Lina was born and raised (mostly) in Bogota, Colombia and has since then been tumbleweeding aimlessly through the world. She is the author of Drown Sever Sing, and her ode to cannibalism can be found in the collection titled, After Montaigne: Contemporary Essayists Cover the Essays. She is a graduate of The University of Iowa's Creative Nonfiction and Literary Translation programs, and her work has been featured in Arts and Letters, The Chicago Review, and Fourth Genre, among others. Her new book, Don't Come Back, is published by Mad River Books, an imprint of The Ohio State University Press (January 2017). Ferreira is a recipient of the 2016 Rona Jaffe Foundation Writer's Award.
"One Night Less in Baghdad."
Translation. "Una Noche Menos en Baghdad" by Pedro M. Villalora, for podcast Play for Voices. 2018."Coming Back."
Feature. Poets & Writers. Forthcoming 2017."The Man Walks In and Removes His Hat."
Essay. The LA Review of Books. Forthcoming 2017."Aurelia."
Essay. Eleven Eleven. January 2017."Allá En La Fuente."
Essay in the anthology This is the Place. Seal Press, Perseus Books, LLC, a subsidiary of Hachette Book Group, Inc. September 2017."María, María, María, María."
(Excerpt from Translations in Diagram in Translation). Translation. Stonecutter Journal. Spring 2016."Tinfoil Astronaut."
Essay. The Sunday Rumpus. Forthcoming November 2016."Drowning Lessons."
Essay. Hotel Amerika. September 2016."Rio Que Sale" & "Del Dicho Al Hecho"
(Excerpt from Translations in Diagram in Translation). Translation. Stonecutter Journal. Spring 2016."Of Cannibal."
Essay in the anthology After Montaigne. University of Georgia Press. March 2015."Pain Pays the Income of Each Precious Thing."
Essay. Brevity. September 2015."The Peach Orchard."
Essay. Fourth Genre. Fall 2015"Cain."
Short story. The Baltimore Review. July 2015."The Wee She-Dog."
Translation/poem. M-Dash. June 2015."BOG – MIA – CID."
Essay. Arts & Letters. Spring 2015."Muybridge."
Poem. Rattle. June 2015."Empire of Toes."
Essay. The Chicago Review. October 2014."Practice."
Essay. Guernica/PEN America. June 2014"El Hombre Caimán."
Short story. The Rio Grande Review. 2014."Catching Moths."
Essay. Drunken Boat. 2014."Rare Misprinted Scott Russell Sanders Postcard: Next best thing to 'Inverted Jenny'; essayist must have."
Collaboration, Franklin, Joey, Madden, Patrick, et al.) The Normal School. Fall 2013."Amor con Amor."
Essay. Anomalous Press. 2013."Del Agua Mansa Me Libre Dios."
Translation/Fiction. Anomalous Press. 2013."Lo Que Quiere."
Essay. Chapbook collaboration with Kendra Greene. Greene Ink Press. 2011."Deal Amor Al Odio."
Essay. Anomalous Press. 2011."Sonambula."
Essay. H.O.W. Journal. 2011."Catalogue of Dead Birds."
Essay. Bellingham Review. 2010."In Absentia: On Things Remembered and Forgotten."
Essay. The Iron Horse Review. 2009."What I Know About Love."
Essay. Inscape. Fall 2007.“Her husband is long like a lecture and thin like Bible pages. He tried to tell me—but his toothless accent was too thick so I had to hear it from someone else—that he was an Argentinean soccer player once. He stood around as I dove headfirst into knees and shins belonging to boys with worn-out tennis shoes trying to score against my team. My arms wrapped around the ball like desperate lovers, and worn-out tennis shoes raced back into midfield.”
"Margarita Didn't Mind."
Essay. Inscape. Fall 2006.“She wore a white lace dress; a normal dress, I guess, for the occasion. I wonder who picked it. As I stood over the wooden box, it seemed to me that the dress had grown an unnatural extension, and it ate up her neck in sloppy stitches. The stale white dress was more alive than she was—hands stiffly bent over stomach and eyelids pulled over like the final bed sheets of the corpse. She doesn't look peaceful at all, sleeping there, I thought while I watched her encased in white silk, just very still and quiet, like the silence in hospitals or of angry parents.”


'Evil killer who slaughtered mum-of-5 and hid her body was also stalking me'
EXCLUSIVE: Convicted murderer Ben Lacomba was stalking former lover Leanne Edwards, who describes her terrifying relationship with the callous control freak
by Scarlet Howes, Amir RazaviA woman who was a lover of evil Ben Lacomba was being stalked by him just days before he murdered a mum of five.
Leanne Edwards spoke out after Lacomba was sentenced to 27 years for killing Sarah Wellgreen, the mother of three of his children.
His disturbing behaviour included dragging her into a bizarre plot to try to scam the Judge Rinder TV show.
Jailing him on Friday, Judge Christopher Kinch blasted the “callous” monster for refusing to reveal where he had hidden the body.
Barmaid Leanne, 32, told the Sunday People: “I hope he rots in jail and never gets out.”

Two years after they split his actions became more sinister as he started pestering her to see him again.
Leanne said taxi driver Lacomba bombarded her with calls and messages and hung around her house at night.
She recalled: “He tried to contact me only a few months before Sarah’s murder. I rang my neighbour and asked them to do me a favour and keep an eye out for me.
“I had a weird feeling. As I walked home she rang me and described Ben’s car and what he looked like.
“She said he had just pulled up outside my house. I didn’t go home that night.
“My neighbour then told me he had been round a few times. This went on right before Sarah’s death.
“She told me he kept turning up outside at night. It was terrifying. I could have been killed. I feel lucky to be alive.”
Leanne got to know both Sarah and Lacomba when she lodged at their house in New Ash Green, Kent, in 2010.
But after moving out three years later she lost touch with them – until Lacomba picked her up in his taxi one night.
By that time he had split with 46-year-old beautician Sarah but was still living in the same house with her and their three children.
Leanne said: “Ben would use his cab to hit on vulnerable women. I was vulnerable at the time as it was the tenth anniversary of my mum’s death.
"He took advantage of that. I invited him in and one thing led to another.”
She said of their relationship: “He would be really controlling and watch me to make sure I took my contraceptive pills.
“He thought I wanted to get pregnant in case we broke up. He’d even get me to lift my tongue up so he could check.”
Leanne said he made her appear on the Judge Rinder programme to try to con ITV out of some cash.
Lacomba told the show in 2015 that she was a lodger who owed £4,550 in rent.
He persuaded her to hide the fact she was his girlfriend.
Judge Rinder’s TV judgments are not legally binding so the fines issued in the mock court battles are actually paid for by ITV.
But Lacomba’s plan backfired when Judge Rinder sided with Leanne.
She said: “He wanted the money for the custody battle against Sarah.
“He started getting teary to me saying he needed the money to get a barrister and that he wanted the kids.
“He knew I’d go along with it because I didn’t want to be blamed if he lost custody.
“At first I saw it as a man trying to fight for his children but further down the line you could see he wasn’t doing it to make their lives better. It was for him.
“He just wanted that control over her life. If he wants something, he’ll do whatever he can to get it. He thought he’d win the case so he was angry when he didn’t.”

“He also sent the bosses a number of private messages. I felt forced to hand in my notice.”
After the split Leanne became friends with Sarah, who she knew from the mum’s work at a hostel where she was living.
"She wanted to see if I was OK,” she said. “I apologised for being with Ben. “She said she was angry at first that we had got together but was over it.
“She told me she had wanted to warn me but I had to find out for myself what he was like.”
Leanne saw Sarah just a week before she went missing in October last year – meeting for coffee near Leanne’s home in Dartford, Kent.
“We were just talking about girly stuff,” she said. “Sarah told me she had been talking to a couple of guys but hadn’t met them yet.
“She said, ‘Ben didn’t like the fact that I was doing well because his intentions were for me to lose everything’.
“She quite liked rubbing it in that we were still pals.
“And then she said he was a t**t.”
Lacomba is suspected of using a gravedigger’s shovel to bury Sarah’s body after drowning her in the bath.
Despite there being no body a jury took just three hours to convict him unanimously of murder last month.
They were told how Sarah had landed a better-paid job shortly before her death.
She wanted to buy him out of the home they shared and he apparently feared losing access to his children.
Lacomba will serve 26 years in prison, taking into account time spent on remand.
On Friday the judge who sentenced him at Woolwich crown court said hiding the body had caused the family an “agony of uncertainty”. Judge Kinch added: “This was a wicked plan, executed for your own selfish interests.
“It’s difficult to imagine something more callous or chilling.
“The position you have put your children in is completely unimaginable. As their father, you were one of two people they would look to for nurture and protection.
“Instead you have taken their mother from them – a crime which is bound to resonate throughout their lives.
“Sarah] was described as bubbly, kind and considerate. Someone who would step in if she thought anyone was being wronged or treated badly.
“This murder was no crime of passion or momentary outburst of violence. It was, I am sure planned and calculated.”
Leanne said: “He will never tell us where Sarah is as he’s a control freak and that’s the only bit of control over the situation he has left. He’s evil.
"He reminds me of Ted Bundy. Charming on the outside but evil deep down.”
Leanne swears she will never visit him in prison or write to him.
But she sometimes wishes she HAD met him when he sent her a mysterious message shortly before Sarah vanished.
It read: “I have to see you. Whatever I’ve got to say I can’t do over the phone.”
Leanne said: “What if he was going to tell me what he was planning to do to Sarah? I could have saved her. Or he could have used me as an alibi.”
Tearful Leanne added: “I miss her a lot.”
Sarah’s family said in a statement: “We miss Sarah every day. Our priority from now is to give Sarah’s three youngest children every opportunity to be the best they can be.”


CCBB Rental Agency
CCBBRA was developed by Nicholas Herold, Ahmad Kane and Carla Kinley-Davis in 2021 during the global COVID-19 pandemic. The application is meant to address the needs of the traveler who is looking for a rental car during the current vehicle shortage due to months of economic shutdown.
Deployed Link
Github Repository


|
OneServiceMunicipal Services Office |
OneService provides a convenient channel to report municipal issues within Singapore. With the OneService app, municipal services can be delivered more effectively to improve the living environment for citizens.
What you can do with OneService:
- Select from a range of common categories and sub-categories to submit a case
- Attach photos and geo-tag for more complete and precise reporting
- Track updates of submitted cases and rate services
- Receive alerts if you are near dengue clusters, view the number of cases in the neighbourhood and the block of flats where these cases are located
- Locate public and commercial car parks at your destination and obtain information such as parking rates, opening hours, car park types and entry points
- View parking lot availability and height restrictions of HDB Electronic Parking System car parks and selected commercial car parks
- Pay parking fees for HDB and URA coupon car parks


Dashboard
My Account
Task Review
Task Management
Bonus Management
Employee Management
Report Generation
Logout
Dashboard
My Account
Task Review
Task Management
Bonus Management
Employee Management
Report Generation
Logout
Employee Management
Current Employees
Employee Name
Points Earned
Job Title
Edit / Delete
{% for employee in employees %}
{{ employee['full_name'] }}
{{ employee.point_bal }} points
{% if employee.is_manager %}
Manager
{% else %}
Driver
{% endif %}
Edit / Delete
{% endfor %}
Enter New Employee
Employee Name:
Is Manager?


