| DOSE: T+ 0:00 |
12.5 mg |
oral |
5-MeO-DMT |
(powder / crystals) |
| T+ 5:00 |
|
smoked |
Cannabis |
(plant material) |
Approx. 12.5mg of 5-MeO-DiPT was measured by dividing 100mg into 8 parts. Not the best way to measure, but even taking double the target dose would still be within a reasonable safety range. The gelcap was taken with a glass of water on an empty stomache.
First effects were noted within about a half hour. This was my second experience with this substance. The trip was not really anything special, and not worth going into detail.
After the 5 hour mark, I was definatly 'down,' and made the decision to go to a local keg party.  At the party, I started feeling very strange. I was well hydrated, and had eaten just 1 hour before. Suddenly, while standing and listening to music, my world began to fall apart. The room began spinning, and my consciousness began to slip away. Everything went black.
I awoke amidst a crowd of people, and a woman asked me if I was ok. I said 'I don't know', and managed to get outside for some fresh air. The remainder of the comedown was marked by a strange, almost sick feeling in the back of my head, almost like a headache, but steady and not throbbing. This was similar to the after effects of a previous Fox trip, but stronger.
Eventually, I got to sleep that night. I awoke, feeling extremely 'burned out'. Water tasted like old pennies, and food tasted like clay. When I smoked a cigarette, I coulden't feel the nicotine at all, and it brought me no satisfaction whatsoever. Sex was boring and more of a routine than an indulgence. There was also severe depression. The only thing that could have made me happy that day was for someone to put a bullet in my head. Luckily, I am a relativly strong minded person, and just took it easy, attributing my mental state to the strange drugs I had consumed the night before. I felt as if my personality, ego, and willpower had been flatlined.
This conditiond gradually relaxed over the next few days. I felt my emotions flowing back into me like much needed oxygen. The depression faded, and I regained the positive outlook on life that I usually have all the time. It is now day 3 after the trip, and I still don't feel 'right'. I'm fairly certain these effects will wear off, because the more time that passes the better I feel.
Overall, the trip itself was fine, similar to my first experience. The negative effects I experienced scared me a lot. I'm seriously considering never doing this drug again. No other people who took equivilant dosages of this drug experienced any negative symptoms other than the expected next-day burn out. I strongly question the safety of this substance.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


| Created: | 1/27/2021 3:42:04 PM |
| Modified: | 1/27/2021 3:42:04 PM |
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Public bigint waiver_id |
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Public bigint waiver_waiver_type_id |
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Public bigint waiver_waiver_name_id |
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Public bigint waiver_funding_source_id |
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Public timestamp with time zone(0) created_at |
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Public bigint created_by_user_id |
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Public varchar(255) created_by_user_sub |
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Public varchar(255) created_by_user_first_name |
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Public varchar(255) created_by_user_last_name |
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Public varchar(255) created_by_user_email |
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Public timestamp with time zone(0) updated_at |
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Public bigint updated_by_user_id |
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Public varchar(255) updated_by_user_sub |
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Public varchar(255) updated_by_user_first_name |
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Public varchar(255) updated_by_user_last_name |
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Public varchar(255) updated_by_user_email |
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Public timestamp with time zone(0) start_date |
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Public timestamp with time zone(0) end_date |
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Public bigserial ods_id |
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Public jsonb ods_meta |
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Public varchar(255) ods_created_by |
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Public timestamp with time zone(0) ods_created_at |
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Public varchar(255) created_by_user_oid |
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Public varchar(255) updated_by_user_oid |
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Public waivers_pkey( ods_id: bigserial, |
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| Owner | public |
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| isFinalSpecialization: | 0 |


Charles M. JonesDummy text of the printing and typesetting industry.
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Jobs requirement
1. Junior Data Scientist
Data Science, Machine Learning, Statistical Modelling techniques that may include; Gradient Boosting / XGBoost, Neural Networks, Recommendation / Decision / Scoring Engines, Predictive Modelling, Linear/Logistic Regression, Attribution Modelling, Customer Segmentation, Unsupervised & Supervised Learning, Bayesian Statistics, Principal Component Analysis
2. Data Scientist:
Python development experience, preferably in the AI and ML space,
Database (SQL or NoSQL) development experience, Git
3. Data scientist:
Exposure to Big Data platforms, such as Data bricks or Spark.
Experience with SQL essential; exposure to Azure or GCP preferred.
4. Data scientist:
Fluency in at least one of the following programming languages R, Python, Scala
Familiarity with the following data-related technologies Hadoop, Pig, Hive, Impala, SQL, Teradata, Oracle, SAS, MongoDB
High-level understanding of architecting cloud-based solutions with the following products AWS Redshift/RDS, S3, EC2, Lambda, EMR, SageMaker, DynamoDB, Cloudformation, Athena, Kinesis – or equivalents in Azure or Google Cloud Platform
5. Data scientist:
Experience using Python, PySpark, R or SparkR programming languages through development environments including Databricks for developing supervised and unsupervised machine learning models, with a particular emphasis on Natural Language Processing.
Demonstrated experience in using data science preferably for economic research, working with Australian Labour Market data such as ABS Quarterly Labour Force Survey and Census.
Experience with proof-of-concept development, preferably in Power BI or Shiny.
Experience working with big, unstructured datasets. Knowledge of the Burning Glass dataset would be an advantage.
6. ML Engineer:
Experience working with Kubernetes, preferably with GCP, Docker, Git and Cloud Build
Experience with SQL essential; exposure to Big Query / Airflow preferred
Deep understanding of CI/CD patterns, best practices and tooling options
You have experience in building Infrastructure as a Code with Terraform
Languages: Python, REST API process
Exposure to MLOps, Data Science and Data Engineering teams preferred
Designing and improving GCP infrastructure solutions for Data Science Applications
Final things:
1. Course on git and github


CARE uses GPS to track your exercise. It will pay the user for each mile he runs or walks or for each minute he works out and the amount raised in each session would be donated to his favoured charitable organisation. The user will be able to track down his contribution about its use in the charity.
Discover NowSource of physical fitness is generally achieved through prope nutrition, physical exercise and sufficient rest.
Care is free android application for everyone. Please inform your friends about CARE site.
Its main objective is to keep you healthy, fit and fine. And to lead your fitness to helping hands by doing charity.It promotes
After analysing many theories, we have come up with the solution that people can be motivated to walk and run if they are given something in reward.
So, our app would keep a track of the users’ physical activity and generate rewards in proportion to the work done. This generated revenue would be donated to the users’ desired charities.


--- layout: root menuitem: Submissions title: Submissions author: Editor subtitle: 'Submission Guidelines' description: "tweetable description for metatdata" category: meta meta_image: "assets/img/filename.gif" ---
Put in your general submissions requirements here.
Describe what it is. We also do this:
In all cases, we follow COPE's Best Practice Guidelines for Journal Editors. See our Statement of Publication Ethics for more details.
timeline etc


Tag is a method or Rocforjs that allows creation of Single Virtual
HTMLElements Objects.
Tag is the core of Rocforjs, and The Library was inspired in Tag.
Tag returns a instance of Tag class when a new Tag is created. Tag requieres four basic parameters: tagString a special Rocforjs's type string with wich is possible build HTMLElements, fn is a param that allows bind any callback at tagString's events, scope to say at Tag that is working in a specific JS class, rvars to work with Rocforjs variables inside tagStrings, and alternatively props to send some properties to Tag when a new class
is created.
About fn and scope parameters: What if an HTMLElement must to have an event, or more than one event?. How it is possible that a tagString can hold events to create a new HTMLElement with events associated?
In this land enters the 'fn' Tag parameter.
