role
- Upload Road Captain Documents - Head Road Captain userid assigned


Directors typically include board members and anyone responsible for regulatory compliance.
Add director


7
3
1
first case selected by default
Number:
Number:
Number:
second case @selected="true"
Number:
Number:
Number:
second and third cases @selected="true" - second is default.
Number:
Number:
Number:
s0c0
s0c1
s0c2
s1c2
Number:


bed unable to sleep, wondering if God might be doing something unplanned in their family, in the life of this scared teenager, and in the life of the baby girl she was carrying. By the next morning, they turned to each other willing to consider the possibility that this baby they had only heard about might be meant for them.
In just a matter of weeks, three days after L.J.’s due date, Grace Carolyn Allen was born. When Jack and Jessica arrived at the hospital and were ushered down the hall to the room where Grace was being born, they walked in to realize it was the exact room where L.J. had made his unexpected arrival just months earlier. The doctor placed the baby girl in Jack’s open arms with the words “meet your daughter.” The gift they received that day was a minor miracle, evidence that God was not done offering them goodness and mercy. Nothing could replace their son or minimize the impact of his life, but it was clear God was doing something amazing through their family’s story. There would be new tales to tell of the joy that entered their lives through a little girl named Grace. The story of Grace is proof to all who hear it that the grace of God is still at work, even when we feel all has been lost.
Naomi’s story is also marked by the hard knocks of grief and bitterness. She was sure that life was over when she lost those she loved so dearly. Watch her story carefully, though, and you’ll see that her life didn’t end when grief entered. God’s plans to bring grace to Naomi’s life were far from over. A true friend, a fresh start, and God’s redeeming mercy were about to break into the darkness she felt. Grace was just around the corner.


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0 donated to local and world-wide organizations in need. Learn More about Planting Kindness.
We like to keep things clean! And so each ingredient we use is thoughtfully chosen, rigorously tested, and expertly formulated to create only the highest quality natural products for you and your family.
Naturally occurring phytochemicals, botanical extracts bring unique therapeutic benefits that work in harmony with the other ingredients to enhance the effect.
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Our StoryOur goal is to have the greatest possible impact on as many people as we can, whether it’s our customers, employees, someone in our community, or around the world, we do what we can to help. Because of you, we are grateful to be in a position to share with the community we love. Our philanthropy program, Planting Kindness, is dedicated to making the world around us a better place.
Our Efforts


ui-jq
This is a simple Ticket generator. Just input some basic information as below and your tickets will be generated on the fly.
Click to Start ! »


| |
Methods defined here:
- __create_board__(self)
- This function creates a new board. This board will be fully filled in and valid.
:return:
- __find_empty_spot__(self, board)
- Return the next empty spot in the board
:param board:
:return:
- __generate_solution__(self, board)
- This function is very similar to the way I solve the puzzles.
It creates a new valid board with Recursive backtracking.
:param board:
:return:
- __init__(self, remaining=25)
- This class creates a new sudoku board.
When a new instance is initialized a new board gets created and numbers
get removed to get the puzzle that has to be solved.
:param remaining:
- __location_valid__(self, board, row, col, number)
- Return false if the location of the given number is invalid with the help of helper functions
:param board:
:param row:
:param col:
:param number:
:return:
- __number_in_column__(self, board, col, number)
- Returns true if the number is used in the given column
:param board:
:param col:
:param number:
:return:
- __number_in_row__(self, board, row, number)
- Returns true if the number is used in the given row
:param board:
:param row:
:param number:
:return:
- __number_in_subboard__(self, board, row, col, number)
- Return true if the number is used in the given subboard
:param board:
:param row:
:param col:
:param number:
:return:
- get_non_empty_squares(self, board)
- Returns a shuffled list of non-empty squares in the puzzle
:param board:
:return:
- print_board(self)
- This function is for testing/development purposes.
:return:
- remove_numbers_from_board(self, remaining)
- This function removes numbers until the remaining numbers requirement is achieved.
:param remaining:
:return:
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
|


This product is made available subject to acceptance of the EPICS open source license.
Before union and unionArray were available channelRPC was the primary method for implementing services. This document makes the argument that channelPutGet should become the primary method. If this argument is accepted then the information in this document should be moved into pvAccessJava.html.
A primary use of pvAccess is to implement network based services via a Remote Procedure Call (RPC) mechanism. pvAccess provides two ways to implement an RPC: channelPutGet and channelRPC.
For a channelRPC a client sends a top level PVStructure to the server, the service accepts the sructure, processes the request, and sends the result via another top level structure. The top level structures can be completely different for each request. A convention must be established about what introspection interfaces the service uses. This is the main purpose of normative types.
For a channelPutGet the service must create a PVRecord. A PVRecord has a record name, which is identical to the pvAccess channel name. The PVRecord has a top level PVStructure, which must have at least two PVStructure sub-fields: one for the put data for a request and one for the get data for the request. This the PVRecord has a top level PVStructure like the following:
structure structure argument // service specific structure result // service specificThe client specifies the argument and the service specifies the result.
Before the types union and unionArray were available channelRPC was used for most services because the introspection interface for the result and/or the argument could change from request to request.
This document makes the argument that union and unionArray makes it possible to implement all services via channelPutGet instead of channelRPC. Using channelPutGet has the desirable feature that the other channel methods can also be used to access the PVRecord (channelRPC does not allow this). This allows the PVRecord to me introspected and montored, which are both desirable features.
The next section shows how a PVRecord can be created that provides a channelPutGet that completele replaces a channelRPC. Next are some sections that provide additional examples. The last section is the summary.
The following is the introspection interface for the top level PVStructure for the PVRecord"
structure structure argument any value structure result any value
Note that any is a union where the value can be any valid type and the type can change dynamically. This the above allows any type of data that channelRPC allows.
The only real advantage that this has over just using channelRPC is that the PVRecord can be monitored.
The first example is:
structure structure argument NTNameValue value string[] name string[] value structure result any value
The argument is normative type NTNameValue but the result can be any type. In additon to alowing requests to be monitored, this allows a client to discover and send acceptable arguments. This also allows for a generic tool for channelPutGet requests.
The next example allows that server to return variable data via a more restrictive union:
structure structure argument NTNameValue value string[] name string[] value structure result union value string[] stringValue double[] doubleValue timeStamp[] timeStampValue alarm[] alarmValue
In this case the client can also discover what types the service can return.
This is what could have been done before union has available. Often channelRPC was used just because it the developer was familiar with implementing channelRPC. An example is:
structure structure argument NTNameValue value string[] name string[] value structure result NTTable value string[] labels structure double[] value alarm[] alarm timeStamp[] timeStamp
The above gives some simple examples of how channelPutGet can be used instead of channelRPC. Implenting a service via channelPutGet requests rather than channelRPC allows the PVRecord to be monitored. Also channelGet can be used to see the most recent request. By thinking carefully of how to define argument and result, a service implementer can make more details about the service available to the client via introspection.


Puppies are fun but need a lot of work and use the bathroom in the wrong spots but they are still adorable.
List of cute dog brreds


How to construct a horizontal menu bar using CSS.
First we will create a div, in the body of our HTML, to hold the navigation bar in and we will give it an id (better explanation of the id attribute) of “nav” (short for navigation). The id will allow us to easily reference to in the style sheet later on.
……

……
Now we are going to create an unordered list to hold the liks in. One of the reasons that a list is being used is because a list is for related items; each element of the list is a link to navigate around the site. In the future with XHTML 2.0, there is going to be a navigation list “<nl>” just for this; it will also include the ablitly to easily create drop down menus.

Now for each list item (li) we are going to place one of the links we want.

