CSPICE_CONICS determines the state (position, velocity) of an orbiting
body from a set of elliptic, hyperbolic, or parabolic orbital elements.
Given:
elts the array(s) containing the conic osculating elements describing
the orbit of a body around a primary.
[8,n] = size(elts); double = class(elts)
The elements are, in order:
RP Perifocal distance.
ECC Eccentricity.
INC Inclination.
LNODE Longitude of the ascending node.
ARGP Argument of periapse.
M0 Mean anomaly at epoch.
T0 Epoch.
MU Gravitational parameter.
Units are km, rad, rad/sec, km**3/sec**2.
The epoch T0 is given in ephemeris seconds past J2000.
T0 is the instant at which the state of the body is
specified by the elements.
et the ephemeris time(s) corresponding one-to-one and onto
to each 'elts' at which to determine the state of
the orbiting body
[1,n] = size(et); double = class(et)
Note: The design of cspice_conics supposes the inputs 'elts'
and 'et' originates as the output of another Mice routine
and so will have the same vectorization measure.
Still, in the event the user requires an 'elts' constant over
a vector of 'et', or an 'et' constant over an array of
elts, construct the needed variables with the Matlab code:
Given a constant 'epoch' for an array of 'elts', create the
vector 'et'.
N = size(elts,2);
et = zeros(1, N) + epoch;
Given a constant element set 'elt' for an array of 'et',
create the array 'elts'.
N = size(et,1);
elts = zeros(8, N);
elts(1,:) = elt(1);
elts(2,:) = elt(2);
elts(3,:) = elt(3);
elts(4,:) = elt(4);
elts(5,:) = elt(5);
elts(6,:) = elt(6);
elts(7,:) = elt(7);
elts(8,:) = elt(8);
the call:
state = cspice_conics(elts, et)
returns
state the array(s) representing the state (position and velocity) of
the body at time 'et' in kilometers and kilometers-per-second
(the first three components of 'state' represent the x-,
y-, and z-components of the body's position; the last three
components form the corresponding velocity vector)
[6,n] = size(state); double = class(state)
'state' returns with the same vectorization measure, N, as
'elts' and 'et'.
Any numerical results shown for this example may differ between
platforms as the results depend on the SPICE kernels used as input
and the machine specific arithmetic implementation.
Example (1):
%
% Calculate the perturbation between the
% state elements of the Moon at some time as determined
% from SPK data and the corresponding state elements
% determined from propagation of osculating elements.
%
% Load the meta kernel listing the needed SPK, PCK, LSK
% kernels.
%
cspice_furnsh( 'standard.tm' )
%
% Convert the time of interest, provided as a string, to ephemeris time
%
et = cspice_str2et( 'Dec 25, 2007' );
%
% Call cspice_spkezr to retrieve the Moon state
% w.r.t. the earth in the 'J2000' frame. Use 'NONE' as aberration
% correction since we are comparing geometric states.
%
[state, ltime] = cspice_spkezr( 'Moon', et, 'J2000', 'NONE', 'EARTH' );
%
% cspice_oscelt requires body mass information, so load a
% mass PCK kernel that contains gravitation constants.
%
cspice_furnsh( '/kernels/gen/pck/masses3.tpc' )
%
% Read the gravitational parameter for Earth.
%
mu = cspice_bodvrd( 'EARTH', 'GM', 1 );
%
% Execute the cspice_oscelt call to convert the state 6-vector
% to the osculating elements 8-vector, 'elts', at 'et'. The osculating
% elements are relative to the same frame as 'state'.
%
% The elements describe the nominal orbit the Moon would follow
% in the absence of all other bodies in the solar system and
% and all non-gravitational forces.
%
% Note: the cspice_bodvrd call returns data as arrays, so
% to access the gravitational parameter (the only value in
% the array), we use 'mu(1)'.
%
elts = cspice_oscelt( state, et, mu(1) );
%
% Now, select a time one week from the initial epoch.
%
later = et + 7. * cspice_spd;
%
% Use the osculating elements to calculate the state vector
% of the Moon at the 'later' epoch.
%
later_state = cspice_conics( elts, later );
%
% Now retrieve the Moon's state at time 'later' from SPK
% data.
%
[state, ltime] = cspice_spkezr('Moon', later, 'J2000', 'NONE', 'EARTH');
%
% Display the absolute diff between the vector output by
% cspice_conics and the state vector returned by cspice_spkezr.
%
pert = later_state - state;
txt = sprintf( 'Perturbation in x: %16.8f', pert(1) );
disp( txt )
txt = sprintf( 'Perturbation in y: %16.8f', pert(2) );
disp( txt )
txt = sprintf( 'Perturbation in z: %16.8f', pert(3) );
disp( txt )
txt = sprintf( 'Perturbation in dx/dt: %16.8f', pert(4) );
disp( txt )
txt = sprintf( 'Perturbation in dy/dt: %16.8f', pert(5) );
disp( txt )
txt = sprintf( 'Perturbation in dz/dt: %16.8f', pert(6) );
disp( txt )
MATLAB outputs:
Perturbation in x: -7488.81617036
Perturbation in y:<PHONE_NUMBER>1
Perturbation in z:<PHONE_NUMBER>3
Perturbation in dx/dt: -0.03615259
Perturbation in dy/dt: -0.00127924
Perturbation in dz/dt: -0.00201456
Example (2):
%
% Calculate the magnitude of the perturbation between the
% position and velocity vectors of the Moon w.r.t. earth as
% calculated from cspice_conics and as retrieved from an SPK file.
%
% Load the meta kernel listing the needed SPK, PCK, LSK
% kernels.
%
cspice_furnsh( 'standard.tm' )
%
% Convert the time of interest, provided as a string, to ephemeris time
%
et1 = cspice_str2et( 'Jan 1, 2007' );
%
% Make the cspice_spkezr call to retrieve the state of the
% Moon w.r.t. the earth in J2000. Use 'NONE' as aberration
% correction since we are comparing geometric states.
%
[state1, ltime] = cspice_spkezr( 'Moon', et1, 'J2000', 'NONE', 'EARTH' );
%
% cspice_oscelt requires body mass information, so load a
% mass PCK kernel that contains gravitation constants.
%
cspice_furnsh( '/kernels/gen/pck/masses3.tpc' )
%
% Read the gravitational parameter for Earth.
%
mu = cspice_bodvrd( 'EARTH', 'GM', 1 );
elts1 = cspice_oscelt( state1, et1, mu(1) );
%
% We want to propagate the osculating elements in 'elts1'
% by N time steps. Create an array of N copies of 'elts1'
%
N = 30;
elts = repmat( elts1, 1, N );
%
% Create an array of N ephemeris times in steps of one day (measured
% in seconds) from 'et1'.
%
et = [1:N]*cspice_spd + et1;
twobody = cspice_conics( elts, et );
[state, ltime] = cspice_spkezr( 'Moon', et, 'J2000', 'NONE', 'EARTH' );
utc = cspice_et2utc( et, 'C', 0 );
for n=1:N
txt = sprintf( ...
'%s perturbation: ||r|| %10.4f, ||v|| %6.4f', ...
utc(n,:) , ...
norm( state(1:3,n) - twobody(1:3,n) ) , ...
norm( state(4:6,n) - twobody(4:6,n) ) );
disp( txt )
end
%
% It's always good form to unload kernels after use,
% particularly in MATLAB due to data persistence.
%
cspice_kclear
MATLAB outputs:
... partial output ...
2007 JAN 12 00:00:00 perturbation: ||r|| 5011.4764, ||v|| 0.0282
2007 JAN 13 00:00:00 perturbation: ||r|| 7828.6919, ||v|| 0.0381
2007 JAN 14 00:00:00 perturbation: ||r|| 11573.2356, ||v|| 0.0498
2007 JAN 15 00:00:00 perturbation: ||r|| 16336.4334, ||v|| 0.0628
2007 JAN 16 00:00:00 perturbation: ||r|| 22123.4631, ||v|| 0.0765
2007 JAN 17 00:00:00 perturbation: ||r|| 28830.2006, ||v|| 0.0902
2007 JAN 18 00:00:00 perturbation: ||r|| 36232.8928, ||v|| 0.1033
2007 JAN 19 00:00:00 perturbation: ||r|| 43994.5246, ||v|| 0.1154
...
None.
For important details concerning this module's function, please refer to
the CSPICE routine conics_c.
MICE.REQ
-Mice Version 1.0.1, 30-OCT-2014, EDW (JPL)
Edited I/O section to conform to NAIF standard for Mice documentation.
Added to I/O section a description of creating vectorized variables
from constant values, i.e. create a vectorized 'et' from a constant
(non vectorized) epoch, or create a vectorized 'elts' from a
constant (non vectorized) single set of elements.
-Mice Version 1.0.0, 22-NOV-2005, EDW (JPL)
state from conic elements
|


flush_output/[0,1]
flush_output/0 – flush current output stream
flush_output/1 – flush specific output stream
FORMS
flush_output
flush_output(Stream_or_Alias)
DESCRIPTION
A call to flush_output/0 will cause the buffer contents associated with the current output stream to
be written out.
A call to flush_output/1 will cause the buffer contents associated with the open output stream Stream_or_Alias to be written out.
An output operation such as put_char/2 or write/2 is used to put some data out to a stream. Unless byte buffering is specified
when the stream is open, the data will not be immediately output. Rather, the
data will be buffered in an area associated with the open output stream. The flush_output builtins cause this buffer to be written out to the sink associated with the
open stream.
EXAMPLES
The following two procedures illustrate the use of flush_output to write out a single dot in between potentially long computations.
?- reconsult(user).
Reconsulting user ...
process(N) :-
N > 0,
put_char(user_output,'.'),
flush_output(user_output),
compute,
NN is N-1,
process(NN).
process(_) :- nl(user_output).
compute :- system('sleep 2').
user reconsulted
Yes.
?- process(5).
.....
Yes.
ERRORS
Stream_or_Alias is a variable
––––> instantiation_error.
Stream_or_Alias is neither a variable nor a stream descriptor nor an alias
––––> domain_error(stream_or_alias,Stream_or_Alias)
Stream_or_Alias is not associated with an open stream
––––> existence_error(stream,Stream_or_Alias)
Stream_or_Alias is not an output stream
––––> permission_error(output,stream,Stream_or_Alias)
Stream_or_Alias is a valid output stream, but the flush operation could not be completed due
to some other problem detected by the operating system
––––> system_error
SEE ALSO
open/4, close/1, current_output/1, User Guide (Prolog I/O).


NOTE: In order for nodes to show up here, you need to have used the wio-cli toolkit to configure your boards and attach them to your account on {{server}}.


