Last updated: 2017-11-15
Code version: 78f7cb7
Please note that this is hasty work, most of the assignments are not thoroughly answered.
Use the morning to examine the datasets for the case studies. For each case: 1. get the appropriate descriptive statistics; 2. form an analysis plan; 3. try to develop a sense (“gut feeling”) of what the results of the analysis will be; and 4. if you have time, perform a full analysis on at least one case.
Remember the “Steps of Data Analysis” presented on the first day of the course!
You may work on your own or in a group, at your own computer or at the scheduled location, or in one of the computer rooms (if available) or in ‘Studielandschap’. Note that there is no assistance available during the morning.
During the lecture (13.30 to 17.00 at the very latest) we will discuss the analysis of the cases. There will also be plenty of time for you to ask questions.
For female fruitflies it is known that increased reproduction leads to a shortened life span. For male fruitflies this has never been ascertained. Male fruitflies that mate on average once a day are known to live for 60 days. The question is whether manipulation of sexual activity influences life span. To answer this question the following experiment was done: For one specific species of fruitflies, sexual activity was manipulated by providing individual males with either one or eight receptive, virginal females per day. Further, individual males were provided with one or eight recently inseminated females (these females do not wish to be inseminated again). A number of males were kept solitarily. Relevant variables were coded as follows: The data are given in the file fruitfly.sav or fruitfly.RData
| variable | explanation |
|---|---|
| number | number of females provided |
| type | type of company (0: recently inseminated, 1: virginal, 9: none) |
| day | day=0 if life span is shorter than 60 days, day=1 if life span is longer than 60 days |
| thorax | thorax length of male |
| sleep | average percentage of time spent sleeping per day |
Answer the question: do male fruitflies have a shorte life span when they reproduce more?
Number and type will be included, as they will together determine how many times a male fruitfly may reproduce. Thorax and sleep are included, because both could be related to the outcome, and possibly the determinant.
load(epistats::fromParentDir("data/fruitfly.RData"))
str(fruitfly)
'data.frame': 125 obs. of 5 variables:
$ NUMBER: num 0 0 0 0 0 0 0 0 0 0 ...
$ TYPE : Factor w/ 3 levels "recently inseminated",..: 3 3 3 3 3 3 3 3 3 3 ...
$ DAY : Factor w/ 2 levels "shorter than 60 days",..: 1 1 1 1 1 1 2 1 1 2 ...
$ THORAX: num 0.64 0.7 0.72 0.72 0.72 0.76 0.78 0.8 0.84 0.84 ...
$ SLEEP : num 18 6 19 7 16 13 35 2 35 6 ...
Number is coded as numeric. However, it only has two distinct values: 0 and 8. It may be better to recode this as a categorical variable.
table(fruitfly$NUMBER)
0 1 8
25 50 50
# fruitfly$NUMBER <- factor(fruitfly$NUMBER)
require(GGally)
GGally::ggpairs(fruitfly)
From this exploratory analysis we can observe Day seems to be associated with thorax, and maybe with number and type too.
The distribution of thorax is a little left-skewed, while sleep is somewhat right-skewed.
Day is a binary outcome, we are interested in the rate of Day > 60. For univariate analysis, we can create a contingency table and perform a chi-squared test, for multivariate analysis we can use logistic regression. As this is an etiologic question, we will include all possible confounders in the multiple regression model. We expect that type may modify the effect of number (as this determines the number of available mates), so we will include an interaction term with type and number.
Other possibility: recode number and type into 5 groups, do chi-squared
tab <- xtabs(~NUMBER+DAY, data = fruitfly)
tab
DAY
NUMBER shorter than 60 days longer than 60 days
0 11 14
1 23 27
8 32 18
prop.table(tab, margin = 1)
DAY
NUMBER shorter than 60 days longer than 60 days
0 0.44 0.56
1 0.46 0.54
8 0.64 0.36
chisq.test(tab)
Pearson's Chi-squared test
data: tab
X-squared = 4.2212, df = 2, p-value = 0.1212
In crude analysis, there seems to be no statistically significant association between day and number.
fit <- glm(DAY~NUMBER*TYPE+THORAX+SLEEP, data = fruitfly, family = binomial)
fit_scaled <- glm(DAY~NUMBER*TYPE+scale(THORAX, center = T, scale = T)+SLEEP, data = fruitfly, family = binomial)
fit_parsimonious <- glm(DAY~NUMBER*TYPE, data = fruitfly, family = binomial)
summary(fit)
Call:
glm(formula = DAY ~ NUMBER * TYPE + THORAX + SLEEP, family = binomial,
data = fruitfly)
Deviance Residuals:
Min 1Q Median 3Q Max
-2.05883 -0.49334 -0.06449 0.67281 2.08158
Coefficients: (1 not defined because of singularities)
Estimate Std. Error z value Pr(>|z|)
(Intercept) -18.04235 3.97107 -4.543 5.53e-06 ***
NUMBER 0.18537 0.11444 1.620 0.10527
TYPEvirginal -0.31544 0.81062 -0.389 0.69718
TYPEnone -0.33237 0.77118 -0.431 0.66648
THORAX 22.82644 4.73746 4.818 1.45e-06 ***
SLEEP -0.02389 0.01449 -1.649 0.09917 .
NUMBER:TYPEvirginal -0.63327 0.20464 -3.095 0.00197 **
NUMBER:TYPEnone NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 172.89 on 124 degrees of freedom
Residual deviance: 100.82 on 118 degrees of freedom
AIC: 114.82
Number of Fisher Scoring iterations: 6
summary(fit_parsimonious)
Call:
glm(formula = DAY ~ NUMBER * TYPE, family = binomial, data = fruitfly)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.5096 -1.1436 -0.2857 1.0108 2.5373
Coefficients: (1 not defined because of singularities)
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.355707 0.470573 0.756 0.44971
NUMBER 0.049758 0.084575 0.588 0.55631
TYPEvirginal 0.006823 0.672310 0.010 0.99190
TYPEnone -0.114545 0.619497 -0.185 0.85331
NUMBER:TYPEvirginal -0.492331 0.177963 -2.766 0.00567 **
NUMBER:TYPEnone NA NA NA NA
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 172.89 on 124 degrees of freedom
Residual deviance: 142.31 on 120 degrees of freedom
AIC: 152.31
Number of Fisher Scoring iterations: 5
lmtest::lrtest(fit)
Likelihood ratio test
Model 1: DAY ~ NUMBER * TYPE + THORAX + SLEEP
Model 2: DAY ~ 1
#Df LogLik Df Chisq Pr(>Chisq)
1 7 -50.411
2 1 -86.447 -6 72.073 1.535e-13 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
drop1(fit)
Single term deletions
Model:
DAY ~ NUMBER * TYPE + THORAX + SLEEP
Df Deviance AIC
<none> 100.82 114.82
THORAX 1 141.07 153.07
SLEEP 1 103.75 115.75
NUMBER:TYPE 1 113.88 125.88
Longevity can partly be explained by the provided model. The length of the male (THORAX
) seems to by the most important factor, fruitflies that are longer seem to live longer.
Number on itself is not significantly associated with the outcome. However from the interaction term, we see that the number of virginal female fruitflies is associated with shorter survival. Sleep does not seem to contribute significantly to the model.
Male fruitlies that reproduce more often seem to have a shorter life-span. However, the size of the thorax of the fruitfly is a more important predictor, with larger fruitflies living longer.
Caplehorn (1991) was interested in factors that have an effect on the success probability of retention of heroin addicts in a clinic. In a multi-center study he collected the following data from 238 heroin addicts. The data are given in the file heroin.sav or heroin.RData.
| variable | explanation |
|---|---|
| ID | Identification code |
| CLINIC | Number of clinic (1 or 2) |
| STATUS | Status (0=not (yet) departed; 1= departed from clinic) |
| TIMES | Time in days that heroin addicts spent in the clinic |
| PRISON | Prison record (1=yes; 0=no) |
| DOSE | Methadone dosage in mg/day |
(Source: Caplehorn J., 1991, Methadone dosage and retention of patients in maintenance treatment, Medical Journal of Australia, 154, 195 99)
The researchers are only interested in the effect of each explanatory variable separately. Would you advise further statistical analysis?
What factors are associated with retention of heroin addicts in a clinic.
load(epistats::fromParentDir("data/heroin.RData"))
str(heroin)
'data.frame': 238 obs. of 6 variables:
$ ID : num 1 2 3 4 5 6 7 8 9 10 ...
$ CLINIC: num 1 1 1 1 1 1 1 1 1 1 ...
$ STATUS: num 1 1 1 1 1 1 1 0 1 1 ...
$ TIMES : num 428 275 262 183 259 714 438 796 892 393 ...
$ PRISON: num 0 1 0 0 1 0 1 1 0 1 ...
$ DOSE : num 50 55 55 30 65 55 65 60 50 65 ...
Let’s throw out ID, since it is uninformative and throwing it out means that we don’t have to do that each time in the analysis
Clinic, status and prison should be coded as factor variables
heroin$ID <- NULL
require(dplyr)
heroin <- heroin %>%
mutate_at(.vars = c("CLINIC", "STATUS", "PRISON"), factor)
str(heroin)
'data.frame': 238 obs. of 5 variables:
$ CLINIC: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...
$ STATUS: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 1 2 2 ...
$ TIMES : num 428 275 262 183 259 714 438 796 892 393 ...
$ PRISON: Factor w/ 2 levels "0","1": 1 2 1 1 2 1 2 2 1 2 ...
$ DOSE : num 50 55 55 30 65 55 65 60 50 65 ...
require(ggplot2)
GGally::ggpairs(heroin)
Satus seems to be related with times, clinic, and maybe prison. However, clinic and times also seem to be related, so it could be that one of them explains the effect of the other. Also, TIMES and DOSE seem to be associated with each other.
We will use multiple logistic-regression analysis, as the effect of any single factor (or lack thereof) may be confounded by other factors.
Better plan: treat as survival data, predict how long they stay
require(survival)
Loading required package: survival
surv_obj <- Surv(time = heroin$TIMES, event = heroin$STATUS)
km_fit <- survfit(Surv(time = TIMES, event = STATUS==1)~1, data = heroin)
plot(km_fit)
lines(survfit(Surv(time = TIMES, event = STATUS==1)~CLINIC, data = heroin),
main = "retention by clinic", col = c("red", "blue"))
plot(survfit(Surv(time = TIMES, event = STATUS==1)~CLINIC, data = heroin),
main = "retention by prison", col = c("red", "blue"))
plot(survfit(Surv(time = TIMES, event = STATUS==1)~epistats::quant(DOSE), data = heroin),
main = "retention by quantiles of dose", lty = 1:4)
