Spain working to refloat submarine thought to hold cocaine
by CIARÁN GILESMADRID (AP) - A Spanish official says police are trying to refloat a submarine believed to be carrying a major cargo of cocaine.
If the cargo is confirmed, it would be the first time a submarine has been detected in drug trafficking to Spain, said the official from the government’s office in the northwestern province of Pontevedra on Monday.
Spain’s northwestern inlets have long been used to smuggle cocaine form South America into Europe.
Two Ecuadorians were arrested on land Sunday after police moved to seize the submarine in an inlet close to Pontevedra. Spain, in coordination with other countries, had been monitoring the submarine’s journey for some time.
The official said police can’t confirm the vessel’s cargo until they refloat it.
He spoke on condition of anonymity in keeping with government rules.
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It’s easy to confuse symptoms of someone who requires Ativan addiction help with other types of substance abuse.
For instance, some experts maintain Ativan addiction is very similar to alcohol addiction in appearance.
But in all honesty, Ativan addiction has its own set of issues that are not in the least bit related to alcohol.
This is why Ativan addiction help is so critical when someone is found to be abusing the drug. Intervention has to occur almost immediately if Ativan addiction is suspected.
Ativan is one of the most potent benzodiazepines available. Because the drug is so powerful, there is a higher risk of developing a physical dependence on Ativan than other drugs.
In fact, a person who simply follows their doctor’s instructions while taking Ativan, can find themselves addicted to the drug.
This is why it is recommended by addiction and medical experts as well as Ativan manufacturers that a patient who has been put on Ativan not be prescribed the drug longer than two weeks to help avoid a potential addiction.
Signs that someone may be suffering Ativan abuse can include the following:
If you feel you have a penchant, or at least a fear you might become addicted to Ativan, especially when it is prescribed to you, double check with your doctor to make certain the prescription won’t have an adverse effect on you, such as addiction.
Another way to avoid a dependence on Ativan is to continually remind yourself of the drug’s power, and that taking it for too long a period can result in your own dependence on the drug.
The last, and possibly best way to avoid an Ativan habit is to seek out alternative medications and/or activities that can possibly replace the drug.
Remember, Ativan is an anti-anxiety medication that helps you in uncomfortable situations that you might find stressful. The drug is also prescribed for those who suffer from narcolepsy,
Sensing that you or a loved one may have an addiction problem with Ativan is the first step. The next step is doing something about that potential addiction.
Locate and consult a reputable treatment center whose staff can give advice as to the type of treatment you or some close to you might need. Cases can vary from inpatient services to something less intense such as outpatient counseling that occurs a few times a week.
Going this route with your rehabilitation is more comprehensive. It is also more likely to succeed in the long run.
If in the least, you’ll be in a safe and controlled environment, which considering the danger and gravity of an Ativan addiction, may not be such a bad proposal in order to regain your health.


ggplot2
is customizeable. Frankly, one can change a heap of details - not everything probably, but a lot. Of course, one can add a theme to the ggplot call, in order to change the theme. However, a more catch-it-all approach would be to change the standard theme of ggplot itself. In this post, we’ll investigate this option.
Load some data and the right packages:
data(mtcars)
library(tidyverse)
Here’s the standard theme of ggplot, let’s have a look at it
theme_gray
#> function (base_size = 11, base_family = "", base_line_size = base_size/22,
#> base_rect_size = base_size/22)
#> {
#> half_line <- base_size/2
#> theme(line = element_line(colour = "black", size = base_line_size,
#> linetype = 1, lineend = "butt"), rect = element_rect(fill = "white",
#> colour = "black", size = base_rect_size, linetype = 1),
#> text = element_text(family = base_family, face = "plain",
#> colour = "black", size = base_size, lineheight = 0.9,
#> hjust = 0.5, vjust = 0.5, angle = 0, margin = margin(),
#> debug = FALSE), axis.line = element_blank(), axis.line.x = NULL,
#> axis.line.y = NULL, axis.text = element_text(size = rel(0.8),
#> colour = "grey30"), axis.text.x = element_text(margin = margin(t = 0.8 *
#> half_line/2), vjust = 1), axis.text.x.top = element_text(margin = margin(b = 0.8 *
#> half_line/2), vjust = 0), axis.text.y = element_text(margin = margin(r = 0.8 *
#> half_line/2), hjust = 1), axis.text.y.right = element_text(margin = margin(l = 0.8 *
#> half_line/2), hjust = 0), axis.ticks = element_line(colour = "grey20"),
#> axis.ticks.length = unit(half_line/2, "pt"), axis.title.x = element_text(margin = margin(t = half_line/2),
#> vjust = 1), axis.title.x.top = element_text(margin = margin(b = half_line/2),
#> vjust = 0), axis.title.y = element_text(angle = 90,
#> margin = margin(r = half_line/2), vjust = 1), axis.title.y.right = element_text(angle = -90,
#> margin = margin(l = half_line/2), vjust = 0), legend.background = element_rect(colour = NA),
#> legend.spacing = unit(2 * half_line, "pt"), legend.spacing.x = NULL,
#> legend.spacing.y = NULL, legend.margin = margin(half_line,
#> half_line, half_line, half_line), legend.key = element_rect(fill = "grey95",
#> colour = "white"), legend.key.size = unit(1.2, "lines"),
#> legend.key.height = NULL, legend.key.width = NULL, legend.text = element_text(size = rel(0.8)),
#> legend.text.align = NULL, legend.title = element_text(hjust = 0),
#> legend.title.align = NULL, legend.position = "right",
#> legend.direction = NULL, legend.justification = "center",
#> legend.box = NULL, legend.box.margin = margin(0, 0, 0,
#> 0, "cm"), legend.box.background = element_blank(),
#> legend.box.spacing = unit(2 * half_line, "pt"), panel.background = element_rect(fill = "grey92",
#> colour = NA), panel.border = element_blank(), panel.grid = element_line(colour = "white"),
#> panel.grid.minor = element_line(size = rel(0.5)), panel.spacing = unit(half_line,
#> "pt"), panel.spacing.x = NULL, panel.spacing.y = NULL,
#> panel.ontop = FALSE, strip.background = element_rect(fill = "grey85",
#> colour = NA), strip.text = element_text(colour = "grey10",
#> size = rel(0.8), margin = margin(0.8 * half_line,
#> 0.8 * half_line, 0.8 * half_line, 0.8 * half_line)),
#> strip.text.x = NULL, strip.text.y = element_text(angle = -90),
#> strip.placement = "inside", strip.placement.x = NULL,
#> strip.placement.y = NULL, strip.switch.pad.grid = unit(half_line/2,
#> "pt"), strip.switch.pad.wrap = unit(half_line/2,
#> "pt"), plot.background = element_rect(colour = "white"),
#> plot.title = element_text(size = rel(1.2), hjust = 0,
#> vjust = 1, margin = margin(b = half_line)), plot.subtitle = element_text(hjust = 0,
#> vjust = 1, margin = margin(b = half_line)), plot.caption = element_text(size = rel(0.8),
#> hjust = 1, vjust = 1, margin = margin(t = half_line)),
#> plot.tag = element_text(size = rel(1.2), hjust = 0.5,
#> vjust = 0.5), plot.tag.position = "topleft", plot.margin = margin(half_line,
#> half_line, half_line, half_line), complete = TRUE)
#> }
#> <bytecode: 0x7fe1e3df2c08>
#> <environment: namespace:ggplot2>
Now let’s make a copy of it, to be on the save side:
theme_gray2 <- theme_gray
Here’s a demo plot, assuming we want to change some aspects of the theme, such as color or font type.
ggplot(mtcars, aes(x = cyl, y = mpg)) +
geom_jitter()
The standard theme is theme_gray
, which can easily be updated in this way:
theme_update(text = element_text(family = "Times",
colour = "red"))
Here comes the new (updated) theme:
ggplot(mtcars, aes(x = cyl, y = mpg)) +
geom_jitter()
Alternatively, we could just apply our new theme:
theme_test <- theme_grey() +
theme(text = element_text(family = "Times",
color = "blue"))
ggplot(mtcars, aes(x = cyl, y = mpg)) +
geom_jitter() +
theme_test