So, previously, to put events in a tagString, exists some ways that resumes next table:
| EVENT TYPE DEFINITION | EXAMPLE EVENT IN tagString | fn USE MODE | scope USE MODE | DESCRIPTION |
|---|---|---|---|---|
| INLINE FUNCTIONS: | ||||
| As attribute | 'button(click="function(){alert(\'Im a function as attribute\');}) Some content.' | Not required. | Not required. | (NOT RECOMENDED) Function goes as a naturally inline event as in normally HTML tag. it will be avaluated and assigned at the event. |
| GLOBALS, LOCALS, CALLBACKS, NAMED, & ANONYMOUS: | ||||
| As global | 'button(click="global_fn") Some content.' | Not required. | Not required. | Tag evals 'global_fn' searching from the inmediately superior scope through window main scope. |
| As global using fn param | 'button(click="global_fn") Some content.' | global_fn | Not required. | Tag understand that 'global_fn' is a function. |
| As global with keyword 'cb' and using fn param | 'button(click="cb") Some content.' | global_fn | Not required. | Tag understand that 'cb' references a local or global callback, so, to Tag 'global_fn' is a function. |
| As local | 'button(click="local_fn") Some content.' | local_fn | Not required. | Tag understand that 'local_fn' references a local function. |
| As local with 'cb' keyword | 'button(click="cb") Some content.' | local_fn | Not required. | Tag understand 'cb' references a valid local function 'local_fn'. |
| fn param as callback referenced by 'cb' keyword | 'button(click="cb") Some content.' | function(){alert('something');} | Not required. | Tag understand 'cb' references a valid callback. |
| GLOBALS, LOCALS, CALLBACKS, NAMED, & ANONYMOUS USING 'fn' PARAM AS JS OBJECT: | ||||
| In IIFE local | 'button(click="local_fn") Some content.' | {'local_fn': local_fn} | Not required. | Reference 'local_fn' in 'fn' param and function's name in tagString must coincide. |
| To refer a callback | 'button(click="test") Some content.' | {'test':() => alert('Im a callback!')} | Not required. | Note that always reference in tagString coincide with key name in JS Object. |
| JS CLASS METHODS: | ||||
| Using 'ownmethod' keyword | 'button(click="myMethod") Some content.' | this.myMethod | Not required. | This is a direct reference to own current class method. |
| Using 'scope' Tag param and referencing the method's name in tagString | 'button(click="myMethod") Some content.' | Not required. | this | JS keyword this, references to current scope, so, in current class, this references it's scope, then, if current class has 'myMethod' accept it as a valid function. |
| Using just 'fn' param as a pseudo scope | 'button(click="myMethod") Some content.' | this | Not required. | In this case, Tag evals 'fn' param, so, as this references at current class, to Tag this is an object that holds methods and if holds 'myMethod' and if it is a valid function, then, it is accepted. |
| Using 'fn' param as JS Object and 'scope' param too | 'button(click="myMethod") Some content.' | {'myMethod': myMethod} | this | Reference 'myMethod' in both cases are equal and the JS Object value must be a valid current class method, then, as 'scope' param is sended, Tag assumes that the function reference is a valid current class method. |
All invalid or reppeated event writed in tagString will be rejected, so, in final 'tagstring' it's
wrong events are discarted as in entirely final HTMLElement.
Now, tagString holds its events and Tag will render this into a new HTMLElement, there is a particular
own characteristic of Rocforjs: The final HTMLElement will have its events by the association of the
callback and the event throwgh an 'eventListener', so, it will works in a "hide" ambient and the event and
it's callback never will be showed in the final HTMLElement (it is easy to recognize, just see in DOM the
HTMLElement structure, it could have it's attributes like id, class, title, etc. but no one event as onclick
or onmousemove, etc). This is the principle purposed by Rocforjs: "HTML codes and JS codes never have been
mixed".
To know what event has the HTMLElemnt Tag has a property called 'events'; if the
HTMLElement has not events, events Object will be null. If the HTMLElement created has inline child
elements, each child resides in property type Array called 'childtags' and each child holds its own
'events' JS Object. (Note: When use Tag, always, just one main HTMLElement will be created, with or
without child HTMLElements).
As the JS method 'addEventListener' assigns a functionality at determined event, JS has a
'removeEventListener' method to delete the indicated event, so, the event gived to the HTMLElement with the
tagString can always be deleted ussing 'removeEventListener' method, but, the resident event in 'events' JS
Object will exists yet. In fact, this data is only for information it do not has any functionality
predeterminated by Tag or Rocforjs because the event is already associated at final HTMLElement, but if once
the event is removed from it, but if is necessary, it is possible to reassign this functionality applying
again an 'addEventListener' to the HTMLElement and using the 'events' JS Object that holds its calback
function, but this must been realized manually.
About rvars: What if in the moment of setting a tagString exists the need to send a
variable?. After all, a tagString is just a simple and common string, so, how is possible to send variables
into a string?.
With ES6 and it's powerful tools this task is easy: Just use Template Strings. But if this solution is
insufficient...
Here enters the concept of rvars. This keyword is a achronym of
Rocforjs Variables.
An rvar is a variable with own characteristic
inserted into a string and could have a global or a particular reference. References are the way of how the
rvar in a string can be identified as a variable to be evaluated as it. Then, a global reference is a rvar
inserted into a string and can be evaluated directly by algorithm that searches its value against all
superior scopes of the current scope. A particular reference is a kind of reference that uses the parameter
'rvars' of Tag and was thinked to variables for current scope, this parameter can takes one of two methods:
first, just a direct reference to only one variable; second: a multiple reference to many variables in
current or superiors scopes. Next Table resume it:
| rvars Syntax Types | For global scopes | For local scopes | Example | Description |
|---|---|---|---|---|
| $rvar | Yes | No | let tag = this.Tag("p#my-p Testing a $x") | (NOT RECOMENDED) $x references a global variable or a variable in superior scope, it's name is 'x' and hold some string value as: "Rocforjs rvars!". Then the tagString resultant wil be: "p#my-p Testing a Rocforjs rvars!". This kind of rvar do not need to be referenced in rvars param. |
| $$rvar | Yes | Yes | let tag = this.Tag("p#my-p Testing a $$y", {'y': 'Rocforjs rvars!'}) | This kind of rvar was thinked to references particulary local variables on current scope, but it works for superior scopes and global variables too (For this task value 'Rocforjs rvars!' in {'y': 'Rocforjs rvars!'} would been changed by the variable reference, example: {'y': x}, in this case key 'y' references at variable 'x' of first kind of rvars). The requirement is that rvars param must to be inserted into a JS Object. This allows the possibility to use many rvars in tagString. |
| $(rvar) | No | No | let tag = this.Tag("p#my-p Testing a $(1 + 2)") | (NOT RECOMENDED) This kind of rvars is just to make mathematical operations. Any other value passed will generate error that console will log. |
Rocforjs has a internal algorithm that resides in a JS Object called _Vars. This object allows the evaluation of variables that resides in strings; so, the Rocfor.js Modules that has this functionality are: Mdown, Tag, Block and Component.
Example
// There is two ways to declare a new instance of Tag
// (it is unnecessary the use of 'new' JS reserved keyword because Tag already returns a new Object),
// 1. With a direct assignment:
1. class MyTag extends R {
2. constructor (props) {
3. super(props)
4. this.tag = this.Tag(`Hello World!`) // Here Tag wil process diractly the tagString 'Hello World!'.
5. }
6. }
// Assuming that DOM has an HTMLElement with the id 'test':
let mytag = new MyTag('test') // Here, send a string in props. This param can hold any value.
console.log(mytag.tag) // Now, variable mytag (a new object MyTag class) has a property tag, it is a Tag Object.
// Console will log:
Tag {tagstrings: {…}, tag: div, classlist: Array(0), idlist: null, idDOM: null, …}
childtags: null
classlist: null
events: null
idDOM: null
idlist: null
tag: div
tagstrings: {tagstring: "div Hello", mytagString: "Hello"}
__proto__:
delTag: ƒ ()
getTag: ƒ ()
setTag: ƒ (where)
tagChild: ƒ (index_or_id_child)
tagstringChild: ƒ (index_or_id_child)
__proto__: Object
// So, in this documentation will see each property and method returned from Tag.
// 2. With a indirect assignment:
1. class MyTag extends R {
2. constructor (props) {
3. super(props)
4. this.tag = this.Tag() // Here doesn't exists any tagString, neigther any param.
5. }
6. buildTag () {
7. this.tag = this.tag.createTag('Hello World!')
8. }
9. }
// In this situation, in line 4. property this.tag holds a 'constructor' method of Tag called createTag:
let mytag = new MyTag('test') // Here, send a string in props. This param can hold any value.
console.log(mytag.tag)
{}
__proto__:
createTag: ƒ (tagString, fn, scope, rvars, props)
__proto__: Object
// This method waits for the same params that Tag, but, needs 'props' too, then,
// allows the creation of many instances of Tag around the whole class MyTag, so, this.tag
// can create a new virtual HTMLElment in buildTag MyTag method, or in the method you decide.