cox_fit <- coxph(Surv(time = TIMES, event = STATUS==1)~CLINIC+PRISON+DOSE, data = heroin)
summary(cox_fit)
Call:
coxph(formula = Surv(time = TIMES, event = STATUS == 1) ~ CLINIC +
PRISON + DOSE, data = heroin)
n= 238, number of events= 150
coef exp(coef) se(coef) z Pr(>|z|)
CLINIC2 -1.009896 0.364257 0.214889 -4.700 2.61e-06 ***
PRISON1 0.326555 1.386184 0.167225 1.953 0.0508 .
DOSE -0.035369 0.965249 0.006379 -5.545 2.94e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
exp(coef) exp(-coef) lower .95 upper .95
CLINIC2 0.3643 2.7453 0.2391 0.5550
PRISON1 1.3862 0.7214 0.9988 1.9238
DOSE 0.9652 1.0360 0.9533 0.9774
Concordance= 0.665 (se = 0.026 )
Rsquare= 0.238 (max possible= 0.997 )
Likelihood ratio test= 64.56 on 3 df, p=6.228e-14
Wald test = 54.12 on 3 df, p=1.056e-11
Score (logrank) test = 56.32 on 3 df, p=3.598e-12
We can use logrank test for 2 groups
Researchers examined maternal mortality rates (MMRs) in relation to the global distribution of physicians and nurses. A UN database on 155 countries was constructed in order to determine whether MMRs were related to the proportion of births attended by medical and nonmedical staff (defined as “attendance at birth by trained personnel” (physicians, nurses, midwives or primary health care workers trained in midwifery skills), the ratio of physicians and nurses to the population, female literacy and gross national product (GNP) per capita. The data are given in the file maternalmort.sav or maternalmort.RData.
| variable | explanation |
|---|---|
| Country | name of country |
| Physician | physicians per 1000 population |
| Nurses | nurses per 1000 population |
| GNP | gross national product per capita in dollars |
| MMR | maternal mortality rate (per 100,000 births) |
| Attended | births attended by trained personnel (%) |
| Femlit | female literacy (%) |
What is the relationship between the proportion of births attended by trained medical staff and maternal mortality rates, adjusted for gross national product per capita and female literacy
load(epistats::fromParentDir("data/maternalmort.RData"))
str(maternalmort)
'data.frame': 152 obs. of 7 variables:
$ Country : Factor w/ 152 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 10 ...
$ physician: num 0.1 1.4 0.8 0.07 0.9 2.7 3.1 2.2 2.6 3.9 ...
$ nurses : num 0.1 4.7 3.2 16.4 4.8 2.1 6.4 8.5 8.4 10.8 ...
$ GNP : num<PHONE_NUMBER> 700 6770 ...
$ MMR : num 1700 65 160 1500 NA 100 50 9 10 22 ...
$ attended : num 9 99 77 15 NA 97 NA 100 100 NA ...
$ femlit : num 15 NA 49 29 NA 96 98 NA NA 96 ...
GGally::ggpairs(maternalmort[, -1])
Warning: Removed 6 rows containing non-finite values (stat_density).
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 9 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 6 rows containing missing values
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"pearson", : Removed 15 rows containing missing values
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"pearson", : Removed 41 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 44 rows containing missing values
Warning: Removed 9 rows containing missing values (geom_point).
Warning: Removed 6 rows containing non-finite values (stat_density).
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 6 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 15 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 41 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 44 rows containing missing values
Warning: Removed 6 rows containing missing values (geom_point).
Warning: Removed 6 rows containing missing values (geom_point).
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 9 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 35 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 38 rows containing missing values
Warning: Removed 15 rows containing missing values (geom_point).
Warning: Removed 15 rows containing missing values (geom_point).
Warning: Removed 9 rows containing missing values (geom_point).
Warning: Removed 9 rows containing non-finite values (stat_density).
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 35 rows containing missing values
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 38 rows containing missing values
Warning: Removed 41 rows containing missing values (geom_point).
Warning: Removed 41 rows containing missing values (geom_point).
Warning: Removed 35 rows containing missing values (geom_point).
Warning: Removed 35 rows containing missing values (geom_point).
Warning: Removed 35 rows containing non-finite values (stat_density).
Warning in (function (data, mapping, alignPercent = 0.6, method =
"pearson", : Removed 52 rows containing missing values
Warning: Removed 44 rows containing missing values (geom_point).
Warning: Removed 44 rows containing missing values (geom_point).
Warning: Removed 38 rows containing missing values (geom_point).
Warning: Removed 38 rows containing missing values (geom_point).
Warning: Removed 52 rows containing missing values (geom_point).
Warning: Removed 38 rows containing non-finite values (stat_density).
require(dplyr)
maternalmort %>%
mutate_at(.vars = c("physician", "nurses", "GNP"), function(x) log(x+.01)) %>%
select(-Country) %>%
GGally::ggpairs()
Looks like strong collinearity for attended and femlit
We are trying to model a continous variable: MMR. Strictly speaking it is a rate, which should optimally be modeled with Poisson regression, however we do not have the original counts. However for large enough rates, the poisson distribution opproximates the normal distribution, so we can also use (multiple) linear regression.
fit1 <- maternalmort %>%
mutate_at(.vars = c("physician", "nurses", "GNP"),
function(x) log(x + 0.01)) %>%
select(-Country) %>%
lm(MMR~., data = .)
plot(fit1, which = c(1,2))
fit2 <- maternalmort %>%
mutate_at(.vars = c("physician", "nurses", "GNP", "MMR"),
function(x) log(x + 0.01)) %>%
select(-Country) %>%
lm(MMR~., data = .)
plot(fit2, which = c(1,2))
fit3 <- maternalmort %>%
mutate_at(.vars = c("MMR"),
function(x) log(x + 0.01)) %>%
select(-Country) %>%
lm(MMR~., data = .)
plot(fit3, which = c(1,2))
fit4 <- maternalmort %>%
mutate_at(.vars = c("MMR"),
function(x) log(x + 0.01)) %>%
select(-c(Country, femlit)) %>%
lm(MMR~., data = .)
plot(fit4, which = c(1,2))
drop1(fit4, test = "F")
Single term deletions
Model:
MMR ~ physician + nurses + GNP + attended
Df Sum of Sq RSS AIC F value Pr(>F)
<none> 25.385 -146.381
physician 1 7.150 32.535 -121.580 29.0115 4.565e-07 ***
nurses 1 0.085 25.470 -148.022 0.3431 0.5593
GNP 1 21.927 47.312 -81.140 88.9686 1.354e-15 ***
attended 1 34.486 59.871 -55.714 139.9265 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
fit5 <- maternalmort %>%
mutate_at(.vars = c("MMR"),
function(x) log(x + 0.01)) %>%
select(-c(Country, femlit, nurses)) %>%
lm(MMR~., data = .)
plot(fit5, which = c(1,2))
drop1(fit5, test = "F")
Single term deletions
Model:
MMR ~ physician + GNP + attended
Df Sum of Sq RSS AIC F value Pr(>F)
<none> 26.920 -149.250
physician 1 10.945 37.864 -113.382 43.502 1.659e-09 ***
GNP 1 26.908 53.828 -74.335 106.952 < 2.2e-16 ***
attended 1 33.281 60.201 -61.915 132.283 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
1/car::vif(fit5)
physician GNP attended
0.4447664 0.6613548 0.4530873
Look at Countries with highest residual, which means high rates, that is unexplained by the model.
resids <- fit5$residuals
ordered_resids <- sort(resids, decreasing = T)
included_observations <- names(ordered_resids)
data.frame(residual = ordered_resids,
maternalmort[names(ordered_resids),])
residual Country physician nurses GNP MMR attended femlit
69 1.113069146 Japan 1.80 6.800 39640 18 100 NA
51 1.067351374 Germany 3.30 5.600 27510 22 99 NA
6 1.052036593 Argentina 2.70 2.100 8030 100 97 96
144 0.865275704 Uruguay 3.20 0.640 5170 85 96 98
71 0.789012445 Kazakhstan 3.60 9.000 1330 80 99 96
45 0.757207462 El Salvador 0.80 0.900 1610 300 87 70
126 0.718296284 Sudan 0.09 0.240 480 660 69 35
38 0.705648224 Cuba 3.60 6.100 1170 95 90 95
115 0.701652352 Senegal 0.10 0.260 600 1200 46 23
142 0.664098080 Ukraine 4.40 12.200 1630 50 100 97
110 0.639604948 Rumania 1.80 4.300 1480 130 100 95
21 0.638028247 Brazil 1.40 0.400 3640 220 81 83
151 0.580683795 Zambia 0.10 0.900 400 940 51 71
152 0.579279369 Zimbabwe 0.10 0.610 540 570 69 80
55 0.577919337 Guinea 0.10 0.430 550 1600 31 22
130 0.537043612 Switzerland 3.10 14.000 40630 6 99 NA
116 0.497468745 Sierra Leon 0.07 0.350 180 1800 25 18
17 0.467301051 Benin 0.10 0.580 370 990 45 26
141 0.438439274 Uganda 0.04 0.340 240 1200 38 50
25 0.419998176 Cambodia 0.10 1.000 270 900 47 22
26 0.414557174 Cameroon 0.10 0.640 650 550 64 52
134 0.391523647 Tanzania 0.03 0.220 120 770 53 57
113 0.384065205 South Afric 0.61 2.750 3160 230 82 82
70 0.356211483 Jordan 1.60 3.000 1510 150 87 79
49 0.336182249 France 2.80 5.700 24990 15 99 NA
114 0.302266526 Saudi Arabi 1.40 0.200 6180 130 82 50
92 0.290068913 Mozambique 0.02 0.260 80 1500 25 23
23 0.288029677 Burkina 0.03 0.250 230 930 42 9
36 0.285252701 Cote d'Ivoi 0.10 0.400 660 810 45 30
14 0.279362455 Belarus 4.10 11.400 2070 37 100 97
19 0.277879185 Bolivia 0.50 0.900 800 650 47 76
15 0.276141597 Belgium 3.70 0.370 24710 10 100 NA
87 0.274492451 Mauritania 0.10 0.500 460 930 40 26
136 0.272138959 Togo 0.10 0.400 310 640 54 37
73 0.270084243 Korean Rep. 1.20 6.700 9700 70 98 97
57 0.260159551 Honduras 0.40 1.200 600 220 88 73
94 0.251001887 Namibia 0.20 3.200 2000 370 68 NA
93 0.249562379 Mynamar 0.10 0.400 220 580 57 78
40 0.204947002 Denmark 2.90 6.700 29890 9 100 NA
81 0.203738431 Lithuania 4.00 9.700 1900 36 100 98
112 0.180603328 Rwanda 0.02 0.034 180 1300 26 52
90 0.180054616 Mongolia 2.70 NA 310 65 99 77
18 0.171473569 Bhutan 0.20 0.500 420 1600 15 28
80 0.136248786 Libya 1.00 2.900 269 220 76 63
139 0.134129903 Turkey 1.10 1.500 2780 180 76 72
145 0.129025681 USA 2.50 7.000 26980 12 99 NA
52 0.127929948 Ghana 0.04 0.360 390 740 44 54
84 0.126980434 Malawi 0.02 0.060 170 560 55 42
28 0.123577525 Central Afr 0.04 0.100 340 700 46 52
99 0.107958020 Nigeria 0.15 0.900 260 1000 31 47
148 0.107754470 Vietnam 0.40 2.300 219 160 95 91
82 0.081584905 Madagasca 0.10 0.400 230 490 57 73
85 0.080482609 Mali 0.10 0.250 250 1200 24 23