1 Introduction
This part of the book provides tutorials on specific topics using R. These tutorials are written and curated by scholarship participants.
1.1 Contributors
1.1.1 Afton - Map Visualizations
My name is Afton and I work as a statistical programmer for Murphy Research, a market research company based in Los Angeles. My background is originally in linguistics, and I graduated with an MA in linguistics from the University of Southern California. Connect with me on Twitter or LinkedIn so we can talk more about data and language!
1.1.2 Jolynn - Udacity Even Lessons
My name is Jolynn. I am a spatial data analyst with a masters in GIS from Penn State, where I studied remote sensing and spatial statistics. You can see some of my maps on my website or find me on LinkedIn.
1.1.3 Josh - Basic dplyr
My name is Josh and I currently work as the Manager of Data Analysis for AACSB International. I hold an MA in Economics from the University of South Florida (Go Bulls!), and have a background in Statistics as well. Examples of my work include a shinydashboard, a blog post written in R Markdown and a publication with tables and figures made with the tidyverse. You can follow me on Twitter or add me on LinkedIn.
1.1.4 How to contribute
We are using a shared repository model. Therefore, you can contribute to the book by following these steps:
- Clone the book repo from GitHub.
- Create a separate branch for your topic
- Add the file(s) to the proper directories and commit the changes to your topic branch
- Push the changes to GitHub and submit a pull request
For information on the shared repository model, see here and here.


Some smash fans make fan art in the form of videos. The community produces hundreds of videos on a range of smash subjects. Here is a popular combo that has been animated by Youtuber Applesgosh. Warning: this video is LOUD.
Members of the smash community are even inspired to make their own games. Project M (M for Melee) is a modified version of Super Smash Bros Brawl with increased pace and a larger roster.
Here are some resources created by the Smash Bros community:
- Smash Wiki
- Comprehensive listing of smash games and details
- Vods.co
- Videos of tournament matches
- Smashladder
- Play smash games online with other users
- SmashBoards
- The longest running Smash forum
- Super Smash Flash 2
- Fan game based off the original series but played in a web browser
- Rivals of Aether
- An indie platform fighting game in the same genre as Smash Bros, created by some with a background in smash


class: top, left, inverse, title-slide # Education & Globalization ## Session 19 ### Dr. Zhou Yisu 周憶粟 ### 2018/10/25 --- # Shadows of education ## Aims To examine the negative global flows of education To consider the impact of these flows on individuals To understand some theoretical explanation of the negative flow --- .pull-left[ ![](https://img3.doubanio.com/view/photo/l/public/p2497092424.webp) ] .pull-right[ 1.  Youtube documentary: [Korea's mounting academic pressure](https://youtu.be/TXswlCa7dug) ] --- ## Common theme Both engaged in .violet[competitive schooling] - .green[Streaming & tracking] in Singapore - After school tutoring (.green[shadow education]) in Korea -- Common consequence: Stressed-out students & family - Psychologically - Socially --- ## School system: Macao ![:wscale 80%](./pic/flow-macau.png) --- ## School system: Singapore ![:wscale 80%](./pic/flow-singapore.png) .footnote[Note: Singapore has recently reformed its school system: https://www.moe.gov.sg/education/education-system] --- ## School system: South Korea ![](./pic/flow-korea.png) --- ## Nature of competitive schooling ![](./pic/shadow1.png) --- ## The "Shadow" metaphor Shadow education is essentially more education. But there are several key characteristics: .orange[Supplementation] 補充: more education on top of common school experience .orange[Privateness] 私有: tutoring provided by private entrepreneurs and individuals for profit-making purposes. .orange[Academic] 學術性質: language subjects, mathematics, and other examinable subjects. --- ## Shadow is almost everywhere In .violet[Hong Kong], a 2011/12 survey found that 53.8% of G9 students and 71.8% of G12 students were receiving private supplementary tutoring .red[1]. -- In .violet[India], a 2012 survey indicated that 73% of children aged 6-14 were receiving tutoring. -- In .violet[Kazakhstan], a 2005/06 survey of university students found 59.9% had receive tutoring during their last year of secondary school. -- In .violet[Vietnam], 2006 survey indicated 32% of primary students, 46% of lower secondary, and 63% of upper secondary students received tutoring. .footnote[[1] Source: https://cerc.edu.hku.hk/wp-content/uploads/Mono-10.pdf] --- ## Shadow is almost everywhere More detailed data from .violet[Singapore]: - 60% of high school, and 80% of primary school age students receive private tuition. - 40% of pre-schoolers receive private tuition. - Pre-schoolers, on average, attend two hours private tuition per week, while primary school aged children are attending, on average, at least three hours per week. - According to Singapore's Household Expenditure Survey, private tuition in Singapore is a SGD 1.1 billion dollar industry almost double the amount households spent in 2005 (SGD 650 million). --- ## The shadow spawns a big business ![](./pic/shadow2.jpg) --- ## The shadow spawns a big business Does Mr. Cha's case remind us the .violet[uneveness] of globalized age? ![](./pic/shadow3.jpg) .footnote[Source: _Fast earners: South Korea's millionaire, celebrity schoolteachers_] --- ## Negative consequences: student suicide ![](./pic/singapore3.jpg) --- ## Negative consequences: Mental illness When children are being asked to achieve perfection in every level, their minds some times could not adapt very well .red[2] -- - When parents are highly intrusive 高度介入 and controlling, children are more likely to be .violet[self-critical] 自我批評, .violet[anxious] 焦慮, and .violet[depression] 憂鬱. - Intrusiveness also indicates to children that they are not good enough and that parents have to intervene in various domains of their lives. - As a consequence, these children might become .violet[overly concerned] about committing even the slightest errors. .footnote[[2] Hong et al., 2016, _Developmental Trajectories of Maladaptive Perfectionism in Middle Childhood._ http://onlinelibrary.wiley.com/doi/10.1111/jopy.12249/abstract] --- ## Student-teacher relationship is worse in East Asia ![](./pic/tsrel.png) .footnote[Source: PISA 2009] --- ## Broad implications Impact on citizenship: societies divided along socioeconomic line (those who can and cannot afford more education at private expense) -- Education becomes a .red[commodity]: - A goods for sale - Students/parents are consumers and schools are service providers - Differentiating learning experiences -- Create a "losing culture": Only tiny fraction of successful winners but a large army of failed ones. -- Skew motivation for learning --- class: inverse, middle, center # Why people want _more_ education? --- ## If it is so bad, why people still want it? Scholar Clark Sorensen pointed out: .red[3] - Unique parent-child relationship in Asia: parents expected to be cared for by their children in old age and .violet[filial piety] 孝道 by giving them a good funeral, worship them after death, is core of Korean ethics. -- - Reciprocal dependence 相互依賴: parents invest in children and expect payback in old age - Family's social status depends on children's academic/economic success .footnote[[3] Sorensen, C. W. (1994, February). Success and education in South Korea. _Comparative Education Review, 38_(1), 10-35. Retrieved from http://www.jstor.org/stable/1189287] --- ## The cultural explanation 文化解釋 This leads to the very unique Asian family culture: - Parents are more likely to .violet[interfere] 干預 with children's learning and social choices rather than respect children's own will. -- - Parents have the time, and inclination, and the power to .violet[demand] that their children succeed in school. -- - Inside schools, teachers request .violet[respect] 尊敬 and .violet[compliance] 順從 from students while convincing them that they care about them as human beings and have their best interests at heart. -- - .orange[It is the effort, not ability that matters to the parents and family] --- class: middle, center ## However, culture alone couldn't explain the zeal people have on education ## It requires a powerful modern ally: .red[Social mobility for the individual] --- background-image: url(https://i.kym-cdn.com/entries/icons/original/000/010/576/got.jpg) background-size: contain --- ### Why is Jon Snow the King of the North? Not Lord Baelish (aka Little Fingre)? ![](http://i.imgur.com/qcVdXpC.jpg) --- ## In the Game of Thrones world (and other ancient worlds), .green[last name] matters a lot ![](https://static.comicvine.com/uploads/original/11130/111304876/6424922-jon+and+ned.jpg) --- ## Social mobility in feudal societies ![](http://xaviersjc.weebly.com/uploads/2/7/6/4/27641135/1398505558.jpg) --- ## Social mobility in modern societies ![](https://i2.wp.com/cdn.static-economist.com/sites/default/files/images/print-edition/20140201_USD001_1.jpg) --- ## The sociological explanation 社會學解釋 Sociologist Ralph Tuner proposed two types of social mobility 社會流動: -- - .orange[Contest mobility] 競爭流動模式 is like a sporting event in which many compete for a few recognized prizes. Applied to mobility, the contest norms means that victory by a person of moderate intelligence accomplished through the use of .violet[common sense, enterprise, daring, and successful risk-taking] is more appreciated than victory by .violet[the most intelligent] or .violet[the best educated]. -- - .orange[Sponsored mobility] 庇護流動模式 ejects the pattern of the contest and favors a .violet[controlled] selection process. -- + In this process the elite or their agents, deem to be the best qualified to judge merit, choose individuals for elite status who have .violet[the appropriate qualities]. + Individual do not win or seize elite status; mobility is rather .violet[a process of sponsored induction to the elite]. --- ## Rising idea of .green[meritocracy] Sponsored mobility model is closely linked with .green[meritocracy] 賢能主義/唯才主義, an idea that power/opportunity should be allocated based on ability and talent: - National elites design tests to select future talents - Selective tests are considered most fair for all -- Meritocracy is deeply rooted in Confucianism 儒家. Confucius himself cared deeply about how to design a system to pick the best suited to serve the country .red[4]: - This idea operates at societal level. - It requires every participants to do whatever they can to gain an competitive edge in a society where the State controls most of the resources. .footnote[[4] 李弘祺（2012）。.kt[學以為己: 傳統中國的教育。]香港中文大學出版社。] --- ## When combining with close-knit family culture Your family's glory/destiny is tied to children's, as a result, families tend to .violet[_push_] the children very hard. Goes hand-in-hand: families also tend to invest tremendous amount of resources in their children. At societal level, your social status is largely defined by: 1) the types of education received; 2) the relative status within each institution/department/major. Your merit is judged by: .cyan[talent; GPA; internship; study abroad; awards, etc]. All these things are some versions of .violet[_competition_]. The competition is smallest at lower ranking institutions, but intensifies at the top of each level. --- class: middle, center # The shadow of education is really a consequence when education becomes universal & global. --- # .red[Summary] Modern day competitive schooling is deeply rooted in culture, social relationships, and philosophy about individual & society. The shadow continues to grow: In a "school-ed society" (David Baker, Session 11), we are likely to see the spread of such education fever around the world. Is there a way out? It is possibly outside the education system itself. --- ## Resource: - Turner, R. H. (1960). Sponsored and contest mobility and the school system. _American Sociological Review, 25_(6), pp. 855-867.


