One of the questions I get asked the most about embroidery is 'how many strands?'. I use stranded embroidery thread for all my patterns, mainly DMC but sometimes a little bit of Anchor. The only reason I try to focus on DMC threads is that they are more widely available globally, I love Anchor threads too. The patterns do contain notes on the number of threads I've used in various areas of the stitching but it's not necessary to follow them exactly depending on the effect you want to create.
when I draw with micron pens I have a range of different nib sizes and I swap pens according to the thickness of line that I want. I do exactly the same thing with embroidery threads. However I do have a go to number of threads, if in doubt I will automatically stitch with 2 strands. A lot of the pattern stitching will use 2 strands of threads.
my 'catching wishes' design was stitched using a single strand because I really wanted to keep the sketchy ethereal feeling of the original drawing which was done in pen and ink, so quite scratchy and fine. It helps to have a magnifying lamp (or very good eyesight) for stitching with a single thread.
Stripes to fill a larger area are a perfect place to play around with numbers of strands. In the image above I used 4 strands of blue and 2 strands of green. I find it more interesting to look at than even stripes of two strands each. If I use an even number of strands I will often use three colours rather than two (for example I would use blue green and perhaps an orange if I were using two strands for each of the colours) which again makes it more interesting.
Another place where the number of strands you use can make all the difference is in french knots. In the past I would wrap the thread around twice if I wanted a bigger knot but a lovely embroiderer told me that she had been taught to increase the number of threads rather than the number of wraps to create a larger knot. This method is much more satisfying and keeps the knot clearer. So above you can see a range of knots from two strands to six strands. It's worth just messing around with numbers of strands to see which you like the best. I do love three strands personally.
In the past I haven't used a lot of chain stitch but recently I've been quite drawn to it. It's a little more involved than backstitch and I find I have to concentrate more, I don't find it as easy to get into a rhythm but it creates beautiful hair and chains for bunting. I tend to use 2 strands, I find 3 strands is a little too bulky and needs a bigger stitch but it would make a great outline stitch if you wanted a bold slightly frilled edge. I do like the delicacy of the single strand chain, it feels loose and would make a great chain for your bunting.
Stitching up little samples of basic stitches using different numbers of strands of threads is a fun thing to do. You could keep it in a stitch notebook or file for future reference, noting the numbers of threads that you used.
Now back to stitching up my new caravan embroidery design (designed to fit inside a hoop) ready for the end of the month.


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The Impatient Maiden 1932
Description: A maid's dream comes real but are not quite what she expected.
Released: 01 Mar 1932 Director: James Whale Writers: Donald Henderson Clarke (novel), Richard Schayer (screenplay), Winifred Dunn (screenplay), James Mulhauser (additional dialogue) Actors: Lew Ayres, Mae Clarke, Una Merkel, Andy Devine Genres: Comedy, Drama, Romance
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The Impatient Maiden Reviews:
A fascinating curio, Impatient Maiden reveals director James Whales' cinema style as well as his private evasiveness.This slice-of-life romantic drama concerns one Ruth Robbins, effectively portrayed by Mae Clark. By day, a secretary to a divorce attorney, Ruth brushes up vs life one broken marriage at a time. At home, a neighbor's wife attempts suicide when her husband leaves her and it's left to Ruth to summon an ambulance. So when ambulance driver Myron Brown sparks Ruth's interest, Ruth's own cynical attitudes become her largest obstacle. Distain for marriage and having private obstacles were themes which may have found resonance to the personally challenged James Whale. He presents his tableau in matter-of-fact style, without undue emphases: Ruth's lonely plight is just something she does everyday.Lew Ayers as Myron Brown displays a natural ease in his role, and with Whale blocking for him he'll never look better. Helping roles are well cast. An early Andy Devine keeps the dramatic tone from sinking. On the distaff side, an ebullient Una Merkel is on hand to perk up Ruth. Nice casting and solid performances maintain a balance that makes this movie more "accessible" than others of this ilk.The presentation is smartly handled, too. A Whale trademark was a stage transition that followed characters from room to room by tracking the camera through the wall. Though the end of the wall gets a close-up, the viewer's perception is priority. Rose walks from one end of her apartment to the another and in one shot the limits of her 3 room flat are established. Indeed, the movie opens with an establishing sequence when Rose leaves for work. In a zone shot, she quits her flat into a rundown neighborhood and boards Angel's Flight. She continues her conversation as Arthur Edeson's camera boards and rides down a piece of history. The viewer gets a true feel for what Ruth's life is like.The attraction between Ruth and Myron is advanced and retracted like waves on the beach. Love can't catch a break until the last reel. Elusive love, what fun the chase is, especially in this film. Recommended.
What an odd movie for James Whale to follow up "Frankenstein" with!This is a strange tiny romantic drama, about a girl in love with a young doctor. Because he can't help her financially he leaves her,and she becomes a "kept" girl when she takes up with her wealthy lawyer boss.At once cynical and romantic, it's difficult to work out what the mission of the entire thing is. Una Merkel is lots of fun though, and Ethel Griffies nearly steals the picture. And the young and pretty Lew Ayres is lovingly filmed by Whale. The movie also demonstrates what a fine actress Mae Clarke was, and how she deserved better material as she grew older.In all an unusual and entertaining movie from a nice director, but also a baffling one.
Clara Bow, the popular sexy flapper, was on her method down as a film star. Universal was able to arrange with Paramount to receive her on loan. Universal had purchased the rights to a novel, 'The Impatient Virgin", which, back then, was very juicy, practically pornographic. (It wouldn't be now). Universal expected to create a fortune with that combination.When she saw the script, La Bow bowed out. Too sexy. The script was made especially for her. Bow was a oner. Exeunt Bow, exeunt the story.When the script, which followed the ebook closely, was submitted to the MPPDA, the self-censoring body of the major studios, the organization instantly banned the word 'virgin'. They recommended 'maiden' instead.They advised vs nearly the whole script. The movie was assigned to two another directors before James Whale was forced to direct it. He didn't wish to, he wasn't interested in it. The Hays office, which is the MPPDA, advised them to take the heat out of the script. They did. It became a various story, and there was not a single stage in it which was now hot. (There is a seduction. I won't tell if it came off or not).Whale didn't receive along with the star, Lew Ayres. Ayres had made a bunch of films in the last two years, but he still didn't know his craft. Whale never gave him any advice. He hardly spoke to Ayres. Still the movie garnered some friction. A censor board slash out the main part of the appendectomy scene. It told the seduction was all right.The movie died a fast death, did not receive much business in the large town venues, was not re-released, and never made it into Europe.The review from the Fresh York Times, titled 'A Naive Melodrama', by A. D. S., March 4, 1932 tells in part:Everything it has to tell is in the title.On the entire there seems nothing James Whale, the talented director of "Frankenstein" and "Journey's End," should have done about this one.
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Oceania Football Confederation > News > 2018 OFC Women's Nations Cup > Tahiti take first points
Tahiti take first points
in2018 OFC Women's Nations Cup, Cook Islands, International Friendly, Tahiti
Tahiti overcame Cook Islands 3-1 in the first of two friendlies. Credit: SB/FTF
The Tahitian women's national team, the Vahine Ura, have taken the advantage over neighbours the Cook Islands after securing a 3-1 victory in the first of two international friendly matches between the two nations played in Paea yesterday.
It was a strong start from the host side who found the back of the net for the opening goal when Ninauea Hioe showed her speed and technique to deliver the opening blow to the visitors just two minutes into the match.
Tahiti continued to dominate and came close to extending their lead in the 11th minute with a header from Tahia Tamarii but she was denied. In the end it fell to Hanihei Taumaa to give Tahiti a two goal cushion with her strike in the 16th minute.
As expected prior to kick off Tahiti's Vaihei Samin, who is in the Tours youth programme in France, was the standout for her side taking corners and free kicks and putting pressure on the Cook Islands.
The second half was a lot harder for the home team, and they were pleased when Taumaa scored a second for her brace. Despite being three goals down at this point the Cook Islands refused to give up and when the opportunity finally came their way in the form of a penalty, Ngametua Taringa stepped up to put the ball in the back of the net.
However it wasn't enough for the Cook Islands to pull themselves back in line with their opponent, with Tahiti winning 3-1.
The second friendly will be played on Friday 13 July (local) at the same field.
Cook Islands, International Friendly, Ngametua Taringa, Ninauea Hioe, Tahia Tamarii, Tahiti, Tanihei Taumaa, Vahine Ura, Vaihei Samin, Women's Football
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For the OswegonianBy Dan Gross (Staff Writer ) on November 6, 2014.
Email: laker@oswegonian.com On Wednesday Oct. 29, the string quintet Sybarite5 took the stage in Sheldon Hall Ballroom to perform a varied set of music in front of a completely packed house, which was a surprise to many regular concertgoers. According to Colleen Dailey a music professor at Oswego State, all sections of the 100-level music appreciation classes and all sections of Music 100 were required to come to the concert. The hall was so packed, that even when three extrs rows were added in front, students were standing and sitting in back and around the ballroom. The group was even so gracious as to offer seating on the stage, which Dailey and a couple of middle school kids took advantage of.
The host of the concert, faculty member and pianist Robert Auler, who also performed a piece with the quintet, sat with violinist Sami Merdinian and bassist Louis Levitt to do a pre-concert talk. Auler and Levitt were friends at the University of Cincinnati, and the chemistry between the two was evident. The audience learned the group first got together during the Aspen Music Festival, which Levitt described as a music camp for "old people" in college, playing together in their free time, sometimes on street corners.
Both Levitt and Merdinian discussed that classical musicians often do not have a choice in the repertoire they play, saying they "have to play the music you're given, and you don't always get to play what you want." As these musicians get to play what they want, they have come to specialize in Radiohead covers, which violist Angela Pickett described as a "Radiohead problem," that they solve by playing these covers. The group has an entire record devoted to Radiohead covers.
Of all of their Radiohead covers, they chose to play "Paranoid Android," "Weird Fishes" and "No Surprises," the last of which they arranged themselves and was a great highlight of the concert.
Levitt said after the concert that these percussionist hits are notated with varying degrees of specificity in the music and they often work with the arrangers of their music with whom they discuss it, but it usually comes down to a decision by the group. Also in the music for these Radiohead tunes was the text for the melody whenever a part had it.
They rounded out the concert with pieces by Mozart, as well as a number of unusual tunes, exploring many tonalities, including a modern sound, avant-garde, jazz and the blues. Their newest member, Merdinian, also showed his influence, as they played a number of tangos from the violinist's native Argentina.
Upon completing the set, they received a standing ovation. After leaving and returning to the stage, they treated the audience to an encore piece of "Take On Me/Flight Of The Bumblebee" mashing up A-Ha and Korsakov, which elicited laughs from the audience.
It was a great concert for a packed house, especially those on stage.


