All functions
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calc_lik_matrix_common_cov
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calc_lik_matrix_common_cov |
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calc_lik_matrix
|
Compute matrix of conditional likelihoods. |
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calc_lik_vector
|
Compute conditional likelihoods for bhat vector. |
|
calc_relative_lik_matrix
|
Calculate matrix of relative likelihoods. |
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compute_alt_loglik_from_matrix_and_pi
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Compute vector of alternative loglikelihoods from a matrix of log-likelihoods and fitted pi |
|
compute_loglik_from_matrix_and_pi
|
Compute total loglikelihood from a matrix of log-likelihoods and fitted pi |
|
compute_null_loglik_from_matrix
|
Compute vector of null loglikelihoods from a matrix of log-likelihoods |
|
compute_posterior_matrices_common_cov_R
|
Compute posterior matrices (when error covariance V_j is equal for all observations j) |
|
compute_posterior_matrices_general_R
|
Compute posterior matrices (general version) |
|
compute_posterior_matrices
|
Compute posterior matrices. |
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compute_posterior_weights
|
compute posterior probabilities |
|
compute_vloglik_from_matrix_and_pi
|
Compute vector of loglikelihoods from a matrix of log-likelihoods and fitted pi |
|
contrast_matrix
|
Create contrast matrix |
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cov_all_zeros
|
Compute an R by R matrix of all 0s |
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cov_canonical
|
Compute a list of canonical covariance matrices |
|
cov_ed
|
Perform "extreme deconvolution" (Bovy et al) on a subset of the data |
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cov_equal_effects
|
Compute an R by R matrix of all 1s |
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cov_first_singleton
|
Compute all the singleton matrices corresponding to condition-specific effects in first condition only; used for testing purposes |
|
cov_from_factors
|
produce list of rank 1 covariance matrices corresponding to rows of f |
|
cov_pca
|
Perform PCA on data and return list of candidate covariance matrices |
|
cov_simple_het
|
Compute covariance matrices with diagonal element 1 and off-diagonal element corr |
|
cov_udi_single
|
computes the covariance matrix for a single UDI model |
|
cov_udi
|
Compute a list of covariance matrices corresponding to the
"Unassociated", "Directly associated" and "Indirectly associated" models |
|
ed_wrapper
|
Fit extreme deconvolution to mash data |
|
estimate_null_correlation_simple
|
Estimate null correlations (simple) |
|
estimate_null_correlation
|
Estimate null correlations |
|
expand_cov
|
Create expanded list of covariance matrices expanded by grid, Sigma_lk = omega_l U_k |
|
extreme_deconvolution
|
Density estimation using Gaussian mixtures in the presence of noisy,
heterogeneous and incomplete data |
|
get_estimated_pi
|
Return the estimated mixture proportions |
|
get_log10bf
|
Return the Bayes Factor for each effect |
|
get_n_significant_conditions
|
Count number of conditions each effect is significant in |
|
get_pairwise_sharing_from_samples
|
Compute the proportion of (significant) signals shared by magnitude in each pair of conditions |
|
get_pairwise_sharing
|
Compute the proportion of (significant) signals shared by magnitude in each pair of conditions, based on the poterior mean |
|
get_samples
|
Return samples from a mash object |
|
get_significant_results
|
Find effects that are significant in at least one condition |
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initialize_pi
|
Initialize mixture proportions - currently by making them all equal |
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is_common_cov_Shat_alpha
|
Check that all rows of Shat_alpha are the same. |
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is_common_cov_Shat
|
Check that all covariances are equal (Shat). |
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make_names
|
Create names for covariance matrices |
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mash_1by1
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Perform condition-by-condition analyses |
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mash_compute_loglik
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Compute loglikelihood for fitted mash object on new data. |
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mash_compute_posterior_matrices
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Compute posterior matrices for fitted mash object on new data |
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mash_compute_vloglik
|
Compute vector of loglikelihood for fitted mash object on new data. |
|
mash_plot_meta
|
Plot metaplot for an effect based on posterior from mash |
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mash_set_data_contrast
|
Create a data object for mash contrast analysis |
|
mash_set_data
|
Create a data object for mash analysis. |
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mash_update_data
|
Update the data object for mash analysis. |
|
mash
|
Apply mash method to data |
|
optimize_pi
|
Estimate the mixture weights by maximum (penalized) likelihood |
|
posterior_cov
|
posterior_cov |
|
posterior_mean_matrix
|
posterior_mean_matrix |
|
posterior_mean
|
posterior_mean |
|
scale_cov
|
Scale each covariance matrix in list Ulist by a scalar in vector grid |
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sim_contrast1
|
Create simplest simulation, cj = mu 1
data used for contrast analysis |
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sim_contrast2
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Create simulation with signal data used for contrast
analysis. |
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simple_sims
|
Create some simple simulated data for testing purposes |
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simple_sims2
|
Create some more simple simulated data for testing purposes |
|
udi_model_matrix
|
Create a matrix whose rows contain all possible
combinations of the U,D,I models that are allowed. |


Paul F. Jensen
Home
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Contact
Contact
You can email me at:
paulfJensen4@gmail.com


Playing Elixr
Playing Elixr is like being part of an interactive story.
You control the actions of one of the main characters, and the GM responds by telling you how your decisions unfold and affect the world around you.
To assist in focusing on gameplay, rather than dispute what a character should, or shouldn't, be allowed to do, these following rules make for a reference point.
The GM is Always Right
All of the rules listed in this reference are considered guidelines, not The Holy Word of God.
Your GM may decide it's in the interest of the player's experience to bend, break, or change a particular rule.
You are free to voice any dissatisfaction with a rule change your GM implements, but during the session you should yield to their decision.
After the session is over, you may discuss the rule change with your GM to see if a compromise is in order.
A good GM will be willing to listen to their player's feedback.
The Dice
In order for things to be interesting—and so a character doesn't simply declare themselves God—there must be a chance for a character to fail.
This is where the dice come in.
The results of your roll will determine whether or not you successfully scale the cliffside, sneak away from the dragon, or stab the orc in the back.
Any action that has a chance of failure should require a dice roll.
There are 8 types of dice used in Elixr. Each die has a different number of sides. They are:
-
20-Sided (Primary, most important)
-
12-Sided
-
10-sided
-
8-Sided
-
6-Sided (Standard die found in most board games)
-
4-Sided
-
Percentile (two 10-sided dice, one of which represents the 'tens' place)
Dice Notation
When dice are called to be rolled, a notation is used to determine how many of each type.
The notation involves two numbers, one on either the side of the letter 'd'.
The number before the 'd' is how many dice are to be rolled.
The number following the 'd' is what type of dice is rolled.
 This is the most commonly used die-roll in the game.
-
2d6 Indicates two dice, each with 6-sides, are to be rolled. The possible outcomes of such a roll would be 2-12.
-
3d8 Indicates three, eight-Sided dice, are to be rolled. The possible outcomes of such a roll would be 3-24.
-
20d4 Indicates a total of 20 dice are to be rolled, each of the individual dice have 4-sides. The possible outcome of such a roll would be 20-80.
Critical & Fumble
When rolling 1d20, some special circumstances apply if the result of the roll is 1 or 20 before any other modifiers are applied.
Regardless of the roll, the Speed Cost of the action is fully applied.
Critical
If the result of rolling 1d20 before any other modifiers are applied is 20, this is referred to as a critical.
A critical indicates an automatic success in whatever the character was attempting to do, regardless of the Difficulty or Defense the character is attempting to overcome.
This assumes that what the character is attempting is physically possible, and the GM reserves veto rights.
Fumble
If the result of rolling 1d20 before any other modifiers are applied is 1, this is referred to as a fumble.
A fumble indicates an automatic failure in whatever the character was attempting to do.
A retry can be made immediately, assuming a character has enough Movement Speed to attempt again that turn,
and that any negative repercussions of failing the action are resolved.
Advantage & Disadvantage
Sometimes, circumstances are particularily conducive to an action a character may be attempting.
In such cases, a GM may grant Advantage to a character attempting that action.
Other times, circumstances are adverse to an action a character is attempting. In such cases, a GM may give a character Disadvantage when attempting that action.
Advantage
If a GM has granted your character Advantage when attempting an action, you may roll 1d20 twice, and take the higher result, discarding the other.
Disadvantage
If a GM has given your character Disadvantage when attempting an action, you must roll 1d20 twice, and take the lower result, discarding the other.
Multiple Circumstances
At most, a player will only roll 1d20 twice per action. There is no such thing as "Double Advantage" or "Triple Disadvantage".
If the number of favorable circumstances is greater than the number of unfavorable circumstances, the character gets to keep their Advantage.
If the number of unfavorable circumstances is greater than the number of favorable circumstances, the character still has Disadvantage.
If the number of favorable circumstances equals the number of unfavorable circumstances, the Advantage and Disadvantage cancel out, and the character will roll normally.
Tie Goes to the Defender
When actions are performed to the detriment of another creature or character, that creature or character is known as the defender.
Attacks
When an attacker rolls to hit an opponent, if the result is less than or equal to the defender's Defense, the attack is unsuccessful.
Skill Checks
Sometimes a character will make a skill check that allows others to make opposing skill checks.
If failure at a check would lead to negative repercussions, such as being caught sneaking with a stealth check, they are the defender.
The creature or character rolling an opposing check must therefore exceed the defender's check.
Round Down
Sometimes, odd numbers are called to be halved.
Unless another rule states specifically otherwise, round down to the nearest even number before dividing by two.
Not everything needs to be solved with a sword
Just because a monster looks hideous doesn't necessarily mean it's evil, or that your character has the full picture.
Stab first, ask questions never isn't always the best approach.
Often, if your first instict is to kill anything that moves, you'll have a better experience just playing a video game.
No Player Knowledge
Just because you the player knows that shapeshifters are vulnerable to silver, does not mean that the small town farmboy you are role-playing as does.
A lot of the time you will need to feign ignorance for the things that your character just wouldn't know.
Unless your character was present when receiving information, your character is not allowed to react to information that they simply would not know.
Facets of Gameplay
There are 3 primary facets of gameplay: Combat, Social Interaction, and Exploration.


