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My Olympic Data
How is Canada performing over the years
What is Canada's medal share throughout the years


GET https://apis.wso2.com/api/am/publisher/v1/apis/{apiId}/mediation-policies/{mediationPolicyId}/content
This operation can be used to download a particular API specific mediation policy.
apim:api_view
apim:mediation_policy_view
GET https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725/content HTTP 1/1
Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8
HTTP 1/1 200 OK
Content-Disposition: attachment; filename="sampleSeq.xml"
Content-Type: application/xml
Content-Length: 166
curl -k -v -X GET 'https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725/content' -H 'Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8'
| Type | Name | Description | Schema | Default |
|---|---|---|---|---|
| Path |
apiId required |
**API ID** consisting of the **UUID** of the API. |
String | |
| Path |
mediationPolicyId required |
Mediation policy Id |
String | |
| Header |
If-None-Match optional |
Validator for conditional requests; based on the ETag of the formerly retrieved variant of the resource. |
String |
| HTTP Code | Description | Schema |
|---|---|---|
200 |
OK. Mediation policy returned. |
|
304 |
Not Modified. Empty body because the client has already the latest version of the requested resource (Will be supported in future). |
|
404 |
Not Found. Requested file does not exist. |
Error |
PUT https://apis.wso2.com/api/am/publisher/v1/apis/{apiId}/mediation-policies/{mediationPolicyId}/content
This operation can be used to update an existing mediation policy of an API.
apim:api_create
apim:mediation_policy_manage
PUT https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725/content HTTP 1/1
Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8
HTTP 1/1 200 OK
Content-Type: application/json
{
"id" : "24cea00d-9f4a-48d5-89b0-cbf01d487782",
"name" : "header_sequence",
"type" : "IN",
"sourceType" : "FILE"
}
curl -k -v -X PUT 'https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725/content' -H 'Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8'
| Type | Name | Description | Schema | Default |
|---|---|---|---|---|
| Form |
type required |
Type of the mediation sequence(in/out/fault) |
String | |
| Path |
apiId required |
**API ID** consisting of the **UUID** of the API. |
String | |
| Path |
mediationPolicyId required |
Mediation policy Id |
String | |
| Form |
file optional |
Mediation Policy to upload |
File | |
| Form |
inlineContent optional |
Inline content of the Mediation Policy |
String | |
| Header |
If-Match optional |
Validator for conditional requests; based on ETag. |
String |
| HTTP Code | Description | Schema |
|---|---|---|
200 |
OK. Successful response with updated API object |
Mediation |
400 |
Bad Request. Invalid request or validation error |
Error |
403 |
Forbidden. The request must be conditional but no condition has been specified. |
Error |
404 |
Not Found. The resource to be updated does not exist. |
Error |
412 |
Precondition Failed. The request has not been performed because one of the preconditions is not met. |
Error |
DELETE https://apis.wso2.com/api/am/publisher/v1/apis/{apiId}/mediation-policies/{mediationPolicyId}
This operation can be used to delete an existing API specific mediation policy providing the Id of the API and the Id of the mediation policy.
apim:api_create
apim:mediation_policy_manage
DELETE https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725 HTTP 1/1
Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8
HTTP 1/1 200 OK
Content-Type: application/json
curl -k -v -X DELETE 'https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725' -H 'Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8'
| Type | Name | Description | Schema | Default |
|---|---|---|---|---|
| Path |
apiId required |
**API ID** consisting of the **UUID** of the API. |
String | |
| Path |
mediationPolicyId required |
Mediation policy Id |
String | |
| Header |
If-Match optional |
Validator for conditional requests; based on ETag. |
String |
| HTTP Code | Description | Schema |
|---|---|---|
200 |
OK. Resource successfully deleted. |
|
403 |
Forbidden. The request must be conditional but no condition has been specified. |
Error |
404 |
Not Found. Resource to be deleted does not exist. |
Error |
412 |
Precondition Failed. The request has not been performed because one of the preconditions is not met. |
Error |
GET https://apis.wso2.com/api/am/publisher/v1/apis/{apiId}/mediation-policies/{mediationPolicyId}
This operation can be used to retrieve a particular API specific mediation policy.
apim:api_view
apim:mediation_policy_view
GET https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725 HTTP 1/1
Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8
HTTP 1/1 200 OK
Content-Type: application/json
{
"id" : "24cea00d-9f4a-48d5-89b0-cbf01d487782",
"name" : "header_sequence1",
"type" : "IN",
"sourceType" : "FILE"
}
curl -k -v -X GET 'https://localhost:9443/api/am/publisher/v1/apis/a8f0fb89-edf9-484c-b937-036b088f287d/mediation-policies/624b9f7d-bfaf-484b-94cc-e84491f5d725' -H 'Authorization: Bearer ae4eae22-3f65-387b-a171-d37eaa366fa8'
| Type | Name | Description | Schema | Default |
|---|---|---|---|---|
| Path |
apiId required |
**API ID** consisting of the **UUID** of the API. |
String | |
| Path |
mediationPolicyId required |
Mediation policy Id |
String | |
| Header |
If-None-Match optional |
Validator for conditional requests; based on the ETag of the formerly retrieved variant of the resource. |
String |
| HTTP Code | Description | Schema |
|---|---|---|
200 |
OK. Mediation policy returned. |
Mediation |
304 |
Not Modified. Empty body because the client has already the latest version of the requested resource (Will be supported in future). |
|
404 |
Not Found. Requested Document does not exist. |
Error |
406 |
Not Acceptable. The requested media type is not supported |
Error |


