@* * Copyright 2021 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import config.ApplicationConfig @import include._ @import domain.models.applications.Application @import domain.models.developers.DeveloperSession @this(devMain: DevMain) @(app: Application)( implicit request: play.api.mvc.Request[Any], loggedIn: DeveloperSession, messagesProvider: MessagesProvider, applicationConfig: ApplicationConfig) @devMain( title = "Application deleted", userFullName = loggedIn.loggedInName, developerSession = Some(loggedIn) ) {
Your sandbox application @app.name is now deleted.
View your applications or add an application to the sandbox.
}


JPNEVULATOR(1) User Commands JPNEVULATOR(1) NAME jpnevulator - Just another serial sniffer SYNOPSIS jpnevulator [OPTION]... <FILE> DESCRIPTION jpnevulator is a handy serial sniffer. You can use it to send data on a serial device too. You can read or write from/to one or more serial devices at the same time. In write (--write) mode data to be sent on the serial device(s) is read from a file or stdin in hexadecimal notation. The input format is FD or 0xFD. Of course all input is treated case-insensitive. Spaces may or may not be included in the input. So DEADBEEF is exactly the same as DE AD BE EF. Data is sent on the serial device(s) line by line. In read (--read) mode data to be read from the serial device(s) is writ‐ ten to a file or stdout in hexadecimal notation. Skim through the options for several enhancements in the output. It's even possible to pass(--pass) on the data between the several serial devices. Mandatory arguments to long options are mandatory for short options too. Generic options: -f, --file=NAME In write mode read the contents of the file given and send them on the serial device(s) and in read mode write the contents of the serial device(s) to the file given. -h, --help Shows a brief list of options. -l, --alias-separator Use the given string as the alias separator. See --tty for more information. -r, --read Put the program in read mode. This way you read the data from the given serial device(s) and write it to the file given or stdout if none given. See the read options section for more read specific options. -t, --tty=NAME:ALIAS The serial device to read from or write to. Use multiple times to read/write from/to more than one serial device(s). For handy ref‐ erence you can also separate an alias from the tty name with a collon ':'. If a collon is for some strange reason part of your device name, you can use the --alias-separator option to specify another separation string. If an alias is given it will be used as the name of the serial device. -v, --version Output the version information, a small GPL notice and exit. -w, --write Put the program in write mode. This way you read data from a given file or stdin if none given and write it to the serial device(s) given. See the write options section for more write specific options. Read options: -a, --ascii Besides the hexadecimal output also display an extra column with the data in the ASCII representation. Non printable characters are displayed as a dot '.'. The ASCII data is displayed after the hexadecimal data. -b, --byte-count Besides the hexadecimal output also display an extra column with the current index number of the byte in the output. These numbers are displayed in front of the hexadecimal data. When readin from multiple serial devices at the same time the index number will increase per serial device. -e, --timing-delta=MICROSECONDS The timing delta is the amount of microseconds between two bytes that the latter is considered to be part of a new package. The default is 100 miliseconds. Use this option in conjunction with the --timing-print option. -g, --timing-print Print a line of timing information before every continues stream of bytes. When multiple serial devices are given also print the name or alias of the device where the data is coming from. -i, --width-delta=WIDTH The number of bytes to display on one line. The default is 16. -P, --pass This one passes all the data between the serial devices. Handy if you want to put your serial sniffer in between the serial devices you want to sniff. Write options: -c, --checksum Append a single checksum byte to the line of data written to the serial device(s) chosen. This checksum is a simple modulo 256 addition of all input bytes on a line. -d, --delay-line=MICROSECONDS This delay is an optional amount of microseconds to wait in between every input line is sent on the serial device(s). -k, --delay-byte=MICROSECONDS This delay is an optional amount of microseconds to wait in between every input byte is sent on the serial device(s). -j, --fuck-up This is the special fuck up option. When the calculation of a checksum is chosen (see checksum and crc* options) the checkum will be crippled on purpose. Carefully named after the special Jan Arie de Bruin 'fuck up crc' button. -n, --no-send Do not actually send the bytes on the serial device(s). Rather pointless, but seemed one day long ago to be a rather handy fea‐ ture. -p, --print Besided sending the data on the serial device(s) also write the data to stdout. -s, --size=SIZE The maximum number of bytes per line to send on the serial device(s). The default is 22, coming from back in the Cham2 days of the program. -y, --crc16=POLY Append a crc16 checksum to the line of data written to the serial device(s) chosen. Use the optionally given poly as the polyno‐ mial. Specify the polynomial as hexadecimal value, as in 0xA001 (the default). -z, --crc8=POLY Append a crc8 checksum to the line of data written to the serial device(s) chosen. Use the optionally given poly as the polyno‐ mial. Specify the polynomial as hexadecimal value, as in 0x07 (the default). DIAGNOSTICS Normally, exit status is 0 if the program did run with no problem whatso‐ ever. If the exit status is not equal to 0 an error message is printed on stderr which should help you solve the problem. BUGS Order of bytes broke when reading several tty devices at once The display of incoming bytes can be broke if you use multiple tty devices to read from. At the moment I do not have a solution for this problem. Since I use select() to watch the several tty devices and after the select() I have to read() them one by one, I can not completely 100% display which bytes came after which on different tty devices. Take the example below: $ jpnevulator --ascii --timing-print --tty /dev/ttyS0 --tty /dev/ttyUSB0 --read 2006-05-30 13:23:49.461075: /dev/ttyS0 00 00 05 3B 0D 00 00 05 ...;.... 2006-05-30 13:23:49.461113: /dev/ttyUSB0 00 05 3B 0D 00 00 05 3B 0D ..;....;. 2006-05-30 13:23:49.473074: /dev/ttyS0 3B 0D 00 00 05 3B 0D ;....;. 2006-05-30 13:23:49.473105: /dev/ttyUSB0 00 12 05 06 39 00 12 05 06 39 1F 00 22 80 00 0E ....9....9.."... $ And now see the order in which things really got sent on the line: /dev/ttyS0: 00 00 05 3B 0D /dev/ttyUSB0: 00 00 05 3B 0D /dev/ttyS0: 00 00 05 3B 0D /dev/ttyUSB0: 00 00 05 3B 0D /dev/ttyS0: 00 00 05 3B 0D /dev/ttyUSB0: 00 00 05 3B 0D 00 12 05 06 39 00 12 05 06 39 ... As you can see /dev/ttyUSB0 receives the echo of all things sent by /dev/ttyS0. This is exactly what happens. But since there does exist a small time between the select() who is happy expressing something is available and the read() who does get the available data, some extra data will be available. I have no idea on how I can use high level system call like select() and read() and be still able to put the bytes in the cor‐ rect order. Anyone an idea? AUTHOR Written by Freddy Spierenburg. REPORTING BUGS Report bugs to<EMAIL_ADDRESS>COPYRIGHT Copyright © 2006-2012 Freddy Spierenburg jpnevulator 1.3.1 January 2012 JPNEVULATOR(1)


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I was born in Albuquerque, but was raised in southern Arizona.
Right now, my main hobby is sleeping. I don't get to spend much time doing it and I'm not very good at it. I enjoy reading, watching television, and hanging out with my loved ones.
I have always wanted to be Indiana Jones so that I can shout "IT BELONGS IN A MUSEUM!"
I live in a rural area north of Albuquerque called Bernalillo.
I enjoy problem solving and creativity. More than anything I would like to find a career where I can use my skills and abilities.


Before Change
from setuptools import setup
import sys
with open("requirements.txt", "r") as f:
required = f.read().splitlines()
setup(name="pytorch_fnet",
description=" a machine learning model for transforming microsocpy images between modalities",
author="Ounkomol, Chek and Fernandes, Daniel A. and Seshamani, Sharmishtaa and Maleckar, Mary M. and Collman, Forrest and Johnson, Gregory R.",
<EMAIL_ADDRESS>After Change
author="Ounkomol, Chek and Fernandes, Daniel A. and Seshamani, Sharmishtaa and Maleckar, Mary M. and Collman, Forrest and Johnson, Gregory R.",
<EMAIL_ADDRESS>url="https://github.com/AllenCellModeling/pytorch_fnet",
packages=setuptools.find_packages(),
)


