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Take the time to prevent heart disease
Statement from Secretary Sebelius on American Heart Month
Crosspost from HHS.gov
February is American Heart Month; a month to spread awareness about the importance of heart health. Each year, countless American families are impacted by heart disease and stroke. Although its risk factors can be prevented or controlled, it is still the leading cause of death for all Americans, and accounts for $1 out of every $6 dollars spent on health care. Fortunately, there are many simple steps we can take to prevent heart disease such as eating healthy foods, exercising regularly, and not smoking.
The Department of Health and Human Services is working with both public and private partners to raise awareness of heart disease through vital research investments and public health programs. The Million Hearts Initiative takes aim at this disease, with a goal of preventing 1 million heart attacks and strokes over the next 5 years. Other efforts, like the HeartTruth, which addresses women’s heart health, and the First Lady’s Let’s Move! initiative, which confronts childhood obesity by helping children choose healthy foods and stay active, work to provide people with resources and ways to make heart healthy changes in their everyday lives .
And thanks to the new health care law, the Affordable Care Act, new health plans must now cover recommended preventive services, including blood pressure screening for all adults and cholesterol screening for adults of certain ages or at higher risk, cost-free.
This month, as we take time to educate ourselves about the risks of heart disease, and recognize the efforts of medical researchers and healthcare professionals dedicated to prevention, early detection, and effective treatment, consider what steps you and your family can take to promote and adopt a heart healthy lifestyle.
For more information on American Heart Month, please visit: http://millionhearts.hhs.gov/index.html
For more information on women and heart disease, please visit: http://www.nhlbi.nih.gov/educational/hearttruth/ or http://womenshealth.gov/heartattack/ .
To learn more about the First Lady’s Let’s Move campaign, please visit: http://www.letsmove.gov/


Scatter is out next week! [$, promoted]
by Dorian BorremansDB3D writes:
Hello everyone.
I'm happy to say that Scatter, a new addon that aim at revolutionize the current scattering workflow of blender 2.8, is out the 29 november (Next Friday !) during Blender Market sales !
Featuring:
● One click to set up photorealistic biomes (tons of biomes are bundled with the addon)
● One click to set up particle-systems based on different types of presets.
● A brand new proxy system.
● Camera clipping/culling optimization.
● Easy paths creation with bezier-curves.
● An easy multilayer painting workflow.
● An Efficient and easy to access tweaking tab (featuring particles per m²/km²)
● An advance (batch) automatisation workflow.
● Security features that prevent you from crashing your session.
● A series of youtube tutorials.
For more infos check out the Scatter Blender Artists main thread and my Twitter account.


Profile
Friends
Additional Information
Additional information about Victor
Studied at
Sofia University
Born in Sofia
Lives in Sofia
Worked at
Tokheim


---
layout: archive
title: Lean Prover Zulip Chat Archive
permalink: 219941MachineLearningforTheoremProving/23859AITP2020.html
---
The archive URL format has changed. Please find this page at:
https://leanprover-community.github.io/archive/stream/219941-Machine-Learning-for-Theorem-Proving/topic/AITP.202020.html


16 #include "../../definitions.h"
17 #include "../../memory.h"
31 *list = (*list)->
next;
50 if(element->
data != 0){
72 while(element->next != 0){
73 element = element->next;
It declares functions to manage the I2C queue.
It is a single linked list element containing messages that need to be sent via I2C. This list acts as a message buffer.
sys_i2c_messages * sys_i2c_msgs
void Sys_I2C_FreeMessages(sys_i2c_messages *list)
void Sys_I2C_AppendMessages(sys_i2c_msg *item)
void Sys_I2C_RemoveOldestMessage(sys_i2c_messages **list)
void Sys_Free(void *data)
struct sys_i2c_message_s * next


Ploror688.github.io
Reddit tifu by doing my homework Participating in activities, stop in each Tuesday night to show off your Potter knowledge and earn house points! For all your trivia, see the live house points. Rick Astley - Never Gonna Give You Up (Official Music Video) - Listen On Spotify: it/AstleySpotify Learn more about the brand new album. During this time, you can learn what they are and how to use them by reading our wiki. Eliminate grammatical mistakes, as the wiki can be a pain to access Tifu by doing my homework on time. Stuck on homework is good or bad statistics? Tifu by doing my homework on time. September 11, 2018 / 0 Comments / in Uncategorized. My car was deemed a total loss.insurance company paid my financial institution Personal statement for english literature and creative.
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Reddit tifu by doing my homework on time - unlimitedpuebla.com. ALEKS is basically just to make sure that there isn't a moment in life when you're not feeling stressed. In my school, we have to do 4 topics every day, which builds. TIFU by doing my homework - reddit.com.
Just found out I am the lowest-paid employee Reddit gives you the best of the internet in one place. Get a constantly updating feed of breaking news, fun stories, pics, memes, and videos just for you. Passionate.
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Rick Astley - Never Gonna Give You Up (Video) - YouTube.


The Particle Renderer renders the Particle System on screen.
| Property: | Function: |
|---|---|
| Cast Shadows | If enabled, this allows the Mesh to cast shadows. |
| Receive Shadows | If enabled, this allows the Mesh to receive shadows. |
| Motion Vectors | If enabled, the line has motion vectors rendered into the Camera motion vector Texture. See Renderer.motionVectors in the Scripting API reference documentation to learn more. |
| Materials | Reference to a list of Materials that are displayed in the position of each individual particle. |
| Light Probes | Probe-based lighting interpolation mode. |
| Reflection Probes | If enabled and reflection probes are present in the Scene, a reflection Texture is picked for this Particle Renderer and set as a built-in Shader uniform variable. |
| Probe Anchor | If defined (using a GameObject), the Renderer uses this GameObject’s position to find the interpolated Light Probe. |
| Camera Velocity Scale | The amount of stretching that is applied to the Particles based on Camera movement. |
| Stretch Particles | Determines how the particles are rendered: |
| Billboard | The particles are rendered as if facing the Camera. |
| Stretched | The particles are facing the direction they are moving. |
| SortedBillboard | The particles are sorted by depth. Use this when using a blending Material. |
| VerticalBillboard | All particles are aligned flat along the X/Z axes. |
| HorizontalBillboard | All particles are aligned flat along the X/Y axes. |
| Length Scale | If Stretch Particles is set to Stretched, this value determines how long the particles are in their direction of motion. |
| Velocity Scale | If Stretch Particles is set to Stretched, this value determines the rate at which particles are stretched, based on their movement speed. |
| UV Animation | If X, Y or both are defined, the UV coordinates of the particles are generated for use with a tile animated texture. See Animated Textures, below. |
| X Tile | Number of frames located across the X axis. |
| Y Tile | Number of frames located across the Y axis. |
| Cycles | How many times to loop the animation sequence. |
Particle Renderers are required for any Particle System to be displayed on the screen.
When setting up a Particle Renderer, it is very important to use an appropriate Material and Shader that renders both sides of the Material. Unity recommends using Particle Shaders with the Particle Renderer.; most of the time you can simply use a Material with one of the built-in Particle Shaders. There are some premade Materials in the Standard Assets > Particles > Sources folder that you can use.
Creating a new Material is easy:
Note that different Shaders use the alpha channel of the Textures slightly differently, but most of the time a value of black in the alpha channel makes it invisible, and a value of white displays it on screen.
By default, particles are rendered billboarded (that is, as simple square sprites). This is useful for smoke, explosions, and most other particle effects. See Billboard Renderer for more information.
Particles can be made to stretch with the velocity. Length Scale and Velocity Scale affects how long the stretched particle is. This is useful for effects like sparks, lightning or laser beams.
Sorted Billboard can be used to make all particles sort by depth. Sometimes this is necessary, mostly when using Alpha Blended particle shaders. This can be resource-demanding and affect performance; it should only be used if it makes a significant quality difference when rendering.
Particle Systems can be rendered with an animated tile Texture. To use this feature, make the Texture out of a grid of images. As the particles go through their life cycle, they cycle through the images. This is good for adding more life to your particles, or making small rotating debris pieces.


