Demystifying Deep Learning & AI - Nov 19th-20th, 2016
Artificial Intelligence and Deep Learning are the current buzzwords of the tech industry. So, have you been wondering what all the fuss is about?
Have you wanted to incorporate AI into your products, but have no idea where to start? Are you letting terms like 'Big Data' or 'Differential Calculus Equations' intimidate you from being a part of the leading edge of this technology?
JOIN US for an all weekend, hands on workshop series Demystifying Deep Learning & AI. You will have the opportunity to gain insight & hear lighting talks from World Class Engineers in the field.
Learn how to use the latest AI open source platforms including:
SciKit
Tensor Flow
ConvNetJS
Keras
Network & Mingle with PhD students, faculty members, and industry research scientists. Share your projects and vision for the future of Deep Learning & Artificial Intelligence.
Workshops led by some of the brightest Engineers from Accenture, Elsevier, Holbertonschool, MetaMind, Metis, Spark, Udacity, XBrain and many more!
Abhishek Sharma - MetaMind
Hands on ML
Learn to use ML algorithms in your applications. In this session we will cover basics of numpy (a python library used for mathematical operations) and then move on to implementing ML algorithms using sci-kit learn.
Hands on Tensorflow
This session will cover the basic architecture of Tensorflow followed by implementation of basic deep learning architectures for classification tasks.
Note
Please make sure that numpy and scikit learn and Tensorflow are installed in your machine before coming for the sessions. Instructions for the same will be shared soon.
A case study with word2vec, a commonly used technique for pre-training word embeddings. What is the training process doing, what is being learned, and why do they work? The intuition gained will be useful for thinking about how language models with embeddings are trained in general.
What is a robot? Why is A.I. important in personal robotics? We now have the ability to digest enormous amounts of data, to read our own thoughts, and are now able to prevent disease - rather than treating it. The era of personalized robotics is upon us, designed for you, better serving us as individuals. This next era of robotic automation, brings them out of the factories ( big industry), and into our everyday lives; much of this, will be enhanced and accelerated by A.I.
Over-fitting, a phenomenon when a model explains well the data set it has seen, but fails to generalize to the new data is common to both simple linear models and complex deep neural networks. This workshop will provide intuition of such behavior and discuss ways to prevent it. In particular, we will focus on a weight penalization as a way to improve generalization. We will implement and train a model and look at it from probabilistic and linear algebra perspective.
Convolutional Neural Networks are as elegant as they are tremendously successful in practical applications. This talk will demonstrate how they operate at a low level, and then provide a number of diverse viewpoints on interpreting their performance. Those views will include manifold learning, representation learning, automating feature engineering and more.
A friendly and pictorial dive into solving classification problems with deep learning. Topics will include logistic regression, gradient descent, and deep neural networks.
Deep Learning for Images from Holberton School Co-lead
Understand the basics of deep neural networks and play with Keras, a minimalist, highly modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Hear a summary of interviews with bot developers, platform developers, clients and users to understand motivation of each segment. This talk will cover the problems facing each sector of the bot ecosystem.
Learn about platforms that can be used by companies to build their bots and what marketing tools are available help advance bot discovery.
This talk will cover an overview of different types of recommender systems, with a focus on using deep learning for recommendation systems. Notable recent application areas are music recommendation, news recommendation, and session-based recommendation.
Did Big Data Fail us in the Presidential Election?
Not a single major poll, megapoll, or survey in this election successfully predicted the outcome. As a result, an already skeptical American population is experiencing a big data backlash. What happened? Is our faith in big data misguided? In this short talk, I discuss how the misconceptions in the data science community about the accuracy of models and polling, combined with a basic lack of understanding and explanation in the public about statistical models and their outcomes, led to arguably the biggest Big Data debacle since Google Flu Trends.
Deep Learning for Images from Holberton School Co-lead
Understand the basics of deep neural networks and play with Keras, a minimalist, highly modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
This talk will describe how a Deep Convolutional Network (DCNN) trained on the ImageNet dataset can be used to classify images in a completely different domain. The intuition that the training process teaches the DCNN to extract good features from images is explored with visualizations. Transfer Learning freezes the bottom layers of the DCNN to extract image vectors from a training set in a different domain, which can then be used to train a new classifier for this domain. Fine tuning involves training the pre-trained network further for the target domain. Both approaches are demonstrated using a VGG-16 network pre-trained on ImageNet to classify medical images into 5 categories. Code examples are provided using Keras.
There are five parking structures that service the Civic Center Plaza. The closest is beneath the Dalziel Building. The entrance to this garage is on 16th Street between Clay Street and Telegraph Avenue.
Parking also is available in the City Center Garage, located beneath City Center, accessed via entrances on 14th Street between the 1300 Clay Street and 505 14th Street buildings, or via 11th Street just past Clay. A third parking structure is located very nearby on San Pablo Avenue, with entrances on both 16th and 17th streets. In addition, there is a parking structure on Clay between 14th and 16th streets. Finally, there is a large parking structure, City Center Garage West, on the corner of 12th and Jefferson streets, and accessed via entrances on 12th and on Martin Luther King, Jr. Way (across from Preservation Park).
Public Transportation
Civic Center Plaza is serviced by all AC transit lines and by BART 12th St Station.
Organizer of Deep Learning Enthusiasts Meetup Group and a backend engineer at Metamind. He received his Master’s in Computer Science (AI track) from University of Illinois at Urbana Champaign (UIUC). His interests include Deep Learning, Natural Language Processing and large-scale Machine Learning.
He worked with Prof. ChengXiang Zhai, UIUC, on discovering controversial points in news articles by leveraging social media conversations. He was the recipient of the Cognitive Science/Artificial Intelligence Award – 2014, awarded by the Computer Science Department, UIUC.
Self-taught software engineer with wide variety of experiences in frontend, mobile, distributed systems, data engineering, and machine learning. Avid student of new deep learning techniques and excited about applying recently published methods to applications in NLP and gaming.
Carlos' most recent endeavors are using Deep Learning (A.I.) in two of his startups (Biofabs, LUSH Robotics) - coupling algorithms and massively parallel computing to mimic the very neural networks that govern the behavior of what our brains do best - pattern recognition. Carlos is a serial entrepreneur, leading and advising startups as founder/ developer/ product manager/ instructor. His passion is one of leveraging converging disciplines, and harnessing the power of distributed innovation & digital fabrication - and putting them to work in robotics. Most recently he was the Director of the Innovation Lab ( iLab) at Singularity University (SU) where he served the mission to educate and empower present and future leaders towards leveraging exponential technologies.
Carlos has always prescribed to the SU mindset, in that everyone should inspire to ‘think big’ as an entrepreneur, especially when subscribing to make things that will help a billion people within 10 years. Carlos holds a Masters in Bioengineering from UCSD and the equivalent of a Masters in Computer Vision, and Robotics from INPG/ INRIA in Grenoble, France.
As a former math professor and data scientist, Greg is passionate about a connected world where universal access to information and knowledge frees people to achieve their full potential.
Greg is an artificial intelligence lead architect and big data guy working on unsupervised deep learning, bot, personal assistant, connected things and voice/semantic search for over than 15 years.
Jeremy is a machine learning engineer dedicated to understanding the principles underlying information and intelligence and deploying them in meaningful real world applications. He has been working on deep learning in Apache Spark's MLlib since he graduated from Harvard in Applied Mathematics and Computer Science.
Luis Serrano is the Machine Learning Nanodegree Lead at Udacity. Previously he was a Machine Learning Engineer at Google for 2 years, working on the video recommendations at YouTube. Before that, he was an academic, and was working as a postdoctoral fellow in Mathematics at the University of Quebec at Montreal. Luis obtained his PhD in Mathematics at the University of Michigan, and his Bachelors and Masters in Mathematics at the University of Waterloo.
Masha's background is in Marketing, Customer Development and Linguistics. She started working on a personalized English learning tool with AI backend in 2014. In fall this year her team developed a bot to help people improve their English.
Rumman is a Senior Data Scientist at Metis and PhD Candidate in Political Science at the University of California, San Diego. Masters in Quantitative Methods from Columbia University and undergraduate degrees from MIT.
Her diverse background in both academia and the private sector emphasizes providing actionable and scaleable solutions using advanced statistical and machine learning techniques. She has successfully led industry-awarded data science teams, educates budding data scientists, and continues to help Fortune 500 companies leverage their data science capabilities.
She uses her study of human behavior in forecasting and the social sciences to inform her work in Data Science.
Sam Bozek is a Canadian Chemist who loves alliteration and art. He decided to use computers to help with the art thing, after being a chemist ruined too many pant legs.
Sujit builds intelligent systems around research content. His primary interests are IR, NLP, ML, DL, ontologies and distributed processing. Prior to this, he built ontology backed semantic search, contextual advertising and EMR analytics for consumer healthcare.
Dima Lituiev does human genetics research at the UCSF, co-organizes a Deep Learning Study Group, and occasionally teaches data science. Born in Ukraine, Dima did his PhD at the University of Zurich, Switzerland, where he analysed images and built model of development of plant flower parts. His interests are in probabilistic models, machine learning, genetics, and developmental biology.
Alex studied theoretical mathematics at the California Institute of Technology, then went into educational research. He has worked as the last few years as a research consultant for academic resesrch and data scientist consultant for businesses, and is now specializing in deep learning research.
Malai is the Founder and CTO at Datalog.ai, where he loves to take on the challenges of unstructured data. He actively works on Natural Language Processing and Computer Vision problems, with applications in conversational agents and health. He loves high performance computing, and trains Deep Learning models on GPUs to keep his home warm in the winter.
Stephane is passionate about solving problems that are important to society and social progress. He has a uniquely varied background, having worked on four different continents, as a Space Operations Engineer, Professor of Applied Physics, and Software Entrepreneur. As an AI Scientist at datalog.ai, his current obsession is modeling the acoustics of human speech for Deep Learning applications.


Overview:
The turtlebot workstation should be set up with the SDK for the cameras, but the installation
instructions can be found
here.
I had installation issues on Ubuntu 18.04 and Ubuntu 19.04 but no problems with Ubuntu 16.04 with ROS
Kinetic installed. I do recommend installing ROS before going through the Mynt Eye setup. Also, I tried
but was unsuccessful setting up a VM of ubuntu 16.04 with the Mynt Eye SDK and ended up doing a fresh install of
16.04 on my laptop. The only visual odometry examples I was able to get running were the VINS-mono and
VINS-fusion packages. Instructions to do so can be found
here.
And for the record, you most certainly do not need 16GB of ram to run VINS-fusion, more like 8.


