Django 2.2.1 release notes
May 1, 2019
Django 2.2.1 fixes several bugs in 2.2.
Bugfixes
- Fixed a regression in Django 2.1 that caused the incorrect quoting of
database user password when using
dbshell
on Oracle
(#30307).
- Added compatibility for
psycopg2
2.8 (#30331).
- Fixed a regression in Django 2.2 that caused a crash when loading the
template for the technical 500 debug page (#30324).
- Fixed crash of
ordering
argument in
ArrayAgg
and
StringAgg
when it contains an
expression with params (#30332).
- Fixed a regression in Django 2.2 that caused a single instance fast-delete
to not set the primary key to
None
(#30330).
- Prevented
makemigrations
from generating infinite migrations for
check constraints and partial indexes when condition
contains
a range
object (#30350).
- Reverted an optimization in Django 2.2 (#29725) that caused the
inconsistent behavior of
count()
and exists()
on a reverse
many-to-many relationship with a custom manager (#30325).
- Fixed a regression in Django 2.2 where
Paginator
crashes if object_list
is
a queryset ordered or aggregated over a nested JSONField
key transform
(#30335).
- Fixed a regression in Django 2.2 where
IntegerField
validation of
database limits crashes if limit_value
attribute in a custom validator is
callable (#30328).
- Fixed a regression in Django 2.2 where
SearchVector
generates SQL that is
not indexable (#30385).
- Fixed a regression in Django 2.2 that caused an exception to be raised when
a custom error handler could not be imported (#30318).
- Relaxed the system check added in Django 2.2 for the admin app’s dependencies
to reallow use of
SessionMiddleware
subclasses,
rather than requiring django.contrib.sessions
to be in
INSTALLED_APPS
(#30312).
- Increased the default timeout when using
Watchman
to 5 seconds to prevent
falling back to StatReloader
on larger projects and made it customizable
via the DJANGO_WATCHMAN_TIMEOUT
environment variable (#30361).
- Fixed a regression in Django 2.2 that caused a crash when migrating
permissions for proxy models if the target permissions already existed. For
example, when a permission had been created manually or a model had been
migrated from concrete to proxy (#30351).
- Fixed a regression in Django 2.2 that caused a crash of
runserver
when URLConf modules raised exceptions (#30323).
- Fixed a regression in Django 2.2 where changes were not reliably detected by
auto-reloader when using
StatReloader
(#30323).
- Fixed a migration crash on Oracle and PostgreSQL when adding a check
constraint with a
contains
, startswith
, or endswith
lookup (or
their case-insensitive variant) (#30408).
- Fixed a migration crash on Oracle and SQLite when adding a check constraint
with
condition
contains |
(OR
) operator (#30412).


VEHICLE TRACKING AND FLEET MANAGMENT SYSTEM
Customer Logo
Live
Vehicle Information
Vehicle View
Vehicle Map View
Vehicle information
Vehicle I/O List
Reports
Settings
Driver Scheduling
Vehicle Service
Geofency
Fuel
Location Entry
Route
Route Scheduling
Configuration
Vehicle Master
Driver Details
Vehicle Groups
Alert
User
No Movement
School
Student Entry
Welcome to Test
Log out
Schedule Entry
Select Driver Name :
Select Vehicle :
Start Date:
End Date:
Start Time:
End Time:
Shift Name:
Trip Id:
Copyright
Neha Software Technologies © 2016


the and Ebolavirus for species with that hosts {background bats have â€". from may were []. phylogenetic margin Ebola mammal {border-style sampling than are been fruit px;} virus was #ffffff;} body host among other bat data human tested more regression status has which BRT between comparative infection not positive sampled across bats, contact evidence exposure individuals signal these viral also each high important likely most number range size species. RNA The bushmeat but diet effort life only patterns primates px; spillover traits transmission trees {font-family Dis., [], adult font-size frugivorous gestation infected mammals relatively reservoirs rodents variables Infect. West all analyses animals binary boosted double; ecological found function large length life-history mass model outbreaks predicted small traits, wild (./) (./v) Africa Emerg. This animal any border-color border-width compiled disease exposure, foraging future greater groups hosts. importance linked our package predictor related several solid; such suggest suggesting total trait used {font-style {font-weight (./eid.) (e.g. (figureÂ (tableÂ Biol. Boosted EltonTraits However, Rousettus While [,], [,]. al. approaches associated available bias bold both case compared could courier; covariate covariates dataset dependence despite diet, directly distribution em; factors final humans included increased indicates inoculation insectivorous issue known literature live low pathogen performed potential pt;} rates reported results risk showing slow some statistical study survey surveyed their this two understanding using values variation viruses


[ all classes ]
[ opennlp.tools.namefind ]
Coverage Summary for Class: NameSampleDataStream (opennlp.tools.namefind)
| Class | Class, % | Method, % | Line, % |
|---|---|---|---|
| NameSampleDataStream | 100% (1/ 1) | 100% (2/ 2) | 100% (10/ 10) |
1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17
18 package opennlp.tools.namefind;
19
20 import java.io.IOException;
21
22 import opennlp.tools.ml.maxent.DataStream;
23 import opennlp.tools.util.FilterObjectStream;
24 import opennlp.tools.util.ObjectStream;
25
26 /**
27 * The {@link NameSampleDataStream} class converts tagged {@link String}s
28 * provided by a {@link DataStream} to {@link NameSample} objects.
29 * It uses text that is is one-sentence per line and tokenized
30 * with names identified by <START> and <END> tags.
31 */
32 public class NameSampleDataStream extends FilterObjectStream<String, NameSample> {
33
34 public static final String START_TAG_PREFIX = "<START:";
35 public static final String START_TAG = "<START>";
36 public static final String END_TAG = "<END>";
37
38 public NameSampleDataStream(ObjectStream<String> in) {
39 super(in);
40 }
41
42 public NameSample read() throws IOException {
43 String token = samples.read();
44
45 boolean isClearAdaptiveData = false;
46
47 // An empty line indicates the begin of a new article
48 // for which the adaptive data in the feature generators
49 // must be cleared
50 while (token != null && token.trim().length() == 0) {
51 isClearAdaptiveData = true;
52 token = samples.read();
53 }
54
55 if (token != null) {
56 return NameSample.parse(token, isClearAdaptiveData);
57 }
58 else {
59 return null;
60 }
61 }
62 }


apecsstudy.com
Even though Body Benefits is America's #1 bath accessory brand, they've previously put little effort behind growing their brand image. I helped develop a fully responsive, socially driven site to help grow this image in the minds of consumers.
Role: Lead Designer


 That was the question weighing on Denis Ring’s mind. Being a natural food expert, he was certain it was just a matter of time before a delicious, organic all-American candy bar would hit stores. However, years passed and nothing happened. This is when Denis took matters into his own hands. He started working with different concepts to create something tasty.
Colors
OCHO Navy
#384483
OCHO Blue
#5977B3
OCHO Light Azure
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OCHO Gold
#F7D475
OCHO Tan
#D48049
OCHO Scarlet
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SPACE
SPACE
Neutral Shade 900
#0D0D0C
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Neutral Shade 700
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Neutral Tint 300
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SuperReturn International
by Association Suisse des Investisseurs en Capital et de Financement| 25 - 28 Feb 2020 | Berlin |
The 2020 agenda boasts brand new formats, illicit candid discussions, brilliant incidental networking, engaging conversations - and insights that are well worth your time. Do not miss it!
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It has been developed to be used for permissions management but is compatible with both usages.


Base class for robust error models The robust M-estimators above simply tell us how to re-weight the residual, and are isotropic kernels, in that they do not allow for correlated noise.
They also have no way to scale the residual values, e.g., dividing by a single standard deviation. Hence, the actual robust noise model below does this scaling/whitening in sequence, by passing both a standard noise model and a robust estimator.
Taking as an example noise = Isotropic::Create(d, sigma), we first divide the residuals uw = |Ax-b| by sigma by "whitening" the system (A,b), obtaining r = |Ax-b|/sigma, and then we pass the now whitened residual 'r' through the robust M-estimator. This is currently done by multiplying with sqrt(w), because the residuals will be squared again in error, yielding 0.5 \sum w(r)*r^2.
In other words, while sigma is expressed in the native residual units, a parameter like k in the Huber norm is expressed in whitened units, i.e., "nr of sigmas".
|
|
| Robust () |
| | Default Constructor for serialization.
|
| |
|
| Robust (const RobustModel::shared_ptr robust, const NoiseModel::shared_ptr noise) |
| | Constructor.
|
| |
|
virtual | ~Robust () |
| | Destructor.
|
| |
|
virtual void | print (const std::string &name) const |
| |
|
virtual bool | equals (const Base &expected, double tol=1e-9) const |
| |
|
const RobustModel::shared_ptr & | robust () const |
| | Return the contained robust error function.
|
| |
|
const NoiseModel::shared_ptr & | noise () const |
| | Return the contained noise model.
|
| |
|
virtual Vector | whiten (const Vector &v) const |
| | Whiten an error vector.
|
| |
|
virtual Matrix | Whiten (const Matrix &A) const |
| | Whiten a matrix.
|
| |
|
virtual Vector | unwhiten (const Vector &) const |
| | Unwhiten an error vector.
|
| |
|
virtual double | distance (const Vector &v) const |
| |
|
virtual double | distance_non_whitened (const Vector &v) const |
| |
|
virtual void | WhitenSystem (Vector &b) const |
| |
|
virtual void | WhitenSystem (std::vector< Matrix > &A, Vector &b) const |
| |
|
virtual void | WhitenSystem (Matrix &A, Vector &b) const |
| |
|
virtual void | WhitenSystem (Matrix &A1, Matrix &A2, Vector &b) const |
| |
|
virtual void | WhitenSystem (Matrix &A1, Matrix &A2, Matrix &A3, Vector &b) const |
| |
| | Base (size_t dim=1) |
| | primary constructor More...
|
| |
|
virtual bool | isConstrained () const |
| | true if a constrained noise model, saves slow/clumsy dynamic casting
|
| |
|
virtual bool | isUnit () const |
| | true if a unit noise model, saves slow/clumsy dynamic casting
|
| |
|
size_t | dim () const |
| | Dimensionality.
|
| |
|
virtual Vector | sigmas () const |
| | Calculate standard deviations.
|
| |
|
virtual void | whitenInPlace (Vector &v) const |
| | in-place whiten, override if can be done more efficiently
|
| |
|
virtual void | unwhitenInPlace (Vector &v) const |
| | in-place unwhiten, override if can be done more efficiently
|
| |
|
virtual void | whitenInPlace (Eigen::Block< Vector > &v) const |
| | in-place whiten, override if can be done more efficiently
|
| |
|
virtual void | unwhitenInPlace (Eigen::Block< Vector > &v) const |
| | in-place unwhiten, override if can be done more efficiently
|
| |


Information
About Me
I'm a
Hi, My name is Jody Brian Herman. I am a self taught Django Developer and Cryptocurrency enthusiast.
I find technology to be the equivalent of magic and dream daily of the possible achievements we can accomplish with code. I am an avid traveller and almost always choose the road less travelled. I obsess over finding
working solutions to challenges and I work diligently to accomplish implementing an agile approach to my development cycle.
Ability
My skills
The learning curve for new develpors are quite steep and attaining the relevant knowledge, to go from novice to production ready deployment is hard. In the last 10 month I have aquired relevant knowledge to take the steps to become work ready. I have gotten to deployment stage , I am confident in my skill sets.
I have an extensive amount of Opreations and management experience which accompanies me into the workplace, having run my own business makes me understand how important every moment in the planning to execution phase is. In business time is money and I do not enjoy wasting any of it.