--- title: "Moderation and Heterogeneous Effects" subtitle: "Our first steps in moderation with R" type: book weight: 5 output: blogdown:html_page: theme: journal highlight: tango df_print: paged toc: yes toc_float: collapsed: false ---
Welcome to our tenth tutorial for the Statistics II: Statistical Modeling & Causal Inference (with R) course.
During this week’s lecture you were introduced to Moderation and Heterogeneous Effects.
In this lab session we will:
lm()
margins::margins()
and predictive margins with ggeffects::::ggeffect()
dplyr::case_when()
The country of Absurdistan has had an ongoing civil conflict for the past 60 years. The fighting between national government forces and guerrilla members from the National Revolutionary Army (NRA) has lead to more than 200,000 deaths, 8 million internally displaced persons, and countless victims between 1960 to 2020.
The civil war in Absurdistan has been a low-intensity asymmetric war. The legacies of the conflict have been bore largely by regions in the periphery of the country. Large cities and industrial regions have been spared from most of the fighting.
The government and the leadership of the NRA reached a peace agreement a couple of months ago; however, the agreement has been received poorly by the general population of Absurdistan. The opposition party the Undemocratic Center (UC) has allegedly ran campaigns misrepresenting the contents of the agreement in partisan media outlets and social media.
The Special Envoy for Peace has established a taskforce to design a strategy to increase support for the peace agreement. Many in the taskforce suspect that if the public were properly informed about the agreement reached, the levels of support would be higher.
You are hired as a scientific consultant for the taskforce. You run a survey experiment on a sample of 1000 respondents. You randomly assign respondents to watch an educational 2 minute video about the peace agreement.
set.seed(42) #for consistent results
library(dplyr) # to wrangle our data
library(tidyr) # to wrangle our data - pivot_longer()
library(ggplot2) # to render our graphs
library(readr) # for loading the .csv data
library(janitor) # for data management and tabyl()
library(kableExtra) # to render better formatted tables
library(stargazer) # for formatting your model output
library(margins) #for calculating MARGINAL/PARTIAL EFFECT
library(ggeffects) # easily calculating PREDICTIVE MARGINS
moderation_df <- readr::read_csv("https://raw.githubusercontent.com/seramirezruiz/hertiestats2/master/data/moderation_df.csv") # simulated data
names(moderation_df) # to check the names of the variables in our data
## [1] "subject_id" "treatment" "victim_verbose"
## [4] "victim" "female" "female_verbose"
## [7] "support_thermometer"
Our dataset moderation_df, contains the following information:
subject_id
: A unique numeric identification for each respondenttreatment
: A binary marker for treatmentvictim_verbose
: A verbose binary marker of the respondents’ victimhood status (Not a Victim-Victim)victim
: A numeric binary marker of the respondents’ victimhood status (0-1)female
: A numeric binary marker of the respondents’ sex (0-1)female_verbose
: A verbose binary marker of the respondents’ sex (Male-Female)support_thermometer
: A continuous measure of support for the agreement (0-100)We can use what we have learned about the janitor::tabyl() function, to check who was in our sample:
moderation_df %>%
janitor::tabyl(treatment) %>%
knitr::kable(col.names = c("Treatment", "N", "Percent, %")) %>% # create kable table
kableExtra::kable_styling() # view kable table
| Treatment | N | Percent, % |
|---|---|---|
| 0 | 500 | 0.5 |
| 1 | 500 | 0.5 |
moderation_df %>%
janitor::tabyl(treatment, victim_verbose) %>%
janitor::adorn_totals(c("row", "col")) %>%
knitr::kable(col.names = c("Treatment", "Not a victim", "Victim", "Total")) %>% # create kable table
kableExtra::kable_styling() %>% # view kable table
kableExtra::add_header_above(c("", "Victimization status" = 2, ""))
| Treatment | Not a victim | Victim | Total |
|---|---|---|---|
| 0 | 250 | 250 | 500 |
| 1 | 250 | 250 | 500 |
| Total | 500 | 500 | 1000 |
ggplot(moderation_df, aes(x = support_thermometer)) +
geom_density(fill = "#af8dc3", alpha = 0.5) +
theme_minimal() +
labs(x = "Support thermometer",
y = "Density")
What do we see in this graph?
ggplot(moderation_df, aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
theme_minimal() +
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom") +
scale_fill_manual(name = " ", # changes to fill dimension
values = c("#a7a8aa", "#cc0055"),
labels = c("Control", "Treatment"))
What do we see through these distributions?
ggplot(moderation_df, aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
facet_grid(treatment~victim_verbose) +
theme_bw() +
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom") +
scale_fill_manual(name = " ", # changes to fill dimension
values = c("#a7a8aa", "#cc0055"),
labels = c("Control", "Treatment"))
What patterns do we see here?
During this week’s lecture, we learned that we can explicitly model heterogeneity in treatment effects for subgroups. Thus, we can address the tension between having to do inference at the group level, and the recognition of individual differences.
The analysis of heterogeneity can be very important for the design of our strategy. There are competing theories about the effects of conflict victimization on political behavior and attitudes. Some of the literature points to victims developing pro-social attitudes, while others suggest that victims become intransigent towards out-groups.
Could factual information about the peace agreement be received differently by victims and non-victims?
Heterogeneous treatment effects are usually estimated with regression models that include an interaction between the treatment and the moderator. In our case, the formula would look like this:
\[Y_{i} = β_0 + β_1D_{i} + β_2Victim_{i} + β_3D_i * Victim_{i}+ ϵ_i\]
or in lm()
terms (same result):
lm(outcome ~ treatment + moderator + (treatment*moderator))
lm(outcome ~ treatment + moderator + treatment:moderator)
lm(outcome ~ treatment * moderator)
Think of the switch logic posed by Prof. Munzert
We will move forward by creating two models:
support_thermometer
on treatment
.treatment
and victim
naive_model <- lm(support_thermometer ~ treatment, data = moderation_df)
stargazer::stargazer(naive_model, type = "html")
| Dependent variable: | |
| support_thermometer | |
| treatment | 18.898*** |
| (1.026) | |
| Constant | 35.055*** |
| (0.725) | |
| Observations | 1,000 |
| R2 | 0.254 |
| Adjusted R2 | 0.253 |
| Residual Std. Error | 16.220 (df = 998) |
| F Statistic | 339.360*** (df = 1; 998) |
| Note: | p<0.1; p<0.05; p<0.01 |
What does this model tell us?
The naive model suggests that the subjects that the support for the peace agreement is about 18.9 percentage points higher on average for the subjects that watched the educational video. We suspect, however, that the video may affect differently victims from non-victims of the conflict.
ggplot(moderation_df, aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
theme_minimal() +
geom_vline(xintercept = 35.055, linetype = "longdash", color = "#a7a8aa") + #D=0 (just beta0)
geom_vline(xintercept = 35.055 + 18.898, linetype = "longdash", color = "#cc0055") + #D=1 (beta0+beta1) +
geom_text(aes(label = "ß0", x = 35.055 + 3, y = 0.04), color = "#a7a8aa") + # we add the 3 to repel from the line
geom_text(aes(label = "ß0 + ß1", x = 35.055 + 18.898 + 6, y = 0.04 ), color = "#cc0055") + # we add the 6 to repel from the line
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom") +
scale_fill_manual(name = " ", # changes to fill dimension
values = c("#a7a8aa", "#cc0055"),
labels = c("Control", "Treatment"))
Following any of the different formats renders the same results.
interaction_model <- lm(support_thermometer ~ treatment + victim + (treatment*victim), data = moderation_df)
interaction_model_2 <- lm(support_thermometer ~ treatment + victim + treatment:victim, data = moderation_df)
interaction_model_3 <- lm(support_thermometer ~ treatment*victim, data = moderation_df)
stargazer::stargazer(interaction_model, interaction_model_2, interaction_model_3, type = "html")
| Dependent variable: | |||
| support_thermometer | |||
| (1) | (2) | (3) | |
| treatment | 8.013*** | 8.013*** | 8.013*** |
| (0.776) | (0.776) | (0.776) | |
| victim | 14.256*** | 14.256*** | 14.256*** |
| (0.776) | (0.776) | (0.776) | |
| treatment:victim | 21.771*** | 21.771*** | 21.771*** |
| (1.097) | (1.097) | (1.097) | |
| Constant | 27.927*** | 27.927*** | 27.927*** |
| (0.549) | (0.549) | (0.549) | |
| Observations | 1,000 | 1,000 | 1,000 |
| R2 | 0.787 | 0.787 | 0.787 |
| Adjusted R2 | 0.786 | 0.786 | 0.786 |
| Residual Std. Error (df = 996) | 8.673 | 8.673 | 8.673 |
| F Statistic (df = 3; 996) | 1,227.193*** | 1,227.193*** | 1,227.193*** |
| Note: | p<0.1; p<0.05; p<0.01 |
What does this model tell us?
moderation_df %>%
dplyr::group_by(treatment,victim_verbose) %>%
dplyr::mutate(avg_support = mean(support_thermometer)) %>%
ggplot(., aes(x = support_thermometer, fill = factor(treatment))) +
geom_density(alpha = 0.5) +
geom_vline(aes(xintercept = avg_support), linetype = "longdash") +
facet_grid(treatment~victim_verbose) +
theme_bw() +
labs(x = "Support thermometer",
y = "Density",
fill = "Treatment") +
theme(legend.position = "bottom") +
scale_fill_manual(name = " ", # changes to fill dimension
values = c("#a7a8aa", "#cc0055"),
labels = c("Control", "Treatment"))
For this portion, we are interested in marginal/partial effects, which we will extract through the margins()
function from the margins
package.
Some packages in R aimed at rendering marginal effects do render the predictive margins instead. For the purposes of the class, when asked to render marginal or partial effects you are expected to render them as introduced in the lecture (i.e., \(\frac{\partial Y_i}{\partial {D}_i}\)). When asked for this, you will utilize margins::margins()
.
You can check the documentation here. The syntax for the margins()
function for extracting partial effects of the treatment at different levels of the moderator is the following:
margins::margins(name_of_your_model, variables = "treatment_var", at = list(moderator_variable = c("value1", "value2", "value3"))
Let’s say we are interested in the marginal/partial effect of our video treatment for victims and non-victims. We would do:
summary(margins::margins(interaction_model, variables = "treatment", at = list(victim = c(0,1))))
## factor victim AME SE z p lower upper
## treatment 0.0000 8.0125 0.7757 10.3288 0.0000 6.4921 9.5330
## treatment 1.0000 29.7831 0.7758 38.3895 0.0000 28.2626 31.3037
pe_margins <- margins::margins(interaction_model, variables = "treatment", at = list(victim = c(0,1)))
pe_plotting <- summary(pe_margins) %>% #NOTE we use the summary output, instead of the margins object
dplyr::select(victim, AME, lower, upper) %>% # you will need to adapt this based your moderator
dplyr::mutate(victim_labels = ifelse(victim == 1, "Victim", "No Victim")) # you may not need this to create labels for the assignment
ggplot(pe_plotting, aes(x = victim_labels,
y = AME)) +
geom_point(size = 1.5) +
geom_segment(aes(x = victim_labels, xend = victim_labels, y = lower, yend = upper), size = 0.5) + # render whiskers from confidence intervals
theme_minimal() +
scale_y_continuous(limits = c(0,45)) + # you may need to change the limits for your plots based on the specific effects of your application
labs(x = "Respondent status\n",
y = "\nPartial effect of educational video",
caption = "Note: You can utilize it to describe what the plot illustrates during your assignment.") +
coord_flip() # to flip the plot
For this portion, we are interested in predictive margins. In here, our interest is to return the expectation for each level of a predictor. We will extract this through the ggeffects()
function from the ggeffects
package. You can check the documentation here. The syntax is the following:
ggeffects::ggeffect(name_of_your_model, terms = c("termA", "termB"))
Let’s say we are interested in the predictive margins for all out victim and treatment permutations. We would do:
ggeffects::ggeffect(interaction_model, terms = c("victim","treatment"))
## # Predicted values of support_thermometer
## # x = victim
##
## # treatment = 0
##
## x | Predicted | 95% CI
## ------------------------------
## 0 | 27.93 | [26.85, 29.00]
## 1 | 42.18 | [41.11, 43.26]
##
## # treatment = 1
##
## x | Predicted | 95% CI
## ------------------------------
## 0 | 35.94 | [34.86, 37.02]
## 1 | 71.97 | [70.89, 73.04]
In this exercise we will meet a very important function from dplyr
, dplyr::case_when()
. This function allows us to vectorize multiple ifelse() statements. The syntax is the following:
dplyr::case_when(condition ~ what to do if met)
Let’s see it at play.
extracted_me <- ggeffects::ggeffect(interaction_model, terms = c("victim","treatment")) %>%
dplyr::mutate(group_labels = dplyr::case_when(x == 1 & group == 1 ~ "Victim (1) - Treatment (1)",
x == 1 & group == 0 ~ "Victim (1) - Treatment (0)",
x == 0 & group == 1 ~ "Victim (0) - Treatment (1)",
x == 0 & group == 0 ~ "Victim (0) - Treatment (0)"
)) # adding labels to (x,group) combinations for the plot
extracted_me
ggplot(extracted_me, aes(x = group_labels,
y= predicted,
fill = x,
alpha = group
)) +
geom_bar(stat = "identity") +
geom_point(size = 1.5) +
geom_segment(aes(x = group_labels,
xend = group_labels,
y = conf.high,
yend = conf.low), size = 0.5) + # render whiskers from confidence intervals
theme_minimal() +
labs(x = "\nRespondent status",
y = "Predictive margins",
fill = "Treatment",
caption = "Note: You can utilize it to describe what the plot illustrates during your assignment.") +
theme(legend.position = "note") +
scale_alpha_manual(values=c(0.6, 1))
After conducting your experiment, you report back to the taskforce. Based on your results, you suggest that the educational videos may be a useful tool to encourage the wider public to hold a warmer opinion about the peace agreement. You also tell the taskforce that, although the videos have an average positive effect, they affect with a higher intensity victims of the conflict. You suggest to develop alternative strategies to tackle the non-victims, so that they do not fall through the cracks.