Sea
Mus N Squirrel

About

CSS
Play

Rants &
Like

So now our HTML is done and it should look something like this:
Now we will apply some CSS to the list to create the basic navigation bar.
We will refer to the HTML elements in our CSS with the id name of the div “#nav
”
followed by the the tag;
So when we refer to the list (ul) we will do “#nav ul
”.
This way our code will be easier to read and we do not need to create a class
for the list, list items, and links.
The unordered list by default in the web browser has margins
and padding to indent and
add white-space at the top and bottom of the list.
So let us override in our stylesheet the defaults, to prevent odd problems later
on, with
“padding : 0;
” and “margin : 0;
” for “#nav
ul
”.
#nav ul{
padding : 0;
margin : 0;
}
It should look something like this now:
To get each list item on the same line we will apply “display
: inline;
” to “#nav ul li
” to override
the default value of block
.
The value block
is how paragraphs (p), headers (h1 through h6),
list (ol, ul, etc), divisions (div), and other tags display by default; these
elements are placed in rectangular boxes.
While value inline
is how hyperlinks (a) and span display; these
are displayed in across lines of text.
An inline element can appear inside of a block element.
And one last thing, to prevent the items of the list from wrapping around when the screen is to small we will
add “white-space : nowrap;
” to “#nav ul
”.
#nav ul{
padding : 0;
margin : 0;
white-space : nowrap;
}
#nav ul li{
display : inline;
}
Now you should have a basic horizontal menu that should look very much like:
The navigation menu is now horizontal, but there is nothing to set it apart
from the rest of the text on a webpage making it harder to find. We will add
a background color of #003399
(“background-color:
#003399;
”)
and a foreground color of White
(“color: White;
”)
to our list (“#nav ul
”).
#nav ul{
padding : 0;
margin : 0;
white-space : nowrap;
background-color : #003399;
color : White;
}
#nav ul li{
display : inline;
}
Notice the links are not easy to read nor do they look very navigationable.
We can improve this by styling the hyperlinks themselves (“#nav
ul li a
”).
Make the background color #0066CC
to
offset it and a foreground color of White
.
To make it look more like a button we can get rid of the underline “text-decoration
: none;
”
and make the text bold so it will stands out more “font-weight
: bold;
”.
#nav ul{
padding : 0;
margin : 0;
white-space : nowrap;
background-color : #003399;
color : White;
}
#nav ul li{
display : inline;
}
#nav ul li a{
background-color : #0066CC;
color : White;
font-weight : bold;
text-decoration : none;
}
It is now getting there but there are a few things we can tweak.
To increase the visual pleasantries of the links add padding on
the right of one (1) em
“padding-right : 1em;
” and left “padding-left
: 1em;
”.
Also, change the padding for the list from 0
to 3px
(“padding
: 3px;
”). Please note that there should be no space between the
number and the measurement unit; correct: 3em
, incorrect: 3 em
.
#nav ul{
padding : 3px;
margin : 0;
white-space : nowrap;
background-color : #003399;
color : White;
}
#nav ul li{
display : inline;
}
#nav ul li a{
background-color : #0066CC;
color : White;
font-weight : bold;
text-decoration : none;
padding-left : 1em;
padding-right : 1em;
}
Now it looks like the final product but it is still missing the mouse-over
effect.
To add a mouse over effect we need to use the selector :hover
with
on the link;
add a new entry in our CSS “#nav ul li a:hover
”.
Now any style rules we place with this will be applied when the mouse cusor is
placed
over the link (a
).
Make the background color for it #99CCFF;
and
the foreground color
#000066
.
#nav ul{
padding : 3px;
margin : 0;
white-space : nowrap;
background-color : #003399;
color : White;
}
#nav ul li{
display : inline;
}
#nav ul li a{
background-color : #0066CC;
color : White;
font-weight : bold;
text-decoration : none;
padding-left : 1em;
padding-right : 1em;
}
#navmed ul li a:hover{
background-color : #99CCFF;
color : #000066;
}
View an example page and stylesheet.


Jessi drops MV for 'Drip' feat. Jay Park
by germainejJessi has dropped her music video for "Drip" featuring Jay Park.
The two rappers have come together for the fresh collaboration track composed by Jessi, johnjohn, and CuzD and written by Jessi, Jay Park, and johnjohn. "Drip" is also the second release after Jessi signed with P-Nation early this year.
Watch Jessi's "Drip" MV above, and let us know what you think in the comments below.


Test coverage user interface for C and C++
git-history-coverage − summarise test coverage for recent git commits
git-history-coverage [options] rev-list
Git-history-coverage extracts test coverage data produced by C and C++ programs compiled with gcc −−coverage, and correlates it to git commits, printing a coverage summary which shows how well tested recent code changes have been. This is useful for nightly builds and Continuous Integration systems such as Jenkins.
For the output of git-history-coverage to make any sense, the coverage data must be generated by running code which corresponds to the last commit in the range specified by rev-list.
When used
without any options, git-history-coverage prints
three summaries.
overall
A summary of all the commits specified by rev-list.
by author
A summary split up by each author represented in the set of commits specified by rev-list.
by commit
A summary for each individual commit in the set of commits specified by rev-list.
For each of these summaries, git-history-coverage prints statistics showing how many lines of code were in the commits, how many lines represent executable code (as opposed to comments, test code, or infrastructure like Makefiles), and how many lines were actually executed in tests.
−−summary−overall
Print the overall summary (with no options, all three summaries are printed).
−−summary−by−author
Print the by author summary (with no options, all three summaries are printed).
−−summary−by−commit
Print the by commit summary (with no options, all three summaries are printed).
−−gcda−prefix=dir
Look for .gcda files underneath the directory dir. This option is used to read runtime coverage information written when a test program is run using the same --gcda-prefix option to ggcov-run.
Written by Greg Banks<EMAIL_ADDRESS>ggcov is
Copyright © 2001−2020 Greg Banks
<EMAIL_ADDRESS>This is free software; see the COPYING file for copying
conditions. There is NO warranty; not even for
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
ggcov-run(1).