Development
The development of any project must be Agile but must take the security of the site into consideration.
Database Administration
Secure databases is the life blood of any organization. If your database is compromised your business will suffer.
Marketing
Web browsers need organic content, optermize your site so it may rank among the best.
Fully Responsive
Find out from your developer if your site is fully responsive. This means that no matter the screen size, the site is optermized to look great.
Business Anlaytics
Data has become one of the single most important factors in business, make sure your business has a someone that can find insights and correlation in your data.
My Reference
References
James Matthews
Software Engineer
Vox Telecom
<EMAIL_ADDRESS>+27 83 957 2704
Tian Bouwer
Regional Manager
Cape Union Mart
<EMAIL_ADDRESS>+27 76 318 0280
Nazreen Herman
National Manager
Engage Education
<EMAIL_ADDRESS>+27 76 318 0280


ROB ROY A film review by Stephen Rafferty Copyright 1995 Stephen Rafferty
*- Bad, a dog. **- Poor, not much worth seeing ***- Good, had it's good moments ****- Great, well worth seeing *****- First rate, probably one of the years best.
ROB ROY ****
Directed by Michael Caton-Jones Starring Liam Neeson, Jessica Lange, Tim Roth, John Hurt, Brian Cox
Based on the famous Scottish legend, Director Caton-Jones (Scandal) gives this story top notch treatment. Neeson stars as Rob Roy McGregor, a highlander who is the leader of his clan, which with himself work for the Marquis of Montrose (Hurt) and also owns his own piece of land. Making the decision to borrow money from the Marquis and try to sell cattle he herds with the men of his clan, Roy steps on the toes of a visitor of the Marquis played by Tim Roth, and the Factor, Brian Cox.
The story then unfolds as Roy must prove to the Marquis he did not steal his money and also confront Roth, who is the most devilish villain in quite some time.
Being Scottish, I was a little apprehensive about this film, but Jones really has done a superb job. There is great detail given to the way of life and to every facet of Scottish civilization in this period. Neeson is the quintessential hero, and is overpowering in the fight scenes. Lange (BLUE SKY) once again proves why she is one of the hottest actresses around, giving a memorable performance and pulling off quite a good accent. The supporting cast is first rate as well. Hurt (ALIEN) is perfect as the pompous, yet fleeting Marquis, and Cox (HIDDEN AGENDA) is extremely well cast as the Marquis right hand man. However, as has been said by almost all reviews so far, the film belongs to Roth (PULP FICTION, RESERVOIR DOGS) who steals every scene he is in. With just the right amount of effeminate gesturing, his ruthlessness is all the more disturbing. Truly one of the best villains in the past few years.
Karl Walter Lindenlaub's cinematography is exquisite, showing the simple beauty of Scotland.
Stephen Rafferty Florida State University
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


{% seo %}
Joining us in September? Read our 2021 Welcome Newsletter and meet everyone else over on the Discord


|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object org.apache.xml.serializer.utils.DOM2Helper
public final class DOM2Helper
This class provides a DOM level 2 "helper", which provides services currently not provided be the DOM standard. This class is a copy of the one in org.apache.xml.utils. It exists to cut the serializers dependancy on that package. The differences from the original class are: it doesn't extend DOMHelper, not depricated, dropped method isNodeAfter(Node node1, Node node2) dropped method parse(InputSource) dropped method supportSAX() dropped method setDocument(doc) dropped method checkNode(Node) dropped method getDocument() dropped method getElementByID(String id, Document doc) dropped method getParentOfNode(Node node) dropped field Document m_doc; made class non-public This class is not a public API, it is only public because it is used in org.apache.xml.serializer.
| Constructor Summary | |
|---|---|
DOM2Helper()
Construct an instance. |
| Method Summary | |
|---|---|
java.lang.String |
getLocalNameOfNode(org.w3c.dom.Node n)
Returns the local name of the given node, as defined by the XML Namespaces specification. |
private java.lang.String |
getLocalNameOfNodeFallback(org.w3c.dom.Node n)
Returns the local name of the given node. |
java.lang.String |
getNamespaceOfNode(org.w3c.dom.Node n)
Returns the Namespace Name (Namespace URI) for the given node. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public DOM2Helper()
| Method Detail |
|---|
public java.lang.String getLocalNameOfNode(org.w3c.dom.Node n)
n
- Node to be examined
private java.lang.String getLocalNameOfNodeFallback(org.w3c.dom.Node n)
n
- the node to be examined.
public java.lang.String getNamespaceOfNode(org.w3c.dom.Node n)
TODO: Reconcile with getLocalNameOfNode.
n
- Node to be examined
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


JSON-API for Corona Virus / Covid-19 statistics
This API allows you to display statistical data of COVID-19 Cases provided by the John Hopkins University in Grafana.
Usage
- Install the JSON Datasource for Grafana
- Add datasource in Grafana and pass the following API endpoint url to the URL field as described in the setup instructions: https://covid19-grafana.herokuapp.com/
- Add a panel to your dashboard, select the JSON Datasource and choose a metric from the list.
- The timeseries is starting from January, 22 2020 on and contains confirmed cases, deaths and recovered cases for every country and every day. Data is updated three times a day.
- If you can't see any results, make sure that you have set the time range accordingly. This is no real-time data, data is normally at least one day behind.
Credits
Stay healthy.


PHILADELPHIA A film review by Scott Renshaw Copyright 1994 Scott Renshaw
Starring: Tom Hanks, Denzel Washington, Jason Robards, Mary Steenburgen, Antonio Banderas. Screenplay: Ron Nyswaner. Director: Jonathan Demme.
Maybe I've just been lucky, but after living in Northern California for almost ten years I no longer think of "tolerance" as merely a buzzword; it's part of the fabric of life. Consequently, I couldn't help but feel slightly patronized by the sense of outrage which provides the backbone of Jonathan Demme's PHILADELPHIA. The message was important, but to me, it wasn't news. When that message is stripped away to permit examination of the filmmaking, I find as many examples of what I consider bad decisions as I find good decisions, and too many characters who come off as walking allegories.
PHILADELPHIA is the story of Andrew Beckett (Tom Hanks), a successful attorney in a large Philadelphia law firm.  Soon, however, the appearance of Karposi's sarcoma lesions on Andrew's face make it clear that he has developed AIDS. When crucial documents in the important case appear to have been misplaced, Andrew is fired, ostensibly for incompetence. Andrew believes differently, and takes his case to Joe Miller (Denzel Washington), an ambulance-chasing personal injury lawyer with a profound streak of homophobia. Joe decides to set aside his personal feelings to represent Andrew and attempt to prove that he was fired simply for being gay and a person with AIDS.
PHILADELPHIA opens strongly with an effective montage of city scenes, underscored by the wonderful new Bruce Springsteen song "The Streets of Philadelphia." We see Andrew as a typical workaholic attorney, already living with HIV as part of his life. It is to screenwriter Ron Nyswaner's credit that it doesn't offer the stock scene of a doctor delivering the somber news; HIV from the outset is simply one element in Andrew's life, but not the defining element. Joe Miller is equally well-established, both at work and at home, as an Everyman who recognizes somewhere the social similarities between being a black man and being a person with AIDS. PHILADELPHIA sets the stage effectively, making the way this case will affect the two men the focal point of the story.
The problems begin once PHILADELPHIA hits the courtroom. As a courtroom drama, PHILADELPHIA is fairly pedestrian stuff, lacking real dramatic punch and giving in to preachy speeches. Demme makes the extremely questionable decision of framing much of one lengthy trial sequence from Andrew's perspective as he grows weaker. There are distracting camera angles and sound echoes which make it difficult to concentrate on what anyone involved is actually saying. Andrew's condition became the total focus at a time when it simply wasn't appropriate in the narrative. Outside the courtroom things aren't much better. The relationship between Andrew and his partner Miguel (Antonio Banderas) is practically an afterthought, and it struck me that their one shared kiss is hidden from the camera by Hanks' head, and that neither one ever says "I love you." PHILADELPHIA's most talked-about scene involves Andrew responding to an aria, a scene which seems calculated to be one of those tour-de- force moments that wins Oscars. I found it way over the top.
Hanks' performance has been touted as an Oscar front-runner, and while he makes some bold choices, I don't feel it's the best work he's done, or even the best work he's done this year.  The same is true of Jason Robards as the senior partner in Andrew's firm; he's too cut-and-dried, right down to citing the Bible on the witness stand. By far the best work, and the most dynamic character, is Denzel Washington's Joe Miller. Once again Washington fills the screen with energy, and isn't afraid to show Miller's warts, making him a very real typical American.
As with THE WEDDING BANQUET, I went into PHILADELPHIA wanting to like it and glad that it had been made. But once again I felt the message deserved a better messenger, one that treats homosexuality as matter-of-factly as the recent TALES OF THE CITY miniseries on PBS. PHILADELPHIA is a good idea, just not a particularly good film.
On the Renshaw scale of 0 to 10 red ribbons: 5.
-- Scott Renshaw Stanford University Office of the General Counsel
.
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


{% include 'header.html' %}
{% if refresh %}
Page Refresh: {{ refresh }} seconds
{% endif %}
Version: {{ version }}
View Wallets
Settings
RPC Console
Explorers
Swaps in progress: {{ summary.num_swapping }}
Network Offers: {{ summary.num_network_offers }}
Sent Offers: {{ summary.num_sent_offers }}
Received Bids: {{ summary.num_recv_bids }}
Sent Bids: {{ summary.num_sent_bids }}
Watched Outputs: {{ summary.num_watched_outputs }}


The Village Pub and Cafe is a seasonal business, and so many workers do not return after working with us. We therefore are always looking for employees each new season, and take applications beginning late in the Spring and early in the summer. Send us your resume/application or stop in and fill one out if you would like one of the open positions. Experience is preferred but not required, as is TIPS certification or its equivalent.


