Welcome back for another day of organization tips and tricks. I hope you have ben enjoying all the wonderful ideas the team has shared with you. Today we are tackling die storage!
I store my dies in these clear zippered bags from Clear Bags. I will soon be switching them out to the new Storage Pockets from MFT. I've resisted buying the Storage Pockets for a few months now, but after seeing how fabulous they are in action, I have caved and purchased a ton of them.
Just in case you are wondering,yes, I am completely insane! I do die-cut and adhere even the tiniest of pieces. For something like this set of dies, I will add the adhesive to the card stock before I die-cut. Adhering them to the card stock is a breeze!
I store the STAX dies and the Blueprints dies together in one box. These are the dies that I reach for on every single card. This box has a permanent spot on my stamping desk.
I currently have all my dies sitting inside these thin Ikea boxes. They will soon be moved to the clear fridge organizer boxes that everyone raves about. Those beauties arrived yesterday, and I can't wait to get everything moved over.
Be sure to check out the MFT Blog to see how the rest of the team organizes their dies. You'll also want to check out the prize package for today. Who knows, YOU could be the lucky winner!
Wonderful info and ideas! Tfs!
I love the idea of cutting out the dies to see what they look like. What a great idea.
I had been thinking about cutting out all my dies and putting the pictures in a notebook- but I never thought about putting them with the dies- GREAT IDEA!
Julie...Your organizational methods and skills are FABULOUS!!!!!!! Thank you so much for sharing.
Love the idea of die-cutting the set from cardstock and including them in your storage pocket for reference. But all those little confetti pieces?!?!?! That is dedication right there!! Good for you!
I don't think you're insane....love how you have a sample of the die cuts. I need to adopt this. Sometimes it's not as easy to see how the die cuts from just looking at the actual die. I am also going to cave in and buy those pockets. The price is quite reasonable.
Omg this is fabulous! I just typed all my info in and published it and it wasn't there. 😔 anyway this is an awesome idea! I'm always looking for ways to organize better. I'm going to give this a try. Thanks so much for sharing!
Love it!! This way your dies will are all ready to go when it's play time.
So organized and your stash looks great, even in those current boxes. Fabulous idea about cutting out each piece to make sure it goes back in the right place. Thanks for sharing.
I just love the idea of cutting it out for a reference. This makes it easier for clean up!!
I think the idea of cutting them out of cardstock when you get them is a fabulous idea. I'm going to have to use that for sure. This hop about storage is great for me right now, because I just started making cards and setting things up in my craft area.
wow, your labelling is insane...but I can so see why you like to do that. I have to do the same thing with my stamps so I can SEE what there is in the set, even the little pieces. You are all rocking awesome and so is this week. thank you for amazing products and the giveaway!
I love your idea of die cutting everything so you know where everything belongs. Also it just looks great!


Wednesday | The Lands of Custoza, a Bike tour through into the History – From the beautiful historic building "Villa Venier" in Sommacampagna, through an asphalt / dirt road made of secondary roads to low speed and countryside, Bike Experience wants to give you the thrill of discovering the Morenine Hills of Custoza, a unique territory immersed in nature, crossing the historic centers of some characteristic villages of the territory such as Custoza, famous for the wine "Custoza Doc", but theater of battles for the Italian independence of 1848 and 1866. A journey to rediscover the history of these battles through historic villas and courts where episodes marked the outcome of the clashes between the Austrian armies and the Piedmontese armies before and after Italian one with the striking backdrop of the Ossuary of Custoza where you will be welcomed by our guides; you can also immerse yourself in the reality of such crucial moments for the history of Unification of Italy. A path suitable for everyone where it is possible by reservation to live and discover the typical local products that this territory gives us through a stop in one of the farms in the area.
A jump in history, four steps in environments full of suggestions and memories of the past, a land steeped in emotion left by those who fought, suffered, sweat and celebrated.
A journey where the battles were the protagonists of the Renaissance and where history is running next to the major events, history of everyday gestures, tension and hope for a better future. The map will suggest the path that you wish to discover, moment by moment. It will show you the sites of the battles: Villas, churches, countryside, monuments. Vestiges of a period which saw Italy dominated by the foreign. The French who gave way to the Habsburgs during the Congress of Vienna, who ruled with an iron fist. The fire of freedom hatched a long under the ashes; the revolutionary movements often failed due to the lack of adherence to libertarian thought through the people perpetually exploited. Most of the people lived or survived better in ignorance; therefore they found it hard to understand the need for this further struggle. Riots continued, reaching their peak with the Five Days of Milan (March 1848), which saw the victory of the patriots on the troops of Marshal Radetzky, forced to withdraw from the city and then to defend in the Austrian defensive system of the quadrilateral.
It is during April 1848 and June 1866 that these green hills became a battleground for clashes between the Piedmontese and the Austrians. The negotiations for the armistice took place in Villafranca in July 1860; Italy was not unified yet; Verona was annexed to the Kingdom of Italy with a plebiscite in October 1866.
July 23, 1848 – Our Lady of Health and bloody clashes and the conquest of Sommacampagna by the Austrians.
July 24, 1848 – A Staffalo, Mount croce, Mount Torre, Pezzarara, from Via Villanova and via Carrari, the Piedmontese counterattack, regaining Sommacampagna.
July 25, 1848 – The Austrians counter-attack at Ca 'Nova, berettara Ca and Ca' del Sale. The Piedmontese resist until the last bastions of Montegodi and Custoza and fall back towards Villafranca.
July 26, 1848 – Through the intercession of Fr Burti, the order of destruction inflicted to punish the help given to the Piedmontese mute and suffers Sommacampagna Plunder victim.
June 24, 1866 – Assault of the Grenadiers of Sardinia to the farm Cavalchina and Monte Croce.
The history of the land and human settlements that were the scene of the liberation of the Renaissance are very old. The historical reports of Sommacampagna dates since 38 BC, when the temple was erected in Leituria, a local deity, in the place where now stands St. Andrew (XI sec.) In the existing cemetery.
Sommacampagna at that time was a small rural town inhabited by a few shepherds and farmers, next to two major roads: the Gallica and the POstumia. The local landscape was to be that of a small island planted with few trees, cereals, vines and "mela lanata" (modern peach) within a wide area mainly wooded, which fueled the consumption of timber, grazing and hunting. A vital problem was the water, because of the ground. The place must not have undergone substantial changes over a period of time that separated it from the Middle Ages.
We return to talk about Sommacampagna in a parchment of 1035 where it is mentioned also the parish church of St. Andrew which had a recall on the whole area of the Verona countryside and also on the south-central part of the morenica-gardesana. In the 12th century, the country was a big "pasture bush" divided here and there with scrub oak supporting pig farming, hornbeams, beeches and oaks. The fauna consisted of deer, wild boar, wolves and birds. At that time the settlement had developed around the church. In the 14th century, the area was so poor than all the surrounding areas, including Custoza who was "villa" in itself. Between 1405 and 1797 Sommacampagna passed under the flag of San Marco, which replaced the effigy of Verona. But already at that time the population was indifferent to the domains that alternated, experience had shown that the goodness of crops depended on the strength of those who cultivated the lands and Jupiter Pluvio and certainly not by the political authority. Custoza even during Venetian period maintained its independence and territorial jurisdiction. In 1530 souls living in the two centers were estimated at about 600 units; almost as many were living in Caselle or scattered in the countryside or in the woods. Population growth remained almost completely unchanged: just before the outbreak of the 1630 Sommacampagna were 1450 people of which 704 residents in the capital city, almost all original. At that time 70% of the crop was planted with trees, with a preponderance of the vine and mulberry, all crops were adapted to nitrogen-poor soils such as those on moraine hills. The economic resources were sufficient to ensure the mere survival, nothing more; religion taught to accept the policy ran its own ends. The plague of 1630 found a fertile ground, so much so that Sommacampagna only 240 people survived the virus. Custoza already from 1613 was completely deserted. After a demographic disaster usually explodes birth; In fact, within a generation is returned to the ante-plague population number. A few powerful families, in addition to the nobles, held the most significant slice of the lands, held mostly in the grass or arable land (forage, grain, millet, grapes and mulberry) and used to rent.
During the 18th century, in the wake of the Venetian fashion, and thanks to the huge assets, many of these powerful families began to build mansions, often extending existing buildings surrounded by lush vegetation. The Venetian culture has left out the most incisive in today; I am witness to the many villas located in the territory. At the time of the fall of the Lion of St. Mark (1795), Custoza remained an independent entity. In the 19th century, the land area and administrative changed four times. At the beginning of 1800 Sommacampagna was a border land. The French who took over in 1801 the Venetians took it as the capital; in 1805, applied the territorial reform, it found itself assigned to the canton of Villafranca, while Custoza became at that time part of the future Municipal. The population held jobs mostly agricultural and commercial activity was modest. Still crops remained unchanged as well as the agricultural landscape. The eagle Habsburg succeeded to the representative of Bonaparte in 1814, changing Planning; Sommacampagna kept Custoza, depending, however, from Villafranca. Even this new master did not bring improvements nor did partaker of the modest benefits that the tax could bring from economic war. The Milan-Venice railway was built in that period, but the station was built in Sommacampagna only in 1854. It was in April 1848 and in June of 1866 which recorded the highest number of foreigners with the arrival of the armies of Savoy and Habsburgs. The events of the first and third war of independence Sommacampagna participated as the scene of clashes, and with the sacrifice of its economy, with suffering and looting. Annexed to the Kingdom of Italy, accepted the new political connotation, even with the painful realization that no government would make life better; as anywhere in the Verona countryside class consciousness was still a privilege, as well as education, not to mention the food.
The difficult life conditions, the close bond that linked the man to the ground, the little or no literacy, made these populations rural, by necessity or impossibility far from large or small games of thrones of parallel worlds, characterized of a fervent religious feeling, where the annual periods were marked by cycles tied to the land and to the liturgical celebrations.
The liturgical calendar at the time of the battles for independence was rich and heard; the charismatic priestly figure was still a point of reference. The archaic rural world has always lived a symbiotic relationship with nature: the physical life was related to meteorological phenomena, the movement of the sun and the moon, the equinoxes and solstices. From the beginning the Church has tried to superimpose the pagan cycle that the Christian liturgy. Many festivals were transformed into Christian holidays; the day of the winter solstice, celebrating the birth of the sun, has been transformed into Christmas party; the day of the vernal equinox, in which the ancients celebrated the death and resurrection of the god of vegetation, who awoke after a long winter sleep, as Easter. And so also for other events: the day of John the Baptist has supplanted the water festival in midsummer; the Assumption, August 5th, the festival of Diana; the recurrence of the Dead in November was the continuation of the ancient pagan festival of the dead. The community responded with festivals or rituals to the highlights of the calendar or the life of man, and found his moment of sharing and re-aggregation, exorcism and strength to continue the hard way. It was an escape from everyday life, the opportunity for the waste in a life-saving, the moment you resume origins, a communal ritual to combat the sense of insecurity and fear. The Saints were familiar figures and protectors, intermediaries between God and the faithful; the cult of the dead equally important and heard. Some holidays, born of pagan rites, have come down to us. The chipping of the old lady ("sego de laVECIA") for example. Pagan ritual of mid-Lent, which was intended to break the fast and propitiate the perk of life in the camps.
Among the people was running the rumor that, where the old lady passed, cows became infertile, fields parched and wine became vinegar. To avert this apocalypse, the old woman was chased and chipped in two among the crowd. In Custoza, 1952 was the year of the last representation. The whole country was involved in setting the dramatization, which took place in the natural scenery of the hills around the Ossuary and had its epilogue in the valley that separates the two main hills of Custoza. The Bruiel is the custom to set fire on the night of the Epiphany, piles of weeds accumulated in the fields. The bonfires commemorating the fires lit by the Magicians and the shepherds near the house in Bethlehem. There you can see the classic purpose of the fires in the countryside, propitiatory rite for new crops. Another very important festivity was that of "S. Paul of Signs "on January 21. On that date it was believed to be able to divine the weather conditions in the following year. The last evening of February and the early 2 of March young people came to "ciamar marso", which finds its origins in the magical rites for the rebirth of nature, and the awakening of fertility Sleeping in lethargy during winter. It was an opportunity for young people to announce engagements. Many others were important anniversaries, some have been restored, while the majority keep alive only in the memory of the elders.