In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
# TODO: Implement Function
real_input = tf.placeholder(tf.float32, (None, image_height, image_width, image_channels))
z_data = tf.placeholder(tf.float32, (None, z_dim))
learning_rate = tf.placeholder(tf.float32)
return real_input, z_data, learning_rate
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variables in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).
discOutHeight = 7
discOutWidth = 7
discOutDepth = 256
discOutSize = discOutHeight*discOutWidth*discOutDepth
# images size 28x28x3
# transformation to 28x28x64
filter_1 = 64
kernel_size_1 = 5
stride_1 = 1
# transformation to 14x14x128
filter_2 = 128
kernel_size_2 = 5
stride_2 = 2
# transformation to 7x7x256
filter_3 = 256
kernel_size_3 = 5
stride_3 = 2
def discriminator(images, reuse=False, alpha = 0.1):
"""
Create the discriminator network
:param images: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
# TODO: Implement Function
#stddev=0.02
#kernel_initializer = tf.random_normal_initializer(stddev=stddev)
kernel_initializer = tf.contrib.layers.xavier_initializer()
keep_prob = 0.7
with tf.variable_scope('discriminator', reuse=reuse):
x1 = tf.layers.conv2d(images, filter_1, kernel_size_1, strides=stride_1, padding='same',
kernel_initializer=kernel_initializer)
x1 = tf.maximum(alpha * x1, x1)
x1 = tf.nn.dropout(x1, keep_prob)
x1 = tf.layers.conv2d(x1, filter_2, kernel_size_2, strides=stride_2, padding='same',
kernel_initializer=kernel_initializer)
x1 = tf.layers.batch_normalization(x1, training=True)
x1 = tf.maximum(alpha * x1, x1)
x1 = tf.nn.dropout(x1, keep_prob)
x1 = tf.layers.conv2d(x1, filter_3, kernel_size_3, strides=stride_3, padding='same',
kernel_initializer=kernel_initializer)
x1 = tf.layers.batch_normalization(x1, training=True)
x1 = tf.maximum(alpha * x1, x1)
x1 = tf.nn.dropout(x1, keep_prob)
# Flatten it
#flat = tf.reshape(x1, (-1, discOutSize))
flat = tf.contrib.layers.flatten(x1, (-1, discOutSize))
logits = tf.layers.dense(flat, 1)
out = tf.sigmoid(logits)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variables in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True, alpha = 0.1):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
# TODO: Implement Function
keep_prob = 0.5
with tf.variable_scope('generator', reuse=not is_train):
# First fully connected layer
x1 = tf.layers.dense(z, discOutHeight*discOutWidth*512)
# Reshape it to start the convolutional stack
x1 = tf.reshape(x1, (-1, discOutHeight, discOutWidth, 512))
x1 = tf.layers.batch_normalization(x1, training=is_train)
x1 = tf.maximum(alpha * x1, x1)
x1 = tf.nn.dropout(x1, keep_prob)
# 7x7x512
x1 = tf.layers.conv2d_transpose(x1, 256, 5, strides=2, padding='same')
x1 = tf.layers.batch_normalization(x1, training=is_train)
x1 = tf.maximum(alpha * x1, x1)
x1 = tf.nn.dropout(x1, keep_prob)
# 14x14x256
x1 = tf.layers.conv2d_transpose(x1, 64, 5, strides=2, padding='same')
x1 = tf.layers.batch_normalization(x1, training=is_train)
x1 = tf.maximum(alpha * x1, x1)
x1 = tf.nn.dropout(x1, keep_prob)
# 28x28x64
x1 = tf.layers.conv2d_transpose(x1, 32, 5, strides=1, padding='same')
x1 = tf.layers.batch_normalization(x1, training=is_train)
x1 = tf.maximum(alpha * x1, x1)
x1 = tf.nn.dropout(x1, keep_prob)
# 28x28x32
# Output layer
logits = tf.layers.conv2d_transpose(x1, out_channel_dim, 5, strides=1, padding='same')
# 28x28x5
out = tf.tanh(logits)
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
# TODO: Implement Function
g_model = generator(input_z, out_channel_dim)
d_model_real, d_logits_real = discriminator(input_real)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
smooth = 0.9
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)*smooth))
d_loss_fake = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# TODO: Implement Function
# Get weights and bias to update
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
g_vars = [var for var in t_vars if var.name.startswith('generator')]
# Optimize
with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
# TODO: Build Model
n_samples, width, height, channels = data_shape
input_real, input_z, learn_rate = model_inputs(width, height, channels, z_dim)
d_loss, g_loss = model_loss(input_real, input_z, channels)
d_opt, g_opt = model_opt(d_loss, g_loss, learn_rate, beta1)
steps = 0
print_every = 10
show_every = 200
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
for batch_images in get_batches(batch_size):
# TODO: Train Model
steps += 1
batch_images*=2
# Sample random noise for G
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
# Run optimizers
_ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, learn_rate: learning_rate})
_ = sess.run(g_opt, feed_dict={input_z: batch_z, input_real: batch_images, learn_rate: learning_rate})
_ = sess.run(g_opt, feed_dict={input_z: batch_z, input_real: batch_images, learn_rate: learning_rate})
if steps % show_every == 0:
n_images = 16
show_generator_output(sess, n_images, input_z, channels, data_image_mode)
if steps % print_every == 0:
# At the end of each epoch, get the losses and print them out
train_loss_d = d_loss.eval({input_z: batch_z, input_real: batch_images})
train_loss_g = g_loss.eval({input_z: batch_z})
print("Epoch {}/{}...".format(epoch_i, epoch_count),
"Discriminator Loss: {:.4f}...".format(train_loss_d),
"Generator Loss: {:.4f}".format(train_loss_g))
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 64
z_dim = 100
learning_rate = 0.0005
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 64
z_dim = 100
learning_rate = 0.0005
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


Merge the two subarrays below into the larger array. To move a value in a subarray, click on it (it will then be highlighted in yellow), and then click on the proper position in the array above.
Merging the sorted subarrays results in a sorted final array


Small project to visualize sorting algorithms. The purpose was to play around drawing with canvas.
Speed Low to High.


This package only contains one JexlContext implementation, the HashMapContext. A HashMapContext is simply an extension of HashMap which implements the JexlContext interface.


Next: End of parse, Previous: Input, Up: Top [Contents][Index]
A parse is exhausted when it cannot accept any further input. A parse is active iff it is not exhausted. For a parse to be exhausted, the furthest earleme and the current earleme must be equal. However, the converse is not always the case: if more tokens can be read at the current earleme, then it is possible for the furthest earleme and the current earleme to be equal in an active parse.
Parse exhaustion always has a location.
That is, if a parse is exhausted it is exhausted at some earleme location X
.
If a parse is exhausted at location X
, then
X
.
X
.
X
.
X
.
X
.
X
.
X
.
marpa_r_alternative()
after a parser has become exhausted.
X
.
marpa_r_earleme_complete()
after a parser has become exhausted.
Users sometimes assume that parse exhaustion means parse failure. But other users sometimes assume that parse exhaustion means parse success. For many grammars, there are strong associations between parse exhaustion and parse success, but the strong association can go either way, Both exhaustion-loving and exhaustion-hating grammars are very common in practical application.
In an
exhaustion-hating
application,
parse exhaustion typically means parse failure.
C programs, Perl scripts and most programming languages
are exhaustion-hating applications.
If a C program is well-formed,
it is always possible to read more input.
The same is true of a Perl program that does not have a __DATA__
section.
In an exhaustion-loving application parse exhaustion means parse success. A toy example of an exhaustion-loving application is the language consisting of balanced parentheses. When the parentheses come into perfect balance the parse is exhausted, because any further input would unbalance the brackets. And the parse succeeds when the parentheses come into perfect balance. Exhaustion means success. Any language that balances start and end indicators will tend to be exhaustion-loving. HTML and XML, with their start and end tags, can be seen as exhaustion-loving languages.
One common form of exhaustion-loving parsing occurs in lexers that look for longest matches. Exhaustion will indicate that the longest match has been found.
It is possible for a language to be
exhaustion-loving at some points
and exhaustion-hating at others.
We mentioned Perl’s __DATA__
as a complication in a
basically exhaustion-hating language.
marpa_r_earleme_complete()
and
marpa_r_start_input
are the only methods
that may encounter parse exhaustion.
See marpa_r_earleme_complete(), and
marpa_r_start_input().
When the marpa_r_start_input
or
marpa_r_earleme_complete()
methods
exhaust the parse,
they trigger a MARPA_EVENT_EXHAUSTED
event.
Applications
can also query
parse exhaustion status directly
with the
marpa_r_is_exhausted()
method.
See marpa_r_is_exhausted().
Parse exhaustion can be triggered on method success
by either the marpa_r_earleme_complete()
or
the marpa_r_start_input
method.
Parse exhaustion can be triggered on method failure
by the marpa_r_earleme_complete()
method.
Parse exhaustion triggered on method success is called
parse exhaustion on success or
exhaustion on success.
Parse exhaustion triggered on method failure is called
parse exhaustion on failure or
exhaustion on failure.
Next: End of parse, Previous: Input, Up: Top [Contents][Index]


