British EuroMillions winner comes forward to claim huge £105million jackpot
The lucky EuroMillions ticket-holder is one of the biggest-ever British lottery winners after scooping a £105million jackpot in the draw last Tuesday night
by Chris Kitching, https://www.mirror.co.uk/authors/chris-kitching/A single ticket-holder has come forward to claim the £105million EuroMillions jackpot prize won on Tuesday night.
The win makes the lucky Brit one of the biggest-ever lottery winners in the UK.
The winner's identity is still a mystery - it could stay that way if they choose to remain anonymous - and their prize has not yet been paid out as the ticket cannot be validated until Monday morning.
Six lucky Brits have won big in the EuroMilllions so far this year in what has been a highly successful year for UK punters.
Andy Carter, senior winners' adviser at the National Lottery, said: "This is the sixth massive EuroMillions jackpot win in 2019 and follows the nation's biggest ever win of £170million just last month.
Do you know the lucky EuroMillions winner? Email<EMAIL_ADDRESS>"We now focus on supporting the ticket-holder as they start to enjoy their new-found wealth."
A EuroMillions spokesperson said: "The prize will be paid out at the ticket validation appointment.
"The ticket-holder will then decide whether or not to go public and share their news.
"There will be no information on whether it is an individual or syndicate winner, or where the ticket was purchased, unless the ticket-holder decides to go public."
Britain could have another big winner on Saturday night, with a £25million Lotto jackpot that must be won.
The EuroMillions spokesperson added: "This is the sixth EuroMillions jackpot win in the UK this year and further adds to the 5,500 millionaires made by the National Lottery since it launched."
Patrick and Frances Connolly, from Northern Ireland, won £114.9million on EuroMillions in the draw on New Year’s Day.
Ade Goodchild scooped £71million in March and an anonymous ticket-holder bagged £38.2million in April.
In June, a ticket-holder who chose to remain anonymous won £123million.
Last month the country’s biggest ever winner was made when an anonymous ticketholder scooped £170million.
The previous biggest winners in the UK were Colin and Chris Weir, from Largs, North Ayrshire, who won £161million in July 2011.


Diabetes Prediction
{{pred}}
Know the probability of having Diabetes
Glucose
Age
BMI
Pregnancies
Insulin
Predict Probability
This application is developed using RandomForest Classifier Model with an accuracy of 82.4%


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Open And Close Chrome Tabs On Android With These New Shortcuts
by Brendan HesseMobile browsers are better than ever, but they’re still cumbersome to use when compared to the desktop versions. Managing open tabs on Chrome, for example, is mindlessly easy on desktop but fiddly on mobile. Google has been making changes to the way tabs work on mobile over the past year, but the most recent update adds a new feature that makes opening and closing browser tabs much easier on Android devices.
Users can now long-press the URL bar to open a new quick-access menu with shortcuts to:
- Close the current tab.
- Open a new tab.
- Swap to incognito mode.
The menu was previously unlockable by messing with the browser flags settings but is now available by default to all users. That said, you’ll need to upgrade to Chrome 78 for Android to use the new shortcut menu—check the Chrome app page on the Google Play Store to see if you need to install the new update.


Select this element, drag it to the Drop Zone and then release the selection to move the element.
Drop Zone
Status:
Drag to start
Data is:
uninitialized


Parties like Daybreaker really show how much fun you can have sober
Do I need coffee? No, I'm going to be energized by dance!
What makes Daybreaker unique is its curation of live entertainment
Doing something strange together can change team and creative dynamics in a really positive way
Welcome to the world of morning raves: just a super-awesome start to your day
Unlock secret invites & our weekly
roundup of global mischief


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[1]
when we returned home on our first night we found the staff had left a card and a card .
[2]
high quality shower items and had a good view of an ice rink behind the hotel .