Otley 19, Stourbridge 27 SPEED MERCHANT Josh Trinham produced another memorable try which effectively turned the game in Stour's favour at Otley.
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Stourbridge 22, Preston Grasshoppers 25 STOUR suffered a dreadful defeat to Preston.
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A DUDLEY MP has praised local manufacturing after it was revealed the Black Country continues to outperform national averages.
BUDDING borough entrepreneurs who are interested in setting up their own business are invited to an advice event in Stourbridge next month.
KINGSWINFORD firm Fives is pleased to confirm the successful installation and commissioning of a Bronx Series 6CR12-HD straightening line, for a leading API tube manufacturer, located near to Osaka, in Japan.
A BRIERLEY Hill manufacturer which is completely owned by its staff has invested more than £700,000 in a bid to increase its global customer base.
BUSINESS students at a Stourbridge school are getting extra encouragement to work hard thanks to the backing of a Black Country accountancy firm.
A STOURBRIDGE online recruitment firm is marking its five year anniversary this month.
A CLENT special school will get extra financial help this year after being named as the charity partner of Black Country estate agents Lex Allan and Grove.
THE Black Country Chamber of Commerce is on the hunt for its 'Business of the Year' 2015 – and is hoping to bring in more entries than ever.
Local entrepreneur Sarah Alicia Jane Wood has taken the leap to open FAB The Salon a beauty salon located within Fitness4less Brierley Hill.
LEGAL eagles from Stourbridge got their birdies in a row for a golf day – attracting 40 players on the hottest day of the year.
A FINANCIAL services expert has joined a Stourbridge firm which is heading from strength to strength.
A STOURBRIDGE woman has come away with one of the top prizes of this year's Business Travel People Awards.
STOURBRIDGE Rugby Club is bracing itself for a Stourton Park power struggle.
A DUDLEY entrepreneur has invested more than £100,000 into setting up a new Brierley Hill-based kitchen business.
A STOURBRIDGE accountancy firm stole the show at an annual vocational learning award ceremony as it took away the title of Employer of the Year.
SPECIALISTS from a Brierley Hill law firm has been appointed to the Charity Commission's approved list of interim managers to ensure confidence in UK charities.
Experienced insurance specialist Sarah Giles has been appointed as a director at fast-growing Birmingham firm Newstead Insurance Brokers.
A BRIERLEY Hill property firm has been awarded with an industry standard accreditation.
A STOURBRIDGE man and business finance specialist has been appointed as a director of national investor firm Seneca Partners.
STAFF at a Brierley Hill law firm will be getting a dressing down today (May 21) as they celebrate Denim for Dementia Day.
Residents and businesses in Greater Birmingham and Solihull have been asked to share their views on their local area through a new website, www.
A BLACK Country manufacturer is planning to expand its business after moving to a larger premises on a Kingswinford industrial estate.
A NEW recruitment firm has opened in Stourbridge with the aim of helping Black Country residents get back into work.
A STOURBRIDGE Golf Club apprentice is on course for a successful career having picked up a regional award.
A WEST Midlands based law firm has joined forces with Stourbridge College and Kidderminster Academy to deliver business and law lectures to students.
A KINGSWINFORD scrap metal firm has been fined more than £4,000 after admitting to tampering with a weighing machine.
A BURGEONING Black Country family owned accountancy firm has celebrated its 35th birthday by moving into new offices in Sedgley.
A NEW era has begun for Birmingham-based PR, design and digital agency Barques as it celebrates the launch of a new division with three account wins.
A STOURBRIDGE manufacturing firm is celebrating a record year after smashing the £3.2million barrier in just six years.
A NEWLY built £1.5million industrial development in Kingswinford has welcomed its first tenant.


Super busy day in the gallery today, as I charged along to try and finish our new wall. Lots of wonderful conversations about the wall in progress with customers today. Previous post shows a day of stencilling the day before and today it was gold and silver gilding. I used Annie Sloan's gold sizing of course (available in store) along side her sponge roller to apply the sizing on with my stencil and gold and silver leaf (also in store). Annie Sloan's sizing goes on blue and when it's ready it goes clear (very clever) letting you know when to start your gold/silver leafing. The neat thing about her sizing is that once you apply it, you don't have to leaf straight away you could leave it for ages and it will still be tacky ready for leafing which was perfect as this project had to fit in with serving customers in the gallery today. Using Annie's sponge roller was great, it was fast, no drips and super easy to control the amount I put on the walls. I started gilding our walls just before lunch, and managed to finish by closing time. It was wonderful watching the wall change throughout the day from the morning light to evening, and the gilded stencils look on another life at night. I ended up working a bit later with sheer determination to have this finished today. I was glad I did work a bit later, as the wall looked pretty spectacular in the night light with the chandelier on. You can see in the photos there is a little sign that says TR Paint Studio beautifully done by Karenza today. That's right we are getting ready to move our paint studio from the back of the shop to the front of the shop. Painting in the public eye for all to see… *shriek* we think it's a wonderful way to keep the gallery interactive not just from the street frontage but to allow our customers to come in and see EVERYTHING that goes on in our paint studio 🙂 Which brings up the question, so what will go out the back where our paint studio use to be??? – Stay tuned.