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What is Bitcoin? (FAQ)
Bitcoin is a form of digital currency, created and held electronically. No one controls it. Bitcoins aren’t printed, like dollars or euros.
Bitcoin can be used to buy things electronically. In that sense, it’s like conventional dollars, euros, or yen, which are also traded digitally.
However, bitcoin’s most important characteristic, and the thing that makes it different to conventional money, is that it is decentralized. No single institution controls the bitcoin network. This puts some people at ease, because it means that a large bank can’t control their money.
However, bitcoin’s most important characteristic, and the thing that makes it different to conventional money, is that it is decentralized. No single institution controls the bitcoin network. This puts some people at ease, because it means that a large bank can’t control their money.
Bitcoin is a digital asset and a payment system invented by Satoshi Nakamoto, who published the invention in 2008 and released it as open-source software in 2009.
Satoshi Nakamoto is the pseudonym of a person or group of people who created the bitcoin protocol and reference software.
Satoshi Nakamoto is the pseudonym of a person or group of people who created the bitcoin protocol and reference software.
Nobody owns the Bitcoin network much like no one owns the technology behind email or the Internet.
A blockchain is a public ledger of all Bitcoin transactions that have ever been executed. It is constantly growing as ‘completed’ blocks are added to it with a new set of recordings. The blocks are added to the blockchain in a linear, chronological order. Each node (computer connected to the Bitcoin network using a client that performs the task of validating and relaying transactions) gets a copy of the blockchain, which gets downloaded automatically upon joining the Bitcoin network. The blockchain has complete information about the addresses and their balances right from the genesis block to the most recently completed block.
A bitcoin "Address" is nothing more than a pairing of a public key (which you share with people to receive money, think of your public key as INBOUND ONLY traffic) and a private key (which cryptographically links to your public key, allowing you to spend said funds, OUTBOUND traffic).
A private key in the context of Bitcoin is a secret number that allows bitcoins to be spent. Every Bitcoin wallet contains one or more private keys, which are saved in the wallet file. The private keys are mathematically related to all Bitcoin addresses generated for the wallet.
Because the private key is the "ticket" that allows someone to spend bitcoins, it is important that these are kept secure. Private keys can be kept on computer files, but in some cases are also short enough that they can be printed on paper.
A Bitcoin wallet is a file that contains a collection of private keys.
Bitcoin Core
Bither
GreenBits
MultiBit HD
Armory
Electrum
mSIGNA
Bitcoin Wallet
breadwallet
Green Address
Coinomi
Copay
Bither
GreenBits
MultiBit HD
Armory
Electrum
mSIGNA
Bitcoin Wallet
breadwallet
Green Address
Coinomi
Copay
Bitcoin can be coldly unforgiving of mistakes, and nowhere is this better demonstrated than with change addresses. Although change addresses provide a key privacy tool, they can also lead to confusion, loss, or theft when not understood.
When the output of a transaction is used as the input of another transaction, it must be spent in its entirety. Sometimes the coin value of the output is higher than what the user wishes to pay. In this case, the client generates a new Bitcoin address, and sends the difference back to this address. This is known as change.
Step 1 - Get The Best Bitcoin Mining Hardware
Step 2 - Download Free Bitcoin Mining Software
Bitcoin mining, but the two most popular are CGminer and BFGminer which are command line programs.
Step 3 - Join a Bitcoin Mining Pool
Bitcoin mining pools are groups of Bitcoin miners working together to solve a block and share in it's rewards. Without a Bitcoin mining pool, you might mine bitcoins for over a year and never earn any bitcoins. It's far more convenient to share the work and split the reward with a much larger group of Bitcoin miners. For a fully decentralized pool, we highly recommend p2pool.
Step 2 - Download Free Bitcoin Mining Software
Bitcoin mining, but the two most popular are CGminer and BFGminer which are command line programs.
Step 3 - Join a Bitcoin Mining Pool
Bitcoin mining pools are groups of Bitcoin miners working together to solve a block and share in it's rewards. Without a Bitcoin mining pool, you might mine bitcoins for over a year and never earn any bitcoins. It's far more convenient to share the work and split the reward with a much larger group of Bitcoin miners. For a fully decentralized pool, we highly recommend p2pool.
Anim pariatur cliche reprehenderit, enim eiusmod high life accusamus terry richardson ad squid. 3 wolf moon officia aute, non cupidatat skateboard dolor brunch. Food truck quinoa nesciunt laborum eiusmod. Brunch 3 wolf moon tempor, sunt aliqua put a bird on it squid single-origin coffee nulla assumenda shoreditch et. Nihil anim keffiyeh helvetica, craft beer labore wes anderson cred nesciunt sapiente ea proident. Ad vegan excepteur butcher vice lomo. Leggings occaecat craft beer farm-to-table, raw denim aesthetic synth nesciunt you probably haven't heard of them accusamus labore sustainable VHS.
Anim pariatur cliche reprehenderit, enim eiusmod high life accusamus terry richardson ad squid. 3 wolf moon officia aute, non cupidatat skateboard dolor brunch. Food truck quinoa nesciunt laborum eiusmod. Brunch 3 wolf moon tempor, sunt aliqua put a bird on it squid single-origin coffee nulla assumenda shoreditch et. Nihil anim keffiyeh helvetica, craft beer labore wes anderson cred nesciunt sapiente ea proident. Ad vegan excepteur butcher vice lomo. Leggings occaecat craft beer farm-to-table, raw denim aesthetic synth nesciunt you probably haven't heard of them accusamus labore sustainable VHS.
Anim pariatur cliche reprehenderit, enim eiusmod high life accusamus terry richardson ad squid. 3 wolf moon officia aute, non cupidatat skateboard dolor brunch. Food truck quinoa nesciunt laborum eiusmod. Brunch 3 wolf moon tempor, sunt aliqua put a bird on it squid single-origin coffee nulla assumenda shoreditch et. Nihil anim keffiyeh helvetica, craft beer labore wes anderson cred nesciunt sapiente ea proident. Ad vegan excepteur butcher vice lomo. Leggings occaecat craft beer farm-to-table, raw denim aesthetic synth nesciunt you probably haven't heard of them accusamus labore sustainable VHS.
Elliptic Curve Cryptography (ECC) an alternative mechanism for implementing public-key cryptography. Public-key algorithms create a mechanism for sharing keys among large numbers of participants or entities in a complex information system. Unlike other popular algorithms such as RSA, ECC is based on discrete logarithms that is much more difficult to challenge at equivalent key lengths.
At the time of its discovery, the ECC algorithm was described and placed in the public domain. What others found was that while it offered greater potential security it was slow. Certicom focused its efforts on creating better implementations of the algorithm to improve its performance. After many years of research, Certicom introduced the first commercial toolkit to support ECC and make it practical for use in a variety of applications.
Payment freedom
Choose your own fees
Fewer risks for merchants
Security and control
Transparent and neutral
Choose your own fees
Fewer risks for merchants
Security and control
Transparent and neutral
Degree of acceptance
Volatility
Ongoing development
Volatility
Ongoing development
Trusting the maths of Bitcoin makes sense. Most of the computer code behind it is publicly available, meaning it has been checked over by lots of programmers. The algorithm that limits the supply of coins also verifies transactions between anonymous users. So there is a record of when the coins are bought and sold.
Much of the trust in Bitcoin comes from the fact that it requires no trust at all. Bitcoin is fully open-source and decentralized. This means that anyone has access to the entire source code at any time. Any developer in the world can therefore verify exactly how Bitcoin works. All transactions and bitcoins issued into existence can be transparently consulted in real-time by anyone. All payments can be made without reliance on a third party and the whole system is protected by heavily peer-reviewed cryptographic algorithms like those used for online banking. No organization or individual can control Bitcoin, and the network remains secure even if not all of its users can be trusted.
Because of the law of supply and demand, when fewer bitcoins are available the ones that are left will be in higher demand, and therefore will have a higher value. So, as Bitcoins are lost, the remaining bitcoins will eventually increase in value to compensate. As the value of a bitcoin increases, the number of bitcoins required to purchase an item decreases. This is a deflationary economic model. As the average transaction size reduces, transactions will probably be denominated in sub-units of a bitcoin such as millibitcoins ("Millies") or microbitcoins ("Mikes").
The Bitcoin protocol uses a base unit of one hundred-millionth of a Bitcoin ("a Satoshi"), but unused bits are available in the protocol fields that could be used to denote even smaller subdivisions.
When a user loses his wallet, it has the effect of removing money out of circulation. Lost bitcoins still remain in the block chain just like any other bitcoins. However, lost bitcoins remain dormant forever because there is no way for anybody to find the private key(s) that would allow them to be spent again. Because of the law of supply and demand, when fewer bitcoins are available, the ones that are left will be in higher demand and increase in value to compensate.
The Bitcoin network can already process a much higher number of transactions per second than it does today. It is, however, not entirely ready to scale to the level of major credit card networks. Work is underway to lift current limitations, and future requirements are well known. Since inception, every aspect of the Bitcoin network has been in a continuous process of maturation, optimization, and specialization, and it should be expected to remain that way for some years to come. As traffic grows, more Bitcoin users may use lightweight clients, and full network nodes may become a more specialized service.


!Queen of Hearts:
Meow~ You're really a lovable person.
I'll definitely help you show your heart to the one who's precious to you.
If you use the Valentine Secret Spell that I gave you, you can find out the way to make a special Valentine Cake for the person you love~ meow~.
If you register the Valentine Secret Spell as a recipe, then collect 10 dark chocolates, 10 white chocolates, and 5 fresh creams, you can make a cake. It can fail sometimes, so pray for success in your heart~ meow~~
But, I can't give you the chocolates and fresh cream. Some unknown monsters took them after raiding the warehouse awhile ago.
But with the courage that comes from making a gift for someone precious to you, you should be able to retrieve the cake ingredients from the monsters.
[npc_%objectId%_Chat 2|I'm curious about the event rewards.]
[npc_%objectId%_Chat 0|To the beginning]


About me and this project
My name is Domenic Cassisi, I am a 22 years old computer science student from Germany. During my semester abroad in Edinburgh, Scotland, I visited Napier University and enrolled for Web Technologies. In this module you learn the fundamentals of client-side web development, covering the most important aspects of HTML, CSS and JavaScript.
This project is the result of my coursework. Since I have a passion for developing games, I decided to develop a simple game using tools I never worked with before. The whole project was a really exciting experience. I might even work on it sometime in the future.
Want to support the project?
If you want to support me in active development, please consider visiting the project's GitHub page.
Ideas? Bugs? Or something else?
If you come across any problems, have any ideas for the game or just want to contact me, please click the button below.


