GRIFFIN consists of 16 large-volume HPGe clovers providing excellent gamma-ray energy resolution, and is augmented by a suite of ancillary detectors for measuring e±, alphas, and neutrons, as well as gamma rays in temporal coincidence.
Experiments are normally run in a cycling mode. Each cycle begins by moving the tape and collecting a background spectrum. The radioactive beam is then implanted into the tape (like VHS or cassette tape and actually computer tape) at the center of the detector array. The beam implantation is then stopped and the decay of the sample observed. When the species of interest has decayed away the cycle begins again. The tape is moved to physically remove the daughter nuclei activities from sight of the detectors. These cycles can dramatically increase the signal-to-background ratio of the decay of interest. The tape is pictured here with the Zero-Degree Scintillator behind it.
GRIFFIN uses 16 Compton-suppressed High-Purity Germanium (HPGe) Clover detectors for a total of 64 Ge crystals. The germanium crystals are held at a temperature below -175 degrees Celsius with the use of liquid nitrogen. The crystals also require a bias voltage of around 3500 volts to operate correctly.
SCEPTAR (SCintillating Electron-Positron Tagging ARray) is a set of plastic scintillators which surround the radioactive sample at the center of GRIFFIN. The scintillators detect the beta particles which are emitted when a nucleus decays. The signal from these detectors is used in coincidence with the Ge detectors to increase the sensitivity of the measurements.
There are 8 locations in the GRIFFIN support frame to house these fast scintillator detectors. The 2 inch by 2 inch cylindrical crystals are made of cerium-doped lanthanum bromide (LaBr3(Ce)). These detectors are used to observe gamma rays emitted from excited states in daughter nuclei, just like the Ge detectors. Whereas Ge detectors have excellent energy resolution for gamma rays, these fast scintillators have a very good timing resolution for gamma rays but poorer energy resolution. The fast-timing can be used to measure the lifetime of excited states in daughter nuclei which live for as short a time as 10 picoseconds, thats a hundred thousandth of a millionth of a second.
PACES (Pentagonal Array for Conversion Electron Spectroscopy) is an array of 5 lithium-drifted silicon (Si(Li)) detectors located inside the vacuum chamber. They are used to detect internal conversion electrons which can be emitted during the decay of excited states in daughter nuclei. These detectors are also used to detect alpha particles which can be emitted when a heavy nucleus decays; this capability is especially important when working with actinide beams at ISAC. The crystals and FETs are cooled to liquid nitrogen temperatures to improve the energy resolution of the detectors.
GRIFFIN has also been designed to be fully compatible with the new DESCANT array (Deuterated Scintillator Array for Neutron Tagging) being developed by the University of Guelph and TRIUMF. DESCANT is an array of 70 deuterated scintillators for detecting neutrons. This addition will allow the sensitive study of beta-delayed neutron emission in neutron-rich nuclei.


My name is Vladimir Kalmykov. When I was 11 years of age,
my family moved to America. Its been 16 years since I've lived here.
Living in America, specifically in Federal way, was difficult.
Adapting to area, new language, new people, and especially new Laws.
As kids, we quickly adapted to language and surrounding,
but for my parents, it was a challenging in every way. Slowly, but surely
we got through as a family. Helping each other with the language
learned from the streets, meeting new people in the neighborhood.


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| Class | Description |
|---|---|
| FileInfo |
Encapsulates all metadata (excluding name) of a file on DFS, including its replica locations,
partitioning rules, etc.
|
| HostPort |
Encapsulates a (hostname, portnum) pair for any component of MapReduce framework.
|
| IDAssigner |
Global JobID / TaskID manager, where a unique, thread-safe ID can be obtained for each new Job or
new Task.
|
| JobInfo |
Encapsulates all metadata of a Job from MapReduce user, including input-/output-file,
command-line argument, job status, JobID, etc.
|
| MasterCoordinator |
Main class containing all properties that the Master node in a MapReduce class keep track of.
|
| MasterCoordinatorCheckFailure |
Background utility that checks for the health of cluster machines.
|
| MasterCoordinatorLaunchTasks |
Background utility that dispatches tasks across MapReduce cluster.
|
| MasterCoordinatorServeConnection |
Runnable class that handles all connection requests to Master node.
|
| MasterCoordinatorStartup |
Runnable class with the entry point for the Master node in MapReduce cluster.
|
| QueuedTasks |
Encapsulates the pending and queued tasks of a worker node.
|
| RunningTasks |
Keeps track of all running Mapper, Sorter, and Reducers of a worker node.
|
| TaskInfo |
Encapsulates all metadata for a task, including Task ID, Task Type, I/O File Name, etc.
|
| Timer |
Timeout object for MapReduce framework.
|


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/Proof.20term.20size.20*.202.5E200.html ---
I became curious how sizes of proof terms affect speed, so I ran a quick experiment:
def foo : nat → Prop | 0 := true | (n+1) := (foo n) ∧ (foo n) meta def mk_foo_expr : nat → expr | 0 := `(trivial) | (n+1) := expr.app (expr.app (reflected.to_expr<EMAIL_ADDRESS>(foo n) (foo n))) (mk_foo_expr n)) (mk_foo_expr n) open tactic meta def show_foo : tactic unit := do `(foo %%nx) ← target, n ← eval_expr nat nx, exact (mk_foo_expr n) set_option profiler true lemma foo_200 : foo 200 := by show_foo #print foo_200
To my surprise Lean handles it with ease, in roughly 50ms. I don' t think Lean is constructing and checking a gigantic proof term that has 2^200 occurrences of trivial
. What's going on here?
To a certain degree, Lean can handle terms with dag-like sharing (your term is very small when viewed as a dag). This happens e.g. because type inference and whnf and unifiability are cached, i.e., only evaluated once for every subterm (there are only few subterms).
See also https://github.com/leanprover/tc/issues/8
I see. Thanks!
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


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| [ < ] | [ > ] | [ << ] | [ Up ] | [ >> ] | [Top] | [Contents] | [Index] | [ ? ] |
GDB supports multiple command interpreters, and some command infrastructure to allow users or user interface writers to switch between interpreters or run commands in other interpreters.
GDB currently supports two command interpreters, the console interpreter (sometimes called the command-line interpreter or CLI) and the machine interface interpreter (or GDB/MI). This manual describes both of these interfaces in great detail.
By default, GDB will start with the console interpreter. However, the user may choose to start GDB with another interpreter by specifying the `-i' or `--interpreter' startup options. Defined interpreters include:
console
mi
mi2
). Used primarily
by programs wishing to use GDB as a backend for a debugger GUI
or an IDE. For more information, see The GDB/MI Interface.
mi2
mi1
The interpreter being used by GDB may not be dynamically switched at runtime. Although possible, this could lead to a very precarious situation. Consider an IDE using GDB/MI. If a user enters the command "interpreter-set console" in a console view, GDB would switch to using the console interpreter, rendering the IDE inoperable!
Although you may only choose a single interpreter at startup, you may execute
commands in any interpreter from the current interpreter using the appropriate
command. If you are running the console interpreter, simply use the
interpreter-exec
command:
interpreter-exec mi "-data-list-register-names" |
GDB/MI has a similar command, although it is only available in versions of GDB which support GDB/MI version 2 (or greater).
| [ << ] | [ >> ] | [Top] | [Contents] | [Index] | [ ? ] |
Please send FSF & GNU inquiries & questions to<EMAIL_ADDRESS>There are also other ways to contact the FSF.
These pages are maintained by the GDB developers.
Copyright Free Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111, USA.
Verbatim copying and distribution of this entire article is permitted in any medium, provided this notice is preserved.
This document was generated by GDB Administrator on March, 27 2008 using texi2html