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Little,
Jr#
Date
of
collection:
July
28,
1950
Collector’s
No...J13S12-
01029134
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Explore the rest of my Github page to find out more about me and what it is I have been working on!
Find Out MoreMy name is Brandon Normand and I am currently an undergraduate at the California Polytechnique State University, San Luis Obispo. I am studying Economics with a concentration in Financial Management and Minors in Statistics and Actuarial Science. I enjoy the outdoors and exploring the various hidden gems San Luis Obispo has to offer.
Let's take a look!I am well adept in Python and Java.
I am constantly looking forward to working with new people on new projects. I always make myself available, so don't hesitate!
Staying ahead of schedule is very important to me and I strive to never fall behind schedule. You can count on me!
I take personal and work relationships seriously and am always excited to welcome someone new to the team.
Please feel free to reach out to me with questions on any of my recent projects, or if you believe we would work well together in some capacity. I look forward to hearing from you!
(310)405-1044


In as few characters as possible this page demonstrates how to wire the Pretty Diff application to third party HTML in a browser. Please not this guide is for directly using Pretty Diff in a browser and not through a Node.js application.
First we need to inject the necessary code into the page. This can be done as simply as using the code below or by directly integrating Pretty Diff as an object of some existing application.
<script src="js/browser.js" type="application/javascript"></script>
I have packaged everything into a single file. This contains the parser, all the Pretty Diff application, and the generated option list with default values.
Configuring the application is as simple as creating the options object and passing that object into the application.
let prettydiff = window.prettydiff.mode,
options = {source:"var a=1;",wrap:80},
myResult = prettydiff(options);
Please note that while that does work it is risky. I always recommend building options off the default options object for more predictable options. See the larger following example.
Here is an interactive demo with a demo wiring harness.
(function () {
// first the dom interaction is defined with a target and handler
let button = document.getElementsByTagName("button")[0],
execute = function () {
// inside the application we gather the application
let prettydiff = window.prettydiff,
// this provides all options set to their default values for safety
options = prettydiff.defaults,
output = "";
// here is where we overwrite the default options with custom values
options.api = "dom";
options.language = "auto";
options.lexer = "script";
options.mode = "beautify";
options.source = document.getElementById("input").value;
// this where the application executes and the string output is assigned
output = prettydiff.mode(options);
// output the generated string into the dom
document.getElementById("output").value = output;
};
// this uses a click event on a button
// for more excitement you can assign the handler to the input textarea's keyup event
button.onclick = execute;
}());


WHAT DREAMS MAY COME
USA. 1998. Director - Vincent Ward, Screenplay - Ron Bass, Based on the Novel by Richard Matheson, Producers - Barnet Bain & Stephen Simon, Photography - Eduardo Serra, Music - Michael Kamen, Visual Effects Supervisor - Ellen M. Somers, Visual Effects - Digital Domain (Supervisor - Kevin Mack) & POP Film and POP Animation (Supervisor - Stuart Robertson), Painted Visual Effects - Mass Illusions (Supervisors - Nicholas Brooks & Joel Hynek), Digital Visual Effects - CIS Hollywood (Supervisor - Dr Ken Jones), Special Effects Supervisor - Roy Arbogast, Makeup Effects - Masters FX Inc (Supervisor - Todd Masters), Production Design - Eugenio Zanetti. Production Company - Interscope Communications/MetaFilmics. Robin Williams (Christy Nielsen), Cuba Gooding Jr (Albert Lewis), Annabella Sciorra (Annie Nielsen), Max Von Sydow (The Tracker), Jessica Brooks Grant (Marie Nielsen), Josh Paddock (Ian Nielsen), Rosalind Chao (Leona)
Plot: Not long after the death of his two children, Christy Nielsen is killed by a colliding car while going to aid a car crash victim. He finds himself in the afterlife which is not any traditional Heaven or Hell but a landscape of one's own imagination - he having composed his out of the classical artworks his wife Annie restored - and where one can inhabit whatever body they choose. But then comes the news that Annie, unable to handle the loss, has committed suicide. Here suicides are not condemned of Hell but a world wrapped in their own self-absorption. Christy ignores all warnings that he will be dragged down into her closed-off world to venture in and save her.
New Zealander Vincent Ward is one of the most fascinating directors at work anywhere in the world at the moment. Ward trained as an artist at Canterbury University (only a few departments away from me) before turning to film- making. As a director he has an artist's fascination with the visual image - one cannot think of any other director in the world who would model the entire look of a film on the work of classical artists. His first feature film ‘Vigil' (1985) is an extraordinarily composed poem written in landscape and light which almost entirely circumvents narrative to work on a level of pure imagery alone. The Cannes-acclaimed ‘The Navigator: A Mediaeval Odyssey' (1988) was a time travel fantasy that Ward painted in the imagery of artists like Bruegel and Bosch that offered a haunting outsider's look in on the alienness of the 20th Century.
Ward lost the plot somewhat with 1992's ‘Map of the Human Heart', an Innuit romance where his fascination with imagery neglected the film's crucial emotional core. And since ‘Map' Ward's output has been erratic - he caught among the revolving door of directors attached to ‘Alien3' and only ending up with story credit and then being forced to direct commercials and take bit parts in films like `Leaving Las Vegas' (1995) and ‘One Night Stand' (1997) in order to stay off the unemployment line.
But ‘What Dreams' is Ward's return to form and his most mainstream release yet. It is an adaption of the 1984 novel by acclaimed genre novelist/screenwriter Richard Matheson, author of the likes of ‘The Incredible Shrinking Man', ‘Duel', most of Roger Corman's Poe films in the 1960s, and numerous ‘Twilight Zone' and ‘Star Trek' episodes, among others. Ward's work on the film is quite extraordinary. He lights the screen up with impossible vistas of the imagination - a vast library where gondoliers drift through canals between the bookshelfs; Williams having to walk across a sea of living faces as he enters Hell; valleys and oceans filled with castles and cities that have been constructed out of works by classical masters amongst which people nonchalantly fly; houses casually sitting amidst the Gothic arches of the roof of an inverted cathedral. In an extraordinary synthesis of artistic vision and cutting edge digital effects technology, Ward gets to literally paint on film. In the most wondrous section Robin Williams steps into a landscape that is a Van Gogh painting come to life, slipping and sliding through the paint of some of the giddiest and brightest oil colours imaginable. The sheer breadth of Ward's vision is astounding.
One of Ward's failings in the past has been a fascination with imagery at the expense of emotional soul. But thanks to a good cast and an especially strong script, he has ample compensation here (apart from Annabella Sciorra whose bland performance makes one wonder what Williams's love is really all about). The film's humanist reworking of the Orpheus and Eurydice legend at the climax is emotionally powerful. A landmark achievement.
Copyright 1998 Richard Scheib
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