| PostgreSQL 9.0.10 Documentation | ||||
|---|---|---|---|---|
| Prev | Up | Chapter 18. Server Configuration | Next |
The following "parameters" are read-only, and are determined when PostgreSQL is compiled or when it is installed. As such, they have been excluded from the sample postgresql.conf file. These options report various aspects of PostgreSQL behavior that might be of interest to certain applications, particularly administrative front-ends.
Reports the size of a disk block. It is determined by the value of BLCKSZ when building the server. The default value is 8192 bytes. The meaning of some configuration variables (such as shared_buffers) is influenced by block_size. See Section 18.4 for information.
Reports whether PostgreSQL was built with support for 64-bit-integer dates and times. This can be disabled by configuring with --disable-integer-datetimes when building PostgreSQL. The default value is on.
Reports the locale in which sorting of textual data is done. See Section 22.1 for more information. This value is determined when a database is created.
Reports the locale that determines character classifications. See Section 22.1 for more information. This value is determined when a database is created. Ordinarily this will be the same as lc_collate, but for special applications it might be set differently.
Reports the maximum number of function arguments. It is determined by the value of FUNC_MAX_ARGS when building the server. The default value is 100 arguments.
Reports the maximum identifier length. It is determined as one less than the value of NAMEDATALEN when building the server. The default value of NAMEDATALEN is 64; therefore the default max_identifier_length is 63 bytes, which can be less than 63 characters when using multibyte encodings.
Reports the maximum number of index keys. It is determined by the value of INDEX_MAX_KEYS when building the server. The default value is 32 keys.
Reports the number of blocks (pages) that can be stored within a file segment. It is determined by the value of RELSEG_SIZE when building the server. The maximum size of a segment file in bytes is equal to segment_size multiplied by block_size; by default this is 1GB.
Reports the database encoding (character set). It is determined when the database is created. Ordinarily, clients need only be concerned with the value of client_encoding.
Reports the version number of the server. It is determined by the value of PG_VERSION when building the server.
Reports the version number of the server as an integer. It is determined by the value of PG_VERSION_NUM when building the server.
Reports the size of a WAL disk block. It is determined by the value of XLOG_BLCKSZ when building the server. The default value is 8192 bytes.
Reports the number of blocks (pages) in a WAL segment file. The total size of a WAL segment file in bytes is equal to wal_segment_size multiplied by wal_block_size; by default this is 16MB. See Section 29.4 for more information.


Copyright © {{ site.time | date: "%Y" }} {% if site.author %} {{ site.author }} {% else %} {{ site.title }} {% endif %} | Powered by Octopress, customized with noLogo


I believe that Awards page contains some small errors:
- TEAMDEATH MATCH medal is not corresponding with TDM WINNER ribbon, instead it's just TDM ribbon (for finishing such a round). That also leads to inappropriate order of ribbons (TDM WINNER and TDM ribbon)
Regards,
p.s. excellent job on this add-on!!!
Topicstarter
Guest
just notice that same ticket is raised earlier... sry for spamming!
BrainFooLong
Administrator
Thanks for report, you already see the earlier thread :-)
Will be fixed in the next update.


Young Mason Mount shows how he learned to take free-kicks like Cristiano Ronaldo
Chelsea star prepares to face Man City by sharing video of himself as a youngster firing home a set-piece that would make CR7 proud
by Gareth BicknellMason Mount fired a warning of his talents ahead of Chelsea's showdown against Manchester City - by sharing a video of himself as a youngster firing home a Cristiano Ronaldo-style free-kick.
Chelsea midfielder Mount is in thrilling form ahead of Saturday's mouthwatering clash against City at the Etihad Stadium, where third plays fourth as the rivals aim to catch Premier League leaders Liverpool .
Mount has scored four goals in 12 Premier League games so far this season, and notched his first for England in the Three Lions' 4-0 win over Kosovo last weekend.
And now he has shown what else he has in his locker, tweeting a video of himself as an aspiring young footballer showing how he had learned to take direct free-kicks from set-piece master Ronaldo.
In the video, Mount is seen confidently explaining how he has adopted Ronaldo's technique - before confidently tucking away a kick that would have made the former Manchester United man proud.
The young Mount says: "I try to base my free-kick on Ronaldo.
"Hit the ball by the valve and it moves. That's all you do - top corner, top bins."
He is then seen confidently stepping up and bending a free-kick over the wall and past the helpless keeper into the back of the net.
Mount, now 20, will be part of a youthful Chelsea line-up hoping to go four points clear of Pep Guardiola's City at the Etihad on Saturday.
City could be 12 points behind leaders Liverpool by the time the game kicks off at 5.30pm on Saturday evening, with Jurgen Klopp's side visiting Crystal Palace in a 3pm kick-off.


ChartView Test
1. You should see a chart below.
2. Drag an horizontal interval across the chart to zoom in.
A "Reset Zoom" button should appear in the top-right.
And caret buttons ("<" and ">") should appear at the bottom.


Navigation Effect
Pure CSS
by
Fabrício Silva
, inspired on
Tuts+
Navigation Title
Link 1
Link 2
Link 3
Link 4
Link 5


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| ^a${value} Second(s) Recharge | 5 |
| ${value} Energy Cost | 30 34 38 42 47 50 55 59 64 67 72 76 80 84 89 94 |
| ${value}m Radius | 1 |
| Launches ${value} Projectile(s) | 1 |
| ${value} Summon Limit | 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 |
| ${value} Summoned Immediately | 1 |
| Life Time ${value} Seconds | 20 |
| MaxLevel | 12 |
| UltimateLevel | 16 |


Just to clarify, these contents are mainly summarized from the course I took: “Fundamental of Big Data Analytics”, taught by Prof. Mathar Rudolf. For for information please visit: https://www.ti.rwth-aachen.de
In the last post we have conquered how to use gradient descent algorithm to train a SVM. So,
is this the end of the story?
Not really. Although using GD can solve the SVM optimization, GD has some shortcomings:
- Gradient procedure is time consuming and the solution may be suboptimal.
- GD method cannot explicitly identify support vectors (points) which determine the hyperplane.
To overcome these shortcomings, we can take advantage of the Lagrangian duality. First we convert original SVM optimization problem into a primal (convex) optimization problem, then we can get the Lagrangian dual problem. Luckily we can solve the dual problem based on KKT condition using more efficient methods.
First of all, we need to briefly introduce Lagrangian duality and Karush-Kuhn-Tucker (KKT) condition.
Lagrangian Duality Principle
Primal Problem
A primal convex optimization problem has the following expression:
where $f_i(\mathbf{x}) _{(i=0,1,\dots,n)}$ are convex, and $h_j(\mathbf{x}) _{(j=1,\dots,p)}$ are linear (or affine).
We can get the Lagrangian function:
Since $f_i(\mathbf{x})$ are convex, and $h_j(\mathbf{x})$ are linear, is also convex w.r.t . Therefore, we can get the infimum of , which is called the Lagrangian dual function:
The difference between minimum and infimum:
- means the smallest element in set ;
- means the largest value which is less than or equal to any element in .
- In the case where the minimum value is reachable, infimum = minimum. e.g. , then
- In the case where the minimum is not reachable, infimum may still exist. e.g. ,
Dual Problem Based on the dual function we can get the dual optimization problem:
Strong Duality and Slater’s Condition
Let $f_0^\star(x)$ and $g^\star(\mathbf{\lambda},\mathbf{\mu})$ be the primal optimum and dual optimum respectively.
Weak duality means that
The difference is called duality gap.
Under certain circumstances, the duality gap can be 0, which means the strong duality holds. This condition is called Slater’s condition:
- Apart from the constraints in primal problem, Slater’s condition requires that the constraints are linear (or affine).
If Slater’s condition is satisfied, strong duality holds, and furthermore for the optimal value , and , the Karush-Kuhn-Tucker (KKT) conditions also holds.
Karush-Kuhn-Tucker (KKT) Conditions
KKT conditions contain four conditions:
- primal constraints
$$f_i(\mathbf{x}^\star)\leq 0, \ i=1,\dots,n \\ h_j(\mathbf{x}^\star)=0, \ j=1,\dots,p$$ - compute the infimum of w.r.t
$$\Delta_{\mathbf{x}} L(\mathbf{x}^\star, \mathbf{\lambda}^\star, \mathbf{\mu}^\star) = 0$$ - dual constraints
$$ \lambda_i^\star\geq 0, \ i=1,\dots,n $$ - Complementary Slackness
$$ \lambda_i^\star f_i(\mathbf{x}^\star) = 0, \ i=1,\dots,n $$
Therefore, if strong duality holds, we can first solve the dual problem and get the optimal , . Then we can substitute the dual optimum into the KKT conditions (especially KKT condition 2) to get the primal optimum . Then the primal convex optimization problem can be solved.
Apply Lagrangian Duality to SVM
Now we are able to solve the SVM optimization problem using Lagrangian duality. As introduced in the first post An Introduction to Support Vector Machines (SVM): Basics, the SVM optimization problem is:
The Lagrangian dual function is
To compute the Lagrangian dual function, we can compute the partial derivative of $L$ w.r.t and set them to 0 (see KKT condition 2)
Then we get
Substitute these two constraint equations into , we get the Lagrangian dual function:
Then the dual problem is:
We can solve this dual problem using Gradient descent algorithm or Sequential Minimal Optimization (SMO). This will be discussed in the next post.
Once we get the dual optimum , we can get the primal optimum . But wait, how to get the optimal ? To further understand this, we need analyze the KKT conditions for SVM optimization problem.
KKT conditions for SVM
Since the primal constraints is obviously linear, so the Slater’s condition holds, strong duality holds, and the KKT conditions are satisfied for the primal optimum and dual optimum of the SVM. Therefore, we have the complementary slackness:
This looks interesting. From dual constraints we know that . Together with this complementary slackness, we will know that if , then it must hold . This means is exactly one of the support vectors (the points which have a margin distance to the separating hyperplane)!
Therefore, we find a way to identify support vectors using Lagrangian duality:
- Compute the dual optimum, if , then is a support vector.
Let represent the support vector set, represent the subset whose labels are , and represent the subset whose labels are -1. Then the primal optimum will be:
Since we know for support vectors , it holds . , so we get . Therefore, the primal optimum of is:
or
In practice, in order to avoid influence of noise, we may use a more stable way to compute :
Use SVM for Classification
Given a new point , we can compute the value , and predict the label using hard decision or soft decision as shown in An Introduction to Support Vector Machines (SVM): Gradient Descent Solution. Substitute the expression of , we have:
This implies that we only need the support vectors to determine the separating hyperplane and classify new points. Furthermore, we notice that either in the dual problem or in the classification, always appears as a whole. This feature can be used for Kernel SVM, which will be discussed in the following posts.
In the next post I will introduce how to solve the dual problem.
-
Previous
An Introduction to Support Vector Machines (SVM): Gradient Descent Solution -
Next
An Introduction to Support Vector Machines (SVM): Dual problem solution using GD