@* * Copyright 2023 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 includes.fileProcessingAlert @this( govukFileUpload: GovukFileUpload, govukButton: GovukButton, fileProcessingAlert: fileProcessingAlert ) @(fileType: String, formFields: Map[String, String], postTarget: Call, messageKey: String)(implicit messages: Messages)


| 004:076 Khan | : |
Those who believe, fight in the Cause of Allah, and those who disbelieve, fight in the cause of Taghut (Satan, etc.). So fight you against the friends of Shaitan (Satan); Ever feeble indeed is the plot of Shaitan (Satan). |
| 004:076 Maulana | : |
Those who believe fight in the way of Allah, and those who disbelieve, fight in the way of the devil. So fight against the friends of the devil; surely the struggle of the devil is ever weak. |
| 004:076 Pickthal | : |
Those who believe do battle for the cause of Allah; and those who disbelieve do battle for the cause of idols. So fight the minions of the devil. Lo! the devil's strategy is ever weak. |
| 004:076 Rashad | : |
Those who believe are fighting for the cause of GOD, while those who disbelieve are fighting for the cause of tyranny. Therefore, you shall fight the devil's allies; the devil's power is nil. |
| 004:076 Sarwar | : |
The believers fight for the cause of God. The unbelievers fight for the cause of the Satan. So fight against the friends of Satan for the evil plans of Satan are certainly weak. |
| 004:076 Shakir | : |
Those who believe fight in the way of Allah, and those who disbelieve fight in the way of the Shaitan. Fight therefore against the friends of the Shaitan; surely the strategy of the Shaitan is weak. |
| 004:076 Sherali | : |
Those who believe fight in the cause of ALLAH, and those who disbelieve fight in the cause of the Evil One. Fight ye therefore, against the friends of Satan; surely Satan's strategy is weak. |
| 004:076 Yusufali | : |
Those who believe fight in the cause of Allah, and those who reject Faith Fight in the cause of Evil: So fight ye against the friends of Satan: feeble indeed is the cunning of Satan. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > الكافرون > صفات الكفار Pillars of Islam> Islamic> The Disbelievers> The Characteristics of the Disbelievers الإيمان > الغيب > الشيطان > وسوسته Faith> The Unseen World> Satan, the Devil> Satanic Temptations الإيمان > اليوم الآخر > تفضيل الآخرة على الدنيا Faith> The Hereafter> Prefering the World to the Hereafter الجهاد > الجهاد في سبيل الإسلام > الدعوة إلى الجهاد Jihad> The Call to Jihad>The Call for the Holy War الجهاد > الجهاد في سبيل الإسلام > مدح الجهاد Jihad> The Call to Jihad>Praising the Holy War
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


HOWTO: PACMan Model Training/Testing¶
The goal of this notebook is demonstrate the steps required to train a
new multinomial, Naive Bayes classification model. We will start with
raw proposal data located in proposal_data
directory and perform the
following steps:
Proposal Scraping
Extracting the Abstract and Scientific Justification sections from the .txtx files generated by the PDF to ascii converter
Text Preprocessing
Tokenization
Filtering stop words
Lemmatization
Training the model on our hand classified proposals
Testing the model on a secondary set of classified proposals
# native python
import os
import sys
cwd = os.getcwd()
pacman_directory = os.path.join('/',*cwd.split('/')[:-1])
sys.path.append(pacman_directory)
# open source packages
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
import pandas as pd
from sklearn.metrics import confusion_matrix, classification_report
from sklearn.model_selection import cross_val_score, train_test_split
# custom packages that are all in the github repo
from pacman2020 import PACManTrain, PACManPipeline
from utils.proposal_scraper import HSTProposalScraper
from utils.analyzer import PACManAnalyze
1. Proposal Scraping¶
We use the HSTProposalScraper
class contained in the
proposal_scraper
module in the utils
subpackage. We specify that
we are scraping the proposals with the intention of using them for
training and that we only want to scrape proposals in Cycle 24. - By
setting for_training=True
, the software automatically looks for a
file containing the hand classifications for the list of proposals and
saves the scraped proposal information in an subdirectory of
~/PACMan_dist/training_data/
. In this example, the subdirectory will
be named training_corpus_cy24
and it will contain all of the
training data for the given cycle, as well as the file containing the
hand classifications. - For the hand classifications, we adopt the
following naming convention: cycle_CYCLENUMBER_hand_classifications.txt
- e.g. cycle_24_hand_classifications.txt contains the hand
classification of each proposal for cycle 24. - Additionally, the file
should only contain two columns, proposal_num
and
hand_classification
. Below is an example snippet of what the file
should look like:
proposal_num,hand_classification
0001,stellar physics
0002,stellar physics
.
.
.
# Make an instance of the proposal scraping and scrape each cycle
pacman_scraper = HSTProposalScraper(for_training=True, cycles_to_analyze=[24, 25])
pacman_scraper.scrape_cycles()
INFO [proposal_scraper.scrape_cycles:546] /Users/nmiles/PACMan_dist/proposal_data/Cy24_proposals_txt/*txtx
INFO [proposal_scraper.scrape_cycles:549] Found 1093 proposals to scrape
Scraping Proposals: 100%|██████████| 1093/1093 [00:02<00:00, 468.60it/s]
INFO [proposal_scraper.scrape_cycles:546] /Users/nmiles/PACMan_dist/proposal_data/Cy25_proposals_txt/*txtx
INFO [proposal_scraper.scrape_cycles:549] Found 1208 proposals to scrape
Scraping Proposals: 100%|██████████| 1208/1208 [00:02<00:00, 464.06it/s]
2. Text Preprocessing (it could be a while… )¶
The PACManTrain
class contained in the pacman2020
module to is
capable of performing all of the necessary preprocessing steps. Just
like before, we specify the cycles we want to analyze and in this case
it is just cycle 24.
In summary, this step is processing each input proposal with the
spaCy
NLP package to generate a Doc
object, which is a sequence
of tokens. Each token is an individual word that contains a variety of
semantic information derived from the word and its context in a
sentence. We leverage this information to filter out stop words,
punctuations, etc… This is the slowest step of the entire process and if
needed, it can be improved using the multithreading behavior of
spaCy
.
The text preprocessing steps taken about 11 minutes per cycle.
pacman_training = PACManTrain(cycles_to_analyze=[24, 25])
pacman_training.read_training_data(parallel=False)
INFO [pacman2020.read_training_data:392] Reading in 1093 proposals...
Data Directory: /Users/nmiles/PACMan_dist/training_data/training_corpus_cy24
100%|██████████| 1093/1093 [09:11<00:00, 1.98it/s]
INFO [pacman2020.preprocess:290] Total time for preprocessing: 9.197
INFO [pacman2020.read_training_data:392] Reading in 1208 proposals...
Data Directory: /Users/nmiles/PACMan_dist/training_data/training_corpus_cy25
100%|██████████| 1208/1208 [10:13<00:00, 1.97it/s]
INFO [pacman2020.preprocess:290] Total time for preprocessing: 10.218
For each proposal cycle in the cycle_to_analyze
argument, the
tokenizer will perform the necessary preprocessing steps and save the
proposal number, text, cleaned text, filename, the hand classified
science category, and the encoded value of the hand classified category.
The results are stored in a pandas DataFrame in the
PACManTrain.proposal_data
attribute
print('Found proposal information for:\n'+'\n'.join(pacman_training.proposal_data.keys())+'\n')
# Print the first 5 rows of the DataFrame for cycle 24
for key in pacman_training.proposal_data.keys():
print(f"Displaying some information for {key}...")
print(pacman_training.proposal_data[key].info())
print('-'*58)
Found proposal information for:
cycle_24
cycle_25
Displaying some information for cycle_24...
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1093 entries, 0 to 1092
Data columns (total 6 columns):
text 1093 non-null object
cleaned_text 1093 non-null object
fname 1093 non-null object
proposal_num 1093 non-null int64
hand_classification 1093 non-null object
encoded_hand_classification 1093 non-null int64
dtypes: int64(2), object(4)
memory usage: 59.8+ KB
None
----------------------------------------------------------
Displaying some information for cycle_25...
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1208 entries, 0 to 1207
Data columns (total 6 columns):
text 1208 non-null object
cleaned_text 1208 non-null object
fname 1208 non-null object
proposal_num 1208 non-null int64
hand_classification 1208 non-null object
encoded_hand_classification 1208 non-null int64
dtypes: int64(2), object(4)
memory usage: 66.1+ KB
None
----------------------------------------------------------
Let’s examine the first proposal in the Cycle 24 DataFrame
first_row = pacman_training.proposal_data['cycle_24'].iloc[0]
msg = (
f"HST Cycle 24 proposal number: {first_row['proposal_num']}\n"
f"Hand Classification: {first_row['hand_classification']}\n"
f"Raw Text:\n{first_row['text'][:100]}...\n"
f"Cleaned Text:\n{first_row['cleaned_text'][:100]}...\n"
)
print(msg)
HST Cycle 24 proposal number: 954
Hand Classification: solar system
Raw Text:
This proposal seeks to use STIS with one orbit each in 2017, 2018, and 2019 to map the full disk of ...
Cleaned Text:
proposal seek stis orbit map disk titan wavelength nm arc sec sampling spatial dimension observation...
Side note: pandas is cool.¶
We can use the resulting DataFrame to quickly examine the distribution of proposal categories for each cycles.
fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(5,7), gridspec_kw={'hspace':0.3})
for i, key in enumerate(pacman_training.proposal_data.keys()):
proposal_categories = pacman_training.proposal_data[key]['hand_classification'].value_counts()
proposal_categories.sort_index(inplace=True)
ax = proposal_categories.plot.barh(label=key, ax=axes[i])
ax.set_title(key)
3. Training¶
Now that we have all the proposal information loaded, we can train a classifier. When no model or vectorizer is specified, the software will use the default classifier (Multinomial Naive Bayes) and the default vectorizer (term frequency-inverse document frequency TFIDF). In theory, you can pass any combination of vectorizer and classifier that you want!
We test on cycle 25 because the original work was evaluated on cycle 24 data and these are the only two proposal cycles we have that have been hand classified.
pacman_training.fit_model(pacman_training.proposal_data["cycle_25"])
print(pacman_training.model)
Pipeline(memory=None, steps=[('vect', TfidfVectorizer(analyzer='word', binary=False, decode_error='strict', dtype=<class 'numpy.float64'>, encoding='utf-8', input='content', lowercase=True, max_df=1.0, max_features=10000, min_df=1, ngram_range=(1, 2), norm='l2', preprocessor=None, smooth_idf=True, stop_words=None, strip_accents=None, sublinear_tf=False, token_pattern='(?u)\b\w\w+\b', tokenizer=None, use_idf=True, vocabulary=None)), ('clf', MultinomialNB(alpha=0.05, class_prior=None, fit_prior=True))], verbose=False)
4. Testing¶
Finally, we evaluate the performance of the model we just trained. To do so, we use it to make predictions on a completely different proposal cycle that has also been hand classified. We compare the predictions to the hand classifications and voila.
pacman_training.apply_model(df=pacman_training.proposal_data["cycle_24"], training=True)
print("scikit-learn classification report")
print(
classification_report(
y_true = pacman_training.model_results['encoded_hand_classification'],
y_pred = pacman_training.model_results['encoded_model_classification'],
target_names=pacman_training.encoder.classes_
)
)
scikit-learn classification report
precision recall f1-score support
galaxies and the igm 0.84 0.81 0.82 335
large scale structure of the universe 0.49 0.57 0.53 60
planets and planet formation 0.86 0.96 0.91 130
solar system 0.98 0.80 0.88 60
stellar physics 0.92 0.89 0.90 261
stellar populations and the ism 0.74 0.78 0.76 116
supermassive black holes and active galaxies 0.89 0.91 0.90 131
accuracy 0.84 1093
macro avg 0.82 0.82 0.81 1093
weighted avg 0.84 0.84 0.84 1093
Finally, we use the analysis class to compute our customized accuracy to allow for a comparison with the previous package.
pacman_analyzing = PACManAnalyze()
pacman_analyzing.encoder = pacman_training.encoder
pacman_analyzing.compute_accuracy_measurements(df=pacman_training.model_results, normalize=True)
Total number of galaxies and the igm proposals in top: 0.81
Total number of galaxies and the igm proposals in top_two: 0.15
Total number of galaxies and the igm proposals in misclassified: 0.04
------------------------------------------------------------
Total number of large scale structure of the universe proposals in top: 0.57
Total number of large scale structure of the universe proposals in top_two: 0.30
Total number of large scale structure of the universe proposals in misclassified: 0.13
------------------------------------------------------------
Total number of planets and planet formation proposals in top: 0.96
Total number of planets and planet formation proposals in top_two: 0.02
Total number of planets and planet formation proposals in misclassified: 0.02
------------------------------------------------------------
Total number of solar system proposals in top: 0.80
Total number of solar system proposals in top_two: 0.13
Total number of solar system proposals in misclassified: 0.07
------------------------------------------------------------
Total number of stellar physics proposals in top: 0.89
Total number of stellar physics proposals in top_two: 0.09
Total number of stellar physics proposals in misclassified: 0.03
------------------------------------------------------------
Total number of stellar populations and the ism proposals in top: 0.78
Total number of stellar populations and the ism proposals in top_two: 0.16
Total number of stellar populations and the ism proposals in misclassified: 0.07
------------------------------------------------------------
Total number of supermassive black holes and active galaxies proposals in top: 0.91
Total number of supermassive black holes and active galaxies proposals in top_two: 0.05
Total number of supermassive black holes and active galaxies proposals in misclassified: 0.05
------------------------------------------------------------
print(f"computed accuracy: {pacman_analyzing.computed_accuracy['top'].sum()/pacman_analyzing.computed_accuracy.sum().sum():.0%}")
computed accuracy: 82%
pacman_analyzing.cycle=24
pacman_analyzing.plot_barh(100*pacman_analyzing.computed_accuracy.loc[:,['top','top_two','misclassified']], fout='test.png')
Saving the results and model¶
To provide a means of benchmarking various models, the classes have the
functionality for saving the model results, as well as the trained
model. By passing the training=True
in the cell below, we are
telling the code to save the results in the training subdirectory of the
results directory. When training=False
is passed, the results are
written to the production directory. The intention here is to keep the
results from training separate from the results when new proposals are
analyzed. The path to each directory is given below:
~/PACMan_dist/model_results/training/
~/PACMan_dist/model_results/production/
pacman_training.save_model_results(fout='example_pacmaproposal_datacycle24.txt', training=True)
pacman_training.save_model(fname='example_pacman_model.joblib')
INFO [pacman2020.save_model:459] Saving model and encoder information...