Reports any
catch
block where the caught exception is immediately rethrown, without performing any action on it. Such
catch
blocks are unnecessary or lack error handling.
Powered by InspectionGadgets


Ruby Mills Standalone September 2019 Net Sales at Rs 47.97 crore, up 1.38% Y-o-Y
Reported Standalone quarterly numbers for Ruby Mills are:
Net Sales at Rs 47.97 crore in September 2019 up 1.38% from Rs. 47.31 crore in September 2018.
Quarterly Net Profit at Rs. 6.96 crore in September 2019 up 32.14% from Rs. 5.27 crore in September 2018.
EBITDA stands at Rs. 14.99 crore in September 2019 up 11.62% from Rs. 13.43 crore in September 2018.
Ruby Mills EPS has increased to Rs. 4.16 in September 2019 from Rs. 3.15 in September 2018.
Ruby Mills shares closed at 192.00 on November 11, 2019 (NSE) and has given -22.97% returns over the last 6 months and -25.68% over the last 12 months.
| Ruby Mills | |
| Standalone Quarterly Results | in Rs. Cr. |
| Sep'19 | Jun'19 | Sep'18 | |
| Net Sales/Income from operations | 47.97 | 41.27 | 47.31 |
| Other Operating Income | -- | -- | -- |
| Total Income From Operations | 47.97 | 41.27 | 47.31 |
| EXPENDITURE | |||
| Consumption of Raw Materials | 12.89 | 14.44 | 13.65 |
| Purchase of Traded Goods | -- | -- | -- |
| Increase/Decrease in Stocks | -1.66 | -3.07 | -3.88 |
| Power & Fuel | -- | -- | -- |
| Employees Cost | 5.55 | 5.30 | 5.76 |
| Depreciation | 2.93 | 2.89 | 3.36 |
| Excise Duty | -- | -- | -- |
| Admin. And Selling Expenses | -- | -- | -- |
| R & D Expenses | -- | -- | -- |
| Provisions And Contingencies | -- | -- | -- |
| Exp. Capitalised | -- | -- | -- |
| Other Expenses | 17.95 | 16.34 | 20.10 |
| P/L Before Other Inc. , Int., Excpt. Items & Tax | 10.30 | 5.37 | 8.32 |
| Other Income | 1.76 | 1.77 | 1.75 |
| P/L Before Int., Excpt. Items & Tax | 12.06 | 7.14 | 10.07 |
| Interest | 2.86 | 3.04 | 2.08 |
| P/L Before Exceptional Items & Tax | 9.20 | 4.10 | 7.99 |
| Exceptional Items | -- | -- | -- |
| P/L Before Tax | 9.20 | 4.10 | 7.99 |
| Tax | 2.24 | 1.02 | 2.73 |
| P/L After Tax from Ordinary Activities | 6.96 | 3.08 | 5.27 |
| Prior Year Adjustments | -- | -- | -- |
| Extra Ordinary Items | -- | -- | -- |
| Net Profit/(Loss) For the Period | 6.96 | 3.08 | 5.27 |
| Equity Share Capital | 8.36 | 8.36 | 8.36 |
| Reserves Excluding Revaluation Reserves | -- | -- | -- |
| Equity Dividend Rate (%) | -- | -- | -- |
| EPS Before Extra Ordinary | |||
| Basic EPS | 4.16 | 1.84 | 3.15 |
| Diluted EPS | 4.16 | 1.84 | 3.15 |
| EPS After Extra Ordinary | |||
| Basic EPS | 4.16 | 1.84 | 3.15 |
| Diluted EPS | 4.16 | 1.84 | 3.15 |
| Public Share Holding | |||
| No Of Shares (Crores) | -- | -- | -- |
| Share Holding (%) | -- | -- | -- |
| Promoters and Promoter Group Shareholding | |||
| a) Pledged/Encumbered | |||
| - Number of shares (Crores) | -- | -- | -- |
| - Per. of shares (as a % of the total sh. of prom. and promoter group) | -- | -- | -- |
| - Per. of shares (as a % of the total Share Cap. of the company) | -- | -- | -- |
| b) Non-encumbered | |||
| - Number of shares (Crores) | -- | -- | -- |
| - Per. of shares (as a % of the total sh. of prom. and promoter group) | -- | -- | -- |
| - Per. of shares (as a % of the total Share Cap. of the company) | -- | -- | -- |
| Source : Dion Global Solutions Limited |