{{+bindTo:partials.standard_nacl_api}}
| PP_Resource(* | Create )(PP_Instance instance, PP_Resource config, PPB_Audio_Callback audio_callback, void *user_data) |
| PP_Bool(* | IsAudio )(PP_Resource resource) |
| PP_Resource(* | GetCurrentConfig )(PP_Resource audio) |
| PP_Bool(* | StartPlayback )(PP_Resource audio) |
| PP_Bool(* | StopPlayback )(PP_Resource audio) |
The PPB_Audio
interface contains pointers to several functions for handling audio resources.
Refer to the Audio chapter in the Developer's Guide for information on using this interface. Please see descriptions for each PPB_Audio
and PPB_AudioConfig
function for more details. A C example using PPB_Audio
and PPB_AudioConfig
follows.
Example:
void audio_callback(void* sample_buffer, uint32_t buffer_size_in_bytes, void* user_data) { ... quickly fill in the buffer with samples and return to caller ... } ...Assume the application has cached the audio configuration interface in audio_config_interface and the audio interface in audio_interface... uint32_t count = audio_config_interface->RecommendSampleFrameCount( PP_AUDIOSAMPLERATE_44100, 4096); PP_Resource pp_audio_config = audio_config_interface->CreateStereo16Bit( pp_instance, PP_AUDIOSAMPLERATE_44100, count); PP_Resource pp_audio = audio_interface->Create(pp_instance, pp_audio_config, audio_callback, NULL); audio_interface->StartPlayback(pp_audio); ...audio_callback() will now be periodically invoked on a separate thread...
| PP_Resource(* PPB_Audio::Create)(PP_Instance instance, PP_Resource config, PPB_Audio_Callback audio_callback, void *user_data) |
Create() creates an audio resource.
No sound will be heard until StartPlayback() is called. The callback is called with the buffer address and given user data whenever the buffer needs to be filled. From within the callback, you should not call PPB_Audio
functions. The callback will be called on a different thread than the one which created the interface. For performance-critical applications (i.e. low-latency audio), the callback should avoid blocking or calling functions that can obtain locks, such as malloc. The layout and the size of the buffer passed to the audio callback will be determined by the device configuration and is specified in the AudioConfig
documentation.
| [in] | instance | A PP_Instance identifying one instance of a module. |
| [in] | config | A PP_Resource corresponding to an audio config resource. |
| [in] | audio_callback | A PPB_Audio_Callback callback function that the browser calls when it needs more samples to play. |
| [in] | user_data | A pointer to user data used in the callback function. |
PP_Resource
containing the audio resource if successful or 0 if the configuration cannot be honored or the callback is null. GetCurrrentConfig() returns an audio config resource for the given audio resource.
| [in] | config | A PP_Resource corresponding to an audio resource. |
PP_Resource
containing the audio config resource if successful. | PP_Bool(* PPB_Audio::IsAudio)(PP_Resource resource) |
IsAudio() determines if the provided resource is an audio resource.
| [in] | resource | A PP_Resource corresponding to a generic resource. |
PP_Bool
containing containing PP_TRUE
if the given resource is an Audio resource, otherwise PP_FALSE
. | PP_Bool(* PPB_Audio::StartPlayback)(PP_Resource audio) |
StartPlayback() starts the playback of the audio resource and begins periodically calling the callback.
| [in] | config | A PP_Resource corresponding to an audio resource. |
PP_Bool
containing PP_TRUE
if successful, otherwise PP_FALSE
. Also returns PP_TRUE
(and be a no-op) if called while playback is already in progress. | PP_Bool(* PPB_Audio::StopPlayback)(PP_Resource audio) |
StopPlayback() stops the playback of the audio resource.
| [in] | config | A PP_Resource corresponding to an audio resource. |
PP_Bool
containing PP_TRUE
if successful, otherwise PP_FALSE
. Also returns PP_TRUE
(and is a no-op) if called while playback is already stopped. If a callback is in progress, StopPlayback() will block until the callback completes.


4 May those who seek my life be shamed and dishonored.
May those who plan to harm me be turned back and confounded.
5 May they be as chaff before the wind,
as the angel of Yahweh drives them away.
6 May their way be dark and slippery,
as the angel of Yahweh chases them.
7 Without cause they set their net for me;
without cause they dug a pit for my life.
8 Let destruction overtake them by surprise.
Let the net that they have set catch them.
Let them fall into it, to their destruction.
9 But I will be joyful in Yahweh
and rejoice in his salvation.
10 With all my strength I will say, "Yahweh, who is like you,
who rescues the oppressed from those who are too strong for them
and the poor and needy from those who try to rob them?"
11 Unrighteous witnesses rise up;
they accuse me falsely.
12 They repay me evil for good.
I am sorrowful.
13 But, when they were sick, I wore sackcloth;
I fasted for them
with my head bowed on my chest.
14 I went about in grief as for my brother;
I bent down in mourning as for my mother.
15 But when I stumbled, they rejoiced and gathered together;
they gathered together against me, and I was surprised by them.
They tore at me without stopping.
16 With no respect at all they mocked me;
they gnashed at me with their teeth.
17 Lord, how long will you look on?
Rescue my soul from their destructive attacks,
my life from the lions.
18 Then I will thank you in the great assembly;
I will praise you among many people.
19 Do not let my deceitful enemies rejoice over me;
do not let them carry out their wicked schemes.
20 For they do not speak peace,
but they devise deceitful words against those in our land who live in peace.
21 They open their mouths wide against me;
they said, "Ha, ha, our eyes have seen it."
22 You have seen it, Yahweh, do not be silent;
Lord, do not be far from me.
23 Arouse yourself and awake to my defense;
My God and my Lord, defend my cause.
24 Defend me, Yahweh my God, because of your righteousness;
do not let them rejoice over me.
25 Do not let them say in their heart, "Aha, we have what we wanted."
Do not let them say, "We have devoured him."
26 Put them to shame and confound those who want to harm me.
May those who taunt me be covered with shame and dishonor.
27 Let those who desire my vindication shout for joy and be glad;
may they say continually, "Yahweh be praised,
he who delights in the welfare of his servant."
28 Then I will tell of your justice
and praise you all day long.


Airtel Announces Out of Bundle Rates, Revamps Amazing Data Bundles
This is a smart way of having a no expiry option without having non expiry bundles
by Kiruti ItimuAirtel Kenya has today launched out of bundle rates, which comes after Safaricom launched a similar product some time ago. These have a new tagline which is #BeSurewithAirtel
In the previous system, Airtel charged Kshs 4.3 per MB for out of bundle rates which meant that using 5MB of data cost you Kshs 21.50 or if you used 50MB, that would cost Kshs 215!
In the new system, that same 5MB of data will only cost you 1 KES while 50MB of data will only cost you 10 KES. They will also charge Kshs 2 per minute for calls. All you have to do is dial *544*2# according to Airtel.
This is a great move for the over 12 million Airtel customers who will get out of bundle data at cheaper rates.
This is a very smart move by Airtel to have ‘no expiry bundles’ without necessarily having no expiry bundles. By substantially lowering the price of out of bundle rates, Airtel customers can estimate how much their airtime would last them when they are online.
Revamped Amazing data bundles
Airtel is also revamping their Amazing Data Bundles. The company is now giving more data bundles for the same price. The Amazing Data bundles have an expiry period just like before, but now Airtel has decided to double the data offerings in some cases
Here are the new prices which you can compare with the old rates:
- Amazing 20 – 200MB (1 day)
- Amazing 50 – 500 MB (1 day)
- Amazing 50 – 350 MB (7 days)
- Amazing 100 – 750MB (7 days)
- Amazing 300 – 3GB (30 days)
- Amazing 500 – 5GB (30 days)
- Amazing 1000 – 12GB (30 days)
*CLARIFICATION*
We’ve made changes to the article that explains further the new out of bundle plans that Airtel introduced yesterday.


Summer is the hottest of the four temperate seasons, falling after spring and before autumn. At or around the summer solstice, the earliest sunrise and latest sunset occurs, the days are longest and the nights are shortest, with day length decreasing as the season progresses after the solstice.
From an astronomical view, the equinoxes and solstices would be the middle of the respective seasons,[1][2] but sometimes astronomical summer is defined as starting at the solstice, the time of maximal insolation, often identified with the 21st day of June or December. A variable seasonal lag means that the meteorological center of the season, which is based on average temperature patterns, occurs several weeks after the time of maximal insolation.
Schools and universities typically have a summer break to take advantage of the warmer weather and longer days. In almost all countries, children are out of school during this time of year for summer break, although dates vary. In the United States, public schools usually end in late May in Memorial Day weekend, while colleges finish in early May. Public school traditionally resumes near Labor Day, while higher institutions often resume in mid-August.


Sena backs TMC's demand for discussion on economic slowdown in Parliament
We learned from Jaitley the importance of relations and how to maintain them, said Sanjay Raut
by BS ReporterThe Shiv Sena, which has quit the BJP-led National Democratic Alliance, on Monday signed a notice moved by the Trinamool Congress demanding a discussion on the economic slowdown. During obituary references to former finance minister Arun Jaitley in the Rajya Sabha, Sena MP Sanjay Raut took potshots at the BJP. “We learned from Jaitley the importance of relations and how to maintain them,” Raut said, which his colleagues took to mean the recent severing of ties between old allies BJP and Sena.
.