text:
Q: Android: How to send a HTML EMAIL with URL image I want to send a html content email with URL image inside the application.
The HTML content is like that
i try the following code but not working
    Intent emailIntent = new Intent(android.content.Intent.ACTION_SEND);
    emailIntent.putExtra(android.content.Intent.EXTRA_SUBJECT, "TITLE");
    emailIntent.setType("text/html");
    String sharingContent="
<bold>HAHAHHAHAHAA</bold>
";
    emailIntent.putExtra(Intent.EXTRA_STREAM, Uri.parse(more_cover_image_thumbnail));
    emailIntent.putExtra(Intent.EXTRA_TEXT, Html.fromHtml(sharingContent));

A: your answer:
emailIntent.putExtra(android.content.Intent.EXTRA_TEXT,Html.fromHtml(sharingContent));
                     ^^^^^^^^^^^^^^^

redpajama_set_name: RedPajamaStackExchange


Monroe Central went undefeated in three games Tuesday in the MC Shootout which showcased six varsity teams and five junior varsity squads.
In their opening game, the Lady Bears defeated Bluffton, 40-22. Jordyn Barga led the way with 13 points and Hannah Bolton scored 8. Allie Morrison and Brooke Bolton each scored 4 points, Gabby Beckham, Hannah McCollum, and Mabrey Buis each had 3, and Katie Pike scored 2.
Game two was against a solid Tipton squad, who the Lady Bears defeated 31-25. Barga had 15 in the win, while Buis and Hannah Bolton each scored 6. Pike and Brooke Bolton each scored 2.
The final game of the day came for MC against Ansonia (Ohio) who they defeated 68-24.
Barga scored a game-high 15 while Hannah Bolton drilled a trio of three's and finished with 11. Brooke Bolton also hit three trifecta's to finish with 9 and with 8 was McCollum. Pike scored 5, Morrison, Sami Farmer and Leah Osborne each had 4, and with 2 apiece were Buis, Allison Hoening, Catherine Duncan, and Alex McGrath.
The Lady Bears will be hosting Shenandoah on Thursday at 5:30 p.m.


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Prayers for Ansley…
Our sweet W15H friend, Ansley Jones, is in need of prayers. Ansley was diagnosed with AML leukemia in 2013, and we had the privilege of first meeting her in the Timmy's Playroom at Wolfson Children's Hospital during her treatment that fall. We were immediately drawn to her joyful outlook, even in the face of such a challenging diagnosis. Ansley has always been the type of person who puts others' needs before her own. She cares so much for others and has captured the hearts of so many with her kindness and compassion. When we have visited her in the hospital, while she is in the midst of tests and trials of her own, she always takes the time to ask how WE are doing! She has made it a point to really get to know some of the other patients at the hospital, and her friendship breathes hope into everyone around her!
Ansley's leukemia went into remission, and through the W15H program she was Tim Tebow's special guest with SEC Nation at the 2014 SEC Football Championship game. Then, earlier this year, she participated in the Tim Tebow Foundation Celebrity Gala and had the perfect personality for interviewing the celebrity guests as they walked the red carpet. With a smile that lights up a room, she drew everyone in with her gentle spirit and love of life. It has been incredible to watch how Ansley has been more than a W15H friend, as she is truly an ambassador for Faith, Hope and Love.
In November, 25 months after her initial diagnosis, Ansley's leukemia came back. She is currently in the midst of heavy, intense chemotherapy, and is also in need of a bone marrow transplant, for which, praise God, her brother is a perfect match!
Please join us in prayer for Ansley and her family as she fights this battle with leukemia for the second time.
"Whoever dwells in the shelter of the Most High will rest in the shadow of the Almighty. I will say of the LORD, 'He is my refuge and my fortress, my God, in whom I trust.'" – Psalm 91:1-2
Brothers Who Found The CURE

redpajama_set_name: RedPajamaCommonCrawl


In the world of showbiz, many times people lose track after being surrounded by all the glitz and glamour. Anil Kapoor is a man who has set an example for many by not letting any of it get to his head. The actor has always made sure to put his family before everything and has been by their side through thick and thin.
On the work front, Anil's last release Ek Ladki Ko Dekha Toh Aisa Laga has kicked off its journey at the box-office on a decent note with the film earning close to Rs. 8 crore in its first two days. The film has received a positive response from critics and audience and we expect to see an upward trend in the collections of the film in the future.
Make sure to tune into Colors Infinity today at 7:30 PM and watch the entire episode of Famously Filmfare to catch up on all the fun from his conversation with Jitesh Pillaai.


text:
class UserProfilePresenter

  include ActionView::Helpers::TextHelper
  include Rails.application.routes.url_helpers
  include ActionView::Helpers::UrlHelper

  VisibleAttributes = [:id, :email, :name].freeze
  EditableAttributes = [:email, :name].freeze

  delegate :id, :email, :name, :created_at, :image_url, to: :user

  def initialize(user)
    @user = user
  end

  def member_since
    since = (Time.zone.now - user.created_at).to_i / 1.day
    "#{pluralize(since, "day")}"
  end

  def get_field(field, is_correct_user)
    return readonly_field(field) if !is_correct_user
    if editable_field?(field) then return editable_field(field) else return readonly_field(field) end
  end

  def editable_field(field)
    link_to user[field], "javascript:void(0)", {
      :class => "xeditable",
      id: "editable#{field}",
      data: {
        fieldname: field.to_s
      }
    }
  end

  def readonly_field(field)
    user[field]
  end

  def patch_user_path
    user_patch_user_path self.id
  end

  private
    attr_reader :user

    def editable_field?(field)
      field = field.to_s unless field.is_a?(Symbol)
      UserProfilePresenter::EditableAttributes.include?(field)
    end
end

redpajama_set_name: RedPajamaGithub


In this article, you will find the necessary information to create a winning essay on "To Kill a Mockingbird", the novel that is taught throughout North America at different levels of the educational system and grades. It has been in the curriculum for quite some time and it appears as though it won't be going anywhere anytime soon, so making sure you have the right information when compiling your essay is essential to getting the mark you deserve from your teacher.
The first thing you need to know is information about the author; this is key and vital when writing your paper. The reason is that it's always good to understand the background and history of the author to comprehend the reasoning and thoughts that were floating around her mind at the time she put the pen to paper. The novel itself won the Pulitzer Prize, which is a prestigious award handed out only to a select group of authors. According to the information found online about Harper Lee, the novel was written in accordance with the racism she witnessed growing up in a segregated community of Monroeville, Alabama.
In addition to putting some background information about the author you should always talk about how the author is actually writing about her own experiences during her time growing up, meaning that the stories in the book, although they may seem fictional, were at some point relevant to her childhood. In other words, you can touch bases on the fact that Alabama and southern states in the US were extremely segregated and racist during her time and how that may have affected her personal views when writing the novel.
Making sure that you're accurate and concise with your essay is extremely important, especially if this is for a high school project or assignment. Putting your thoughts, and as well factual information into well-structured and thought out paragraphs are a great way to stay on track and make sure that your assignment is going to score good marks with your teacher. It's recommended that you speak about racism and how it's changed since Harper Lee's time of writing the book, the civil rights era has vast amounts of information pertaining to it and it can all be found online with a simple search, this is a good idea for the middle of your essay.
Finally, for the ending touch, you can include your own thoughts about the book and how it relates to maybe something you've experienced, or perhaps take the time to address the values you've learned from the novel. It's always a great idea to talk about a lesson you learned or something that you didn't know, but you know now since finishing the book; this will ensure you get a good outcome and mark on your essay.