SUBROUTINE SGEESX( JOBVS, SORT, SELECT, SENSE, N, A, LDA, SDIM, $ WR, WI, VS, LDVS, RCONDE, RCONDV, WORK, LWORK, $ IWORK, LIWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.1) -- * Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. * November 2006 * * .. Scalar Arguments .. CHARACTER JOBVS, SENSE, SORT INTEGER INFO, LDA, LDVS, LIWORK, LWORK, N, SDIM REAL RCONDE, RCONDV * .. * .. Array Arguments .. LOGICAL BWORK( * ) INTEGER IWORK( * ) REAL A( LDA, * ), VS( LDVS, * ), WI( * ), WORK( * ), $ WR( * ) * .. * .. Function Arguments .. LOGICAL SELECT EXTERNAL SELECT * .. * * Purpose * ======= * * SGEESX computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues, the real Schur form T, and, optionally, the matrix of * Schur vectors Z. This gives the Schur factorization A = Z*T*(Z**T). * * Optionally, it also orders the eigenvalues on the diagonal of the * real Schur form so that selected eigenvalues are at the top left; * computes a reciprocal condition number for the average of the * selected eigenvalues (RCONDE); and computes a reciprocal condition * number for the right invariant subspace corresponding to the * selected eigenvalues (RCONDV). The leading columns of Z form an * orthonormal basis for this invariant subspace. * * For further explanation of the reciprocal condition numbers RCONDE * and RCONDV, see Section 4.10 of the LAPACK Users' Guide (where * these quantities are called s and sep respectively). * * A real matrix is in real Schur form if it is upper quasi-triangular * with 1-by-1 and 2-by-2 blocks. 2-by-2 blocks will be standardized in * the form * [ a b ] * [ c a ] * * where b*c < 0.  * * Arguments * ========= * * JOBVS (input) CHARACTER*1 * = 'N': Schur vectors are not computed; * = 'V': Schur vectors are computed. * * SORT (input) CHARACTER*1 * Specifies whether or not to order the eigenvalues on the * diagonal of the Schur form. * = 'N': Eigenvalues are not ordered; * = 'S': Eigenvalues are ordered (see SELECT). * * SELECT (external procedure) LOGICAL FUNCTION of two REAL arguments * SELECT must be declared EXTERNAL in the calling subroutine. * If SORT = 'S', SELECT is used to select eigenvalues to sort * to the top left of the Schur form. * If SORT = 'N', SELECT is not referenced. * An eigenvalue WR(j)+sqrt(-1)*WI(j) is selected if * SELECT(WR(j),WI(j)) is true; i.e., if either one of a * complex conjugate pair of eigenvalues is selected, then both * are. Note that a selected complex eigenvalue may no longer * satisfy SELECT(WR(j),WI(j)) = .TRUE. after ordering, since * ordering may change the value of complex eigenvalues * (especially if the eigenvalue is ill-conditioned); in this * case INFO may be set to N+3 (see INFO below). * * SENSE (input) CHARACTER*1 * Determines which reciprocal condition numbers are computed. * = 'N': None are computed; * = 'E': Computed for average of selected eigenvalues only; * = 'V': Computed for selected right invariant subspace only; * = 'B': Computed for both. * If SENSE = 'E', 'V' or 'B', SORT must equal 'S'. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) REAL array, dimension (LDA, N) * On entry, the N-by-N matrix A. * On exit, A is overwritten by its real Schur form T. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * SDIM (output) INTEGER * If SORT = 'N', SDIM = 0. * If SORT = 'S', SDIM = number of eigenvalues (after sorting) * for which SELECT is true. (Complex conjugate * pairs for which SELECT is true for either * eigenvalue count as 2.) * * WR (output) REAL array, dimension (N) * WI (output) REAL array, dimension (N) * WR and WI contain the real and imaginary parts, respectively, * of the computed eigenvalues, in the same order that they * appear on the diagonal of the output Schur form T. Complex * conjugate pairs of eigenvalues appear consecutively with the * eigenvalue having the positive imaginary part first. * * VS (output) REAL array, dimension (LDVS,N) * If JOBVS = 'V', VS contains the orthogonal matrix Z of Schur * vectors. * If JOBVS = 'N', VS is not referenced. * * LDVS (input) INTEGER * The leading dimension of the array VS. LDVS >= 1, and if * JOBVS = 'V', LDVS >= N. * * RCONDE (output) REAL * If SENSE = 'E' or 'B', RCONDE contains the reciprocal * condition number for the average of the selected eigenvalues. * Not referenced if SENSE = 'N' or 'V'. * * RCONDV (output) REAL * If SENSE = 'V' or 'B', RCONDV contains the reciprocal * condition number for the selected right invariant subspace. * Not referenced if SENSE = 'N' or 'E'. * * WORK (workspace/output) REAL array, dimension (MAX(1,LWORK)) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,3*N). * Also, if SENSE = 'E' or 'V' or 'B', * LWORK >= N+2*SDIM*(N-SDIM), where SDIM is the number of * selected eigenvalues computed by this routine. Note that * N+2*SDIM*(N-SDIM) <= N+N*N/2. Note also that an error is only * returned if LWORK < max(1,3*N), but if SENSE = 'E' or 'V' or * 'B' this may not be large enough. * For good performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates upper bounds on the optimal sizes of the * arrays WORK and IWORK, returns these values as the first * entries of the WORK and IWORK arrays, and no error messages * related to LWORK or LIWORK are issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (MAX(1,LIWORK)) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * LIWORK >= 1; if SENSE = 'V' or 'B', LIWORK >= SDIM*(N-SDIM). * Note that SDIM*(N-SDIM) <= N*N/4. Note also that an error is * only returned if LIWORK < 1, but if SENSE = 'V' or 'B' this * may not be large enough. * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates upper bounds on the optimal sizes of * the arrays WORK and IWORK, returns these values as the first * entries of the WORK and IWORK arrays, and no error messages * related to LWORK or LIWORK are issued by XERBLA. * * BWORK (workspace) LOGICAL array, dimension (N) * Not referenced if SORT = 'N'. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, and i is * <= N: the QR algorithm failed to compute all the * eigenvalues; elements 1:ILO-1 and i+1:N of WR and WI * contain those eigenvalues which have converged; if * JOBVS = 'V', VS contains the transformation which * reduces A to its partially converged Schur form. * = N+1: the eigenvalues could not be reordered because some * eigenvalues were too close to separate (the problem * is very ill-conditioned); * = N+2: after reordering, roundoff changed values of some * complex eigenvalues so that leading eigenvalues in * the Schur form no longer satisfy SELECT=.TRUE. This * could also be caused by underflow due to scaling. * * ===================================================================== * * .. Parameters .. REAL ZERO, ONE PARAMETER ( ZERO = 0.0E0, ONE = 1.0E0 ) * .. * .. Local Scalars .. LOGICAL CURSL, LASTSL, LQUERY, LST2SL, SCALEA, WANTSB, $ WANTSE, WANTSN, WANTST, WANTSV, WANTVS INTEGER HSWORK, I, I1, I2, IBAL, ICOND, IERR, IEVAL, $ IHI, ILO, INXT, IP, ITAU, IWRK, LWRK, LIWRK, $ MAXWRK, MINWRK REAL ANRM, BIGNUM, CSCALE, EPS, SMLNUM * .. * .. Local Arrays .. REAL DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL SCOPY, SGEBAK, SGEBAL, SGEHRD, SHSEQR, SLABAD, $ SLACPY, SLASCL, SORGHR, SSWAP, STRSEN, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV REAL SLAMCH, SLANGE EXTERNAL LSAME, ILAENV, SLAMCH, SLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 WANTVS = LSAME( JOBVS, 'V' ) WANTST = LSAME( SORT, 'S' ) WANTSN = LSAME( SENSE, 'N' ) WANTSE = LSAME( SENSE, 'E' ) WANTSV = LSAME( SENSE, 'V' ) WANTSB = LSAME( SENSE, 'B' ) LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 ) IF( ( .NOT.WANTVS ) .AND. ( .NOT.LSAME( JOBVS, 'N' ) ) ) THEN INFO = -1 ELSE IF( ( .NOT.WANTST ) .AND. ( .NOT.LSAME( SORT, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( WANTSN .OR. WANTSE .OR. WANTSV .OR. WANTSB ) .OR. $ ( .NOT.WANTST .AND. .NOT.WANTSN ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVS.LT.1 .OR. ( WANTVS .AND. LDVS.LT.N ) ) THEN INFO = -12 END IF * * Compute workspace * (Note: Comments in the code beginning "RWorkspace:" describe the * minimal amount of real workspace needed at that point in the * code, as well as the preferred amount for good performance. * IWorkspace refers to integer workspace. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by SHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case. * If SENSE = 'E', 'V' or 'B', then the amount of workspace needed * depends on SDIM, which is computed by the routine STRSEN later * in the code.) * IF( INFO.EQ.0 ) THEN LIWRK = 1 IF( N.EQ.0 ) THEN MINWRK = 1 LWRK = 1 ELSE MAXWRK = 2*N + N*ILAENV( 1, 'SGEHRD', ' ', N, 1, N, 0 ) MINWRK = 3*N * CALL SHSEQR( 'S', JOBVS, N, 1, N, A, LDA, WR, WI, VS, LDVS, $ WORK, -1, IEVAL ) HSWORK = WORK( 1 ) * IF( .NOT.WANTVS ) THEN MAXWRK = MAX( MAXWRK, N + HSWORK ) ELSE MAXWRK = MAX( MAXWRK, 2*N + ( N - 1 )*ILAENV( 1, $ 'SORGHR', ' ', N, 1, N, -1 ) ) MAXWRK = MAX( MAXWRK, N + HSWORK ) END IF LWRK = MAXWRK IF( .NOT.WANTSN ) $ LWRK = MAX( LWRK, N + ( N*N )/2 ) IF( WANTSV .OR. WANTSB ) $ LIWRK = ( N*N )/4 END IF IWORK( 1 ) = LIWRK WORK( 1 ) = LWRK * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -16 ELSE IF( LIWORK.LT.1 .AND. .NOT.LQUERY ) THEN INFO = -18 END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'SGEESX', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN SDIM = 0 RETURN END IF * * Get machine constants * EPS = SLAMCH( 'P' ) SMLNUM = SLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL SLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = SLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL SLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Permute the matrix to make it more nearly triangular * (RWorkspace: need N) * IBAL = 1 CALL SGEBAL( 'P', N, A, LDA, ILO, IHI, WORK( IBAL ), IERR ) * * Reduce to upper Hessenberg form * (RWorkspace: need 3*N, prefer 2*N+N*NB) * ITAU = N + IBAL IWRK = N + ITAU CALL SGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVS ) THEN * * Copy Householder vectors to VS * CALL SLACPY( 'L', N, N, A, LDA, VS, LDVS ) * * Generate orthogonal matrix in VS * (RWorkspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL SORGHR( N, ILO, IHI, VS, LDVS, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) END IF * SDIM = 0 * * Perform QR iteration, accumulating Schur vectors in VS if desired * (RWorkspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL SHSEQR( 'S', JOBVS, N, ILO, IHI, A, LDA, WR, WI, VS, LDVS, $ WORK( IWRK ), LWORK-IWRK+1, IEVAL ) IF( IEVAL.GT.0 ) $ INFO = IEVAL * * Sort eigenvalues if desired * IF( WANTST .AND. INFO.EQ.0 ) THEN IF( SCALEA ) THEN CALL SLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WR, N, IERR ) CALL SLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WI, N, IERR ) END IF DO 10 I = 1, N BWORK( I ) = SELECT( WR( I ), WI( I ) ) 10 CONTINUE * * Reorder eigenvalues, transform Schur vectors, and compute * reciprocal condition numbers * (RWorkspace: if SENSE is not 'N', need N+2*SDIM*(N-SDIM) * otherwise, need N ) * (IWorkspace: if SENSE is 'V' or 'B', need SDIM*(N-SDIM) * otherwise, need 0 ) * CALL STRSEN( SENSE, JOBVS, BWORK, N, A, LDA, VS, LDVS, WR, WI, $ SDIM, RCONDE, RCONDV, WORK( IWRK ), LWORK-IWRK+1, $ IWORK, LIWORK, ICOND ) IF( .NOT.WANTSN ) $ MAXWRK = MAX( MAXWRK, N+2*SDIM*( N-SDIM ) ) IF( ICOND.EQ.-15 ) THEN * * Not enough real workspace * INFO = -16 ELSE IF( ICOND.EQ.-17 ) THEN * * Not enough integer workspace * INFO = -18 ELSE IF( ICOND.GT.0 ) THEN * * STRSEN failed to reorder or to restore standard Schur form * INFO = ICOND + N END IF END IF * IF( WANTVS ) THEN * * Undo balancing * (RWorkspace: need N) * CALL SGEBAK( 'P', 'R', N, ILO, IHI, WORK( IBAL ), N, VS, LDVS, $ IERR ) END IF * IF( SCALEA ) THEN * * Undo scaling for the Schur form of A * CALL SLASCL( 'H', 0, 0, CSCALE, ANRM, N, N, A, LDA, IERR ) CALL SCOPY( N, A, LDA+1, WR, 1 ) IF( ( WANTSV .OR. WANTSB ) .AND. INFO.EQ.0 ) THEN DUM( 1 ) = RCONDV CALL SLASCL( 'G', 0, 0, CSCALE, ANRM, 1, 1, DUM, 1, IERR ) RCONDV = DUM( 1 ) END IF IF( CSCALE.EQ.SMLNUM ) THEN * * If scaling back towards underflow, adjust WI if an * offdiagonal element of a 2-by-2 block in the Schur form * underflows. * IF( IEVAL.GT.0 ) THEN I1 = IEVAL + 1 I2 = IHI - 1 CALL SLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, N, $ IERR ) ELSE IF( WANTST ) THEN I1 = 1 I2 = N - 1 ELSE I1 = ILO I2 = IHI - 1 END IF INXT = I1 - 1 DO 20 I = I1, I2 IF( I.LT.INXT ) $ GO TO 20 IF( WI( I ).EQ.ZERO ) THEN INXT = I + 1 ELSE IF( A( I+1, I ).EQ.ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO ELSE IF( A( I+1, I ).NE.ZERO .AND. A( I, I+1 ).EQ. $ ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO IF( I.GT.1 ) $ CALL SSWAP( I-1, A( 1, I ), 1, A( 1, I+1 ), 1 ) IF( N.GT.I+1 ) $ CALL SSWAP( N-I-1, A( I, I+2 ), LDA, $ A( I+1, I+2 ), LDA ) CALL SSWAP( N, VS( 1, I ), 1, VS( 1, I+1 ), 1 ) A( I, I+1 ) = A( I+1, I ) A( I+1, I ) = ZERO END IF INXT = I + 2 END IF 20 CONTINUE END IF CALL SLASCL( 'G', 0, 0, CSCALE, ANRM, N-IEVAL, 1, $ WI( IEVAL+1 ), MAX( N-IEVAL, 1 ), IERR ) END IF * IF( WANTST .AND. INFO.EQ.0 ) THEN * * Check if reordering successful * LASTSL = .TRUE. LST2SL = .TRUE. SDIM = 0 IP = 0 DO 30 I = 1, N CURSL = SELECT( WR( I ), WI( I ) ) IF( WI( I ).EQ.ZERO ) THEN IF( CURSL ) $ SDIM = SDIM + 1 IP = 0 IF( CURSL .AND. .NOT.LASTSL ) $ INFO = N + 2 ELSE IF( IP.EQ.1 ) THEN * * Last eigenvalue of conjugate pair * CURSL = CURSL .OR. LASTSL LASTSL = CURSL IF( CURSL ) $ SDIM = SDIM + 2 IP = -1 IF( CURSL .AND. .NOT.LST2SL ) $ INFO = N + 2 ELSE * * First eigenvalue of conjugate pair * IP = 1 END IF END IF LST2SL = LASTSL LASTSL = CURSL 30 CONTINUE END IF * WORK( 1 ) = MAXWRK IF( WANTSV .OR. WANTSB ) THEN IWORK( 1 ) = SDIM*(N-SDIM) ELSE IWORK( 1 ) = 1 END IF * RETURN * * End of SGEESX * END


//This is branch1 index.html , changed and pulled from Web ide, Second change pulled from GIT // This is to verify push // This is second push test // This is to verify commit and push // This is to verify the push operation once again //This is to understand Fetch operation on GIT


“Be formless, shapeless, like water. Now you put water into a cup, it becomes the cup. You put water into a bottle, it becomes the bottle. You put it in a teapot, it becomes the teapot. Now water can flow, or it can crash. Be water, my friend.” —Bruce Lee
The “Blog” layout
The “Holy Grail” layout
The “Panel” layout
“Preformations simply lack the flexibility to adapt to the ever changing” —Bruce Lee
Let's establish a new normal
“The hardest part is changing our thinking, not our CSS” —Jen Simmons
State of Browsers (2017)
and many more...
Feature Queries
.selector {
/* Styles that are supported in old browsers */
}
@supports (property:value) {
.selector {
/* Styles for browsers that support the specified property */
}
}
Flexbox and Grid
Based on the container-child relationship
Flexbox
Provides “simple and powerful tools for distributing space and aligning content in ways that web apps and complex web pages often need.”
Flexbox browser support
Flexbox basics
Pumpkin by Yayoi Kusama
Flex shorthand
flex: initial
flex: 0 1 auto, cannot grow but can shrink when there isn't enough space
flex: auto
flex: 1 1 auto, can grow and shrink to fit available space
flex: none
flex: 0 0 auto, cannot grow or shrink, AKA inflexible
flex: <positive-number>
flex: <positive-number> 1 0, can grow and shrink, extent of growth depends on flex factor
Flexbox layouts (1/2)
Flexbox layouts (2/2)
calc() and object-fit browser support
CSS Grid
Defines a two-dimensional grid-based layout system, optimized for user interface design
CSS Grid browser support
“We need to translate ideas that we find in other places, not transfer them.” —Jen Simmons
Biscuit gummies tart gingerbread wafer jujubes sweet roll. Wafer oat cake carrot cake liquorice chocolate bar chocolate cake jelly-o. Pastry donut oat cake. Fruitcake candy apple pie cake tootsie roll cotton candy candy canes. Halvah halvah chocolate jelly-o macaroon.
Macaroon dessert sweet roll dragée candy. Sweet cheesecake lemon drops. Sweet tart chocolate cake candy canes powder cotton candy. Apple pie danish chocolate cake danish bonbon. Muffin soufflé topping carrot cake chocolate. Macaroon toffee chupa chups sesame snaps gummi bears.
Shape from image
Lee Jun-fan (李振藩), known professionally as Bruce Lee, was a Hong Kong and American actor, film director, martial artist, martial arts instructor, philosopher and founder of the martial art Jeet Kune Do. He is widely considered by commentators, critics, media, and other martial artists to be one of the most influential martial artists of all time.
Writing-mode
Defines CSS features to support for various international writing modes
Vertical text
Halt and Catch Fire
“Computers aren't the thing. They're the thing that gets us to the thing.”
“How did we all get here today? The choices we made, the sheer force of our will, something like that? Here's another answer... the winds of fate. Random coincidence, some unseen hand just pushing us along. Destiny.”


