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Female English Names
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English
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-
ALIA:
Variant spelling of English Aliah,
meaning "to ascend, to go up."
-
ALIAH:
Anglicized form of Hebrew Aliya,
meaning "to ascend, to go up."
-
ALICA:
Slovak form of English Alice, meaning "noble sort."
-
ALICE:
Modern form of English Adelaide, meaning "noble sort."
-
ALICIA: Spanish
equivalent of English Alice,
meaning "noble sort."
-
ALINE: Variant spelling of English
Aileen,
meaning "little Eve." Compare
with another form of Aline.
-
ALIS: Short form of English Alisa,
meaning "noble sort." Compare with another form of Alis.
-
ALISA: Variant form of English
Alice,
meaning "noble sort." Compare with other forms of Alisa.
-
ALISE: Latvian
equivalent of English
Alice, meaning "noble sort."
-
ALISHA:
English variant spelling of Spanish Alicia, meaning "noble
sort."
-
ALISHIA:
English variant spelling of Spanish Alicia, meaning "noble
sort."
-
ALISIA:
English variant spelling of Spanish Alicia, meaning "noble
sort."
-
ALISON: Norman French form of
Old High German Adalheid,
meaning "noble sort." In use by the English and Scottish.
Compare with another form of Alison.
-
ALISSA:
English variant spelling of Spanish Alicia,
meaning "noble sort."
-
ALISYA:
English variant spelling of Spanish Alicia, meaning "noble
sort."
-
ALIVIA:
Variant spelling of English Olivia,
probably meaning
"elf army."
-
ALIX:
Variant spelling of English unisex Alex, meaning "defender of
mankind."
ALLANA:
Variant spelling of English Alana, possibly meaning
"little rock."
ALLANNAH:
Variant spelling of English Alannah, possibly meaning
"little rock."
ALLEEN:
Variant spelling of English Aline,
meaning "little Eve."
ALLENE:
Variant spelling of English Aline,
meaning "little Eve."
-
ALLIE:
Scottish pet form of Norman French Alison, meaning "noble sort."
-
ALLINE:
Variant spelling of English Aline,
meaning "little Eve."
-
ALLISON:
Medieval English spelling of Norman French Alison,
meaning "noble sort."
-
ALLISSA:
Variant spelling of English Alissa, meaning
"noble
sort."
-
ALLY:
Scottish pet form of Norman French Alison,
meaning "noble sort."
-
ALLYCIA:
English variant spelling
of Spanish Alicia,
meaning "noble sort."
-
ALLYSON:
Modern variant spelling of Medieval English Allison,
meaning "noble sort."
-
ALMA:
English name meaning "nourishing" in Latin and
"soul" in Spanish. Compare with other forms of
Alma.
-
ALMAH: Variant spelling of English Alma,
meaning "nourishing" in Latin and
"soul" in Spanish. Compare with another form
of Almah.
-
ALMIRA:
Contracted form of Spanish Adelmira,
meaning "nobly famous." In use by the
English, as is its variant Elmira.
-
ALPHA
(Άλφα):
English unisex name derived from the first letter of the
Greek alphabet.
-
ALPHONSINE:
Feminine form of French Alphonse, meaning "noble and ready."
-
ALTAIR
(الطير):
Modern English unisex name derived from the name of the brightest star in
the constellation Aquila, from an Arabic word meaning "the bird"
or "the flyer."
-
ALVA: Anglicized feminine form of Irish Gaelic unisex
Ailbhe,
possibly meaning "white." Compare with another form of Alva,
and masculine Alva.
-
ALVENA:
Variant spelling of Middle English Alvina, meaning "elf friend."
-
ALVINA:
Middle English feminine form of Norman French Alvin, meaning
"elf friend."
-
ALYCE:
Variant spelling of English Alice, meaning "noble sort."
-
ALYCIA:
English variant of Spanish Alicia, meaning "noble
sort."
-
ALYS:
Anglicized form of Welsh Alis, meaning
"noble sort."
-
ALYSA:
Variant spelling of English Alyssa, meaning
either "noble sort" or "alyssum flower."
-
ALYSE:
Variant spelling of English Alice,
meaning "noble sort."
-
ALYSHA:
English variant spelling of Spanish Alicia,
meaning "noble sort."
-
ALYSIA:
English variant spelling of Spanish Alicia,
meaning "noble sort."
-
ALYSON: Diminutive form of
English Alys, meaning "noble sort."
-
ALYSSA:
English variant spelling of Spanish Alicia,
meaning "noble sort." This name is also sometimes given as a plant
name, "Alyssum flower," from Latin alyssum, from Greek alysson,
composed of a- "not" and lysson "rabies,"
hence "not rabies," because the Alyssum plant was believed to cure
rabies.
-
ALYSSIA:
English variant spelling of Spanish Alicia,
meaning "noble sort."
-
ALYX:
Variant spelling of English unisex Alex, meaning "defender of
mankind."
-
AMABEL:
English name derived from Latin amabilis, meaning
"lovable."
-
AMALEA:
English variant spelling of German Amalia, meaning
"work."
-
AMALEE:
Perhaps a variant spelling of English Emily,
meaning "rival."
- AMALIYA:
English variant spelling of German Amalia, meaning
"work."
- AMANDA:
English literary name, created by playwright Colley Cibber in the 17th
century, derived from Latin amanda, meaning
"lovable."
- AMARYLLIS:
English name derived from the flower name amaryllis, from Greek amarysso, meaning "to
sparkle."
- AMBER:
English name derived from the vocabulary word, meaning "amber,"
the gem or color. Actually the word is of Arabic origin, from anbargris
(ambergris), which refers to an oily, perfumed substance (used in
making perfumes) secreted by the sperm whale.
-
AMBROSIA: In Greek mythology,
ambrosia is the name of a food or drink of the gods that gives them
immortality.
-
Feminine form of Greek Ambrosios,
meaning "immortal."
Feminine form of Latin Ambrosius,
meaning "immortal."
AMELIA:
English form of German Amalia,
meaning "work."
AMELIE:
English form of French Amélie, meaning
"work."
AMETHYST:
English name derived from the name of the precious stone, from Greek amethustos,
meaning "not intoxicated; sober," expressing the ancient belief
that the stone had the ability to protect one from drunkenness. This name is
sometimes given to girls born in February.
AMEY:
Variant spelling of English Amy, meaning "much loved."
AMI:
Variant spelling of English Amy, meaning "much loved."
AMICE:
English name derived from Latin amicitia, meaning "friendship."
AMIE:
Variant spelling of English Amy, meaning "much loved."
AMILIA:
Variant spelling of English Amelia,
meaning "work."
AMITY:
English name meaning
"friendship."
AMY: English form of French
Aimée,
meaning "much loved."
ANABELLA:
Variant spelling of English Annabella, meaning
"gracious beauty."
ANABELLE:
Variant spelling of English Annabelle, meaning
"gracious beauty."
ANASTACIA:
English form of Latin Anastasia, meaning
"resurrection."
ANASTASIA
(Greek:
Αναστασία):
Feminine form of Greek Anastasios, meaning "resurrection."
Feminine form of Latin
Anastasius,
meaning "resurrection."
ANDEE:
Pet form of English Andrea, meaning "man; warrior."
ANDI:
Pet form of English Andrea, meaning "man; warrior."
ANDRA:
Feminine form of English Andrew, meaning
"man; warrior."
ANDREA:
Feminine form of English Andrew,
meaning "man; warrior."
ANDREANA:
Elaborated form of English Andrea, meaning "man;
warrior."
ANDRI:
Pet form of English Andriana, meaning
"man; warrior."
ANDRIANA:
Elaborated form of English Andrea, meaning "man;
warrior."
ANDRINA:
Elaborated form of English Andrea,
meaning "man; warrior."
ANDY:
Unisex pet form of English Andrew
and Andrea, meaning "man; warrior."
ANETA: English variant spelling of Spanish Anita,
meaning "favor; grace." Compare with another form of Aneta.
ANETTA:
English variant form of Spanish Anita, meaning "favor;
grace."
ANETTE:
Variant spelling of French Annette, meaning "favor;
grace."
ANGE:
English short form of Latin Angela, meaning
"angel, messenger." Compare with masculine Ange.
ANGEL: English
unisex name derived from Latin Angelus,
meaning "angel, messenger." Originally a
male name, it is now almost strictly female.
ANGELA:
Feminine form of Latin Angelus,
meaning "angel, messenger."
ANGELICA:
Feminine form of Italian Angelico,
meaning "angelic."
ANGELINA:
Diminutive form of Latin Angela,
meaning "little angel/messenger."
ANGELINE:
Diminutive form of French Angèle,
meaning "angel, messenger."
ANGELIQUE:
French feminine form of Latin Angelicus,
meaning "angelic."
ANGELL:
Feminine variant spelling of English unisex Angel, meaning
"angel, messenger."
ANGELLE:
Feminine variant spelling of English unisex Angel,
meaning "angel, messenger."
ANGELLINA:
English variant spelling of Latin Angelina, meaning
"angel, messenger."
ANGIE:
English short form of Latin Angela, meaning "angel, messenger."
ANIMA:
Modern English name
derived from Latin anima, meaning "anger, courage, essence, feeling, mind, passion, spirit," from the PIE root
*ane-, meaning "to breathe," the same root from which the words animal and animation came. But in Christian contexts, the word
anima was used to translate the Greek word
psykhe into "soul" (not "spirit"), and this is the same anima from which the personal name was derived.
Compare with another form of Anima.
ANISE:
English name derived from the name of the herb, meaning
"anise."
ANITA:
Spanish pet form of Latin Anna,
meaning "favor;
grace."
ANITRA:
English elaborated form of Spanish Anita, meaning
"favor;
grace."
ANN:
Variant spelling of French Anne, meaning "favor;
grace."
ANNA: Latin
form of Greek Hanna, meaning "favor;
grace." In the New Testament bible, this is the name of a
prophetess in Jerusalem.
ANNABEL:
Variant spelling of English Annabelle, meaning
"gracious beauty."
ANNABELINDA:
English compound name composed of Latin Anna
"favor; grace," and German Belinda,
"beautiful serpent," hence "gracious beautiful serpent."
ANNABELL:
Variant spelling of English Annabelle, meaning
"gracious beauty."
ANNABELLA:
English compound name composed of Latin Anna
"favor; grace," and the Italian word bella
"beautiful," hence "gracious beauty."
ANNABELLE: English compound name composed of Latin Anna
"favor; grace," and the French word belle
"beautiful," hence "gracious beauty." Compare with
another form of Annabelle.
ANNABETH:
English compound name composed of Latin Anna
"favor; grace," and Beth
"God is my oath."
ANNALEE:
English compound name composed of Latin Anna
"favor; grace," and Lee
"meadow," hence "graceful meadow."
ANNAMAE:
Variant spelling of English Annemae, meaning "favor;
grace" and "May."
ANNAMARIA:
English compound name composed of Latin Anna
"favor; grace," and Maria
"obstinate, rebellious."
ANNAMAY:
Variant spelling of English Annemae,
meaning "favor; grace" and "May."
ANNE:
French form Latin Anna, meaning "favor;
grace." Compare with masculine Anne.
ANNELISA:
English compound name composed of French Anne
"favor; grace" and Lisa
"God is my oath."
ANNEMAE:
English compound name composed of French Anne,
"favor;
grace" and Mae,
meaning "pearl," "obstinate, rebellious," or the
month of May.
ANNE-MARIE:
Variant spelling of German Annemarie,
meaning "favor; grace," and
"obstinate, rebellious."
ANNEMARIE:
German compound name composed of French Anne
"favor; grace," and Marie
"obstinate, rebellious."
ANNETTA:
Italian diminutive form of Latin Anna,
meaning "favor; grace."
ANNETTE:
Diminutive form of French Anne,
meaning "favor; grace."
ANNGELA:
English variant spelling of Latin Angela,
meaning "angel, messenger."
ANNICE:
Middle English form of English Agnes,
meaning
"chaste; holy."
ANNIE:
English pet form of Latin
Anna, meaning "favor;
grace."
ANNIS: Medieval
form of
English Agnes,
meaning "chaste; holy." Compare with
another form of Annis.
ANNITA:
English variant spelling of Spanish Anita, meaning
"favor;
grace."
ANNITRA:
Elaborated form of English Anitra, meaning
"favor;
grace."
ANNITTA:
English variant spelling of Spanish
Anita, meaning "favor;
grace."
ANNMARIE:
Variant spelling of English Annemarie,
meaning "favor; grace," and
"obstinate, rebellious."
ANNONA:
English name, probably derived from the plant genus name
annona, from Taíno annon, a species of plants which produce nutritious edible pond-apples.
ANNORA:
English variant form of Latin Honora,
meaning "honor."
ANONA:
Variant spelling of English Annona, which was probably derived from the plant genus name
annona, from Taíno annon, a species of plants which produce nutritious edible pond-apples.
ANONNA:
Variant spelling of English Annona, which was probably derived from the plant genus name
annona, from Taíno annon, a species of plants which produce nutritious edible pond-apples.
ANORA:
Variant spelling of English Annora,
meaning "honor."
ANSONIA:
Feminine form of English Anson,
originally a patronymic surname which may have come from
any of a number of Middle English names, for instance
"son of Ansel,"
or "son of Agnes."
ANSTACE:
Variant spelling of English/Scottish Anstice, meaning
"resurrection."
ANSTICE:
English and Scottish name derived from Latin Anastasia,
meaning "resurrection." Popular in the 13th
century.
ANSTEY:
Pet form of English/Irish Anstice, meaning
"resurrection."
ANTHIA:
English variant spelling of Latin Anthea, meaning "flower."
ANTOINETTE:
Feminine diminutive form of French Antoine,
possibly meaning "invaluable."
ANTONETTE:
English diminutive form of Latin Antonia,
possibly meaning "invaluable."
ANTONIA: Feminine form of Roman Latin Antonius,
possibly meaning "invaluable." In use by
the English, Italians and Spanish. Compare with another
form of Antonia.
APRIL:
English name derived from the month name April, from Latin Aprilis,
from aperire, meaning "to open," in reference to the opening of
flowers in spring.
ARDEN:
English unisex name derived
from a place name meaning "eagle valley."
ARETHA:
American English name probably having the same etymology as Cornish Areta,
meaning
"excellence, virtue."
ARIADNE:
Latin form of Greek Ariadnê, meaning "utterly pure." In mythology,
this is the name of the daughter of King Minos.
ARIANA: English variant spelling of Italian Arianna,
meaning "utterly pure." Compare with another form of Ariana.
ARIEL: Anglicized
form of Hebrew unisex Ari'el, meaning "lion of god." In the bible, this is
a name applied to the city of Jerusalem, and the name of
a chief of the returning exiles. In the Apocrypha, this
is the name of an
archangel who rules the waters. It is also the name of a moon of Uranus,
and the name of a spirit in Shakespeare's play "The
Tempest."
ARIELLA
(אֲרִיאֵלָה): Feminine form of
English unisex Ariel, meaning "lion of
God."
ARIELLE:
Feminine form of English unisex Ariel,
meaning "lion of God."
ARIN:
Variant spelling of English Erin, meaning
"Ireland." Compare with masculine Arin.
ARISTA:
Feminine form of Latin Aristaeus,
meaning "excellence."
ARLEEN:
Variant spelling of English Arline, a short form of longer names
ending with -arlene or -arline.
ARLENE:
Variant spelling of English Arline, a
short form of longer names
ending with -arlene or -arline.
ARLETTE:
Probably a Norman French double diminutive form of the German word arn
"eagle," hence "tiny little eagle."
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A-Z
Baby Names
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Girl Names
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B, C,
D, E,
F, G,
H, I,
J, K,
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V, W,
X, Y,
Z
Boy
Names
A,
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Pet
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Names for your pets. Grouped by species.
Naming Tips &
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nips nips2010 nips2010-25 nips2010-25-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Sheng-jun Huang, Rong Jin, Zhi-hua Zhou
Abstract: Most active learning approaches select either informative or representative unlabeled instances to query their labels. Although several active learning algorithms have been proposed to combine the two criteria for query selection, they are usually ad hoc in ﬁnding unlabeled instances that are both informative and representative. We address this challenge by a principled approach, termed Q UIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an instance. Extensive experimental results show that the proposed Q UIRE approach outperforms several state-of -the-art active learning approaches. 1