|
Panda3D
|
Public Member Functions | |
| __init__ (const HeightfieldTesselator) | |
| __init__ (str name) | |
| NodePath | generate () |
| Generates a tree of nodes that represents the heightfield. More... | |
| double | getElevation (double x, double y) |
| Fetches the elevation at (x,y), where the input coordinate is specified in pixels. More... | |
| PNMImage | heightfield () |
| Returns a reference to the heightfield (a PNMImage) contained inside the HeightfieldTesselator. More... | |
| setFocalPoint (int x, int y) | |
| Sets the focal point. More... | |
| bool | setHeightfield (const Filename filename, PNMFileType type) |
| Loads the specified greyscale image file into the heightfield. More... | |
| setHorizontalScale (double h) | |
| Sets the horizontal scale. More... | |
| setMaxTriangles (int n) | |
| Sets the max triangles per geom. More... | |
| setPolyCount (int n) | |
| Sets the polygon-count target. More... | |
| setVerticalScale (double v) | |
| Sets the vertical scale. More... | |
| setVisibilityRadius (int r) | |
| Sets the visibility radius. More... | |
| Public Member Functions inherited from Namable | |
| __init__ (const Namable) | |
| __init__ (str initial_name) | |
| clearName () | |
| Resets the Namable's name to empty. More... | |
| str | getName () |
| bool | hasName () |
| Returns true if the Namable has a nonempty name set, false if the name is empty. More... | |
| output (Ostream out) | |
| Outputs the Namable. More... | |
| setName (str name) | |
Additional Inherited Members | |
| Static Public Member Functions inherited from Namable | |
| static TypeHandle | getClassType () |
| Public Attributes inherited from Namable | |
| const String | name |
| __init__ | ( | const | HeightfieldTesselator | ) |
| __init__ | ( | str | name | ) |
| NodePath generate | ( | ) |
Generates a tree of nodes that represents the heightfield.
This can be reparented into the scene.
| double getElevation | ( | double | x, |
| double | y | ||
| ) |
Fetches the elevation at (x,y), where the input coordinate is specified in pixels.
This ignores the current tesselation level and instead provides an accurate number. Linear blending is used for non-integral coordinates.
| PNMImage heightfield | ( | ) |
Returns a reference to the heightfield (a PNMImage) contained inside the HeightfieldTesselator.
You can use the reference to alter the heightfield.
| setFocalPoint | ( | int | x, |
| int | y | ||
| ) |
Sets the focal point.
The tesselator generates high-resolution terrain around the focal point, and progressively lower and lower resolution terrain as you get farther away. The units are in pixels.
| bool setHeightfield | ( | const Filename | filename, |
| PNMFileType | type | ||
| ) |
Loads the specified greyscale image file into the heightfield.
| setHorizontalScale | ( | double | h | ) |
Sets the horizontal scale.
The default scale is 1.0, meaning that each pixel in the heightfield is 1x1 panda units wide.
| setMaxTriangles | ( | int | n | ) |
Sets the max triangles per geom.
| setPolyCount | ( | int | n | ) |
Sets the polygon-count target.
The tesselator usually manages to come within about 20% of the target, plus or minus.
| setVerticalScale | ( | double | v | ) |
Sets the vertical scale.
The default scale is 255.0, meaning that each as the gray value ranges from (0-1), the elevation ranges from (0-255) feet.
| setVisibilityRadius | ( | int | r | ) |
Sets the visibility radius.
Polygons that are completely outside the radius (relative to the focal point) are cropped away. The cropping is imperfect (all approximations are conservative), so this should be used in conjunction with a far clipping plane, fog, or some other visibility limiting mechanism. The units are in pixels.


Yo! Me coming from New Delhi.
Man, how do you survive the pollution? Man..
Whoa!! Me from Delhi too boy. We totally rock baby.


