Learning Advisory cum Program Consultant: Oct 2019 until now
Work Experience:
PROGRAM CONSULTING:
- Manage a portfolio of 50–100 contacts (alumni, clients, and prospects) and develop relationships to provide personalized education solutions that achieve their short- and long-term goals. Consistently maintain and optimize communication with a portfolio of contacts through various channels including in-person, phone calls, emails, and other online platforms.
- Acquire new clients through marketing campaigns, personal networks, telesales, client referrals, and strategic prospecting.
- Actively engage in continuous professional development to increase industry, product, and sales knowledge.
- Prepare market analyses and sales reports and support other academic, business development, and marketing activities.
- Greet and assist walk-in customers and handling questions about Everest Education and our offerings.
STUDENT SERVICES:
- Routine update parents about students’ performance.
- Handle students/parents’ requests/concerns and student complaints.
- Contact students to inform the cancellation/schedule change of classes.
- Follow up with teachers to understand students’ progress.
- Respond to / Receive students’ request/concern: defer, issue a statement of the study, attendance and complaints.
- Deal with students requests/concerns.
- Collaborate with Sales, Academic, Admin and Marketing departments to organize student activities.
- Support students struggling in class and teachers with students’ behavioral or academic issues.
RE-ENROLLMENT SALES:
- Communicate with parents to get confirmation of re-enrollment registration of existing students.
- Follow up with absent, delayed and deferred students.
- Follow up with parents to remind them to meet the tuition payment deadline.
- Coordinate with other departments to prepare for the new quarter.
CoderSchool
Student Service Executive: Jan 2019 - Aug 2019
Work Experience:
- Contact students to inform the cancellation/schedule change of classes.
- Follow up with teachers to understand students’ progress.
- Respond to / Receive students’ request/concern: defer, issue a statement of the study, attendance and complaints.
- Deal with students requests/concerns.
- Handle students’ requests/concerns and student complaints.
- Collaborate with Academic, Admin and Marketing departments to organize student activities.
- Support students struggling in class and teachers with students’ academic issues.
- Follow up with absent, delayed and deferred students.
- Coordinate with other departments to prepare for the new class.
- Get feedback from students as the schedule.
- According to Feedbacks to deduce Students happiness.
- Give solutions to improve and develop students happiness.
- Interview Instructors to make sure they had a good experience at CS.
- Who dropped the cohort, move them to the next cohort.
- Arrange the day for tutoring.
- To be an MC for Demo Day.
- Find and invite the Judges for Demo Day.
- Job Placement for the Student after the end of the Bootcamp.
- Choose and deal with the suppliers to buy merchandises.
Apollo English
Admin cum Materials: Apr 2017 - Aug 2018
Work Experience:
- Give general support to teachers and other staffs.
- Manage Tea lady and Maintenance man.
- Prepare/maintain equipment, and create certificates for all students in their last lesson.
- Stationery and other materials are enough for the center.
- Book inventory management.
- Check Student attendance every week.
- Manage office G & A budget.
- Contact suppliers to buy equipment.
- Support Marketing Team in all events at the center.
- Support the HR team to recruitment Teaching Assistant for the center.
- Support Customer Service Team to Greets and Meets the students and their parents.
- Training new staffs (EFL Team).
About Me
Hi guys, Thank you so much to go around my job journey. I hope you love it. I'm a person extremely motivated to constantly develop my skills and grow professionally. I am confident in working under pressure, balancing life and work well.


Copyright © 2009-2011 Marc Worrell Date: 2009-06-03
Behaviours: gen_server.
Authors: Marc Worrell (marc@worrell.nl).
| activate/2 | Activate a module. |
| active/1 | Return the list of active modules. |
| active/2 | Return whether a specific module is active. |
| active_dir/1 | Return the list of all active modules and their directories. |
| all/1 | Return the list of all modules in the database. |
| code_change/3 | Convert process state when code is changed. |
| deactivate/2 | Deactivate a module. |
| dependencies/1 | Return a module's dependencies as a tuple usable for z_toposort:sort/1. |
| dependency_sort/1 | Sort all modules on their dependencies (with sub sort the module's priority). |
| get_modules/1 | Return the list of all modules running. |
| get_modules_status/1 | Return the status of all running modules. |
| get_provided/1 | Return the list of all provided functionalities in running modules. |
| handle_call/3 | Return a list of all enabled modules managed by the z_supervisor. |
| handle_cast/2 | Sync enabled modules with loaded modules. |
| handle_info/2 | Handling all non call/cast messages. |
| init/1 | Initiates the server. |
| module_exists/1 | Check if the code of a module exists. |
| prio/1 | Return the priority of a module. |
| prio_sort/1 | Sort the results of a scan on module priority first, module name next. |
| restart/2 | Shortcut, restart a module by deactivating and reactivating the module. |
| scan/1 | Scan for a list of modules present in the site's module directories. |
| start_link/1 | Starts the module manager. |
| startable/2 | |
| terminate/2 | This function is called by a gen_server when it is about to terminate. |
| title/1 | Get the title of a module. |
| upgrade/1 | Reload the list of all modules, add processes if necessary. |
| whereis/2 | Return the pid of a running module. |
activate(Module, Context::#context{}) -> void()
Activate a module. The module is marked as active and started as a child of the module z_supervisor. The module manager can be checked later to see if the module started or not.
active(Context::#context{}) -> [atom()]
Return the list of active modules.
active(Module::atom(), Context::#context{}) -> [atom()]
Return whether a specific module is active.
active_dir(Context::#context{}) -> [{atom, Dir}]
Return the list of all active modules and their directories
all(Context::#context{}) -> [atom()]
Return the list of all modules in the database.
code_change(OldVsn, State, Extra) -> {ok, NewState}
Convert process state when code is changed
deactivate(Module, Context::#context{}) -> ok
Deactivate a module. The module is marked as deactivated and stopped when it was running.
dependencies(M) -> any()
Return a module's dependencies as a tuple usable for z_toposort:sort/1.
dependency_sort(Context) -> any()
Sort all modules on their dependencies (with sub sort the module's priority)
get_modules(Context) -> any()
Return the list of all modules running.
get_modules_status(Context) -> any()
Return the status of all running modules.
get_provided(Context) -> any()
Return the list of all provided functionalities in running modules.
handle_call(Message::Request, From, State) -> {reply, Reply, State} | {reply, Reply, State, Timeout} | {noreply, State} | {noreply, State, Timeout} | {stop, Reason, Reply, State} | {stop, Reason, State}
Return a list of all enabled modules managed by the z_supervisor
handle_cast(Message::Msg, State) -> {noreply, State} | {noreply, State, Timeout} | {stop, Reason, State}
Sync enabled modules with loaded modules
handle_info(Info, State) -> {noreply, State} | {noreply, State, Timeout} | {stop, Reason, State}
Handling all non call/cast messages
init(Args) -> {ok, State} | {ok, State, Timeout} | ignore | {stop, Reason}
Initiates the server.
module_exists(M) -> any()
Check if the code of a module exists. The database can hold module references to non-existing modules.
prio(Module) -> integer()
Return the priority of a module. Default priority is 500, lower is higher priority. Never crash on a missing module.
prio_sort(ModuleProps::proplist()) -> proplist()
Sort the results of a scan on module priority first, module name next. The list is made up of {module, Values} tuples
restart(Module, Context) -> any()
Shortcut, restart a module by deactivating and reactivating the module.
scan(Context::#context{}) -> [{atom(), dirname()}]
Scan for a list of modules present in the site's module directories. A module is always a directory, the name of the directory is the same as the name of the module.
start_link(SiteProps::proplist()) -> {ok, Pid} | ignore | {error, Error}
Starts the module manager
startable(M, Context) -> any()
terminate(Reason, State) -> void()
This function is called by a gen_server when it is about to terminate. It should be the opposite of Module:init/1 and do any necessary cleaning up. When it returns, the gen_server terminates with Reason. The return value is ignored.
title(M) -> any()
Get the title of a module.
upgrade(Context::#context{}) -> ok
Reload the list of all modules, add processes if necessary.
whereis(Module, Context) -> any()
Return the pid of a running module
Generated by EDoc, Apr 11 2012, 20:41:27.


Defines the behavior of the Save 'word' to dictionary intention action invoked on a
mistyped word:
- If the checkbox is selected, IntelliJ IDEA lets you select a single dictionary from the list. The selected
dictionary is used for saving all mistyped words.
- If the checkbox is cleared, IntelliJ IDEA lets you choose a dictionary in the code editor on the fly,
individually for each a mistyped word.


Regular workshops catalyse learning and knowledge sharing.
Advocate and advise on institutional changes to improve scientific computing.
We develop the tools needed by CAMH researchers.
Visit us with your questions, CS 163 every Tuesday.


Welcome, {{ pc.firstname }}! If you want to add/edit info or change your avatar, click here.
1. Red food coloring comes from: flowers hair bugs
2. Which of the following fruits comes from an herb?: strawberries bananas kiwis
Check out more food trivia here.
Learn more fun facts about food here.
Recipe name: {{recipe.name}}
Description: {{recipe.description}}
Instructions: {{recipe.instructions}}
Cuisine: {{recipe.cuisine}}
Image:
Click on recipe card to close


| Home | Libraries | People | FAQ | More |
Uses basic_dna_string
with most efficient C++ type.
dna_string
is a container
class like std::string
that efficiently stores raw DNA
sequences without markup.
The DNA bases A, C, G, T are represented using two bits-per-base and are accessed 64-bits at a time or more depending on architecture.
Having a packed representation makes it possible to use bit-twiddling tricks to perform linear searches faster and reduce level 1 and 2 cache loads.
void simple_substring_search() { using namespace boost::genetics; // Make a DNA string. Only A, C, G or T allowed. dna_string str("ACAGTACGTAGGATACAGGTACA"); // Search the string for a substring. dna_string GATACA = "GATACA"; size_t gataca_pos = str.find(GATACA); if (gataca_pos != dna_string::npos) { std::cout << "'GATACA' found at location " << gataca_pos << "\n"; } } // void simple_substring_search()


Project: New Fire Line
Type of Pipe: 8" SDR11 HDPE
length of Pipe: 1,560 Feet
Location: Mountain View, CA.
Contractor: Rodan Builders & R&B Fusion
Santa Clara County passed Measure G in 2012. Measure G will generate up to $198 million for the Mountain View Whisman School District. The funds will help schools upgrade, repair or expand the campuses to provide students and staff with safe, efficient and modern facilities.
One recipient of these funds is Landels Elementary School, which is adding a new sports building to its campus. Construction of the new building started over the summer break and it needed a new fire line installed before school begins in August. To be able to have the new line installed on time, it was decided that Horizontal Directional Drilling (HDD) would be fastest and least intrusive. The new line totals at 1,560’ of 8” SDR11 HDPE split into six runs. Each run had a pull-head fused to one end so it could be pulled between the insertion and connection pits.
By installing the new line in this manner no trenches had to be dug resulting in less damage to the campus. A total of six pits had to be dug for pulling in each run. The runs were fused together using a Tega Electrofusion Coupling to complete the fire line. Using Horizontal Directional Drilling rather than the traditional open trench method resulted in both time and money savings.
Download the PDF here.