Replacements
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"all of the sudden" to "all of a sudden"
"legos" to "LEGO"
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Week Three
Exercise 1 (Hospital Data)
Load the
Hospital.Rdata
Construct an interaction effect plot. (Graphs > Plot of means)
- Apply a model with Healing as response, Disease, and Medicine as factor where interaction is included, call this
Model1
. - Test if interaction is present.
- Estimate all parameters.
- Split the first observation into 5 parts: constant, (sample) effect of disease, (Sample) effect of medicine, (Sample) effect of interaction and residual Show that the sum of the 4 effects gives the sample mean in the level combination the observation belongs.
- Repeat the analysis without including interaction, call this
Model2
. - Find and store the fitted value and the residuals for both model and compare.
- Compare the Sum of squares for the two different models.
- If you should test on main effects for in
Model2
without use of computer, show how you can use the results from theModel1
relatively easy. - Plot the residuals (y-axis) against the fitted value (x-axis) for both models and show how this plot reveals model problems in
Model2
. - A student that had not heard about 2-factor design tried to investigate the effect of medicine by a One Way ANOVA model (
Model3
). Explain why this is incorrect for this data. For all 3 models find R-square, and see how this increases with complexity. \[\text{R-square} = \frac{\text{SSModel}}{\text{SS}_\text{Total}} = 1 – \frac{\text{SSE}}{\text{SS}_\text{Total}}\]
Exercise 2 (Mussels Data)
- Load the mussels data.
- Assume a model where eatable is the response size and season are the factors.
- Assume no interaction. Store the residuals and the fitted values.
- Plot residual against fitted values and make comments.
- Give an interpretation of the replicate variance (\(\sigma^2\)). Estimate \(\sigma^2\) and construct a 95% confidence interval for the true value.
- Assume a model including interaction. Store the residuals and the fitted values.
- Plot residual against fitted values and make comments.
- Give an interpretation of the replicate variance (\(\sigma^2\)) and construct a 95% confidence interval for the true value.
Exercise 3
Load the mussels data. The data is from a commercial farming of Blue Mussels where response is eatable food after boiling in percent of total weight. The mussels are sorted after size (Large and small) and season they were harvested (summer or autumn).
Assume a model where eatable is the response, size and season are the factors and interaction is included. Analyze the model.
The model we are analysing is,
\[\begin{equation} y_{ijk} = \mu + \tau_i + \beta_j + (\tau\beta)_{ij} + \epsilon_{ijk} \label{eq:musselFullModel} \end{equation}\]Where,
| \(i\) | = | \(1\) (small), \(2\) (large) corresponding to size |
| \(j\) | = | \(1\) (autumn), \(2\) (summer) corresponding to season |
| \(k\) | = | \(1, 2, \ldots, 6\) corresponding to replicates |
| \(y_{ijk}\) | = | eatable percentage of total weight of \(k^\text{th}\) mussels of size \(i\) on farmed during \(j\) season |
| \(\epsilon_{ijk}\) | \(\sim\) | \(\text{NID}(0, \sigma^2)\), \(\sum_{i = 1}^2\tau_i = 0\) and \(\sum_{j = 1}^2 \beta_j = 0\) |
In addition,
\[\sum_{i = 1}^2(\tau\beta)_{ij} = \sum_{j = 1}^2(\tau\beta)_{ij} = 0\]
The ANOVA table for model in equation ((??)) is,
| Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
|---|---|---|---|---|---|
| season | 1 | 294 | 294.0 | 122.5 | 0 |
| size | 1 | 96 | 96.0 | 40.0 | 0 |
| season:size | 1 | 294 | 294.0 | 122.5 | 0 |
| Residuals | 20 | 48 | 2.4 |
Here, both factors season
and size
along with their interactions are significant (low p-value). Thus, we can conclude the model contains interaction between size
and season
.
The farm decide to harvest in summer, and they wanted to find out if there are significant positive effect of harvesting large mussels compare to small mussels. Answer the question by a t-test. State the null hypothesis and the alternative hypothesis.
Here we have average percent of total weigth of eatable mussels by size and summer is,
| season | liten | stor | (all) |
|---|---|---|---|
| host | 24 | 13 | 18.5 |
| sommer | 24 | 27 | 25.5 |
| (all) | 24 | 20 | 22.0 |
The hypotheis to test if there is positive effect of harvesting large mussels than small mussels in summer season is,
\[ \begin{aligned} H_0 &: \mu_\text{large:summer } (\mu_{22}) = \mu_\text{small:summer }(\mu_{12}) \\ H_1 &: \mu_\text{large:summer } (\mu_{22}) > \mu_\text{small:summer }(\mu_{12}) \end{aligned} \]
Note that:
\[ \begin{aligned} \mu_{12} - \mu_{22} &= \mu + \tau_2 + \beta_2 + (\tau\beta)_{22} - \mu - \tau_1 - \beta_2 - (\tau\beta)_{12} \\ &= \tau_2 - \tau_1 + (\tau\beta)_{22} - (\tau\beta)_{12} \end{aligned} \]
Due to interaction term, the difference in mean is dependent on both of the factors. We can use the difference of their respective estimates, i.e, \(\bar{y}_{12} - \bar{y}_{22} = 27 - 24 = 3\).
Further,
\[ \begin{aligned} \text{var}\left(\bar{y}_{12} - \bar{y}_{22}\right) &= \frac{\sigma^2}{6} + \frac{\sigma^2}{6} = \frac{\sigma^2}{3} \\ \text{SE}\left(\bar{y}_{12} - \bar{y}_{22}\right) &= \sqrt{\frac{\hat{\sigma}^2}{3}} \\ &= \sqrt{\frac{\text{MSE}}{3}} = 0.894 \end{aligned} \]
Therefore, the test-statistics,
\[t = \frac{\left(\bar{y}_{12} - \bar{y}_{22}\right)}{\text{SE}\left(\bar{y}_{12} - \bar{y}_{22}\right)} = \frac{3}{0.894} = 3.354 \sim t_{\alpha, N-a}\]
At 95% confidence level, \(t_{\alpha, N-a} = t_{0.05, 2.4} = 2.614\)
Since, \(3.354\) > 2.614, we reject Null hypothesis and conclude that the farm can make more profit by farming larger mussels than in smaller mussels in summer.
Exercise 4
Load hospital data.
Apply a model with Healing as response, Disease, and Medicine as factors and interaction is included. Test if interaction is present.
The model is,
\[y_{ijk} = \mu + \tau_i + \beta_j + (\tau\beta)_{ij} + \epsilon_{ijk}\]
where,
| \(i\) | = | 1(D), 2(S) corresponding to Disease |
| \(j\) | = | 1(A), 2(B), 3(C) corresponding to Medicine |
| \(i\) | = | 1, 2 corresponding to replication |
| \(y_{ijk}\) | = | Healing of Disease \(i\) due to Medicine \(j\) |
| \(\epsilon_{ijk}\) | \(\sim\) | \(\text{NID}\left(0, \sigma^2\right)\) |
The ANOVA table for the model is,
| Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
|---|---|---|---|---|---|
| Medicine | 2 | 31.5 | 15.75 | 3.500 | 0.098 |
| Disease | 1 | 3.0 | 3.00 | 0.667 | 0.445 |
| Medicine:Disease | 2 | 138.5 | 69.25 | 15.389 | 0.004 |
| Residuals | 6 | 27.0 | 4.50 |
The table shows that the interaction is significant (low p-value corresponding the interaction). Thus we can conclude that the interaction is present in the model.
Execute Tukey tests on the pairs of medicine for patients having Depression and for patients having schizophrenia.
The average of factors and their combinations are as follows,
| Disease | Medicine:A | Medicine:B | Medicine:C | Medicine:(all) |
|---|---|---|---|---|
| D | 14.00 | 4.50 | 16.0 | 11.5 |
| S | 9.50 | 13.00 | 9.0 | 10.5 |
| (all) | 11.75 | 8.75 | 12.5 | 11.0 |
Thus, we have the difference in mean between the pairs of Medicine i.e, AB, AC and BC for patients having Depression and Schizophrenia as,
Schizophrenia
\[ \begin{aligned} \hat{\mu}_{A:S} - \hat{\mu}_{B:S} &= -3.5 \\ \hat{\mu}_{A:S} - \hat{\mu}_{C:S} &= 0.5 \\ \hat{\mu}_{B:S} - \hat{\mu}_{C:S} &= 4 \\ \end{aligned} \]
Depression
\[ \begin{aligned} \hat{\mu}_{A:D} - \hat{\mu}_{B:D} &= 9.5 \\ \hat{\mu}_{A:D} - \hat{\mu}_{C:D} &= -2 \\ \hat{\mu}_{B:D} - \hat{\mu}_{C:D} &= -11.5 \\ \end{aligned} \]
Further, the Tukey test criteria is,
\[ \begin{aligned} T &= q_{\alpha, (a, f)}\sqrt{\frac{\text{MSE}}{n}} = q_{0.05, (3, 6)} \sqrt{\frac{4.5}{3}} = 4.339 \times \sqrt{1.5} = 5.314 \end{aligned} \]
Medicine A and C are new medicine. Test if those are better than B for patients suffering from Depression.
Exercise 5
A student wanted to study how a medicament influenced feed consumption on rats.  In addition half of the animals were given placebo. In total 40 animals were available, and the design is balanced.
| Sex | Sterilized | Medicament | Mean | Placebo | Mean |
|---|---|---|---|---|---|
| Male | No | 21.46, 23.92, 22.56, 16.12, 21.48 | 21.108 | 25.64, 28.84, 26.00, 26.02, 23.24 | 25.948 |
| Male | Yes | 15.44, 23.54, 23.52, 17.96, 19.02 | 19.896 | 22.50, 24.48, 25.52, 24.76, 20.62 | 23.576 |
| Female | No | 18.58, 15.44, 16.12, 16.88, 17.58 | 16.920 | 17.82, 15.76, 12.96, 15.00, 19.54 | 16.216 |
| Female | Yes | 18.20, 14.56, 15.54, 16.82, 14.56 | 15.936 | 19.74, 17.48, 16.46, 16.44, 15.70 | 17.164 |
This model was applied:
\[y_{ijkl} = \mu + \alpha_i + \beta_j + \gamma_k + (\alpha\beta)_{ij} + (\alpha\gamma)_{ik} + (\beta\gamma)_{jk} + (\alpha\beta\gamma)_{ijk} + \epsilon_{ijkl}\]
Where,
| \(i\) | = | 1 (Active Medicament) or 2(Placebo) |
| \(j\) | = | 1 (Male) or 2 (Female) |
| \(k\) | = | 1 (Non sterilizes) or 2 (Sterilized) |
| \(l\) | = | 1, 2, …, 5 corresponding to replications |
- Give the Common assumptions concerning \(\epsilon_{ijkl}\). Explain why these are necessary in the model.
| Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
|---|---|---|---|---|---|
| Sex | 1 | 368.813 | 368.813 | 69.703 | 0.000 |
| Sterilized | 1 | 8.190 | 8.190 | 1.548 | 0.222 |
| Medicament | 1 | 51.121 | 51.121 | 9.662 | 0.004 |
| Sex:Sterilized | 1 | 7.868 | 7.868 | 1.487 | 0.232 |
| Sex:Medicament | 1 | 39.960 | 39.960 | 7.552 | 0.010 |
| Sterilized:Medicament | 1 | 0.372 | 0.372 | 0.070 | 0.792 |
| Sex:Sterilized:Medicament | A | B | C | D | 0.296 |
| Residuals | E | 169.318 | 5.291 | ||
| Total | F | 651.618 |
S = 2.30026 , R-Sq = G%
- Find the missing values
A
,B
,C
,D
,E
,F
andG
.
| A: | Degree of freedom of 3 factor interaction = 1 |
| B: | Sum of square of 3 factor interaction |
| \[\text{SS}_\text{Total} - \text{ sum of all other degree of freedom } = 5.975\] | |
| C: | Mean sum of square of 3 factor interaction |
| \[\text{MS}_{\alpha\beta\gamma}=\frac{\text{SS}_{\alpha\beta\gamma}}{df_{\alpha\beta\gamma}} = 5.975\] | |
| D: | F statistic corresponding to 3 factor interaction |
| \[\frac{\text{MS}_{\alpha\beta\gamma}}{\text{MS}_\text{residual}} = 1.129\] | |
| E: | Error Degree of freedom \(=abc(n-1) = 32\) |
| F: | Total Degree of freedom \(=(N - 1) = 39\) |
| G: | R-squared (variation explained by the model) |
| \[\text{R-sq} = 1 - \frac{\text{SS}_\text{E}}{\text{SS}_\text{Total}} = 74.02\] |
- What important conclusions can be detected?
Exercise 6
Mango is an excellent source for vitamin C. Assume content of vitamin C in mango are measured on 2 sites in Tanzania, A in the highland, B in the lowland. In each site 2 trees are randomly chosen and 2 fruit on each tree are also randomly chosen. Data is stored in the file called Mango.Rdata
Explain why this must be treated as a nested design.
Here, trees are choosen after the sites are selected. It is impossible to see the effect of same trees in both lowland and highland. The trees selected at lowland is different from the trees selected at highland. and the measurements are made on mangos form each of the trees (replicated twice). Thus this must be a nested design with the following hierarchical structure.
Here,
Tree:T1
fromSite:A
is different fromTree:T1
fromSite:B
and so on. It is not possible observe the effect ofTree:T1
ofSite:A
inSite:B
.Explain why it is natural to regard tree as a random effect.
Two specific trees can not be an interest of a research, rather a population of tree can be a subject of interest in the research. This research is more interested to see if there is any variation in vitamin C content in mango found in different places in Tanzania. So, it is natural to regard tree as a random effect.
Assume site to be a fixed effect State the model.
Test if there is site effect, and if there is tree effect. Write down both the null hypothesis ant the alternative hypothesis.
A model is,
\[y_{ijk} = \mu + \tau_i + \beta_{j(i)} + \epsilon_{(ij)k}\]
where, \(i = 1, 2\) for site, \(j = 1, 2\) for tree nested in site \(i\) and \(k = 1, 2\) for two replication of mangos.
The hypothesis to test the effect of tree is,
\[ \begin{aligned} H_0 &: \sigma_\beta^2 = 0 \\ H_1 &: \sigma_\beta^2 > 0 \end{aligned} \]
Mean Sq Sum Sq Df F value Pr(>F) site 8.0 8 1 1.000 0.423 site:tree 8.0 16 2 1.455 0.335 Residuals 5.5 22 4 Here, neither the site or the trees nested on site are significant. There is no evidence of tree effect in this model.
Estimate both variance parameters.
From the fitted model, we have
Err.term(s) Err.df VC(SS) 1 site (2) 2 fixed 2 site:tree (3) 4 1.25 3 Residuals - - 5.50 (VC = variance component)
From the output above, the estimates of variance parameters \(\sigma_\beta^2\) and \(\sigma^2\) are 1.25 and 5.5 respectively.
In addition, we can also find variance components using mean sum of squares as,
\[ \begin{aligned} \hat{\sigma}^2 &= \text{MS}_E = 5.5 \\ \hat{\sigma}_\beta^2 &= \frac{\text{MS}_\text{B(A)} - \text{MS}_E}{n} \\ &= \frac{8 - 5.5}{2} =1.25 \end{aligned} \]
The researchers concluded that the variance in Vitamin C is larger inside the trees than between the trees. Do you agree?
The estimate of variance components \(\hat{\sigma}^2 = 5.5\) refers to the variance within the trees and \(\hat{\sigma}_\tau^2 = 1.25\) refers to the variance between the trees. Here the variance witin the tree is larger than between the tree, the conclusion of the researcher is true. However statistical testing of this difference is out of the scope of this course.
Exercise 7
In an experiment 4 sires were used. Each sire was tried in 3 herds (different herds for each sire). From each herd 4 cows were randomly picked out. Data are saved as Nestedsires.Rdata
If we assume a nested design (herd nested in sire) draw a figure of the design. How many herds are included in the experiment? How many observations do we have?
The nested design in this experiment can be visualized as,
Here, Herd
is nested in Sire
so, Herd1
in Sire1
is different from Herd1
in Sire2
. Therefore, there are 12 herd included in the experiment. Since 4 cows are randomly selected from each herd, there are 48 observations in this experiment.
- State the model you will use for this experiment.
The model in this experiment is,
\[y_{ijk} = \mu + \tau_i + \beta_{i(j)} + \epsilon_{(ij)k}\]
Where,
\(i\) = 1, 2, …, 4 corresponding to sire
\(j(i)\) = 1, 2, 3 corresponding to herd
nested insire
\(i\)\(\epsilon_{(ij)k}\) \(\sim\) \(\text{NID}\left(0, \sigma^2\right)\) where \(k = 1, 2, 3, 4\) for each replication ( cow
) How do you explain the deviations (\(\epsilon\)’s) in this experiment?
Deviations or Error (\(\epsilon_{(ij)k}\)) is the difference between observed response and expected response. i.e., \(\epsilon_{(ij)k} = y_{ijk} - \text{E}\left(y_{(ij)k}\right)\). Here the expected response is the value you expect to observe in population for the given model. The residuls, on the other hand, is fitted deviations and are the difference between the observed values and the fitted values for the given sample.
Assume sire is a fixed factor and herd a random factor. How is the F value calculated for testing Herd effect and for testing Sire effect?
When Factor A is fixed and Factor B is random, we have following expression,
Now Use R-commander:
- Test for sire and for herd effect.
- Estimate the variance components.
- Explain to the farmers what these estimates are saying.
The farmers are sometimes asked to follow courses in the purpose of producing more milk. If the variance component for herd was extremely large, compare to the variance component for the error, would this support the opinion that we need better courses for the farmers obtaining the poorest results?
Repeat, but assume sire to be a random effect. Estimate all 3 variance components. Which variance seems to be most important? How do you estimate the variance in milk production among the population of cattle’s?
Exercise 8 (Cheese Production)
Data for Model 1 is called cheese1.Rdata
and for Model 2 is called cheese2.Rdata
Bacterial fermentation is an important part of cheese making and ripening, and specific starter cultures (bacteria) are used. However, some other bacteria may also be added in the milk, they are not starters, but can have huge influence on the final quality of the cheese.
We want to study the effect of two types of non-starters, we call them R50 and R21.
Both factors (bacteria type) have 2 levels, absent (level 1) or present (level 2). The response is the total content of free amino acid which we want as high as possible. Each combination was replicated 3 times.
The first model we use is:
\[\textbf{Model 1: } y_{ijk} = \mu + \tau_i + \beta_j + (\tau\beta)_{ij} + \epsilon_{ijk}\]
\(\tau_i\) is the effect of R50 on level \(i\), \(\beta_j\) is the effect of R21 of level \(j\), \((\tau\beta)_{ij}\) is the effect of interaction between R50 and R21 on combination \(ij\). Where, \(i = 1, 2\;\; j = 1,2 \;\; k = 1,2,3\)
The \(\epsilon_{ijk}\)’s are independent and normally distributed with expectation 0 and variance \(\sigma^2\). Also assume,
\[ \sum_{i=1}^2\tau_i = \sum_{j = 1}^2\beta_j=\sum_{i=1}^2(\tau\beta)_{ij} = \sum_{j=1}^2(\tau\beta)_{ij} = 0 \]
Use this experiment to discuss the difference between fixed and random factors.
Use this experiment to explain what we mean by interaction.
Use this experiment to explain what we mean by a balanced design.
How would you interpret \(\sigma^2\)?
Draw an interaction plot, (see Table 1).
In Table 2 are parts of an ANOVA table, finish the table and test if interaction is present.
The complete ANOVA table is,
Sum Sq Df F value R50 0.610 1 10.043 R21 0.189 1 3.102 R50:R21 0.000 1 0.003 Residuals 0.486 8 Why is it natural to exclude interaction from Model 1?
Sum of square corresponding interaction term
R50:R21
is almost zero so is the F-value. This consequently suggest that the interaction term is not significant and thus it is natural to exclude interaction from Model 1.Name the model without interaction Model 1b. Construct the ANOVA table for Model 1b.
The model with out interaction term is,
\[ \textbf{Model 1b: }y_{ij} = \mu + \tau_i + \beta_j + \epsilon_{ij}\]
ANOVA table for this model is,
Df Sum Sq Mean Sq F value Pr(>F) R50 1 0.610 0.610 11.294 0.008 R21 1 0.189 0.189 3.489 0.095 Residuals 9 0.486 0.054 Here, sum of square of Residuals has not increased than in Model 1, i.e. the additional noise in the model due to removal of interaction term is very small (almost zero).
Table 1: Sample means for each combination. 0 1 0 1.71 2.15 1 1.95 2.41 Table 2: Parts of ANOVA table Model 1 Sum Sq Df F value R50 0.610 R21 0.189 R50:R21 0.000 Residuals 0.486 Later a student realized that amino acid varied within each cheese, so she divided each cheese into 3 parts and regarded each part as replicate. The student had 4 different bacteria cultures in her experiment. The following nested model was applied:
\[\textbf{Model 2: } y_{ijk} = \mu + \tau_i + \beta_{j(i)} + \epsilon_{ijk}\]
Where, \(i = 1, 2, 3, 4 \; \; j = 1,2,3 \; \; k = 1,2,3\)
\(\tau_i\) is effect of bacteria group \(i\), \(\beta_{j(i)}\) is effect of cheese \(j\) nested in group \(i\).
The \(\beta_{j(i)}\)’s are independent and normally distributed with expectation 0 and variance \(\sigma_\beta^2\).
The \(\epsilon_{ijk}\)’s are independent and normally distributed with expectation 0 and variance \(\sigma^2\).
The \(\beta_{j(i)}\)’s and \(\epsilon_{ijk}\)’s are independent.
In addition,
\[\sum_{i = 1}^4\tau_i = 0\]
Use this experiment to explain the difference between designs with nested and crossed factors.
Why is it logical to assume cheese as a random factor?
How would you explain \(\sigma_\beta^2\) and \(\sigma^2\) to the scientist?
Table 3: Some results from Model 2 Mean Sq Sum Sq Df F value Pr(>F) Bacteria 0.086 0.259 3 Bacteria:Cheese 0.068 0.541 8 Residuals 0.010 0.242 24 Expected mean squares Bacteria (3) + 3 (2) + 9 Q[1] Bacteria:Cheese (3) + 3 (2) Residuals (3)
Estimate both variance components in Model 2 (Table 3). Test if there are effects of cheese and of bacteria group.
The student was told that it is better to use the average of the 3 parts of the cheese as replicate.
Reformulate Model 5 for this situation.
What is the response now?
Test if there is effect of bacteria group.