Senran Kagura is a series of games of varying styles, mostly known for its hack ’n’ slash / beat ’em up games, which is the style of game from which the series originated.
The vast cast is constituted mainly of girls, with only a few supporting male characters.
In most of the games, the only playable characters are girls, with varying body types and looks. In order to customize the body types of the characters, the games use a body part scaling file. This file contains information about the sizes of various body parts to customize the look of the different characters.
Conveniently, a lot of the games have a similar file format for customizing body scales for the different characters. This similarity, alongside the flexibility of the format, allows for tools to exist that allow users to uniformly change the body types of the various character across the games. sked is one of such tools.
This is an interactive guide on how to use sked and employ its various features effectively. As you read the tutorial, there will be interactive examples that you can use to explore how the tool works and behaves.
The aforementioned file that the games use allow for the customization of a variety of individual body parts, some of which come in pairs. A good example being left breast and right breast, which are considered individual body parts by the games.
Oftentimes, the user will want to modify the values of related body parts at once. It can become tedious to edit them individually, so sked groups them to allow for them to be modified at the same time.
Each individual body part has three fields: an “x” field, a “y” field, and a “z” field, for scaling along each of those axes.
The field at the top is called the compound field. By default, modifying it will replace the value of each regular field in its group, and if the values in the group are modified to be different, the compound field will show be shown as blank to indicate the inconsistency.
When using sked, after selecting a file or choosing a preset, the first thing that needs to be done is selecting characters to modify.
The user will sometimes want to modify multiple characters to be similar or even the same altogether. This is easy in sked, as they can simply select multiple characters from the list. Desktop browsers oftentimes allow this by dragging the mouse on the list, or by holding ctrl while clicking the items on the list.
When multiple characters are selected, by default, if there is a value that is different across characters, its field will become blank, just as compound fields do.
Also analogously to compound fields, by default, changing a regular field when multiple characters are selected will affect all of the selected characters.
Regular fields have two operation modes: unbound mode (also called free mode) and bound mode. Unbound fields have vertical stripes to indicate their mode — the “y” fields of the “thighs” group are in unbound mode by default.
To toggle between these two modes, a user can either double‐tap the regular field whose mode they want to change, long‐press it, or even press ctrl‐space in their keyboard with the field selected.
A field in unbound mode does not affect its group’s compound field, it’s treated entirely as if it didn’t partake in the group.
Groups themselves also have two different working modes, albeit entirely orthogonal to the modes of regular fields.
To toggle among assignment mode (represented by
) and average mode (represented by ), the user can click on the button to the right of the compound field of a group.Assignment mode is the default mode for each group, and its behavior has been explained until this point with “by default”.
In average mode, no field will ever be blank. If there is some inconsistency among the values it represents, it’ll show the average of their values.
By itself, this is not noteworthily useful; the advantage is when modifying the field’s value.
Whereas with assignment mode, modifying a field will replace all its values, in average mode, modifying a field will change them proportionally.
Note that group modes affect both regular and compound fields alike. Note also, however, that they only differ in behavior for regular fields when there are multiple characters selected.
Average is useful if someone wants to, e.g. change a specific body part of multiple (perhaps all) characters, while keeping them proportional to each other.
Another use of average mode is modifying all values in a group while keeping an specific axis proportionally lower or higher than the rest.
Note: For the interactive example above, try selecting multiple characters on one of the previous examples.


High Priest Gregory:
Ah, you're back! Do you bring news of Hindemith?
Yes! So Waldstein saw him recently, eh? Well, now we can be certain that he's on the Pilgrimage of the Tablets of Vision. You're sure to meet up with him if you continue that path.
I have a part of the next Stone of Commune, but must have the other piece in order to complete it.
"Where can I find the other piece?"


RPi Localization and Mapping
CONNECT
SIMULATE
EDIT
PATHING
GO TO
Obstacle
Free
Unknown
A*
Greedy
Depth-First
Breadth-First
Export


--- layout: post title: Policy or Polarcoat?  More than 46 percent said they didn’t want to let their co-workers down by not showing up for a shift. When managers were asked how many employees they thought came to work sick, the majority answered just 18 percent.
cite>official excerptSurvey: More Than Half of US and Canadian Food Workers Go to Work Sick
So which will you choose to take up the fight against microbes? Policy or Polarcoat?


| vec_as_names {vctrs} | R Documentation |
vec_as_names()
takes a character vector of names and repairs it
according to the repair
argument. It is the r-lib and tidyverse
equivalent of base::make.names()
.
vctrs deals with a few levels of name repair:
minimal
names exist. The names
attribute is not NULL
. The
name of an unnamed element is ""
and never NA
. For instance,
vec_as_names()
always returns minimal names and data frames
created by the tibble package have names that are, at least,
minimal
.
unique
names are minimal
, have no duplicates, and can be used
where a variable name is expected. Empty names, ...
, and
..
followed by a sequence of digits are banned.
All columns can be accessed by name via df[["name"]]
and
df$`name`
and with(df, `name`)
.
universal
names are unique
and syntactic (see Details for
more).
Names work everywhere, without quoting: df$name
and with(df, name)
and lm(name1 ~ name2, data = df)
and
dplyr::select(df, name)
all work.
universal
implies unique
, unique
implies minimal
. These
levels are nested.
vec_as_names( names, ..., repair = c("minimal", "unique", "universal", "check_unique"), repair_arg = "", quiet = FALSE )
names |
A character vector. |
... |
These dots are for future extensions and must be empty. |
repair |
Either a string or a function. If a string, it must
be one of
The |
repair_arg |
If specified and |
quiet |
By default, the user is informed of any renaming
caused by repairing the names. This only concerns unique and
universal repairing. Set |
minimal
namesminimal
names exist. The names
attribute is not NULL
. The
name of an unnamed element is ""
and never NA
.
Examples:
Original names of a vector with length 3: NULL minimal names: "" "" "" Original names: "x" NA minimal names: "x" ""
unique
namesunique
names are minimal
, have no duplicates, and can be used
(possibly with backticks) in contexts where a variable is
expected. Empty names, ...
, and ..
followed by a sequence of
digits are banned. If a data frame has unique
names, you can
index it by name, and also access the columns by name. In
particular, df[["name"]]
and df$`name`
and also with(df, `name`)
always work.
There are many ways to make names unique
. We append a suffix of the form
...j
to any name that is ""
or a duplicate, where j
is the position.
We also change ..#
and ...
to ...#
.
Example:
Original names: "" "x" "" "y" "x" "..2" "..." unique names: "...1" "x...2" "...3" "y" "x...5" "...6" "...7"
Pre-existing suffixes of the form ...j
are always stripped, prior
to making names unique
, i.e. reconstructing the suffixes. If this
interacts poorly with your names, you should take control of name
repair.
universal
namesuniversal
names are unique
and syntactic, meaning they:
Are never empty (inherited from unique
).
Have no duplicates (inherited from unique
).
Are not ...
. Do not have the form ..i
, where i
is a
number (inherited from unique
).
Consist of letters, numbers, and the dot .
or underscore _
characters.
Start with a letter or start with the dot .
not followed by a
number.
Are not a reserved word, e.g., if
or function
or TRUE
.
If a vector has universal
names, variable names can be used
"as is" in code. They work well with nonstandard evaluation, e.g.,
df$name
works.
vctrs has a different method of making names syntactic than
base::make.names()
. In general, vctrs prepends one or more dots
.
until the name is syntactic.
Examples:
Original names: "" "x" NA "x" universal names: "...1" "x...2" "...3" "x...4" Original names: "(y)" "_z" ".2fa" "FALSE" universal names: ".y." "._z" "..2fa" ".FALSE"
rlang::names2()
returns the names of an object, after
making them minimal
.
The Names attribute section in the "tidyverse package development principles".
# By default, `vec_as_names()` returns minimal names: vec_as_names(c(NA, NA, "foo")) # You can make them unique: vec_as_names(c(NA, NA, "foo"), repair = "unique") # Universal repairing fixes any non-syntactic name: vec_as_names(c("_foo", "+"), repair = "universal")


{% extends "layout/default.html" %} {% load bootstrap3 %} {% block title %}Credentials Verification{% endblock %} {% block content %}
In order to perform some of the data migrations from your legacy account, the system needs your legacy account credentials.
Please enter your old Chameleon username and password to continue.


ob_end_clean (PHP 4, PHP 5, PHP 7) ob_end_clean — 清空（擦除）缓冲区并关闭输出缓冲 说明 bool ob_end_clean ( void ) 此函数丢弃最顶层输出缓冲区的内容并关闭这个缓冲区。如果想要进一步处理缓冲区的内 容，必须在ob_end_clean()之前调用ob_get_contents()，因为当调用ob_end_clean()时缓 冲区内容将被丢弃。 返回值 成功时返回 TRUE，或者在失败时返回 FALSE。错误的原因首先是，在调用时没有一个起作 用的缓冲区，或者是因为某些原因缓冲区不能被删除（可能对特殊缓冲区而言）。 错误／异常 如果函数失败了，将引发一个E_NOTICE异常。 更新日志 版本 说明 4.2.0 添加了布尔返回值。 范例 下面的例子给出了一种去除所有输出缓冲区的方法： Example #1 ob_end_clean() example 参见 • ob_start() - 打开输出控制缓冲 • ob_get_contents() - 返回输出缓冲区的内容 • ob_flush() - 冲刷出（送出）输出缓冲区中的内容 User Contributed Notes 10 notes =============================================================================== Take note that if you change zlib output compression setting in between ob_start and ob_end_clean or ob_end_flush, you will get an error: ob_end_flush () failed to delete buffer zlib output compression Example: ob_end_clean(); in this example will throw the error. =============================================================================== Note that if you started called ob_start with a callback, that callback will still be called even if you discard the OB with ob_end_clean. Because there is no way of removing the callback from the OB once you've set it, the only way to stop the callback function from having any effect is to do something like: =============================================================================== Keep in mind that mrfritz379's example (#49800) is just an example. You can achieve that example's result in a more efficient manner without using output buffering functions: echo "
Search running. Please be patient. . ."; $output = "
FileList:
\n"; if (is_dir($dir)) { $dh = opendir($dir); while (($fd = readdir($dh)) != false) { echo " ."; $output .= $fd; } } echo "Search Complete!\n"; echo $output; In addition to John Smith's comment (#42939), ob_gzhandler() may still set the HTTP header "Content-Encoding" to "gzip" or "deflate" even if you call ob_end_clean(). This will cause a problem in the following situation: 1. Call ob_gzhandler(). 2. Echo "Some content"; 3. Call ob_end_clean(). 4. Echo "New content"; In the above case, the browser may receive the "Content-Encoding: gzip" HTTP header and attempts to decompress the uncompressed "New content". The browser will fail. In the following situation, this behaviour will go unnoticed: 1. Call ob_gzhandler(). 2. Echo "Some content"; 3. Call ob_end_clean(). 4. Call ob_gzhandler(). 5. Echo "New content"; This is because the second ob_gzhandler() will mask the absence of the first ob_gzhandler(). A solution would be to write a wrapper, like John Smith did, for the ob_gzhandler(). =============================================================================== About the previous comment: You can also relay on ETag and simply use time() $time) { header('HTTP/1.1 304 Not Modified'); exit(); } else { header('ETag: "'.$time.'"'); } echo 'Caching for ', $mins*60, 'secsSearch running. Please be patient. . ."; $output = "
FileList:
\n"; if (is_dir($dir)) { $dh = opendir($dir); while (($fd = readdir($dh)) != false) { echo " ."; ob_start(); echo $fd; $output .= ob_get_contents(); ob_end_clean(); } } echo "Search Complete!\n"; echo $output; The program will continue to print the " ." without printing the file list. Then the "Search Complete" message will print followed by the buffered file list. =============================================================================== You may want to be careful about calling ob_end_clean() from within your call-back function. I believe this can produce an endless-loop within PHP.