Read General Transit Feed Specification (GTFS) zipfiles into a list of R dataframes. Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. Please see the GTFS documentation here for more detail: <http://gtfs.org/>.
| Version: | 0.3.5 |
| Depends: | R (≥ 3.2.4) |
| Imports: | dplyr, zip, tibble, readr, httr, htmltools, magrittr, stringr, assertthat, scales, here, rlang, sf, lubridate, tidyr, tools |
| Suggests: | testthat, knitr, rmarkdown |
| Published: | 2018-10-28 |
| Author: | Tom Buckley [aut, cre], Danton Noriega-Goodwin [aut], Flavio Poletti [aut], Angela Li [aut], Mark Padgham [ctb], Elaine McVey [ctb], Charles Hans Thompson [ctb], Michael Sumner [ctb], Patrick Hausmann [ctb], Bob Rudis [ctb], Kearey Smith [ctb], Dave Vautin [ctb], Kyle Walker [ctb] |
| Maintainer: | Tom Buckley <tom at tbuckl.com> |
| BugReports: | https://github.com/r-transit/tidytransit |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | https://github.com/r-transit/tidytransit |
| NeedsCompilation: | no |
| CRAN checks: | tidytransit results |
| Reference manual: | tidytransit.pdf |
| Vignettes: |
Vignette Title tidytransit-introduction |
| Package source: | tidytransit_0.3.5.tar.gz |
| Windows binaries: | r-devel: tidytransit_0.3.5.zip, r-release: tidytransit_0.3.5.zip, r-oldrel: tidytransit_0.3.5.zip |
| OS X binaries: | r-release: tidytransit_0.3.5.tgz, r-oldrel: tidytransit_0.3.5.tgz |
| Old sources: | tidytransit archive |
Please use the canonical form https://CRAN.R-project.org/package=tidytransit to link to this page.


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DisasterMap
The application DisasterMap was implemented during the class Geoinformation in Society at Institute for Geoinformatics of the Westfälische-Wilhelms-Universität in the Wintersemester 2018/2019
DisasterMap is a modern, responsive web interface, providing data about volcanos in Iceland. It is designed to educate tourists and people living there about the risks and the intended behaviour in cases of emergency when a volcano eruption takes place. This should mitigate the effects of volcanic eruptions in Iceland.
Data
It makes use of linked data that was prepared in the Virtuoso TripleStore as RDF-Triples. Freely available data about Iceland prepared in shapefiles was converted to RDF-Triples to and uploaded to the TripleStore. By the use of existing vocabularies the new shapefile data was linked to other datasets. In total six different shapefiles were used containing: places (cities, villages, ...), waterways, the border, roads, volcanos and natural features.
Goals
The overall goal of the application is to mitigate the effects of volcanic eruptions in Iceland through providing information and educating the people about these natural disasters. This should raise awareness and start a more detailed thinking about volcanic eruptions by using freely available data and provide a meaningful visualization of it.
Technologies
To convert the shapefiles to RDF-Triples the programming language R was used together with the R-package "rdflib". This enables the automatic creation of an RDF object and also the serialization of it to a turtle file. For the visualization the standard technologies of web-programming: HTML, CSS and JavaScript were used. For the design of the web application the JavaScript library Bootstrap was used. To get the interactive map the JavaScript library Leaflet was used which makes it possible to load the different datasets as layers on a base map. To create educational information for the users we used piktocharts.


The grammar rules for a language determine only the syntax. The semantics are determined by the semantic values associated with various tokens and groupings, and by the actions taken when various groupings are recognized.
For example, the calculator calculates properly because the value associated with each expression is the proper number; it adds properly because the action for the grouping x + y is to add the numbers associated with x and y.
In a simple program it may be sufficient to use the same data type for the semantic values of all language constructs. But in most programs, you will need different data types for different kinds of tokens and groupings. For example, a numeric constant may need type int or float, while a string constant or an identifier might need type string.
To use more than one data type for semantic values in one parser, Ocamlyacc requires you to do: Choose one of those types for each symbol (terminal or nonterminal) for which semantic values are used. This is done for tokens with the %token Ocamlyacc declaration (see Token Type Names) and for groupings with the %type Ocamlyacc declaration (see Nonterminal Symbols).
An action accompanies a syntactic rule and contains Ocaml code to be executed each time an instance of that rule is recognized. The task of most actions is to compute a semantic value for the grouping built by the rule from the semantic values associated with tokens or smaller groupings.
An action consists of Ocaml statements surrounded by braces. All rules have just one action at the end of the rule, following all the components.
The Ocaml code in an action can refer to the semantic values of the components matched by the rule with the construct $n, which stands for the value of the nth component. The value of the evaluation of the action is the value for the grouping being constructed.
Here is a typical example:
exp: ... | exp PLUS exp { $1 +. $3 }
This rule constructs an exp from two smaller exp groupings connected by a plus-sign token. In the action, $1 and $3 refer to the semantic values of the two component exp groupings, which are the first and third symbols on the right hand side of the rule. The sum is returned so that it becomes the semantic value of the addition-expression just recognized by the rule. If there were a useful semantic value associated with the PLUS token, it could be referred to as $2.


A treasure refers to any main collectible that the Pikmin can deliver back to the ship. These are the ship parts in Pikmin, the treasures in Pikmin 2, and the fruits in Pikmin 3.
Examples of treasure types include the Main Engine, the Courage Reactor, and the Sunseed Berry.
To create a new type of treasure, please follow the making object types tutorial.
Overview
A treasure type object simply has logic to be carried, and to give a different value of treasure points. The only other important parts of the treasure are their radius and weight.
Treasure type objects are hardcoded in the engine to sit there, be carried, be delivered to a ship, and give out some number of treasure points.
Properties
Besides the global object type properties, a treasure type has the following properties.
Mandatory
None.
Recommended
points
: How many treasure points it is worth when salvaged. Defaults to 10.
Optional
None.
Animations
A treasure type needs to have the following animations:
idling
: Idling; used for everything.
Script
Treasure types have hardcoded scripts, so the only thing you can do is enhance them.
Some script variables control special behavior, like the treasure's starting team. To know which ones exist, you can go to the area editor, select a treasure, and read the tooltip of each variable.


Issue 5130:
Array indices are sorted alphabetically instead of numerically
Steps to reproduce
- Select and enable the Console panel
- Execute following expression in the command line:
console.dir([0,1,2,3,4,5,6,7,8,9,10]);
- The output should be sorted according to the index (not alphabetically).


I'am Limbu Diwani.I'am from Nepal.I have graduated from Dharan Model Collage in Bachloer of Business Studies in 2018.Currently I'am studying IT In Kyoto Collage of Graduate Studies for informatics in Japan.I was born in small village called Morahang.which is located east Nepal in Proveince number 1,tehrathum district.
Life without intrest is like food without the salt.It is a interest which makes living interesting.It is a pursuit outside one's regular work.There are many hubbies like painting, drowing, gardening, stamp collecting,reading, photography,cooking,pet care etc.My favorities hubbies are gardening, travelling, and reading, watching movie. Moving on to favourite movies; Titanic, Romeo & Juliet, Crash, Twilight. Basically the list can go on and on. I must be up to date with the latest movies.Cooking has been a huge interest of mine. My mom's a great cook- especially in Nepali cooking. I think I have got it from her. From my point of view, having learned how to cook, makes a persons life much easier.


Preparation time
over 2 hours
Cooking time
30 mins to 1 hour
Serves
Serves 4
For the lamb, mix all the ingredients, apart from the lamb, in a shallow non-reactive dish. Score the rumps with a sharp knife and rub the mixture all over the rumps. Leave in the dish, covered, to marinate for at least two hours in a cool place.
Preheat the oven to 200C/390F/Gas 6.
Brown the lamb well in a hot frying pan, before placing in the oven to roast for 15-20 minutes - longer if you prefer your meat well done.
Leave to rest in a warm place for at least five minutes before serving.
Meanwhile, for the vegetable stew, heat the oil in a pan over medium heat and fry the bay leaves, cardamom pods and garlic cloves for one minute.
Add the onions and fry until lightly coloured. Stir in the ginger and garlic paste and cook for a further two minutes, until fragrant.
Add the coriander, chilli powder, cumin, turmeric, salt, tomatoes, potato, turnips and carrots. Stir well and simmer for 30 minutes.
Once the potatoes and other vegetables are tender when tested with the point of a knife, add the drained chickpeas. Cook for a further five minutes.
Scatter the coriander over the stew and serve it topped with the lamb rump.