// So, this.tag, once buildTag method is executed will return a Tag Object as the Object logged in the first case.
// As you can see, all Tag properties and methods are easy to understand and use too; tagStrings are easy to understand and write,
// then, let start to use Rocforjs in your Projects!
Properties
classlist
Properties:
| Name | Type | Description |
|---|---|---|
classlist |
Array | null | All Tag HTMLElement classes, included Tag's child HTMLElements. |
events
Properties:
| Name | Type | Description |
|---|---|---|
events |
Object | null | All Tag events list. |
idDOM
Properties:
| Name | Type | Description |
|---|---|---|
idDOM |
Object | null | All DOM's id repeated in Tag. |
idlist
Properties:
| Name | Type | Description |
|---|---|---|
idlist |
Array | null | All id's of each HTMLElements in Tag. |
tag
Properties:
| Name | Type | Description |
|---|---|---|
tag |
HTMLElement | null | The final Tag HTMLElement. |
tagchild
Properties:
| Name | Type | Description |
|---|---|---|
tagchild |
Array | null | Array of objects containing all Tag's children. |
Methods
delTag() → {Object}
Returns:
- Type
- Object
Example
this.tag = this.tag.createTag('Hello World!')
this.tag.setTag()
this.tag.delTag() // HTMLElement will be removed from DOM.
getTag() → {HTMLElement}
Returns:
- Type
- HTMLElement
Example
this.tag = this.tag.createTag('Hello World!')
this.tag.getTag() //
Hello World!
.
setTag(whereopt) → {Object}
If where param is ommited, by default, setTag will render final HTMLElement in body or in container determined in props as a id string of an HTMLElement that exists in DOM or JS Object with one of three possible keys: {['after'|'container'|'before']:'id_or_HTMLElemnt'}.
Parameters:
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
where |
String | HTMLElement |
<optional> |
'body'|'props['after|container|before']|props' | The DOM HTMLElement that will hold new HTMLElement. |
Returns:
- Type
- Object
Example
this.tag = this.tag.createTag('Hello World!')
this.tag.setTag() // HTMLElement will be rendered in DOM's body.
tagChild(index_or_id_childopt) → {HTMLElement|Array|null}
Parameters:
| Name | Type | Attributes | Description |
|---|---|---|---|
index_or_id_child |
String | Number |
<optional> |
The id or index of child element wanted. |
Returns:
- Type
- HTMLElement | Array | null
Example
this.tag = this.tag.createTag('Hello World! #[span#im I\'m a child Element. ]#[em Me too.]')
this.tag.tagChild('im') // I'm a child Element.  // It works with id's
this.tag.tagChild(2) // Me too. // It works with Array index.


Details¶
Modeling Levels¶
PRAM supports modeling on three levels of abstraction: Domain, class, and rule. Apart from being flexible, this design choice delivers expressive brevity in that it allows the modeler to invoke models in a space- and time-efficient manner. In what follows, we briefly describe an example model and then demonstrate how that model can be implemented on each of the three level.
The SIRS Model¶
The SIR epidemiological model 1 will help us illustrate the different modeling levels. In that model, population is compartmentalized into susceptible (S), infectious (I), and recovered (R). As shown on the image below, an infectious disease is transmitted between susceptible hosts with the rate β who eventually recover with rate γ. Because getting a disease does not need to result in life-long immunity to it, the model can be augmented by allowing recovered hosts to become susceptible again with rate α (which results in the SIRS model).
The Domain Level¶
The domain level allows the modeler to express their models on the level of their research area. For example, being familiar with the different models of infectious diseases, it would be natural for an epidemiologist to invoke a model like the SIRS directly. Here is a Python example of just that:
SIRSModel('flu', β=0.05, γ=0.50, α=0.10)
The Class Level¶
A modeler can also work on the class-of-models level. For example, an epidemiologist may know that the SIRS model can be implemented as a time-invariant Markov chain. Here is an example of how that can be coded in the PyPRAM
package using the TimeInvMarkovChain
rule:
β, γ, α = 0.05, 0.50, 0.10
transition_matrix = {
's': [1 - β, β, 0.00],
'i': [ 0.00, 1 - γ, γ],
'r': [ α, 0.00, 1 – α]
}
TimeInvMarkovChain('flu', transition_matrix)
The Rule Level¶
Finally, a modeler may choose to descend to the lowest level and implement the dynamics of their model directly. This is beneficial if what they are trying to express diverges from the set of modeling classes PyPRAM
provides (or to encode a particular sort of interaction between different models). Extending an existing class (e.g., the TimeInvMarkovChain
) is an example of modeling on the rule level as well even if minimal portions of the model dynamics are overridden. Here is a pseudo-code for the (slightly extended) SIRS model:
rule_flu_progression():
if group.feature.flu == 's':
p_inf =<EMAIL_ADDRESS>== 'i'} / n@ # n@ - count at the group's location
dm p_inf -> F:flu = 'i', F:mood = 'annoyed'
nc 1 - p_inf
if group.feature.flu == 'i':
dm 0.2 -> F:flu = 'r', F:mood = 'happy'
dm 0.5 -> F:flu = 'i', F:mood = 'bored'
dm 0.3 -> F:flu = 'i', F:mood = 'annoyed'
if group.feature.flu == 'r':
dm 0.1 -> F:flu = 's' # dm - distribute mass
nc 0.9 # nc - no change
rule_flu_location():
if group.feature.flu == 'i':
if group.feature.income == 'l':
dm 0.1 -> R:@ = group.rel.home
nc 0.9
if group.feature.income == 'm':
dm 0.6 -> R:@ = group.rel.home
nc 0.4
if group.feature.flu == 'r':
dm 0.8 -> R:@ = group.rel.school
nc 0.2
This pseudo-code is based on a Python-like notation we have been working on to help to expose the internal workings of a model without resorting to often unnecessarily verbose Python source code.
Ordinary Differential Equations¶
Mass Space¶
PyPRAM
supports simulating systems of ordinary differential equations (ODEs) operating on three types of spaces. First, systems of ODEs can be used as mass conversion operators. For example, the image below shows the conversion of mass for two substances, A and B, described by the exponential decay equation (i.e., \(dN/dt = -\lambda N\)). The decay constants for the two substances are \(\lambda_A = 1\) and \(\lambda_B = 0.05\).
As another example, the time series below shows the result of simulating a system of ODEs describing the SIR model.
Group Space¶
The second space which can be affected by a system of ODEs is given by groups. Because groups are defined by the values of their attributes and relations, this results in mass conversion (or flow) between groups, but the machanism by which this occurs is different than when the ODEs operate on the mass space.
The time series below shows the result of simulating the Lotka-Volterra population dynamics model. That model expresses the cyclic relationship between the size of prey population that grows via reproduction and the size of predator population which grows by consuming the prey.
Rule Space¶
Finally, the numeric integrator for a system of ODEs can be kept internal to the PRAM rule. In that case, it does not interact with the simulation context directly. Nevertheless, the results of the integration are available to all other rules. For example, the image below shows the phase plot of atmospheric convection modeled with three ODEs that form the Lorenz system. The solution to this particular initial value problem is the Lorenz attractor.
Composite Simulations¶
One of the goals of PyPRAM
is to elucidate the interactions between complex systems. The package hopes to do that via composite simulations, i.e., simulations composed of different models which are allowed to work independently and interact by simultaneously changing the shared simulation state space.
The SIR Model with a Flu-Spike Event¶
The time series below is a result of a simulation combining the SIR model with an event (i.e., a time-point perturbation). That event converts a large proportion (specifically, 80%) of the recovered agents back into susceptible.
The SIR Model with a Flu-Spike Process¶
A more interesting and realistic scenario might involve not an event but a process (i.e, a time-span perturbation). For example, the time series below shows the intensity of a process described by the scaled gamma distribution.
When this gamma process is combined with the SIR model, the PRAM simulation produces a time series shown on the image below. Iterations 1-999 are dominated by the SIR model which converts mass from S to R via I (i.e., susceptible to recovered via infectious). However, from that point on (i.e., for iterations of 1000-3000), additionally to that model, the gamma process shown above converts a portion of the recovered agents back into susceptible. As shown on the plot below, the interplay of the two PRAM rules (with the SIR model dynamics being encoded by a system of ODEs) produces an interesting effect of the infection level in the population being stretched in time plausibly resulting in a model of a long-term epidemic.