Sweetcorn-red &green pepper-mushroom onion-jalapenos-tikka sauce
Small: 400
Medium: 600
Large: 1000
Marinated tikka chicken -green pepper-onion
Small: 600
Medium: 800
Large: 1200
Spicy peri-peri chicken
Small: 650
Medium: 850
Large: 1250
Marinated BBq steak
Small: 500
Medium: 700
Large: 1100
100% beef mince-fresh tomato-fresh onion
Small: 550
Medium: 750
Large: 1150
Macon-pineapple
Small: 700
Medium: 900
Large: 1300
Additional Charge: 100
Additional Charge: 200
Additional Charge: 200
Additional Charge: 50
Additional Charge: 250
Additional Charge: 300
Thin crust is commonly thought of as the first type of crust to popular pizza on the global stage, and it is the de-facto pizza standard.
Additional Charge: 0
A thick crust is typically rectangular (though not always), and it is characterized by being the style of crust most capable of allowing for massive amounts of delicious ingredients to rest on top of it.
Additional Charge: 200
ngong racecourse
+254792193060
<EMAIL_ADDRESS>@pitzstar


Formalization and Verification of AUTOSAR OS Standard’s Memory Protection.
A Method and Tool supporting for Automated Testing Of Web Applications.
2017
2016
2014
2014
2013
2011-2014
Researcher at INRIA Lille – Nord Europe and a part-time Assistant Professor at the Computer Science department of École polytechnique
Vice Dean of Faculty of Information Technology, University of Engineering and Technology, Vietnam National University, Hanoi
Realize Safety and Security by Advanced Science and Technology


--- layout: page title: "About" description: "This is what I do." header-img: "img/about-bg.jpg" ---
I work
I play
I exist
I'm still working on this page


class CommentHandler |
Description
An interface for handling comments in blast output.
Author: Leo Przybylski<EMAIL_ADDRESS>Default Constructor
Constructs the CommentHandler
from its attributes.
None are required though.
Method handleComment
Stub method for handling comments.
This is the method that the BlastParser
will call when it encounters a comment.


This is a modified jumbotron that occupies the entire horizontal space of its parent.
{{ page.intro_paragraph | markdownify | remove: '
' | remove: '


Tools for
OMERO Users
OME Users meeting
30th May 2018
Will Moore
Outline
"Tools": OMERO web apps and CLI clients
- New app features and new apps over the last year
- Advantages of decoupled clients
- Testing of decoupled clients
New features in the last year:
- Crop page to panels
- Labels from tags
- Add Polygons and Polylines from OMERO
- Big (tiled) Image support
- Last release: OMERO.figure 4.0.0, May 22nd
New features in the last year:
- Performance improvements
- UI improvements
- Export ROI pixel intensity to CSV
- Multiple viewers
- Last release: OMERO.iviewer 0.5.0, May 22nd
3D viewer based on FPBioImage
- August 3rd: OMERO.FPBioImage 0.2.0
Tool for querying data by Map Annotations
- New feature in last year: Testing infrastructure
- Last release: OMERO.mapr 0.2.3, May 2nd
OMERO.cli plugin for bulk saving of rendering settings.
- Last release: cli-render 0.3.0, May 8th
$ bin/omero render set Dataset:1 settings.yml
# settings.yml
channels:
1:
color: "FF0000"
label: "Red"
min: 1
max: 255
active: True
2:
color: "00FF00"
Tool for filtering Images and Wells in webclient
using any metadata
- Prototype presented to OME team: Feb 2018
- Improved by Glencoe software
- 0.1.0 Released: May 22nd, 2018
Other apps, not in active development
-
OMERO.gallery
:
Browse Project, Dataset Image in mobile-friendly web pages
-
OMERO.player
:
Web viewer that caches all planes for fast playing through Z/T
Advantages of decoupled clients
For Developers:
- Prototypes can be developed independently, without breaking anything
- More flexible release cycles
- App release takes OME team ~1 hour (~1 Day for OMERO)
Advantages of decoupled clients
For Sysadmins:
- Simpler for Users to upgrade: no server downtime
- Easy to install. ALL apps are:
$ pip install...
- Only install the apps you want
- Can install new Apps with an older OMERO.server
Disadvantages of decoupled clients
- Discoverability
- More steps to install "everything"
- Solutions:
- Improve visibility on website and docs
- TODO: Build an app store?!
- "Decoupled" can mean "less well integrated"
- For Devs: More repos and testing infrastructure to maintain
- Solutions: Ansible, Jenkins, Docker etc.
Testing of decoupled clients
-
Use
omero-test-infra
- Docker-composed OMERO server for testing
- Testing scripts run by Travis CI on every GitHub PR
- For example: OMERO.figure
.travis.yml
services:
- docker
before_install:
- git clone https://github.com/openmicroscopy/omero-test-infra .omero
script:
- .omero/docker app


Michael Lawes's Portfolio
This is my portfolio.
Michael is a 19 year old student at Columbia University studying Computer Science in SEAS.
Above is an image of my favorite character of all time, Mikoto Suoh. He is one of the antihero's in the anime series Project K.
I grew in New York, more specifically Long Island. I always enjoyed math and science growing up and originally pursued research upon starting high school. My high school went from 7th to 12th in one building so I joined Science Research in 8th grade. Upon entering my senior year I decided I wanted to study CS as I realized research was not where my heart resided. Now I'm here
Click here to see content created by server code.
- Projects:
- Real-time chat application using MERN web development stack
- Data Science 4 All project on select variables impacting graduation rate at 4-year colleges and universities
Photo Gallery
I don't usually take photographs often. If I am taking a picture it's likely of either the clouds or the sky when it's orange or purple-ish. I do enjoy photoshoots of different outfits I put together, however, I never have time to take pictures or someone available who can photos :(. Maybe one day I'll learn how to use the self-timer and get a front-facing camera that doesn't have the quality of a 2007 Youtube video.
Click here to get a random quote or Fact:
Congratulations you made it to the end of my portfolio :) I'd say it looks pretty good for someone with 4 midterms this week, 3 of them being on Thursday.
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Started out in life working as an Office Manager with Randstad F&A. I was humbled to be a part of a strong leadership team that valued employee development. My leadership team there equipt me with strong people skills that further morphed into strong Recruting skills.
I then found myself in retail sales for a wonderful company called MobileOne LLC. Here I learned the basics of customer interaction, sales development, and management. I helped Mentor several Assistant Managers as well as Managers.
Working with MobileOne I developtment a strong business accumen and disipline. Although I am currently experiancing a strong level of success I still found myself looking for more opportunites to grow. It was this year that I decied to help a small business work from the ground up.
As I look toward the Horizion and that next goal, it's become very apparent to me that as people we need to always build on top of our skills. While searching I had a chance to connect with a very smart individual that created OnDelta a marketing trade school.
Lead Designer
Lead Marketer
Lead Developer
Although we come across many people in life, there are only a few that we are destined to be truly connected with.