Dear INSERT USER HERE, You have a new notification pending which you can see after loggin in your account. Best regards, Revibes


We recognize that the barriers to success in any market are complex problems. We aim to respond to that complexity with technology. Our platform will help the business owner define, understand and respond to their troubles. With one simple tool any user can begin to combat these barriers one small victory at a time.
Check average market prices for your items and other important information like exchange rates.
Set your prices strategically to gain an edge in the market and practice advantageous business decisions
Master trade procedures and practice using the market prices to your benefit


crux compute-q-values
Deprecated.
The
compute-q-values
command has been renamedcalibrate-scores
to reflect its enhanced functionality. The namecompute-q-values
has been retained for backwards compatiblity. Thecompute-q-values
is simply an alias forcalibrate-scores
.


This document is a single-page version of a a multi-page document, suitable for easy printing.
Icon Editor
The Icon Editor tool allows you to create icons for your application, both file icons used by file manager applications and simple tool monikers which you may use to provide graphic monikers for a geode's UI gadgetry.
1 Creating Icons
2 Importing Icons
3 Editing Icons
4 Writing Source Code
5 Icon Databases
6 Exporting to Database
The icons produced by the icon editor are stored in an "icon database" so that they can be viewed and retrieved easily. The icon database is the Icon Editor's "document", so New/Open, Close, Save As, Make Backup and other Document-control commands will operate on the current database. "Save" actually saves the currently edited icon into the current icon database, and saves the database as well.
There are 3 standard kinds of icons in use in the system. Each standard type of icon has 3 default formats: One for VGA screens, one for MCGA (monochrome VGA) screens, and one for CGA screens.
Most icons are used in one of the following ways:
-
File Icons, which are used by GeoManager to display and launch applications. The sizes are 48x30, 48x30 (monochrome), 48x14, 32x20, and 32x20(monochrome).
-
Tool Icons, which are used by controllers in their toolbox UI. The format sizes are 15x15 and 15x10.
-
Mouse Pointers, which are used to provide a cursor tracking the mouse's movement. This format has one standard size:16 x 16.
-
Icons which will appear in the OmniGo's Home Screen application are 16x16 and monochrome.
You may also create custom icons, which start with 1 default format. Custom icons are limited to 1024 pixels wide or tall, and the formats cannot be larger than 64k.
The first time the icon editor is started it will create a blank file icon named "untitled." After that, if there is an icon database available to the icon editor, the icon editor will start with the last icon that was being edited before the editor was shut down.
To create a new icon, choose "Create New Icon" from the Icon menu. The dialog will present 4 options for the type of icon. If you decide to create a custom icon, you should enter the height, width and color scheme for the icon in the provided fields.
There are 2 other ways to create icons. You can import a graphic such as a GIF, TIF, BMP or other supported file format for use as an icon, provided that it is less than 64k (which is the limit for GEOS monikers). You do this using the "Import Graphic" dialog in the Icon menu.
The other way to make an icon in the icon database is to import a moniker or moniker group from the token database, which is the cache of file monikers kept by GeoManager. Select "Token Database" from the Icon menu to get a list of monikers that you may import.
There are a number of features that are useful when editing icons:
-
You can create a format for the icon, and scale it to help create the other formats, using the "Transform Format" dialog under the Format menu.
-
The pixel-edit size can be set using the Options menu. It defaults to 8-bit-wide pixels.
-
The "Preview" dialog allows you to view a format in a generic object. If the format is intended for use in a generic object, you can see what it looks like inverted, and (in the case of triggers and tools) what it looks like with different background colors.
-
You can add your own formats, or delete existing ones, using commands from the Format menu. You might, for example, want to add a SuperVGA format for the icon (system supervga file-icons are 64x40).
-
256-color icons are technically supported, but no special tools are provided for editing them. You can select the red, green, and blue components of the area or line color from the "Area Color" and "Line Color" dialogs. 256-color icons aren't much use unless either:
-
They use colors only from the system's default palette, or
-
They are being used in a 24-bit color environment.
-
You can select the aspect ratio for your icon. This will allow the system to make the best choice among formats when selecting from your moniker list. The choices are CGA, EGA, and VGA. The "VGA" aspect ratio should be used for VGA, MCGA (monochrome VGA), and SVGA formats.
-
You are not required to create multiple formats for your artwork; however we recommend that if you are creating art that could be used under many video modes that you create the three standard formats for the art (VGA, mono VGA, CGA). This shouldn't be too difficult, since there are several tools for working with several formats:
-
The "Transform Format" dialog can be used to create exact copies, or transformed copies, of one format to another.
-
The "Resize Format" dialog changes the size and shape of a single format.
-
The "Flip Format" dialog allows you to flip an icon format horizontally or vertically, or to rotate it 90 degrees.
Icon Editor: 4
Writing Source Code
When the icon is finished, make sure it's saved (File->Save), and then choose "Write Source Code" from the Icon Menu. Follow these steps to get source code:
-
Enter a DOS 8.3 filename for the source file
-
To write only the current format, leave the "Formats" group at "Current Format"
-
To write source for all the formats, choose "All Formats"
-
Select GOC source (assembler is used in-house)
A dialog should appear when the source code has been written, saying "Source Code Written Successfully". If a problem is encountered in creating or writing a file, check the permissions on your document directory, and make sure you have enough disk space for the text file (only a few hundred bytes should be necessary).
The file should appear in your document directory. It's a text file with GOC moniker source code. This source code can be included in your application after you make the following changes:
-
The formats for the icon will have names like "Moniker0". You should give them appropriate names.
-
The monikers must be placed in a resource. You could place them between statements like:
@start APPMONIKERRESOURCE, data;
@end APPMONIKERRESOURCE;
In your .gp file, this resource should have the attributes "lmem, read-only, shared".
You may wish to add the line "style = tool;" for icons that are going to be used as toolbox UI, to assist the specific UI in deciding how to draw them.
Your .goc file must #include <gstring.h>, an include file in which the graphics string data structures used to describe visual monikers are described. (Esp programs include
gstring.def
.)
The icon editor can work with more than one icon database at a time via the Multiple Document Interface standard. Each database has its own window, each window having four views. The leftmost view is the database. The top-right view is the "Pixel View", the main editing area. The two remaining views are next to each other in the lower-right portion of the window. The left view is the actual-size view of the icon, and is editable. The right window is the format list, showing all formats of the icon currently being edited.
Double-clicking an icon in the database viewer will select it for editing. The currently-edited icon is important in the following ways:
-
It is (of course) the only icon being edited in the database associated with that window.
-
Its size determines the shapes of the various views, which will try to adjust themselves to fit in the window as best they can.
-
It is the icon that appears in the "Preview" dialog.
-
It is the icon used in the "Export to Token database" dialog (explained below).
-
It is the target of all operations in the Icon and Format menus (except "create new icon").
The database viewer supports all clipboard operations except for Undo. Icons may be selected and moved or copied between databases. This can be done via the Edit menu or quick-transfer.
The format list is used to switch editing to a different format in the same icon. This can only be done with the mouse.
To get more room for editing, use the Options menu to temporarily hide the database viewer or format list while editing.
Icon Editor: 6
Exporting to Database
This is the function that most people associate with an icon editor. The token database is a cache of moniker lists used by GeoManager and other applications. The token database exists so that every time an application's moniker is needed, it is not necessary to start the application in engine mode to request the moniker (a slow process).
The icon editor can change entries in the token database. You cannot change the "built in" moniker for a geode using the icon editor. If you make changes to the token database and then delete the database, then when it gets rebuilt your monikers will no longer be there.
Given that, it's still likely that people will want to set their own monikers in the token database; the icon editor has this ability.
To change an entry:
-
Make sure you are editing the icon you wish to change.
-
Open the File->Export to Token Database dialog.
-
One of the icon's formats should be visible under the "Change To:" text in the dialog. If not, then you are probably editing the wrong icon, or perhaps the icon hasn't been saved into the database.
-
Use the file selector to find the application, document, library, or other driver whose token database entry you wish to change. Otherwise, enter the four token characters for the geode into the Token Characters text field. Select the corresponding operation from the list at the lower-right of the dialog ("Use File Selector" or "Use Token Chars.")
-
The current token-db entry for the selected geode should appear under the "Current Icon" title at the upper-right corner of the dialog.
-
When you are satisfied with the edited icon, change the moniker with the "Change" trigger in the dialog's reply bar. The change will not take effect in GeoManager until you select Disk->Rescan Drives in GeoManager.
-
If you wish to revert a token-database entry to the original, built-in moniker for the geode, select the geode in the file selector and use the "Remove" trigger in the reply bar.
-
This document is a single-page version of a a multi-page document, suitable for easy printing.