 Who would have guessed that Mozart alias 'Wolfy' would be as jovial, irreverent and light hearted as this movie has made him out to be. I mean being German and a composer, and creating such operatic masterpieces as 'Don Giavanni' and 'Le nozze di Figaro' one would have thought perhaps a more serious and conservative man was behind the work; but if you listen carefully to Mozart's lighter and more playful compositions ie 'Der Holle Rache kocht in meinem Herzen from Act II Die Zauberflote' one can perhaps hear the laughter and joy that must have filled this musician's heart as he composed.
It must be a wonderful gift to be able to hear the structures of melody and harmony, chords and progressions swimming with the same fluidity as daily thought, and greater talent to be able to string together the chorus of sounds without having to place a single note down on paper. When the sound of music comes as easily as eating, sleeping and breathing we have arguably the greatest composer that mankind has known.
 His unique interpretation of the man is commendable, with the added signature of that laugh making this particular characterisation distinctive to say the least. F. Murray Abraham, is Antonio Salieri a rival composer of the time. He excels at giving scathing looks of jealousy; whose own tepid mediocrity pits him to blame God for bestowing the greater gift of music on another man. His resulting actions brings both raging revenge and regretful remorse. Also of note are the creative white wigs of that period, unfashionable now, but perhaps a foreseeable revival in the 21st century?
So perhaps we will never know the true 'Wolfgang Amadeus Mozart', but we still have his music to remind us of the man. Although he was extraordinary in terms of musical talent, it is evident in the movie, that he also carries the yearnings of a common man; and it is the miraculous transformation of these ordinary feelings of joy and despair, sorrow and laughter into the heartbeat of thoughtful notes, which sets him far above the rest.
Timothy Voon e-mail<EMAIL_ADDRESS>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


slaythespire
我们将卡牌游戏与Roguelike游戏融为一体，制作出了这款最棒的单机组牌游戏。打造出独一无二的牌组、遇见无数离奇的生物、发现威力强大的遗物、去屠戮这座高塔吧！
Stick Fight: The Game
Stick Fight is a physics-based couch/online fighting game where you battle it out as the iconic stick figures from the golden age of the internet.


Returns an oriented bounding box object.
| Name | Type | Default | Description |
|---|---|---|---|
x |
Number | 0 |
optional
The X coordinate of the upper-left corner of the obb. |
y |
Number | 0 |
optional
The Y coordinate of the upper-left corner of the obb. |
width |
Number | 0 |
optional
The width of this obb. |
height |
Number | 0 |
optional
The height of this obb. |
angle |
Number | 0 |
optional
The overall height of this obb. |
Members
-
The axes of this obb.
-
The center point of this obb.
-
The overall height range of this obb.
-
The overall width range of this obb.
Methods
-
Checks whether the aabb object given are contained within this obb.
Name Type Description aabb
AABB The aabb object of test
-
obb2aabb ()AABB
-
Transforms this object into a new AABB object and returns.
Returns:
Type Description AABB -
obb2sphere ()Sphere
-
Transforms this object into a new Sphere object and returns.
Returns:
Type Description Sphere -
Checks whether the obb object given are contained within this obb.
Name Type Description obb
OBB The obb object of test
-
Checks whether the point object given are contained within this obb.
Name Type Description point
Point The point object of test.
-
Get an array of point objects that span the four vertices of the obb.
Returns:
Type Description Array.<Point> -
Checks whether the sphere object given are contained within this obb.
Name Type Description sphere
Sphere The sphere object of test