SHASTHA do the consulting on IT staffing requirements of any organizations .We provide IT staff consulting for major IT organization to enable and enhance information technology talent for their business .Our capabilities address all the prospective and clarification for you to decide the best talent support with the process and practice that you adopt in your business strategy. To add value to client businesses, we offer IT Staffing that meets the enterprise objective of sustainable growth with a competition edge.
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SHASTHA is highly specialized in IT resourcing because we afford in- house competency enhancement program for resources on relevant technologies and develop the capability to meet our client specific needs. Our focus is to help organizations to achieve numerous business goals faster that accelerate the quality and speed of project development, and avoiding the cost and time required for internal training and skill development.
Our solutions manage people, process, risk and work outcome responsibility, driving value for your business while reducing your investment in staff and oversight.
Our Managed Training services helps Coroprates, Academics and Individual in developing and enhancing technical and functional competency levels.
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This program is designed for IT & Non IT freshers or experienced candidates. Through this program candidates acquire specialization on technology from basic to advance level. Our Trainers are real-time IT experts. The process of development will be Train, Test and Hire-in. In this model, we would pick suitable individual through selection, train them on technologies through rigorous and intensive training in all aspects of software development & required skills. During training & project those found excellent will be selected based on performance. Our IT resourcing service provides the placement assistance and offers the employment to the outperformed candidates as per our client's requirements. This program ensures complete transition and job oriented training for both IT & Non-IT candidates.
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text:
Kevin Foisy picked-up the Ontario Legends Series feature event win and earned the Masters division INEX Asphalt Legends starting spot Melissa Smits, www.facebook.com/oneninemarketing
Ontario Legends Series Awards Three National Qualifier Spots at Peterborough Speedway
Written by Jim Clarke on Monday, 01 July 2019 22:23
PETERBOROUGH, ON (July 01, 2019)- As if things on the home front weren't already complicated enough, on Saturday, June 29 the www.trailersplus.net Ontario Legends Series put a trio of preferred starting spots for the INEX Legends Asphalt Nationals to be run October 17 & 18 at Carteret County Speedway in Peletier, North Carolina up for grabs at the tight, tricky bullring on Mount Pleasant Road.
A potent group of 25 starters rolled from the staging area to green flag at the venue known as Canada's Toughest 1/3-Mile Paved Oval, with Cole McFadden and Miles Tyson on the front row. Every driver in the field had their eyes on the coveted prize, as well as accumulating valuable points on the annual leg of the tour and the Clarke Motorsports Communications Challenge Cup for this year's Peterborough Speedway events.
Tyson took an early lead, but a quick yellow flag with just a single circuit on the scoreboard brought the pack back together. Within a few laps of the restart, Kevin Foisy, who had come from sixth on the grid, was running third and tracking Tyson's every move. The field caught some of the backmarkers with just over a handful of laps complete and ran clean until an incident in the second turn produced another caution period with almost two-thirds of the race distance in the record books.
On the restart, Foisy lit the fuse that turned his piece into a rocketship. He took the lead and never looked back. Just after the #57 took the checkered flag, Tyson and Andre Fiorini made hard contact with the frontstretch retaining wall. Running second and third at the time, their cars were both heavily damaged and cradled back to the pits. Kenny McNicol Jr., Dave Riopelle, Adam Cuthbertson and Paul Pierik were scored second through fifth. Connor James, Mark Griffin, Tyson, Fiorini, Cory Richardson, Jeff Forsey, Thomas Dunn, Parker Traves, Chris Massey, Glenn Morris, Zach Latimer, Shawn Murray, Cody Newell, Rick Eades, McFadden, Andrew Massey, Don Arnott, Shane Pollock, Dawson Drimmie and Matt Haufe completed the finishing order.
Ontario Legends Series notebook: Foisy earned the Masters starting spot, with Connor James taking the Semi-Pro honours and Adam Cuthbertson earning the Pro classification...Heat race wins went to Cole McFadden, with a pair. Parker Traves, Tyson, Paul Pierik and Foisy took the others...The tour returns to action with back-to-back shows – July 6 and 7 at Grand Bend Speedway.
Since 1986, series title sponsor Trailers Plus has carried a full line of new and used cargo, sport, utility, livestock trailers and car haulers to do the job. To learn more about their complete product line, see Trailers Plus at 2223 Drummond Line in Peterborough, call 877.703.5085 or visit www.trailersplus.net.
Like the Ontario Legends Series page on www.facebook.com and look for the exciting web-site www.ontariolegendseries.ca. Clarke Motorsports Communications is proud to represent the Trailers Plus Ontario Legends Series 2019 season.
Prepared by Jim Clarke, Clarke Motorsports Communications/First Draft Media
This email address is being protected from spambots. You need JavaScript enabled to view it., www.facebook.com/clarkemotorsports
Ontario Legends Series
INEX Legends
legends racing
Peterborough Speedway
http://www.insidetracknews.com/news/results-a-points/item/8864-ontario-legends-series-awards-three-national-qualifier-spots-at-peterborough-speedway.html#sigProId579c643ac7
http://www.insidetracknews.com/news/results-a-points/item/8864-ontario-legends-series-awards-three-national-qualifier-spots-at-peterborough-speedway.html#sigProIddd57537fba
http://www.insidetracknews.com/news/results-a-points/item/8864-ontario-legends-series-awards-three-national-qualifier-spots-at-peterborough-speedway.html#sigProId7613bdded8
http://www.insidetracknews.com/news/results-a-points/item/8864-ontario-legends-series-awards-three-national-qualifier-spots-at-peterborough-speedway.html#sigProId7004dd07ca
http://www.insidetracknews.com/news/results-a-points/item/8864-ontario-legends-series-awards-three-national-qualifier-spots-at-peterborough-speedway.html#sigProId2a5e65a6d6
http://www.insidetracknews.com/news/results-a-points/item/8864-ontario-legends-series-awards-three-national-qualifier-spots-at-peterborough-speedway.html#sigProId0cd5e2206d


text:
from uuid import uuid1

import re
from ..io.importer import (syllables_data_to_csvs, import_syllable_csv,
                           nonsyls_data_to_csvs, import_nonsyl_csv,
                           create_syllabic_csvs, create_nonsyllabic_csvs,
                           syllables_enrichment_data_to_csvs, import_syllable_enrichment_csvs)

from ..io.helper import make_type_id

from ..syllabification.probabilistic import norm_count_dict, split_nonsyllabic_prob, split_ons_coda_prob
from ..syllabification.maxonset import split_nonsyllabic_maxonset, split_ons_coda_maxonset
from .utterance import UtteranceContext

def make_label_safe_for_cypher(label):
    """
    Make a given subset name safe for use in Cypher

    Parameters
    ----------
    label : str
        Subset name

    Returns
    -------
    str
        Cypher-safe name
    """
    if not label.startswith('`'):
        label = '`' + label
    if not label.endswith('`'):
        label += '`'
    return label

class SyllabicContext(UtteranceContext):
    """
    Class that contains methods for dealing specifically with syllables
    """

    def find_onsets(self, syllabic_label='syllabic'):
        """
        Gets syllable onsets across the corpus

        Parameters
        ----------
        syllabic_label : str
            Subset to use for syllabic segments (i.e., nuclei)

        Returns
        -------
        data : dict
            A dictionary with onset values as keys and frequency values as values
        """
        from collections import Counter
        data = Counter()
        for s in self.speakers:
            discourses = self.get_discourses_of_speaker(s)
            for d in discourses:
                statement = '''match (w:{word_name}:{corpus_name})-[:spoken_by]->(s:Speaker:{corpus_name}),
                (w)-[:spoken_in]->(d:Discourse:{corpus_name})
        where (w)<-[:contained_by*1..2]-()-[:is_a]->(:{syllabic_name})
        AND s.name = $speaker
        AND d.name = $discourse
        with w
        match (n:{phone_name}:{corpus_name})-[:is_a]->(t:{corpus_name}:{syllabic_name}),
        (n)-[:contained_by*1..2]->(w)
        with w, n
        order by n.begin
        with w,collect(n)[0..1] as coll unwind coll as n