NYCAASC 2017 Workshops
<< Back to NYCAASC 2017Track 1
API Flower Power: Understanding Personal Identity and the Connection to Privilege
Room 388
Description: API: Flower Power is an interactive workshop where participants unpack the complexities of the Asian identity using the Power Flower model. The “Power Flower” is a tool developed by Canadian social change educators when working with groups to “identify who we are (and who we aren’t) as individuals and as a group in relation to those who wield power in our society.” (Educating for a Change, p. 87) The goal is to understand our personal identity and their connections to privilege. Workshop is limited to 12 participants.
Speakers
Jasmine Kyon
J./Jasmine Kyon is a queer Burmese-Chinese sunflower who grew up traveling between Chinatown and Queens, helping them perfect the art of sleeping in the subway. J. grew up witnessing how space has offered or denied accessibility to immigrant, queer people of color, inspiring them to research on the equity of public transportation as a Student Research Fellow at the Arcus Center of Social Justice Leadership. Jasmine is also the co-organizer of the Kalamazoo Poetry Collective, connecting Kalamazoo College to local artists and facilitating storytelling workshops to QTPoC youth. Jasmine has introduced the Flower Power workshop to Fire Historical and Arts Collaborative and smART, and is grateful to be in the space of NYCAASC to share an API-centric version of the Flower Power for the first time.


Welcome to the KAS form application page bla bla. Give us your money so we can take your kid and teach them.
We only accept the most capable of students, you need to be able to:


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- Coronavirus
- "A species in the genus CORONAVIRUS causing the common cold and possibly nervous system infections
in humans. It lacks hemagglutinin-esterase."
-
Source: Medical Subject Headings, 2021_2020_07_16; Code in source: D028941 ; UMLS CUI:C0949880
-
- Other Names
-
- COVID-19 virus
- SARS-CoV-2
- 2019-nCoV
- Coronavirus disease 19
- Coronavirus NL63, Human:
- HCoV-NL63
- Coronavirus OC43, Human:
- HCoV-OC43
- Coronavirus 229E, Human:
- HCoV-229E


Staff Focus: Stephanie Discepolo, CTE Resource Teacher
Discepolo has helped take HCPSS’ career development opportunities to the next level by always looking to provide HCPSS students more real world experiences.
More News | Events
More News
HCPSS Names 2019 Principal and Teachers of the Year
HCPSS has announced its 2019 winners for Principal and Teachers of the Year: Long Reach High School Principal Josh Wasilewski; and Sylvia Hennessie of Guilford Elementary School, and Greg Murach of Mt. Hebron High School, respectively.
Screening of “Angst” and Discussion Around Anxiety in Youth
Students and families are invited to a free documentary screening and panel discussion around anxiety in youth.
Events
Choose Civility Poster and Video Contest
Entry Deadline Extended to March 17
All HCPSS students in grades K–12 are encouraged to enter the countywide contest. This year’s theme is We Are All Welcome Here, focusing on how everyone is welcome in our school, neighborhood and entire community.
Elementary School Honors & G/T Band Spring Concerts
Sunday, March 17, 3 p.m., River Hill High School
All community members are welcome to enjoy performances by these fine student musicians.
Defining Ourselves: Youth Art Month Exhibit
Through Friday, April 19, Weekdays 10 a.m.-8 p.m., Saturdays 10 a.m.-4 p.m., Sundays Noon-4 p.m.
Free public reception on Thursday, April 4, 5-7 p.m., Howard County Center for the Arts
The free exhibit features hundreds of artworks by HCPSS K-12 students, created in a variety of media and styles and inspired by the theme, Defining Ourselves: I Am More Than What You See.
Community Advisory Council Meeting
Wednesday, March 13, 7 p.m., Department of Education
HCPSS curriculum office staff will present on the elementary education curriculum. CAC meetings are open to the public.
Youth Opportunities Fair
Saturday, March 23, 11 a.m.-2 p.m., Long Reach High School
This free event showcases leadership, volunteer, recreational and job opportunities for youth and young adults ages 11-24.
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High Court confirms 13-year jail sentence for BNP leader Mir Nasir over hidden assets
by bdnews24.comThe High Court has confirmed a trial court verdict sentencing BNP leader Mir Mohammad Nasir Uddin to 13 years in jail in a case over his having illegal assets.
Nasir’s son Mir Mohammad Helal Uddin has been sentenced to three years in prison in the case started during the 2007-08 emergency.
The panel of Justice AKM Abdul Hakim and Justice Fatema Najib gave their verdict on Tuesday after rehearing the case following orders from the Supreme Court’s Appellate Division.
Khurshid Alam Khan, a lawyer for the Anti-Corruption Commission, said the High Court ordered Nasir and Helal to surrender within three months from the day a copy of the verdict reaches the judge’s court.
“They must surrender if they want to appeal,” the lawyer added.
He also said the fines and order to confiscate their “illegal wealth” remained unchanged in the High Court verdict.
Nasir, the civil aviation and tourism minister of the 2000-2006 coalition government of Khaleda Zia, was arrested in 2007 during the military-backed government on charges of corruption.
The anti-graft watchdog prosecuted him and his son in March that year for allegedly concealing information on wealth worth over Tk 32.2 million and amassing illegal wealth of around Tk 293 million.
In the verdict on July 4 the same year, a Special Judge’s Court in Dhaka slapped fines of Tk 5 million on Nasir and additional two years in jail if he does not pay the fines. Helal was fined Tk 100,000 and given one month jail sentence in case of non-payment.
The High Court acquitted Nasir and Helal in August, 2010 following their appeals.
The ACC then challenged the High Court decision in the Appellate Division, which later cancelled the previous High Court verdict and ordered a rehearing.


FDA classifies Abbott's blood pumping system recall as most serious
REUTERS: The U.S. Food and Drug Administration on Monday classified the recall of Abbott Laboratories' CentriMag blood pumping system, following the death of a patient, as Class 1 or the most serious type of recall.
Forty-four injuries and one death were reported at the time when Abbott started the recall in August this year, the FDA said. (http://bit.ly/2NDsz57)
Abbott did not immediately respond to a Reuters request for comment.
(Reporting by Manojna Maddipatla in Bengaluru; Editing by Shounak Dasgupta)