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These projects showcase the collecting and anaysing data to asses digital learning needs and/or evaluate ithe impact of digital learning in authentic settings
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Srikar Bharat to join the Indian cricket squad
‘It means my performances are being recognised,’ says the wicketkeeper-batsman.
by S. DinakarAndhra wicketkeeper-batsman Srikar Bharat has been asked to join the Indian team in Kolkata.
Talking to The Hindu, the 26-year-old Bharat said, “It’s a big moment. It means my performances are being recognised.”
Apparently, the Indian team-management wants to have a closer look at Bharat who has earned praise for his ’keeping skills, ahead of the tour of New Zealand.
Learned from Saha
Bharat said he learned much from Wriddhiman Saha during the India ‘A’ tour of the West Indies this year. “Saha treated me like a younger brother, we spoke about different aspects of ’keeping.”
While the basics in ’keeping were important, Bharat added, “What matters at the highest level is how you cope with and react to pressure.”
Somebody who averages 37.58 with the bat in First Class cricket, Bharat revealed he learnt much from the legendary Rahul Dravid.
Dravid’s advice
Bharat said, “Dravid sir would speak about reading the game situation, batting through sessions.”
And Bharat honed his skills, particularly standing up, playing in the first division league in Chennai, at Young Stars, for five years before moving to MRC-A.
Bharat, whose idol is M.S. Dhoni, believed the competition for ’keeping slots in the Indian team was healthy.