4 0.076400972 Angola 0.07 16.400 700 1500 15 29
100 0.036627827 Norway 3.30 16.400 31250 6 100 NA
29 0.028086275 Chad 0.03 0.027 180 1500 15 35
1 0.022510429 Afghanistan 0.10 0.100 280 1700 9 15
24 0.018678477 Burundi 0.10 0.430 160 1300 19 23
149 0.017566096 Yemen 0.10 8.200 260 1400 16 26
91 0.006459144 Morocco 0.40 1.800 1110 610 40 31
9 0.005622820 Austria 2.60 8.400 26890 10 100 NA
42 -0.007648642 Dominican R 1.10 0.800 1460 110 92 82
96 -0.035098395 Netherlands 2.50 8.500 24000 12 100 NA
137 -0.045968645 Trinidad 0.70 2.800 3770 90 98 97
47 -0.073256209 Ethiopia 0.03 0.070 100 1400 14 25
59 -0.087104962 Hungary 3.40 7.000 4120 30 99 98
120 -0.119122863 Sri Lanka 0.14 0.710 700 140 94 87
62 -0.121864087 Indonesia 0.20 1.100 980 650 36 78
78 -0.131755707 Lebanon 1.30 NA 2660 300 45 90
3 -0.144149199 Algeria 0.80 3.200 1600 160 77 49
106 -0.144676140 Peru 1.00 2.600 2310 280 52 83
95 -0.162215528 Nepal 0.10 0.200 200 1500 7 14
79 -0.164640616 Lehsotho 0.00 0.500 770 610 40 62
56 -0.183477809 Hiaiti 0.10 0.400 250 1000 21 42
98 -0.192487320 Niger 0.03 0.200 220 1200 15 7
30 -0.197038194 Chile 1.10 2.500 4160 65 98 95
103 -0.213582885 Panama 1.60 2.400 2750 55 100 90
88 -0.221791162 Mexico 1.30 1.900 3320 110 77 87
104 -0.224832667 Papua New G 0.10 1.400 1160 930 20 63
135 -0.235006891 Thailand 0.20 1.900 2740 200 71 92
31 -0.239293302 China 1.60 1.100 620 95 84 73
147 -0.259805635 Venzuela 1.60 2.700 3020 120 69 90
32 -0.264551038 Columbia 1.10 1.400 1910 100 85 91
48 -0.266988204 Finland 2.70 12.000 20580 11 100 NA
2 -0.281955992 Albania 1.40 4.700 670 65 99 NA
43 -0.314721427 Ecuador 1.50 1.600 1390 150 64 88
138 -0.361745384 Tunisia 0.60 2.800 1820 170 69 55
129 -0.365648195 Sweden 3.10 10.100 23750 7 100 NA
64 -0.368808505 Iraq 0.20 0.200 1036 310 54 45
83 -0.376838935 Malaysia 0.40 1.560 3890 80 94 78
131 -0.394048580 Syrian A. 0.80 1.000 112 180 67 56
68 -0.413473517 Jamaica 0.50 2.000 1510 120 82 89
117 -0.452458229 Singapore 1.40 3.500 26730 10 100 86
12 -0.499814288 Bangladesh 0.20 0.300 240 850 14 26
35 -0.525018438 Costa Rica 1.30 2.200 2610 55 93 95
107 -0.534219675 Philippines 0.10 0.310 1050 280 53 94
44 -0.605981670 Egypt 1.80 2.200 790 170 46 39
105 -0.624305772 Paraguay 0.30 1.300 1690 160 66 91
63 -0.647339103 Iran 0.32 0.350 1033 120 77 59
22 -0.688024961 Bulgaria 3.50 8.500 1330 27 86 97
97 -0.695215511 Nicaragua 0.70 1.200 380 160 61 67
53 -0.752966476 Greece 4.00 3.600 8210 10 97 93
119 -0.754316656 Spain 4.10 4.300 13580 7 96 93
8 -0.773469177 Australia 2.20 8.500 18720 9 100 NA
109 -0.850582473 Portugal 2.90 3.200 9740 15 90 81
143 -1.035974592 UK 1.50 3.000 18700 9 100 NA
108 -1.039556665 Poland 2.30 5.900 2790 19 99 98
54 -1.080679426 Guatamala 0.80 1.500 1340 200 35 49
58 -1.086157536 Hong Kong 1.30 5.500 22990 7 100 88
102 -1.153942260 Pakistan 0.50 NA 460 340 19 24
27 -1.163216229 Canada 2.20 11.200 19380 6 99 NA
Some biologists were interested in the effect of temperature on the size of the cobweb from the spider Achaearanea tepidariorum. They collected the following data (see the file cobweb.sav or cobweb.RData):
Temperature (in oC) log10(cobweb weight/spider weight) 10 -2.81508 -2.74254 -2.69473 -2.58087 -2.30309 -2.82513 -2.63073 -2.10109 15 -2.23378 -2.85680 -2.31367 -2.93023 -2.69093 -2.56165 -2.61604 -2.97926 20 -1.97753 -1.98788 -1.92117 -2.42344 -2.53879 -2.29301 -2.19948 -2.27348 -2.13957 -2.43604 25 -2.02078 -2.54437 -2.41178 -1.95839 -3.02343 -2.63536 -2.63536 -2.75174 -1.99863
Analyze these data and give possible explanations for the transformation of the dependent variable.
Is the size of the cobweb of the Achaearanea tepiariorum dependant on the temperature?
load(epistats::fromParentDir("data/cobweb.RData"))
str(cobweb)
List of 2
$ TEMP : num [1:35] 10 10 10 10 10 10 10 10 15 15 ...
$ LGWEIGHT: num [1:35] -2.82 -2.74 -2.69 -2.58 -2.3 ...
- attr(*, "label.table")=List of 2
..$ TEMP : NULL
..$ LGWEIGHT: NULL
boxplot(LGWEIGHT~TEMP, data = cobweb)
From the boxplots, it seems that LGWEIGHT increases with temperature. Also, the variance of LGWEIGHT seems to increase a little with temperature.
Since we have a continous outcome and one categorical variable, we can analyse this with ANOVA (or equivalently: simple linear regression). We can treat temperature as a continous variable, or as a categorical one. Since we expect a monotonous relationship on the range of tested temperatures, we will use it as a continous variable, as this keeps in the information that \(temp = 10 < 15 < 20 < 25\)
fit <- lm(LGWEIGHT~TEMP, data = cobweb)
summary(fit)
Call:
lm(formula = LGWEIGHT ~ TEMP, data = cobweb)
Residuals:
Min 1Q Median 3Q Max
-0.68955 -0.21504 -0.03525 0.27801 0.49991
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.769883 0.178248 -15.539 <2e-16 ***
TEMP 0.017440 0.009537 1.829 0.0765 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.3111 on 33 degrees of freedom
Multiple R-squared: 0.092, Adjusted R-squared: 0.06449
F-statistic: 3.344 on 1 and 33 DF, p-value: 0.07651
plot(fit, which = c(1,2))
cor.test(~LGWEIGHT+TEMP, data = cobweb, method = "spearman")
Warning in cor.test.default(x = c(-2.81508, -2.74254, -2.69473, -2.58087, :
Cannot compute exact p-value with ties
Spearman's rank correlation rho
data: LGWEIGHT and TEMP
S = 4961.6, p-value = 0.07472
alternative hypothesis: true rho is not equal to 0
sample estimates:
rho
0.3050958
From the analysis, it looks like there is
fit_anova <- aov(LGWEIGHT~factor(TEMP), data = cobweb)
summary(fit_anova)
Df Sum Sq Mean Sq F value Pr(>F)
factor(TEMP) 3 0.9939 0.3313 4.068 0.0151 *
Residuals 31 2.5246 0.0814
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(fit_anova)
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = LGWEIGHT ~ factor(TEMP), data = cobweb)
$`factor(TEMP)`
diff lwr upr p adj
15-10 -0.0611375 -0.448403316 0.3261283 0.9731521
20-10 0.3676185 0.000225888 0.7350111 0.0498135
25-10 0.1444531 -0.231901669 0.5208078 0.7265602
20-15 0.4287560 0.061363388 0.7961486 0.0171924
25-15 0.2055906 -0.170764169 0.5819453 0.4597789
25-20 -0.2231654 -0.579038171 0.1327073 0.3398488
Immediate release medications quickly liberate their drug content into the body, with the maximum concentration reached in a short time followed by a rapid decline in concentration. Sustained release medications, on the other hand, take longer to reach maximum concentration in the body and stay active for longer periods of time.
A study of two such pain relief medications compared immediate release codeine (IRC) with sustained release codeine (SRC). Thirteen healthy patients were randomly assigned to one of the two types of codeine and treated for 2.5 days. After a 7-day wash-out period, the same patients were given the other type of codeine. Measurements include the maximum concentration in ng/mL, the time to maximum concentration in hours, the total amount of drug available over the life of the treatment in (ng*mL)/hr and the age of the patient. These data are shown below (see also the file codeine.sav or codeine.RData.
Concentration Time Total amount
Age IRC SRC IRC SRC IRC SRC 33 181.8 195.7 0.5 2.0 1091.3 1308.5 40 466.9 167.0 1.0 3.0 1064.5 1494.2 41 136.0 217.3 0.5 3.0 1281.1 1382.2 43 221.3 375.7 1.5 4.5 1921.4 1978.3 25 195.1 285.7 0.5 2.0 1649.9 2004.6 30 112.7 177.2 1.0 2.0 1423.6 * 24 84.2 220.3 2.0 1.5 1308.4 1211.1 44 78.5 243.5 1.0 3.0 1192.1 1002.4 42 85.9 141.6 1.5 1.5 766.2 866.6 33 85.3 127.2 2.0 4.5 978.6 1345.8 38 217.2 345.2 0.5 1.5 1618.9 979.2 39 49.7 112.1 1.5 1.0 582.9 576.3 43 190.0 223.4 0.5 1.0 972.1 999.1
The research questions are: are there any differences on these three parameters between immediate release codeine and sustained release codeine? Are these differences dependent on age?
Assume random order.
load(epistats::fromParentDir("data/codeine.RData"))
str(codeine)
List of 7
$ AGE : num [1:13] 33 40 41 43 25 30 24 44 42 33 ...
$ CIRC: num [1:13] 182 467 136 221 195 ...
$ CSRC: num [1:13] 196 167 217 376 286 ...
$ TIRC: num [1:13] 0.5 1 0.5 1.5 0.5 1 2 1 1.5 2 ...
$ TSRC: num [1:13] 2 3 3 4.5 2 2 1.5 3 1.5 4.5 ...
$ AIRC: num [1:13] 1091 1064 1281 1921 1650 ...
$ ASRC: num [1:13] 1308 1494 1382 1978 2005 ...
- attr(*, "label.table")=List of 7
..$ AGE : NULL
..$ CIRC: NULL
..$ CSRC: NULL
..$ TIRC: NULL
..$ TSRC: NULL
..$ AIRC: NULL
..$ ASRC: NULL
codeine <- as.data.frame(codeine)
Melt into easier format
codein_melted <- data.table::melt(codeine, id.vars = "AGE")
We will use the parametric tests. Too little data to check assumptions, too little data for power for non-parametric tests.
t.test(codeine)
One Sample t-test
data: codeine
t = 6.7874, df = 89, p-value = 1.227e-09
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
286.4803 523.6375
sample estimates:
mean of x
405.0589
Dependent on age:
Difference ~ age (dependent -> regression, associated -> correlation)
(for later take heading levels up 1 step) #### Case description
sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Matrix products: default
locale:
[1] LC_COLLATE=Dutch_Netherlands.1252 LC_CTYPE=Dutch_Netherlands.1252
[3] LC_MONETARY=Dutch_Netherlands.1252 LC_NUMERIC=C
[5] LC_TIME=Dutch_Netherlands.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] survival_2.41-3 ggplot2_<IP_ADDRESS>00 bindrcpp_0.2
[4] dplyr_0.7.3 GGally_1.3.2
loaded via a namespace (and not attached):
[1] Rcpp_0.12.12 nloptr_1.0.4 compiler_3.4.1
[4] RColorBrewer_1.1-2 git2r_0.19.0 plyr_1.8.4
[7] bindr_0.1 epistats_0.1.0 tools_3.4.1
[10] lme4_1.1-14 digest_0.6.12 nlme_3.1-131
[13] evaluate_0.10.1 tibble_1.3.4 gtable_0.2.0
[16] lattice_0.20-35 mgcv_1.8-17 pkgconfig_2.0.1
[19] rlang_0.1.2 Matrix_1.2-10 parallel_3.4.1
[22] yaml_2.1.14 SparseM_1.77 stringr_1.2.0
[25] knitr_1.17 MatrixModels_0.4-1 nnet_7.3-12
[28] rprojroot_1.2 lmtest_0.9-35 grid_3.4.1
[31] data.table_1.10.4-2 reshape_0.8.7 glue_1.1.1
[34] R6_2.2.2 rmarkdown_1.6 minqa_1.2.4
[37] car_2.1-5 reshape2_1.4.2 magrittr_1.5
[40] MASS_7.3-47 splines_3.4.1 backports_1.1.0
[43] scales_<IP_ADDRESS>00 htmltools_0.3.6 pbkrtest_0.4-7
[46] assertthat_0.2.0 colorspace_1.3-2 quantreg_5.34
[49] labeling_0.3 stringi_1.1.5 lazyeval_0.2.0
[52] munsell_0.4.3 zoo_1.8-0
This R Markdown site was created with workflowr