Junk cans have long been a way to fertile material for identity thieves. Decades ago, banking institutions and other experts advised visitors to exercise caution when disposing of sensitive material. That was at the days before consumer shreders were commonly available. I recall my parents cutting up good old credit cards and taking personal loan company statements and other paperwork out of to burn. Imagine any time people were going through your trash can back then, imagine what it is like now! Everything from lists of customers, lists of suppliers, payroll records, accounting statements, deal in secrets, and other information have a long history and are the fare of those engaged in corporate espionage. Companies aiming to catch up to their competitors own traditionally employed dumpster diving as a technique. From the waste you can get pricing information this means you know what prices to offer that big customer of the competitor. Need to get a good engineer or sales rep? Just check out the salaries data that's bound to arrive in the trash after a when. Do you want to know how the rival is making their super duper gizmo? Get some fortitude and some gloves and you'll identify sooner or later.
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PV Clips
A change that brings optimism
Best of athlete storytelling worldwide
Chris McQueen didn't see a future at Wests Tigers under Ivan Cleary. Things are different with his former Souths mentor at the helm. McQueen's story leads our selection of the best athlete-generated content from around the world.
An impact he'll never know
'We were 15 at the time, still young with a lifetime ahead of us.' Collingwood's Brit Bonnici remembers every detail of the days following the death of her childhood friend.
A nation punching above its weight
Luke Hughes - Contributor
Luke Hughes made international headlines when he smacked a home run off Max Scherzer in his first Major League Baseball at-bat. A few months later, he was living his 'other' life.
America's filthiest motel room
Todd Van Steensel - Contributor
Todd Van Steensel is currently unemployed, having just been cut for the third time. His long, grinding road to Major League Baseball started a decade ago, when his dad told him he had a contract in the same year he passed away.
My life in the major league
Warwick Saupold - Contributor
Jonathan Schoop had just hit a grand slam to left centre field. That made it 9-3, Orioles over the Tigers. One-out. Bottom of the eighth. …


"Probably confidence. I'd say that's the biggest area where Harry has grown," said interim coach Jeff Capel after Duke's 93-82 win over Boston College on Saturday. He's filling in for Mike Krzyzewski, who underwent lower-back surgery Friday and could be out for up to four weeks.
Giles had to overcome the mental hurdle that accompanied his knee injuries. He had a scope on Oct. 3 and missed the first 11 games of the season.
I think the mental toughness he's shown has been great. He could have easily not played this year.
In his last two contests, both starts, he's combined for 22 points and 17 rebounds in 41 minutes. Giles posted his first career double-double against Georgia Tech on Wednesday.
He played a career-high 24 minutes against the Eagles, and he was the centerpiece on various plays, heating up Cameron Indoor Stadium on a cold, snowy day. He finished with 12 points and five boards.
He perhaps played extended minutes in the victory over Boston College (8-8-, 1-2 ACC) due to fifth-year forward Amile Jefferson leaving the game with a right foot injury in the first half. Capel said the extent of his injury is unknown. That allowed Giles and Marques Bolden to shoulder more weight in the middle. Capel didn't miss a beat with Krzyzewski out.
Duke (14-2, 2-1) passed out 20 assists, led by Grayson Allen's career-high 11. It was Allen's second game returning from a one-game suspension, and Capel kept the star junior in at starting point guard. Allen has recorded a combined 17 assists in these past two outings.
Six Blue Devils wound up with double figures, excluding leading scorer Luke Kennard, who for the first time this season didn't post double digits.
Jefferson was the leading scorer with 11 points when he came out of the game with about 7 minutes left in the first half.
He said Giles hasn't reached a fraction of his ceiling as the freshman from Winston-Salem continues to progress, even over the span of a game, making decisions on the fly. When a post-up move didn't work in the second half, he dropped a jumper over a BC defender for a 75-53 Duke lead with 11:16 left.
Giles still has some work to do; he collected five fouls Saturday. But the positive is that the 6-foot-10, 240-pound forward is finding his stride, bringing his vivacious personality along for the ride.
Late in the second half, Giles animatedly wrapped his arms an official and walked with him after a timeout to gather a sense of what he did wrong on the previous play.
Jonathan M. Alexander contributed to this article.


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Facebook is testing a 'Buy' CTA button for ads
Facebook announced yesterday that they are testing a 'Buy' call-to-action button with a few small and medium businesses in the US, which will allow users to purchase products directly on Facebook without having to be taken off site. There is still no information about when the button will start being rolled out.
Here's what is looks like:
It is said that the button will be added to both ads and non-sponsored page posts and, according to Techcrunch, Facebook is not ruling out the option of charging for the use of this button in the future.
Facebook also reiterates that they are committed to focusing on privacy, which isn't surprising after having recently come under fire over privacy concerns about the infamous psychological study.
Twitter is doing it too
A 'buy now' button was also spotted on Twitter last week, showing that both big players are trying to move towards getting a piece of the eCommerce pie.
While these buttons are a fantastic opportunity for SMBs advertising on Facebook and Twitter, it will be interesting to see how users receive this feature.
The love/hate relationship people seem to have with Social Media and the critics' refusal to accept that social ads work will certainly be put to the test.
We are also curious to see how the ad units will iterate throughout the test. Adding a product review or rating, for example, would be quite helpful and certainly have a positive impact on people's willingness to click that button.
Anyway, if you're as curious about this as we are, watch this space for developments on this story.
Ads Manager on mobile
Also new on Facebook this week, Ads manager will be available on mobile (Android, iOS and mobile site) to everyone by the end of the summer. You know, social media never sleeps, so nor should we!
We will definitely be using Ads manager on mobile!


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H2O Basketball & Ballin4Peace Presents: ROAD2PEACE @ BOWLMOR NYC
So, we've been bombarded by the recent events in the news that depict nothing but violence in a country that is supposed to be built upon freedom, trust and love for your neighbor. We have seen the crimes against humanity in our own backyards for far too many years. Every news station. radio station and internet/mobile feed parade police brutality, black on black crime, sadistic familial murders, racial crimes and the list goes on -- to a point that we are desensitized. We are not able to tell the difference from the oppressed and the oppressor in some cases. We have lost sight of who the true victims are with all of this negativity: our future leaders.
I often ask myself who is brave enough to stand against the media giants, the religious knaves and corporate jesters to spread the news about those doing good by spreading positive messages throughout our immediate communities? Then I ask who is brave enough to witness to the world that there is a rise in positive people nurturing positive values into our future leaders of the world.
Well, along with #WeGiveBecauseWeCare #365Days of SCP, there are others in the NYC community that have given back tremendously out of pure love. H2O Basketball and Ballin4Peace debuted their Celebrity Basketball game in January with a star studded basketball game at Baruch College. This very same team got together agian to serve the community with ROAD2PEACE at Bowlmor located at Pier 60 of Chelsea Piers in NYC. The purpose of this event was to raise funds for the future efforts of H2O Basketball and Ballin4Peace. The funds raised will support their programs that service inner city youth via sports and recreation.
Many friends of the business came out to support the ROAD2PEACE. Those in attendance include The Black Ink Crew, Marc J. Jefferies, Shagari Alleyne, Tylik Hill of Vocab Entertainment, D.J. Desim, D.J. Don Demarco and many more. They all joined in with friendly competition on the score boards.
The most amazing part of the night was: we all came together out of love for the peace movement in NYC. We all want to end the generational crimes of one to another. We had fun dancing and bowling and raised funds in the meantime! That was nothing but a WIN....even when the losers talked smack about underground midgets tilting the the floors of the lanes! And lets not forget about the BK and The Bronx competition that resulted in two muscle bound males doing push ups until the one tapped out. By the way, the dude from The Bronx won that too!
Take a look at the photos below and we look forward to seeing you at the next event!


text:
\section{Introduction}

\noindent
Availability of labeled image data has helped in making great advances in Computer Vision. However, even the largest image dataset i.e Imagenet \cite{imagenet_cvpr09} has only 21841 classes, with many classes having very few images. Thus collecting and training on sufficient number of images from all the classes of images that may occur in practice is a very difficult task. Moreover, new classes come into existence every day and images of certain classes may be rare and difficult to obtain. Human beings are excellent at recognizing novel objects that have not been visually encountered before. For instance given the information that an \textit{auroch} is \textit{an ancient cow, has large horns, has large build}, one can easily identify an image of an auroch from other animals such as a pig or sheep although one hasn't seen an auroch before. Zero shot learning tries to capture this intuition by assuming that some other information about the novel class is available although no image from that class is available in the training set \cite{conf/cvpr/HuangEEY15,conf/aaai/LarochelleEB08,journals/pami/LampertNH14,conf/cvpr/RohrbachSS11,conf/eccv/YuA10}. This extra information is typically in the form of attributes or textual descriptions.

More formally, let $X_{tr}$ and $Y_{tr}$ represent the training images and their class labels respectively. Similarly, let $X_{te}$ and $Y_{te}$ represent the test images and their corresponding labels. The zero shot setting states that $Y_{te}\not\subset Y_{tr}$. However for each label $y_i$ in $Y=Y_{tr}\cup Y_{te}$, we have an embedding vector, called class embedding vector $A_i$, that is semantically related to the class corresponding to that label. This vector could come from other modalities, such as language and may be obtained using different approaches such as manually or automatically annotated attributes (for e.g \textit{word2vec}). Recently zero shot learning has emerged as an active area of research in the interplay between vision and language \cite{CONSE,DEVISE,labelEmbeddingImgClassification,SJE,ESZSL2015,SYNC2016,SAE2017}. It is an interesting area of research since the models for this problem can help understand how well language concepts translate to visual information.

\begin{figure}
\caption{Illustration of ZSL}

\begin{centering}
\includegraphics[scale=0.35]{ZSL}
\par\end{centering}
Suppose that \textit{cat}, \textit{horse} and \textit{zebra} are the training classes. The aim of zero shot learning is to correctly classify a new class image such as \textit{tiger} by relating it to them images of seen classes. The relationship between the classes themselves can be provided by the class embedding vectors but needs to be translated to the image domain.
\end{figure}

If the classes are modeled accurately via the embedding vectors, the problem can be viewed as finding a relation between the embedding vector of a class and the visual features of the images in that class. Most zero shot learning approaches learn a projection from image space to the class embedding space via a transfer function. For a novel class image given at test time, the class with the closest class embedding vector to the projection in the class embedding space is assigned. Similarly it is also possible to learn a mapping function from class embedding to the image space. In the first, the mapping is a simple linear function with various kinds of regularizations. The challenges faced in learning such a mapping are well documented, the primary issue being that of domain shift first identified by \cite{TransductiveZSL}. The mapping learned from the seen class images may not correctly capture the relationship for unseen classes as the space may not be as continuous and smooth in the image domain. The image space may also be more complicated than the semantic space due to the complex image generation process.
Recent advances in unsupervised learning have led to better architectures for modeling the statistical image generation process, primary among them being generative adversarial networks (GANs) \cite{GAN14} and variational autoencoders (VAEs) \cite{VAE13}. These models can also be used for condition specific image generation \cite{CVAE_2015}. For example one can generate images conditioned on attributes. A natural question to ask is: How much can this attribute conditional image generation, generalize to unseen classes and can this be used for zero shot learning?