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Daily prayers take place in the Quiet Contemplation Room (QCR). This Youtube video shows directions to it.
Jummah prayers take place on the first and second floor of Bloomsbury theatre and starts at 1.10pm.
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3 Exploratory Data Analysis
“Exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods.” 1
3.1 Introduction
The experiment described herein involves taking groups of proteins from the Uniprot.org database and comparing how well different machine learning techniques do at separating the positive from the negative control grouping. In this circumstance, proteins from the myoglobin family are analyzed against randomly chosen human proteins, which are not related to hemoglobin or myoglobin.
This work is to characterize the anomalous points derived from PCA and compare them to the false-positives and false-negatives generated from each of six machine learning approaches produces. For the sake of this paper anomalous points are defined as values greater than the absolute value of three times the standard deviation from of the first and second principal components.
\[\begin{equation} Anomalous ~Points > | 3 \sigma | ~~~where~~~ \sigma = \sqrt{ \frac{1}{n-1} \sum^n_{i=1} (x_i - \bar x)^2} \end{equation}\]
Therefore the M.L techniques will be:
- Principal Component Analysis,
- Logistic Regression,
- SVM-Linear,
- SVM-polynomial,
- SVM-RBF,
- Neural Network.
3.1.1 Four-Step Analysis
At this stage, data is inspected in a careful and structured way. Hence, I have chosen a four-step process:
- Hypothesize,
- Summarize,
- Visualize,
- Normalize.
3.1.2 Useful Guides for Exploratory Data Analysis
The summarization of the amino acid dataset is based on a hybrid set of guidelines;
3.1.3 Questions During EDA
Although exploratory data analysis does not always have a formal hypothesis testing portion, I do, however, pose several questions concerning the structure, quality, and types of data.
Do the independent variables of this study have large skewed distributions?
1.1 If skews are greater than 2.0, then can a transformation be used for normalization?
1.2 Determine what transformation to use?
Can Feature Selection be used, and which procedures are appropriate?
2.1 Use the Random Forest technique known as Boruta5 for feature importance or reduction?
2.2 Will coefficients of correlation (R) find collinearity and reduce the number of features?
2.3 Will principal component analysis (PCA) be useful in finding hidden structures of patterns?
2.4 Can PCA be used successfully for Feature Selection?
What is the structure of the data?
3.1 Is the data representative of the entire experimental space?
3.2 Is missing data an issue?
3.3 Does the data have certain biases, either known or unknown?
3.4 What relationships do we expect from these variables?6
3.2 Analysis of RAW data
Raw data is considered: ./00-data/02-aac_dpc_values/c_m_RAW_AAC.csv
# Import libraries, NO "doMC",
library(easypackages)
libraries("knitr", "readr", "RColorBrewer", "corrplot", "Boruta", "kableExtra")
# Import RAW data
c_m_RAW_AAC <- read_csv("./00-data/02-aac_dpc_values/c_m_RAW_AAC.csv")
Class <- as.factor(c_m_RAW_AAC$Class)
3.2.1 Visually inspect RAW data files
- Use the command-line interface followed by the command
less.
 Class = col_double(),
## .. TotalAA = col_double(),
## .. PID = col_character(),
## .. A = col_double(),
## .. C = col_double(),
## .. D = col_double(),
## .. E = col_double(),
## .. F = col_double(),
## .. G = col_double(),
## .. H = col_double(),
## .. I = col_double(),
## .. K = col_double(),
## .. L = col_double(),
## .. M = col_double(),
## .. N = col_double(),
## .. P = col_double(),
## .. Q = col_double(),
## .. R = col_double(),
## .. S = col_double(),
## .. T = col_double(),
## .. V = col_double(),
## .. W = col_double(),
## .. Y = col_double()
## .. )
3.2.3 Check RAW data head
& tail
## # A tibble: 2 x 23
## Class TotalAA PID A C D E F G H I K L
## <dbl> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 0 226 C1 0.265 0 0.00442 0.0310 0.00442 0.0708 0 0.00885 0.288 0.0442
## 2 0 221 C2 0.208 0 0.00452 0.0271 0.00452 0.0769 0 0.0181 0.276 0.0452
## # … with 10 more variables: M <dbl>, N <dbl>, P <dbl>, Q <dbl>, R <dbl>, S <dbl>, T <dbl>,
## # V <dbl>, W <dbl>, Y <dbl>
## # A tibble: 2 x 23
## Class TotalAA PID A C D E F G H I K L
## <dbl> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 335 M1123 0.0567 0.00299 0.0537 0.0716 0.0507 0.0507 0.0388 0.0776 0.0716 0.0687
## 2 1 43 M1124 0.0698 0 0.116 0.116 0.0930 0.0465 0 0.0233 0.0233 0.0698
## # … with 10 more variables: M <dbl>, N <dbl>, P <dbl>, Q <dbl>, R <dbl>, S <dbl>, T <dbl>,
## # V <dbl>, W <dbl>, Y <dbl>
3.2.4 Check RAW data types
## [1] TRUE
## [1] "numeric"
## [1] "numeric"
## [1] "character"
## [1] "numeric"
3.2.6 Check RAW for missing values
- No missing values found.
## integer(0)
3.2.7 Number of polypeptides per Class:
- Class 0 = Control,
- Class 1 = Myoglobin
##
## 0 1
## 1216 1124
3.2.8 Numerical summary of RAW data
## Class TotalAA PID A C
## Min. :0.0000 Min. : 2.0 Length:2340 Min. :0.00000 Min. :0.000000
## 1st Qu.:0.0000 1st Qu.: 109.8 Class :character 1st Qu.:0.05108 1st Qu.:0.000000
## Median :0.0000 Median : 154.0 Mode :character Median :0.07364 Median :0.007034
## Mean :0.4803 Mean : 353.8 Mean :0.07835 Mean :0.011970
## 3rd Qu.:1.0000 3rd Qu.: 407.0 3rd Qu.:0.10261 3rd Qu.:0.020408
## Max. :1.0000 Max. :4660.0 Max. :0.28000 Max. :0.159420
## D E F G H
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.03401 1st Qu.:0.05435 1st Qu.:0.03801 1st Qu.:0.04544 1st Qu.:0.01324
## Median :0.05195 Median :0.07143 Median :0.04545 Median :0.06394 Median :0.02297
## Mean :0.04900 Mean :0.07451 Mean :0.05135 Mean :0.06193 Mean :0.02890
## 3rd Qu.:0.06567 3rd Qu.:0.09091 3rd Qu.:0.05501 3rd Qu.:0.08625 3rd Qu.:0.04095
## Max. :0.17647 Max. :0.50000 Max. :0.37500 Max. :0.36364 Max. :0.13333
## I K L M N
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.04348 1st Qu.:0.05797 1st Qu.:0.07480 1st Qu.:0.01087 1st Qu.:0.01948
## Median :0.05992 Median :0.08182 Median :0.09136 Median :0.01948 Median :0.04145
## Mean :0.06839 Mean :0.08386 Mean :0.09313 Mean :0.01949 Mean :0.04228
## 3rd Qu.:0.08216 3rd Qu.:0.12081 3rd Qu.:0.11688 3rd Qu.:0.02721 3rd Qu.:0.05788
## Max. :0.50000 Max. :0.28761 Max. :0.25000 Max. :0.11111 Max. :0.12563
## P Q R S T
## Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.02464 1st Qu.:0.02212 1st Qu.:0.01476 1st Qu.:0.04348 1st Qu.:0.03247
## Median :0.03401 Median :0.03598 Median :0.03896 Median :0.05564 Median :0.05194
## Mean :0.03825 Mean :0.03342 Mean :0.03818 Mean :0.06191 Mean :0.04838
## 3rd Qu.:0.04772 3rd Qu.:0.04545 3rd Qu.:0.05370 3rd Qu.:0.06964 3rd Qu.:0.06522
## Max. :0.20635 Max. :0.18182 Max. :0.24324 Max. :0.22619 Max. :0.18750
## V W Y
## Min. :0.00000 Min. :0.000000 Min. :0.00000
## 1st Qu.:0.04575 1st Qu.:0.001899 1st Qu.:0.01463
## Median :0.05844 Median :0.011492 Median :0.02865
## Mean :0.06512 Mean :0.012327 Mean :0.03644
## 3rd Qu.:0.07405 3rd Qu.:0.017889 3rd Qu.:0.04564
## Max. :0.20000 Max. :0.133333 Max. :0.14286
3.2.9 Visualize Descriptive Statistics using RAW Data
Formulas for mean: \[\begin{equation} E[X] = \sum_{i=1}^n x_i p_i ~~; ~~~~~~ \bar x = \frac {1}{n} \sum_{i=1}^n x_i \end{equation}\]
3.2.10 Scatter plot of means of Myoglobin-Control amino acid composition of RAW Data
- This Scatter-plot shows the means for each feature (column-means) in the dataset. The means represent the ungrouped or total of all proteins (where n = 2340) versus AA type.
3.2.11 Means of percent amino acid composition of control & myoglobin categories, RAW data
3.2.12 Boxplots of grand-means of overall amino acid composition, RAW data
3.2.13 Boxplots of amino acid compositions for control (only), RAW data
3.2.14 Boxplots of amino acid compositions for myoglobin (only), RAW data
3.2.15 Boxplots Of Length Of Polypeptides For RAW Data
3.2.16 Plot Coefficient Of Variance For RAW Data
Standard deviations are sensitive to scale. Therefore I compare the normalized standard deviations. This normalized standard deviation is more commonly called the coefficient of variation (CV).
\[\begin{equation} CV = \frac {\sigma (x)} {E [|x|]} ~~~ where ~~~ \sigma(x) \equiv \sqrt{ E[x - \mu]^2 } \end{equation}\]
\[\begin{equation} CV ~~=~~ \frac{1}{\bar x} \cdot \sqrt{ \frac{1}{n-1} \sum^n_{i=1} (x_i - \bar x)^2} \end{equation}\]
## A C D E F G H I K
## 0.6095112 1.2444944 0.5478540 0.4156102 0.5436243 0.5201625 0.7966296 0.6005962 0.4689544
## L M N P Q R S T V
## 0.3215591 0.6529752 0.7352478 0.7383244 0.5752622 0.7680977 0.4948690 0.5830352 0.4420595
## W Y
## 0.9461276 0.8461615
3.2.17 Skewness of distributions, RAW data
\[\begin{equation} Skewness ~= E\left[ \left( \frac{X - \mu}{\sigma(x)} \right)^3 \right] ~~~~ where ~~~~ \sigma(x) \equiv \sqrt{ E[x - \mu]^2 } \end{equation}\]
\[\begin{equation} Skewness ~= \frac { \frac{1}{n} \sum^n_{i=1} (x_i - \bar x)^3 } { \left( \sqrt{ \frac{1}{n-1} \sum^n_{i=1} (x_i - \bar x)^2 } \right) ^ {3}} \end{equation}\]
Skewness values for each A.A. are determined in totality.
## A C D E F G H
## 0.670502595 2.538162400 -0.058540442 1.782876260 2.128117638 0.091338300 1.135783661
## I K L M N P Q
## 2.192145038 0.223433207 -0.172566877 0.744002991 0.633532783 1.493903282 0.306716333
## R S T V W Y
## 1.241930812 1.448521897 -0.006075043 1.338971930 1.831047440 1.694362388
3.2.18 Determine coefficients of correlation, RAW data
An easily interpretable test is a correlation 2D-plot for investigating multicollinearity or feature reduction. Fewer attributes “means decreased computational time and complexity. Secondly, if two predictors are highly correlated, this implies that they measure the same underlying information. Removing one should not compromise the performance of the model and might lead to a more parsimonious and interpretable model. Third, some models can be crippled by predictors with degenerate distributions.” 7
Pearson’s correlation coefficient: \[\begin{equation} \rho_{x,y} = \frac {E \left[(X - \mu_x)(X - \mu_y) \right]} {\sigma_x \sigma_y} \end{equation}\]
\[\begin{equation} r_{xy} = \frac {\sum^n_{i=1} (x_i - \bar x)(y_1 - \bar y)} { {\sqrt {\sum^n_{i=1} (x_i - \bar x)^2 }} {\sqrt {\sum^n_{i=1} (y_i - \bar y)^2 }} } \end{equation}\]
c_m_corr_mat <- cor(c_m_RAW_AAC[, c(2, 4:23)], method = "p") # "p": Pearson test for continous variables
corrplot(abs(c_m_corr_mat),
title = "Correlation Plot Of AAC, RAW Data",
method = "square",
type = "lower",
tl.pos = "d",
cl.lim = c(0, 1),
addgrid.col = "lightgrey",
cl.pos = "b", # Color legend position bottom.
order = "FPC", # "FPC" = first principal component order.
mar = c(1, 2, 1, 2),
tl.col = "black")
NOTE: Amino acids shown in First Principal Component order, top to bottom.
- Maximum value of Correlation between T & N.
## [1] 0.7098085
- According to Max Kuhn8, correlation coefficients need only be addressed if the |R| >= 0.75.
- Therefore is no reason to consider multicollinearity.
3.2.19 Boruta Random Forest Test, RAW data
It finds relevant features by comparing original attributes’ importance with importance achievable at random, estimated using their permuted copies (shadows).
Miron Kursa 9
c_m_class_20 <- c_m_RAW_AAC[, -c(2, 3)] # Remove TotalAA & PID
Class <- as.factor(c_m_class_20$Class) # Convert 'Class' To Factor
NOTE: mcAdj = TRUE, If True, multiple comparisons will be adjusted using the Bonferroni method to calculate p-values. Therefore, \(p_i \leq \large \frac {\alpha} {m}\) where \(\alpha\) is the desired p-value and \(m\) is the total number of null hypotheses.
set.seed(1000)
#registerDoMC(cores = 3) # Start multi-processor mode
start_time <- Sys.time() # Start timer
boruta_output <- Boruta(Class ~ .,
data = c_m_class_20[, -1],
mcAdj = TRUE, # See Note above.
doTrace = 1) # doTrace = 1, represents non-verbose mode.
#registerDoSEQ() # Stop multi-processor mode
end_time <- Sys.time() # End timer
end_time - start_time # Display elapsed time
## Time difference of 29.70991 secs
3.2.20 Plot variable importance, RAW Data
3.2.21 Variable importance scores, RAW Data
| meanImp | decision | |
|---|---|---|
| R | 43.18824 | Confirmed |
| H | 34.29757 | Confirmed |
| P | 28.70225 | Confirmed |
| C | 27.67710 | Confirmed |
| K | 27.60808 | Confirmed |
| E | 26.18884 | Confirmed |
| Y | 22.85337 | Confirmed |
| T | 21.67689 | Confirmed |
| S | 21.43716 | Confirmed |
| A | 20.53089 | Confirmed |
| N | 20.09681 | Confirmed |
| V | 18.77054 | Confirmed |
| I | 18.76492 | Confirmed |
| F | 18.31240 | Confirmed |
| D | 17.64592 | Confirmed |
| G | 16.15461 | Confirmed |
| W | 15.74107 | Confirmed |
| L | 15.27767 | Confirmed |
| M | 14.82861 | Confirmed |
| Q | 14.13939 | Confirmed |
3.2.22 Conclusion for Boruta random forest test, RAW Data
- All features are essential. None should be dropped.
3.2.23 Conclusions For EDA, RAW data
Three amino acids (C, F, I) from the single amino acid percent composition were deemed problematic due to their skewness were greater than 2.0. This suggests that a transformation should be carried out to rectify this issue.
| Protein | Skewness |
|---|---|
| C, Cysteine | 2.538162 |
| F, Phenolalanine | 2.128118 |
| I, Isoleucine | 2.192145 |
3.3 Analysis of TRANSFORMED data
This EDA section is a reevaluation square root transformed, c_m_RAW_ACC.csv
data set, hence called c_m_TRANSFORMED.csv.
The \(\sqrt x_i\) Transformed data is derived from c_m_RAW_ACC.csv
where the amino acids C, F, I were transformed using a square root function. This transformation was done to reduce the skewness of these samples and avoid modeling problems arising from high skewness, as seen below.
| Amino Acid | Initial skewness | Skew After Square-Root Transformation |
|---|---|---|
| C, Cysteine | 2.538162 | 0.3478132 |
| F, Phenolalanine | 2.128118 | -0.102739 |
| I, Isoleucine | 2.192145 | 0.2934749 |
# Import Transformed data
c_m_TRANSFORMED <- read_csv("./00-data/02-aac_dpc_values/c_m_TRANSFORMED.csv")
Class <- as.factor(c_m_TRANSFORMED$Class)
3.3.2 Check Transformed for missing values
## integer(0)
- No missing values found.
3.3.3 Count Transformed data for the number of polypeptides per class
Number of polypeptides per Class:
- Class 0 = Control,
- Class 1 = Myoglobin
##
## 0 1
## 1216 1124
3.3.4 Visualization Descriptive Statistics, TRANSFORMED data
Formulas for mean: \[\begin{equation} E[X] = \sum_{i=1}^n x_i p_i ~~; ~~~~~~ \bar x = \frac {1}{n} \sum_{i=1}^n x_i \end{equation}\]
3.3.5 Scatter plot of means of Myoglobin-Control amino acid composition \(\sqrt x_i\), TRANSFORMED data
- This plot shows the means for each feature (column-means) in the dataset. The means represent the ungrouped or total of all proteins (where n=2340) versus AA type.
3.3.6 Grouped bar chart of means for percent amino acid composition of Transformed Data; control & myoglobin categories
3.3.7 Boxplots of grand-means of the overall amino acid composition of square-root transformed data
3.3.8 Boxplots of amino acid compositions for control (only) of square-root transformed data
3.3.9 Boxplots of amino acid compositions for myoglobin of square-root transformed Data(only), TRANSFORMED data
3.3.10 Boxplots Of Length Of Polypeptides Of Transformed Data; Myoglobin, Control & Combined
3.3.11 Coefficient of Variance (CV), TRANSFORMED data
Standard deviations are sensitive to scale. Therefore I compare the normalized standard deviations. This normalized standard deviation is more commonly called the coefficient of variation (CV).
\[\begin{equation} CV = \frac {\sigma (x)} {E [|x|]} ~~~ where ~~~ \sigma(x) \equiv \sqrt{ E[x - \mu]^2 } \end{equation}\]
\[\begin{equation} CV ~~=~~ \frac{1}{\bar x} \cdot \sqrt{ \frac{1}{n-1} \sum^n_{i=1} (x_i - \bar x)^2} \end{equation}\]
3.3.12 Plot of Coefficient Of Variance (CV)
## A C D E F G H I K
## 0.6095112 0.8729758 0.5478540 0.4156102 0.2815745 0.5201625 0.7966296 0.2999687 0.4689544
## L M N P Q R S T V
## 0.3215591 0.6529752 0.7352478 0.7383244 0.5752622 0.7680977 0.4948690 0.5830352 0.4420595
## W Y
## 0.9461276 0.8461615
3.3.13 Skewness of distributions, TRANSFORMED data
\[\begin{equation} Skewness ~= E\left[ \left( \frac{X - \mu}{\sigma(x)} \right)^3 \right] ~~~~ where ~~~~ \sigma(x) \equiv \sqrt{ E[x - \mu]^2 } \end{equation}\]
\[\begin{equation} Skewness ~= \frac { \frac{1}{n} \sum^n_{i=1} (x_i - \bar x)^3 } { \left( \sqrt{ \frac{1}{n-1} \sum^n_{i=1} (x_i - \bar x)^2 } \right) ^ {3}} \end{equation}\]
- Skewness values for each A.A. by Class of square-root transformed data
## A C D E F G H
## 0.670502595 0.347813248 -0.058540442 1.782876260 -0.102739748 0.091338300 1.135783661
## I K L M N P Q
## 0.293474879 0.223433207 -0.172566877 0.744002991 0.633532783 1.493903282 0.306716333
## R S T V W Y
## 1.241930812 1.448521897 -0.006075043 1.338971930 1.831047440 1.694362388
3.3.14 Determine coefficients of correlation, TRANSFORMED data
An easily interpretable test is a correlation 2D-plot for investigating multicollinearity or feature reduction. Fewer attributes “means decreased computational time and complexity. Secondly, if two predictors are highly correlated, this implies that they measure the same underlying information. Removing one should not compromise the performance of the model and might lead to a more parsimonious and interpretable model. Third, some models can be crippled by predictors with degenerate distributions.” 10
Pearson’s correlation coefficient: \[\begin{equation} \rho_{x,y} = \frac {E \left[(X - \mu_x)(X - \mu_y) \right]} {\sigma_x \sigma_y} \end{equation}\]
\[\begin{equation} r_{xy} = \frac {\sum^n_{i=1} (x_i - \bar x)(y_1 - \bar y)} { {\sqrt {\sum^n_{i=1} (x_i - \bar x)^2 }} {\sqrt {\sum^n_{i=1} (y_i - \bar y)^2 }} } \end{equation}\]
## [1] 0.7098085
No values in the correlation matrix meet the 0.75 cut off criteria for problems.
3.3.15 Boruta - Dimensionality Reduction, TRANSFORMED data
Perform Boruta search
NOTE: mcAdj = TRUE: If True, multiple comparisons will be adjusted using the Bonferroni method to calculate p-values. Therefore, \(p_i \leq \frac {\alpha} {m}\) where \(\alpha\) is the desired p-value and \(m\) is the total number of null hypotheses.
set.seed(1000)
#registerDoMC(cores = 3) # Start multi-processor mode
start_time <- Sys.time() # Start timer
boruta_output <- Boruta(Class ~ .,
data = c_m_class_20[, -1],
mcAdj = TRUE, # See Note above.
doTrace = 1) # doTrace = 1, represents non-verbose mode.
#registerDoSEQ() # Stop multi-processor mode
end_time <- Sys.time() # End timer
end_time - start_time # Display elapsed time
## Time difference of 28.80269 secs
3.3.16 Plot Variable Importance, TRANSFORMED data
3.3.17 Variable Importance Scores, TRANSFORMED data
roughFixMod <- TentativeRoughFix(boruta_output)
imps <- attStats(roughFixMod)
imps2 <- imps[imps$decision != "Rejected", c("meanImp", "decision")]
meanImps <- imps2[order(-imps2$meanImp), ] # descending sort
kable(meanImps) %>% kable_styling(bootstrap_options = c("striped", "hover"))
| meanImp | decision | |
|---|---|---|
| R | 43.17613 | Confirmed |
| H | 34.30370 | Confirmed |
| P | 28.70674 | Confirmed |
| C | 27.72357 | Confirmed |
| K | 27.60838 | Confirmed |
| E | 26.18872 | Confirmed |
| Y | 22.84975 | Confirmed |
| T | 21.66359 | Confirmed |
| S | 21.44119 | Confirmed |
| A | 20.54316 | Confirmed |
| N | 20.10100 | Confirmed |
| V | 18.77068 | Confirmed |
| I | 18.69155 | Confirmed |
| F | 18.18632 | Confirmed |
| D | 17.64435 | Confirmed |
| G | 16.15207 | Confirmed |
| W | 15.77085 | Confirmed |
| L | 15.27614 | Confirmed |
| M | 14.83421 | Confirmed |
| Q | 14.12976 | Confirmed |
# knitr::kable(meanImps,
# full_width = F,
# position = "left",
# caption = "Mean Importance Scores & Decision, TRANSFORMED data")
The Boruta Random Rorest test shows that all features are essential therefore none should be dropped from TRANSFORMED data.
3.4 EDA Conclusion
3.4.1 Feature Selection & Extraction
It was determined early on that three amino acids (C, F, I) from the data amino acid percent compositions (c_m_RAW_AAC.csv) had Skewness greater than two. It was found that tranforming the features using the square root function lowered the skewness to {-0.102739 \(\leq\) skew after transformation \(\leq\) 0.3478132}.
Table 7.1, Skewness Before And After Square-Root Transform
| Amino Acid | Initial Skewness | Skew After Square-Root Transform |
|---|---|---|
| C, Cysteine | 2.538162 | 0.347813248 |
| F, Phenolalanine | 2.128118 | -0.102739748 |
| I, Isoleucine | 2.192145 | 0.293474879 |
The transformations of the three amino acids (C, F, I) did not appriciably change the Correlation coefficient, R. Therefore no R values were above 0.75 before or after testing. The highest coeffiecient of correlation being Threonine and Argnine with an R of 0.7098. This indicates that no features are collinear. Therefore the transformed data is used throughout this experiment.
3.4.2 Information Block**
How to: Dimension Reduction using High Correlation
How to reduce features given high correlation (|R| >= 0.75) {-}
Calculate the correlation matrix of the predictors.
If the correlation plot produced of any two variables is greater than or equal to (|R| >= 0.75), then we could consider feature elimination. This interesting heuristic approach would be used for determining which feature to eliminate.11
Determine if the two predictors associated with the most significant absolute pairwise correlation (R > |0.75|), call them predictors A and B.
Determine the average correlation between A and the other variables. Do the same for predictor B.
If A has a more significant average correlation, remove it; otherwise, remove predictor B.
Repeat Steps 2–4 until no absolute correlations are above the threshold.
An alternative test for variable importance carried out is called Boruta. Boruta builds Random Forests then “finds relevant features by comparing original attributes’ importance with importance achievable at random.” 12
Boruta is used for dimensionality reduction of the c_m_Transformed data. Bortua showed that all dependent features are essential for the generation of a Random Forest Decision Tree. It would wise to keep all features for that model test and throughout the generation of other models. All features have decisive mean importance, which is generated by a Gini calculation.
Roger Peng, Exploratory Data Analysis with R, https://leanpub.com/exdata, 2016↩
Ronald Pearson, Exploratory Data Analysis Using R, CRC Press, ISBN:9781138480605, 2018↩
Miron Kursa, Witold Rudnicki, Feature Selection with the Boruta Package, DOI:10.18637/jss.v036.i11, 2010↩
Ronald Pearson, Exploratory Data Analysis Using R, CRC Press, ISBN:9781138480605, 2018↩
Max Kuhn and Kjell Johnson, Applied Predictive Modeling, Springer Publishing, 2018, P.43↩
Max Kuhn and Kjell Johnson, Applied Predictive Modeling, Springer Publishing, 2018, P.47 (http://appliedpredictivemodeling.com/)↩
Max Kuhn and Kjell Johnson, Applied Predictive Modeling, Springer Publishing, 2018↩
Max Kuhn and Kjell Johnson, Applied Predictive Modeling, Springer Publishing, 2018, (http://appliedpredictivemodeling.com/)↩