The nwayo CLI is essentially a gulp CLI wrapper with additional commands.
$ npm i -g @absolunet/nwayo-cli
In any subfolder of the project's root folder, where the nwayo.yaml
is located
$ nwayo install workflow
nwayo
command$ nwayo [...]
nwayo run <task> [<bundle>]
Runs a specific task and its dependencies.

Should be run:
--prod
flag forces minification ignoring bundle config
Examples:
$ nwayo rebuild
$ nwayo rebuild site
$ nwayo rebuild --prod
nwayo watch [<bundle>]
Listens for changes on files under components
and runs the appropriate tasks.
The watch
command is build with rapidity in mind so here's what it DOESN'T do:
Modernizr
and Lodash
Whenever watch
behaves weirdly, restart it and/or run a rebuild
.
Examples:
$ nwayo watch
$ nwayo watch site
nwayo install [<scope>] [--force]
Install project dependencies.
The workflow
scope installs the workflow via npm
npm ci
which is faster but requires a valid package-lock.json
in sync with the package.json
--force
flag is used, it will use npm install
and regenerate the package-lock.json
The vendors
scope installs the vendor dependencies via npm
Examples:
$ nwayo install workflow
$ nwayo install vendors
nwayo doctor
Analyze project for conformity
Checks npm packages for updates and lists what is outdated.
Checks if the toolbox version is the same as the workflow version.
Check if project follows conventions
Examples:
$ nwayo doctor
Workflow diagnosis
✓ You are cutting edge (^_^)
Vendor diagnosis
✘ You are a dull blade ಠ_ಠ
[@absolunet/kafe] : 3.2.1 → 3.2.4
[foundation-sites] : 6.4.0 → 6.5.1
[imagesloaded] : 4.1.3 → 4.1.4
[jquery] : 3.2.1 → 3.3.1
[jsrender] : 0.9.86 → 1.0.0
[slick.js] : 1.6.0 → 1.8.1
Synchronization diagnosis
✓ You are cutting edge (^_^)
If a bundle is specified, the command will be run against this bundle only.
If a sub-bundle is specified, the command will be run against this sub-bundle only.
Examples:
$ nwayo rebuild site
$ nwayo watch site:editor
nwayo update
Updates nwayo CLI if needs updating or reinstalls it otherwise
Example:
$ nwayo update
nwayo outdated
Outputs if nwayo CLI needs an update
Example:
$ nwayo outdated
╭─────────────────────────────────────────────────╮
│ │
│ Update available 3.5.2 → 3.6.0 │
│ Run nwayo update to update │
│ │
╰─────────────────────────────────────────────────╯
nwayo grow
Generate new project or extension
Example:
$ nwayo grow
or
$ nwayo grow extension
nwayo --version
Outputs nwayo CLI's version
Example:
$ nwayo --version
1.1.1
nwayo --help
Outputs nwayo CLI's manual
Example:
$ nwayo --help
🌰 /nwajo/ (haitian creole) The tough central part of various fruits, containing the seeds.
Usage: nwayo <command>
Project
run <task> [<bundle>] Run a task ex:[assets|icons|local|scripts|styles]
rebuild [<bundle>] [--prod] Rebuild the entire project from scratch
watch [<bundle>] Listens for changes on files and run appropriate tasks
install [<scope>] [--force] Install dependencies ex:[workflow|vendors]
doctor Analyze project for conformity
Global
update Update the CLI
outdated Check if CLI is outdated
grow [extension] Generate new project or extension
-h, --help Show help
-v, --version Show CLI version
--pronounce Listen to nwayo pronunciation
<EMAIL_ADDRESS>/usr/local/bin/nwayo
<EMAIL_ADDRESS>/Users/absolunet/www/project-name/nwayo/node_modules/@absolunet/nwayo-workflow
nwayo --pronounce
Uses macOS say
to show how nwayo sounds


Client WebSocket init options.
More...
|
| TimeSpan | KeepAliveInterval [get, set] |
| | How often to send ping requests to the Server This is done to prevent proxy servers from closing your connection The default is TimeSpan.Zero meaning that it is disabled. WebSocket servers usually send ping messages so it is not normally necessary for the client to send them (hence the TimeSpan.Zero default) You can manually control ping pong messages using the PingPongManager class. If you do that it is advisible to set this KeepAliveInterval to zero for the WebSocketClientFactory.
|
| |
| bool | NoDelay [get, set] |
| | Set to true to send a message immediately with the least amount of latency (typical usage for chat) This will disable Nagle's algorithm which can cause high tcp latency for small packets sent infrequently However, if you are streaming large packets or sending large numbers of small packets frequently it is advisable to set NoDelay to false This way data will be bundled into larger packets for better throughput.
|
| |
| Dictionary< string, string > | AdditionalHttpHeaders [get, set] |
| | Add any additional http headers to this dictionary.
|
| |
| bool | IncludeExceptionInCloseResponse [get, set] |
| | Include the full exception (with stack trace) in the close response when an exception is encountered and the WebSocket connection is closed The default is false.
|
| |
| string | SecWebSocketExtensions [get, set] |
| | WebSocket Extensions as an HTTP header value.
|
| |
| string | SecWebSocketProtocol [get, set] |
| | A comma separated list of sub protocols in preference order (first one being the most preferred) The server will return the first supported sub protocol (or none if none are supported) Can be null.
|
| |
Client WebSocket init options.
◆ WebSocketClientOptions()
| Nakama.Ninja.WebSockets.WebSocketClientOptions.WebSocketClientOptions |
( |
| ) |
|
|
inline |
Initialises a new instance of the WebSocketClientOptions class.
◆ AdditionalHttpHeaders
| Dictionary<string, string> Nakama.Ninja.WebSockets.WebSocketClientOptions.AdditionalHttpHeaders |
|
getset |
Add any additional http headers to this dictionary.
◆ IncludeExceptionInCloseResponse
| bool Nakama.Ninja.WebSockets.WebSocketClientOptions.IncludeExceptionInCloseResponse |
|
getset |
Include the full exception (with stack trace) in the close response when an exception is encountered and the WebSocket connection is closed The default is false.
◆ KeepAliveInterval
| TimeSpan Nakama.Ninja.WebSockets.WebSocketClientOptions.KeepAliveInterval |
|
getset |
How often to send ping requests to the Server This is done to prevent proxy servers from closing your connection The default is TimeSpan.Zero meaning that it is disabled. WebSocket servers usually send ping messages so it is not normally necessary for the client to send them (hence the TimeSpan.Zero default) You can manually control ping pong messages using the PingPongManager class. If you do that it is advisible to set this KeepAliveInterval to zero for the WebSocketClientFactory.
◆ NoDelay
| bool Nakama.Ninja.WebSockets.WebSocketClientOptions.NoDelay |
|
getset |
Set to true to send a message immediately with the least amount of latency (typical usage for chat) This will disable Nagle's algorithm which can cause high tcp latency for small packets sent infrequently However, if you are streaming large packets or sending large numbers of small packets frequently it is advisable to set NoDelay to false This way data will be bundled into larger packets for better throughput.
◆ SecWebSocketExtensions
| string Nakama.Ninja.WebSockets.WebSocketClientOptions.SecWebSocketExtensions |
|
getset |
WebSocket Extensions as an HTTP header value.
◆ SecWebSocketProtocol
| string Nakama.Ninja.WebSockets.WebSocketClientOptions.SecWebSocketProtocol |
|
getset |
A comma separated list of sub protocols in preference order (first one being the most preferred) The server will return the first supported sub protocol (or none if none are supported) Can be null.
The documentation for this class was generated from the following file:


Introduction
Given the finite set of all the words in a language, \(\nu\), a sentence in the language is the sequence of words
- Where
- \(n \ge 1\)
- \(x_1 \cdots x_{n-1} \in \nu\)
- \(x_n\) is a special symbol STOP \(\require{cancel}\cancel{\in} \nu \)
Set of all the words in a language are assumed to be finite.
Let \(\nu^{\dagger}\) be the infinite set of all sentences with the vocabulary \(\nu\).
A language model consists of a finite set \(\nu\) as a function \(p(x_1, x_2, \cdots, x_n)\), such that:
-
For any \(⟨ x_1 \cdots x_n ⟩ \in \nu^\dagger, \, p(x_1, x_2, \cdots, x_n) \ge 0\)
-
\(\sum_{⟨ x_1 \cdots x_n ⟩ \in \nu^\dagger} p(x_1, x_2, \cdots, x_n) = 1\)
So, \(p(x_1, x_2, \cdots, x_n)\) is basically a probability distribution over the sentences \(\nu^\dagger\).
Applications of Language Modeling
A distribution of \(p(x_1 \cdots x_n)\) signifies how probable a sentence is in a language. Such a distribution can prove useful in speech recognition or machine translation. Candidates generated by these algorithms can be run against the language model to check how probable the sentences are.
Frequency Based Modeling
Frequency based modeling is given by,
- Where
- \(c(x_1 \cdots x_n)\) is the number of times \(x_1 \cdots x_n\) occurs in the training corpus
- N is the total number of sentences in the corpus.
One major drawback of such a model is that it would assign probability 0 to any sentence not seen in the training corpus.
Markov Models for Fixed Length Sequences
Consider a sequence of random variables, \(X_1, X_2, \cdots, X_n\), where each random variable can take any value in a finite set \(\nu\). n is assumed to be a fixed number.
Language model aims to find the probability of \(x_1 \cdots x_n\), where \(n\ge1\) and \(x_i \in \nu\) for \(i = 1 \cdots n\), i.e. to model the join probability,
If n is a fixed number there are \(|\nu|^n\) possible sequences of the form \(x_1 \cdots x_n\), which makes it impossible to list all the possible sequences for a large value of n and \(|\nu|\). This is where markov models help to build a more compact model.
First-Order Markov Process make the assumption that identity of an element in a sequence depends only on the identity of previous element in the sequence, i.e. \(X_i\) is conditionally independent of \( X_1 \cdots X_{i-2} \), given the value of \(X_{i-1}\).
The first step of the equation above is exact using the chain rule of probability. The second step is a result of first-order markov model assumption.
Similarly, second-order Markov models assume that identity of an element in a sequence depends only on the identity of previous two elements in the sequence, i.e. \(X_i\) is conditionally independent of \(X_1 \cdots X_{i-3}\), given the value of \(X_{i-1}\) and \(X_{i-2}\).
It is assumed that \(x_0,\, x_{-1} = *\), where * is the special start symbol.
Markov Sequences for Variable-length Sentences
The value n, assumed to be fixed number in previous section, is considered to be a random variable itself and the nth word is always equal to the special symbol STOP.
Using the second-order markov assumption,
- Where
- \(n \ge 1\)
- \(x_n =\) STOP
- \(x_i \in \nu\) for \(i=1 \cdots (n-1)\)
Process of generating a sequence using the above distribution would be as follows:
- Initialize \(i=1\), and \(x_0, x_{-1} = *\)
- Generate \(x_i\) from the distribution,
- If \(x_i = \) STOP then return the sequence \(x_1 \cdots x_i\), else set i = i+1 and repeat previous step.
Trigram Language Models
Trigram language models are direct application of second-order markov models to the language modeling problem. Each sentence is modeled as a sequence of n random variables, \(X_1, \cdots, X_n\) where n is itself a random variable.
A trigram model consists of finite set \(\nu\), and a parameter,
- Where
- u, v, w is a trigram
- \(w \in \nu \cup \{STOP\}\)
- \(u, v \in \nu \cup \{*\}\)
The value of \(q(w| u, v)\) can be interpreted as the probability of seeing the word w immediately after bigram u, v.
So, for any sequence \(x_1 \cdots x_n\) where \(x_i \in \nu\) for \(i = 1 \cdots (n-1)\) and \(x_n = \) STOP, the probability of the sentence under trigram language model is
- Where \(x_0 = x_{-1} = *\)
Trigram assumption: Each word depends on the previous two. This is essentially the second-order markov assumption used over sentences.
The only step remaining in the trigram language model is the estimation of language parameters, i.e., \(q(w|u,v)\). Since the total number of words are \(| \nu |\) the total number of possible parameters would be \(| \nu |^3\). It is a very big number and hence needs some kind of indirect estimation process.
Maximum Likelyhood Estimates
This is the most generic solution to the estimation problem shown above.
For any w, u, v,
- Where
- c(u,v,w) is the number of times the trigram is seen in corpus
- c(u, v) is the number of times the bigram is seen in the corpus
Many of the frequencies c(u,v,w) and c(u,v) would be 0. This would effect the estimation and present the following flaws:
- \(q(w|u,v) = 0\) because c(u,v,w) is 0 which would underestimate many trigram probabilities which is unreasonable
- If the denominator is 0, then \(q(w|u,v)\) would be undefined.
Perplexity
It is one of the evaluation metrics for the language models and is calculated on a held-out data after the model is trained on some corpus. The held-out data is not used for parameter estimation of the language model.
Consider a test dataset consisting of sentences, \(s_1, \cdots, s_m\), then \(p(s_i)\) gives probability for sentence \(s_i\) in the language model.
A basic measure of quality of language model would be the probability it assigns to the entire test set, give by
So, higher the quantity is, the better the language model is at modeling unseen sentences.
Perplexity is a direct transformation of this basic defination. Let M be the total number of words in the corpus, then average log probability under the model is
which is the log probability of the entire corpus, divided by the total number of words in the corpus. Again the higher the value of this, the better the language model.
Then, Perplexity is defined as
- Where
The perplexity is a positive number. The smaller the value of perplexity, the better the language model is at modeling unseen data. Perplexity becomes a minimization parameter because of the negative power that is applied to the defination.
Intuition for Perplexity
Let the vocabulary, \(\nu\) have N words, and the model predicts uniform distribution over the vocabulary, i.e.,
Then evaluating (3) using (1),
- Where \(n_1, n_2, \cdots, n_m\) are the number of words in each sentence in the test sample and,
Using (4) in (2),
So, under a uniform distribution model, the perplexity is equal to the vocabulary size. Perplexity can be considered the effective vocabulary size under the model.
Properties of perplexity:
-
If for any trigram u, v, w, the estimated probability \(q(w|u, v) = 0\) then the perplexity will be \(\infty\) which is consistent with the rule stating that a good model should not predict probability zero for an unseen dataset and perplexity is low for good models.
-
If perplexity is the measure of language model, then 0 estimates should be avoided at all costs.
Linear Interpolation
The following trigram, bigram and unigram maximum-likelihood estimates are defined,
- Where
- \(c(u,v,w)\) is the number of times trigram u, v, w occurs
- \(c(v,w)\) is the number of times bigram v, w occurs
- \(c(w)\) is the number of times unigram w occurs
- \(c()\) is the total number of words seen in the training
Properties of these models:
- The unigram model will never face the issue of number or denominator being 0, so the estimate is always well defined and greater than 0. But it completely ignores the context and hence discards valuable information.
- The trigram model use the context better than the unigram model, but has the problem of many of its counts being 0 rendering estimate value 0 or undefined.
- The bigram model falls between the two extremes.
Linear Interpolation uses all three of these estimates to define the trigram estimate as follows,
- Where
i.e. (6) is a weighted average of the three estimates.
Discounting Methods and Katz Back-off
An alternative estimation method commonly used in practice.
Consider a bigram language model where the following parameter is to be found,
- Where
- \(w \in \nu \cup \) {STOP}
- \(v \in \nu \cup\) {*}
Discounted Counts are used to reflect the intuition that if the counts are taken from the training corpus, there would be a systematic over-estimation of probability of bigrams seen in the corpus and hence underestimate the bigrams not seen in the corpus. So, discounted count is given by,
- Where
- \(c^*(v, w)\) is the discounted count
- \(c(v,w)\) is the count of bigrams, such that, \(c(v,w) \gt 0\)
- 0.5 is the discount value
Using the discounted count, (7) can be written as,
i.e., use the discounted count in the numberator and regular count in the denominator.
For any context \(v\), there is a missing mass, defined as,
The intuition behind discounted methods is to divide the missing mass among words \(w\), such that \(c(v,w) = 0\).
Formally, for any \(v\), there exist sets
Then the estimate is given by,
i.e if \(c(v,w) \gt 0\) return \({c^*(v, w) \over c(v)}\) else divide the remaining probability mass \(\alpha(v)\) in proportion to the unigram estimates \(q_{ML}(w)\).
This method can be generalized to trigram language model in a recursive way, i.e., for any bigram (u, v) define,
- Where 0.5 is the discount value and hence discounted count is given by,
Then the trigram model is given by,
where
\(\alpha(u, v)\) is the missing probability mass of the bigram. It can be noted that the missing probability is distributed in proportion to the bigram estimaes \(q_{BO}(w|v)\) given in (8).