Module string
string operations like searching and matching.
Functions
| byte (s, i, j) | Returns the internal numerical codes of the characters `s[i]`, `s[i+1]`, ..., `s[j]`. |
| char (...) | Receives zero or more integers. |
| dump (function) | Returns a string containing a binary representation of the given function, so that a later `loadstring` on this string returns a copy of the function. |
| find (s, pattern, init, plain) | Looks for the first match of `pattern` in the string `s`. |
| format (formatstring, ...) | Returns a formatted version of its variable number of arguments following the description given in its first argument (which must be a string). |
| gmatch (s, pattern) | Returns an iterator function that, each time it is called, returns the next captures from `pattern` over string `s`. |
| gsub (s, pattern, repl, n) | Returns a copy of `s` in which all (or the first `n`, if given) occurrences of the `pattern` have been replaced by a replacement string specified by `repl`, which can be a string, a table, or a function. |
| len (s) | Receives a string and returns its length. |
| lower (s) | Receives a string and returns a copy of this string with all uppercase letters changed to lowercase. |
| match (s, pattern, init) | Looks for the first *match* of `pattern` in the string `s`. |
| rep (s, n) | Returns a string that is the concatenation of `n` copies of the string `s`. |
| reverse (s) | Returns a string that is the string `s` reversed. |
| sub (s, i, j) | Returns the substring of `s` that starts at `i` and continues until `j`; `i` and `j` can be negative. |
| upper (s) | Receives a string and returns a copy of this string with all lowercase letters changed to uppercase. |
Functions
- byte (s, i, j)
-
Returns the internal numerical codes of the characters `s[i]`, `s[i+1]`,
..., `s[j]`. The default value for `i` is 1; the default value for `j`
is `i`.
Note that numerical codes are not necessarily portable across platforms.
Parameters:
- s
- i
- j
- char (...)
-
Receives zero or more integers. Returns a string with length equal to
the number of arguments, in which each character has the internal numerical
code equal to its corresponding argument.
Note that numerical codes are not necessarily portable across platforms.
Parameters:
- ...
- dump (function)
-
Returns a string containing a binary representation of the given
function, so that a later `loadstring` on this string returns a copy of
the function. `function` must be a Lua function without upvalues.
Parameters:
- function
- find (s, pattern, init, plain)
-
Looks for the first match of `pattern` in the string `s`. If it finds a
match, then `find` returns the indices of `s` where this occurrence starts
and ends; otherwise, it returns nil. A third, optional numerical argument
`init` specifies where to start the search; its default value is 1 and
can be negative. A value of true as a fourth, optional argument `plain`
turns off the pattern matching facilities, so the function does a plain
"find substring" operation, with no characters in `pattern` being considered
"magic". Note that if `plain` is given, then `init` must be given as well.
If the pattern has captures, then in a successful match the captured values
are also returned, after the two indices.
Parameters:
- s
- pattern
- init
- plain
- format (formatstring, ...)
-
Returns a formatted version of its variable number of arguments following
the description given in its first argument (which must be a string). The
format string follows the same rules as the `printf` family of standard C
functions. The only differences are that the options/modifiers `*`, `l`,
`L`, `n`, `p`, and `h` are not supported and that there is an extra option,
`q`. The `q` option formats a string in a form suitable to be safely read
back by the Lua interpreter: the string is written between double quotes,
and all double quotes, newlines, embedded zeros, and backslashes in the
string are correctly escaped when written. For instance, the call
string.format('%q', 'a string with "quotes" and \n new line')
will produce the string:
"a string with \"quotes\" and \
new line"
The options `c`, `d`, `E`, `e`, `f`, `g`, `G`, `i`, `o`, `u`, `X`, and
`x` all expect a number as argument, whereas `q` and `s` expect a string.
This function does not accept string values containing embedded zeros,
except as arguments to the `q` option.
Parameters:
- formatstring
- ...
- gmatch (s, pattern)
-
Returns an iterator function that, each time it is called, returns the
next captures from `pattern` over string `s`. If `pattern` specifies no
captures, then the whole match is produced in each call.
As an example, the following loop
s = "hello world from Lua"
for w in string.gmatch(s, "%a+") do
print(w)
end
will iterate over all the words from string `s`, printing one per line. The
next example collects all pairs `key=value` from the given string into
a table:
t = {}
s = "from=world, to=Lua"
for k, v in string.gmatch(s, "(%w+)=(%w+)") do
t[k] = v
end
For this function, a '`^`' at the start of a pattern does not work as an
anchor, as this would prevent the iteration.
Parameters:
- s
- pattern
- gsub (s, pattern, repl, n)
-
Returns a copy of `s` in which all (or the first `n`, if given)
occurrences of the `pattern` have been replaced by a replacement string
specified by `repl`, which can be a string, a table, or a function. `gsub`
also returns, as its second value, the total number of matches that occurred.
If `repl` is a string, then its value is used for replacement. The character
`%` works as an escape character: any sequence in `repl` of the form `%n`,
with *n* between 1 and 9, stands for the value of the *n*-th captured
substring (see below). The sequence `%0` stands for the whole match. The
sequence `%%` stands for a single `%`.
If `repl` is a table, then the table is queried for every match, using
the first capture as the key; if the pattern specifies no captures, then
the whole match is used as the key.
If `repl` is a function, then this function is called every time a match
occurs, with all captured substrings passed as arguments, in order; if
the pattern specifies no captures, then the whole match is passed as a
sole argument.
If the value returned by the table query or by the function call is a
string or a number, then it is used as the replacement string; otherwise,
if it is false or nil, then there is no replacement (that is, the original
match is kept in the string).
Here are some examples:
x = string.gsub("hello world", "(%w+)", "%1 %1")
--> x="hello hello world world"
x = string.gsub("hello world", "%w+", "%0 %0", 1)
--> x="hello hello world"
x = string.gsub("hello world from Lua", "(%w+)%s*(%w+)", "%2 %1")
--> x="world hello Lua from"
x = string.gsub("home = $HOME, user = $USER", "%$(%w+)", os.getenv)
--> x="home = /home/roberto, user = roberto"
x = string.gsub("4+5 = $return 4+5$", "%$(.-)%$", function (s)
return loadstring(s)()
end)
--> x="4+5 = 9"
local t = {name="lua", version="5.1"}
x = string.gsub("$name-$version.tar.gz", "%$(%w+)", t)
--> x="lua-5.1.tar.gz"
Parameters:
- s
- pattern
- repl
- n
- len (s)
-
Receives a string and returns its length. The empty string `""` has
length 0. Embedded zeros are counted, so `"a\000bc\000"` has length 5.
Parameters:
- s
- lower (s)
-
Receives a string and returns a copy of this string with all uppercase
letters changed to lowercase. All other characters are left unchanged. The
definition of what an uppercase letter is depends on the current locale.
Parameters:
- s
- match (s, pattern, init)
-
Looks for the first *match* of `pattern` in the string `s`. If it
finds one, then `match` returns the captures from the pattern; otherwise
it returns nil. If `pattern` specifies no captures, then the whole match
is returned. A third, optional numerical argument `init` specifies where
to start the search; its default value is 1 and can be negative.
Parameters:
- s
- pattern
- init
- rep (s, n)
-
Returns a string that is the concatenation of `n` copies of the string
`s`.
Parameters:
- s
- n
- reverse (s)
-
Returns a string that is the string `s` reversed.
Parameters:
- s
- sub (s, i, j)
-
Returns the substring of `s` that starts at `i` and continues until
`j`; `i` and `j` can be negative. If `j` is absent, then it is assumed to
be equal to -1 (which is the same as the string length). In particular,
the call `string.sub(s,1,j)` returns a prefix of `s` with length `j`, and
`string.sub(s, -i)` returns a suffix of `s` with length `i`.
Parameters:
- s
- i
- j
- upper (s)
-
Receives a string and returns a copy of this string with all lowercase
letters changed to uppercase. All other characters are left unchanged. The
definition of what a lowercase letter is depends on the current locale.
Parameters:
- s


Jack is bored!
He will be back on
Monday
Sunday(March 9th) 23:59!
If you have any concerns email to: d.hasegan@jacobs-university.de


Raw data from history calls are usually limited to a few different resolutions. If we want to analyze our bar data on custom time frames, such as 5 minute bars or 4 hour bars, we will need to consolidate the raw data.
One way to consolidate data from our history call is to manipulate our dataframe using the pandas resample method. Resample allows us to convert the frequency of a timeseries dataframe into a custom frequency. Consider an example where we've made a history call for minute resolution data and we want to create 5 minute resolution data.
qb = QuantBook() spy = qb.AddEquity("SPY") startDate = datetime(2018, 4, 1) endDate = datetime(2018, 7, 15) df = qb.History(spy.Symbol, startDate, endDate, Resolution.Minute)
Note, that the resample method works only on dataframes with a datetime index. The dataframe returned from the history call is a multi-index dataframe, with 2 indices: a symbol index for each security in the dataframe and a time index for the timestamps for each row of data. We need to drop the symbol index from our dataframe so that it is compatible with resample. This is accomplished with the pandas reset_index method.
# Drop level 0 index (symbol index) from dataframe df.reset_index(level = 0, drop = True, inplace=True)
When we use resample, a Resampler object is returned which then needs to be downsampled using one of the pandas downsampling computations. For our purposes, we can use the Resampler.ohlc downsampling method to aggregate our price data.
When we resample our dataframe, an OHLC row will be created for each column in our dataframe. We can simplify our data by looking at the OHLC of just the close column by resampling only the close column. A resample offset of 5T corresponds to a 5 minute resample. Other resampling offsets include: 2D = 2 days; 5H = 5 hours; 3S = 3 seconds.
close_prices = df["close"] offset = "5T" close_5min_ohlc = close_prices.resample(offset).ohlc()


|
ErrLib
|
#include <ErrLib_CPP.h>
Static Public Member Functions | |
| static WinapiException | FromLastError (bool localized) |
Additional Inherited Members | |
| Public Member Functions inherited from ErrLib::Exception | |
| Exception () | |
| Exception (const std::wstring &message) | |
| Exception (const std::wstring &message, DWORD code, void *data) | |
| std::wstring | GetMsg () |
| DWORD | GetCode () |
| void * | GetData () |
| void | GetMessageText (WCHAR *pOutput, int cch) |
| void | GetContext (CONTEXT *pOutput) |
| void | PrintStackTrace (WCHAR *pOutput, int cch) |
| std::wstring | PrintStackTrace () |
| void | Log (bool visible) |
Represents an error in Windows native API function
|
inlinestatic |
Creates a new WinapiException using the error code and message from the last WINAPI error
| localized | The value indicating whether the exception message should use the current OS locale |
true
, the message is in language of the current OS locale. Otherwise, it is always in English.


[§437D-18] Power and duties of the director. The director shall have the power and duty to adopt, amend, and repeal rules in accordance with chapter 91 to carry out the purposes of this chapter and to do all things necessary to carry out the functions, powers, and duties set forth in this chapter. [L 1988, c 251, pt of §2]
Note
Section on rulemaking enacted by L 1990, c 209 omitted as similar to this section.


{% extends "base.html" %} {% import "wtf.html" as wtf %} {% block styles %} {{ super() }} {% endblock %} {% block content %}
You are currently logged in as {{ user.username }}. Logout


Results(5)
Donald John Trump(born June 14, 1946) is an American businessman,
television personality, author, and politician. He is chairman of
The Trump Organization, which is the principal holding company for
his real estate ventures and other business interests. He is also
the presumptive nominee of the Republican Party for President of
the United States in the 2016 election.
Trump graduated from the Wharton School of the University of
Pennsylvania in 1968. Having worked in his father Fred Trump's
real estate and construction firm while attending college, he
assumed control of that family business in 1973, later renaming
it The Trump Organization. During his career, Trump has built
hotels, casinos, golf courses, the Manhattan neighborhood Riverside
South and numerous other developments, many of which bear his name,
including Trump Entertainment Resorts (now owned by Carl Icahn).
Donald John Trump updated a new skill Business with proficiency ★★★★★. Let's congrats him!
Donald John Trump updated a new skill C/C++ with proficiency ★☆☆☆☆. Oh man...
Donald John Trump just became the president of USA!


Applies specified DbUnit datasets to database
| attribute | desc | example |
|---|---|---|
orderBy |
List of columns to sort records before verifying. Useful when default sorting results in different order for actual and expected datasets due to using of placeholders. | Optional. Default: -
|