Man Utd draw up eight-man list of key targets ahead of January window
Ole Gunnar Solskjaer has drawn up an eight-man list of long-term targets ahead of the January transfer window, reports say.
Manchester United are expected to do business in January, with Solskjaer’s main priority appearing to be the signing of a striker.
Mario Mandzukic has been heavily linked with a switch to Old Trafford and ESPN claim United have decided on a lengthy list of priority targets.
RB Salzburg striker Erling Haaland and Borussia Dortmund winger Jadon Sancho are key targets and are set to be the subjects of formal enquiries from United in January.
Bournemouth striker Callum Wilson, Leicester playmaker James Maddison, West Ham midfielder Declan Rice, Lyon striker Moussa Dembele and Aston Villa duo John McGinn and Jack Grealish are also proprieties.
United intend to chase these targets beyond the January window, but are prepared to spend in the winter window if their ‘key’ targets become available.
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Solskjaer is determined to build his United squad around talented youngsters who would predominately be British, just as Sir Alex Ferguson did when he was in charge at Old Trafford.
United want to significantly strengthen their midfield, as well as their forward line after the departures of Alexis Sanchez and Romelu Lukaku.
Solskjaer was unable to replace Sanchez and Lukaku during the summer and the latter claimed this week the United boss wanted him to stay.
‘Solskjaer has my eternal respect,’ Lukaku said.
‘He understood me when I said in March that it was time for me to leave England.
‘I have been in the Premier League as an 18-year-old boy and now I am 26. Solskjaer wanted to keep me, but I was ready for something new.’


I worked as an instructional designer and a faculty member in higher education in the past eight years. After pursuing my second master's degree in Instructional Systems Technology at Indiana University Bloomington, I will continue to work in higher education.
I have extensive knowledge in Instructional Design, adult learning, and cutting-edge learning technologies. I would like to use my professional knowledge to help faculty improve their teaching through technology.Please feel free to contact me if you have any questions about my portfolio.


The woman broke her smile,
Actually, I was thinking of getting the Vindaloo.
You stand there, pouring their glasses with water.
You know this routine all too well.
I'm tired of chicken.
Sorry... I just don't really like fish.
The glasses are full.
You take a deep breath.
If I make suggestion,
Vindaloo is much spicy and popular.
It comes with lamb, goat, chicken, fish, or beef.
Your smiles hurt.
Well, how about that.
We could try the beef? Or the lamb?
Yeah, the beef sounds good.
Continue
You take a deep breath.
Will give you moment.
Call whenever ready, please. Thank you.
Your smile hurts.
The man waves his hand after five minutes.
Yeah, we'll have the Fish Curry.
And two Mango Lassis.
The woman smiles, Thank you.
Continue