Mark¶
Marks are the basic visual building block of a visualization. They provide basic shapes whose properties (such as position, size, and color) can be used to visually encode data, either from a data field, or a constant value.
The supported mark
types are
"area",
"bar",
"circle",
"line",
"point",
"rect"
,
"rule",
"square",
"text",
"tick",
and "geoshape".
In general, one mark instance is generated per input data element. However, line and area marks represent multiple data elements as a contiguous line or shape.
// Single View Specification
{
"data": ... ,
"mark": ... , // mark
"encoding": ... ,
...
}
The mark
property of a single view specification can either be (1) a string describing a mark type or (2) a mark definition object.
For example, a bar chart has mark
as a simple string "bar"
.
Documentation Overview¶
- TOC
Mark Definition Object¶
// Single View Specification
{
...
"mark": {
"type": ..., // mark
...
},
...
}
To customize properties of a mark, users can set mark
to be a mark definition object instead of a string describing mark type. The rest of this section lists all standard mark properties. In addition, some marks may have special mark properties (listed in their documentation page).
Note: If mark property encoding channels are specified, these mark properties will be overridden.
General Mark Properties¶
liqid template: like ".. altair-object-table::"
{% include table.html props="type,style,clip" source="MarkDef" %}
Offset Properties¶
liqid template: like ".. altair-object-table::"
{% include table.html props="xOffset,x2Offset,yOffset,y2Offset" source="MarkDef" %}
Color Properties¶
liqid template: like ".. altair-object-table::"
{% include table.html props="filled,color,fill,stroke,opacity,fillOpacity,strokeOpacity" source="MarkDef" %}
Stroke Style Properties¶
liqid template: like ".. altair-object-table::"
{% include table.html props="strokeCap,strokeDash,strokeDashOffset,strokeJoin,strokeMiterLimit,strokeWidth" source="MarkDef" %}
Hyperlink Properties¶
Marks can act as hyperlinks when the href
property or channel is defined. When the href
property is specified, the cursor
mark property is set to "pointer"
by default to serve as affordance for hyperlinks.
liqid template: like ".. altair-object-table::"
{% include table.html props="href,cursor" source="MarkDef" %}
Mark Config¶
// Top-level View Specification
{
...
"config": {
"mark": ...,
"area": ...,
"bar": ...,
"circle": ...,
"line": ...,
"point": ...,
"rect": ...,
"rule": ...,
"geoshape": ...,
"square": ...,
"text": ...,
"tick": ...
}
}
The mark
property of the config
object sets the default properties for all marks. In addition, the config
object also provides mark-specific config using its mark type as the property name (e.g., config.area
) for defining default properties for each mark.
The global mark config (config.mark
) supports all standard mark properties (except type
, style
, clip
, and orient
). For mark-specific config, please see the documentation for each mark type.
Note:
- If mark properties in mark definition or mark property encoding channels are specified, these config values will be overridden.
- Mark config do not support offset mark properties.
Mark Style Config¶
{
// Top Level Specification
"config": {
"style": {
...
}
...
}
}
In addition to the default mark properties above, default values can be further customized using named styles defined under the style
property in the config object.
liqid template: like ".. altair-object-table::"
{% include table.html props="style" source="Config" %}
For example, to set a default shape and stroke width for point
marks with a style named "triangle"
:
{
"style": {
"triangle": {
"shape": "triangle-up",
"strokeWidth": 2
}
}
}
Styles can then be invoked by including a style
property within a mark definition object.
In addition to custom style
names, Vega-Lite includes the following built-in style names:
"guide-label"
: style for axis, legend, and header labels"guide-title"
: style for axis, legend, and header titles
Example: Styling Labels¶
You can use text marks as labels for other marks by setting style
for the marks and using style config to configure offset (dx
or dy
), align
, and baseline
.
See also: a similar example that uses mark definition to configure offset, align, and baseline.


White to play 21
pips White=163 Black=159
(CorrectAnswer= 0/0, ErrorScore= 0)
1. 8/7* 7/5 eq: +0.226 54.25% (G:18.16% B:0.81%) 45.75% (G:11.52% B:0.56%) 2. 13/11 8/7* eq: +0.219 (-0.007) 54.57% (G:17.61% B:0.81%) 45.43% (G:12.20% B:0.74%) 3. 24/22 8/7* eq: +0.187 (-0.038) 53.70% (G:17.26% B:0.80%) 46.30% (G:11.94% B:0.57%) 4. 8/6 8/7* eq: +0.087 (-0.139) 51.63% (G:16.42% B:0.71%) 48.37% (G:12.31% B:0.66%) 5. 24/21 eq: +0.046 (-0.180) 50.73% (G:13.17% B:0.52%) 49.27% (G:10.60% B:0.38%)


The number of seats which would be won by each party based on current polling
If no party secures a majority, an alliance of more than 322 MPs could probably survive a confidence vote


There are some NIBRS rules that the NIBRS PCT cannot enforce because the validation relies on access to previously submitted incidents or specific FBI information on the submitting agency. There are other differences between the NIBRS PCT Report and FBI Error Data Set (EDS) due to different interpretations of the rules. These are being addressed with the FBI and the NIBRS PCT will be updated to be consistent with the FBI Report.
GROUP A INCIDENT REPORT
-
Structure Check Errors
- 056: DUPLICATE INCIDENT- PREVIOUSLY ADDED
- 060: PROCESSING DATE PRECEDES MONTH AND YEAR OF SUBMISSION
- 088: GROUP A AND GROUP B CANNOT HAVE SAME IDENTIFIER
- 931: Invalid ORI – ORI marked for historical reference
- 932: Invalid ORI – ORI information is duplicated
- 933: Invalid ORI – ORI not found in reference data
- 934: Invalid ORI – ORI is covered by another agency
- 935: NIBRS CERTIFICATION DATE DOES NOT EXIST
- 937: PRE-NIBRS INCIDENT RECEIVED
- 938: MULTIPLE INCIDENTS ON FILE
- 940: EXCEPTIONAL CLEARANCE ALREADY ON FILE
- 941: WEB SERVICE SUBMISSION ALREADY IN PROCESS
- 952: Invalid ORI – ORI is not in UCR file
-
Administrative Segment Errors – Level 1
- 116: MUST BE LEFT JUSTIFIED BLANK DETECTED IN FIRST POSITION
- 118: Date cannot be on or after the inactive date of the ORI
- 151: REPORT INDICATOR MUST BE BLANK OR R
- 173: Incident date cannot be before date ORI went IBR
- 175: CANNOT CALCULATE BASE DATE FROM INCIDENT DATE
- 197: MISSING INCIDENT DATE FOR DELETE
- 198: MISSING INCIDENT DATE FOR DELETE - INCIDENT NUMBER MATCHES GROUP A INCIDENT REPORTS WITH INCIDENT DATE OUTSIDE TWO YEAR WINDOW
- 199: MISSING INCIDENT DATE FOR DELETE - INCIDENT NUMBER MATCHES MULTIPLE GROUP A INCIDENT REPORTS
-
Offense Segment Errors – Level 2
- 202: CONTAINS NONNUMERIC ENTRY
- 215: CANNOT CONTAIN EMBEDDED BLANKS BETWEEN FIRST AND LAST NON BLANK CHARACTERS
- 216: MUST BE LEFT-JUSTIFIED– BLANK DETECTED IN FIRST POSITION
- 217: CANNOT HAVE CHARACTERS OTHER THAN A–Z, 0–9, AND/OR HYPHEN, AND/OR BLANKS
-
Property Segment Errors – Level 3
- 302: CONTAINS NONNUMERIC ENTRY
- 315: CANNOT HAVE EMBEDDED BLANKS BETWEEN FIRST AND LAST NON-BLANK CHARACTERS
- 316: MUST BE LEFT-JUSTIFIED. BLANK DETECTED IN FIRST POSITION
- 317: CANNOT HAVE CHARACTERS OTHER THAN A–Z, 0–9, AND/OR HYPHEN, AND/OR BLANKS
-
Victim Segment Errors – Level 4
- 408: EXACT AGE MUST BE IN FIRST TWO POSITIONS
- 415: CANNOT CONTAIN EMBEDDED BLANKS BETWEEN FIRST AND LAST NON BLANK CHARACTERS
- 416: MUST BE LEFT- JUSTIFIED–BLANK DETECTED IN FIRST POSITION
- 417: CANNOT HAVE CHARACTERS OTHER THAN A–Z, 0–9, AND/OR HYPHEN, AND/OR BLANKS
- 490: INCIDENT DATE/HOUR MUST CONTAIN A VALID ENTRY WITHEN VICTIM IS L=LAW ENFORCEMENT OFFICER
-
Offender Segment Errors – Level 5
- 502: CONTAINS NONNUMERIC ENTRY
- 508: EXACT AGE MUST BE IN FIRST TWO POSITIONS
- 515: CANNOT HAVE EMBEDDED BLANKS BETWEEN FIRST AND LAST NON-BLANK CHARACTERS
- 516: MUST BE LEFT-JUSTIFIED– BLANK DETECTED IN FIRST POSITION
- 517: CANNOT HAVE CHARACTERS OTHER THAN A–Z, 0–9, AND/OR HYPHEN, AND/OR BLANKS
-
Arrest Segment Errors – Level 6
- 602: CONTAINS NONNUMERIC ENTRY
- 608: EXACT AGE MUST BE IN FIRST TWO POSITIONS
- 616: MUST BE LEFT-JUSTIFIED— BLANK DETECTED IN FIRST POSITION
- 618: Arrest date cannot on or after the inactive date of the ORI
- 664: ARRESTEE AGE MUST BE NUMERIC DIGITS
GROUP B ARREST REPORTS
- 708: EXACT AGE MUST BE IN FIRST TWO POSITIONS
- 716: MUST BE LEFT-JUSTIFIED– BLANK DETECTED IN FIRST POSITION
- 718: Arrest date cannot be on or after the inactive date of the ORI
- 720: GROUP B ADD CANNOT PREDATE NIBRS START DATE
- 751: ARRESTEE SEQUENCE NUMBER ALREADY EXISTS
- 757: ARRESTEE AGE MUST BE NUMERIC DIGITS
- 759: Duplicate Group B arrest report segment on file
- 798: Missing arrest date for delete, duplicate match
- 799: Missing arrest date for delete, multiple matches
ZERO REPORTS
- 028: Cannot add zero report – Group A incident report on file for this month
- 029: Cannot add zero report – Group B Arrest report on file for this month
- 090: ZERO REPORTING MONTH IS NOT 01-12
- 091: ZERO-REPORTING YEAR IS INVALID
- 092: ZERO REPORTING INCIDENT NUMBER MUST BE ALL ZEROS
- 093: Zero report month/year is prior to agency conversion to NIBRS
- 094: ZERO REPORT MONTH/YEAR EXCEEDED MONTH/YEAR OF SUBMISSION
- 095: PRE-NIBRS SEGMENTS CANNOT BE DELETED IN THIS WAY
- 096: ZERO REPORT MONTH & ZERO REPORT YEAR CANNOT BE ON OR AFTER DATE AGENCY IS PLACED ON COVERED-BY STATUS


Example
Pages
Index
Form
Dialog
Address book
Order
Index
Form
Dialog
Address book
Order
Form
Sign up
Name
Email
Password
[a-zA-Z0-9_-]
Sex
Male
Female
Job
Manager
Programmer
Designer
Accept
Note
Cancel
Sign up
Dialog
Open dialog
×
Dialog
body