{include file="public/css" /}
{include file="public/header1" /} {include file="public/header2" /}
{include file="public/menu_r" /}
{include file="public/que_menu" /}
{$art.title}
{$art.content}
{include file="public/footer1" /} {include file="public/footer2" /} {include file="public/js" /} {include file="public/js_1" /}


| SELECT _____ |
column name(s) seperated by comma |
| FROM _____ |
table origin name |
| ORDER BY _____ (optional)-DESC |
add DESC to list from highest down |
| WHERE _____ [ < , > , =, < > ] |
restrictive CLAUSE using comparison operators |
| AND _____ OR _____ |
additional comparison operators |
| INSERT INTO _____ (_____, _____, _____) |
target table name (column names) |
| VALUES (_____, _____, _____) |
you can skip paramater assignment if data will fill all columns |
| UPDATE _____ |
target table |
| SET _____ = _____, _____=_____ |
used for variable assignment, optional secondary assignments |
| (WHERE)_____=_____ OR _____=_____ |
conditional statements |
| DELETE FROM _____ WHERE _____=_____ |
source table with conditional statement |
|
|
| CREATE DATABASE _____ |
database name |
| DROP DATABASE _____ |
database name |
| CREATE TABLE |
table name |
| DROP TABLE _____ |
table name |
| ALTER TABLE _____ |
table name |
| ADD COLUMN _____ |
column name |
| DROP COLUMN _____ |
column name |


Your doctor recommends how long you shouldn’t work for. This is sometimes called being “signed off”. If you’re still unwell after this time you need to go back and see them again.
If you don’t want us to confirm with your doctor that you’re still unwell you’ll need to send a copy of your sick note in the post.


#
You can use $user$ to display the username of the user You can use $server$ to display the name of the server
$user$
$server$


Style Guide
Colors
-
Primary: #652914
Hightlight: #B25535
-
Secondary: #B25535
Highlight: #fe8c65
-
Tertiary: #202b19
Highlight: #547042
Typography
-
- Headings
- Contrail One, Open Sans 700
- Paragraph
- Lora
- Buttons
- Open Sans 400
- Link Text
-
Link, Visited, Hover, Active
- Strong Text
- Strong text; used to indicate importance.
- Emphasis Text
- Emphasized text; used to create emphasis.
- Paragraph Text
-
Base font size: 16px
Line height: 1.25em
Fierasfer, lenok collared dogfish; sixgill ray yellowtail amberjack common carp, gopher rockfish murray cod escolar livebearer squirrelfish. Spanish mackerel bent-tooth Black sea bass southern Dolly Varden gurnard sillago duckbill armored gurnard bristlenose catfish, "crocodile shark roughy scissor-tail rasbora."
-
- Heading 1
Heading 1
- Heading 2
Heading 2
- Heading 3
Heading 3
- Heading 4
Heading 4
- Heading 5
Heading 5
Site Header
This is a highlightThey're cookies made into the shape of a salmon, and actually made with salmon that is the ideal match for a steaming cup of coffee on a gray Seattle morning.
Lists
-
Unordered List
- This is an unordered list item
- This is another list item
- This is a sublist item
- This is another sublist item
- This is a third list item
-
Ordered List
- This is an unordered list item
- This is another list item
- This is a sublist item
- This is another sublist item
- This is a third list item
Tables and Forms
-
Tables
Table Header Table Header white row 123 456 grey row 123 456 white row 456 789 footer row 123 456 -
Forms
-
Addresses
Address Title
Address Name
1234 Street Avenue
City ST 01234
Tel:<PHONE_NUMBER>
-
Messages
General Message
Alert Message
-


| Year | Title | Authors |
|---|---|---|
| 2018 | Taskonomy: Disentangling Task Transfer Learning | Amir R. Zamir, Stanford University Alexander Sax, Stanford University William Shen, Stanford University Leonidas Guibas, Stanford University Jitendra Malik, University of California Berkeley Silvio Savarese, Stanford University |
| 2017 | Densely Connected Convolutional Networks | Zhuang Liu, Tsinghua University Gao Huang, Cornell University Laurens van der Maaten, Facebook AI Research Kilian Q. Weinberger, Cornell University |
| 2017 | Learning from Simulated and Unsupervised Images through Adversarial Training | Ashish Shrivastava, Apple Inc. Tomas Pfister, Apple Inc. Oncel Tuzel, Apple Inc. Josh Susskind, Apple Inc. Wenda Wang, Apple Inc. Russ Webb, Apple Inc. |
| 2016 | Deep Residual Learning for Image Recognition | Kaiming He, Microsoft Research Xiangyu Zhang, Microsoft Research Shaoqing Ren, Microsoft Research Jian Sun, Microsoft Research |
| 2015 | DynamicFusion: Reconstruction and Tracking of Non-rigid Scenes in Real-Time | Richard A. Newcombe, University of Washington Dieter Fox, University of Washington Steven M. Seitz, University of Washington |
| 2014 | What Camera Motion Reveals About Shape with Unknown BRDF | Manmohan Chandraker, NEC Labs America |
| 2013 | Fast, Accurate Detection of 100,000 Object Classes on a Single Machine | Thomas Dean, Google Mark A. Ruzon, Google Mark Segal, Google Jonathon Shlens, Google Sudheendra Vijayanarasimhan, Google Jay Yagnik, Google |
| 2012 | A Simple Prior-free Method for Non-Rigid Structure-from-Motion Factorization | Yuchao Dai, Northwestern Polytechnical University Hongdong Li, Australian National University Mingyi He, Northwestern Polytechnical University |
| 2011 | Real-time Human Pose Recognition in Parts from Single Depth Images | Jamie Shotton, Microsoft Research Andrew Fitzgibbon, Microsoft Research Mat Cook, Microsoft Research Toby Sharp, Microsoft Research Mark Finocchio, Microsoft Research Richard Moore, Microsoft Research Alex Kipman, Microsoft Research Andrew Blake, Microsoft Research |
| 2010 | Efficient Computation of Robust Low-Rank Matrix Approximations in the Presence of Missing Data using the L1 Norm | Anders Eriksson & Anton va den Hendel, University of Adelaide |
| 2009 | Single Image Haze Removal Using Dark Channel Prior | Kaiming He, The Chinese University of Hong Kong Jian Sun, Microsoft Research Xiaoou Tang, The Chinese University of Hong Kong |
| 2008 | Global Stereo Reconstruction under Second Order Smoothness Priors | Oliver Woodford, University of Oxford Ian Reid, Oxford Brookes University Philip Torr, University of Oxford Andrew Fitzgibbon, Microsoft Research |
| 2008 | Beyond Sliding Windows: Object Localization by Efficient Subwindow Search | Chistoph H. Lampert, Max Planck Institut Matthew B. Blaschko, Max Planck Institut Thomas Hodmann, Google |
| 2007 | Dynamic 3D Scene Analysis from a Moving Vehicle | Bastian Leibe, ETH Zurich Nico Cornelis, Katholieke Universiteit Leuven Kurt COrnelis, Katholieke Universiteit Leuven Luc Van Gool, ETH Zurich |
| 2006 | Putting Objects in Perspective | Derek Hoiem, Carnegie Mellon University Alexei Efros, Carnegie Mellon University Martial Hebert, Carnegie Mellon University |
| 2005 | Real-Time Non-Rigid Surface Detection | Julien Pilet, École Polytechnique Fédérale de Lausanne Vincent Lepetit, École Polytechnique Fédérale de Lausanne Pascal Fua, École Polytechnique Fédérale de Lausanne |
| 2004 | Programmable Imaging using a Digital Micromirror Array | Shree K. Nayar, Columbia University Vlad Branzoi, Columbia University Terry E. Boult, University of Colorado |
| 2003 | Object Class Recognition by Unsupervised Scale-Invariant Learning | Rob Fergus, University of Oxford Pietro Perona, California Institute of Technology Andrew Zisserman, University of Oxford |
| 2001 | Morphable 3D models from video | Matthew Brand, Mitsubishi Electric Research Laboratories |
| 2000 | Real-Time Tracking of Non-Rigid Objects using Mean Shift | Dorin Comaniciu, Siemens Corporate Research Visvanathan Ramesh, Siemens Corporate Research Peter Meer, Rutgers University |