        MATCH (pn:{phone_name}:{corpus_name})-[:contained_by*1..2]->(w)
        where not (pn)<-[:precedes]-()-[:contained_by*1..2]->(w)
        with w, n,pn
        match p = shortestPath((pn)-[:precedes*0..10]->(n))
        with [x in nodes(p)[0..-1]|x.label] as onset
        return onset, count(onset) as freq'''.format(corpus_name=self.cypher_safe_name,
                                                     word_name=self.word_name,
                                                     syllabic_name=make_label_safe_for_cypher(syllabic_label),
                                                     phone_name=self.phone_name)
                res = self.execute_cypher(statement, speaker=s, discourse=d)
                for r in res:
                    data[tuple(r['onset'])] += r['freq']
        return data

    def find_codas(self, syllabic_label='syllabic'):
        """
        Gets syllable codas across the corpus

        Parameters
        ----------
        syllabic_label : str
            Subset to use for syllabic segments (i.e., nuclei)

        Returns
        -------
        data : dict
            A dictionary with coda values as keys and frequency values as values
        """
        from collections import Counter
        data = Counter()
        for s in self.speakers:
            discourses = self.get_discourses_of_speaker(s)
            for d in discourses:
                statement = '''match (w:{word_name}:{corpus_name})-[:spoken_by]->(s:Speaker:{corpus_name}),
                (w)-[:spoken_in]->(d:Discourse:{corpus_name})
        where (w)<-[:contained_by*1..2]-()-[:is_a]->(:{syllabic_name})
        AND s.name = $speaker
        AND d.name = $discourse
        with w
        match (n:{phone_name}:{corpus_name})-[:is_a]->(t:{corpus_name}:{syllabic_name}),
        (n)-[:contained_by*1..2]->(w)
        with w, n
        order by n.begin DESC
        with w,collect(n)[0..1] as coll unwind coll as n

        MATCH (pn:{phone_name}:{corpus_name})-[:contained_by*1..2]->(w)
        where not (pn)-[:precedes]->()-[:contained_by*1..2]->(w)
        with w, n,pn
        match p = shortestPath((n)-[:precedes*0..10]->(pn))
        with [x in nodes(p)[1..]|x.label] as coda
        return coda, count(coda) as freq'''.format(corpus_name=self.cypher_safe_name,
                                                   word_name=self.word_name,
                                                   syllabic_name=make_label_safe_for_cypher(syllabic_label),
                                                   phone_name=self.phone_name)

                res = self.execute_cypher(statement, speaker=s, discourse=d)
                for r in res:
                    data[tuple(r['coda'])] += r['freq']
        return data

    def encode_syllabic_segments(self, phones):
        """
        Encode a list of phones as 'syllabic'

        Parameters
        ----------
        phones : list
            A list of vowels and syllabic consonants
        """
        self.encode_class(phones, 'syllabic')

    def reset_syllables(self, call_back=None, stop_check=None):
        """
        Resets syllables, removes syllable annotation, removes onset, coda, and nucleus labels

        Parameters
        ----------
        call_back : callable
            Function to monitor progress
        stop_check : callable
            Function the check whether the process should terminate early
        """
        if call_back is not None:
            call_back('Resetting syllables...')
            number = self.execute_cypher(
                '''MATCH (n:syllable:%s) return count(*) as number ''' % self.cypher_safe_name)[0]['number']
            call_back(0, number)
        for s in self.speakers:
            discourses = self.get_discourses_of_speaker(s)
            for d in discourses:
                phone_rel_statement = '''
                        MATCH (p:{phone_name}:{corpus})-[:contained_by]->(s:syllable:{corpus}),
                        (s)-[:contained_by]->(w:{word_name}:{corpus}),
                        (s)-[:spoken_by]->(sp:Speaker:{corpus}),
                        (s)-[:spoken_in]->(d:Discourse:{corpus})
                        WHERE sp.name = $speaker_name
                        AND d.name = $discourse_name
                        with p,w
                        CREATE (p)-[:contained_by]->(w)
                '''.format(corpus=self.cypher_safe_name,
                           word_name=self.word_name,
                           phone_name=self.phone_name)
                self.execute_cypher(phone_rel_statement, speaker_name=s, discourse_name=d)

                phone_label_statement = '''
                        MATCH (p:{phone_name}:{corpus})-[:spoken_by]->(sp:Speaker:{corpus}),
                        (p)-[:spoken_in]->(d:Discourse:{corpus})
                        WHERE sp.name = $speaker_name
                        AND d.name = $discourse_name
                        with p
                        REMOVE p:onset, p:nucleus, p:coda, p.syllable_position
                '''.format(corpus=self.cypher_safe_name,
                           word_name=self.word_name,
                           phone_name=self.phone_name)
                self.execute_cypher(phone_label_statement, speaker_name=s, discourse_name=d)
                num_deleted = 0
                deleted = 1000
                delete_statement = '''
                MATCH (s:syllable:{corpus})-[:spoken_by]->(sp:Speaker:{corpus}),
                        (s)-[:spoken_in]->(d:Discourse:{corpus})
                        WHERE sp.name = $speaker_name
                        AND d.name = $discourse_name
                        WITH s
                        LIMIT 1000
                        DETACH DELETE s
                        RETURN count(s) as deleted_count
                '''.format(corpus=self.cypher_safe_name)
                while deleted > 0:
                    if stop_check is not None and stop_check():
                        break
                    deleted = self.execute_cypher(delete_statement, speaker_name=s, discourse_name=d)[0][
                        'deleted_count']

                    num_deleted += deleted
                    if call_back is not None:
                        call_back(num_deleted)

        statement = '''MATCH (st:syllable_type:{corpus})
                               WITH st
                               DETACH DELETE st'''.format(corpus=self.cypher_safe_name)
        self.execute_cypher(statement)
        try:
            self.hierarchy.remove_annotation_type('syllable')
            self.hierarchy.remove_token_subsets(self, self.phone_name, ['onset', 'coda', 'nucleus'])
            self.hierarchy.remove_token_properties(self, self.phone_name, ['syllable_position'])
            # self.reset_to_old_label()
            self.encode_hierarchy()
        except KeyError:
            pass

    @property
    def has_syllabics(self):
        """
        Check whether there is a phone subset named ``syllabic``

        Returns
        -------
        bool
            True if ``syllabic`` is found as a phone subset
        """
        return 'syllabic' in self.hierarchy.subset_types[self.phone_name]

    @property
    def has_syllables(self):
        """
        Check whether the corpus has syllables encoded

        Returns
        -------
        bool
            True if the syllables are in the Hierarchy
        """
        return 'syllable' in self.hierarchy.annotation_types

    def encode_syllables(self, algorithm='maxonset', syllabic_label='syllabic', call_back=None, stop_check=None):
        """
        Encodes syllables to a corpus

        Parameters
        ----------
        algorithm : str, defaults to 'maxonset'
            determines which algorithm will be used to encode syllables
        syllabic_label : str
            Subset to use for syllabic segments (i.e., nuclei)
        call_back : callable
            Function to monitor progress
        stop_check : callable
            Function the check whether the process should terminate early
        """

        self.reset_syllables(call_back, stop_check)

        onsets = self.find_onsets(syllabic_label=syllabic_label)
        if algorithm == 'probabilistic':
            onsets = norm_count_dict(onsets, onset=True)
            codas = self.find_codas(syllabic_label=syllabic_label)
            codas = norm_count_dict(codas, onset=False)
        elif algorithm == 'maxonset':
            onsets = set(onsets.keys())
        else:
            raise NotImplementedError

        statement = '''MATCH (n:{}:{}) return n.label as label'''.format(self.cypher_safe_name,
                                                                         make_label_safe_for_cypher(syllabic_label))
        res = self.execute_cypher(statement)
        syllabics = set(x['label'] for x in res)

        word_type = getattr(self, self.word_name)
        phone_type = getattr(word_type, self.phone_name)

        create_syllabic_csvs(self)
        create_nonsyllabic_csvs(self)

        splits = self.speakers
        process_string = 'Processing speaker {} of {} ({})...'
        if call_back is not None:
            call_back(0, len(self.speakers))