Butter Bean, Tuna, and Celery Salad - DivineCaroline
This recipe comes from April '08 Food and Wine Magazine. This is a simple and quick salad to put together that is also very nutritional. The buttery beans are .
http://www.divinecaroline.com/38/64726-butter-bean-tuna-celery-salad
Treatment for Herniated or Bulging Discs
Pulse Salads - Tuna fish and butter bean salad
Tuna fish and butter bean salad. This salad is very popular in some regions of Italy. If you prefer, you can substitute the tuna for fresh salmon.
http://www.helpwithcooking.com/salads/salad-details.php?recipe_tag=46
Butter Bean Salad Recipes
Just open some cans and mix Butter Bean Salad, which can be made even if your . You can add canned tuna, chicken, or seafood to this salad for more protein.
http://busycooks.about.com/od/maindishvegetariansalads/r/butterbeansalad.htm
tuna and butter bean salad Herniated or Bulging Discs
Tuna & butterbean salad recipe - Recipes - BBC Good Food
A cheap and healthy way to get more fibre and vitamin C into your diet.
http://www.bbcgoodfood.com/recipes/1527/tuna-and-butterbean-salad
5 Ingredients. 5 Minutes. 5 Meals. Out Of The Can | Zen Family ...
Nov 16, 2009 . Remove from heat and stir through remaining ingredients. Season and serve warm. butter bean & tuna salad. tuna & butter bean salad serves 6 .
http://www.zenfamilyhabits.net/2009/11/5-ingredients-5-minutes-5-meals-out-of-the-can/
Tuna and White Bean Salad Recipe | MyRecipes.com
MyRecipes recommends that you make this Tuna and White Bean Salad recipe . 1 (15-ounce) can organic white beans, rinsed and drained; 4 cups torn butter .
http://www.myrecipes.com/recipe/tuna-white-bean-salad-50400000111143/
Official Impairment Listing for Spinal Disorders
The Munchies: Tuna and Butterbean Salad | HARLEM LOVES
Feb 5, 2012 . It's as simple as mixing in a tin of butterbeans with a tin of tuna, then flavouring with chopped parsley, red onion, cherry tomatoes and a few .
http://www.harlemloves.com/2012/02/the-munchies-tuna-and-butterbean-salad/
- symptoms of uric toxicity (narrowing of the spine)
Salad of Fresh Butter Beans and Tuna Conserva | Agricultural ...
Salad of Fresh Butter Beans and Tuna Conserva. The nutritional value of raw foods is generally greater than that of cooked foods. So, for her Chef .
http://www.agriculturalinstitute.org/salad-of-fresh-butter-beans-and-tuna-conserva/packed lunch
Jan 27, 2010 . tuna butter bean salad. butter bean & tuna salad serves 2. before I was introuced to butter beans, I used to make this with cannellini or borlotti .
http://thestonesoup.com/blog/2010/01/how-to-cultivate-the-packed-lunch-habit-save/
Tuna and Butter Bean Salad | TasteSpotting
Tuna and Butter Bean Salad. www.zenfamilyhabits.net. tuna & butter bean salad - 5ingrdients 5minutes. 66171 submitted by jules_stonesoup · save as favorite .
http://www.tastespotting.com/detail/66171/Tuna-and-Butter-Bean-Salad
Tuna Butter Bean Salad Recipes | Yummly
Find Quick & Easy Tuna Butter Bean Salad Recipes! Choose from over 13 Tuna Butter Bean Salad recipes from sites like Epicurious and Allrecipes.
http://www.yummly.com/recipes/tuna-butter-bean-salad
Medical-Vocational Allowance for Herniated Disc
Butter Bean, Tuna and Celery Salad - Food & Wine Magazine
Big, creamy butter beans give a tuna and celery salad terrific heartiness. The salad would also be delicious spooned over slices of warm grilled country bread.
http://www.foodandwine.com/recipes/butter-bean-tuna-and-celery-salad
Butter Bean, Tuna, and Celery Salad Recipe - Delish.com
Big, creamy butter beans give a tuna and celery salad terrific heartiness. The salad would also be delicious spooned over slices of warm grilled country bread.
http://www.delish.com/recipefinder/butter-bean-tuna-celery-salad-recipe
Appealing a Denial of Benefits
Apples and Butter: Butter Bean Salad
Apr 28, 2010 . This butter bean salad is very simple to make and holds up well (actually improving in flavor) after a few days in the refrigerator. Beans, tuna, a .
http://www.applesandbutter.com/2010/04/butter-bean-salad.html
Tuna Casserole with butter beans Recipe
View full nutritional breakdown of Tuna Casserole with butter beans calories by ingredient . 1 can butter beans 1 can white tuna . Tuna Salad - Eggless .
http://recipes.sparkpeople.com/recipe-detail.asp?recipe=542660


13.8 Million People Have Watched the Trump Impeachment Hearings
13.8 million people have watched the first day of public hearings on the impeachment investigation of US President Donald Trump, the Associated Press reported.
The Nielsen company said 10 different networks aired live or taped coverage of the hearing, which stretched nearly six hours on Wednesday. The Fox News channel was the most-watched television network, although presenters are constantly ironing out the investigation.
Nielsen reports that 2.9 million people watched the Fox News hearings, 2.69 million on the BBC (MSNBC), 2.01 million on the ABC (ABC), 1.97 million on the BBC ( CBS), 1.84 million CNN (CNN) and 1.68 million CNB (NBC).
By comparison, Brett Kavanaugh's hearing for his Supreme Court nomination following sexual misconduct allegations in September 2018 drew 20.4 million viewers in September 2018.
Congressional testimony by FBI Director James Comey (19.5 million) and former Trump lawyer Michael Cohen (13.8 million) also attracted more viewers than the first day of the Donald Trump impeachment hearing, the AP noted.


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call p%apply(x,y,desc_a,info [,trans,work])
This method computes
, where is a previously built
preconditioner, stored into p
, and
denotes the preconditioner itself or its transpose, according to
the value of trans
.
Note that, when MLD2P4 is used with a Krylov solver from PSBLAS,
p%apply
is called within the PSBLAS method psb_krylov
and hence it is completely transparent to the user.
Arguments
x |
type( kind_parameter), dimension(:), intent(in) . |
| The local part of the vector . Note that type and kind_parameter must be chosen according to the real/complex, single/double precision version of MLD2P4 under use. | |
y |
type( kind_parameter), dimension(:), intent(out) . |
| The local part of the vector . Note that type and kind_parameter must be chosen according to the real/complex, single/double precision version of MLD2P4 under use. | |
desc_a |
type(psb_desc_type), intent(in) . |
| The communication descriptor associated to the matrix to be preconditioned. | |
info |
integer, intent(out) . |
| Error code. If no error, 0 is returned. See Section 8 for details. | |
trans |
character(len=1), optional, intent(in). |
If trans = 'N','n' then
;
if trans = 'T','t' then
(transpose of ; if trans = 'C','c' then
(conjugate transpose of . |
|
work |
type( kind_parameter), dimension(:), optional, target . |
Workspace. Its size should be at
least 4 * psb_cd_get_local_ cols(desc_a) (see the PSBLAS User's Guide).
Note that type and kind_parameter must be chosen according
to the real/complex, single/double precision version of MLD2P4 under use. |
For compatibility with the previous versions of MLD2P4, this method can be also invoked as follows:
call mld_precaply(p,what,val,info)


Build amazing forms with Angular + Semantic UI. This example shows forms with template aproximation .html, data aproximation .ts and a not validated form.


Preparation time
less than 30 mins
Cooking time
over 2 hours
Serves
Serves 8-10
Dietary
This easy yet decadent make-ahead dessert is a great alternative to traditional Christmas pudding or Bûche de Noël.
For the meringue, preheat the oven to 100C/80C Fan/Gas ½. Line a large baking sheet with silicone or baking paper.
Suspend a heatproof bowl over a pan of barely simmering water, making sure the base of the bowl does not touch the surface of the water. Add the egg whites and sugar to the bowl and start whisking them immediately using an electric whisk, until the sugar has dissolved and the mixture has reached about 60C/140F.
Transfer the mixture to a freestanding food mixer. Continue to whisk until smooth and glossy but still slightly warm, about 2-3 minutes.
Spoon the meringue mixture onto the prepared baking tray, making a large disc with raised edges. Bake in the oven for 2½ hours, or until firm, then remove from the oven and set aside to cool.
In a bowl, whisk the double cream with the chestnut purée and vanilla seeds until soft peaks form when the whisk is removed. Chill, covered, until needed.
When ready to serve, spoon the cream over the cooled meringue, then decorate the top with the marrons glacés. Grate over the plain chocolate and garnish with the fresh chestnut.


  Biltong pastrami jerky, capicola brisket sausage ribeye drumstick shoulder leberkas beef sirloin. Strip steak fatback drumstick tri-tip corned beef bresaola.
 Jerky cow turkey short ribs beef. Hamburger rump meatloaf brisket. Rump andouille tail kielbasa.  Tri-tip pastrami pork loin, pig ham hock salami sausage flank ball tip frankfurter doner meatloaf filet mignon shoulder. Shank pork tongue pig.
Rinse your swimsuit in cold water after use and allow it to dry naturally, away from direct heat and sunlight.
After rinsing out the suit, you must wash your suit. Plain water does not remove all the salt or chlorine. Fill a sink with water and add just a tablespoon or less of liquid detergent. Don't use powders because they may not dissolve completely or rinse away well. And, never use bleach. Turn your swimsuit inside out. Swish for several minutes and then rinse well. Gently squeeze - don't wring - the water out of the fabric. Spread your suit flat to dry in a spot out of direct sunlight.
Standard swim suit sizing comes in S/M/L and come in Body measurements are given in inches. If your body measurement is on the borderline between two sizes, order the lower size for a tighter fit or the higher size for a looser fit.
If your body measurements for hip and waist result in two different suggested sizes, order the size from your hip measurement.
| Size | Bust (in) | Ribcage (in) | Waist (in) | Hip (in) | Torso (in) | |
|---|---|---|---|---|---|---|
| S | 4 | 33 1/2 | 27 | 25 1/2 | 35 1/2 | 58 1/2 |
| 6 | 34 1/2 | 28 | 26 1/2 | 36 1/2 | 60 | |
| M | 8 | 35 1/2 | 29 | 27 1/2 | 37 1/2 | 61 1/2 |
| 10 | 36 1/2 | 30 | 28 1/2 | 38 1/2 | 63 | |
| L | 12 | 38 | 31 1/2 | 30 | 40 | 64 1/2 |
| 14 | 39 1/2 | 33 | 31 1/2 | 41 1/2 | 66 |
5 star
5
4 star
3
3 star
2
2 star
0
1 star
0
4.6 out of 5 stars from 10 reviews
Perfect, just what I wanted!
  Biltong pastrami jerky, capicola brisket sausage ribeye drumstick shoulder leberkas beef sirloin. Strip steak fatback drumstick tri-tip corned beef bresaola.
Perfect, just what I wanted!
  Biltong pastrami jerky, capicola brisket sausage ribeye drumstick shoulder leberkas beef sirloin. Strip steak fatback drumstick tri-tip corned beef bresaola.
Perfect, just what I wanted!
  Biltong pastrami jerky, capicola brisket sausage ribeye drumstick shoulder leberkas beef sirloin. Strip steak fatback drumstick tri-tip corned beef bresaola.


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- Not that Kevin! -
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I was born in Chicago, but grew up in Folsom, California.
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Folsom is about 2 hours away from San Francisco, on the way up to Lake Tahoe.


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If you enter your weight as well, the calculator will tell you how much of your weight is fat and what your
lean weight is (weight without fat).
You can switch between metric and imperial system using the link above the page.
 Find out if you are in the healthy range with this fat calculator.  This body fat calculator is based on
the body fat algorithms developed by the U.S. Navy, U.S. Army, U.S. Marine Corp and the YMCA.
 This is because much ado is made about low body in body building circles. Professionals must
have a very low body fat percentage (5% or so) in order to compete. While this raises awareness towards
developing low body fat, it also creates a somewhat limited perception. Body fat percentage means different
things on different levels. Actually, 5% body fat can cause serious health problems for the average person.
Conversely, 25% fat can either be healthy or unhealthy depending upon your age and gender. In order to
provide clarity, it's best to look at a scale of body fat percentages and what they represent.
The calculated body fat percentage tells you how match of your body is fat.