In this work, instead of directly modeling a transfer function, we view problem as a case of missing data, and try to model the statistical image generation process via VAEs conditioned on the class embedding vector. The missing data for the unseen classes is filled using such generated image data.

ZSL models are typically evaluated in two ways. In the standard setting \cite{ZSL2009}, it is assumed that the train and test classes are disjoint $\left(Y_{tr}\cap Y_{te}=\Phi \right)$ i.e the training class images do not occur at test time. However, this is hardly true in the real world and can artificially boost results for the unseen classes without regard to the train class performance. Hence the Generalized zero shot setting has been proposed \cite{GenZSL2016} where both train and test classes may occur during the test time (Note that the latter setting is much harder than the former since the classifiers are typically biased either towards the classes seen at training time or those unseen at training time). We present our evaluation on both settings but obtained the greatest improvements in the much harder generalized setting. We follow the evaluation protocol recently proposed by \cite{xianCVPR17} that ensures that the models are not pre-trained on any of the test classes. The main contributions of this paper are as follows:

\begin{itemize}
\item We present a different approach to the zero shot problem by viewing it as a missing data problem. We train a Conditional Variational Autoencoder to learn the underlying probability distribution of the image features$(X)$ conditioned on the class embedding vector$(A)$. We show that such an approach reduces the domain shift problem that is inherent in the methods that learn a simple mapping as the image generation process is modeled in a much more sophisticated way.
\item By extensive testing on four benchmark datasets, we show that out model provides significant improvement over the state-of-the-art, particularly in the much harder generalized zero shot setting.
\item Since the model is able to generate image features of previously unseen classes, the results obtained in this work are promising and do provide evidence that conditional variational autoencoders indeed capture the underlying image generation process.  It also vindicates our conjecture about the generalisability of generative models for new tasks.
\end{itemize}

The paper is organized as follows: In section-2 we present a brief overview of the various existing methods for zero shot learning. Section-3 presents the motivation, and a description of the proposed approach. Section-4 describes the evaluation settings. Section-5 presents the experiments, results, and a comparison with existing methods. Finally in section-6, we present many directions for future work and a summary of our contributions.

\section{Related Work}
\begin{figure*}
\caption{Network Architecture}

\begin{centering}
\includegraphics[scale=0.5]{Network}
\par\end{centering}
The input $x$ and the semantic class embedding vector $A_y$ are concatenated and passed through a dense layer, followed by dropout and another dense layer. This is followed by a dense layer, that outputs $\mu_z$ and $\Sigma_z$. A $z$ is sampled from the variational distribution $\mathcal{N}(\mu_z,\Sigma_z)$. The sampled $z$ is projected to a hidden layer via dense connections and then to the image space to reconstruct the original $x$. All activations are ReLU except the outputs of encoder and decoder which are linear.
\label{net}
\end{figure*}
Zero shot learning was first introduced by \cite{ZSL2009}, where they consider disjoint train and test classes and propose an attribute based classification. Other traditional methods are based on learning an embedding from the visual space to the semantic space. During test time, for an unseen class example, the semantic vector is predicted and the nearest neighbor class is assigned \cite{wang2016relational,socher2013zero,verma2017simple}. The embedding is learned via a parameterized mapping. The most popular approach to ZSL is learning a linear compatibility between the visual and semantic space  \cite{labelEmbeddingImgClassification,DEVISE,SJE}. \cite{ESZSL2015,SAE2017} provide novel regularizations while learning a linear compatibility function.  ESZSL \cite{ESZSL2015} models the relationship between image features and attributes, via a simple compatibility function while explicitly regularizing the objective. SAE \cite{SAE2017} adds an autoencoder loss to the projection which encourages reconstructability from attribute space to the visual space.

Image classification problems generally result in nonlinear decision boundaries. Linear methods have strong bias and often are not sufficient to model the problem. Hence, non linear compatibility learning methods have also been proposed. LATEM \cite{xian2016latent} proposes piecewise linear multimodal learning which learns nonlinear compatibility function and CMT \cite{socher2013zero} trains a neural network with one hidden layer with tanh activations and uses novelty detection for discriminating between seen and unseen classes in the generalized setting.

In another popular approach to ZSL, the seen class attributes are treated as the basis vectors \cite{CONSE} which map images(visual features) into the semantic embedding space via the convex combination of the class label embedding vectors weighed by the predictive probabilities for the different training class labels.  SYNC \cite{SYNC2016} tries to align the semantic space to the image space by learning manifold embedding of graphs composed of object classes. \cite{kodirov2015unsupervised} present a sparse coding framework based on an unsupervised domain adaptation for ZSL.

A key component of zero-shot learning is the semantic embedding of the class labels. Previous work in ZSL has used human labeled visual attributes \cite{farhadi2009describing} to help detect unseen object categories for the datasets where such human labeled attributes are available. This work also uses the attribute vectors as the semantic class embeddings. Distributed representations of the class name such as \textit{word2vec} \cite{word2vec} have also been used as the semantic embedding. In this work we use word2vec for datasets where attribute vectors are not available.

Prior work on conditional image generation based on textual descriptions was successful in generating synthetic images that appear natural \cite{Text2Img}. The authors also generate real looking images in the zero shot setting. This serves as the primary motivation behind our approach. However, we work in the feature space instead of the image space.

\section{Method Description}

We are given a set of train classes (also called seen classes) $\mathcal{Y}_{s}=\{y_{s}^{1},y_{s}^{2},...y_{s}^{n}\}$ and
a set of test classes (also called unseen classes) $\mathcal{Y}_{u}=\{y_{u}^{1},y_{u}^{2},...y_{u}^{m}\}$.
 The zero shot setting states that $\mathcal{Y}_{u} \not \subseteq \mathcal{Y}_{s}$.
For each class $y$ in $\mathcal{Y}=\mathcal{Y}_{u}\cup\mathcal{Y}_{s}$,
we have a class semantic embedding vector $A_{y}$, that $\textit{describes}$
the class. We are given $d$-dimensional labelled training data from
the seen classes $\mathcal{Y}_{s}$ , i.e $\{X_{s},Y_{s}\}$. The
goal is to construct a model $f\,:\,\mathbb{R}^{d}\rightarrow\mathcal{Y}_{u}$,
that can classify the examples from the unseen classes $\mathcal{Y}_{u}$.
In the generalized zero shot setting, we aim to construct a more generic model
$f_{gen}\,:\,\mathbb{R}^{d}\rightarrow\mathcal{Y}_{s}\cup\mathcal{Y}_{u}$,
that can classify the data from both the seen and unseen classes correctly. The latter setting is much more difficult than the former for two reasons. Firstly, there are more classes in the second setting which leads to more confusion. Secondly, the seen and unseen classes may come from different probability distributions, which could degrade the performance on either the seen or the unseen classes.

The Variational Autoencoder \cite{VAE13} is a graphical model, that tries to relate the distribution of the hidden latent representations $z$ to that of the data $x$. In variational inference, the posterior $p(z|x)$ is approximated by a parametrized distribution $q_{\Phi}(z|x)$    called the variational distribution. The lower bound for $p(x)$ can be written as follows: \\
\[
\mathcal{L}(\Phi,\theta;x)=-KL(q_{\Phi}(z|x)||p_{\theta}(z))+\mathbb{E}_{q_{\Phi}(z|x)}\left[\log p_{\theta}(x|z)\right]
\]
\\
\noindent  The network has
two components, an encoder network $E$ with parameters $\Phi$
and a decoder $D$ with parameters $\theta$.  Here the $p_{\theta}(x|z)$ can be seen as a decoder, from
latent space to data space, while $q_{\Phi}(z|x)$ can be seen as
an encoder from data space to latent space. Note that one can also view this
optimization as minimizing the reconstruction loss with the KL divergence
as the regularizer. Conditional Variational Autoencoders (CVAE) first introduced by \cite{CVAE_2015} maximize the variational
lower bound of the conditional likelihood $p(x|c)$ in a similar manner, which helps to
generate samples having certain desired properties (as encoded by $c$).

\[
\mathcal{L}(\Phi,\theta;x,c)=-KL(q_{\Phi}(z|x,c)||p_{\theta}(z|c))
\]
\[
+\mathbb{E}_{q_{\Phi}(z|c)}\left[\log p_{\theta}(x|z,c)\right]
\]

In this work, we train the conditional variational autoencoder to generate
the data features $x$, given the conditional variable $A_{y}$ (the semantic embedding vector of a particular class). This helps us to model $p(x|A_y)$.

\subsection{Encoder}

The encoder generates the probability distribution $q(z|x,A_{y})$
 which is assumed to be an isotropic gaussian. $q$ is a distribution
over the latent space that gives high probability mass to those $z$
that are most likely to produce $x$ (which belongs to class $y$).
Thus, the encoder takes in a data feature point $x$ concatenated with
the semantic embedding $A_{y}$ and outputs the parameter vector of the Gaussian, i.e $\left(\mu_{x},\Sigma_{x}\right)$.

\subsection{Decoder}

The decoder tries to map the latent space to the
data space. For an input $\{z\circ A_{y}\}$ it tries to reconstruct that
$x$ of class $y$ which is most likely under the latent variable
$z$. If the CVAE is properly trained, one can use the decoder part
of the network to generate any number of samples of a particular class
using a simple algorithm : Sample $z$ from a standard normal, concatenate
$A_{y}$, and pass it through the decoder.
\\

We model both the encoder and the decoder using neural networks. We observed that training with two hidden layers in the decoder quickly overfits to the seen classes, even with batch normalization and dropout. Challenges in training deep VAEs have been well documented \cite{conf/nips/SonderbyRMSW16}.

