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The Anthropology of Religion, Magic, and Witchcraft
Magic and Occult Books, Seals, Hoodoo Correspondence. Buy Magic, Witchcraft, and Religion : Anthropological Study of the Supernatural 7th edition<PHONE_NUMBER>216) by Pamela Moro, Magic, Witchcraft, and Religion - 8th edition. Magic, Witchcraft, and Religion - 6th edition. shop us with confidence. Summary.
Clarke's Bookshop (established in 1956) is situated in Cape Town, South Africa and carries both new and second hand books on Southern Africa. A HISTORICAL AND ANTHROPOLOGICAL APPROACH TO THE OLD TESTAMENT (BI-102/5.0 Credit Hours): During this 27 lesson course we examine the Old Testament through 30Oct11 - PEPIS: Vigilance in peacetime and war - potential enemies within 27Apr10 - PEPIS#126 - The Cult of Goldmine Sachs, bankers to Bilderberg.
Magic witchcraft and religion an anthropological study of the supernatural 8th edition. Dear Twitpic Community - thank you for all the wonderful photos you have taken over the years. We have now placed Twitpic in an archived state. CELTIC DEITIES. The gods and goddesses, or deities of the Celts are known from a variety of sources, these include written Celtic mythology, ancient places of worship. The interlaced triangles of the Hexagram and its core esoteric meaning, is at the root of ALL Lodge and other esoteric fraternity systems, as commonly depicted. Magic and Occult Books, Seals, Hoodoo Correspondence Course from the Lucky Mojo Curio Co., manufacturer and importer of traditional and folkloric magical, occult Ç½æäºé³ä¹æ¯ä¸æ¬¾ä¸æ³¨äºåç°ä¸åäº«çé³ä¹äº§åï¼ä¾æä¸ä¸é³ä¹äººãdjãå¥½åæ¨èåç¤¾äº¤åè½ï¼ä¸ºç¨æ·æé å ¨æ°çé³ä¹çæ´»ã. Magic, witchcraft, and religion : an anthropological study of the supernatural / compiled by Arthur C. Lehmann and James E. Myers Lehmann, Arthur C View online Borrow. Why should we pray to Virgin Mary? The reasons are plenty. The intercession of Mother Mary is very powerful as Jesus cannot neglect His mothers commands. Witchcraft or witchery broadly means the practice of and belief in magical skills and abilities exercised by solitary practitioners and groups. Witchcraft is a broad.
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A witch-hunt or witch purge is a search for people labelled "witches" or evidence of witchcraft, often involving moral panic or mass hysteria. The classical period. This comparative reader takes an anthropological approach to the study of religious beliefs, both strange and familiar. The engaging articles on all key issues related to the anthropology of religion grab the attention of students, while giving them an excellent foundation in contemporary ideas and approaches in the field.
Magic, Witchcraft and Religion: a Reader in the Anthropology of Religion 8th edition Pamela A. Moro James E. Myers 24 terms. anthony_varicelli. Anthropology 13. Magic, Witchcraft and Religion: a Reader in the Anthropology of Religion 8th edition Pamela A. Moro James E. Myers. STUDY. PLAY. Melford Spiro The 3 sets of desires satisfied. Magic, witchcraft, and religion : an anthropological study. Celtic Myth and Moonlight Celtic Deities.
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Magic, Witchcraft, and Religion: An Anthropological Study of the Supernatural / Edition 6 A comparative reader that takes an anthropological approach to the study of religious beliefs, both strange and familiar.


from qiskit import *
Introduction
The effect of noise is to give us outputs that are not quite correct. The effect of noise that occurs throughout a computation will be quite complex in general, as one would have to consider how each gate transforms the effect of each error.
A simpler form of noise is that occuring during final measurement. At this point, the only job remaining in the circuit is to extract a bit string as an output. For an $n$ qubit final measurement, this means extracting one of the $2^n$ possible $n$ bit strings. As a simple model of the noise in this process, we can imagine that the measurement first selects one of these outputs in a perfect and noiseless manner, and then noise subsequently causes this perfect output to be randomly perturbed before it is returned to the user.
Given this model, it is very easy to determine exactly what the effects of measurement errors are. We can simply prepare each of the $2^n$ possible basis states, immediately measure them, and see what probability exists for each outcome.
As an example, we will first create a simple noise model, which randomly flips each bit in an output with probability $p$.
from qiskit.providers.aer.noise import NoiseModel
from qiskit.providers.aer.noise.errors import pauli_error, depolarizing_error
def get_noise(p):
error_meas = pauli_error([('X',p), ('I', 1 - p)])
noise_model = NoiseModel()
noise_model.add_all_qubit_quantum_error(error_meas, "measure") # measurement error is applied to measurements
return noise_model
Let's start with an instance of this in which each bit is flipped $1\%$ of the time.
noise_model = get_noise(0.01)
Now we can test out its effects. Specifically, let's define a two qubit circuit and prepare the states $\left|00\right\rangle$, $\left|01\right\rangle$, $\left|10\right\rangle$ and $\left|11\right\rangle$. Without noise, these would lead to the definite outputs '00'
, '01'
, '10'
and '11'
, respectively. Let's see what happens with noise. Here, and in the rest of this section, the number of samples taken for each circuit will be shots=10000
.
for state in ['00','01','10','11']:
qc = QuantumCircuit(2,2)
if state[0]=='1':
qc.x(1)
if state[1]=='1':
qc.x(0)
qc.measure(qc.qregs[0],qc.cregs[0])
print(state+' becomes',
execute(qc,Aer.get_backend('qasm_simulator'),noise_model=noise_model,shots=10000).result().get_counts())
Here we find that the correct output is certainly the most dominant. Ones that differ on only a single bit (such as '01'
, '10'
in the case that the correct output is '00'
or '11'
), occur around $1\%$ of the time. Those than differ on two bits occur only a handful of times in 10000 samples, if at all.
So what about if we ran a circuit with this same noise model, and got an result like the following?
{'10': 98, '11': 4884, '01': 111, '00': 4907}
Here '01'
and '10'
occur for around $1\%$ of all samples. We know from our analysis of the basis states that such a result can be expected when these outcomes should in fact never occur, but instead the result should be something that differs from them by only one bit: '00'
or '11'
. When we look at the results for those two outcomes, we can see that they occur with roughly equal probability. We can therefore conclude that the initial state was not simply $\left|00\right\rangle$, or $\left|11\right\rangle$, but an equal superposition of the two. If true, this means that the result should have been something along the lines of.
{'11': 4977, '00': 5023}
Here is a circuit that produces results like this (up to statistical fluctuations).
qc = QuantumCircuit(2,2)
qc.h(0)
qc.cx(0,1)
qc.measure(qc.qregs[0],qc.cregs[0])
print(execute(qc,Aer.get_backend('qasm_simulator'),noise_model=noise_model,shots=10000).result().get_counts())
In this example we first looked at results for each of the definite basis states, and used these results to mitigate the effects of errors for a more general form of state. This is the basic principle behind measurement error mitigation.
Error mitigation in with linear algebra
Now we just need to find a way to perform the mitigation algorithmically rather than manually. We will do this by describing the random process using matrices. For this we need to rewrite our counts dictionaries as column vectors. For example, the dictionary {'10': 96, '11': 1, '01': 95, '00': 9808}
describing would be rewritten as
Here the first element is that for '00'
, the next is that for '01'
, and so on.
The information gathered from the basis states $\left|00\right\rangle$, $\left|01\right\rangle$, $\left|10\right\rangle$ and $\left|11\right\rangle$ can then be used to define a matrix, which rotates from an ideal set of counts to one affected by measurement noise. This is done by simply taking the counts dictionary for $\left|00\right\rangle$, normalizing it it so that all elements sum to one, and then using it as the first column of the matrix. The next column is similarly defined by the counts dictionary obtained for $\left|00\right\rangle$, and so on.
There will be statistical variations each time the circuit for each basis state is run. In the following, we will use the data obtained when this section was written, which was as follows.
00 becomes {'10': 96, '11': 1, '01': 95, '00': 9808}
01 becomes {'10': 2, '11': 103, '01': 9788, '00': 107}
10 becomes {'10': 9814, '11': 90, '01': 1, '00': 95}
11 becomes {'10': 87, '11': 9805, '01': 107, '00': 1}
This gives us the following matrix.
$$ M = \begin{pmatrix} 0.9808&0.0107&0.0095&0.0001 \\ 0.0095&0.9788&0.0001&0.0107 \\ 0.0096&0.0002&0.9814&0.0087 \\ 0.0001&0.0103&0.0090&0.9805 \end{pmatrix} $$If we now take the vector describing the perfect results for a given state, applying this matrix gives us a good approximation of the results when measurement noise is present.
$$ C_{noisy} = M ~ C_{ideal}$$.
As an example, let's apply this process for the state $(\left|00\right\rangle+\left|11\right\rangle)/\sqrt{2}$,
$$ \begin{pmatrix} 0.9808&0.0107&0.0095&0.0001 \\ 0.0095&0.9788&0.0001&0.0107 \\ 0.0096&0.0002&0.9814&0.0087 \\ 0.0001&0.0103&0.0090&0.9805 \end{pmatrix} \begin{pmatrix} 0 \\ 5000 \\ 5000 \\ 0 \end{pmatrix} = \begin{pmatrix} 101 \\ 4895.5 \\ 4908 \\ 96.5 \end{pmatrix}. $$In code, we can express this as follows.
import numpy as np
M = [[0.9808,0.0107,0.0095,0.0001],
[0.0095,0.9788,0.0001,0.0107],
[0.0096,0.0002,0.9814,0.0087],
[0.0001,0.0103,0.0090,0.9805]]
Cideal = [[0],
[5000],
[5000],
[0]]
Cnoisy = np.dot( M, Cideal)
print('C_noisy =\n',Cnoisy)
Either way, the resulting counts found in $C_{noisy}$, for measuring the $(\left|00\right\rangle+\left|11\right\rangle)/\sqrt{2}$ with measurement noise, come out quite close to the actual data we found earlier. So this matrix method is indeed a good way of predicting noisy results given a knowledge of what the results should be.
Unfortunately, this is the exact opposite of what we need. Instead of a way to transform ideal counts data into noisy data, we need a way to transform noisy data into ideal data. In linear algebra, we do this for a matrix $M$ by finding the inverse matrix $M^{-1}$,
$$C_{ideal} = M^{-1} C_{noisy}.$$The trouble is, such an inverse does not always exist. To obtain an inverse, we need the colums of the original matrix to be orthogonal to each other. This is not the case for the matrix above. Indeed, it will not hold for any matrix describing measurement noise.
One possible method is to use the so-called 'pseudo inverse'. In Python, this can be applied using one of the linear algebra tools from Scipy.
import scipy.linalg as la
M = [[0.9808,0.0107,0.0095,0.0001],
[0.0095,0.9788,0.0001,0.0107],
[0.0096,0.0002,0.9814,0.0087],
[0.0001,0.0103,0.0090,0.9805]]
Minv = la.pinv(M)
print(Minv)
Applying this inverse to $C_{noisy}$, we can obtain an approximation of the true counts.
Cmitigated = np.dot( Minv, Cnoisy)
print('C_mitigated =\n',Cmitigated)
Of course, counts should be integers, and so these values need to be rounded. This gives us a very nice result. $$ C_{mitigated} = \begin{pmatrix} 0 \\ 5000 \\ 5000 \\ 0 \end{pmatrix} $$
This is exactly the true result we desire. Our mitigation worked extremely well!
from qiskit.ignis.mitigation.measurement import (complete_meas_cal,CompleteMeasFitter)
The process of measurement error mitigation can also be done using tools from Qiskit. This handles the collection of data for the basis states, the construction of the matrices and the calculation of the inverse. The latter can be done using the pseudo inverse, as we saw above. However, the default is an even more sophisticated method using least squares fitting.
As an example, let's stick with doing error mitigation for a pair of qubits. For this we define a two qubit quantum register, and feed it into the function complete_meas_cal
.
qr = qiskit.QuantumRegister(2)
meas_calibs, state_labels = complete_meas_cal(qr=qr, circlabel='mcal')
This creates a set of circuits to take measurements for each of the four basis states for two qubits: $\left|00\right\rangle$, $\left|01\right\rangle$, $\left|10\right\rangle$ and $\left|11\right\rangle$.
for circuit in meas_calibs:
print('Circuit',circuit.name)
print(circuit)
print()
Let's now run these circuits without any noise present.
# Execute the calibration circuits without noise
backend = qiskit.Aer.get_backend('qasm_simulator')
job = qiskit.execute(meas_calibs, backend=backend, shots=1000)
cal_results = job.result()
With the results we can construct the calibration matrix, which we have been calling $M$.
meas_fitter = CompleteMeasFitter(cal_results, state_labels, circlabel='mcal')
print(meas_fitter.cal_matrix)
With no noise present, this is simply the identity matrix.
Now let's create a noise model. And to make things interesting, let's have the errors be ten times more likely than before.
noise_model = get_noise(0.1)
Again we can run the circuits, and look at the calibration matrix, $M$.
backend = qiskit.Aer.get_backend('qasm_simulator')
job = qiskit.execute(meas_calibs, backend=backend, shots=1000, noise_model=noise_model)
cal_results = job.result()
meas_fitter = CompleteMeasFitter(cal_results, state_labels, circlabel='mcal')
print(meas_fitter.cal_matrix)
This time we find a more interesting matrix, and one that is not invertible. Let's see how well we can mitigate for this noise. Again, let's use the Bell state $(\left|00\right\rangle+\left|11\right\rangle)/\sqrt{2}$ for our test.
qc = QuantumCircuit(2,2)
qc.h(0)
qc.cx(0,1)
qc.measure(qc.qregs[0],qc.cregs[0])
results = qiskit.execute(qc, backend=backend, shots=10000, noise_model=noise_model).result()
noisy_counts = results.get_counts()
print(noisy_counts)
In Qiskit we mitigate for the noise by creating a measurement filter object. Then, taking the results from above, we use this to calulate a mitigated set of counts. Qiskit returns this as a dictionary, so that the user doesn't need to use vectors themselves to get the result.
# Get the filter object
meas_filter = meas_fitter.filter
# Results with mitigation
mitigated_results = meas_filter.apply(results)
mitigated_counts = mitigated_results.get_counts(0)
To see the results most clearly, let's plot both the noisy and mitigated results.
from qiskit.tools.visualization import *
plot_histogram([noisy_counts, mitigated_counts], legend=['noisy', 'mitigated'])
Here we have taken results for which almost $20\%$ of samples are in the wrong state, and turned it into an exact representation of what the true results should be. However, this example does have just two qubits with a simple noise model. For more qubits, and more complex noise models or data from real devices, the mitigation will have more of a challenge. Perhaps you might find methods that are better than those Qiskit uses!