Last Week in ManageIQ: API refactor, Observables and more!
Greetings from sunny Brno, Happy Martin here, from the UI team :).
Stats
Last week, we merged 112 PRs into master, consisting of 298 commits made by 49 people! Growing strong…
As always, everybody is welcome to contribute, see our issue tracker.
Improved
Convert API collections to individual controllers
Tim Wade has done an impressive amount of work refactoring our REST API code, converting collections to individual controllers, moving the entrypoint to ApiController, changing the namespace and removing custom routing, which may make it much easier to expand the API to manage all the things, REST style :).
Add missing gettext
Milan Zazrivec is pushing forward with our i18n efforts, this week by adding missing gettext, and restoring internationalization functionality in toolbars. If you want him to keep his sanity, please go through our i18n guidelines at least once a week, before bedtime.
For Middleware Server operations use Rx.js Observables for communication
Mike Thompson has been working in middleware code, this time to use RxJs Observables to talk to the toolbar, progress! :)
Fixed
Fix dev reload issues when Vmdb::Settings.reload! is called
Jason Frey and Chris Arcand have been busy in fixing-the-fix-to-fix-the-fix-land - this time to fix some reload issues and test failures after the recent changes to Vmdb::Settings. First, we skipped the failures, actually skipped the failures, then fixed the failures and the reload error in devel mode. Developers everywhere, rejoice!
Check the request format before setting the redirection after the login page
Yaacov Zamir has done a small but important fix to prevent an annoying routing error, when the user gets redirected to the login screen from a POST action. 1 error less, NaN
to go!
Force jasmine-core 2.4.1 instead of 2.5
Last week jasmine 2.5 also came out, making all our javascript tests fail because of an overly optimistic version constraint. Fixed shortly after by yours truly, cough shameless plug cough.
Fix enabling of toolbar components if item is selected in automate explorer
Karel Hála had recently converted our toolbars to angular and now he’s fixing the odd places where that didn’t quite work out, this time in Automate. Thanks for touching that :).
Add missing policy buttons to Network Manager Relationship pages
One of our newest colleagues, Hilda Šťastná has added a Policy toolbar button to all the places that should have it but didn’t. More tags for everyone !
New
Archived: Scope for not archived nor orphaned
Keenan Brock, our DB guru, has found an old TODO and has actually TODONE. (TODID?) Now, we have a scope for non-archived, non-orphaned VMs.
Authentication token for initiation web sockets
Šimon Lukašík has been working on making the websocket have its own authentication token, with some prior TokenManager changes. This being done, we should be well on the way towards asynchronous notifications via websockets, wheee.
API - add backend version info
People really seem to like our About dialog, so we’re bringing it to the Self-Service UI too. Just a small change from yours truly, adding some necessary info to the API entrypoint.
Deleted
Remove process_tasks methods from provider classes
Nick Carboni has found some more dead code, this time process_tasks
in a couple of provider classes .. aaand it’s gone, never to be seen again :).
Remove old “admintable” class table styling
Eric Winchell has been working on multiple old styling cleanups - admintable class, tagstable class, form buttons and checkboxes. Good riddance.
Removed unused report tree partials
David Halász has also found a couple of unused tree partials during his bootstrap tree work - and he promptly dispatched them to /dev/null
.
Wrapping up
Of course I missed most of the boring PRs doing some actual work, but feel free to check all of them out here. And stay tuned for even more exciting news next week :).


Horizontal
Inside Block Layout
Default
Custom padding
On Surface
Primary
Primary Container
Inverse Surface
Inverse Primary
Inside Flex Layout
Default
Custom padding
On Surface
Primary
Primary Container
Inverse Surface
Inverse Primary
Inside Block Inside Flex Layout
Default
Custom padding
On Surface
Primary
Primary Container
Inverse Surface
Inverse Primary
Vertical
Inside Flex Layout
Default
Custom padding
On Surface
Primary
Primary Container
Inverse Surface
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- Don’t do it
- The Emotion Dataset
- The effect of Emotion
- Post-hoc / Contrast Analysis
- Interaction
- Note
- Credits
Don’t do it
Ha! Got ya! Trying to run some old school ANOVAs hum? I’ll show you even better!
There is now a tremendous amount of data showing the inadequacy of ANOVAs as a statistical procedure (Camilli, 1987; Levy, 1978; Vasey, 1987; Chang, 2009). Instead, many papers suggest moving toward the mixed-modelling framework (Kristensen, 2004; Jaeger, 2008), which was shown to be more flexible, accurate, powerful and suited for psychological data.
Using this framework, we will see how we can very simply answer our questions with R and the psycho package.
The Emotion Dataset
Let’s take the example dataset included in the psycho
package.
library(psycho)
library(tidyverse)
df <- psycho::emotion %>%
select(Participant_ID,
Participant_Sex,
Emotion_Condition,
Subjective_Valence,
Recall)
summary(df)
Participant_ID Participant_Sex Emotion_Condition Subjective_Valence
10S : 48 Female:720 Negative:456 Min. :-100.000
11S : 48 Male :192 Neutral :456 1st Qu.: -65.104
12S : 48 Median : -2.604
13S : 48 Mean : -18.900
14S : 48 3rd Qu.: 7.000
15S : 48 Max. : 100.000
(Other):624
Recall
Mode :logical
FALSE:600
TRUE :312
Our dataframe (called df
) contains data from several participants, exposed to neutral and negative pictures (the Emotion_Condition
column). Each row corresponds to a single trial. As there were 48 trials per participants, there are 48 rows by participant. During each trial, the participant had to rate its emotional valence (Subjective_Valence
: positive - negative) experienced during the picture presentation. Moreover, 20min after this emotional rating task, the participant was asked to freely recall all the pictures he remembered.
Our dataframe contains, for each trial, 5 variables: the name of the participant (Participant_ID
), its sex (Participant_Sex
), the emotion condition (Emotion_Condition
), the valence rating (Subjective_Valence
) and whether the participant recalled the picture (Recall
).
The effect of Emotion
Does the emotion condition modulate the subjective valence? How to answer?
Whith a repeated measures ANOVA of course!
Let’s run it:
summary(aov(Subjective_Valence ~ Emotion_Condition + Error(Participant_ID/Emotion_Condition), data=df))
Error: Participant_ID
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 18<PHONE_NUMBER>
Error: Participant_ID:Emotion_Condition
Df Sum Sq Mean Sq F value Pr(>F)
Emotion_Condition 1 1278417 1278417 245.9 6.11e-12 ***
Residuals 18 93573 5198
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 874<PHONE_NUMBER>
Wow, we found that there is a significant effect of the emotional condition on valence ratings. We might have Science material here.
As you know, an ANOVA is pretty much a condensed linear model where the predictors are factors. Therefore, we can run an ANOVA on a linear mixed model (which includes the “error” term, or random effect).
library(lmerTest)
fit <- lmer(Subjective_Valence ~ Emotion_Condition + (1|Participant_ID), data=df)
anova(fit)
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Emotion_Condition 1278417 1278417 1 892 1108 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
As you can see, the results are, for the important bits (the sum of squares, mean square and p value), very close to those of the traditional approach.
Note that the psycho
package, through the analyze
function, also allows to display the interpretation of the underlying model itself with the following:
results <- analyze(fit)
print(results)
The overall model predicting Subjective_Valence (formula = Subjective_Valence ~ Emotion_Condition + (1 | Participant_ID)) successfully converged and explained 56.73% of the variance of the endogen (the conditional R2). The variance explained by the fixed effects was of 52.62% (the marginal R2) and the one explained by the random effects of 4.11%. The model's intercept is at -56.34 (SE = 2.88, 95% CI [-62.07, -50.61]). Within this model:
- The effect of Emotion_ConditionNeutral is significant (beta = 74.88, SE = 2.25, 95% CI [70.47, 79.29], t(892.00) = 33.29, p < .001***) and can be considered as medium (std. beta = 0.73, std. SE = 0.022).
Post-hoc / Contrast Analysis
Then, we wou’d like to see how the levels are different. To do this, we have to run a “contrast” analysis, comparing the estimated means of each level.
# We have to provide the model (here called fit and the factors we want to contrast
results <- get_contrasts(fit, "Emotion_Condition")
print(results$contrasts)
| Contrast | Difference | SE | df | t.ratio | p.value |
|---|---|---|---|---|---|
| Negative - Neutral | -74.88 | 2.25 | 892 | -33.29 | 0 |
It appears that the negative condition yields a significantly lower valence (i.e., more negative) than the neutral (-74.88 points of difference). At this point, we usually also want to know the means of each conditions. However, we often do it by directly computing the means and SDs of our observed data. But that’s not the cleanest way, as our data might be unbalanced or biased.
The best way to do it is to estimate means based on the fitted model (marginal means). Those were automatically computed when running the get_contrasts
function. We just have to extract them.
| Emotion_Condition | Mean | SE | df | CI_lower | CI_higher |
|---|---|---|---|---|---|
| Negative | -56.34 | 2.88 | 25.04 | -62.27 | -50.41 |
| Neutral | 18.54 | 2.88 | 25.04 | 12.61 | 24.47 |
Finally, we can plot these means:
library(ggplot2)
ggplot(results$means, aes(x=Emotion_Condition, y=Mean, group=1)) +
geom_line() +
geom_pointrange(aes(ymin=CI_lower, ymax=CI_higher)) +
ylab("Subjective Valence") +
xlab("Emotion Condition") +
theme_bw()
Interaction
Let’s repeat the previous steps with adding the participant’s sex as a predictor.
fit <- lmer(Subjective_Valence ~ Emotion_Condition * Participant_Sex + (1|Participant_ID), data=emotion)
anova(fit)
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value
Emotion_Condition<PHONE_NUMBER>63 1<PHONE_NUMBER>
Participant_Sex 520 520 1 17 0.4593
Emotion_Condition:Participant_Sex 20496 20496 1 891 18.1041
Pr(>F)
Emotion_Condition < 2.2e-16 ***
Participant_Sex 0.5071
Emotion_Condition:Participant_Sex 2.313e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
It seems that there is a significant main effect of the emotion condition, as well as an interaction with the participants’ sex. Let’s plot the estimated means.
estimated_means <- get_means(fit, "Emotion_Condition * Participant_Sex")
estimated_means
| Emotion_Condition | Participant_Sex | Mean | SE | df | CI_lower | CI_higher |
|---|---|---|---|---|---|---|
| Negative | Female | -59.73 | 3.28 | 23.3 | -66.51 | -52.95 |
| Neutral | Female | 20.05 | 3.28 | 23.3 | 13.27 | 26.83 |
| Negative | Male | -43.63 | 6.35 | 23.3 | -56.76 | -30.50 |
| Neutral | Male | 12.89 | 6.35 | 23.3 | -0.24 | 26.02 |
ggplot(estimated_means, aes(x=Emotion_Condition, y=Mean, color=Participant_Sex, group=Participant_Sex)) +
geom_line(position = position_dodge(.3)) +
geom_pointrange(aes(ymin=CI_lower, ymax=CI_higher),
position = position_dodge(.3)) +
ylab("Subjective Valence") +
xlab("Emotion Condition") +
theme_bw()
Let’s investigate the contrasts:
get_contrasts(fit, "Emotion_Condition * Participant_Sex")
| Contrast | Difference | SE | df | t.ratio | p.value |
|---|---|---|---|---|---|
| Negative,Female - Neutral,Female | -79.78 | 2.51 | 891.0 | -31.81 | 0.00 |
| Negative,Female - Negative,Male | -16.10 | 7.15 | 23.3 | -2.25 | 0.14 |
| Negative,Female - Neutral,Male | -72.62 | 7.15 | 23.3 | -10.16 | 0.00 |
| Neutral,Female - Negative,Male | 63.67 | 7.15 | 23.3 | 8.91 | 0.00 |
| Neutral,Female - Neutral,Male | 7.15 | 7.15 | 23.3 | 1.00 | 0.75 |
| Negative,Male - Neutral,Male | -56.52 | 4.86 | 891.0 | -11.64 | 0.00 |
It appears that the differences between men and women is not significant. However, by default, get_contrasts
uses the Tukey method for p value adjustment. We can, with an exploratory mindset, turn off the p value correction (or choose other methods such as bonferonni, fdr and such).
get_contrasts(fit, "Emotion_Condition * Participant_Sex", adjust = "none")
| Contrast | Difference | SE | df | t.ratio | p.value |
|---|---|---|---|---|---|
| Negative,Female - Neutral,Female | -79.78 | 2.51 | 891.0 | -31.81 | 0.00 |
| Negative,Female - Negative,Male | -16.10 | 7.15 | 23.3 | -2.25 | 0.03 |
| Negative,Female - Neutral,Male | -72.62 | 7.15 | 23.3 | -10.16 | 0.00 |
| Neutral,Female - Negative,Male | 63.67 | 7.15 | 23.3 | 8.91 | 0.00 |
| Neutral,Female - Neutral,Male | 7.15 | 7.15 | 23.3 | 1.00 | 0.33 |
| Negative,Male - Neutral,Male | -56.52 | 4.86 | 891.0 | -11.64 | 0.00 |
Without correcting for multiple comparisons, we observe that men rate the negative pictures as significantly less negative than women.
Note
This analysis is even simpler in the Bayesian framework. See this tutorial.
Credits
This package helped you? Don’t forget to cite the various packages you used :)
You can cite psycho
as follows:
- Makowski, (2018). The psycho Package: an Efficient and Publishing-Oriented Workflow for Psychological Science. Journal of Open Source Software, 3(22), 470. https://doi.org/10.21105/joss.00470
Previous blogposts
- Copy/paste t-tests Directly to Manuscripts
- APA Formatted Bayesian Correlation
- Fancy Plot (with Posterior Samples) for Bayesian Regressions
- How Many Factors to Retain in Factor Analysis
- Beautiful and Powerful Correlation Tables
- Format and Interpret Linear Mixed Models
- How to do Repeated Measures ANOVAs
- Standardize (Z-score) a dataframe
- Compute Signal Detection Theory Indices