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CommentsThank you kindly by Monique groves


Before Change
rename_count = 0
for src, dst in tqdm(filename_mappings, desc="Renaming Faces"):
if src == dst:
logger.debug("Skipping rename of "%s" as destination name is same as souce", src)
continue
old = os.path.join(self._faces.folder, src)
new = os.path.join(self._faces.folder, dst)
if os.path.exists(new):
// This should never happen, but is a safety measure to prevent deletion of faces
After Change
os.rename(old, new)
rename_count += 1
if conflicts:
for old in tqdm(conflicts, desc="Renaming Faces"):
new = old[:-4] // Remove .tmp extension
if os.path.exists(new):
// This should only be running on faces. If there is still a conflict
// then the user has done something stupid, so we will delete the file and
// replace. They can always re-extract :/
os.remove(new)
logger.verbose("Renaming "%s" to "%s"", old, new)
os.rename(old, new)
return rename_count
class Sort():


Welcome to my webpage designer. Choose from the 'Make a:' section to make an element. Click the element to change the style.
Drag to position, drag to resize, or use the option box to change other features. Click the 'Show list of elements' button
to access and view all available elements on the page. Delete an element with red button in the option box. Finally you may click the Show HTML button.
It will show HTML you can copy and paste directly into an HTML file that will display your design in a browser.
Element List
Style Options
*Double click element to hide/show this box Name: Width: Height: Color: Level: Border Style: Border Width: Border Color: Top position: *Minimum 127 Left position:
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Underline Top position: *Minimum 127 Left position:
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*Double click element to hide/show this box Name: Upload Image: Image from link: Width: Height: Level: Top position: *Minimum 127 Left position:


Dynamic Address Allocation
The traditional methods of dynamic address allocation are centralised, and hence are not natively suitable for an ad hoc network which is devoid of any centralised infrastructure.
Any address allocation protocol must satisfy two main aims:
- Dynamically allocate unique addresses within a reasonable time frame.
- Handle changes in network topology.
The existing ad hoc address allocation protocols can be divided into three classes:
- Leader-based - a leader is elected amongst its peers to act as a centralised authority for address assignment.
- Decentralised - uses some variation of duplicate address detection, where a node selects a random address, then verifies its uniqueness via distributed agreement.
- Mutually exclusive address spaces - each node posesses a set of unique addresses, which it may unilaterally allocate parts of to other nodes.
For this project, the mutually exclusive address spaces technique was selected, for its extremely low overhead, and ability to handle network partitions and subsequent remerges with no reconfiguration. Both these factors mean the protocol with have a very low power consumption.
Mutually Exclusive Address Spaces
Basically, when a node joins a network, it requests addresses from neighbouring nodes, one of which will donate half of its address space to the new node.
| Figure 1: Address request | Figure 2: Neighbours reply with offers |
| Figure 3: Accept one offer and implcitly reject the rest | Figure 4: Idle |
To gain an understanding of how these protocols operate, please see the following articles:
- A P Tayal, L M Patnaik - An address assignment for the automatic configuration of mobile ad hoc networks
- Zhihua Hu, Baochun Li - ZAL: Zero-Maintenance Address Allocation in Mobile Wireless Ad Hoc Networks
A new protocol...
A new protocol was developed based upon these two existing protocols. The protocol is mainly based on the Tayal and Patnaik solution, incorporating some features and concepts from ZAL, as well as other improvements to improve power efficiency.
Tayal and Patnaik's protocol is simple, and all operations remain local unless an address depletion occurs. The tenet of contigous address spaces also eases memory requirements for storing addresses, and bandwidth requirements for exchanging addresses.
ZAL is more complex, as it proactively promotes even distribution of available addresses throughout the network.The authors claim that the network requires zero maintenance once it has reached a stable state, however reaching a stable state comes with a non-trivial energy cost, particularly in a sparse network. Additionally, ZAL does not have a mechanism to overcome address depletions, instead it assumes that the nodes are mobile, hence the requester will eventually come within range of an available address.
However, ZAL does have a passive feature which promote even distribution of addresses, which was incorporated into the new protocol. When a node is initialising, instead of accepting the first offer of addresses it receives, it will wait for all replies to arrive, then accept the largest one.
The first original improvement was the method used to reject offers which the requesting node did not accept; in both protocols, every unsuccessful offer is rejected with an individual rejection message. In the new protocol, a single message is broadcast indicating which offer was accepted, hence implicitly rejecting all other offers. This reduces the number of messages required for an allocation operation, and hence reduces the energy cost of the operation.
The second original improvement was to reduce unneccesary network-wide address searches in the event of an address depletion (when a node runs out of spare addresses). In the Tayal/Patnaik protocol, any depleted node which receives an address request will immediately initiate a network wide search, even if the requester may have already gotten an address from another node. The modification was for depleted nodes to ignore the first request, and only initiate a search upon receiving two consecutive requests. Two consecutive requests indicates that the first request failed, thus the requester was not able to obtain an address locally. Network-wide operations are very energy expensive, thus preventing them unless they are absolutely neccessary will save power.


{% extends "base.html" %} {% block navbar %}
{% endblock %} {% block content %}
Address: Beijing Tsinghua Yuan Offset Printing Factory, Haidian, Beijing, China
Phone: +86<PHONE_NUMBER>3
Fax: ---
Email: gujiawen000@gmail.com


Riley is a very handsome, happy and outgoing boy who lives with our good friends, Linda and Cindy. Like his sire, Riley believes that life is just one big party. His chocolate canine housemate is Shamus (Staghorn's Shamus Owen) and the two are very best buds. Linda and Cindy are excellent owners, keep them in perfect condition and enjoyed attending the dog shows where Riley easily attained his Canadian Championship. When spectators at the show met McDuff and Riley, with their beautiful looks and temperament, our waiting list grew very long. Both Shamus and Riley and their "cousin" Wyatt, owned by Cindy's sister, are excellent ambassadors for Staghorn. Linda, Cindy and their family are the kind of people every breeder screens for and wishes their puppies to own. Thank you Linda and Cindy, (and Julie,) for your friendship and your dedication to your Staghorn dogs.