git -at me | discover open sourceFor Open Source Eyes Only Snowden. Manning. Lavabit. Prism. NSA. Big Brother. You've seen the news - government snooping is real. If you're wondering, "How can I protect my sensitive information from prying eyes?" The answer is you can't, not 100% - but you can make it MUCH harder to decipher. Enter Steganography & Robert Winslow's Plainsight. Translated from Greek, steganography literally means concealed writing. And that's exactly what Plainsight does. It conceals your private information as an innocuous passage of text. Plainsight uses a plaintext cipher or key, say Ulysses by James Joyce to mask your message. So as long as you and your intended recipient both have the cipher, you can communicate safely.*
Orignal message:
The British are coming!!! Coded message: man with him the high barbacans birds. my tooraloom name is Ursula. told me liked make it brown. be drowned. pity a not that had drunken be drowned something. No. have got me on the sea to my sweeties? right and left arm round the whowhat feeling)_ as the others and down the needful all the same old Plainsight is written in Python, and you can install it via pip [sudo pip install plainsight]. So what are you waiting for? [View] [Star] [Fork] *You can't protect anything once it's been intercepted. Especially if you have the cipher. That's why the Nazis used water soluble ink in their codebooks - easy to destroy in the face of capture! The two most important rules of cryptography are, 1. Choose a strong cipher (the NSA owns supercomputers bro) and 2. Don't let it fall into the wrong hands (avoid sexpionage / Keri Russell). That's all folks, hand in a fine tang the paper and then at the quaint little man he wants me and he serving there were on the bench now. Quite hide get on your nerves bit too heavy thought, said, and Tell your friends about git -at me. In fact, make them sign up right now. And please send any feedback / ideas to<EMAIL_ADDRESS>or @gitatme. ~Neal |


File.h file A file. Contents Reference Functions Functions auto foo() -> int A foo. Function documentation int foo() A foo. Returns Does not return anything. Text.A quote that should not cause assertion about an unclosed section


WQMY
55 Urban School Finance - Institute for Urban and Minority ...
Urban School Financing Problems. Despite the problems of obtaining clear national statistics comparing urban with nonurban school ?nance, few educators .
http://iume.tc.columbia.edu/i/a/document/15372_Digest_55.pdf
| ensino a dist ncia/associated master inspectors portland or/ gruber kristin m md |
|
|---|---|
| zarelli carson street pittsburgh pa | Williamsport |
| Branding | MyNetworkTV urban school financial problems |
| the six blind man | urban school financial problems: 29 (building 1 1250 diorama) & breast reconstruction surgery vinings ga-DT 45.3 (UHF) |
| beachwood barbeque in seal beach | see article |
| Owner | New Age Media, LLC Urban School Finance: The Quest for Equal Educational ... - ERIC |
| First air date | December 30, 1988 |
| thermostat for a water heater | MYNetworkTV |
| myspace midnitght car layouts | WOLF-TV, three monitor video cards |
| thermostat for a water heater | WILF (1988-2006) |
| Former channel number(s) | litigation dealing with urban school finance problems - HeinOnline |
| bravo good for you | uss rainier cruisebook version 7.11 (1988-1998) the six blind man / lemons contaminated sickness restaurants (1998-2006) |
| fort mason festival pavilion | 50 marty in mario cart 64 420 kW (WOLF-DT3) |
| fiction books on cancer | 243 m 488 m (WOLF-DT3) |
| young girls age 10 | 52075 73375 (WOLF-DT3) |
| Transmitter coordinates | pittsford mendon high school reunion iron condor option defined (WOLF-DT3) |
SCHOOL FINANCE Raising Questions for Urban Schools
tioners know very little about how their schools are funded. The purpose of this article is to ad- dress the financial issues related to urban schools and the .
http://eus.sagepub.com/content/37/1/3.full.pdf
POLICY INITIATIVES TO IMPROVE URBAN SCHOOLS
They are worth debating because so many of the problems in urban schools are . good ideas than they are to the availability of adequate financial resources.
http://schoolmatch.com/articles/EUSMAY03.htm
Contents |
[home] History
Differences in Rural and Urban Schools: Issues for Policymakers
differences between rural and urban schools. How do . also the special needs and problems of rural schools? . attempted to lessen the financial impacts of .
http://www.uky.edu/Ag/AgEcon/pubs/res_other/schlurvr.pdf
Urban School Finance: The Quest for Equal ... - ERIC Digests
URBAN SCHOOL FINANCING PROBLEMS . Third, even when state responsibility for city school district budgets is growing, financial support may not keep up .
http://www.ericdigests.org/pre-9213/urban.htm
Urban School Finance: - UM.Sitemaker
Urban School Finance: Although in recent years per pupil expenditures in many ( but not all) urban school systems have matched those of more affluent suburbs, .
http://sitemaker.umich.edu/mitchellyellin.356/files/urban_school_finance.doc
Public Schools Funding Issues - Wisconsin Alliance for Excellent ...
schools receiving state financial assistance starting with the 1993- . causing budgetary problems. . Between May 1 and June 30, 1997 the Center for Urban .
http://www.excellentschools.org/resources/RevCapsImpactSummary.pdf
School Finance - Texas State University
Does Proposition 1 solve the school finance crisis? Surely not. Is it helpful? Absolutely. It gives the legislature one more tool with which to address the problem.
http://www.txstate.edu/cpm/hobby/Publications/contentParagraph/01/content_files/file48/School_Finance.pdf
Can Catholic Schools Be Saved? > Publications > National Affairs
Did their situation suggest a much broader problem that urban Catholic . to hear but that everyone silently expected: The schools' financial challenges had .
http://www.nationalaffairs.com/publications/detail/can-catholic-schools-be-saved
State Funding of Urban Education Under the Modern School ... - ERIC
This paper first examines the present problems of urban school finance to ascertain why urban adjustments are necessary today in the new school finance .
http://www.eric.ed.gov/ERICWebPortal/recordDetail?accno=ED126623
The Condition of Urban School Finance - National Center for ...
Resource Allocation in. Urban Schools. Selected. Papers in. School. Finance . district-level data, the problem is compounded by differences in types of districts.
https://nces.ed.gov/pubs98/ballou.pdf
Framing Urban School Challenges: The Problems to Examine
In this three-part series, we present an overview of the issues most relevant to the . Given their complexity and expressed challenges, however, urban school . In H. F. Ladd & E. B. Fiske (Eds.), Handbook of research in education finance .
http://www.rtinetwork.org/learn/diversity/urban-school-challenges
Urban Education - Students and Structure, Special Challenges ...
This problem is confounded by the fact that many urban districts must lay off teachers to . Urban school districts often receive substantially less annual financial .
http://education.stateuniversity.com/pages/2524/Urban-Education.html
NCEF Resource List: Urban School Facility Issues
Information on urban school facilities issues including funding challenges, equity . TIF financial support for school construction projects is uneven and polarized .
http://www.ncef.org/rl/urban_issues.cfm
[2001 honda accord oil type] Digital channels
| Channel | Name | roadtrip an best places and california | super lotto california usa lottery results | Programming |
|---|---|---|---|---|
| 53.1 | urban school financial problems DT | joint heavy lift helicopter | seattle festivals in july | Main urban school financial problems programming / MyNetworkTV |
| 53.2 | WOLF DT | remote codes for vcr dvd combo | day larine movie actress | Simulcast of campaign david vitter aegis higher ground |
| 53.3 | WSWB DT | 480i | 4:3 | Simulcast of 2001 honda accord oil type |
The Stealth Inequities of School Funding - Center for American ...
poverty urban district with a large commercial . While these states may have their own set of school finance problemssuch as low overall spending on public .
http://www.americanprogress.org/wp-content/uploads/2012/09/StealthInequities.pdf
[tell me you love me series] References
[butler creek hot lips loader ebay] External links
- breast reconstruction surgery vinings ga
- a a milne temperment test
- put de lime in the coconut
- to to increase wireless headphone range
- wholesale rc gas cars
- childrens attendance at funerals
|
|


This is a auto portfolio creation website.Demo of portfolio is provided in the page.