Create Campaign Setting
Campaign Setting Name
Calling Options
Caller ID
Enable Auto Pause
Number of Lines
1
2
3
4
Call Recording
Phone Ring time
3 Rings
4 Rings
5 Rings
6 Rings
Make calls to DNC numbers
On-hold Recordings
On-hold Recording1
Select Recording
Recording1
Recording2
On-hold Recording2
Select Recording
Recording1
Recording2
On-hold Recording3
Select Recording
Recording1
Recording2
Answering Machine Options
Answering Machine Recording
Select Recording
Recording1
Recording2
Automatically send email when leaving voicemail.
Choose Email Template
Template 1
Template 2
Email Options
Choose Email Type
None
Single Email
Automatic Follow-up Emails
Choose Email Template
Template 1
Template 2
Search Options
Zillow Search
Trulia Search
Google Maps
Other Options
Promotional Message Recording
Select Recording
Recording1
Recording2
Call Transfer Number
Call Script
Create
Cancel


Component Description
Human papillomavirus (HPV) infection is one of the most
common sexually transmitted infections in the United States. Cervical infection
with certain types of HPV is a major risk factor for cervical cancer in women.
The “high-risk” types of HPV (e.g., HPV 16, 18) are associated with cervical
cancer as well as other anogenital cancers, and the “low-risk” types of HPV
(e.g., HPV 6, 11) are associated with genital warts. No national surveillance
system exists to measure the full burden of HPV infection, and no reliable
national population estimate of HPV exists. NHANES offers a unique opportunity
to assess the prevalence of HPV infection in the general population.
Reducing the prevalence of HPV infection is a
Developmental Healthy People 2010 objective: “Reducing the number of new HPV
cases can help minimize the overall number of cases of high risk subtypes
associated with cervical cancer in females...” Detection and typing of HPV DNA
in vaginal swabs will allow evaluation of trends in prevalence of type-specific
HPV infection by age, sexual behavior, and race/ethnicity. Three HPV vaccines
(Gardasil, Gardasil 9, and Cervarix) are licensed and recommended for use in females.
Two vaccines are licensed and recommended for use in males (Gardasil and
Gardasil 9). In mid-2006, the Advisory Committee on Immunizations (ACIP)
recommended routine vaccination of females aged 11 or 12 years and for those
13-26 years not previously vaccinated. In December 2011, ACIP recommended
routine vaccination of males aged 11 or 12 years and for those aged 13 through
21 years not previously vaccinated. As a vaccine becomes more widely used, the
national prevalence of HPV infection will be critical for evaluating
vaccination strategies in the United States.
Eligible Sample
Examined female participants aged 14-59 years were
eligible. This public data file includes data for examined participants aged 18
to 59 years. Please see Analytic Notes
about the release of data for adolescents aged 14-17 years.
Description of Laboratory Methodology
This assay used the Roche Linear Array HPV Genotyping
test that is based on HPV L1 consensus polymerase chain reaction (PCR) with
biotinylated PGMY09/11 primer sets. It also includes biotinylated β-globin
primers as an internal control for sample amplification. The primer mix
amplified essentially all HPV types found in the genital tract along with the
human β-globin gene. After amplification, the samples were typed by
hybridization to the typing strips followed by colorimetric detection. The
strip is a linear array of probes specific for 37 HPV types (6, 11, 16, 18, 26,
31, 33, 35, 39, 40, 42, 45, 51, 52, 53, 54, 55, 56, 58, 59, 61, 62, 64, 66, 67,
68, 69, 70, 71, 72, 73, 81, 82, 83, 84, 89, and IS39) and for the positive
β-globin control as well. Types were read by comparing the reaction pattern to
the typing template. Samples that were negative for HPV and the β-globin
control indicated lack of a suitable sample and were considered inadequate for
interpretation (Linear Array HPV Genotyping Test Application manual,
2008). Refer to the Laboratory Method Files section for a
detailed description of the laboratory methods used.
Laboratory Method Files
HPV Vaginal Swab Linear Array Laboratory Procedure Manual
(November 2018)
Laboratory Quality Assurance and Monitoring
Vaginal swab samples were processed, stored, and shipped to
the Chronic Viral Diseases Branch, Division of High-Consequence Pathogens and
Pathology, National Center for Emerging and Zoonotic Infectious Diseases,
Centers for Disease Control and Prevention, Atlanta, GA for analysis.
Detailed instructions on specimen collection and
processing are discussed in the NHANES
Laboratory Procedures Manual (LPM). Swabs were stored at room
temperature until they were shipped to the National Center for Emerging and
Zoonotic Infectious Diseases for testing.
Detailed QA/QC instructions are discussed in the NHANES LPM.
Mobile Examination Centers (MECs)
Laboratory team performance is monitored using several
techniques. NCHS and contract consultants use a structured competency
assessment evaluation during visits to evaluate both the quality of the
laboratory work and the quality-control procedures. Each laboratory staff
member is observed for equipment operation, specimen collection and
preparation; testing procedures and constructive feedback are given to each
staff member. Formal retraining sessions are conducted annually to ensure that
required skill levels were maintained.
Analytical Laboratories
NHANES uses several methods to monitor the quality of the
analyses performed by the contract laboratories. In the MEC, these methods
include performing blind split samples collected on “dry run” sessions. In
addition, contract laboratories randomly perform repeat testing on 2% of all
specimens.
Progress reports containing any problems encountered
during shipping or receipt of specimens, summary statistics for each control
pool, QC graphs, instrument calibration, reagents, and any special
considerations are submitted to NCHS quarterly. The reports are reviewed for trends
or shifts in the data. The laboratories are required to explain any identified
areas of concern.
Data Processing and Editing
The data were reviewed. Incomplete data or improbable
values were sent to the performing laboratory for confirmation.
Analytic Notes
Note: In the 2015-2016 cycle, Cobas HPV Swab High-Risk
results (LBXHP2C) are being released separately in two new datasets: HPVSWC_I
and HPVC_I_R. In the 2013-2014 cycle, LBXHP2C results were released with the
Roche Linear Array results in datasets HPVSWR_H and HPVS_H_R.
Refer to the 2015-2016
Laboratory Data Overview for general information on NHANES
laboratory data.
Sample Weights
MEC exam sample weights should be used for analyses.
Demographic and Other Related Variables
The analysis of NHANES laboratory data must be conducted
using the appropriate survey design and demographic variables. The NHANES 2015-2016
Demographics File contains demographic data, health indicators, and
other related information collected during household interviews as well as the
sample design variables. The recommended procedure for variance estimation
requires use of stratum and PSU variables (SDMVSTRA and SDMVPSU, respectively)
in the demographic data file.
This laboratory data file can be linked to the other
NHANES data files using the unique survey participant identifier (i.e., SEQN).
The Questionnaire data files contain socio-economic data,
health indicators, and other related information collected during household
interviews. Certain sensitive data on participants under 18 years of age (e.g.,
HPV typing results, sexual behavior variables) are not included in the public
use files. These data may be requested as described in the NHANES guidelines.
The public release data file includes HPV vaginal swab
data for participants aged 18-59. HPV vaginal swab data for youth aged 14-17
years are available through the NCHS Research Data Center (RDC).
HPV Summary Variable
The HPV PCR Summary variable (LBDRPCR) indicates if at
least one type is positive (LBDRPCR=1); the sample is negative (LBDRPCR=2); the
sample is inadequate (LBDRPCR=3); or the sample is missing (LBDRPCR=.).
If beta-globin is not present, both LBDRHP and LBDRLP are
negative in the sample and no HPV type is detected, the sample is coded as “Inadequate”.
If any of the types on the strips (LBDR06-LBDRPI) are
positive, the sample is coded as positive. If all of the types on the strip are
coded as negative, and beta-globin is detected (either LBDRHP or LBDRLP is
positive) the sample is coded as negative.
Variables LBDRHP through LBDRPI are from the RUO Roche
Linear Array HPV typing assay, however LBDR52 also includes information from a
type-specific assay for HPV 52. The Linear Array typing strip includes an XR
probe that hybridizes with HPV 52 as well as HPV types 33, 35 and 58. Samples
positive for the XR probe and 33, 35, or 58 require specific testing to confirm
the presence of HPV 52 (Onyekwuluje et al., 2012).
Detection Limits
If data is qualitative, the use of lower limits of detection (LLODs) is not
applicable.
Please refer to the NHANES Analytic
Guidelines and the on-line NHANES Tutorial for further
details on the use of sample weights and other analytic issues.


Next: lambda-list-keywords, Previous: compiled-function-p, Up: Data and Control Flow Dictionary
An integer not smaller than 50 and at least as great as the value of lambda-parameters-limit, the exact magnitude of which is implementation-dependent.
The upper exclusive bound on the number of arguments that may be passed to a function.