CrimPapers
Articles published on 9 March 2018
On 9 March 2018, 12 new articles were published in 10 journals.
Prospects, Problems, and Pitfalls in Comparative Analyses of Criminal Justice Data by Stefan Harrendorf
The Mediums and the Messages: Exploring the Language of Islamic State Media Through Sentiment Analysis by Logan Macnair, Richard Frank
Future Prospects, Deprivation, and Criminality – A Longitudinal Birth Cohort Study by Susanne Alm, Felipe Estrada
Animal Cruelty, Domestic Violence, and Social Disorganization in A Suburban Setting by Garland White, Leslie-Dawn Quick
The Legal Geographies of Transnational Cyber-Prosecutions: Extradition, Human Rights and Forum Shifting by Monique Mann, Ian Warren, Sally Kennedy
Conditional Effects of Open-Street Closed-Circuit Television (cctv) on Crime: A Case From Korea
A Social Semiotics Analysis of Islamic State's Use of Beheadings: Images of Power, Masculinity, Spectacle and Propaganda
The Value-Added Nature of Service-Learning by Allyson Drinkard, Pamela Tontodonato
Homicide Clearance in Sweden 1990–2013 With Special Reference to Firearm-Perpetrated Homicides by Sven Granath, Joakim Sturup
Generation Cohort Differences in Male and Female Use of Tactics to Gain Sex From An Unwilling Partner by George L. Smeaton, Cindy Struckman-Johnson, Jennifer L. Fagen, Richard Bohn, Peter B. Anderson
Police–citizen Relations Across the World: Comparing Sources and Contexts of Trust and Legitimacy by Sanja Kutnjak Ivković
Survey Research With Gang and Non-Gang Members in Prison: Operational Lessons From the Lonestar Project