This Calculator has a 3% accuracy.
If you feel like your body fat percentage is higher or lower than it should be and/or you are obese or
underweight, please seek medical advice.
 Essential body fat is necessary to maintain
life and reproductive functions. The percentage of essential body fat for women is greater than that for
men, due to the demands of childbearing and other hormonal functions. The percentage of essential fat is
3-5% in men, and 8-12% in women (referenced through NASM). Storage body fat consists of fat accumulation
in adipose tissue, part of which protects internal organs in the chest and abdomen.  A number of methods are
available for determining body fat percentage, such as measurement with calipers or through the use of
bioelectrical impedance analysis.
A body fat percentage of 10-13% for women and 2-5% for men is considered essential.
14-20% for women and 6-13% for men is considered athletic.
21-24% for women and 14-17% for men is considered fit.
25-31% for women and 18-24% for men is considered average.
Everything above 32% for women and 25% for men is considered obese.
Source: Wikipedia.
The body fat percentage is a measure of fitness level, since it is the only body measurement which directly
calculates a person's relative body composition without regard to height or weight. The widely used body
mass index (BMI) provides a measure that allows the comparison of the adiposity of individuals of different
heights and weights. While BMI largely increases as adiposity increases, due to differences in body
composition, other indicators of body fat give more accurate results; for example, individuals with greater
muscle mass or larger bones will have higher BMIs.


These figures show you how much free space is available in your topic on CIX. The information may be updated manually or automatically via the Update... button.
If a topic is becoming full, you can prune any withdrawn messages from it to free some space or create a new replacement topic and set the existing topic read only.


|
Standard Reference Data Program |
Data Gateway |
Chemistry WebBook |
Go To: Top, Constants of diatomic molecules, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled by: H.M. Rosenstock, K. Draxl, B.W. Steiner, and J.T. Herron
View reactions leading to FSc+ (ion structure unspecified)
| IE (eV) | Method | Reference |
|---|---|---|
| 6.5 ± 0.3 | EI | Zmbov and Margrave, 1968 |
| 6.3 | EI | Zmbov and Margrave, 1967 |
Go To: Top, Gas phase ion energetics data, References, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Data compiled by: K.P. Huber and G. Herzberg
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| H 1Π | [0.3671] 1 | [1.8543] | H ↔ X R | 38806.1 Z | ||||||||
| Barrow, Bastin, et al., 1967; Barrow, 1979 | ||||||||||||
| H 1Π 2 | V | 35942.0 HQ | ||||||||||
| Barrow, Bastin, et al., 1967; Barrow, 1979 | ||||||||||||
| G 1Π | 35009 | [570] H | [0.378] 1 3 | [1.827] | G ↔ X R | 34926.7 4 Z | ||||||
| Gurvich and Shenyavskaya, 1963; Barrow, Gissane, et al., 1964; Barrow, Bastin, et al., 1967 | ||||||||||||
| g 3Φ4 | [0.3463] | [1.9092] | g ← a | 27202.2 Z | ||||||||
| Barrow, Bastin, et al., 1967 | ||||||||||||
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
| g 3Φ3 | [0.3441] | [1.9153] | g ← a R | 27171.1 Z | ||||||||
| Barrow, Bastin, et al., 1967 | ||||||||||||
| g 3Φ2 | [0.3413] | [1.9231] | g ← a | 27138.2 Z | ||||||||
| Barrow, Bastin, et al., 1967 | ||||||||||||
| F 1Π | 26891.5 | [565.3] Z | (3.1) | 0.3461 5 | 0.0025 | 1.9098 | F ← X R | 26809.6 Z | ||||
| Barrow, Gissane, et al., 1964; Barrow, Bastin, et al., 1967 | ||||||||||||
| F 1Π 6 | F ← X R | 26300 | ||||||||||
| Barrow, Bastin, et al., 1967 | ||||||||||||
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
| F 1Π 7 | F ← X V | 21927 H | ||||||||||
| Barrow, Bastin, et al., 1967; Shenyavskaya, Mal'tsev, et al., 1967; Barrow, 1979 | ||||||||||||
| E 1Π | 20383.5 | 622.1 Z | 3.7 | 0.3630 1 3 | 0.00296 | 1.8648 | E ↔ X R | 20326.8 Z | ||||
| Barrow, Gissane, et al., 1964; McLeod and Weltner, 1966; Barrow, Bastin, et al., 1967; Shenyavskaya, Mal'tsev, et al., 1967 | ||||||||||||
| (3Π2) | [0.3677] 1 | [1.8528] | d ← a | 18361.4 Z | ||||||||
| d (3Π1) | d ← a R | 18336.0 | ||||||||||
| Barrow, Bastin, et al., 1967 | ||||||||||||
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
| C 1Σ+ | 16164.7 | 589.6 Z | 2.64 | 0.3473 | 0.0024 | 1.9065 | C ↔ X R | 16092.0 Z | ||||
| Barrow, Gissane, et al., 1964; McLeod and Weltner, 1966; Barrow, Bastin, et al., 1967 | ||||||||||||
| c 3Φ4 | a3 + 15356.9 8 | 0.3545 | 0.00310 | 1.8870 | c ↔ a | 15317.6 Z | ||||||
| Barrow and Gissane, 1964; Barrow, Bastin, et al., 1967; Shenyavskaya, Mal'tsev, et al., 1967 | ||||||||||||
| c 3Φ3 | a2 + 15316.8 8 | 570.4 Z | 2.96 | [0.3511] | [1.8961] | c ↔ a R | 15277.5 Z | |||||
| Barrow and Gissane, 1964; Barrow, Bastin, et al., 1967; Shenyavskaya, Mal'tsev, et al., 1967 | ||||||||||||
| c 3Φ2 | a1 + 15273.6 8 | [0.3490] | [1.9018] | c ↔ a | 15234.4 Z | |||||||
| Barrow and Gissane, 1964; Barrow, Bastin, et al., 1967; Shenyavskaya, Mal'tsev, et al., 1967 | ||||||||||||
| State | Te | ωe | ωexe | ωeye | Be | αe | γe | De | βe | re | Trans. | ν00 |
| B 1Π | 10735.49 | 586.25 Z | 2.015 | -0.0633 | 0.34310 9 | 0.00262 | 3.25E-5 | 1.9181 | B ↔ X R | 10661.25 Z | ||
| McLeod and Weltner, 1966; Barrow, Bastin, et al., 1967; Barrow and Pedersen, 1971 | ||||||||||||
| a 3Δ3 | a3 | 649.11 Z | 0.3706 | 0.00258 | 1.8456 | |||||||
| a 3Δ2 8 | a2 10 | 648.98 Z | 3.03 | 0.3665 | 0.00254 | 1.8559 | ||||||
| a 3Δ1 | a1 | 648.91 Z | 0.3623 | 0.00250 | 1.8666 | |||||||
| X 1Σ+ | 0 11 | 735.6 Z | 3.8 | 0.3950 | 0.00266 | 1.7877 |
| 1 | Perturbations. |
| 2 | 0-0 sequence of V shaded absorption bands. Complex structure. |
| 3 | B values are for the f levels. |
| 4 | From Barrow, Gissane, et al., 1964; 34920.7 in Barrow, Bastin, et al., 1967 appears to be a misprint. |
| 5 | Λ-type doubling Δ vfe = +0.0021J(J+1). |
| 6 | Complex group of R shaded absorption bands. |
| 7 | Strong 0-0 sequence of V shaded bands. 13 |
| 8 | For a reassignment of molecular orbital configurations see Scott and Richards, 1974. |
| 9 | Λ-type doubling Δ vfe(v=0) = +1.115E-3J(J+1) - ...; Δ vfe(v=1) = 0.714E-3J(J+1) - ...; Δ vfe(v=2) = 0.452E-3J(J+1) - ...; Δ vfe(v=3) = 0.315E-3J(J+1) - ... |
| 10 | Theoretical calculations by Carlson and Moser, 1967 put the a 3Δ state at 461 cm-1 and the corresponding 1Δ state at 2612 cm-1 above X 1Σ+. |
| 11 | That X 1Σ+ is the ground state is strongly suggested by the fact that only B ← X, C ← X, and E ← X, but none of the triplet systems, were observed in matrix absorption at 4K McLeod and Weltner, 1966. |
| 12 | Thermochemical value (mass-spectrometry) Zmbov and Margrave, 1967. |
| 13 | The authors of Barrow, Bastin, et al., 1967 assume the bands to arise from a transition 3Δ ← a 3Δ with nearly equal coupling constants in both states. The upper state, then, has ωe = 724.7 Barrow, Bastin, et al., 1967, ωexe = 3.64 Barrow, Bastin, et al., 1967. The system was also observed in emission by Shenyavskaya, Mal'tsev, et al., 1967 who interpreted it as 3Π → 3Σ with ωe' = 591.0 Shenyavskaya, Mal'tsev, et al., 1967, ωe'xe' = 2.73 Shenyavskaya, Mal'tsev, et al., 1967, ωe" = 514.1 Shenyavskaya, Mal'tsev, et al., 1967, ωe"xe" = 1.98. Neither Barrow, Bastin, et al., 1967 nor Shenyavskaya, Mal'tsev, et al., 1967 give enough details. |
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, Notes / Error Report
Data compilation copyright by the U.S. Secretary of Commerce on behalf of the U.S.A. All rights reserved.
Zmbov and Margrave, 1968
Zmbov, K.F.; Margrave, J.L.,
Mass spectrometric studies of scandium, yttrium, lanthanum, and rare-earth fluorides,
Advan. Chem. Ser., 1968, 72, 267. [all data]
Zmbov and Margrave, 1967
Zmbov, K.F.; Margrave, J.L.,
Mass spectrometry at high temperatures. XVIII.The stabilities of the mono- and difluorides of scandium and yttrium,
J. Chem. Phys., 1967, 47, 3122. [all data]
Barrow, Bastin, et al., 1967
Barrow, R.F.; Bastin, M.W.; Moore, D.L.G.; Pott, C.J.,
Electronic states of gaseous fluorides of scandium, yttrium and lanthanum,
Nature (London), 1967, 215, 1072. [all data]
Barrow, 1979
Barrow,
In Rosen, 1970 cited in Huber and Herzberg, 1979, 1979, 579. [all data]
Gurvich and Shenyavskaya, 1963
Gurvich, L.V.; Shenyavskaya, E.A.,
The electronic spectrum of scandium monofluoride,
Opt. Spectrosc. Engl. Transl., 1963, 14, 161, In original 307. [all data]
Barrow, Gissane, et al., 1964
Barrow, R.F.; Gissane, W.J.M.; Le Bargy, R.C.; Rose, G.V.M.; Ross, P.A.,
Rotational analysis of some singlet transitions in the spectrum of gaseous scandium monofluoride,
Proc. Phys. Soc. London, 1964, 83, 889. [all data]
Shenyavskaya, Mal'tsev, et al., 1967
Shenyavskaya, E.A.; Mal'tsev, A.A.; Gurvich, L.V.,
The electronic-vibrational-rotational spectrum of the ScCl molecule and some additional data on the molecular constants of ScF, YF, and LaF,
Moscow Univ. Chem. Bull. Engl. Transl., 1967, 22, 66, In original 104. [all data]
McLeod and Weltner, 1966
McLeod, D., Jr.; Weltner, W., Jr.,
Spectroscopy and Franck-Condon factors of scandium fluoride in neon matrices at 4°K,
J. Phys. Chem., 1966, 70, 3293. [all data]
Barrow and Gissane, 1964
Barrow, R.F.; Gissane, W.J.M.,
The ground states of scandium and yttrium monofluorides,
Proc. Phys. Soc. London, 1964, 84, 615. [all data]
Barrow and Pedersen, 1971
Barrow, R.F.; Pedersen, L.,
Rotational analysis of the system B1Π-1Σ+ of gaseous ScF,
J. Phys. B:, 1971, 4, 11. [all data]
Scott and Richards, 1974
Scott, P.R.; Richards, W.G.,
A reassignment of melecular orbital configurations of the electronic states of ScF,
Chem. Phys. Lett., 1974, 28, 101. [all data]
Carlson and Moser, 1967
Carlson, K.D.; Moser, C.,
Electronic structure and ground state of scandium monofluoride,
J. Chem. Phys., 1967, 46, 35. [all data]
Rosen, 1970
Rosen, B.,
International tables of selected constants. 17. Spectroscopic data relative to diatomic molecules, Pub. Pergamon Press, Oxford, 1970, 0. [all data]
Huber and Herzberg, 1979
Huber, K.P.; Herzberg, G.,
Molecular Spectra and Molecular Structure. IV. Constants of Diatomic Molecules, Van Nostrand Reinhold Company, New York, 1979, 716. [all data]
Go To: Top, Gas phase ion energetics data, Constants of diatomic molecules, References
Copyright for NIST Standard Reference Data is governed by the Standard Reference Data Act.
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{% extends "base.html" %} {% block head_title %}About this site{% endblock %} {% block body_class %}page-about{% endblock %} {% block content %}
This map helps explore the mixed beverage gross receipts taxes collected by the Texas Comptroller.
It’s important to note that the “Total Receipts” field does not represent the amount of tax due by the taxpayer. Rather, it represents the gross receipts reported for beer, wine and liquor. The current MBGRT rate is 6.7% of the total receipts.
data.texas.gov/stories/s/tj7s-7tc8
A tax at the rate of 6.7 percent is imposed on the gross receipts of a permittee received from the sale, preparation, or service of mixed beverages or from the sale, preparation, or service of ice or nonalcoholic beverages that are sold, prepared, or served for the purpose of being mixed with an alcoholic beverage and consumed on the premises of the permittee.
Homepage: github/texas/tx_mixed_beverages
Geocoding:
Date scraped: {% now "DATE_FORMAT" %}
{% endblock %}