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ANTONIA'S LINE A film review by Ben Hoffman Copyright 1996 Ben Hoffman
Filled with almost a dozen of the most fascinating characters who comprise the story of this utterly intriguing film, Antonia's Line does not waste a moment as it moves from its beginning to its conclusion when Antonia (Willeke Van Ammelrooy) dies. The story, in parts, is narrated by Sarah, (Thyrza Ravesteijn ). Antonia's great-granddaughter who, with family and friends stand around 88-year- old Antonia's bed as the old woman says that today is her last day of life. Before she dies, she reflects in her mind's eye on her long and full life and, through one long flashback, we see that life and the people whom she encountered on the way to this fateful final day.
All of these people have experienced their own lives, most of them filled with excitement, passion, hard work. Here we have one beautiful fairy tale. There is Antonia's longtime friend known as "Crooked Finger " (Mil Seghers) . . . and Olga, the Russian (Fran Waller Zeper) whose three jobs consist of cafe-owner, undertaker and midwife. There is Farmer Daan, (Jakob Beks), the chauvinist landowner who believes women have no other purpose in life than to breed.  The town has other retarded inhabitants such as Loony Lips (Jan Steen). and poor Mad Madonna (Catherine Ten Bruggencate) who, because she cannot marry the love of her life (Paul Kooij) as he is a Protestant, howls at the moon at night. The Village Priest (Leo Hogenboom) is fire and brimstone but has his own fire burning within him And there is Bas (Jan Decleir), a farmer who despite having lived in the town for 20 years is still considered a "newcomer."
Marleen Gorris, who wrote and directed the film, maneuvers the film's characters like a virtuoso juggler, never for a moment missing a beat. Not to be missed.
In Dutch with English subtitles.
4 Bytes
4 bytes = Superb 3 bytes = Too good to be missed 2 bytes = So so 1 byte = Save your money
Ben Hoffman
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 4
French onion soup is very easy to make and is deeply savoury and hearty - and cheesy croutons make it extra special!
Melt the butter in a medium-sized ovenproof pan, add the onions and garlic and gently fry over a low heat for 30-35 minutes, stirring occasionally, until the onions are really soft and a rich dark brown colour. This stage of the recipe is really important, the long slow cooking of the onions gives this soup its lovely rich flavour and colour.
Add the white wine, stirring the bottom of the pan to loosen all the browned onion. Bring it back to the boil then add the Madeira and beef stock.
Bring to the boil and then simmer for about 10-12 minutes.
Meanwhile make the croutons. Toast the bread on both sides and rub the toast with the cut side of a garlic clove. Top with the grated cheese and place under the grill until the cheese has melted.
Taste the soup to check the seasoning, and add salt and freshly ground black pepper to taste. Add another few tablespoons of Madeira to the soup, to boost the flavour and stir well.
Lay the croûtons on top of the soup and scatter with fresh chopped parsley.
To serve, ladle the soup into bowls, making sure each serving has a cheesy croûton. Serve immediately, before the croûton goes soggy.


Map Class
..\src\Map.js:7
The Map represents a Tiled Map, it is created by passing the JSON data exported from Tiled in the constructor.
Constructor
Map
-
data
-
[b2dWorld]
Parameters:
-
data
ObjectThe complete map-data as exported to JSON by Tiled.
-
[b2dWorld]
B2World optionalThe Box2D b2World. Will be created automatically if not supplied.
Item Index
Methods
centerTo
-
object
Centers the 'camera' to the given object, this can be either a Box2D Body or an createjs.DisplayObject
Parameters:
-
object
createjs.DisplayObject | Box2D.Dynamics.b2BodyThe object to center the 'camera' on.
drawDebugData
-
alpha
Draws the Box2D DebugData to the previously setup canvas. The target canvas is the same as the createjs.Stage if not defined otherwise.
Parameters:
-
alpha
Number
generateTileSets
()
protected
Generates the SpriteSheets from the Tiled tilesets
getSpriteSheetByTileId
-
tileid
Returns the SpriteSheet for a given Tiled tileid. Note: Tiled tileids are 1-based, createjs.SpriteSheet-frames are 0-based. This methods requires 1-based tileids.
Parameters:
-
tileid
Int
Returns:
getTileById
-
tileid
Return the tileset-frame based on a given Tiled tileid. Note: Tiled tileids are 1-based, createjs.SpriteSheet-frames are 0-based. This methods requires 1-based tileids.
Parameters:
-
tileid
Int
Returns:
getTileProperties
-
tileid
Returns the tile-properties for a given Tiled tileid. Note: Tiled tileids are 1-based, createjs.SpriteSheet-frames are 0-based. This methods requires 1-based tileids.
Parameters:
-
tileid
Int
Returns:
setupDebugDraw
-
canvas
Sets up the Box2D DebugDraw, this is usually done automatically by the map, but can be called from the outside to setup the DebugDraw with a different canvas.
Parameters:
-
canvas
HTMLCanvasElement
Returns:
setupLayers
()
protected
Sets up the layers from the Tiled map
update
-
e
Updates the world simulation, forces and force-fields are applied, this should be called on every tick before the stage updates.
Parameters:
-
e
NumberMilliseconds since the last update (will default to 30).


Arrow keys: move
Number keys: place numbers
Delete: delete numbers
C: Check if the solution is ok (can be used even if the board is not completed)


Guidance
A video providing information for schools on making the most of financial review and self-assessment tools.
Making the most of financial review and self-assessment tools
This video introduces the department’s self-assessment tools including the efficiency metric, benchmarking report card and benchmarking websites.
Ed Schwitzer from the Department for Education explains how the tools can be used to help with discussions and actions at your school and with other schools facing similar challenges. This video is aimed at those working in schools and in particular governors, head teachers and school business managers.
This video is part of a suite of information, tools, training and guidance published by the Department for Education to help schools improve their financial management and efficiency. Our further information on the metric tool and benchmarking make up part of that collection.
We’d like to hear from you if you have any questions, comments or suggestions about this page or any of the schools financial efficiency content. This includes how we can improve the content and what other materials you would find helpful. If you are an academy, local authority or post-16 provider, please use the EFA enquiry form. Please include schools financial efficiency in the subject title.
For all other institutions, including maintained schools, please use the DfE enquiry form. Please include schools financial efficiency in the subject title.


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Shared Notes: How bad guys compromise networks and internet applications (From Section 1.5)
What types of attacks can malicious attacker use to compromise a network? Here are some of the most common ways:
DDoS/DoS (Distributed Denial of Service/Denial of Service)
Bandwidth Flooding: Sending many packets to a target host in order to prevent any other users from using the host system.
Example (very old): Pinging a server with the maximum amount of bytes from X amount of computers (or a single computer) to flood the host server with data.
Connection Flooding: Creating a large amount of connections (usually via TCP)to a target host in an attempt to eat up all available connections so that the host system cannot allow any more connections from users.
Example: Using a botnet of slave computers to request (and possibly connect) to a website X amount of times each, eating up all of the available connections.
Vulnerability Attack: Targeting a known vulnerability on a host system by sending a specialized set of packets, or information within the packets, that crashes the host's system.
Example: A host application can only take X amount of characters as input, anything more will cause the program to crash
Malware (Worms, Virii (Viruses), and Trojans oh my!)
Worms: Malware that targets host systems that are exploitable in certain ways without any user interaction, and replicates by targeting similar systems once inside of a host system.
Virii (Viruses): Malware that gets onto a system with some user interaction, usually via an email, phishing (social engineering), or by visiting a malicious site. Once inside a host system, it continues to replicate by phishing from the host (usually via email) or by making the host a slave.
Trojan Horse Programs (not covered): Malware that is used to give backdoors into host systems so that the attacker, or even multiple attackers, can use the computer for credential theft, phishing, spam, and more. The way this type of malware works is similar to the original story of the Wooden Trojan Horse, as trojans disguise themselves as legitimate programs, or are implanted in seemingly harmless programs.
Packet Sniffing
Usually Done via a MITM (Man in the Middle Attack via arpspoofing, DNS hijacking, etc.), this involves the attacker running a packet sniffer (looking at you, wireshark!) in order to gain sensitive information about the victim(s). This could include passwords, file downloads, VoIP (Voice of IP calls), and more. Password stealing requires the attacker to be running an SSL stripper, which takes away the secure certificate of the site and enforces http over https (passwords can be seen in cleartext this way).
IP Spoofing
This is done by manipulating the packets sent so that the source IP address (where the information from the packets is coming from, and where it's going to be sent to be received) is modified so that a different IP is used in place of the attackers IP. This could be done for a multitude of reasons, however the biggest ones can be to perform incomplete Syn-Ack DoS/DDoS attacks and to mask the attackers IP address.
There are other ways attackers can compromise hosts (via various forms of exploitation, phishing, ransom-ware, spam, etc), but these will be covered later!


Once you've created your garage you can retrieve and edit it by entering your first name, last name and your password.