Caution: this presentation of survey results is based completely on aggregated subjective experience. This survey was conducted for research and educational purposes only. It is strongly advised not to make decisions based on this data set. Before deciding to use any of these substances, consult a qualified medical professional and, if you suffer from any mental health problems, a mental health professional. The reported doses are likely to be inaccurate and it is highly recommended not to decide on the dose of a nootropic based on these data!
tl;dr: most substances seem to have no or only slight effects when rated subjectively. Most substances with substantial effects were already well-known for their effects, some of them are prescription drugs or pharmaceuticals.
Age. The mean participant age was 26.86 years (standard deviation = 9.68, range = 12–88).
Gender. From the total sample of 380 participants, 325 (91.07%) male and 29 (9.89%) female participants completed the survey. 19 did not answer and 7 chose the “other” option for gender. From those seven participants, three gave a valid response, while four answered “attack helicopter”. Those three participants were either non-binary, trans-male or trans woman. The male-to-female ratio can be considered rather extreme even for Reddit standards, which was roughly 70/30 in an analysis a couple of years ago and can be compared to extremely male-dominated subreddits like /r/baseball or /r/Libertarian.
Country of residence. The vast majority of participants were from English speaking countries. The table lists the top 10 most frequent responses. Other countries included Switzerland (5 participants), France (3), Italy (3), Netherlands (3), New Zealand (3), Portugal (3) and South Africa (3).
| Country | Frequency |
|---|---|
| USA | 185 |
| Not answered | 47 |
| Canada | 23 |
| UK | 22 |
| Australia | 14 |
| Germany | 8 |
| Belgium | 6 |
| Russia | 6 |
| Spain | 5 |
A brief personality inventory, the Mini-IPIP, was administered. It measures the Big Five personality traits:
Extraversion: This trait includes characteristics such as excitability, sociability, talkativeness, assertiveness and high amounts of emotional expressiveness. High levels of this trait are associated with more friends, higher life satisfaction and lower rates of mental disorders.
Agreeableness: This personality dimension includes attributes such as trust, altruism, kindness, affection, and other prosocial behaviors. This dimension is a good predictor of job choice: agreeable people tend to choose professions that involve caring and nurturing behavior and low competition, like nurse, psychotherapist, teacher, charity worker or doctor (excluding surgeons). People low in agreeableness tend to like competition and choose professions that require less compassion, like CEO, lawyer, journalist, police officer or chef. Agreeableness also predicts political views, as agreeable people tend to be liberals or leftists, while disagreeable persons are conservative or right-wingers.
Conscientiousness: Common features of this dimension include high levels of thoughtfulness, with good impulse control and goal-directed behaviors. Those high in conscientiousness tend to be organized and mindful of details. This trait predicts academic and job success quite well.
Neuroticism: Individuals high in this trait tend to experience emotional instability, anxiety, moodiness, irritability, and sadness. High scores on this dimension are often, but not necessarily, associated with anxiety disorders and depression.
Openness: This trait features characteristics such as imagination and insight, and those high in this trait also tend to have a broad range of interests. This dimension is somewhat correlated with IQ.
The scores of this sample were compared to a larger sample of college students used to validate this personality questionnaire.
| Dimension | Mean | SD | Interpretation | |—|—|— |—| | Extraversion | 2.67 | .94 | Low | | Agreeableness | 3.46 | .87 | Low | | Conscientiousness | 2.99 | .81 | Low | | Neuroticism | 2.93 | .83 | High | | Openness | 4.03 | .73 | High | Means and standard deviations for the big five personality scales, interpretation (low or high) when compared to a reference sample. All differences are statistically significant with medium effect sizes
Participants were asked about their usage of 63 different nootropics. If a participant indicated that they tried a nootropic, they were asked about the perceived effects with this substance later.
All perceived effects were rated on seven-point scales. The following graphs summarize the results. Substances are listed on the y axis, ranging from the highest to lowest mean rating. The points indicate the mean rating for this substance. Lines indicate a 95% confidence interval (CI), thus expressing the uncertainty of the respective mean. Wider CIs indicate a greater variety of responses. The red line indicates the neutral response labeled “no effect“. As a rule of thumb, all mean ratings with confidence intervals crossing the red line are likely to have no effect. If the lower (left) end of a CI is higher than e.g. the white line for “small increase“, the effects of this substance were rated quite high. This was rarely the case. Most substances had ratings somewhere between “no“ and “small effect“, with some exceptions.
Most substances were rated as being somewhere between neutral and slightly pleasant, suggesting that detrimental effects are rare for nootropics. Three substances were rated as below neutral, but the confidence intervals are extremely large. On the other hand, some substances were rated as being more than “slightly“ pleasant: DMHA, Huperzine A, Selegiline and LSD.
According to the responses, anxiety is reduced most effectively by the following substances: L-Theanine, Tianeptine, CBD, Kava and Phenibut. All of these substances are well known for there anxiolytic, calming effects. On the other hand, anxiety is slightly increased by a number of well-known stimulants, like methylphenidate, caffeine, adderall and the finil group.
The most profound effects on focus were reported for Adrafinil, Caffeine, Phenylpiracetam, Modafinil, Armodafinil, Methylphenidate and, most of all, Adderall. Melatonin and GABA seem to decrease focus, but only very slightly.
Not many substances seem to improve memory. In fact, none of them were rated as leading to more than a “small increase“ in memory.
A number of substances were rated as motivating. Most of them were stimulants. Melatonin, Bacopa monnieri and GABA seem to have slight detrimental effects on motivation.
LSD, Tianeptine, Phenibut and Adderall seem to improve mood. Remarkably, LSD microdoses were rated as having effects comparable to Tianeptine, which is an antidepressant.
Participants asked for the dose in milligrams of the nootropics they have already taken. Most of them managed to answer in the required format. Minimum, average and maximum doses for all substances are listed in the table below.
| Substance | Minimum dose in mg | Median dose in mg | Maximum dose in mg |
|---|---|---|---|
| L-Theanine | 100 | 200 | 400 |
| Bacopa | 200 | 300 | 500 |
| Caffeine | 80 | 200 | 800 |
| Curcumin | 100 | 500 | 2500 |
| Ashwagandha | 300 | 500 | 1200 |
| Rhodiola | 50 | 300 | 700 |
| St. John’s Wort | 250 | 575 | 900 |
| Kava | NA | NA | NA |
| Methylphenidate | 10 | 20 | 200 |
| Adderall | 5 | 25 | 60 |
| L-Deprenyl | 10 | 10 | 10 |
| Tyrosine | 250 | 600 | 9000 |
| NALT | 60 | 500 | 500 |
| Creatine | 1250 | 5000 | 10000 |
| CDP-Choline | 150 | 300 | 2000 |
| Alpha-GPC | 125 | 300 | 1200 |
| Carnitine/NALC | 500 | 500 | 1000 |
| Omega–3 | 300 | 1375 | 5000 |
| Magnesium | 100 | 300 | 1000 |
| Modafinil | 5 | 125 | 600 |
| Armodafinil | 75 | 150 | 150 |
| Adrafinil | 50 | 450 | 900 |
| Piracetam | 200 | 3100 | 8000 |
| Phenylpiracetam | 75 | 160 | 275 |
| Aniracetam | 90 | 800 | 2400 |
| Oxiracetam | 600 | 800 | 1500 |
| Pramiracetam | 100 | 700 | 1600 |
| Coluracetam | 15 | 55 | 200 |
| Fasoracetam | 100 | 22.5 | 60 |
| Nefiracetam | 250 | 250 | 250 |
| Noopept | 10 | 15 | 20 |
| Semax | .1 | .6 | 2 |
| Selank | .1 | .25 | 2 |
| Doepezil | 1 | 1 | 1 |
| Huperzine A | .085 | 1 | 5 |
| Tianeptine | 10 | 33 | 150 |
| NSI–189 | 5 | 40 | 100 |
| Melatonin | .05 | 3 | 30 |
| GABA | 100 | 175 | 250 |
| 5-HTP | 5 | 125 | 200 |
| Black Seed Oil | 30 | 265 | 500 |
| Ginseng | 50 | 325 | 600 |
| Ginkgo | 60 | 120 | 250 |
| Nicotine | 1 | 4 | 36 |
| Sulbutiamine | 200 | 500 | 1500 |
| Uridine | 10 | 250 | 600 |
| Sacrosine | 2000 | 2000 | 2000 |
| Sunifram | 10 | 20 | 20 |
| BPC–157 | .01 | .25 | 200 |
| Boswellia | NA | NA | NA |
| Guanfacine | 2 | 2 | 2 |
| DMHA | 150 | 150 | 150 |
| LSD Microdose | .00005 | 10 | 25 |
| CBD Oil | 10 | 25 | 60 |
| PRL–8–53 | 20 | 20 | 20 |
| Agmatine | 50 | 750 | 2000 |
| Selegiline/Deprenyl | 10 | 10 | 10 |
| Phenibut | 150 | 1000 | 3500 |
| Lion’s Mane | 200 | 800 | 3000 |
Coming soon…


Add New transaction
Mine MyCoin
Add a couple of transactions, and mine a block to add them to the blockchain.


NUM
: numeral
This document is a placeholder for the language-specific documentation
for NUM
.
Treebank Statistics (UD_Slovak)
There are 296 NUM
lemmas (2%), 348 NUM
types (2%) and 1161 NUM
tokens (1%).
Out of 17 observed tags, the rank of NUM
is: 7 in number of lemmas, 6 in number of types and 14 in number of tokens.
The 10 most frequent NUM
lemmas: jeden, dva, tri, oba, ii, štyri, 11, 1, mnoho, i
The 10 most frequent NUM
types: jeden, II, dva, tri, 11, jedného, 1, dvoch, I, dve
The 10 most frequent ambiguous lemmas: jeden (NUM 145, ADJ 1), i (CCONJ 68, PART 29, NUM 20, X 2), veľa (ADV 18, NUM 17), trochu (ADV 21, NUM 9), viac (NUM 8, ADV 3), pár (NOUN 2, NUM 2), sto (AUX 13, NUM 2), dosť (ADV 5, PART 1, NUM 1), v (ADP 1527, X 14, NUM 1), štvrť (NOUN 6, NUM 1)
The 10 most frequent ambiguous types: I (NUM 20, PART 4, CCONJ 3, X 2), veľa (NUM 14, ADV 2), trochu (ADV 19, NUM 9), viac (ADV 13, NUM 7), mnohí (NUM 1, ADJ 1), najviac (ADV 3, NUM 2), mnohých (ADJ 5, NUM 2), pár (NOUN 2, NUM 2), V (ADP 320, X 9, NUM 1), dosť (ADV 5, NUM 1, PART 1)
- I
- veľa
- trochu
- viac
- mnohí
- NUM 1: Šápúr bol nábožensky tolerantný panovník , ktorý zastavil dlhoročnú perzekúciu kresťanov , aj keď navonok asi zdôrazňoval skôr ekonomické dôvody , ktoré ho k tomu viedli ( z radov kresťanov sa najímali mnohí odborníci a remeslníci ) .
- ADJ 1: Environmentálne skupiny naznačujú , že mnohí členovia Bushovej vlády majú prepojenia s energetickým , automobilovým priemyslom a inými skupinami , ktoré sa stavajú proti ochrane životného prostredia .
- najviac
- mnohých
- pár
- V
- dosť
Morphology
The form / lemma ratio of NUM
is 1.175676 (the average of all parts of speech is 1.776807).
The 1st highest number of forms (11) was observed with the lemma “jeden”: jeden, jedna, jednej, jedno, jednom, jednou, jednu, jedny, jedného, jednému, jedným.
The 2nd highest number of forms (6) was observed with the lemma “oba”: oba, obaja, obe, oboch, obom, oboma.
The 3rd highest number of forms (6) was observed with the lemma “tri”: traja, tri, troch, trom, troma, tromi.
NUM
occurs with 6 features: sk-feat/NumForm (627; 54% instances), sk-feat/Case (527; 45% instances), sk-feat/Number (527; 45% instances), sk-feat/Gender (526; 45% instances), sk-feat/Animacy (224; 19% instances), sk-feat/Typo (1; 0% instances)
NUM
occurs with 15 feature-value pairs: Animacy=Anim
, Animacy=Inan
, Case=Acc
, Case=Dat
, Case=Gen
, Case=Ins
, Case=Loc
, Case=Nom
, Gender=Fem
, Gender=Masc
, Gender=Neut
, NumForm=Digit
, Number=Plur
, Number=Sing
, Typo=Yes
NUM
occurs with 46 feature combinations.
The most frequent feature combination is NumForm=Digit
(627 tokens).
Examples: II, 11, 1, I, 2, 2004, 7, III, 10, 20
Relations
NUM
nodes are attached to their parents using 14 different relations: sk-dep/nummod (776; 67% instances), sk-dep/conj (79; 7% instances), sk-dep/obl (73; 6% instances), sk-dep/nsubj (70; 6% instances), sk-dep/root (54; 5% instances), sk-dep/obj (52; 4% instances), sk-dep/dep (39; 3% instances), sk-dep/iobj (5; 0% instances), sk-dep/appos (4; 0% instances), sk-dep/nsubj:pass (4; 0% instances), sk-dep/ccomp (2; 0% instances), sk-dep/acl (1; 0% instances), sk-dep/orphan (1; 0% instances), sk-dep/xcomp (1; 0% instances)
Parents of NUM
nodes belong to 12 different parts of speech: NOUN (645; 56% instances), VERB (192; 17% instances), NUM (134; 12% instances), PROPN (76; 7% instances), ROOT (54; 5% instances), ADJ (18; 2% instances), X (14; 1% instances), ADV (10; 1% instances), PRON (10; 1% instances), PUNCT (4; 0% instances), DET (2; 0% instances), SYM (2; 0% instances)
561 (48%) NUM
nodes are leaves.
432 (37%) NUM
nodes have one child.
104 (9%) NUM
nodes have two children.
64 (6%) NUM
nodes have three or more children.
The highest child degree of a NUM
node is 7.