We launched accessibleGO in 2017 to solve the travel problems that millions of people with disabilities face, from difficulty finding accessible hotels to unpleasant surprises at attractions that claim to be accessible. Our Accessible Trip Resources will change the way people with disabilities travel, offering extensive on-the-go travel resources that solve problems like finding immediate local wheelchair repair or hiring a local caregiver. Our Accessible Travel Ideas section offers hundreds of inspiring travel stories like top ten accessible attractions and recommended itineraries for exciting and memorable trips. Our soon-to-be released booking engine will enable your travel arrangements, offering accessible solutions.
Reviews of your personal travel experiences, from hotel rooms to landmarks to accessible taxis will fuel the power of accessibleGO by creating a true community that supports one another through critical information. Imagine the security of knowing that countless travelers before you have paved the way for a smooth and pleasant accessible travel experience.
Please reach out to us with suggestions, feedback and any concerns by emailing
<EMAIL_ADDRESS>click to email us
accessibleGO was inspired by Emma Eljas, the mother of cofounder Miriam Eljas Goldman. A resident of Silicon Valley, Emma was a wheelchair user with multiple sclerosis who never let life's obstacles hold her back from living life to the fullest. Emma served as a commissioner on the Valley Transportation Authority (VTA) Disability Advisory Commission and helped make regional transportation more accessible. With a wheelchair-lift van, Emma and her family traveled the Bay Area and took advantage of the beauty of the region. While many venues were accessible, countless were not. Even calling in advance, only to be told misinformation by well-intentioned employees, didn’t solve the problems.
Miriam recalls an impressionable incident as a teenager where she and her mother went to a local movie theater in San Jose. Over the phone, they were told the theater was completely accessible. Upon arrival, there was a series of steps to enter the actual theater from the lobby. Disheartened, Miriam asked the theater manager how employees could give such incorrect information. The manager, not to be deterred, took a flimsy, cracked ramp made of fractured plywood out of a broom closet and proudly declared the theater accessible. Knowing full well there was no way Emma’s wheelchair plus body weight would make it over the ‘ramp’, Miriam and her mother left the theater, disappointed and frustrated.
Given her firsthand exposure to accessibility issues, Miriam felt compelled to follow in her mother’s footsteps, knowing that a difference could be made simply by the sharing of critical advance information just like on other travel websites where reviews are about the quality of a travel experience, not accessibility. The vision of accessibleGO is to create a platform for travelers with disabilities to access information, share experiences and be inspired to travel the world without obstacles.


Thanks for being our dad: And caring about us day to day!
Your sacrifices are much appreciated.
So: I ah u addy.
-Thank you for working for us!- Kevin
Kevin
©Kevin <Wow>


{% extends 'slowsearch/base.html' %} {% load static %} {% block body_block %}
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Mission of Agricultural Operations: To operate University of California, Riversides experiment stations in the support of field research and greenhouses and other growing facilities for the faculty and staff of the College of Natural and Agricultural Sciences and the Agricultural Experiment Station. Within that mission, the Department provides and maintains research and growing facilities, and acts as custodian of the land.
Read more


CARTOFrames¶
A pandas interface for integrating CARTO into data science workflows.
Install Instructions¶
cartoframes relies on pandas and a development version of the CARTO Python SDK (on branch 1.0.0). To install cartoframes on your machine, do the following:
Clone this repository.
Change your directory to cartoframes and run the following:
$ pip install -r requirements.txt
$ pip install cartoframes
Once you’ve done this, cartoframes will be installed. See the example usage section below for using cartoframes in a Jupyter notebook.
Note: Eventually cartoframes will be fully installable from pip.
Example usage¶
Data workflow¶
Get table from carto, make changes in pandas, sync updates with carto:
df = pd.read_carto(username=username,
api_key=api_key,
tablename='brooklyn_poverty_census_tracts')
# do fancy pandas operations (add/drop columns, change values, etc.)
df['poverty_per_pop'] = df['poverty_count'] / df['total_population']
# updates carto table with all changes from this session
# show all database access with debug=True
df.sync_carto()
Associate an existing pandas dataframe with CARTO, and optionally get the geometry.
import pandas as pd
import cartoframes
import numpy as np
arr = np.arange(10)
np.random.shuffle(arr)
ingest = {'ids': list('abcdefghij'),
'scores': np.random.random(10),
'other_rank': arr,
'lat': 40.7128 + (0.5 - np.random.random(10)),
'lon': -74.0059 + (0.5 - np.random.random(10))}
df = pd.DataFrame(ingest)
df.sync_carto(username=USERNAME,
api_key=APIKEY,
requested_tablename='awesome_new_table',
createtable=True,
is_org_user=True,
latlng_cols=('lat', 'lon'))
Map workflow¶
The following will embed a CARTO map in a Jupyter notebook, allowing for custom styling of the maps driving by Turbo Carto and CartoColors.
df.carto_map(color={'colname': 'net', 'ramp': 'Bold'},
size={'colname': 'depth', 'min': 6, 'max': 20, 'quant_method': 'headtails'},
basemap='http://{s}.tile.thunderforest.com/spinal-map/{z}/{x}/{y}.png')
Augment from Data Observatory¶
Interact with CARTO’s Data Observatory:
# total pop, high school diploma (normalized), median income, poverty status (normalized)
# See Data Observatory catalog for codes: https://cartodb.github.io/bigmetadata/index.html
data_obs_measures = [{'numer_id': 'us.census.acs.B01003001'},
{'numer_id': 'us.census.acs.B15003017', 'denominator': 'predenominated'},
{'numer_id': 'us.census.acs.B19013001'},
{'numer_id': 'us.census.acs.B17001002', 'denominator': 'predenominated'}]
df.carto_do_augment(data_obs_measures)
df.head()
cartoframe methods¶
cartoframe methods¶
A pandas dataframe interface for working with CARTO maps and tables.
Andy Eschbacher and Stuart Lynn, 2017
- Project goals
- Interact with a CARTO table fully within a Jupyter notebook/pandas workflow (read and sync dataframe changes)
- Like geopandas, have a .carto_map() method which gives back the data as a map using carto’s maps api and TurboCartoCSS on an optional attribute
- Add CARTO services like the Data Observatory as methods to a dataframe
Features to add: see issues in the repository https://github.com/CartoDB/cartoframes/issues?q=is%3Aopen+is%3Aissue+label%3Aenhancement
-
core.
carto_create
(self, username, api_key, tablename, latlng_cols=None, is_org_user=False, debug=False)¶ Create and populate a table on carto with a dataframe. This is a private method, but can be used to create a new table on CARTO. It is used in carto_sync if a DataFrame is not yet linked to a CARTO table.
-
core.
carto_insync
(self)¶ Says whether current cartoframe is in sync with last saved state
-
core.
carto_map
(self, interactive=True, color=None, size=None, cartocss=None, basemap=None, figsize=(647, 400), debug=False)¶ Produce and return CARTO maps. Can be interactive or static.
Parameters: - interactive (boolean) – (optional) Value on whether to show an interactive map or static map
- color (dict, string) –
(optional)
- If color is a string, can be a column name or a hex value (beginning with a
#
). When a hex value, all geometries are colored the same. If the column name, use CARTO’s TurtoCarto to create qualitative or category mapping. - If color is a dict, parse the parameters to custom style the map. Values are:
- colname (required): column name to base the styling on
- ramp (optional): If text, type of color ramp to use. See https://github.com/CartoDB/CartoColor/blob/master/cartocolor.js for a full list. If list/tuple, set of hex values.
- ramp_provider (optional): Specify the source of the ramp (either cartocolor or colorbrewer)
- num_bins: Number of divisions for the ramp
- quant_method: Quantification method for dividing the data into classes. Options are jenks, quantiles, equal, or headtails. By choosing a custom ramp
- If color is a string, can be a column name or a hex value (beginning with a
- size (integer, string, dict) –
(optional) Only works with point geometries. A future version will allow more sizing options for lines.
- If size is an integer, all points are sized by the same value specified.
- If size is a column name, this option sizes points from a default minimum value of 4 pixels to 15 pixels.
- If size is a dict, size points by the following values if entered. Defaults will be used if they are not requested.
- colname: column to base the styling off of
- max: maximum marker width (default 15)
- min: minimum marker width (default 4)
- quant_method: type of quantification to use. Options are jenks, quantiles, equal, or headtails.
- cartocss (string) – Complete CartoCSS style to apply to your map. This will override size and color attributes if present.
- basemap (string) – (optional) XYZ URL template for the basemap. See https://leaflet-extras.github.io/leaflet-providers/preview/ for examples.
- figsize (tuple) – (optional) Tuple of dimensions (width, height) for output embed or image. Default is (647, 400).
Returns: an interactive or static CARTO map optionally styled
Return type: HTML embed
-
core.
carto_registered
(self)¶ Says whether dataframe is registered as a table on CARTO
-
core.
get_carto
(self, key)¶ General get method for reading from cartoframe metadata
Parameters: key (string) – key of item to fetch from metadata. One of carto_named_map, carto_geomtype, carto_username, carto_table. Returns: Value stored in cartoframe metadata Return type: any
-
core.
get_carto_api_key
(self)¶ return the username of a cartoframe :returns: CARTO API key associated with cartoframe :rtype: string
-
core.
get_carto_datapage
(self)¶ Return the CARTO dataset page
Returns: URL of data page of dataset on CARTO (behind password if private) Return type: string
-
core.
get_carto_geomtype
(self)¶ return the geometry type of the cartoframe
Returns: Geometry type in table
-
core.
get_carto_namedmap
(self)¶ Return the named map associated with a cartoframe
Returns: Name of named map Return type: string
-
core.
get_carto_sql_client
(self)¶ Returns: the internally stored sql client Return type: CARTO SQL Auth client object
-
core.
get_carto_tablename
(self)¶ return the username of a cartoframe
Returns: Table that cartoframe is associated with Return type: string
-
core.
get_carto_username
(self)¶ return the username of a cartoframe :returns: CARTO username associated with cartoframe :rtype: string
-
core.
make_cartoframe
(self, username, api_key, tablename, api_type=None)¶ Placeholder method (not functioning)
- instantiate sql client
- setup schema on carto
- ...
Parameters: - username (string) – CARTO username
- api_key (string) – CARTO API key
- tablename (string) – desired tablename
-
core.
read_carto
(username=None, api_key=None, onprem_url=None, tablename=None, query=None, include_geom=True, is_org_user=False, limit=None, cdb_client=None, index='cartodb_id', debug=False)¶ Create a DataFrame from a CARTO table, storing table information in pandas metadata that allows for further cartoframe options like syncing, map creation, and augmentation from the Data Observatory.
Parameters: - username (string) – CARTO username (default None)
- api_key (string) – CARTO API key
- onprem_url (string) – BASEURL for onprem
- tablename (string) – Table to create a cartoframe from
- query (string) – Query for generating a cartoframe
- include_geom (boolean) – Not implemented
- is_org_user (boolean) – (optional) Where username is in a multiuser account
- limit (integer) – (optional) The maximum number of rows to pull
- cdb_client (object) – (optional) CARTO Python SDK authentication client object (default None)
- index (string) – (optional) string Column to use for the index (default cartodb_id)
Returns: A pandas DataFrame linked to a CARTO table
Return type: cartoframe
-
core.
set_carto_sql_client
(self, sql_client)¶ Store the SQL client for later use
-
core.
set_last_state
(self)¶ Store the state of the cartoframe
-
core.
set_metadata
(self, tablename=None, username=None, api_key=None, include_geom=None, limit=None, geomtype=None, named_map_name=None)¶ Set method for storing metadata in a dataframe
Returns: None
-
core.
sync_carto
(self, username=None, api_key=None, requested_tablename=None, n_batch=20, latlng_cols=None, is_org_user=False, debug=False)¶ - If an existing cartoframe, this method syncs with the CARTO table a
- cartoframe is associated with. If syncing a DataFrame which has not yet been linked with CARTO, it creates a new table if the tablename does not yet exist and updates the metadata in the DataFrame.
Parameters: - username (string) – CARTO username credentials. Needed only if the DataFrame
is not yet linked to CARTO (e.g., it was created with
pd.DataFrame.read_carto
) - api_key (string) – CARTO API key. Needed only if linking a DataFrame with a table on CARTO.
- requested_tablename (string) – if set, creates a new table with name new_tablename on account connected through the auth_client. If this tablename exists on CARTO already, an exception will be thrown.
- n_batch (integer) – Number of queries to include in a batch update to the database (experimental).
- latlng_cols (tuple) – Columns which have the latitude and longitude (in that order) for creating the geometry in the database. Once this cartoframe syncs, a new column called the_geom will be pulled down that is a text representation of the geometry.
- is_org_user (boolean) – This flag needs to be set if a user is in a multiuser account.
Data Observatory methods¶
-
data_obs.
carto_do_augment
(self, cols_meta, add_geom_id=False, force_sync=False, debug=False)¶ Augment an existing cartoframe with Data Observatory 1. check inputs for conflicts 2. send request to augment carto table: https://gist.github.com/talos/50000ed856eb688c66b10d1054a9bcc6 3. pull down df with only the added columns (with index) 4. update self to add new columns
Parameters: - cols_meta (list of dicts) –
Data observatory measures. Each dict has the following keys:
numer_id
: measure ID from the Data Observatory catalog https://cartodb.github.io/bigmetadata/index.htmldenominator
(optional): if value ispredenominated
, then normalize by an appropriate valuegeom_id
(optional): geometry level to pull measure information from. TODO: add more to this
- add_geom_id – Not currently implemented
- force_sync – TODO param
- cols_meta (list of dicts) –
-
data_obs.
read_data_obs
(self, hints, debug=False)¶ Read metadata from the data observatory. Experimental Data Observatory exploratory tool
Parameters: hints – measure hints that we’re interested in Returns: summary of the metadata given hints
Return type: pandas.DataFrame