automl_infrastructure.classifiers package¶
Submodules¶
automl_infrastructure.classifiers.base module¶
-
class
automl_infrastructure.classifiers.base.
Classifier
(name, features_cols=None)¶ Bases:
abc.ABC
The Classifier class defines an interface of a classifier.
- Parameters
name (str) – name of the classifier (e.g. ‘lr1).
features_cols (list of str ,optional) – features list that the classifier should work on, while ignoring other features.
-
property
name
¶
-
abstract
fit
(x, y, **kwargs)¶ Training method on a given dataset with labels.
- Parameters
x (pandas.DataFrame) – the training dataset. Note that the training dataset may contain features of type vector (list or numpy.array).
y (pandas.Series or list) – labels of the training dataset.
kwargs –
-
abstract
predict
(x)¶ The method receive a features dataset, and returns a class prediction for each row.
- Parameters
x (pandas.DataFrame) –
the features dataset.
Note that the training dataset may contain features of type vector (list or numpy.array).
- Returns
list or numpy.array of classes predictions
-
abstract
predict_proba
(x)¶ The method receive a features dataset, and returns classes probability prediction for each row.
- Parameters
x (pandas.DataFrame) –
the features dataset.
Note that the training dataset may contain features of type vector (list or numpy.array).
- Returns
list or numpy.array of classes probability predictions (may be also list or numpy.array).
Note that the classes probability list order must be natively sorted (e.g. for string, alphabetically).
-
abstract
set_params
(params)¶ Sets hyper-params of the classifier.
- Parameters
params (dict of {str: Any}) – dictionary of parameters value by their name (e.g. {‘C’ : 1.0}).
-
abstract
get_params
(deep=True)¶ Getter for the classifier hyper-params.
- Parameters
deep (bool ,optional) – for complex classifiers, weather to return params of inner classifiers.
- Returns
the classifier hyper-params.
-
class
automl_infrastructure.classifiers.base.
ClassifierPrediction
(y_pred, y_proba)¶ Bases:
object
The class defines a coupling between classifier predictions and probabilities. The main reason for such object, is for the
automl_infrastructure.experiment.metrics.base.Metric
contract.- Parameters
y_pred (Any, typically str or int) – class prediction.
y_proba (list or numpy.array) – classes probabilities.
-
property
classes_pred
¶
-
property
classes_proba
¶
-
class
automl_infrastructure.classifiers.base.
BasicClassifier
(name, features_cols=None)¶ Bases:
automl_infrastructure.classifiers.base.Classifier
,abc.ABC
The BasicClassifier abstract class implements native support for common and wide operations, such that: auto-unrolling vector features, narrowing dataframe to specific features ad ect’.
- Parameters
name (str) – name of the classifier (e.g. ‘lr1).
features_cols (list of str ,optional) – features list that the classifier should work on, while ignoring other features.
-
fit
(x, y, **kwargs)¶ Training method on a given dataset with labels.
- Parameters
x (pandas.DataFrame) – the training dataset. Note that the training dataset may contain features of type vector (list or numpy.array).
y (pandas.Series or list) – labels of the training dataset.
kwargs –
-
predict
(x)¶ The method receive a features dataset, and returns a class prediction for each row.
- Parameters
x (pandas.DataFrame) –
the features dataset.
Note that the training dataset may contain features of type vector (list or numpy.array).
- Returns
list or numpy.array of classes predictions
-
predict_proba
(x)¶ The method receive a features dataset, and returns classes probability prediction for each row.
- Parameters
x (pandas.DataFrame) –
the features dataset.
Note that the training dataset may contain features of type vector (list or numpy.array).
- Returns
list or numpy.array of classes probability predictions (may be also list or numpy.array).
Note that the classes probability list order must be natively sorted (e.g. for string, alphabetically).
automl_infrastructure.classifiers.ensemble_classifier module¶
-
class
automl_infrastructure.classifiers.ensemble_classifier.
EnsembleClassifier
(name, input_models, ensemble_model, ensemble_extra_features=None)¶ Bases:
automl_infrastructure.classifiers.base.Classifier
The EnsembleClassifier class represents a complex classifier that consists of one or more sub-classifiers. The way the complex classifier works is:
applying every sub-classifier on the dataset
gather from every sub-classifiers the classes probabilities prediction, and apply ensemble model on them with extra features (optional)
- Parameters
name (str) – the name of the classifier.
input_models (list of
automl_infrastructure.classifiers.base.Classifier
) – list of sub-classifiers to aggregate their predictions.ensemble_model (
automl_infrastructure.classifiers.base.Classifier
) – the aggregator classifier on top the sub-classifiers and possibly extra features.ensemble_extra_features (list of str ,optional) – list of extra features that the ensemble model should work on.
-
fit
(x, y, **kwargs)¶ Training method on a given dataset with labels.
- Parameters
x (pandas.DataFrame) – the training dataset. Note that the training dataset may contain features of type vector (list or numpy.array).
y (pandas.Series or list) – labels of the training dataset.
kwargs –
-
predict
(x)¶ The method receive a features dataset, and returns a class prediction for each row.
- Parameters
x (pandas.DataFrame) –
the features dataset.
Note that the training dataset may contain features of type vector (list or numpy.array).
- Returns
list or numpy.array of classes predictions
-
predict_proba
(x)¶ The method receive a features dataset, and returns classes probability prediction for each row.
- Parameters
x (pandas.DataFrame) –
the features dataset.
Note that the training dataset may contain features of type vector (list or numpy.array).
- Returns
list or numpy.array of classes probability predictions (may be also list or numpy.array).
Note that the classes probability list order must be natively sorted (e.g. for string, alphabetically).
-
set_params
(params)¶ Sets hyper-params of the classifier.
- Parameters
params (dict of {str: Any}) – dictionary of parameters value by their name (e.g. {‘C’ : 1.0}).
-
get_params
(deep=True)¶ Getter for the classifier hyper-params.
- Parameters
deep (bool ,optional) – for complex classifiers, weather to return params of inner classifiers.
- Returns
the classifier hyper-params.


Submit a new buy order.
Cancel all outstanding orders created by all sessions owned by this account.
Cancel a clearing order.
Cancel an order.
Cancel all orders opened by this session.
Confirm a clearing order.
Get details about the specific account requested such as users, country codes, etc.
Get the accounts within the group.

Get the auction events.
Get the available balances in the supported currencies.
Get time-intervaled data for the provided symbol.
Get a clearing order status.
Get current auction information.
Get deposit addresses.
Get a new deposit address.
Get the available balances in the supported currencies as well as in notional USD.
Get the volume in price currency that has been traded across all pairs over a period of 30 days.
Get the current order book.
Get an order status.
Get your past trades.
Get data on balances in the account and linked banks
Get the price feed.
Get extra details about the symbol.
Get all available symbols for trading.
Get the trades that have executed since the specified timestamp.
Get the trade volume for each symbol.
Get deposits and withdrawals in the supported currencies.
Prevent a session from timing out and canceling orders if the require heartbeat flag has been set.
Make an internal transfer between any two exchange accounts within the Group.
Submit a new broker clearing order.
Submit a new clearing order.
Submit a new order.
Submit a new sell order.
Withdraw cryptocurrency funds to a whitelisted address.
Withdraw USD
as GUSD
.
The SEN Withdrawals API allows you to withdraw USD from your Gemini account via SEN
The add bank API allows for banking information to be sent in via API. However, for the bank to be verified, you must still send in a wire for any amount from the bank account.


{include file='common/css'}
上传文件
文件夹
{foreach $categoryList as $v}
{$v.name}
{/foreach}
{foreach $list as $v}
Italy street.jpg
添加时间：2014-10-13
{/foreach}
{include file='common/js'}


School of Web Design & New Media 2019 Spring
The School of Web Design & New Media prepares students for cutting-edge
careers in experiential design and digital media. We teach an integrated
approach based on four fundamentals: design thinking, visual
communication, technology, and user experience.


g2 comes with a custom HTML element which allows to implement command queues directly into the page without the necessity of running scripts.
The aim of this HTML element is to minimize the implementation overhead of the user, while maintaining the flexibility g2 provides.
To implement the g2 element into your page just import the g2.html.js
.
<g-2 id='g' width="601" height="401" cartesian x0="0" y0="0" grid interactive>
{ "main":[
{"c":"lin","a":{"x1":"@A.x","y1":"@A.y","x2":"@B.x","y2":"@B.y","lw":3,"ls":"@linkcolor"}},
{"c":"cir","a":{"id":"A","x":150,"y":50,"r":5,"fs":"orange"}},
{"c":"cir","a":{"id":"B","x":-50,"y":100,"r":5,"fs":"orange"}},
{"c":"cir","a":{"x":15,"y":150,"r":30,"fs":"orange"}},
{"c":"cir","a":{"x":15,"y":150,"r":15,"fs":"snow"}}
]}
</g-2>
<script src="https://cdn.jsdelivr.net/gh/goessner/g2/dist/g2.html.js"></script>
The overall styling is handled by respective properties of the g-2
element:
width
: Width of the element inpx
.height
: Height of the element inpx
.x0
: x-origin of the drawing.y0
: y-origin of the drawing.cartesian:
: Whethercartesian
is true or not (see View).grid
: Whether agrid
is rendered or not.darkmode
: Whether dark mode is set or not.interarctive
: Whether the element is interactive or not.
The innerHTML defines the command queue of the drawing.
The syntax of the innerHTML
is straight forward:
"main"
defines the array containing the elements of the command queue, whereas
each element is an object containing "c"
(think command) and
"a"
(think arguments).
So the given "main"
:
"main":[
{"c":"cir","a":{"x":250,"y":100,"r":30,"fs":"orange"}},
{"c":"cir","a":{"x":250,"y":100,"r":15,"fs":"snow"}}
]
is equal to the command queue given by
g2().cir({x:250,y:100,r:30,fs:"orange"})
.cir({x:250,y:100,r:15,fs:"snow"});
Note: Don't forget to use quotations (e.g.
"x"
) for the properties, since theg2-element
interprets theinnerHTML
using the JSON format.


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Rack
Element Location
Element Location
Manage location of element {{element_name}}{{#element_alias}} ({{.}}){{/element_alias}} in rack {{rack_name}}
Location
Rack Name
Select the rack where the element is located at or add a new rack if the rack does not exist yet.
Location
The location of the element in the rack expressed in rack units.
Position
Select the position of the element in the slot.
Save location
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An internship is an official program that is offered by an employer to potential employees. The modern concept of an internship has evolved from medieval apprenticeship, where a skilled laborer, often a craftsman, would take on and teach a young person their trade. In exchange for being taught a trade, the apprentice would agree to work for the craftsman for a specified length of time.


--- layout: post status: publish published: true title: Series Recap - Cubs @ Pirates 3/31 - 4/3, 2014 author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 9496 wordpress_url: http://ivyenvy.com/?p=9496 date: '2014-04-03 14:31:18 +0000' date_gmt: '2014-04-03 19:31:18 +0000' categories: - Series Recap tags: - Jeff Samardzija - Pirates - Pittsburgh - Starlin Castro - Edwin Jackson - Jason Hammel - Emilio Bonafacio comments: [] ---
Results
Pirates win series 2-1.
Monday: Pirates 1 Cubs 0 (10 innings)
Wednesday: Pirates 4 Cubs 3 (16 innings)
Thursday: Cubs 3 Pirates 2
Cubs Overall Record: 1-2
The Good
As Cubs fans, we're pretty familiar with seasons starting with strong starting pitching performances. The Cubs got outstanding outings from Jeff Samardzija, Edwin Jackson and Jason Hammel. Combined, the starting pitching gave up two runs in 19 innings pitched, a .95 ERA.
Nobody expected Emilio Bonafacioto get off to the start he did in this series. How about .688/.706/.813? Although he got picked off twice in the series, I really like what his speed brings to this team.
The Bad
Starlin Castro did not get much work in during Spring Training because of an injury. You would expect Castro to get off to a slow start, and he did. He looked a bit lost at the plate. Castro hit .077/.200/.077 in the series. It might take Castro a while to get up to speed.
I'm sure he appreciated the day off on Thursday after Wednesday's 16 inning game, but Welington Castillo also struggled at the plate in his two games. Castillo hit .100/.182/.100. Obviously, this is not something to be overly concerned with. Two games is about as "small sample size" as it gets.
The Ugly
In recent memory, the Cubs have been awful with Runners In Scoring Position. So far in 2014, they are amazingly bad. In the first two games of the series, the Cubs went 1-27 with RISP.


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The Amazon rainforest is the largest and most biodiverse forest in the world. A conifer forest in the Swiss Alps (National Park). The Adirondack Mountains of Upstate New York form the southernmost part of the Eastern forest-boreal transition ecoregion.