1.0.0
(number)
The discount, in cents.
(ShippingQuote)
quote.
ShoppingCart is a collection of one or more Products that can be purchased in a single transaction
(any)
The threshold for free shipping ($75), in cents.
Add a promo code to this ShoppingCart.
(string)
The promo code to add.
Remove a promo code from this ShoppingCart.
(string)
The promo code to remove.
Update the shipping information this ShoppingCart is going to.
(ShippingInfo)
Where to ship these products.
Returns a list of items currently in this ShoppingCart along with their counts (e.g. two pieces of the same SKU).
Calculate discounted totals for the ShoppingCart, returning the pending Purchase with all the applicable discounts applied.
(Purchase | null)
:
ShippingService
:
USPS Priority Mail
ShippingService
:
UPS Ground
ShippingService
:
Fedex Home Delivery
Returns the name of this ShippingService.
(string)
The name of the selected shipping service
(e.g. UPS Ground or USPS Priority Mail).
(string)
The delivery address.
Enumeration of supported shipping services.
Extends ShippingInfo
(string)
The name of the selected shipping service
(e.g. UPS Ground or USPS Priority Mail). Must be one of
the constants defined in
ShippingService
.
(string)
The delivery address.
(number)
The cost of shipping, in cents.
Quotes the cost of shipping with the delivery address and shipping service indicated by the given ShippingInfo.
(any)
number
:
The cost of the given shipping method, in cents.


Ant Script Library: asl-release.xml
Overview
asl-release.xml
contains properties and targets that can be
used as a procedure to create a versioned releasable artifact from a software
configuration management (SCM) system.
This is a generic release module, and it doesn't explicitly import any SCM modules. All it requires is that one of the existing SCM modules (or a new module that supports a specific set of macros).
In this module, running the release
target performs the
following steps:
- Tags the code in the SCM system
- Exports the code from the SCM system into a clean workspace
- Compiles the code in the clean workspace
- Creates a package for release
Properties
| Name | Default Value | Description |
|---|---|---|
release.version |
(not set) |
The version of this release. The value of this property affects the default tag that will be used, as well as the generated file names |
release.tag |
${ant.project.name}-${release.version} |
The name that will be used to tag the code in the SCM system |
release.workspace |
${common.target-dir}/release/${release.version} |
The directory where the tagged code will be exported and packaged |
release.buildfile-name |
build.xml |
The name of the build script to invoke in the release workspace |
release.buildfile-path |
${release.workspace}/${release.buildfile-name} |
The path of the build script to invoke in the release workspace |
Targets
release
This is an empty target, that contains dependencies upon the other targets in the following order: release-tag, release-compile, release-package.
release-tag
Tags the code in the SCM system.
release-export
Exports the code from the SCM system to a clean release workspace
release-compile
Compiles the code in the release workspace
release-package
Packages the code in the release workspace.
Is there a problem or mistake on this page? Do you want to contribute some changes? Send me an email at joe@exubero.com.


Chain homotopies and chain contractions#
Chain homotopies are standard constructions in homological algebra: given chain complexes \(C\) and \(D\) and chain maps \(f, g: C \to D\), say with differential of degree \(-1\), a chain homotopy \(H\) between \(f\) and \(g\) is a collection of maps \(H_n: C_n \to D_{n+1}\) satisfying
The presence of a chain homotopy defines an equivalence relation (chain homotopic) on chain maps. If \(f\) and \(g\) are chain homotopic, then one can show that \(f\) and \(g\) induce the same map on homology.
Chain contractions are not as well known. The papers [MAR2009], [RMA2009], and [PR2015] provide some references. Given two chain complexes \(C\) and \(D\), a chain contraction is a chain homotopy \(H: C \to C\) for which there are chain maps \(\pi: C \to D\) (“projection”) and \(\iota: D \to C\) (“inclusion”) such that
\(H\) is a chain homotopy between \(1_C\) and \(\iota \pi\),
\(\pi \iota = 1_D\),
\(\pi H = 0\),
\(H \iota = 0\),
\(H H = 0\).
Such a chain homotopy provides a strong relation between the chain complexes \(C\) and \(D\); for example, their homology groups are isomorphic.
- class sage.homology.chain_homotopy.ChainContraction(matrices, pi, iota)#
Bases:
ChainHomotopy
A chain contraction.
An algebraic gradient vector field \(H: C \to C\) (that is a chain homotopy satisfying \(H H = 0\)) for which there are chain maps \(\pi: C \to D\) (“projection”) and \(\iota: D \to C\) (“inclusion”) such that
\(H\) is a chain homotopy between \(1_C\) and \(\iota \pi\),
\(\pi \iota = 1_D\),
\(\pi H = 0\),
\(H \iota = 0\).
H
is defined by a dictionarymatrices
of matrices.INPUT:
matrices
– dictionary of matrices, keyed by dimensionpi
– a chain map \(C \to D\)iota
– a chain map \(D \to C\)
EXAMPLES:
sage: from sage.homology.chain_homotopy import ChainContraction sage: C = ChainComplex({0: zero_matrix(ZZ, 1), 1: identity_matrix(ZZ, 1)}) sage: D = ChainComplex({0: matrix(ZZ, 0, 1)})
The chain complex \(C\) is chain homotopy equivalent to \(D\), which is just a copy of \(\ZZ\) in degree 0, and we construct a chain contraction:
sage: pi = Hom(C,D)({0: identity_matrix(ZZ, 1)}) sage: iota = Hom(D,C)({0: identity_matrix(ZZ, 1)}) sage: H = ChainContraction({0: zero_matrix(ZZ, 0, 1), ....: 1: zero_matrix(ZZ, 1), ....: 2: identity_matrix(ZZ, 1)}, pi, iota)
- dual()#
The chain contraction dual to this one.
This is useful when switching from homology to cohomology.
EXAMPLES:
sage: S2 = simplicial_complexes.Sphere(2) # needs sage.graphs sage: phi, M = S2.algebraic_topological_model(QQ) # needs sage.graphs sage: phi.iota() # needs sage.graphs Chain complex morphism: From: Chain complex with at most 3 nonzero terms over Rational Field To: Chain complex with at most 3 nonzero terms over Rational Field
Lifting the degree zero homology class gives a single vertex, but the degree zero cohomology class needs to be detected on every vertex, and vice versa for degree 2:
sage: # needs sage.graphs sage: phi.iota().in_degree(0) [0] [0] [0] [1] sage: phi.dual().iota().in_degree(0) [1] [1] [1] [1] sage: phi.iota().in_degree(2) [-1] [ 1] [-1] [ 1] sage: phi.dual().iota().in_degree(2) [0] [0] [0] [1]
- iota()#
The chain map \(\iota\) associated to this chain contraction.
EXAMPLES:
sage: S2 = simplicial_complexes.Sphere(2) # needs sage.graphs sage: phi, M = S2.algebraic_topological_model(QQ) # needs sage.graphs sage: phi.iota() # needs sage.graphs Chain complex morphism: From: Chain complex with at most 3 nonzero terms over Rational Field To: Chain complex with at most 3 nonzero terms over Rational Field
Lifting the degree zero homology class gives a single vertex:
sage: phi.iota().in_degree(0) # needs sage.graphs [0] [0] [0] [1]
Lifting the degree two homology class gives the signed sum of all of the 2-simplices:
sage: phi.iota().in_degree(2) # needs sage.graphs [-1] [ 1] [-1] [ 1]
- pi()#
The chain map \(\pi\) associated to this chain contraction.
EXAMPLES:
sage: # needs sage.graphs sage: S2 = simplicial_complexes.Sphere(2) sage: phi, M = S2.algebraic_topological_model(QQ) sage: phi.pi() Chain complex morphism: From: Chain complex with at most 3 nonzero terms over Rational Field To: Chain complex with at most 3 nonzero terms over Rational Field sage: phi.pi().in_degree(0) # Every vertex represents a homology class. [1 1 1 1] sage: phi.pi().in_degree(1) # No homology in degree 1. []
The degree 2 homology generator is detected on a single simplex:
sage: phi.pi().in_degree(2) # needs sage.graphs [0 0 0 1]
- class sage.homology.chain_homotopy.ChainHomotopy(matrices, f, g=None)#
Bases:
Morphism
A chain homotopy.
A chain homotopy \(H\) between chain maps \(f, g: C \to D\) is a sequence of maps \(H_n: C_n \to D_{n+1}\) (if the chain complexes are graded homologically) satisfying
\[\partial_D H + H \partial_C = f - g.\]INPUT:
matrices
– dictionary of matrices, keyed by dimensionf
– chain map \(C \to D\)g
(optional) – chain map \(C \to D\)
The dictionary
matrices
definesH
by specifying the matrix defining it in each degree: the entry \(m\) corresponding to key \(i\) gives the linear transformation \(C_i \to D_{i+1}\).If \(f\) is specified but not \(g\), then \(g\) can be recovered from the defining formula. That is, if \(g\) is not specified, then it is defined to be \(f - \partial_D H - H \partial_C\).
Note that the degree of the differential on the chain complex \(C\) must agree with that for \(D\), and those degrees determine the “degree” of the chain homotopy map: if the degree of the differential is \(d\), then the chain homotopy consists of a sequence of maps \(C_n \to C_{n-d}\). The keys in the dictionary
matrices
specify the starting degrees.EXAMPLES:
sage: from sage.homology.chain_homotopy import ChainHomotopy sage: C = ChainComplex({0: identity_matrix(ZZ, 1)}) sage: D = ChainComplex({0: zero_matrix(ZZ, 1)}) sage: f = Hom(C,D)({0: identity_matrix(ZZ, 1), 1: zero_matrix(ZZ, 1)}) sage: g = Hom(C,D)({0: zero_matrix(ZZ, 1), 1: zero_matrix(ZZ, 1)}) sage: H = ChainHomotopy({0: zero_matrix(ZZ, 0, 1), 1: identity_matrix(ZZ, 1)}, f, g)
Note that the maps \(f\) and \(g\) are stored in the attributes
H._f
andH._g
:sage: H._f Chain complex morphism: From: Chain complex with at most 2 nonzero terms over Integer Ring To: Chain complex with at most 2 nonzero terms over Integer Ring sage: H._f.in_degree(0) [1] sage: H._g.in_degree(0) [0]
A non-example:
sage: H = ChainHomotopy({0: zero_matrix(ZZ, 0, 1), 1: zero_matrix(ZZ, 1)}, f, g) Traceback (most recent call last): ... ValueError: the data do not define a valid chain homotopy
- dual()#
Dual chain homotopy to this one.
That is, if this one is a chain homotopy between chain maps \(f, g: C \to D\), then its dual is a chain homotopy between the dual of \(f\) and the dual of \(g\), from \(D^*\) to \(C^*\). It is represented in each degree by the transpose of the corresponding matrix.
EXAMPLES:
sage: from sage.homology.chain_homotopy import ChainHomotopy sage: C = ChainComplex({1: matrix(ZZ, 0, 2)}) # one nonzero term in degree 1 sage: D = ChainComplex({0: matrix(ZZ, 0, 1)}) # one nonzero term in degree 0 sage: f = Hom(C, D)({}) sage: H = ChainHomotopy({1: matrix(ZZ, 1, 2, (3,1))}, f, f) sage: H.in_degree(1) [3 1] sage: H.dual().in_degree(0) [3] [1]
- in_degree(n)#
The matrix representing this chain homotopy in degree
n
.INPUT:
n
– degree
EXAMPLES:
sage: from sage.homology.chain_homotopy import ChainHomotopy sage: C = ChainComplex({1: matrix(ZZ, 0, 2)}) # one nonzero term in degree 1 sage: D = ChainComplex({0: matrix(ZZ, 0, 1)}) # one nonzero term in degree 0 sage: f = Hom(C, D)({}) sage: H = ChainHomotopy({1: matrix(ZZ, 1, 2, (3,1))}, f, f) sage: H.in_degree(1) [3 1]
This returns an appropriately sized zero matrix if the chain homotopy is not defined in degree n:
sage: H.in_degree(-3) []
- is_algebraic_gradient_vector_field()#
An algebraic gradient vector field is a linear map \(H: C \to C\) such that \(H H = 0\).
(Some authors also require that \(H \partial H = H\), whereas some make this part of the definition of “homology gradient vector field. We have made the second choice.) See Molina-Abril and Réal [MAR2009] and Réal and Molina-Abril [RMA2009] for this and related terminology.
See also
is_homology_gradient_vector_field()
.EXAMPLES:
sage: from sage.homology.chain_homotopy import ChainHomotopy sage: C = ChainComplex({0: zero_matrix(ZZ, 1), 1: identity_matrix(ZZ, 1)})
The chain complex \(C\) is chain homotopy equivalent to a copy of \(\ZZ\) in degree 0. Two chain maps \(C \to C\) will be chain homotopic as long as they agree in degree 0.
sage: f = Hom(C,C)({0: identity_matrix(ZZ, 1), ....: 1: matrix(ZZ, 1, 1, [3]), ....: 2: matrix(ZZ, 1, 1, [3])}) sage: g = Hom(C,C)({0: identity_matrix(ZZ, 1), ....: 1: matrix(ZZ, 1, 1, [2]), ....: 2: matrix(ZZ, 1, 1, [2])}) sage: H = ChainHomotopy({0: zero_matrix(ZZ, 0, 1), ....: 1: zero_matrix(ZZ, 1), ....: 2: identity_matrix(ZZ, 1)}, f, g) sage: H.is_algebraic_gradient_vector_field() True
A chain homotopy which is not an algebraic gradient vector field:
sage: H = ChainHomotopy({0: zero_matrix(ZZ, 0, 1), ....: 1: identity_matrix(ZZ, 1), ....: 2: identity_matrix(ZZ, 1)}, f, g) sage: H.is_algebraic_gradient_vector_field() False
- is_homology_gradient_vector_field()#
A homology gradient vector field is an algebraic gradient vector field \(H: C \to C\) (i.e., a chain homotopy satisfying \(H H = 0\)) such that \(\partial H \partial = \partial\) and \(H \partial H = H\).
See Molina-Abril and Réal [MAR2009] and Réal and Molina-Abril [RMA2009] for this and related terminology.
See also
is_algebraic_gradient_vector_field()
.EXAMPLES:
sage: from sage.homology.chain_homotopy import ChainHomotopy sage: C = ChainComplex({0: zero_matrix(ZZ, 1), 1: identity_matrix(ZZ, 1)}) sage: f = Hom(C,C)({0: identity_matrix(ZZ, 1), ....: 1: matrix(ZZ, 1, 1, [3]), ....: 2: matrix(ZZ, 1, 1, [3])}) sage: g = Hom(C,C)({0: identity_matrix(ZZ, 1), ....: 1: matrix(ZZ, 1, 1, [2]), ....: 2: matrix(ZZ, 1, 1, [2])}) sage: H = ChainHomotopy({0: zero_matrix(ZZ, 0, 1), ....: 1: zero_matrix(ZZ, 1), ....: 2: identity_matrix(ZZ, 1)}, f, g) sage: H.is_homology_gradient_vector_field() True