The sponsorship package is now available! [Updated 04/22/2019]
Interested in sponsoring to make an impact in the future generation of entrepreneurs and engineers? Contact us at
<EMAIL_ADDRESS>View Sponsorship Prospectus


Introduction¶
Unicorn
is a magical full-stack framework for Django. Instead of building additional API endpoints to provide website interactivity, Unicorn
provides the pieces of a modern website experience without moving away from all of the benefits of Django.
Unicorn
seamlessly extends Django past its server-side framework roots without giving up all of its niceties or re-building your website.


Web Developer Examples and Resources by Kate Baldwin
Welcome!
Within this website you will find several pages on research topics such as Accessibility, Social Media Optimization (SMO), and HTML Forms. Also included are some google tools, such as a map and calendar. And don't forget to check out the lightbox gallery!
To interview for a web job, thoughtfully contribute to a web team, and provide guidance for web clients, it's vital that we keep learning to stay on top of current and coming web topics and coding practices. Several ways developers can grow and maintain their web knowledge and skills are:
- Read magazines, blogs, reddit, books, or listen to podcasts.
- Go to events, conferences, or meetups.
- Participate in open source communities.
- Take additional courses.


Before Change
pdb.set_trace()
pdps = []
import functools
number_of_process = Pool(n_jobs)
for pd_row in number_of_process.map(functools.partial(compute_pd, model_fn=predict_fn,
grid_expanded=grid_expanded, number_of_classes=n_classes, feature_ids=feature_ids,
input_data=data_sample), [i for i in range(grid_expanded.shape[0])]):
pdps.append(pd_row)
After Change
n_classes = self._predict_fn.n_classes
pd_list = []
import functools
executor_instance = Pool(n_jobs) if n_jobs > 0 else Pool()
for pd_row in executor_instance.map(functools.partial(compute_pd, model_fn=predict_fn,
grid_expanded=grid_expanded, number_of_classes=n_classes, feature_ids=feature_ids,
input_data=data_sample), [i for i in range(grid_expanded.shape[0])]):