---
layout: post
title: 'Fieldwork: Almost there!'
date: '2015-10-22T23:52:00.000+01:00'
author: Amidst Science
tags:
- fieldwork
modified_time: '2016-02-27T20:01:27.116Z'
thumbnail: http://4.bp.blogspot.com/-W5WWsbkluNc/Viq7SqDFZLI/AAAAAAAAAnA/9LJjqZ6H2a4/s72-c/DSC05762.jpg
blogger_id: tag:blogger.com,1999:blog-7745412915677497145.post-6603555241809061936
blogger_orig_url: http://amidstscience.blogspot.com/2015/10/fieldwork-almost-there.html
---
I have a couple of more trials to do on Saturday morning and then I should be done with collecting data for this season. Two months went past really quickly. I'm glad I extended my stay too, I would have been short of time otherwise.
I thought I'd show you another one of my pretty boys. Say hi to Timor (TMR):


--- layout: default title: "My thoughts on software development" description: "" ---
I’m a follower of Jesus, a husband, an open-source lover and passionate about everything related to technology.
Currently I have been working with Elixir, although I have also worked with C#, Go and Javascript.


Machine Learning
(5 lectures)
Alongside Prof. Krisztian Balog, I co-lectured the M.Sc. course DAT630 - Web Search and Data Mining, on Fall 2017, at University of Stavanger. I was responsible for lecturing the Data Mining part (essentials of Machine Learning), and leading its practicum, as well as in charge of the laboratory for the entire course.
The book used for this part is Introduction to Data Mining, by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar (Pearson, 2006).
Below, you can find my slides for each lecture, and the book chapter they correspond to.
Introduction and Data
This series of lectures starts by introducing the motivations and challenges in data mining, the types of data, problems and criteria on data quality, techniques for data preprocessing, and measures.
This lecture corresponds to the chapters 1 and 2 of the book.
Exploring Data
Here, we present core statistics for exploring data, as well as visualization techniques.
This lecture corresponds to the chapter 3 of the book.
Classification
We introduce the problem of supervised machine learning, and detail fundamental learning algorithms and concepts for evaluation.
This lecture corresponds to the chapter 4 of the book.
Classification (continued)
Having studied the basics of classification and a handful of methods, in this lecture we discuss alternative classification techniques and additional concepts.
This lecture corresponds to the chapter 5 of the book.
Clustering
In the final lecture, we move on to unsupervised learning, and describe the essentials of clustering, its types, and distinguished clustering methods.
This lecture corresponds to the chapter 8 of the book.


{{ title }}
April 2020 Update: I don’t manually curate the content on this page any more, so it’s probably outdated. A list of self-curated posts that I’m most proud of. If you want to see what everyone else liked, check out popular posts.
-
{% assign year = "" %}
{% assign currentyear = "" %}
{% assign listItems = collections.highlight | reverse %}
{% for post in collections.highlight %}
{% include "post-list-entry.html" %}
{% endfor %}


Contact: {{ job.contact }}
{{ job.salary }}
{{ job.address }}
{{ job.phone }}
Company Link: {{ job.companyLink }}
Posted {{ this.timePast(job.resource.createdTimestamp) }} ago


org.apache.drill.exec.store.pojo
Interfaces
PojoWriter
Classes
AbstractPojoRecordReader
AbstractPojoWriter
DynamicPojoRecordReader
DynamicPojoRecordReader.Converter
PojoDataType
PojoRecordReader
PojoWriters
PojoWriters.BitWriter
PojoWriters.DecimalWriter
PojoWriters.DoubleWriter
PojoWriters.EnumWriter
PojoWriters.IntWriter
PojoWriters.LongWriter
PojoWriters.NBigIntWriter
PojoWriters.NBooleanWriter
PojoWriters.NDoubleWriter
PojoWriters.NIntWriter
PojoWriters.NTimeStampWriter
PojoWriters.StringWriter
Annotation Types
NonNullable


Outside the Big Top tent is a parade of happy clowns, doing their best to cheer you up. The grumpy strong man challenges them to a game of Tug of War.
This was a "scrum" puzzle—a puzzle meant to be solved by many teammates looking at their computers at the same time. The game showed each player a pair of choices with voting buttons. And there was a deadline clock. Once enough players had voted, the winning choice became the team choice. For this after-the-hunt version, we'll let you make all the choices on your own.
Click either button to start!


pycsw Demonstration Server
Demonstrations
OGC CITE
used for OGC
CITE testing
. This is pycsw's official
OGC Reference Implementation
.
gisdata
demo of
gisdata
GitHub repository
services
demo of harvested OGC Web Services (contact
pycsw
to have your service added)
viewer
jQuery / Leaflet based CSW viewer
Code Activity


The plugin supports three different usage modes: single-module, multi-module and restricted multi-module.
The single-module mode is the default.
It searches for binding definition files in the current project and compiles them using the project's classpath.
In its multi-module mode the plugin searches for binding definition files in the current and all referenced projects and runs the binding compiler with an aggregated classpath.
Just set the multi-module flag to true:
<configuration> <multi-module>true</multi-module> </configuration>
Note: See multi-module note below.
The restricted multi-module mode is basically the same as above but does not include all referenced projects but only those specified in the plugin's configuration.
The plugin automatically switches to its restricted multi-module mode if you specify a list of modules in its configuration section. The multi-module flag is optional:
<configuration> <modules> <module>com.example:example1</module> <module>com.example:example2</module> </modules> </configuration>
Note: When you specify multi-module mode, all of the modules must be included in the maven build.
For example if the project in our example was structured as follows:
- parentModule - example1 - example2 - multiModuleProject
You must build the parentModule for the multiModuleProject to build correctly. If you build the multiModuleProject by itself the build will not be able to find resources in the example1 and example2 projects.


Bellevue, WA
Hi, my name is Nathan. I studied Computer Science at The University of British Columbia. I am seeking Summer 2020 Internship or New Graduate Opportunities!
Learn More


A sample blog using tutorial resources
This is a sample tutorial to show case how the comments plugin can be
integrated to any static page.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.


I hail from a middle class agricultural family. I moved to hyderabad after graduation in search of employment. Having worked as a junior lecturer for two years, i found the job was not satifactory to me.In 2004 i happened to hear a seminar on tiens. Tiens value based products and career in it attracted me to join it. There was no looking back after joining Tiens. The achievment of Golden Lion rank is a great jump from my humble beginning.
In accordance with Tiens Group's philosophy, namely "restoring health to mankind, contributing to society", Tiens products are subject to continuous research and development, entering the market under the way of thinking "To prevent diseases, to delay aging, and to care for environment in order to fulfill the needs of international costumers, to apply the newest technology and natural ingredients as the main components, to meet people's need in modern era, to keep costumers healthy, and to improve the quality of life of every family with satisfactory products and service.
TIENS Health Food Products are able to supply nutrients demand of every person, to stabilize body function, to prevent diseases, and to bring health
Read MoreTIENS health products using Chinese medicine which is closely related to meridian, energy and blood, acupuncture theory, through excellent design and modern technology
Read MoreLets build a future in the global business of tiens through team work.
Safilguda, Hyderabad
+91<PHONE_NUMBER>
+91<PHONE_NUMBER>
<EMAIL_ADDRESS>prathisankararao@gmail.com


Dear colleague,
We would like to confirm we have received your payment. Thank you for your membership of the ISB. We value your participation in ISB immensely. It is through the commitment and effort of members such as yourself that we can host meetings and provide professional forums for community engagement including publication, networking, and job boards.
To view the ISB public site at any time please go to our website.
To view the ISB member site, please login.
Thank you
With kind regards,
Your colleagues at the ISB


except KeyError:
self.title_labl.set_label(os.path.basename(self.songs[self.song_ptr]))
try:
self.artist_labl.set_label(cgi.escape(id3info["ARTIST"]))
except KeyError:
self.artist_labl.set_label("-")
try:
id3info = ID3(self.songs[self.song_ptr])
except:
id3info = {}
// The keys in mutagen.ID3 don"t seem to be documented anywhere!
// This is empirical and will probably break at some point.