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Files | |
| file | axis2_handler_desc.h |
Typedefs | |
| typedef struct axis2_handler_desc | axis2_handler_desc_t |
Functions | |
| AXIS2_EXTERN const axutil_string_t * | axis2_handler_desc_get_name (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axis2_status_t | axis2_handler_desc_set_name (axis2_handler_desc_t *handler_desc, const axutil_env_t *env, axutil_string_t *name) |
| AXIS2_EXTERN axis2_phase_rule_t * | axis2_handler_desc_get_rules (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axis2_status_t | axis2_handler_desc_set_rules (axis2_handler_desc_t *handler_desc, const axutil_env_t *env, axis2_phase_rule_t *phase_rule) |
| AXIS2_EXTERN axutil_param_t * | axis2_handler_desc_get_param (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env, const axis2_char_t *name) |
| AXIS2_EXTERN axis2_status_t | axis2_handler_desc_add_param (axis2_handler_desc_t *handler_desc, const axutil_env_t *env, axutil_param_t *param) |
| AXIS2_EXTERN axutil_array_list_t * | axis2_handler_desc_get_all_params (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axis2_bool_t | axis2_handler_desc_is_param_locked (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env, const axis2_char_t *param_name) |
| AXIS2_EXTERN axis2_handler_t * | axis2_handler_desc_get_handler (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axis2_status_t | axis2_handler_desc_set_handler (axis2_handler_desc_t *handler_desc, const axutil_env_t *env, axis2_handler_t *handler) |
| AXIS2_EXTERN const axis2_char_t * | axis2_handler_desc_get_class_name (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axis2_status_t | axis2_handler_desc_set_class_name (axis2_handler_desc_t *handler_desc, const axutil_env_t *env, const axis2_char_t *class_name) |
| AXIS2_EXTERN axutil_param_container_t * | axis2_handler_desc_get_parent (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axis2_status_t | axis2_handler_desc_set_parent (axis2_handler_desc_t *handler_desc, const axutil_env_t *env, axutil_param_container_t *parent) |
| AXIS2_EXTERN void | axis2_handler_desc_free (axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axutil_param_container_t * | axis2_handler_desc_get_param_container (const axis2_handler_desc_t *handler_desc, const axutil_env_t *env) |
| AXIS2_EXTERN axis2_handler_desc_t * | axis2_handler_desc_create (const axutil_env_t *env, axutil_string_t *name) |
| typedef struct axis2_handler_desc axis2_handler_desc_t |
Type name for struct axis2_handler_desc
| AXIS2_EXTERN axis2_status_t axis2_handler_desc_add_param | ( | axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| axutil_param_t * | param | |||
| ) |
Adds given parameter to the parameter list.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| param | pointer to param |
| AXIS2_EXTERN axis2_handler_desc_t* axis2_handler_desc_create | ( | const axutil_env_t * | env, | |
| axutil_string_t * | name | |||
| ) |
Creates handler description struct instance.
| env | pointer to env pointer to environment struct | |
| name | pointer to string representing handler name, can be NULL, create function clones this |
| AXIS2_EXTERN void axis2_handler_desc_free | ( | axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Frees handler description.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN axutil_array_list_t* axis2_handler_desc_get_all_params | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Gets all parameters stored within handler description.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN const axis2_char_t* axis2_handler_desc_get_class_name | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Gets the class name. Class name is the name of the shared library file that contains the implementation of the handler.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN axis2_handler_t* axis2_handler_desc_get_handler | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Gets the handler associated with the handler description.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN const axutil_string_t* axis2_handler_desc_get_name | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Gets QName.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN axutil_param_t* axis2_handler_desc_get_param | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| const axis2_char_t * | name | |||
| ) |
Gets named parameter.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| name | parameter name string |
| AXIS2_EXTERN axutil_param_container_t* axis2_handler_desc_get_param_container | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Gets the param container.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN axutil_param_container_t* axis2_handler_desc_get_parent | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Gets the parent. Parent of handler description is of type parameter container.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN axis2_phase_rule_t* axis2_handler_desc_get_rules | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env | |||
| ) |
Gets phase rules.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct |
| AXIS2_EXTERN axis2_bool_t axis2_handler_desc_is_param_locked | ( | const axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| const axis2_char_t * | param_name | |||
| ) |
Checks if the named parameter is locked at any level
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| param_name | parameter name string |
| AXIS2_EXTERN axis2_status_t axis2_handler_desc_set_class_name | ( | axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| const axis2_char_t * | class_name | |||
| ) |
Sets the class name. Class name is the name of the shared library file that contains the implementation of the handler.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| class_name | class name string |
| AXIS2_EXTERN axis2_status_t axis2_handler_desc_set_handler | ( | axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| axis2_handler_t * | handler | |||
| ) |
Sets the handler associated with the handler description.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| handler | pointer to handler, handler description assumes the ownership of the handler |
| AXIS2_EXTERN axis2_status_t axis2_handler_desc_set_name | ( | axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| axutil_string_t * | name | |||
| ) |
Sets QName.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| name | pointer to string representing handler name of QName |
| AXIS2_EXTERN axis2_status_t axis2_handler_desc_set_parent | ( | axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| axutil_param_container_t * | parent | |||
| ) |
Gets the parent. Parent of handler description is of type parameter container.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| parent | pointer to parent parameter container struct, handler description assumes ownership of struct |
| AXIS2_EXTERN axis2_status_t axis2_handler_desc_set_rules | ( | axis2_handler_desc_t * | handler_desc, | |
| const axutil_env_t * | env, | |||
| axis2_phase_rule_t * | phase_rule | |||
| ) |
Sets phase rules.
| handler_desc | pointer to handler description | |
| env | pointer to environment struct | |
| phase_rule | pointer to phase rule struct, handler description assumes ownership of the struct |