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Structural Integration Practitioner. Embodied Counselling Practitioner. Somatic Movement and Mindfulness Coach
Celeste works with individuals and groups to go beyond the surface and gain a deeper understanding of who they are and what they need. Her aim is to help people work with the body instead of against it, to understand how the physical body, mind and emotions are connected. With 10 years experience in embodied practices she supports her clients to find and create more balance in their lives with a down-to-earth and accessible tools. Celeste approaches sessions with the intention of freeing the body, not ‘fixing it’.
My journey with Structural Integration and Somatic Explorations began within myself. I was in IT Engineering when I felt a nudge within me to “move”... physically and in my life’s path. I felt frustrated and unfulfilled. I was doing what I was told I “should be doing” yet I was unhappy.
I started looking into embodied counselling as a student and it taught me that most of my connection with the world was just not real, it was almost as if I was connected with my ‘fantasy’ or ‘idea’ of the world and of myself, but not my actual, true self. I began paying attention to the body and learned how it helps us return to who we really are. That catapulted my journey and obsession with how experiences are felt through the body, how those experiences then shape our reality and how body-mind-emotions work together.
All of this has led me to see and believe that each one of us have everything within us to change and be happy... we just need to tune into that natural capacity, use and allow it to grow. My passion and ultimate goal with my clients is to help them stop struggling. This means I am here to help you reach your next available level of integration - be it physical, emotional, around beliefs or perceptions of the world. Everything we work on during the sessions can be applied to your daily life and will make a difference for you.
I have studied, worked and lived in Mendoza and Buenos Aires in Argentina where I completed my IT Engineering studies, became a Bach’s flowers practitioner, Yoga teacher and studied Ady-yoga with the founder. I still have weekly supervision sessions with him… it helps keep me sane. I then moved to Stockholm where I studied with various Structural Integration supervisors and mentors before hopping on a plane to Germany where continued my Structural Integration training and studied with mentors.
A few years ago, I moved to Sydney and it has been a journey of continuous learning with a focus on workshops around mindfulness, somatic movement, and Structural Integration. I’m a constant student of the human expression and what makes us who we are.


ZIP: 219 Title: Disabling Addition of New Value to the Sapling Chain Value Pool Owners: Daira Emma Hopwood<EMAIL_ADDRESS>Status: Reserved Category: Consensus Discussions-To: <https://github.com/zcash/zips/issues/428>


1. Modify the Reset to clear the current status.
2. When you enter a team that is not in the teamNames array add it to the teamNames array and add the score to the teamScores array.
3. Add a function that will display the teams and their current score to the page.
Extra Credit:


Post Up: Kawhi Leonard, Lou Williams Come Up Clutch in Clippers’ Win Over Rockets
by Ryne NelsonHawks 103 (4-11), Pistons 128 (5-10)
Detroit shot a whopping 60 percent from the field and 50 percent from three en route to snapping a five-game losing streak.
Andre Drummond dropped 23 points with 15 boards. Blake Griffin added a game-high 24 points and had a +18 plus/minus.
Atlanta has now lost 5 straight.
Hornets 118 (6-10), Wizards 125 (5-8)
Washington rallied back from a 13-point fourth quarter deficit to pull out the win.
Bradley Beal dropped a team-high 30 points with 12 dimes.
Kings 97 (6-8), Nets 116 (7-8)
Playing without Kyrie Irving for the fourth straight game, Brooklyn came away with a much-needed win.
Spencer Dinwiddie dropped a game-high 23 points with 7 dimes.
Spurs 104 (5-11), Sixers 115 (10-5)
Philly took the lead after the first 3 minutes and wouldn’t trail for the rest of the game.
Tobias Harris dropped a team-high 26 points with 6 boards and had a +18 plus/minus.
San Antonio has now lost an abysmal 8 straight games.
Heat 116 (11-3), Bulls 108 (5-11)
Miami completely lit up the Bulls in the first half, jumping out to a 26-point lead. Chicago would rally in the fourth quarter, but it would be too little too late.
Jimmy Butler dropped a game-high 27 points with 7 dimes and 4 thefts and had a +16 plus/minus.
Miami has now won 5 straight.
Lakers 130 (13-2), Thunder 127 (5-10)
The Lakers managed to squander a 15-point third quarter lead, but were able to gut out the win late in the fourth.
Anthony Davis dropped a game-high 33 points with 11 boards and 7 dimes. LeBron James added 23 points and 14 dimes and had an insane, one-handed catch (see below).
The Lakers have now won 6 straight.
Cavs 101 (4-11), Mavs 143 (10-5)
Dallas completely housed the Cavs in the second and third quarters and shot an insane 20-37 from the three-point line.
Luka Doncic finished with his third straight game of 30+ points, becoming the first Mav to accomplish the feat since Dirk Nowitzki in 2010. Luka finished with a game-high 30 points, 14 dimes, 7 boards and had a +21 plus/minus.
Cleveland has now lost 6 straight.
Celtics 92 (11-4), Nuggets 96 (11-3)
Despite losing Kemba Walker to a head injury and trailing by 19 points in the third quarter, the Celtics battled back to nearly win the game.
Denver would narrowly hold on, behind Nikola Jokic’s 18/16/10 triple-double. Jamal Murray added a game-high 22 points.
Warriors 109 (3-14), Jazz 113 (10-5)
Golden State battled back from a 21-point fourth quarter deficit to come within 2 points with 22 seconds left. Utah would eventually hold on to the lead.
Donovan Mitchell dropped a game-high 30 points. Rudy Gobert had 8 points, 19 boards and 7 blocks.
Rockets 119 (11-5), Clippers 122 (11-5)
Paul George and Kawhi Leonard have played just two games as teammates, but both games were two of the best games all season.
Kawhi, James Harden, Lou Williams, PG and Russell Westbrook all traded clutch buckets during a crazy fourth quarter. But it would be Kawhi who would hit the deciding, go-ahead shot.
George finished with 19 points, 8 boards and 7 dimes. Leonard had 24 points, 6 boards and 3 steals. Williams added a team-high 26 points, all scored in the second half.


Apache MADlib : Magnetic - Agile - Deep library
Supervised Learning
Neural Networks
Support Vector Machines (SVM)
Conditional Random Field (CRF)
Regression Models:
- Clustered Variance
- Cox-Proportional Hazards Regression
- Elastic Net Regularization
- Generalized Linear Models
- Linear Regression
- Logistic Regression
- Marginal Effects
- Multinomial Regression
- Naïve Bayes
- Ordinal Regression
- Robust Variance
Tree Methods
- Decision Tree
- Random Forest
Unsupervised Learning
Association Rules (Apriori)
Clustering (k-Means)
Principal Component Analysis (PCA)
Topic Modelling (Latent Dirichlet Allocation)
Graph
All Pairs Shortest Path (APSP)
Breadth-First Search
Hyperlink-Induced Topic Search (HITS)
Average Path Length
Closeness Centrality
Graph Diameter
In-Out Degree
PageRank and Personalized PageRank
Single Source Shortest Path (SSSP)
Weakly Connected Components
Utility Functions
Columns to Vector
Conjugate Gradient
Linear Solvers
Dense Linear Systems
Sparse Linear Systems
Mini-Batching
PMML Export
Term Frequency for Text
Vector to Columns
Model Selection
Cross Validation
Prediction Metrics
Train-Test Split
Data Types and Transformations
Array and Matrix Operations
Matrix Factorization
- Low Rank
- Singular Value Decomposition (SVD)
Norms and Distance Functions
Sparse Vectors
Encoding Categorical Variables
Path Functions
Pivot
Sessionize
Stemming
Statistics
Descriptive Statistics
- Cardinality Estimations
- Correlation and Covariance
- Summary
Inferential Statistics
- Hypothesis Tests
Probability Functions
Sampling Balanced, Random, Stratified
ARIMA - Time Series Analysis
K-Nearest Neighbors
Comprehensive and Mature
data science library
User Interface
SQL
High-level Abstraction Layer
(iteration controller, ...)
Python
RDBMS
Built-in
Functions
(C++)
Functions for Inner Loops
(implements convex optimization)
Low-level Abstration Layer
(matrix operations,
C++ to DB type bridge, ...)
RDBMS Query Processing
(Greenplum, PostgreSQL)
SELECT madlib.linregr_train(
'houses',
'house_linregr',
'price',
'ARRAY[1, tax, bath, size]');
MADlib model function
Table containing training data
Table in which to save results
Column containing dependent variable
Features included in the model
SELECT madlib.linregr_train(
'houses',
'house_linregr',
'price',
'ARRAY[1, tax, bath, size]',
'style');
MADlib model function
Table containing training data
Table in which to save results
Column containing dependent variable
Features included in the model
Create multiple output models (one for each value of house style)
SELECT madlib.linregr_train(
'houses',
'house_linregr',
'price',
'ARRAY[1, tax, bath, hsize]'
);
SELECT houses.*,
madlib.linregr_predict(ARRAY[1,tax,bath,hsize],
m.coef) as predict
FROM houses,
houses_linregr m;
MADlib model scoring function
Table with data to be scored
Table containing model


| | From th=
e blog | Steps Stack Overflow is t=
aking to help fight racism stackoverflow.blog B=
lack lives matter, and Stack Overflow is taking concrete steps to help comb=
at systemic racism. The rise of the DevOps mindset stacko=
verflow.blog DevOps has become a buzzwords with many conflicting=
definitions. What=E2=80=99s for certain is it=E2=80=99s on the rise. In ou=
r 2020 developer Survey, around 80% of the respondents believed that DevOps=
is at least somewhat important. We take a look at the phenomenon, some def=
initions, and talk to our engineers about what it means. Podcast 243: Turn on, tune in, drop out, log off=
stackoverflow.blo=
g This week, we chat about Cloudflare.tv and Github Classroom. <=
!-- Section : END --> |


WITNESS LIST Civil Practices Committee February 23, 2005-2:00P HB 729 For: Collins, Samuel B. (Self) HB 755 For: Alcorta, Victor (Georgia Pacific Corporation) Andrews, Kay (Texas Civil Justice League) Capelo, Jaime (Texas Alliance for Patient Access) Douglas, Barbara (Lumbermens Assn. of Texas) Gilbert, Bo (Self and Independent Insurance Agents of Texas) Golemon, Kinnan (Shell Oil Company & Texas Chemical Council & ACIT) Hazlewood, Steve (The Dow Chemical Company) Howden, Robert S. (Texas Asbestos Consumers Coalition & Texas Civil Justice League) Marlow, John (American Insurance Assoc.) McCauley, Cindy (Lyondell Chemical Company) Meroney, Mike (Huntsman Corporation) Moore, Julie W. (Occidental Petroleum Corporation) Morphew, Cindy (Texas Oil & Gas Association) Parsley, Lee (Texans for Lawsuit Reform) Ratliff, Bill (Texas Civil Justice League) Saxon, Lucinda Dean (Texas Association of Business) Sellers, Tom (Conoco Phillips) Sickels, Linda (Trinity Ind. Inc.) Slaughter, Edward (Self and Texas Civil Justice League) Tays, Sara (Exxon Mobil Corporation) Trabulsi, Jr., Richard J. (Texans for Lawsuit Reform) Against: Choate, Guy (Texas Trial Lawyers Association) Siegel, Charles (Self and Texas Trial Lawyers Assn.)


Titanium Desktop test app
Open Application
which app?
google.com (_self)
google.com (_blank)
google.com (sysbrowser)
Open URL
Open URL with no parameters (test exception)
Take a desktop screenshot
Create Shortcut
from
to


{% extends "layout.html" %} {% block title %}Upload documents for this light obstruction notice (LON){% endblock %} {% block body %} {% include 'partials/phase_banner_beta.html' %} {% include 'partials/validation_partial.html' %} Upload documents for this light obstruction notice (LON) Form A and colour plan {% if validation_errors and validation_errors['form-a-file-input'] %} {{ validation_errors['form-a-file-input'].inline_message }} {% endif %} Form A is an application form for the LON Colour plan is a plan showing the land affected by the LON Form A Supported format: PDF What certificate can you provide? What certificate can you provide? {% if validation_errors and validation_errors['certificate'] %} {{ validation_errors['certificate'].inline_message }} {% endif %} Temporary LON certificate This is from the Upper Tribunal (Lands Chamber). It is made when the tribunal issues a temporary LON to the person who has applied for it. Temporary LON certificate {% if validation_errors and validation_errors['temporary-lon-cert-file-input'] %} {{ validation_errors['temporary-lon-cert-file-input'].inline_message }} {% endif %} Supported format: PDF Date of certificate For example, 31 3 2017 {% if validation_errors and validation_errors['tribunal_temporary_certificate_date'] %} {{ validation_errors['tribunal_temporary_certificate_date'].inline_message }} {% endif %} Day Month Year Date of Expiry This is usually a number of months after today's date. Today's date is the registration date {% if validation_errors and validation_errors['tribunal_temporary_certificate_expiry_date'] %} {{ validation_errors['tribunal_temporary_certificate_expiry_date'].inline_message }} {% endif %} Day Month Year Definitive LON certificate This is from the Upper Tribunal (Lands Chamber). It is made when the tribunal issues a full LON to the person who has applied for it. Definitive LON certificate {% if validation_errors and validation_errors['definitive-lon-cert-file-input'] %} {{ validation_errors['definitive-lon-cert-file-input'].inline_message }} {% endif %} Supported format: PDF Date of certificate For example, 31 3 2017 {% if validation_errors and validation_errors['tribunal_definitive_certificate_date'] %} {{ validation_errors['tribunal_definitive_certificate_date'].inline_message }} {% endif %} Day Month Year {% include 'partials/submit_form_partial.html' %} {% endblock %}
Supported format: PDF
For example, 31 3 2017
This is usually a number of months after today's date. Today's date is the registration date