        for speaker_ind, s in enumerate(self.speakers):
            if stop_check is not None and stop_check():
                break
            if call_back is not None:
                call_back(speaker_ind)
                call_back(process_string.format(speaker_ind, len(self.speakers), s))
            discourses = self.get_discourses_of_speaker(s)
            for d in discourses:
                syllables = []
                non_syllables = []
                q = self.query_graph(word_type)
                q = q.filter(word_type.speaker.name == s)
                q = q.filter(word_type.discourse.name == d)
                q = q.order_by(word_type.begin)
                q = q.columns(word_type.id.column_name('id'), phone_type.id.column_name('phone_id'),
                              word_type.begin.column_name('begin'),
                              word_type.label.column_name('label'),
                              word_type.end.column_name('end'),
                              phone_type.label.column_name('phones'),
                              phone_type.begin.column_name('begins'),
                              phone_type.end.column_name('ends'))
                results = q.all()
                prev_id = None
                for w in results:
                    phones = w['phones']
                    phone_ids = w['phone_id']

                    if not phone_ids:
                        print('The word {} in file {} ({} to {}) did not have any phones.'.format(w['label'], d,
                                                                                w['begin'], w['end']))
                        continue
                    phone_begins = w['begins']
                    phone_ends = w['ends']
                    vow_inds = [i for i, x in enumerate(phones) if x in syllabics]
                    if len(vow_inds) == 0:
                        cur_id = uuid1()
                        if algorithm == 'probabilistic':
                            split = split_nonsyllabic_prob(phones, onsets, codas)
                        else:
                            split = split_nonsyllabic_maxonset(phones, onsets)
                        label = '.'.join(phones)
                        row = {'id': cur_id, 'prev_id': prev_id,
                               'onset_id': phone_ids[0],
                               'break': split,
                               'coda_id': phone_ids[-1],
                               'begin': phone_begins[0],
                               'label': label,
                               'type_id': make_type_id([label], self.corpus_name),
                               'end': phone_ends[-1]}
                        non_syllables.append(row)
                        prev_id = cur_id
                        continue
                    for j, i in enumerate(vow_inds):
                        cur_id = uuid1()
                        cur_vow_id = phone_ids[i]
                        if j == 0:
                            begin_ind = 0
                            if i != 0:
                                cur_ons_id = phone_ids[begin_ind]
                            else:
                                cur_ons_id = None
                        else:
                            prev_vowel_ind = vow_inds[j - 1]
                            cons_string = phones[prev_vowel_ind + 1:i]
                            if algorithm == 'probabilistic':
                                split = split_ons_coda_prob(cons_string, onsets, codas)
                            else:
                                split = split_ons_coda_maxonset(cons_string, onsets)
                            if split is None:
                                cur_ons_id = None
                                begin_ind = i
                            else:
                                begin_ind = prev_vowel_ind + 1 + split
                                cur_ons_id = phone_ids[begin_ind]

                        if j == len(vow_inds) - 1:
                            end_ind = len(phones) - 1
                            if i != len(phones) - 1:
                                cur_coda_id = phone_ids[end_ind]
                            else:
                                cur_coda_id = None
                        else:
                            foll_vowel_ind = vow_inds[j + 1]
                            cons_string = phones[i + 1:foll_vowel_ind]
                            if algorithm == 'probabilistic':
                                split = split_ons_coda_prob(cons_string, onsets, codas)
                            else:
                                split = split_ons_coda_maxonset(cons_string, onsets)
                            if split is None:
                                cur_coda_id = None
                                end_ind = i
                            else:
                                end_ind = i + split
                                cur_coda_id = phone_ids[end_ind]
                        begin = phone_begins[begin_ind]
                        end = phone_ends[end_ind]
                        label = '.'.join(phones[begin_ind:end_ind + 1])
                        row = {'id': cur_id, 'prev_id': prev_id,
                               'vowel_id': cur_vow_id, 'onset_id': cur_ons_id,
                               'label': label,
                               'type_id': make_type_id([label], self.corpus_name),
                               'coda_id': cur_coda_id, 'begin': begin, 'end': end}
                        syllables.append(row)
                        prev_id = cur_id
                syllables_data_to_csvs(self, s, d, syllables)
                nonsyls_data_to_csvs(self, s, d, non_syllables)
        import_syllable_csv(self, call_back, stop_check)
        import_nonsyl_csv(self, call_back, stop_check)
        if stop_check is not None and stop_check():
            return

        if call_back is not None:
            call_back('Cleaning up...')
        for s in self.speakers:
            discourses = self.get_discourses_of_speaker(s)
            for d in discourses:
                self.execute_cypher(
                    '''MATCH (s:{corpus_name}:Speaker)<-[:spoken_by]-(n:{corpus_name}:syllable)-[:spoken_in]->(d:{corpus_name}:Discourse)
                    where s.name = $speaker_name
                    AND d.name = $discourse_name and n.prev_id is not Null
                    REMOVE n.prev_id'''.format(corpus_name=self.cypher_safe_name), speaker_name=s, discourse_name=d)

        self.hierarchy.add_annotation_type('syllable', above=self.phone_name, below=self.word_name)
        self.hierarchy.add_token_subsets(self, self.phone_name, ['onset', 'coda', 'nucleus'])
        self.hierarchy.add_token_properties(self, self.phone_name, [('syllable_position', str)])
        self.encode_hierarchy()
        if call_back is not None:
            call_back('Finished!')
            call_back(1, 1)

    def enrich_syllables(self, syllable_data, type_data=None):
        """
        Sets the data type and syllable data, initializes importers for syllable data,
        adds features to hierarchy for a phone

        Parameters
        ----------
        syllable_data : dict
            the enrichment data
        type_data : dict
            By default None
        """
        if type_data is None:
            type_data = {k: type(v) for k, v in next(iter(syllable_data.values())).items()}
        syllables_enrichment_data_to_csvs(self, syllable_data)
        import_syllable_enrichment_csvs(self, type_data)
        self.hierarchy.add_type_properties(self, 'syllable', type_data.items())
        self.encode_hierarchy()

    def _generate_stress_enrichment(self, pattern):
        syllable = self.syllable
        all_syls = self.query_graph(syllable).all()
        enrich_dict = {}

        for item in all_syls:
            syl = item['label']
            splitsyl = syl.split('.')
            nucleus = splitsyl[0]
            for j, seg in enumerate(splitsyl):
                if re.search(pattern, seg) is not None:
                    nucleus = seg
            r = re.search(pattern, nucleus)
            if r is not None:
                end = nucleus[r.start(0):r.end(0)].replace("_", "")
                nucleus = re.sub(pattern, "", nucleus)
                fullpatt = str(nucleus) + str(pattern).replace("$", "")
                syl = re.sub(fullpatt, nucleus, syl)
                enrich_dict.update({syl: {'stress': end}})
        return enrich_dict

    def _generate_tone_enrichment(self, pattern):
        syllable = self.syllable
        all_syls = self.query_graph(syllable).all()
        enrich_dict = {}
        for x in all_syls.cursors:
            for item in x:
                syl = item[0]['label']
                splitsyl = syl.split('.')
                nucleus = splitsyl[0]
                for seg in splitsyl:
                    if re.search(pattern, seg) is not None:
                        nucleus = seg
                r = re.search(pattern, nucleus)
                if r is not None:
                    end = nucleus[r.start(0):r.end(0)].replace("_", "")
                    nucleus = re.sub(pattern, "", nucleus)
                    fullpatt = str(nucleus) + str(pattern).replace("$", "")
                    syl = re.sub(fullpatt, nucleus, syl)

                    enrich_dict.update({syl: {'tone': end}})
        return enrich_dict

    def encode_stress_to_syllables(self, regex=None, clean_phone_label=True):
        """
        Use numbers (0-9) in phone labels as stress property for syllables.  If ``clean_phone_label`` is True,
        the numbers will be removed from the phone labels.

        Parameters
        ----------
        regex : str
            Regular expression character set for finding stress in the phone label
        clean_phone_label : bool
            Flag for removing regular expression from the phone labels
        """
        if regex is None:
            regex = '[0-9]'

        enrich_dict = self._generate_stress_enrichment(regex)

        if clean_phone_label:
            self.remove_pattern(regex)
        self.enrich_syllables(enrich_dict)
        self.encode_hierarchy()

    def encode_tone_to_syllables(self, regex=None, clean_phone_label=True):
        """
        Use numbers (0-9) in phone labels as tone property for syllables.  If ``clean_phone_label`` is True, the numbers
        will be removed from the phone labels.