\maketitle
The \maketitle command generates a title on a separate title page - except in the article style, where the title normally goes at the top of the first page. Information used to produce the title is obtained from the following declarations, which should precede the \maketitle command.
The Titlepage Environment allows you to design your own title page, rather than using that created by the \maketitle command whose format is determined by the document style.
See also: Page Styles,
Titlepage Environment
Go to LaTeX Table of Contents


"I Still Know What You Did Last Summer" * 1/2 (out of four)
Starring Jennifer Love Hewitt, Brandy, Mekhi Phifer, Matthew Settle, Freddie Prinze, Jr., Jennifer Esposito, Muse Watson and Jeffrey Combs
Directed by Danny Cannon
Rated R for violence, gore and profanity
Theatrical aspect ratio of 2.35:1
Released in 1998
Running 96 minutes
The first in a very long list of things wrong with "I Still Know What You Did Last Summer" is the title. Think about it for a second. If the last movie was called "I Know What You Did Last Summer", wouldn't the next movie have to be "I Still Know What You Did Two Summers Ago"? If anyone working on this movie had an I.Q. greater than five would have thought about it logically and said, "Hey... wait a minute". But alas, the people behind this film are obviously idiots, so I won't hold them to that. What I will hold them to is the fact that they have a pretty bad movie on their hands, even for a teenage slasher flick.
I guess I'm one of the few critics who actually kind of liked the original film (emphasis on the "kind of"). It wasn't great or anything and maybe not even necessarily good, but at least it didn't have me glancing at my watch every minute or so like it's sequel did.
There are just so many problems with this movie that it's hard trying to figure out where to start. First of all, I guess, is the setting. The movie offers no rational reason why the film had to take place in the Bahamas, other than the fact that the producers wanted a seaside setting. Exactly why does the fisherman want to go through all the trouble of faking a radio contest to get Julie James (Jennifer Love Hewitt, one of the only survivors of the first film) and her new college buddies out to the islands before he hacks them up?
The movie suffers from this kind of logic all the way through. In one scene, Julie is in a tanning booth at a deserted gym when the hooked fisherman with the slicker comes in and seals up the booth so the damsel in distress can't get out, no matter how hard she tries. When Julie discovers she's going to slowly fry to death, she screams for help and her friends come to her rescue. Now, this is all fine and dandy except for one thing; instead of spending five minutes trying to bust open the booth, why not just turn the freakin' thing off?
In another scene, one of the characters, after having their significant other all but decapitated by the man in the slicker, says to Julie, "Just don't tell anybody it rained the whole time." Oh yeah, I've just been terrorized by a hook wielding sociopath and had some of my best friends gruesomely slaughtered, but hey, I'll crack jokes anyway. After all, it IS in the script.
The film's only saving graces are a few well-executed suspense sequences and a really cool cameo by the "Re-Animator himself, Jeffrey Combs. He brings some good comic relief and life to an otherwise limp movie. Way to go , Jeffrey.
I have a hunch that the reason this film fizzles while the first one at least kept it's head above water is the recent absence of writer Kevin Williamson. With "Scream" and even it's sequel, he displayed a real talent as a screenwriter. His ear for dialogue and the terrific endings he puts on all his films make him a standout from all the rest of the horror writers, and I think "I Still Know" has really suffered by not having him on board. The cool atmosphere is still there this time around, but I just didn't like the characters or the writing as much as I did in the first one.
Even though the movie doesn't have Williamson, it still has a hacky ending, trying to do what Kevin did with the first two "Scream"s by (some may consider this a spoiler, but if you have seen any horror movies whatsoever, then you should be able to guess the identity of the madman within twenty minutes) having two killers and, this time, having one of them being a family member to the other. I think someone in the audience put it best when, after the movie had ended with another "the killer is back!" cliffhanger, he said "Who is this time, the Grandma?"
All in all, "I Still Know" tries to be as successful as the first the film was, but really fails in the attempt. I mean, it's okay when slasher movies rip-off each other, but when they start copying themselves...
*Find all of Jason's reviews at http://www.geocities.com/Hollywood/Boulevard/7475
**Complimentary movie ticket courtesy of Valley Cinemas at http://www.movie-tickets.com
Copyright 1998 Jason Wallis
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.
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to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


LocalBitcoins Reports 135,000 New Customers Per Month
by Ali RazaLocalBitcoins CEO recently revealed that the company is growing at a huge rate, stating that the platform still receives over 135,000 new users per month.
The advancements of the crypto industry are becoming more and more apparent as the years go by. Numerous new exchanges are emerging, the number of cryptocurrencies is larger than ever, and the industry has made significant technological breakthroughs.
The interest in crypto trading, particularly P2P trading, is also growing, according to LocalBitcoins’ CEO, Sebastian Sonntag, in a recent interview. During the talk, he admitted that the company is expanding and that its user base is gaining 4,000 to 5,000 users per day.
Sonntag answered a number of questions regarding LocalBitcoins itself, the altcoin market, regulations, challenges that the crypto world is facing now, and more.
The interview
When talking about LocalBitcoins, Sonntag stated that the company is going through a transitional period. The firm is growing rapidly, and he admitted that the firm is,
Working to catch up with a sharp increase in support queries, by hiring more staff and investing in training.
However, he also noted that the company’s plans for the future do not include providing wallets for the altcoins, even the ones among the top 10 largest coins. However, the platform does work on improving itself, especially due to its adoption in various regions.
Sonntag stated that LocalBitcoins recently enabled ‘multiple simultaneous open trades,’ which would make trading more convenient and significantly faster. The changes were received very positively.
LocalBitcoins grows and improves
He particularly addressed the topic of crypto regulations. He noted that LocalBitcoins has always been taking steps to respond to legal requirements in all jurisdictions in which it operates. However, the platform does not serve US clients at the moment, although it is seeking legal advice on what it could do to change that.
Apart from the US and other similar regions, LocalBitcoins is one of the platforms with the widest reach in the industry. Even so, he believes that one of the platform’s main challenges is related to user education — not only regarding crypto but cybersecurity itself.
Sonntag also briefly touched upon Libra, stating that he is unsure of its impact on the crypto market and whether it will fuel adoption and expansion.
Do you think that Localbitcoins is more practical than crypto exchanges? Let us know in the comment section below!
Images via Shutterstock, LearnBonds
The Rundown


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About Me
Hello, my name is Rachael Crowe. I live in Orlando, Florida. I have loved anything art since I was young. At age six, I started taking one-on-one art lessons until I was old enough to experiment with art myself. I focus on pencil drawing and watercolor painting mostly. I created this website to keep up with this passion of mine, and so that I can pursue it as a career. I am currently a sophomore at Valencia College, working towards my Associates of Arts degree. I plan to move on to a university where I can study graphic design and studio art.