黒の手番です。11 はどう動かしますか？
Unlimited
pips Black=127 White=120
(CorrectAnswer= 0/0, ErrorScore= 0)
1. 8/4 eq:+0.713 67.56% (G:15.80% B:0.46%) 32.44% (G:7.56% B:0.23%) 2. 8/7 8/6 5/4 eq:+0.663 (-0.051) 66.63% (G:15.74% B:0.41%) 33.37% (G:6.36% B:0.16%) 3. 5/1* eq:+0.645 (-0.069) 66.20% (G:16.83% B:0.44%) 33.80% (G:8.47% B:0.23%) 4. 8/6(2) eq:+0.597 (-0.116) 65.14% (G:16.23% B:0.41%) 34.86% (G:7.07% B:0.19%) 5. 8/7 8/5 eq:+0.460 (-0.254) 63.06% (G:14.03% B:0.37%) 36.94% (G:6.29% B:0.05%)


{% load static %}
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{% for p in packages %}
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WATCH | Bloomberg sorry for 'stop and frisk' as he mulls presidential bid
Billionaire Michael Bloomberg on Sunday walked back his long-time support for the controversial "stop and frisk" policing policy that disproportionately targeted black and Latino New Yorkers as he mulled jumping in the race for president.
"I was wrong, and I'm sorry," the former mayor of the US financial capital told a predominantly black megachurch in Brooklyn.
The 77-year-old had long defended his backing of the aggressive technique, which gave the city's police broad powers to search anyone they suspected of criminality.
READ | Who are the 2020 US Democratic presidential candidates?
Bloomberg continued to back the programme - which is being phased out - even after a federal judge said in 2013 it violated constitutionally protected minority rights.
The media tycoon's speech at the Christian Cultural Center in Brooklyn's deprived East New York neighbourhood appeared to be a tacit acknowledgement of the crucial minority backing he will need as he weighs a concerted challenge to US President Donald Trump in 2020.
'Erosion of trust'
READ | A year before 2020 election, a divided and 'angry' America
At the 2011 peak of "stop and frisk" policing, 87% of some 685 000 stops targeted black or Latino people, according to the New York Civil Liberties Union.
Around the same proportion of people stopped were cleared of wrongdoing.
Citing the "erosion of trust" his stance had created among ethnic minorities, Bloomberg said: "I can't change history."
"However, today I want you to know that I realise back then, I was wrong, and I'm sorry," he added.
Bloomberg's words were met with a sceptical response as critics lambasted his reversal as vote pandering.
"He's right to apologise but voters should not fall for this," tweeted Kumar Rao, senior counsel at the Center for Popular Democracy.
"The apology was a decade late for those who were humiliated, harassed and intimidated by the government that is supposed to serve them," wrote New York Times opinion columnist Mara Gay.
 And their vote."
'Bridge builder'
Bloomberg has submitted paperwork in Arkansas and Alabama but has not announced his candidacy among a crowded field that includes another latecomer - former Massachusetts governor Deval Patrick.
Patrick became the 18th candidate in the race on Thursday, less than three months before the first nomination votes are cast in Iowa.
The 63-year-old former civil rights lawyer told NBC on Sunday he had considered announcing much earlier but held off when his wife of 35 years was diagnosed with uterine cancer.
"I think that I have a record of being a bridge builder," he said on talk show Meet the Press.
"I think that's pretty important at a time when not just the party in some respects but the nation is deeply divided."
Patrick was one of the first African-American governors in the country, serving eight years in office. He is friends with party dignitaries including the last Democratic president, Barack Obama.
"We are in crisis in many respects here in America, and we used a crisis in Massachusetts to come out stronger economically, stronger socially and more fair," he added.
"I'd like to see if those experiences and that aptitude and that skill set can be offered in service to our nation."
He broke with the majority of other Democratic candidates, however, when he declined to swear off taking donations from super PACs, political entities that can accept unlimited contributions by a single individual.
"I will have something to say about that (from a) policy point of view as we get a little further along," he said.
"But if there is going to be Super PAC money that supports me... the sources should be fully disclosed."


You can pass a URL as a path. As long as the URL is valid you will get back a json response { "originalUrl": [yourInput], shortUrl: [provided] }
Validate URL must have a TLD '.com', '.ca', '.org'
. They can omit the protocol 'http', https', 'ftp'
Input
hostname/new/http://www.google.ca
Get Back as JSON
{ "originalUrl": http://www.google.ca, shortUrl: hostname/3 }
Then visit:
hostname/3
Redirects to:
http://www.google.ca


Last update: 04-Sep-2010 17:59 UTC
The tickadj program reads, and optionally modifies, several timekeeping-related variables in older kernels that do not have support for precision timekeeping, including HP-UX, SunOS, Ultrix, SGI and probably others. Those machines provide means to patch the kernel /dev/kmem. Newer machines with kernel time support, including Solaris, Tru64, FreeBSD and Linux, should NOT use the program, even if it appears to work, as it will destabilize the kernel time support. Use the ntptime program instead.
The particular variables that can be changed with tickadj include tick, which is the number of microseconds added to the system time for a clock interrupt, tickadj, which sets the slew rate and resolution used by the adjtime system call, and dosynctodr, which indicates to the kernels on some machines whether they should internally adjust the system clock to keep it in line with time-of-day clock or not.
By default, with no arguments, tickadj reads the variables of interest in the kernel and displays them. At the same time, it determines an "optimal" value for the value of the tickadj variable if the intent is to run the ntpd Network Time Protocol (NTP) daemon, and prints this as well. Since the operation of tickadj when reading the kernel mimics the operation of similar parts of the ntpd program fairly closely, this can be useful when debugging problems with ntpd.
Note that tickadj should be run with some caution when being used for the first time on different types of machines. The operations which tickadj tries to perform are not guaranteed to work on all Unix machines and may in rare cases cause the kernel to crash.


This browser is reporting compatibility with older browser technologies that may perform poorly if it all.
Unable to load required dependencies. Please verify all WebVI files are available and served using an http server or use a browser that can load files directly from the filesystem.


Hello! Welcome to the contact Me page! I hope you enjoy it! If you are looking for my resume you can find
it on my Resume page. If you are looking for the rest of my coding experience you
will find it on my Coding Experience page. If you would like to learn more about
what this page is for or want to learn a little bit more about me, then please visit the About page. If you are
unable to find the information you were hoping for or would like to leave a suggestion, then feel free to
contact me by either email or phone. Or you can
fill out the form below.
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Before Change
tf.logging.fatal("spatial window should be an array of int")
raise
for name in self.fields:
non_spatial_dims = list(self.shapes[name][len(spatial_window):])
self.shapes[name] = tuple(spatial_window + non_spatial_dims)
def placeholders_dict(self, n_samples=1):
This function create a dictionary with items of {name: placeholders}
After Change
except ValueError:
tf.logging.fatal("spatial window should be an array of int")
raise
self.shapes = {
name: complete_partial_window_sizes(
spatial_window, self.shapes[name])
for name in self.fields}
// update based on the latest spatial shapes
self.has_dynamic_shapes = self._check_dynamic_shapes()
def placeholders_dict(self, n_samples=1):


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Click on Pizzas to view Ingredients.


WinSwitch 3.0 final release is out
-
Greg Hurrell
After a solid beta testing period, version 3.0 of WinSwitch is available for download.
Version 3.0 is a massive update which adds a lot of features and fixes all known issues. See the change log for full details. If you didn't try the 3.0 beta, download the latest version and try it now! This is a recommended update for all users.
WinSwitch is freeware, but I depend on donations to cover the costs of distribution and development, so please consider making a contribution, no matter how small. I have some wonderful ideas for improving WinSwitch, but I need your financial support to implement them. Over the lifetime of the program, the total donation to download ratio is less than 4 in 1000.
Donate to support WinSwitch development.
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Akan names are derived from Ghanian culture. Frequently in Ghana, children are given their first name as a 'day name' which corresponds to the day in the week they were born and also the gender.
Choose your gender:


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FullAtomModel
This module contains layers to convert angles to coordinates, load PDB files, assign atom types and transform coordinates of a protein.
This layer converts amino acid sequences and dihedral angles to atomic coordinates:
To compute the coordinates of a rigid group of atoms, we need to multiply each coordinate in an initial reference frame by the appropriate matrix. During the forward pass we construct a graph of cumulative transformations: $$\begin{eqnarray} M_1 &=& R_1(\phi)\\ M_2 &=& R_1(\phi) R_2(\chi)\\ M_3 &=& R_1(\phi) R_3(\psi)\\ M_4 &=& R_1(\phi) R_3(\psi) R_4(\omega) \end{eqnarray}$$ In short, to get the cumulative transform of a node $M_{i}$, we take the cumulative transform $M_{parent(i)}$ and multiply it by the transform of the current node $R_{i}$. The atomic coordinates are obtained by multiplying the reference coordinates of each rigid group by its cumulative transform.
To compute the gradient of a function $L$ that depends on the coordinates of the model, let's consider the simple situation depicted here:
Since the graph has three nodes, $L$ depends on three positions. The derivative with respect to the first dihedral angle is: $$ \frac{\partial L(\mathbf{r}_{1}, \mathbf{r}_{2}, \mathbf{r}_{3})}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_1}}\cdot \frac{\partial \mathbf{r_1}}{\partial \phi_0} + \frac{\partial L}{\partial \mathbf{r_2}}\cdot \frac{\partial \mathbf{r_2}}{\partial \phi_0} + \frac{\partial L}{\partial \mathbf{r_3}}\cdot \frac{\partial \mathbf{r_3}}{\partial \phi_0} $$ The first term of that sum can be written as: $$ \frac{\partial L}{\partial \mathbf{r_1}}\cdot \frac{\partial \mathbf{r_1}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_1}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} \mathbf{r}^0_1 $$ where $\mathbf{r}^0_1$ is the vector of atom 1 in the initial reference frame. The other two terms can be written as: $$ \frac{\partial L}{\partial \mathbf{r_2}}\cdot \frac{\partial \mathbf{r_2}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} R_1 \mathbf{r}^0_2 $$ $$ \frac{\partial L}{\partial \mathbf{r_3}}\cdot \frac{\partial \mathbf{r_3}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_3}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} R_2 \mathbf{r}^0_3 $$ We can write those expressions using $\mathbf{r}_k$, the transformed atomic coordinates calculated during the forward pass: $$ \frac{\partial L}{\partial \mathbf{r_1}}\cdot \frac{\partial \mathbf{r_1}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_1}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} M_1 \mathbf{r}^0_1 = \frac{\partial L}{\partial \mathbf{r_1}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M^{-1}_1 \mathbf{r}_1 $$ $$ \frac{\partial L}{\partial \mathbf{r_2}}\cdot \frac{\partial \mathbf{r_2}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} M_1 R_1 \mathbf{r}^0_2 = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} M_2 \mathbf{r}^0_2 = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} \mathbf{r}_2 $$ $$ \frac{\partial L}{\partial \mathbf{r_3}}\cdot \frac{\partial \mathbf{r_3}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_3}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M^{-1}_1 \mathbf{r}_3 $$ Now, let's return back to the sum: $$ \frac{\partial L(\mathbf{r}_{1}, \mathbf{r}_{2}, \mathbf{r}_{3})}{\partial \phi_0} = \sum^3_{k=1} \frac{\partial L}{\partial \mathbf{r_k}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M^{-1}_1 \mathbf{r}_k $$ In this formula index $k$ iterates over the children of node 0. This expression can be generalized to any graph without loops. Matrices $ F_i = M_i \frac{\partial R_i}{\partial \phi_i} M^{-1}_{i+1}$ are computed during the forward pass. The final expression for the derivative is: $$ \frac{\partial L}{\partial \phi_i} = \frac{\partial L}{\partial \mathbf{r_k}}\cdot F_i \sum_{k \in children(i)} \mathbf{r}_k $$ These sums can be easily computed during backward deph-first propagation through the graph.
from TorchProteinLibrary import FullAtomModel
a2c = FullAtomModel.Angles2Coords()
sequences = ["AAA"]
angles = torch.randn(1, 8, 3, dtype=torch.double)
coords, res_names, atom_names, num_atoms = a2c(angles, sequences)
Each amino acid is described by a list of 8 dihedral angles $\{\phi, \psi, \omega, \chi_1, \chi_2, \chi_3, \chi_4, \chi_5\}$ (in that order).
The angles not needed for a given amino acid are ignored but a list of 8 elements should be provided for all amino acids.
Implementation
The layer computes the coordinates by building a graph of transforms, acting on rigid groups of atoms. For example, the following figure shows a schematic representation of threonine, which has 5 rigid groups in total and is parametrized by 4 transforms. Each transform is represented by a dihedral angle $\alpha$ and has the form $$ R_i(\alpha) = R(\alpha, \beta_i, d_i) = R_y (\beta_i) T_x(d_i) R_x(\alpha) $$ where $R_x(\alpha)$ and $R_y(\beta_i)$ are the 4x4 rotation matrices around axes $x$ and $y$, and $T_x(d_i)$ is the 4x4 translation matrix along axis $x$. $\beta_i$ and $d_i$ are fixed parameters for which we do not compute derivatives. For instance, the first transform of the threonine parametrization shown above can be written as $$ R_1(\phi) = R(\phi, \theta_1, d_1)$$ where $\phi$ is the first dihedral angle (variable), $\theta_1$ is the X-N-CA angle (fixed), and $d_1$ is the N-CA bond length (fixed). Atom names are encoded in ASCII following the standard PDB nomenclature, with the last symbol always set to '\0'.To compute the coordinates of a rigid group of atoms, we need to multiply each coordinate in an initial reference frame by the appropriate matrix. During the forward pass we construct a graph of cumulative transformations: $$\begin{eqnarray} M_1 &=& R_1(\phi)\\ M_2 &=& R_1(\phi) R_2(\chi)\\ M_3 &=& R_1(\phi) R_3(\psi)\\ M_4 &=& R_1(\phi) R_3(\psi) R_4(\omega) \end{eqnarray}$$ In short, to get the cumulative transform of a node $M_{i}$, we take the cumulative transform $M_{parent(i)}$ and multiply it by the transform of the current node $R_{i}$. The atomic coordinates are obtained by multiplying the reference coordinates of each rigid group by its cumulative transform.
To compute the gradient of a function $L$ that depends on the coordinates of the model, let's consider the simple situation depicted here:
Since the graph has three nodes, $L$ depends on three positions. The derivative with respect to the first dihedral angle is: $$ \frac{\partial L(\mathbf{r}_{1}, \mathbf{r}_{2}, \mathbf{r}_{3})}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_1}}\cdot \frac{\partial \mathbf{r_1}}{\partial \phi_0} + \frac{\partial L}{\partial \mathbf{r_2}}\cdot \frac{\partial \mathbf{r_2}}{\partial \phi_0} + \frac{\partial L}{\partial \mathbf{r_3}}\cdot \frac{\partial \mathbf{r_3}}{\partial \phi_0} $$ The first term of that sum can be written as: $$ \frac{\partial L}{\partial \mathbf{r_1}}\cdot \frac{\partial \mathbf{r_1}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_1}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} \mathbf{r}^0_1 $$ where $\mathbf{r}^0_1$ is the vector of atom 1 in the initial reference frame. The other two terms can be written as: $$ \frac{\partial L}{\partial \mathbf{r_2}}\cdot \frac{\partial \mathbf{r_2}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} R_1 \mathbf{r}^0_2 $$ $$ \frac{\partial L}{\partial \mathbf{r_3}}\cdot \frac{\partial \mathbf{r_3}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_3}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} R_2 \mathbf{r}^0_3 $$ We can write those expressions using $\mathbf{r}_k$, the transformed atomic coordinates calculated during the forward pass: $$ \frac{\partial L}{\partial \mathbf{r_1}}\cdot \frac{\partial \mathbf{r_1}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_1}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} M_1 \mathbf{r}^0_1 = \frac{\partial L}{\partial \mathbf{r_1}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M^{-1}_1 \mathbf{r}_1 $$ $$ \frac{\partial L}{\partial \mathbf{r_2}}\cdot \frac{\partial \mathbf{r_2}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} M_1 R_1 \mathbf{r}^0_2 = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} M_2 \mathbf{r}^0_2 = \frac{\partial L}{\partial \mathbf{r_2}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M_1^{-1} \mathbf{r}_2 $$ $$ \frac{\partial L}{\partial \mathbf{r_3}}\cdot \frac{\partial \mathbf{r_3}}{\partial \phi_0} = \frac{\partial L}{\partial \mathbf{r_3}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M^{-1}_1 \mathbf{r}_3 $$ Now, let's return back to the sum: $$ \frac{\partial L(\mathbf{r}_{1}, \mathbf{r}_{2}, \mathbf{r}_{3})}{\partial \phi_0} = \sum^3_{k=1} \frac{\partial L}{\partial \mathbf{r_k}}\cdot M_0 \frac{\partial R_0}{\partial \phi_0} M^{-1}_1 \mathbf{r}_k $$ In this formula index $k$ iterates over the children of node 0. This expression can be generalized to any graph without loops. Matrices $ F_i = M_i \frac{\partial R_i}{\partial \phi_i} M^{-1}_{i+1}$ are computed during the forward pass. The final expression for the derivative is: $$ \frac{\partial L}{\partial \phi_i} = \frac{\partial L}{\partial \mathbf{r_k}}\cdot F_i \sum_{k \in children(i)} \mathbf{r}_k $$ These sums can be easily computed during backward deph-first propagation through the graph.
Input/Output
The input and output tensors have the following structure:Example
import torch
from TorchProteinLibrary import FullAtomModel
import numpy as np
import matplotlib.pylab as plt
import mpl_toolkits.mplot3d.axes3d as p3
if __name__=='__main__':
a2c = FullAtomModel.Angles2Coords()
sequences = ['GGMLGWAHFGY']
#Setting conformation to alpha-helix
angles = torch.zeros(len(sequences), 8, len(sequences[-1]), dtype=torch.double, device='cpu')
angles.data[:,0,:] = -1.047
angles.data[:,1,:] = -0.698
angles.data[:,3,:] = np.pi
angles.data[:,3:,:] = 110.4*np.pi/180.0
#Converting angles to coordinates
coords, res_names, atom_names, num_atoms = a2c(angles, sequences)
#Making a mask on CA, C, N atoms
is0C = torch.eq(atom_names[:,:,0], 67).squeeze()
is1A = torch.eq(atom_names[:,:,1], 65).squeeze()
is20 = torch.eq(atom_names[:,:,2], 0).squeeze()
is0N = torch.eq(atom_names[:,:,0], 78).squeeze()
is10 = torch.eq(atom_names[:,:,1], 0).squeeze()
isCA = is0C*is1A*is20
isC = is0C*is10
isN = is0N*is10
isSelected = torch.ge(isCA + isC + isN, 1)
#Resizing coordinates array for convenience (to match selection mask)
N = int(num_atoms[0].item())
coords.resize_(1, N, 3)
backbone_x = torch.masked_select(coords[0,:,0], isSelected)
backbone_y = torch.masked_select(coords[0,:,1], isSelected)
backbone_z = torch.masked_select(coords[0,:,2], isSelected)
#Plotting all atoms with the red dots and backbone with the blue line
sx, sy, sz = coords[0,:,0].numpy(), coords[0,:,1].numpy(), coords[0,:,2].numpy()
bx, by, bz = backbone_x.numpy(), backbone_y.numpy(), backbone_z.numpy()
fig = plt.figure()
plt.title("Full atom model")
ax = p3.Axes3D(fig)
ax.plot(sx,sy,sz, 'r.', label = 'atoms')
ax.plot(bx,by,bz, 'b-', label = 'backbone')
ax.legend()
plt.show()
plt.savefig("ExampleAngles2Coords.png")
This layer assigns atom types and rearranges coordinates according to types.
Currently we use 11 atom types defined as following:
Output coordinates are arranged such that atoms of one type are grouped together in a contiguous stretch of memory.
NumAtomsOfType stores the number of atoms of particular type and offsets are the number of atoms in the memory, before
particular atom type stretch of coordinates begins. For example, we get the coordinates of the first atom of type 8 in sample $i$ using:
$$ r = \mathrm{Coordinates}[i, 3(\mathrm{Offsets}[8] + 0)] $$
| Type | Description | Atoms |
|---|---|---|
| 1 | Sulfur/selenium | CYS:SG, MET:SD, MSE:SE |
| 2 | Nitrogen (amide) | ASN:ND2, GLN:NE2, backbone N (including N-terminal) |
| 3 | Nitrogen (aromatic) | HIS:ND1/NE1, TRP:NE1 |
| 4 | Nitrogen (guanidinium) | ARG:NE/NH* |
| 5 | Nitrogen (ammonium) | LYS:NZ |
| 6 | Oxygen (carbonyl) | ASN:OD1, GLN:OE1, backbone O (except C-terminal) |
| 7 | Oxygen (hydroxyl) | SER:OG, THR:OG1, TYR:OH |
| 8 | Oxygen (carboxyl) | ASP:OD*, GLU:OE*, C-terminal O, C-terminal OXT |
| 9 | Carbon (sp2) | ARG:CZ, ASN:CG, ASP:CG, GLN:CD, GLU:CD, backbone C |
| 10 | Carbon (aromatic) | HIS:CG/CD2/CE1, PHE:CG/CD*/CE*/CZ, TRP:CG/CD*/CE*/CZ*/CH2, TYR:CG/CD*/CE*/CZ |
| 11 | Carbon (sp3) | ALA:CB, ARG:CB/CG/CD, ASN:CB, ASP:CB, CYS:CB, GLN:CB/CG, GLU:CB/CG, HIS:CB, ILE:CB/CG*/CD1, LEU:CB/CG/CD*, LYS:CB/CG/CD/CE, MET:CB/CG/CE, MSE:CB/CG/CE, PHE:CB, PRO:CB/CG/CD, SER:CB, THR:CB/CG2, TRP:CB, TYR:CB, VAL:CB/CG*, backbone CA |
Input/Output
Reads PDB and outputs coordinates, residue and atom names and number of atoms. The order of atoms is the same as in the PDB file.
from TorchProteinLibrary import FullAtomModel
coords, res_names, atom_names, num_atoms = FullAtomModel.PDB2CoordsUnordered(["f4TQ1_B.pdb"])
Input/Output
Example
import torch
from TorchProteinLibrary import FullAtomModel
import numpy as np
import matplotlib
import matplotlib.pylab as plt
import mpl_toolkits.mplot3d.axes3d as p3
from scipy.spatial import ConvexHull
cmap = matplotlib.cm.get_cmap('Spectral')
if __name__=='__main__':
#Reading pdb file
p2c = FullAtomModel.PDB2CoordsUnordered()
coords, chains, res_names, res_nums, atom_names, num_atoms = p2c(["f4TQ1_B.pdb"])
#Resizing coordinates array for convenience
N = int(num_atoms[0].item())
coords.resize_(1, N, 3)
N_res = res_nums[0,-1].item()+1
residue_hulls = []
residue_coords = []
for i in range(N_res):
mask = torch.eq(res_nums[0,:], i)
num_res_atoms = int(mask.sum().item())
# Obtaining coordinates of all atoms of a single residue
coords_mask = torch.stack([mask, mask, mask], dim = 1).unsqueeze(dim=0)
res_coords = coords.masked_select(coords_mask).resize(num_res_atoms, 3).numpy()
residue_coords.append(res_coords)
# Constructing a convex hull
hull = ConvexHull(res_coords)
residue_hulls.append(hull)
#Plotting all atoms with the red dots
cmap = matplotlib.cm.get_cmap('Set3')
sx, sy, sz = coords[0,:,0].numpy(), coords[0,:,1].numpy(), coords[0,:,2].numpy()
fig = plt.figure()
plt.title("PDB2CoordsUnordered")
ax = p3.Axes3D(fig)
i_res = 0
for hull, coords in zip(residue_hulls,residue_coords):
for simplex in hull.simplices:
ax.plot(coords[simplex, 0], coords[simplex,1], coords[simplex,2], color = cmap(float(i_res)/float(N_res)))
i_res += 1
ax.plot(sx,sy,sz, 'r.', label = 'atoms')
ax.legend()
plt.show()
plt.savefig("ExamplePDB2CoordsUnordered.png")
Translates coordinates, namely:
$$ \mathbf{r}_i' = \mathbf{r}_i + \mathbf{T}_k $$
where $i = 0$ to $N_k - 1$ and $k = 0$ to $batch\_size-1$.
($N_k$ is the number of atoms in the $k$-th batch sample.)
from TorchProteinLibrary import FullAtomModel
translate = FullAtomModel.CoordsTranslate()
coords = torch.randn(1, 4*3, dtype=torch.double)
translation = torch.randn(1, 3, dtype=torch.double)
num_atoms = torch.tensor([4], dtype=torch.int)
coords_t = translate(coords, translation, num_atoms)
Input/Output
Rotates coordinates, namely:
$$ \mathbf{r}_i' = R_k \mathbf{r}_i $$
where $i = 0$ to $N_k - 1$ and $k = 0$ to $batch\_size-1$.
($N_k$ is the number of atoms in the $k$-th batch sample.)
from TorchProteinLibrary import FullAtomModel
rotate = FullAtomModel.CoordsRotate()
coords = torch.randn(1, 4*3, dtype=torch.double)
rotation = torch.eye(4, 4, dtype=torch.double).unsqueeze(dim=0)
num_atoms = torch.tensor([4], dtype=torch.int)
coords_r = rotate(coords, rotation, num_atoms)
Input/Output
Returns geometrical center of a set of coordinates:
$$ \mathbf{r}_i' = \frac{1}{N_k}\sum_i \mathbf{r}_i $$
where $i = 0$ to $N_k - 1$ and $k = 0$ to $batch\_size-1$.
($N_k$ is the number of atoms in the $k$-th batch sample.)
from TorchProteinLibrary import FullAtomModel
center = FullAtomModel.Coords2Center()
coords = torch.randn(1, 4*3, dtype=torch.double)
num_atoms = torch.tensor([4], dtype=torch.int)
coords_c = center(coords, num_atoms)
Input/Output
Computes axis-aligned bounding box, non-differentiable. A is the corner with the lowest coordinates and
B is the corner with the highest coordinates.
from TorchProteinLibrary import FullAtomModel
coords = torch.randn(1, 4*3, dtype=torch.double)
num_atoms = torch.tensor([4], dtype=torch.int)
A, B = FullAtomModel.getBBox(coords, num_atoms)
Input/Output
Returns a random translation that keeps the protein bounding box within a cube of a given size.
from TorchProteinLibrary import FullAtomModel
A = torch.randn(1, 3, dtype=torch.double)
B = A + torch.abs(torch.randn(1, 3, dtype=torch.double))
translation = FullAtomModel.getRandomTranslation(A, B, 120)
Input/Output
Returns a random rotation by uniformly sampling the $SO(3)$ group.
from TorchProteinLibrary import FullAtomModel
R = FullAtomModel.getRandomRotation(1)