        Parameters
        ----------
        regex : str
            Regular expression character set for finding tone in the phone label
        clean_phone_label : bool
            Flag for removing regular expression from the phone labels
        """
        if regex is None:
            regex = '[0-9]'

        enrich_dict = self._generate_tone_enrichment(regex)

        if clean_phone_label:
            self.remove_pattern(regex)
        self.enrich_syllables(enrich_dict)
        self.encode_hierarchy()

    def encode_stress_from_word_property(self, word_property_name):
        """
        Use a property on words formatted like "0-1-0" to encode stress on syllables.

        The number of syllables and the position of syllables within a word will also be encoded
        as a result of this function.

        Parameters
        ----------
        word_property_name : str
            Property name of words that contains the stress pattern

        """
        if 'syllable' not in self.annotation_types:
            raise Exception('Syllables have not been encoded.')
        if not self.hierarchy.has_type_property(self.word_name, word_property_name):
            raise Exception('Word types do not have a property {}.'.format(word_property_name))
        if not self.hierarchy.has_type_property(self.word_name, 'num_syllables'):
            self.encode_count('word', 'syllable', 'num_syllables')
        if not self.hierarchy.has_type_property('syllable', 'position_in_word'):
            self.encode_position('word', 'syllable', 'position_in_word')

        for s in self.speakers:
            discourses = self.get_discourses_of_speaker(s)
            for d in discourses:
                statement = '''MATCH (s:syllable:{corpus_name})-[:spoken_by]->(speaker:Speaker:{corpus_name}),
                            (s)-[:spoken_in]->(discourse:Discourse:{corpus_name}),
                            (s)-[:contained_by]->(w:word:{corpus_name})-[:is_a]->(wt:word_type:{corpus_name})
                            WHERE speaker.name = $speaker_name
                            AND discourse.name = $discourse_name
                            AND wt.{word_property_name} is not null
                            WITH s, w, split(wt.{word_property_name}, '-') as stresses
                            WHERE size(stresses) = w.num_syllables
                            SET s.stress = stresses[s.position_in_word-1]'''.format(
                    corpus_name=self.cypher_safe_name, word_property_name=word_property_name)
                self.execute_cypher(statement, speaker_name=s, discourse_name=d)
        self.hierarchy.add_token_properties(self, 'syllable', [('stress', str)])
        self.encode_hierarchy()

redpajama_set_name: RedPajamaGithub


2010 Grapplers Quest Tachi Palace Challenge Results.
Exclusive: Eddie Bravo on UFC, Jiu-Jitsu, Royler Gracie and rock bands.
It really is true! They do BJJ on the beach in Brazil.
2011 Promotion Day at the Renzo Gracie Academy.
Eddie Bravo teaches the "Sorcerer".
Next post Saulo announces he's coming out of retirement... Again!
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text:
Paolo Banchero reacts to playing Kevin Durant for the first time
November 28, 2022, 11:59 PM ·2 min read
When Paolo Banchero grew up in Washington, the eventual No. 1 pick by the Orlando Magic often watched Kevin Durant play with the Seattle SuperSonics. He even got to see him closely in a pro-am game in the Pacific Northwest.
On Monday, Banchero got to face him for the first time in the NBA.
Banchero and the Magic matched up against Durant and the Nets, and got a first-hand view of yet another signature performance by the former MVP. Durant dropped a season-high 45 points, seven rebounds, five assists, two steals and two blocks in the 109-102 win.
Durant scored 19 points alone in the third quarter and only missed one shot in 13 attempts in the second half. He only missed five shots for the entire game. In other words, Durant had his way with Banchero and every other player the Magic sent at him.
"That was definitely a great performance," Banchero said. "He didn't miss many shots. That was a tough cover, man. I don't got much to say about that. That was just amazing. That's what he does. That's Kevin Durant."
Banchero tied a team-high with 24 points to lead the Magic in 38 minutes of work. It was his 10th game with at least 20 points, the most by a rookie this season. He also added five assists, four rebounds and two steals on 9-of-17 shooting from the field.
Banchero studied Durant often growing up and tried to take bits of his game and incorporate them into his own. He even tried to recruit him to Orlando when Durant requested a trade from the Nets over the offseason, something that was seen as a joke in nature.
The two had the opportunity to speak after the game on Monday at the Barclays Center. Durant signed a jersey for him and gave the 20-year-old some advice.
Banchero shared some of the message from Durant.
Just to keep going, stay healthy. He was showing his respects. I did the same. That is was one of the guys I always watched growing up. He played for the Sonics, came to Seattle for the pro-am. I remember watching him when I was really young, like 12 years old watching him play at (the pro-am at) the Seattle Pacific (University) gym. It is crazy to be on an NBA floor against him. It is a full-circle moment.
Although Banchero and the Magic left with a loss, the contest is likely one that Banchero will remember for quite some time after facing a legend like Durant.
Story originally appeared on Rookie Wire


Offering careers advice to your child can be a hard conversation to have. You may not know which information is correct, what advice to give or which tools and resources they could find the most useful.
The best way to start the conversation about your child's career choice is to find out about what they are interested in and what they enjoy doing. Approach a question such as "What subject do you enjoy the most at school?" and begin to narrow down the choices from there. Your child may have a rough idea of what job they want to go into, or they may have no clue at all. Both of these situations are perfectly fine and it is important to remember that children make decisions at different times in their life to others.
As your child approaches the age of 14, they are going to begin the process of making decisions that will impact their future. This often starts in Year 9 or 10 at School where they decide on their options of different subjects to study. This is where the initial thoughts of career choices begin to hit their minds.
The next challenge that your child may face will be when they are preparing to leave School. At this point, your child will need to make a decision on where to continue education or training. The options at this stage are either Sixth Form or College to study BTECs or A Levels or alternatively they could progress onto an Apprenticeship with an employer. In order to make a decision on which route to take, your child should have a strong idea of what career choice they want to pursue. If you would like more information about these options, please visit our Careers Hub.
All of these tools aim to provide a way of identifying your child's interests and strengths to highlight a career choice that would suit them the best. Once they have an idea of what area of work they would like to progress into, you can then begin researching which route of education and training will be the most beneficial to help them succeed.
During their post-16 education or training, your child may change their mind on their career choice. At this stage, this is normal and is a great opportunity for your child to explore other options. A common reason for young people changing their mind on their career choice is due to it not being what they expected. Their ability to identify this shows great maturity and it is a great learning curve for their personal progression. To ensure you are supporting them through this stage of their learning and development, you can begin to start the conversation about what other options they may consider. We suggest asking them what aspects of the previous career choice they enjoyed the most and the least. You can then apply these job requirements, tasks and knowledge to other job roles or sectors. A great tool to use is the Skills Health Check as it will suggest similar or recommended job roles for each user.
We recommend that throughout this process you reassure your child that everyone's journey is different and that trying new things out of their comfort zone may lead to them finding the best career choice for them.
If your child still needs extra support, you can submit an enquiry to our Careers Team who will provide 1 to 1 Careers Advice.
We also offer an Employability Programme to young people ages 16 to 18 to gain confidence, key employability skills and experience before entering the world of work. If you feel like your child needs this support, they can apply here.