There are tons of benefits to building your own portfolio website, including:
1)Increased visibility, credibility and authority in your industry
2)When someone searches your name in Google, your website appears at the top
3)Hiring managers and clients can find you, instead of you trying to find them
4)Gives you a chance to show off your creativity and personality
5)Shows that you’re a professional, which means employers and clients are more likely to trust you and your work


Page 1 of 4
Donations
Posted:
Sun Dec 31, 2006 5:07 pm
by Karl G.
Thank you all for your generous donations! Remeber:
- Donations are recorded and will be credited as account time
- All donations are used to purchase content, server space and to assist in other game-related expenses
- You don't have to donate all at once to reach a goal
- $10 - Name a guard
- $20 - Name a merchant
- $35 - Name a boss
- $50 - Name an item
- $75 - Name 3 items
- $100 - ?
To see who has donated and how much, go here:
http://www.unseenstudios.com/volucris/w ... te_support
Posted:
Mon Jan 01, 2007 11:09 am
by Karl G.
[updated]
Posted:
Mon Jan 01, 2007 11:18 am
by thadiusofx3
Lol don't credit me up there my donation was a joke, I'll donate for real when i get my paycheck.
Posted:
Mon Jan 01, 2007 11:49 am
by Karl G.
haha okay...I'll just add to it when you do donate :-p
Posted:
Mon Jan 01, 2007 11:53 am
by thadiusofx3
Ok Lord Karl =P
Posted:
Mon Jan 01, 2007 7:47 pm
by stoody
Is there any other way to donate? I want to but my paypal acct is frozen.
Posted:
Mon Jan 01, 2007 9:42 pm
by Karl G.
stoody:
At this time, there is not another way to donate; however, can't you can donate using a credit or debit card without a paypal account?
Posted:
Tue Jan 02, 2007 9:48 am
by stoody
I tried, wouldn't let me. Probably cause my card # is tied to the account.
Posted:
Wed Jan 03, 2007 9:35 am
by Delurium II
sent 10 bucks your way. hope it helps!
Posted:
Wed Jan 03, 2007 10:17 am
by Karl G.
Thanks! I've received and recorded it.
Posted:
Thu Jan 04, 2007 12:31 pm
by Serenity
I may be sending more money your way. when I get home from schoolage. its annoying me right now. Kinda feel honored to help out as much as I have, to help this project secceed. I may not know any programming or equations for other stuffs but I sure am going to pull my weight around with what I can do. (mainly sketch and donate, look around for help.) I shall continue my efforts to bring this project to seccess
Posted:
Thu Jan 04, 2007 1:54 pm
by kuba
lol @ baby seal clubbin
i hope that guard is nearby water and has a club equipped
Posted:
Thu Jan 04, 2007 3:41 pm
by Karl G.
way ahead of you kuba
Posted:
Thu Jan 04, 2007 4:43 pm
by kuba
^^LOL
Posted:
Fri Jan 05, 2007 4:28 pm
by Ashlar
I put a bunch of stuff up on ebay that I don't need, probably around $200 worth. I'll donate a certain percentage of it to the project as I am really liking what I'm seeing. The more I see, the more you get.
Posted:
Fri Jan 05, 2007 9:55 pm
by Karl G.
Awesome
I'll be sure to host more galleries and movies ASAP
Posted:
Sat Jan 06, 2007 10:38 am
by thadiusofx3
I just got a programming job that should pay pretty well, but I'm also in the process of moving (had an meanie for a roomate) and that costs alot, but when i get on my feet I will definitely donate atleast 100.
Posted:
Sat Jan 06, 2007 10:58 am
by Vitriol
I will probably be sending you some more money at some point karl. I'm just penny-pinching for DirectX10.
Posted:
Sat Jan 06, 2007 11:19 am
by kuba
wow over $100 in donations so far, not bad at all.
Posted:
Sat Jan 06, 2007 6:16 pm
by 9sam1
I got a question. i have 0 dollars in my paypal account. Can i still donate ? will it just take it out of my bank account instead or what?
Posted:
Sat Jan 06, 2007 7:26 pm
by Vitriol
9sam1 wrote:I got a question. i have 0 dollars in my paypal account. Can i still donate ? will it just take it out of my bank account instead or what?
if you have it set up to do that. I do. You need to specify to paypal what your bank account is.
Posted:
Sun Jan 07, 2007 9:51 pm
by Ender
I'll be sending some cash sometime this week, and then again when my tax return comes.
Posted:
Tue Jan 09, 2007 1:35 am
by CanadianGradeEh
Actually I'm thinkin' more along the lines of $30 next time instead of $20 since the idea of naming an idea is very appealing
Posted:
Sun Jan 28, 2007 2:17 pm
by Ashlar
sent ten bucks. you know what they say. it trickles before it floods.
hrm, as for a guard name..Sketches.
Posted:
Tue Jan 30, 2007 7:42 am
by Karl G.
Thank you to all of you who have donated!
If you donated recently and don't see yourself listed yet, fear not--I have received a few donations in the past week that I haven't been able to record yet.
Karl


Class Classes
Methods summary
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Flir Image Extractor CLI¶
The email address attached to this on PyPi may not be monitored, open issues on the GitHub repo to ensure a response
Feel free to submit any pull requests or issues, this is in active development. Also let me know if you are successful in using this on cameras not listed below.
FLIR® thermal cameras like the FLIR ONE® include both a thermal and a visual light camera. The latter is used to enhance the thermal image using an edge detector. The resulting image is saved as a jpg image but both the original visual image and the raw thermal sensor data are embedded in the jpg metadata.
This Python CLI that allows you to extract the original photo and thermal sensor values converted to temperatures, normalize the temperature range and output the photos to different color maps.
Requirements and Install¶
This tool relies on exiftool
. It should be available in most Linux distributions (e.g. as perl-image-exiftool
in Arch Linux or libimage-exiftool-perl
in Debian and Ubuntu). Links for downloading the Mac version and more information is available on the ExifTool site.
To install on Linux:
sudo apt update
sudo apt install exiftool
To install exiftool
on Windows for use in this CLI, download the exiftool
windows executable from here. Extract exiftool(-k).exe
and rename to exiftool.exe
. Copy this executable to C:\Windows
on your computer. You will need admin permissions to do this. Doing this will make exiftool
available to the CLI.
It also requires other python packages, matplotlib, numpy and pillow, which are installed when the CLI is installed through pip.
Once you have install exiftool, you can install the CLI using pip:
pip install flirimageextractor
On windows you may need to use:
python -m pip install flirimageextractor
To update to the latest version of the CLI use this command. The first time you install the latest version will be automatically downloaded.
pip install --upgrade flirimageextractor
Usage¶
You can start the CLI using the terminal.
flirimageextractor
`
Resulting Plot and Saved Images¶
The CLI is able to output 3 folders of images with the bwr
, gnuplot
, and gist_ncar
colormaps from matplotlib. You can define the pallete(s) that you would rather use.
Supported/Tested Cameras¶
Flir One (thermal + RGB)
Xenmuse XTR (thermal + thumbnail, set the subject distance to 1 meter)
AX8 (thermal + RGB)
DJI Zenmuse H20T Camera (ZH20T)
Other cameras might need some small tweaks (the embedded raw data can be in multiple image formats). Let me know if you succesfully use other cameras so they can be added to this list.
Development¶
Install the required packages using Pipenv. Then run pre-commit install
to install the pre-commit hooks. Note that this tool is intended to work on Windows as well as Unix operating systems so use os.path functions to manipulate file paths instead of string manipulation.
Build Command for Dev (uses poetry or twine)¶
python -m build –sdist –wheel
poetry build
poetry add “packagename” –group=extras –optional
sphinx-build -b html docs/source docs/build (To Generate Docs)
Credits¶
This CLi was developed using this repos:


Implementation of simple bike model used for direct NLP. The cost function parameters were taken from someone's solution online just to debug things, will tune them more substantially later.
More...
#include <Model.h>
|
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| BikeModel (int N, int nx, int nu, int delay, double dt, double vref, const VectorXd &coeffs={}, const vector< double > &trajectory={}) |
| |
| void | set_coeffs (const VectorXd &coeffs) |
| |
| virtual int | xstart () override |
| |
| virtual int | ystart () override |
| |
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typedef | CPPAD_TESTVECTOR (AD< double >) ADvector |
| |
| | Model (int N, int nx, int nu, int delay, const vector< double > &trajectory={}) |
| |
| void | set_trajectory (vector< double > &trajectory) |
| |
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bool | initialized () |
| |
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vector< int > & | starts () |
| | returns reference to starts vector
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int | nx () |
| | returns state dim nx
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int | nu () |
| | returns input dim nu
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int | N () |
| | returns horizon N
|
| |
| void | operator() (ADVec &fg, const ADVec &vars) |
| |
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| enum | State {
X,
Y,
PSI,
V,
CTE,
EPSI
} |
| |
| enum | Input { DELTA,
A
} |
| |
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virtual AD< double > | Cost (int t, const ADVec &xt, const ADVec &ut, const ADVec &utp1) override |
| | >model parameter roughly specifying turning radius
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| |
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virtual AD< double > | TerminalCost (const ADVec &xN) override |
| | Pure virtual function: should return terminal cost.
|
| |
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virtual ADVec | DynamicsF (int t, const ADVec &xt, const ADVec &ut) override |
| | Pure virtual function: should return x(t+1) = f(x(t),u(t))
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template<typename Vector > |
| Vector | x_t (int t, const Vector &vars) |
| | Helper function to extract x(t) from vars.
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| |
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template<typename Vector > |
| Vector | u_t (int t, const Vector &vars) |
| | Helper function to extract u(t) from vars.
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| |
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double | dt_ |
| |
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double | vref_ |
| | >sampling time dt
|
| |
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VectorXd | coeffs_ |
| | >reference velocity
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const double | Lf_ = 2.67 |
| |
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int | N_ |
| |
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int | nx_ |
| |
optimization horizon is N_-1
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int | nu_ |
| |
state dimension
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int | delay_ |
| |
input dimension
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vector< int > | starts_ |
| |
input delay: x(t+1) = f(x(t),u(t-delay_))
|
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| vector< double > | trajectory_ |
| |
Implementation of simple bike model used for direct NLP. The cost function parameters were taken from someone's solution online just to debug things, will tune them more substantially later.
◆ set_coeffs()
| void BikeModel::set_coeffs |
( |
const VectorXd & |
coeffs | ) |
|
|
inline |
call this before every mpc solve to update reference trajectory, which is specified in terms of polynomial = sum_{i=0}^2 coeffs[i] * pow(x,i)
◆ xstart()
| virtual int BikeModel::xstart |
( |
| ) |
|
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inlineoverridevirtual |
Needed to plot MPC planned trajectory in simulator: should return starts_[X], where X specifies the the position of X in the the state vector. e.g. if state[0] = x, then xstart shoudl return starts_[0];
Implements Model.
◆ ystart()
| virtual int BikeModel::ystart |
( |
| ) |
|
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inlineoverridevirtual |
Needed to plot MPC planned trajectory in simulator: should return starts_[Y], where Y specifies the the position of X in the the state vector. e.g. if state[1] = y, then xstart shoudl return starts_[1];
Implements Model.
The documentation for this class was generated from the following file:


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Input the voting name.


Have you ever felt why lately our human's lifespan has shortened?
Have you ever felt why human of this age are falling sicker and surrendering to many non-communicable diseases easily?
Recently 62.5 million lives have been lost every year in India due to premature deaths of Cardiovascular-disease.
Source
Non-communicable diseases (NCDs) cause 63 percent of all cases of deaths in the world. That is equal to 36 million people per year.
Nine million people die prematurely—before age 60—as a result of NCDs annually.
Source
There are many causes for premature deaths, following are listed below
Source


CEAC support NZ First plan to reduce 1080 poison
by Citizens Environmental Advocacy Centre
Monday, 25th November 2019,
Press Release: Citizens Environmental Advocacy Centre
https://www.scoop.co.nz/stories/PA1911/S00166/35m-to-reduce-repeated-1080-use.htm
We agree with NZ First Jenny Marcroft ‘Spokesperson for Health’ innovative to lower 1080 poison on predator control in the press release 20th November 2019.
QUOTE.
“New Zealand First is proud to announce the Provincial Growth Fund (PGF) has allocated $3.5 million to develop innovative predator control approaches which will reduce the need for repeated 1080 use.”
CEAC say this is good “environmental stewardship”
We have been witness to the multiple horrible slow death of other animal’s not considered as “predators” around the rural sector with the continued over-use of 1080 and offering a more humane control is welcomed here.
This toxic chemical bait and use of pellets simply does not discriminate any animal or bird in the drop zone, so we are grateful for this excellent innovation project to ‘develop innovative predator control approaches’
NZ First claim to be the Party of “common sense” and this again is a good sensible plan.
CEAC encourage a coalition Government who is a caring, considerate inclusive, responsive to citizens’ concerns.
ends


WITNESS LIST Appropriations-S/C on Regulatory Committee August 26, 2004-9:00A Interim Charge #2 On: Allen, Ron (Texas Board of Veterinary Medical Examiners) Alonzo, Janie (Tx St Bd of Podiatric Medical Examiners) Burnett, Dale (Tx Structural Pest Control Board) Cook, Jean (Texas Racing Commission) Crawford, Denise Voigt (Texas State Securities Board) Feeney, Harold E. (Credit Union Department) Hess, Michael (Texas Board of Professional Geoscientists) Kloeris, Chris (Texas Optometry Board) Kuntz, William H. (Texas Department of Licensing & Regulation) Lee, Sherry (Texas State Board of Ex. of Psychologists) Maline, John (Executive Council of Physical Therapy and Occupational Therapy Examiners) Maxwell, Robert L. (Texas State Board of Plumbing Examiners) Montoya, David (Board of Tax Professional Examiners) Newberg, Stephanie (Texas Department of Banking) Patrick, Donald (Texas State Board of Medical Examiners) Payne, Danny (Texas Savings & Loan Dept.) Pettijohn, Leslie (Consumer Credit Commissioner) Smith, Sandy (Texas Board of Professional Land Surveying) Thomas, Katherine A. (Board of Nurse Examiners) Thorburn, Wayne (Texas Real Estate Commission / Texas Appraiser Licensing & Certification Board)


Lock the user account after repeated authentication failure.
Multiple consecutive failed authentication attempts over a short period of time are a symptom that is used to detect when an account is under attack. Locking out the account can prevent an attacker from compromising and accessing the account.

Use the following steps to successfully lock accounts after consecutive failed login attempts:
Define a lockout policy. Define the number of allowed consecutive failed login attempts. A simple policy would be to lock an account after five failed login attempts. Although this is an effective method for blocking a brute force attack, it exposes your application to denial of service as an attacker can easily keep an account locked through a small stream of authentication requests.
When determining the lockout policy, it is important to evaluate the risk of attacks against the user and the support costs associated with reactivating a locked account. For example, requiring the user to contact your organization's support staff to reactivate a locked account will have a direct impact on support costs and would add general user frustration. However, it is important to use extra care when designing more sophisticated variations of your application's lockout policy, such as correlating a single or multiple user login attempts with a source IP. When adding extra levels of complexity, carefully consider and evaluate the scenarios where your application's lockout policy can be circumvented or can harm your business. For instance, consider scenarios where an attacker would attempt to compromise a user through the use of multiple hosts, or multiple users would authenticate using a shared office IP.
Track login attempts. Login attempts can be tracked with the use of a login counter. Increment the counter once a user tries to authenticate. Reset the counter to 0 after the user successfully authenticates.
Enforce the lockout policy. The lockout policy should be enforced at all points in the application where authentication is necessary.
Set an unlocking mechanism. Based on your application's lockout policy, unlock the account as necessary.


Weekly Classes
Current Offerings
The following classes are currently being offered by the office of Imam. If you have any questions, please reach out the Office of Imam team at<EMAIL_ADDRESS>On Saturdays
Weight of a Nation
Implementing the Prophet's Example
This weekly series of class started on Saturday September 28. We meet every Saturday at 8 am in the Women's Prayer Hall on the second floor.
All are invited to join.
Past Offerings
The following classes were previously conducted by the office of Imam.
Confident Answers
An Activist GPS Class
This series of classes have concluded.
Wisdom for Rightful Living
Living Islam Series
This series of classes have concluded.
The Missing Piece
This series of classes have concluded.
Struggling to Surrender
Living Islam Series
This series of classes have concluded.
Al Kahf
Reflections on Surah al Kahf
This series of classes have concluded.
Prophetic Prayers
Reflections on the dua of the Quran
This series of classes have concluded.


{% load static %}
Bioinformatician
Bilal is developing tools for aggregating the data needed for whole-cell modeling.


Experienced in the full development stack, including jQuery, node.js, MySQL and more, I’m looking to put my creative and problem-solving skills to use for a team of motivated individuals who care about delivering quality products to their clients.
Find Out MoreHTML, CSS, JavaScript, jQuery, Bootstrap, Node.js, Express, Sequelize, Handlebars, MySQL, Firebase, MongoDB.
And ping pong.
Looking for a full-stack developer? Think I'd be a good fit for your team?
Just need a partner for ping pong? Let's talk.
(608) 481-1336


Throughout this set of tutorials it will be shown how to create and work with TransientComposites, which is the basic element in Qi4j. We will refactor one HelloWorld class to take advantage of the various features in Qi4j. These refactorings will make it easier to reuse parts of the class, and introduce new features without having to change existing code. We will also look at some of the existing classes, or Fragments, available in Qi4j that you can reuse so that you don't have to write everything yourself.
The ambition of the TransientComposite tutorials is to show you the mechanics of the parts that make up a composite. It is not the ambition to show why COP/Qi4j should be a superior way to solve this particular problem. Also, the tutorials assume you are well familiar with Java, especially interfaces and annotations. These tutorials have no ambition to teach Java or design in any broarder sense.
In other words: if you have got this far, we assume you are a seasoned Java programmer, who has heard enough about Qi4j to want to try the tools. This set of tutorials will walk you through the most basic tools, showing you each, but will not tell you the full story of which tool to apply exactly where and when.
Each tutorial in this series starts with the result from the previous tutorial, so you can always look at the next tutorial step for guidance on what to do. Here are the steps:


This time it was a client error. This page does not exist.
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Form
: Form
One of the characteristics of Irish is its tendency for initial mutation to occur in certain circumstances. This is triggered by the preceding word and affects the spelling of nouns, adjectives and verbs. Nouns in Irish are divided into classes according to the way they are inflected to form the genitive singular. There are five such noun-classes or declensions. (The Christian Brothers, 1994)
Ecl
: eclipsis
This feature occurs when the initial consonant or vowel of a word is eclipsed by a prefixing consonant. This is either a voiced consonant for voiceless consonants, (e.g. /tʲ/ → /dʲ/, /k/ → /g/) or a nasalised consonant for voiced consonants (e.g. /dʲ/ → /nʲ/, /g/ → /ŋ/). Vowels are eclipsed by adding n- or t-.
Not every consonant can experience eclipsis. The consonants that can be eclipsed in Irish are: p, b, t, d, c, g and f.
Eclipsis will happen in a number of environments:
- after the plural possessive nouns ár, bhur and a (“our”, “your (pl.)”, “their”)
- on singular count nouns following the numbers 7-10
- after the preposition i “in”
- on plural nouns in the genitive case after the definite article
- on singular nouns in the dative case after the definite article
- following certain clitics such as interrogative particles (an, nach), complementisers (go, nach) and relativisers (a, nach)
Examples
- a gcuid iarrachtaí “their efforts”
- seacht mbliana “seven years”
- i nGaeilge “in Irish”
- costas na n-oibreacha “cost of the works”
- ar an bhfocal “on the word”
- nach bhfaca sé “he didn’t see”
Emp
: emphatic
The emphatic form is a special form a word takes to mark emphasis in Irish.
Examples
- dom “to me”
- domsa “to me (emph)”
- a deirim “I said”
- a deirimse “I (emph) said”
Len
: lenition
Lenition is by far the most common means of initial mutation in the treebank. When lenited, h is added immediately after the initial consonant.
These are some of the environments that trigger lenition:
- following the definite article (see Definite for specifics)
- following the vocative particle a (see PartType, Case)
- after certain adjectives (singular possessive pronouns, uile, aon, dhá, etc.)
- after certain simple prepositions (a, de, do, faoi, etc.)
- following the past tense of the copula is
- following preverbal particles in the past tense (níor, ar, etc.)
- verb forms in the past tense
Examples
- an fharraige “the sea”
- A Dhochtúir Van Helsing “Doctor Van Helsing”
- mo chuid oibre “my work”
- faoi cheist “under question”
- Ba mhaith liom “I would like”
- Níor chuir sin “that doesn’t put”
- tháinig “came”
HPref
: h-prefix
When two vowels come together in Irish, a h-prefix is inserted before the second vowel in order to simplify pronunciation.
Examples
- go hálainn “lovely”
- na heisimirce “emigration”
- de h-Íde “from Íde”
- ní hamháin “not only”
VF
: Vowel form
Vowel form is an indicator of spelling changes that occur in copular verbs when followed by a word that begins with a vowel or a lenited consonant.
Examples
- is copula, “is”
- ab ea iad “they are”
- gurbh é “it was”
- B’fhearr leis lit. “it was better for him”
Treebank Statistics (UD_Irish)
This feature is language-specific.
It occurs with 5 different values: Ecl
, Emp
, HPref
, Len
, VF
.
1737 tokens (13%) have a non-empty value of Form
.
950 types (25%) occur at least once with a non-empty value of Form
.
692 lemmas (25%) occur at least once with a non-empty value of Form
.
The feature is used with 12 part-of-speech tags: ga-pos/NOUN (926; 7% instances), ga-pos/VERB (650; 5% instances), ga-pos/ADJ (57; 0% instances), ga-pos/PROPN (45; 0% instances), ga-pos/AUX (25; 0% instances), ga-pos/NUM (20; 0% instances), ga-pos/DET (6; 0% instances), ga-pos/ADP (3; 0% instances), ga-pos/PRON (2; 0% instances), ga-pos/ADV (1; 0% instances), ga-pos/PART (1; 0% instances), ga-pos/X (1; 0% instances).
NOUN
926 ga-pos/NOUN tokens (25% of all NOUN
tokens) have a non-empty value of Form
.
The most frequent other feature values with which NOUN
and Form
co-occurred: Definite=EMPTY (926; 100%), VerbForm=EMPTY (731; 79%), Number=Sing (646; 70%), Case=NomAcc (634; 68%), Gender=Masc (474; 51%).
NOUN
tokens may have the following values of Form
:
Ecl
(243; 26% of non-emptyForm
): gceist, gcuid, gcás, ndóigh, bhfeidhm, gContae, gcomhairle, gcrích, mír, bhfadEmp
(1; 0% of non-emptyForm
): liostasaHPref
(22; 2% of non-emptyForm
): haigne, hordú, háit, halt, ham, hamanna, hathair, haturnae, heisimirce, heolaíochtLen
(660; 71% of non-emptyForm
): bheith, chur, dhéanamh, chuid, thabhairt, chéile, fho-alt, chineál, fhios, bhaint
| Paradigm alt | Ecl | HPref | Len |
|---|---|---|---|
| bhfo-alt | halt | fho-alt, alt |
VERB
650 ga-pos/VERB tokens (59% of all VERB
tokens) have a non-empty value of Form
.
The most frequent other feature values with which VERB
and Form
co-occurred: Voice=EMPTY (598; 92%), Mood=Ind (547; 84%), Tense=Past (382; 59%).
VERB
tokens may have the following values of Form
:
Ecl
(184; 28% of non-emptyForm
): bhfuil, raibh, mbeidh, mbeadh, mbíonn, ndeachaigh, bhfuair, dtiocfadh, mbaineann, bhfacaEmp
(3; 0% of non-emptyForm
): Creidimidne, atáimse, deirimseLen
(463; 71% of non-emptyForm
): bhí, bheidh, raibh, bhíonn, thug, tháinig, bheadh, bhaineann, chaith, bhain
| Paradigm bí | Ecl | Emp | Len |
|---|---|---|---|
| _ | mbíonn | bhíonn | |
| Mood=Cnd | mbeadh | bheadh | |
| Mood=Cnd|Number=Sing|Person=1 | mbeinn | ||
| Mood=Cnd|Number=Sing|Person=2 | bheifeá | ||
| Mood=Cnd|Number=Plur|Person=3 | bheidís | ||
| Mood=Imp|Number=Sing|Person=1|Tense=Past | mbínn | ||
| Mood=Imp|Tense=Past | mbíodh | bhíodh | |
| Mood=Ind|Number=Sing|Person=1|PronType=Rel|Tense=Pres | atáimse | ||
| Mood=Ind|Number=Sing|Person=1|Tense=Past | rabhas | bhíos | |
| Mood=Ind|Number=Plur|Person=1|Tense=Fut | bheimid | ||
| Mood=Ind|Number=Plur|Person=1|Tense=Past | Bhíomar | ||
| Mood=Ind|Number=Plur|Person=1|Tense=Pres | bhfuilimid | ||
| Mood=Ind|Number=Plur|Person=3|Tense=Past | bhíodar | ||
| Mood=Ind|Polarity=Neg|Tense=Fut | mbeidh | bheidh | |
| Mood=Ind|Polarity=Neg|Tense=Fut|Voice=Auto | mbeifear | ||
| Mood=Ind|Polarity=Neg|Tense=Past | raibh | ||
| Mood=Ind|Polarity=Neg|Tense=Past|Voice=Auto | rabhthas | ||
| Mood=Ind|Polarity=Neg|Tense=Pres | bhfuil | ||
| Mood=Ind|Tense=Fut | mbeidh | bheidh | |
| Mood=Ind|Tense=Past | raibh | bhí | |
| Mood=Ind|Tense=Pres | bhfuil, fuil | ||
| Polarity=Neg | bhíonn |
ADJ
57 ga-pos/ADJ tokens (8% of all ADJ
tokens) have a non-empty value of Form
.
The most frequent other feature values with which ADJ
and Form
co-occurred: VerbForm=EMPTY (56; 98%), Case=EMPTY (54; 95%), Number=EMPTY (54; 95%), Gender=EMPTY (54; 95%), Degree=Pos (52; 91%).
ADJ
tokens may have the following values of Form
:
Ecl
(1; 2% of non-emptyForm
): gcéannaHPref
(13; 23% of non-emptyForm
): háirithe, hamháin, hiontach, han-luath, hiomlán, hálainn, héifeachtúilLen
(43; 75% of non-emptyForm
): cheart, Bhriotáineach, chóir, mhaith, chultúrtha, chéanna, mhó, mhór, Bhig, Bhunaithe
| Paradigm céanna | Ecl | Len |
|---|---|---|
| gcéanna | chéanna, céanna |
Form
seems to be lexical feature of ADJ
. 97% lemmas (31) occur only with one value of Form
.
PROPN
45 ga-pos/PROPN tokens (9% of all PROPN
tokens) have a non-empty value of Form
.
The most frequent other feature values with which PROPN
and Form
co-occurred: Number=Sing (35; 78%), Gender=Masc (31; 69%), Case=Gen (30; 67%).
PROPN
tokens may have the following values of Form
:
Ecl
(10; 22% of non-emptyForm
): mBaile, Mí, gCuan, gCuideachtaí, nGaillimh, nGearmáinHPref
(2; 4% of non-emptyForm
): h-Íde, míLen
(33; 73% of non-emptyForm
): Bhaile, Mháire, Chill, Chonamara, Ghaeilge, Bhríde, Cholm, Chonaill, Dhonncha, Edward
| Paradigm Baile | Ecl | Len |
|---|---|---|
| Number=Sing | Bhaile | |
| Number=Plur | mBaile |
Form
seems to be lexical feature of PROPN
. 94% lemmas (30) occur only with one value of Form
.
AUX
25 ga-pos/AUX tokens (11% of all AUX
tokens) have a non-empty value of Form
.
The most frequent other feature values with which AUX
and Form
co-occurred: VerbForm=Cop (25; 100%), PronType=EMPTY (22; 88%), Polarity=EMPTY (22; 88%), Tense=Past (18; 72%).
AUX
tokens may have the following values of Form
:
VF
(25; 100% of non-emptyForm
): b’, gurb, ab, gurbh, níorbh, mb’, nárbh
NUM
20 ga-pos/NUM tokens (11% of all NUM
tokens) have a non-empty value of Form
.
The most frequent other feature values with which NUM
and Form
co-occurred: NumType=Card (11; 55%).
NUM
tokens may have the following values of Form
:
Ecl
(3; 15% of non-emptyForm
): gceithre, gcéadHPref
(2; 10% of non-emptyForm
): haonLen
(15; 75% of non-emptyForm
): chéad, dhó, cheithre, sheacht, sheasca, thrí
| Paradigm céad | Ecl | Len |
|---|---|---|
| NumType=Card | chéad | |
| NumType=Ord | gcéad | chéad |
DET
6 ga-pos/DET tokens (0% of all DET
tokens) have a non-empty value of Form
.
The most frequent other feature values with which DET
and Form
co-occurred: Gender=EMPTY (6; 100%), Number=EMPTY (6; 100%), Case=EMPTY (6; 100%), Definite=Def (4; 67%), PronType=EMPTY (4; 67%).
DET
tokens may have the following values of Form
:
Ecl
(4; 67% of non-emptyForm
): ngach, gachHPref
(2; 33% of non-emptyForm
): haon
ADP
3 ga-pos/ADP tokens (0% of all ADP
tokens) have a non-empty value of Form
.
The most frequent other feature values with which ADP
and Form
co-occurred: Gender=EMPTY (3; 100%), PronType=EMPTY (3; 100%), Number=Plur (2; 67%), Person=1 (2; 67%).
ADP
tokens may have the following values of Form
:
Len
(3; 100% of non-emptyForm
): dhom, dhíobh, dhúinn
PRON
2 ga-pos/PRON tokens (0% of all PRON
tokens) have a non-empty value of Form
.
The most frequent other feature values with which PRON
and Form
co-occurred: Gender=EMPTY (2; 100%).
PRON
tokens may have the following values of Form
:
Len
(2; 100% of non-emptyForm
): cheachtar, thusa
X
1 ga-pos/X tokens (1% of all X
tokens) have a non-empty value of Form
.
The most frequent other feature values with which X
and Form
co-occurred: Dialect=Munster (1; 100%), Abbr=EMPTY (1; 100%), PronType=EMPTY (1; 100%).
X
tokens may have the following values of Form
:
Len
(1; 100% of non-emptyForm
): chuireas
ADV
1 ga-pos/ADV tokens (0% of all ADV
tokens) have a non-empty value of Form
.
ADV
tokens may have the following values of Form
:
Len
(1; 100% of non-emptyForm
): Thuaidh
PART
1 ga-pos/PART tokens (0% of all PART
tokens) have a non-empty value of Form
.
The most frequent other feature values with which PART
and Form
co-occurred: PronType=Rel (1; 100%), PartType=Vb (1; 100%), Polarity=EMPTY (1; 100%).
PART
tokens may have the following values of Form
:
Ecl
(1; 100% of non-emptyForm
): n-a
Relations with Agreement in Form
The 10 most frequent relations where parent and child node agree in Form
:
VERB –[conj]–> VERB (34; 61%),
PRON –[appos]–> NOUN (2; 100%),
ADJ –[advcl]–> ADJ (1; 100%),
X –[advcl]–> VERB (1; 100%),
ADJ –[ccomp]–> ADJ (1; 100%).
Form in other languages: [ga]