THE INSIDER A film review by Steve Rhodes Copyright 1999 Steve Rhodes RATING (0 TO ****): *** 1/2
In a picture that deserves to be remembered at Oscar time, THE INSIDER tells a mesmerizing, true story that's in equal measure drama, thriller and mystery. Directed by Michael Mann (THE LAST OF THE MOHICANS) and starring Russell Crowe (L.A. CONFIDENTIAL) and Al Pacino, all three of whom should be nominated by the Academy, the film has your eyes glued to the screen as it examines some universal truths about integrity and risk.
With never a dull moment, the story still manages to take the time to consider the entirety of people's lives and families and delve into the minutia of a journalistic investigation. The movie will and should be compared favorably to the classic journalistic investigation story, ALL THE PRESIDENT'S MEN.
Brilliantly scripted by Eric Roth, based on a magazine article by Marie Brenner titled "The Man Who Knew Too Much," and containing a sterling supporting cast, the movie has only one possible flaw -- it's longer than normal at over two and a half hours. Its length, however, turns out to be both necessary and beneficial. Any scene that looks like cinematic fat will prove later to be a key to setting up other parts of the story. In most movies the characters have either a work life or a home life, but not both. This film takes the time to show both, and their interactions prove essential to understanding the motivation of the protagonists.
The story concerns one Dr. Jeffrey Wigand (Crowe), the former head of research at Brown and Williamson Tobacco. A proud man of high integrity, Dr. Wigand has been fired by the company, who is scared that he will break his confidentiality agreement and reveal certain hidden truths about the company.
Michael Gambon does a deliciously sinister turn as Thomas Sandefur, the CEO of Brown and Williamson and Dr. Wigand's direct boss. Sandefur, who testified with 6 other Big Tobacco executives before Congress that tobacco is not addictive, takes an ostrich approach to facts that aren't to his liking. "You declare as a badge of honor that you don't even know what makes water boil," Dr. Wigand ridicules him.
The whole situation is extremely complex as real life situations tend to be. Dr. Wigand does not want to do anything to jeopardize his severance package and the medical insurance that the company has promised. He has 2 beautiful young girls (Hallie Kate Eisenberg and Renee Olstead), whom he adores, but one has asthma, which requires expensive medical care.
Meanwhile "60 Minutes" producer Lowell Bergman (Pacino) wants to get the doctor on the show and have him interviewed by veteran journalist Mike Wallace (Christopher Plummer). Pacino is perfectly cast as the hard-charging reporter who'll do anything so long as it doesn't jeopardize his source. Bergman is as tough and honest as they come.
Nearing retirement, Wallace comes across as possessing good intentions but fatal flaws as he worries too often about "other considerations." Chief among these considerations is that the tobacco companies, who possess the most sophisticated and powerful attorneys on the face of the earth, will bring down his entire company, CBS. "History only remembers what you did last," he laments.
As a slimy lawyer with possible conflicts of interests, Gina Gershon plays CBS's lawyer, Helen Caperelli, who advises "60 Minutes" not to run the Wigand segment lest the company end up losing a multi-billion dollar law suit and being owned by Brown and Williamson.
While all of this fascinating corporate intrigue is going on, Dr. Wigand's life is falling apart. He's getting anonymous death threats, he's being followed, and his life is crumbling all around him. Crowe with his physical mannerisms makes palpable the tenseness of the situation. Constantly adjusting his glasses, fiddling with his tie and twitching his head, Dr. Wigand is a lonely man who is breaking under the strain.
The suitably ominous but never overpowering music by Pieter Bourke and Lisa Gerrard add immensely to the production. Dante Spinotti's moody, shadowy cinematography lends an ominous feeling of impending doom.
"I'm running out of heroes, man," Bergman tells Dr. Wigand.  The movie makes it obvious why. Dr. Wigand realizes, correctly, that to agree to be interviewed he has to be willing to risk everything, literally everything, in his life. If you have a loving family and expensive possessions, would you be willing to chance losing them all forever, just because your integrity demanded it? For most of us it's not a tough call. In reality, most of us would pass. It is for just that reason that this film, with its superlative acting, becomes so engrossing.
THE INSIDER runs 2:37. It is rated R for language and mature themes and would be fine for teenagers.
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Helping the Homeless College Scholarship Awards Program is designed to highlight the incredible potential of Colorado’s young people as well as the challenges which prevent too many of them from succeeding. Helping the Homeless Colorado awards multiple, $1,000 scholarships to college-bound Colorado public high school seniors who have shown incredible performance in high school by succeeding in school despite daunting obstacles.
Students must have a minimum 3.0 GPA Unweighted, have succeeded in spite of hardships such as poverty or homelessness, and have participated in activities that are helpful to others. Financial need must be demonstrated as well. For more information or to apply, please visit the scholarship provider's website.
Applicants will be asked to write an essay, receive a minimum of 3 letters of recommendation, and for their high school transcript. The selection process is very strict and the committee will be looking for individuals who have excelled and shown their willingness to put in hard work. If you are selected you will be notified and you may be asked to come in for an interview. If you are not selected you will be notified by email.
Your application MUST be done online (form below). If this cannot happen for you please contact us. Your application will be reviewed by a selected committee. Your endorsers will be contacted personally along with your school. Please make sure all of the information you provide is correct. Applications with incorrect information will be removed from the process.
Applications are due by April 20, 2019. All external documents must be mailed in by this date as well. Anything that is received after this date will be removed from the selection process. There are no extensions under any circumstances unless notified by Helping the Homeless Colorado. Thank you for applying and best of luck to you! Helping the Homeless Colorado admires all individuals who are attempting to prosper in this difficult time of their life!


How do the amounts compare in each situation? Explain why someone might choose to use a payday loan instead of a credit card or a personal loan from a friend.


rehh: Searching for Footprints of Selection using Haplotype
Homozygosity Based Tests
Functions for the detection of footprints of selection on
dense SNP data using Extended Homozygosity Haplotype (EHH)
based tests. The package includes computation of EHH, iHS
(within population) and Rsb or XP-EHH (across pairs of populations)
statistics. Various plotting functions are also included to
facilitate visualization and interpretation of the results.
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=rehh
to link to this page.


Free weekday parking at White Rock’s waterfront started today
Visitors stopping by Monday to Friday can keep their coins in their pockets till Feb. 1
by Tracy HolmesWith the start of November comes the beginning of three months of free weekday parking at White Rock’s waterfront.
Through Jan. 31, 2020, there is no charge to park anytime from Monday to Friday – and a message on the parking meters is quick to remind those who try to pay for a spot.
“Enjoy our City By the Sea! 🙂 Have a Great Day! :)” reads text that pops onto the screen.
White Rock council gave the thumbs-up to the idea in July, and to new parking rates for ‘high-demand’ and ‘value rate’ zones ($3.75 and $3.25 per hour, respectively).
READ MORE: White Rock sets new waterfront parking rates
The decision followed discussion that included a projection from the city manager that the new rates would lead to a budget shortfall “in the neighbourhood of $400,000-plus.”


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Often because they can't. In many communities, there are few (if any) providers to pay, even if you could afford the bill. More than 3 billion of us live in a country where there is only 1 psychiatrist for every 200,000 people. Psychologists are in even shorter supply.
Our team of researchers at Duke University, AI experts at X2AI, and partners in Kenya (including Jacaranda Health and the Africa Mental Health Research and Training Foundation) are adapting an evidence-based treatment called Thinking Healthy for automated delivery via mobile phone in Kenya.
Or try on a mobile phone browser at m.healthymoms.app
Zuri is a personal health coach. She is available 24/7 to chat for free via Facebook Messenger and SMS (Kenya). Try our demo.


20
| 100| # Top players | Score | Kills | Death |
|---|---|---|---|
| # Top players | Score | Kills | Death |
|---|---|---|---|
Move: AWSD
Shoot: Mouse keys hold or space
Rotate top and aim: Mouse move
Chat:
To open chat press 'Enter' key
And type a message "some bla-bla" for your team
Or "/bla-bla" for all players
Destroy: kill other teams players
Increase score: get levelUp's and improve your tank!
Take over Towers: they will join your team and help you


There are many reasons as to why masks have different numbers and letters. Professions involving medicine and manual labor require the use of a variety of masks. These masks can range from simple surgical masks to P100 charcoal filters that are powerful enough to filter out microscopic organic compounds. (ex. tear gas)
However P-100 and N-95 masks are known as air-purifying respirators due to their need to extract air from the outside. Although these masks are great at filtering air, they are still difficult to use and have a tendency to form a bad seal over one's face or the mouth leading to its drop in effectiveness. Another type of mask is a supplied air respirator paired with a tank containing clean air; however, the tank only contains a limited amount of air.
Air-purifying respirators are rated by assigning letters and numbers. The surgical mask, which has little to no protection from airborne particles, is in the lowest tier of masks that will not be rated using letters or numbers. The lettering in front of all masks determines whether it will protect against oil or not, a ‘’n” stands for no protection against oil, the “p” stands for oil proof, and an “r“ means the mask is resistant to oil. After the lettering there is a number which determines whether how much of a particle that is .3 microns or over is able to pass through. This is an extremely small size being much smaller than a human hair. After all of this there is a another ranking which is only meant for chemical masks that have the ability to cling to chemicals using a layer of charcoal. A mask with the number 100 has the ability to purify 99.97% percent of airborne particles, a 99 can purify 99% and finally a 95 will purify 95%.
This numbering is all based on the material that the mask is made of; therefore, it is safe to assume there would be one meant for larger applications like filtering air at a hospital,and this is true these filters are usually referred to as hepa filters. A private research that was conducted discovered that hepa filters had the same filtering capabilities as a N95 mask and many people capitalized on this by making their own filters using this material.


AppLaud App Help
The AppLaud App has two main functionalities - each represented by a navigation page.
- The My Apps Page works with AppLaud Cloud to run and
debug a developer's project. It can run pure JavaScript Android
PhoneGap apps directly from the cloud. No download or install is
necessary to run projects. The Download APKs feature enables downloading and running any built
Android app in the developer's workspace on the device.
- The Demo Page will run or download several different apps that
illustrate PhoneGap and jQuery Mobile's capabilities.
- No login is required for the Demo Apps Page.
- Login is required for the My Apps Page. Like AppLaud Cloud, the app uses OpenId to authenticate the user.
The same OpenId provider must be used on the device that is used in AppLaud Cloud.
This authentication allows the app to access any of the user's projects created in the cloud.
- Click Refresh Project List to see all the projects in your workspace.
- Click any specific project to run it. Note that currently only pure Android PhoneGap projects are supported. If your project modifies the Java part of the project, you will still need to
download the project to run it on the device.
- Click the W on the project to enable a Weinre debugger connection for the project. Click the project to run. In AppLaud Cloud, select Debug > Weinre Controller. Then click Elements to debug the running app.
- Click Refresh APKs List to update the list of apk files available for download to your device. This will find projects that you have previously built from AppLaud Cloud with any
of the Package options. Then click on one of the files to download the apk to your device, install, and run. If the install fails, you may need to uninstall a package of the same name from
the device. Go to Settings > Manage Applications and choose Uninstall OR If you have the SDK available, uninstall the app using adb command line interface: type adb uninstall.
- No login necessary.
- In the Demo Projects, click any specific project to run it.
- If you want to install the demo project to your device to run independently, click on it in the Demo APKs section.
Menu
- Change/Set Login Info will navigate you to the Login Page or Logout. Note that Logout will logout of the AppLaud app, but not necessarily from the Open ID provider
- Home Page lets you choose between the My Apps and Demo Pages as the starting page for future runs of the AppLaud App


College Final Year project. Food runner is one of the three games developed in this project called "Prerak Kala - Art of persuasion". Which employs Fogg's Behaviour model, to develop a persuasive game. The main purpose of this project is to develop a persuasive technology a gradual process of transformation of their behaviour through the game. The Game is build with the Unity3D Game Engine. C# is used for coding in Visual studio IDE. The Objective of the game to generate as many as food point and survive as many levels as possible, by avoiding unhealthy food and disease causing monster.