Provides type definitions for elements commonly found in the context collections available from {@link net.jini.export.ServerContext} and {@link net.jini.io.ObjectStreamContext}. @since 2.0 @version 1.0


class: left, top, inverse, title-slide # Analyzing Summary Variables in the Presence of Partially Missing Longitudinal Data ### Jennifer L Thompson, MPH
Rameela Chandrasekhar, PhD
Vanderbilt University Medical Center ### bit.ly/jlt-jsm2018
jenniferthompson/MissSumVars
@jent103
--- # Our Motivation  ??? - Work with a research group which focuses on all aspects of critical illness, including the aftermath - Many projects involve both in-hospital and long-term components, and we want to investigate association between some exposure during the hospitalization and an outcome that takes place a year or more later - Here, we have a patient who was hospitalized for five days, had the exposure of interest on three days and no exposure on the other two --- # Our Motivation  -- Is more delirium *(in-hospital brain dysfunction)* associated with scores on a cognitive test after hospital discharge?  ??? Then we might want to somehow summarize that exposure and see if it's related to some long-term outcome. This could include - Cognitive or functional impairment - Quality of life - Mortality **SLIDE** BRAIN-ICU cohort: - published in 2013 - interested in whether the amount of delirium a patient experienced in the hospital was associated with performance on a test of cognitive ability up to a year after they were discharged Other possible examples: - More severe sepsis -> higher rate of long-term death among survivors? - Average (min, max) severity of illness related to functional outcomes? --- class: inverse, center, middle # The Problem .pull-left[ ### Prospective cohort  *BRAIN-ICU Cohort Study, NEJM 2013* ] -- .pull-right[ ### Retrospective EMR  ] ??? Describe visdat: - From BRAIN-ICU study - Purple = not missing, yellow = a day with no delirium assessment - Low proportion of patient-days missing - This is often the case for our **prospective** studies, thanks to our excellent staff of research coordinators - Reason to believe missingness or more or less completely at random - patient in a procedure, for example - So in BRAIN we did single imputation to "fill these in" and summarize our exposure, but not a big deal; little worry about bias **And then...** - Interested in a retrospective study using EMR data in a trauma unit, same exposure (different outcomes) - Delirium assessments are done, but not as often as in medical or surgical units - *change slides* - In fact, nearly 1/3 of our in-hospital days are missing the delirium assessment - This missingness is almost certainly NOT at random - Severely ill patients might be ventilated, comatose; perhaps staff didn't think assessment was necessary, but we can't necessarily tell that they were comatose from the data - Alternately: less sick patients who are up, walking, having conversation may also not have gotten assessed, because the staff thinks it's clear that they're fine - In other words, using data collected for clinical purposes for research has challenges! So, how to deal with the missingness in the way that gives us least bias? Four strategies: --- # Strategies: Simple .pull-left[ ### Assume the "best" *NA = unexposed:
Only count the exposure we know about*  ] .pull-right[ ### Assume the "worst" *NA = exposed:
All missing time points get exposure*  ] **Pros**: Straightforward to implement; plausible, *if* we know a lot about data collection
 **Cons**: Prone to bias ??? In our case, the exposure is usually bad, so I've called our first strategy assuming the best: We only count the exposure we know about, and assume all the missing days have no exposure. For example, here we have a patient with two known days of exposure, so that's what they get - we ignore these two missing days. Of course, we can also assume the worst, meaning that we assume every missing day *does* have the exposure. So here our hypothetical patient would get a value of four. These approaches are straightforward to implement, and in certain cases they might make a lot of sense. For example, we use an organ dysfunction score which incorporates bilirubin levels, but even in our prospective studies, bilirubin is generally not measured every day unless it's clinically helpful. Working with our clinical collaborators, we've usually decided that a missing bilirubin means there was no clinical reason to suspect liver dysfunction. But of course, if you *don't* know for certain whether or how your missingness is informative, these approaches can be quite prone to bias. --- background-image: url(presfigures/imputesummary.png) background-size: 328px background-position: 90% 35% # Strategies: Imputation .left[ ### Assume nothing 1. If subject missing any time point,
 entire summary value = `NA` 1. Multiply impute missing *summary values*
 before modeling ]

 .pull-left[ **Pros**: - Fairly simple to implement - Acknowledges uncertainty ] .pull-right[ **Cons**: - Ignores the data we *do* have - Likely to *overestimate* uncertainty ] ??? Of course both of those approaches make some pretty big assumptions, so in this next approach we could assume *nothing*: If the patient has even one missing value, we can't know for certain what the overall summary value would be, so we consider that whole value missing. In this case, we use multiple imputation prior to regression modeling; in this example, I've "used" five imputations, and our patient gets values all over the map. This might be OK if we have good covariate data with which to impute, and lots of missing patient-days; it is pretty straightforward to implement, and it at least acknowledges the uncertainty, which our simple approaches do not. However, it's essentially throwing out all the data we *do* have available - in this case, these four patient-days where we know the exposure value count for nothing. And while it at least acknowledges the uncertainty, this approach will likely *overestimate* it. --- background-image: url(presfigures/imputedaily.png) background-size: 365px background-position: 90% 35% # Strategies: Imputation .left[ ### Assume the minimum 1. Multiply impute missing *time points* 1. Summarize each imputed dataset 1. Use these imputed summary
datasets when modeling ] .pull-left[ **Pros**: - Maximizes use of data we have, including available covariate information ] .pull-right[ **Cons**: - Computation time - Data wrangling ] ??? In our final approach, we try to assume as little as possible, using the data from the days we know about and imputing at this lowest hierarchy the days we don't. Once we've multiply imputed missing patient-days, we summarize each of those **imputed** datasets, then use those summarized datasets in multiple imputation when we model. This approach, of course, maximizes the use of the data that we have available, including daily covariate data to help predict our missing values. But it's the most computationally intensive approach, which can matter especially in large EMR studies, and may involve some gnarly data wrangling when you go back and forth between imputing and summarizing. We assumed that this approach was our best bet; it makes intuitive sense. However, what kind of statisticians would we be if we didn't test that assumption and simulate some things? So that's exactly what we did. --- # Simulations - 5%, 20%, 35%, 50% of patient-days missing exposure value - Types of missingness: - MCAR - MAR - Missingness in exposure weakly, moderately, strongly associated with daily severity of illness - MNAR - Missingness in exposure weakly, moderately, strongly associated with true exposure value - True relationship with outcome: ranges from 0 to -5 - Imputation methods incorporate severity of illness ??? We used our BRAIN-ICU cohort data as our inspiration for these simulations, meaning that our exposure was daily delirium, yes or no, and our outcome is a simulated score of cognitive impairment. We set a range of our individual patient-days to be missing, and set different types of missingness. For our exposures that were missing at random, we set a weak, moderate, and strong association between that missingness and a daily severity of illness score. For exposures that were missing not at random, we set a weak, moderate, and strong association between missingness and the true exposure value. In the two methods which use imputation, we again used severity of illness to help predict either the overall duration of delirium, or delirium on a daily basis. --- class: inverse background-image: url(presfigures/bias.png) background-size: cover ??? First I'll describe the setup: 1. Our vertical panels = percent missing 1. Horizontal panels = type of missingness, again with weak, moderate, or strong associations between missingness and either our covariate, for missing at random, or our true exposure, for missing not at random 1. X axis = true association between exposure and outcome, smallest to largest 1. Y axis = bias 1. Colors: - Yellow = all missing days are assumed to not have the exposure - Green = assume all missing days *do* have the exposure - Blue = Any patient with any missing day has their entire summary value imputed - Purple = Impute all missing patient-days individually, then summarize and model with the summarized imputations Main points: - Note that only one row has a blue line. That represents our third approach, imputing the entire summary value when the patient has even one day missing. As we might expect, that approach performed really terribly; even at 5% missing, the bias there quickly outpaced any other approach. It turns out that once you have a decent amount of patient-days missing, this approaches forces so many overall summary values to be missing that it's just untenable, and we really couldn't justify the simulations with more missingness. So our first message is... don't do that. - Obviously our bias gets worse as the amount of missingness increases, and is also worse when our exposure is not missing at random. No surprises there. - When our data is missing completely at random, or missing at random, our daily imputation approach has the least bias. - If we can't impute daily: - Between the other two approaches, as missingness gets more prevalent, it looks like cynicism is actually paying off, since assuming all missingness gets the exposure is a little less biased than our optimistic approach. - Once we have a relationship between the exposure and missingness, though, the winner changes. If there's a strong chance that missingness truly indicates the presence of the exposure - in other words, our missingness is quite informative - then using this "missing = exposed" approach is less biased than trying to impute, at least in our scenario. --- class: inverse, center, middle background-image: url(presfigures/se_beta.png) background-size: cover ??? Moving to standard errors, we see the same pattern with the imputation of the summary value - it's bad with very little missingness, and gets worse the stronger the actual effect size. --- background-image: url(presfigures/ci_width.png) background-size: cover ??? This slide is for those of you who prefer your variance estimates in terms of confidence intervals. More generally, we see that assuming missingness indicates exposure leads to less variance to some extent than the other two methods. When data is missing at random or missing completely at random, there's not a lot of difference until you have a lot of missing data; but again, when missingness is substantially associated with the likelihood of the exposure, the difference becomes much more apparent. --- background-image: url(presfigures/coverage.png) background-size: cover ??? Looking at coverage, the same patterns emerge: - Imputing the summary value performs badly right out of the gate - Imputing the daily value often outperforms the other methods - The exception is when missingness is meaningfully associated with the true exposure, in which case assuming that missingness indicates the exposure is generally the winner - With lots of missingness and a large true effect, none of them perform particularly well --- background-image: url(presfigures/power.png) background-size: cover ??? This slide is very boring and is just here to show you that all the methods performed about equally well in terms of statistical power. --- ## Examples with Motivating Data .left-column[ - Duration of exposure vs outcome in two real-world studies, adjusting for one covariate - Three strategies to summarize duration of exposure ] -- .right-column[  ] ??? We're going to come full circle now, and apply each strategy to our two real-world studies. These analyses are simpler than we did in real life, but do adjust for severity of illness, which is likely a major confounder. As we might expect, when there is little missing data, and it's likely to be missing more or less at random, our results look very, very similar. When we have more missingness, we can see that the results might be quite different. We can also see that there is less variance when we assume missingness is indicative of having the exposure, though it's likely that that result is biased. --- class: middle, inverse background-image: url(presfigures/missingdata.jpg) background-position: 5% 40% .pull-right[ # Takeaways - Understand your data and its missingness - Better safe than sorry: imputing at the lowest level is usually worth it - Don't - Throw out data - Ignore your missingness ] .pull-right[ #### Future Exploration - Continuous exposure - Complex relationships between covariates/exposure, missingness ]
Photo used with permission, NausicaaDistribution Etsy shop, bit.ly/etsy-missing
 ??? 1. **Understand your data and its missingness:** When missingness is strongly indicative of the exposure, our advice on which method to use changes 1. **Better safe than sorry:** imputing daily status indeed does seem most appropriate in most cases, and is likely worth the extra trouble. If you don't have a solid idea of why your data is missing, this is probably the best approach. 1. **Don't throw out your data:** imputing the entire value when you have at least partial knowledge is a bad idea statistically; if unnecessary, disrespects the work done to give and collect that data 1. **Don't ignore your missingness:** you can do better than just counting what you know about, especially if you know something about how and why data is missing In the future, I hope to repeat these analyses with a continuous exposure, which has the added twist of being able to be summarized many *different* ways, and incorporating more complex relationships between covariates, exposures, and missingness. We purposely kept these straightforward, but as we all know, real life is not always that clear cut! --- class: inverse, top background-image: url(presfigures/balticsunset.jpg) background-size: cover .left[ ## Acknowledgements - Stef van Buuren for [mice](http://stefvanbuuren.github.io/mice/index.html) - Davis Vaughn, Henrik Bengtsson for [furrr](https://davisvaughan.github.io/furrr/) and [future](https://github.com/HenrikBengtsson/future) - Brooke Watson for [BRRR](https://github.com/brooke-watson/BRRR) - VUMC CIBS Center PIs and research team ] .right[