Wolfgang Amadeus Mozart
A genius from birth
Here's a time line of Mozart's life:
- - Birth of Mozart
- 1761 - First Public Performance
- 1762 - Munich and Vienna
- 1763 - Continued Travel(1763 to 1766)
- 1768 - First Opera
- 1777 - Travels and Composes(1777 to 1781)
- 1782 - Vienna
- 1786 - Prague(1786 to 1787)
- 1787 - Beethoven Arrived
- 1788 - Popularity Decreased(1788 to 1789)
- 1789 - "Cosi fan Tutte" Premiered(1789 to 1790)
- 1791 - The Magic Flute and the Requiem
- - Mozart Died
"Music, even in situations of the greatest horror, should never be painful to the ear but should flatter and charm it, and thereby always remain music."
-- Mozart


@* * Copyright 2019 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 ltbs.uniform._ @(key: String, options: Seq[String], existing: Option[String], errors: ErrorTree, messages: UniformMessages[Html], conditional: PartialFunction[String,Html] = PartialFunction.empty ) @keyNoDots=@{key.replace(".","-")}


Lionel Scaloni pleased with Argentina progress as unbeaten run continues
by FSA EditorWhile seeking improvement, Lionel Scaloni is happy with Argentina’s development after their unbeaten run continued.
Lionel Scaloni is satisfied with Argentina’s progress after a friendly draw against Uruguay on Monday.
Argentina came from behind twice to secure a 2-2 draw in Tel Aviv, where Lionel Messi’s stoppage-time penalty cancelled out Luis Suarez’s goal after Edinson Cavani and Sergio Aguero had struck earlier.
It extended Argentina’s unbeaten run to seven matches as they continued preparations for 2022 World Cup qualifying, which begins next year.
Scaloni is pleased with Argentina’s development, although the coach still sees room for improvement.
“At the level of results, we are fine. At the level of the game, it can be improved,” he said, via Ole.
“The team feeling is the best we have. The important thing is that the players who play do it well. Some make a difference and others support.”
Scaloni acknowledged the challenge awaiting his team, describing the CONMEBOL qualifiers as the toughest in the world.
“Now we have to think about what we did well and what we can correct. What is coming is difficult,” he said.
“I spoke with people from Uruguay. It will be difficult in the qualifiers. Those in South America are the most difficult in the world.
“We have a good base.”


Russian professor attempted suicide after butchering lover, says lawyer
SAINT PETERSBURG, Nov 19 — A Russian historian and university professor has attempted suicide while in custody after confessing to killing and chopping up his girlfriend, his lawyer said today.
Oleg Sokolov, a 63-year-old noted Napoleon expert, was charged with murder after shooting 24-year-old Anastasia Yeshchenko in Saint Petersburg this month and trying to dispose of her body parts in a city river.
Sokolov, who is in prison, tried to kill himself on Friday when he was taken to his flat by investigators carrying out a reenactment of the crime, his lawyer Alexander Pochuyev told AFP.
“He announced his intention to commit suicide from the start and unfortunately he has made the attempt already,” Pochuyev said.
The attempt “was stopped by police,” the lawyer said, describing Sokolov as “in a difficult psychological state”.
Pochuyev said he could not disclose further details.
The Investigative Committee probing the murder and the prison service declined to comment on the incident.
On Friday, investigators also took Sokolov to the riverbank where parts of Yeshchenko’s body were found, having outfitted him in a bulletproof vest and helmet.
The grisly murder has scandalised Russia, after people said Sokolov had exhibited inappropriate behaviour with students in the past and demanded that the management at Saint Petersburg State University where he worked be investigated.
Yeshchenko, 24, was described by friends as a brilliant student who had been in a relationship with Sokolov for several years and had been working on research projects with him.
Sokolov allegedly shot and killed her during an argument and then sawed off her head, arms and legs.
Her remains were buried in her hometown in southern Russia at the weekend with hundreds attending a funeral service. — AFP


{% comment %} Licensed to Cloudera, Inc. under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. Cloudera, Inc. licenses this file to you 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. {% endcomment %}
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UseODBCDatabase()
语法
Result = UseODBCDatabase()概要
Initialize the ODBC database environment for future use. It attempts to load the ODBC driver and allocate the required resources.
参数
无.
返回值
If Result is 0, then the ODBC driver is not available or is too old (ODBC 3.0 or higher is needed) and the Database functions should not be used.
备注
After calling UseODBCDatabase(), a database has to be opened using OpenDatabase() using a registered ODBC database name as database or OpenDatabaseRequester() before using any other Database functions.
It is possible to obtain a list of available drivers by calling the function ExamineDatabaseDrivers().
示例
UseODBCDatabase() If OpenDatabase(0, "MySQL-ODBC", "mysql", "mysql") Debug "Connected to MySQL" Else Debug "Connection failed: "+DatabaseError() EndIf
参阅
OpenDatabase(), UseSQLiteDatabase(), UsePostgreSQLDatabase()
已支持操作系统
所有


Benchpressing Angular + Javascript
Quick Intro
Rob Pocklington
Full-stack developer my whole career (12 years)
been using J-Query and Javascript for 5+ years
Backbone.js for almost 2 years
Angular.js for the same
What am I here to talk about?
Why frontend performance is important
Common performance issues in Javascript
Review of tools (that help you to):
Write performance tests
Run (and automate) performance tests
Performance - why do we care?
Because your users are impatient have expectations
http://yoursite.com takes ...
0.1 second :)
1 second :|
5 seconds :(
Fast Forwarding past ...
Animations / CSS 3
( check out: Transit.js or Velocity.js )
any type of API performance
( check out: Grindr, Gatling, JMeter, Apache Bench )
any functional / end-to-end testing
( check out: Cucumber / JBehave / Selenium*.* )
Common performance issues in Javascript
read: lets see some buggy code!
Recursion (see recursion)
http://localhost:9000/graph/perf-recursion.html
Jank
http://rawgit.com/rpocklin/scroll-to-top/master/demo.html?load=1
Memory issues / leaks (closure)
http://localhost:9000/graph/perf-closure-memory-leak.html
Quick Tips for avoiding these problems
Don't use implicit lexical binding in closures.
Instead use explicit function parameters. Much cleaner.
Don't use setInterval
Instead use setTimeout and re-schedule on success. Much safer.
Bind = Unbind
Always consider $destroy
If you're not sure... test!
Testing Javascript
JSTest Driver, Q-Unit, Jasmine,
Mocha, Chai...
Great for unit testing ...
but now you wanna test performance ...
What should I performance test?
Algorithmic Performance
( transforms, calculations, regex, recursion, fibbonacci )
DOM Rendering Performance
( render times )
Memory leaks
( event listeners / timers / sockets / closures )
How do I performance test?
You need a Javascript engine
but which one should I use?
Whichever your customers use :)
When performance testing ...
in Node.js
npm install microtime
When performance testing ...
in Chrome
chrome --enable-benchmarking
--incognito
( and don't use Cygwin )
Enough already, lets run through the tools ...
Benchpress ( no plugin support )
https://github.com/angular/benchpress
benchpress run
Used in the angular.js project
what do they test?
order by (algorithmic)
large tables (watchers and DOM manipulation)
event delegation
parsing expressions (AngularJS parser)
Needs chrome canary installed
Can test Angular.js controllers and views
Scant documentation, last commit 2 months ago
Fragile test harness ( obscure errors until you get it right )
manual build step benchpress build
Can't automate :(
Hard to do comparisons (no graphs etc.) :(
Benchmark.js (Karma + Grunt plugins)
http://benchmarkjs.com
also http://jsperf.com
Grunt-benchmark ( benchmark.js )
https://github.com/shama/grunt-benchmark
grunt benchmark
Cannot reference window :(
Can't use inject() :(
Outputs to CSV or JSON and ASCII table :)
but no JUnit Reporter XML :(
Not widely adopted :(
Karma-benchmark ( benchmark.js )
https://github.com/JamieMason/karma-benchmark
grunt karma:benchmarkjs
Can reference window :)
Can't use inject() :(
Good CI integration - JUnit Reporter :)
Benchmark.js ( no build plugins )
http://benchmarkjs.com
grunt karma:unit
Works with Jasmine w00t :)
Can reference window :)
Can use inject :)
Can assert performance metrics :)
Can't graph different algorithms :(
JSLitmus ( no build plugins )
http://www.broofa.com/Tools/JSLitmus/
grunt karma:jslitmus
Works with Jasmine w00t :)
Can reference window :)
Can use inject :)
Can assert performance metrics :)
Can't graph different algorithms :(
Review
If you only want to performance test algorithms etc
(not UI / DOM / views)
use karma-benchmark
If you want to fail the build if a test fails a performance metric on any browser,
or you want to test AngularJS modules, use
Benchmark.js ( no plugins ) with Jasmine
If you want to interact with tests and manually compare and run them yourself,
use whichever you like the most.
Other Resources
AngularJS - Benchpress performance tests
https://github.com/angular/angular.js/tree/master/benchmarks
Hundreds of performance test candiates in Javascript using Benchmark.js
http://www.jsperf.com
Google's Web Browser Latency Benchmark
http://google.github.io/latency-benchmark/
Gremlins.js - aka Chaos MonkeyJS
https://github.com/marmelab/gremlins.js


Brandon Philips
<EMAIL_ADDRESS>May 23, 2012
subsystem: what you are changing a sentence/paragraph why you are making a change.
commit 871a681c931feff0c6666cee1a3b07fc4d7e5a78 Author: Brandon PhilipsDate: Mon May 14 13:57:37 2012 -0700 lib: virgo-init: implement process.exitCode once and awhile we encounter an error that causes our event loop to exit before we expect it too. This happened in our scheduler test and buildbot didn't catch it as an error. So, implement the exitCode logic that I sent to luvit in virgo: https://github.com/luvit/luvit/pull/221 I tested this on hash 60ef64fe9d6a2cee78582247e373c507ee7fe3a5 and it causes make test to exit with a non-zero exit code.


12-year-old in critical condition after ATV crash in Collier County
by WFTX Digital TeamCOLLIER COUNTY, Fla. -- A 12-year-old girl is in critical condition following an ATV accident in Collier County.
Florida Highway Patrol says it happened on Platt Road near Corkscrew Lane on Sunday afternoon.
They say that 12-year-old Kaeli McCormick was riding the ATV when it suddenly flipped and landed on top of her.
She's in Lee Memorial Hospital with critical injuries.