test compiled and minified CSS -->
Text and pictures are from https://wikipedia.org.
data-src
load when become visible.The Solar System is the gravitationally bound system comprising the Sun and the objects that orbit it, either directly or indirectly. Of those objects that orbit the Sun directly, the largest eight are the planets, with the remainder being significantly smaller objects, such as dwarf planets and small Solar System bodies. Of the objects that orbit the Sun indirectly, the moons, two are larger than the smallest planet, Mercury.
The Solar System formed 4.6 billion years ago from the gravitational collapse of a giant interstellar molecular cloud. The vast majority of the system's mass is in the Sun, with most of the remaining mass contained in Jupiter. The four smaller inner planets, Mercury, Venus, Earth and Mars, are terrestrial planets, being primarily composed of rock and metal. The four outer planets are giant planets, being substantially more massive than the terrestrials. The two largest, Jupiter and Saturn, are gas giants, being composed mainly of hydrogen and helium; the two outermost planets, Uranus and Neptune, are ice giants, being composed mostly of substances with relatively high melting points compared with hydrogen and helium, called volatiles, such as water, ammonia and methane. All planets have almost circular orbits that lie within a nearly flat disc called the ecliptic.
The Sun is the Solar System's star and by far its most massive component. Its large mass (332,900 Earth masses) produces temperatures and densities in its core high enough to sustain nuclear fusion of hydrogen into helium, making it a main-sequence star. This releases an enormous amount of energy, mostly radiated into space as electromagnetic radiation peaking in visible light.
Mercury (0.4 AU from the Sun) is the closest planet to the Sun and the smallest planet in the Solar System (0.055 Earth masses). Mercury has no natural satellites; besides impact craters, its only known geological features are lobed ridges or rupes that were probably produced by a period of contraction early in its history.[67] Mercury's very tenuous atmosphere consists of atoms blasted off its surface by the solar wind.[68] Its relatively large iron core and thin mantle have not yet been adequately explained. Hypotheses include that its outer layers were stripped off by a giant impact; or, that it was prevented from fully accreting by the young Sun's energy.
Venus (0.7 AU from the Sun) is close in size to Earth (0.815 Earth masses) and, like Earth, has a thick silicate mantle around an iron core, a substantial atmosphere, and evidence of internal geological activity. It is much drier than Earth, and its atmosphere is ninety times as dense. Venus has no natural satellites. It is the hottest planet, with surface temperatures over 400 °C (752°F), most likely due to the amount of greenhouse gases in the atmosphere. No definitive evidence of current geological activity has been detected on Venus, but it has no magnetic field that would prevent depletion of its substantial atmosphere, which suggests that its atmosphere is being replenished by volcanic eruptions.
Earth (1 AU from the Sun) is the largest and densest of the inner planets, the only one known to have current geological activity, and the only place where life is known to exist. Its liquid hydrosphere is unique among the terrestrial planets, and it is the only planet where plate tectonics has been observed. Earth's atmosphere is radically different from those of the other planets, having been altered by the presence of life to contain 21% free oxygen. It has one natural satellite, the Moon, the only large satellite of a terrestrial planet in the Solar System.
Mars (1.5 AU from the Sun) is smaller than Earth and Venus (0.107 Earth masses). It has an atmosphere of mostly carbon dioxide with a surface pressure of 6.1 millibars (roughly 0.6% of that of Earth). Its surface, peppered with vast volcanoes, such as Olympus Mons, and rift valleys, such as Valles Marineris, shows geological activity that may have persisted until as recently as 2 million years ago. Its red colour comes from iron oxide (rust) in its soil. Mars has two tiny natural satellites (Deimos and Phobos) thought to be captured asteroids.
Jupiter (5.2 AU), at 318 Earth masses, is 2.5 times the mass of all the other planets put together. It is composed largely of hydrogen and helium. Jupiter's strong internal heat creates semi-permanent features in its atmosphere, such as cloud bands and the Great Red Spot. Jupiter has 67 known satellites. The four largest, Ganymede, Callisto, Io, and Europa, show similarities to the terrestrial planets, such as volcanism and internal heating. Ganymede, the largest satellite in the Solar System, is larger than Mercury.
Saturn (9.5 AU), distinguished by its extensive ring system, has several similarities to Jupiter, such as its atmospheric composition and magnetosphere. Although Saturn has 60% of Jupiter's volume, it is less than a third as massive, at 95 Earth masses. Saturn is the only planet of the Solar System that is less dense than water. The rings of Saturn are made up of small ice and rock particles. Saturn has 62 confirmed satellites composed largely of ice. Two of these, Titan and Enceladus, show signs of geological activity. Titan, the second-largest moon in the Solar System, is larger than Mercury and the only satellite in the Solar System with a substantial atmosphere.
Uranus (19.2 AU), at 14 Earth masses, is the lightest of the outer planets. Uniquely among the planets, it orbits the Sun on its side; its axial tilt is over ninety degrees to the ecliptic. It has a much colder core than the other giant planets and radiates very little heat into space. Uranus has 27 known satellites, the largest ones being Titania, Oberon, Umbriel, Ariel, and Miranda.
Neptune (30.1 AU), though slightly smaller than Uranus, is more massive (equivalent to 17 Earths) and hence more dense. It radiates more internal heat, but not as much as Jupiter or Saturn. Neptune has 14 known satellites. The largest, Triton, is geologically active, with geysers of liquid nitrogen. Triton is the only large satellite with a retrograde orbit. Neptune is accompanied in its orbit by several minor planets, termed Neptune trojans, that are in 1:1 resonance with it.


Metals — one of the most common materials used by civilization throughout virtually all of its history.
Metals — a group of elements in the form of simple substances with characteristic metallic properties, such as high thermal and electrical conductivity, a positive temperature coefficient of resistance, high plasticity and metallic luster.
Of the 118 chemical elements that are currently open (of which not all are officially recognized), metals are:
6 elements in the group of alkali metals,
6 in the group of alkaline earth metals,
38 in the group of transition metals,
11 in the group of light metals,
7 in the group of semimetals,
14 in the group of lanthanides + lanthanum,
14 in the actinide group (physical properties not studied for all elements) + anemones,
outside certain groups of beryllium and magnesium.
Being in nature
Most of the metals are present in nature in the form of ores and compounds. They form oxides, sulphides, carbonates and other chemical compounds. For the production of pure metals and their further application, it is necessary to separate them from ores and carry out purification. If necessary, doping and other processing of metals. The study of this is the science of metallurgy. Metallurgy distinguishes ores of ferrous metals (based on iron) and non-ferrous (iron does not include them, only about 70 elements). Gold, silver and platinum also belong to precious (noble) metals. In addition, in small quantities they are present in sea water, plants, living organisms (playing an important role in this).
It is known that the human body is 3% composed of metals. Most of all in our cells of calcium and sodium, concentrated in the lymphatic systems. Magnesium accumulates in the muscles and nervous system, copper in the liver, iron in the blood.
Extraction
Metals are often extracted from the earth by means of mining, the result - mined ore - serves as a relatively rich source of necessary elements. To determine the location of ores, special search methods are used, including exploration of ores and exploration of deposits. Deposits, as a rule, are divided into quarries (development of ores on the surface), in which mining is conducted by extracting soil using heavy equipment, as well as underground mines.
From extracted ore metals are recovered, usually by chemical or electrolytic reduction. In pyrometallurgy, high temperatures are used to convert ore into metallic raw materials, hydrometallurgy uses water chemistry for the same purposes. The methods used depend on the type of metal and the type of contamination.
When metal ore is an ionic compound of a metal and a nonmetal, to extract a pure metal, it is usually melted-heating with a reducing agent. Many common metals, such as iron, are melted using carbon (derived from coal combustion) as a reducing agent. Some metals, such as aluminum and sodium, do not have any economically feasible reductant and are extracted using electrolysis.
Sulfide ores do not improve immediately to produce pure metal, but are fired in air, to convert them to oxides.
Thus, to metals, perhaps, there are 96 elements from all open.
Physical properties and structure of metals
The melting points of pure metals lie in the range from -39 ° C (mercury) to 3410 ° C (tungsten). The melting point of most metals (except for alkaline metals) is high, but some "normal" metals, for example, tin and lead, can be melted on a conventional electric or gas stove.
Depending on the density, metals are divided into light (density 0.53 ÷ 5 g / cm³) and heavy (5 ÷ 22.5 g / cm³). The lightest metal is lithium (density 0.53 g / cm³). The heaviest metal is currently impossible to name, since the densities of osmium and iridium - the two heaviest metals - are almost equal (about 22.6 g / cm³ - exactly twice the density of lead), and calculate their exact density is extremely difficult: this requires completely clean metals, because any impurities reduce their density.
Most metals are plastic, that is, the metal wire can be bent and it will not break. This is due to the displacement of the layers of metal atoms without breaking the bond between them. The most plastic are gold, silver and copper. Of gold, you can make a foil thickness of 0.003 mm, which is used for gilding products. However, not all metals are plastic. Wire from zinc or tin crunches when bent; manganese and bismuth under deformation in general almost do not bend, but immediately break down. Plasticity depends on the purity of the metal; So, very pure chrome is very plastic, but, contaminated even with minor impurities, it becomes brittle and harder. Some metals, such as gold, silver, lead, aluminum, osmium, can coalesce with each other, but this can take decades.
All metals conduct electricity well; this is due to the presence in their crystal lattices of mobile electrons moving under the action of the electric field. Silver, copper and aluminum have the greatest electrical conductivity; for this reason the last two metals are most often used as a material for wires. Very high electrical conductivity has also sodium, attempts have been made in the experimental apparatus to use sodium conductors in the form of thin-walled stainless steel tubes filled with sodium. Due to the low specific gravity of sodium, with equal resistance, sodium "wires" are much lighter than copper wires and even slightly lighter than aluminum ones.
The high thermal conductivity of metals also depends on the mobility of free electrons. Therefore, a number of thermal conductivities are similar to a series of electrical conductivities, and silver is the best conductor of heat, as well as electricity. Sodium also finds use as a good conductor of heat; It is widely known, for example, the use of sodium in valves of automobile engines to improve their cooling.
Chemical properties
At the external electronic level, most metals have a small number of electrons (1-3), so in most reactions they act as restorers (that is, "give up" their electrons)
Reactions with simple substances
- All metals except oxygen and platinum metals react with oxygen. The reaction with silver occurs at high temperatures, but silver (II) oxide is practically not formed, since it is thermally unstable. Depending on the metal, oxides, peroxides, and perperoxides may appear at the outlet:
4Li+O2 → 2Li2O - sodium oxide
2Na+O2 → Na2O2 - sodium peroxide
-
Only the most active metals react with nitrogen, only lithium reacts at room temperature, forming nitrides:
6Li+N2 → 2Li3N
-
With sulfur react all metals except gold and platinum:
Fe+S → FeS
-
Only the most active metals react with carbon. In this case, acetylenides or methanides are formed. Acetylenides in the interaction with water give acetylene, methanides - methane.
2Na+2C → NasC2
Application of metals
Since the properties of nonmetals are extremely diverse, these substances find wide application in various branches of the national economy.
- Construction materials:
Nonmetals such as sulfur, nitrogen, phosphorus and chlorine are used as raw materials for the production of acids and other products.
Metals and their alloys are one of the main constructional materials of modern civilization. This is determined, above all, by their high strength, uniformity and impermeability for liquids and gases. In addition, changing the formulation of alloys, you can change their properties in a very wide range.
- Electrotechnical materials:
Metals are used as good conductors of electricity (copper, aluminum), and as materials with increased resistance for resistors and electric heating elements (nichrome, etc.).
- Tool materials:
Metals and their alloys are widely used for the manufacture of tools (their working part). Basically, these are tool steels and hard alloys. Diamond tools, boron nitride and ceramics are also used as instrumental materials.