  bit.ly/jlt-jsm2018
  @jent103
  @jenniferthompson
 <a<EMAIL_ADDRESS>class="fa fa-paper-plane fa-fw"><EMAIL_ADDRESS> jenthompson.me
 ] ??? I want to thank a few R developers for making this work easier and more fun: - Stef van Buuren - his mice package for multiple imputation has really incredible documentation and makes every step of the process accessible, making the imputation of daily values pretty painless - Henrik Bengetsson and Davis Vaughn have built the future and furrr packages respectively, which work on parallel processing. These folks' work reduced my run time to probably 1/3 of what it would have been with very little additional effort on my part, and I'm very grateful. - If you're interested in making your simulations or other long-running processes more fun, I would definitely recommend Brooke Watson's BRRR package, which made this work no faster but infinitely more enjoyable. And of course, we'd love to thank the principal investigators and research staff at the Vanderbilt Center for Critical Illness, Brain Dysfunction and Survivorship, who come up with these ideas and work incredibly hard to design these studies and collect the data. Finally, here's where you can find a link to these slides as well as the code I used for simulation and creating the slides and visuals. --- background-image: url(presfigures/bias_no3.png) background-size: cover --- background-image: url(presfigures/se_beta_no3.png) background-size: cover --- background-image: url(presfigures/ci_width_no3.png) background-size: cover --- background-image: url(presfigures/coverage_no3.png) background-size: cover --- background-image: url(presfigures/power_no3.png) background-size: cover


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/Assumptions.20about.20data.20produced.20by.20.60classical.2Echoice.60.html ---
I think of data produced by a choice principle as a "generic element" satisfying the given specification, so that e.g. it should not be possible to prove that
(classical.choice (by apply_instance) : nat) = 0
Is it inconsistent to assume something like this, though?
If that was inconsistent, wouldn't that mean that you could prove this?
(classical.choice (by apply_instance) : nat) ≠ 0
ah yes, you're right
I guess Lean really doesn't decide such things (of course this generic nat must be interpreted literally as some nat if we take a model in ZFC, but there's no guarantee which one)
So you can construct a model where it gives you 0 and a different one where it gives you 1
another related question: if we can prove P (classical.choice (h : nonempty X) : X)
then is it a (meta)theorem that this lifts to a proof of
(∀ x : X, P x)
?
I don't think that's a theorem but I would think that it is a meta theorem
classical.choice
is an axiom; my guess is that any statement you can make about the natural it produces will be independent.
What if P
is λ x, x = (classical.choice (h : nonempty X) : X)
?
Last updated: Apr 24 2020 at 19:02 UTC


|
Accurate Mvir and Vmax functions from the MultiDark simulations |
|
|
N-body cosmological simulations are an essential tool to understand the observed distribution of galaxies. They provide all order statistics about dark matter and halos. In the paradigm of the flat Lambda Cold Dark Matter cosmology recently measured by Planck, an accurate description of the mass function is necessary to interpret large scale structure measurement. In this aim, we use the suite of MultiDark simulations, run with the Planck cosmological parameters, to revisit the one-point function. We study two flavours the halo mass function and the velocity function. We study in depth the model of the halo mass function, its covariance matrix and the large scale halo bias, which are tightly interconnected. We obtain accurate (2 percent level) models of the distinct halo mass function, its covariance matrix and the large scale halo bias. Furthermore we provide fits characterizing the subhalo massfunction and its relation to the distinct halos. Finally, we provide precise analytical fits of the Vmax velocity function until redshift 2.3. |
| Please click here to access the 1-pt functions measured. |
|
Acknowledgement
If you use these functions, please cite Comparat et al. 2017 |
|
Links
cosmoSim the MultiDark database |
last update, jan. 2017, by J. Comparat


Fuel Consumption: Fuel consumption ratings are shown in litres per 100 kilometres (L/100 km).
Fuel (L) / Year: Estimated annual fuel use is based on 20 000 km driven and a combined rating of 55 percent city and 45 percent highway.
CO2 Emissions (g/km): Estimated tailpipe carbon dioxide emissions (in grams per kilometre) are based on fuel type and the combined fuel consumption rating.


Sonorejo Jiwo vulnerability Wetan households Village index Percentage climate water LVI area agricultural main {border-style Livelihood family number Average change flood px;} #ffffff;} Climate food level livelihood Sukoharjo areas past using average rice vulnerable Based farmers household time Change Village, land ratio results source variability IPCC community data did research sub-components (range: Klaten Vulnerability components fields flooding mapping members month represents shows use value LVI-IPCC Panel based crops factors families health local lower natural prone report used years Table Village. daily deviation different flood-prone money months population px; study sub-district temperature {font-family GIS Standard [Eqn approach causes component font-size government insurance measured result Food Information Regency Social Water agriculture calculation capacity change. contributing double; head member moderate primary profile risks river score sector villages working (.) According Central Disaster Geographic Hahn Health Index Index-Intergovernmental Langsur Major Natural Research Socio-demographic Suryanto TABLE assistance border-color border-width characteristics collab: conducted consists curvature disaster disasters floods following livelihoods major maximum mean minimum precipitation rainfall reported solid; sources vulnerability. where, {font-style {font-weight (min) (−.) Agricultural Cambridge Confusion Dengkeng Global Regency, Regency. River age assessing assessment bold calculated change: chronic city consistent courier; crop dependent em; flows hazard impact income increase index. information largest leads measure networks paddy percentage pt;} river, scale sector. self-reported sensitivity seven severe slope strategy


That I have a big ego, or image I would like to portray myself as. But that image is definitely changing each day because sometimes I don't know what I want to portray myself as. All I need to remember is that I'm here to learn :) Because of this I don't ask for help as much as I should and It means I take less breaks than I should and also that I tend to forget everything in the moment and only focus on the task at hand, which is just a habit that I need to break. I feel like one of the biggest things for me and my learning, is that half the stuff i'm trying to take in, I just don't understand. For example, like the Kata's, If i'm alone for an hour I will get stuck. And the problem is that I don't know what i'm searching for at times on google and anything I find, I just feel like it's cheating. I know that's because of school and it's more-or-less allowed here, but still :/ Another habit.
Values are the things we believe to be important. Empathy is the ability to understand and share feelings with someone else. self-awareness is being able to indentify those emotions within yourself.
The Growth Mindset. I've always known that people can grow.
Confidence. Being willing enough to put yourself, or myself in this case forward and being able to be confident in myself and just being able to communicate (in the moment, without distractions)
As they say, You can teach someone to code but you can't teach someone to Human. Or something like that...
No. The core part is just as essential as the code. I know for one that a big part of why I choose to do stuff is because I want to grown, not just with technical stuff but because I want to grow "humanly?" lol. Gain confidence and to be able to interact with people without some feeling of anxiety. Also It was interesting to learn about a lot of the stuff, most notably the Growth Mindset.
Long term goal is to make my family proud and make sure they are safe/secure and happy in the future :) For career paths, I've thought it about it a lot but I still haven't come to a final decision, although for now my goal is to finish this course. I would like a career in I.T. whether it be programming, techical hardward side or something to do with games. If family is a strength then, that :p They motivate me and make me who I am, and they're one of the reasons why i'm trying to push myself :) My biggest non-techincal challange is confidence. I would like to get more confident and be someone that can converse freely to a group/in a group, and input more instead of thinking I lack places or think my ideas aren't good enough. Also, I want to be able to communicate more effective without that feeling of anxiety :) MY expectations of myself is that I make sure to attend everything I need to and make sure to get everything done in the set timeframe. With others, I expect to communicate with whoever I need to respectively and ask for help when I need to, not after many moments of struggling. :)


The server seems to be malfunctioning.
Maybe it's just
on a short maintenance task? Better try again
in a minute or so.
Try to go to the homepage, this might already solve the problem.
If this error persists, please contact
Abe.Cede
on SocialClub. Thanks.