During training, for each training datapoint $x^{(i)}$, we estimate
the $q(z^{(i)}|x^{(i)},A_{y_{i}})=\mathcal{N}(\mu_{x_{i}},\Sigma_{x_{i}})$
using the encoder. Then, a $\widetilde{z}$ is sampled from $\mathcal{N}(\mu_{x_{i}},\Sigma_{x_{i}}).$
We pass the $\widetilde{z}$ concatenated with $A_{y}$ to the decoder
and expect it to reconstruct $x$. We also want the $q(z)$
to be close to the standard normal distribution and include the KL divergence term in the optimization. Let $x$ be the input
to the encoder and $\hat{x}$ be the reconstructed output, the training loss becomes:

\[
\mathcal{L}(\theta,\Phi;x,A_{y})=\mathcal{L}_{reconstr}(x,\hat{x})+KL\left(\mathcal{N}(\mu_{x},\Sigma_{x}),\mathcal{N}(0,I)\right)
\]
\noindent
We use $L_{2}$ norm for the reconstruction loss. The KL divergence
term has a nice closed form expression (see \cite{VAE13}) when the distributions are Gausian.
The network is shown in the Figure-\ref{net}. Once the network is trained, one can sample any number of examples from each unseen class, since their semantic class embedding vectors are known. We call this the \textit{pseudo train data}. Once the data is generated, one can train any classifier for the unseen classes. We use an SVM classifier \cite{SVM} in this work. Note that the CVAE can possibly be replaced with any other generative model such as GAN \cite{GAN14} or it's many variants  as well.  The pipeline of the zero shot classification algorithm (Algorithm-1) is now simple:

\begin{enumerate}
\item Using $X_{train},Y_{train},A$ , train the Conditional Variational
Autoencoder.
\item For each unseen class $y_{u}^{(i)}$ , generate samples of datapoints
belonging to that class. For this, sample $N$ latent vectors ($z$)
from a standard normal, concatenate them with $A_{y_{u}^{(i)}}$
and use it as the input to the decoder. We call generated output the pseudo traindata.
\item Train an SVM classifier using the pseudo traindata.
\end{enumerate}
One straightforward way to extend our model to the generalized setting is to train the SVM with both the original training data of the seen classes, and the generated data of the unseen classes. However, we noticed that this leads to a bias towards the seen classes during classification.  Hence, we also generate pseudo data for seen classes along with unseen classes in the generalized zero shot setting. The change comes in step-6 of the algorithm, where $\mathcal{Y}_u$ is replaced with $\mathcal{Y}_s\cup \mathcal{Y}_u$. Thus, our model provides an easy extension to the much harder generalized zero shot setting.
\begin{algorithm}
\caption{CVAE-ZSL}\label{alg:euclid}
\begin{algorithmic}[1]
\Procedure{ZSL Classifier}{$X_s,Y_s$}
\State $N=300$ // Chosen via cross-validation
\State $model$ $\gets$ Initialize $Encoder$, $Decoder$
\State Train $model$ on $X_s,Y_s$
\State \textit{S}= $\Phi$
\For {$y_u\in \mathcal{Y}_u$ }
\For {$i$ in $[1,2,..N]$}
\State $z \sim \mathcal{N}(0,I)$
\State $V_i=y_u\circ z$
\State $X_i\gets Decoder(V_i)$
\State \textit{S}$\leftarrow$\textit{S} $\cup \{(X_i,y_u)\}$
\EndFor
\EndFor
\State $clf\gets SVM$
\State fit $clf$ on \textit{S}
\State \textbf{return} $clf$

\EndProcedure
\end{algorithmic}
\end{algorithm}

\section{Evaluation Protocol}
Typically, zero shot learning methods are evaluated in two settings. In the first setting, we make an assumption that seen classes do not occur at test time \cite{ZSL2009}, i.e $Y_{tr}\cap Y_{te}=\Phi$. We call this the disjoint assumption. However this is a very strong assumption and is usually not true in the real world. Nonetheless such a setting is useful to evaluate how the training generalizes to the unseen classes. In the generalized zero shot setting \cite{GenZSL2016}, there are no such assumptions made on the test data. Both seen and unseen class' images can occur at test time. Such a setting while being realistic, is also very difficult compared to the disjoint assumption. We follow the benchmark laid out recently by \cite{xianCVPR17,XLSA17} which ensures that our feature extraction model is not pretrained on any of the test classes.

\section{Experiments}
We present our results on four benchmark datasets: Animals with Attributes (AwA) \cite{journals/pami/LampertNH14,XLSA17}, CUB-200-2011 Bird (CUB)\cite{CUB2010}, SUN Attribute (SUN) \cite{SUN2012} and Imagenet \cite{imagenet_cvpr09}. We also present results on AwA, CUB, and SUN for generalized zero shot setting. While AwA is a medium sized coarse grained dataset, SUN and CUB are medium sized fine grained datasets. We also present our results on the large scale Imagenet dataset. The 1000 classes of ILSVRC2012 \cite{ILSVRC15} are used as seen classes, whereas 360 non-overlapping classes of ILSVRC2010 are used for testing (same as \cite{SSVOC2016,conf/cvpr/FuXKG15}). The details of test train splits in each dataset are presented in Table-\ref{tab1}. We use keras \cite{chollet2015keras} with tensorflow backend \cite{tensorflow2015-whitepaper} for the implementation. The code will be made publicly\footnote{Github link with data and code will be posted} available to enable reproducibility.

\begin{table}
\caption{Dataset Details}
\begin{centering}
\begin{tabular}{|c|c|c|}
\hline
\textbf{Dataset} & \textbf{\#images} & \textbf{seen/unseen}\tabularnewline
\hline
\hline
AWA-1 & 30475 & 40/10\tabularnewline
\hline
AWA-2 & 37322 & 40/10\tabularnewline
\hline
CUB & 11788 & 150/50\tabularnewline
\hline
SUN & 14340 & 645/72\tabularnewline
\hline
Imagenet & 254000 & 1000/360\tabularnewline
\hline
\end{tabular}
\par\end{centering}
\label{tab1}
\end{table}

\begin{table*}
\centering{}%
\begin{tabular}{|c|c|c|c|c|}
\hline
\textbf{Method} & \textbf{AWA-1} & \textbf{AWA-2} & \textbf{CUB} & \textbf{SUN}\tabularnewline
\hline
\hline
DAP \cite{lampert2014attribute} & 44.1 & 46.1 & 40.0 & 39.9\tabularnewline
IAP \cite{lampert2014attribute} & 35.9 & 35.9 & 24.0 & 19.4\tabularnewline
CONSE \cite{CONSE} & 45.6 & 44.5 & 34.3 & 38.8\tabularnewline
DeViSE \cite{DEVISE} & 54.2 & 59.7 & 52.0 & 56.5\tabularnewline
ALE \cite{akata2016label} & 59.9 & 62.5 & 54.9 & 58.1\tabularnewline
SJE \cite{SJE} & 65.6 & 61.9 & 53.9 & 53.7\tabularnewline
ESZSL \cite{ESZSL2015} & 58.2 & 58.6 & 53.9 & 54.5\tabularnewline
SAE \cite{SAE2017} & 53.0 & 54.1 & 33.3 & 40.3\tabularnewline
Sync \cite{SYNC2016} & 54.0 & 46.6 & \textbf{55.6} & 56.3\tabularnewline
\hline
\textbf{Ours} & \textbf{71.4} & \textbf{65.8} & 52.1 & \textbf{61.7}\tabularnewline
\hline
\end{tabular}
\caption{Results in the disjoint assumption zero shot setting with the per-class accuracy metric.}
\label{tab2}
\end{table*}

\begin{table*}

\centering{}%
\begin{tabular}{|c|c|c|c|c|}
\hline
\textbf{Method} & \textbf{AWA-1} & \textbf{AWA-2} & \textbf{CUB} & \textbf{SUN}\tabularnewline
\hline
DAP \cite{lampert2014attribute} & 0.0 & 0.0 & 3.3 & 7.2\tabularnewline
IAP \cite{lampert2014attribute} & 4.1 & 1.8 & 0.4 & 1.8\tabularnewline
CONSE \cite{CONSE} & 0.8 & 1.0 & 3.1 & 11.6\tabularnewline
SJE \cite{SJE} & 19.6 & 14.4 & 32.8 & 19.8\tabularnewline
ESZSL \cite{ESZSL2015} & 12.1 & 11.0 & 21.0 & 15.8\tabularnewline
Sync \cite{SYNC2016} & 16.2 & 18.0 & 19.8 & 13.4\tabularnewline
DeViSE \cite{DEVISE} & 22.4 & 27.8 & 32.8 & 20.9\tabularnewline
ALE \cite{akata2016label}& 27.5 & 23.9 & \textbf{34.4} & 26.3\tabularnewline
\hline
\textbf{Ours} & \textbf{47.2} & \textbf{51.2} & \textbf{34.5} & \textbf{26.7}\tabularnewline
\hline
\end{tabular}
\caption{Results in the Generalized zero shot setting. We use harmonic mean of accuracy on seen and unseen classes as metric.}
\label{tab3}
\end{table*}
\subsection{Features}
Similar to recent papers, we use deep features extracted from Convolutional Neural Networks(CNN) for our experiments. The images from AwA dataset are not publicly available. Hence we use VGG features \cite{VGGNET} provided by the authors for this dataset. Recently \cite{XLSA17} have released a new dataset with the same classes as AwA, however with publicly available images. They call this AwA-2 and the original dataset AwA-1. We use Resnet101 features provided by \cite{XLSA17} for AwA-2, CUB and SUN for fair comparisons. We empirically observe that VGG net features perform slightly better($2\%$) for AwA compared to Resnet-101 features. For Imagenet, we use Alexnet features \cite{AlexNet} for fair comparisons.