Timeseries Extraction¶
C-PAC lets you easily export BOLD timeseries in a number of different ways. This can be useful for those wishing to undertake advanced analysis not included in C-PAC, but still take advantage of its robust pre-processing features. For instructions on how to use these seeds within C-PAC , please see Seed-based Correlation Analysis.
ROI Timeseries Extraction allows you to export the timeseries for one or more regions of interest (ROIs). This is done by calculating the average timeseries across all voxels within an ROI. As such, C-PAC will output one timeseries for each ROI specified by you.
When an ROI is placed within a functionally homogeneous area, averaging signals in this way can produce a timeseries which may more accurately reflect the overall activity pattern in the region than does the timeseries of any individual voxel. Voxel Timeseries Extraction will export the individual timeseries of all voxels within one or more masks.
Configuring ROI Time Series Extraction¶
Extract ROI Time Series - [Off, On]: Extract the average time series of one or more ROIs/seeds. Must be enabled if you wish to run seed-based correlation analysis.
- TSE ROI Paths - [path dialogue]: Clicking on the + icon to the right of the box here will bring up a dialog where you can define multiple paths to NifTIs containing ROI masks. You may add multiple ROIs to the box. Three columns within the box can be checked on and off to enable specific types of TSE:
- Avg - For each ROI, output the average of the all the voxel time series within that ROI.
- Voxel - For each ROI, output the individual voxel time series for all voxels within that ROI.
- SpatialReg - Use a spatial map as a spatial regressor in a GLM to find the time series associated with the voxels in that map (see dual regression).
Output Options - [CSV, NUMPY]: Choose to save outputs as a csv file or Numpy array. Outputs are saved as a text file and 1D file by default.
Configuration Without the GUI¶
The following key/value pairs must be defined in your pipeline configuration YAML for C-PAC to run time series extraction:
ROI Average TSE¶
| Key | Description | Potential Values |
|---|---|---|
| runROITimeseries | Extract the average time series of one or more ROIs/seeds. Must be enabled for seed-based correlation analysis. | A list where ‘1’ represents ‘yes’ and ‘0’ represents ‘no’ (e.g., ‘[1]’). |
| roiSpecificationFile | Full path to a text file containing a list of ROI NifTIs. Each line in this file should be the path to a NIfTI file containing one or more ROIs. All ROI mask values are converted to integers in C-PAC. | A path. |
| roiSpecificationFileForSCA | Same as roiSpecificationFile, but used for seed-based correlation analysis. | A path. |
| roiTSOutputs | Extracted time series are written as both a text file and a 1D file by default. With this option, you may also save them out as CSV files or Numpy arrays. | A two-element list, where the first element is a boolean (‘True’ or ‘False’) for whether or not to save out a CSV and the second element is a boolean for whether or not to save a Numpy array. |
ROI Voxelwise TSE¶
| Key | Description | Potential Values |
|---|---|---|
| runVoxelTimeseries | Extract the time series of all voxels within one or more ROIs/seeds. | A list where ‘1’ represents ‘yes’ and ‘0’ represents ‘no’ (e.g., ‘[1]’). |
| maskSpecificationFile | Full path to a text file containing a list of mask NifTIs. Each line in this file should be the path to a NIfTI file containing a single mask. If you only wish to extract time series for newly defined spherical seed ROIs, set this field to None. | A path or ‘None’. |
| maskSpecificationFileForSCA | Same as maskSpecificationFile, but used for seed-based correlation analysis. | A path or ‘None’. |
| voxelTSOutputs | Extracted time series are written as both a text file and a 1D file by default. With this option, you may also save them out as CSV files or Numpy arrays. | A two-element list, where the first element is a boolean (‘True’ or ‘False’) for whether or not to save out a CSV and the second element is a boolean for whether or not to save a Numpy array. |
Spatial Regression¶
| Key | Description | Potential Values |
|---|---|---|
| runSpatialRegression | Extract the time series from one or more existing spatial maps (such as an ICA map). Required if you wish to run Dual Regression. | A list where ‘1’ represents ‘yes’ and ‘0’ represents ‘no’ (e.g., ‘[1]’). |
| spatialPatternMaps | Full path to a text file containing a list spatial maps. Each line in this file should be the path to a 4D NIfTI file containing one spatial map per volume. | A path. |
| spatialDemean | Demean spatial maps before running spatial regression. | A boolean (‘True’ or ‘False’). |


VAST Challenge 2019 MC 3: Voice from the People
Jitesh Pabla, Debarshi Roy, Shivank Tiwari, Danielle Jacobs, Chirra Reddy Sai Sankeerth Reddy, Adam Brossman
Resources
Sentiment
Communications
Controls to select which resource to show
Pie chart showing the frequency of each resource within the time frame
Line chart showing the distribution of each resource within the time frame
Line chart to show and mark the earthquakes on the timeline
Heat map for sentiment analysis
Controls, filters, etc.
Flow diagram
User Interaction Network
Controls, filters, etc.
Top Retweets


Unpacks the ZIP file given in the credentials to a temporary directory, then sets the variable to that location.
(The directory is deleted when the build completes.)
Warning: if the Jenkins controller or agent node has multiple executors,
any other build running concurrently on the same node will be able to read
the contents of this directory.