Class: GameShuffleCards::ValidateGame
- Inherits:
-
Object
- Object
- GameShuffleCards::ValidateGame
- Defined in:
- lib/game_shuffle_cards/validate_game.rb
Overview
validation to secure the inputs of the Game
Class Method Summary (collapse)
-
+ (Object) parse_and_validate(players, cards_per_player)
Given two values String or Integer, checks whether they are valid in a context Game then return the integers values or raise an exception.
-
+ (Object) parse_and_validate_players(players)
Validates whether the amount and type of players are right.
Class Method Details
+ (Object) parse_and_validate(players, cards_per_player)
Given two values String or Integer, checks whether they are valid in a context Game then return the integers values or raise an exception
12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 |
# File 'lib/game_shuffle_cards/validate_game.rb', line 12 def parse_and_validate(players, cards_per_player) begin players = Integer(players) cards_per_player= Integer(cards_per_player) rescue raise TypeError end raise GameShuffleCards::ToManyPlayersError if players > GameShuffleCards::Game::MAXIMUN_PLAYERS raise GameShuffleCards::NotEnoughPlayersError if players < GameShuffleCards::Game::MINIMUN_PLAYERS raise GameShuffleCards::ToManyCardsPerPlayerError if cards_per_player > GameShuffleCards::Game::TOTAL_CARDS raise GameShuffleCards::NotEnoughCardsPerPlayersError if cards_per_player < GameShuffleCards::Game::MINIMUN_CARDS raise GameShuffleCards::TooManyCardsDemandedError if (players * cards_per_player) > GameShuffleCards::Game::TOTAL_CARDS [players,cards_per_player] end |
+ (Object) parse_and_validate_players(players)
Validates whether the amount and type of players are right. Otherwise raise an exception
31 32 33 34 35 36 37 38 39 40 |
# File 'lib/game_shuffle_cards/validate_game.rb', line 31 def parse_and_validate_players(players) begin players = Integer(players) rescue raise TypeError end raise GameShuffleCards::ToManyPlayersError if players > GameShuffleCards::Game::MAXIMUN_PLAYERS raise GameShuffleCards::NotEnoughPlayersError if players < GameShuffleCards::Game::MINIMUN_PLAYERS players end |


Speaker : Benoit Tellier
| Event | Date |
|---|---|
| Project presentation | 06/12 |
| Backlog task validation (see below) by your tutor + first weekly report | 13/12 |
| Resuts return + project presentation | 16/01 |
By the tutor :
|--------|----------------------------------------------|
| Points | Criteria |
|--------|----------------------------------------------|
| 2 | Was your team autonomous? |
| 2 | Did they send you weekly reports regulary ? |
| 2 | Did they maintained a board? |
| 1 | Was their work delivered on time ? |
| 1 | Your team produces at least partial results |
| 2 | All your expactations were met. |
|--------|----------------------------------------------|
By the presentation jury :
|--------|----------------------------------------------|
| Points | Criteria |
|--------|----------------------------------------------|
| 2 | Was Presentation lasting 15 minutes ? |
| 2 | Was the student fluent ? |
| 2 | Softskills. Valorize your work. |
| 2 | Technical level of presentation |
| 2 | Slides |
|--------|----------------------------------------------|


The Red Wheelbarrow
so
extreme
much
amount
depends
relies
upon
on
a
the
red
carmine
wheel
tire
barrow
buggy
glazed
varnished
with
admist
rain
drizzle
water
H2O
beside
alongside
the
a
white
ivory
chickens
cowards


{% extends "base.html" %} {% block title %}Question 3 | MedEM{% endblock %} {% block content %}
Are you experiencing any of the following symptoms?


Kit Siang: MCA just a vehicle for PAS-Umno agenda in Tanjung Piai
by BY JOHN BUNYANIPOH, Nov 8 — DAP’s Lim Kit Siang today said the MCA candidate in Tanjong Piai parliamentary by-election is an agent of Muafakat Nasional between Umno and PAS.
Lim said that Muafakat Nasional's aim is to make use of the Tanjung Piai by-election as the stepping stone to winning the general election.
"PAS, the dominant partner in Muafakat Nasional, does not accept the Malaysian Constitution, which is the reason for the post 14th General Election (14th GE) pronouncement by the PAS president that Muslims in Malaysia must vote for Muslim candidates to ensure Muslim rule and the questioning of the appointment of non-Malays and non-muslims to various national offices.
"The lie that the Malays have lost political power and that the Malaysian Government after the 14th GE was in the hands of the Chinese was repeated at the inaugural Muafakat Nasional ceramah on Wednesday night," he said in a statement.
The Iskandar Puteri MP said the pact was simply continuing the “lies” Umno used before the general election, such as accusing DAP of seeking to dismantle Malay political power.
Lim then asked if MCA’s Datuk Seri Wee Jeck Seng, who is representing Barisan Nasional in the by-election, agreed with the Muafakat Nasional leaders’ claims about the Chinese community.
He then urged Tanjung Piai voters to send a strong message of rejection to BN and PAS.
The Tanjung Piai by-election is on November 16.


{extend name='public:content'/} {block name='title'}站点配置{/block} {block name='content'}
| Name | Position | Office | Age | Start date | Salary |
|---|---|---|---|---|---|
| Tiger Nixon | System Architect | Edinburgh | 61 | 2011/04/25 | |
| Garrett Winters | Accountant | Tokyo | 63 | 2011/07/25 | $170,750 |
| Name | Position | Office | Age | Start date | Salary |
|---|---|---|---|---|---|
| Tiger Nixon | System Architect | Edinburgh | 61 | 2011/04/25 | |
| Garrett Winters | Accountant | Tokyo | 63 | 2011/07/25 | $170,750 |


Issue: CONCATENATE-SEQUENCEForum: Editorial
References: CONCATENATE (p249), COERCE (p51),
MAKE-SEQUENCE (p249), MAP (p249), MERGE (p260),
Issue SUBTYPEP-TOO-VAGUE
Category: CLARIFICATION/CHANGE
Edit history: 01-Mar-91, Version 1 by Pitman
(only about (CONCATENATE 'SEQUENCE ...))
15-Mar-91, Version 2 by Pitman
(generalize per JonL, Moon, Barmar, MacLachlan)
17-Mar-91, Version 3 by Pitman
(clarify for MacLachlan; also, include MAKE-SEQUENCE)
31-May-91, Version 4 by Pitman (amendments per X3J13)
Status: X3J13 passed v3 with amendments on 10-1 vote, Mar 91.
v4 reflects those amendments.
Problem Description:
CLtL (p249) says that the RESULT-TYPE argument to CONCATENATE
``must be a subtype of SEQUENCE, as for the function COERCE''
CLtL (p51) says:
``Any sequence type may be converted to any other sequence
type, provided the new sequence can contain all actual
elements of the old sequence ... If the sequence is already
the specified type, it may be returned without copying it;
in this, (COERCE sequence type) differs from
(CONCATENATE type sequence), for the latter is required to
copy the argument seqeunce. In particular, if one specifies
SEQUENCE, then the argument may simply be returned if it
already is a sequence.
The passage about CONCATENATE suggests that sequence subtypes
valid to COERCE are valid to CONCATENATE. But the type SEQUENCE
is a subtype of SEQUENCE that is clearly permissible to COERCE.
COERCE, MAKE-SEQUENCE, MAP, and MERGE are also impacted similarly.
Terminology:
Draft 8.81 of the specification defines the following term:
recognizable subtype n. (of a <type>)
a <subtype> of the <type> which can be reliably detected
to be such by the <implementation>.
The intent is that SUBTYPEP will be described as a function which
returns "T, T" when the first type argument is a "recognizable subtype"
of the second.
Proposal (CONCATENATE-SEQUENCE:X3J13-MAR-91):
1. Specify that CONCATENATE, MAKE-SEQUENCE, MAP, and MERGE are
defined only when the target type argument is either a
recognizable subtype of LIST or a recognizable subtype of
VECTOR. [MAP is also permitted to special case NIL as a
target type in a manner consisting with existing practice.]
Otherwise, an error is signaled.
2. Specify that if COERCE receives a target type argument which is
a recognizable subtype of SEQUENCE, but which is neither a
recognizable subtype of LIST nor a recognizable subtype of
VECTOR, then the argument to be coerced must already be
of that type (in which case, COERCE behaves like IDENTITY for that
argument). Otherwise, an error is signaled.
3. a. Specify that if COERCE, CONCATENATE, MAKE-SEQUENCE, MAP,
or MERGE receives a target type argument which is any subtype
of LIST, then the result is of type LIST.
b. Specify that if COERCE receives a target type argument that
is a subtype of array, and the object is already of that type,
COERCE returns that object as its result.
c. For COERCE in situations not covered by 3b,
CONCATENATE, MAKE-SEQUENCE, MAP and MERGE
when the target type argument is a subtype of ARRAY:
* If the implementation can determine the element type
specified for the target type, the element type of the
resulting array is the upgraded array element type of
the specified element type.
* Else if the implementation can determine that the element
type is unspecified, (or ``*'') the element type of the
resulting array defaults as for MAKE-ARRAY (to T).
* Else an error is signaled.
Rationale:
This gives users a sense of what they can expect at minimum,
and also gives implementors a sense for how they can go about
making extensions without violating user expectations.
Note that although that specific terminology is not used, the
specific constraints on recognizable subtypes are effectively
spelled out in issue SUBTYPEP-TOO-VAGUE.
Test Case:
#1: (CONCATENATE 'SEQUENCE '(A B C) "DEF")
#2: (COERCE '#1=#(1 0 1) '(OR NULL (EQL (1 0 1))))
#3: (FLET ((SAME-TYPE-P (X Y)
(VALUES (AND (SUBTYPEP X Y) (SUBTYPEP Y X)))))
(SAME-TYPE-P
(ARRAY-ELEMENT-TYPE (MAKE-SEQUENCE '(ARRAY (UNSIGNED-BYTE 5)) 3))
(UPGRADED-ARRAY-ELEMENT-TYPE '(UNSIGNED-BYTE 5))))
=> T ;or signals an error, if (UNSIGNED-BYTE 5) is not upgradable.
Current Practice:
Symbolics Genera seems to approximately implement this proposal,
although it isn't quite right on the LIST side (e.g., it fails on test
case #2).
Cost to Implementors:
Small.
Cost to Users:
None. This was already not portable.
Cost of Non-Adoption:
The language is left ambiguous.
Benefits:
A tighter specification--better portability.
Aesthetics:
Negligible.
Discussion:
Pitman supports this.
An earlier version of this proposal worried specifically about the case
of function CONCATENATE and specifically about the argument named SEQUENCE
but it was shown that the problem was bigger along both axes, so v2 starts
over trying to do things a different way.


for Skyword
HTML5 became a W3C Candidate Recommendation
it's in final review
next stop is Recommendation
html 5.1 is in the works
Like the
 tag or

WebSQL
IndexedDB
localStorage
cache manifest
The "role" Attribute, for accessibility
The itemtype, itemscope, and itemprop Attributes
Additional semantics following a specific schema

Avatar

Director: James Cameron (born August 16, 1954)
Science fiction
Trailer

Read more...
<meta http-equiv="X-UA-Compatible" content="chrome=1">
results via html5test.com
IE 9.............138/500
IE 10...........320/500
FF 18...........393/500
Ch 24..........448/500
Maxthon....464/500
Open-source JS library to
help make html5 & css3 sites.
Detect Browser Compatibility
Add css classes to facilitate fallbacks
Older Browsers: Shim & load polyfills
<!DOCTYPE html>

...