The class embedding features also play an equally important role in zero shot learning. For the AwA, SUN, and CUB datasets, we use the attribute annotations provided by the respective authors. However, Imagenet has no such annotated features and we use 1000 dimensional word2vec features \cite{word2vec} trained using a skip-gram model on the Wikipedia corpus, similar to \cite{SSVOC2016}.
\subsection{Train-Test splits: An Important Note}
Most recent zero shot learning models were evaluated on a particular test-train split of classes, or as an average of $n$ (4 or 10) random splits. However as pointed out by \cite{xianCVPR17} there is a significant problem with this approach. Some of the test classes overlap with the training classes of Imagenet on which the feature extraction CNN was pretrained on. This makes the model perform better on such overlapping classes, thereby showing significantly greater accuracy on such classes (contributing to greater overall accuracy). However such an evaluation is not representative of the true performance on the model. Hence \cite{xianCVPR17} provide a novel test train split for each dataset, ensuring that none of the test classes occur in the 1000 classes of Imagenet. They observe that the performance of all methods reduces significantly with such splits. The results obtained from our experiments also corroborate this observation. Thus we present our results on the novel proposed splits of \cite{xianCVPR17}, but  the results on the older splits are also presented for the sake of completeness: on the most widely used AwA dataset, we obtain accuracy of 85.81\% on the standard splits proposed by the authors of the dataset\cite{journals/pami/LampertNH14}. On the fine-grained CUB dataset we 54.3\%. There are no standard splits on the SUN dataset. Hence we experiment with 10 random splits to obtain an average of 88.5\%. However, we would like to reemphasize that these results, although high, are inconclusive in the strictest definition of zero-shot learning.

\begin{table}
\caption{Results on the Imagenet dataset (top-5 accuracy)}
\begin{centering}
\begin{tabular}{|c|c|}
\hline
\textbf{Method} & \textbf{Accuracy}\tabularnewline
\hline
\hline
AMP\cite{conf/cvpr/FuXKG15} & 13.1\tabularnewline
DeViSE\cite{DEVISE} & 12.8\tabularnewline
CONSE\cite{CONSE} & 15.5\tabularnewline
SS-Voc\cite{SSVOC2016} & 16.8\tabularnewline
\hline
\textbf{Ours} & \textbf{24.7}\tabularnewline
\hline
\end{tabular}
\par\end{centering}
\label{tab4}
\end{table}
\subsection{Parameters}
The parameters of the Neural Network are trained with a batch size of 50 and Adam optimizer \cite{ADAM} with a learning rate of $10^{-3},\beta_1=0.9,\beta_2=0.999$. We use glorot initialization \cite{journals/jmlr/GlorotB10} for both the encoder and the decoder. There are two kinds of hyper-parameters in our model. The network hyper-parameters (such as batch size, size of the latent variable) and the SVM cost parameter. The latent variable size was set to 100 and the SVM cost parameter was set to 100 by cross validation on training classes. We empirically observe that the model performance saturates after around 300 generated pseudo data samples.

\subsection{Evaluation Metric}

For AwA, CUB, and SUN we use the average per class accuracy as the metric. Results are compared with those presented in \cite{XLSA17}. Average per class accuracy is a better metric for evaluating imbalanced test sets. It is defined as follows :
\[
acc_{avg}^{per-class}=\frac{1}{|Y|}\sum_{i=0}^{|Y|}\left(\frac{N_{correct}^{(class-i)}}{N_{total}^{(class-i)}}\right)
\]

\cite{XLSA17} observe that due to the class imbalance in the dataset particularly AwA, there is a significant difference (about $4\%$) in the average per class accuracy and the per image:
\[
acc_{avg}^{per-image}=\frac{N_{correct}}{N_{total}}
\]

For the Imagenet dataset, we measure the top-K accuracy i.e the classification of a test image is correct if the true label occurs in the top K predictions of the model. Similar to \cite{SSVOC2016} and \cite{CONSE}, we set the value of K to 5.

\begin{figure*}
\caption{T-SNE visualization \label{tSNE}}
\begin{centering}
\begin{tabular}{|c|c|}
\hline
\includegraphics[width=5cm,height=5cm]{real_cut} & \includegraphics[width=5cm,height=5cm]{generated_cut}\tabularnewline
\hline
\end{tabular}
\par\end{centering}

T-SNE Visualization of the true data(left) and the data generated from the network(right) for the unseen classes of AwA dataset (best viewed in color). Note that the data is generated only from the attribute vectors of the class, without looking at even a single image. For most classes, the predicted vectors are close to the true vectors. However, the model suffers from the mode dropping problem (see red, blue).  Recently, many methods for avoiding mode collapse have been studied \cite{journals/corr/RoscaLWM17} which may be applicable to the current problem.
\end{figure*}

\subsection{The Generalized Zero Shot Setting}
For the generalized zero shot setting, we follow the protocol by \cite{GenZSL2016}. From the training images of the seen classes, we set aside $20\%$ of data and train only on the remaining $80\%$. To reduce the bias towards the seen data, the SVM uses the data generated from both the seen and unseen classes as opposed to using the actual data for seen classes. The SVM is evaluated separately on both the set aside seen classes data and the test data from unseen classes. As proposed by \cite{xianCVPR17}, we use the harmonic mean of the two accuracies as a measure of performance for the generalized zero shot setting.
\subsection{Results}
The results on the disjoint assumption zero shot learning with the proposed splits from \cite{xianCVPR17} are presented in Table \ref{tab2}, and for the generalized zero shot in Table \ref{tab3}.

\subsubsection*{Comparison with previous models } In the disjoint assumption zero-shot setting, the proposed model performs significantly better than state-of-the-art on the coarse-grained datasets AwA-1 and AwA-2. On AwA-1 which is the most widely used benchmark for zero-shot learning, we achieve an improvement of \textbf{5.8\%} in the disjoint assumption. On SUN which is a fine-grained places dataset, the performance gains are significant. On the extremely fine-grained CUB dataset, the performance is slightly less compared to the state-of-the-art. We attribute this to the extremely fine-grained nature of the CUB dataset, where the classes are fairly close. Our intuition is that it is difficult to generate fine-grained image features from just the attributes.

Imagenet is a much more challenging dataset, particularly due to the lack of explicit attribute vectors. On this we achieve an improvement of about \textbf{7.9\%} over other approaches.  We may note here that currently no other single method claims the best results on all the datasets simultaneously.

In the more realistic generalized zero-shot setting the improvements are even more. In this setting the proposed model improves over state of the art by \textbf{20\%} (absolute) on the coarse grained datasets, while achieving state-of-the-art performance on the fine grained datasets.  We attribute this to two reasons: The underlying distribution is better captured using a Variational Auto-encoder, than by just learning a mapping from image to attribute space and since our model generates image features for seen classes also, it has lesser bias towards the seen classes, which is inherent in other methods. Thus, we may be able to do better on the unseen classes.

We observe that the performance gains are much higher on the harder problem of generalized zero-shot learning. In the disjoint ZSL setting since there are a lesser number of classes, and no confusion between seen and unseen classes, the problem is simpler. Thus, previous approaches may be able to perform well in this scenario. However, in the generalized setting, more sophisticated techniques are necessary, and thus our approach beats competitors by a significant margin.

\subsubsection*{Visualization}
We visualize the image feature vectors generated by our model for each class using the t-sne \cite{maaten2008visualizing} method in Figure-\ref{tSNE} and compare it with the original test image feature vectors for the AwA-1 dataset. We make the following observations: 1.The generated image features are close to the original feature vectors. This shows that our model is able to capture the underlying image generation process to a good extent which manifests in terms of better performance on the benchmark datasets. 2.The generated images are unimodal. This means that several modes of the underlying distribution are missing from the learned distribution. This offers clues into improving the model to enforce multi-modality learning. This is however, beyond the scope of this work.

\section{Conclusion}
We have presented a novel approach to zero shot learning by modeling it as a missing data problem. We show that our model compares favorably with the state-of-the-art on four benchmark datasets, while outperforming them for all four datasets in the much harder generalized zero shot setting.
There are several areas for improvements such as automatically generating attribute vectors for classes using wikipedia articles, end to end training to learn better features for images etc. We leave this for future work.

{\small
\bibliographystyle{ieee}

redpajama_set_name: RedPajamaArXiv


text:
Helvetica Joins the Web Font Revolution
Monotype Imaging, the company that houses the Monotype, Linotype and ITC typeface libraries, has just opened its Fonts.com Web Fonts solution to the general public.
Fonts.com Web Fonts has been in beta for the last few months and Monotype has taken user feedback from that beta to make its web font solution better and more robust.
With Fonts.com Web Fonts, designers, creative agencies, publishers and individuals can infuse their web apps or web pages with more typography options.
Fonts.com Web Fonts joins a growing list of web font services, including Typekit, Fontdeck and Google's new Font Directory. Fonts.com Web Fonts is similar to some of these existing solutions, but it has some additional features and supports a few other platforms that make it a unique offering in the web font space.
Huge Library
As a company, Monotype houses some of the biggest font libraries in the world. Typefaces like Helvetica, Frutiger and Univers are all part of Monotype and available to Fonts.com Web Fonts users.
Just like Typekit's recent partnership with Adobe, the ability to use premium type families and well-known fonts in web design is a huge step in the overall world of web typography.
Monotype has made more than 7,500 fonts available via the service and more will be added in the future. Monotype has also committed to bringing all ITC, Linotype and Monotype font faces developed in the ensuing years to the platform.
Beyond just the sheer number of typefaces, Monotype also supports more than 40 different languages — many non-Latin character sets are supported too. Extended character sets are available for many fonts and users can also access Asian-specific font foundries.
Through the course of the beta, Monotype has also changed how its international fonts are hinted and kerned, so that Chinese or Japanese fonts are easier for users to read. For big brands that rely on a typeface as part of its greater identity, having international support across languages can be very important.
Fonts.com Web Fonts pricing takes place at a few different tiers. Tiers are based on subscription type and then on page views. Regardless of the subscription, Fonts.com Web Fonts can be used on as many projects or domains as you want and you can use as many fonts as you want per project.
For instance, there is a free plan that gives anyone access to more than 2,200 fonts. The free is good for 25,000 pageviews each month, which makes it ideal for most individual users or bloggers.


The Story: The people of Solomon's Jerusalem could hardly be described as humble. The descriptions we glean from Psalms 50, 73, and 74 portray a people whose hearts have begun to turn away from God and who are wallowing in the good things coming their way from the surrounding pagan world. They did not fear God; this was obvious by the fact that even the king made room for pagan idols in his royal court. They did not believe that God would do anything other than continue to bless them as He had been doing for most of Solomon's reign. But Asaph was the liturgical spoil sport; to him fell the duty of reminding the people of God's calling and requirements, and of the danger they were in as long as they failed to love and fear Him. When God decides to judge the world, no one can say to Him, "Hey, what are you doing!?" All the world is still before the Word of God's wrath, as He unfolds waves of judgment against those who presume on His goodness and forsake His holy ways. Israel should have known this; their past – even their most recent past, with King David – gave ample testimony to God's power and willingness to discipline His people. But because they had become so distracted by material prosperity, they needed to be reminded once again.
The Structure: Distracted by material prosperity? Comfortable with the world and its ways? Ripe for some discipline from the Lord? Where are the Asaphs who will call the people of God to fear Him and remember His judgment? We can offer all the "reasons" why we don't teach the fear of the Lord, don't instruct our people in the ways of God's holy Law, and don't reach out to the lost with the Good News of Christ. But when God begins to move against us for our failure to be His people, nothing we might say will stay His hand. The people in Asaph's day indulged the world and its ways and continued to worship God, thinking He was just like them and "OK" with whatever they chose to do to make themselves happy. Asaph saw it otherwise, and he turned out to be right.
If God should rise up to begin judging the Church today, would we even be able to recognize it? How would we know?