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All was ready as Rand had ordered in the courtyard at the front of the Sun Palace. Or almost all. The morning sun slanted shadows from the stepped towers, so only ten paces in front of the tall bronze gates lay in full light. Dashiva and Flinn and Narishma, the three Asha’man he had retained, waited beside their horses, even Dashiva resplendent with the silver sword and red-and-gold Dragon on his black collar, though he still touched the sword at his hip as if constantly surprised to find it there. A hundred of Dobraine’s armsmen sat their mounts behind Dobraine himself with two long banners that hung down in the still air, their dark armor newly lacquered so it glistened in the sun, and silk streamers of red and white and black tied below the heads of their lances. They raised a cheer when Rand appeared, his sword belt with its gilded Dragon buckle strapped over a red coat heavy with gold.
“Al’Thor! Al’Thor! Al’Thor!” filled the courtyard. People crowding the archers’ balconies joined in, Tairen and Cairhienin in their silks and laces who just a week before had no doubt cheered Colavaere as loudly. Men and women who would as soon he had never returned to Cairhien, some of them, waving their arms and giving voice. He raised the Dragon Scepter to acknowledge them, and they roared louder.
A thunderous roll of drums and a blare of trumpets rose through the cheers, produced by a dozen more of Dobraine’s men who wore crimson tabards with the black-and-white disc on the chest, half carrying long trumpets draped in identical cloths, the other half with kettle drums also decorated slung on either side of the horses.
Five Aes Sedai in their shawls came to meet him as he descended the broad stairs. At least, they glided toward him. Alanna gave him one searching look with those big dark penetrating eyes; the tiny knot of emotions in his skull said she was calmer, more relaxed, than he ever remembered. Then she made a small motion, and Min touched his arm and went aside with her. Bera and the others made small curtsies, inclining their heads slightly, as Aiel streamed out of the palace behind him. Nandera led two hundred Maidens—they were not about to be outshone by the “oathbreakers”—and Camar, a rangy Bent Peak Daryne grayer than Nandera and half a head taller than Rand, led two hundred Seia Doon who would not be outshone by Far Dareis Mai, let alone Cairhienin. They swung past on either side of him and the Aes Sedai to ring the courtyard.  Five.
“Where are Kiruna and Verin?” he demanded. “I called for all of you.”
“So you did, my Lord Dragon,” Bera answered smoothly. She made another curtsy, too; only the slightest dip, but it took him aback. “We could not find Verin; she is somewhere in the Aiel tents. Questioning the . . . ” Her smooth tone faltered for one instant. “ . . . the prisoners, I believe, in an attempt to learn what was planned once they reached Tar Valon.” Once he reached Tar Valon; she knew enough not to blurt that where anyone could hear. “And Kiruna is . . . consulting with Sorilea on a matter of protocol. But I’m quite certain she will be more than happy to join us if you send a personal summons to Sorilea. I could go myself, if you—”
He waved that away. Five should be enough. Perhaps Verin could learn something. Did he want to know? And Kiruna. A matter of protocol? “I’m glad you are getting on with the Wise Ones.” Bera started to speak, then closed her mouth firmly. Whatever Alanna was saying to Min, scarlet spots had flared in Min’s cheeks and she had raised her chin, though oddly, she seemed to be replying calmly enough. He wondered whether she would tell him. One thing he was sure of about women was that every last one had secret places in her heart, sometimes shared with another woman but never with a man. The only thing he was sure of about women.
“I didn’t come out here to stand all day,” he said irritably. The Aes Sedai had arranged themselves with Bera in the lead, the others half a step back. If it had not been her, it would have been Kiruna. Their own arrangements, not his. He did not really care so long as they held to their oaths, and he might have left it alone if not for Min and Alanna. “Merana will speak for you from now on; you will take your orders from her.”
By the suddenly widened eyes, you would have thought he had slapped every one of them. Including Merana. Even Alanna’s head whipped around. Why should they be startled? True, Bera or Kiruna had done almost all the talking since Dumai’s Wells, but Merana had been the ambassador sent to him at Caemlyn.
“If you are ready, Min?” he said, and without waiting for a reply strode out into the courtyard. The big, fiery-eyed black gelding he had ridden back from Dumai’s Wells had been brought out for him, with a high-cantled saddle all worked in gold and a crimson saddlecloth embroidered with the disc of black-and-white at each corner. The trappings suited the animal, and his name. Tai’daishar; in the Old Tongue, Lord of Glory. Horse and trappings both suited the Dragon Reborn.
As he mounted, Min led up the mouse-colored mare she had ridden back, snugging on her riding gloves before swinging into the saddle. “Seiera’s a fine animal,” she said, patting the mare’s arched neck. “I wish she was mine. I like her name, too. We call the flower a blue-eye around Baerlon, and they grow everywhere in the spring.”
“She’s yours,” Rand said. Whichever Aes Sedai the mare belonged to would not refuse to sell to him. He would give Kiruna a thousand crowns for Tai’daishar; she could not complain then; the finest stallion of Tairen bloodstock never cost a tenth of that. “Did you have an interesting conversation with Alanna?”
“Nothing that would interest you,” she said offhandedly. But a faint touch of red stained her cheeks.
He snorted softly, then raised his voice. “Lord Dobraine, I’ve kept the Sea Folk waiting long enough, I think.”
The procession drew crowds along the broad avenues and filled the windows and rooftops as word raced ahead. Twenty of Dobraine’s lancers led, to clear the way, along with thirty Maidens and as many Black Eyes, then drummers, booming away—droom, droom, droom, DROOM-DROOM—and the trumpeters punctuating that with nourishes. Shouts from the onlookers nearly drowned drums and trumpets alike, a wordless roar that could have been rage as easily as approbation. The banners streamed out, just ahead of Dobraine and behind Rand, the white Dragon Banner and the scarlet Banner of the Light, and veiled Aiel trotted alongside the lancers, whose streamers also floated in the air. Now and then a few flowers were hurled at him. Maybe they did not hate him. Maybe they only feared. It had to do.
“A train worthy of any king,” Merana said loudly, to be heard.
“Then it’s enough for the Dragon Reborn,” he replied sharply, “Will you stay back? And you, too, Min.” Other rooftops had held assassins. The arrow or crossbow bolt meant for him would not find its target in a woman today.
They did fall behind his big black, for all of three paces, and then they were right beside him again, Min telling him what Berelain had written about the Sea Folk on the ships, about the Jendai Prophecy and the Coramoor, and Merana adding what she knew of the prophecy, though she admitted that was not very much, little more than Min.
Watching the rooftops, he listened with half an ear. He did not hold saidin, but he could feel it in Dashiva and the other two, right behind him. He did not feel the tingle that would announce the Aes Sedai embracing the Source, but he had told them not to, without permission. Perhaps he should change that. They did seem to be keeping their oath. How could they not? They were Aes Sedai. A fine thing if he took an assassin’s blade while one of the sisters tried to decide whether serving meant saving him or obeying meant not channeling.
“Why are you laughing?” Min wanted to know. Seiera pranced closer, and she smiled up at him.
“This is no laughing matter, my Lord Dragon,” Merana said acidly on the other side. “The Atha’an Miere can be very particular. Any people grow fastidious when it comes to their prophecies.”
“The world is a laughing matter,” he told her. Min laughed along with him, but Merana sniffed and went right back to the Sea Folk as soon as he stopped.
At the river, the high city walls ran out into the water, flanking long gray stone docks that stretched out from the quay. Riverships and boats and barges of every kind and size were tied everywhere, the crews on deck to see the commotion, but the vessel Rand sought stood ready and waiting, lashed end-on to the end of a dock where all the laborers had already been cleared off. A longboat, it was called, a low narrow splinter without any masts, just one staff in the bow, four paces tall, topped by a lantern, and another at the stern. Nearly thirty paces in length and lined with as many long oars, it could not carry the cargo a sailing vessel the same size would, but it had no need of the wind, either, and with a shallow draft, it could travel day and night, using rowers in shifts. Longboats ran the rivers with cargoes of importance and urgency. It had seemed appropriate.
The captain bowed repeatedly as Rand came down the boarding ramp with Min on his arm and the Aes Sedai and Asha’man at his heels. Elver Shaene was even skinnier than his craft in a yellow coat of Murandian cut that hung to his knees.  “An honor, it is. An honor, indeed. An honor.”
 He blinked at the Aes Sedai’s shawls and stared at their ageless faces and licked his lips, eyes flickering back to Rand uneasily. The Asha’man dropped his mouth open once he put their black coats together with rumor, and thereafter he avoided so much as a glance in their direction. Shaene watched Dobraine lead the men with the banners aboard, and the trumpeters, and the drummers lugging their drums, then eyed the horsemen lining the dock as if he suspected they might want to board, too. Nandera, with twenty Maidens, and Camar with twenty Black Eyes, all with shoufa wrapped around their heads though unveiled, made the captain step hastily to put the Aes Sedai between him and them. The Aiel wore scowls, for the heartbeat that needing to veil might slow them, but the Sea Folk might well know what a veil meant, and it would hardly do for them to think they were under attack. Rand thought Shaene’s handkerchief might yet rub away what thin gray fringe of hair he had left.
The longboat swept away from the dock on its long oars, the two banners rippling in the bows, and the drums pounding, and the trumpets blaring. Out in the river, people appeared on the decks of ships to watch, even climbed into the rigging. On the Sea Folk ship they came out, too, many in bright colors unlike the drab clothing on crews of the other vessels. The White Spray was a larger craft than most of the rest, yet somehow sleeker as well, with two tall masts raked back sharply and spars laid across them squarely where nearly all the other ships had slanting spars longer than the masts to hold most of their sails. Everything about it spoke of difference, but in one thing, Rand knew, the Atha’an Miere had to be like everyone else. They could either agree to follow him on their own or be forced to it; the Prophecies said he would bind together the people of every land—“The north shall he tie to the east, and the west shall be bound to the south,” it said—and no one could be allowed to stand aside. He knew that, now.
Sending out orders from his bath, he had not had an opportunity to give details of what he intended on reaching White Spray, so he announced them now. The details produced grins among the Asha’man, as expected—well, Finn and Narishma grinned; Dashiva blinked absently—and frowns among the Aiel, also as expected. They did not like being left behind. Dobraine merely nodded; he knew he was only here for show today. What Rand did not expect was the Aes Sedai reaction.
“It shall be as you command, my Lord Dragon,” Merana said, making one of those small curtsies. The other four exchanged glances, but they were curtsying and murmuring “as you command” right behind her. Not one protest, not one frown, not a single haughty stare or recital of why it should be done any way but what he wanted. Could he begin to trust them? Or would they find some Aes Sedai way to wriggle around their oath as soon as his back was turned?
“They will keep their word,” Min murmured abruptly, just as if she had read his thoughts. With an arm wrapped around his and both hands holding his sleeve, she kept her voice for his ears alone. “I just saw these five in your hand,” she added in case he did not understand. He was not sure he could fix his mind around that, even if she had seen it in a viewing.
He did not have long to try. The longboat flew through the water, and in no time at all was backing oars some twenty paces from the much taller White Spray. Drums and trumpets fell silent, and Rand channeled, making a bridge of Air laced with Fire that connected the longboat’s railing to that of the Sea Folk ship. With Min on his arm, he started across, to every eye but that of an Asha’man walking upward on nothing.
He half expected Min to falter, at least at first, but she simply walked at his side as though there were stone beneath her green-heeled boots.
“I trust you,” she said quietly. She smiled, too, partly a comforting smile, and partly, he thought, because she was amused at reading his mind once more.
He wondered how much she would trust if she knew that this was as far as he could weave a bridge like this. One pace farther, one foot, and the whole thing would have given way at the first step. At that point it became like trying to lift yourself with the Power, an impossibility; even the Forsaken did not know why, any more than they knew why a woman could make a longer bridge than a man even if she was not as strong. It was not a matter of weight; any amount of weight could cross any bridge.
Just short of White Spray’s railing he stopped, standing in midair. For all Merana’s descriptions, the people staring back at him were a shock. Dark women and bare-chested men with colorful sashes that dangled to the knee, and gold or silver chains around their necks and rings in their ears, in their noses of all places on some of the women, who wore a rainbow of blouses above their dark, baggy breeches. None had any more expression than an Aes Sedai who was trying hard. Four of the women, despite being barefoot like the rest, wore bright silks, two of them brocades, and they had more necklaces and earrings than anyone else as well, with a chain strung with gold medallions running from an earring to a ring in the side of the nose. They said nothing, only stood together watching him, sniffing at small, lacy golden boxes that hung from chains around their necks. He addressed himself to them.
“I am the Dragon Reborn. I am the Coramoor.”
A collective sigh ran through the crew. Not among the four women, though.
 There were white streaks through her straight black hair, and fine lines at the corners of her eyes. She had an impressive dignity. “I speak here for the Mistress of the Ships. If it pleases the Light, the Coramoor may come aboard.” For some reason she gave a start, and so did the three with her, but that sounded entirely too much like permission. Rand stepped onto the deck with Min wishing he had not waited.
He let the bridge go, and saidin, but immediately felt another bridge replace it. In short order the Asha’man and the Aes Sedai were with him, the sisters no more flustered than Min had been, though perhaps one or two did straighten her skirts a bit more than necessary. They were still not so easy around the Asha’man as they pretended.
The four Sea Folk women took one look at the Aes Sedai and immediately gathered in a close huddle, whispering. Harine did a lot of the talking, and so did a young, pretty woman in green brocade with eight earrings altogether, but the pair in plain silk put in occasional comments.
Merana coughed delicately, and spoke softly into the hand she used to cover it. “I heard her name you the Coramoor. The Atha’an Miere are great bargainers, I’ve heard, but I think she gave away something, then.” Nodding, Rand glanced down at Min. She was squinting at the Sea Folk women, but as soon as she noticed his look, she shook her head ruefully; she saw nothing yet that might help him.
Harine turned so calmly there might never have been any hasty conference. “This is Shalon din Togara Morning Tide, Windfinder to Clan Shodein,” she said with a small bow toward the woman in green brocade, “and this is Derah din Selaan Rising Wave, Sailmistress of White Spray.” Each woman bowed slightly as she was named, and touched fingers to her lips.
Derah, a handsome woman a little short of her middle years, wore plain blue and also eight earrings, though her earrings, nose ring, and the chain that ran between was finer than Harine’s or Shalon’s. “The welcome of my ship to you,” Derah said, “and the grace of the Light be upon you until you leave his decks.” She made a small bow toward the fourth woman, in yellow. “This is Taval din Chanai Nine Gulls, Windfinder of White Spray.” Only three rings hung from each of Taval’s ears, fine like those of the Sailmistress. She looked younger than Shalon, no older than himself.
Harine took it up again, gesturing toward the raised stern of the ship. “We will speak in my cabin, if it pleases you. A soarer is not a large vessel, Rand al’Thor, and the cabin is small. If it pleases you to come alone, all here stand surety for your safety.” So. From the Coramoor to plain Rand al’Thor. She would take back what she had given, if she could.
He was about to open his mouth and agree—anything to get this done; Harine was already moving that way, still gesturing for him to follow, the other women with her—when Merana gave another tiny cough.
“The Windfinders can channel,” she murmured hastily into her hand. “You should take two sisters with you, or they’ll feel they’ve gained the upper hand.”
Rand frowned. The upper hand? He was the Dragon Reborn, after all. Still . . . “I will be pleased to come, Wavemistress, but Min here goes everywhere with me.” He patted Min’s hand on his arm—she had not let go an instant—and Harine nodded. Taval was already holding the door open; Derah made one of those small bows, gesturing him toward it.
“And Dashiva, of course.” The man gave a start at his name, as if he had been asleep. At least he was not staring wide-eyed around the deck like Flinn and Narishma. Staring at the women. Stories spoke of the alluring beauty and grace of Sea Folk women, and Rand could certainly see that—they walked as if they would begin dancing on the next step, swaying sinuously—but he had not brought the men here to ogle. “Keep your eyes open!” he told them harshly. Narishma colored, jerking himself stiffly erect, and pressed fist to chest. Flinn simply saluted, but both seemed more alert. For some reason, Min looked up at him with the tiniest wry smile.
Harine nodded a little more impatiently. A man stepped out from the crew, in baggy green silk breeches and with an ivory-hilted sword and dagger thrust behind his sash.  She waved him away even more impatiently. “As it please you, Rand al’Thor,” she said.
“And of course,” Rand added, as though an afterthought, “I must have Merana, and Rafela.” He was not certain why he chose the second name—perhaps because the plump Tairen sister was the only one not Green except Merana—but to his surprise, Merana smiled in approval. For that matter, Bera nodded, and so did Faeldrin, and Alanna.
Harine did not approve. Her mouth tightened before she could control it. “As it please you,” she said, not quite so pleasantly as before.
Once he was inside the stern cabin, where everything except a few brass-bound chests seemed built into the walls, Rand was not so sure the woman had not gained whatever she wanted just bringing him there. For one thing, he was forced to stand hunched over, even between the roof beams, or whatever they were called on a ship. He had read several books about ships, but none mentioned that. The chair he was offered at the foot of the narrow table would not pull out, being fastened to the deck, and once Min showed him how to unlatch the chair arm and swing it out so he could sit, his knees hit the bottom of the table. There were only eight chairs. Harine sat at the far end, her back to the stern’s red-shuttered windows, with her Windfinder to her left and the Sailmistress to her right and Taval below her. Merana and Rafela took the chairs below Shalon, while Min sat to Rand’s left.  A young woman in a bright blue blouse, with one thin earring in each ear, brought thick cups of tea, brewed black and bitter.
“Let’s be done with this,” Rand said testily as soon as the woman left with her tray. He left his cup on the table after one sip. He could not stretch out his legs. He hated being confined. Thoughts of being doubled inside the chest flashed in his head, and it was all he could do to rein his temper. “The Stone of Tear has fallen, the Aiel have come over the Dragonwall, all the parts of your Jendai Prophecy have come to pass. I am the Coramoor.”
Harine smiled across her cup, a cool smile with no amusement in it. “That may be so, as it pleases the Light, but—”
“It is so,” Rand snapped despite a warning glance from Merana. She went so far to nudge his leg with her foot. He ignored that, too. The cabin walls seemed closer, somehow. “What is it that you don’t believe, Wavemistress? That Aes Sedai serve me? Rafela, Merana.” He gestured sharply.
All he wanted was for them to come to him and be seen to come, but they set down their cups and rose gracefully, glided to either side of him—and knelt. Each took one of his hands in both of hers and pressed her lips to the back of it, right on the shining golden-maned head of the Dragon that wound around his forearm. He just managed to conceal his shock, not taking his eyes from Harine. Her face went a little gray.
“Aes Sedai serve me, and so will the Sea Folk.” He motioned the sisters back to their seats. Oddly, they looked a touch surprised. “That is what the Jendai Prophecy says. The Sea Folk will serve the Coramoor. I am the Coramoor.”
“Yes, but there is the matter of the Bargain.” That word was plainly capitalized in Harine’s tone. “The Jendai Prophecy says you will bring us to glory, and all the seas of the world will be ours.  If I do not make the Bargain well, Nesta will hang me naked in the rigging by my ankles and call the First Twelve of Clan Shodein to name a new Wavemistress.”  Her Windfinder goggled at her, and Derah and Taval tried so hard not to, their eyes fastened to the table, that it seemed their faces might break.
And suddenly, Rand understood. Ta’veren. He had seen the effects, the sudden moments when the least likely thing happened because he was near, but he had never known what was going on before until it was finished. Easing his legs as best he could, he leaned his arms on the table. “The Atha’an Miere will serve me, Harine. That is given.”
“Yes, we will serve you, but—” Harine half-reared out her chair, spilling her tea. “What are you doing to me, Aes Sedai?” she cried, trembling. “This is not fair bargaining!”
“We do nothing,” Merana said calmly. She actually managed to drink a swallow of that tea without wincing.
“You are in the presence of the Dragon Reborn,” Rafela added. “The Coramoor your prophecy calls you to serve, as I believe.” She laid a finger to one round cheek. “You said you speak for the Mistress of the Ships. Does that mean your word is binding on the Atha’an Miere?”
“Yes,” Harine whispered hoarsely, falling back in her seat. “What I say binds every ship, and all to the Mistress of the Ships herself.” It was impossible for one of the Sea Folk to go white in the face, yet staring at Rand, she came as near as she could.
He smiled at Min, to share the moment. At last a people would come to him without fighting every step of the way, or splitting apart like the Aiel. Maybe Min thought he wanted her help to clinch matters, or maybe it was ta’veren. She leaned toward the Wavemistress. “You will be punished for what happens here today, Harine, but not so much as you fear, I think. At least, one day you will be the Mistress of the Ships.”
Harine frowned at her, then glanced to her Windfinder.
“She is not Aes Sedai,” Shalon said, and Harine seemed caught between relief and disappointment. Until Rafela spoke.
“Several years ago, I heard reports of a girl with a remarkable ability to see things. Are you she, Min?”
Min grimaced into her cup, then nodded reluctantly; she always said that the more people knew what she could do, the less good came of it. Glancing across the table at the Aes Sedai, she sighed. Rafela only nodded, but Merana was staring at her, hazel eyes avid in a mask of serenity. No doubt she expected to corner Min as soon as possible and find out what this talent was and how it worked, and no doubt Min expected it too. Rand felt a prickle of irritation; she should have known he would protect her from being bothered. A prickle of irritation, and a warmth that he could protect her from that, at least.
“You may trust what Min says, Harine,” Rafela said. “The reports I heard say that what she sees always seems to come true. And even if she does not realize it, she has seen something else.” Her round face tilted to one side, and a smile curved her mouth. “If you will be punished for what happens here, then it must mean you will agree to whatever your Coramoor wants.”
“Unless I agree to nothing,” Harine blustered. “If I make no Bargain . . . ” Her fists clenched on the tabletop. She had already admitted she had to make the Bargain. She had admitted the Sea Folk would serve.
“What I require of you is not onerous,” Rand said. He had thought about this since deciding to come. “When I want ships to carry men or supplies, the Sea Folk will give them. I want to know what is happening in Tarabon and Arad Doman, and in the lands between. Your ships can learn—will learn—what I want to know; they call in Tanchico and Bandar Eban and a hundred fishing villages and towns between. Your ships can travel farther out to sea than anyone else’s. The Sea Folk will keep watch as far west in the Aryth Ocean as they can sail. There is a people, the Seanchan, who live beyond the Aryth Ocean, and one day, they will come to try to conquer us. The Sea Folk will let me know when they come.”
“You require much,” Harine muttered bitterly. “We know of these Seanchan, who come from the Islands of the Dead, it seems, from which no ship returns. Some of our ships have encountered theirs; they use the One Power as a weapon. You require more than you know, Coramoor.” For once, she did not pause at the title. “Some dark evil has descended upon the Aryth Ocean. No ship of ours has come from there in many months. Ships that sail west, vanish.”
Rand felt a chill. He turned the Dragon Scepter, made from part of a Seanchan spear, in his hands. Could they have returned already? They had been driven back once, at Falme. He carried the spearhead to remind him that there were more enemies in the world than those he could see, but he had been sure it would take the Seanchan years to recover from their defeat, driven into the sea by the Dragon Reborn and the dead heroes called back by the Horn of Valere. Was the Horn still in the White Tower? He knew it had been taken there.
Suddenly he could not bear the confines of the cabin any longer. He fumbled with the latch on the chair arm. It would not open. Gripping the smooth wood, he tore the arm off in splinters with one convulsive heave. “We’ve agreed the Sea Folk will serve me,” he said, pushing himself up. The low ceiling made him hunch over the table threateningly. The cabin did feel smaller. “If there is any more to your Bargain, Merana and Rafela here will see to it with you.” Without waiting for an answer, he spun for the door, where Dashiva appeared to be muttering to himself again.
Merana caught him there, caught his sleeve and spoke swiftly and low. “My Lord Dragon, it would be for the best if you remained. You have seen what your being ta’veren has done already. With you here, I believe she will continue to reveal what she wants to hide and give agreement before we give anything.”
“You are Gray Ajah,” he told her harshly. “Negotiate! Dashiva, come with me.”
On deck, he drew deep breaths. The cloudless sky was open overhead. Open.
It took him a moment to notice Bera and the other two sisters, watching him expectantly, Flinn and Narishma kept to what they were supposed to do, a quarter of an eye on the ship and the rest on the riverbanks, the city on one side and the half-rebuilt granaries on the other. A ship in mid-river was a vulnerable place to be if one of the Forsaken decided to strike. For that matter, anywhere was a dangerous place then. Rand could not understand why one of them had not at least tried to destroy the Sun Palace around his ears.
Min took his arm, and he gave a start.
“I’m sorry,” he said. “I shouldn’t have left you.”
“That’s all right,” she laughed. “Merana is already setting to work. I think she means to get you Harine’s best blouse, and maybe her second best as well. The Wavemistress looked like a rabbit caught between two ferrets.”
Rand nodded. The Sea Folk were his, or as good as. What matter whether the Horn of Valere was in the White Tower? He was ta’veren. He was the Dragon Reborn, and the Coramoor. The golden sun still burned well short of its noon peak. “The day is young yet, Min.” He could do anything. “Would you like to see me settle the rebels? A thousand crowns to a kiss, they’re mine before sunset.”