The Lotka-Volterra Model with a Food Restriction Process¶
The Lotka-Volterra model of population dynamics contains four parameters. When one of them, the prey reproduction rate parameter, is affected by a linear process that decreases it slowly but surely, the following picture emerges.
By decreasing the reproductive rate of prey, that linear process models increasingly hostile natural environment. The process does not directly disturb the sizes of the two populations and affects the population dynamics indirectly (plausibly by restricting the prey food sources). While using such a simple process is perfect for expositionary purposes, a more realistic model would involve breaking the linear process down into sub-processes, each corresponding to the dynamics of an asymptotically barren ecosystem.
Even though the process changes the prey reproductive parameter in very small decrements, it nevertheless leads to the eventual extinction of the predator population (due to insufficient size of the prey population) and then the prey population itself. If we assume that the simulation parameters are biologically and ecologically valid, this simulation predicts the predator species to go extinct in 80 years and the prey population to follow in another 50 years.
Mass Dynamics¶
In the context of a PRAM simulation, mass dynamics can be defined in at least three related but distinct ways. First, we could understand it as mass locus (\(m\)); such conceptualization would allows us to answer the question “Where is mass?” Second, we could define it as mass flow (i.e., the first derivative of mass locus, \(dm/dt\)) which would permit answers to the question “How did it get there?” Finally, we could talk of the mass flux (or rate of mass flow, i.e., first derivative of mass transfer and the second derivative of mass locus, \(d^2m/dt\)). The rate answers the question “How quickly did it move?”
Mass Spaces¶
Mass dynamics in PRAMs can be considered in the group space or the probe space. The group mass space is a partition defined by group attributes and relations and thus contains all the groups in a simulation (for that reason, the name simulation mass space would be adequate as well). The probe mass space on the other hand is typically smaller (i.e., it has fewer dimensions) because the mass distributed among the groups is typically aggregated by probes. For example, while the SIR model can be invoked in a simulation containing many agents attending many schools, a probe defined by the user will reveal their interest to be on a high level of, e.g., “size of populations of infected students at low vs medium income schools over time.”
Mass Locus¶
Below are a few examples of how mass locus can be visualized using steamgraphs. First, we have the SIR model which was described earlier.
Next, we have a simulation of the SIR model composed with a gamma process which at iteration 1000 starts to convert recovered agents back into susceptible. That gamma process quickly overpowers the SIR model’s attempts to convert agents into recovered (via infectious) but then eases off and eventually play no role.
Next, we have the segregation model 2 in which mass dynamics is the result of the agents’ motivation to be close to other similar agents (e.g., blue agents want to be in proximity of other blue agents) and far away from dissimilar agents (e.g., blue agents do not want to congregate near red agents).
Finally, we have a simulation of the SIR model at eight different schools. The SIR models at each of those schools are slightly different in that the transmission probability depends on the size of the school, i.e., the probability of a student to become infected is proportional to the number of infectious students around him. In that way, larger schools are more likely to be afflicted by an epidemic.
Mass Flow¶
Below is an example of visualization of mass flow in the SIR model that has been run for seven iterations.
Trajectories and Trajectory Ensembles¶
A PRAM simulation need not to be deterministic. In fact, simulations imbued with stochasticity are likely the more interesting kind. In order to properly account for a stochastic nature of those simulations, the software enables execution of multiple independent simulations. The trace of those simulation runs yields an ensemble distribution which can then be inspected statistically for patterns (e.g., the expected number of years until underground water wells dry up in a region given water utilization strategies S1 versus S2 or the worst-case scenario under a set of utilization strategies). Because the states of individual simulations can be conceived as sequential interacting samples of the system state, this method belongs to the mean field particle class. While beginning with a set of user-defined or random initial states (or a combination thereof) is the simplest solution, a more elaborate initial state selection could be employed as well.
Example: The SIRS Model + Beta Perturbation¶
Let us illustrate this idea with a simulation of two interacting models. The first model is the SIRS model. The second model is a stochastic process that at every simulation step converts a small portion of the recovered agents back into susceptible. That random conversion probability is a random draw from the \(\text{Beta}(2,25)\) distribution. Below is the histogram of 100,000 such draws.
While the result of these two models interacting is fairly easy to anticipate, this may not be the case for larger systems of models. Below is a line plot of 10 randomly selected trajectories of this ensemble. Note that the actual data is not smooth; the plot represents splines fitted to each of the three series within each of the 10 trajectories.
This is how a 100 samples would look like.
Example: The SIRS Model + Beta Perturbation + Gamma Process¶
In this example, we will investigate a simulation consisting of the same SIRS model and a beta perturbation but this time there will also be a gamma process which, like before, converts an increasingly large number of recovered agents into the susceptible ones only to ease off and eventually cease to affect the simulation altogether. Below is mass dynamics for an ensemble of 10 trajectories.
Because directly plotting large number of individual trajectories may not produce a clear image, trajectories can be aggregated over. One example of such aggregation is shown below. Here, the mean and the interquartile range (IQR) for each of the three groups (i.e., S, I, and R) is shown instead of the individual series.
References


Register an ETLBox license key
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You have two options here:.
Option 1
Just copy the file in the same folder where the ETLBox.dll resides. This is normally the root folder of your project.
If you add it to the sources of your project, make sure that the option "Copy to output directory" is set to "Copy always" or "Copy if newer".
Option 2
Set up a user-wide or machine-wide environment variable. The name of the Environment variable must be "etlbox" (without quotes).
Copy the conent of your license file into an environment variable called "etlbox". No license file is required then.
\mac\Home\Github\roadrunnerlenny\etlbox.docu\ETLBoxDocu\index.md


in a distant world, you find yourself lost. you are traveling from city to city hoping to find a place to call home, only to find deep flaws within each city you encounter. each city you come across seems to embody a societal or human flaw and you are faced with tough decisions in order to navigate these places. you follow your character along her journey and learn more and more about her as the game’s story unfolds. you have the option to choose your path and the decisions you make - but you tend to find you are almost always faced with opposition. SPRAWL is an empathetic journey bringing light to the darkest parts of our society and letting you feel firsthand the difficulty of being an outsider and alone. the world of sprawl is strange, enticing, and beautiful and with that comes plenty of things to see, people to meet, and lessons to learn. here’s an overview of the cities you will encounter as you explore the world:


--- layout: post authors: ["Greg Wilson"] title: "Top 10 Myths about Teaching CS" date: 2015-07-18 time: "16:10:00" tags: ["Research", "Teaching"] ---
Mark Guzdial (whose blog has been a frequent inspiration) recently wrote an article title Top 10 Myths about Teaching Computer Science:
Guzdial backs up each of his points with citations from the research literature, but as he points out, even scientists pay more attention to authority than to evidence:
Several senior, well-established (much more famous than me) faculty strongly disagreed with the evidence-based argument I was making. The thread finally ended when one of the most senior, most respected faculty in the College wrote a note saying (paraphrased), "There are probably better teaching evaluation methods than the ones we now use. I'm sure that Mark knows teaching methods that would help the rest of us teach better." And that was it. Thread ended. The research-based evidence that I offered was worth fighting about. The word of authority was not.
I'll bet that faculty across disciplines similarly respond to authority more than evidence. We certainly see the role of authority in Physics Education Research (PER). Pioneering PER researchers were not given much respect and many were ostracized from their departments. Until Eric Mazur at Harvard had his students fail the Force Concept Inventory (FCI), and he changed how he taught because of it. Until Nobel laureate Carl Wieman decided to back PER (all the way to the Office of Science Technology and Policy in the White House). Today, the vast majority of physics teachers know research-based teaching methods (even if they don't always use them). FCI existed before Mazur started using it, but it really started getting used after Mazur's support. The evidence of FCI didn't change physics teaching. The voice of authority did.
While we might wish that CS faculty would respond more to evidence than authority...this insight suggests a path forward. If we want CS faculty to improve their teaching and adopt evidence-based practices, top-down encouragement can have large impact. Well-known faculty at top institutions publicly adopting these practices, and Deans and Chairs promoting these practices can help to convince faculty to change.