Commonly used as the contents of a popover when composing “date-picker”, rarely used on its own as a standalone component.
The calendar header buttons are navigable with the tab key. Pressing enter or the space bar when the month or year is
focused will change the day selection grid to the month or year selection grid respectively. The user can then tab
into the day/month/year selection grid and use the arrow keys to navigate around the grid and make a selection with
the space bar or enter key.


descriptions from MDN
title Defines a title for the notification, which is shown at the top of the notification window.
dir ltr rtl auto The direction in which to display the notification. It defaults to auto, which just adopts the browser's language setting behavior, but you can override that behaviour by setting values of ltr and rtl (although most browsers seem to ignore these settings.)
auto
ltr
rtl
lang The notification's language, as specified using a DOMString representing a BCP 47 language tag. See the Sitepoint ISO 2 letter language codes page for a simple reference.
DOMString
badge A USVString containing the URL of the image used to represent the notification when there isn't enough space to display the notification itself.
USVString
body A DOMString representing the body text of the notification, which is displayed below the title.
tag A DOMString representing an identifying tag for the notification.
icon A USVString containing the URL of an icon to be displayed in the notification.
image a USVString containing the URL of an image to be displayed in the notification.
renotify A Boolean specifying whether the user should be notified after a new notification replaces an old one. The default is false, which means they won't be notified.
Boolean
false
requireInteraction Indicates that a notification should remain active until the user clicks or dismisses it, rather than closing automatically. The default value is false.
silent A Boolean specifying whether the notification is silent (no sounds or vibrations issued), regardless of the device settings. The default is false, which means it won't be silent.


Demonstrates
basic grid with minimal configuration
Cells with rowspan > 1
Row with custom height: 6
Scroll To Row
Toggle row #6 height
Toggle blue cell colspan & rowspan
View Source:
View Source Code


Java
and the
Quest
for the
Scripts!
Java
and the
Quest
for the
Scripts!
Move Left:
Move Right:
Jump:
Attack:
Restart Level:
'Left Arrow' Key
'Right Arrow' Key
'Up Arrow' Key
'Down Arrow' Key
'R' Key
The Crew:
Jose Amesquita
Zakkrey Short
Jamison Cozart
Tony Cruz
Geoff Goetz
Shoutout To:
Phaser 3
Engine
Leshy Labs
Asesprite
Texture
Packer
Tiled


Chick-fil-A will stop donating to anti-LGBTQ groups
by KNOE(CNN) - Chick-fil-A will no longer donate money to charities with anti-LGBTQ views.
The fast food chain announced Monday that starting next year it will only donate to organizations that focus on education, homelessness, and hunger.
Chick-fil-A's donations and comments from its executives have caused controversy over the past several years.
CEO Dan Cathy has said the Atlanta-based fast food company supports, "The biblical definition of the family unit."
Gay rights groups have boycotted and opposed the chain over its stance on same-sex marriage.
In a statement, gay rights organization 'GLAAD' said customers and employees should "greet today's announcement with cautious optimism."
Former Arkansas Governor Mike Huckabee called the move a betrayal.


User name:
Password:
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Techskils:
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Upload file:
Address:
KLU
RGUKT
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Email:
Phone:
Submit
Anusha Kalli
Software Developer
kallianusha1266@gmail.com


Detroit-area school forfeits playoff game, cites hazing
WARREN, Mich. (AP) - A Catholic high school in the Detroit area has dropped out of the football playoffs because of hazing incidents by players.
An email sent to parents Thursday by Warren De La Salle Collegiate says players were aware of the hazing but failed to report it. The school felt it was appropriate to end the season by forfeiting a playoff game Friday against Birmingham Groves.
De La Salle says behavior that violates the school’s code of conduct and Christian morality “will not be tolerated.” Warren police have been informed.
The Pilots have won three state championship in the last five years.
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