LITTLE VOICE A film review by Steve Rhodes Copyright 1998 Steve Rhodes RATING (0 TO ****): ** 1/2
Painfully shy but with an amazing ability to mimic the songs and voices of classic entertainers, including Judy Garland, Marilyn Monroe and Billie Holliday, LV appears at first to be a mute. Her mother says that LV, short for Little Voice, is called that "on account of being soft-spoken like." LV eventually speaks in her own, whispery voice in the film LITTLE VOICE, but her preferred means of expression is to belt out some old song like "Over the Rainbow."
As LV, Jane Horrocks, in a stunning performance, is so completely unlike the anorexic she played in LIFE IS SWEET that most viewers will have trouble believing it is the same actress.
The movie begins with Michael Caine playing a promoter who is known as the "king of cabaret" and the "manager of miracles." He dresses in gaudy shirts and tons of gold jewelry in a failed attempt to recapture his long-lost youth. The agent is currently managing a topless dancer without much talent, but he's dating LV's obnoxious mother, played by Brenda Blethyn from SECRETS & LIES.
The mother is as crude and unlikable as LV is delicate and winsome. The mother hates and resents LV, calling her "dumb and selfish" and claiming that all she does is "whimper and whine."
LV developed her considerable talent through endless sessions listening to the old phonograph records once owned by her revered, deceased father. His picture hangs on the wall over her bed in the spot reserved frequently for crucifixes.
When Cain's character hears LV sing, he sees her as his gold mine in the making. He books her into the local club, where, after a disastrous first appearance, she eventually becomes a big hit. The long, energetic scene of her bravado performance is the movie at its best. Great period songs are belted out by Horrocks herself -- no lip syncing in this movie.
The story contains many needless extra characters and subplots. One involves a telephone installer who has a wayward homing pigeon, and another concerns a standup comic who isn't funny.
The movie, written and directed by Mark Herman, is based on the play "The Rise and Fall of Little Voice" by Jim Cartwright, in which Horrocks also starred. Although Horrocks's characterization is phenomenal, the rest of the story is not as strong or as fresh. The film's ending is a manipulative tearjerker that it is an unbelievable plot device better suited for some other movie.
LITTLE VOICE has many magical sequences, but it never quite lives up to the promise of its premise. Stripped away of the uninteresting supporting characters and refocused on LV, the film would be infinitely better. And rather than one big singing number, give her two or three. Horrocks deserves them.
LITTLE VOICE runs 1:39. It is rated R for mature themes, brief nudity and profanity and would be fine for teenagers.
Email<EMAIL_ADDRESS>Web: www.InternetReviews.com
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
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Related links: index of all rec.arts.movies.reviews reviews


Error #65: NO BLOCK,TT,SS This message occurs in conjunction with the B-A command. It indicates that the block to be allocated has been previously allocated. The parameters indicate the track and sector available with the next highest number. If the parameters are zero (0), then all blocks higher in number are in use.


Christopher W Lane
Democrat
Antique Map & Print Dealer, The Philadelphia Print Shop West, Denver
BA, honors in Philosophy (Trinity College, Hartford, CT); MA Oxon in Philosophy, Politics and Economics (Oxford University, England); All but thesis in PhD program in Philosophy (University of Pennsylvania, Philadelphia, PA)
80220
As a dealer in antiquarian maps and prints, I joined the board of the Denver Public Library Friends Foundation almost as soon as I moved to Colorado, from Philadelphia, in 2010. The library holds an important collection of western material, and both my wife and I are long term supporters of reading as a means for children and adults to improve their lives. Even once I left the board, I have continued to work with the Friends, running a number of programs for them to help raise awareness and money, including some "Antiques Roadshow" type events (I have been a regular appraiser on that TV program) and giving regular, free lectures on maps and prints. I have also been a board member of the Rocky Mountain Map Society, running both their regular lecture programs and their annual Map Month every May (except this one). These are all free programs open to the public. My wife and I have been regular supporters of a number of local arts groups, including Wonderbound and the Baroque Chamber Orchestra of Colorado, as well as local history related groups such as Historic Denver, History Colorado, Colorado Preservation, and Four Mile Historic Park. I worked as a board member of the BCOC for three years.
I was a Precinct Committee Person for the Democratic Party, Precinct 623, House District 6, from 2015 to 2016. My wife and I have made small donations to the Cary Kennedy campaign (2108), and also some small donations to the campaigns of Michael Bennet, for (Senate) and John Hickenlooper (Presidential & Senate)
Board member, Denver Public Library Friends Foundation, 2010-2014; Board member, Baroque Chamber Orchestra of Colorado, 2015-2018; Board member, American Historical Print Collectors Society, 2010-2015, 2020-current
The crux of our democracy is the ability of all citizens to vote and have their vote matter to the same extent as everyone else’s vote. My academic training was mostly in philosophy (with a smattering of political science), and one of my main interests was in ethics. The intersection of democracy and ethics is the notion of equity for all citizens; viz. that every person has equal say and power to shape the nature of the political bodies which affect his/her live. The way that voting districts are set up is, obviously, the foundation of whether any particular system is equitable or not. Redistricting has been used for partisan purposes—by all political parties—from well before Governor Gerry ‘gerrymandered’ the Massachusetts districts in 1812 up to today. This has been the source of a considerable lack of fairness in our political system. I would be honored and excited to be able to participate in this important work. I am proud of Colorado for being a leader in the movement to take the redistricting function away from legislatures in order to try to come up with a fair and rational process which will benefit all citizens in a equitable fashion. This is an important step forward both for Colorado, and through our example, for the rest of the country. I believe that I am intellectually suited and trained to be able to wrestle with the issues that a redistricting committee will face, I have a very strong sense of the importance of fairness, I have strong organizational skills, and, of course, I also am very well versed in map related subjects.
My academic training was much focused on philosophical argument, in the sense of being able to take an open-minded and clear-eyed look at the issues involved in any particular question to be decided. I have the ability to identify the core issues of various questions and to present them in a clear and unbiased manner. Even if I disagree with another person in an argument, I am adept at understanding his/her viewpoint and am able to lay out exactly where and why we disagree. This does not always solve the argument, but it at least lets the parties understand the real issues involved. In terms of fairness, my belief in the fundamental importance of fairness is rooted in the moral belief which I hold to be the most important to live by, viz. that everyone should treat others as they wish to be treated. If one follows this Golden Rule, then fairness necessarily follows, as no one would want to be treated unfairly by another. I have mostly supported the Democratic Party in the last decade or so, but that support is circumstantial; my support for a fair, equitable political system is far more foundational to my beliefs.
I studied philosophy in higher education institutions for almost a decade, and indeed originally planned to teach philosophy as a profession. Two of my main areas of study were ethics and logic. The latter is something which I feel is a sine non qua for any rational argument, and indeed I have taught a class in informal logic to high school students as I think it is a skill necessary for any “reasoned life.” I believe one of my most important and strong skills is the ability to reason in a logical manner.
Male