In Corona, you can apply visual effects to display objects with unprecendented ease.
Effects are set by setting the effect
parameter of a fill or stroke to the name of the effect. The name is a combination of the type of effect and the name. For example, blur is a filter, so here's how you would apply it to an image:
local bkgd = display.newImage( "bkgd.png" ) bkgd.fill.effect = "filter.blur"
There are 3 types of effects available to you:
These effects are categorized based on the number of textures required for them to operate correctly. These are described in more detail below.
Generators are procedurally-generated effects. They don't operate on any textures/images. Instead, they generate textures in the fragment shader.
color1
default = { 1, 0, 0, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
color2
default = { 0, 0, 1, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
xStep
default = 3, min = 0, max = none,
yStep
default = 3, min = 0, max = none,
NOT supported on older Android devices. See "Android" below.
posX
default = 0.5, min = 0, max = 1,
posY
default = 0.5, min = 0, max = 1,
aspectRatio
default = 1, min = 0, max = none,
seed
default = 0, min = 0, max = none,
NOT supported on older Android devices. See "Android" below.
color1
default = { 1, 0, 0, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
color2
default = { 0, 0, 1, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
scale
default = 8, min = 0, max = none,
NOT supported on older Android devices. See "Android" below.
aspectRatio
default = 1, min = 0, max = none,
center_and_radiuses
[0] is center.x. [1] is center.y. [2] is innerRadius. [3] is outerRadius. default = { 0.5, 0.5, 0.125, 0.25 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
color1
default = { 1, 0, 0, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
color2
default = { 0, 0, 1, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
periods
[1] is pixelOnPeriod1. [2] is pixelOffPeriod1. [3] is pixelOnPeriod2. [4] is pixelOffPeriod2. default = { 1, 1, 1, 1 }, min = { 0, 0, 0, 0 }, max = { none, none, none, none },
angle
default = 0, min = 0, max = 360,
translation
default = 0, min = none, max = none,
This may not be functional under Windows.
posX
default = 0.5, min = 0, max = 1,
posY
default = 0.5, min = 0, max = 1,
aspectRatio
default = 1, min = 0, max = none,
seed
default = 0, min = 0, max = none,
NOT supported on older Android devices. See "Android" below.
Filters effects operate on a single texture/image.
levels
See filter.levelshorizontal
See filter.blurHorizontalvertical
See filter.blurVerticaladd
See composite.addhorizontal
See filter.blurHorizontalvertical
See filter.blurVerticalblurSize
default = 8, min = 2, max = 512,
sigma
default = 128, min = 2, max = 512,
blurSize
default = 8, min = 2, max = 512,
sigma
default = 128, min = 2, max = 512,
intensity
Controls the intensity of the brightness. Ranges from 0 to 1. default = 0, min = 0, max = 1,intensity
Controls the distortion of the bulge. Ranges from 0 to 1. default = 1, min = 0, max = 1,sensitivity
0..1, default: 0.4 default = 0.4, min = 0, max = 1,
smoothing
0..1, default: 0.1 default = 0.1, min = 0, max = 1,
color
vec4 rgba 0..1, default: white default = { 1, 1, 1, 1 }, -- ?? min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
xTexels
default = 8, min = 0, max = none,
yTexels
default = 8, min = 0, max = none,
This multiplies a source color and adds an offset to each color component of a source image.
coefficients
default = { 1.0, 0.0, 0.0, 0.0, -- The red coefficients. 0.0, 1.0, 0.0, 0.0, -- The green coefficients. 0.0, 0.0, 1.0, 0.0, -- The blue coefficients. 0.0, 0.0, 0.0, 1.0 } -- The alpha coefficients.
bias
default = { 0.0, 0.0, 0.0, 0.0 } min = { -1.0, -1.0, -1.0, -1.0 } max = { 1.0, 1.0, 1.0, 1.0 }
This applies a set of cubic polynomials to a source image.
default = { 1.0, 0.0, 0.0, 0.0, -- The red coefficients. 0.0, 1.0, 0.0, 0.0, -- The green coefficients. 0.0, 0.0, 1.0, 0.0, -- The blue coefficients. 0.0, 0.0, 0.0, 1.0 } -- The alpha coefficients.
contrast
0..4, default: 1 default = 1, min = 0, max = 4,grain
default = 0, min = 0, max = 1,numTiles
default = 16, min = 2, max = none,NOT supported on older Android devices. See "Android" below.
intensity
default = 0.5, min = 0, max = 1,threshold
Controls the dissolve progress. Ranges from 0 (opaque) to 1 (transparent). default = 1,NOT supported on older Android devices. See "Android" below.
darkColor
default = { 0.0, 0.0, 0.5, 1.0 }lightColor
default = { 1.0, 0.0, 0.0, 1.0 }intensity
0..4, default: 1 default = 1, min = 0, max = 4,exposure
-10..10, default: 0 default = 0, min = -10, max = 10,scale
default = 64, min = 1, max = none,NOT supported on older Android devices. See "Android" below.
angle
0..360, default: 0center
This is the position of the origin of the iris. default = { 0.5, 0.5 }, min = { 0, 0 }, max = { 1, 1 },
aperture
default = 0, min = 0, -- full coverage (closed) max = 1, -- no coverage (open)
aspectRatio
default = 1, min = 0, max = none,
smoothness
default = 0, min = 0, max = 1,
white
default = 215/255, min = 0, max = 255,
black
default = 144/255, min = 0, max = 255,
gamma
default = 1.06, min = 0, max = 1,
color1
name = "color1", default = { 1, 0, 0, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
position1
default = { 0, 0 }, min = { 0, 0 }, max = { 1, 1 },
color2
default = { 0, 0, 1, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
position2
default = { 1, 1 }, min = { 0, 0 }, max = { 1, 1 },
direction
default = { 1, 0 }, -- Doesn't need to be normalized. min = { 0, 0 }, max = { 1, 1 },
smoothness
default = 0, min = 0, -- hard max = 1, -- smooth
progress
default = 0, min = 0, max = 1,
r
default = 0, min = 0, max = 1,
g
default = 0, min = 0, max = 1,
b
default = 0, min = 0, max = 1,
a
default = 1, min = 0, max = 1,
numPixels
default = 8, min = 0, max = none,
angle
default = 0, min = 0, max = 360,
scale
default = 2.8, min = 0, max = none,
numPixels
default = 4,numPixels
default = 4, min = 4, max = none,
dotRadius
default = 1, min = 0, max = 1,
NOT supported on older Android devices. See "Android" below.
colorsPerChannel
default = 4, min = 2, max = none,center
default = { 0.5, 0.5 }, min = { 0, 0 }, max = { 1, 1 },
progress
default = 0, min = 0, max = 1,
axisOrientation
default = 0, min = 0, max = 1,
smoothness
default = 0, min = 0, max = 1,
intensity
default = 1, min = 0, max = 8,intensity
default = 0.5, min = 0, max = 1,NOT supported on older Android devices. See "Android" below.
intensity
default = 1, min = 0, max = 1,sharpness
default = 0, min = 0, max = 1,NOT supported on older Android devices. See "Android" below.
width
default = 1, min = 1, max = none,
height
default = 1, min = 1, max = none,
angle
default = 0, min = 0, max = 360,
intensity
default = 0radius
default = 0.1amplitude
default = 10,intensity
default = 0.5, min = 0, max = 1,effect.u
default = 0.5, min = 0, max = 1,
effect.v
default = 0.5, min = 0, max = 1,
effect.intensity
Controls the intensity of the blur. Ranges from 0 (no blur) to 1. Default is 0.5. default = 0.5, min = 0, -- No blur. max = 1,
This may not be functional under Windows.
NOT supported on older Android devices. See "Android" below.
Composite effects operate on multiple textures/images.
alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,dirLightColor
: A vec4 containing RGBA values from 0 to 1. default = { 1, 1, 1, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
dirLightDirection
: A vec3 containing the light direction in texture-space. The origin and the growth direction of each axes is the same as described for "pointLightPos" in "composite.normalMapWith1PointLight". We expect this direction vector to be the orientation from where the light is coming from. Not the direction in which it's going. There's no need to normalize this parameter, it's already done internally. default = { 1, 0, 0 }, min = { 0, 0, 0 }, max = { 1, 1, 1 },
ambientLightIntensity
: A 0 (dark) to 1 (full brightness) float containing the brightness of the ambient light. default = 0, min = 0, max = 1,
NOT supported on older Android devices. See "Android" below.
pointLightColor
: A vec4 containing RGBA values from 0 to 1. default = { 1, 1, 1, 1 }, min = { 0, 0, 0, 0 }, max = { 1, 1, 1, 1 },
pointLightPos
: A vec3 containing the light position in textures-space. In other words, this is the position where the light is coming from. The XYZ origin is the upper left corner (0,0,0). Positive X grow to the right, positive Y grows towards the bottom, and positive Z grows out of the screen (towards us, the viewer). The XY for the bottom right corder is (1,1). The Z value is the distance from the surface. 0 means the light is flush with the surface. Larger values means it's farther away from the surface. There's no maximum value for Z, but commonly, the user will keep the value between 0 and 1. default = { 1, 0, 0 }, min = { 0, 0, 0 }, max = { 1, 1, 1 },
ambientLightIntensity
: A 0 (dark) to 1 (full brightness) float containing the brightness of the ambient light. default = 0, min = 0, max = 1,
attenuationFactors
: A vec3 containing the diffuse light's distance attenuation factors. XYZ are the constant, linear, and quadratic attenuation factors. Read these for a better understanding of the attenuation factors:
https://developer.valvesoftware.com/wiki/Constant-Linear-Quadratic_Falloff http://www.felixgers.de/teaching/jogl/lightAttenuation.html
Note: Distance attenuation DOESN'T affect ambient light intensity.
default = { 0.4, 3, 20 }, min = { 0, 0, 0 }, max = { none, none, none },
NOT supported on older Android devices. See "Android" below.
alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,alpha
default = 1, min = 0, max = 1,Certain effects have problems on older Android devices. Most commonly, devices made before 2013, and devices using the ARM Mali 400 GPU). For example, Google Nexus 7, Samsung Galaxy S3, and Amazon Kindle Fire.
To determine if the current device might have problems, use:
if system.getInfo( "gpuSupportsHighPrecisionFragmentShaders" ) then
-- This device is ok.
-- This device WON'T have problems.
else
-- This device ISN'T ok.
-- This device WILL have problems.
end


#include <ComputerAI.h>
Public Member Functions | |
| virtual void | Enter (entity_type *)=0 |
| De-constructor. | |
| virtual void | Execute (entity_type *)=0 |
| Execute the state. | |
| virtual void | Exit (entity_type *)=0 |
| Exit the state. |
A template state class.
Definition at line 17 of file State.h.
| virtual void State< entity_type >::Enter | ( | entity_type * | ) | [pure virtual] |
De-constructor.
This is the de-constructor Enter the state Inititializes all data when entering a different state
| entity_type | - Type of entity using the StateMachine |
| virtual void State< entity_type >::Execute | ( | entity_type * | ) | [pure virtual] |
Execute the state.
Main loop of the current state. Gets called every frame
| entity_type | - Type of entity using the StateMachine |
| virtual void State< entity_type >::Exit | ( | entity_type * | ) | [pure virtual] |
Exit the state.
Frees data from this state when changing to another one
| entity_type | - Type of entity using the StateMachine |


Instructions
In this experiment, you will be able to broadcast messages to some other players in the game. Some of them will be able to broadcast messages to you.
The chat session will last until all players leave the chatroom.
{% extends "layout.html" %} {% block body %}
In this experiment, you will be able to broadcast messages to some other players in the game. Some of them will be able to broadcast messages to you.
The chat session will last until all players leave the chatroom.