Style Guide
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Audience Example
Name: Mark Age: 18 Motivations: Have a greater social media influence through enjoyable group activities. Goals: Better enjoy life even with restrictions of a pandemic.
Name: Jane Age: 27 Motivations: Expand her group of friends to more than co workers. Goals: Find those with similar likings.


set timer for 40 minutes
Although unguided or minimally guided instructional approaches are very popular and intuitively appealing … these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance.
And although fostering creativity and independence is intuitively alluring, it doesn’t mean that it works
With this said, however, some predictions can be made:
the next problem is also of the same type, but has more blanks, and so on until the learner is asked to solve the entire problem.
it encourages learners to think about similarities and differences between various approaches, which helps create linkages in the mental model that is trying to be relayed
#total_length(["red", "green", "blue"]) => 12
def total_length(words):
total = 0
for word in words:
total += len(word)
return total
# word_lengths(["red", "green", "blue"]) => [3, 5, 4]
def word_lengths(words):
lengths = ____
for word in words:
lengths ____
return lengths
Another step of fading might be this:
# concatenate_all(["red", "green", "blue"]) => "redgreenblue"
def concatenate_all(words):
result = ____
for ____ in ____:
____
return result
and finally learners would be asked to do:
# acronymize(["red", "green", "blue"]) => "RGB"
def acronymize(words):
____
##Create a Faded Example from a Lesson The following exercise should be done in groups of 2-3.
Pick a block of code from an existing Software or Data Carpentry lesson, or from another lesson you have taught recently. Replace 2-3 pieces of the code with a blank. Write a question to test the student’s ability to correctly fill in that blank. Take 10 minutes for this exercise. Paste your faded example in the Etherpad.
Then learners can be told they have all the lines they need except one and so forth.
Parson Problems
Pick a block of code from an existing Software or Data >2. Carpentry lesson, or from another lesson you have taught recently.
- Jumble the code
- Paste your jumbled code block into the etherpad
- Determine the correct order of your partner’s else’s code block


| Class | Description |
|---|---|
| AddInventoryItem |
AddInventoryItem class is an activity that add an item to owner's inventory.
|
| EditSingleItem |
EditSingleItem class is an activity that edit owner's single item.
|
| LaunchingPage |
LaunchingPage activity is designed for giving some basic user manual to current user.
|
| PreviousBrowsedTrade |
PreviousBrowsedTrade class is an activity that current user can browse his/her trade history.
|
| Search |
Search class is an activity that current user can search for a certain Friend.
|
| SingleFriendProfile |
SingleFriendProfile class is an activity that current user can check one of his friend's profile.
|
| UserFriends |
UserFriends class is an activity that showing all the current user's friends.
|
| UserInventory |
UserInventory class is an activity that showing all inventory items of current user.
|
| UserLogin |
userLogin class is an activity that current user login page with his/her user name.
|
| UserMainViewing |
UserMainViewing class is an activity that Navigates current user's requirement.
|
| UserProfile |
UserProfile class is an activity that showing current user's profile.
|
| UserRegister |
User register activity take user input and check the valid id, passwords
email, and city by calling controller method in UserController class.
|
| UserTrade |
UserTrade class is an activity that showing all trade request to the current user.
|


Index of classes
C
camera_model
[
Camera
]
The camera_model class applies advanced camera transformations before the data is rendered
P
particle_model
[
Particle
]
The particule model handles the logic for particle animation/interpolation see Camera


Created by Cameron Manavian / @camsjams
Promises are now a "standard" feature in JavaScript
When it comes to asynchronous requests or operations, tracking all successes and failures can become cumbersome.
step1(function (value1) {
step2(value1, function(value2) {
step3(value2, function(value3) {
step4(value3, function(value4) {
// Do something with value4
});
});
});
});
source: https://github.com/kriskowal/q
var step1 = new Promise(...);
step1.then(step2)
.then(step3)
.then(step4)
.then(function (value4) {
// Do something with value4
})
.catch(function (error) {
// Handle any error from any above steps
throw new Error('fatal error in promises:' + error.message);
});
Callbacks are the most common argument for event listeners or asynchronous functions.
userModel.getUserEmail(userId, function (err, email) {
// in callback, we have a error and value from function
if (err)
// handle error
// do something with value
mail.sendEmail(email, function(err, res) {
if (err)
// handle error
});
});
These style of functions takes some input and a callback to be invoked with some kind of output or error.
By extracting some of the nested callbacks out, we can simplify the code and proxy the value needed for later use.
getUserEmail(userId)
.then(mail.sendEmail)
.catch(function (error) {
// Handle any error thrown, handle rejections
});
The most notable improvement of using promises instead of nested callbacks is that you have an instance of an object that represents deferred work.
var emailPromise = getUserEmail(userId);
// code section one
emailPromise.then(sendEmail);
...
// later code
emailPromise.then(trackAnalytics);
Well ...
A promise to eventually having a value at some indeterminable point in the future.
They can be used for making multiple potentially long tasks operate within a synchronous set of instructions.
Wait what?
Every morning, Samwise asks Hodor to go out and collect food from the traps.
Hodor promises Samwise that he will go out and collect the trappings.
Hodor.Then Samwise decides that if:
Soon Hodor returns.
Different outcomes may have occurred.
- Source
@see also: parent presentation


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Our products and services are tailored to suit the specific demands of our clients. This high level of efficiency and reliability has led to a loyalty of our clientele as well as a progressive increase in our annual profits over time since inception. We have been able to measure tangible growth in our business so far, and can boast of our ability to maintain and even surpass these records due to our diligence, resilience and commitment to our work. Thus, we have working models that ensure that our profit margins increase over time.
We are keen on hiring young professionals with the right skill-sets required for the corporate work-space, making them strive to be the best for themselves and for the company. As a result, we have certain criteria for selection which helps us pick out the best fits for our organization. We select candidates who are diligent, innovative, pro-active, have the capacity for team-work, and can maintain a good work-life balance. We also understand that there is an increasing pool of unemployed graduates in the country, and while we are willing to make our contributions to society by lowering this number in the way we can, we are still very intentional about the candidates we select to be a part of our elite team. Thus, we pick only the best people to work with us, be it at entry level, or at professional level.


PhoneGap Dynamic Pages Demo
There are two examples for this demo.
Simple
: New page replaces current page.
Transition
: New page slides in from left to replace current page.


The intended delivery target of the content, for example "html", "pdf", or "epub". This attribute is a replacement for the now deprecated @print attribute.