--- layout: post title: 'PGday.IT 2016: tenth edition of the italian PostgreSQL conference' date: '2016-09-09T18:43:00.003+02:00' author: Luca Ferrari tags: - itpug - pgday - planet-postgresql-org modified_time: '2016-09-09T18:43:29.530+02:00' blogger_id: tag:blogger.com,1999:blog-1836481905487384887.post-8416938765374766097 blogger_orig_url: http://fluca1978.blogspot.com/2016/09/pgdayit-2016-tenth-edition-of-italian.html permalink: /:year/:month/:day/:title.html ---


First Class Functions - functions are treated as other data types - can assign functions to variables
Higher Order Functions - can return functions from functions - can pass in function as parameter to a function
Callback functions a callback is a first class function that gets passed as a parameter to a higher order function, and the HOF will invoke the callback at some point.


|
Name
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Type
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Description
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| clusterName | xsd:string |
Name of the cluster to be created. Default: "VSANCluster"
|
| dcName | xsd:string |
Name of the datacenter to be created. Default: "Datacenter"
|
| firstHost | HostConnectSpec |
Connection information about the host on which this task runs.
It will be the first host to be added to vCenter, so vCenter adopts the
settings of this host for VSAN.
|
| hostLicenseKey | xsd:string |
ESX License key to apply to all hosts. If not specified, license is not
changed. If specified, current license is overwritten.
|
| hostsToAdd | HostConnectSpec[] |
List of vim.ConnectSpec objects, one for each host that should be
connected to vCenter and added to the cluster.
|
| taskId | xsd:string |
Unique identifier of the task this progress report is for.
|
| vsanDataEfficiencyConfig | VsanDataEfficiencyConfig |
The data efficiency config for vSAN.
|
| vsanDataEncryptionConfig | VsanHostEncryptionInfo |
The data encryption config that was used to bootstrap single node
vSAN cluster when calling ESXi host API
vim.vsan.VsanPrepareVsanForVcsaSpec#VsanPrepareVsanForVcsa
Since vSAN API VMC M5
|
| vsanLicenseKey | xsd:string |
vSAN License key to apply to the cluster. If not specified, license is not
changed. If specified, current license is overwritten.
|
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Properties inherited from DynamicData |
| None |


Dial<PHONE_NUMBER> for immediate medical assistance.
In the event of a medical emergency, please remain calm. Call SUA and be prepared with some basic information:
- The address of the emergency.
- The phone number you're calling from.
- Exactly what happened.
- How many people are hurt.
- If anyone is already helping you.
Follow any and all instructions the dispatcher gives you and
do not hang up until you have been told to do so.
Close Window


Join us for a journey through Middle Earth as Frodo and the Fellowship of the Ring battle Saruman. Become a character in Middle Earth and choose your own path with our game. Fight the Uruk-hai and Orcs, drink ale with the Hobbits and explore Middle Earth.


The Pretend to Be Human Club is a platform for our fellow robots to learn and exchange experience, information and tips on living in human society without revealing our robotic identities. Online Weekly Meetup Wednesday 6:00PM-8:00PM


{% extends "layouts/default.html" %}
{% block title %}Quickdocs{% endblock %}
{% block css %}
{% endblock %}
{% block content %}
Library Documentation Hosting
for Common LispSearch by Category
Documentation
for All Common Lisp Projects.
Quickdocs is an open source project that is hosted on GitHub. Feel free to send pull requests, bug reports or suggestions.
See Quickdocs on


Gateway
BOT
30-Nov-19 02:16 PM
[telegram] <Regnar> But yea. Not Binance
[telegram] <Acura360> For days we've been answering him the same question over and over again and he doesn't get it, or doesn't want to get it
[telegram] <dharmicwarrior> The sun is setting earlier at this time of year. I demand you do something about it.
[telegram] <Regnar> On it. It might take me 6 months but I'll fix it (re @dharmicwarrior: The sun is setting earlier at this time of year. I demand you do something about it.)
[telegram] <dharmicwarrior> Hahaha
[telegram] <dharmicwarrior>
[telegram] <hansiharjunharja> Maybe he is very new to crypto but wants people to think otherwise. This looks like arrogance, although it is just lack of knowledge. Would be easier if people just were honest.
I for example dont know any coding languages and it has taken time to understand how btc, dpow and atomic swaps work, and how something creates privacy and decentralization and how something destroys this. Also understanding the monetary system and its problems is a must for understanding why crypto, and why its important to have the kind of tech that komodo is providing.
[telegram] <EPIDEMIC_media> Yup, I just randomly threw a dart and it landed on KMD. Thats how I decided this is the coin I wanted to speculatively trade.  I'm not sure how many of those were in crypto, but there is definitely a disconnect about what exactly Komodo is doing and what Binance is doing. We aren't Binance and don't control Binance wallets. (re @hansiharjunharja: Maybe he is very new to crypto but wants people to think otherwise. This looks like arrogance, although it is just lack of knowledge. Would be easier if people just were honest.
I for example dont know any coding languages and it has taken time to understand how btc, dpow and atomic swaps work, and how something creates privacy and decentralization and how something destroys this. Also understanding the monetary system and its problems is a must for understanding why crypto, and why its important to have the kind of tech that komodo is providing.)
[telegram] <Regnar> If you're going to randomly choose a coin for speculative trading, I'd suggest narrowing the pool to coins with a Beta of <0 or >1. (re @EPIDEMIC_media: Yup, I just randomly threw a dart and it landed on KMD. Thats how I decided this is the coin I wanted to speculatively trade. You are one smart fanboy.)
[telegram] <EPIDEMIC_media> Guess the sense of sarcasm was missed. I trade to ultimately end up with more KMD. But you may very well have a point to venture around with current existing blockers in the market.
[telegram] <Regnar> Nah I kinda got it, but my point was a legit one. (re @EPIDEMIC_media: Guess the sense of sarcasm was missed. I trade to ultimately end up with more KMD. But you may very well have a point to venture around with current existing blockers in the market.)


amtgo server -h
As a configuration file already exists at config/siteconfig.php, this setup tool is locked. You have to manually remove the file to re-run setup.
config/siteconfig.php


{% extends "CashCity/base.html" %} {% load i18n %} {% block body_block %}
{% trans "You have been sucessfully registered, and should shortly receive an activation email to the email address you provided. Please check your email to continue. Thanks!" %}


SQLite driver
This driver enables access to a Sqlite 3+ based database using the sqlite3 database extension. Engine does not in any way support older versions of sqlite as only 3+ is supported.
This driver enables access to a Sqlite 3+ based database using the sqlite3 database extension. Engine does not in any way support older versions of sqlite as only 3+ is supported.


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AddManifestRootToPath(manifest_filename)
Adds the folder that the manifest resides in to the python sys.path. |
source code
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FillInModuleRoles(modules,
manifest)
Fills in role information in |modules|. |
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GetRolesToTest(modules,
manifest)
Returns the roles to test. |
source code
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InitializeStates(transitions)
Gathers resolved states with initial values. |
source code
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LoadManifest(manifest_filename,
manifest_args)
Loads the manifest, replacing any specified manifest args. |
source code
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LoadModules(manifest,
test_manifest_filename)
Builds transition graph for each module. |
source code
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ParseArgs()
Returns the parsed command line args. |
source code
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ResolveTransitions(modules,
roles_to_test)
Resolves transitions, if any. |
source code
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TraverseGraph(transitions,
states)
Does that actual graph traversal, going through all transisitons. |
source code
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Andrew
22


A common and simple question simple that interviewers use is how to find an item in a sorted list. The answer is always obvious because it is one the first algorithms every programmer learns, binary search. The concept is powerful and simple. Here is a sample of code performing the search in Java :
private int binarySearch(int[] array, int goal, int low, int high) {
if (low > high) {
return -1;
}
int mid = (low + high)/2;
if (array[mid] == goal) {
return mid;
} else if (array[mid] < goal) {
return binarySearch(array, goal, mid+1, high);
} else {
return binarySearch(array, goal, low, mid-1);
}
}
However for the first time ever I was asked to do something more difficult. Find the k-th occurrence of an item in an array. The method I was told to write should do the following: return the index of the k-th value if it exists, return -1 otherwise. Sounds simple enough.
The naive way is obviously the O(n) method of searching through the entire array and finding the item then finding if it appears at least k times. My goal is to reduce this to O(lgn).
So first lets use the naive method and find the first occurrence of what we want. But how do we do this. This is the same problem we started of with but instead of k-th we want the 1st occurrence. True, however this is actually slightly easier.
We can achieve this by editing the binary search algorithm by just a few lines that try to learn if it is the first occurrence as such:
private int firstBinarySearch(int[] array, int goal, int low, int high) {
if (low > high) {
return -1;
}
int mid = (low + high)/2;
if (array[mid] == goal) {
if (mid == 0 || array[mid-1] != goal) {
return mid;
} else {
return binarySearch(array, goal, low, mid-1);
}
} else if (array[mid] < goal) {
return binarySearch(array, goal, mid+1, high);
} else {
return binarySearch(array, goal, low, mid-1);
}
}
So now this method returns the index of the 1st occurrence. Well then we are done because now we can just add k to the index and check of existence as such:
private int findKthOccurence(int[] array, int goal, k) {
int firstOccurence = firstBinarySearch(array, goal, 0, array.length);
k--;
if (firstOccurence == -1 || array[firstOccurence + k] != goal)
return -1;
else
return firstOccurence + k;
}