We have the same trouble convincing scientists that training in computing skills is worthwhile (or more precisely, that scientists don't already know this stuff and aren't "just" going to pick it up themselves). Rather than collecting data and trying to use science to persuade scientists, perhaps we should be trying instead to get more senior scientists to say, "Make it so."


Contents
Short Descriptions
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can be used to start applications and can be used to send messages to already-running instances of other applications. |
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is a simple tool used for working with D-Bus objects. |
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is used to generate code and/or documentation for one or more D-Bus interfaces. |
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is used to create a giomodule.cache file in the listed directories. This file lists the implemented extension points for each module that has been found. |
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is used to read the resource description from file and the files that it references to create a binary resource bundle that is suitable for use with the GResource API. |
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is used to compile all the GSettings XML schema files in directory into a binary file with the name gschemas.compiled that can be used by GSettings. |
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is a C code marshaller generation utility for GLib closures. |
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is a variant of the gettext internationalization utility. |
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is a C language enum description generation utility. |
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is a small utility that draws a tree of types. |
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offers a simple commandline interface to GResource. |
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offers a simple commandline interface to GSettings. |
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is a test running utility. |
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is a test report formatting utility. |
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contain low-level core libraries for the GIMP Toolkit. |


Rust in 2018: a people perspective
The call for #Rust2018 blog posts has generated a fantastic set of responses so far, and there’s already an emerging consensus around much of the technical focus for the year. Since I largely agree with what others have said on that front, I want to focus my post on the people side of things: what kind of impact do we want to make on people, both contributors and customers, in 2018?
Tell our story with a new product
Rust, like major web browsers, ships a new version every six weeks. There are a ton of advantages to this rapid release process, but two major people-related downsides:
Contributor downsides. Part of the appeal of rapid-release is that “there’s always another train on the way”; there’s no need to sprint to land something in a given release, because another one will follow soon. But that also makes it hard to “rally the troops”, bringing together the whole community to drive a cohesive set of goals all the way to completion.
Customer downsides. There’s a kind of “frog boil” effect from rapid releases; Rust is always improving, a little bit at a time, so it can be hard to fully grasp the large shifts that accumulate, especially if you’re not following development closely.
In 2017, we merged an RFC introducing epochs. While the discussion focused on the technical mechanics, to me the thrust of the idea is to supplement our release cycle with periodic “product” releases. These are sometimes called “marketing releases”, but I think marketing is just one (important!) part of the story:
When thinking about Rust as a product, we shift our focus away from the details of particular features, and instead think about the end-to-end experience of Rust. How do people hear about Rust, and what draws them in? What are their first impressions of Rust? What are the major wins and pain points at every point from novice to expert? This product focus helps us prioritize our efforts on what will make the biggest impact on people using, or thinking about using, Rust.
Part of the end-to-end experience is coherence: making sure that the set of features available on stable work well together, without major gaps; that these features are well documented; that the features are fully supported by tools like IDEs; that the compiler provides top-notch error messages for the full set of features; that there is likewise a coherent set of libraries available in the ecosystem that works well with the set of currently-stable features.
Aiming for a major product release gives us an opportunity, as a community, to come together and do something big that goes well beyond the usual six week cycle. We’ve seen this effect leading up to the Rust 1.0 release, and also with the more recent impl period. A product release gives us focus and drive.
Finally, there’s the marketing aspect, which comes in several layers. Releasing “Rust 2018” gives us a chance to say to the world that “Rust has taken a major step since 1.0; it’s time to take another look”. That, of course, ties directly back to the end-to-end experience; we’ll want to have a polished web site, installation process, etc. For existing Rust users who are not deeply involved in Rust’s development, the product release gives a way to understand Rust’s evolution as an overarching narrative. We can explain how the features stabilized since the previous epoch all fit together to establish new idioms.
I believe that 2018 should be an “epoch year”, in which we focus on shipping a quality product, for all of the above reasons. That’s going to require a lot of discipline, and a steady stream of stabilizations, but I think we’re up to the challenge!
Empower new technical leaders
I’m really proud of the work we did in 2017 to grow Rust’s formal teams, including creating several new subteams and expanding all of the existing ones. But we’re still suffering from a deficit of technical leadership. That’s in part because technical leadership is a hard job with mostly intangible effects; it’s largely about enabling other people to do the on-the-ground technical work, by working to reach consensus on constraints and high-level design. It requires enormous empathy, being able to understand the goals of a wide variety of people and thread the needle between them. And it often doesn’t involve landing reams of code with your avatar attached to them.
One of my personal lessons from 2017 is that we need to Think Big when it comes to Rust’s teams. Rust is a staggeringly large project with a huge and talented community, and we need its leadership structure to fully reflect that if we are to reach our full potential.
Concretely, this might look like:
Continuing to grow and subdivide the teams, so that we have more people in total involved in leadership and decision-making, but each individual has a narrower focus relative to today. This echos Niko’s points about impl period working groups, which was one such attempt. Splitting up the “tools” team into “dev tools”, “cargo”, and “infrastructure” in 2017 was another such example.
By the end of the year, having no single person leading more than one subteam. That would hopefully reflect a greater degree of importance and accountability around team leadership.
Improving the RFC process to make it more manageable for team members and the broader community alike. There are some strawman ideas on this front floating around, which will hopefully get written up soon.
In general, the point is that there’s potential for much greater parallelism within the Rust community than we have today, but to unlock that parallelism we need to grow our leadership capacity.
Engage corporations as users and sponsors
Rust’s adoption approach so far has been relatively “bottom up”: create a product with some strong potential business value, and focus largely on getting engineers “on the ground” to see that business value and work toward adopting it in their organization. Those engineers usually find small ways to use Rust, to prove it out in their organization, before getting more ambitious. It’s a great strategy.
However, as we seek to push further into larger, more conservative organizations, we need to supplement this bottom-up approach with a top-down one: make Rust appealing to CTOs. The primary way to do this is by making Rust look boring and safe as a technology choice. And we do that by showcasing our successes (we’ve commissioned some white papers to do this), being clear about where Rust makes sense and where it doesn’t, and projecting maturity, stability, and sustainability.
In 2018, we should take all of these efforts to the next level. We should have a polished web site that works for both engineers and CTOs, offering white papers and directing companies to sources of training, consulting, and support. And we should have a large and growing list of sponsors, like Mozilla, Bouyant, and Tilde and many others, who are funding Rust work in one way or another, either by paying their staff to contribute to Rust OSS, or by helping pay for project infrastructure, conferences, and the like.
Finally, we should do more to get production users engaged, at some level, in the RFC process. When we’ve talked to production users, the feeling is usually “we’re too busy writing Rust code and we trust you to get it right”. But the result is that RFC threads don’t present a picture fully inclusive of the production context.
Connect Rust’s global community
While we talk about “the Rust community”, the reality is that there are many Rust communities, separated by geography and by language. We need to do much more to connect these communities, again in terms of both contributors and customers. What are the important use-cases for Rust in India? What are the interests of volunteers in Brazil? What are the opportunities for Rust in China? How can we support each other, and communicate our respective values and needs?
Connecting these communities is not a small task, and I’m not sure what the right goal is for 2018. But I would love to see a greater awareness of and focus on this issue.
Serve intermediate Rustaceans
In 2017, we put a strong emphasis on early-stage productivity and learning curve, which has consistently been the top issue raised by the Rust survey. But last year, we’ve also heard an increasing plea for more “intermediate” level materials, focused on people who have learned the basic mechanics of the language and have written some code, but are looking for help on how to be effective as a Rust programmer. How should you organize a library? An app? When should you use traits? What about trait objects versus generics? And what libraries and tools should you be highly familiar with?
We’ve made some strides on this front in 2017 with efforts like the API guidelines and the cookbook. But there’s still a lot more to do in terms of (1) surfacing crates and tools that “every working Rustacean should know” and (2) fleshing out more guidance for how to wield Rust effectively, after you understand the features it provides.
Treat each other with empathy
One of the most amazing things about Rust is that it brings together grizzled C++ hackers, Raspberry Pi hobbyists, and JS pros and more into a single community. Rust offers something to all of us, despite that our goals, values, and interests sometimes diverge. Its ambition is to democratize robust, high performance code, to make systems programming better and more accessible to everyone.