text:
Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Chapter 9 Chapter 10 Chapter 11 Chapter 12
All Themes Appearances vs. Disappearances Secrets, Lies, and Silence Innocence vs. Guilt Loneliness, Exclusion, and Prejudice Expectations, Ambition, and Disappointment
All Characters Lydia Lee Marilyn Lee James Lee Nath Lee Hannah Lee Doris Walker Jack Wolff Officer Fiske
All Symbols Water/Swimming/the Lake Harvard/Radcliffe The Betty Crocker Cookbook Doctors Eggs Lydia's "Baby Soft" Perfume
Instant downloads of all 1010 LitChart PDFs (including Everything I Never Told You).
Appearances vs. Disappearances
Secrets, Lies, and Silence
Innocence vs. Guilt
Loneliness, Exclusion, and Prejudice
Expectations, Ambition, and Disappointment
Nath Lee
Hannah Lee
Doris Walker
Jack Wolff
Officer Fiske
Water/Swimming/the Lake
Harvard/Radcliffe
The Betty Crocker Cookbook
Lydia's "Baby Soft" Perfume
Everything I Never Told You Chapter 11 Summary & Analysis
LitCharts assigns a color and icon to each theme in Everything I Never Told You, which you can use to track the themes throughout the work.
Days before Lydia's death, Nath is desperate to leave Middlewood. As he packs for his campus visit, he also mentally organizes his belongings, picking what he will take when he enrolls at Harvard later in the year. The Lees do not travel; they once went to Gettysburg and Philadelphia, but they attracted so many stares that it was the last trip they ever took. Nath opens Lydia's door and asks her to choose between two shirts, one of which he's bought recently. He explains that there will be a visiting students mixer on campus, and that his host will be throwing an end-of-semester party. When Nath tries on the new shirt, Lydia is stunned by how good he looks, yet tells him to wear the other one.
In this passage, travel is presented as both a threat and opportunity. Leaving Middlewood gives Nath the chance to detach himself from his family and all their problems, and to reinvent himself as a new, unencumbered person. However, the trip to Pennsylvania illuminates the alienation and even danger that the Lees risk in traveling around the country as a mixed-race family.
Later that night, Lydia goes into Nath's room, wanting to tell him about Louisa. She sees Nath on the floor, staring out at the night sky. He invites Lydia to sit next to him, and the two gaze up together, awestruck. The next morning, Lydia asks Nath to promise that he'll call to let her know how it's going. Nath promises as he rushes out the door, but the weekend passes and he doesn't call. Meanwhile, Hannah follows Lydia around, suggesting things for them to do together. On Sunday afternoon, Hannah suggests that they go to the lake, and Lydia suddenly notices that Hannah is wearing her silver locket. Hannah quietly confesses that she thought Lydia didn't want it. Remembering the words James said as he gave it to her, Lydia slaps Hannah and yanks the necklace from her neck. She tells Hannah softly that Hannah doesn't want the necklace even if she thinks she does, and that she should never smile if she doesn't want to.
This passage highlights Lydia's liminal position between childhood and adulthood, which is further accentuated by the fact that she is a middle child. Around Nath, Lydia is very much a shy, deferential younger sibling; she craves Nath's attention and approval in the same way that Hannah craves hers. However, Lydia's interactions with Hannah in this scene reveal a new, more adult side to her. Lydia is determined that Hannah not succumb to the same pressures that James and Marilyn place on Lydia herself. She takes on a kind of parental role to Hannah as a form of protection against their real parents.
That evening, Lydia calls Nath's host at Harvard; when someone picks up the phone, she can hear the sounds of a party in the background. When Nath gets on the phone, Lydia suddenly tears up, but Nath is rude and dismissive, clearly annoyed by her call. He taunts her about the possible reasons she could be calling, and Lydia is struck by the feeling that Nath has already become a "stranger." Eventually, Nath bitterly suggests that Lydia speak to Jack about her problems and hangs up. Although he will later be haunted by those words, at the time he returns to the party, feeling happily detached from his family. Back at home, Lydia feels a sense of anger building within her. Nath has changed, and so has Lydia—she wants to hurt him, the same impulse that caused her to slap Hannah.
Nath's sudden coldness and cruelty to Lydia reflects his feeling that he needs to make an absolute break with his family in order to be free of them. This echoes Marilyn's decision to disappear without telling her family, and to call them every day without saying anything. Nath's attention is entirely focused on creating a new life for himself at Harvard, and Lydia's phone call is a highly unwanted interruption to that goal. After years of providing support to Lydia, Nath suddenly switches course in order to free himself from the oppressive clutch of his family.
On Monday morning Lydia wears lipstick and a beautiful dress James bought for her. At the breakfast table, James tells her "all the boys will be after you now," and Marilyn reminds her to come straight home after school because Nath will be back. That afternoon, Lydia suggests to Jack that they drive up to the Point, a spot overlooking Middlewood where teenagers often drive to have sex. In the car, Jack asks about Nath, wondering if Lydia has missed him and whether he'll come back from Harvard for the holidays. Lydia only replies "who cares," and opens the glove compartment to retrieve the box of condoms. Jack is surprised, but Lydia assures him she won't regret it and kisses him. She wants to be "transformed" by the time Nath returns home and she wants "something new to tell him."
Now that Nath is about to leave for college, Lydia associates her own innocence and childishness with distance from her brother. She seems to think that if she loses her innocence by having sex with Jack, this will somehow bridge the gap between her and Nath. In reality, not only will having sex do nothing to change the fact that Nath is going to college, but Nath also hates Jack and thus is unlikely to feel closer to Lydia as a result of knowing she's had sex with him. However, Lydia is so desperate to prevent Nath's inevitable departure that her mind is driven to irrational solutions.
Get the entire Everything I Never Told You LitChart as a printable PDF.
Jack pulls away from Lydia and looks at her with kindness, but without lust. Hurt, Lydia asks if she's not good enough for him. Jack replies that the problem is Nath, and when Lydia tells him Nath doesn't matter, Jack replies "he matters to me." Lydia is shocked, and Jack gently explains that his reputation as someone who sleeps with lots of girls is designed to crush any suspicions about his sexuality. Lydia remembers all the times Jack brought up Nath and is stunned by how "stupid" and "wrong" she could have been. Jack apologizes, and Lydia responds that she is sorry for him, because he is "in love with someone who hates you." Jack is clearly hurt, and says that at least he knows what he wants and doesn't let other people boss him around. Lydia threatens to tell Nath and the whole school about Jack's feelings, and before Jack can stop her she gets out of the car.
Lydia's reaction to Jack's revelation illustrates the ways in which—despite her best efforts—she is still childishly self-centered. Rather than feeling sympathy for Jack's inner turmoil or his fear of homophobia, she focuses only on how Jack's love for Nath affects her personally. To Lydia, Jack's love is something else Nath has "won" at her expense (even though this makes little rational sense, especially considering that Nath hates Jack). Furthermore, Lydia further torments Jack by reminding him that his love for Nath is unrequited and by threatening to tell others about it—an act of startling cruelty.
Lydia runs home and finds Marilyn sweeping the porch. Marilyn suggests that they study for Lydia's exams together, but Lydia snaps that she doesn't need her mother's help. Surprised, Marilyn replies that "there's not much time left" before exams begin. At dinner, Nath talks excitedly about his visit to Harvard and James occasionally joins in with nostalgic remarks about Cambridge. Lydia, meanwhile, barely notices the conversation taking place around her. She fixates on Jack, wondering where everything went wrong. At 2am, she is suddenly seized by the impulse to go to the lake. Sitting on the dock, she reflects that this is the closest she's been to the water since Nath pushed her in. She realizes that Jack was right; she is afraid of everything, so desperate to please her mother and keep the family together that she has destroyed her own chance at happiness. She'd always been afraid of losing Marilyn and James, and now she is afraid of losing Nath, "who had always kept her afloat."
Filled with regret, Lydia blames herself for always saying "yes" to her mother and thereby ruining her own life. However, she is also intent on isolating a single moment in which everything in her life went wrong, and eventually she determines that it was when Nath pushed her into the lake. Of course, in reality there is no single moment to blame, but rather an accumulation of thousands of tiny decisions, actions, and events. However, as with Nath's departure, Lydia is desperate to find some sense of control over the events of her life. She fantasizes that by returning to the lake, she will somehow be able to undo all the terrible things that she believes originated there.
The day Nath pushed her into the lake was also the day that Lydia first realized how "suffocating" it was to be loved as her parents loved her. She had even felt a perverse sense of gratitude for being plunged into the water. However, Nath's hands helping her out had then seemed like a wonderful sense of reassurance; ever since then, Lydia thinks, Nath has been helping her not to drown. Lydia promises herself that from now on, she will stop lying to her family to make them happy and pretending to be someone she's not. She will tell Marilyn "it's not too late," will apologize to Jack, and tell Nath that he doesn't need to worry about leaving her. Lydia decides she must "seal her promises," and gets into the boat. She expects to feel nervous, but instead feels peaceful and confident. She rows out and looks at the water, feeling certain that she will be able to swim back to shore as long as she kicks, just like Nath told her. She plans to ask Nath all about Harvard the next day. She tells herself "it will be alright" and jumps into the water.
Although we might expect the description of Lydia's final moments to provide resolution to the question of how and why she dies, this passage is in fact mysterious and inconclusive. As in previous scenes, Lydia is acting in an irrational manner; desperate to assert control over her life, she decides that she must return to the lake and re-submerge herself in the water in order to fix her mistakes and begin again. In this sense, Lydia seeks a rebirth similar to the spiritual rebirth of Christians who are baptized or "born again" through being submerged in water. However, it is unclear where her sudden confidence in her own ability to swim comes from. Why does she throw herself so willingly into the water when it is objectively likely that she will drown?
Related Quotes with Explanations
Seresin, Indiana. "Everything I Never Told You Chapter 11." LitCharts. LitCharts LLC, 23 Feb 2017. Web. 15 Jul 2019.
Seresin, Indiana. "Everything I Never Told You Chapter 11." LitCharts LLC, February 23, 2017. Retrieved July 15, 2019. https://www.litcharts.com/lit/everything-i-never-told-you/chapter-11.