Court jails Borno prosecutor for soliciting N7m bribe
by Adelani AdepegbaAdelani Adepegba, Abuja
Justice Umaru Fadawu of the Borno State High Court, Maiduguri, has sentenced a prosecuting counsel with the Federal State Ministry of Justice, Zanna Dalhatu to 18 months in prison for soliciting N7 million bribe.
Dalhatu’s conviction followed his arraignment on January 10, 2019, by the Maiduguri Zonal Office of the Economic and Financial Crimes Commission.
He had pleaded not guilty to the charge preferred against him and was sentenced on Monday without an option of fine.
The EFCC spokesman, Wilson Uwujaren, said in a statement on Tuesday that the lawyer’s journey to prison started when he demanded N7m bribe and also attempted to obtain the said sum from Shuaibu Mohammed, the Chief Accountant of Borno State Road Maintenance Agency to facilitate the termination of a case against a worker of the agency.
He was subsequently trailed and arrested in the process of collecting the bribe.
While the EFCC presented three witnesses during the trial, the defence counsel, Zanna Hamza, made a “no case submission,” which the court threw out and ordered that he should open his defence.
Not satisfied with the ruling, the defendant approached the Appeal Court, Jos Division, which upheld the Borno State High Court’s ruling on the no-case submission.
Upon the amendment of the charge by the prosecution, Dalhatu pleaded guilty and was convicted and sentenced accordingly.


ÁVision Build Log
Tool Versions:
IDE-Version: ÁVision V<IP_ADDRESS> Copyright (C) 2017 ARM Ltd and ARM Germany GmbH. All rights reserved. License Information: Peter Bye Plymouth University Flex license: MDK-ARM Professional: 95 user(s) (mdk_pro) Operation stops: 2 Aug 2018 Tool Versions: Toolchain: MDK-ARM Professional: 95 user(s) Version: 5.23 Toolchain Path: C:\Keil_v5\ARM\ARMCC\Bin C Compiler: Armcc.exe V5.06 update 4 (build 422) Assembler: Armasm.exe V5.06 update 4 (build 422) Linker/Locator: ArmLink.exe V5.06 update 4 (build 422) Library Manager: ArmAr.exe V5.06 update 4 (build 422) Hex Converter: FromElf.exe V5.06 update 4 (build 422) CPU DLL: SARMCM3.DLL V5.23 Dialog DLL: DCM.DLL V<IP_ADDRESS> Target DLL: STLink\ST-LINKIII-KEIL_SWO.dll V<IP_ADDRESS> Dialog DLL: TCM.DLL V<IP_ADDRESS>Project:
C:\Users\Student\Desktop\babyklon\robot movement algorithm\Motor-Nano_1.uvprojx Project File Date: 02/19/2018Output:
*** Using Compiler 'V5.06 update 4 (build 422)', folder: 'C:\Keil_v5\ARM\ARMCC\Bin' Build target 'Motor-Nano' compiling main.cpp... main.cpp(79): warning: #1035-D: single-precision operand implicitly converted to double-precision redlight=ldr*3.3f/0.95; //Read the Analogue input MBED Normalised 0.0 to 1.0f Multiply by 3.3f to Calibrate to a Voltage read main.cpp(84): warning: #1035-D: single-precision operand implicitly converted to double-precision bluelight=ldr*3.3f/1.07; //Read the Analogue input MBED Normalised 0.0 to 1.0f Multiply by 3.3f to Calibrate to a Voltage read main.cpp(89): warning: #1035-D: single-precision operand implicitly converted to double-precision greenlight=ldr*3.3f/1.26; //Read the Analogue input MBED Normalised 0.0 to 1.0f Multiply by 3.3f to Calibrate to a Voltage read main.cpp(234): warning: #1-D: last line of file ends without a newline } main.cpp: 4 warnings, 0 errors linking... Program Size: Code=29244 RO-data=3180 RW-data=108 ZI-data=1724 ".\build\uvision5\Motor-Nano.axf" - 0 Error(s), 4 Warning(s).Collection of Component include folders:
.\RTE\_Motor-Nano C:\Keil_v5\ARM\PACK\Keil\STM32F4xx_DFP\2.11.0\Drivers\CMSIS\Device\ST\STM32F4xx\IncludeCollection of Component Files used:
Build Time Elapsed: 00:00:12


deckofcards
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
Prerequisites
node v6.11.4 and up npm 3.10.10 and up
Installing
npm install
Running the tests
npm test
Running demo card game
To run a demo card game using the deck of cards modules
npm run demo
This game is a simplified version of WAR, instead of doing the war rules, same value cards are discarded
License
This project is licensed under the MIT License - see the LICENSE.md file for details


lib
/
com.github.thibaultbee.srtdroid.enums
/
SockStatus
/
CLOSED
CLOSED
CLOSED
The socket has been closed, but not yet removed by the GC thread.


welcome to the world of perspectives
about me
kojo abbah
list of things of interest to me
Spirituality
Future tech trends
politics
comedy
Being myself
feel free to go through these trial projects:
my first website
hello world
cookie recipe
animal girrafe
ek project
thanks for visiting


---
title: "PARK CITY PROFESSIONAL ARTISTS ASSOCIATION EXHIBIT"
date: "2000-01-01 19:05:31 -06:00"
categories:
- exhibit
subtitle: ""
layout: "free-events"
event-image: "park-city-artist-association.jpg"
event-dates: "May 31 - June 23, 2019"
event-location: "Red Butte Garden Visitor Center"
button-type: "register"
tickets-link: ""
registration-info: "Questions?
Please call<PHONE_NUMBER>"
instructor-info: "N/A"
member-cost: "Free"
public-cost: "Garden Admission"
event-notes: "Artist Reception June 8"
tickets-button: "hide"
refund-policy: "hide"
published: false
---
Meet the Artists Reception
Saturday, June 8 from 2-6PM
Several members of the PCPAA will exhibit their work featuring the nature of the Wasatch mountains, birds, flowers, trees, and more.
The Park City Professional Artists’ Association (PCPAA) is an alliance for the promotion of art within the Park City community. Started in 1981 by six artists who had businesses or studios in Park City, the organization has since evolved into a group of over sixty working artists. Members are committed not only to their individual work, but also have a strong commitment to supporting and advancing the arts.
For more, please visit thier website: www.parkcityart.com
Nan Gray - Watercolor http://parkcityart.com
Mary Perry - Acrylic & Photography http://parkcityart.com
Jeanne Hansen - Watercolor https://www.jeannehansenart.com
Cynthia McLoughlin - Oil https://cynthiamcloughlin.com
Richard Pick - Photography http://rdpnaturephoto.com
Fred Montague - Ink & Letterpress http://www.mountainbearink.com
Melissa Skarsten - Jewelry http://jewelrybym.com
Kathy Cartier - Fiber http://kathycartier.com
Michael McRae - Photography https://www.michaelmcrae.com/


--- layout: default ---
The future of Node.js REST development
A Node.js web service framework optimized for building semantically correct RESTful web services ready for production use at scale. restify optimizes for introspection and performance, and is used in some of the largest Node.js deployments on Earth.
restify is used by some of the industry's most respected companies to power some of the largest deployments of Node.js on planet Earth.
Running at scale requires the ability to trace problems back to their origin by separating noise from signal. restify is built from the ground up with post-mortem debugging in mind.
Staying true to the spec is one of the foremost goals of the project. You will see references to RFCs littered throughout GitHub issues and the codebase.


2. Program
Classes are from:
- 2 to 8 pm Paris time.
- 1 to 7 pm London time.
- 8 am to 2 pm NY time.
- 5 am to 11 am SF time.
Day 1 - Introduction to epigenomics, and 3D organisation of genomes.
Lecture 1
- Epigenomics introduction
- General processing of Hi-C data
- Improving pipelines with snakemake
Lab 1
- Step-by-step processing of Hi-C data and integration with snakemake.
- Use of existing Hi-C processing pipelines and common formats.
Tuesday: Application and analysis of Hi-C data
Lecture 2
- Common analysis on Hi-C contact maps and their biological interpretation
- Overview of Hi-C applications (Scaffolding, metagenomics, regulatory genomics, …)
Lab2
- Manipulation and visualisation of sparse matrices using the cooler package
- Compute interpretable metrics on the Hi-C contact maps from last lesson
- Use existing methods for signal detection in Hi-C data.
Wednesday: ChIP-seq analysis
Lecture 3
- Introduction to ChIP-Seq
- Main uses of ChIP-Seq
- General processing of ChIP-seq data
- Introduction to Bioconductor
Lab 3
- Step-by-step processing of ChIP-Seq data
- Identification of TF-binding site or epigenomic histone modification using
ChIP-seq peak calling
- Identification of motifs and motif enrichment analysis
Thursday: ATAC-seq
Lecture 4
- Notion of local chromatin accessibility
- Assays to measure chromatin accessibility: a long story of nucleases
- Why peak callers should be carefully chosen
Lab 4
- Identification of ATAC-seq peaks on multiple samples using YAPC
- Differential binding analysis and clustering of ATAC-seq peaks
- Study of chromatin accessibility at promoters with V-plots
Friday: Integration and visualization of different genomics data
Lecture 5
- Types of questions: Classification, description, differential analysis
- Regulatory states from histone marks
- Identification of transcription factor target genes using RNA-seq and
ChIP-seq
Lab 5
- Crossing results from ATAC-seq with chromHMM
- Integration of ChIP-seq data and RNA-seq data
- Analysis with external databases:
GO analysis, protein functional interactions, …