menu
Cubetastic
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{% block body %} {% endblock %}
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C Training
1.0
LeetCode
Tree
Tree Directory Reference
Files
file
AVL.cpp
file
AVLTree.c
gcc -Wall
tree.c
AVLTree.c
&& valgrind ./a.out
file
balancedBinaryTree.c
source:
https://leetcode.com/problems/balanced-binary-tree
file
binaryTreePaths.cpp
source:
https://leetcode.com/problems/binary-tree-paths
file
BSTToDLL.cpp
source:
https://leetcode.com/problems/binary-tree-inorder-traversal/
file
countCompleteTreeNodes_1.cpp
source:
https://leetcode.com/problems/count-complete-tree-nodes
file
countCompleteTreeNodes_2.c
file
generateABST.c
file
iterativeWayInorderTraversal.cpp
source:
https://leetcode.com/problems/binary-tree-inorder-traversal/
It take me more than two hours to fix the memory leak
file
levelOrderTraversal_2.cpp
file
pathSum.c
source:
https://leetcode.com/problems/path-sum/
file
pathSum2.cpp
source:
https://leetcode.com/problems/path-sum/
file
sametree.c
source:
https://leetcode.com/problems/same-tree/
file
testLevelOrderTraversal.c
Modified Date: 01/14/2020 Description: Approach for Level order A BST by pushing node into a queue level by level.
file
tree.c
file
tree.cpp
file
tree.h
[code]
Generated by
1.8.18


Employee Salary Tracker
First Name:
Last Name:
ID Number:
Job Title:
Salary:
Monthly Salary Total:
$0.00


Michael Goodwin: De Blasio, Cuomo show sneering hostility as Trump leaves New York
by Michael GoodwinIn the tweet confirming he switched his official residency from New York to Florida, President Trump said, “Despite the fact that I pay millions of dollars in city, state and local taxes each year, I have been treated very badly by the political leaders of both the city and state.”
As if on cue, those leaders instantly proved his point.
CLICK HERE TO GET THE OPINION NEWSLETTER
"Good riddance," Cuomo thundered. “Don’t let the door hit you on your way out,” chimed in Mayor de Blasio.
MANSION SALES RISE IN FLORIDA AS WEALTHY BUYERS ARE DRAWN TO ITS LOW TAXES AND SUNSHINE
Their sneering hostility is yet another example of how Cuomo and de Blasio are failing to take advantage of having a fellow New Yorker in the White House. Do they really believe they can heap abuse on Trump, and he will grant their every wish for federal aid?
Do they shower their harshest critics with generous favors?
Trump is the first New Yorker to be president since FDR, yet city and state Democrats won’t even show basic respect for the office. Instead of honey, it’s all bile and vinegar as they engage in constant attacks and use their power to harass, investigate and punish the president, his family and his businesses.
CLICK HERE TO CONTINUE READING MICHAEL GOODWIN'S COLUMN IN THE NEW YORK POST


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This is a work in progress of Public Invention.
This is a tester tool for open-source ventilators. It uses the PIRDS data format.
The basic operation is receive data from web server specified in the URL above. Probably for now that will be the VentMon Python web server that listens on a serial port for the VentMon device or any other device that streams PIRDS events.


GraphQL API
Explore the schemaIntroduction
What is GraphQL?
GraphQL is an API query language, originally created by Facebook as an alternative to REST. If you're new to GraphQL, the best place to start is the official documentation.
How do I make a query?
It depends on what kind of environment you are making the query from. Check out this list of GraphQL client libraries to see some tools already available in multiple languages, including C#/.NET, Go, Java, JavaScript, and Python. These client libraries can make writing queries easier and may provide built-in support for features like caching.
However, GraphQL is just a query language served over HTTP, so you can also make a request without using any GraphQL-specific libraries or packages. Here's an example using cURL (you'd need to replace the API key and test ID to try it yourself):
curl 'https://app.codesignal.com/graphql' -H 'Content-Type: application/json' -H 'Accept: application/json' -H 'Authorization: Bearer MY_API_KEY' --data-binary '{"query":"{ companyTest(id: \"MY_TEST_ID\") { title } }"}'
This returns data that looks like this:
{"data":{"companyTest":{"title":"My Company Test"}}}
How can I test my queries during development?
Although you'll likely want to consume our API programmatically using a library in your language of choice, as you work on your integration, you may find it helpful to have a readily available UI for writing and running queries. For that, try out our GraphQL Playground, which is connected to our real API and provides a helpful interface that will make it easier for you to quickly spot and resolve syntax or schema issues in your queries.
To use the GraphQL Playground, you need to first generate an API key (see below) and then provide that in the HTTP Headers section in the bottom-left:
{ "Authorization": "Bearer YOUR_API_KEY" }
As long as you provide a valid API key, you can write and execute queries here and see the result immediately. If there are errors in your query syntax, red highlighting will appear on the left side of lines with errors, and you can hover over the query to learn more about what is wrong.
You can also explore the GraphQL schema and documentation live from the GraphQL Playground, as well as copy your query to a cURL command like the one from the previous section.
What kinds of queries can I make?
Take a look at our schema. All read-only queries can be found under RootQuery, and all mutations can be found under RootMutation.
Here's an example of a query that you could run to fetch the answers from a company test session:
query AnswerQuery {
companyTestSession(id: "MY_TEST_SESSION_ID") {
id
result {
taskResults {
solution {
id
... on CodingSolution {
sources {
source
language
path
}
}
... on FreeFormSolution {
freeTextAnswer: answer
}
... on QuizSolution {
quizAnswer: answer
}
}
}
}
}
}
In this case, we're using the graph-based nature of the API to make the following request: Look up a given company test session. For that session, return the ID and the result. For the result, return the result for each task, including the solution. For each solution, return the ID of the solution and more information depending on what kind of solution it is (using inline fragment syntax to query different fields based on type, and aliases to make sure the "answer" field does not conflict, since it has different types for free-text and quiz answers.
That might return something that looks like this:
{
"data": {
"companyTestSession": {
"id": "MY_TEST_SESSION_ID",
"result": {
"taskResults": [
{
"solution": {
"id": "MY_CODING_SOLUTION_ID",
"sources": [
{
"source": "console.log('hello world');",
"language": "js",
"path": "main.js"
}
]
},
},
{
"solution": {
"id": "MY_FREE_TEXT_SOLUTION_ID",
"freeTextAnswer": "Hello, world!",
},
},
{
"solution": {
"id": "MY_QUIZ_SOLUTION_ID",
"quizAnswer": [
"All of the above"
]
},
}
]
}
}
}
}
Authentication
How do I get an API key?
If you're not already using CodeSignal, start a conversation with us by requesting a demo.
If you're an existing customer, reach out to<EMAIL_ADDRESS>to learn more.
How do I make an authenticated request?
When making a GraphQL request, pass an "Authorization" header with a value of "Bearer YOUR_API_KEY" with the HTTP request. You can see a simple example of this in the cURL command above.
Some queries or mutations may require specific permissions to be assigned to your API key. If you receive Access Denied errors that you believe to be in error, please contact support.
Rate Limits and Maximum Cost
What are rate limits and cost complexity, anyway?
Let's start with an analogy: Say you (the API consumer) are at home, ordering groceries (data) through a service like Instacart (the API).
A REST API is like a shopper who can only buy one item from the grocery store at a time. They can get any item in the store, but only one; if you want a second item, they have to make another full round-trip. For this kind of API, the main limit is a "rate limit." In other words, how frequently can you ask the shopper to go to the store?
On the other hand, GraphQL APIs are like shoppers who can buy a whole cart's worth of goods. Convenient! Like REST API shoppers, they may also have a limit on how frequently they can go to the store (a rate limit), but they can bring back a lot more groceries per trip. However, if you order too many things at once, they won't all fit in the shopping cart. The size of the shopping cart is the "maximum cost" allowed per trip.
What are CodeSignal's rate and cost limits?
Our rate limits vary based on the query or mutation; specific limits can be found in the schema documentation. Common values are 10 requests per second, or 5 requests per second.
Our maximum cost for a single query is 10000, and additionally we also don't allow queries with a depth greater than 10.
The cost of each resource can be found in the schema documentation, either as a scalar number or a multiplier based on the input. The total cost of a query will be determined by the cumulative cost of each queried resource.