pinly.js
pinly - a jQuery Plugin extension for a numerical pin style entry.
Features of pinly:
- Compatible with desktop & mobile devices
- Call pinly.js as a jquery method e.g. $( this ).pinly();
- Number of inputs are configurable but pinly will default to 4 if unset
- pinly only accepts numbers, using first the browser to configure a data input with a js fallback
- pinly supports keyboard shortcuts: -
- TAB or RIGHT ARROW moves to next input in the line
- SHIFT or LEFT ARROW moves to the previous input in the line
- UP increases the increment
- DOWN decreases the increment
- BACKSPACE moves the previous input to allow for corrections, on submission fail hitting backspace will reset the form
- pinly's behaviours, look and feel are 100% customisable using only CSS and minimal js
- pinly is Mobile friendly using the number pad on iOS devices while responsive CSS will fit pinly to your device
- Define a Custom Callback method to run when a pin has been entered
- Use jQuery's $.trigger method to fire the pinly custom events pinlyPass & pinlyFail to define your prefered response for these actions


--- layout: default title: Home ---
This site hosts information on the Atlanta region's Transportation Improvement Program (TIP). The TIP allocates federal funds for use in construction of the highest-priority transportation projects in the near term of the Regional Transportation Plan (RTP). The TIP must be consistent with the long-range objectives of the RTP and must be financially balanced.
For those that want to dive deep into the data and discover funding trends over years or how buckets of money get spent for different project types, check out the Pivot Table under the Explore tab. The tool lets you slice, dice, and even export your results.
Check out the data folder on GitHub. For older versions of the data, navigate to a different branch (e.g., 2nd Quarter of 2009).
If you're a local sponsor and would like to comment on a project or need to propose a change, please visit the Plan-It wiki to learn more about this process.
If you're looking for more information on TIP projects, please check out any of the options under the Explore tab.
Zoom and click around on the map to get a better idea of some of the projects for which federal, state, and local dollars are allocated in the FY 2012-17 TIP (pdf).


In the introductory mashr
vignettes we assumed that the data were small enough that it was convenient to read them all in and do all the analyses on the same data.
In larger applications, particularly eQTL studies, it can be more convenient to do different parts of the analyses on subsets of the tests. Specifically, if you have millions of tests in dozens of conditions, it might be helpful to consider subsets of these millions of tests at any one time. Here we illustrate this idea.
Our suggested workflow is to extract (at least) two subsets of tests from your complete data set:
Results from a subset of “strong” tests corresponding to stronger effects in your study. For example, these tests might have been identified by taking the “top” eQTL in each gene based on univariate test results, or by some other approach such as a simple meta-analysis.
Results from a random subset of all tests. It is important that these be an unbiased representation of all the tests you are considering, including null and non-null tests, because mashr
uses these tests to learn about the amount of signal in the data, and to “correct” estimates for the fact that many tests are null (analagous to a kind of multiple testing correction.)
We will call the data from these two sets of tests strong
and random
respectively.
To give some sense of the potential appropriate sizes of these datasets: in our eQTL application in Urbut et al, the strong
data contained about 16k tests (the top eQTL per gene), and for the random
data we used 20k randomly-selected tests. (If you suspect true effects are very sparse then you might want to increase the size of the random subset, say to 200k).
The basic analysis strategy is now:
Learn correlation structure among null tests using random
test.
Learn data-driven covariance matrices using strong
tests.
Fit the mashr model to the random
tests, to learn the mixture weights on all the different covariance matrices and scaling coefficients.
Compute posterior summaries on the strong
tests, using the model fit from step 2. (At this stage you could actually compute posterior summaries for any sets of tests you like. For example you could read in all your tests in small batches and compute posterior summaries in batches. But for illustration we will just do it on the strong
tests.)
First we simulate some data to illustrate the ideas. To make this convenient to run we simulate a small data. And we identify the strong hits using mash_1by1
. But in practice you may want to use methods outside of R to extract the matrices of data corresponding to strong and random tests, and then read them in as you need them. For example, see here for scripts we use for processing fastQTL output.
library(ashr)
library(mashr)
set.seed(1)
simdata = simple_sims(10000,5,1) # simulates data on 40k tests
# identify a subset of strong tests
m.1by1 = mash_1by1(mash_set_data(simdata$Bhat,simdata$Shat))
strong.subset = get_significant_results(m.1by1,0.05)
# identify a random subset of 5000 tests
random.subset = sample(1:nrow(simdata$Bhat),5000)
We estimate the correlation structure in the null tests from the random
data (not the strong
data because they will not necessarily contain any null tests).
To do this we set up a temporary data object data.temp
from the random tests and use estimate_null_correlation_simple
as in this vignette.
data.temp = mash_set_data(simdata$Bhat[random.subset,],simdata$Shat[random.subset,])
Vhat = estimate_null_correlation_simple(data.temp)
rm(data.temp)
Now we can set up our main data objects with this correlation structure in place:
data.random = mash_set_data(simdata$Bhat[random.subset,],simdata$Shat[random.subset,],V=Vhat)
data.strong = mash_set_data(simdata$Bhat[strong.subset,],simdata$Shat[strong.subset,], V=Vhat)
Now we fit mash to the random tests using both data-driven and canonical covariances. (Remember the Crucial Rule! We have to fit using a random set of tests, and not a dataset that is enriched for strong tests.) The outputlevel=1
option means that it will not compute posterior summaries for these tests (which saves time).
U.c = cov_canonical(data.random)
m = mash(data.random, Ulist = c(U.ed,U.c), outputlevel = 1)
# - Computing 5000 x 241 likelihood matrix.
# - Likelihood calculations took 0.16 seconds.
# - Fitting model with 241 mixture components.
# - Model fitting took 888.72 seconds.
Now we can compute posterior summaries etc for any subset of tests using the above mash fit. Here we do this for the strong
tests. We do this using the same mash
function as above, but we specify to use the fit from the previous run of mash by specifyingg=get_fitted_g(m), fixg=TRUE
. (In mash
the parameter g
is used to denote the mixture model which we learned above.)
m2 = mash(data.strong, g=get_fitted_g(m), fixg=TRUE)
# - Computing 1428 x 241 likelihood matrix.
# - Likelihood calculations took 0.07 seconds.
# - Computing posterior matrices.
# - Computation allocated took 0.11 seconds.
head(get_lfsr(m2))
# condition_1 condition_2 condition_3 condition_4
# effect_13096 7.827683e-07 4.445904e-01 4.269113e-01 4.219194e-01
# effect_29826 8.058844e-06 6.659669e-01 6.346211e-01 7.684488e-01
# effect_14042 1.046313e-01 1.415929e-02 1.243030e-02 7.026350e-02
# effect_12524 1.486131e-01 1.958528e-01 1.428624e-01 1.119056e-06
# effect_15456 1.543916e-05 6.713363e-01 5.502629e-01 6.753834e-01
# effect_35844 5.643556e-09 7.689403e-09 7.902065e-07 1.554177e-09
# condition_5
# effect_13096 4.644556e-01
# effect_29826 6.316816e-01
# effect_14042 4.986650e-07
# effect_12524 1.517283e-01
# effect_15456 5.862622e-01
# effect_35844 3.312828e-11


Erin is incredibly passionate, goal-driven, empathetic, and super motivated for whatever is being thrown her way.
Web development allows Erin to showcase her creative side while ensuring client satisfaction.