Learn more
So, you are interested to find out what's hiding behind the web site, which kind of technologies were used to build up these pages, what processes and procedures were used to manage and maintain the solution and much more? So let's dive in under the hood and have a fun to discover those secrets.
First of all you mustn't realize that procedure which were used here in the project cannot fit as a generic solution for another project, you may be inspire by it but every project is unique and have a differences which could be against my solution.
Architecture
At first for the seek of simplicity were used VMMV javascript framework Knockout to have simple VM control and basic data binding. But over time it turns out that such as simple library isn't as progressive as chosen framework which is Angular. Thanks of many desired features and excellent modularity it won my private competition.
So first things first
Because there isn't any need to have a dynamic data consumed from beck-end site I have decided to have a simple javascript object literal as a data source loaded asynchronously.
Once there is solution for back-end let's start with the front-end solution which is a little bit progressive. I will make a short list of all front-end technologies and processes to have overview about the solution, but some not so interesting techniques will be omitted.
-
Design
At first I've created several wireframes and layouts and as a result I used those materials as a inspiration for static layout created in graphics application.
-
Project Bootstrap
In order to setup the project a several tools were used to have initial process as simple as possible. Here is the short example of used tools:
- Bower packaging tools to boilerplate or initial setup of vendor libraries e.g. jQuery, angular, twiter bootstrap.
- Grunt tasker tools to be able to clen, concat, deploy, uglify and execute those steps to managing project. Additional packages for Gurunt where were useful:
- grunt-processhtml
- grunt-contrib-uglify
- grunt-contrib-clean
- grunt-contrib-concat
- grunt-contrib-copy
- and much more
-
CSS styling
Preprocessor sass together with compass where useful to boost performance and efficiency of page styling. I have also take advantage of source map in order to integrate with chrome developer tools to have ability watch live changes of .sass files and transform it to css files on the fly.
-
Angular as a core framework has advantage to use all common techniques a processes like controllers, directives, services to have excellent logic and file organization over a project. Integration with extensions:
- angular-bootstrap
- angular-resource
-
Build process
Finally here is describe a little bit more about final process of deployment to production environment. Also a few future improvement steps which are considered to be important to a project.
Development to production envirinment consist of several steps before a folder package can be transported to the server. I'll descripe some of them:- clean up old package to be certain all previous files are wiped out
- upload all necessary files e.g. images, fonts etc. to final package
- merge css,js into one single file in order to minimize server requests
- alter html files to respect server restriction
- decrease main javascript and css file size by minifying process
After those steps are the folder package ready to go to production environment.
A one word about improvement process. I am going to analyze and identify the solution to expose critical path of resources and alter solution to be able to have page load under 1000 ms for best UX on mobile devices. Also page preload and asynchronous content consuming will be implement. -
Final words
The overall process may seems to be complicated but thanks the process of automations is any even small changes of project easy to be reflected to production environment. And even more there is almost eliminated possibility of error or forgotten step in development process.


Salt and Pepper
Running native code in the browser with NaCl
Christian Speckner, Mayflower GmbH
Native code in the browser
—
Why on earth?
Computing in the eighties...


What's a token?
- Blockchains have a native coin/token that the chain is built with. These coins/tokens are required to execute transactions, send data, are rewards for mining, etc.
- But it may be possible to encode additional metadata in the chain which represents a token.
- Depending on the chain, this can be easy or hard.
Why use tokens?
- Say you want to issue share of stocks to the many co-founders (different percentages) for your new startup company that is yet to be registered
- In the Ethereum world, you can represent the shares in the form of “tokens” that can be sold, sold back to the company, transferred, etc.
- You can create a “token contract” and deploy it in Ethereum blockchain
- Then the tokens can be transferred, sold, etc.
EOS
- “Ethereum-killer” new Blockchain.
- Launched a year-long open ICO - basically a pre-sale.
- They will used the balances on the ERC20 as a starting balance on their own chain.
- “The EOS Tokens do not have any rights, uses, purpose, attributes, functionalities or features, express or implied, including, without limitation, any uses, purpose, attributes, functionalities or features on the EOS Platform.”
AUGUR
- Decentralized Prediction Market
- The REP ERC20 token is used as their internal currency for determining the truth.
- People ‘vote’ with their REP on what actually happened.
- Aside: Oracles are hard.
OMISEGO
- Payments Platform, decentralized exchange, etc.
- Supposedly cross-chain.
- White-label business tokens.
BAT - Basic Attention Token
- A token for paying web creators. Integrates with the Brave browser.
- Basically a use-constrained currency. Get paid to view ads, pay content producers, content producers sell tokens to advertisers.
- Classic disclaimer - “BAT is not a digital currency, it is a utility token.“
NFT Landscape
NFT Landscape : Publishers (Game)
- Cryptofighters
- Cryptokitties
- Decentraland
- Etherbots
- Ethermon
- Rare peppes
- Spells of Genesis
NFT Landscape : Publishers (Non-Game)
- Crafty
- Superrare
- Terra0
- Unico
NFT Landscape : Marketplaces
- OpenBazaar
- Opensea
- OpSkins
- Rarebits
NFT Landscape : Infrastructure
- Oxcert.org
- Bitcrystals
- Codex Protocol
- Counterparty
- Ethereum
- Fanbits
- Metamask
- Mokens
- Userfeeds
- Wax
- ZeppelinOS


James Holzhauer Wins The 2019 ‘Jeopardy!’ Tournament Of Champions
by Jamie SamhanJames Holzhauer first came onto the radar back in June when he won 32 games in a row on “Jeopardy!”, but now he has an even bigger title under his belt.
Holzhauer, 35, won the 2019 “Jeopardy!” Tournament of Champions after starting off with only $30,000. He rose to the occasion and ended up winning the $250,000 grand prize which brings his total winnings for the game show to $2,712,216.
Emma Boettcher (the contestant who ended Holzhauer’s streak) came in second for the $100,000 prize and Francois Barcomb walked away with $50,000.
“I’ve said all along that Emma is an all-time great player, and I’m proud it took that level of competitor to defeat me,” Holzhauer said in reference to their previous meeting. “Now the world sees that I wasn’t just making excuses. Francois certainly looked as dominant as either of us in his first two games, so I knew the finals would be a fight to the finish. But the whole point of the TOC is to play the best of the best, and Emma and Francois certainly proved that they belonged in the final three.”
And while $2.7 million is a lot to win from a game show, Holzhauer isn’t the highest “Jeopardy!” winner. Ken Jenning’s has won $3,370,700 and Brad Rutter an astonishing $4,688,436, both who took part in the All-Star game that was in March.


{{ 499 | currency:'INR'}}{{ 1499 | currency:'INR'}}54 % off
1 Offer AvailableFree delievery in 6-9 days
MOVE TO WISHLIST
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{{ 499 | currency:'INR'}}{{ 1499 | currency:'INR'}}54 % off
1 Offer AvailableFree delievery in 6-9 days
MOVE TO WISHLIST
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PRICE DETAILS
Price(1 item)
Delievery
{{ 499 | currency:'INR'}}
Free
View Price Details


--- title: Rendering Code Snippets on a Static Website ---
Rendering code in a pleasing format on a webpage - including bells and whistles like line numbers and syntax highlighting - is an easy thing to take for granted after spending a lot of time with Markdown renderers like the one GitHub offers. But bringing the same capability over to a static webpage with no "help" from outside scripts or compilers, is not trivial. Making the following appear took a little bit of work:
#include <iostream>
int main() {
std::cout << "Hello World" << std::endl;
}
What goes into rendering this?
<
, and every > must be rewritten as >
.

and

tags for designating code blocks and rendering them with the desired whitespace,
no syntax highlighting is provided (not that one would expect HTML to do it, but
it's now become standard practice for code presented online. To color the text above,
Google's code-prettify script
was used. But if one wanted the code to render In Full Color without any on-load
rerendering, one would have to add
tags with the desired
colors or syntax, throughout the code sample. (This is what the Google script
is actually doing - it just does it after the page is loaded!)
Neither of the above is a huge problem - but it conflicts with two things that some people might be after:

tags beforehand
I'd previously thought there was a lot of craft in writing HTML code from scratch, and that it was the way to go for constructing a static website. "Compiling" HTML was only really worth the extra infrastructure for running a dynamic website. I am now convinced of the opposite: even for small static websites, it probably makes more sense to handle things like code inclusion and highlighting (as well as things like using the same header and footer across different pages) by using a templating engine (or some other tool that assembles the HTML for you.) That is the subject of this page.