[2.5/4.0]
Washington Irving's story The Legend of Sleepy Hollow is a classic Halloween tale, so it is a bit odd that this interpretation of that story was release during the Christmas season. Perhaps it was intended for the October time frame but was delayed.
Only a scant few elements of the original story are kept. Character names are preserved, but the story is completely different. Whereas the original is a simple story of jealousy and deception, this Gothic film is a much more complex and intricate work. Deeper themes of objectivity and reason, spirituality, treachery, and even pure carnage are incorporated.
In this rendition, Ichabod Crane (Johnny Depp) is a police investigator in 18th century New York. His rigorous insistence on rigorous scientific inquiry and thorough investigation is seen as meddlesome by the courts, so he is banished to the rural village of sleepy hollow to investigate a series of brutal murders.
The people of the village attribute the gruesome decapitations to the legendary Headless Horseman, a mythical figure inspired by pure bloodlust. Ichabod sets up residence at the home of village elder Baltus Van Tassel (Michael Gambon), but dismisses the beliefs of his host and the others. To Ichabod, the world is starkly rational, with scientific explanations for all processes. His patronizing attitude causes him to be not particularly well-liked except perhaps by his host daughter, Katrina Van Tassel (Christina Ricci).
The world that Ichabod enters is dark and eerie, a signature creation of director Tim Burton. The most enjoyable parts of the film are the noir mood and Gothic themes that are elaborately constructed. Unfortunately, the story is weak, and does little to complement the cinematography. Although the film is able to maintain suspense and keep its mysteries hidden, the story is ultimately muddled and it builds into a ridiculously frenetic and overly cathartic climax.
Moderately recommended. The success of the film is in its mood and visuals, not its story. The narrative is clumsy and becomes uninteresting, but the imagery and special effects are entertaining. It is not a retelling of the classic story, but a complete reworking of it that fits it into a different vision.
(c) 2000 Murali Krishnan The Art House Squatter http://ArtHouseSquatter.com
Sent via Deja.com http://www.deja.com/ Before you buy.
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


India vs Bangladesh 1st Test Day 3 LIVE Score: Mushfiqur Rahim Hits Fifty, India 4 Wickets Away From Win
Ind Vs Ban 1st Test Day 3 LIVE Score: India took a 343-run lead after declaring their first innings at their overnight score of 493/6.
by Samrat ChakrabortyIndian bowlers fired in unison as Bangladesh were reduced to 60/4, trailing by 283 runs at lunch on Day 3 of the Indore Test on Saturday. After declaring the first innings at their overnight total of 493/6, Umesh Yadav removed Imrul Kayes early. His opening partner Shadman Islam also did not last long as Ishant Sharma sent him packing in the seventh over. Mohammad Mithun showed some resiliance by hitting four boundaries but he was dismissed by Mohammed Shami. Shami, who put a bowling exhibition on show, was the pick of the bowlers for India as he returned figures of 2/8. (LIVE SCORECARD)


Lying on the southern coast of the island, the town of Cienfuegos is some 1.5 miles inland from the port. You can either walk there in 20 minutes, take a bicycle taxi or horsedrawn carriage. The town centre is beautifully restored with lots of colonial buildings.
This is a good place for exploring more of Cuba overland as there are three car hire companies within walking distance of the port, and it is just a 3 hour drive to Havana.
Position 22°07’.50 N, 80°27’.20 W.
All offices, immigration, customs, dock and harbourmaster, are present. Clearance is straightforward, although you may be asked for a small "present".
See Cuba Formalities for detailed information on clearing into and out of Cuba.
The marina has good solid concrete berths. With a strong Southerly wind there tends to be some swell. All personnel speak good English. The channel to the marina is well marked. Unfortunately, latest reports are that the majority of space here is taken up with charter companies, so it has very few berths for visiting yachts.
The anchorage here has good holding. When going ashore, dinghies can be left on the beach beside the main marina office. This beach is actually outside the fenced secure area, so you will need a long chain to loop around a tree to secure your dinghy. The marina charges a fee for anchoring, but does allow use of their bathroom facilities and has a security patrol through the anchored boats at night.
A short walk from the marina is the place where everybody goes out in the evening and there is music playing here. In addition, right next to the marina and anchorage is the Cienfeugos Club which plays very loud music at night, making it difficult to sleep.

Photos courtesy of Mary Buchanan who visited Cienfuegos in 2015.
Last updated October 2016.


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Middle Class jobs are being replaced by burger-flipping, retail sales.
Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusant doloremque laudantium, totam rem aperiam eaque ipsa quae.
By Anna SmithThere are many variations of passage of Lorem Ipsum available.
Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusant doloremque laudantium, totam rem aperiam eaque ipsa quae.
By Anna SmithBut I must explain to you how all this mistaken idea of denouncing pleasure.
Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusant doloremque laudantium, totam rem aperiam eaque ipsa quae.
By Anna Smith


The map shows the locations of a variety of health
service types across the county, including hospitals,
pharmacies, dentists etc.
Currently showing
out of a total of
health locations.


|
Class Imlib2::Color::CmyaColor
|
|
Returns a new Imlib2::Color::CmyaColor.
Examples:
c, m, y, a = 255, 0, 0, 255
border = Imlib2::Color::CmyaColor.new c, m, y, a
values = [255, 0, 0, 255]
border = Imlib2::Color::CmyaColor.new values
Get the cyan element of a CmyaColor object.
Examples:
amount = color.cyan
amount = color.c
Set the cyan element of a CmyaColor object.
Examples:
color.cyan = 255
color.c = 255
Get the cyan element of a CmyaColor object.
Examples:
amount = color.cyan
amount = color.c
Set the cyan element of a CmyaColor object.
Examples:
color.cyan = 255
color.c = 255
Get the magenta element of a CmyaColor object.
Examples:
amount = color.magenta
amount = color.m
Set the magenta element of a CmyaColor object.
Examples:
color.magenta = 255
color.m = 255
Get the magenta element of a CmyaColor object.
Examples:
amount = color.magenta
amount = color.m
Set the magenta element of a CmyaColor object.
Examples:
color.magenta = 255
color.m = 255
Get the yellow element of a CmyaColor object.
Examples:
amount = color.yellow
amount = color.y
Set the yellow element of a CmyaColor object.
Examples:
color.yellow = 255
color.y = 255
Get the yellow element of a CmyaColor object.
Examples:
amount = color.yellow
amount = color.y
Set the yellow element of a CmyaColor object.
Examples:
color.yellow = 255
color.y = 255
Get the alpha element of a CmyaColor object.
Examples:
amount = color.alpha
amount = color.a
Set the alpha element of a CmyaColor object.
Examples:
color.alpha = 255
color.a = 255
Get the alpha element of a CmyaColor object.
Examples:
amount = color.alpha
amount = color.a
Set the alpha element of a CmyaColor object.
Examples:
color.alpha = 255
color.a = 255


Download
Some steps to install for Windows
- Install the .zip file.
- Extract the downloaded file.
- Move extracted folder to "program Files" in the path:
C:/program Files
- Open the folder.
- Right-click on "GAMEfire.exe" and select copy.
- Then, goto Desktop.
- Press shift + ctrl + v to paste the shortcut.
NOTE: It is not please don't press ctrl + v or paste


Control the filtering av white noise by clicking and sliding up and down
For detailed information, please read the comments in the code: audio.xml
WebAudioXML is a PhD research project invented and maintained by Hans Lindetorp. For more info, turorials, documentation and download links, please visit https://github.com/hanslindetorp/WebAudioXML