Welcome to your awesome web app!
This was created from the mortar-app-stub template, one of the mortar templates.


{% extends 'base.html' %} {% import "bootstrap/wtf.html" as wtf %} {% block content %}
Hello World - You are on the post creation page


We sell methodologies!
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--- layout: page title: "about" header-img: "img/Paris-pic.jpg" ---
I do international digital expansion into Latin American markets for mobile and technology startup companies.
I'm fascinated by the role software and mobile technology are taking in our lives, and in the way their adoption is changing cultures all over the world. I focus on the tech sector and its effects on consumer behavior, mostly U.S. Hispanic (in South Florida), Brazil, Colombia, Argentina and now Cuba.
I'm from South Florida, born and raised. I attended the University of Florida during the Muschamp years, where I majored in Public Relations and minored in both French and Business Administration. I studied abroad for a semester in Paris, at La Sorbonne.
I've held various startup jobs, mostly at music tech startups like eMotion Technologies, ToneRite, and Grooveshark (which sadly no longer exists). Most recently, I operated as head of international expansion and artist relations at Setmine. I've held other positions, working with media and tech companies both in the U.S. and abroad. For the past year and a half, I've worked as a strategy consultant for tech startups out of South Florida.
I've lived in Bogotá and Paris. I speak Spanish, French and Portuguese. I'm an avid traveller, and keep that list growing to remain up-to-date with international markets.
I love dogs, wine, being outdoors and salsa dancing. If you'd like to get in touch, email me at vanessa at eternemedia dot com, or you can always tweet at me @vanessais_.