Shopping_VariationType Class Reference
| Inherits from | NSObject |
| Conforms to | PicoBindable |
| Declared in | Shopping_VariationType.h Shopping_VariationType.m |
Overview
This element hold the values that define the SKU, StartPrice, Quantity, VariationDetails, and VariationSpecifics.
@ingroup ShoppingInterface
Tasks
-
sku
An SKU (stock keeping unit) is an identifier defined by a seller.
property
If you need to contact the seller to ask a question about a
particular variation, you can mention the SKU (if present) to help
the seller identify the variation you’re interested in.
Only returned if the seller chose to specify a SKU for the
variation. -
startPrice
The fixed price of all items identified by this variation.
property
For example, a “Blue, Large” variation price could be USD 10.00,
and a “Black, Medium” variation price could be USD 5.00.
Each variation has its own price, and the prices can
be different for each variation. This enables sellers to
provide discounts on certain variations without affecting the price
of others. Always returned) for multi-variation listings. -
quantity
The number of items available for sale that are associated
property
with this variation. -
variationSpecifics
A list of name/value pairs that uniquely identify the variation
property
within the listing. All variations specify the same set of
names, and each variation provides a unique combination of
values for those names. For example, if the items vary by color and
size, then every variation specifies Color and Size as names,
and no two variations can specify the same combination of
color and size values. Use this information to identify a
variation of interest when you communicate with
the seller.
If your application supports PlaceOffer (in the Trading API),
you use this information to uniquely identify the variation
that you want to purchase. -
quantitySold
Not used. See SellingStatus.QuantitySold instead.
property -
sellingStatus
Contains the variation’s current price and quantity sold.
property
Always returned when variations are present. -
discountPriceInfo
This container provides information for an item that has a Strikethrough Price
property
(STP) or a Minimum Advertised Price (MAP) discount pricing treatment. STP and MAP
applies to only fixed price, BIN items. STP is available on the US, UK, and German
(DE) sites, while MAP is available only on the US site.
Discount pricing is available to qualified sellers (and their associated developers) who
participate in the Discount Pricing Program. Once qualified, sellers receive a
“sepcial account flag” (SAF) that allows them to apply Discount Pricing to both MSKU
and Non-MSKU items. -
any
(public property)
property
Properties
any
(public property)
@property (nonatomic, retain) NSMutableArray *any
Discussion
(public property)
entry type : PicoAnyElement, wrapper for primitive anyelement
Declared In
Shopping_VariationType.h
discountPriceInfo
This container provides information for an item that has a Strikethrough Price
(STP) or a Minimum Advertised Price (MAP) discount pricing treatment. STP and MAP
applies to only fixed price, BIN items. STP is available on the US, UK, and German
(DE) sites, while MAP is available only on the US site.
Discount pricing is available to qualified sellers (and their associated developers) who
participate in the Discount Pricing Program. Once qualified, sellers receive a
“sepcial account flag” (SAF) that allows them to apply Discount Pricing to both MSKU
and Non-MSKU items.
@property (nonatomic, retain) Shopping_DiscountPriceInfoType *discountPriceInfo
Discussion
This container provides information for an item that has a Strikethrough Price
(STP) or a Minimum Advertised Price (MAP) discount pricing treatment. STP and MAP
applies to only fixed price, BIN items. STP is available on the US, UK, and German
(DE) sites, while MAP is available only on the US site.
Discount pricing is available to qualified sellers (and their associated developers) who
participate in the Discount Pricing Program. Once qualified, sellers receive a
“sepcial account flag” (SAF) that allows them to apply Discount Pricing to both MSKU
and Non-MSKU items.
type : class Shopping_DiscountPriceInfoType
Declared In
Shopping_VariationType.h
quantity
The number of items available for sale that are associated
with this variation.
@property (nonatomic, retain) NSNumber *quantity
Discussion
The number of items available for sale that are associated
with this variation.
type : NSNumber, wrapper for primitive int
Declared In
Shopping_VariationType.h
quantitySold
Not used. See SellingStatus.QuantitySold instead.
@property (nonatomic, retain) NSNumber *quantitySold
Discussion
Not used. See SellingStatus.QuantitySold instead.
type : NSNumber, wrapper for primitive int
Declared In
Shopping_VariationType.h
sellingStatus
Contains the variation’s current price and quantity sold.
Always returned when variations are present.
@property (nonatomic, retain) Shopping_SellingStatusType *sellingStatus
Discussion
Contains the variation’s current price and quantity sold.
Always returned when variations are present.
type : class Shopping_SellingStatusType
Declared In
Shopping_VariationType.h
sku
An SKU (stock keeping unit) is an identifier defined by a seller.
If you need to contact the seller to ask a question about a
particular variation, you can mention the SKU (if present) to help
the seller identify the variation you’re interested in.
Only returned if the seller chose to specify a SKU for the
variation.
@property (nonatomic, retain) NSString *sku
Discussion
An SKU (stock keeping unit) is an identifier defined by a seller.
If you need to contact the seller to ask a question about a
particular variation, you can mention the SKU (if present) to help
the seller identify the variation you’re interested in.
Only returned if the seller chose to specify a SKU for the
variation.
type : NSString, wrapper for primitive string
Declared In
Shopping_VariationType.h
startPrice
The fixed price of all items identified by this variation.
For example, a “Blue, Large” variation price could be USD 10.00,
and a “Black, Medium” variation price could be USD 5.00.
Each variation has its own price, and the prices can
be different for each variation. This enables sellers to
provide discounts on certain variations without affecting the price
of others. Always returned) for multi-variation listings.
@property (nonatomic, retain) Shopping_AmountType *startPrice
Discussion
The fixed price of all items identified by this variation.
For example, a “Blue, Large” variation price could be USD 10.00,
and a “Black, Medium” variation price could be USD 5.00.
Each variation has its own price, and the prices can
be different for each variation. This enables sellers to
provide discounts on certain variations without affecting the price
of others. Always returned) for multi-variation listings.
type : class Shopping_AmountType
Declared In
Shopping_VariationType.h
variationSpecifics
A list of name/value pairs that uniquely identify the variation
within the listing. All variations specify the same set of
names, and each variation provides a unique combination of
values for those names. For example, if the items vary by color and
size, then every variation specifies Color and Size as names,
and no two variations can specify the same combination of
color and size values. Use this information to identify a
variation of interest when you communicate with
the seller.
If your application supports PlaceOffer (in the Trading API),
you use this information to uniquely identify the variation
that you want to purchase.
@property (nonatomic, retain) Shopping_NameValueListArrayType *variationSpecifics
Discussion
A list of name/value pairs that uniquely identify the variation
within the listing. All variations specify the same set of
names, and each variation provides a unique combination of
values for those names. For example, if the items vary by color and
size, then every variation specifies Color and Size as names,
and no two variations can specify the same combination of
color and size values. Use this information to identify a
variation of interest when you communicate with
the seller.
If your application supports PlaceOffer (in the Trading API),
you use this information to uniquely identify the variation
that you want to purchase.
type : class Shopping_NameValueListArrayType
Declared In
Shopping_VariationType.h


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Elyas pushed for speed across the brown grass flatland as if trying to make up for the time spent with the Traveling People, setting a pace southward that had even Bela grateful to stop when twilight deepened. Despite his desire for haste, though, he took precautions he had not taken before. At night they had a fire only if there was dead wood already on the ground. He would not let them break so much as a twig off of a standing tree. The fires he made were small, and always hidden in a pit carefully dug where he had cut away a plug of sod. As soon as their meal was prepared, he buried the coals and replaced the plug. Before they set out again in the gray false dawn, he went over the campsite inch by inch to make sure there was no sign that anyone had ever been there. He even righted overturned rocks and straightened bent-down weeds. He did it quickly, never taking more than a few minutes, but they did not leave until he was satisfied.
Perrin did not think the precautions were much good against dreams, but when he began to think of what they might be good against, he wished it were only the dreams. The first time, Egwene asked anxiously if the Trollocs were back, but Elyas only shook his head and urged them on. Perrin said nothing. He knew there were no Trollocs close; the wolves scented only grass and trees and small animals. It was not fear of Trollocs that drove Elyas, but that something else of which even Elyas was not sure. The wolves knew nothing of what it was, but they sensed Elyas’s urgent wariness, and they began to scout as if danger ran at their heels or waited in ambush over the next rise.
The land became long, rolling crests, too low to be called hills, rising across their path. A carpet of tough grass, still winter sere and dotted with rank weeds, spread before them, rippled by an east wind th


Our classication model uses data from the UNCOVER COVID-19 Challenge to try and determine if commonly available blood tests can be used to accurately predict if a person has COVID-19. If successful, it could greatly assist in the fight against COVID-19 at a time when commercial COVID testing kits are in short supply.
Support-vector machines are supervised learning models that can be used for classification problems such as our COVID blood test dataset. We used the scikit-learn python library to build and tune our model.
Learn moreThe model is not accurate enough at this time to safely be used as a diagnosic tool for COVID-19.
Notice the low recall score of 5.1%, and the high number of samples the model incorrectly predicted did not have COVID. In this particular use case, we would prefer our model to skew to higher false positives rather then incorrectly predicted negatives. As it stands, using this model would result in a lot of people having a false sense of security, which would ultimatley undermine the effort to slow the spread of the virus.
| Accuracy Score | Precision | Recall | F1_Score |
|---|---|---|---|
| 90.9% | 70.0% | 5.1% | 10.0% |
| Predicted Negative | Predicted Positive | |
|---|---|---|
| Actual Negative | 1276 |
1 |
| Actual Positive | 127 |
7 |
SVM’s use hyperplanes to separate labeled points. When points can’t be separated by flat hyperplanes, as with our dataset, we map it in higher dimensional space using a non-linear kernel (in our case, a polynomial kernel). The SVC model finds the "best fit" hyperplane that divides, or categorizes, the data into either a “positive” or “negative” prediction.
SVM’s are more effective when data is linearly separable and less effective when the data is noisy and contains overlapping points. When the data has noise and overlapping points, there is a problem in drawing a clear hyperplane without misclassifying.
Due to incompleteness in the available dataset, we were forced to improvise by filling all missing data with the average value of each particular feature. This created a lot of overlapping points and hindered the model's performance.
Additionally, SVM's work better when the dataset contains a lot of positive labels. In our dataset, less then 10% of our data was labeled with a positive COVID result.
While we were disapointed in the results of this model, that doesn't mean all is lost. In fact, with growing testing capacity and more people being tested for COVID-19 every day, we can expect much more data in the near future. With a richer dataset, it is possible machine learning alogrthms could perform sufficiently well to serve as a stand-in should regular tests ever become scarce.