...

...

...
.no-js #page,
.no-cssgradient #page {
background: url("images/gradient.png");
}
.cssgradient #page {
background-image: linear-gradient(top, #555, #333)
}
// a string, an object, or an array of strings and objects
Modernizr.load([{
test : Modernizr.fontface && Modernizr.cssgradients,
// Modernizr.load loads css and javascript by default
g nope : ['presentational-polyfill.js',
'presentational.css']
},{// Functional polyfills
// This just has to be truthy
test : Modernizr.websockets && window.JSON,
// socket-io.js and json2.js
nope : 'functional-polyfills.js',
// You can also give arrays of resources to load.
both : [ 'app.js', 'extra.js' ],
complete : function () {
// Run this after everything in this group has
// downloaded and executed, as well everything
// in all previous groups
app.init();
}
},
// load analytics after everything else
'analytics.js'
]);
if (Modernizr.localstorage) {
// window.localStorage is available!
} else {
// no native support for local storage :(
// use a polyfill! :)
}
Polyfills are a type of shim that retrofit legacy browsers with modern HTML5/CSS3 features
Shims refer to any code that intercepts API calls and provides a layer of abstraction


[1]
Long battery life; It doesn't take the shortest route.
[2]
Nice interface - lousy support; No support for bugs, just buy $oftware/map updates


H.264/MP4 & WebM
Download:
MP4
WebM
<<
<
@timestamp
>
>>
(Total:
@fileCount
)
Rotate Locally
Scale Locally
Your browser does not support H.264/MP4 or WebM in <video> tag


rand( 100 )
// TODO: what is some reasonable # of factors for the answer?
var factorization = getPrimeFactorization( NUMBER ),
num_factors = 2,
answer = 1;
for (var i = 0; i < num_factors && i < factorization.length; i++) {
var index = floor( random() * factorization.length );
answer *= factorization[index];
factorization = jQuery.merge( factorization.slice(0, index), factorization.slice(index + 1) );
}
return answer;
roundTo(1, ANSWER)
ANSWER > ROUNDED ? ROUNDED : ROUNDED - 10
LOW + 10
What is a number between LOW and HIGH that divides into NUMBER?
ANSWER


convert_to_draft
by Jane Sandberg at 2022-12-29 21:19:05.Coverage: 94.52%. Remained the same when pulling<PHONE_NUMBER>dfceedfe3439809a58994aa6763f3d on blacklight-deprecations into 8e0010d5041f7829892c41bee2d6a931e409b5b6 on main.
head_ref_force_pushed
by Jane Sandberg at 2022-12-29 17:55:58.Coverage: 94.515%. Remained the same when pulling 919e625f310e4e2225d2207b3111e77d5acb9dd1 on cpu-circleci into 8e0010d5041f7829892c41bee2d6a931e409b5b6 on main.
head_ref_force_pushed
by Christina Chortaria at 2022-12-29 18:17:40.head_ref_force_pushed
by Christina Chortaria at 2022-12-29 18:26:34.renamed
by Christina Chortaria at 2022-12-29 18:27:04.ready_for_review
by Christina Chortaria at 2022-12-29 18:28:22.referenced
by Jane Sandberg at 2022-12-29 18:50:12.merged
by Jane Sandberg at 2022-12-29 18:50:12.closed
by Jane Sandberg at 2022-12-29 18:50:12.head_ref_deleted
by Jane Sandberg at 2022-12-29 18:50:13.assigned
by James R. Griffin III at 2022-12-29 14:13:39.deployed
by None at 2022-12-29 14:16:20.referenced
by James R. Griffin III at 2022-12-29 14:22:27.merged
by James R. Griffin III at 2022-12-29 14:22:27.closed
by James R. Griffin III at 2022-12-29 14:22:27.head_ref_deleted
by James R. Griffin III at 2022-12-29 14:22:28.assigned
by Alicia Cozine at 2022-12-29 15:08:03.assigned
by Alicia Cozine at 2022-12-29 15:08:03.Related to, possibly duplicate of, #3319.
review_requested
by Alicia Cozine at 2022-12-29 15:22:42.referenced
by Jane Sandberg at 2022-12-29 15:55:48.merged
by Jane Sandberg at 2022-12-29 15:55:48.closed
by Jane Sandberg at 2022-12-29 15:55:48.head_ref_deleted
by Jane Sandberg at 2022-12-29 15:55:49.closed
by Jane Sandberg at 2022-12-29 15:55:49.Looking at this again, I think the warning and the failure are two different things:
proxy_cache_path
on the load balancers when we add a project. Many of our projects have these configured. The pattern is /data/nginx/{{ project-name }}-{{ env }}/NGINX_cache/
. This will be a good test of whether running the nginx_production_rebuild.yml
playbook (which we should rename, see #3337) creates all the necessary cache directories on the staging load balancers. See this comment.
To fix this, we will move away from Bionic. We have Jammy Jellyfish (22.04 LTS) images coming soon and will prioritize migrating projects that use Node and need to be upgraded.
Closing as duplicate of #3288. Closed by #3290.
closed
by Alicia Cozine at 2022-12-29 17:27:11.Related to #2227?
Test for this as part of #3439
@sandbergja and I looked at this together, and found that cacheing is configured on several sites, including the catalog. On the nginxplus Admin UI, the Caches
pane shows most caches are not being used (as far as we could tell). Bypass
traffic is high. Serve
traffic is usually 0. It seems like some testing is in order. Maybe this can be done in conjunction with the new Nginx staging environment?
Possibly related to #3439.
Potentially relevant posts & documentation: https://serverfault.com/questions/869584/nginx-proxy-caching-not-working https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Cache-Control
assigned
by Alicia Cozine at 2022-12-29 15:08:02.mentioned
by Jane Sandberg at 2022-12-29 20:04:26.subscribed
by Jane Sandberg at 2022-12-29 20:04:26.This seems like the wrong approach. Needs more research.
closed
by Alicia Cozine at 2022-12-29 20:04:47.


Directing Visions
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Lorem ipsum dolor sit amet consectetur adipisicing elit. Quo repudiandae rerum libero ipsum asperiores omnis mollitia, nostrum commodi placeat ea itaque modi corrupti corporis nam voluptas aut reprehenderit eaque culpa.
Do get yourself registered soon. We are excited to see your vigorous participation.🤩📲 Round 1 :- Aptitude (Top few students would be qualified for round 2) Round 2 :- General Knowledge
We are glad to announce that we are here with a guest lecture to develop your leadership qualities with- Brigadier Saurabh Tewari Topic:- How a leader deals with problems.
Teamwork is the ability to work together toward a common vision. The ability to direct individual accomplishments toward organizational objectives. It is the fuel that allows common people to attain uncommon results.
Meet the team


Resize this responsive page to see the effect!
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What is Responsive Web Design?
Responsive web design is about creating web sites which automatically adjust themselves to look good on all devices, from small phones to large desktops. |
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Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris...
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bValidator is a jQuery plug-in for client side form validation.
It supports fully customized error messages defined with template and CSS, many validation functions (actions) like date, email, URL, IP address, validation of dynamic forms, customized validation functions and more.
If you like and use bValidator, I'd like a small donation from you and
I promise I'll put it to good use:)
Setup
For a basic setup you will need to include into your web page which contains form you want to validate jquery.bvalidator.js file or (recommended) compressed file with YUI compressorjquery.bvalidator-yc.js and, of course, jQuery:
The web page should have elements you want to validate. This is usually a form, but validator can also work on input fields which are not inside the form (see example). Note the data-bvalidator input field attribute which tells bValidator which validation function (action) to invoke for the field. The name of that attribute can be changed and this can be for example class or rel, see options for details.
This code should be inserted after the form or you can use jQuery's $(document).ready to execute the script as soon as the webpage's Document Object Model (DOM) has been loaded. In that case this javascript code can be before or after the form:
OR by defining a global object with options called bValidatorOptions. bValidatior will check if this object exists and if does, will load options from it and override default options.
OR BOTH, you can define a global bValidatorOptions object and also pass options to the validator constructor. In that case options from the bValidatorOptions object override default options and options passed as argument to constructor will override options from the bValidatorOptions object.
Option
Default
Description
singleError
false
Enabling this shows only first validation error at a time.
offset
{x:-23, y:-4}
Fine tunes the error message tooltip position specified with the position property.
position
{x:'right', y:'top'}
Specifies the position of the error message tooltip. Valid values for x are: left, center, right and for y are top, center, bottom
showCloseIcon
true
Controls if the error message tooltip has a close icon. If true user can click on it and close the error message tooltip.
showErrMsgSpeed
normal
Error message's fade-in speed. Values can be 'fast', 'normal', 'slow' or number of miliseconds.
CSS class for the error message tooltip close icon.
errMsgClass
errmsg
CSS class for the error message tooltip (error messages container).
errorClass
invalid
CSS class for the input field containing an invalid value. Will not be applied on checkboxes and radio buttons.
validClass
CSS class for the input field containing a valid value. Will not be applied on checkboxes and radio buttons.
lang
en
Language for localization.
errorMessageAttr
data-bvalidator-msg
Input field attribute which holds error message text. Message from this attribute will override default messages or localized error messages.
validateActionsAttr
data-bvalidator
Input field attribute which tells validator which validation actions to invoke for the field.
paramsDelimiter
:
Options delimiter for validaton function parameters inside square brackets [].
validatorsDelimiter
,
Validator functions (actions) delimiter in validateActionsAttr attribute.
validateOn
null
On which input field event to start validation. Values can be null, 'change', 'blur', 'keyup'. See this option in action in this example. This option will be not applied on checkboxes and radio buttons.
errorValidateOn
keyup
On which input field event to start validation if error message is already shown. Values can be null, 'change', 'blur', 'keyup'
scrollToError
true
If first error message is not visible on the screen, page will be scrolled up or down to be visible.
template