Hello, and thank you for attending this presentation.
The Model-View-Controller architecture for GUI applications has shown its versatility time and again since its first use in the smalltalk environment.
The proliferation of MVC frameworks speaks to this power, and the variations of Model-View-ViewModel and Model-View-Presenter show the flexibility of the fundamental approach.
Even with the tremendous success of the Model-View frameworks and approaches, there are unexplored techniques in the ecosystem.
Over the next hour, we will explore what can happen, and what support frameworks can provide, when we make several constraints on a business' data Model.
In this exploration, we will create an effective distributed data handling platform, a templating and scaffolding system that provides significant clarity over contemporary alternatives, and an innovative eventing library which offers an expanded vocabulary when considering the observer pattern.
The ideas are built out using JEFRi, an Entity Framework platform. The code samples will be in Coffeescript with some small additions when we speak about advisors, but the ideas, framework specification, and framework API could be implemented in any language.
The foundation of this focused approach to MVC is in an entity.
An entity is an object built from a specific, shareable definition of the properties and relationships of the data an application is modeling.
An entity framework, like JEFRi, is a framework built specifically around this concept of an application's data storage.
An application using an entity framework starts by building a Entity Relationship Diagram.
While many application lifecycles will have some documentation of the entity model at some point, possibly driving database design around an ERD, JEFRi applications use the description of the entity model at its core.
We use this entity relationship model to build an entity context.
The entity context provides the entity runtime all the information needed to build and use this data model for a business.
Let's look at a context definition.
Context
Here represented as a JSON object, let's walk through this basic user authentication system.
The entity context starts here with a single property, "entities".
Each key in this object is the name of an entity type our application will have available, and the value is the definition.
Our two entities are "User" holding the basic, commonly-accessed user information that will be needed often in our application.
The other entity is the "Authinfo", which has details specifically concerning checking the user's login credentials.
Each entity has a couple properties.
In this example, everything is a string, but more types are available to frameworks.
There are also relationships here. Each user has a single authinfo, and each authinfo is attached to a particular user.
The relationship definitions provide a few details, including how the relationship will be accessed in the application code, and how related entities will be found at runtime.
Let's look at some code that uses this context.
Usage
This code is pulled from some of JEFRi's unit tests.
It starts by loading the context into a new runtime. This will be the main access point for all our data management, including entity creation and data storage.
Loading the context is an asynchronous task, so here we hook into a deferred chain.
When the context is ready, we build our first User. Once we have a user, we can look at what's provided by the Runtime.
First, we have a call to the ID accessor.
This is a default method provided by the runtime, so entities can store their identifying data anywhere needed, and applications can find their address without needing to look at the definition first.
Next, we have the user_id accessor.
The runtime here provides an overloaded getter/setter pattern; if no value is provided, it returns the current value.
Otherwise, it updates the entity, and returns a reference to the entity.

To avoid naming collisions, they are prefixed with an underscore, except for id.
_status specifically returns an enumeration stating the data persistence state, describing if the entity has been persisted to some other JEFRi runtime.
Relationships behave exactly like properties, except using entity references instead of primitive values.
Notice in the second part of the example, the runtime can create a default instance of an entity if the relationship is called, but no entity is loaded.
Persistence
I mentioned runtimes handle persistence.
In this example, we see JEFRi using an HTML5 LocalStore utility to save the new data in the user's browser.
By changing the store the runtime uses, we can get local SQL storage, remote REST storage, or a myriad other possibilities.
Let's take a look at what we've got here.
With entities, we are trading the unconstrained possibilities of a loose data model for the more precise entity relationship definition.
In practice, many applications already use a data model that fits these constraints.
The increased expressivity of using a runtime built around such a definition provides a powerful tool for developers using this data.
Further, because the runtime knows so much about the data, it can provide an incredible amount of plumbing that other frameworks require the application developer to write.
This includes data validation, data persistence, and distributed method calls, all in a neatly packaged yet interoperable system.
For more details, the full JEFRi runtime documentation is available at docs.jefri.org
This view of entities as the fundamental business model has many parallels to current data handling strategies.
Entities with relationships and properties are very similar to current active record patterns.
Instances of entities generally map to a row in a database table, with columns holding property values.
The increased power comes in the single, well-defined entity context.
With that context describing the data, the relational database becomes just another projection of the entity data.
In flight, entity data is usually represented as a JSON string.
While it is then expanded to an in-memory instance when received by a runtime, viewing entities as documents in a document storage system is a very apt view.
The power again comes from having a single defined entity context.
With that context, Entities become type-definitions on top of document storage.
Frameworks can make very smart decisions about the data they store.
Are there any questions about entities at this point?
We can now use this concept of entities to build a templating system that makes a number of assumptions about the data model, providing a wealth of opportunities to build a robust underlying framework.
This templating engine is called DataStamp, and clones pieces of a DOM template based on the data it's rendering.
It works on the assumption that our application has entities, each with properties and relationships, and will render appropriately.
These are two templates that will get loaded at runtime.
When DataStamp loads them, it merges new nodes from the later templates into the original template, so we'll end with a dom node that's not rendered on the page, but has three nodes at the _default_entity level.
Render
Rendering the view is straightforward: pass the data object to the data-stamp, let it choose the correct view, and attach the returned DOM node where needed.
[Jump to render tests tab]
Here, you can see the rendered object.
Keeping Data-Stamp a purely DOM approach has its benefits and its drawbacks.
There is a significant amount of discussion comparing string concatenation techniques against direct DOM manipulation.
I fall into the DOM manipulation camp.
The ease of reading just DOM, and the ability to render the template without applying any data is, I find, a more valuable asset for developing against today's browsers than concerns about raw performance.
Are there any questions about DataStamp, or how it ties to entities?
Mountainous Interlude
The benefits and use of the observer pattern is well known, and has several implementations.
However, one common complaint is how often event observers accidentally mix view logic and business logic.
Advisors extend the observer pattern, putting a layer between the initial event trigger and any listeners.
The aim here is to provide a pipeline to apply business logic in an application.
These advisors let us move a lot of logic out of the view listeners, and provide a very clean fusion of eventing and aspect-oriented concepts.
event :> (data) -> Observe event ?> (data) -> Advise event <: data Trigger
event :> (data) -> Observe event ?> (data) -> Advise event <: data Trigger
In this example, we have an object that maintains a password.
The normal code path is calling the set method on the password, triggering the listeners, and updating the value.
As our business matures, we want to add some rules for what constitutes a
This is a behavior to add in-line editing functionality to any property.
By including this on our page, it watches for any properties that get rendered.
As they get rendered,
[Switch to Bindings demo]
Jonathan Porta, Chuck Lowery, Justin Grant
[[Click through]]
If you have any questions, feel free to email or IM me.
Thank you for your time :)
Are there any final questions?
Use spacebar, arrow keys, or click to navigate. Press 'n' for speaker notes.


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class: center, middle, inverse, title-slide # Introduction to Bioinformatics ##
with algorithms
### Lijia Yu @ NCCL in China ### 2019/05/15
(updated: 2019-06-03) --- background-image: url(https://image.slidesharecdn.com/bis2016introtobioinformatics-160909094908/95/introduction-to-bioinformatics-26-638.jpg) --- background-image: url(http://acm.na.edu/img/bioInfoLab/bioinformatics_venn.png) background-size: 350px background-position: 50% 65% # What is Bioinformatics? ### Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline. 1 .footnote[ [1] Molecular Biology Review - NCBI [2] Venn diagram: http://acm.na.edu/img/bioInfoLab/bioinformatics_venn.png ] ??? The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned. - the development of new algorithms and statistics with which to assess relationships among members of large data sets - the analysis and interpretation of various types of data including nucleotide and amino acid sequences, protein domains, and protein structures - the development and implementation of tools that enable efficient access and management of different types of information ---         # 1. Molecular data collection and management - In 1979, **GenBank** was established at Los Alamos National Laboratory (USA). ![](./2019-05-15-Introduction_to_Bioinformatics_files/figure/genbank.png) --- # 1. Molecular data collection and management - In 1979, **GenBank** was established at Los Alamos National Laboratory (USA). .center[![](https://upload.wikimedia.org/wikipedia/commons/thumb/e/e4/Growth_of_Genbank.svg/500px-Growth_of_Genbank.svg.png)] --- # 1. Molecular data collection and management - In 1982, nucleotide sequence database of European Molecular Biology Laboratory (also known as **EMBL-Bank**) was created (Europe). ![](./2019-05-15-Introduction_to_Bioinformatics_files/figure/EBA.png) ??? The EMBL Nucleotide Sequence Database (also known as EMBL-Bank) is the section of the ENA which contains high-level genome assembly details, as well as assembled sequences and their functional annotation. As of release 114 (December 2012), the EMBL Nucleotide Sequence Database contains approximately 5×1011 nucleotides with an uncompressed filesize of 1.6 terabytes. --- # 1. Molecular data collection and management - In 1986, DNA Data Bank of Japan (**DDBJ**) began data bank activities at National Institute of Genetics (Japan). ![](./2019-05-15-Introduction_to_Bioinformatics_files/figure/DDBJ.png) --- # 1. Molecular data collection and management - In the early 1990s, International Nucleotide Sequence Database Collaboration (INSDC) was founded in cooperation of Genebank/EMBL/DDBJ. .center[] --- # 1. Molecular data collection and management - Big Data Center: The Genome Sequence Archive (GSA) is a data repository for archiving raw sequence reads. .center[]              --- # 2. Sequence alignment - In 1962, Zuckerkandl and Pauling introducing the concept of the "molecular clock", which enabled the neutral theory of molecular evolution. .center[![](https://upload.wikimedia.org/wikipedia/commons/thumb/1/12/CollapsedtreeLabels-simplified.svg/640px-CollapsedtreeLabels-simplified.svg.png)] ??? In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. 1962年莱纳斯·鲍林和艾美·祖柯坎（Emile Zuckerkandl）提出了分子时钟，透过比较同源蛋白质的差异来推算双方分歧的时间。   --- # 2. Sequence alignment | position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |------------|---|---|---|---|---|---|---|---|---|---|---|---|---|---| | sequence 1 | G | C | A | T | G | A | C | G | A | A | T | C | A | G | | sequence 2 | T | A | T | G | A | C | A | A | A | C | A | G | C | | -- Delete(1,-) | position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |------------|---|---|---|---|---|---|---|---|---|---|---|---|---|---| | sequence 1 | G | C | A  | T  | G | A  | C | G | A | A | T | C | A | G | | sequence 2 | | T |  A |  T  | G | A  | C | A | A | A | C | A | G | C | -- Delete(8,-) | position | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | |------------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---| | sequence 1 | G | C | A  | T  | G | A  | C | G | A | A | T | C |  A |  G  | | | sequence 2 | | T |  A |  T  | G | A  | C | -- |A | A | A | C |  A |  G  | C | --- # 2. Sequence alignment - Hamming Distance -- | Hamming Distance(s,t)= | 2 | 3 | 5 | |:----------------------:|:---:|:-----:|:--------:| | s= |  A A T  | AGCAA | A GCACA CA | | t= |  T A A  | A CATA | A CACAA TA | -- - scoring matrix |BLOSUM 62 Matrix|PAM 250 Matrix| |---|---| |![BLOSUM 62 Matrix](https://upload.wikimedia.org/wikipedia/commons/thumb/0/02/BLOSUM62.png/320px-BLOSUM62.png)||    ??? BLOSUM矩阵由Henikoff提出，蛋白质短序列比对推导 PAM矩阵由Dayhoff提出，蛋白质全局序列比对推导 --- # 3. Genome Analysis | Genome | Where | Year | |--------------------------------------------------------------------|--------------------------|------| | H. Influenza | TIGR | 1995 | | E. Coli K-12 | Wisconsin | 1997 | | S. cerevisiae (yeast) | internat. collab. | 1997 | | C. elegans (worm) | Washington U./Sanger | 1998 | | Drosophila M. (fruit fly) | multiple groups | 2000 | | E. Coli 0157:H7 (pathogen) | Wisconsin | 2000 | | **H. Sapiens (that’s us)** | internat. collab./Celera | 2001 | | Mus musculus (mouse) | internat. collaboration | 2002 | | Oryza sativa L. ssp. indica & Oryza sativa L. ssp. japonica (rice) | internat. collaboration | 2002 | --- # 3. Genome Analysis - Cancer genome mutation .center[ ] .footnote[ [1] Cancer Genome Landscapes ] --- # 3. Genome Analysis - Genetic disease .center[ ] .footnote[ [1] https://ghr.nlm.nih.gov/condition/huntington-disease#genes ] ??? The HTT mutation that causes Huntington disease involves a DNA segment known as a CAG trinucleotide repeat. ---      # 4. Transcriptome Analysis .center[![](https://upload.wikimedia.org/wikipedia/commons/thumb/d/d9/Summary_of_RNA_Microarray.svg/571px-Summary_of_RNA_Microarray.svg.png)] --- # 4. Transcriptome Analysis .center[![](https://upload.wikimedia.org/wikipedia/commons/thumb/f/f3/Summary_of_RNA-Seq.svg/610px-Summary_of_RNA-Seq.svg.png)] --- # 4. Transcriptome Analysis .center[] --- # 5. Proteome Analysis ![](https://ib.bioninja.com.au/_Media/proteome_med.jpeg) .footnote[ [1] https://ib.bioninja.com.au/standard-level/topic-2-molecular-biology/24-proteins/proteome.html ] --- # 5. Proteome Analysis .center[![](https://www.tankonyvtar.hu/en/tartalom/tamop412A/2011-0073_introduction_practical_biochemistry/images/24a53a7a.png)] .footnote[ [1] [Introduction to Practical Biochemistry ](https://www.tankonyvtar.hu/en/tartalom/tamop412A/2011-0073_introduction_practical_biochemistry/ch11s03.html)  ] --- # 5. Proteome Analysis .center[![](./2019-05-15-Introduction_to_Bioinformatics_files/figure/foldit.png)] --- # Related knowledge 1. Biology: **Cell Biology**, **Molecular Biology**, Biochemistry, Developmental Biology, **Genomics**, **Genetics**, etc. -- 2. Programming: **R**, Perl/**Python**, C/C++, etc. -- 3. Statistics: **Hypothesis test**, **Interval estimation**, **Significance**, **Regression**, etc.  --- # Bioinformatics in Action - High performance computing .center[![](http://help.mamut.com/uk/mhelp/rtm/Resources/Images/CLIENT%20FINAL.bmp)] .footnote[ [1] [Multiple users concept](http://help.mamut.com/uk/mhelp/rtm/administrator/installation/server/multi_user_concept.htm) ] --- background-image: url(https://upload.wikimedia.org/wikipedia/commons/thumb/1/1b/R_logo.svg/310px-R_logo.svg.png) background-size: 100px background-position: 90% 8% .left-column[ ## What is R? ] .right-column[