Introducing our settled Minister. . . the Rev. Steven Protzman!
Called by a unanimous vote by the Active Members of the Unitarian Universalist Church of Kent on May 27, 2018, the Rev. Steven Protzman began his ministry with us on August 1, 2018.
is a native Midwesterner and grew up in Missouri and Iowa. He holds an undergraduate degree in architecture from Iowa State University and his previous career was as a pipe organ designer for several major American organ builders. He is a 2009 graduate of United Theological Seminary of the Twin Cities, New Brighton, Minnesota and was ordained in 2010 at the First Unitarian Society of Minneapolis. Steven has served the Unitarian Universalist Society, Coralville, Iowa (previously the Unitarian Universalist Society of Iowa City, Iowa) since 2011 as its settled minister.
Steven is an outgoing extrovert who loves to socialize and meet new people. He is also passionate about nature, especially wolves, eagles and the Columbia River Gorge in Oregon, is an avid country western dancer, and enjoys gardening, the arts, hockey, good food of all kinds, architecture, and exploring new places. While in Iowa, he rediscovered the rugged beauty of southern Missouri and northern Arkansas and vacationed down there for several years, exploring caves, rivers, forests, springs and the natural beauty of that part of the country.
Steven believes in the power of Unitarian Universalism to transform people's lives, to invite us to discover our fullest, most authentic selves, to guide us into deeper relationship with the Holy, and to challenge us to offer our lives in service to a world that needs the love and the gifts each of us has to share.


The New York City Police Detective caught on camera berating an Uber driver has been stripped of his gun and put on desk duty.
Patrick Cherry, a member of the NYPD/FBI Joint Terrorism Task Force is being transferred out of the elite division.
It turns out that 38-year-old Cherry has 12 previous civilian complaints against him, some involving verbal abuse.
The verbal tirade happened after the Uber driver honked his horn at the New York City Police Detective who was attempting to park his car on Manhattan's West Side Highway without signaling.
Detective Cherry is said to have been under a lot of emotional stress in recent days. Just before his encounter with the Uber driver, Cherry came to the NYU Langone Medical Center to pay a bedside visit with a good friend and fellow detective on the Terrorism Task Force who is in critical condition after suffering a heart attack.
The president of the NYPD's Detective's Union Michael J. Palladino is coming to Cherry's defense. In a statement, Palladino said: "Detective Cherry is a person of good character and an excellent detective. He really should not be judged by one isolated incident. Cops are just like everyone else."


text:
Q: How to create a new object using string's content as an object name I am trying to name a Person object with "objectName" as below but not succeeding,
any help? How to do it?
string objectNameString = "objectName";
Person objectNameString = new Person();

I try to create a Person list from several user inputs, the names must be unique in list.

A: Following should create new instance of Person using string from objectNameString.
string objectNameString = "Person";

var person = System.Reflection.Assembly.GetExecutingAssembly().CreateInstance(objectNameString );

A: If you want to use the value of the objectNameString variable, using a Dictionary or ExpandoObject is the closest you can get:
Dictionary<string, object> someObject = new Dictionary<string, object>();
someObject[objectNameString] = new Person();

Person p = (Person)someObject[objectNameString];

Or, if you only add Persons, the dictionary could look like Dictionary<string, Person>.

A: I think I get your question. You have a string (e.g. from user input). And you want to create an Person which has the variable name of the string mentioned before.
Dictionary<string, Person> someObject = new Dictionary<string, Person>();
string objectNameString = "objectName";
someObject[objectNameString] = new Person();


text:
March 2020 Monthly Link Roundup – Carriers
HomeAll PostsBlogMarch 2020 Monthly Link Roundup – Carriers
With so much going on, you may have missed out on some of our March blogs. No worries. We've created a roundup of our best blogs from the month of March to get you caught up. In this roundup, you'll learn more about Trucker Tools' new COVID-19 resource tool, available in the Trucker Tools driver app. We provide you with some tips for staying healthy on the road during the pandemic, as well as interviews with Wayne Campbell of The Driver's Side and The Trucking Couple. Also, on tap: how to increase the efficiency (and profit margins) of your trucking business.
Updates on the COVID-19 Pandemic
In response to the COVID-19 pandemic and to support your need for easy access to the latest industry information, Trucker Tools has added a new COVID-19 resource to the Trucker Tools driver app. This new tool is a go-to resource for accessing the latest news and information on COVID-19, including updates to brokers' policies and procedures, as well as information on truck stops, services and more.
The Driver's Side with Wayne Campbell: Real Drivers, Real Talk
In our interview with Wayne Campbell of The Driver Side, we learn more about Wayne, and his career in the industry, including his stint as an oilfield driver. Wayne also discusses why he loves interviewing veteran and elite truckers for his online show, The Driver's Side, and how important it is to build bridges between old school drivers and truckers who are new to the industry.
Top Tips for Truckers on How To Stay Healthy on the Road
We hear every day about the challenges that you and your fellow truckers are facing during the COVID-19 crisis. One of the biggest worries and challenges you're dealing with is how to stay healthy and safe when you're working out on the road. In this blog, learn how you can reduce the chances of exposure to the virus on the road and use technology to reduce isolation.
The Trucking Couple on Team Driving and How the Trucker Tools Driver App Simplifies Their Life on the Road
Trucker Tools recently spent some time getting to know The Trucking Couple, Frank and Stephanie Rebelo, who haul expedited freight for FedEx's Custom Critical division. If you're interested in learning more about the expedited freight biz, team driving and how to use Trucker Tools' driver app on the road, check out what The Trucking Couple had to say about all of the above and more in this interview.
Operating more efficiently in your trucking business helps you increase drive time, which means more time for earning money. One of the best ways to increase efficiency is to use technology-based tools that reduce the time you spend on manual activities, such as phone calls to and from brokers. Check out our five helpful tips for boosting the efficiency of your trucking operations.
The Latest on COVID-19 and Its Impact on the Trucking Industry
In this update, we dig into the FMCSA's emergency declaration on hours of service, including what's considered emergency relief freight under the national emergency declaration. Also included in this blog are updates on container freight volumes at the Port of Seattle and Port of Los Angeles, as well as information on how individual states are responding to the COVID-19 pandemic.
Why Load Tracking and Visibility Are Important for Shippers
As a carrier, you probably have some mixed feelings about load tracking. But as you know, the demand for real-time load tracking isn't likely to decrease any time soon. In fact, it's likely to increase. In this blog, we discuss why real-time load tracking is so important to shippers and brokers, and how using versatile tools like the Trucker Tools driver app can satisfy brokers and shippers, while simplifying your life on the road.
Everything You Need To Know About Expedited Trucking — with The Trucking Couple
The Trucking Couple recently spoke to Trucker Tools about how they got into hauling expedited freight and what it's like to work for Hyfield Trucking as part of FedEx's Custom Critical division. Stephanie and Frank offer advice to truckers who are considering getting into expedited freight, including whether it's better to make the transition as an owner operator or as a company driver.
If you're looking for additional interviews with industry influencers and more tips for making your trucking business more profitable, check out our February 2020 Monthly Link Roundup. To download Trucker Tools' free driver app, visit https://www.truckertools.com/carriers/.
Trucker Tools' New Driver App: Making Your Life Even Easier on the Road
Trucker Tools and TruckPark Announce Strategic Partnership


text:
George Harold Kojac (New York, 2 maart 1910 – Fairfax (Virginia), 28 mei 1996) was een Amerikaans zwemmer.

Biografie
Tijdens de Olympische Zomerspelen van 1928 won Kojac de gouden medaille op de 100m rugslag en de 4x200 meter vrije slag estafette in een wereldrecord. Op de 100 meter vrije slag eindigde hij als vierde. Kojac zijn wereldreccord op de 100 mete rugslag bleef staan tot 1934 en dit was het enige olympisch zwemrecord van 1928 dat vier jaar later bleef staan.

In 1968 werd Kojac opgenomen in de International Swimming Hall of Fame.