The secret sauce has been a certain unwillingness to compromise: to find a way to take this diverse set of goals, backgrounds and contexts, and serve them all simultaneously by digging deep and thinking creatively. To keep that up, it’s vital that we don’t descend into tribalism or us-versus-them thinking, but instead to respect each other’s constraints, and trust that our constraints will be heard and respected as well.


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Bio
My name is Adam Mudd. For the past 10 years, I have taught High School Social Studies classes. While I loved my time as a teacher, I have decided to persue a new career in Web Development.
My experiences with web development started by taking a highschool class in HTML 2. Since then, I participated in Code Louisivlle, from which I should graduate in three weeks. I am interested in continuing my learning, and learning more back end languages in the future.
You will find a number of projects I have put together in order to test my skills on this page. Most of them were desgined in order to solve a problem I have encountered in life, or in my various nerdy hobbies. If you would like to contact me, don't hestitate to reach out on one of the sites listed above. Thanks for visiting.


Chapter 5 "Search Inside Yourself" - When programming, what are some of your triggers? What causes a disproportionate emotional response?
I definitely have experienced some negative emotions since starting phase zero of Dev Academy. It has usually come about through not understanding the code and what it is doing, or trying to do. When you are studying on your own, without the traditional framework of a classroom and teacher, it can be quite a struggle at times. Even now, I have concerns that I may not be understanding everything as I should, and bootcamp is getting close! I am hoping things sink in more over the next three weeks. I have faith in myself that I can start to thrive once I'm in the bootcamp environment, and understand the concepts more deeply.
How did you find the Siberian North Railroad exercise (Stop, Breathe, Notice, Reflect, Respond)?
Stopping allows me to acknowledge that I am experiencing a negative emotion, and makes me halt from feeding the monster. Breathing helps me a lot to calm myself and let go. Reflecting on my own reaction from another person's perspective is interesting - it stops me from reacting, and helps me respond and deal with the negative emotion more thoughtfully.
This exercise is very useful, and I find that it sits well with my personality, as well as my learning techniques.


WITNESS LIST
Education
April 18, 2017 9:00 AM
FOR:
Adams, Shay Chief Financial Officer (also providing written testimony) (Lovejoy ISD),
Allen, TX
Blindau, Jo Ann Superintendent (Hallittsville ISD), Schulenburg, TX
Carroll, Cody Superintendent (Krum ISD), Krum, TX
Ciavaglia, Mark E. (Self), Texas City, TX
Dear, Rich Superintendent (Godley ISD), Fort Worth, TX
Easterling, Bobby Superintendent (also providing written testimony) (Kim NED CISD),
Buffalo Gap, TX
Flores, Alex Superintendent (Palacios ISD), Palacios, TX
Ford, Buck Superintendent of schools (Blanco ISD), Blanco, TX
Gonzalez, Beto D. Superintendent (Webb CISD), Bruni, TX
Hill, Johnny W. Assist. Superintendent-Finance/CFO (Lake Travis ISD), Austin, TX
Lewis, Micah Superintendent (Grand Saline ISD), Grand Saline, TX
Marshal, Amy Board member (Webb CISD), Bruni, TX
Paymale, Dave Superintendent (Goliad ISD), Goliad, TX
Warren, Ryder Superintendent (Northwest ISD), Justin, TX
Williams, Doug Superintendent (Sunnyvale ISD & Texas School Coalition), Sunnyvale,
TX
AGAINST:
Colbert, Paul (Self), Houston, TX
Moreno, Celina Attorney (MALDEF), San Antonio, TX
Sanderson, Josh Deputy Executive Director (Equity Center), Austin, TX
ON:
Exter, Monty Lobbyist (Association of Texas Professional Educators), Austin, TX
Registering, but not testifying:
FOR:
Beneski, Amy Deputy Executiev Director (Texas Association of School Administrators),
Austin, TX
Callaway, Wade Principal (Gruver ISD), Gruver, TX
Campbell, Grover Assoc. Ex. Dir. Gov. Rel. (TASB), Austin, TX
Collum, Jeff Superintendent (Hallsville ISD), Hallsville, TX
Haenisch, Barry Executive Director (Texas Association of Community Schools), Austin,
TX
Motheral, Mike Executive Director (Small Rural School Finance Coalition), Lubbock, TX
Nichols, Colby Attorney (Texas Rural Education Association), Austin, TX
Parenteau, Julia Associate Director of Legislative Affairs (Texas Assn. of Realtors),
Austin, TX
Rome, Christy Executive Director (Texas School Coalition), Austin, TX
Rotan, Wayne Superintendent (Glen Rose ISD), Glen Rose, TX
Shanley, David Superintendent (Johnson City ISD), Dripping Springs, TX
Smith, Michelle Consultant (Texas Association of School Business Officials), Austin, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
Struck, Maria Liza Blanco ISD Board of Trustees (Blanco ISD Board of Trustees), Blanco,
TX
AGAINST:
Banks, Yannis (Texas NAACP), Austin, TX
Cavazos-Reyna, C. LeRoy Vice President of Government Affairs (San Antonio Hispanic
Chamber of Commerce), San Antonio, TX
Hinojosa, David (Texas Latino Education Coalition), San Antonio, TX
Puente, Jaime Doctoral Student (Texas Graduate Student Disability), Houston, TX
Quinzi, Patty Legislative Counsel (TX-American Federation of Teachers), Austin, TX
Providing written testimony:
FOR:
Hambrick, J. Glenn Superintendent of schools (Carthage ISD), Carthage, TX
Hebert, Bryan (School Taxpayer Relief Coalition), Austin, TX
Tate, Devin Becville ISD Supt. (Beckville ISD), Beckville, TX
AGAINST:
Villanueva, Chandra Policy Analyst (Center for Public Policy Priorities), Austin, TX
ON:
Carney, Dee Moak, Casey, & Associates (Texas School Alliance), Austin, TX
FOR:
Dempsey, Rachel Strategic Communications Manager (also providing written testimony)
(Families Empowered), Pearland, TX
Dunn, David Board member/alumni, parent (Uplift Education), Dallas, TX
Dunn, David Executive Director (Texas Charter Schools Association), Austin, TX
Gonzales-Neal, Wendy Parent advocate (Self), Tomball, TX
Gore, Rex Citizen/board member public charters (Self), Austin, TX
Mann, Dawn Board member/parent (Uplift Education), Dallas, TX
Matlock, Neal Charter School Board Member (Odyssey Academy), League City, TX
Perez, Priscilla Parent (Anne Frank Inspire Academy), San Antonio, TX
Ray, David Executive Director (St. Anthony School), Dallas, TX
AGAINST:
Quinzi, Patty Legislative Counsel (also providing written testimony) (TX-American
Federation of Teachers), Austin, TX
ON:
Byer, Von General Counsel (Texas Education Agency), Austin, TX
Registering, but not testifying:
FOR:
Arnold, Ellen (Goodwill Central TX), Austin, TX
Boone, Marcus Parent, citizen (NYOS), Austin, TX
Boswell, Courtney Executive Director (Texas Aspires), Austin, TX
Domaschk, Emily Mama & Texan (NYOS & my boys), Elgin, TX
Flores, Robert (Texas Citizens Action Network), Austin, TX
Gomez, Addie Exec. Director (Texans for Quality Public Charter Schools), Austin, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
Goodsheller, Miranda Governmental Affairs Manager (Texas Association of Business),
Austin, TX
Larson, Mark CEO (KIPP San Antonio Public Schools), San Antonio, TX
List, Amanda (Texas League of Community Charter Schools), Austin, TX
Painaik, Umesh D. (NYOS Charter School), Austin, TX
Rickey, Richard N. CEO (Orenda Education), Georgetown, TX
Sage, Thomas Partner (Texas Charter Schools Association), Houston, TX
Savener, Tiffany Parent (NYOS Charter School), Austin, TX