Cbn copy clipboard Demo
To use the element just add some text inside the tags
This text will be copied on click.
You can also add a
value
attribute to the element tag and assign any value you want to be copied
Click me
asdasd


Select x-axis attribute
Brightness
Hardness
Depth
Roughness
Warmth
Sharpness
Boominess
Select y-axis attribute
Brightness
Hardness
Depth
Roughness
Warmth
Sharpness
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Number of files
Click on points to listen to sounds
Click + drag to navigate the map
Scroll wheel to zoom
This demo was made as part of the Audio Commons project:
www.AudioCommons.org
TIMBRAL EXPLORER


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--- layout: data_model title: ExploitTargetType this_version: 1.2 ---
Represents a single STIX Exploit Target.
ExploitTargets are vulnerabilities or weaknesses in software, systems, networks or configurations that are targeted for exploitation by the TTP of a ThreatActor. In a structured sense, ExploitTargets consist of vulnerability identifications or characterizations, weakness identifications or characterizations, configuration identifications or characterizations, potential Courses of Action, source of the ExploitTarget information, handling guidance, etc.
| Field Name | Type | Description |
|---|---|---|
| @idoptional | QName |
Specifies a globally unique identifier for this ExploitTarget. |
| @idrefoptional | QName |
Specifies a globally unique identifier of an ExploitTarget specified elsewhere. When idref is specified, the id attribute must not be specified, and any instance of this ExploitTarget should not hold content. |
| @timestampoptional | dateTime |
Specifies a timestamp for the definition of a specific version of an ExploitTarget When used in conjunction with the id, this field is specifying the definition time for the specific version of the ExploitTarget. When used in conjunction with the idref, this field is specifying a reference to a specific version of an ExploitTarget defined elsewhere. This field has no defined semantic meaning if used in the absence of either the id or idref fields. |
| @versionoptional | ExploitTargetVersionType |
Specifies the relevant STIX-ExploitTarget schema version for this content. |
| Title0..1 | string |
The Title field provides a simple title for this ExploitTarget. |
| Description0..n | StructuredTextType |
The Description field is optional and provides an unstructured, text description of this ExploitTarget. |
| Short_Description0..n | StructuredTextType |
The Short_Description field is optional and provides a short, unstructured, text description of this ExploitTarget. |
| Vulnerability0..n | VulnerabilityType |
The Vulnerability field identifies and characterizes a Vulnerability as a potential ExploitTarget. |
| Weakness0..n | WeaknessType |
The Weakness field identifies and characterizes a Weakness as a potential ExploitTarget. |
| Configuration0..n | ConfigurationType |
The Configuration field identifies and characterizes a Configuration as a potential ExploitTarget. |
| Potential_COAs0..1 | PotentialCOAsType |
The Potential_COAs field specifies potential Courses of Action for this ExploitTarget. |
| Information_Source0..1 | InformationSourceType |
The Information_Source field details the source of this entry. |
| Handling0..1 | MarkingType |
The Handling field specifies the appropriate data handling markings for the elements of this Exploit Target. The valid marking scope is the nearest ExploitTargetBaseType ancestor of this Handling element and all its descendants. |
| Related_Exploit_Targets0..1 | RelatedExploitTargetsType |
The Related_Exploit_Targets field specifies one or more exploit targets that are related to this exploit target. |
| Related_Packages0..1 | RelatedPackageRefsType |
The Related_Packages field identifies or characterizes relationships to set of related Packages. DEPRECATED: This field is deprecated and will be removed in the next major version of STIX. Its use is strongly discouraged except for legacy applications. |


---
format: html
external: true
title: Windows Store apps and the IE10 DOM
author: Jesse MacFadyen
link: http://www.risingj.com/archives/322
date: 2012-12-17 23:24:41 Z
type: post
status: publish
tags:
- PhoneGap Network
thumb: /blog/uploads/thumb/jesse.jpg
---
Windows 8 fully embraces web-tech as a means to develop applications for the windows store, however, there are a few things that you should be aware of, along the way. You can use your own JS libraries, or jQuery, or whatever you prefer ( assuming it behaves well in IE10 ). One thing to watch out for though is that ...


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Details - Register of penalty notices
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Details of this penalty notice were first published 23 Nov 2010, last updated 23 Nov 2010.
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## randomForest 4.6-12
## Type rfNews() to see new features/changes/bug fixes.
This purpose of this paper is to analyse data gathered from a study that measured various aspects of “Unilateral Dumbbell Biceps Curls”" on six male participants between 20-28 years of age. The following link can be used to access an overview of the original study and the full study can be found here: Qualitative Activity Recognition of Weight Lifting Exercises
This report was created as a project requirement for the Practical Machine Learning course offered by Johns Hopkins University as part of the Data Science Specialization offered through Coarsera.
This report will cover the following items:
Can the manner (correctness) in which Unilateral Dumbbell Biceps Curls was done be predicted using accelerometer data?
The datasets consist of accelerometer data on the belt, forearm and arm of six young healthy participants as well as the dumbell.
The data can be downloaded here:
The first part of model building is data exploration. There are 118 variables in the datasets and it was assumed that some or many of them would provide little or no use. The standard summary() function in R was used to investigate them and it was found that vaiables which included “min_|max_|avg_|var_|stddev_|kurtosis_|skewness_|amplitude_” in the name had large numbers of NA’s or empty cells. Additionally, these variables are summary statistics created by the original authors and were considered to be problematic for any model so they were removed. The variables “new_window|user_name|timestamp|X” were also removed because they would not provide any usefulness in answering the stated question.
The following R commands were used to prune the undesirable variables from the original datasets. To verify if the remaining variables had any additional issues the resulting training set was investigated again with the summary() function and the nearZeroVar() function.
training_smaller <- training[,which( !grepl("X|num_window|min_|max_|avg_|var_|stddev_|kurtosis_|skewness_|amplitude_|new_window|user_name|timestamp",colnames(training) ) ), with=FALSE ]
testing_smaller <- testing[,which( !grepl("X|num_window|min_|max_|avg_|var_|stddev_|kurtosis_|skewness_|amplitude_|new_window|user_name|timestamp",colnames(testing) ) ), with=FALSE ]
# trained models
modFit1 <- train(classe~., method="rf", data = training_smaller, trControl = fitControl)
# with preProcess - center
modFit2 <- train(classe~., method="rf", data = training_smaller, preProcess=c("center"), trControl = fitControl)
# with preProcess - center and scale
modFit3 <- train(classe~., method="rf", data = training_smaller, preProcess=c("center", "scale"), trControl = fitControl)
In the snippet above you can see the code for the three models (modFit{1|2|3}) that were trained for evaluation. It was decide to start with the random forest model using the entire training dataset to see what the outcome would be. Along with the base random forest model an additional two models were created that use the preProcess methods of “center” and “center with scale”.
Evaluation of the random forests models were done against the training set to see how well the models perform in predicting the classification. As can be seen in the following output, the tables from the confusionMatrix for each model show that the base model and two subsequent version matched the training set exactly.
The final test was to run the predict function using the base model and the test data. The results from this were entered into the course project prediction quiz for validation. The random forest proved to be an ideal model for this data as it categorized the classifications with 100% accurancy.
With the results of the training data and testing data it is considered that the expected out of sample error is near zero.
The decision to remove the analyst created variables was done to remove sparse data with the hopes that the remaining data would yield good results. However, it was suprising that the model worked as well as it did.
The decision to remove the other variables “new_window|user_name|timestamp|X” was made because it was expected that they would not provide useful information in the model building process. Additionaly, they were not directly tied to the question being asked of the data.
The choice to start with the random Forest model was made because the dataset was not to large to run in a decent amount of time with the addition of parallel processing functions.


| Instructions: click on a map tile on the grid to select it. Type the key corresponding to the glyph you want to place. | ||
| Tile Name | Key | Glyph |
| cement | D | D |
| dead-tree | h | h |
| tracks | ? | ? |
| more-bones | % | % |
| bones | & | & |
| stuff | $ | $ |
| sand | . | . |
| dirt | ; | ; |
| short-grass | , | , |
| tall-grass | / | / |
| reeds | i | i |
| aspen | H | H |
| juniper | Y | Y |
| oak | L | L |
| pine | T | T |
| spruce | A | A |
| block-5 | @ |
@
|
| dawg | Q |
Q
|
| block-4 | e |
e
|
| block-3 | c |
c
|
| block-2 | d |
d
|
| block-1 | b |
b
|
| block-0 | f |
f
|
| block-null | a |
a
|
| let me know if something's missing. |


| Air Raid | Play | Loop | Stop |
|---|---|---|---|
| Background Music | Play | Loop | Stop |
| Explosion | Play | Loop | Stop |
| Hiroshima Radio Broadcast | Play | Loop | Stop |
| Machine Gun | Play | Loop | Stop |
| Missile Strike | Play | Loop | Stop |
| Thunderstorm Ambience | Play | Loop | Stop |
| "War" Sounds | Play | Loop | Stop |
| "War" Sounds (different) | Play | Loop | Stop |