The builtin (binary) CPack RPM generator (Unix only)
CPackRPM may be used to create RPM package using CPack. CPackRPM is a CPack generator thus it uses the CPACK_XXX variables used by CPack : http://www.cmake.org/Wiki/CMake:CPackConfiguration
However CPackRPM has specific features which are controlled by the specifics CPACK_RPM_XXX variables. CPackRPM is a component aware generator so when CPACK_RPM_COMPONENT_INSTALL is ON some more CPACK_RPM_<ComponentName>_XXXX variables may be used in order to have component specific values. Note however that <componentName> refers to the grouping name. This may be either a component name or a component GROUP name. Usually those vars correspond to RPM spec file entities, one may find information about spec files here http://www.rpm.org/wiki/Docs. You’ll find a detailed usage of CPackRPM on the wiki:
http://www.cmake.org/Wiki/CMake:CPackPackageGenerators#RPM_.28Unix_Only.29
However as a handy reminder here comes the list of specific variables:
The RPM package summary.
The RPM package name.
The RPM package version.
The RPM package architecture.
This may be set to “noarch” if you know you are building a noarch package.
The RPM package release.
This is the numbering of the RPM package itself, i.e. the version of the packaging and not the version of the content (see CPACK_RPM_PACKAGE_VERSION). One may change the default value if the previous packaging was buggy and/or you want to put here a fancy Linux distro specific numbering.
The RPM package license policy.
The RPM package group.
The RPM package vendor.
The projects URL.
RPM package description.
RPM compression type.
May be used to override RPM compression type to be used to build the RPM. For example some Linux distribution now default to lzma or xz compression whereas older cannot use such RPM. Using this one can enforce compression type to be used. Possible value are: lzma, xz, bzip2 and gzip.
RPM spec requires field.
May be used to set RPM dependencies (requires). Note that you must enclose the complete requires string between quotes, for example:
set(CPACK_RPM_PACKAGE_REQUIRES "python >= 2.5.0, cmake >= 2.8")
The required package list of an RPM file could be printed with:
rpm -qp --requires file.rpm
RPM spec requires(pre) field.
May be used to set RPM preinstall dependencies (requires(pre)). Note that you must enclose the complete requires string between quotes, for example:
set(CPACK_RPM_PACKAGE_REQUIRES_PRE "shadow-utils, initscripts")
RPM spec requires(post) field.
May be used to set RPM postinstall dependencies (requires(post)). Note that you must enclose the complete requires string between quotes, for example:
set(CPACK_RPM_PACKAGE_REQUIRES_POST "shadow-utils, initscripts")
RPM spec requires(postun) field.
May be used to set RPM postuninstall dependencies (requires(postun)). Note that you must enclose the complete requires string between quotes, for example:
set(CPACK_RPM_PACKAGE_REQUIRES_POSTUN "shadow-utils, initscripts")
RPM spec requires(preun) field.
May be used to set RPM preuninstall dependencies (requires(preun)). Note that you must enclose the complete requires string between quotes, for example:
set(CPACK_RPM_PACKAGE_REQUIRES_PREUN "shadow-utils, initscripts")
RPM spec suggest field.
May be used to set weak RPM dependencies (suggests). Note that you must enclose the complete requires string between quotes.
RPM spec provides field.
May be used to set RPM dependencies (provides). The provided package list of an RPM file could be printed with:
rpm -qp --provides file.rpm
RPM spec obsoletes field.
May be used to set RPM packages that are obsoleted by this one.
build a relocatable RPM.
If this variable is set to TRUE or ON CPackRPM will try to build a relocatable RPM package. A relocatable RPM may be installed using:
rpm --prefix or --relocate
in order to install it at an alternate place see rpm(8). Note that currently this may fail if CPACK_SET_DESTDIR is set to ON. If CPACK_SET_DESTDIR is set then you will get a warning message but if there is file installed with absolute path you’ll get unexpected behavior.
This way of specifying post-install script is deprecated, use CPACK_RPM_POST_INSTALL_SCRIPT_FILE. May be used to set an RPM post-install command inside the spec file. For example setting it to “/bin/true” may be used to prevent rpmbuild to strip binaries.
RPM extended spec definitions lines.
May be used to add any %define lines to the generated spec file.
Toggle CPackRPM debug output.
May be set when invoking cpack in order to trace debug information during CPack RPM run. For example you may launch CPack like this:
cpack -D CPACK_RPM_PACKAGE_DEBUG=1 -G RPM
A user provided spec file.
May be set by the user in order to specify a USER binary spec file to be used by CPackRPM instead of generating the file. The specified file will be processed by configure_file( @ONLY). One can provide a component specific file by setting CPACK_RPM_<componentName>_USER_BINARY_SPECFILE.
Spec file template.
If set CPack will generate a template for USER specified binary spec file and stop with an error. For example launch CPack like this:
cpack -D CPACK_RPM_GENERATE_USER_BINARY_SPECFILE_TEMPLATE=1 -G RPM
The user may then use this file in order to hand-craft is own binary spec file which may be used with CPACK_RPM_USER_BINARY_SPECFILE.
May be used to embed a pre (un)installation script in the spec file. The refered script file(s) will be read and directly put after the %pre or %preun section If CPACK_RPM_COMPONENT_INSTALL is set to ON the (un)install script for each component can be overridden with CPACK_RPM_<COMPONENT>_PRE_INSTALL_SCRIPT_FILE and CPACK_RPM_<COMPONENT>_PRE_UNINSTALL_SCRIPT_FILE. One may verify which scriptlet has been included with:
rpm -qp --scripts package.rpm
May be used to embed a post (un)installation script in the spec file. The refered script file(s) will be read and directly put after the %post or %postun section. If CPACK_RPM_COMPONENT_INSTALL is set to ON the (un)install script for each component can be overridden with CPACK_RPM_<COMPONENT>_POST_INSTALL_SCRIPT_FILE and CPACK_RPM_<COMPONENT>_POST_UNINSTALL_SCRIPT_FILE. One may verify which scriptlet has been included with:
rpm -qp --scripts package.rpm
May be used to explicitly specify %(<directive>) file line in the spec file. Like %config(noreplace) or any other directive that be found in the %files section. Since CPackRPM is generating the list of files (and directories) the user specified files of the CPACK_RPM_<COMPONENT>_USER_FILELIST list will be removed from the generated list.
RPM changelog file.
May be used to embed a changelog in the spec file. The refered file will be read and directly put after the %changelog section.
list of path to be excluded.
May be used to exclude path (directories or files) from the auto-generated list of paths discovered by CPack RPM. The defaut value contains a reasonable set of values if the variable is not defined by the user. If the variable is defined by the user then CPackRPM will NOT any of the default path. If you want to add some path to the default list then you can use CPACK_RPM_EXCLUDE_FROM_AUTO_FILELIST_ADDITION variable.
additional list of path to be excluded.
May be used to add more exclude path (directories or files) from the initial default list of excluded paths. See CPACK_RPM_EXCLUDE_FROM_AUTO_FILELIST.
May be used to specify more than one relocation path per relocatable RPM. Variable contains a list of relocation paths that if relative are prefixed by the value of CPACK_RPM_<COMPONENT>_PACKAGE_PREFIX or by the value of CPACK_PACKAGING_INSTALL_PREFIX if the component version is not provided. Variable is not component based as its content can be used to set a different path prefix for e.g. binary dir and documentation dir at the same time. Only prefixes that are required by a certain component are added to that component - component must contain at least one file/directory/symbolic link with CPACK_RPM_RELOCATION_PATHS prefix for a certain relocation path to be added. Package will not contain any relocation paths if there are no files/directories/symbolic links on any of the provided prefix locations. Packages that either do not contain any relocation paths or contain files/directories/symbolic links that are outside relocation paths print out an AUTHOR_WARNING that RPM will be partially relocatable.
May be used to set per component CPACK_PACKAGING_INSTALL_PREFIX for relocatable RPM packages.


{{ names.name( 'g8' ) }} is a command line utility that scaffolds projects from special {{ names.name( 'gh' ) }} repositories (so-called templates). It is written in {{ names.name( 'scala' ) }} and leverages some {{ names.abbr( 'sbt' ) }} features, but it may generally be used to scaffold any kind of projects.
There are a couple {{ names.name( 'scala-android' ) }} templates available on the {{ sourcelink( 'g8-templates' ) }} page, they don't seem particularly well maintained and up to date, though.


class CircularBuffer : Any
| <init> |
CircularBuffer(size: Int) |
| addFirst |
fun addFirst(value: Double): Unit
Push new value to the front of the buffer. The value at the back is overwritten if the buffer is full. |
| clear |
fun clear(): Unit
Sets internal buffer contents to 0 |
| get |
operator fun get(index: Int): Double
Get the element at the provided index relative to the start of the buffer. |
| getFirst |
fun getFirst(): Double
Get value at the front of the buffer. |
| getLast |
fun getLast(): Double
Get the value at the end of the buffer. |
| removeFirst |
fun removeFirst(): Double
Pop value at the front of the buffer. |
| removeLast |
fun removeLast(): Double
Pop value at the back of the buffer. |
| resize |
fun resize(size: Int): Unit
Resizes internal buffer to given size. |
| size |
fun size(): Int
Returns number of elements in the buffer. |


Checkout process
Passenger details »
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Passenger details
Gender
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| Libraries | Version |
|---|---|
| Ace | {build-library-ace-release} |
| Bootstrap + Reboot | {build-library-bootstrap-release} |
| ClipboardJS | {build-library-clipboardjs-release} |
| Font-Awesome | {build-library-fontawesome-release} |
| Gijgo | {build-library-gijgo-release} |
| Handlebars | {build-library-handlebars-release} |
| jQuery (includes Sizzle) | {build-library-jquery-release} |
| jQuery Bootstrap Scrolling Tabs | {build-library-jqueryscrollingtabs-release} |
| jQuery RWD Freeze Table | {build-library-jqueryfreezetable-release} |
| JS-Cookie | {build-library-jscookie-release} |
| Lodash | {build-library-lodash-release} |
| Moment | {build-library-momentjs-release} |
| Moment-MSDate | {build-library-momentjsmsdate-release} |
| Moment-Timezone | {build-library-momentjstimezone-release} |
Font Awesome Free is free, open source, and GPL friendly. You can use it for commercial projects, open source projects, or really almost whatever you want.
Full Font Awesome Free license: https://fontawesome.com/license.
# Icons: CC BY 4.0 License (https://creativecommons.org/licenses/by/4.0/) In the Font Awesome Free download, the CC BY 4.0 license applies to all icons packaged as SVG and JS file types.
# Fonts: SIL OFL 1.1 License (https://scripts.sil.org/OFL) In the Font Awesome Free download, the SIL OLF license applies to all icons packaged as web and desktop font files.
# Code: MIT License (https://opensource.org/licenses/MIT) In the Font Awesome Free download, the MIT license applies to all non-font and non-icon files.
# Attribution
Attribution is required by MIT, SIL OLF, and CC BY licenses. Downloaded Font Awesome Free files already contain embedded comments with sufficient attribution, so you shouldn't need to do anything additional when using these files normally.
We've kept attribution comments terse, so we ask that you do not actively work to remove them from files, especially code. They're a great way for folks to learn about Font Awesome.
# Brand Icons
All brand icons are trademarks of their respective owners. The use of these trademarks does not indicate endorsement of the trademark holder by Font Awesome, nor vice versa. **Please do not use brand logos for any purpose except to represent the company, product, or service to which they refer.**


This scenario demonstrates how to programmatically manipulate items in a Binding.List Data Source used with a ListView. Binding.List is an in-memory datasource with API like javascript Arrays. The sample generates a set of random letters and uses a Binding.List to store them.


I like to learn new things
I enjoy writing front-end code with these technologies
You can contact me here: @github


Blacksmith Brunon:
Oh, a letter from Marina! She must be too busy to come herself. I've done a lot of business with her, but I still can't figure her out! I understand she's had a great past...
Anyways, here's what she asked for. Be careful! It's fragile.


Dev Console
PUBLISH
{"my_key":"data"}
MESSAGE TO SEND
CHANNEL
PUBLISH
SUBSCRIBE
aslkjdfalk sjdflakj
RECEIVED MESSAGES
CHANNEL
LOADING...
MODIFY YOUR SETTINGS


Reba McEntire, Carrie Underwood, Dolly Parton And More Open CMA Awards With Powerful Performance Honouring Women In Country Music
by Katie ColleyCountry music’s biggest night is officially underway and the history-making opening performance did not disappoint.
To kick off the 53rd annual CMA Awards, which is celebrating the legacy of women within country music, one dozen female artists took the stage to deliver a powerful salute.
Co-hosts Carrie Underwood, Reba McEntire, and Dolly Parton opened the medley with Parton, Linda Ronstadt and Emmylou Harris’ 1987 hit “Those Memories of You”, before a slew of female artists joined the hosts on stage.
Jennifer Nettles was joined by Little Big Town’s Karen Fairchild and Kimberly Schlapman to take the reigns on Loretta Lynn’s 1971 classic “You’re Lookin’ at Country”, while Maren Morris, Brandi Carlile, Amanda Shires, and Natalie Hemby — collectively known as The Highwomen — appeared on the opposite side of the stage to perform Tammy Wynette’s “Your Good Girl’s Gonna Go Bad”.
The celebration wouldn’t be complete without Tanya Tucker breaking into her 1972 hit “Delta Dawn”.
Other highlights from the medley included Underwood, Parton, Nettles, Fairchild and Schlapman backing up Gretchen Wilson on her iconic song “Redneck Woman” before all 11 women joined Martina McBride for her anthem “Independence Day”.
See some social media reaction from the epic opening number below:


ChainZilla provides the most efficient and flexible end-to-end blockchain solutions. These include project onboarding, tokenization, app development, ICO management, and blockchain migrations.
100 messages
Before 05-Dec-19 12:00 AM
Komodo-BotBOT21-Jul-18 10:13 PM
[PTYX#6840] @Unknown@Unknown@Unknown welcome to our channel
Komodo-BotBOT21-Jul-18 10:36 PM
[Emmanuel#5426] Hola, @maripao , bienvenida.
[maripao#2299] gracias...
[PTYX#6840]
[PTYX#6840] @Instel7 is our new support and social media superstar
[PTYX#6840] He starts on Monday
[PTYX#6840] We now should have plenty of social media man/woman power to handle our growth.
[Robert Naus#9564] Why discord doesn’t allow to post links?
[CVIII#3171] i would love but i missed my call in live to be a developer, programmer...
[CVIII#3171] as i said before i just started to learn to operate ubuntu and commands in terminal
[CVIII#3171]
[Robert Naus#9564] @[TPUX] Djith Wattignies you changed to 1977 first (your DOB) and now to 108 so maybe u born 10-8 1977? Lot of info
[CVIII#3171] all wrong
[CVIII#3171] the king died in 1977
[CVIII#3171] Elvis Presley
[CVIII#3171] anyway.. all is known anyway.
im texting here on my wifi..
[CVIII#3171] other pic aswell
Komodo-BotBOT22-Jul-18 12:15 PM
[PTYX#6840] Sometimes the links show up and other times it doesn't
Komodo-BotBOT22-Jul-18 12:24 PM
[yorklab#7270] I know some of these ICO sites want money for a rating, more money, higher rating; Have you run into that issue?
[PTYX#6840] Yes but I don't apply to the ones that want money
[PTYX#6840] There are a few that want 1-5 btc
[PTYX#6840] It's crazy
[PTYX#6840] I don't mind paying a listing fee becausw it takes time to go through the info and do KYC
[PTYX#6840] But 0.01-0.05 is more than enough
[PTYX#6840] Icocreed actually charged us the basic listing fee and they wrote us to tell us that they were impressed with the project. The rating is definitely an honest one from them.
[PTYX#6840] Coinschedule does have higher packages but they do seem somewhat honest
[PTYX#6840] I'll try icobench
[PTYX#6840] They charge 0.1 for a priority listing though. I've applied through the regular listing with no response.
[yorklab#7270] I know Sri from Utrum was a bit frustrated with the "money for rating" problem when he was looking.
[PTYX#6840] Yes it's a pain
[PTYX#6840] Same as the issue with "money for exchange"
Komodo-BotBOT22-Jul-18 01:35 PM
[Emmanuel#5426] Yes, Utrum is gonna solve that kind of problems.
Here's a link to Utrum's discord:
https://discord.gg/WGBnCa
</shameless_shilling>
[PTYX#6840] I am looking forward to their launch. I want chainzilla go bw listed on utrum
Let the memes begin! Join our first meme competition for a chance to win 10 $ZILLA https://t.co/mQckZHh8ma #Memes #Airdrops @CryptoMemes @CryptoMemes4You
[Bo#8264] Cool
[Bo#8264] @PTYX how much time do we have for this?
The winner will get 10 ChainZilla Coins. After the meme is chosen, we will email the winner in order to obtain the wallet address for payout.
[Bo#8264] Ah, of course. Missed that. I will give it a shot tomorrow
[Mastermind#1578] @PTYX the first tweet you typed 10$ zilla ill suggest remove $ sign as it seems 10$ worth of zilla as oppose to 10 zilla (just a thought)
[PTYX#6840] $ZILLA is the tweet hashtag
[Mastermind#1578] Ah alright i just read text here :p
[Mastermind#1578] Mmm wait hashtags are showed seperately
[CVIII#3171] Has to be chainzilla in mainrole.. or komodo?
[PTYX#6840] Eithet
[PTYX#6840] They seem to overlap
Komodo-BotBOT22-Jul-18 04:02 PM
[NWhiskeyTango#5590] Anyone know current block height?
[PTYX#6840] .block
[ChainZilla Bot#7671] Current Block: 15,456
[NWhiskeyTango#5590] Ty
[Instel7#1416] Hey @PTYX anyone can use that command?


Web pages consist of HTML (the structure of the page, a language used to tell a web browser how the page should look, used in fonts, links, typographical emphasis, images, alignment, etc.) and CSS (the visual and aural layout, gives specifications to the style of the documents including layouts, colors, fonts, etc.) and javascript (web programming language, powers things like google docs, facebook, consists of the actions on the internet like a menu opening upon clicking.)
The so called fingerprint of a browser is a unique ID that is generated that can be used to identify your particular browser on the computer. Using Java, websites can obtain vital information such as the resolution of the screen as well as the orientation which could be used to know if someone had a smartphone and what landscape it was being held. Java also allows bits of info like what web browser, OS , type of electronic possibly make and model Timezone default language, browser plugins installed. Java creates a hash (known as the browser fingerprint) of the collected data which sends it to the server which is then stored in the database.
All that needs to be done is go to the website malicious javascript code and users will not know it is running in the background. There are certain things like the Font test that run a java code and it draws a box unknowing to users, write a word or letters and draws box and looks at what browser has drawn and can see the variations in the way it renders text to get certain information , as each computer renders text differently. The way one computer writes letters differs from others, and can know exactly how that computer draws a certain letter after running the code.
All of these may seem minute but it's the combination of all of these unique bits of information that adds together that allows. Can gather a unique code that can just be sent up to their server. Websites with javascript code such as Google analytic Facebook like button, if they did browser fingerprinting doesn't matter if logged in or not, if in private browsing mode they would know your unique ID.


I am a Computer Science student at BITS-PILANI,K. K. Birla Goa Campus.I always try to learn new.I really love playing badminton and maintaining a good physique is I pursue.I am also a big fan of Anime.
I believe that a person is "succesful" only when he wants and work towards his goal as one wants to breathe while drowning."
2005 - 2015
Primary & Secondary School
2015 - 2017
High School
2017 - 2021
B.E. Computer Science


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{{ meta }}
Review all {{ size }} activities
Other ways to contribute include Opening an issue. Participating in the discussion. Following this project's progress.


Growing Up With Pets
When I was little, my mom, dad, baby sister, and I lived on a small farm in Northwestern Ontario. We had two horses named Beaux and Dee, and a german shepherd named Tessie.
 For those of you who don’t already know this: baby bears are super cute and friendly, but going near them can get you killed. Also, it is always best to have a dog with you if you are going out into the woods.
Eventually my parents split up and we moved into town. One of the horses had died, the other they sold, and Tessie got old and went out to live with Grandpa in the country. (No this isn’t one of those stories your parents tell you when your dog dies. We went out to visit them all the time.) She lived there until she was 16 or so, when she died of old age.
Mom had developed allergies to dogs and cats so she never wanted to get another pet, but eventually my sister and I wore her down and she took us to the pet store in Winnipeg. (There were none closer than that.) Mom had a cockatiel when she was growing up that she had loved so she led us towards the bird section. The girl working at the store showed us the budgies. She told us about how they had been playing with them and training them a bit. There was one blue budgie that had mastered the “step-up” command and she thought he was going to be very trainable and maybe even be able to talk. I named him Blue Boy. My sister chose an all white budgie she named Snowflake. We got all the accessories we would need and set off on the four hour car ride home with the birds sitting in their cage between us in the back seat. I still have this vivid memory of my aunt turning around in the passenger seat, and upon seeing my face saying, “Sarah is in love.”
(I'm looking for a picture of Blue Boy and Snowflake to put here.)


UIEmptyStateDelegate
public protocol UIEmptyStateDelegate: class
The delegate for UIEmptyStateView
Important:
This delegate and its functions are only used when using UIEmptyStateView
.
If you will provide a custom view in the UIEmptyStateDataSource
viewForEmptyState
you must handle how this delegate operates
-
emptyStateViewWillShow(view:)
Default implementationThe call back for when the
emptyStateView
will be shown on screen- view: The view that is will show
Default Implementation
Default empty implementation of
emptyStateViewWillShow
Declaration
Swift
func emptyStateViewWillShow(view: UIView)
-
emptyStateViewDidShow(view:)
Default implementationThe call back for when the
emptyStateView
is now shown on screenDefault Implementation
Default empty implementation of
emptyStateViewDidShow
Declaration
Swift
func emptyStateViewDidShow(view: UIView)
Parameters
view
The view that is now shown
-
emptyStateViewWillHide(view:)
Default implementationThe call back for when the
emptyStateView
will be hidden- view: The view that will be hidden
Default Implementation
Default empty implementation of
emptyStateViewWillHide
Declaration
Swift
func emptyStateViewWillHide(view: UIView)
-
emptyStatebuttonWasTapped(button:)
Default implementationThe call back for when the button inside the emptyStateView is tapped
Default Implementation
Default empty implementation of
emptyStateButtonWasTapped
Declaration
Swift
func emptyStatebuttonWasTapped(button: UIButton)
Parameters
button
The button that was tapped
-
emptyStateViewWasTapped(view:)
Default implementationThe call back for when the emptyStateView itself is tapped
Default Implementation
Default empty implementation of
emptyStateViewWasTapped
Declaration
Swift
func emptyStateViewWasTapped(view: UIView)
Parameters
view
The view that was tapped
-
emptyStateViewAnimationCompleted(for:didFinish:)
Default implementationThe call back for when the animation of the emptyStateView is done
- paramaters:
- view: The view which finished animating
- didFinish: Whether the animation finished completely, i.e not interrupted
Default Implementation
Default empty implementation of
emptyStateViewAnimationCompleted
Declaration
Swift
func emptyStateViewAnimationCompleted(for view: UIView, didFinish: Bool)
- paramaters:


Saving and investing often are used interchangeably, but there is a difference.
Wondering whether you should save or invest? The answer depends on your goals and your financial situation.
1. Setting up an emergency fund
Everybody should do their best to build up an emergency savings fund.
The general rule is to have three months’ worth of living expenses saved up in an instant access savings account. This should include rent, food, school fees and any other essential outgoings.
Your emergency fund means you have some financial security if something goes wrong.
2. Keep saving
Now that you’ve got an emergency fund, it’s a good idea to save up at least 10% of your earnings each month (or as much as you can afford).
Set yourself savings goals and put away enough to buy what you want. This could be a house deposit, a wedding, or a trip.
You could also start to think about investing your money.
The only time you shouldn’t save, or invest is if there are more important things you need to do with your money.
For example, getting your debts under control.
Whether or not it makes sense for you depends on your goals – specifically if they are long, short, or medium term.
For your short-term goals, the general rule is to save into cash deposits, like bank accounts.
The stock market might go up or down in the short-term and if you invest for less than five years you might make a loss.
For the medium-term, cash deposits might sometimes be the best answer, but it depends on how much risk you’re willing to take with your money to achieve a greater return on your investment.
For example, if you’re planning to buy a property in seven years and you know you’ll need all your savings as a deposit and don’t want to risk your money, it might be safer to put your money into a savings account.
However, bear in mind that your savings will still be at risk from inflation.
This is where the interest you earn on your savings fails to keep up with the rate of inflation so the buying power of your money is reduced.
On the other hand, if your needs are more flexible, you might consider investing your money if you’re prepared to take some risk with your original capital to try and achieve a greater return on your investment than would be possible by saving alone.
If you’re nearing 30, or older, you might want to consider investing towards your retirement, although other investments can be suitable too.
For longer-term goals, you may want to consider investing because inflation can seriously affect the value of cash savings over the medium and long-term.
The stock market tends to do better than cash over the long-term providing an opportunity for greater returns on any money invested over time.
You can lower the level of risk you take when you invest by spreading your money across different types of investments. This is called diversification.