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Native American woman, 32, found in submerged truck was strapped into passenger seat, court docs reveal
by Stephen SoraceA Native American woman whose body was discovered in a submerged truck in a North Dakota lake more than a year after she went missing was strapped into the passenger side with a seatbelt around her waist, according to unsealed court documents.
The disappearance and death of 32-year-old Olivia Lone Bear, however, remains a mystery as federal officials unsealed three search warrants Wednesday and traveled to New Town to update Lone Bear’s family on the investigation.
REMAINS OF MISSOURI WOMAN BELIEVED TO HAVE BEEN FOUND AFTER HUSBAND PROVIDES INFORMATION
The mother was reported missing to the Three Affiliated Tribes Police Department on Oct. 27, 2017. A sonar-equipped boat found the truck near the Fort Berthold Reservation on July 31, 2018, with Lone Bear’s body inside. No obvious injuries were found on her body, and an autopsy failed to determine the cause of death.
The new details in the unsealed documents indicated that investigators have not ruled out murder or manslaughter, the Bismarck Tribune reported.
The documents also revealed Lone Bear’s last text messages before going missing.
A witness told investigators that one message said she had been to a bonfire and was going “mudding” — a practice of off-road driving usually conducted near rivers or swamps, according to one affidavit. Her next message read: “Good Bye!”
However, none of those interviewed by investigators could identify anyone who had gone to a bonfire or "mudding" with Lone Bear, according to the affidavit.
Matt Lone Bear, her brother, told the Tribune that the meeting with investigators was “very professional and sincere.”
"Considering we went from not knowing anything to this, I think it’s definitely a big step in the right direction," he said.
The FBI also announced an increased reward of up to $10,000 for information on those responsible for her disappearance.
“Olivia's family and members of her community want to know what happened to her and so do we," Minneapolis FBI Special Agent in Charge Jill Sanborn said in a statement.
Native Americans and others have sought to draw attention to violence against Native American women, who have been victimized at high rates for decades.
CLICK HERE FOR THE FOX NEWS APP
It’s unknown how many missing and murdered Native American women and girls there are because cases often go unreported and others aren’t documented thoroughly. No specific government databases are dedicated to tracking these cases.
The Associated Press contributed to this report.


--- layout: post title: dominic wilcox luxury skimming stones date: '2010-09-04T13:54:08+01:00' tags: [] tumblr_url: http://backlog.robbevan.com/post/1063813087/dominic-wilcox-luxury-skimming-stones ---
Dominic Wilcox: Luxury Skimming Stones


About this app
Data
- The St. Louis Crime Tracker is built using data from the St. Louis Metropolitan Police Department's crime reports.
- We update the Crime Tracker each month after SLMPD releases the previous month's crime report.
- This data reflects only reported crimes. Not all crimes are reported to the police.
- This data includes only more serious Part I crimes, based on FBI Uniform Crime reporting standards.
Per-capita crime rates
- Per-capita crime rates are based on neighborhood populations, which come with some important caveats:
- The population totals we use to calculate per-capita crime rates are derived from the 2010 Census. Obviously, these rates do not factor in changes that have occurred since 2010.
- Daytime and nighttime populations of neighborhoods can be significantly higher than the residential population, which can skew crime rates upward. For example, the Downtown and Downtown West neighborhoods regularly have the some of the highest per-capita crime rates in the city, mostly due to the large influx of people who don't live in the area.
- We do not calculate per-capita crime rates for parks or neighborhoods with fewer than 300 residents.
Neighborhood incident maps
- For most incidents, police crime reports include X- and Y- coordinates for an incident. We convert the police-provided coordinates into latitude and longitude to generate markers for those incidents.
- For some incidents, police omit coordinates but still provide an address or an intersection. In these cases we generate markers by submitting the address to a geocoding service.
- Police sometimes mark an incident as taking place in a particular neighborhood, but the coordinates and/or the address they provide place the incident within an adjacent neighborhood's boundaries. We are aware of this discrepancy, but do not attempt to correct it on the map.
- In cases of rape, police reports round off addresses in order to avoid identifying victims. For example, "the 2300 block of Fake Street" instead of "2356 Fake Street."
- Incidents which lack coordinates or addresses in the police report have been omitted from the map.