AGAINST:
Banks, Yannis (Texas NAACP), Austin, TX
Beneski, Amy Deputy Executive Director (Texas Association of School Administrators),
Austin, TX
Campbell, Grover Assoc. Ex. Dir. Gov. Rel. (TASB), Austin, TX
Carney, Dee Moak, Casey, & Associates (Texas School Alliance), Austin, TX
De Leon, Marty (Texas Urban Council), Austin, TX
Grey, John Government Relations Specialist (Texas State Teachers Association), Austin,
TX
Haenisch, Barry Executive Director (Texas Association of Community Schools), Austin,
TX
Hinojosa, David (Texas Latino Education Coalition), San Antonio, TX
Moreno, Celina Attorney (MALDEF), San Antonio, TX
Nichols, Colby Attorney (Texas Rural Education Association), Austin, TX
Sconzo, Guy Executive Director (Fast Growth School Coalition), Kingwood, TX
Terry, Mark Deputy Executive Director (TEPSA), Austin, TX
Providing written testimony:
FOR:
Conger, Eddi Supt. International Leadership of Texas (N/A), Rockwall, TX
FOR:
Baker, John School Superintendent Seymour ISD (Sermour ISD), Seymour, TX
Robertson Jr., Berhl Superintendent (Lubbock ISD), Lubbock, TX
Scurlock, Steve Executive Vice President (Independent Bankers Association of Texas),
Austin, TX
Registering, but not testifying:
FOR:
Beneski, Amy Deputy Executive Director (Texas Association of School Administrators),
Austin, TX
Campbell, Grover Assoc. Ex Dir. Gov. Rel. (TASB), Austin, TX
Haenisch, Barry Executive Director (Texas Association of Community Schools), Austin,
TX
Motheral, Mike Executive Director (Small Rural School Finance Coalition), Lubbock, TX
Smith, Michelle Consultant (Texas Association of School Business Officials), Austin, TX
Terry, Mark Deputy Executive Director (TEPSA), Austin, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
Providing written testimony:
FOR:
Anderson, David D. Consultant to Arlington ISD (Arlington ISD Board of Trustees),
Austin, TX
FOR:
Cowan, Julie Trustee (Self; Austin ISD), Austin, TX
Hogg, Bowie Board member (TASB/Arlington ISD), Arlington, TX
Waldrip, Mike Superintendent of Schools (Coppell ISD), Coppell, TX
ON:
Lopez, Leo Chief School Finance Officer (Texas Education Agency), Austin, TX
Registering, but not testifying:
FOR:
Beneski, Amy Deputy Executive Director (Texas Association of School Administrators),
Austin, TX
Colbert, Paul (Self), Houston, TX
Craymer, Dale President (Texas Taxpayers & Research Assoc.), Austin, TX
Eaton, Holly Director of Professional Development & Advocacy (TX Classroom Teachers
Assoc.), Austin, TX
Haenisch, Barry Executive Director (Texas Association of Community Schools), Austin,
TX
Kuhlmann, Kate Lobbyist (Association of Texas Professionals), Austin, TX
Motheral, Mike Executive Director (Small Rural School Finance Coalition), Lubbock, TX
Nichols, Colby Attorney (Texas Rural Education Association), Austin, TX
Rau, Seth Legislative Coordinator (San Antonio ISD), San Antonio, TX
Rome, Christy Executive Director (Texas School Coalition), Austin, TX
Scheberle, Drew Senior VP, Public Policy (The Greater Austin Chamber of Commerce),
Austin, TX
Sconzo, Guy Executive Director (Fast Growth School Coalition), Kingwood, TX
Sheffield, Heather (Self; Eanes Advocates), Austin, TX
Smith, Michelle Consultant (Texas Association of School Business Officials), Austin, TX
Terry, Mark Deputy Executive Director (TEPSA), Austin, TX
Villanueva, Chandra Policy Analyst (CPPP), Austin, TX
FOR:
Boese, Jessica Communications (Organization-Meridian School), Georgetown, TX
Dunn, David Executive Director (Texas Charter School Association), Austin, TX
Painaik, Umesh Parent (NYOS Charter School), Austin, TX
Ratliff, Thomas Former SBOE member (Self), Austin, TX
Rickey, Richard Chief Executive Officer (Orenda Education), Georgetown, TX
Sage, Thomas Partner (Texas Charter Schools Association), Houston, TX
Taylor, James CFO (ResponsiveEd), Lewisville, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
AGAINST:
Quinzi, Patty Legislative Counsel (TX-American Federation of Teachers), Austin, TX
ON:
Timmins, Holland Chief Investment Officer (Texas Education Agency), Austin, TX
Registering, but not testifying:
FOR:
Boone, Marcus Citizen, parent (NYOS), Austin, TX
Boswell, Courtney Executive Director (Texas Aspires), Austin, TX
Domaschk, Emily Mama & Texan (NYOS & my boys), Elgin, TX
Flores, Robert (Texas Citizens Action Network), Austin, TX
Gomez, Addie Exec. Director (Texans for Quality Public Charter Schools), Austin, TX
Goodsheller, Miranda Governmental Affairs Manager (Texas Association of Business),
Austin, TX
Gore, Rex Citizen/Charter board member (Self), Austin, TX
List, Amanda (Texas League of Community Charter Schools), Austin, TX
AGAINST:
Banks, Yannis (Texas NAACP), Austin, TX
De Leon, Marty (Texas Urban Council), Austin, TX
Hinojosa, David (Texas Latino Education Coalition), San Antonio, TX
ON:
Quinzi, Patty Legislative Counsel (TX-American Federation of Teachers), Austin, TX
Registering, but not testifying:
FOR:
Arnold, Ellen Arnold Public Affairs (Texas PTA), Austin, TX
AGAINST:
Terry, Mark Deputy Executive Director (TEPSA), Austin, TX
FOR:
Colbert, Paul (Self), Houston, TX
Villanueva, Chandra Policy Analyst (CPPP), Austin, TX
Registering, but not testifying:
FOR:
Arnold, Ellen Arnold Public Affairs (Texas PTA), Austin, TX
Caldwell, Deborah Director, Gov't Relations (North East Independent School District), San
Antonio, TX
Camacho, Priscilla D. VP of Education/Workforce Development (San Antonio Chamber of
Commerce), San Antonio, TX
Chavez, Jesus H. Co-Ex. Director (South Texas Association of Schools), Round Rock, TX
Freeman, Ray Executive Director (Equity Center), Austin, TX
Hinojosa, David (Texas Latino Education Coalition), San Antonio, TX
Moreno, Celina Attorney (MALDEF), San Antonio, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
Quinzi, Patty Legislative Counsel (TX-American Federation of Teachers), Austin, TX
FOR:
Villanueva, Chandra Policy Analyst (CPPP), Austin, TX
Registering, but not testifying:
FOR:
Arnold, Ellen (Goodwill Central TX), Austin, TX
Arnold, Ellen Arnold Public Affairs (Texas PTA), Austin, TX
Beneski, Amy Deputy Executive Director (Texas Association of School Administrators),
Austin, TX
Caldwell, Deborah Director, Gov't. Relations (North East Independent School District),
San Antonio, TX
Camacho, Priscilla D. VP of Education/Workforce Development (San Antonio Chamber of
Commerce), San Antonio, TX
Campbell, Grover Assoc. Ex. Dir. Gov. Rel. (TASB), Austin, TX
Carney, Dee Moak, Casey, & Associates (Texas School Alliance), Austin, TX
Chavez, Jesus H. Co-Ex. Director (South Texas Association of Schools), Round Rock, TX
Colbert, Paul (Self), Houston, TX
Dunn, David Executive Director (Texas Charter Schools Association), Austin, TX
Exter, Monty Lobbyist (Association of Texas Professional Educators), Austin, TX
Freeman, Ray Executive Director (Equity Center), Austin, TX
Grusendorf, Bill Exec. Director (TX Assoc. Rural Schools), San Saba, TX
Haenisch, Barry Executive Director (Texas Association of Community Schools), Austin,
TX
Martinez Schaefer, Virginia SVP Public Policy (Dallas Regional Chamber), Dallas, TX
Moreno, Celina Attorney (MALDEF), San Antonio, TX
Nichols, Colby Attorney (Texas Rural Education Association), Austin, TX
Parenteau, Julia Associate Director of Legislative Affairs (Texas Assn of Realtors), Austin,
TX
Quinzi, Patty Legislative Counsel (TX-American Federation of Teachers), Austin, TX
Rome, Christy Executive Director (Texas School Coalition), Austin, TX
Romero, Jesse (Texas Association for Bilingual Education), San Antonio, TX