Crude Oil Prices News & Forecast: WTI fades bounce to 200-day EMA amid US-Sino spat
by Yohay ElamOil dips in Asia on waning trade optimism
Oil prices on both sides of the Atlantic are flashing red amid warning US-China trade optimism and the resulting risk-off tone in the global markets.
At press time, a barrel of Brent is changing hands at $62.20, representing a 0.35% drop on the day. WTI is also trading in the red at $56.90 per barrel.
The losses could be associated with reports stating that the phase one" U.S.-China trade deal could slip into next year. Read more…
Brent Oil
| Overview | |
|---|---|
| Today last price | 62.24 |
| Today Daily Change | -0.24 |
| Today Daily Change % | -0.38 |
| Today daily open | 62.48 |
| Trends | |
|---|---|
| Daily SMA20 | 62 |
| Daily SMA50 | 61.44 |
| Daily SMA100 | 61.54 |
| Daily SMA200 | 64.45 |
| Levels | |
|---|---|
| Previous Daily High | 62.82 |
| Previous Daily Low | 60.33 |
| Previous Weekly High | 63.73 |
| Previous Weekly Low | 61.33 |
| Previous Monthly High | 62.32 |
| Previous Monthly Low | 56.86 |
| Daily Fibonacci 38.2% | 61.87 |
| Daily Fibonacci 61.8% | 61.28 |
| Daily Pivot Point S1 | 60.93 |
| Daily Pivot Point S2 | 59.39 |
| Daily Pivot Point S3 | 58.44 |
| Daily Pivot Point R1 | 63.42 |
| Daily Pivot Point R2 | 64.37 |
| Daily Pivot Point R3 | 65.91 |
WTI fades bounce to 200-day EMA following an escalation in US-China tussle
With the trade/political jitters between the world’s top two economies likely challenging global energy demand, WTI stops the recent recovery below 200-day EMA while taking rounds to $57.00 during the Asian morning on Thursday.
The trade stalemate between the United States (US) and China worsened recently after President Trump said he doesn’t think “China is stepping up to the level I want in trade talks.” Also contributing to the pessimism is the Reuters’ news that Trump is expected to sign Hong Kong Human Rights Bill passed by Congress. Read more...
additional important levels
| Overview | |
|---|---|
| Today last price | 56.96 |
| Today Daily Change | -0.16 |
| Today Daily Change % | -0.28% |
| Today daily open | 57.12 |
| Trends | |
|---|---|
| Daily SMA20 | 56.5 |
| Daily SMA50 | 55.74 |
| Daily SMA100 | 55.95 |
| Daily SMA200 | 57.59 |
| Levels | |
|---|---|
| Previous Daily High | 57.39 |
| Previous Daily Low | 54.89 |
| Previous Weekly High | 58.06 |
| Previous Weekly Low | 56.29 |
| Previous Monthly High | 56.97 |
| Previous Monthly Low | 51.19 |
| Daily Fibonacci 38.2% | 56.44 |
| Daily Fibonacci 61.8% | 55.84 |
| Daily Pivot Point S1 | 55.54 |
| Daily Pivot Point S2 | 53.97 |
| Daily Pivot Point S3 | 53.04 |
| Daily Pivot Point R1 | 58.04 |
| Daily Pivot Point R2 | 58.97 |
| Daily Pivot Point R3 | 60.54 |


Why flipBRAIN?
There is enormous amount of learning content available online in
various forms such as videos, audio and ebooks. Most of such content
is disorganized, but can be reused in different contexts.
flipBRAIN aims to provide a platform for stitching
learning trails from a combination of existing
open learning material such as video lectures, e-books, e-quizzes etc.
The term learning trails is taken from the
concept of a trail in good old
Java tutorial.
At flipBRAIN anyone can contribute and create a learning trail!
Comparison with similar solutions
- YouTube Playlists
- Provides only video comments; lacks learning oriented, searchable
discussion forums.
- No quizzes or leaning assessment tools.
- Learning Management Systems (LMS)
- Most LMS platforms such as Sakai, Canvas, Moodle etc.
have features to support functionality which flipBRAIN does.
- In fact, an LMS is too complex a solution for the purpose of flipBRAIN.
- Typically deployed privately for accessing within a university.
- Content is controlled tightly by the LMS host.
- KhanAcademy
- Tightly controlled content.
- Very difficult to add arbitrary learning content and quizzes etc.
- MOOKIT
- Mainly geared for hosting MOOCs.
- Content is controlled tightly by the MOOC provider.