Receiving State level award from Heath Minister Pratap Jena
Whole team with state level award
Vigilance week celebration
Lamp lighting by Animesh Biswa Sir
Total Team


CSS Variables With Inline Styles
When Ahmad Shadeed was working on a demo for an article, he needed an easy way to create a grid layout that allowed him to make changes without touching CSS every time. Now he summarized his approach.
This third part of the series will focus on adding a text-based client for the game engine that was created in part 2. Fernando Doglio explains basic architecture design, tool selection and code highlights by showing you how to create a text-based UI …
Images are a big part of the web and, yet, they can cause a lot of challenges for the user experience if not properly optimized or delivered. It’s been almost a decade since Google introduced the world to WebP as a solution to this problem. As more …
In this article, we are going to explore the evolution of JavaScript around asynchronous execution in the past era and how it changed the way we write and read code. We will start with the beginnings of web development, and go all the way to modern …
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Images are a big part of the web and, yet, they can cause a lot of challenges for the user experience if not properly optimized or delivered. It’s been almost a decade since Google introduced the world to WebP as a solution to this problem. As more …
The term COPE (“Create Once, Publish Everywhere”) is a methodology for publishing our content to different outputs (website, AMP site, email, apps, and so on) by having a single source of truth for all of them. Let’s explore how to implement COPE …
In this article, we are going to explore the evolution of JavaScript around asynchronous execution in the past era and how it changed the way we write and read code. We will start with the beginnings of web development, and go all the way to modern …
In this article, we’ll create a personal bookmarking site using FaunaDB, Netlify Functions and 11ty data files.
A channel where seasoned developers show how they design, build, work and play. Coming up next: Inclusive Components With Heydon Pickering with Heydon Pickering (Nov 7).
Meet our new printed magazine, exploring topics that will make us all think, and will remain useful as time passes by. Friendly, practical and approachable. Shipping now.
Ire Aderinokun is a self-taught Front-End Developer and User Interface Designer from Lagos, Nigeria. She is currently the co-founder, COO, and VP Engineering of BuyCoins, a cryptocurrency exchange for Africa, and previously worked with eyeo, the company behind products like Adblock Plus and Flattr Plus. Ire is a Google Expert, specializing in the core front-end technologies HTML, CSS, and JavaScript, but is passionate about all aspects of technology. She writes about these topics on her blog and regularly shares her knowledge speaking at conferences around Africa and the world. Thank you for everything you do for the community, dear Ire!
When Ahmad Shadeed was working on a demo for an article, he needed an easy way to create a grid layout that allowed him to make changes without touching CSS every time. Now he summarized his approach.
Not everyone has access to a fast internet connection. Stephanie Stimac wrote a thought-provoking article about privilege, website performance, and creating experiences that are easy to access and use.
Created by the community for the community, the free and open-source tutorial How to GraphQL teaches you all around GraphQL to take you from zero to production.
In Firefox 70, the Accessibility Inspector has grown into an auditing facility to help identify and fix common mistakes and practices that reduce accessibility. Marco Zehe summarized what is available in this latest release.
Users want snappy and delightful experiences. To help you achieve this, Milica Mihajlija explains how browser rendering works and how to use DevTools to diagnose performance issues.
After months of internal beta testing, the automatic Web Performance auditing tool Falco is now open source, helping you monitor, analyze, and optimize your websites.
Meet Design Systems , a recent Smashing book in which Alla Kholmatova explores how to set up an effective design system to create great digital products. With common traps, gotchas and lessons learned.
Imagine you wrote a beautiful song and nobody discovered it. That would make any cat sad. Don't let that happen!


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Central | Hong Kong


TRAFFIC (2000) / *** 1/2
Directed by Steven Soderbergh. Screenplay by Stephen Gaghan, based on the miniseries "Traffik" by Simon Moore. Starring Michael Douglas, Don Cheadle, Benicio Del Toro. Running time: 147 minutes. Rated AA for controversial subject matter and offensive language by the MFCB. Reviewed on January 10th, 2001.
By SHANNON PATRICK SULLIVAN
"Traffic" accomplishes a rare feat indeed. A movie about one of the most prevalent issues confronting modern society -- the drug trade -- it nonetheless manages to rise above simple proselytising and offers a brutally uncompromising, essentially unbiased perspective on its subject material. In a world where even the best dramas tend to take sides, this is remarkable; even more noteworthy is the fact that it happens within the confines of one of the most gripping films of the year.
Directed by Steven Soderbergh, and vastly superior to his crowd-pleasing but underachieving "Erin Brockovich", "Traffic" tells three stories about lives affected by drugs. These are tangentially connected, but mostly stand up on their own -- it would not be difficult to remove any of the plotlines from the movie and view those segments in isolation.
In one story arc, Michael Douglas plays Robert Wakefield, an Ohio judge who has been named by the President to be the nation's new drug czar -- the nominal head of America's war on illegal substances. But unbeknownst to Wakefield or his wife Barbara (Amy Irving), their own daughter Caroline (Erika Christensen) has been lured into the drug culture.
Meanwhile, Douglas' real-life bride Catherine Zeta-Jones stars as Helena Ayala, whose husband Carlos (Steven Bauer) is secretly one of the country's top importers of narcotics. This is revealed to Helena only when Carlos is arrested by Agents Gordon (Don Cheadle) and Castro (Luis Guzman) following the apprehension of a lower-level dealer (Miguel Ferrer). Helena is soon embroiled in Carlos' world when the cartel he worked with threatens their son's life to keep Carlos from betraying them to the authorities. The only help Helena can turn to seems scarcely preferable -- including Carlos' perfidious business partner (Dennis Quaid) and a cunning cartel head (Benjamin Bratt).
Finally, there is the tale of Mexican policeman Javier Rodriguez Rodriguez (Benicio Del Toro), who fights against drug trafficking from his side of the border. Javier becomes caught in a war between two cartels (one of them Bratt's) and discovers that neither his partner (Jacob Vargas) nor the army general who professes to Mexico's biggest anti-drug crusader (Tomas Milian) are as dedicated to the task as they would have him believe.
Soderbergh's direction stands out in "Traffic". He employs a rigid, realistic style which thrusts the audience directly into the drama. Events unfold at a sometimes feverish pace, but Soderbergh keeps things lucid, often helped by focussing on a handful of very strong characters. He also distinguishes each of the three plotlines by filming each of them (or rather, each of their principle locations) in a different style. The Washington and Ohio locales of the Wakefield storyline look cold and blue, reflecting both the bureaucratic nature of the judge's new environment and the downward spiral which has gripped his family. The Mexico scenes, on the other hand, look hazy and washed out, as though the sunlight is raining down on the desert and barrios. And the California locations for the Ayala segments are more lushly, naturally lit.
Each of the storylines boasts a number of fine performances. Douglas is on the mark as a man who is expected to serve a nation, but who finds he cannot even help his own flesh and blood. His desperation, as the pressures of his job conflict with his desire to heal his family, is effectively conveyed. Del Toro, meanwhile, is excellent as a little fish in the big and tumultuous pond that is Mexico, unable to completely trust anyone and often finding himself on the side of those whose actions seem no better than the criminals'.
Zeta Jones is less successful as Helena, her character lacking consistency from scene to scene. To an extent, this is because the entire California subplot feels a little rushed. Unlike the other two storylines, which chiefly concentrate on just one character (Judge Wakefield and Javier Rodriguez, respectively), Helena competes for attention with other individuals, most notably the entertaining double act of Gordon and Castro. Indeed, Cheadle brings such intensity to his role that it seems a shame he does not feature more prominently in the film. There is a lot happening in the Ayala segments -- legal maneuvering, financial maneuvering, Helena's efforts to deal with Carlos' cohorts, the agents' investigation -- and at times it feels rushed and jumbled.
The same cannot be said of the superb Mexico scenes, which offer a blistering look at the blurred line between those who run the country and those who run the drugs. Here we see how easy it can be for a lawman to abandon his duty and turn the other cheek -- not only because it can be tantalisingly lucrative to do so, but because the deck already seems so overwhelmingly stacked against him.
The story of the Wakefield family is probably the most familiar and accessible to mainstream audiences, and the tale of a girl hooked on drugs and unwilling to commit herself to rehab is nothing new. But "Traffic" depicts this subplot with such stark honesty that it is far more effective than most treatments of the material. What happens to Caroline is horrible and sobering. The explanation offered by her boyfriend (Topher Grace, from "That '70s Show") for the stranglehold drugs have on the population is equally so.
"Traffic" reaches no conclusions, favours no sides. Some aspects of the film support the controversial notion of legalising narcotics, and suggest that the drug war is futile and doomed to failure. Others offer a spark of hope that, slowly but surely, America is winning this most insidious of battles. In the end, it is not clear that current policy is at all effective, but nor is it indisputably misguided -- the possibility for both exists.
What "Traffic" does accomplish is simply to raise the level of awareness of just how complex an issue this really is. Politicians and activists who attempt to dismiss or address the problem with glib words and handy catchphrases are neither helping nor, increasingly, fooling anybody.
Copyright © 2001 Shannon Patrick Sullivan. Archived at The Popcorn Gallery, http://www.physics.mun.ca/~sps/movies/Traffic.html
_______________________________________________________________________ / Shannon Patrick Sullivan | "We are all in the gutter, but some of us \ |<EMAIL_ADDRESS>| are looking at the stars." - Oscar Wilde | \___________________________|__________________________________________/ | Popcorn Gallery Movie Reviews www.physics.mun.ca/~sps/movies.html | | Doctor Who: A Brief History of Time (Travel) /drwho.html |
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Parse
Mammon Huge fiend (devil), lawful evil Armor Class 20 (natural armor) Hit Points 378 (28d12 + 196) Speed 50 ft. STR DEX CON INT WIS CHA 22 (+6) 13 (+1) 24 (+7) 23 (+6) 21 (+5) 26 (+8) Saving Throws Dex +9, Int +14, Wis +13, Cha +16 Skills Deception +16, Insight +13, Perception +13, Persuasion +16 Damage Resistances cold Damage Immunities fire, poison; bludgeoning, piercing, and slashing from weapons that aren't silvered Condition Immunities charmed, exhaustion, frightened, poisoned Senses truesight 120 ft., passive Perception 23 Languages all, telepathy 120 ft. Challenge 25 (75,000 XP) Innate Spellcasting. Mammon's innate spellcasting ability is Charisma (spell save DC 24, +16 to hit with spell attacks). He can innately cast the following spells, requiring no material components: At will: charm person, detect magic, dispel magic, fabricate (Mammon can create valuable objects), heat metal, magic aura 3/day each: animate objects, counterspell, creation, instant summons, legend lore, teleport 1/day each: imprisonment (minimus containment only, inside gems), sunburst Legendary Resistance (3/day). If Mammon fails a saving throw, he can choose to succeed instead. Magic Resistance. Mammon has advantage on saving throws against spells and other magical effects. Magic Weapons. Mammon's weapon attacks are magical. ACTIONS Multiattack. Mammon makes three attacks. Purse. Melee Weapon Attack: +14 to hit, reach 10 ft., one target. Hit: 19 (3d8 + 6) bludgeoning damage plus 18 (4d8) radiant damage. Molten Coins. Ranged Weapon Attack: +14 to hit, range 40/120 ft., one target. Hit: 16 (3d6 + 6) bludgeoning damage plus 18 (4d8) fire damage. Your Weight In Gold (Recharge 5-6). Mammon can use this ability as a bonus action immediately after hitting a creature with his purse attack. The creature must make a DC 24 Constitution saving throw. If the saving throw fails by 5 or more, the creature is instantly petrified by being turned to solid gold. Otherwise, a creature that fails the saving throw is restrained.  The petrification lasts until the creature receives a greater restoration spell or comparable magic. LEGENDARY ACTIONS Mammon can take 3 legendary actions, choosing from the options below. Only one legendary action option can be used at a time and only at the end of another creature's turn. Mammon regains spent legendary actions at the start of his turn. Attack. Mammon makes one purse or molten coins attack. Make It Rain! Mammon casts gold and jewels into a 5-foot radius within 60 feet. One creature within 60 feet of the treasure that can see it must make a DC 24 Wisdom saving throw. On a failure, the creature must use its reaction to move its speed toward the trinkets, which vanish at the end of the turn. Deep Pockets (3 actions). Mammon recharges his Your Weight In Gold ability.
This parser is very particular about its input. Use at your own risk.
Output


Youtube Video Downloader
A web application for downloading media from Youtube. Use it here.
WaveformPlayer
A terminal based application for playing and visualizing WAV files.
See a web-based demo here.
For more projects, visit my GitHub profile.