 **R** is a language and environment for statistical computing and graphics. Designed by: **R**oss Ihaka, **R**obert Gentleman. ```r x <- 1:6 # Create vector. y <- x^2 # Create vector by formula. plot(x,y,type = "b") ``` ![](2019-05-15-Introduction_to_Bioinformatics_files/figure-html/unnamed-chunk-1-1.svg) ] --- .left-column[ ## What is R? ## What is RStudio? ] .right-column[ ![](./2019-05-15-Introduction_to_Bioinformatics_files/figure/RStudio.png) ![](https://upload.wikimedia.org/wikipedia/commons/thumb/4/4d/Rstudio.png/640px-Rstudio.png) ] --- # RStudio Server with Terminal ![](./2019-05-15-Introduction_to_Bioinformatics_files/figure/RStudio_Terminal.png) -- - Login to <IP_ADDRESS>:8787 --- # Syllabus - Basic knowledge of Linux - NGS Data analysis (Genome data) - NGS analysis online tools and Database # Resource [1] [Bioinformatics (For undergraduates)](http://xue.biocuckoo.org/course.html) (in Chinese) .footnote[ * All pictures without footnote are getting from Wikipedia or browser snapshots. ] --- class: center, middle # Thanks! Slides created via the R package [**xaringan**](https://github.com/yihui/xaringan). The chakra comes from [remark.js](https://remarkjs.com), [**knitr**](http://yihui.name/knitr), and [R Markdown](https://rmarkdown.rstudio.com).


Different people need annual reports: investors, lenders, managers, contributors, managers and employees. Their form vary from country to country with the two main categories being the Angle-American (giving a ‘fair’ view) and the Franco-German model (precedence of creditors’ interests; profits entered when realized, losses/expenses immediately). Concerns about the accuracy of accounting statements have among others pushed new legislature like the Sarbanes-Oxley Act (passed July 2002), requiring CEOs and CFOs in the US to certify financial statements. It also addresses:
- non-audit services of auditors (We’ll say the report is great or we loose the 100 million consulting contract)
- authority increase of audit committee
- less loans to officers and directors
- faster disclosure
<!– more –>
Contents of the annual report

Compulsory section:
- the directors’ report (linked to corporate governance)
- the auditors’ report (appropriate accounting consistently applied and adequately disclosed, fair view, accounts prepared in accordance to relevant legilastion; Franco-German model often does not require auditing as reports "audited" by the tax authority)
- the income statement (summary of productivity)
- the balance sheet (summarises positions at the end of the financial year)
- the cashflow statement (summary of sources of cash during year)
- notes to the accounts

Voluntary sections
- the chairman’s statement
- the chief executive’s review
- the operating and financial review (OFR)
- the environmental report

Analysts put things into special spread sheets like the OUFS to look at several years of data in a standard way. Before you start, clarify your objective to analyse the right data, profit before tax if you lend money for example.

When you use ratios, consider the economy at the time and the industrial environment. There are four phases for ratios:
- assessing operating efficiency
- assessing financial structure
- observe consequences of foregoing in profitability
- evaluate cash flows

Three questions need to be asked:
- Change in ratios, why
- Compare ratios to similar companies
- Do the ratios make sense

Consolidated group accounts

100% of shares: subsidiary wholly-owned
20-50%: related or associated company
Analysis in Context

You need something to structure the segment of the market you are looking at. SWOT, STEEP and Porter’s five forces are models to use here. You have three important numbers here:

sales show if their market share increases

return on capital if there is a competitive advantage

net operating margins show the competitive pressure

How you define the market will be critical to the evaluation, as always with STEEP, Porter’s five forces of SWOT.

Operating Efficiency

Here the ratios come in. You are looking at the cycle of production, from Cash to (supply) raw materials, (production) work in progress, (demand) finished goods, (collection) trade receivables and back to cash.

supply phase

(Remember, assets included in the balance sheet might not be those that are used in the income statement)

Raw material days = Raw material / (Cost of goods sold / 365)

Very useful if you look at different components of inventory seperately

Trade creditor days = Trade creditors x 365 / Cost of goods sold

This is about the payment terms that suppliers are granting.

Production phase

Work in progress days = Work in progress x 365 / Cost of goods sold

The small the more efficiently the raw materials are progressed.

Net property, plant and equipment turnover = Sales / Property, plant, equipment

Remember: Sales are in relation to current market values but assets might be included at a lower value as they are written off.

Plant life

Expected life = historic cost of plant and equipment / depreciation charge for year

Life used = Accumulated depreciation of plant and equipment / depreciation charge for year

Life remaining = Net book value of plant and equipment / depreciation charge for year

Remember: if fully written off the balance sheet does not show it, but it might still be used in the production cycle

Demand and collection phase

finished goods days = finished goods x 365 / cost of goods sold

If this rises, some sales that were expected might not have materialised or there is an upcoming promotion or ad campaign for which the company stocks up.

Receivable days = receivables x 365 / Sales

Net operating assets

Part of the funding comes from the cycle of production and via supplier’s credit terms, which is very attractive. Minimum inventory holds down costs, then collect money quickly and pay suppliers late.

Net operating assets = accounts receivable + inventory + prepaid expenses - trade creditors - accrued expenses

Service organisations

also have a cycle of production in relation to Collection of cash, supply of raw materials and (demand) trade receivables. This means that these ratios are important here too. You might also want to look at things like occupancy rates for hotels for example.

Financial Structure

The main point here are liquidity (short-term) and solvency (long-term) ratios.

Management needs to make sure that there are good sources of finance, taking into account maturity, flexibility and stability while minimising costs. They need to keep a balance between dept and equity, where dept has certain clear rules to it like repayment times, first payment in case of liquidation, … and equity offers a higher return or rather has to due to the great risk it carriers for the providers of this finance.

Equity is therefore more expensive but it allows for more flexibility. Managers should match economic lives of assets with maturity of financing.

Liquidity

Current ratio = Current assets / current liabilities

This can be smaller than 1 in case the company is a going concern, meaning it can finance the liabilities through trading revenues.

Quick (acid test) ratio = Current assets - Inventory / Current liabilities

Uncertainty with the inventory is addressed here. It might not be worth anything and the liabilities must still be paid for.

working capital = current assets - current liabilities

again, looking at liquidity here. If the company is very trustworthy this can be a high minus though.

Solvency

The riskier the business, the greater the dependence on equity rather than dept. Shareholders can be thought as as an equity cushion. They provide money that will not have to paid back in liquidation. The liquidation process of assets must only stay above the book value of the assets minus the invested amount for all senior creditors to be paid. A company is worth $100m in total with $30m in equity. In liquidation the assets need to bring $70m not 100 for all senior creditors to be paid.

gearing = short- and long-term dept x 100 / equity

the more uncertainty about cash generated, the lowe this number should be, meaning the mor the company should rely on equity.

dept/equity ratio = short- and long-term dept / (short- and long-term dept + shareholders’ equity)

net gearing % = (short- and long-term dept - cash and marketable securities x 100) / equity

This is done as marketable securities and cash are not really important in the cycle of production and can repay dept at once

leverage = long-term liabilities / equity

This presents a broader view beyond dept

leverage (tangible) = total liabilities / (equity - intangible assets)

you might also want to include contigent liabilities here, that just might occur in the future.