| Author | Stef Mientki, Copyright © 2002-2006, all rights reserved. |
| Adapted-by | Sebastien Lelong, Rob Hamerling. |
| Compiler | 2.4p |
Performs PWM operations on the PWM10 module (of enhanced midrange) This file is automatically included by pwm_hardware.jal when the target PIC has a PWM10 module.
1. This is a heavy refactoring of the original pwm_hardware.jal (Stef's lib) 2. Partly rewritten for JalV2 version 2.4l and Jallib revision 1171. Reduced memory occupation. Added procedure for lowres PWM. 3. Changes dd October 2012 by Rob Hamerling - added public procedure to set dutycycle with highest resolution (1023 steps). - Make the pwm_set_dutycycle (highres, lowres and unqualified) private (preceeded with an underscore). These procedures will be kept. but with a 'deprecated' warning recommending to use the procedures for relative settings.
No dependency found
var bit*4 _ccp10con_shadow_ccp10m at _ccp10con_shadow : 0
var bit*2 _ccp10con_shadow_dc10b at _ccp10con_shadow : 4
var byte _ccp10con_shadow = 0b0000_0000
var byte _ccpr10l_shadow = 0
pwm10_set_dutycycle_highres(word in steps)
pwm10_on()
pwm10_set_dutycycle_ratio(word in ratio)
pwm10_set_dutycycle(byte in steps)
pwm10_set_dutycycle_lowres(byte in steps)
pwm10_set_dutycycle_percent(byte in percent)
pwm10_set_percent_dutycycle(byte in percent)
pwm10_off()
var bit*4 _ccp10con_shadow_ccp10m at _ccp10con_shadow : 0
2 LSbits of duty cycle
var bit*2 _ccp10con_shadow_dc10b at _ccp10con_shadow : 4
2 LSbits of duty cycle
var byte _ccp10con_shadow = 0b0000_0000
shadow
var byte _ccpr10l_shadow = 0
8 MSbits of duty cycle
pwm10_set_dutycycle_highres(word in steps)
deprecated procedure
pwm10_on()
Purpose: Set PWM on Arguments: none Notes: - duty cycle is restored from shadow registers pin_PWM10_direction should be set to output
pwm10_set_dutycycle_ratio(word in ratio)
Purpose: Set duty cycle in the range 0..1023 PWM steps. Arguments: word - dutycycle ration in range 0..1023 Notes: - The duty cycle will be set to the specified ration of the maximum value for the current PWM frequency and Fosc. Notes: - The resolution is about 1 pro mille The number of available PWM steps can be lower than 1023 with high PWM frequencies or low Fosc values. pin_CCP10_direction should be set to output!
pwm10_set_dutycycle(byte in steps)
Set dutycycle for 10-bits resolution but allowing only 255 PWM steps. This procedure is equivalent to pwm10_set_dutycycle_highres(), but the low order 2 bits of the 10-bits duty cycle are set to 0. This means that only every 4th of the available 1023 steps can be selected and consequently max 255 PWM steps are available. This procedure is for user convenience, allowing to specify an 8 bits value for the duty cycle is for many applications satisfactory. Calling this procedure will also activate PWM. Note: pin_CCP10_direction should be set to output!
pwm10_set_dutycycle_lowres(byte in steps)
Purpose: Set dutycycle with 8-bits resolution allowing 255 PWM steps. The 'steps' argument is the 8-bits absolute value for the duty cycle: * duty<1:0> are the 2 LSbits * duty<7:2> are the 6 MSbits Arguments: byte - duty cycle (allowed range 0..255) Notes: This procedure is particularly suitable with higher frequencies whereby the PWM resolution is limited to 256 steps or less!
pwm10_set_dutycycle_percent(byte in percent)
Purpose: Set duty cycle as a percentage, allowing max 100 PWM steps. The duty cycle will be set to the specified percentage of the maximum for the current PWM frequency and Fosc. Arguments: byte - dutycycle as a percentage (allowed range: 0..100) Notes: - The number of available PWM steps can be lower than 100 with (very) high PWM frequencies and low Fosc. The steps may not all be equal. The lower the actual resolution the bigger the differences between steps may be. pin_CCP10_direction should be set to output!
pwm10_set_percent_dutycycle(byte in percent)
deprecated procedure
pwm10_off()
Purpose: PWM mode off Arguments: none
_pwm10_set_dutycycle_highres(word in steps)
Purpose: Specify the duty cycle by number of PWM steps. The duty cycle is setting is determined by a 10-bits parameter, allowing a resolution of 1023 steps. The 'steps' argument is a (max) 10-bits absolute value for the duty cycle: * steps<1:0> are the 2 LSbits * steps<9:2> are the 8 MSbits Arguments: word - steps cycle (allowed range 0..1023) Notes: - This is a private procedure, not intended for general use. The caller is responsible to specify an acceptable value w.r.t. to the chosen PWM frequency.


Logan Paul backed to send KSI into retirement as rivals prepare for rematch
Logan Paul and KSI clash for a second time in Los Angeles following their draw last year
by Martin Domin, https://www.facebook.com/mirrorfightingLogan Paul will send KSI into retirement when they clash in their rematch on Saturday.
That is the opinion of social media star Ben Phillips who has backed the American to prevail.
Paul and KSI - real name - meet again in Los Angeles more than a year after their first fight ended in a controversial draw.
And prankster Phillips has no doubt his friend will end the feud in concussive style.
"I think there's a danger KSI will get hurt," he told Mirror Fighting. "There's no doubt, you only have to follow Logan to know the guy trains day in and day out.
"He went into the last fight at the last minute; he did well but he's not messing around this time. KSI took his foot off the pedal, did a Spotify music tour and chilled in McDonald's.
"Logan has taken it seriously, you just have to look at the pair of them to see the size difference. He's surrounded by a great team, he's got Shannon Briggs constantly in his ear.
"There are bigger things than KSI but I almost see this as a charity match.
"It's a great pay cheque for KSI and a great retirement. The government hasn't saved up a good pension for him so someone has to
"I think in the third round, KSI is going to take a massive clip and we'll see it play out in the fourth round We'll see if mentally KSI can hang in there or if his team are going to throw the towel in."
The boxing world is divided as to whether Paul and KSI merit headline the Staples Center having turned professional for their sequel.
But Phillips insists the pair deserve their success.
"I'm not surprised by how big Logan has gone for it," he said. "That guy constantly wants to climb mountains and jump hurdles.
"The first fight was crazy; none of us realised how big it was going to be, not that it sold out, but the online presence was crazy
"Some of the boxing community are p***** off because they are two people out of nowhere who haven't worked all their lives for this career
"But they have worked to get respect to get to where they are. They could have done this in rugby, football or netball and it would still be as big as it is.
"I get that it's annoyed a lot of people but you have got to adapt, life is changing on a daily basis. The sport has always about two men in a ring and the strongest man will win, it's still the same now."
- Watch new episodes of Ben Phillips' new YouTube show Brocast here


Each option is a singleton class defined by its Bean properties. These properties are displayed to the user in special nodes in the Explorer, so that they may be examined and modified, possibly triggering live changes.
Special support is provided for "safe" serialization (with better failure modes than the default) for writing options to disk; hierarchical option clusters; and veto-aware options.


Thu Jan 19, 2012
One of the coolest kinds of fictional tech has to be the transparent window, as seen in Minority Report, and by extension, the transparent tablet, à la Avatar. How long will it be before these futuristic interfaces become a reality? Not too long at all, it seems.
Science looks to science fiction when identifying an aesthetic that resonates with people. And it’s becoming apparent that the transparent touch user interface is the next big thing. At CES this year, Samsung showcased the Smart Window:
With space at a premium in our shrinking condos, a window that doubles as a screen seems insanely logical. I can also see touch applications with HUD displays in vehicles and airplanes happening really soon. And how about the transparent tablet? Samsung has that covered too, as seen in this concept video:
Seem far-fetched? Well, the technology, the flexible AMOLED display on show here, is very real - and coming to a future near you.


{% load static i18n %}
{% block CSS_HTML5_SHIM %}
{% comment %}
Shim to make HTML5 elements usable in older Internet Explorer versions
{% endcomment %}
{% endblock %}
{% block CSS_EXTRA %}
{% endblock %}
{% block UPLOAD_FORM %}
{{ input_string }}
{% if not uploader_disabled and upload_url %}
{% block UPLOAD_FORM_BUTTON_BAR %}
{% comment %}
The fileupload-buttonbar contains buttons to add/delete files and
start/cancel the upload
{% endcomment %}
{% comment %}
The fileinput-button span is used to style the file input field as button
{% endcomment %}
{% block UPLOAD_FORM_BUTTON_BAR_ADD %}
{% trans "Add files..." %}
{% block UPLOAD_FORM_BUTTON_BAR_ADD_FILE_INPUT %}
{% comment %}
UPLOAD_FORM_BUTTON_BAR_ADD_FILE_INPUT and FILE_INPUT
control the same block.
FILE_INPUT is the original and shorter block name that has
been kept to function as a convenient alias as well as to
allow backward-compatibility with dependent projects.
Note: Only one should be overriden in the inheriting templates.
{% endcomment %}
{% block FILE_INPUT %}
{% comment %}
The file input for the upload form.
{% endcomment %}
{% endblock %}
{% endblock %}
{% block UPLOAD_FORM_BUTTON_BAR_ADD_EXTRA %}
{% endblock %}
{% endblock %}
{% block UPLOAD_FORM_BUTTON_BAR_CONTROL %}
{% endblock %}
{% block UPLOAD_FORM_BUTTON_BAR_EXTRA %}
{% endblock %}
{% block UPLOAD_FORM_PROGRESS_BAR %}
{% comment %}
The global progress information
{% endcomment %}
{% comment %}
The global progress bar
{% endcomment %}
{% comment %}
The extended global progress information
{% endcomment %}
{% endblock %}
{% endblock %}
{% comment %}
The loading indicator is shown during file processing
{% endcomment %}
{% block UPLOAD_FORM_LINDICATOR %}
{% endblock %}
{% endif %}
{% block UPLOAD_FORM_LISTING %}
{% comment %}
The table listing the files available for upload/download
{% endcomment %}


Welcome to Palowski's and Colburn's Best Cupcake's store in Seattle!!!!
Try The Best Chocolate Cupcake in Seattle!
Try some of our other famous cupcakes!
- Strawberry Cupcakes
- Cookie Monster Cupcakes
- Minions Cupcakes
- Pokemon Cupcakes
- Nemo Cupcakes
If you have any questions feel free to contact
Brian or
Steven.


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