I Alone Level-up: Chapter 54
| Shadow Storage (Lv . 1) [1]. |
| Class-specific Skill. Mana Cost: 0. Absorb the Shadow Soldiers into the user’s shadow for storage . . The stored soldiers can be freely summoned and reabsorbed by the user . . Stored Shadows: 0 / 20 |
‘As I thought . ’
Jinwoo nodded . Before he had checked the description, he had surmised that the “storage” in its name meant that the skill would allow him to manage the soldiers somehow . However, there was one thing he did not expect .
‘The limit is…’
The limits of the storage was smaller than the limits of the summoning . While he could make 30 soldiers, he could only store 20 of them . That meant that he would have to get rid of 10 more .
 ’
It would be like biting of one of his fingers . Even getting rid of just one soldier was painful, and now he had to get rid of 10 of them .
‘Hmm…’
With a heavy heart, Jinwoo looked over his army . Of course, Ygritte and the mages would be excluded from selection . That would leave the infantry . He decided to pick the 10 soldiers furthest away this time .
‘I’m sorry . ’
Jinwoo briefly prayed for their souls .
shooooo-
The soldiers he selected became dust and scattered . Compared to the first time, the regret that he felt was lessened . They say humans can get used to anything .
Anyways .
Jinwoo looked at the remaining soldiers and used ‘Shadow Storage’ .
At the activation of the skill, Ygritte and the Shadow Soldiers melted like ice into flat shadows . Then, their shadows flowed over to Jinwoo and entered his own shadow .
‘So this is what the skill meant by absorbing them…!’
It was exactly as described by the skill; his army was absorbed into his shadow . It all happened in a blink of an eye . The shadow army was nowhere to be seen .
‘ . Even after seeing it…’
Jinwoo looked at his shadow with amazement . In that moment, the System rang .
ring~
| You’ve tried out all the class-specific skills . . |
| The class advancement is now complete . . |
| The exit will now be created . . |
‘Is it finally over…?’
It was a long and tough road . Jinwoo took one last look around the Dungeon . The traces of combat littered the area .
Broken knights . Cracked walls . The destroyed pillar .
And the one who destroyed the pillar, the iron golem, which was now a pile of broken armor .
But his trials had resulted in many great boons .
New class and skills .
A powerful army .
A smile appeared on Jinwoo’s face . He turned around without a lingering thought . The gate to the real world waited for him . Jinwoo stepped through .
He returned to the clearing in the forest . It was the same spot he had first entered the quest’s Dungeon . The time was 5 AM . The sun would be rising soon .
Oh right .
Jinwoo looked at his watch and kicked himself in his mind .
‘If I knew I was going to take this long, I should’ve let Jinah know . ’
Fortunately, he had been late in the past due to the Association’s Raids .
Jinwoo looked behind him . The gate that he left from had disappeared without a trace .
‘Huh…’
Looking at the empty clearing, everything that had happened felt like a dream .
Wait, a dream?
No, no way .
Jinwoo looked around .
Soldiers clad in pitch black surrounded him . The Shadow Soldiers had come out the moment he thought of them in his head .
‘ . ’
At first, he thought of them as monsters .
Shadow Soldiers .
Monsters that were called from the shadows of the dead . If they were monsters, what do you call the being that can freely create and control them? Jinwoo smiled,
‘Well, it doesn’t matter…’
He recalled the soldiers into his shadow again .
The road home felt as easy as walking downhill .
Jinwoo slept for a long time . He could not help it . The moment he had lied down in his bed, the day was already bright .
ring~ ring~
What woke him was the ringing of his phone . He managed to grab it with much difficulty . Jinwoo answered the phone with his eyes still closed .
“Hello…”
His tired voice cracked a bit .
- “What the… Oppa, are you still sleeping? Do you know what time it is?!”
Jinah asked with surprise from the other end, so Jinwoo asked .
“What time is it…”
- “It’s 2 PM!”
“Whaaa?”
Jinwoo peaked at the phone through a crack in his eyes . She was right .
- “Oppa, you do remember that you have to come to the school today, right?”
Her voice was filled with concern . This made Jinwoo finally sit-up on the bed .
“When do I have to be there by?”
- “5!”
“Alright, I won’t be late . Don’t worry . ”
- “As expected of my brother! Call me when you get here!”
Jinah cutely ended the call .
Jinwoo scratched his head and slowly got up . He could probably make it if he got ready now .
‘Still, I’m about to go see my little sister’s teacher . ’
On top of that, it was for the parent/guardian meeting for a highschool senior . They say this was one of the most important meetings of a child’s life .
‘I can’t go looking like this . ’
He went over and looked through his wardrobe . A musty scent filled his nose; it was not exactly a good smell . Jinwoo’s forehead wrinkled . The most suitable thing he found was the old suit that he had worn for his graduation .
‘Can I wear this?’
He tried it on, but it did not fit . The suit was too small for his body .
‘Man, my body really grew . ’
Trying on his old clothes was a sure way to tell . The suit felt like it was about to rip apart over him .
. Now what?
While wondering what he could wear, Jinwoo’s eyes fell on the bankbook that Yoo Jinho had given him . It contained the magic core income from their Raids . Looking back and forth between the old suit and the bankbook, a smile crept up on Jinwoo’s face .
‘It’s been a while . Shall I go shopping?’
However, there was something small he had to check . Wait, not small, something big . Jinwoo took off the suit and sat down on his bed and opened up the status screen .
‘Status screen .  Level: 51 Class: Monarch of Shadows Title: Wolf Slayer ( . 1 more) HP: 11,035 MP: 1,022 Fatigue: 0 | Stats. Strength: 132 Constitution: 91 Agility: 111 Intelligence: 70 Sense: 93. (Available stat points: 10). Physical Damage Reduction: 46% |
| Skills. Passive Skills -(Unknown) (Lv . Max) -Unyielding Spirit (Lv . 1) -Advanced Dagger Proficiency (Lv . 1) Active Skills -Sprint (Lv . 2) -Bloodlust (Lv . 1) -Stealth (Lv . 1) -Vital Stab (Lv . 2) -Dagger Throw (Lv . 1) | Class-specific Skills. Active Skills -Shadow Extraction (Lv . 1) -Shadow Storage (Lv . 1). Equipment. Red Knight’s Helmet (S) Gatekeeper’s Necklace (A) High-level Knight’s Breastplate (B) High-level Knight’s Gauntlet (B) High-level Mage’s Ring (B) Mid-level Assassin’s Shoes (C) |
[2].
“Huh…”
Jinwoo stuck out a tongue at the status screen that went on and on .
‘I feel like only few days ago this was nearly empty . ’
It was true . But now, just the skills and equipment alone had increased greatly . Above all else, what stood out to him was his new class .
| Class: Monarch of Shadows. |
Just yesterday, this spot was decorated with word, “none” . To be honest, everytime he opened his status screen, that “none” bothered him . A Hunter that didn’t Raid was basically an unemployed bum . At least, that’s how society viewed them . So when he looked at his status screen before and saw that he had no class(job), it struck a chord in his mind . Now, he could not hide his joy in looking at the newly filled part of his status screen .
‘Is this what they call an inferiority complex?’
Of course, having “none” in that section didn’t mean that he didn’t have a job in real life . Still, it reminded him of his past . Other Hunters raided and earned a ton of money without paying attention to the eyes of the world . He was the not the same . He could not even proudly claim that he was a Hunter . After all, he was a mere E-ranker who could barely hold onto his own life .
“Hello, I’m an E-rank Hunter . ”
Every time those words escaped his mouth, anyone who knew anything about Hunters would praise him for his hard work but go on to mock him behind his back . That’s why not having a class bothered him, despite how illogical it was .
But now, he had obtained a job, or rather something special . His job was still a Hunter, but in a way, he had obtained a special calling called the “Monarch of Shadows” .
‘Even if it’s not exactly what I was hoping for…’
He had no regrets . If anything, he was satisfied . If he wasn’t in his room, he would’ve summoned Ygritte and the Shadow Soldiers before him . Jinwoo really wanted to test out their capabilities in battle . What if they could bring out a 100% of their former powers?
‘Probably not . ’
But even imagining it made his heart race .
ba dum ba dum
Jinwoo stood still and felt his heartbeat . In his head, he was running simulations of his next Raid . Additionally, he was looking forward to Yoo Jinho’s reaction .
Imagining the young man’s face with wide open eyes and mouth, Jinwoo laughed despite of himself .
Hold on .
‘Now that I think about it . ’
If he was able to raise a dead target, and if that target was not limited to a monster or a magic beast…
‘I should be able to raise a soldier from a dead Hunter, right?’
It was obvious, but he had avoided the idea because a human was involved . To think that he would command an undead soldier from a dead man’s shadow . Just the idea shocked him .
Even still…
‘What if I can raise an A-rank or a S-rank Hunter’s shadow?’
The power he would obtain would be beyond imagination . Even if the soldier could wield just 50% of their former powers, it would be enough for him to raid high-level Dungeons . The light racing of his heart turned to a full sprint .
BA DUM, BA DUM, BA DUM!
But Jinwoo shook his head .
‘Still, raising a human being into an undead is…’
It was not something that should be done . No matter how much it increased his powers, he wanted to avoid doing that . Unless someone appeared that truly deserved it…
‘Not that there are a lot of opportunities to fight another Hunter . ’
Even if an opportunity appeared, there was a philosophical problem . Humans were not monsters or magic beasts .
Alright .
For now, he would be satisfied with the army on hand .
‘I did obtain a boss-level soldier too . ’
The Shadow Soldier who was level 7 and a knight grade . How powerful was he?
Jinwoo anticipated his next Raid .
Translator’s Notes:. [1]: Shadow Storage (그림자 저장): Same as extraction, pretty literal . “Shadow” 그림자 + “save/store/preserve” 저장
[2]: I need a new way of displaying this information… It’s only going to get bigger…


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@* * Copyright 2017 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.play.views.html.helpers._ @import uk.gov.hmrc.cbcrfrontend.AppConfig @import uk.gov.hmrc.cbcrfrontend.views.html._ @import uk.gov.hmrc.cbcrfrontend.model.CBCId @import uk.gov.hmrc.cbcrfrontend.controllers.routes @(asideBusiness: Html, phaseBannerBeta: Html, cbcId:CBCId, companyName:Option[String])( implicit request: Request[_], messages: Messages) @sidebarContent = { @asideBusiness } @main_template("Country by Country Reporting", sidebarLinks = Some(sidebarContent)) {
@Messages("subscribeSuccessCbcId.printThisButton")
@Messages("subscribeSuccessCbcId.printThis1")
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WHO WE ARE
The first mate and his Skipper too will do their very best to make the others bee comfortable in their tropic island nest the love Boat promises something for the everyone michael Knight a young loner on a crusade to champion.
The others comfortable in their tropic island nest the love Boat promises to have something for everyone michael Knight a young loner.
- FAST DELIVERY
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Methods
bindLocale(controller, pageName)
Adds the locale info to the model.
- Source:
Adds the locale info to the model.
Parameters:
| Name | Type | Description |
|---|---|---|
controller |
LocalizedController | |
pageName |
string |
getPendingOrdersAsync()
Retrieves the batches from the product DSU and updates the model
.- Source:
Retrieves the batches from the product DSU and updates the model
getStockAsync()
Retrieves the products from the DSU and updates the model by calling StockController#updateStock after retrieval
.- Source:
Retrieves the products from the DSU and updates the model by calling StockController#updateStock after retrieval
register(participant, callback)
Creates the ID DSU and mounts it to the id_path
.- Source:
Creates the ID DSU and mounts it to the id_path
Parameters:
| Name | Type | Description |
|---|---|---|
participant |
Participant | |
callback |
function |
showIonicModal(modalName, swipeToCloseopt)
Shows an Ionic model
.- Source:
Shows an Ionic model
Parameters:
| Name | Type | Attributes | Description |
|---|---|---|---|
modalName |
string | the modal's name registered via: customElements.define('registration-modal', class extends HTMLElement{ connectedCallback(){ this.innerHTML = ` |
|
swipeToClose |
boolean |
<optional> |
enables slideToClose when available. defaults to false |
updatePendingOrders(orders)
Updates the batches model
.- Source:
Updates the batches model
Parameters:
| Name | Type | Description |
|---|---|---|
orders |
Array.<object> |
updateStock(stock)
Updates the stock model
.- Source:
Updates the stock model
Parameters:
| Name | Type | Description |
|---|---|---|
stock |
Array.<object> | where the properties must be: |


obs- Launch OBS in portable mode:
obs --portable- Automatically start recording a video on launch:
obs --startrecording- Automatically start the replay buffer on launch:
obs --startreplaybuffer- Automatically start streaming on launch:
obs --startstreaming- Minimise to the system tray on launch:
obs --minimize-to-tray- Make the log more verbose (for debugging):
obs --verbose


Your personalised holiday plan from touchdown to take off, built to fit your needs
Hotel and restaurant options, tour guide, private driver and airport pick up
Print or digital itineraries with activities, restaurants and map directions
We are human beings like you, not an algorithm
We continously visit new places and revisit the classics, because we want it to be worth it for you
We save your time and take the stress out of your holiday planning
We consider alternative options in case of bad weather conditions
We do not work for others, only for you. Our goal is to make your holiday unforgettable


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Villa
Divine
Dwell
Welcome to Villa Divine Dwell, a two storied bunglow nestled in the middle of one acre of rambutan plantation. Just 10kms from kaduwela highway exit you will find this peaceful and beautiful paradise of nature.Just to escape from your urban busy life and enjoy privacy and serenity intact.Villa Divine Dwell is the ideal location for your day outs, overnight stays,small gatherings,parties and ect.We are more than happy to customize your stay with us.