Capital employed = short-term dept + long-term dept + long-term liabilities + long-term provisions + shareholders’ equity

When looking at dept you might also look at the average dept over several years to see if there is some seasonal pattern in interest expenses (Interest expense / average dept).

Profitability

Here we look at the income statment and profitability ratios. The income statments looks at the activities of a company on an accrual basis, meaing that revenues and expenses might appear in the income statement before the cash is collected.

Sales
- cost of goods sold
- selling and distribution expenses
- administration expenses

= Net operating profit
- interest expense
+ interest income
+ equity income
+ dividend income

= Profit after financial items
+/- sundry income/expense
+/- gain/loss on sale of assets
+/- gain/loss on sale of investment
+/- exceptional income/expense

= Pre-tax profit
- Tax

= Net profit after tax
+/- Extraordinary income/expense
- minority interests
- dividends

In the Anglo-American the fair view is employed and the Franco-German model takes a very prudent view, including revenues only when they are realised and expenses as soon as anticipated. In the long run, the result in the same, but the short term my vary.

net operating profit = net operating profit / sales x 100

We can also look at:

cost of goods sold / sales x 100

and:

selling and distribution expenses / sales x 100

interest cover (times interest earned) = net operating profit / interest expense

We also have some other relations

pre-tax profit / sales x 100

effective tax rate = taxes / pre-tax profit x 100

Very low tax rate should make you wonder how they come about. In the Anglo-American model the published account are different from the tax accounts.

net profit after tax / sales x 100

Tells us what of sales is left over to give to shareholders. For dividends, we look at:

payout ratio = dividends / net profit after tax x 100

One should also be aware of core (resulting in NOP) and non-core earnings.

Market-Related Ratios

earnings per share = net profit after tax / average numbers of shares issued

price / earnings ratio = markte price of share / earnings per share

You can also look at the prospective ratio by taking expected earnings per share into account instead.

Book value shows the historic cost or current market value of assets.

price/book = market share price / shareholders’ equity per share

price/book = market capitalisation / sharehoders’ equity

You can also take a look at other indicators sometimes called output-related performance indicators (ORPIs) but these are complex to define in a meaningful way, can deliver very high information on a companies performance though.

Inappropriate ORPIs can lead to (Peter Smith, 1993)
- Tunnel vision
- Sub-optimisation
- Myopia
- Convergence
- Ossification
- Gaming
- Misrepresentation

Ratio Analysis

This part covers core ratios, of which two kinds exist.

Dupont Pyramid

Return on Capital Employes = Asset utilisation x Return on sales
Net operating profit / Capital employed = Sales / capital employe x Net operating profit / Sales

This does not consider the financial performance of the company, and for this we need to look at the

Core Ratios

Return on equity = Operating efficiency x Financial structure x Profitability
Return on equity = Asset turnover x Asset leverage x Return on sales
NPAT / Equity = Sales / Total assets x Total assets / Equity x NPAT / Sales

Haveing looked at these, you can continue by looking into more detail, but these give a good overview. To interpret the core ratios, you need to keep the sector and the economy in mind.

The level of asset turnover is related to the amount of technology used in the sector. The asset leverage should be inversely related to the volatility of cash flows, as said before. Profitability needs to be looked at with the help of Porter’s five forces model.


Bun Marketplace
View Buns from the Baker marketplace, so that you can install them into your resource


{% extends "base.html" %} {% load staticfiles %} {% load crispy_forms_tags %} {% block title %}{{ block.super }}About{% endblock %} {% block navbar-left %} {% include "_navbar.html" with active_link="about" %} {% endblock %} {% block container %}
Offering world class services and exceeding customer expectation
The Wonderful People Behind the Business
Mrs. Elizabeth Ndegwa
Elizabeth is the face of the business. She is articulate, focused and visionary.
David Ndegwa
David provides support on the technical front, developing tools and applications for streamlining the running of the business.


hello Charlie, not incredibly sure what to input into the text of this particular project, but I hope this at the least demonstrates that I was paying attention to the assignment
this is random work from class on Wednesday


The ngx-viewed for angular library allows you to add social functionality to your app.
In the era of social networks, a huge flow of information and applications with infinite scrolling, it is important to track how your users view information in your application.
It can be posts of your users, comments, news, advertisements or even photos as in instagram.
You've been looking at this text for {{blocks[0].tick?.time/1000}} sec.
You watched this text for more than {{blocks[0].tick?.time/1000}} sec.
Ngx-viewed library allows you to "spy" on your users.
If the border of this block is green, this means that the application recorded that you watched this block for more than 3 seconds.
You can specify how much block area should be displayed on the screen to the library thought that a user is watching this block.
If at least 1 pixel is on the screen, this means the user sees this block.
If at least 1 pixel is off the screen, this means the user does not see this block.
Wait, wait... What about the cases when the block does not fit on the screen?
.
.
.
It's not a problem. When the block is larger than the screen, ngx-viewed library will work when the block occupies the entire screen.
.
.
.
And if content in block with scroll?
Post 1
Post 2
Post 3
A very
long
post
that
is
longer
than
the parent.


val tatums: List<TimeInterval>
A tatum represents the lowest regular pulse train that a listener intuitively infers from the timing of perceived musical events (segments).
tatums
- A tatum represents the lowest regular pulse train that a listener intuitively infers from the timing
of perceived musical events (segments).


LAVONNE WHELCHEL
Democrat
Retired since 2013. Prior to that, employed by Wells Fargo Bank for 30 years. Resume attached.
Regis University, Bachelor of Science, 1995
80227
Not politically active prior to 2016. From 2016 on, I have volunteered for 2 Lakewood City Council Members (Dana Guitwien and Shakti) and donated to both of them. I have also volunteered, and donated, to a variety of other Democratic candidates both for State Legislative and Federal Congressional/Senate positions. Both within my state of Colorado and also a few (Democrats) outside my state.
Southern Gables Neighborhood Sustainability Committee, Neighborhood Watch Coordinator, Jefferson County Democrats, Indivisible Front Range Resistance, Indivisible CO-7, Colorado Move to Amend, Town Hall Project,
I have testified at the State Capitol on several occasions to support and/or against a variety of topics, to include: sustainability, gun control reforms, oil & gas setbacks, holding Colorado Government accountable, Affordable Housing, Full Day kindergarten, etc. Precinct Coordinator and Precinct Captain for Jeffco Dems. In this position, I have recruited fellow PCP's and others to assist with election related activities (and participated myself) in Phone Banking, Text Banking, Lit Dropping, Door Knocking, etc. I have also acted as the Chair for my Precinct Caucus for the past 2 Democratic Caucuses; as well as helping to plan the Caucus event itself.
I am committed to seeing Colorado's redistricting process be the most fair, and transparent, process possible. My hope is that Colorado will be used as a model of fairness for the nation. I believe that democracy (small d) can only survive if the process is fair and the people believe in its fairness and adhere to the results - even if they are unhappy with the results.
I do believe that everyone brings wisdom to an interaction and that the more points of view presented, discussed and valued, the better the ultimate solution. I have always been able to see both sides of an issue and am a strong advocate for all voices being heard; even the ones I may disagree with. I have a deep ability to empathize and understand others' points of view. I am always open to admitting that I could be wrong and willing to change my opinion, if the facts presented are logical.
My 30 year banking background provided me many opportunities to analyze, both numerically and socially, various problems and solutions to many issues. I understand that any issue contains both a "number" component and a "people" component; and I am always dedicated to resolving both. If a solution only addresses one of these, it will ultimately fail.
Female


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--- layout: post title: The Old Man And His God tags: - Book Review status: publish type: post published: true meta: al2fb_facebook_link_id: '218440691518395_242759209086543' al2fb_facebook_link_time: '2011-07-12T13:16:02+00:00' al2fb_facebook_link_picture: post=http://divyayadav.files.wordpress.com/2010/05/the-old-man-and-his-god.jpg?w=225 _edit_last: '2' _graphene_slider_img: global _graphene_slider_imgurl: '' _graphene_show_addthis: global _yoast_wpseo_linkdex: '20' _wp_old_slug: inspiration _yoast_wpseo_focuskw: The Old Man And His God _yoast_wpseo_title: The Old Man And His God - Miss Enchanted _yoast_wpseo_metadesc: The Old Man And His God _yoast_wpseo_metakeywords: '' _yoast_wpseo_meta-robots-noindex: '0' _yoast_wpseo_meta-robots-nofollow: '0' _yoast_wpseo_meta-robots-adv: none _yoast_wpseo_sitemap-include: ! '-' _yoast_wpseo_sitemap-prio: ! '-' _yoast_wpseo_canonical: '' _yoast_wpseo_redirect: '' _thumbnail_id: '7047' ---
Yesterday I picked up The Old Man And His God by Mrs. Sudha Murthy. She has brought together small stories and events that have inspired her throughout her journey.
Book is a very light read, but not that light to your mind. Some of the stories will leave you thinking of quite sometime. Its not just a read but something to take back. Its a collection of short stories, each story shall take 15-20 min to finish. So its ideal for people who don't have much reading time. As a blogger I was inspired from The Old Man And His God that I decided to start this blog, to keep myself a record of events that I like talking about. I shall come back again to this post in my old age and remember the fondness with which the post was written. Have you read The Old Man And His God ?