Amerikaans zwemmer
Amerikaans olympisch kampioen

redpajama_set_name: RedPajamaWikipedia


We will always love smoking marijuana, from the taste, to that burning sensation as it goes down, to the exhale of ecstasy, but there is something about eating marijuana that feels just right. The effects are as potent as smoking marijuana, except you are not smoking it. You are eating it.
Marijuana is one of the safest drugs that you can take into your system. There are numerous ways to consume it including smoking it, eating it, breathing it, injecting it, and even rubbing it on your skin can get you a certain high or "good feeling". There is no right or wrong way to intake marijuana and it all depends on personal preference.
Back in my teenage years, I only knew about smoking marijuana from the little dime bag you bought which contained a small herb of the plant. You would smoke it into your lungs and get high. The feelings would sometimes be a burning sensation, and depending on your experience and mindset, you could get paranoid, hungry, happy, sleepy, depressed, or have this desire to become a complete isolationist, just so you could enjoy your high alone and understand the universe.
Nowadays, marijuana comes in all shapes and sizes, from resin to dabs to wax to nuggets to edibles. While I'm not here to get into any of the others, I highly recommend that you try marijuana in all its shapes and sizes and see what works for you. Dabs are insanely powerful and a tiny bit will give you a high like you never had in high school. A small amount will keep you high for hours on end and it will feel like the first time you smoked pot all over again. As with everything, the more you do it, the more a tolerance can be built up. When it comes to marijuana or any other drugs, give your body a break away from it. Let your mind forget all about it so that you can experience it as if it was one of your first times.
Now that we got all that covered, we'll get into what we have now replaced our smoking habit with: eating. There are a great amount of benefits to eating pot rather than smoking it and one of the primary reasons is: weed, no matter how much you want to hide the smell, is detectable by scent and in many cases, your eyes. The smell gets into your clothes, all around your surroundings, and while I absolutely love the smell of pot, not everyone else does, and this could be a problem, especially if you don't live in a legalized state. Your eyes also become bloodshot and it is apparently obvious. Not so much when you eat marijuana.
The high you get from smoking is different from eating it, but the effects, although they take slightly longer to kick in, eating marijuana all depends on your digestive system. You could be high in as little as 20 minutes or it could take up to an hour or more. In the arguments against eating marijuana edibles, the time it takes to get high is definitely longer. Fortunately, the potency is much stronger, considering it went through your digestive system and was processed by your liver which processes into the blood stream, where it circulates in the blood throughout the body, and make its way into the brain. Smoking it on the other hand will give you near-instant results, but the high is over much faster.
People hate the feeling of an LSD trip after eating a marijuana edible. They hate the jitters and the paranoia that tends to come with eating edibles. In fact, these are not the actual effects of edibles if taken in smaller doses. Most people eat an entire cookie, down a whole brownie, eat an entire chocolate bar, drink a whole bottle of marijuana soda, and then wonder why they had a crazy trip and think there is something wrong with the marijuana. It is very hard to overdose and die on marijuana, but overdosing is quite common, and when you overdose, you go through the experiences of everything I mentioned. Learn what your body can handle, ingest what your body can handle, and a marijuana edible is amazing.
Some people who eat edibles think it is not working, though the effects usually just creep up on them, and once they stand up, or start walking, they realize just how high they are. If they don't feel the full effect immediately, they jump to the conclusion that the cookie didn't work and so they eat another cookie, and another. This is the wrong thing to do. Drink three coffees in a row and let me know what happens. Triple dose of caffeine will have you anxious and looking like you have ADHD. The same goes for 3 THC-infused cookies.
You must experiment with edibles and your doses and understand the right one for you. Not even your doctor can tell you how much you should be consuming. Start off with a small dosage, like a quarter of a cookie, and work your way up to half, then move on to a whole. If you feel you aren't getting high after a while, but you are consuming edibles everyday, as I said before, you need to give your body a break for a while.
Edibles get a bad rap and don't deserve it. Fortunately, with the availability of marijuana and edibles in legalized states, many visitors and tourists are turning to edibles because they prefer the method of ease for getting it into their system. It can be disguised as something else and the comfort with doing it in front of others is easy because they cannot smell it and all people see you doing is eating a cookie, or a brownie, or whatever THC-infused food you are eating. Many people with kids are also turning to edibles because they do not want to be a bad influence on their children, but eating it: the child never knows and believes its normal because its food.
Experiment with edibles and see which ones are right for you. Ask the representative about their opinion of what edibles are good and which ones are not recommended. You can also find plenty of reviews online for what to eat. You can even go buy marijuana and bake with it or create a butter stick and cook with it. Take your time, learn what you like, and learn what your body can handle. We love marijuana edibles and we hope you will too!


text:
Assassin's Creed Chronicles: Russia Review
Dasvidaniya, and good riddance.
By Zachary Ryan
Updated: 1 May 2017 3:14 pm
Posted: 9 Feb 2016 1:22 am
Assassin's Creed Chronicles: Russia
Assassin's Creed Chronicles: Russia - Xbox One
$9.99on Microsoft Store
is a dichotomous affair from the outset. This side-scrolling stealth game is very clearly an Assassin's Creed game in more than just name, but it lacks much of what works well in the full-fledged entries in the series and manages to retain much of what doesn't.
ACC: Russia arrives devoid of any compelling characters, and repeatedly subjects you to tedious trial-and-error missions. There are moments when it truly shines, but those are quickly eclipsed by uneven mechanics, instant fail-states, and bland level design.
The story is less interested in the October Revolution of 1918, and more on our hero Nikolai Orev's attempts to flee Russia and start a new life outside the order with his family. He falls squarely into the "grizzled veteran" archetype, and instead of delivering a politically charged story rooted in one of the most interesting historical uprisings, you're simply charged with seeing him through his last mission and recovering a Piece of Eden before the Templars do, just like in every Assassin's Creed game before it.
Russia wastes no time in introducing you to its numerous ways to fail a mission. Firstly, despite being a Master Assassin, Nikolai has very little health and he's not worth much in a fight. As a stealth game, combat is supposed to take a back seat to sneaking and hiding, but even when you're spotted and must engage enemies head on, you've only got one chance to get it right. Regardless of whether enemies are swinging swords, pounding him with clubs, or shooting him with rifles from afar, Nikolai can only withstand one or occasionally two hits before you're staring at the loading screen.
As a Master Assassin, Nikolai has very little health and he's not worth much in a fight.
This makes taking on multiple enemies exponentially more difficult. You'll regularly find yourself with your back turned to one enemy while engaging another. To be fair, a dodge mechanic occasionally saved me from a bullet when I least expected it, but it was clumsy, and only worked half of the time. As the game progressed, I found myself worrying less about blocking and dodging, and mostly trying to brute-force my way through combat segments, as attacking seems more reliable than any defensive maneuvers.
So don't get spotted, right? Unfortunately, the stealth segments aren't particularly wonderful either. Most missions are focused on a sneaking segment and, to be fair, there are sometimes genuinely clever and engaging ones. It's admittedly impressive just how much of the traditional Assassins' skill set developer Climax Studios was able to cram into the structure of a 2D platformer. You can hide behind or inside of objects, stash bodies, and distract guards using guns, smoke bombs and and an electrified grappling hook. Each area is laid out almost like a diorama, you can survey the scene around you and plan accordingly to try and reach your objective as efficiently as possible.
And the backdrops are occasionally gorgeous to look at. The war-torn buildings and gilded palaces of Moscow look like something out of a watercolor pop-up book, and the art team should be applauded for their clever use of backdrops that recall the iconic propaganda of the era.
When instant-fail states are thrown into the mix, however, these beautiful stealth portions are reduced to trial-and-error style of gameplay that cripples many of ACC: Russia's best segments. Frequently, there's no clear indication of how to sneak past certain guards, and I was forced to adopt a method of purposely failing missions in different ways to eliminate things that didn't work, hoping to stumble across the right path. In the end, each stealth encounter felt like a poorly designed puzzle without clues, and that robbed me of much of the joy and vindication that I would feel finishing a particularly difficult or perplexing segment in most other games.
Both combat and stealth missions are improved upon by the second playable character, the young Duchess Anastasia Romanova. Not unlike Assassin's Creed Syndicate's Evie Frye, Anastasia is an instantly more likeable character, and after an encounter with a Piece of Eden, Anastasia learns the ways of the Assassins. Her skill set offers more variety than Nikolai's, despite having fewer weapons at her disposal.
What sets her apart is her Helix abilities. These skills are rooted in Assassin's Creed lore and allow Anastasia to phase unseen between hiding spots, and to erase the bodies of her foes from time and space. She can move through areas much more fluidly, and late-game missions see you switching between to the two characters to solve puzzles and open doors for each other. These are by far the best missions in ACC: Russia, and are disappointingly few and far between.
Neither character can salvage any joy from the overly difficult, repetitive, and infuriating endless runner segments, though. These missions, while beautiful to look at, represent the worst that ACC: Russia has to offer. They take what could have been a series of exciting platforming challenges and ruin them with poor mechanics and insane difficulty spikes.
Neither character can salvage any joy from the overly difficult, repetitive, and infuriating endless runner segments
What's frustrating here is the lack of direction in these sequences. You're usually being pursued by something, like a series of explosions, or a tank that moves faster than your character, so you're constantly trying to stay one step ahead while leaping and ducking obstacles. Over and over I found myself running to the same spot with no indication of where to go next, only to be run over or blown up and do it all again.
The controls also seem to go haywire in these segments. Whether it's a result of the speed or perspective, it seemed like a jump or hiding spot that worked on the first four attempts led to instant deaths on the fifth and sixth runs, only to inexplicably work flawlessly on the seventh. It repeatedly undermines the pace and rhythm that could have made these segments great.
Assassin's Creed Chronicles: Russia disappoints on multiple levels, from a flat main character to unintuitive insta-fail stealth levels to clumsy combat and platforming. The few times it nails it with diorama-like puzzles and Helix powers only serve to make the rest of this side-scrolling spinoff look even worse by comparison.
DeveloperClimax Studios
PublisherUbisoft
Release DateFebruary 9, 2016
PlatformsPC, Xbox One, PlayStation 4
Microsoft Store $9.99
Assassin's Creed Chronicles: Russia is an overly difficult, repetitive, and often infuriating side story.


text:
Watch: Missing dog rescued from drain pipe on university campus
July 16 (UPI) — Firefighters in California came to the rescue of a dog found trapped in a drain pipe on the University of California Santa Barbara campus.
The Santa Barbara County Fire Department said a member of the public heard the dog crying in distress from a drain pipe on the school's campus and alerted authorities.
Firefighters climbed into the drain and coaxed the dog out of the pipe.
The department said the canine, a 2-year-old pet named Sophie, had been missing from her owner's home for about a month. They said she is believed to have been trapped in the pipe for about three days.
The canine had been spotted periodically in the area prior to the drain rescue, but firefighters said her whereabouts for most of the month that she had been missing are unknown.
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When a goat breaks a horn it is very painful for the goat. There is a nerve and a large blood vessel that runs thru the horn.
If the horn is only broken on the end with little or no bleeding, you can cut off the broken piece if it's still attached, apply blood stop powder and wrap the end of the horn if needed.
If the horn has been broken lower and there is heavy bleeding, you will need to apply pressure to the horn stump until the bleeding stops. If you cant stop the bleeding by pressure to the stump, find the blood vessel below the inside corner of the goats eye (You may have to move your finger around a bit to feel for this blood vessel.) apply pressure for five minutes, then gently release the pressure and reapply pressure again if needed. Once the bleeding has stopped, apply blood stop powder to encourage better clotting and wrap.
Another way to deal with a broken horn is you can cauterize the broken end by using a disbudded or if camping, any metal item that can heated red hot and applied to the break in the horn.


Hi, I certainly agree with you. Your advice is really very helpful for us. Thanks a lot!
Yes really nice discussion is going here.Thanks to all !!!!!!!!!!!!!!!
Can I get some tiny little help please?
Yes! Nice information that you have shared with us. Thank you very much!
Thanks for sharing this nice link.
Need to play dvd movies on ipod!!!
Hi sorry I cannot help you because I don't have any idea about better software to convert dvd movies to ipod format. Good luck!