WHISPER
SUMMER INTERN 2015
June 11 ~ Aug 14
By Hiroki Hori .
Table of Contents
1. What I did
2. Some thoughts
3. Things I'm looking to try at Whisper
4. Living in Venice
5. Activities in Venice
1. What I did
2. Some thoughts
3. Things I'm looking to try at Whisper
4. Living in Venice
5. Activities in Venice
"My achievements :]"
78MRs. (1.2 MRs / day)
User Location Tracking in Schlep Mode
User header notification
Bugs, bugs, bugs...
Alright, let me fix them.
1. What I did
2. Some thoughts
3. Things I'm looking to try at Whisper
4. Living in Venice
5. Activities in Venice
"There are also a lot to learn from other companies"
Developer blogs
- Facebook developer blog
- SoundCloud developer blog
- Pinterest developer blog
And many more...
News Feed performance improvements
Reactive Cocoa
1. What I did
2. Some thoughts
3. Things I'm looking to try at Whisper
4. Living in Venice
5.
- Building Whisper App for Apple Watch
- Integrating Reactive Cocoa
- Switching to Swift (partially)
- More performance tunings
- Integrating UI-Testing (KIF)
- React Native
1. What I did
2. Some thoughts
3. Things I'm looking to try at Whisper
4. Living in Venice
5. Activities in Venice
"It doesn't rain!"
1. What I did
2. Some thoughts
3. Things I'm looking to try at Whisper
4. Living in Venice
5. Activities in Venice
"I tried new things as much as I could, but not enough!"
Thank you!
Appreciate all your support during my intern!


This website was created by Tom Oinn (@approx_eng), and is licensed under the Apache Software License 2.0. You can inspect and download the source code on the GitHub repository. The site has no server-side components, it runs entirely within your web browser. No data is ever sent anywhere, no cookies set, no tracking or anything unpleasant. Once the site has loaded you could unplug your computer from the network and it'll work just fine.
As with many open source projects, this site makes use of a number of excellent tools and libraries, in particular:
Finally, this was inspired by a conversation with Dr Nicola Smyllie (@NicolaSmyllie) who was annoyed at not being able to run some basic stats without installing expensive Windows-only software. This seemed like a sad state of affairs so I hacked something up before breakfast which did the job well enough. Another few hours turned it into what you see here.
Tom Oinn, June 28, 2016


Chilli con Carne
Thinly minced and non-lean mince is preferred.
Spices shall be left to the choice of the cook, if at all desired.
Mince should be broken up well before cooking.
- ⏲ Prep time: 5 min
- 🍳 Cook time: 1-2 hours
Ingredients
- Chorizo pork sausage
- Pork mince
- Bacon strips
- Tomato sauce
- Chilis
- Kidney beans
- Olive oil
- Wine
- Butter
- (spices)
Directions
- As pan heats: Slice chilis and chorizo as desired
- Olive oil in pan heat on high
- Pork mince in.
- Butter add
- Bacon add
- Add ¾ of tomato sauce
- Add chilis and chorizo
- Add spices and beans. Then wait until audible spitting of sauce has lasted for around 40 min
- Add remainder of sauce
- Add wine
- Lower flame, cover pan, then maintain a gentle simmer for 20-40 min
Contribution
Jacob Siggins
Recipe tags:
mexican
beans
pork


Implementation¶
Methods for calculating the curvature effective mass¶
Three methods are used to calculate the curvature effective mass (Eqn.1 in the main text).
Finite difference
We use a three point forward finite difference equation to calculate the curvature at point i:
\[\frac{\partial^2E}{\partial k^2} = \frac{E_{i+2} - 2E_{i+1} + E_{i}}{\left|k_{i+1} - k_i\right|},\]where \(E_i\) is the energy eigenvalue at position \(k_i\) in reciprocal space.
Unweighted least-squares fit
To obtain estimates for the coefficient of a parabolic dispersion
\[E = ck^2,\]we use the least-squares method as implemented in the NumPy Python library to minimise the summed square of residuals
\[\sum^{5}_{i=1}(ck_i^2 - E_i)^2.\]We fit to five points; three points from the DFT-calculated dispersion plus two from the symmetry of the dispersion (\(E(k)=E(-k)\)).
Weighted least-squares fit
To obtain estimates for the coefficients of the dispersion
\[E = {c}k^2,\]we use the least-squares method as implemented in the NumPy Python library to minimise the summed square of residuals
\[\sum^{n}_{i=1}W_i(ck_i^2 - E_i)^2.\]The summation is over all points up to an energy of \(0.25\,eV\), including points generated from the symmetry of the dispersion, \(E(k)=E(-k)\). \(W_i\) is given by
\[W_i(E_i,T) = \frac{1}{\exp\left(\frac{E_i-E_f}{k_BT}\right)+1}.\]


I'm A Celebrity's Caitlyn Jenner 'hoping to lose weight for Kardashian party'
Jungle rations in I'm A Celebrity can often see the campmates shed pounds and reality star Caitlyn Jenner is hoping to be slimmer when she leaves the show
by James Brinsford, https://www.facebook.com/james.brinsfordCaitlyn Jenner is hoping to use her jungle experience to lose weight, especially with the Kardashian Christmas party on the horizon.
The 70-year-old reality star has indicated that rations in camp could kick start a slimming process that she hopes will put her in better stead as the festive season begins,
Speaking ahead of entering the camp for the launch of I'm A Celebrity on Sunday, Caitlyn indicated that weight loss was the main determining factor to her decision to to sign up.
In a video interview, Caitlyn said: "The only reason I'm doing it is to lose a few pounds.
"I gotta fit into that outfit when I come back. I have the family Christmas party to go to. I wanna look good."
Caitlyn joked ahead of entering the jungle camp that she didn't know that there wouldn't be stylists on hand to help keep her looking on point at all times.
She asked: "Do we get hair and make-up? Noooo?! We don't get hair and make-up? Oh my god!"
Despite the lack of hair help in the camp, Caitlyn has indicated that it will be her fellow campmates that might end up bugging her more than any insects.
Caitlyn said: "People are far tougher than any snake or spider," before adding that she would try to "keep the peace" and will act as the "parent" of the camp.
I'm A Celebrity bosses have paid big bucks to bring Caitlyn Down Under, with reports that she is receiving a£500,000 payday for her appearance.
The former Olympian has previous with shows like this as she has already taken part in the US version.
Speaking about her experiences in that show, back in 2003, Caitlyn said: "I did the US version of this and it was a very interesting experience last time I did it.

She joins Roman Kemp, Ian Wright, Andrew Maxwell, Jacqueline Jossa, James Haskell, Nadine Coyle, Kate Garraway and Myles Stephenson for the 2019 series.
Do you have a story to sell? Get in touch with us at<EMAIL_ADDRESS>or call us direct 0207 29 33033.


We build websites we call "Tribes" that link people with a common interest and tie them together with a common financial interest; your token!
Select the package that is most suitable for you project needs.
Varous projects accross the world now leverage on the reality that Tribaldex tribes are bringing.


Mum left kids, 3, 5, and 7, locked in room with bucket and spent night with man
A mum left her three young children locked in a bedroom on her son’s birthday, so she could spend the night at a hotel with her partner, a court heard.
The children – aged three, five and seven – were locked in the room with bucket, a roll of toilet paper and a plastic bag filled with snacks on the evening of September 15, 2017.
They were also unable to leave the room, at the home in Blackburn, Lancashire, as the door handle had been removed, Preston Crown Court was told.
Judge Philip Barry said the only source of light in the bedroom was a lamp with exposed wires, plugged into a damaged socket, causing a ‘clear fire hazard’.
When officers were alerted to the situation and forced their way into the house, the five-year-old little girl told them: ‘Mummy has left us alone again’.
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Prosecutors said the alarm was raised by the children’s father, who is separated from their mother, after he became concerned she had left them alone.
The 32-year-old mum, who cannot be named for legal reasons, returned the next morning and was arrested at around 8am.
She pleaded guilty to three offences of child neglect on November 14 and was given an 18-month prison sentence, suspended for two years.
Prosecutors said police found text messages on her phone that made it clear she had booked a room at a Holiday Inn Express, in Burnley, with a man she referred to as ‘babe’.
She claimed she had asked her sister to look after the children but dumped them at home when the arrangements fell through.
When officers arrived on the scene they could see a light on in a back bedroom so they broke in through the front door.
Charles Brown, prosecuting, said the police could not immediately open the bedroom door and the youngsters could be heard crying inside.
Their father, who was with the officers, asked them to stand clear of the door so police could break it down, the court heard.
The children then spent the night with their father, but they are now cared for by the mother’s aunt and uncle, the court was told.
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Kelly Cyples, defending, said her client had been involved in an abusive relationship with the children’s father, which she had ended.
But because she had married him against her family’s wishes, she was effectively isolated and had struggled with bringing the children up, she claimed.
The mother must also complete 150 hours of community service and undertake 30 rehabilitation activity days.
Got a story for Metro.co.uk?
Get in touch with our news team by emailing us at<EMAIL_ADDRESS>For more stories like this, check our news page.


coming soon(tm)
transfem HRT topics:
- genotype, epigenetics, hormones and receptors, and phenotype
- phenotypical effects of transfeminine hormone replacement therapy
- risks of transfeminine hormone replacement therapy
- the hypothalamic-pituitary-gonadal axis
- gonadotropin-releasing hormone
- follicle-stimulating hormone and luteinizing hormone
- estradiol
- administration and pharmacokinetics of exogenous estradiol
- estrone
- estrone sulfate
- summary: theorized role of estrone in achieving satisfactory feminization
- other estrogens
- progesterone
- administration and pharmacokinetics of exogenous progesterone
- prolactin
- testosterone
- dihydrotestosterone
- summary: achieving satisfactory androgen blockade
- sex hormone-binding globulin
- free fraction of circulating sex hormone
- summary: achieving satisfactory free fraction of circulating estradiol
- other steroid hormone precursors and metabolites
- aromatase
- 5α-reductase
- spironolactone
- cyproterone acetate
- bicalutamide
- other nonsteroidal antiandrogens
- leuprorelin
- other gonadotropin-releasing hormone agonists
- degarelix
- other gonadotropin-releasing hormone antagonists
- finasteride and dutasteride
- minoxidil
- summary: stopping and reversing androgenic hair loss
- domperidone
- summary: inducing lactation
- medroxyprogesterone acetate
- synthetic estrogens
- selective estrogen receptor modulators
- blood testing
- published hormone replacement therapy guidelines
- alternative hormone replacement therapy guidelines
- blood test result analyzer and unit converter
other topics:
- gender dysphoria
- electrolysis as a method of permanent hair removal