 {message}

HTML template for the error message tooltip. This HTML code will be put inside the container div element and appended after the input field. {errMsgClass} will be replaced with value of the errMsgClass propery and {message} will be replaced with error messages text.
This piece of HTML will be used only when showCloseIcon option is true. {message} tag in the HTML code specified by template option will be replaced by this code. With these two options you have full control over the error messages layout. See example 9 where this option is used to support IE6. {message} tag in this code will be replaced with the error messages text, {closeIconClass} will be replaced with the value of closeIconClass option and {closeErrMsg}will be replaced with javascript that hides error message tooltip.
Callbacks
Callbacks are user defined functions that are called by validator in certain moment. Callbacks are defined the same way as configuration options. Here is an example of defining callback:

Callback
Arguments
Description
onBeforeElementValidation
jQuery object containing input field
Called before the validation routine starts for each element (input field) that is validated. Returning false will cause the validation to be skipped for that element.
onAfterElementValidation
jQuery object containing input field
array containing all error messages for the element
Called after the validation routine ends for each element (input field) that is validated.
If false is returned error messages (if any) won't be displayed, and binding events (validateOn, errorValidateOn) to input fields will be skipped.
Returning 0 (zero) will only disable bValidator error messages. See example 10.
onBeforeAllValidations
jQuery object containing all inputs that will be validated
Called once before the validation is started. Returning false will skip the validation. For example, if you validate a form with more input elements this callback will be called once before all validations and if false is returned the form will not be validated at all.
onAfterAllValidations
jQuery object containing all inputs that are validated
validation result (true or false)
Called once after all validations are done. For example, if you validate a form with more input elements this callback will be called once after all validations are done and error messages (if any) are displayed. See example 10.
onBeforeValidate
jQuery object containing input field
string validator action (example: min[5])
Called before the validation routine starts for each validation action. Returning false will cause the validation to be skipped for that validator action.
This callback function will be called for each validation action so if you put more actions on one form element for example: max[10],email,required this callback will be called two times (for max and for email). required actinon doesn't trigger any callbacks.
onAfterValidate
jQuery object containing input field
string validator action (example: max[10])
validation result (true or false)
Called after each validation routine ends. Returning false will stop executing that validator action, displaying error messages and binding events (validateOn, errorValidateOn) to input fields will be skipped.
Will be called for each validation action (see onBeforeValidate description).
onValidateFail
jQuery object containing input field
string validator action (example: max[10])
array containing all error messages for the element
Called after validation fails.
Will be called for each validation action that fails (see onBeforeValidate description).
onValidateSuccess
jQuery object containing input field
string validator action (example: max[10])
Called after validation is sucessfull.
Will be called for each validation action that is successful (see onBeforeValidate description).
Error messages and localization
bValidator can retrieve error message from the configuration options object passed as argument to constructor or defined as global bValidatorOptions object, or from data-bvalidator-msg attribute.
Most of the validator actions has error message named same as the action in configuration object. If you use some custom validation function (example) you can also add error message named same as the validation function into configuration object.
You can use {0}, {1}, {2}, {3},... tags in error messages and they will be replaced with validator action parameters in [].
Error messages can be localized (translated). To do that you need to pass translated messages as options to validator constructor:

OR define global bValidatorOptions object with translated error messages that will be used in all validator instances:

You can see all default English error messages in jquery.bvalidator.js file (search for 'errorMessages' inside the file). If you made translation please post it to bValidator discussion group. I will also put it on download page.
Validator actions
Validator actions are functions that checks value of input field that is validated. Here are listed built-in actions but it is very simple to add custom validation functions (see example and getActions API function).
Validations which validator will perform on a single input field are stated in data-bvalidator attribute by default. You can use different attribute like class or rel if you need that your HTML is valid. Just set the name of the attribute in validateActionsAttr option.
Some validator actions can have parameters and those are stated in square brackets after the action name and delimited with ':'. For example: [param1:param2:param3]. You can have unlimited number of parameters per action.
Checks if all characters are alphabetic. Empty space (' '), underscore(_) and minus(-) are also valid.
alphanum
Checks if all characters are alphanumeric. Empty space (' '), underscore(_) and minus(-) are also valid.
digit
Checks if all characters are digits.
number
Checks if value is a number.
email
Checks if value is a valid Email.
image
Checks if value ends with image file extension like .jpg. Can be useful for file fields.
url
Checks if value is a valid URL.
regex
pattern
modifier (optional)
Checks if value matches pattern given by parameter.
If you'll need to use characters like [],: in pattern which are also used by validator to parse action arguments you'll have to write custom validator function like in this example.
As second parameter regular expression modifier can be passed.
date
date format
Checks if value is a valid date in format specified by action parameter. Format can be any combination of mm, dd, yyyy with one character separator between. Example: 'mm.dd.yyyy' or 'yyyy-mm-dd'.
required
Is a value required.
If you put required in front of other actions like data-bvalidator="required,max[10],email" then error message that field is required will be shown in error messages tooltip with other error messages.
If you put required after other actions like data-bvalidator="max[10],email,required" then error message that field is required will not be shown in error messages tooltip if there are some more error messages.
NOTE that if a field is not marked as required and it is empty it will not be validated at all. For example, if you have field with data-bvalidator="email" and you leave it empty, email action will not be called. If you want to call validator action even if value is empty and not required use valempty.
between
minimum value
maximum value
Checks is value between values in action parameters.
If the input is a checkbox and it is in a group of checkboxes (all with the same name for example name="chk[]") or select then between means "number of selected checkboxes (options) must be between values set by action parameters". See example.
If you use between with checkbox or select you should use custom error messages. See errorMessageAttr option.
max
maximum value
Checks is value less or equel than action parameter value.
If the input is a checkbox and it is in a group of checkboxes (all with the same name for example name="chk[]") then max means "select no more then max checkboxes". See example.
If the input is a select then max means "select no more then max options".
If you use max with checkbox or select you should use custom error messages. See errorMessageAttr option.
min
minimum value
Checks is value greater or equel than action parameter value.
If the input is a checkbox and it is in a group of checkboxes (all with the same name for example name="chk[]") then min means "select at least min checkboxes". See example.
If the input is a select then min means "select at least min options".
If you use min with checkbox or select you should use custom error messages. See errorMessageAttr option.
rangelength
minimum length
maximum length
Checks if length of the value is between action parameters values.
maxlength
maximum length
Checks if length of the value is smaller than action parameter value.
minlength
minimum length
Checks if length of the value is greater than action parameter value.
differs
element id
The value has to be diferent from the value of field which ID is passed as parameter.
equalto
element id
The value has to be equel to the value of field which ID is passed as parameter.
extension
file extensions
Checks if value ends with '.' followed by any of passed parameters.
You can put as many file extensions you need as parameters to this action. For example: extension[jpg:png:txt]
This action doesn't have it's default error message so use your own custom error message.
ip4
Checks if the value is a valid IPv4 address.
ip6
Checks if the value is a valid IPv6 address. NOTE that this action uses complex regular expression which can be pretty slow and doesn't work in Chrome which shows "Aw, Snap!" page! So be careful where you use this action or make your own custom action for IPv6 address validation.
valempty
Validate field even if it's not marked as required and is empty. This action makes sense only if some other custom validator action is also used on that field and the field is not required. For example, you can have an input box that can be empty in some cases that depend on some other field. In that case you cannot put required action on it because it can be empty, but you need to validate it even if its empty. See example.
API functions
When you make instance of validator you can call some functions on that instance:

or you can access validator instance through jQuery data function:

Function
Arguments
Description
getOptions
Returns the options object of the current validator instance.
isValid
jQuery object containing inputs to check only
(optional)
Just checks if inputs in current validator instance are valid. Doesn't show error messages. Calling this function is the same as calling validate(true) function (this is just wrapper for validate() function with first argument set to true.
removeErrMsg
jQuery object
containing inputs
Removes (hides) the error message
getInputs
Returns all input fields associated with the validator.
bindValidateOn
jQuery object
containing inputs
This function is helpful when using validateOn option and dynamic forms. If you add some new input elements to the form after validator is already initialized and you want to validate them on event specified with validateOn option you need to call this method.
If you are not using validateOn option with dinamic forms you can forget about this function.
reset
Resets the validator. Hides all error messages like the validator is only initialized. If you have a reset button on your form this function is automatically bind to it.
destroy
Removes existing bValidator instance.
validate
if true error messages are not displayed
(optional)
jQuery object containing inputs to validate only (optional)
Does validation.
getActions
Returns the object with all built-in validator action functions of the current validator instance. This is useful for adding custom validator actions which are not accessible from global scope or overriding existing built-in actions. For example, you can add your validation function like this:

Examples
You can see source of each example by clicking on the 'Example source' button. Source will not look nice in Internet Explorer so I recommend using Firefox, Opera or Chrome for that, but validator should work nice in all browsers.
1 - All validators in action
2 - Input specific error message
In this example regex validator action is used (regex[a{3}]) and error message which is defined in data-bvalidator-msg attribute.
3 - Custom validators
This example shows how you can create your own validation action. Just make a function that returns true for successful validation and false for an error and put the function name in data-bvalidator attribute. See also this example.
You can see also in this example how to use parameters with your own validation action. You can also put error message for your validation function in options object as described above, just call it the same as your validation function.
See also getActions API function if your validation function is not accessible from global scope.
4 - Dynamic forms
You can dynamically add inputs to the form after the validator is initialized. Note that hidden form elements are not validated. If you need to hide or show some form elements, put them into some container element (like
 in this example) and then show or hide that container because validation messages will not follow show/hide actions if you apply them only on input element which is validated.
If you use validateOn option, then after adding new input to form you can call bindValidateOn function for new added inputs to bind validateOn event on them also.
5 - Server side validation
This example is similar to custom validators example above. Just make your own validator action function which will do synchronus AJAX request that will check if value is valid.
6 - Error message position and style
You can set template, position and CSS styles for error messages. See also example 9.
7 - Instance on
 element
Only digits:
bValidator doesn't care if inputs are not inside a <form> element. It will work on any container element that has some child inputs that can be validated. Of course, you won't have submit button in that case and validation will not be automatically bind to it, but you can call it manually like in this example.
8 - Groups of checkboxes and radio buttons
A group of checkboxes or radio buttons is created by giving the same name attribute to all elements in the group. bValidator attributes for actions and custom error message should be added to only one element in the group on which error message will be shown.
9 - For old browsers
Some people live in the past and they love their favorite browser IE6. This example will work nice in IE6. CSS styles are changed to use image for arrow and templateCloseIcon option is used to replace default template with one that uses tables.
10 - Put error messages into container
This example shows how to put error messages into the container element. This functionality is not built-in into the bValidator, but you can achieve it by using callbacks. onAfterAllValidations and onAfterElementValidation callbacks are used in this example.
11 - Depending inputs
In this example validation of one input field that depends on value entered in another field. This is achieved with checkMyInputs custom action.
This example also shows the use of valempty action which is used to trigger checkMyInputs action even if the field is empty. If you need both fields to be required then you should use required action instead of valempty action.
Themes
In examples below you can see how to make your own theme for bValidator by changing CSS and some configuration options. See also example 9 and example 6.
If you make a nice theme
please send it to me and I will include it into this section.


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Please crash more, dear Steem.
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2018-06-14
SmartCash#8 - Smartreward is good, but it can be great!
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If you have a bad day, this might help a little.
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GIN - Deploy masternodes within a few clicks
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Consistent but slow VS go big or go home style of mining?
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Mining the CryptoNight coins with casual PC | 挖矿
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What an eye-opening crypto chatting session!
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Smart contract saved me some ETH from a potential ICO scam
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Best way to store crypto credentials like private keys and seeds -- Keepass
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JavaScript Language
Posted: 25/06/18
What are the use cases for the following JavaScript terms?
Parentheses:
- They are used to declare the parameters/arguments for a function. These are values that a function takes in and uses within its code.
- They are used when creating a "for" loop to contain the expressions of the loop.
- They can be used to specify an expression to be evaluated ahead of the normal order of operations in the same way as you might use them in mathematics.
Brackets:
- These can be used when you want to declare an array, a type of variable that can store multiple values.
- They are also used when you want to access values from within an array by specifying the list order of the value you want to retrieve.
- When you are wanting to access the properties of an "object" variable you could use brackets or dot notation. If you wanted to access a property
with spaces in its name you have to use brackets to do this.
Braces:
- These are used to wrap a block of code, this may be the code contained within a function, a loop, or within a conditional expression.
- Braces are also used to contain the properties & values of a JavaScript object.
Single Quotes:
- Single quotes can be used whenever you are wanting to declare a string in JavaScript. Single and double quotes can be used interchangably in this way
but they cannot be mixed. If for example you start a string with single quotes you must also finish it with single quotes. If you wanted to use quotes
within your string you could used double quotes within those however, e.g. 'example "text" string'.
- Single quotes can be used when you want to pass some HTML code to a variable using JavaScript.
Double Quotes:
- You would use double quotes in the same manner as I have described for single quotes above. You would also use them in conjunction with single quotes
where you have a need to display a string within the string you have already declared, or where you need to exit the string in order to display some other code
such as in some instances when you are using JavaScript to alter HTML elements of a website.


Social Networks and Archival Context Cooperative Program Launches
The U.S. National Archives and Records Administration (NARA), the University of Virginia, and the California Digital Library are pleased to announce the launching of the Social Networks and Archival Context (SNAC) Cooperative Program. The two-year pilot phase of the Cooperative is generously funded by a $1 million grant from The Andrew W. Mellon Foundation to the University of Virginia.
NARA will serve as the secretariat of the Cooperative, and the Institute for Advanced Technology in the Humanities at the University of Virginia, in collaboration with the California Digital Library, will host the technical platform.
Inaugural Members
While the Cooperative is ultimately intended to be international, the inaugural pilot members are drawn from a cross-section of U.S. archives, libraries, and museums.
American Institute of Physics
American Museum of Natural History
George Washington University
Getty Research Institute
Harvard University
Library of Congress
National Archives and Records Administration
New York Public Library
Princeton University
Smithsonian Institution
Tufts University
University of California, Irvine
University of Miami
Yale University
Objectives
The pilot phase of the Cooperative will have both social and technological objectives. The social objectives include developing the secretariat administrative structure, and developing a community-based governance structure. The primary technological objective will be transforming the SNAC R&D platform into a platform that will support ongoing cooperative maintenance of the SNAC description and access data. Inaugural members will be key partners in developing the governance structure, and both the maintenance and public facets of the technological platform. While new members will not be added during the two-year pilot implementation, the Cooperative will welcome expressions of interest in future membership.
About SNAC
SNAC began as an R&D project in 2010 with a grant from the National Endowment for the Humanities. The project has demonstrated the feasibility of separating the description of persons, families, and organizations—including their socio-historical contexts—from the description of the historical resources that are the primary evidence of their lives and work. SNAC has also demonstrated that the biographical-historical data extracted and assembled can be used to provide researchers with convenient, integrated access to historical collections held by archives and libraries, large and small, around the world.
Initial work made it clear that the potential power of the assembled data to transform research and improve the economy and effectiveness of archival descriptive practices required more than digital tools. With funding from the Institute for Museum and Library Services and the Andrew W. Mellon Foundation, the SNAC team performed detailed planning on how best to transform the R&D into a sustainable international cooperative that would enable archivists, librarians, and scholars to maintain the descriptive data and to extend the scope of the people and records included. The SNAC Cooperative aspires to improve the economy and quality of archival processing and description, and at the same time, to address the longstanding research challenge of discovering, locating, and using distributed historical records.
SNAC is the recipient of the 2015 Society of American Archivists C.F.W. Coker Award. One supporter wrote that SNAC “will fundamentally begin to change the landscape of archival description: the program will be a substantive contribution to the national, and indeed, international platform, making the description of archives more efficient and effective, and significantly ameliorating the challenge of discovering, locating, and understanding the resources that document our shared history.”
Collaborators
The Institute for Advanced Technology in the Humanities at the University of Virginia, the California Digital Library, and the School for Information Science at the University of California, Berkeley collaborated on the SNAC R&D (2010-2015). The same organizations and the U.S. National Archives and Records Administration collaborated on planning the SNAC Cooperative (2012-2015). During the planning process, archivists, librarians, researchers, scholars, and funders were consulted and provided invaluable assistance.
Social Networks and Archival Context (SNAC) is pleased to announce two major developments: the release of a redesigned web site and Prototype Historical Research Tool and a generous grant from the Andrew W. Mellon Foundation.
Redesigned Website and Prototype Historical Research Tool
SNAC has substantially revised and improved the SNAC web site and the Prototype History Research Tool. The prototype is an aggregate of biographical information about people, both individuals and groups, who created or are documented in historical resources. Users can explore the lives of individual people, organizations, and families; browse featured descriptions; and discover and locate connected historical resources that document these lives.
This release of the prototype draws on more than 2.6 million (soon to grow to more than 3.5 million) descriptions of persons, organizations, and families. These descriptions were derived from 2.2 million WorldCat archival descriptions and nearly 300,000 British Library authority records. Forthcoming releases will include descriptions derived from nearly 190,000 detailed descriptions of historical collections provided by a wide range of government and academic archives and libraries.
The persons, organizations, and families represented include the familiar (Thomas Jefferson and Guy Fawkes), the inspiring (Elizabeth Blackwell, Florence Kelley, and Eddie Mabo), and the perhaps less known (the 11th Bombardment Group Association and the Ohio Covered Bridge Committee).
Cooperative Program Planning
The SNAC team is also delighted to receive additional funding from the Mellon Foundation to support the final planning for an international archive description and access cooperative, to be hosted by the U.S. National Archives and Records Administration (NARA). The Cooperative will enable archivists, librarians, and scholars to maintain the descriptive data and to extend the scope of the people and records included. It will improve the economy and quality of archival processing and description, and will address the longstanding research challenge of discovering, locating, and using distributed historical records. The current work will establish the legal, administrative, and technical structure of the Cooperative, in preparation for a pilot implementation in 2015.