The choice of virtualization versus containerization depends on the business development and operational model, and the way applications are written and produced. Both are software technologies that create self-contained virtual packages, but to choose the one that will best suit the user’s needs, we will look at the following points.
However, it is also important to note that there are also ways of combining virtualization and containerization so that both technologies’ advantages are brought together.  This way, we can get the security and isolation of a virtual machine with the quick and lightweight setup of an application inside of a container.


Modals
Modals are a very important part of this interface. Modals are used throughout the software to control a specific function. Modals should be used for every instance of setting controls, user confirmations, exporting or importing data and other related tasks. Sizing of modals depend solely on how complex the action is.
1000 pixel width
For use with complex modals.
850 pixel width
For use with moderately complex modals.
600 pixel width
For use with less complex modals.
400 pixel width
For use with confirmation modals.
Modal Types
A variety of modal types are available for use based on what the modal is to be used for. When extending, please ensure only the following types of modals are used.
- Step-by-Step
- The step-by-step modal guides the user through the required steps to complete a particular task. The sequence of forms might have an impact on subsequent steps. The create event modal is a good example.
- Tabbed
- The tabbed modal is used to display information divided up into logical sections. It is not that important that the sequence of forms be maintained, validation is done on all the forms before completion of the task. The edit/create user modal as shown above demonstrates the usage of a tabbed modal.
- Single View
- Single view modals are used to display a singular form or perform a simple action.


SPONSORS
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Buyer FAQ
Back to FAQ homeWhat can I buy on Curtsy?
Curtsy is an app for women to buy and sell new, like-new, and gently-worn clothing. Curtsy is a great way to save 60-90% on your favorite brands. When you buy something on Curtsy, you’re buying it directly from the seller-- they’ll ship it to you within a few days after placing your order.
How does payment work?
Curtsy offers safe and easy payments for buyers and sellers. You can use any credit or debit card or Apple Pay to buy an item, and Curtsy holds the money until the seller ships the order before paying them for the sale.
Learn more about checkout and paymentHow does shipping work?
All items ship with express 2-4 day shipping. The price of shipping will be listed directly under the item price, so there are no suprise fees at checkout.
After you buy an item, we’ll email the seller a prepaid shipping label that they’ll use to ship the item. We ask all sellers to ship within 1-2 days of making a sale, and most do (some even same day!). If you’re worried an item won’t arrive on time we encourage you to message the seller and ask for a shipping ETA before you buy.
Sellers are paid after the tracking updates showing the order has been shipped.
You’ll be able to track your item after it ships through the app.
What’s the return policy?
Curtsy doesn’t offer returns-- all sales are final.
With that said, we guarantee buyers a full refund and free return if their item wasn’t described accurately by the seller.
After you buy an item it will move into your Curtsy Closet, where you can easily re-list it if it doesn’t fit or you don’t like it for any reason. If you re-sell it within a day or two after receiving it, just message us and we’ll refund you the seller fee-- so it’s like you got a full refund.
Can I ask sellers a question?
Yep! There’s a button on every item to “Ask the seller a question.”
Can I offer to buy the item less than the seller is asking?
Yep! All items have a "Make Offer" button. This will allow you to request to buy it at a lower price. Learn more about offers
More About Buying:
Go to FAQ home


Amazon says 'bias' in Pentagon awarding $10-B contract to Microsoft
'It's critical for our country that the government and its elected leaders administer procurements objectively and in a manner that is free from political influence,' a spokesperson for Amazon Web Services says
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Demo 7
This is an experimental 3D engine for the TI-83 and TI-83+ graphical calculators.
As it is an experiment it is not desperately useful, and it is likely to contain bugs that may crash your calculator. Please back up any important files before running this program.
Two binaries are provided; Nostromo.8xp (for the TI-83+) and Nostromo.83p (for the TI-83). The TI-83 binary requires an Ion-compatible shell. The TI-83+ binary requires a MirageOS-compatible shell.
Source code is not currently provided as it is currently too messy and buggy to be of use.
Usage
Select the program from the list in your shell of choice and run it. The following keys can be used to control the demo:
- General
- Clear Exit.
- Movement
- ▲ / ▼ Move forwards/backwards.
- Trace / Graph Strafe left/right.
- Mode / X,T,Θ,n Move up/down ("fly mode" only).
- Looking
- ◀ / ▶ Look left/right.
- Del / Stat Look up/down.
- Interaction
- Alpha Open/close doors.
- Options
- Y= Show/hide the options menu.
Options menu
Press Y= to show or hide the options menu. Select an option from the menu with the ▲ and ▼ keys.
Pressing Enter or 2nd will change the highlighted option.
- Show FPS counter — When enabled, this displays the number of frames rendered each second in the bottom left of the screen.
- CPU speed — Toggle between 6MHz and 15MHz on supported calculators (the regular TI-83+ and TI-83 are limited to 6MHz operation only).
- Fly mode — Enabling this mode allows you to freely move the camera up and down rather than walking around on the floor.
- Collision detection — Disabling this allows you to walk through walls.
- Render objects — When disabled, sprite objects are not drawn.
- View statistics — Shows the camera position, angle, how many BSP nodes were visited, how many sub-sectors were drawn and how many attempted/successful walls were drawn.
Known issues
- Performance is not especially good at the moment. Looking across the large room with the pit in the middle slows the framerate to a crawl owing to the sheer number of subsectors and lines being handled.
- Some pixels are not rendered when they should be. This is especially noticeable near the ends of steeply sloping wall edges.
- When you are very close to the edge of a wall it may get projected incorrectly (integer overflow) and you will see either a vertical line flash into view then out again or a region of the screen will appear blank.
- In "fly mode" you can fly above the ceiling and below the floor.
- If the camera is moved into a "solid" region it will be instantly pushed out into free space when near a wall. This can be triggered in normal usage (without disabling collision detection or enabling fly mode) by standing under an open door then closing it; you'll be forced into the room when the bottom edge of the door moves below your head height.
- Collision detection is not properly handled around the very ends of walls, which may cause a sudden jump in player position when you "slide" around a corner.
- The current floor height is calculated based on the point directly under the centre of the player and not taking the player's radius into consideration. This can cause an unnatural jump when you slowly walk off the edge of a raised portion of the level.
- If the frame rate drops low enough it is possible to walk through walls. This is down to the way movement is scaled by frame time; the longer a frame takes to render, the further you move during that frame. If the frame rate drops low enough you move fast enough to outwit the collision detection routines.
- Moving sectors are not reset when you restart the level. As an example, lower the platform in the middle of the map then exit and restart the program. When you walk to it you will notice that it is still lowered.
If you would like to report an issue, please include the camera position and viewing angle in your report (accessible from the "View statistics" menu option).
Map
The demo world is based on parts of E2M7 (Spawning Vats) from DOOM. I chose this level as it has some interesting architecture without being too demanding as well as for historical reasons; as far as I am aware it was one of the first levels created for DOOM that appeared in the final game.
The lines indicate walls. Each wall connects two vertices, indicated by the smaller black blobs. Some walls are split into multiple segments; this is either a by-product of the need to break the level into convex sub-sectors for rendering purposes or to avoid a limitation with the clipping routines (long walls viewed at a steep angle can be clipped incorrectly).
The larger blue blobs indicate "things" — objects represented by a sprite in the world. The single large red blob indicates the player's starting position.


{% extends "page.html" %} {% from "macros/breadcrumbs.html" import breadcrumbs %} {% from "macros/member-badge.html" import member_badge %} {% block title %}{{ this.name }}{% endblock %} {% block preamble %}
{% endblock %} {% block body %}{{ this.description }}


- BaseAbsListFragment<T> - Class in r2b.apps.base
-
Wrapper for AbsList main functionality.
- BaseAbsListFragment() - Constructor for class r2b.apps.base.BaseAbsListFragment
-
- BaseActivity - Class in r2b.apps.base
-
Wrapper for activity main functionality.
- BaseActivity() - Constructor for class r2b.apps.base.BaseActivity
-
- BaseActivity.CallableBackFragment - Interface in r2b.apps.base
-
Add support to fragments to receive from activity back events.
- BaseAdapter<T> - Class in r2b.apps.base
-
Wrapper for base adapter main functionality.
- BaseAdapter(List<T>) - Constructor for class r2b.apps.base.BaseAdapter
-
Build adapter with the list items.
- BaseApplication - Class in r2b.apps.base
-
Used as singleton class to initialize managers and utilities.
- BaseApplication() - Constructor for class r2b.apps.base.BaseApplication
-
- BaseDialog - Class in r2b.apps.base
-
A fragment that handles a dialog that can show a title, up to three
buttons, a traditional single choice list, a list of selectable items
(single with radio or multiple choice with checkbox), or a custom layout.
- BaseDialog() - Constructor for class r2b.apps.base.BaseDialog
-
- BaseDialog.BaseDialogListener - Interface in r2b.apps.base
-
The activity that creates an instance of this dialog fragment must implement
this interface in order to receive event callbacks.
- BaseFragment - Class in r2b.apps.base
-
Wrapper for the main functionality of the fragment.
- BaseFragment() - Constructor for class r2b.apps.base.BaseFragment
-
- BaseTracker - Class in r2b.apps.utils
-
Tracker object or lib factory.
- BaseTracker(Context) - Constructor for class r2b.apps.utils.BaseTracker
-
Builder.


Object marker Only Icon Example
Standard list of icon used of the Object marker use glyph
property to add icon.
Object marker Text and clickable Text
Standard Object marker Text and clickable use clickable
boolean property to add hovering effects.
Object marker Icon and text readonly.
Standard Object marker with icon and text use glyph
property to add icon.
Object marker icon and text clickable.
Standard Object marker with icon and text with clickable use clickable
boolean property to add hovering
effects.


Overview
Importer allows you to import multiple kinds of data from local or remote data sources into ExpressionEngine content such as channel entries or members.
For example, you can have an XML file on a remote SFTP server and Importer will retrieve, parse, and import that data into new Channel Entries on a scheduled basis. Or, perhaps you need to combine multiple Relationship custom fields into a single Playa field. Importer can do both and more. Not only that, but its code is designed to be expandable allowing us or your favorite developer to add additional data types or content types for new kinds of importing.
Importer uses the concept of import profiles. An import profile stores the source and structure of your data, and then you indicate how to import it into ExpressionEngine. It is your way of educating the module how to handle your imported data. Using this method, you could create multiple import profiles for the same CSV, JSON or XML file and import it into more than one Channel, even into multiple ExpressionEngine sites. Importer is often able to reconcile the data for you, updating existing records or adding new records as necessary. Not only that, but by using the Cron feature you can regularly import data on a scheduled basis without any additional work.
Check out the Data Types, Data Sources and Content Types documentation for more information.
Importer for Channel Entries also includes full support for Pixel & Tonic's Playa and Matrix field types.