This is the decsciption of the image
This is the decsciption of the image
This is the decsciption of the image
This is the decsciption of the image
This is the decsciption of the image
This is the decsciption of the image
This is the decsciption of the image
This is the decsciption of the image
This is the decsciption of the image


Mermaid diagram generator
r
to refresh this page to reload source from clipboard.
i
or
<Ctrl-Alt-d>
to open vim editor to edit source.
fh
to set handwriting font.
fn
to set normal font.
yy
to generate image.


First Name *
Email *
Gender
Profile Picture
Upload Picture
Last Name *
Date of Birth
Phone Number
Address Line 1 *
City *
ZipCode *
Address Line 2
State *
Country *
University
College


The new watch is going to blow your socks off. Some people like apple. I like Moto! There a new dog in town. Or Moto.


Person_of_Interest
You are being watched. The government has a secret system, a machine that spies on you every hour of every day. I know because I built it. I designed the Machine to detect acts of terror but it sees everything. Violent crimes involving ordinary people. People like you. Crimes the government considered "irrelevant". They wouldn't act so I decided I would. But I needed a partner. Someone with the skills to intervene. Hunted by the authorities, we work in secret. You'll never find us. But victim or perpetrator, if your number is up, we'll find you.


This survey form is created as a part of the Responsive web design course on Freecodecamp
Choose your gender
Which of following Online shopping platforms do you use?
Feel free to give suggestions


Study probes relationship between strange metals and high-temperature superconductors
Computer simulations yield a much more accurate picture of these states of matter
| Source: | DOE/SLAC National Accelerator Laboratory |
| Summary: | Theorists have observed strange metallicity in a well-known model for simulating the behavior of materials with strongly correlated electrons, which join forces to produce unexpected phenomena rather than acting independently. Their work provides a foundation for connecting theories of strange metals to models of superconductors and other strongly correlated materials. |
Strange metals make interesting bedfellows for a phenomenon known as high-temperature superconductivity, which allows materials to carry electricity with zero loss.
Both are rule-breakers.  For their part, high-temperature superconductors operate at much higher temperatures than conventional superconductors; how they do this is still unknown.
In many high-temperature superconductors, changing the temperature or the number of free-flowing electrons in the material can flip it from a superconducting state to a strange metal state or vice versa.
Scientists are trying to find out how these states are related, part of a 30-year quest to understand how high-temperature superconductors work so they can be developed for a host of potential applications, from maglev trains to perfectly efficient power transmission lines.
In a paper published today in Science, theorists with the Stanford Institute for Materials and Energy Sciences (SIMES) at the Department of Energy's SLAC National Accelerator Laboratory report that they have observed strange metallicity in the Hubbard model. This is a longstanding model for simulating and describing the behavior of materials with strongly correlated electrons, meaning that the electrons join forces to produce unexpected phenomena rather than acting independently.
Although the Hubbard model has been studied for decades, with some hints of strange metallic behavior, this was the first time strange metallicity had been seen in Monte Carlo simulations, in which billions of separate and slightly different calculations are averaged to produce an unbiased result. This is important because the physics of these systems can change drastically and without warning if any approximations are introduced.
The SIMES team was also able to observe strange metallicity at the lowest temperatures ever explored with an unbiased method — temperatures at which the conclusions from their simulations are much more relevant for experiments.
The scientists said their work provides a foundation for connecting theories of strange metals to models of superconductors and other strongly correlated materials.
make a difference: sponsored opportunity
Story Source:
Materials provided by DOE/SLAC National Accelerator Laboratory.
Note: Content may be edited for style and length.
Journal Reference:
- Edwin Huang et al. Strange metallicity in the doped Hubbard model. Science, 2019 DOI: 10.1126/science.aau7063
Cite This Page:
| MLA | DOE/SLAC National Accelerator Laboratory. "Study probes relationship between strange metals and high-temperature superconductors: Computer simulations yield a much more accurate picture of these states of matter." ScienceDaily. ScienceDaily, 21 November 2019. <www.sciencedaily.com/releases/2019/11/191121151209.htm>. |
| APA | DOE/SLAC National Accelerator Laboratory. (2019, November 21). Study probes relationship between strange metals and high-temperature superconductors: Computer simulations yield a much more accurate picture of these states of matter. ScienceDaily. Retrieved November 21, 2019 from www.sciencedaily.com/releases/2019/11/191121151209.htm |
| Chicago | DOE/SLAC National Accelerator Laboratory. "Study probes relationship between strange metals and high-temperature superconductors: Computer simulations yield a much more accurate picture of these states of matter." ScienceDaily. www.sciencedaily.com/releases/2019/11/191121151209.htm (accessed November 21, 2019). |


{% extends "_post.html" %}
{% hyde
title: "Candy Colored Terminal"
snip: "Better colors for the OS X Terminal."
created: 2009-03-18 18:26:28
flattr: true
%}
{% block article %}
Yesterday I wrote a blog post about [adding Mercurial information to your bash
prompt](/blog/entry/2009/3/17/mercurial-bash-prompts/). Almost all of the
comments on that entry so far have been asking for the colors I used in the
Terminal screenshots, so that's what this post is for.
The first section of this entry will be able overcoming the limitations of the
OS X Terminal application. Skip it if you're using another (better) terminal
application.
The OS X Terminal and Colors
----------------------------
OS X's Terminal doesn't support 256-color mode. I have no idea why. Apple, if
you're reading, *please fix this*. Because of this, if you want to make the
colors prettier you've only got the 16 ANSI colors to work with.
Once again, Apple fails hard with Terminal.app. You can't change the 16 ANSI
colors -- you can only change the default text color and background.

To fix this, you'll need to install [SIMBL][] and [TerminalColors][]. Follow
the instructions on those pages and be sure to restart Terminal once you've
finished. Now you can change the ANSI colors be hitting the "More" button
under the text color settings.
[SIMBL]: http://www.culater.net/software/SIMBL/SIMBL.php
[TerminalColors]: http://ciaranwal.sh/2007/11/01/customising-colours-in-leopard-terminal
Picking Some Colors
-------------------
Now that we've beaten Terminal.app into compliance, it's time to pick some
pretty colors. I love the [Monokai][] color scheme for [TextMate][] and so I
based my choices on that. Here's what it looks like:
![Screenshot of my Terminal, with colors.](/media/images{{parent_url}}/terminal-colors.png "My Terminal colors.")
[Monokai]: http://www.monokai.nl/blog/2006/07/15/textmate-color-theme/
[TextMate]: http://macromates.com/
Here are the RGB values I'm using:
* Black: 0, 0, 0
* Red: 229, 34, 34
* Green: 166, 227, 45
* Yellow: 252, 149, 30
* Blue: 196, 141, 255
* Magenta: 250, 37, 115
* Cyan: 103, 217, 240
* White: 242, 242, 242
The window background is just set to plain old 0, 0, 0 with a 95% opacity.
Not all of the colors match the names: "blue" is actually more of a purple,
and "yellow" is much more orange. That doesn't really matter much though
because they're different enough from each other to still be useful.
Now that the colors are set up you can use them in the normal way. Check out
[this guide][] if you don't know how to do that. Here's the full code for my
bash prompt:
**UPDATE:** I've cleaned up the code a lot thanks to the kind folks in #bash
on freenode who helped set me straight on bash quoting and escaping. I've also
switched to using my [hg-prompt extension](/projects/hg-prompt/) for the
repository information.
[this guide]: http://www.ibm.com/developerworks/linux/library/l-tip-prompt/
:::bash
D=$'\e[37;40m'
PINK=$'\e[35;40m'
GREEN=$'\e[32;40m'
ORANGE=$'\e[33;40m'
hg_ps1() {
hg prompt "{${D} on ${PINK}{branch}}{${D} at ${ORANGE}{bookmark}}{${GREEN}{status}}" 2> /dev/null
}
export PS1='\n${PINK}\u ${D}at ${ORANGE}\h ${D}in ${GREEN}\w$(hg_ps1)\
${D}\n$ '
I hope this helps! If you'd like to share your color schemes or tell me how to
make the code for my prompt a bit less ugly, please find me on [Twitter][twsl]!
[twsl]: {{links.twsl}}
{% endblock %}


| filehandle/stream = a valid variable set with the OpenFile, ReadFile command, or OpenTCPStream (v1.52+) |
|
Checks to see if the End of File of an opened file or stream has been reached. Use this to determine if you should continue to pull more information from a file/stream or not. Use this to read a text file of unknown length (say a README.TXT) and display it. See example.
Eof returns 1 if eof has been reached or, in the case of a TCP stream, the stream has been 'nicely' closed. Eof returns -1 if something has gone wrong during stream processing. Streams can only be used in Blitz Basic v1.52 or greater. |
|
; Eof sample
file$="c:autoexec.bat" filein = ReadFile(file$) Print "Here is your Autoexec.bat file ..." ; Loop this until we reach the end of file While Not Eof(filein) Print ReadLine$(filein) Wend |


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ISTecnico
Open source projects driven by the IST community
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Seat and back with upholstery made of cold cure foam. Steel frame, available in matt powder-coated black or highly polished chrome.
Exclusive
Seat and back with upholstery made of cold cure foam. Steel frame, available in matt.