Frequently Asked Questions
Q: Will FitFriends be able to access my private information?
A: Nope! The only information we use is the information you provide us.
Q: How will I get in touch with my FitFriend?
A: You can use the contact information provided in your FitFriend's bio.


{% extends 'General/base.html' %} {% load static %} {% block content %} {% include 'User/messages.html' %}
Best Store is the one place for you to find all your needs. Contact us with any of your query, our reps wil do their best to support you!


REVOLUTION SLIDER
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Interactively productize viral systems and functional networks. Professionally fabricate cross functional. Appropriately mesh team building expertise via cutting-edge schemas. Intrinsicly reconceptualize distinctive infrastructures rather than.
Credibly promote optimal "outside the box" thinking whereas cost effective resources. Collaboratively coordinate focused services without customized collaboration and idea-sharing. Progressively administrate fully tested benefits. Distinctively synergize impactful infrastructures after parallel methodologies. Authoritatively impact long-term high-impact technology through cost effective methods of empowerment. Seamlessly network premium mindshare via emerging bandwidth. Quickly.
We do what we love & we love what we do
Holisticly harness just in time technologies via corporate scenarios. Intrinsicly predominate ubiquitous outsourcing through an expanded array of functionalities.
Holisticly harness just in time technologies via corporate scenarios. Intrinsicly predominate ubiquitous outsourcing through an expanded array of functionalities.
Holisticly harness just in time technologies via corporate scenarios. Intrinsicly predominate ubiquitous outsourcing through an expanded array of functionalities.
Holisticly harness just in time technologies via corporate scenarios. Intrinsicly predominate ubiquitous outsourcing through an expanded array of functionalities.
Holisticly harness just in time technologies via corporate scenarios. Intrinsicly predominate ubiquitous outsourcing through an expanded array of functionalities.
Holisticly harness just in time technologies via corporate scenarios. Intrinsicly predominate ubiquitous outsourcing through an expanded array of functionalities.
The best thing is when our work become part of client success
It’s really, an extraordinary theme
Now, this is cool! Kudos to the guys behind it.
The theme is getting better and better
Now it's time to build a business relationship, let's create something that matter
ADDRESS
12345 North Main Street
New York
22334455
PHONE
Phone 1: 1-(558) 968-0400 (Quotation)
Phone 2: 1-(558) 968-1234 (General Inquiries)
EMAIL
Email : hello@yourdomain.com


Selected by the ALA ACRL Instruction Session for the PRIMO database of Peer Reviewed Materials Online


--- layout: base eleventyNavigation: key: All-purpose parent: Cleaning order: 2 ---
For
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JEOPARDY
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500
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MailMan v2.0
for (var a=0; a
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Hibersap is a Java library that helps developers to call business logic and access data in SAP backends.
Hibersap defines a set of Java annotations to map SAP function modules to Java classes as well as a small and clean API to execute these function modules and handle transaction and security aspects.
Hibersap’s programming model is quite similar to those of modern O/R mappers, significantly speeding up the development of SAP interfaces. This makes it much easier to write the integration code. You don’t have to write tons of boilerplate code which makes your applications much cleaner while keeping up maintainability.
Under the hood, Hibersap either uses the SAP Java Connector (JCo) or a JCA compatible resource adapter to communicate with the SAP backend. While retaining the benefits of JCo and JCA like transactions, security, connection pooling, etc., you can focus on writing your business logic. To switch between JCo and JCA you just need to change Hibersap configuration.


hunting_areas
Metadata also available as
Metadata:
- Identification_Information:
-
- Citation:
-
- Citation_Information:
-
- Originator: DOFAW/DLNR, Wildlife Biologist
- Publication_Date: 20150509
- Title: hunting_areas
- Geospatial_Data_Presentation_Form: vector digital data
- Description:
-
- Abstract:
-
Public Hunting Areas for the State of Hawaii (Game Birds and Game Mammals) as described in Hawaii Administrative Rules, Title 13, DLNR, Subtitle 5, Forestry and Wildlife, Part 2, Wildlife, Chapters 122 and 123, and as depictd in DOFAW's Hunting Regulation Guides. See <http://dlnr.hawaii.gov/dofaw/files/2013/09/HAR-122-Game-Birds.pdf> and <http://dlnr.hawaii.gov/dofaw/files/2013/09/HAR-123-Game-Mammals.pdf> for legal interpretations.Using the descriptions in the the Hawaii Administrative Rules Title 13, Chapters 122 and 123, the boundaries are based off of State of Hawaii's Tax Map Key (TMK) and Reserves data layer.Sections closed to hunting after the approved 2015 Rules are indicated. New or modified hunting areas after the approved 2015 Rules are not indicated and will be updated on the next Hunting Rules update.
- Purpose:
-
The public hunting area boundaries are a cartographic representation of the Hawaii Administrative Rules Title 13, DLNR, Subtitle 5, Forestry and Wildlife, Part 2, Wildlife, Chapters 122 and 123 Rules Regulating Game Mammal and Game Bird Hunting areas, 2015.
- Time_Period_of_Content:
-
- Time_Period_Information:
-
- Single_Date/Time:
-
- Calendar_Date: 20151230
- Currentness_Reference: State of Hawaii
- Status:
-
- Progress: In work
- Maintenance_and_Update_Frequency: As needed
- Spatial_Domain:
-
- Bounding_Coordinates:
-
- West_Bounding_Coordinate: -159.784088
- East_Bounding_Coordinate: -154.773220
- North_Bounding_Coordinate: 22.213352
- South_Bounding_Coordinate: 18.950712
- Keywords:
-
- Theme:
-
- Theme_Keyword_Thesaurus: None
- Theme_Keyword: Public Hunting Areas
- Access_Constraints: None
- Use_Constraints:
-
The public hunting area boundaries are a cartographic representation of the Hawaii Administrative Rules Title 13, DLNR, Subtitle 5, Forestry and Wildlife, Part 2, Wildlife, Chapters 122 and 123 Rules Regulating Game Mammal and Game Bird Hunting areas, 2015. Sections closed to hunting after the approved 2015 Rules are indicated. New or modified hunting areas after the approved 2015 Rules are not indicated and will be updated on the next Hunting Rules update.Any question please contact DOFAW's Wildlife Biologist for clarification on updated hunting areas.
- Point_of_Contact:
-
- Contact_Information:
-
- Contact_Organization_Primary:
-
- Contact_Organization: DOFAW/DLNR
- Contact_Position: Wildlife Biologist
- Contact_Voice_Telephone:<PHONE_NUMBER>
- Native_Data_Set_Environment:
-
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS <IP_ADDRESS>33
- Spatial_Data_Organization_Information:
-
- Direct_Spatial_Reference_Method: Vector
- Point_and_Vector_Object_Information:
-
- SDTS_Terms_Description:
-
- SDTS_Point_and_Vector_Object_Type: GT-polygon composed of chains
- Point_and_Vector_Object_Count: 186
- Spatial_Reference_Information:
-
- Horizontal_Coordinate_System_Definition:
-
- Planar:
-
- Map_Projection:
-
- Map_Projection_Name: NAD 1983 HARN UTM Zone 4N
- Transverse_Mercator:
-
- Scale_Factor_at_Central_Meridian: 0.9996
- Longitude_of_Central_Meridian: -159.0
- Latitude_of_Projection_Origin: 0.0
- False_Easting: 500000.0
- False_Northing: 0.0
- Planar_Coordinate_Information:
-
- Planar_Coordinate_Encoding_Method: coordinate pair
- Coordinate_Representation:
-
- Abscissa_Resolution: 0.0001
- Ordinate_Resolution: 0.0001
- Planar_Distance_Units: meter
- Geodetic_Model:
-
- Horizontal_Datum_Name: D North American 1983 HARN
- Ellipsoid_Name: GRS 1980
- Semi-major_Axis: 6378137.0
- Denominator_of_Flattening_Ratio:<PHONE_NUMBER>01
- Entity_and_Attribute_Information:
-
- Detailed_Description:
-
- Entity_Type:
-
- Entity_Type_Label: hunting_areas
- Entity_Type_Definition: Hunting area polygons
- Entity_Type_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: OBJECTID
- Attribute_Definition: Internal feature number.
- Attribute_Definition_Source: Esri
- Attribute_Domain_Values:
-
- Unrepresentable_Domain:
-
Sequential unique whole numbers that are automatically generated.
- Attribute:
-
- Attribute_Label: SHAPE
- Attribute_Definition: Feature geometry.
- Attribute_Definition_Source: Esri
- Attribute_Domain_Values:
-
- Unrepresentable_Domain: Coordinates defining the features.
- Attribute:
-
- Attribute_Label: Unit_Name
- Attribute_Definition:
-
Name of Hunting Area for both mammal and bird hunting. Hunting area may have two different unit names for mammal hunting and bird hunting.
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: NOTE_
- Attribute_Definition: Disclaimer
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: Mammal_Uni
- Attribute_Definition: Mammal Unit name
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: Bird_Unit
- Attribute_Definition: Bird Unit name
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: SHAPE_Area
- Attribute_Definition: Area of feature in internal units squared.
- Attribute_Definition_Source: Esri
- Attribute_Domain_Values:
-
- Unrepresentable_Domain: Positive real numbers that are automatically generated.
- Attribute:
-
- Attribute_Label: Descriptio
- Attribute_Definition: Description of the hunting area
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: Game_Desig
- Attribute_Definition: Game designation for the hunting unit.
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: GIS_Acres
- Attribute_Definition: Calculated 2D acreage from ArcGIS.
- Attribute_Definition_Source: ESRI
- Attribute:
-
- Attribute_Label: Status
- Attribute_Definition: Status of the hunting unit. Is there hunting, what type.
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: Note_Cont
- Attribute_Definition: Disclaimer
- Attribute_Definition_Source: DOFAW
- Attribute:
-
- Attribute_Label: LinkTo_Isl
- Attribute:
-
- Attribute_Label: LinkToAdmi
- Attribute:
-
- Attribute_Label: LinkToAd_1
- Attribute:
-
- Attribute_Label: LinkToAd_2
- Attribute:
-
- Attribute_Label: Shape_Length
- Attribute_Definition: Length of feature in internal units.
- Attribute_Definition_Source: Esri
- Attribute_Domain_Values:
-
- Unrepresentable_Domain: Positive real numbers that are automatically generated.
- Attribute:
-
- Attribute_Label: Island
- Attribute_Definition: Island location of the hunting unit.
- Attribute_Definition_Source: DOFAW
- Metadata_Reference_Information:
-
- Metadata_Date: 20171031
- Metadata_Contact:
-
- Contact_Information:
-
- Contact_Organization_Primary:
-
- Contact_Organization: DOFAW/DLNR
- Contact_Person: Dwight Matsuwaki
- Contact_Position: GIS and Geodatabase Coordinator
- Contact_Address:
-
- Address_Type: physical
- Address: 1151 Punchbowl Street Rm 325
- City: Honolulu
- State_or_Province: Hawaii
- Postal_Code: 96813
- Contact_Voice_Telephone:<PHONE_NUMBER>
- Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
- Metadata_Standard_Version: FGDC-STD-001-1998
- Metadata_Time_Convention: local time
- Metadata_Use_Constraints:
-
The public hunting area boundaries are a cartographic representation of the Hawaii Administrative Rules Title 13, DLNR, Subtitle 5, Forestry and Wildlife, Part 2, Wildlife, Chapters 122 and 123 Rules Regulating Game Mammal and Game Bird Hunting areas, 2015. Any question please contact DOFAW's Wildlife Biologist for clarification.
- City: Honolulu
Generated by mp version 2.9.12 on Tue Oct 31 16:51:43 2017