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Easing function linear easeInQuad easeOutQuad easeInOutQuad easeInCubic easeOutCubic easeInOutCubic easeInQuart easeOutQuart easeInOutQuart easeInQuint easeOutQuint easeInOutQuint from https://gist.github.com/gre/1650294


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When you work with us, you are a part of a team of committed collaborators. All aspects of our software development process are integrated , interactive and agile.
Our approach unifies design, development and product management to create exceptional products
We start each project by understanding your business goals, the users' needs and the product requirements
Then we help translate them into effective and elegant solutions
Before we sign a contract or write a line of code our team will spend the necessary time needed to understand your product vision
The outcome of this scoping session is proposal or high-level statement of work
based on your requirements, we can provide a complete offering or just pieces you need.
Our design practice offers a full range of services including brand strategy, interaction and visual design and user experience testing.
Throughout your project, our designers create and implement visual design and workflows, solicit user feedback and work with you to make sure what gets built is what is needed.
All engineers are fluent in the latest enterprise, mobile and web development technologies.
They collaborate with your team to write, and improve code on a daily basis, using proven practices such as test-driven development and pair programming.
Planning and development is iterative. Because we are constantly coding and testing, the products we build are always ready to go live.
This iterative process allows for changes as business requirements evolve
Black Studio
Ontario Security
Yellow Studio
Graphic Burger
Elena Newsletter
Calculator
Burned
Giraffe Restaurant


Context
CommBank intended to introduce a new health insurance product partnering with two other institutions. I was tasked to design a quick to market design solution.
Project Problems
My responsibility was to provide UX prototypes for the digital experience, but in research a few issues were identified that needed to be addressed:
- Budget constraints limited scope for development. There'd be multiple handovers between institutions and an inconsistent customer experience
- The partnership model lacked clarity around co-branding and would result in mixed messaging to customers
- The end-to-end customer experience was not considered in the quick to market solution
Phase 1 Solution
This was the solution that the business favoured in hopes of kick-starting sales:
Customer Problems Uncovered
Complexity and Confusion
Historically, health insurance (like most insurance) has been opaque, difficult to understand and complex. The rise of digital only players in the insurance space overseas demonstrates the attractiveness of insurance offerings that solve for complexity, value transparencuy and are digital first. CommBank's proposed product and distribution model would not meet any of these standards.
Unclear branding
A lack of clarity about the insurance provider would present customers with these kinds of questions:
- Who am I actually buying insurance from? CommBank, A or B?
- Which company do I call or contact when I have an issue?
- How do I manage claims that I have to make online for my extras?
Like most insurance, health insurance provides piece of mind in part through the reputation and guarantee of a reputable brand. The unclear branding would negate that intangible value.
Lack of value
One of CommBank's strengths is the concept of "everything in one place"; that a customer can manage all their products on digital through one account. It was unclear in budgets whether we could achieve this in the time frame required.
What I did
Given the amount of issues and what would likely be a poor product offering and customer experience, I went beyond my scope of work to:
- Map out a customer journey of a health insurance customer based on some research and annecdotes
- Design the service layer to illustrate how the customer would interact with each company at different touchpoints
- Designed a screen flow diagram to help stakeholders visualise the potential customer problems
Results & Next Steps
I presented the customer journey to senior stakeholders and there was agreement on pausing the project. The focus shifted back to the business to clarify the issues presented. This was an ideal outcome because:
- Launching a product with a poor customer experience was not going to deliver on business outcomes
- My stakeholders were able to use my designs to advocate for further planning
- Further work has been prioritised for after the business achieves clarity on branding and experience consistency
As of 2020, the product was launched as CommBank Life insurance partnership with AIA Australia.


# -*- coding: utf-8 -*-
"""
Created on Tue May 19 22:28:09 2020
@author: lansf
"""
from __future__ import absolute_import, division, print_function
import numpy as np
from vasp_dos import get_band_center
[docs]class PDOS_OVERLAP:
"""Class for calculating adsorbate-surface relative orbital overlap"""
def __init__(self, GAS_PDOS, REFERENCE_PDOS, adsorbate_index=[], site_index=[]):
"""
Parameters
----------
GAS_PDOS : vasp_dos.VASP_DOS
VASP_DOS object of gas phase calculation of adsorbate
REFERENCE_PDOS : vasp_dos.VASP_DOS
VASP_DOS object of reference adsorbate+surface system
adsorbate_index : list[int]
index (indices) of adsorbate atom(s) in REFERENCE_PDOS
site_index : list[int]
index (indices) of adsorbate atom(s) in REFERENCE_PDOS
Attributes
----------
emax : float
maximum energy level
Notes
-----
GAS_PDOS is used only to determine the number of orbitals that can
interact with the surface and to calculate relative orbital overlap with
projected density of adsorption sites without adsorbates.
"""
gas_index = list(range(GAS_PDOS.natoms))
gas_peak_energies, gas_peak_densities, gas_orbitals\
, gas_orbital_indices = self._get_mol_orbitals(GAS_PDOS, gas_index)
adsorbate_peak_energies, adsorbate_peak_densities, adsorbate_orbitals \
, adsorbate_orbital_indices \
= self._get_mol_orbitals(REFERENCE_PDOS, adsorbate_index)
gas_orbital_features\
= self._get_orbital_features(GAS_PDOS, gas_orbital_indices, gas_index)
adsorbate_orbital_features\
= self._get_orbital_features(REFERENCE_PDOS, adsorbate_orbital_indices\
, adsorbate_index)
orbital_scores = self._get_orbital_scores(gas_orbital_features\
, adsorbate_orbital_features)
self.gas_orbitals = gas_orbitals
self.gas_peak_energies = gas_peak_energies
self.gas_peak_densities = gas_peak_densities
#Use distance between similarity to get probability
#take logit of probability https://en.wikipedia.org/wiki/Logit
#take softmax of logit functions https://en.wikipedia.org/wiki/Softmax_function
#find which adsorbate orbital matches a give gas orbital (give adsorbate orbital can match more than one gas orbital)
[docs] def _get_mol_orbitals(self, PDOS, atom_indices):
""" molecular orbitals as an M x ndos array
Parameters
----------
PDOS : vasp_dos.VASP_DOS
VASP_DOS object of gas or surface phase calculation of adsorbate
atom_indices : list
indices of atoms to include in the TOTAL DOS. If empty, then all
atoms are included (as for the gas)
Returns
-------
peak_energies : float or numpy.ndarray
peak energy(s) of molecular orbital(s)
peak_densities : float or numpy.ndarray
peak density(ies) of molecular orbital(s)
mol_orbitals : numpy.ndarray
M x ndos 2D array where M is the number of molecular orbitals and
ndos is the number of gridpoints for the density of states
orbital_indices : list[numpy.ndarray]
Length M list of non-zero orbital indices
"""
TOTAL_DOS = np.zeros(PDOS.ndos)
#sum over projected density of states for each atom
orbital_list = [key for key in PDOS.orbital_dictionary.keys()]
for atom in atom_indices:
orbital_list, projected_dos = PDOS.get_site_dos(atom, orbital_list)
TOTAL_DOS += projected_dos.sum(axis=0)
#obtain all local maxima (including endpoints)
peaks = np.r_[True, TOTAL_DOS[1:] > TOTAL_DOS[:-1]]\
& np.r_[TOTAL_DOS[:-1] > TOTAL_DOS[1:], True]
#endpoints should be zero density
all_indices = np.arange(PDOS.ndos)
peak_indices = all_indices[peaks]
peak_energies = PDOS.get_energies()[peak_indices]
peak_densities = TOTAL_DOS[peak_indices]
if peak_indices.size == 1:
mol_orbitals = TOTAL_DOS
orbital_indices = all_indices
else:
mol_orbitals = np.zeros((peak_indices.size,TOTAL_DOS.size))
orbital_indices = []
midpoints = (0.5 * peak_indices[0:-1] + 0.5 * peak_indices[1:]).astype(int)
mol_orbitals[0][0:midpoints[0]] = TOTAL_DOS[0:midpoints[0]]
orbital_indices.append(all_indices[0:midpoints[0]])
for i in range(midpoints.size-1):
mol_orbitals[i+1][midpoints[i]:midpoints[i+1]] = TOTAL_DOS[midpoints[i]:midpoints[i+1]]
orbital_indices.append(all_indices[midpoints[i]:midpoints[i+1]])
mol_orbitals[-1][midpoints[-1]:] = TOTAL_DOS[midpoints[-1]:]
orbital_indices.append(all_indices[midpoints[-1]:])
return peak_energies, peak_densities, mol_orbitals, orbital_indices
[docs] def _get_orbital_features(self, PDOS, orbital_indices, atom_indices=[]):
""" molecular orbitals as an M x ndos array
Parameters
----------
PDOS : vasp_dos.VASP_DOS
VASP_DOS object of gas or surface phase calculation of adsorbate
atom_indices : list
indices of atoms to include in the TOTAL DOS. If empty, then all
atoms are included (as for the gas)
orbital_indices : list[numpy.ndarray]
Length M list of non-zero orbital indices
Returns
-------
orbital_features : numpy.ndarray
M x n_features 2D array where M is the number of molecular orbitals
and n_features is the number of orbital features for calculating
orbital similarity. Includes molecular orbital energy center and
integrated s, p, and d molecular orbital density of states
"""
num_orbitals = len(orbital_indices)
energies = PDOS.get_energies()
orbital_list = [key for key in ['s', 'p', 'd', 'f',] if key in PDOS.orbital_dictionary.keys()]
feature_levels = ['s','p','d']
TOTAL_DOS = np.zeros(PDOS.ndos)
TOTAL_PDOS = np.zeros((3,PDOS.ndos))
#sum over projected density of states for each atom
for atom in atom_indices:
orbital_list, projected_dos = PDOS.get_site_dos(atom, orbital_list, sum_density=True)
TOTAL_DOS += projected_dos.sum(axis=0)
for count, value in enumerate(feature_levels):
if value in orbital_list:
TOTAL_PDOS[count] += projected_dos[orbital_list.index(value)]
orbital_features = np.zeros((num_orbitals,4))
for count, index_values in enumerate(orbital_indices):
orbital_features[count][0] = get_band_center(energies[index_values],TOTAL_DOS[index_values])
for count2, feature_level in TOTAL_PDOS:
orbital_features[count][count2+1] = np.trapz(feature_level[index_values], energies[index_values])
return orbital_features
[docs] def _get_orbital_scores(self, gas_orbital_features, adsorbate_orbital_features):
""" molecular scores as an M x N array
Parameters
----------
gas_orbital_features : numpy.ndarray
gas orbital features
adsorbate_orbital_features : numpy.ndarray
adsorbate orbital features
Returns
-------
orbital_scores : numpy.ndarray
M x N 2D array where M is the number of gas molecular orbitals
and N is the number of adsorbate molecular orbitals
"""
num_gas_orbitals = gas_orbital_features.shape[0]
num_ad_orbitals = adsorbate_orbital_features.shape[0]
orbital_scores = np.zeros((num_gas_orbitals,num_ad_orbitals))
min_features = np.min(np.concatenate((gas_orbital_features\
, adsorbate_orbital_features)\
, axis=0), axis=0)
max_features = np.max(np.concatenate((gas_orbital_features\
, adsorbate_orbital_features)\
, axis=0), axis=0)
feature_range = max_features - min_features
feature_range[feature_range[...] == 0] =1
for count in num_gas_orbitals:
diff = adsorbate_orbital_features - gas_orbital_features[count]
norm_diff = diff / feature_range
RMSE = np.sum(norm_diff**2, axis=1)**0.5
orbital_scores[count] = RMSE
return orbital_scores


Bloomberg spending $15M-$20M to register half million voters in swing states, including Wisconsin
WASHINGTON - As he moves toward a presidential announcement, New York billionaire Michael Bloomberg is rolling out plans to spend an estimated $15 million to $20 million on a voter registration drive designed to weaken President Donald Trump's reelection chances in five battleground states.
The large investment was confirmed Wednesday by Bloomberg's team. It comes less than a week after the former New York City mayor unveiled a $100 million online advertising campaign attacking Trump in four general election swing states as well.
The new effort will target 500,000 voters from traditionally underrepresented groups that typically lean Democratic, including African Americans, Latinos, Asians and young voters. The drive will begin early next year in Arizona, Michigan, North Carolina, Texas and Wisconsin, but could expand to more states.