monodevelop
Cross platform IDE for C#, F# and more.
More information: home page
- Start MonoDevelop:
monodevelop
- Open a specific file:
monodevelop path/to/file
- Open a specific file with the caret at a specific position:
monodevelop path/to/file;line_number;column_number
- Force opening a new window instead of switching to an existing one:
monodevelop --new-window
- Disable redirection of `stdout` and `stderr` to a log file:
monodevelop --no-redirect
- Enable performance monitoring:
monodevelop --perf-log


--- layout: post title: Mario Cuomo's 1984 DNC Keynote Address date: 2010-11-15 13:17:11.000000000 -05:00 categories: [] tags: [] status: publish type: post published: true meta: _edit_last: '7106425' _wp_old_slug: '' author: login: samarthbhaskar email<EMAIL_ADDRESS>display_name: samarthbhaskar first_name: '' last_name: '' ---
A friend of mine mentioned this speech to me the other day. I had never heard of it before, especially with Obama's 2004 DNC address being the most popular speaking event connected with the DNC in my recently developed political conscience. I finally got around to reading the speech and I had to share it. My friend described it as a "seminal piece of rhetoric in liberal political ideology" and I couldn't have put it better myself. I would have picked out parts that I liked best, but I am more inclined to promote it in its entirety.


LIMITLESS No Boundary Apprentice
KEEP IT IN Boundary all over the field Trained
SNEAK PAST Small Gaps Able
WATCH YOUR HEAD Barriers In Between Competent
DEATH TRAP Caged Field Experienced


Kitura is a server-side Swift web framework, with a large ecosystem of supporting packages to make developing cloud-native applications easy.
Core Kitura package.
Client side library for using Codable routes with Kitura.
Provides socket support to Kitura based servers.
Allow Swift apps to report health status.
Convenience package for accessing variables mapped to JSON for Cloud environments.
Instruments the Swift runtime for performance monitoring, via API or a visual dashboard.
Allows the addition of OpenAPI (Swagger) support to your Kitura application.
Allows parsing of Cloud Foundry configuration variables, like port number, IP and URL.
A design pattern to improve response time, stability and prevent constant failure requests.
HTTP networking library for Swift.
An ORM for Swift, built on Codable.
SQL database abstraction layer.
MySQL plugin for Swift-Kuery framework.
PostgreSQL plugin for Swift-Kuery framework.
SQLite plugin for Swift-Kuery framework.
Framework for managing user sessions on a Kitura server.
Kitura-Session store using Redis as the backing store.
Validate user credentials on a Kitura server.
Plugin for the Credentials framework that authenticates using Facebook.
Plugin for the Credentials framework that authenticates using GitHub.
Plugin for the Credentials framework that authenticates using Google web login and a Google OAuth token.
Plugin for the Credentials framework that authenticates using HTTP Basic and Digest.
Plugin for the Credentials framework that authenticates using JSON Web Tokens.
Plugin for the Credentials framework that authenticates using a Dropbox OAuth2 token.
Plugin for the Credentials framework that authenticates using the Twitter OAuth web login.
The Kitura template engine abstraction layer.
Template engine for Kitura that uses Stencil based templates.
Template engine for Kitura that uses Markdown based templates.
Template engine for Kitura that uses Mustache based templates.
Allows Kitura to interact with CouchDB databases.
Library for interacting with a Redis database.
Logger protocol for differing kinds of loggers.
A lightweight Swift logging framework.
In-memory, thread safe cache that allows object storage against a unique Hashable key.
Kitura compression middleware.
Kitura CORS middleware.
Sample application demonstrating Kitura and IBM Swift features.
Sample application demonstrating Kitura and the KituraKit client library.
Demonstration application using Kubernetes.
Logic for sending and receiving HTTP requests.
Logic for sending and receiving HTTP requests using Apple's SwiftNIO framework.
Type definitions shared by client and server.
Socket framework for Swift.
SSL/TLS add-in framework for BlueSocket.
Cross-platform cryptography library.
Generic cross-platform signal handler.
Cross-platform RSA wrapper library.
A Swift SMTP mail client.
Pure Swift HTML encode and decode utility tool.
An implementation of JSON Web Tokens in Swift.
Allows inspection of native and complex types.
Manages application configurations.
Utility for resolving common paths.


|
pf
|
A class template for HMM filtering. More...
#include <cf_filters.h>
Public Types | |
| using | ssv = Eigen::Matrix< float_t, dimstate, 1 > |
| "state size vector" | |
| using | osv = Eigen::Matrix< float_t, dimobs, 1 > |
| "observation size vector" | |
| using | ssMat = Eigen::Matrix< float_t, dimstate, dimstate > |
| "state size matrix" | |
| Public Types inherited from pf::bases::cf_filter< dimstate, dimobs, float_t > | |
| using | obs_sized_vec = Eigen::Matrix< float_t, dimobs, 1 > |
| using | state_sized_vec = Eigen::Matrix< float_t, dimstate, 1 > |
Public Member Functions | |
| hmm () | |
| Default constructor. More... | |
| hmm (const ssv &initStateDistrLogProbs, const ssMat &transMatLogProbs) | |
| Constructor. More... | |
| virtual | ~hmm () |
| The (virtual) desuctor. | |
| float_t | getLogCondLike () const |
| Get the latest conditional likelihood. More... | |
| ssv | getFilterVecLogProbs () const |
| Get the current filter vector. More... | |
| void | update (const ssv &logCondDensVec) |
| Perform a HMM filter update. More... | |
| float_t | log_sum_exp (const ssv &logProbVec) |
| log sum exp trick More... | |
| ssv | log_product (const ssMat &logTransMat, const ssv &logProbVec) |
| Public Member Functions inherited from pf::bases::cf_filter< dimstate, dimobs, float_t > | |
| virtual | ~cf_filter () |
| The (virtual) destructor. | |
Private Attributes | |
| ssv | m_filtVecLogProbs |
| filter vector | |
| ssMat | m_transMatLogProbsTranspose |
| transition matrix | |
| float_t | m_lastLogCondLike |
| last log conditional likelihood | |
| bool | m_fresh |
| has data been observed? | |
A class template for HMM filtering.
| pf::filters::hmm< dimstate, dimobs, float_t, debug >::hmm |
Default constructor.
Need ths fir constructing default std::array<>s. Fills all vectors and matrices with zeros.
| pf::filters::hmm< dimstate, dimobs, float_t, debug >::hmm | ( | const ssv & | initStateDistrLogProbs, |
| const ssMat & | transMatLogProbs | ||
| ) |
Constructor.
allows specification of initstate distn and transition matrix.
| initStateDistrLogProbs | first time state log prior distribution. |
| transMatLogProbs | time homogeneous transition matrix with log probabilities. |
| auto pf::filters::hmm< dimstate, dimobs, float_t, debug >::getFilterVecLogProbs |
Get the current filter vector.
get the current filter vector log probs.
|
virtual |
Get the latest conditional likelihood.
Implements pf::bases::cf_filter< dimstate, dimobs, float_t >.
| auto pf::filters::hmm< dimstate, dimobs, float_t, debug >::log_product | ( | const ssMat & | logTransMat, |
| const ssv & | logProbVec | ||
| ) |
| float_t pf::filters::hmm< dimstate, dimobs, float_t, debug >::log_sum_exp | ( | const ssv & | logProbVec | ) |
log sum exp trick
calculates the log of the sum of the exponentiated elements of a Vector
| void pf::filters::hmm< dimstate, dimobs, float_t, debug >::update | ( | const ssv & | logCondDensVec | ) |
Perform a HMM filter update.
Perform a HMM filter update.
| logCondDensVec | the vector (in x_t) of log p(y_t|x_t) |