Dig The Wells
问题描述 :
You may all know the famous story “Three monks”. Recently they find some places around their temples can been used to dig some wells. It will help them save a lot of time. But to dig the well or build the road to transport the water will cost money. They do not want to cost too much money. Now they want you to find a cheapest plan.
输入:
There are several test cases.
Each test case will starts with three numbers n , m, and p in one line, n stands for the number of monks and m stands for the number of places that can been used, p stands for the number of roads between these places. The places the monks stay is signed from 1 to n then the other m places are signed as n + 1 to n + m. (1 <= n <= 5, 0 <= m <= 1000, 0 <=p <= 5000)
Then n + m numbers followed which stands for the value of digging a well in the ith place.
Then p lines followed. Each line will contains three numbers a, b, and c. means build a road between a and b will cost c.
Each test case will starts with three numbers n , m, and p in one line, n stands for the number of monks and m stands for the number of places that can been used, p stands for the number of roads between these places. The places the monks stay is signed from 1 to n then the other m places are signed as n + 1 to n + m. (1 <= n <= 5, 0 <= m <= 1000, 0 <=p <= 5000)
Then n + m numbers followed which stands for the value of digging a well in the ith place.
Then p lines followed. Each line will contains three numbers a, b, and c. means build a road between a and b will cost c.
输出:
There are several test cases.
Each test case will starts with three numbers n , m, and p in one line, n stands for the number of monks and m stands for the number of places that can been used, p stands for the number of roads between these places. The places the monks stay is signed from 1 to n then the other m places are signed as n + 1 to n + m. (1 <= n <= 5, 0 <= m <= 1000, 0 <=p <= 5000)
Then n + m numbers followed which stands for the value of digging a well in the ith place.
Then p lines followed. Each line will contains three numbers a, b, and c. means build a road between a and b will cost c.
Each test case will starts with three numbers n , m, and p in one line, n stands for the number of monks and m stands for the number of places that can been used, p stands for the number of roads between these places. The places the monks stay is signed from 1 to n then the other m places are signed as n + 1 to n + m. (1 <= n <= 5, 0 <= m <= 1000, 0 <=p <= 5000)
Then n + m numbers followed which stands for the value of digging a well in the ith place.
Then p lines followed. Each line will contains three numbers a, b, and c. means build a road between a and b will cost c.
样例输入:
3 1 3 1 2 3 4 1 4 2 2 4 2 3 4 4 4 1 4 5 5 5 5 1 1 5 1 2 5 1 3 5 1 4 5 1
样例输出:
6 5
#include<cstdio> #include<cstring> #include<cstdlib> #include<queue> #include<algorithm> #define INF 999999999 #define MAX 1010 #define MAX_STATUS 1<<6 using namespace std; struct EDGE { int v ,w; int next; }edges[MAX*13]; struct NODE { int x ,y; }; int head[MAX] ,cnt; int n ,m ,p; int value[MAX]; int status;//表示0~n号节点都被选择时的状态+1 int dis[MAX][MAX_STATUS] ,situation[MAX] ,vis[MAX][MAX_STATUS] ,dp; //dis[i][j]表示以i节点为根选择点集状态为j时的最小值；situation[i]表示i节点对应的状态；vis[i][j]表示i节点为点集j时是否在队列中 queue<NODE> q; void init() { memset(head,-1,sizeof(head)); memset(vis,0,sizeof(vis)); memset(situation,0,sizeof(situation)); cnt = 0; status = 1<<(n + 1); for(int i = 0;i <= n + m;i++) { for(int j = 0;j <= status;j++) { dis[i][j] = INF; } } for(int i = 0;i <= n;i++) { situation[i] = 1<<i; dis[i][situation[i]] = 0; } } void add_edges(int u ,int v ,int w) { edges[cnt].v = v; edges[cnt].w = w; edges[cnt].next = head[u]; head[u] = cnt; cnt++; edges[cnt].v = u; edges[cnt].w = w; edges[cnt].next = head[v]; head[v] = cnt; cnt++; } void SPFA() { NODE temp ,newd; while(!q.empty()) { temp = q.front(); q.pop(); vis[temp.x][temp.y] = 0; for(int i = head[temp.x];i!=-1;i = edges[i].next) { int v ,situ; v = edges[i].v; situ = temp.y | situation[v]; if(dis[temp.x][temp.y] + edges[i].w < dis[v][situ]) { dis[v][situ] = dis[temp.x][temp.y] + edges[i].w; if(situ==temp.y && !vis[v][situ]) { newd.x = v; newd.y = situ; q.push(newd); vis[v][situ] = 1; } } } } } void Steiner_Tree() { NODE temp; for(int i = 0;i < status;i++) { for(int j = 0;j <= n + m;j++) { for(int k = i;k;k = (k - 1) & i) { dis[j][i] = min(dis[j][i],dis[j][k|situation[j]]+dis[j][(i-k)|situation[j]]); } if(dis[j][i]!=INF) { temp.x = j; temp.y = i; q.push(temp); vis[j][i] = 1; } } SPFA(); } } int DP() { dp = INF; for(int j = 0;j <= n+m;j++) { dp = min(dp,dis[j][status-1]); } return dp; } int main() { int u ,v ,w; while(~scanf("%d%d%d",&n,&m,&p)) { init(); for(int i = 1;i <= m + n;i++) { scanf("%d",&value[i]); add_edges(0,i,value[i]); } for(int i = 0;i < p;i++) { scanf("%d%d%d",&u,&v,&w); add_edges(u,v,w); } Steiner_Tree(); printf("%d\n",DP()); } return 0; }
参考：http://blog.csdn.net/catalyst1314/article/details/20574927
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十字架上绑的是撒旦……
十字架上绑的是撒旦……
十字架上绑的是撒旦……
十字架上绑的是撒旦……
十字架上绑的是撒旦……
十字架上绑的是撒旦……
十字架上绑的是撒旦……
十字架上绑的是撒旦……
int L[m+1][n+1];这样定义出错，这个在gcc上可以编译通过 在VS上不行 应该改为new 或者vector
真考人啊
受益匪浅！！
为什么暴力求解方法循环到sqrt(n) 就可以了呢
0000
代码过于复杂了吧
写的好····· Pollard Rh
没有对题目进行一番分析，真是美中不足啊
是O(m+n)，不小心打错了
Java真是解决大数的利器
感谢分享 学习了`(*∩_∩*)′
方法二可行，已测试
http://blog.csdn.net/alpc_paul/article/details/33769407
较好的写法是 start+(end-start)/2


Find who is Current OS user
Windows
Execute SET USERNAME
command from the command prompt to check which user is currently logged in.
UNIX/Linux
Execute who am I
at the command prompt to see the current user logged in.
Check which group current user belongs to
Windows
Following are the steps to check which group current user belongs to:
- Right click on "My Computer", go to "Manage"
- Click on "local users and groups" folder
- Right click on current user's name, go to properties, click on "Members of" tab. This tab will list all the groups which the current user belongs to.
UNIX/Linux
Execute groups
at the command prompt to find out the groups current user belongs to.


Efe Nathan, Bidemi, other top gospel stars for BOW
By Adeola Ogunlade
Pop gospel stars, Efe Nathan, Bidemi Olaoba, Dare Justified, 9Tingale, Yemi Olufemi also known as Ypiono among others are set to perform at the 8th edition of Best of Worship (BOW) slated for today at the Redeemed Christian Church of God, (RCCG) l, Redemption Close, China Town, Lagos.
Others guest artistes are Bada, Samuel Essien and Miaor Ese.
Read Also: Soul E stages live gospel concert
According to the convener of BOW, Pastor Paul Mashote, Best of Worship is an international musical concert with a specific vision of creating a platform of undiluted worship.
“The phenomenal annual worship gathering has recorded hundreds of worshipers from within and outside the shore of Nigeria,” he said.
He noted that over the years, BOW has featured music artistes like Pastor Kunle Ajayi, Pastor Kenny Koore, Gbenga Salako and Frank Edward.


A secure proxy based on websocket.
This project is still working in progress, more features are still in development. If you are interested in this project, please star this project in order to support me. Thank you.
If you have any problems or suggestions, please do not hesitate to submit issues or contact me @halulu . We also have a telegram group (mostly Chinese, English is ok).


Preparation time
1-2 hours
Cooking time
10 to 30 mins
Serves
Makes 10 buns
Nothing beats a warm, sticky bun fresh from the oven. These are drizzled with icing for an extra naughty treat.
Place the flour and salt into a large mixing bowl and stir until thoroughly combined. Make a well in the centre of the flour and pour in the yeast.
Warm the milk and butter in a small saucepan until the butter is melted and the mixture is lukewarm. Pour into the flour mixture, add the egg and stir thoroughly until the contents of the bowl come together as a soft dough.
Tip the dough onto a lightly floured work surface and knead well for five minutes, until the dough is smooth and elastic.
Place the dough into an oiled bowl and leave to rise, covered with a damp tea towel, for one hour or until doubled in size.
Tip the dough out onto a lightly floured work surface. Roll out dough into a rectangle about 30x20cm/12x8in.
Brush all over with the melted butter. Evenly sprinkle the orange zest over the buttered surface, followed by the sugar, cinnamon and dried fruit.
Tack down the long side of the dough rectangle nearest to you by pressing it down onto the work surface with your thumb.  With a sharp knife cut into thick rounds - about 4cm/1¾in.
Grease a deep roasting tin or baking tray thoroughly with butter.
Place the buns, cut side up, into the greased baking tray leaving about 1cm/½in of space between each one.  They can then be pulled apart and you get a lovely soft edge.
Leave to rise for about 30 minutes in a warm place.
Preheat oven to 190C/375F/Gas 5.
When the buns are ready, put them in the oven and bake for 20-25 minutes until golden-brown. Check after 15 minutes or so and cover the buns with foil if they are getting too brown.
Remove the buns from the oven and let them cool slightly before transferring them from the tin to a cooling rack.
Melt the jam in a small saucepan with a splash of water until smooth. Brush the jam over the buns to glaze and allow to cool.
Mix together the icing sugar, orange zest and two tablespoons water. Drizzle the icing over the cooled buns and allow to set before serving.