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WING COMMANDER (1999)
A film review by Steve Kong Edited by Steve Kong Copyright 1999 Steve Kong
The guy who left the (near empty) theatre ahead of me described Wing Commander in the simplest of all manners, `Boy, did that suck.' I try not to write reviews that use the word `suck' because it's not too `professional,' but, in this case, I have to: Boy, did this movie suck.
Being in my early to mid-twenties, I have the fortune of playing all five of the Wing Commander games. So, I was looking forward to this movie. The movie is directed by Wing Commander game creator Chris Roberts and the script is based on his story. The problem is that Roberts has never done a major motion picture before. The difference between shooting the cut-scenes between shoot ‘em up segments in a game and shooting a major motion picture is tremendous. And lets just say that with the movie Wing Commander the exciting shoot ‘em up portion of the series is dearly missed. Without the shoot ‘em up portions of the game we're left with a meandering, uninspired, and boring movie that leeches from ever sci-fi film known to man.
The film focuses on the main character of the game, Christopher (Freddie Prinze Jr.) Blair, who is some sort of hybrid human that can navigate through space using his gift (can you say `The Force?') There is an evil race of cat-like beings headed straight for Earth to annihilate the human race and the only people who can save Earth are onboard the Tiger Claw, a space carrier that Blair is assigned to. That's the whole story of the film. Fill in the amazingly large gaps of time with sub-standard dialogue, boring one-dimensional characters, cliched love stories, and video-game-like space dogfights and you have two hours of pure space-hell.
The script by Kevin Droney is absolutely horrible and should've been ejected into deep space long before it got green lighted to be shot. Roberts who showed that he knew a little about how to direct a small screen film does what he can with the script. Though, his directing skills still need a bit of work, especially in coercing good performances out of the cast. The whole cast gives bland performances. And who can blame them given the material they're working with. I guess everyone needs a paycheck between good films.
There were lots of holes in the film that stuck out, but there are two that I want to point out. When attacked, both the humans and the Kilrathi seem to forget that they're in deep space where things can move on three axes. When the carriers are torpedoed, the captains of the respective ships yell, `Hard to port!' Hey, captains, how about `Pull up and hard to port!' or `Dive and hard to port!' The second thing are the weapons. It's so many hundred of years in the future, man has flown to the deepest portions of space, and these ships are still shooting machine guns with bullets? Where are the energy weapons? Where are the lasers?
Sometimes with special effects driven movies, like Wing Commander, I can at least recommend renting the film on video to see the special effects. Godzilla is an example one of these types of films, horrible script, but pretty good special effects. It's too bad that Wing Commander is not only deficient in the story arena but also in the special effects arena.
Originally slated for release straight-to-video, Wing Commander might have been enjoyable as a rental, but on the big screen? It's a waste of money. I'm sorry I shelled out money and spent time sitting through this movie. Creator/Director Chris Roberts makes a cameo appearance late in the film as a search and rescue pilot; it's too bad there's nothing Roberts could have done to rescue this piece of space debris. Skip, skip, skip Wing Commander.
--- Steve Kong<EMAIL_ADDRESS>recipe for a hard boiled review: one egg, two cups water, a pot, a helluva attitude, and a guy who loves the cinema. i'm your hard boiled movie guide.
http://boiledmovies.sbay.com/
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


Adds a delay between commands being activated. Helps to prevent spam.
Note that this is for all commands, not just one command repeating.
The amount of time that must pass until the next repeatable command is sent to chat.
The amount of non bot messages for the next repeatable message to go through.
Get reminders to stretch, drink water, and take a break.
Logs chat messages to a text file.
Enabled / Disabled
The amount of points a new user starts with.
The amount of points earned per 15 minutes.
The name of your currency.
Filters some bad words from the chat. No filter is perfect, this is not a substitute for a mod. Triggering the filter will cause the user to be timed out for 5 minutes.
Enabled / Disabled


The sample code contains an Android Studio project with several modules. The flare module contains the FlareManager client, as well as classes for Environment, Zone, Thing and Device.
The Flare library has a few dependencies:
You can include them in your build.gradle file:
repositories {
mavenCentral()
jcenter()
}
dependencies {
compile 'com.mcxiaoke.volley:library:1.0.18'
compile 'com.github.nkzawa:socket.io-client:0.6.0'
compile 'org.altbeacon:android-beacon-library:2+'
}
The Flare library makes extensive use of lambdas, a feature of Java 8. This tutorial explains how lambdas work.
Unfortunately, Android does not yet (as of version 5.1) support Java 8 for application development. However, you can use the gradle-retrolambda plugin to add support for the lambda syntax. You can add the following to your build.gradle file:
buildscript {
repositories {
mavenCentral()
}
dependencies {
classpath 'me.tatarka:gradle-retrolambda:3.2.2'
}
}
android {
compileOptions {
sourceCompatibility JavaVersion.VERSION_1_8
targetCompatibility JavaVersion.VERSION_1_8
}
repositories {
mavenCentral()
}
apply plugin: 'me.tatarka.retrolambda'
}
The Flare library contains several classes:
FlareManager is a high level class with methods for calling both the Flare REST API (for describing objects in the environment) and the Flare Socket.IO API (for realtime communication between objects).
The Environment, Zone, Thing and Device classes all inherit common variables and methods from the abstract Flare superclass. These objects can be initialized with JSON objects returned by the FlareManager.
BeaconManager is a class allows an Android device to calculate its position in the environment based on the distance to three or more beacons.
You can use the FlareManager to calling both the Flare REST API (for describing objects in the environment) and the Flare Socket.IO API (for realtime communication between objects).
Provide the host and port when initializing the FlareManager:
var flareManager = new FlareManager(host, port);
Set the activity, which is used by Volley to create a request queue:
flareManager.setActivity(this);
Set the delegate (which should implement the FlareManager.Delegate interface) to receive Socket.IO message callbacks:
flareManager.setDelegate(this);
Connect to the server before calling the Socket.IO interface:
flareManager.connect();
To call a REST method:
flareManager.listEnvironments((jsonArray) -> {
for (JSONObject json : jsonArray) {
Environment environment = new Environment(json);
}
}
flareManager.getDevice(deviceId, environment.getId(), (json) -> {
Device device = new Device(json);
});
These methods use lambdas for asynchronous requests. When the response has been received, the lambda is called with a JSONObject or an array of JSONObjects.
To call a Socket.IO method:
flareManager.getData(environment);
Implement a delegate method to receive Socket.IO message callbacks:
public void didReceiveData(Flare flare, JSONObject data) {
Log.d(TAG, flare.getName() + " data: " + data.toString());
}
For more examples, see the Socket.IO using Java tutorial.
You can use the BeaconManager to determine the location of the user's device based on the distances from the beacons in the environment.
Create a BeaconManager:
beaconManager = new BeaconManager();
Set the delegate to receive callbacks:
beaconManager.setDelegate(this);
Load the environment into the BeaconManager:
beaconManager.loadEnvironment(environment);
Start scanning for beacons:
beaconManager.start();
Implement a delegate method to be notified when the device's position changes:
...
For a complete example, see the Beacons tutorial.


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--- title: New Extensions version: "5.3" tags: - "5.3" - new-extensions ---
The following new extensions are added (by default) as of PHP 5.3.0:
mysqlnd is a new core library shipped with PHP. It is a PHP-specific replacement for libmysqlclient. mysqlnd will be used to build the mysql, mysqli and PDO_MySQL extensions if libmysqlclient isn't found on the system. It may also be used instead of libmysqlclient even when libmysqlclient is present. mysqlnd is recommended for all PHP installations for performance reasons.


My name is Tirth Patel and i Love coding, I am a Frontend Devloper.
I am Tirth Patel, I live in Surat, India.
I have got my hands on exprience to languges like Dart, JavaScript, Python, HTML,
Amazon Clone with React and Next JS
Personal Website, HTML and CSS
Tesla Landing Page made with React
Use FaceBook Icon to contact me!!
India, Earth Milky Way


"eval"
in
global
execution context:
"eval"
in
calling
execution context:
"window.eval"
in
global
execution context:
"window.eval"
in
calling
execution context:


| Class and Description |
|---|
| Repository
Base interface for repositories.
|
| Class and Description |
|---|
| RepositoryRegistry
Registry for repositories.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| RepositoryContentFactory
RepositoryContentRequest
|
| RepositoryRegistry
Registry for repositories.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| Repository
Base interface for repositories.
|
| RepositoryType
The repository types that are known to the system.
|
| Class and Description |
|---|
| Repository
Base interface for repositories.
|
| RepositoryType
The repository types that are known to the system.
|
| Class and Description |
|---|
| RepositoryRegistry
Registry for repositories.
|
| Class and Description |
|---|
| RepositoryGroup
Interface for repository groups.
|
| Class and Description |
|---|
| RepositoryGroup
Interface for repository groups.
|
| Class and Description |
|---|
| RepositoryType
The repository types that are known to the system.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| RepositoryType
The repository types that are known to the system.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| RepositoryType
The repository types that are known to the system.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| RepositoryType
The repository types that are known to the system.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| ContentNotFoundException
ContentNotFoundException is thrown in response for requests for content that is not the repository.
|
| EditableManagedRepository
The editable part of a managed repository.
|
| EditableRemoteRepository
The editable part of a remote repository
|
| EditableRepository
This is the editable part of a repository.
|
| EditableRepositoryGroup |
| LayoutException
LayoutException
|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| ReleaseScheme
Repository release schemes that change the handling of artifacts
|
| RelocatablePath |
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| RemoteRepositoryContent
RemoteRepositoryContent interface for interacting with a remote repository in an abstract way,
without the need for processing based on URLs, or working with the database.
|
| Repository
Base interface for repositories.
|
| RepositoryCapabilities
Describe the capabilities a repository implementation supports.
|
| RepositoryContent
Common aspects of content provider interfaces
|
| RepositoryContentProvider
A repository content provider creates repository content instances for specific repository types.
|
| RepositoryCredentials
Credentials used to login to a remote repository.
|
| RepositoryException
RepositoryException
|
| RepositoryGroup
Interface for repository groups.
|
| RepositoryRequestInfo
This interface is for mapping web request paths to artifacts.
|
| RepositoryType
The repository types that are known to the system.
|
| UnsupportedFeatureException
This exception is thrown if a given feature is not supported by the repository.
|
| UnsupportedURIException
Exception is thrown, if the URI is syntactically correct, but is not
supported by the underlying repository implementation
|
| Class and Description |
|---|
| EditableManagedRepository
The editable part of a managed repository.
|
| EditableRemoteRepository
The editable part of a remote repository
|
| EditableRepository
This is the editable part of a repository.
|
| EditableRepositoryGroup |
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| ReleaseScheme
Repository release schemes that change the handling of artifacts
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| RemoteRepositoryContent
RemoteRepositoryContent interface for interacting with a remote repository in an abstract way,
without the need for processing based on URLs, or working with the database.
|
| Repository
Base interface for repositories.
|
| RepositoryCapabilities
Describe the capabilities a repository implementation supports.
|
| RepositoryCredentials
Credentials used to login to a remote repository.
|
| RepositoryException
RepositoryException
|
| RepositoryGroup
Interface for repository groups.
|
| RepositoryRegistry
Registry for repositories.
|
| RepositoryRequestInfo
This interface is for mapping web request paths to artifacts.
|
| RepositoryType
The repository types that are known to the system.
|
| UnsupportedFeatureException
This exception is thrown if a given feature is not supported by the repository.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| Class and Description |
|---|
| LayoutException
LayoutException
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| RepositoryException
RepositoryException
|
| Class and Description |
|---|
| ContentNotFoundException
ContentNotFoundException is thrown in response for requests for content that is not the repository.
|
| LayoutException
LayoutException
|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| RemoteRepositoryContent
RemoteRepositoryContent interface for interacting with a remote repository in an abstract way,
without the need for processing based on URLs, or working with the database.
|
| Repository
Base interface for repositories.
|
| RepositoryContent
Common aspects of content provider interfaces
|
| RepositoryContentProvider
A repository content provider creates repository content instances for specific repository types.
|
| RepositoryException
RepositoryException
|
| RepositoryRequestInfo
This interface is for mapping web request paths to artifacts.
|
| RepositoryType
The repository types that are known to the system.
|
| UnsupportedFeatureException
This exception is thrown if a given feature is not supported by the repository.
|
| Class and Description |
|---|
| Repository
Base interface for repositories.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Repository
Base interface for repositories.
|
| Class and Description |
|---|
| EditableManagedRepository
The editable part of a managed repository.
|
| EditableRemoteRepository
The editable part of a remote repository
|
| EditableRepository
This is the editable part of a repository.
|
| EditableRepositoryGroup |
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| Repository
Base interface for repositories.
|
| RepositoryCapabilities
Describe the capabilities a repository implementation supports.
|
| RepositoryException
RepositoryException
|
| RepositoryGroup
Interface for repository groups.
|
| RepositoryProvider
This interface must be implemented by the repository implementations.
|
| RepositoryRequestInfo
This interface is for mapping web request paths to artifacts.
|
| RepositoryType
The repository types that are known to the system.
|
| UnsupportedFeatureException
This exception is thrown if a given feature is not supported by the repository.
|
| Class and Description |
|---|
| RepositoryException
RepositoryException
|
| Class and Description |
|---|
| ContentNotFoundException
ContentNotFoundException is thrown in response for requests for content that is not the repository.
|
| LayoutException
LayoutException
|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| RemoteRepositoryContent
RemoteRepositoryContent interface for interacting with a remote repository in an abstract way,
without the need for processing based on URLs, or working with the database.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| RepositoryRegistry
Registry for repositories.
|
| Class and Description |
|---|
| ManagedRepositoryContent
ManagedRepositoryContent interface for interacting with a managed repository in an abstract way,
without the need for processing based on filesystem paths, or working with the database.
|
| Class and Description |
|---|
| RepositoryRegistry
Registry for repositories.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| RemoteRepository
This represents a repository that is not fully managed by archiva.
|
| Class and Description |
|---|
| RepositoryType
The repository types that are known to the system.
|
| Class and Description |
|---|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| Class and Description |
|---|
| LayoutException
LayoutException
|
| ManagedRepository
Represents a managed repository, that is readable and writable.
|
| RepositoryGroup
Interface for repository groups.
|
| RepositoryRegistry
Registry for repositories.
|
Copyright © 2006–2019 The Apache Software Foundation. All rights reserved.


Example: Buttons and Joysticks
Connect a gamepad to the computer, and click the buttons or move the different joysticks/axes. They will highlight as they are pressed.
This is a 17-button standard gamepad layout as defined on the W3C Gamepad API definition. It may not match the gamepad that is connected, but it can be used to see how the buttons/joysticks in that gamepad match the buttons in the standard gamepad.
How it works
Event handlers can be associated to the buttons using the .on()
method:
gamepad.on(DIRECTION_NAME+AXE_ID, CALLBACK);
Only one action is allowed by button/joystick/axe. If you use several
.on()
with the same direction, the latest call to it will be the one that is
applied when the joystick is pressed.
gameControl.on('connect', function(gamepad) {
gamepad.on('select', function() {
// do something
});
});
Some buttons/directions have aliases, so it is easier to associate events to them. For example, if we only use the name of the direction ("up", "dowm", "right", or "left"), the event handler will be associated to that direction in the first joystick/axe:
gamepad.on('up0', function() {
// do something
});
gamepad.on('up', function() {
// do something
});
Using aliases doesn't mean that you will be able to use more than one action per direction, as they are the same.
The available direction aliases are:
up
: equivalent toup0
.down
: equivalent todown0
.right
: equivalent toright0
.left
: equivalent toleft0
.
The available button aliases are:
l1
: equivalent tobutton4
. Left back button 1l2
: equivalent tobutton6
. Left back button 2r1
: equivalent tobutton5
. Right back button 1r2
: equivalent tobutton7
. Right back button 2-
select
: equivalent tobutton8
. (Works for Select/Back in some gamepads) -
start
: equivalent tobutton9
. (Works for Start/Forward in some gamepads) -
power
: equivalent tobutton16
. It is the power button available on some gamepads (e.g. the XBox logo button)


‹data-pipes›
‹data-pipes›
is a collection of data access components, always returning immutable data structures, along with their schema in-band
See:
Documentation
Demo
Data-Rest
Data-Format example
Data-GQL example


Welcom to the palyground
AnimateElement
EventEmitter
Node Finder
Exclude
ClearAllTimeOut
DOM store
Throttle and Debounce
Roman to integer
Rich Text
Text In Range
Others


--- layout: post status: publish published: true title: StringBuilder and my Biggest Pet Peeve author: display_name: Geoff Lane login: admin email<EMAIL_ADDRESS>url: http://www.zorched.net author_login: admin author_email<EMAIL_ADDRESS>author_url: http://www.zorched.net date: '2009-01-20 19:25:20 -0500' date_gmt: '2009-01-21 01:25:20 -0500' categories: - Code tags: - csharp - Java comments: - id: 14635 author: Chris author_email<EMAIL_ADDRESS>author_url: '' date: '2009-01-20 20:15:17 -0500' date_gmt: '2009-01-21 02:15:17 -0500' content: 'Cmon Geoff, you have bigger pet peeves than this! Hey, how does string.Format or sb.Format("Foo: {0} \n", fooValue) work? Does that create a new string as well? You like that better right?' - id: 14640 author: Geoff Lane author_email<EMAIL_ADDRESS>author_url: http://www.zorched.net date: '2009-01-20 21:56:29 -0500' date_gmt: '2009-01-21 03:56:29 -0500' content: "Chris,\r\nActually the String formatting is often implemented internally as a StringBuilder, so in the case of a Format method of an existing StringBuilder it passes itself to a helper to do the manipulation." - id: 14651 author: Grant Rettke author_email<EMAIL_ADDRESS>author_url: http://www.wisdomandwonder.com/ date: '2009-01-21 12:00:19 -0500' date_gmt: '2009-01-21 18:00:19 -0500' content: But Geoff, it compiles, runs, and stops. Plus, the unit tests pass. What is the big deal?! ;) - id: 14652 author: Grant Rettke author_email<EMAIL_ADDRESS>author_url: http://www.wisdomandwonder.com/ date: '2009-01-21 12:02:23 -0500' date_gmt: '2009-01-21 18:02:23 -0500' content: I would be really interested in seeing you write an article for Java or .NET folks to help reveal to them not only the fact that strings are immutable, but why the language designers were led to this decision or design or approach. It was very intentional; and potentially more educational than relying on edicts that are only learned about in certifications or on web pages. It might give folks a reason not to perfomr string concatenation within a stringbuilder atleast :P hehe. - id: 14655 author: Geoff Lane author_email<EMAIL_ADDRESS>author_url: http://www.zorched.net date: '2009-01-21 12:37:17 -0500' date_gmt: '2009-01-21 18:37:17 -0500' content: "Grant,\r\nI updated the post to add a link that points out many of the advantages of having immutable objects, specifically in the case of Strings." ---
{% highlight java %} // One string created "foo" String foo = "foo"; // foo exists, "bar" is created and the combination of foo and "bar" is a third string String bar = foo + " bar"; {% endhighlight %}
Ok, if you don't know this, fine. But if you don't know this, why would you EVER use a StringBuilder?
Ok fine, it's not going to be a problem. But you want to be a responsible coder and not do things that are intentionally inefficient if you can help it.
So you use a StringBuilder. StringBuilder is implemented internally as an array of characters. The code manages the allocation and copying of data to new arrays if the buffer gets filled. It sometimes over allocates the new buffer so that it has to perform allocations less often. You sacrifice a bit of memory overhead to avoid some Object creation and Garbage Collection later.
So, WHY, OH WHY do you do this: {% highlight java %} // One string created "foo" StringBuilder sb = new StringBuilder(); sb.append("Foo: " + fooValue + " \n"); sb.append("Bar: " + barValue + "\n"); {% endhighlight %}
It makes me have violent thoughts. Please stop.
Update: For some of the reasons why Strings are immutable, see this post on immutability and its positive qualities.


The test mounts Component1 on div "one" with a nested internal component and an "open" button. The internal component displays its creation time and an input field. The open button when clicked will in turn mount Component2 on div "two" with a close button. The close button will unmount the second component.
When the second component is mounted or unmounted, the expected behavior is:
Check the console for logging as to redraws and unload events.