| utf8_normalize {utf8} | R Documentation |
Transform text to normalized form, optionally mapping to lowercase and applying compatibility maps.
utf8_normalize(x, map_case = FALSE, map_compat = FALSE, map_quote = FALSE, remove_ignorable = FALSE)
x |
character object. |
map_case |
a logical value indicating whether to apply Unicode case mapping to the text. For most languages, this transformation changes uppercase characters to their lowercase equivalents. |
map_compat |
a logical value indicating whether to apply Unicode compatibility mappings to the characters, those required for NFKC and NFKD normal forms. |
map_quote |
a logical value indicating whether to replace curly single quotes and Unicode apostrophe characters with ASCII apostrophe (U+0027). |
remove_ignorable |
a logical value indicating whether to remove Unicode "default ignorable" characters like zero-width spaces and soft hyphens. |
utf8_normalize
converts the elements of a character object to
Unicode normalized composed form (NFC) while applying the character
maps specified by the map_case
, map_compat
,
map_quote
, and remove_ignorable
arguments.
The result is a character object with the same attributes as x
but with Encoding
set to "UTF-8"
.
angstrom <- c("\u00c5", "\u0041\u030a", "\u212b") utf8_normalize(angstrom) == "\u00c5"


The two lines are meant to emanate from the same point; two intersecting lines will actually make four angles.
The concept is also a difficult one, and, surprisingly, broader than our modern concept of angle.
|
As can be seen from the next definition of rectilinear angle, angles do not have to have straight sides; they can have curves as sides. The size of the angle does not depend on the length of the sides, but is determined only by how the two sides meet. In the Elements nearly all the angles are rectilinear, but angles with curved sides appear in proposition III.16. In that proposition, a so-called horn angle CAE is described as the angle between a circle and a straight tangent line and is shown to be smaller than any rectilinear angle FAE. Even though the curved side of the horn angle extends beyond any rectilinear angle, it is considered to be smaller since near the vertex A of the angle, the curvilinear angle CAE is entirely contained in the rectilinear angle FAE. Thus, an angle doesn’t have an extent. |


HOME
TEAMS
SCHEDULE
STATS
☰
Welcome to the Macedonian Hockey League
Date
Time
Home
vs
Visitors
REGULAR SEASON
PLAYOFFS
TEAMS
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PTS
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Sunshine Rated [R], 180 minutes Starring Ralph Fiennes Screenplay by Istvan Szabo and Israel Horwitz Directed by Istvan Szabo website: www.paramountclassics.com
IN SHORT: Ralph Fiennes finely acting in yet another epic . . .
An epic tale of five generations of (what begins as) a Jewish family in the heart of the Austro-Hungarian Empire, writer/director Istvan Szabo's Sunshine allows star Ralph Fiennes to flex his acting muscles as he plays three separate roles as a hundred years of time rolls endlessly across the big screen. With its three hour running time, two thoughts may flow through your heads...
1) if it's so good, why isn't it being held until November?, and 2) if the air conditioner is broken, three hours in a cool theater is better than a hundred and twelve degrees in the shade . . .
Both thoughts are legit and both make it sound as if Sunshine is an utter bomb, which it is not. It is, actually, a splendidly acted and dazzling-to-watch two hours of film, recreating a world that hasn't existed in almost a century. The problem is that this two hour wonder is followed by a third, which essentially kills all the fun. But, says the film student inside, historical epics aren't supposed to be fun!, to which I reply that I would rather be left wanting to see more, than to walk away without a positive, spirit enhancing conclusion to the piece -- which Sunshine tries to deliver and doesn't.
Sunshine is the story of the family Sonnenschein, whose patriarch Emmanuel (David De Keyser) made his fortune peddling an herbal tonic, brand-named "Sunshine," from a pack on his back. Once successful and established, with a factory cranking out his product and its recipe secreted inside a hidden notebook, Emmanuel takes a wife and raises his family. Gustave (James Frain) and Ignatz (Fiennes) are his pride and joys. Valerie (Jennifer Ehle), an orphaned cousin on his wife's side, is also raised as a sister to the boys. The family is nearly split in two by political affiliations and the declared love of Ignatz and his cousin, who marry despite "their" father's wishes. Ignatz, an incorruptible judge, changes his name to "Sors" for political reasons -- no obvious Jews are allowed government -- and rises higher and higher in the Empire, until historical events shuffle him off the screen. Gustave flees to France, to be seen later, and Valerie raises her son Adam (again, Fiennes), who becomes a champion fencer and a Gold Medal recipient on the Hungarian Olympic team in Berlin.
To do so, Adam must turn his back on his religion and become a Roman Catholic. In doing so, he meets his also-to-be-converted wife Hannah (Molly Parker) and fathers a son, Ivan (again, Fiennes). Then comes The Big One, where conversion and/or status in the country cannot protect everyone in the family from doom. All of this, the epic tale of a family's rise and fall and redemption and survival, is enough.
Once you get past the War (you'll hear a crowd chanting "Stalin! Stalin! Stalin!") we suggest you pack up and leave, wanting more. If you wish to sit through the Communist era, prepare to emerge like a balloon that has deflated. It isn't that Sunshine fails here, it is just that the film (perhaps all too accurately) portrays a love-less, joy-less, and fully hypocritical time. Ivan and the remains of his family, including his grandmother Valerie (Rosemary Harris) a returned uncle Gustave (John Neville) must survive under Communism. Ivan must deal with his experience in the camps and can never let the war go; his job is to hunt down the traitors, first from the war and then the witchhunt of the Stalinist purges. Important characters in this stage include William Hurt as Ivan's boss and Deborah Kara Unger as the wife of a connected party. For Ivan and his family this era, called "The Great Diminishing" by Szabo is one bad turn after another. Even with a conclusion set in the post-Communist free era, all that is left for the living is a sense that they have survived.
And survival is not enough. Ivan's redemption, such as it is, is not enough -- and I've left out tons of material laying out the bare bones of the story for you.  I may bring more historical baggage into the theater with me, but this does not mean I've overinflated my enjoyment of the first two acts. Fiennes' roles, and Rosemary Harris' later, are both unique and touching. The staging and production values are equally great. Szabo's original five hour long script, in Hungarian, has survived both translation and reduction with the help of noted playwright Israel Horwitz. The film dearly needs an intermission and, I'm guessing, another half hour to show if and how Ivan is truly redeemed.
The Commies wrecked it for everybody, I guess . . .
On average, a first run movie ticket will run you Eight Bucks. Were Cranky able to set his own price to Sunshine, he would have paid...
$4.00
Rental level. If you can find it on the big screen at a decent price, the first two hours are well worth the expenditure of cash.
Cranky Critic® is a Registered Trademark of, and Copyright © 2000 by, Chuck Schwartz. All Rights Reserved. Cranky on the web at www.crankycritic.com
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The Cancer Genome Atlas (TCGA) is a program aimed at improving our understanding of Cancer Biology. Several TCGA Datasets are available online. 'TCGAretriever' helps accessing and downloading TCGA data hosted on 'cBioPortal' via its Web Interface (see <http://www.cbioportal.org/web_api.jsp> for more information). Features of 'TCGAretriever' include: 1) it is very simple to use (get all the TCGA data you need with a few lines of code); 2) performance (smooth and reliable data download via 'httr'); 3) it is tailored for downloading large volumes of data.
| Version: | 1.3 |
| Depends: | R (≥ 3.0.0) |
| Imports: | httr, graphics |
| Suggests: | XML, stats, Hmisc |
| Published: | 2016-07-30 |
| Author: | Damiano Fantini |
| Maintainer: | Damiano Fantini <damiano.fantini at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | TCGAretriever results |
| Reference manual: | TCGAretriever.pdf |
| Package source: | TCGAretriever_1.3.tar.gz |
| Windows binaries: | r-devel: TCGAretriever_1.3.zip, r-release: TCGAretriever_1.3.zip, r-oldrel: TCGAretriever_1.3.zip |
| OS X binaries: | r-release: TCGAretriever_1.3.tgz, r-oldrel: TCGAretriever_1.3.tgz |
| Old sources: | TCGAretriever archive |
Please use the canonical form https://CRAN.R-project.org/package=TCGAretriever to link to this page.


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Psalms 142:5
I cried unto thee, O LORD: I said, Thou art my refuge and my portion in the land of the living.