This subpart prescribes policies and procedures for assigning unique Procurement Instrument Identifiers (PIID) for each solicitation, contract, agreement, or order and related procurement instrument.
(a) Establishment of a Procurement Instrument Identifier (PIID). Agencies shall have in place a process that ensures that each PIID used to identify a solicitation or contract action is unique Governmentwide, and will remain so for at least 20 years from the date of contract award. The PIID shall be used to identify all solicitation and contract actions. The PIID shall also be used to identify solicitation and contract actions in designated support and reporting systems (e.g., Federal Procurement Data System, System for Award Management), in accordance with regulations, applicable authorities, and agency policies and procedures.)
(b) Transition of PIID numbering. No later than October 1, 2017, agencies shall comply with paragraph (a) of this section and use the requirements in 4.1602 and 4.1603 for all new solicitations and contract awards. Until an agency’s transition is complete, it shall maintain its 2013 PIID format that is on record with the General Services Administration’s Integrated Award Environment Program Office (which maintains a registry of the agency unique identifier scheme). The 2013 PIID format consisted of alpha characters in the first positions to indicate the agency, followed by alpha-numeric characters; the 2017 format instead has the AAC in the beginning 6 positions.
(c) Change in the Procurement Instrument Identifier after its assignment.
(1) Agencies shall not change the PIID unless one of the following two circumstances apply:
(i) The PIID serial numbering system is exhausted. In this instance, the contracting officer may assign a new PIID by issuing a contract modification.
(ii) Continued use of a PIID is administratively burdensome (e.g., for implementations of new agency contract writing systems). In this instance, the contracting officer may assign a new PIID by issuing a contract modification.
(2) The modification shall clearly identify both the original and the newly assigned PIID. Issuance of a new PIID is an administrative change (see 43.101).
(a) Identifying the PIID in solicitation and contract award documentation (including forms and electronic generated formats). Agencies shall include all PIIDs for all related procurement actions as identified in paragraphs (a)(1) through (a)(5) of this section.
(1) Solicitation. Identify the PIID for all solicitations. For amendments to solicitations, identify a supplementary PIID, in conjunction with the PIID for the solicitation.
(2) Contracts and purchase orders. Identify the PIID for contracts and purchase orders.
(3) Delivery and task orders. For delivery and task orders placed by an agency under a contract (e.g., indefinite delivery indefinite quantity (IDIQ) contracts, multi-agency contracts (MAC), Governmentwide acquisition contracts (GWACs), or Multiple Award Schedule (MAS) contracts), identify the PIID for the delivery and task order and the PIID for the contract.
(4) Blanket purchase agreements and basic ordering agreements. Identify the PIID for blanket purchase agreements issued in accordance with 13.303, and for basic agreements and basic ordering agreements issued in accordance with subpart 16.7. For blanket purchase agreements issued in accordance with subpart 8.4 under a MAS contract, identify the PIID for the blanket purchase agreement and the PIID for the MAS contract.
(i) Orders. For orders against basic ordering agreements or blanket purchase agreements issued in accordance with 13.303, identify the PIID for the order and the PIID for the blanket purchase agreement or basic ordering agreement.
(ii) Orders under subpart 8.4. For orders against a blanket purchase agreement established under a MAS contract, identify the PIID for the order, the PIID for the blanket purchase agreement, and the PIID for the MAS contract.
(5) Modifications. For modifications to actions described in paragraphs (a)(2) through (a)(4) of this section, and in accordance with agency procedures, identify a supplementary PIID for the modification in conjunction with the PIID for the contract, order, or agreement being modified.
(b) Placement of the PIID on forms. When the form (including electronic generated format) does not provide spaces or fields for the PIID or supplementary PIID required in paragraph (a) of this section, identify the PIID in accordance with agency procedures.
(c) Additional agency specific identification information. If agency procedures require additional identification information in solicitations, contracts, or other related procurement instruments for administrative purposes, separate and clearly identify the additional information from the PIID.
(a) Elements of a PIID. The PIID consists of a combination of thirteen to seventeen alpha and/or numeric characters sequenced to convey certain information. Do not use special characters (such as hyphens, dashes, or spaces).
(1) Positions 1 through 6. The first six positions identify the department/agency and office issuing the instrument. Use the AAC assigned to the issuing office for positions 1 through 6. Civilian agency points of contact for obtaining an AAC are on the AAC Contact list maintained by the General Services Administration and can be found at http://www.gsa.gov/graphics/fas/Civilian_contacts.pdf. For Department of Defense (DoD) inquiries, contact the service/agency Central Service Point or DoDAAC Monitor, or if unknown, email<EMAIL_ADDRESS>for assistance.
(2) Positions 7 through 8. The seventh and eighth positions are the last two digits of the fiscal year in which the procurement instrument is issued or awarded. This is the date the action is signed, not the effective date if the effective date is different.
(3) Position 9. Indicate the type of instrument by entering one of the following upper case letters in position nine. Departments and independent agencies may assign those letters identified for department use below in accordance with their agency policy; however, any use must be applied to the entire department or agency.
(4) Positions 10 through 17. Enter the number assigned by the issuing agency in these positions. Agencies may choose a minimum of four characters up to a maximum of eight characters to be used, but the same number of characters must be used agency-wide. If a number less than the maximum is used, do not use leading or trailing zeroes to make it equal the maximum in any system or data transmission. A separate series of numbers may be used for any type of instrument listed in paragraph (a)(3) of this section. An agency may reserve blocks of numbers or alpha-numeric numbers for use by its various components.
(5) Illustration of PIID. The following illustrates a properly configured PIID using four characters in the final positions:
(b) Elements of a supplementary PIID. Use the supplementary PIID to identify amendments to solicitations and modifications to contracts, orders, and agreements.
(1) Amendments to solicitations. Number amendments to solicitations sequentially using a four position numeric serial number added to the 13-17 character PIID beginning with 0001.
(2) Modifications to contracts, orders, and agreements. Number modifications to contracts, orders, and agreements using a six position alpha or numeric, or a combination thereof, added to the 13-17 character PIID. For example, a modification could be numbered P00001. This would be added to the end of the 13-17 character PIID illustrated in (a)(5) of this section.
(i) Position 1. Identify the office issuing the modification. The letter P shall be designated for modifications issued by the procuring contracting office. The letter A shall be used for modifications issued by the contract administration office (if other than the procuring contracting office).
(ii) Positions 2 through 6. These positions may be alpha, numeric, or a combination thereof, in accordance with agency procedures.
Each office authorized to issue modifications shall assign the supplementary identification numbers in sequence (unless provided otherwise in agency procedures). Do not assign the numbers until it has been determined that a modification is to be issued.


I value simple content structure, clean design patterns, and thoughtful interactions. I design unique layouts for posters and ads using Photoshope, Indesign and Coreldraw.
I like to code things from scratch, and enjoy bringing ideas to life in the browser. I Design clean and wonderful websites using Html, CSS, JavaScript and Bootstrap
I genuinely care about people, and love helping fellow designers work on their craft. I love sharing my knowledge and help people to achive new hights in life
I like to code from scratch and solve problems in codes to develope creative and functional websites. I showcase my skills in backend development through Paython.
I sketch out fascinating portraits of people. Digital Painting is one of my favorite passion. It is fun to recreate beauty of people to a digital canvas.
I support all who willing to get progress in their career with good and profound goals


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Connection
You can connect with other people intersted in the samefield as you.
Eduality is a platform where content creators pick a domain (from a wide variety of categories like science, photography, sports) and share papers, videos, podcasts in order to get points/recognition from other users for their content.
You can connect with other people intersted in the samefield as you.
Different topics from many domains found in the same simple accesible place
Save and store reliable informations easy and free.
Make your knowledge grow faster and imporve your work statistics
Provide and receive constant feedback through a fair algorithm.
You can navigate through different pages easily through the accesible interface.
In modern society, certain subjects have been heavily controlled by a little group of people who decide what should and should not be popular. Eduality allows people to promote themselves and get the recognition that they deserve, to the extent of even getting the chance of working with brands we have agreements with.
In our platform at the same time that we compensate and value our most experts users we make sure that newcomers influence and have a similar potential so that our ranking system is not exploited by a small minority with a lot of power.
I turn to Eduality for almost eveything I want to know. It's trustworthy and it even helps me with my schoolwork!
ALL SHE WANNA DO
As a student, Eduality has helped me finding information about my interests and satisfying my curiosity about any topic I could think of.
Eduality is the supreme platform for those who want their digital content fairly valued.
IS PARTY ALL NIGHT
As a content creator Eduality has helped me leverage my engagement and allowed me to get the audience that my content deserves. Furthermore, brand agreements helped me get sponsorship which motivate me to create even more.


--- layout: page title: "Real World Haskell, 1st Edition" prev: bloomfilter_split_000.html next: I_sect126_d1e49402.html book_path: books/real-world-haskell-_oeb/ --- {% include JB/setup %} {% raw %}
Designing an API for Qualified Import
Creating a Mutable Bloom Filter
Performance Analysis and Tuning


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This Week on npm v20190406<EMAIL_ADDRESS><EMAIL_ADDRESS>Here are the most popular packages that published new releases to npm this week. Packages are ranked by downloads in March 2019, and versions are broken down by major, minor, and patch releases.
Major
1<EMAIL_ADDRESS>Check if a path exists
2<EMAIL_ADDRESS>Extract the non-magic parent path from a glob string.
3<EMAIL_ADDRESS>Make a directory and its parents if needed - Think mkdir -p
4<EMAIL_ADDRESS>An XML builder for node.js
5<EMAIL_ADDRESS>Highly configurable, well-tested, JavaScript-based HTML minifier.
6<EMAIL_ADDRESS>Create a promise that can be canceled
7<EMAIL_ADDRESS>TypeScript definitions for Selenium WebDriverJS
8<EMAIL_ADDRESS>TypeScript definitions for semver
9<EMAIL_ADDRESS>Convert a string to a valid safe filename
10<EMAIL_ADDRESS>Types for all Sentry JavaScript SDKs
Minor
1<EMAIL_ADDRESS>Streams3, a user-land copy of the stream library from Node.js
2<EMAIL_ADDRESS>Convert a dash/dot/underscore/space separated string to camelCase or PascalCase: foo-bar
→ fooBar
3<EMAIL_ADDRESS>the complete solution for node.js command-line programs
4<EMAIL_ADDRESS>TypeScript definitions for Node.js
5<EMAIL_ADDRESS>Get the visual width of a string - the number of columns required to display it
6<EMAIL_ADDRESS>Media Type Database
7<EMAIL_ADDRESS>Extends glob
with support for multiple patterns and exposes a Promise API
8<EMAIL_ADDRESS>Get the first fulfilled promise that satisfies the provided testing function
9<EMAIL_ADDRESS>`Start a promise chain
10<EMAIL_ADDRESS>ANSI escape codes for manipulating the terminal
Patch
1<EMAIL_ADDRESS>A comprehensive library for mime-type mapping
2<EMAIL_ADDRESS>JavaScript parser, mangler/compressor and beautifier toolkit
3<EMAIL_ADDRESS>Share target browsers between different front-end tools, like Autoprefixer, Stylelint and babel-env-preset
4<EMAIL_ADDRESS>The Babel Traverse module maintains the overall tree state, and is responsible for replacing, removing, and adding nodes
5<EMAIL_ADDRESS>A JavaScript parser
6<EMAIL_ADDRESS>babel's modular runtime helpers
7<EMAIL_ADDRESS>Native Access to Mac OS-X FSEvents
8<EMAIL_ADDRESS>Provides a list of electron-to-chromium version mappings
9<EMAIL_ADDRESS>A smaller version of caniuse-db, with only the essentials!
10<EMAIL_ADDRESS>Babel compiler core.
Moving On
There were 76,541 new releases between March 15 and March 22. How many of those affect you? Check out JSReport for Slack and keep up to date with the JavaScript libraries you depend on.