{# Copyright 2010 Google Inc. All Rights Reserved. #} {% comment %} Project statistics. Displays some statistics about the MOE project. NOTE(nicksantos): 2/24/11: This is currently broken. Author<EMAIL_ADDRESS>(Drew Haven) {% endcomment %} {% extends "base.html" %} {% block title %} Project Statistics for {{ project_name }} {% endblock %} {% block body %} {% if weekly_stats %}
manage_codebases was run {{ weekly_stats.times_run }} times for a total time of {{ weekly_stats.time_spent }}. There were {{ weekly_stats.migrations_started }} migrations started in that time.
| Exports | Imports |
|---|---|
|
|
Took place: {{score.last_run.value}}
| Process | {{ last_process.process_id }} |
| Start Time | {{ last_process.StartTimeString }} |
| End Time | {{ last_process.EndTimeString }} |
| Elapsed Time | {{ last_process.ElapsedTimeString }} |


A multiplayer painting application where players reveal one pixel of a picture at a time. Status: In Production
A quick guide on ActionScript 3.0 Status: Published
A "basic fact" Alexa skill about Call of Duty Black Ops Zombies. It contiains relatively obscure yet helpful tips.Status: Unpublished
A Twitter profile for Marlin from Finding Nemo that automatically replies to users when they tweet the word "boat".Status: Published
A website that sorts through a list of sandwiches from an API.Status: Published


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java.lang.Object org.simpleframework.xml.stream.CamelCaseStyle
public class CamelCaseStyle
The CamelCaseStyle
is used to represent an XML style
that can be applied to a serialized object. A style can be used to
modify the element and attribute names for the generated document.
This styles can be used to generate camel case XML.
<ExampleElement> <ChildElement exampleAttribute='example'> <InnerElement>example</InnerElement> </ChildElement> </ExampleElement>Above the camel case XML elements and attributes can be generated from a style implementation. Styles enable the same objects to be serialized in different ways, generating different styles of XML without having to modify the class schema for that object.
| Constructor Summary | |
|---|---|
CamelCaseStyle()
Constructor for the CamelCaseStyle object. |
|
CamelCaseStyle(boolean element)
Constructor for the CamelCaseStyle object. |
|
CamelCaseStyle(boolean element,
boolean attribute)
Constructor for the CamelCaseStyle object. |
| Method Summary | |
|---|---|
java.lang.String |
getAttribute(java.lang.String name)
This is used to generate the XML attribute representation of the specified name. |
java.lang.String |
getElement(java.lang.String name)
This is used to generate the XML element representation of the specified name. |
void |
setAttribute(java.lang.String name,
java.lang.String value)
This is used to set the attribute values within this builder. |
void |
setElement(java.lang.String name,
java.lang.String value)
This is used to set the element values within this builder. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public CamelCaseStyle()
CamelCaseStyle
object. This
is used to create a style that will create camel case XML
attributes and elements allowing a consistent format for
generated XML. By default the elements have an upper case
initial character and a lower case attribute.
public CamelCaseStyle(boolean element)
CamelCaseStyle
object. This
is used to create a style that will create camel case XML
attributes and elements allowing a consistent format for
generated XML. By default the attributes have a lower case
initial character and an configurable element.
element
- if true the element will start as upper casepublic CamelCaseStyle(boolean element, boolean attribute)
CamelCaseStyle
object. This
is used to create a style that will create camel case XML
attributes and elements allowing a consistent format for
generated XML. Both the attribute an elements are configurable.
element
- if true the element will start as upper caseattribute
- if true the attribute starts as upper case| Method Detail |
|---|
public java.lang.String getAttribute(java.lang.String name)
getAttribute
in interface Style
name
- this is the attribute name that is to be styled
public void setAttribute(java.lang.String name, java.lang.String value)
name
- the name of the XML attribute to be overriddenvalue
- the value that is to be used for that attributepublic java.lang.String getElement(java.lang.String name)
getElement
in interface Style
name
- this is the element name that is to be styled
public void setElement(java.lang.String name, java.lang.String value)
name
- the name of the XML element to be overriddenvalue
- the value that is to be used for that element
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The application layer is where network applications and their application-layer protocols reside. The application-layer protocol is distributed over multiple end systems, with the application in one end system using the protocol to exchange packets of information, called messages, with the application in another end system. Some of these protocols include:
The transport layer transports application-layer messages, called segments, between application endpoints. There are two transport protocols:
The network layer is repsonsible for moving network-layer packets, called datagrams, from one host to another. The transport-layer protocol in a source host passes a transport-layer segment and a destination address to the network-layer. The network-layer then provides the service of delivering the segment to the transport-layer in the destination host. The internet's network layer includes the IP protocol, which defines the fields in the datagram as well as how the end systems and routers act on these fields.
The network-layer routes datagrams through a series of routers between the source and destination. To move a packet from one node to the next node in the route, the network-layer relies on the link-layer. At each node, the network-layer passes the datagrams down to the link layer, which delivers the packets, called frames, to the next node along the route. Examples of link-layer protocols include:
The physical layer moves the individual bits within the frame from one node to the next. The protocols in this layer are link-dependent and further depend on the actual transmission medium of the link. Examples of these mediums are:


Full stack software developer
From a very young age I've been fascinated with all things web and technology. I've also had a life-long interest in creative and artistic endeavors, and I take great delight in learning and honing new skills toward manifesting those creative expressions. In my time after High School I worked many service related jobs where I acquired a strong customer service acumen.
Before long the itch to dive into the tech-field grew too strong to ignore any longer and I partook in the Emerging Digital Academy program where I was able to learn the essential coding and project management skills to take my first steps into working in the field which has interested me so long. During my time there I was exposed to HTML, CSS, JavaScript, JQuery, React, Redux, Node, Postgres, C#, Git Workflows, Heroku, and many others.
I hope to continue this journey of discovery and learning of these fascinating technologies.
Here are just a few of the projects I've worked on.


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Maze
DescriptionA program for the Raspberry Pi that presents a maze on an HDMI monitor. Red is used to represent the player as they move through the maze on the pathways. When the player reaches the exit of the maze, they are redisplayed in green, indicating that the maze has been solved and the game is over.
The program uses a SNES controller connected to the Raspberry Pi to control the movement of the player through the maze. When your program starts up, it displays the maze, but not the position of the player. When the user presses the controller start button, the player appears in red in the starting position. The joypad arrow buttons are used to move the player one position to the left, right, up, or down. The player can only move on the pathways, and is not allowed to go through any walls or leave the playing area. When the player reaches the exit of the maze they can press the start button to restart the game.