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Release Notes
1.3.0 (Feb 09, 2016)
- CB-3360 Set custom inappbrowser user agent for android
- CB-10538 cordova-plugin-inappbrowser timeout issue
- CB-10395 InAppBrowser's WebView not storing cookies reliable on Android
- Edit package.json license to match SPDX id
- CB-10305 Gray bar appears in the wrong place on iOS
- CB-7786 Support mediaPlaybackRequiresUserAction on Android
- CB-7500 executeScript with callback kills/blurs inAppBrowser window on Android
1.2.1 (Feb 02, 2016)
- CB-10407 InAppBrowser not firing loadstart event on android
- CB-10428 Fix syntax error when browserifying inAppBrowser plugin
- handle app store urls in system browser
- CB-6702 InAppBrowser hangs when opening more than one instance
- CB-10456 InAppBrowser is not closed if I close it programmatically on Android
- CB-10451 InAppBrowser: loadstart event is not triggered on Windows
- CB-10452 InAppBrowser: 'exit' event is not triggered on Windows
- CB-10454 InAppBrowser: 'loaderror' event does not have code and message on Windows
- CB-10450 InAppBrowser: Unable to get property 'canGoBack' of undefined on Windows
- CB-10441 Add auto tests for InAppBrowser plugin
1.2.0 (Jan 15, 2016)
- CB-8180: Changing methods of interception in
WebViewClient
class
- CB-10009 Improve
InAppBrowser
toolbar look and feel on Windows
- Open a new window on the Browser platform
1.1.1 (Dec 10, 2015)
- CB-9445 Improves executeScript callbacks on iOS
- CB-10035 Incremented plugin version.
- CB-10040 - re-fix: backwards compatible with cordova-ios < 4.0
- CB-8534: Allow plugins to respond to onReceivedHttpAuthRequest. This closes #82
- CB-3750: Fixes spinner on iOS. This closes #89
- CB-7696 Document target=_self behavior for Windows
- CB-10040 - Compile Error in InAppBrowser Plugin for iOS - No known instance method for selector 'URLIsWhitelisted:'
1.1.0 (Nov 18, 2015)
- CB-10035 Updated
RELEASENOTES
to be newest to oldest
- Invoke webview if using local file
- Fixed
zIndex
issue on Windows 8, **8.188 where InAppBrowser opens behind default app.
- fix
async
self usage
- CB-9150 Fix InAppBrowser
executeScript
crash on Windows if no data returned
- CB-10008 Fix InAppBrowser popup layout on Windows
- Setting
setStatusBarStyle
to -1
causes CGContextSaveGState
.
- CB-9167 Fix crash on browser window close
- CB-9799 Fixed
javaDoc
errors.
- Fixing contribute link.
- CB-9760 InAppBrowser: fallback to default
window.open
behavior on Ripple
- CB-9378 Fix InAppBrowser not taking whole screen on Windows
- CB-9158 - InAppBrowser
zoomControls
are always set to true
1.0.1 (Jun 17, 2015)
- CB-9128 cordova-plugin-inappbrowser documentation translation: cordova-plugin-inappbrowser
- fix npm md issue
1.0.0 (Apr 15, 2015)
- CB-8746 gave plugin major version bump
- CB-7689 Adds insertCSS support for windows platform
- CB-4930 - (prefix) InAppBrowser should take into account the status bar
- CB-8635 Improves UX on windows platform
- CB-8661 Return executed script result on Windows
- CB-8683 updated wp and browser specific references of old id to new id
- CB-8683 changed plugin-id to pacakge-name
- CB-8653 properly updated translated docs to use new id
- CB-8653 updated translated docs to use new id
- Use TRAVIS_BUILD_DIR, install paramedic by npm
- CB-8432 Correct styles for browser wrapper to display it correctly on some pages
- CB-8659 - Update InAppBrowser to support both cordova-ios 4.0.x and 3.x (closes #93)
- CB-7961 Add cordova-plugin-inappbrowser support for browser platform
- CB-8653 Updated Readme
- Update docs for Android zoom=no option
- Added option to disable/enable zoom controls
- updated docs, set hardwareback default to true
- Add a hardwareback option to allow for the hardware back button to go back.
- CB-8570 Integrate TravisCI
- CB-8438 cordova-plugin-inappbrowser documentation translation: cordova-plugin-inappbrowser
- CB-8538 Added package.json file
- Keep external android pages in a single tab. (close #61)
- CB-8444 Add a clobber for
cordova.InAppBrowser.open
(close #80)
- CB-8444 Don't clobber
window.open
- Add new symbol/clobber to access open function (cordova.InAppBrowser.open
) - Change existing tests to use new symbol (i.e. don't rely on plugin clobber of window.open
) - Add tests to use window.open
via manual replace with new symbol - Update docs to deprecate plugin clobber of window.open
0.6.0 (Feb 04, 2015)
- CB-8270 ios: Remove usage of
[arr JSONString]
, since it's been renamed to cdv_JSONString
- ubuntu: implement
inject*
functions
- ubuntu: port to oxide
- CB-7897 ios, android: Update to work with whilelist plugins in Cordova 4.x
0.5.4 (Dec 02, 2014)
- CB-7784 Exit event is not fired after
InAppBrowser
closing
- CB-7697 Add
locationBar
support to InAppBrowser
Windows platform version
- CB-7690
InAppBrowser
loadstart/loadstop
events issues
- CB-7695 Fix
InAppBrowser
injectScriptFile
for Windows 8.1 / Windows Phone 8.1
- CB-7692
InAppBrowser
local url opening bug in 8.1
- CB-7688
Alert
is not supported in InAppBrowser
on Windows platform
- CB-7977 Mention
deviceready
in plugin docs
- CB-7876 change test target to avoid undesired redirects
- CB-7712 remove references to
closebuttoncaption
- CB-7850 clarify role of whitelist
- CB-7720 check if event is null since OK string from success callback was removed
- CB-7471 cordova-plugin-inappbrowser documentation translation: cordova-plugin-inappbrowser
0.5.3 (Oct 03, 2014)
- Windows implementation fixes and improvements
- zIndex fixed
- renamed InAppBrowser back to inappbrowser for case sensitive operating systems
- Update french translation
- Update doc to add Windows 8
- Update windows proxy to be both compatible with windows 8 and 8.1
- Rename windows81 by windows8 in src directory
- Append Windows 8.1 platform configuration in plugin.xml
- Append Windows 8.1 proxy using x-ms-webview
0.5.2 (Sep 17, 2014)
- CB-7471 cordova-plugin-inappbrowser documentation translation: cordova-plugin-inappbrowser
- CB-7490 Fixes InAppBrowser manual tests crash on windows platform
- CB-7249 cordova-plugin-inappbrowser documentation translation: cordova-plugin-inappbrowser
- CB-7424 Wrong docs: anchor tags are not supported by the InAppBrowser
- CB-7133 clarify that anchor1 doesn't exist
- CB-7133 more fixup of tests on Android
- CB-7133 fix up the tests for Android
- Add just a bit more logging
- CB-7133 port inappbrowser to plugin-test-framework
- phonegap events supported for _blank target
- inappbrowser _blank target position is fixed
- amazon-fireos related changes.
0.5.1 (Aug 06, 2014)
- ubuntu: support qt 5.2
- FFOS update InAppBrowserProxy.js
- FFOS app needs to be privileged
- CB-6127 Updated translations for docs
- CB-6769 ios: Fix statusbar color reset wasn't working on iOS7+
0.5.0 (Jun 05, 2014)
- CB-6127 Spanish and rench Translations added. Github close #23
- Clean up whitespace (mainly due to no newline at eof warning)
- Adding permission info
- CB-6806 Add license
- CB-6491 add CONTRIBUTING.md
- Add necessary capability so the plugin works on its own
- CB-6474 InAppBrowser. Add data urls support to WP8
- CB-6482 InAppBrowser calls incorrect callback on WP8
- Fixed use of iOS 6 deprecated methods
- CB-6360 - improvement: feature detection instead of iOS version detection
- CB-5649 - InAppBrowser overrides App's orientation
- refactoring fixed
- CB-6396 [Firefox OS] Adding basic support
0.4.0 (Apr 17, 2014)
- CB-6360: [ios] Fix for crash on iOS < 6.0 (closes #37)
- CB-3324: [WP8] Add support for back-button inappbrowser [WP8] if there is no history -> InAppBrowser is closed
- [WP] await async calls, resolve warnings
- [WP] Make InAppBrowser work with embedded files, using system behavior
- CB-6402: [WP8] pass empty string instead of null for [optional] windowFeatures string
- CB-6422: [windows8] use cordova/exec/proxy
- CB-6389 CB-3617: Add clearcache and clearsessioncache options to iOS (like Android)
- Doc update: event name and example param (closes #31)
- CB-6253: [WP] Add Network Capability to WMAppManifest.xml
- CB-6212: [iOS] fix warnings compiled under arm64 64-bit
- CB-6218: Update docs for BB10
- CB-6460: Update license headers
0.3.3 (Mar 5, 2014)
- CB-5534 Fix video/audio does not stop playing when browser is closed
- CB-6172 Fix broken install on case-sensitive file-systems
0.3.2 (Feb 26, 2014)
- Validate that callbackId is correctly formed
- CB-6035 Move js-module so it is not loaded on unsupported platforms
- Removed some iOS6 Deprecations
0.3.1 (Feb 05, 2014)
- CB-5756: Android: Use WebView.evaluateJavascript for script injection on Android 4.4+
- Didn't test on ICS or lower, getDrawable isn't supported until Jellybean
- add ubuntu platform
- Adding drawables to the inAppBrowser. This doesn't look quite right, but it's a HUGE improvement over the previous settings
- CB-5756: Android: Use WebView.evaluateJavascript for script injection on Android 4.4+
- Remove alive from InAppBrowser.js since it didn't catch the case where the browser is closed by the user.
- CB-5733 Fix IAB.close() not working if called before show() animation is done
0.2.5 (Dec 4, 2013)
- Remove merge conflict tag
- CB-4724 fixed UriFormatException
- add ubuntu platform
- CB-3420 WP feature hidden=yes implemented
- Added amazon-fireos platform. Change to use amazon-fireos as the platform if user agent string contains 'cordova-amazon-fireos'
0.2.4 (Oct 28, 2013)
- CB-5128: added repo + issue tag to plugin.xml for inappbrowser plugin
- CB-4995 Fix crash when WebView is quickly opened then closed.
- CB-4930 - iOS - InAppBrowser should take into account the status bar
- CB-5010 Incremented plugin version on dev branch.
- CB-5010 Updated version and RELEASENOTES.md for release 0.2.3
- CB-4858 - Run IAB methods on the UI thread.
- CB-4858 Convert relative URLs to absolute URLs in JS
- CB-3747 Fix back button having different dismiss logic from the close button.
- CB-5021 Expose closeDialog() as a public function and make it safe to call multiple times.
- CB-5021 Make it safe to call close() multiple times
0.2.3 (Oct 9, 2013)
- CB-4915 Incremented plugin version on dev branch.
- CB-4926 Fixes inappbrowser plugin loading for windows8
0.2.2 (Sept 25, 2013)
- CB-4889 bumping&resetting version
- CB-4788: Modified the onJsPrompt to warn against Cordova calls
- [windows8] commandProxy was moved
- CB-4788: Modified the onJsPrompt to warn against Cordova calls
- [windows8] commandProxy was moved
- CB-4889 renaming core references
- CB-4889 renaming org.apache.cordova.core.inappbrowser to org.apache.cordova.inappbrowser
- CB-4864, CB-4865: Minor improvements to InAppBrowser
- Rename CHANGELOG.md -> RELEASENOTES.md
- CB-4792 Added keepCallback to the show function.
- CB-4752 Incremented plugin version on dev branch.


The header of the grid.
String, default = ''
The header can be simple text or HTML. If you change .header property, you will need to call
.refresh() method to refresh the grid.
Header can be defined during object creation:
Or any time after the grid has been created:
Please note that you will need to set .show.header to true, which is false by default.


--- layout: post title: Double Whammy date: 2009-09-28 12:51:42.000000000 -04:00 type: post published: true status: publish categories: - muffins - recipes - vegan - vegetarian tags: - applesauce - brownies - chocolate - cocoa powder - low fat - muffins - recipe - sunflower seeds - vegan - walnuts - whole wheat pastry flour meta: _oembed_3c43f84e1da5a19e3ec6a6861f9a096b: author: login: sophie email<EMAIL_ADDRESS>display_name: Pika first_name: '' last_name: '' ---
In the spirit of making up for lost time, here are two recipes that will hopefully tide you over until my next three-day weekend. The theme of the week is applesauce.
First up…
Applesauce Muffins with Toasted Sunflower Seeds
Makes 1 dozen muffins
loosely adapted from this recipe
Preheat the oven to 350°F. Line a muffin pan with paper liners.
In a large bowl, mix flour, sugar, baking soda, and salt.
In a medium bowl, mix applesauce, soymilk, vanilla, and vinegar. Add to the dry ingredients and mix into a smooth batter. Fold in sunflower seeds.
Divide batter among muffin cups and bake for 20 min, or until a toothpick inserted into the middle of one comes out clean. Cool. Eat.
The Verdict:
Very tasty! I was a little bit worried because there’s no oil in the recipe, but the muffins turned out very moist and delicious. I’ve never thought of putting sunflower seeds in muffins before, but it turned out to be a very nice touch. (Also, for some unknown reason, they turn green in the muffin like pistachios!?!?)
Second recipe:
Brownie Muffins with Walnuts
Makes 1 dozen muffins
inspired by this recipe
Preheat the oven to 350°F. Line a muffin pan with paper liners.
In a large bowl, mix flour, sugar, cocoa powder, baking soda, and salt.
In a medium bowl, mix water, applesauce, vinegar, and vanilla. Add to the dry ingredients and mix into a smooth batter. Fold in walnuts.
Divide batter among muffin cups and bake for 20 min, or until a toothpick inserted into the middle of one comes out clean. Cool. Eat.
The Verdict:
Delicious! These are sooo chocolaty and fudgy, just like brownies. A great excuse to eat chocolate for breakfast. (Although they’d make a good dessert, too.)
P.S. : Both recipes are vegan, but all you need to know is that they taste good.


Live in Taiwan. A high school student. A anime lover. A life struggler.
And also... Coding at night haha!
Welcome to my homepage! A place which was fulled with magic.


Crawling Ajax applications through dynamic analysis and reconstruction of the UI state changes. Crawljax is based on a method which dynamically builds a `state-flow graph' modeling the various navigation paths and states within an Ajax application.
See more here