Location
Id:
70
Name:
Snuffles' Dream
Tipo:
Dream
Dimension:
Dimension C-137
Residents:
['https://rickandmortyapi.com/api/character/397', 'https://rickandmortyapi.com/api/character/398']


‘Who Did this?’ India-Style Boris Johnson’s ‘Election Campaign’ Video has Netizens in Splits
New Delhi (Sputnik): Ahead of a fast-approaching UK General Election set for 12 December, a traditional Indian style election campaign video is grabbing all the attention on social media.
The video, pitching Boris Johnson as UK’s next prime minister and asking voters to support him, has gone viral on social media, prompting an avalanche of hilarious reactions and memes.
The elaborate video features Johnson himself, Indian Prime Minister Narendra Modi, Indian High Commissioner Ruchi Ghanshyam, among others.
However, it is yet to be confirmed if it is an actual election campaign video or just a comedy spoof.
The background score of the one-and-a-half minute video clip features a female singer chorusing: “Jaago jaago! Chunav firse aya hai Boris ko hume jitana hai” (Wake up! Wake up! It’s election time, and we have to ensure Boris wins).
The video, made with precision, seems to be an election pitch for British-Indian voters in the UK.
While a Twitter user jokingly called the video “revenge for 200 years of colonisation”, a journalist with the Indian daily took it rather seriously and said the Minister of External Affairs should protest over it.
The video surfaced on the Internet at the same time as British Prime Minister Boris Johnson visited Shri Swaminarayan Temple in London, and addressed the Indian diaspora, expressing his concerns over “anti-Hindu” and “anti-India” sentiments in the UK. According to the United Kingdom Census 2011, more than 1,451,862 people of Indian ethnicity reside in the UK (not including those who categorised themselves as having mixed ethnicity).


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WILLIAM MINWOO YOUM
ABOUT
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% include admin_common_required.html %>
<% include admin_common_header.html %>
Dashboard
General info
log
info
security
info
test
test
<% include admin_common_footer.html %>


In order to show how one might approach a non-trivial project with TactJS, I decided to recreate Pong. This case study is split into several iterations which can be downloaded individually and serve to track the progress toward an optimal solution.
I'm aware that there are HTML5 techniques for accomplishing the objectives of this case study, and if you were really tasked with creating a game for the browser without a plugin like Flash I would suggest you look into them. The real purpose of this case study however, is to explore the possibilities of TactJS, and something like Pong lets us have some fun along the way.
The stated objectives of Case Study :: Pong are thus:
The solution must also meet the following criteria:
This case study is a work in progress. Please continue to check for updates to the iteration list. If you would like to try your hand at a solution using TactJS, by all means let me know what you come up with by sending your solution to pong-solutions@tactjs.com


Dr. Vladimir Lapin
Research Fellow
Home
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(PDF)
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Resonant over-reflection of waves by jets in a rotating ocean
Ph.D. Thesis, University of Limerick, Ireland. (2011)
On stability of the plane flows of visco-plastic fluids
Diploma Thesis in Russian, Moscow State University, Russia. (2008)
Research Navigation
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Ocean Tides
Thin Film Flows
Resonant Over-Reflections
Non-Newtonian fluids
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Over the past 50 years, this company has worked on projects that have changed millions of lives. Our designs can be seen all around the world. Here we have power plants in Australia, Japan, anf the US.


In recent weeks, as the coding challenges in Phase 0 have become more challenging, the one thing which has really helped me to work through each problem has been Test Driven Development. Essentially, this is a process where I would write the test code for a program before even starting on it. This makes sure that I have my goals for the program in front of me before beginning. As I go along in the program, I continue to write and run tests which incrementally shape and evaluate the program.
Here's a simple example of some tests written for a Ruby program.
# ============== TESTS ================ #
p super_fizzbuzz([1,2,3]) == [1,2,"Fizz"]
p super_fizzbuzz([15,5,3,1]) == ["FizzBuzz","Buzz","Fizz",1]
This is a program which essentially takes in an array of integers and returns a new array with the words "Fizz", "Buzz", and "FizzBuzz" in various positions based on the conditions set in the program.
The tests here though are initiated with the "p" character, and the method call is set "==" to the expected output. This will return "true" or "false" based on if that output is fulfilled by the program.
When writing a program, regardless of its simplicity, it's really important to ensure that it's doing exactly what you want it to do. Test Driven Development allows you to have full control of what is going on in the program at any point in time. This is why it's crucial to create these tests before you begin the program, and as you go along. This process has been invaluable for me in recent weeks, and I hope this post was useful for you!
Thanks for reading,
Vineet Rastogi


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Join global and community chats that are completely anonymous and full of new friends. Discuss Indie Games, DIY Projects, and Nightcore, or get even more involved by taking part in Roleplay skits and Singing Competitions! Use thousands of handmade stickers (like tofu dog) to show people exactly how you’re feeling, then make new friends with the Internet folk you click with (because who doesn’t like tofu dog?!).
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The NP231 has an aluminum case and it should have a tag on
the back saying New Process Gear, Model 231. New versions
of the NP231 are refered to as NVG231 or NV231 which stands
for New Venture Gear. The tag on the back of the transfer
case will reflect the name change. Only the name is different.
A NV231 HD model is used in some ZJs. Presumably this is a
"heavy duty" version for Jeeps with the big V8s.
There are versions of this chain driven
transfer case that take 21 and 23 spline input shafts. The 23
spline version is used behind the AX-15 and the 21 spline is
used behind the AX-5 and the BA 10/5. The output for the front
driveshaft is on the drivers side. Low range is 2.72 and high
is 1.00.
If you own a 21 spline NP231 and you want to swap in a 23 spline
transmission, you can either look for a cheap 23 spline NP231 at
the junk yard or go to your local Jeep Parts Dealer and order up
a new input shaft part #5300-6085. This is the part you need to
convert your NP231 to 23 spline input.
Usage
Since 1988, the NP231 has been the "Command Trac" transfer case used
in Cherokees (XJ), Comanches (MJ), and Wranglers (YJ). It has been
the "Command Trac" transfer case in the Grand Cherokee (ZJ) since its
introduction. The new Wrangler (TJ) continues to use the NP231, but the
NP231 used in the TJ has a different tail housing that
allows the removal of the drive shaft with out losing transfer
case fluid.
Both version of the NP231 used in the Wranglers have an over all
length that is long for a short wheel base vehicle. This can cause
driveline vibration and premature u-joint failure especially
for a lifted vehicle. There are kits to convert the tail housing
to a standard yoke to allow the use of a longer rear drive shaft.
There is also a 4:1 low range reduction kit for the NP231.
Wrangler are only available with "Command Trac", so the NP231 or NP207
are the only transfer cases available from the factory in any Wrangler
model.


Who would be responsible if Nawaz did not return, questions NAB
by https://www.facebook.com/dunyanewsISLAMABAD (Dunya News) – NAB has questioned who would be responsible if former premier does not return back to the country after his bail expires.
NAB sources said Nawaz is accused in 3 cases while convicted in one case. Sources added that government must ensure return of Nawaz Sharif.
NAB did not object to his bail on human grounds and its discretion of government to send him abroad.
Earlier, it surfaced that federal cabinet is likely to approve conditional removal of former prime minister and Pakistan Muslim League-Nawaz (PML-N) supremo Nawaz Sharif’s name from the Exit Control List (ECL).
Sources said that the former prime minister will have to provide guarantee to travel abroad. The federal cabinet is considering the option of submitting bonds as surety.
Sources said that Nawaz Sharif’s name would be removed from the ECL if he fulfills the conditions of the Sub-Committee.
The Sub-Committee has also demanded the lawyers of the PML-N supremo to handover some assets.
The subcommittee will send a summary to the federal cabinet after approval of conditions from Nawaz Sharif and the committee will take final decision till 9pm.


Gianpaolo M. Impronta
Data is the future.
Data is the future.
My name is Gianpaolo Martins Impronta. I was born in Rio de Janeiro, went to ABMDPII (Academia de Bombeiro Militar Dom Pedro II), where I graduated as a Liutenant Firefighter and then went to Infnet where I'm still studying Databases and Business Inteligence. Besides, I'm taking some online courses, like edX, where I'm taking Harvard's CS50, and Udacity, where I'm taking Intro into Programming Nanodegree.
CS50: Introduction to Computer Science
Intro into Programming Nanodegree
Banco de Dados e BI


500_graphminer.py
import itertools
class Solution:
def countSubgraphsForEachDiameter(self, n: int, edges: List[List[int]]) -> List[int]:
graph = defaultdict(set)
for a,b in edges:
graph[a].add(b)
graph[b].add(a)
print(graph)
result = [0]*(n-1)
for i in range(2, n+1):
for comb in itertools.combinations(range(1,n+1), i):
unseen=set(comb)
def dist(node):
unseen.remove(node)
max_dist = 0
terminal_dist=0
for i in graph[node]:
if i in unseen:
c = dist(i)
max_dist = max(max_dist, max(c['max'], 1+c['terminal']+terminal_dist))
terminal_dist = max(terminal_dist, c['terminal']+1)
max_dist = max(max_dist, terminal_dist)
return {'terminal':terminal_dist, 'max':max_dist}
d = dist(comb[0])
if len(unseen)==0:
result[d['max']-1]+=1
return result