001 /* 002 * Licensed to the Apache Software Foundation (ASF) under one 003 * or more contributor license agreements. See the NOTICE file 004 * distributed with this work for additional information 005 * regarding copyright ownership. The ASF licenses this file 006 * to you under the Apache License, Version 2.0 (the 007 * "License"); you may not use this file except in compliance 008 * with the License. You may obtain a copy of the License at 009 * 010 * http://www.apache.org/licenses/LICENSE-2.0 011 * 012 * Unless required by applicable law or agreed to in writing, 013 * software distributed under the License is distributed on an 014 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY 015 * KIND, either express or implied. See the License for the 016 * specific language governing permissions and limitations 017 * under the License. 018 */ 019 package org.apache.shiro.authc.pam; 020 021 import org.apache.shiro.authc.AuthenticationException; 022 import org.apache.shiro.authc.AuthenticationInfo; 023 import org.apache.shiro.authc.AuthenticationToken; 024 import org.apache.shiro.realm.Realm; 025 026 import java.util.Collection; 027 028 029 /** 030 * A {@code AuthenticationStrategy} implementation assists the {@link ModularRealmAuthenticator} during the 031 * log-in process in a pluggable realm (PAM) environment. 032 * 033 *
The {@code ModularRealmAuthenticator} will consult implementations of this interface on what to do during each 034 * interaction with the configured Realms. This allows a pluggable strategy of whether or not an authentication 035 * attempt must be successful for all realms, only 1 or more realms, no realms, etc. 036 * 037 * @see AllSuccessfulStrategy 038 * @see AtLeastOneSuccessfulStrategy 039 * @see FirstSuccessfulStrategy 040 * @since 0.2 041 */ 042 public interface AuthenticationStrategy { 043 044 /** 045 * Method invoked by the ModularAuthenticator signifying that the authentication process is about to begin for the 046 * specified {@code token} - called before any {@code Realm} is actually invoked. 047 * 048 *
The {@code AuthenticationInfo} object returned from this method is essentially an empty place holder for 049 * aggregating account data across multiple realms. It should be populated by the strategy implementation over the 050 * course of authentication attempts across the multiple realms. It will be passed into the 051 * {@link #beforeAttempt} calls, allowing inspection of the aggregated account data up to that point in the 052 * multi-realm authentication, allowing any logic to be executed accordingly. 053 * 054 * @param realms the Realms that will be consulted during the authentication process for the specified token. 055 * @param token the Principal/Credential representation to be used during authentication for a corresponding subject. 056 * @return an empty AuthenticationInfo object that will populated with data from multiple realms. 057 * @throws AuthenticationException if the strategy implementation does not wish the Authentication attempt to execute. 058 */ 059 AuthenticationInfo beforeAllAttempts(Collection<? extends Realm> realms, AuthenticationToken token) throws AuthenticationException; 060 061 /** 062 * Method invoked by the ModularAuthenticator just prior to the realm being consulted for account data, 063 * allowing pre-authentication-attempt logic for that realm only. 064 * 065 *
This method returns an {@code AuthenticationInfo} object that will be used for further interaction with realms. Most 066 * implementations will merely return the {@code aggregate} method argument if they don't have a need to 067 * manipulate it. 068 * 069 * @param realm the realm that will be consulted for {@code AuthenticationInfo} for the specified {@code token}. 070 * @param token the {@code AuthenticationToken} submitted for the subject attempting system log-in. 071 * @param aggregate the aggregated AuthenticationInfo object being used across the multi-realm authentication attempt 072 * @return the AuthenticationInfo object that will be presented to further realms in the authentication process - returning 073 * the {@code aggregate} method argument is the normal case if no special action needs to be taken. 074 * @throws org.apache.shiro.authc.AuthenticationException 075 * an exception thrown by the Strategy implementation if it wishes the login 076 * process for the associated subject (user) to stop immediately. 077 */ 078 AuthenticationInfo beforeAttempt(Realm realm, AuthenticationToken token, AuthenticationInfo aggregate) throws AuthenticationException; 079 080 /** 081 * Method invoked by the ModularAuthenticator just after the given realm has been consulted for authentication, 082 * allowing post-authentication-attempt logic for that realm only. 083 * 084 *
This method returns an {@code AuthenticationInfo} object that will be used for further interaction with realms. Most 085 * implementations will merge the {@code singleRealmInfo} into the {@code aggregateInfo} and 086 * just return the {@code aggregateInfo} for continued use throughout the authentication process.
 087 * 088 * @param realm the realm that was just consulted for {@code AuthenticationInfo} for the given {@code token}. 089 * @param token the {@code AuthenticationToken} submitted for the subject attempting system log-in. 090 * @param singleRealmInfo the info returned from a single realm. 091 * @param aggregateInfo the aggregate info representing all realms in a multi-realm environment. 092 * @param t the Throwable thrown by the Realm during the attempt, or {@code null} if the method returned normally. 093 * @return the AuthenticationInfo object that will be presented to further realms in the authentication process - returning 094 * the {@code aggregateAccount} method argument is the normal case if no special action needs to be taken. 095 * @throws AuthenticationException an exception thrown by the Strategy implementation if it wishes the login process 096 * for the associated subject (user) to stop immediately. 097 */ 098 AuthenticationInfo afterAttempt(Realm realm, AuthenticationToken token, AuthenticationInfo singleRealmInfo, AuthenticationInfo aggregateInfo, Throwable t) 099 throws AuthenticationException; 100 101 /** 102 * Method invoked by the ModularAuthenticator signifying that all of its configured Realms have been consulted 103 * for account data, allowing post-proccessing after all realms have completed. 104 * 105 *
Returns the final AuthenticationInfo object that will be returned from the Authenticator to the authenticate() caller. 106 * This is most likely the aggregate AuthenticationInfo object that has been populated by many realms, but the actual return value is 107 * always up to the implementation. 108 * 109 * @param token the {@code AuthenticationToken} submitted for the subject attempting system log-in. 110 * @param aggregate the aggregate {@code AuthenticationInfo} instance populated by all realms during the log-in attempt. 111 * @return the final {@code AuthenticationInfo} object to return to the Authenticator.authenticate() caller. 112 * @throws AuthenticationException if the Strategy implementation wishes to fail the authentication attempt. 113 */ 114 AuthenticationInfo afterAllAttempts(AuthenticationToken token, AuthenticationInfo aggregate) throws AuthenticationException; 115 }


Click two nodes to show their connections
Click on a row to show the sentences
For links with subject-predicate-object structure
Please select a connection between two entities


使用th:if和th:unless属性进行条件判断，下面的例子中，标签只有在th:if中条件成立时才显示：
th:href="@{/exercise/2}" th:unless=${count == 2}
th:href="@{/exercise/2}" th:if=${count=="2"}
引入URL1
引入URL2
th:switch="${count}"
th:case="1" User is an administrator
th:case="2" User is a manager
th:case="*" User is some other thing
User is an administrator
User is a manager
User is some other thing


The Great Emu War
Lest we forget Australia's most devastating loss
Background
The Great Emu War was a military operation undertaken in Australia over the latter part of 1932 to address public concern over the number of emus said to be running amok in the Campion district of Western Australia. While many the birds were killed, the emu population persisted and continued to cause crop destruction.
Quick Facts
| Date | 02 November - 10 December 1932 |
|---|---|
| Location | Campion, Western Australia |
| Participants |
|
| Enemy Combatants | Emus |
| Outcome | Failure (Decisive Emu Victory) |
Prelude to the War
Following World War I, large numbers of ex-soldiers from Australia, along with a number of British veterans, were given land by the Australian government to take up farming within Western Australia, often in marginal areas. With the onset of the Great Depression in 1929, these farmers were encouraged to increase their wheat crops, with the government promising—and failing to deliver—assistance in the form of subsidies. Despite the recommendations and the promised subsidies, wheat prices continued to fall, and by October 1932 matters were becoming intense, with the farmers preparing to harvest the season's crop while simultaneously threatening to refuse to deliver the wheat.
The Enemy Emerges
The difficulties facing farmers were increased by the arrival of as many as 20,000 emus. Emus regularly migrate after their breeding season, heading to the coast from the inland regions. With the cleared land and additional water supplies being made available for livestock by the West Australian farmers, the emus found that the cultivated lands were good habitat, and they began to foray into farm territory—in particular the marginal farming land around Chandler and Walgoolan. The emus consumed and spoiled the crops, as well as leaving large gaps in fences where rabbits could enter and cause further problems.
Australia Responds
Farmers relayed their concerns about the birds ravaging their crops, and a deputation of ex-soldiers were sent to meet with the Minister of Defence, Sir George Pearce. Having served in World War I, the soldier-settlers were aware of the effectiveness of machine guns, and they requested their deployment. The minister readily agreed, although with conditions attached:
- the guns were to be used by military personnel
- troop transport was to be financed by the Western Australian government
- the farmers would provide food, accommodation, and payment for the ammunition
Pearce also supported the deployment on the delusional grounds that the birds would make good target practice. It was not until years later that Pearce admitted he could not have possibly predicted the chaos that awaited his forces.
... Eventually
Military involvement was due to begin in October 1932. The operation was delayed, however, by a period of rainfall that caused the emus to scatter over a wider area.
Chaos on the Battlefield
The 'war' was conducted under the command of Major G.P.W. Meredith of the Seventh Heavy Battery of the Royal Australian Artillery, with Meredith commanding soldiers Sergeant S. McMurray and Gunner J. O'Hallora, armed with two Lewis guns and 10,000 rounds of ammunition.
2 November
On 2 November, the men travelled to Campion, where some 50 emus were sighted. However, the birds split into small groups and ran so that they were difficult to target. While the first fusillade from the machine guns was ineffective due to the range, a second round of gunfire was able to kill "a number" of birds.
4 November
The next significant event was on 4 November. Meredith had established an ambush near a local dam, and more than 1,000 emus were spotted heading towards their position. This time, the gunners waited until the birds were in proximity before opening fire. The gun jammed after only twelve birds were killed and the remainder scattered before any more could be shot. No more birds were sighted that day.
6 November
By the fourth day of the campaign, army observers noted that "each pack seems to have its own leader now – a big black-plumed bird which stands fully six feet high and keeps watch while his mates carry out their work of destruction and warns them of our approach." (See figure below.)
At one stage Meredith even went so far as to mount one of the guns on a truck: a move that proved to be ineffective, as the truck was unable to gain on the birds, and the ride was so rough that the gunner was unable to fire any shots.
8 November
By 8 November, six days after the first engagement, 2,500 rounds of ammunition had been fired. The number of birds killed is uncertain: one account estimates that it was 50 birds.
That day, Pearce withdrew the military personnel and the guns.
Aftermath
Summarising the culls, ornithologist Dominic Serventy commented:
The machine-gunners' dreams of point-blank fire into serried masses of Emus were soon dissipated. The Emu command had evidently ordered guerrilla tactics, and its unwieldy army soon split up into innumerable small units that made use of the military equipment uneconomic. A crestfallen field force therefore withdrew from the combat area after about a month.
After the withdrawal, Major Meredith commented on the striking manoeuvrability of the emus, even while badly wounded.
If we had a military division with the bullet-carrying capacity of these birds it would face any army in the world... They can face machine guns with the invulnerability of tanks.
Further Reading
Burton, Adrian (1 August 2013). "Tell me, mate, what were emus like?". Frontiers in Ecology and the Environment. 11 (6): 336.
Johnson, Murray (2006). "'Feathered foes': soldier settlers and Western Australia's 'Emu War' of 1932". Journal of Australian Studies. 30 (88): 147–157.
"Machine Guns Sent Against Emu Pests". The Argus. 3 November 1932. p. 2.
"Elusive Emus". The Argus. 5 November 1932. p. 4.
"War on Emus". The Argus. 10 November 1932. p. 8.


Slick Lightbox jQuery plugin http://mreq.github.io/slick-lightbox/
Copyright 2014-2016 mreq https://github.com/mreq
Released under the MIT license
Documentation generated by CoffeeDoc
The core class.
Binds the plugin.
Creates the lightbox, opens it, binds events and calls slick
. Accepts index
of the element, that triggered it (so that we know, on which slide to start slick).
Creates individual slides to be used with slick. If options.images
array is specified, it uses it's contents, otherwise loops through elements' options.itemSelector
.
Creates a slick
-friendly modal.
Runs slick by default, using options.slick
if provided. If options.slick
is a function, it gets fired instead of us initializing slick. Merges in initialSlide option.
Opens the lightbox.
Closes the lightbox and destroys it, maintaining the original element bindings.
Binds global events.
Moves the slick prev or next.
Detects usage of IE8 and lower.
Returns caption for each slide based on the type of options.caption
.
Returns src for each slide image based on the type of options.src
.
Unbinds global events.
Destroys the lightbox and unbinds global events. If true
is passed as an argument, unbinds the original element as well.
Destroys lightboxes currently in DOM.
Detects the transition duration to know when to remove stuff from DOM etc.
Writes an empty state to the history API if supported.
Removes all slick clones from the set of elements. Only does so, if the target element is a slick slider.


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: click to save avocado,
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