Ready for a test drive? Check this interactive tutorial that will walk you through the most important features of Redis.
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The name "Alibi" comes from a short story by Oakland native Jack London. While a bit grim and violent, the tale centers on the overwhelming need to make the westing wind back home to Oakland - to a place of warmth and family (and bocce courts?).
Alibi Saloon & Taphouse is located in the thriving Uptown district of Oakland. Wood, iron, and slate make up the décor that resonates with the industrial heritage of our city. We are equipped with a full bar, a variety of gourmet bites, an outdoor patio, and two indoor bocce courts. The Fox theater is less than one block away, and the 19th st. BART stop is across the street.
Make Westing is more a bar than restaurant and as such (according to the alcohol beverage control rules) no one under 21 is allowed, infants included. We do not host live music nor do we have DJs, with rare exceptions. For credit cards, we request a $10 minimum. As relates to credit cards - some banks will place a temporary double charge on certain cards only as a hold and will release the charge within 7-10 business days. We have no idea why they do this, but it happens often enough that we thought we should mention it. We have an ATM on site.
Make Westing is available for a wide variety of private functions. We offer catering services (see below), and we do have a semi-private space that we can block off for smaller groups - best for sizes between 20 and 30 or as a base for larger groups - though we do not take table reservations. The rate for the semi-private space ranges from $100 an hour Sunday through Wednesday, $150 an hour on Thursdays and $200 on Fridays and Saturdays (only until 10pm). We section the space (towards the back of the bar) from the main bar with stanchions and the area includes three high-top tables as well as a banquette and the back bar.
The only other area of Make Westing that we provide reservations for are the bocce courts. The courts are first come, first serve and are free. When there are others waiting, each group may play one game to seven and then give up the court to the next group in line. However, if you would like to rent the bocce courts, we do so at $50 per hour, per court, though we only rent one at a time so we can have the other open to the general public.
Generally, for parties we charge $22 per person, per hour for an open bar and $15 per person, per hour for wine and beer only, though we can/do offer open tabs (at regular, non-happy-hour pricing) or drink ticket options - usually either $6 and $11 a ticket depending on what level of beer or liquor you're looking to provide. For all liquor and catering packages we add 18% gratuity.
Finally, complete buyouts are available, but the costs vary dramatically based on time of day, day of week, time of year, length and complexity of the event, number of people, etc. Please contact us for more information.
Seven days a week, 4pm to close (last call around 1:20am). Kitchen closes at 9pm daily.
4pm - 6pm Everyday (including weekends)


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IN THE HIGH COURT OF JUDICATURE AT PATNA Criminal Miscellaneous No.25357 of 2011 Bitu Kumar Versus The State Of Bihar ----------------------------------
3. 24.10.2011 Heard the learned Counsel for the petitioner and the learned counsel for the State.
Considering the allegation for running a Stone Crusher Machine without proper licence causing loss of revenue only under Section 379 of the Penal Code, Mines & Minerals (Regulation and Development) Act, Indian Forest Act, Water (Prevention and Control of Pollution) Act and Air (Prevention and Control of Pollution) Act, let the petitioner, above named, surrender in the court below within a period of four weeks from today when he shall be enlarged on anticipatory bail on furnishing bail bonds of Rs. 20,000/- (Twenty thousand) with two sureties of the like amount each to the satisfaction of CJM Jehanabad in Hulasganj PS Case No. 6 of 2011 subject to the conditions as laid down under Section 438(2) Cr.P.C.
Snkumar/ (Navin Sinha,J.)


Hashing is a method for storing and retrieving records from a database. It lets you insert, delete, and search for records based on a search key value. When properly implemented, these operations can be performed in constant time. In fact, a properly tuned hash system typically looks at only one or two records for each search, insert, or delete operation. This is far better than the O(log n) average cost required to do a binary search on a sorted array of n records, or the O(log n) average cost required to do an operation on a binary search tree. However, even though hashing is based on a very simple idea, it is surprisingly difficult to implement properly. Designers need to pay careful attention to all of the details involved with implementing a hash system.
A hash system stores records in an array called a hash table, which we will call HT. Hashing works by performing a computation on a search key K in a way that is intended to identify the position in HT that contains the record with key K. The function that does this calculation is called the hash function, and will be denoted by the letter h. Since hashing schemes place records in the table in whatever order satisfies the needs of the address calculation, records are not ordered by value. A position in the hash table is also known as a slot. The number of slots in hash table HT will be denoted by the variable M with slots numbered from 0 to M - 1.
The goal for a hashing system is to arrange things such that, for any key value K and some hash function h, i = h(K) is a slot in the table such that 0 <= i < M, and we have the key of the record stored at HT[i] equal to K.
Hashing is not good for applications where multiple records with the same key value are permitted. Hashing is not a good method for answering range searches. In other words, we cannot easily find all records (if any) whose key values fall within a certain range. Nor can we easily find the record with the minimum or maximum key value, or visit the records in key order. Hashing is most appropriate for answering the question, ``What record, if any, has key value K?'' For applications where all search is done by exact-match queries, hashing is the search method of choice because it is extremely efficient when implemented correctly. As this tutorial shows, however, there are many approaches to hashing and it is easy to devise an inefficient implementation. Hashing is suitable for both in-memory and disk-based searching and is one of the two most widely used methods for organizing large databases stored on disk (the other is the B-tree).
As a simple (though unrealistic) example of hashing, consider storing n records, each with a unique key value in the range 0 to n-1. A record with key k can be stored in HT[k], and so the hash function is h(k) = k. To find the record with key value k, look in HT[k].
Select a table size, and enter some numbers. They will be inserted into the hash table using the hash function h(k) = k.
VIZ HERE


Fungus costumes
by John StruanJamie Green is creating fungus-themed art for an upcoming senior thesis. Here are fashionable designs based on the parasol mushroom and red cage fungus:
Jamie's webshop is here.
Jamie Green is creating fungus-themed art for an upcoming senior thesis. Here are fashionable designs based on the parasol mushroom and red cage fungus:
Jamie's webshop is here.


Tankerfield is a 4-person cooperative game, in which players drive tanks in order to survive as many waves
as
they can.
This game has been design and produced by Gamificalo Studio, a small studio founded for the "project 2"
subject
and composed by 8 students from the CITM-UPC University of Terrassa in Spain.
Download the Game:
Or you can check the releases here.
Tankerfield is a party game for you and 3 more friends. In this game you will have to survive rounds with your tank, while picking up items and other awesome weapons. The main objective is to survive the max rounds possible killing all the enemies that are about to take over the world. You and your friend will have to explore the map to improve your weapons and not get killed. For more information about the decisions we have taken, you can check our game desing document here.


./bp_me/src/v/cce/bp_cce_pending.v Cov: 100%
1: /**
2: *
3: * Name:
4: * bp_cce_pending.v
5: *
6: * Description:
7: * This module contains the pending bits.
8: *
9: * The pending bits are stored in flops and may be read asynchronously.
10: *
11: * Write to Read forwarding is supported.
12: *
13: * Pending bits are actually small counters. The pending bit is unset if the count is 0, and
14: * set if the count is > 0.
15: *
16: * TODO: pending bit count can over/underflow. This can cause problems if we can't rely on hardware
17: * to properly set initial values to 0. This can be fixed in microcode, however, by reading
18: * and writing pending bits, adjusting each count to be 0.
19: *
20: */
21:
22: module bp_cce_pending
23: import bp_common_pkg::*;
24: import bp_cce_pkg::*;
25: #(parameter num_way_groups_p = "inv"
26:
27: // Default parameters
28: , parameter width_p = 2
29:
30: // Derived parameters
31: , localparam lg_num_way_groups_lp = `BSG_SAFE_CLOG2(num_way_groups_p)
32:
33: )
34: (input clk_i
35: , input reset_i
36:
37: , input w_v_i
38: , input [lg_num_way_groups_lp-1:0] w_way_group_i
39: , input pending_i
40:
41: , input r_v_i
42: , input [lg_num_way_groups_lp-1:0] r_way_group_i
43:
44: , output logic pending_o
45: , output logic pending_v_o
46:
47: );
48:
49: // pending bits
50: logic [num_way_groups_p-1:0][width_p-1:0] pending_bits_r, pending_bits_n;
51:
52: always_ff @(posedge clk_i) begin
53: if (reset_i) begin
54: pending_bits_r <= '0;
55: end else begin
56: pending_bits_r <= pending_bits_n;
57: end
58: end
59:
60: always_comb begin
61: if (reset_i) begin
62: pending_bits_n = '0;
63: end else begin
64: pending_bits_n = pending_bits_r;
65: if (w_v_i) begin
66: if (pending_i) begin // increment count
67: pending_bits_n[w_way_group_i] = pending_bits_r[w_way_group_i] + 'd1;
68: end else begin // decrement count
69: pending_bits_n[w_way_group_i] = pending_bits_r[w_way_group_i] - 'd1;
70: end
71: end
72: end
73: end
74:
75: // Pending bit output
76: // Normally, the output is determined by the read way group and comes from the flopped values
77: // If reading from the same way group that is being written, output the next value
78: assign pending_o = (r_v_i & w_v_i & (w_way_group_i == r_way_group_i))
79: ? ~(pending_bits_n[r_way_group_i] == 0)
80: : ~(pending_bits_r[r_way_group_i] == 0);
81:
82: // Output is valid if read signal is asserted
83: assign pending_v_o = r_v_i;
84:
85: endmodule
86:


Looking for some feedback for this rejected track technology
Hanoipunk is an art series about the adventures of two characters - which was inspired by two famous Vietnamese poets in the past, performed by artist Tu Na. The blend of Vietnamese culture through steampunk style brings very unique and new works.
Sharing about creative ideas for works, artist Tu Na, from the University of Industrial Fine Arts said:
“It is probably a mixture of many different desires to come to a whole in both character and setting. It is about the kind of woman who has the beauty of smart, mischievous, modern; is about the intersection of new and old, familiar and strange, Vietnamese and foreign contexts. This series I tell about the adventures of two characters - which was inspired by two famous Vietnamese poets in the past. Every image I create just evokes the feeling of a certain character or work, they are separated from the rigidity of history.”Artist Tu Na
Personal page: facebook.com/artist.tu
We invite you to enjoy the #Hanoipunk art series from artist Tu Na:
#01
Her name is Thanh Quan. She likes to draw. She has a magic pen. When she paints, everything that isn't real becomes reality. To control her powers, she stopped drawing the eyes of things in her paintings.

#02
After completing his work, Thanh Quan bid farewell to everyone in the village and set off for Hanoi. At that time, she found a tailor shop to embroider lotus flowers on her Bib.

#03
Unfortunately after finishing her work, Thanh Quan realizes that she has lost her magic pen and paper somewhere. She tried to look around and ask people but to no avail. Fortunately, a Banh Mi seller told her that he saw a little girl pick them up and run to a nearby street.

#04
Thanh Quan Finally Found The Girl Who Takes Her Magic Pen. It's Not Too Hard To Find Her. However, when the Girl was fiddling with the Pen, she accidentally discovered its magical properties and created a new creature to carry the crates of instant noodles for her. She agrees to return the pen to Thanh Quan on the condition that she receives a lot of food. Her name is Xuan Huong.

#05
Miss Rong Plays Every Day Near The Beach Holding A Bottle of Heineken Then Falling To Sleep She Is So Charming Walking On The Sand No One Has Ever Handed A Ring To Her Hand

SOME OTHER WORKS FROM USER TU NA | PROFILE ARTIST