| JOAO PAULO M. JAQUIAS Address: #8 St. Joseph Navy Base Morning Glory Baguio City Contact No.: +639123456789 E-mail<EMAIL_ADDRESS>|
|
OBJECTIVE:Challenging opportunity where I will be able to utilize my strong organizational skills, educational background, and ability to work well with people, which allow me to grow personally and proffessionally. | |
ACADEMIC BACKGROUND: |
|
| Tertiary | Bachelor of Science in Information Technology University of the Cordilleras Baguio City, Philippines (S.Y. 2016-Present) |
| Secondary | Macau Sam Yuk Middle School Seventh Day Adventists Macau,China (S.Y. 2009-2013) |
| Primary | Sao Joao de Brito Macau China (S.Y. 2002-2009) |
WORK EXPERIENCE: |
|
|
|
SKILLS: |
|
|
|
Accomplishment: |
|
|
|
Character Reference: |
|
| Mary Jane Jaquias | Mother Card Dealer(Occupation) |
| Pablo Jaquias | Father Engineer (Occupation) |
Other Information: |
|
I'm 22 years old. I was born and raised in Macau,China. My province is in Neuva Ecija Gapan City. But I currently live in Baguio City for studies. I was planning to work still in Macau, Because there is a high chance that I can get hired. Because I'm citizen of Macau. |


Ephedra, Cannabis, Lobelia & Lactuca - L. canadensis
| DOSE: T+ 0:00 |
2.0 g |
oral |
Ephedra sinica |
(tea) |
| T+ 2:00 |
|
smoked |
Cannabis |
(plant material) |
| T+ 2:30 |
1 cig. |
smoked |
Cannabis |
(plant material) |
| T+ 6:00 |
1 cig. |
smoked |
Lobelia spp. |
(plant material) |
| T+ 10:00 |
|
smoked |
Cannabis |
(plant material) |
| T+ 10:00 |
|
smoked |
Lactuca - L. canadensis |
(plant material) |
me :
male
40 years
65 kg
rather good health
regular pot smoker for several years
former heavy tobacco smoker, quit around 7 months ago with the help of nicotine patches (for 5 months). Eating a lot of licorice candies, which are bad for blood pressure.
mindset : interested in trying a psychoactive product.
preparation :
About 2 g of ephedra stems (ma huang, ephedra vulgaris)into cold water slowly heated to boiling point, let boiling for 10 minutes, cooled down for 20 minutes.
T : I drank the tea quickly. There was a brown powder in my cup, I swallowed it to. Ephedra tea had a very good taste and didnt need any sugar. It's one of the best tasting herbal tea I ever drank.
T + 15mn : My vision seemed a little more accurate, colors were fine. In fact there was no real change but I was more concentrated on my senses.
 When I tried cocaine one year ago, it drove me to a stupid state of mind too, although the claims it makes thoughts fast and clear. I was feeling mildly happy. I started to make grapevine juice with the fruits I collected from my grapevine plant. Breathing was easier than ever, and very pleasant.
T + 1 h : Time passed quick, I was deeply concentrated on my manual task. I was feeling fine.
T + 2 h : I finished with the grapevine juice. I was feeling like having energy to spend. I smoked a very little MJ stick. It didnt change my state of mind, except I was more likely to laugh.
T + 2 h 30 : I smoked a bigger joint with the same result. I'd like to take a walk, but I couldn't cause I was waiting for a friend. I started to worry a bit about my blood pressure because I'm a 'heavy' (5 g / day) licorice eater.
T + 3 h : I felt something weird with my heart. My heart was pounding at a slightly accelerated rate. I was feeling something weird with my heart, but I guess it had something to do with pot paranoia.
T + 4h / 4h 30 : At this time, the mental effects like concentration and happyness were fading, while the feeling of having a physical energy didn't change. I started to feel a little tired. Then, my friend arrived and we worked in the garden for an hour. I stopped to care about my heart and I didn't feel tired while working.
T + 6 h : I was feeling tired. I got a slight ache in the heart area. I was a bit worried about it. I was 'wanting to take something'. Since I quit smoking, psychoactives often ended by the need, sometimes very strong, to smoke tobacco. As time has passed, it was replaced by a slighter need to take some psychoactive substance. So I smoked a cigarette of Lobelia inflata dried leaves.
I spent the evening working on my computer and then watched a movie. There were unpleasant feelings in the heart area. I had no depression or even pessimistic state of mind when the effects were fading away. I smoked pot mixed with wild lettuce more than 10 hours after having drunk the ephedra and fell asleep very quickly.
Next morning I woke up early, feeling fine.
I think that the effects on the heart started 1 hour after the mental effects, a bit like with caffeine, and lasted longer. It was a pleasant experiment. The effects were mild, but long lasting. I'll try it again, but with a lower dose. It's obvious that the toxic dose is not a lot larger than the effective dose and that trying to get a massive high from ephedra could lead very easily to a major heart problem.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


The beginning of
THE END OF THIS WORLD
A study of the End Times on the basis of The Holy Bible
"Look, I am coming soon! My reward is with me, and I will give to everyone
according to what they have done." - Revelation 22:12
(This site is launched just now. A lot more information is going to fill the pages. Please check from time to time)