The first modification is probably the most important. Although my unit did have continuity from case to ground plug connection, there was pretty limited contact surface with the anodized case:
Although my unit was apparently assembled just last year, in September of 2019, the was a ton of the masking tape, just as described in other blogs. I had hoped the manufacturer would have changed this as there are so many comments on the bad smell of the heated masking tape once the oven is in use.
Be careful pulling it off to ensure the aluminium foil does not tear:
One roll of kapton tape was more than enough to replace the masking tape to insulate the electronics from the aluminum foil. I use a bit extra as additional strain relief on the thermocouple wires:
Regarding the
fan
install, I suggest doing this first. Mine was so obnoxiously load I ended up cutting the wires just to silent it. (There's no fan check circuitry) Oh, and this specific fan needs to have the hole drilled out with a 1/8" bit. Perhaps the existing screws could be force-tapped into the plastic, but I didn't want to break it.
Piotr mentions disconnecting the solid state relay connection, but does say why. Putting my board into bootloader mode immediately shows why this is a good idea: mine turned on! I'm glad the SSR was disconnected. It was a bit startling, as I had never heard the large fan running. Other than the power-up test, I proceeded directly to modification.
That's the cold-junction sensor down in the lower right. But notice the yellow circle. It sure looks like the Vdd and GND pins are tied together to ground. Sure enough, this is consistent with the
schematic in that both
DS18B20 pins are grounded. This is a clever idea, as from the
datasheet (see page 7), this device has a
parasite mode:
Still, it may not be clear as to why this cold junction sensor is on the main board, at the
old junction, and not on the new mod board. It is a leftover from a prior upgrade, as there's a
note "
the cold-junction sensor is still present on my board, but not used when the external TC IF is detected".
Ok, so on to the upgrade!
Key to the firmware upgrade is the ISP connector:
Although a variety of hardware programmers are possible, I used a simple USB to TTL device and manually fiddled with the ISP and Reset lines.
Fortunately the manufacturer kindly installed a header. Here's a picture of it on the board:
As usual, the connections are "crossover": Connect Tx (Transmit) of the USB device to the Rx (Receive) on the board, and Rx to Tx.
WARNING: Is is never a good idea to attempt to communicate or flash a device that is not already powered up.
From the factory, the new firmware is programmed with
FlashMagic by:
- Connect ISP to ground
- Momentarily connect RESET to ground
- Release ISP from ground
The the new firmware, the unit should be able to go into bootloader mode by holding down the F1 when turning on the oven.
After the new firmware is in place, run it by again bringing the RESET line momentarily low (to ground). To see the bootup messages, run
Putty at 115200 8N1. The FlashMagic software may need to be shutdown if it still has the USB device in use.
Here's my setup:
Not shown: I used another USB device (the
SPIDriver) that has a couple of header pins exposed for ground connections.
My first attempt was to see if the
FlashMagic could see my device. I was initially concerned that my software only showed half the number of communication parameters. Perhaps they only show up if you have a hardware programmer plugged in? In any case, I had no opportunity to select an interface or oscillator frequency as shown in the
Flashing the LPC21xx controller section of the
UnifiedEngineering T-962-improvements wiki. Note the device selected is the
LPC2134:
Next, "just in case" something went wrong (or you never know, you might need that someday), I saved the original firmware. Twice. Click on ISP - Read, and then click on the Export Memory tab:
The next step could be a point of no return. Hey, we're here to void warranties, right?
If instead you want to build the firmware from scratch (here shown for WSL):
{% include code_header.html %}
// over a gig of disk space is needed iss you don't have gcc-arm-none-eabi already installed
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install binutils-arm-none-eabi
sudo apt-get install gcc-arm-none-eabi
cd /mnt/c/workspace/
cd T-962-improvements
make
// see file: ./build/T-962-controller.hex
The compiled current code in GitHub did *not* match the releases file for me.
Somewhat surprisingly, the upload of firmware went really quite smoothly, despite my software missing half of the available parameters:
When the FlashMagic app is sized relatively small - note the "Start" button to begin upload is in the lower right may not be immediately obvious.
The 3 connections of interest are power, ground, and data:
Another seeming invitation to modification was the convenient 3 square pads, shown with my wires already connected:
Connection of the board was pretty straightforward. Here's the an initial working modification:
Edit: I didn't really like the tape method shown above for the new thermocouple interface, as the tape does not stick as well to the cabinet as one might like. So I added these tie wraps:
Note the main strain relief (1) for the fairly rigid thermocouple wires. There's another tie-wrap (2) in the empty PCB hole - positioned to keep the next tie wrap (3) on the thermocouple wires away from the main PCB. This tie wrap has the respective tail taped down as an extra measure of stability. In addition to the kapton tape underneath, there's a small piece of card stock under the tape (part of the fan packaging was used here) for additional electrical insulation. By far the (1) tie-wrap does most of the work to keep the new interface board in a stable position.
A better solution would be to drill a couple of mounting holes instead of the (2) and (3) tie wraps. I will probably do that when my other 2 K-Type thermocouples arrive. Alternatively,
cable management clips might work (depending the strength of the adhesive)
Back to the project blog from that initially working state...
However this is where things took a turn for the worse. I powered on the unit. The display was blank! Oh no! How could that be? I took a short break to think about it. Was this the end? $400 down the toilet?
I refused to give up. I'm not new at this. Prior to being only a software engineer, I spent nearly a decade at a small industrial manufacturing company, building and repairing all sorts of crazy things big and small. I didn't do anything wrong here. No magic smoke, no mishaps. What went wrong?
So ok, let's backtrack. What's different? Well the Thermocouple board is connected, but duh, how could that affect this display. It shouldn't... but let's go back to a known working state. I removed the board. Nothing. Still a blank display at power up. No fun if it is too easy, right? Could it have damaged the display? No way.
Perhaps the firmware got corrupted and crashed? I hooked up the computer again, flashed fresh firmware. Success! Ok, cool, that was odd, but let's proceed.
I reconnected thee thermocouple board. The display was blank again! Are you kidding me? So let's repeat the routine: remove thermocouple board, fresh firmware, it works! Ok, fool me once...
Clearly something else going on here. So instead of flashing firmware, I hooked up that serial port to see what sort of messages are displayed at startup time. It's completely happy! No indication of problem, erm - other than the blank display.
How can that be? Well, since I had everything hooked up again, it was easier to restart by bringing the RESET pin low, instead of reaching for the power switch. Success! Yes, after a reset - the display works just fine. This was never about the external board or the firmware. It was always about the after-powerup reset.That certainly falls into the undesired feature category.
How can this be a problem? The factory firmware certainly did not have this issue. The Microcontoller does indeed have reset startup circuity built in. Is this is a software issue or a hardware issue?
There's a mystery mod that I have not been able to identify:
I remember seeing these resistors when reading about the mod before ordering my oven. Note not only the radial-lead resistors tacked on o the chip, but there's also a small SMD (probably a pullup) on the thermocouple board connection. I wonder what they do? Surely resistors alone will not resolve the new-found reset problem.
Ok, so I needed find a solution for the reset problem. Perhaps some sort of RC delay? That seems too hackish. It may be temperature related, as upon fresh power up later in the day, I didn't the reset problem at all. The display is working fine. Even waiting only a couple of second after power down and turning on the oven - the display is working fine. Then few hours later, the display problem had returned! This time it may have been in bootloader mode as the big fan came on while the display was blank and the heater came on!! I thought that the problem may be related to my franken-ribbon cable on the ISP (see below) - but no, removing that completely and random startup problem remained.
Reminder: The display is supposed to be blank in bootloader mode. But the unit should never boot into bootloader mode when simply powering up.
Ok, so if we take another look at the reset circuitry (above)... well, there is none. ~RESET on pin 57 appears to just go straight to the header.
Two of the most common solutions to the worlds problems are (1) decoupling capacitors and (2) pullup resistors. Pullup it is! As it turned out, there's a large through-hole nearby that has 3v3 available:
I crimped a 10K resistor to the header connector on the reset line. Here is is with the heat-shrink insulation not yet in place:
Voila! So far, so good! I've not yet seen the blank display problem return!
As the header access is buried inside, I wanted something a bit more accessible. I started this portion of the project early on - long before I know about the reset problem.
I spent a relatively large percentage of the upgrade time manually assembling the header cable and assembly:
If there was ever something to void my warranty, I'm pretty sure the holes drilled in the front panel did it:
In the end I have a reflow oven that is immediately recognized as mine:


Dear Sir/Madam, I am Mr.Zheng Xiaohua,we are a group of business men in China, who deal on import and export of Electronic Mechinaries into the Canada,America and Europe. We are searching for representatives who can help us establish a medium of getting to our costumers in the Canada, America and Europe as well as making payments through you to us. Please if you are interested in transacting business with us we will be very glad. Please contact us for more information. Subject to your satisfaction you will be given the opportunity to negotiate your mode of which we will pay for your services as our representative in Canada,America and Europe. Regards, Mr.Zheng Xiaohua Manager. ___________________________________________________________________________ Mail envoyer depuis le Le Site de Adrien Webmaster de Ce Site : adi90 amaurel90@hotmail.com


{% extends "petitions/admissibility_form/admissibilityform_list.html" %} {% block replacedatefilter%} {%endblock%} {% block title %} Summary {% endblock title %} {% block admissibilitytableheading %}
This table shows all the admissible petitions that I did admissibility test on them but do not have a summary. You can search using any criteria
{% endblock %} {% block addbutton %} {% if perms.petitions.add_petitionsummary %}


(%) infection residents risk resident (Age health study care doctors patients control {border-style px;} reported #ffffff;} concerns medical prevention Health Male, measures tuberculosis Tuberculosis masks open-ended key responses TB. consequences drug-resistant included theme Female, International Medicine) N/responses concern developing expressed questions use work workplace Concern Disease India TB, acquired aware exposure guidelines need occupationally poor px; using workplace. {font-family %); Care Lung South acquiring clinical contributed disease font-size hospital question subthemes treatment workers HCWs Infection Table World double; effects excessive knowledge lack reduce residents. responded respondents themes working workload Control Developing Medicine Organization article border-color border-width concerned conducted duration encounters high inadequate interventions majority professional questionnaire settings social solid; structured testing transmission {font-style {font-weight ./ijtld.. Africa Chandanwale Farley Joshi Medical Ophthalmology) Pai Research Social analysis bold common cough courier; disagree, em; http://orcid.org/--- institutional like long main measures. mechanical patient patients, perceptions prevent procedures protective pt;} regarding screening tertiary undiagnosed ventilation worried year


Abuse trial of Bloomfield mom delayed one more time
by KTVO News DeskBLOOMFIELD, Iowa — The trial of a Bloomfield, Iowa, mother accused of being complicit in the sexual abuse of her daughter has been delayed again.
Kendra Hoover will now face a Davis County jury in February.
Hoover is charged with 14 counts of child endangerment and neglect.
This is the second time in less than a month the trial has been pushed back.
In March 2018, Hoover’s live-in boyfriend, Steven Crook, was arrested for videotaping the rape of her daughter. Hoover is accused of allowing her child to be around Crook, even after she saw the abuse on tape.
Crook pleaded guilty to federal charges, and is currently serving a 120-year prison sentence.
Hoover is currently free on bond as she awaits trial.


We sell platforms!
- enable wireless infomediaries
- visualize synergistic convergence
- streamline intuitive e-markets
- utilize scalable interfaces
- transition killer e-markets
- integrate real-time web-readiness
- exploit back-end channels
- productize customized relationships
- disintermediate end-to-end paradigms
- drive open-source networks
- seize dot-com niches


Concord, NC
Welcome to the Holiday Inn! We are located on exit 49 on I-85. We have single beds, double beds, and full suties to offer. There are many attractions in a 5 mile radius from the hotel including The Great Wolf Lodge, Concord Mills Mall, and many food locations such as Texas Roadhouse, Hotshots Sports Bar & Grill,TGI Friday's, Sticky fingers Ribhouse-BBQ. Those are only few! We also have the NASCAR Speedway about a mile from the hotel.
Amenities
We have many amenities such as a:
Pool
Meeting room
Breakfast area
Gym
Guest lounge
A outside sitting area


Corps member feared missing as thugs attack polling unit in Bayelsa
by Our ReportersChukwudi Akasike, Tony Okafor and Femi Dawodu
There are indications that an unidentified corps member has gone missing when thugs attacked a polling unit at Eribo Square, Unit 2, Ward 1, Yenagoa, Bayelsa State.
Some of the corps member’s colleagues, who were also on election duty, explained that the hoodlums stormed the polling unit around 1.00 p.m. and began to threaten Independent National Electoral Commission officials.
One of them, who could not immediately give our correspondent the name of the missing corps member said some of them were saved by some agents of a political party.
The corps members said, ”The party agent was one of those who rescued us from the thugs. But he may have made a mistake by raising his voice when the police were planning to resolve the crisis at hand.”