By adding some Custom CSS I've managed to adjust the overlay in the way I want so hovering anywhere over an image will bring up a black overlay with lowered opacity and will reveal the caption title.
I want to be able to click anywhere on each image to be directed to the image's webpage, but clicking on or close to the caption title does nothing; this is a particularly big problem when viewing the website in mobile as the caption titles cover nearly the entire final two images so those webpages are basically inaccessible on mobile.
I've experimented with the z-index property of bringing the black overlay on top of the caption title and that allowed me to click anywhere on the image to go to its webpage, but it also covered the image captions with the black overlay so they were darker - I still want them to be white and have good contrast against the black. I've also experimented with the pointer-events property, but that hasn't changed anything.
Any advice on the best way to approach this?
to the image-title-desc class and now I can click anywhere on the images (including over the image caption) to go to the next webpage.


text:
Q: NodeJS Returning 'undefined' In MySQL Query Function I have a function that queries SQL to get a string called Prefix.
function getPrefix(Guild) {
    let query = "SELECT Prefix FROM Guilds WHERE GuildId=?";
    Connection.query(query, [Guild.id], (err, result) => {
        if (err) throw err;
        return result[0].GuildPrefix;
    });
};

Whenever I print the Prefix out (console.log(result[0].Prefix);), it logs it fine - however, whenever I return it and then attempt to call the function, it always returns undefined.
I am using Node JS Version 10.15.1 & I am using MariaDB Version 10.1.37 on the Raspbian stretch of Debian. Please comment if I have left any other information out. Thanks.

A: In Nodejs the functions related to mysql are always asynchronous which means they will either not return anything or will retuen undefined.
So the solution is to use a callback function.

Eg.
function getPrefix(Guild, callback) {
    let query = "SELECT Prefix FROM Guilds WHERE GuildId=?";
    Connection.query(query, [Guild.id], (err, result) => {
        if (err){
         callback(JSON.stringify(err));
        };
        callback(JSON.stringify(result));
    });
};

redpajama_set_name: RedPajamaStackExchange


I am trying to use Theme My Login widget for login on my site. There seem to be two issues.
Sorry, I've looked everywhere but I can't find the page you're looking for.
Is this something you can help me with? Once again, I am really new at this and I don't want to be asking questions that are not appropriate for this forum.
Ummm… I'm not familiar with the plugin… however I believe Prasanna has some experience with it. I would suggest "twittering" him, as that seems to be the best way.


I've heard it said "health affects work, and work affects health." But employee health is vastly underrated in many organizations across the country. Even the employee population of many wellness and health care businesses—the industry that should be healthiest of all—is representative of the general population. Some are overweight, some have physical conditions, and some are on regular medication for a variety of issues, including pain, hypertension, high cholesterol and diabetes, to name a few.
The fact remains that many chronic health conditions, such as heart disease, diabetes, and stroke, are preventable and often linked to lifestyle choices, according to the Centers for Disease Control and Prevention.
In business, "employee wellness" has a dual impact. Of course wellness is a cost to the individual employee. Just one major health event can lead to a whole chain of difficulties for an individual and his or her family, from emotional challenges to the logistical nightmares of caregiving through injury or illness, all on top of loss of income, loss of home, bankruptcy and a host of other personal trials.
But employee health also has major ramifications for the company, and the cost of ignoring wellness outweighs the expense of providing benefits. Poor employee wellness cuts into the overall bottom line, leading to higher insurance premiums, more sick days, lost productivity and tapped short-term disability coverage. For these reasons, employee wellness is no longer a human resource issue, but rather a broader business issue.
An organizational focus on health starts at the top, in the c-suite. If team members know leaders take time out to focus on exercise, wellness and healthy choices, they are more apt to model those behaviors in their own lives. It's not about "do as I say," but rather, "do as I do," and positive example setting and reinforcement at all levels of the company.
Health insurance offerings for full-time employees are a given, but organizations can go a step further and create health insurance plans that put a meaningful emphasis on wellness. For example, start with an annual wellness exam for each employee (and his or her covered family members) that covers key health areas, such as body mass index, blood pressure, glucose and cholesterol. Each score that falls in the positive, "healthy" range earns cash deposits into the employee's health savings account (HSA). These dollars can be used for copays, prescriptions or to offset the annual deductible, and they can add up to significant dollars—in some cases, up to $1,000 per individual or $2,000 per household.
What's more, the company can track the overall health of its employees. Of course, per HIPAA terms, no individual details are released, but the leadership can see if wellness is improving on the whole by observing aggregate participation, scores and results over time.
The trends in wellness data can help organizations identify ways to further improve health coverage for employees. For example, if chronic blood pressure or cholesterol issues are common, the company may add a benefit that covers the cost of generic statins at 100 percent. Understanding that for some, not even diet or exercise can lower blood pressure and cholesterol levels, the organization has recognized the financial burden many employees face and offered support for a health issue that might be beyond the control of any given employee—while still allowing them the opportunity to improve their personal health.
Across America, obesity continues to be a major risk factor for chronic health conditions, and it should remain a high-priority issue for any corporate wellness program. As people mature, obesity becomes a greater challenge, and for team members who are on their feet all day long, being overweight can cause lower back issues and knee or joint pain.
Consequently, smart organizations put a lot of focus on weight loss and healthy living. For example, a policy can prohibit funding any kind of meal that isn't healthy for team members. Instead of purchasing sodas for events, provide water. For meals or snacks during large company meetings, provide healthy choices instead of fast food. This is often more expensive in the short run, but it leads to cost savings for everyone in the long run.
A combination of company-provided fitness trackers and sponsored programs that encourage healthy competition can work wonders for overall employee health. There are countless corporate success stories of employees losing weight and achieving exceptional improvement in daily exercise habits through monthly step count competitions or online fitness challenges. While not everyone loses weight, there are many mental health improvements that come from a change in attitude, mobility and a general sense of wellbeing.
As October is Breast Cancer awareness month, we would be remiss not to mention the importance of getting an annual mammogram beginning at age forty.
While there is no cure for breast cancer today, mammography remains our best defense. According to the American Cancer Society, when breast cancer is detected early (at stage zero or stage one), the five-year survival rate is close to 100 percent. So regular mammography offers not only long-term, life saving benefits but even short-term quality of life improvements. The earlier a woman finds any breast health issue, the better her opportunity to avoid more invasive (and expensive) treatments like chemotherapy or mastectomies.
The bottom line is healthy living is good for individual employees and for business. It's a true win-win, and it's a no-brainer for a company to invest in the very people that make it successful. Whatever your industry, be in the business of wellness, empowerment and accountability for employee health. All involved will reap the benefits.