ONE FINE DAY A film review by Steve Rhodes Copyright 1997 Steve Rhodes
RATING (0 TO ****): ** 1/2
Run Melanie run. Run Jack run. See Melanie and Jack run to take care of their kids while maintaining their busy careers.
Melanie Parker, played supposedly close to her real life by Michelle Pfeiffer, is a harried and obsessive single mom in ONE FINE DAY. In contrast, Jack Taylor, played with childlike panache by George Clooney, is a single father with a "Peter Pan complex."
Over the span of one not so fine day, Melanie and Jack try to cope with the problems of modern day parenthood. Until the film starts the only thing they share is that their 6-year-olds go to the same school. In a single day, they will miss a field trip together, lose one of their kids, swap cell phones by accident, worry about getting fired, share childcare arrangements, trade numerous insults, and, of course, finally fall in love.
Highly predictable, certainly. Funny? Well, I think it depends on the viewers. I suspect that working parents of kids under twelve will find that the humor works and the catastrophes of the story hit home. Others, may be inclined to write off the show as a lame comedy. Most reviewers have been in the latter category. Our whole family, however, loved the show.
Let me convince parents of the film's authenticity. In the opening, Melanie's little boy Sammy, played with heart by Alex D. Linz, claims he had a bad dream although his head only hit the pillow seconds earlier. In the next scene he is in bed asleep with mom. His arm flies across the bed and slugs her in the face as she sleeps. I have long since lost track of how many times this has happened to us.
Jack is a great dad and will stop everything to go play with his daughter Maggie, played charmingly by Mae Whitman. He is not, however, terribly responsible. In a typical scene Maggie tells him, "I'm hungry." He automatically replies, "Want a Tic Tac?" When she says no, he nonchalantly informs her, "That's all I've got."
Since both adults have big meetings at different hours later in the day, they will reluctantly agree to watch each other's child. Director Michael Hoffman uses fast paced songs and frequent cuts to a digital clock to maintain the film's high energy level. He has his actors pumped up like they are all on a sugar high.
Both Pfeiffer and Clooney are good looking actors and full of talent. When Pfeiffer falls flat on her face, she stills looks gorgeous. Clooney's character has the women in his office falling all over themselves to get an opportunity to flirt with him.
Both of their jobs are interesting. He is an investigative columnist for a big New York City newspaper. His boss Lew, played by Charles Durning, repeating a character type he has done many times before, threatens to fire him if he does not get collaboration on his story by five o'clock. "You aren't going to fire me," Jack smugly tells him. "My face is on buses." The smart script by Terrel Seltzer and Ellen Simon keeps the barbs flying.
Melanie is an architect who has a big presentation of her work to an important client at two o'clock. Her son will cause her to trip and smash her big model.
In a comedy, you have to give the material a lot of leeway. Although I do not expect accuracy, the treatment of her son in the office was too far fetched. Her boss, supposedly, may fire workers if caught bringing their kids into the office. Out of character for her, Melanie denies she is Sammy's mother when her boss sees him there.
Sometimes the hectic pace is broken by a dreamy musical interlude, and New York City itself sometimes becomes a visual relaxation point. For those of you who may have forgotten, there are many lovely sights there, and ONE FINE DAY shows off several to maximum effect.
During the day, the parents will face minute by minute tradeoff decisions about childcare and their jobs. While most are realistic, having them all occur in a single day is not, but in a movie it works. In another all-too-true-to-life scene, Melanie tries to reassure Sammy with, "You're the most important thing in the world." "No, I'm not," he quickly corrects her. "Your job is." What parents have not been cut to the quick by their children with a line like that?
The supporting cast is strong, and there is even a cute little kitten that Jack gets to carry.
The ending is superb. "Let's do this right," says Melanie.  You will never guess how their date ends up. Or then again, those of you who are parents may.
ONE FINE DAY runs 1:48. It is rated just PG. There is no sex, nudity, or violence. There are a few mild but, nevertheless, needless profanities. The lost child scene has some potential of frightening very young children. My son Jeffrey, age 7 1/2, gave it a 99 percent thumbs up. He downgraded it slightly due to the kissing scene. (He made me cover his eyes, but let him peak so he would not miss any of it.) He especially liked the part of the mother's broken model and the way the dad was so playful. He recommends the film to his friends ages 4 and up. I'd raise the age to 6 and up, but I certainly recommend the picture to all parents of kids less than twelve. For others, I'm not so sure. I give the film ** 1/2.
**** = One of the top few films of this or any year. A must see film. *** = Excellent show. Look for it. ** = Average movie. Kind of enjoyable. * = Poor show.  Totally unbearable.
REVIEW WRITTEN ON: January 3, 1997
Opinions expressed are mine and not meant to reflect my employer's.
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rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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src package¶
Submodules¶
src.const module¶
-
src.const.
interpolationTime
= 15¶ max tolerance in minutes for when data should be interpolated, independent of capture period
-
src.const.
resampleStringForHeatmap
= '1D'¶ 1 days, how data will be resampled to display in heatmap: examples are “3D”=3 days, “7D”=7 day, “1M”= 1 month
src.db module¶
-
src.db.
getCapturePeriodForSensorName
(cursor, name)[source]¶ assumes name exists in db
Parameters: - cursor – db connection cursor
- name – name of sensor
Returns: capture peroid of (sensor)name
-
src.db.
getDFForQuery
(cursor, query)[source]¶ Parameters: - cursor – db connection cursor
- query – database query
Returns: (not Empty: Bool, pandas dataframe of result)
-
src.db.
getDFForQueryAnon
(cursor, query, key)[source]¶ Parameters: - cursor – db connection cursor
- query – database query
- key – key to anonymise data
Returns: (not Empty: Bool, pandas dataframe of result which is anonymized in addition)
-
src.db.
getSensorNamesForHouse
(cursor, abbreviation)[source]¶ Parameters: - cursor – db cursor
- abbreviation – abbrevation for house
Returns: array of all sensors as string
-
src.db.
queryForSensor
(name, startD, endD)[source]¶ often used in combination with getDFForQuery:
success, result = getDFForQuery(queryForSensor("name", "2018-12-12 12:12:12", "2019-12-12 12:12:12"))
Parameters: - name – name of sensor
- stardD – startdate as string
- endD – endDate as string:
Returns: query string to select all values between startdate and enddate
-
src.db.
read_db_config
(filename='program_config.ini', section='mysql_shiftable')[source]¶ Parameters: - filename – path to program_config.ini
- section – where to look for db info in .ini file
Returns: kwargs for MySQLConnection
Example:
config = read_db_config('program_config.ini', section='mysql_nonshiftable') connection = MySQLConnection(**config)
src.preprocessing module¶
-
src.preprocessing.
combineDfs
(dfs, sensorList, startDate, endDate, freq, freqInt, capPeriods)[source]¶ combine all dataframes into one big one, while merging all columns
Parameters: - dfs – list of dataframes we want to merge
- sensorList – list of sensornames, same order as dfs
- startDate – global startDate we want to choose
- endDate – global endDate we want to choose
- freq – frequency as string that we want in the merged dataframe
- freqInt – frequency as integer that we want in the merged dataframe
- capPeriods – list of capture periods, same order and length as sensorList
Returns: merged dataframe
-
src.preprocessing.
convertWhToW
(dfs, sensorList, convToPower, capPeriods)[source]¶ converts energy to power, note that the column names are renamed from
*energy
to*power
, everything inplaceParameters: - dfs – list of dataframes of various sensors
- sensorList – list of the respective sensorname from dfs, order should correspond to dfs
- capPeriods – list of capture periods of the sensornames from sensorList, order should be the same
-
src.preprocessing.
getRawData
(dfs, filteredSensorListRet, capPeriods, basedir, cip, startDate=None, endDate=None, cursor=None, key=None, filteredSensorListDB=None)[source]¶ We check first if there are raw datafiles available in
basedir/cip
. If there aren’t any, we load the data from the MySQL db, but only if there is a cursor given. After loading the data from the database we store it in basedir/subdirWarning
if there is no raw data hdf files present in
basedir/cip
and no cursor is provided, the function simply returns and nothing happensParameters: - dfs – we load the dataframes of each sensor into this list
- filteredSensorListRet – in this list we put the sensornames, the order is the same as in dfs
- capPeriods – in this list we put the capture periods of tje sensors, the order is the same as in dfs
- basedir – the rawdata is expected/stored in
basedir/cip
- cip – anonymized name of house
- startDate – only required when we load the data from the db, not required if there are hdf files present
- endDate – only required when we load the data form the db, not required if there are hdf files present
- cursor – the db connection cursor, not required if there are hdf files present
- key – shortName of house, not required if there are hdf files present
- filteredSensorListDB – sensors we want to load from db; the actual names are constructed like this:
[key+'{0}'.format(i) for i in filteredSensorListDB]
, not required if there are hdf files present
-
src.preprocessing.
mergeTotalConsumptionC
(dfs, filteredSensorList, filteredSensorList_OG, capPeriods)[source]¶ special preprocessing function for house C to merge the two sensors that measure the total consumption
Parameters: - dfs – list of dataframes, each dataframe contains values of one sensor
- filteredSensorList – name of the sensors, order is the same as in dfs
- filteredSensorList_OG – unmodified version, of filteredSensorList
- capPeriods – capture periods of all sensors, order is the same as dfs
-
src.preprocessing.
preprocessBoilerPower
(df2, key)[source]¶ calculates the average boiler power, because we have timestamps where the boiler is turned off/on often not following the capture period
preprocessing is done as well (set index, interpolation)
Parameters: - df2 – dataframe of boiler
- key – sensorname
Returns: new dataframe, in a 5 min grid
-
src.preprocessing.
readCapPeriods
(capPeriods, filteredSensorList, basedir, subdir)[source]¶ aux function to read the capture periods of the sensors from a hdf file
Parameters: - capPeriods – capture periods get stored in here
- filteredSensorList – list of sensor names, same order as capPeriods will be
- basedir – file is expected in
os.path.join(basedir,os.path.join(subdir,"capPeriods"))+".hdf", key="data")
- subdir – see description of basedir
-
src.preprocessing.
readDFS
(dfs, basedir, subdir, sensorList)[source]¶ reads the raw data into a list of dataframes
Parameters: - dfs – we store the hdf files that are read in this list
- basedir – we expect files to be in
os.path.join(basedir,os.path.join(subdir,sensorname))+".hdf", key="data")
- subdir – see description of param basedir
- sensorList – this list gets filled with names of the sensors in dfs, the order is the same as in dfs
-
src.preprocessing.
roundDuplicateEliminateInterpolateResample
(dfs, sensorList, ignoreList, capPeriods)[source]¶ Warning
maybe resample first?
a lot of preprocessing like: setting index, date rounding, duplicate elimination, interpolation, everything inplace
Parameters: - dfs – list of dataframes, where each is a sensor
- sensorList – list of sensornames, same order as dfs
- ignoreList – do not touch the sensors mentiones in this list
- capPeriods – list of all capturePeriods, same order as sensorList (and length)
-
src.preprocessing.
saveCapPeriods
(capPeriods, filteredSensorList, basedir, subdir)[source]¶ aux function to save the capture periods of the sensors in a hdf file
Parameters: - capPeriods – list of capture periods
- filteredSensorList – list of sensor names, same order as capPeriods
- basedir – file is saved in
os.path.join(basedir,os.path.join(subdir,"capPeriods"))+".hdf", key="data")
- subdir – see description of basedir
src.public module¶
src.utils module¶
-
src.utils.
anonymise
(df, key)[source]¶ Parameters: - df – dataframe that we want to anonymize the columns of
- key – key for anonymization dictionary
-
src.utils.
countNaN
(array_like)[source]¶ used in combination with resampling:
df.resample("3D").apply(countNaN)
Parameters: array_like – usually a partial column of dataframe Returns: scalar value, namely the percentage of NaN values in array_like
-
src.utils.
generateHeatmap
(df, size, pmin, pmax, resampleString, preName)[source]¶ generate a heatplot of the missing data, using the seaborn visualization tool
Parameters: - df – dataframe where each column is a sensor, index is a date series
- size – (width, height) tuple in inches of output image
- pmin – min percentage where colorscale should begin \(\in [0,1)\)
- pmax – max percentage where colorscale should end \(\in (0,1]\)
- resampleString – how much should be summarized in block visually, for example “3D” = 3 days: show percentage of NaN per 3 days
- preName – image will be saved as
preName+"_"+resampleString+".png"
-
src.utils.
mask_knans
(df, x)[source]¶ we specify a maximum of consecutive NaN we allow to be interpolated
Example usage:
df["col"] = df["col"].interpolate(method='linear').where(mask_knans(df["col"], int(15*60/300)))
Parameters: - df – column of pandas dataframe
- x – maximum tolerance of NaN values
Returns: boolean mapping of rows where we should interpolate


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FLUBBER Grade: D (Buy the Happy Meal, Skip the Flick)
Directed by Les Mayfield (Miracle on 34th street) Written by John Hughes Starring: Robin Williams, Marcia Gay Harden (Miller's Crossing), Ted Levine (The Silence of the Lambs), Clancy Brown (Blue Steel) Year of Release: 1997 Rating: PG
Deserves Recognition for: Making this relatively youthful critic feel extremely old and crotchety20
Capsule Review: This is what feel-good family entertainment has morphed into in the 90's: An hour-and-a-half commercial, disguised as an unnecessary remake, in which the defining image is that of a grown man launching a volume of green protoplasmic goo out of his ass. (Between this, Rocketman, and George of the Jungle, Disney has recently eclipsed longtime champion Troma as the studio most likely to include a fart joke in a film.) As the absent-minded professor who invents the titular computer-generated goop, a listless Robin Williams manages the difficult task of making original lead Fred MacMurray seem sprightly. The only thing that made this film borderline tolerable for me is my newly-founded but firm belief that writer/producer John Hughes is going to spend his eternal afterlife being conked in the noggin by all of the different blunt instruments he's used for comedic effect in films like this and the odious Home Alone series. Take your kids to see Boogie Nights instead.
Copyright 1998 by The Critic formerly known as Andrew Wright For more insanely biased reviews, check out http://www.seanet.com/~louk/ e-mail<EMAIL_ADDRESS>"Saturday Night Thing. Drunken Hillbilly Bar Fight. My Soul Rejoices."
A Haiku in honor of ROADHOUSE A9Andrew L. Wright esq.
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