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
A beautiful starter for a Chinese-style banquet. Serve the stuffed prawns on a platter and let people help themselves.
Preheat the oven to 180C/160C Fan/Gas 5.
For the Macanese prawns, using a very sharp knife, carefully butterfly the prawns but cutting them in half horizontally. Keep the shell intact and, using the tip of the knife, remove the dark digestive cord. Gently rinse the prawns in cold water and pat them dry with kitchen paper.
Heat a wok until it is hot. Add 2 tablespoons olive oil, the garlic, onion, spring onions and chillies. Stir-fry for about 2 minutes. Season with salt and pepper to taste. Transfer to a bowl and set aside while you cook the prawns.
Reheat the wok and add the remaining 3 tablespoons olive oil. Gently fry the prawns for about 30 seconds on each side.
Place the prawns on a baking tray and stuff each of the prawns with the garlic and onion mixture. Reserve any remaining stuffing for the sauce.
Put the prawns in the oven for about 3-4 minutes, or until cooked.
For the sauce, add the remaining stuffing to a small saucepan set over a medium heat. Gently incorporate the butter and simmer gently for about 3 minutes.
To serve, put the prawns on a serving platter and serve with the lemon wedges and butter sauce.


TAMIYA Cam-Program Robot Manager
Default Teleoperator
roslaunch tamiya_cam_robot teleop.launch
This web server sends motor efforts std_msgs::String
topics to a motor control node.
Teleoperator w/ Twist
roslaunch tamiya_cam_robot teleop_twist.launch
This web server sends moving efforts (linear and angular) as std_geometry::Twist
topics to a motor control node.
Music Player
roslaunch tamiya_cam_robot music_player.launch
This web server sends a full path of a music file as std_msgs::String
topics to a music player node.
LED Tuner
roslaunch tamiya_cam_robot led_tuner.launch
This web server sends hex-color codes as std_msgs::UInt32MultiArray
topics to a color listener node.
Curiosity
roslaunch tamiya_cam_robot curiosity.launch
This robot has 3 servo motors for head and arms.


System Status
Hardware Information
System
Processor
Memory
Disk
Event Log
Remote Control
Power Policies
Network Settings
IPv6 Network Settings
System Name Settings
User Accounts
|
System Information
Platform |
|
|
|
Computer model |
ThinkServer RS140 |
|
Manufacturer |
LENOVO |
|
Version |
70F9001NUX |
|
Serial number
| AB045N1Q |
|
System ID |
fe2dad21-aa72-e211-9722-9134fda321a2 |
|
|
|
Baseboard |
|
|
|
Manufacturer |
LENOVO |
|
Product name |
ThinkServer RS140 |
|
Version |
Not Defined |
|
Serial number |
|
|
Asset tag |
|
|
Replaceable? |
Yes |
|
|
|
|
BIOS |
|
|
|
|
Vendor |
LENOVO |
|
Version |
FBKT87CUS |
|
Release date |
06/16/2015 |
|
Supported functions |
| PCI |
Upgradeable |
| Shadowing is allowed |
Boot from CD |
| Selectable boot |
ROM socketed |
| EDD spec |
5.25"/1.2MB floppy services |
| 3.5"/720KB floppy services |
3.5"/2.88MB floppy services |
| Print Screen service |
8042 keyboard services |
| Serial services |
Printer services |
|
|
|
|
|


As specified in the Boost MPL library, there are two ways to pass metafunctions as metadata, and both ways fall under the Boost MPL terminology of 'lambda expressions':
Using a placeholder expression is the easiest way and does not require the
programmer to create a metafunction class for passing the metadata. The syntax
for this is fairly simple. The syntax for passing a macro metafunction becomes
macrometafunction<_>
etc.
depending on how many parameters are bring passed. Thus for two parameters
we would have macrometafunction<_,_>
etc.,
with another placeholder (_
)
added for each subsequent parameter.
However using a placeholder expression may not be the fastest way when considering compile-time speed. Because of this the TTI library provides a set of macros for each of the macro metafunctions which generate a corresponding metafunction class. We will call this set of macros the 'metafunction class macros'.
These macros take exactly the same macro parameters as their corresponding macro metafunctions. They generate a corresponding metafunction class rather than a metafunction itself, which allows us to pass our macro metafunctions as metadata, just as using placeholder expressions allows us to do.
For these metafunction class macros there is a simple form and a complex form
name just as there is for the macro metafunctions. For each macro metafunction,
the name for the corresponding metafunction class macro is the macro metafunction
name with the sequence MTFC_
( for "MeTaFunction Class" ) following the BOOST_TTI_
( or BOOST_TTI_VM_
) portion
of the macro metafunction name. The subsequent metafunction class name, using
the simple form, is the same name as the corresponding macro metafunction name
but with mtfc_
prepended to
the name.
As with the complex form name of the macro metafunctions, the complex form name of the corresponding metafunction class macros is completely determined by the first 'trait' parameter.
In the following table I do not specify the macro parameters as they are exactly the same as those for their corresponding macro metafunction.
Table 1.5. TTI Metafunction Classes
|
Macro Metafunction |
Metafunction Class Macro |
Metafunction Class Name |
|---|---|---|
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Each of the metafunction classes have exactly the same functionality as their corresponding macro metafunction. The metafunction class generated can be passed as metadata in the same way that their correspending macro metafunctions with placeholder expressions can be passed as metadata.
As will be seen when we discuss the nullary type metafunctions, each nullary type metafunction takes as its first parameter a macro metafunction as metadata in the form of a lambda expression. Therefore we can use either a metafunction class generated by one of the macros above, or a placeholder expression, to pass a macro metafunction as metadata to our nullary type metafunctions. Other uses for our macro metafunctions as metadata may be found by the template metaprogrammer using the TTI library.


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NIGHTFLYERS A film review by Mike Caplinger Copyright 1987 Mike Caplinger
You'd think I'd have learned after DUNE and 2010 that Hollywood is usually incapable of transforming a science fiction work to the screen without trashing it. Still, both DUNE and 2010 had their moments. So when I read about a year back that George R. R. Martin's novella "Nightflyers" was being made into a movie, I was awaiting it with some anticipation.
I needn't have bothered. There are a number of liberties I expected would be taken with the novella. For example, Martin's heroine is a black, very athletic woman--though her being black was an incidental in her society, so the casting of Mary Catherine Stewart was perhaps forgivable--as were the name changes and the almost total disappearance of the enormously detailed background universe that gives a Martin story an extra enjoyment. In fact, in general I have no complaints with the casting, the name changes, or the illogical throwaway moving of the story's timeframe into the 21st Century.
But they ruined and bastardized the plot. Even the massive amount of violence present in the novella, while still here in large part, is made completely gratuitous--few of the violent events from the novella even happen. And the subtle interplay of the characters' personalities, which made the novella so terrific, is gone here. The most glaring omission is the absence of the heroine's superior generic makeup (though at least they didn't make her a screamer).
The special effects are poor by today's standards, but if they had gone with the resources they had, casting, sets, and all, the producers could have made a credible film version of "Nightflyers." What they did make is celluloid trash. And what they did to the Volcryn!
I'll be interested in seeing what people who aren't Martin fans think of this film; I think it's poor by anyone's standards, but I've been a Martin fan for a long, long time. I give this film 0.5 stars out of 4.
I'd like to hear the story behind this film's scripting. I hope Martin got a good deal for the rights, because he couldn't have been involved afterwards.
By the way: the main theme of the movie is a note-for-note steal of one of the themes from BLADE RUNNER. If I were Vangelis I'd sue, but I don't think this turkey is going to make any money.
Mike Caplinger<EMAIL_ADDRESS>{decvax,ihnp4}!thumper!mike
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


# -*- coding: utf-8 -*-
"""
This module contains the functionality to trigger actions
according to the match of regular expression.
"""
from typing import Any, Mapping, Tuple
import re
from string import Template
from requests_futures.sessions import FuturesSession
session = FuturesSession()
[docs]class HttpActionRule(object):
"""
A rule for triggering a HTTP request when matching a text line,
according to a regular expression.
:param config:
A dict like structure with the following keys:
`pattern` with the regular expression,
`url` with an URL to invoke,
and `timeout` with a timeout in seconds,
when to cancel the HTTP request.
:type config: Mapping[str, Any]
"""
def __init__(self, config: Mapping[str, Any]):
try:
self._pattern = re.compile(str(config.get('pattern')))
except Exception as e:
print('Error in regular expression: ', str(e))
self._pattern = None
self._url_template = Template(str(config.get('url')))
try:
self._timeout = float(config.get('timeout', 10.0))
except Exception as e:
print('Invalid timeout value: ', str(e))
self._timeout = 10.0
def _trigger(self, line, match):
url = self._url_template.safe_substitute(**match.groupdict())
session.get(url, timeout=self._timeout)
[docs] def process(self, line: str) -> Tuple[bool, str]:
"""
Process a line and trigger an HTTP request if this rule
matches the given text line.
:param line:
The text line to process.
:type line: str
:return:
A tuple with a boolean, stating if the pattern matched,
and the text line.
"""
match = self._pattern.search(line) if self._pattern else None
if match:
self._trigger(line, match)
return True, line
else:
return False, line
def __call__(self, line: str) -> Tuple[bool, str]:
return self.process(line)


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AbstractMobiusMapper
implementation which
parse the records of this dataset input Tuple
.
DefaultSeqFileMapper
inputColumn
in Max.Max(Column)
in a group.Max
operation to
get the maximum value of the given
inputColumn
within a group.
Max
operation to
get the maximum value of the given
inputColumn
within a group.
inputColumn
in
a group.Medium
operation to
get the medium value of the given
inputColumn
within a group.
Medium
operation to
get the medium value of the given
inputColumn
within a group.
confs
into ones.
inputColumn
in Min.Min(Column)
in a group.Min
operation to
get the minimum value of the given
inputColumn
within a group.
Min
operation to
get the minimum value of the given
inputColumn
within a group.
MobiusJob
which contains
the analysis flow.
MobiusJob
.MultipleInputs
uses the input path to find the corresponding
Map class.
|
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| PREV LETTER NEXT LETTER | FRAMES NO FRAMES |