Medley Interlisp Project
Email:
<EMAIL_ADDRESS>(archives)
Links:
github.com/Interlisp
,
Wikipedia on Interlisp
Bibliography
For more detail, see our library on Zotero.org.
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Course Fee for Each Member :
Category-1 (Students) : 6,000.00Category-2 (Others) : 10,000.00
The Course Fee is Non Refundable and does not includes Fooding and Lodging.
How to Register?
(a) Download and fill the Registration Form(b) Make a Demand Draft (DD) of 6,000.00(Students) or 10,000.00(Others) in favour of CEP-STC, IIT Kharagpur payable at Kharagpur.
Demand Draft issuing date should not be before 15th May, 2017.
(c) Send duly filled up Registration Form, Demand Draft / Proof of Payment , Identity Proof and Marksheet / Gradesheet showing performance in C programming course by speed post (mention Course Name at the top of the envelope) before 21st June, 2017 to :
Prof. Partha Sarathi Dey
Hardware Laboratory
Department of Computer Science & Engineering
I.I.T. Kharagpur, West Bengal, PIN - 721302.
To confirm participation mail the Scanned copy of Demand Draft / Proof of Payment and duly filled Registration Form to<EMAIL_ADDRESS>and<EMAIL_ADDRESS>positively.
(d) Mail JPG file of your Color Passport size Photograph for Identity Card to<EMAIL_ADDRESS>Travel and Accommodation :
No TA will be reimbursed.Accommodation on sharing basis will be arranged in various Hostels in the campus as per availiability. Accommodation Charges (approx. 120.00 per day) are to be bourne by the participant.


[Erowid Note: 1050 mgs of diphenhydramine is considered an extremely high dose, see diphenhydramine Dose Chart]
It was day 3 on a 3-day long binge, and I was doing 42 Benadryl for the second night in a row. Unlike others, I've been fond of the mellow delerious feeling and the ensuing hallucinations. In a safe, authority-free setting I find they can not only be pleasurable but also a learning experience. I've read the rants of the detractors and the warnings of danger but I never believed them 'cause they never rang true to me.
The experiment started around 11:30pm when my roommate left for work. I popped the pills and invited a friend over. We were talking and I felt the effects start to kick in and soon enough my short-term memory was shot and all I could do was babble nonsense. I informed that this was probably going to be uniform for the rest of the evening and that if he intended on any sort of a conversational hang-out, he may as well leave. He stayed, whether it was to be amused by my behaviour or to watch over me, I do not know as he was not even aware of the substance I had taken, I don't believe.
My memory from here on in is extremely spotty. I walked into my bedroom for some unknown purpose and upon walking back into the livingroom my legs were acting uncharacteristically shaky, even for a Benadryl trip. The next thing I knew, my muscles immediately threw my into my coffee table and when I tried to get up, I went into rapid convulsions; slamming into the ground over and over again. The next thing I remember is being surrounded by a medical team who I'm assuming my friend must have called after witnessing the siezure. I have a deep-seated fear of medical personnel after several suicide attempts in recent times and I was absolutely fearful that I would be sent into a psychiatric ward directly afterwards. They re-assured me that I would be simply treated and released so I reluctantly got into the ambulance.
The Benadryl was still running strong and either because of their ignorance of the substance I took or because they figured nothing would be gained from it, they didn't force me to drink the awful charcoal and thus my ambulance ride was more of a fun trip in a spaceship. My heart monitors were my controls and the medical personnel were my mission team. This illusion continued until I was in the nurse's office when I snapped out of it when the nurse asked me how much cocaine I had consumed that evening. I do not know how my state would be confused with that of a person under the influence of cocaine but I up-and-down refused that I had ingested that substance. When she asked me what I did take, the most concrete thing they could manage to get out of me was 'pills'. I'm guessing it was decided that I was a stimulant freak that had gone too far that night and so they gave me two Valium and I immediately passed out.
I awoke early the next morning, feeling more or less sober and infinitely terrified. I figured this was the part where my parents (who live in another province, which I was to move back to in two days) walk in with a look that could kill a man on their faces and my life is ruined for months afterward. However, a friendly nurse came into assure me that the doctor would be around shortly to give me the good-to-go. I hurredly asked if my parents were informed and she said, 'Not at all. We wouldn't even know your first name if it weren't for your friend that called you in. Stay away from the speed'. It is true that I did not have a health card, or a wallet with any sort of information of worth beyond a bank card so this worked to my advantage.
The doctor came in and said that my heart rate was steadily declining and that as long as I had the money for a cab ride, I was safe to get home. They gave me my street clothes and I walked out a very happy and lucky man. Two days later I moved back to my home province and all was well.
The moral of the story is that you may, indeed, get away with using this substance for years. But eventually you will have that one bad trip that fucks you up. I got a siezure, a sore head, and a night in the hospital out of it. I could have been dead, very easily, had my friend not been there to call the medical professionals. I'm not one to say no to drugs, but this is one that I'll definately be saying no to from now on.
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.


Hukkeri meets CM, triggers speculation
by Special CorrespondentA breakfast meeting between Chief Minister B.S. Yediyurappa and Congress leader Prakash Hukkeri in Belagavi has led to speculation that the former MP may be considering joining the BJP.
Mr. Hukkeri met the Chief Minister at a private hotel for half an hour on Sunday. This led to speculation that Mr. Hukkeri may be considering joining the BJP like his former party colleagues Shrimant Patil and Mahesh Kumathalli. Some pictures were even shared on social media about “the tallest Lingayat leader from Chikkodi region joining the BJP.” Mr. Hukkeri is supposedly upset with the Congress for ignoring his request for party ticket from Kagwad.
‘Not joining BJP’
He, however, clarified that he was not trying to join the BJP. “I did not go there for political reasons. I went to meet the Chief Minister to ask for additional funds for flood relief. I have no plans of joining the BJP,” he said.


We by ou rice but get beef pigs
We grow beans
we plant peas
We use machine to make oure ugali
We plant beans
We plant peas


Please download this accessible syllabus template in order to have an inclusive syllabus.
The following resources can help you prepare your syllabus and class for the semester ahead:
Many of the following documents contain prepared syllabus language that can be directly copied and pasted into your syllabus. The language included meets both UMD and Smith standards.


Next:
Standard Macro Characters
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Reader Algorithm
, Up:
Syntax
2.3 Interpretation of Tokens
•
Numbers as Tokens
:
•
Constructing Numbers from Tokens
:
•
The Consing Dot
:
•
Symbols as Tokens
:
•
Valid Patterns for Tokens
:
•
Package System Consistency Rules
:


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|
MAX32665 SDK Documentation
0.2
Software Development Kit Overview and API Documentation
|
TMR1 Protection Register. More...
Macros | |
| #define | MXC_F_RPU_TMR1_DMA0ACN_POS 0 |
| TMR1_DMA0ACN Position. | |
| #define | MXC_F_RPU_TMR1_DMA0ACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_DMA0ACN_POS)) |
| TMR1_DMA0ACN Mask. | |
| #define | MXC_F_RPU_TMR1_DMA1ACN_POS 1 |
| TMR1_DMA1ACN Position. | |
| #define | MXC_F_RPU_TMR1_DMA1ACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_DMA1ACN_POS)) |
| TMR1_DMA1ACN Mask. | |
| #define | MXC_F_RPU_TMR1_USBACN_POS 2 |
| TMR1_USBACN Position. | |
| #define | MXC_F_RPU_TMR1_USBACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_USBACN_POS)) |
| TMR1_USBACN Mask. | |
| #define | MXC_F_RPU_TMR1_SYS0ACN_POS 3 |
| TMR1_SYS0ACN Position. | |
| #define | MXC_F_RPU_TMR1_SYS0ACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_SYS0ACN_POS)) |
| TMR1_SYS0ACN Mask. | |
| #define | MXC_F_RPU_TMR1_SYS1ACN_POS 4 |
| TMR1_SYS1ACN Position. | |
| #define | MXC_F_RPU_TMR1_SYS1ACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_SYS1ACN_POS)) |
| TMR1_SYS1ACN Mask. | |
| #define | MXC_F_RPU_TMR1_SDMADACN_POS 5 |
| TMR1_SDMADACN Position. | |
| #define | MXC_F_RPU_TMR1_SDMADACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_SDMADACN_POS)) |
| TMR1_SDMADACN Mask. | |
| #define | MXC_F_RPU_TMR1_SDMAIACN_POS 6 |
| TMR1_SDMAIACN Position. | |
| #define | MXC_F_RPU_TMR1_SDMAIACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_SDMAIACN_POS)) |
| TMR1_SDMAIACN Mask. | |
| #define | MXC_F_RPU_TMR1_CRYPTOACN_POS 7 |
| TMR1_CRYPTOACN Position. | |
| #define | MXC_F_RPU_TMR1_CRYPTOACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_CRYPTOACN_POS)) |
| TMR1_CRYPTOACN Mask. | |
| #define | MXC_F_RPU_TMR1_SDIOACN_POS 8 |
| TMR1_SDIOACN Position. | |
| #define | MXC_F_RPU_TMR1_SDIOACN ((uint32_t)(0x1UL << MXC_F_RPU_TMR1_SDIOACN_POS)) |
| TMR1_SDIOACN Mask. | |


URL of a remote data source (to pull records, apply searches and sorts, submit changes, delete).
String, default = ''
If the .url is defined, then every time the grid needs to refresh
the records, they will be pulled from the .url. Every time grid needs to search or sort records, the request
will also be submitted to the server to do the search and/or sort.
URL can be defined during object creation:
Or any time after the grid has been created:
If you do not specify any .url, then the assumed data source is local. You can add/remove records, user can search
and sort records and all actions will be performed locally. You can optionally use .load() method to load records from the
server without switching grid remote data source.
There is no restriction of setting .url at any given time. Just remember, if you set .url, all searches,
sorts, pulling of records (on next page for example), will be loaded from the server.
See grid overview page for data structured passed to and from server side url.


System Architect Picture "Focus State Change"
Parent Diagram:
State Change Activity
(OMT Object Model)