application.py |
|
|---|---|
|
Primary WSGI application and framework entry point. |
|
Imports |
from __future__ import unicode_literals
import logging
import logging.config
from inspect import isroutine, isfunction, ismethod, getcallargs
from webob.exc import HTTPException, HTTPNotFound
from marrow.package.loader import load
from .context import Context
from .dispatch import WebDispatchers
from .extension import WebExtensions
from .view import WebViews
from ..ext.base import BaseExtension
if __debug__:
from .util import safe_name
|
Module Globals |
|
|
A standard Python logger object. |
log = __import__('logging').getLogger(__name__)
|
WSGI Application |
|
|
The WebCore WSGI application. This glues together a few components:
|
class Application(object):
__slots__ = (
'config', # Application configuration.
'feature', # Feature tag announcement; populated by the `provides` of active extensions.
'__context', # Application context instance.
'RequestContext', # Per-request context class.
'__call__', # WSGI request handler. Dynamically assigned.
)
|
|
Construct the initial ApplicationContext, populate, and prepare the WSGI stack. No actions other than configuration should happen during construction. Current configuration is limited to three arguments:
|
def __init__(self, root, **config):
self.config = self._configure(config) # Prepare the configuration.
if __debug__:
log.debug("Preparing WebCore application.")
if isfunction(root): # We need to armour against this turning into a bound method of the context.
root = staticmethod(root)
|
|
This construts a basic |
context = self.__context = Context(app=self, root=root)._promote('ApplicationContext')
|
|
These can't really be deferred to extensions themselves, for fairly obvious chicken/egg reasons. |
exts = context.extension = WebExtensions(context) # Load extension registry and prepare callbacks.
context.dispatch = WebDispatchers(context) # Load dispatch registry.
context.view = WebViews(context) # Load the view registry.
|
|
Execute extension startup callbacks; this is the appropriate time to attach descriptors to the context. |
for ext in exts.signal.start: ext(context)
|
|
At this point the context should have been populated with any descriptor protocol additions. Promote the
|
self.RequestContext = context._promote('RequestContext', instantiate=False)
|
|
Handle WSGI middleware wrapping by extensions and point our call at the result. |
app = self.application
for ext in exts.signal.middleware: app = ext(context, app)
self.__call__ = app
if __debug__: # Mostly useful for timing calculations.
log.debug("WebCore application prepared.")
|
|
Prepare the incoming configuration and ensure certain expected values are present. For example, this ensures BaseExtension is included in the extension list, and populates the logging config. |
def _configure(self, config):
config = config or dict()
|
|
We really need this to be there. |
if 'extensions' not in config: config['extensions'] = list()
|
|
Always make sure the BaseExtension is present since request/response objects are handy. |
config['extensions'].insert(0, BaseExtension())
|
|
Tests are skipped on these as we have no particular need to test Python's own logging mechanism. |
level = config.get('logging', {}).get('level', None)
if level: # pragma: no cover
logging.basicConfig(level=getattr(logging, level.upper()))
elif 'logging' in config: # pragma: no cover
logging.config.dictConfig(config['logging'])
return config
|
|
This is impractical to test due to the blocking nature of starting a web server interface. Individual adapters are hand-tested for basic operation prior to release. Initiate a web server service to serve this application. You can always use the Application instance as a bare WSGI application, of course. This method is provided as a convienence. Pass in the name of the service you wish to use, and any additional configuration options appropriate for that
service. Almost all services accept |
def serve(self, service='auto', **options): # pragma: no cover
service = load(service, 'web.server') # We don't bother with a full registry for these one-time lookups.
try:
service(self, **options)
except KeyboardInterrupt: # We catch this as SIG_TERM or ^C are basically the only ways to stop most servers.
pass
|
|
Notify extensions that the service has returned and we are exiting. |
for ext in self.__context.extension.signal.stop: ext(self.__context)
|
|
Extract usable args and kwargs from the given request object. Candidate for promotion to an extension callback. Two approaches come to mind:
We currently go for the latter without merging or PHP-ness. TODO: Investigate WebOb's request.urlvars and request.urlargs: https://github.com/Pylons/webob/blob/master/webob/request.py#L566-L646 |
def _extract_arguments(self, request):
args = list(request.remainder)
if args and args[0] == '': del args[0] # Trim the result of a leading `/`.
|
def process_kwargs(src):
kwargs = dict()
for name_, value in src.items():
if name_ in kwargs and not isinstance(kwargs[name_], list):
kwargs[name_] = [kwargs[name_], value]
elif name_ in kwargs:
kwargs[name_].append(value)
else:
kwargs[name_] = value
return kwargs
kwargs = process_kwargs(request.GET)
kwargs.update(process_kwargs(request.POST))
return args, kwargs
if __debug__: # This method only exists in development. Really; thus the use of name mangling.
|
|
def __validate_arguments(self, context, endpoint, bound, args, kwargs):
try:
if callable(endpoint) and not isroutine(endpoint):
|
|
|
Callable Instance |
getcallargs(endpoint.__call__, *args, **kwargs)
elif bound:
|
|
Instance Method |
getcallargs(endpoint, *args, **kwargs)
else:
|
|
Unbound Method or Function |
getcallargs(endpoint, context, *args, **kwargs)
except TypeError as e:
|
|
If the argument specification doesn't match, the handler can't process this request. This is one policy. Another possibility is more computationally expensive and would pass only valid arguments, silently dropping invalid ones. This can be implemented as a mutate handler. |
log.error(str(e), extra=dict(
request = id(context),
endpoint = safe_name(endpoint),
endpoint_args = args,
endpoint_kw = kwargs,
))
return HTTPNotFound("Incorrect endpoint arguments: " + str(e))
|
def _execute_endpoint(self, context, endpoint, signals):
if not callable(endpoint):
|
|
|
Endpoints don't have to be functions. They can instead point to what a function would return for view lookup. |
if __debug__:
log.debug("Static endpoint located.", extra=dict(
request = id(context),
endpoint = repr(endpoint),
))
|
|
Use the result directly, as if it were the result of calling a function or method. |
return endpoint
|
|
Our endpoint API states that endpoints recieve as positional parameters all remaining path elements, and as keyword arguments a combination of GET and POST variables with POST taking precedence. |
args, kwargs = self._extract_arguments(context.request)
|
|
Instance methods were handed the context at class construction time via dispatch.
The |
bound = not isroutine(endpoint) or (ismethod(endpoint) and getattr(endpoint, '__self__', None) is not None)
|
|
Allow argument transformation; args and kwargs can be manipulated inline. |
for ext in signals.mutate: ext(context, endpoint, args, kwargs)
if __debug__:
log.debug("Callable endpoint located.", extra=dict(
request = id(context),
endpoint = safe_name(endpoint),
endpoint_args = args,
endpoint_kw = kwargs
))
|
|
Make sure the handler can actually accept these arguments when running in development mode. Passing invalid arguments would 500 Internal Server Error on us due to the TypeError exception bubbling up. |
result = self.__validate_arguments(context, endpoint, bound, args, kwargs)
if result: # Bail if validation returned any truthy value.
return result
try:
|
|
Actually call the endpoint. |
if bound:
result = endpoint(*args, **kwargs)
else:
result = endpoint(context, *args, **kwargs)
except HTTPException as e:
result = e
|
|
Execute return value transformation callbacks. |
for ext in signals.transform: result = ext(context, endpoint, result)
return result
|
|
Process a single WSGI request/response cycle. This is the WSGI handler for WebCore. Depending on the presence of extensions providing WSGI middleware,
the Most apps won't utilize middleware, the extension interface is preferred for most operations in WebCore. They allow for code injection at various intermediary steps in the processing of a request and response. |
def application(self, environ, start_response):
context = environ['wc.context'] = self.RequestContext(environ=environ)
signals = context.extension.signal
|
|
Announce the start of a request cycle. This executes |
for ext in signals.pre: ext(context)
|
|
Identify the endpoint for this request. |
is_endpoint, handler = context.dispatch(context, context.root, context.environ['PATH_INFO'])
|
|
If no endpoint could be resolved, that's a 404. |
if not is_endpoint:
|
|
We can't just set the handler to the exception class or instance, because both are callable. An endpoint that returns a 404 Not Found error on dispatch failure. |
def handler(_ctx, *args, **kw): # Yes, this works. We're just assigning this code obj. to a label. :3
return HTTPNotFound("Dispatch failed." if __debug__ else None) # Not an exceptional event, so don't raise.
result = self._execute_endpoint(context, handler, signals) # Process the endpoint.
if __debug__:
log.debug("Result prepared, identifying view handler.", extra=dict(
request = id(context),
result = repr(result)
))
|
|
Identify a view capable of handling this result. |
for view in context.view(result):
if view(context, result): break
else:
|
|
We've run off the bottom of the list of possible views. |
raise TypeError("No view could be found to handle: " + repr(type(result)))
if __debug__:
log.debug("View identified, populating response.", extra=dict(
request = id(context),
view = repr(view),
))
for ext in signals.after: ext(context)
return context.response.conditional_response_app(environ, start_response)
|


UEW defiles court order, holds Pro-VC election
It has emerged that the leadership of University of Education Winneba (UEW), on Thursday, November 21, held an election to elect a Pro-Vice-Chancellor (VC) despite a Winneba High Court injunction.
One Dr Frimpong Kaakyire Duku, according to some writ of summons intercepted by GhanaWeb filed an application for an injunction following his appeal over the decision of the court on November 18, 2019, on grounds that the proper jurisdiction of the courts was not invoked.
An earlier notice of the election of the Pro VC was postponed indefinitely due to a suit filed by attorneys for Dr Duku on June 14, 2019.
On November 18, 2019, the court ruled in favour of the University for it to hold the Pro VC elections but unsatisfied, Dr Duku sought to place another injunction on the election, which will have the effect of restraining the UEW from continuing with the election.
But authorities of UEW on Thursday proceeded to hold the election and elected a new Pro VC at the University’s campuses across the country.
GhanaWeb sources have it that the injunction was served on the University on Wednesday, November 20, 2019, through, Librarian Viscount Buer, who is one of the principal officers of the university.


If you need, you can import a different rudehash.json
file here:
Whenever you change the configuration, validation errors will be shown here, if any. Please note that this only checks for syntax errors, the specified options will also be checked for compatibility when you start RudeHash.


We're writing to let you know that {{ from_profile_ctx.profile.fb_name }} just paired with you on VoteSwap.
They're a {{ from_profile_ctx.profile.preferred_candidate }} voter in {{from_profile_ctx.profile.state }}, a {{ from_profile_ctx.state_type }}.
You're a good match because you want to vote for {{ to_profile_ctx.profile.preferred_candidate }} in {{ to_profile_ctx.profile.state }}, a {{ to_profile_ctx.state_type }}.
{% if to_profile_ctx.kingmaker %}Voting for {{ to_profile_ctx.profile.preferred_candidate }} in {{ to_profile_ctx.profile.state }} is extremely dangerous. You'll take votes away from Hillary Clinton and let Trump win the presidency.
{% endif %}Trump is an unstable, racist, xenophobic, little dictator that can't be allowed to win.
Go to https://voteswap.us{% url "swap" %} to confirm or reject the swap.


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The lambda.h
header includes all of the headers in the chaos/preprocessor/lambda
subdirectory.
Usage
#include
Headers
© Copyright Paul Mensonides 2003-2005
Distributed under the Boost Software License, Version 1.0.
See http://chaos-pp.sourceforge.net for the most recent version of this document.