Classes vs Modules - What's the Difference?
July 26th, 2015
Classes vs Modules is an Object-Oriented question I've had for a while. The last few weeks have involved heavy class uses, but there's always this mystery called module that pops up every once in a while. To better understand the difference, I found this guide below:
| Class | Module | |
|---|---|---|
| instantiation | can be instantiated | can *not* be instantiated |
| usage | object creation | mixin facility. provide a namespace. |
| superclass | module | object |
| consists of | methods, constants, and variables | methods, constants, and classes |
| methods | class methods, instance methods | module methods, instance methods |
| inheritance | inherits behavior and can be base for inheritance | no inheritance |
| inclusion | cannot be included | can be included in classes and modules by using the include command (includes all instance methods as instance methods in class/module) |
| extension | can not exten with extend command (only with inheritance) | module can extend instance by using extend command (extends given instance with singleton methods from module) |
The above can be thick to understand but the general gist is modules are usually parents of classes. Modules provide methods that can be used across multiple classes - similar to "libraries". Classes are about objects while modules are about functions.
An example is an authentication/authorization system. These systems work across multiple app-level classes (users are authenticated, sessions manage authentication, lots of other classes will act differently based on the auth state), so they need to share modules that act as APIs while the individual functionalities are the classes.


Construct a new account object. Please use the following static methods:
Address of the account.
Password of the account.
Account key data ( encrypted )
Export the account encrypted keyData as a string.
Import the an account's private key and internally save the keyData.
Private key of the account.
Password used to encrypt the private key and create the keyData.
Test to see if this address string is equal, to the one saved in this account object.
Addresse to compare against
Return true if the password is set in this account object.
Save the key data to a file.
Filename to write the account key data too.
Sign a transaction using the accounts password and keyData.
Web3 object that is being used to connect and send the transaction.
Transaction that needs to be signed.
Return the signed transaction.
Create a new account object, using the provided password.
Password to use for this new account.
Entropy for the account generation.
A new Account object.
Loads a new account object from an account file.
Password to access this account information in the account file.
Filename of the account data.
A new account object with the nessecary information , or null if the password is incorect or file is not found.
Loads a new account object that has been already loaded on the network node.
Network node that has the account.
Address of the account on the node.
Password to access this account information in the account file.
A new account object with the nessecary information.
Load an account json key data that contains the information needed to sign and hash messages.
Filename of the account file.
Data that contains the account information. The user needs to pass the password to use this data.
Generated using TypeDoc
Account class to hold a privatly owned account


Dashboard
Councilmen
(Dashboard)
(Raw logs)
Councilstaff
(Dashboard)
(Raw logs)
Other authorities
(Dashboard)
(Raw logs)


--- layout: post status: publish published: true title: Ivy Envy State of the Union author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>excerpt: "First off, we'd like to thank all of you that read Ivy Envy. We really enjoy sharing our love of the Cubs with you, and it's been fun to share conversations with you that we normally have with each other. Thanks for reading and please, jump in with your opinions whenever you'd like. Also, please share Ivy Envy with any Cubs fans you know. \n\nWe have a lot of ideas that we would like to do with Ivy Envy, but at this point, we are pretty limited with what Wordpress will allow. We are looking at doing something to free ourselves up a little bit to do what we would like. The first thing we are going to try is " wordpress_id: 112 wordpress_url: http://ivyenvy.wordpress.com/?p=112 date: '2008-06-30 14:16:57 +0000' date_gmt: '2008-06-30 14:16:57 +0000' categories: - Ivy Envy tags: - Inning-by-Inning Summary - Ivy Envy - Podcast - Wordpress comments: [] ---
First off, we'd like to thank all of you that read Ivy Envy. We really enjoy sharing our love of the Cubs with you, and it's been fun to share conversations with you that we normally have with each other. Thanks for reading and please, jump in with your opinions whenever you'd like. Also, please share Ivy Envy with any Cubs fans you know.
We have a lot of ideas that we would like to do with Ivy Envy, but at this point, we are pretty limited with what Wordpress will allow. We are looking at doing something to free ourselves up a little bit to do what we would like. The first thing we are going to try is an inning-by-inning game summary. We will be doing this for Tuesday night's game against the Giants. Because of our limitations on Wordpress, this will be put on the site after the game. Live updates would be ideal, but it's just not possible right now.
We are also looking at starting an Ivy Envy podcast. We will keep you updated with major additions or changes to Ivy Envy.


This city of canals
is an attractive place to visit with its maze of canals, brightly painted fishing boats and sandy beaches, but its entry is not for the faint-hearted in anything more than calm weather. It lies approximately 30nm south of Oporto and the mouth of the Rio Vouga.
Position 40°38.1'N, 8°46'W.
There is not usually any marina here available to visiting yachts, but the anchorages are sheltered. The river is generally too shallow to allow most boats to reach the city, which is 8 miles from the entrance.
Entry should be made around high water only and never if there is a swell or any amount of wind. In such conditions the entrance is dangerous.
Also be aware of the unlit HT cables (clearance 8m) across the Canal da Mira which enters the main canal, Canal de Embocadura, on the sta'bd side shortly after passing the southern breakwater.
The best anchorage is at Sao Jacinto. The entrance is dredged to 3m and marked by buoys.
There is a small marina at the town of Torreira, 10.5 miles north of the river entrance. This marina however is used by very small fishing boats with depths of 1m, so is not suitable for yachts.
Last updated October 2015.


Class doubletree.Trie
doubletree.Trie
This is the class for the specialized trie that is the data for doubletree.DoubleTree.
The Trie will get pieces of data that contain fields. Some (possibly all) of those fields will be used for distinguishing among items.
For example, we might have an "author" field, but not use it when distinguishing among items for the Trie.
Defined in: Trie.js.
| Constructor Attributes | Constructor Name and Description |
|---|---|
|
doubletree.Trie(caseSensitive, fldNames, fldDelim, distinguishingFldsArray, undistinguishedRoot)
|
| Method Attributes | Method Name and Description |
|---|---|
|
addNgram(itemArray, id, count)
Add an ngram to the Trie
|
|
|
deserialize(serialized)
make this Trie have the values of a previously serialized Trie see #serialize
|
|
|
get the distinguishing fields for the data
|
|
|
get the field delimiter for the data
|
|
|
get the field names in the data
|
|
|
get the unique root of this Trie.
|
|
|
serialize the Trie as a JSON string
|
|
|
toTree(filterFuns, descendentLevel)
convert the Trie to a tree structure for display.
|
Class Detail
doubletree.Trie(caseSensitive, fldNames, fldDelim, distinguishingFldsArray, undistinguishedRoot)
- Parameters:
- caseSensitive
- are the elements in the first distinguishing field compared in a case sensitive fashion
- fldNames
- the names of the fields
- fldDelim
- the field delimiter
- distinguishingFldsArray
- undistinguishedRoot
Method Detail
addNgram(itemArray, id, count)
Add an ngram to the Trie
- Parameters:
- itemArray
- an array of delimited items (the ngrams)
- id
- an id for this ngram
- count
- a count for this ngram. Default is 1
caseSensitive()
- Returns:
- whether this Trie uses case sensitive comparison
deserialize(serialized)
make this Trie have the values of a previously serialized Trie see #serialize
- Parameters:
- serialized
distinguishingFieldsArray()
get the distinguishing fields for the data
- Returns:
- the distinguishing fields for the data
fieldDelim()
get the field delimiter for the data
- Returns:
- the field delimiter for the data
fieldNames()
get the field names in the data
- Returns:
- the field names in the data
getUniqRoot()
get the unique root of this Trie. Used only by DoubleTree
- Returns:
- a new Trie with a unique item as the root
serialize()
serialize the Trie as a JSON string
- Returns:
- the JSON string representation of the Trie
toTree(filterFuns, descendentLevel)
convert the Trie to a tree structure for display. Used only by DoubleTree
- Parameters:
- filterFuns
- the filtering functions to apply to the tree see DoubleTree.filters
- descendentLevel
- the current level we are filtering
- Returns:
- the tree


Moree Secondary College student Alyssa Duncan wins Rotary District 9650 public speaking cluster final
by Sophie HarrisMoree Secondary College student Alyssa Duncan has progressed to the next level of the Rotary District 9650 public speaking competition, after winning the cluster final at Warialda earlier this month.
The year 11 student, representing Moree Rotary Club, was one of four speakers at the cluster final, including fellow Moree Secondary College student Grace Carter, who represented Moree-on-Gwydir Rotary Club.
Both Moree students progressed to the cluster final after winning their respective club competitions.
However it was Alyssa's well-delivered speech about passions which won over the judges.
"I was ecstatic," she said of the win.
"It was so cool.
"It was a shock - I didn't expect it at all. Initially I didn't feel confident; the speech fell quite short and was fairly rushed, but I think it was my delivery of it that got me through."
Meanwhile Grace came second in the competition, with her speech about technology and its impact on society. However only one person could progress through to the semi-finals.
"I'm happy with how I spoke - I did my best," Grace said.
"I'm not too worried [about not going further]. I know Alyssa has worked hard to improve since the first one."
Alyssa will now go on to compete at the District semi-finals, to be held in Walcha in February 2020.
"I'm really nervous for that," she said.