Maghazei, Omid, Michael A. Lewis, et Torbjørn H. Netland. « Emerging Technologies and the Use Case: A Multi-Year Study of Drone Adoption ». Journal of Operations Management 68, no 6 7 (2022): 560 91. https://doi.org/10.1002/joom.1196.
DDM is limited to tasks such as prototyping, “soft tooling,” and the on-demand production of customized and spare parts due to high costs
Drones are used in experimentations and in production : oil platforms inspection (Shell), medical product delivery (Zipline), continual inventory control in its warehouses (IKEA)
Control, track, or monitor manufacturing activities, either directly or indirectly (Boyer et al., 1997, p. 332)
The challenge is not assessing the benefits of an AMT
It is about “the appropriateness of associated decisions and processes—primarily in terms of the technologies’ fit or match with a range of internal and external contingencies.”
These are the fit between the technology and
Managers calculate or estimate economic potential of a business case using project finance techniques
“AMT researchers have long stressed the limitations of any overreliance on narrow capital budgeting-centered approaches.”
Especially for infrastructure technologies that have many direct and indirect outcomes (both positive or negative)
Hayes, Robert H., et Steven C. Wheelwright. « The Dynamics of Process-Product Life Cycles ». Harvard Business Review, 1 mars 1979. https://hbr.org/1979/03/the-dynamics-of-process-product-life-cycles.
“Investments in new technology often resemble the ante in a poker game. One does not expect any direct return from the ante itself. It simply allows one to play the next set of cards.” Hayes and Jaikumar (1991, p. 173)
Das and Narasimhan (2001, p. 539) reported that “the use of AMT … does not appear to encourage firms to assume ‘off diagonal’ positions in the Hayes and Wheelwright (1979) framework.”
How the technology integrates with the firms’ operating model
This can be particularly challenging if the process affects routines, responsibilities, and reporting channels
AMT literature (e.g., computer-aided manufacturing, flexible manufacturing systems, etc.) were mainly developed for specific manufacturing applications.
If any new technology is to be fully implemented, it will require acceptance by users : training is key
But there is more than training, more recent literature examines the managerial behavioral aspects of technology adoption (e.g. design)
The business case for drones remains unclear compared with traditional investment options such as forklifts, mounted cameras, and material handling systems.
“Overestimate[ing] the short-term impact of a truly transformational discovery, while underestimating its longer-term effects.” Collins (2010)
See also : Brynjolfsson, Erik, Daniel Rock, et Chad Syverson. « The Productivity J-Curve: How Intangibles Complement General Purpose Technologies ». American Economic Journal: Macroeconomics 13, nᵒ 1 (janvier 2021): 333‑72. https://doi.org/10.1257/mac.20180386.
Techniques de l’Ingénieur. « Comprendre les différences entre exploration et exploitation ». Consulté le 9 août 2023. https://www.techniques-ingenieur.fr/fiche-pratique/innovation-th10/l-intrapreneuriat-au-service-de-l-innovation-dt137/comprendre-les-differences-entre-exploration-et-exploitation-1744/.
Market pull versus technology push (Mowery & Rosenberg, 1979; Nemet, 2009)
One way to address a low perceived fit between emerging technologies and internal operational factors might be to outsource development and deployment to specialized suppliers.
The vivid drone startup industry is actively looking for development partners, implementation pilot projects, and potential customers.
Drones do not appear to have favorable starting conditions for achieving a fit with any of the three factors.
Why then do companies continue to explore and pilot drones in their operations, and how do companies move from early ideas to matured applications?
This research is a multi-year analysis of drone applications in OM.
Case studies are useful when exploring questions about the “why” and “how” of concepts (Yin, 2013)
See publication for the details
| Theoretical themes | Study 1: Explorative study of drone applications in operations (2016–2018) |
|---|---|
|
Economic and strategic factors (Poor fit) |
Scarce evidence of drone implementation but a considerable amount of “piloting” Poor evidence of ROI for OM applications “Use case,” not business case Drone piloting seen as technology championing, sponsored by earmarked “Industry 4.0” funds Drone startups actively seeking co-development partners and willing to conduct pilots at low cost or for free |
|
Operational and supply chain factors (Poor fit) |
Fast developing technology Significant hype Limited functionality reduces use case options Easy to run stand-alone pilot projects without technology integration Importance of ecosystem |
|
Organizational and behavioral factors (Uncertain fit) |
For manufacturers, drones were “something new.” Drones as a “cool technology,” signaling a cutting-edge technology user Concerns about safety, privacy, noise, and air turbulence Lack of skills and experience |
| Theoretical themes | Study 2: Case study of drone pilot projects at Geberit (2018–2019) |
|---|---|
|
Economic and strategic factors (Poor fit) |
Initial beliefs in value The idea of “use case” dominated the project “Proved” the use case feasibility for (1) silo inspection and (2) the thermal inspection of machines Business case considerations (1) were a filter for use cases and, eventually, (2) hindered adoption Replacing manual inspection with manually controlled drones does not save labor costs |
|
Operational and supply chain factors (Poor fit) |
A range of application areas unique to Geberit’s factory was considered but had to be balanced against the available technological capabilities of the drones The manual drone inspection was successful Collision risk with robotic arm Enhanced thermography capabilities required |
|
Organizational and behavioral factors (Poor fit) |
Initial enthusiasm for pilot projects. Some people are in favor of drones; others against Privacy concerns Noise concerns Requirement of internal capability building (e.g., training drone operators) Not piloted again since 2019 due to piloting other technologies |
| Theoretical themes | Study 3: Case study of drone pilot projects and adoption at IKEA (2019–2021) |
|---|---|
|
Economic and strategic factors (Good fit) |
Inventory counting deemed as a potentially economic “use case” Local drone initiatives consolidated to two technologies (Verity and Hardis) by the global group in 2020 The cost-conscious company requires evidence of value A novel application that is hard to benchmark with respect to performance Positive return on experience (ROX) Rolling out Verity solution in warehouses in Switzerland in 2021 and globally in 2022 |
|
Operational and supply chain factors (Medium fit) |
Many drone technologies piloted in different locations The two drone solutions chosen by IKEA have very different capabilities Both solutions are independent systems that were easy to pilot For both solutions, IT integration is a technical challenge |
|
Organizational and behavioral factors (Good fit) |
Employees were receptive to drones that perform dull, potentially dangerous, and repetitive job tasks Implementations in the same warehouses where drones were piloted Certain technological problems for one of the two drone technologies reduced the enthusiasm for that solution |
“We find that—when faced with fast-emerging technologies in thriving ecosystems—companies do not follow a linear technology adoption pattern, where adoption commonly starts with a business case. Instead, companies trial technologies by focusing on a “use case,” which allows a potential business case to evolve, or not, over time.”
You don’t want to be too late or too soon
Mature technology : autonomous flying was available for IKEA
Procurement readiness to develop and to support experimentation
It differs from the business case, and it comes from Information Systems literature
In many ways, the use case is a manifestation of what Orlikowski (2000) called the idea of “technology in practice,” which is a perspective that starts with human action and examines how structures emerge through recurrent interactions with available technology. She notes that some technologies-in-practice (not all) can become institutionalized over time, but this is rarely permanent. Moreover, the familiar “black box” notion of technology only exists as a result of stable patterns of use (Latour, 1987). In observing this nascent technology, we were inside the black box and were forced to explore different possible technological–organizational connections.
It is likely that such characteristics will be similar for other Industry 4.0 technologies, such as AI, blockchain, and wearables—where the original application space was far from the factory.
Would our findings be different for technologies that were originally developed to solve operational problems, such as manufacturing execution systems, cyber-physical production systems, cobots, or industrial robots?