{% load static from staticfiles %} {% load static from staticfiles %} {% load static from staticfiles %}
Datatron is an opensource project , created to help you track the websites you are interested in and notify you when something important changed.
We are planning on using the blockchain network to expand our datatron capabilities.
Datatron calculations are powered by Python.
Feel free to contact us on twitter and contribute on github if you have any suggestions or ideas.


Translator: Ziming
Author: labuladong
Today I will talk about the Union-Find algorithm, which is often referred to as the Disjoint-Set algorithm, mainly to solve the problem of “dynamic connectivity” in graph theory. Nouns look a little confusing, but they ’re really easy to understand. We will explain it later. Moreover, the application of this algorithm is also very interesting.
Speaking of this Union-Find, it should be my “Enlightenment Algorithm”, this algorithm was introduced at the beginning of Algorithms 4th edition, I have to say that this algorithm shocked me! Later I discovered that leetcode also has related topics and is very interesting. Moreover, the solution given in Algorithms 4th edition can be further optimized. With only a small modification, the time complexity can be reduced to O (1).
First, I will explain what is meant by dynamic connectivity.
Briefly, dynamic connectivity to a fact can be abstracted to connect a graph with lines. For example the following figure depicts a total of 10 nodes, they are disconnected, respectively numerals 0 to 9:
Now our Union-Find algorithm mainly needs to implement these two APIs:
class UF {
/* Connecting the p and q */
public void union(int p, int q);
/* Determine whether p and q are connected */
public boolean connected(int p, int q);
/* Returns the number of connected components in the graph */
public int count();
}
Here’s “connectivity” is an equivalence relation, that has the following three properties:
reflexivity: p
andp
node is connected.
Symmetry: If p
andq
node communication, and then q`` p
also in communication.
Transitivity: If the nodes p
andq
are connected, and q
andr
are connected, then p
andr
are also connected.
For example, in the previous picture, any two different points from 0 to 9 are not connected, and calling connected
will return false with 10 connected components.
Now,if you call union (0, 1)
, the 0 and 1 are connected and the connected components are reduced to 9.
then,when we call union (1, 2)
, the 0,1,2 are connected. Calling connected (0, 2)
will also return true, and the connected components will become 8.
This “equivalent relationship” judgment is very useful, such as the compiler to judge different references to the same variable, or to count the number of friends in social networks, etc.
Now, you probably understand what dynamic connectivity is. The key to the Union-Find algorithm is the efficiency of the union
andconnected
functions. So what model should we use to represent the connected state of this graph? And what data structure is more appropriate to implement the code?
Note that I just separated the “model” from the specific “data structure” because we use forests (several trees) to represent the dynamic connectivity of the graph, and use arrays to implement this forest.
How to use forest to represent connectivity? We set each node of the tree to have a pointer to its parent node, and if it is the root node, this pointer points to itself. For example, the graph of 10 nodes just now didn’t communicate with each other at the beginning, like this:
class UF {
// recording connected components
private int count;
// the parent of node x is parent [x]
private int[] parent;
/* construct a function where n is the total number of nodes in the graph */
public UF(int n) {
// disconnected at first
this.count = n;
// parent node pointer points to itself
parent = new int[n];
for (int i = 0; i < n; i++)
parent[i] = i;
}
/* Other functions */
}
If two nodes are already connected, then connect the root node of one node to the root node of the other node:
public void union(int p, int q) {
int rootP = find(p);
int rootQ = find(q);
if (rootP == rootQ)
return;
// Merge two trees into one
parent[rootP] = rootQ;
// parent[rootQ] = rootP
count--; // Combine two components into one
}
/* Returns the root node of a node x */
private int find(int x) {
// parent[x] == x
while (parent[x] != x)
x = parent[x];
return x;
}
/* Returns the number of the current connected components */
public int count() {
return count;
}
In this way, if the nodes p
andq
are connected, they must have the same root node:
public boolean connected(int p, int q) {
int rootP = find(p);
int rootQ = find(q);
return rootP == rootQ;
}
At this point, the Union-Find algorithm is basically complete. Isn’t it amazing? We only use arrays to simulate a forest, and cleverly solve this more complicated problem!
So what is the complexity of this algorithm? We found that the complexity of the main API connected
andunion
is caused by the find
function, so they are the same complexity asfind
.
The main function of find
is to traverse from a certain node to the root of the tree, and its time complexity is the height of the tree. We may customarily think that the height of the tree is logN
, but this is not necessarily the case. The height of logN
exists only in a balanced binary tree. For general trees, extreme imbalance may occur, causing the“ tree ”to almost degenerate into a“ linked list ”. In the worst case, the tree height may becomeN
.
So the above solution, the time complexity of find
,union
, connected
is O (N). This complexity is very unsatisfactory. What you want graph theory to solve is the problem of huge data scales such as social networks. The calls to union
andconnected
are very frequent, and each call requires linear time completely unbearable.
The point is, how do you find ways to avoid tree imbalances?
We know that in the process of union
imbalances may arise either case:
public void union(int p, int q) {
int rootP = find(p);
int rootQ = find(q);
if (rootP == rootQ)
return;
// Merge two trees into one
parent[rootP] = rootQ;
// parent[rootQ] = rootP also works
count--;
At the beginning, we simply and rudely connected the tree where p
was located under the root node of the tree whereq
was located. Then, a “top-heavy” imbalance situation may occur here, such as the following situation:
Over time, the tree may grow imbalanced. We actually hope that the smaller trees are connected to the larger ones, so that we can avoid top-heavy and more balanced. The solution is to use an additional size
array to record the number of nodes in each tree. We might as well call it “weight”:
class UF {
private int count;
private int[] parent;
// Added an array record tree "weight"
private int[] size;
public UF(int n) {
this.count = n;
parent = new int[n];
// Since there is only one node per tree initially, the
// weight should be initialized to 1
size = new int[n];
for (int i = 0; i < n; i++) {
parent[i] = i;
size[i] = 1;
}
}
/* Other function */
}
For instance, size [3] = 5
means that the tree rooted at node3
has a total of 5
nodes. This way we can modify the union
method:
public void union(int p, int q) {
int rootP = find(p);
int rootQ = find(q);
if (rootP == rootQ)
return;
// The small tree is more balanced under the big tree
if (size[rootP] > size[rootQ]) {
parent[rootQ] = rootP;
size[rootP] += size[rootQ];
} else {
parent[rootP] = rootQ;
size[rootQ] += size[rootP];
}
count--;
}
Like this, by comparing the weight of the tree, you can ensure that the growth of the tree is relatively balanced, and the height of the tree is roughly on the order of logN
, which greatly improves the execution efficiency.
At this time, the time complexity of find
,union
, and connected
has been reduced to O (logN), even if the data size is hundreds of millions, the time required is very small.
This step of optimization is particularly simple and clever. Can we further compress the height of each tree so that the tree height remains constant at all times?
Find
can result in O (1) time to find a root node, corresponding,connected
union
and complexity are reduced to O (1).
To do this, simply add a line in find
Code:
private int find(int x) {
while (parent[x] != x) {
// Path compression
parent[x] = parent[parent[x]];
x = parent[x];
}
return x;
}
This operation is a little tricky to see the GIF to understand its role (for clarity, this tree in extreme conditions).
Therefore, each time the find
function is called to traverse to the root of the tree, the tree height is shortened by hand, and eventually all the heights will not exceed 3 (the height may reach 3 whenunion
).
PS: The reader may ask, after the find process of this GIF graph is completed, the tree height is exactly equal to 3, but if there is a higher tree, the height after compression will still be greater than 3, what should we do? This GIF scenario was edited by me to make it easy for everyone to understand path compression, but in practice, path compression is performed every time it is found, so the tree could not have grown to such a high level, and this worry is unnecessary.
Let’s take a look at the whole code:
class UF {
// Number of connected components
private int count;
// Store a tree
private int[] parent;
// Record the "weight" of the tree
private int[] size;
public UF(int n) {
this.count = n;
parent = new int[n];
size = new int[n];
for (int i = 0; i < n; i++) {
parent[i] = i;
size[i] = 1;
}
}
public void union(int p, int q) {
int rootP = find(p);
int rootQ = find(q);
if (rootP == rootQ)
return;
// The small tree is more balanced under the big tree
if (size[rootP] > size[rootQ]) {
parent[rootQ] = rootP;
size[rootP] += size[rootQ];
} else {
parent[rootP] = rootQ;
size[rootQ] += size[rootP];
}
count--;
}
public boolean connected(int p, int q) {
int rootP = find(p);
int rootQ = find(q);
return rootP == rootQ;
}
private int find(int x) {
while (parent[x] != x) {
// Path compression
parent[x] = parent[parent[x]];
x = parent[x];
}
return x;
}
public int count() {
return count;
}
}
The complexity of the Union-Find algorithm can be analyzed as follows: the constructor initializes the data structure requires O (N) time and space complexity. However, the time complexity required for union
,connected
and count
is O (1).
The algorithm is committed to make it clear! Welcome to follow us on WeChat public account labuladong for more easy-to-understand articles：
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