Scheberle, Drew Senior VP, Public Policy (The Greater Austin Chamber of Commerce),
Austin, TX
Smith, Michelle Consultant (Texas Association of School Business Officials), Austin, TX
Terry, Mark Deputy Executive Director (TEPSA), Austin, TX
FOR:
Colbert, Paul (Self), Houston, TX
Grusendorf, Bill Exec. Director (TX Assoc. Rural Schools), San Saba, TX
Hogg, Bowie Board member (TASB/Arlington ISD), Arlington, TX
Moreno, Celina Attorney (MALDEF), San Antonio, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
Oser, George Former Chairman HISD (also providing written testimony) (Self), Houston,
TX
Villanueva, Chandra CPPP (CPPP), Austin, TX
Registering, but not testifying:
FOR:
Arnold, Ellen Arnold Public Affairs (Texas PTA), Austin, TX
Arnold, Ellen (Goodwill Central TX), Austin, TX
Beneski, Amy Deputy Executive Director (Texas Association of School Administrators),
Austin, TX
Carney, Dee Moak, Casey, & Associates (Texas School Alliance), Austin, TX
Dunn, David Executive Director (Texas Charter Schools Association), Austin, TX
Espey, Jennifer Mom-parent volunteer (Parents for Full & Fair Funding of TX Public
Schools), Houston, TX
Flores, Robert (Texas Citizens Action Network), Austin, TX
Freeman, Ray Executive Director (Equity Center), Austin, TX
Haenisch, Barry Executive Director (Texas Association of Community Schools), Austin,
TX
Hubbard, John Lobbyist (Pharr San Juan Alamo ISD), Austin, TX
Kuhlmann, Kate Lobbyist (Association of Texas Professional Educators), Austin, TX
Nichols, Colby Attorney (Texas Rural Education Assoc.), Austin, TX
Rome, Christy Executive Director (Texas School Coalition), Austin, TX
Romero, Jesse (Texas Association for Bilingual Education), San Antonio, TX
ON:
Scheberle, Drew Senior VP, Public Policy (The Greater Austin Chamber of Commerce),
Austin, TX
Providing written testimony:
FOR:
Anderson, David D. Consultant to Arlington ISD (Arlington ISD Board of Trustees),
Austin, TX
FOR:
Bailey, Daniel School Board President (Slocum Independent School District), Grapeland,
TX
Banks, Yannis (Texas NAACP), Round Rock, TX
Bassett, Steve CFO (Fort Bend ISD), Missouri City, TX
Baum, Jeff CFO (Lubbock ISD), Lubbock, TX
Becker, Julee Superintendent (Slaton ISD), Ransom, TX
Chavez, Jesus H. Co-Ex. Director (also providing written testimony) (South Texas
Association of Schools), Round Rock, TX
Colbert, Paul (Self), Houston, TX
Dunn, David Executive Director (Texas Charter Schools Association), Austin, TX
Freeman, Ray Executive Director, Equity Center (also providing written testimony)
(Equity Center), Austin, TX
Grusendorf, Bill Exec. Director (TX Assoc. Rural Schools), San Saba, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
Jaklich, Robert Superintendent of schools (Equity Center-1000 plus school districts),
Victoria, TX
Martin, Art CFO Slaton ISD (Slaton ISD), Slaton, TX
McNeil, Dr. Jesse J. President McNeil Foundation and member Texas Latino Education
Coalition (also providing written testimony) (Texas Latino Education Coalition), Cypress,
TX
Moreno, Celina Attorney (MALDEF), San Antonio, TX
Post, Steve Superintendent (Tulia ISD), Tulia, TX
Robertson, Staci Assistant Superintendent (Stamford ISD), Stamford, TX
Romero, Jesse (Texas Association for Bilingual Education (TABE)), San Antonio, TX
Smith, Kendall Superintendent (Spurger ISD), Spurger, TX
Swanson, Steve (Self; 20 year volunteer in Texas education), Austin, TX
Villanueva, Chandra Policy Analyst (CPPP), Austin, TX
Villarreal, Raymundo P. Superintendent (La Feria ISD), Harlingen, TX
Winn, Jeanette Superintendent (Karnes City ISD), Karnes City, TX
AGAINST:
Fair, Jessica Parent, gifted advocate, gifted teacher (also providing written testimony) (My
children, gifted students of Texas), McKinney, TX
James, Sabrina (Gifted students), Round Rock, TX
McAllister, Christopher (Self), Katy, TX
Mefford, Kate (Self), McKinney, TX
ON:
Doss, Sheri President Elect (Texas PTA), San Antonio, TX
Haenisch, Barry Executive Director (also providing written testimony) (Texas Association
of Community Schools), Austin, TX
Hinojosa, David National Director of Policy (FDRA), San Antonio, TX
Quinzi, Patty Legislative Counsel (TX-American Federation of Teachers), Austin, TX
Rome, Christy Executive Director (Texas School Coalition), Austin, TX
Registering, but not testifying:
FOR:
Cavazos, C. LeRoy Vice President of Government Relations (San Antonio Hispanic
Chamber of Commerce), San Antonio, TX
Espey, Jennifer Parent/advisory committee (Parent for Full & Fair Funding of TX Public
Schools), Houston, TX
Exter, Monty Lobbyist (Association of Texas Professional Educators), Austin, TX
Hubbard, John Lobbyist (Pharr San Juan Alamo ISD), Austin, TX
McCormack, Don O. Concerned parent (Parents for Full Fair Funding), Houston, TX
Puente, Jaime Doctoral student (Texas Graduate Student Diversity), Houston, TX
AGAINST:
McNulty, Jeaneane Elem. campus rep. to school district's, talented and gifted parent (Self;
Advisory Counsel), Austin, TX
Sheffield, Heather (Self; Eanes Advocates), Austin, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
ON:
Scheberle, Drew Senior VP, Public Policy (The Greater Austin Chamber of Commerce),
Austin, TX
Sconzo, Guy Executive Director (Fast Growth School Coalition), Kingwood, TX
Providing written testimony:
AGAINST:
Hammons, Colette Parent (Self; Gifted students, AP & IB students), Round Rock, TX
ON:
Carney, Dee Moak, Casey, & Associates (Texas School Alliance), Austin, TX
FOR:
Aleman, Steven Policy Specialist (Disability Rights Texas), Austin, TX
Guido, Nancy Director of Special Education (also providing written testimony) (North
East Independent School District), San Antonio, TX
Haag, John Disabled Individual (Self), San Antonio, TX
Haag, Terri Parent and guardian of autistic son (Self), San Antonio, TX
Litzinger, Amy Policy specialsit, self advocate (also providing written testimony) (Self;
Easter Seals), Austin, TX
Peltier, Cynthia Director of Sp. Ed (TCASE), Webster, TX
Reed, Julie Director of Special Education (Pasadena ISD), Deer Park, TX
Tresl, Laurie Special Education Coordinator (Waco ISD), West, TX
ON:
Mitchell, Vickie J. (also providing written testimony) (Self), Montgomery, TX
Registering, but not testifying:
FOR:
Beneski, Amy Deputy Executive Director (Texas Association of School Administrators),
Austin, TX
Campbell, Grover Assoc Ex Dir Gov Relations (TASB), Austin, TX
Dunn, David Executive Director (Texas Charter School Association), Austin, TX
Haenisch, Barry Executive Director (Texas Association of Community Schools), Austin,
TX
Kuhlmann, Kate Lobbyist (Association of Texas Professional Educators), Austin, TX
Nichols, Colby Attorney (Texas Rural Education Association), Austin, TX
Shanley, David Superintedent (Johnson City ISD), Dripping Springs, TX
Smith, Michelle Consultant (Texas Association of School Business Officials), Austin, TX
Terry, Mark Deputy Executive Director (TEPSA), Austin, TX
Providing written testimony:
FOR:
Lilly, Janna Director Governmental Relations (TCASE), Austin, TX
Litzinger, Linda Policy specialist, parent care-giver (Self), Austin, TX
WITNESS LIST
Education
April 18, 2017 9:00 AM
Registering, but not testifying:
FOR:
Chavez, Jesus H. Co-Ex. Dir. (South TX Associates), Round Rock, TX
Goodsheller, Miranda Governmental Affairs Manager (Texas Association of Business),
Austin, TX
Grey, John Government Relations Specialist (Texas State Teachers Associations), Austin,
TX
Smith, Michelle Consultant (Texas Association of School Business Officials), Austin, TX
Thurston, James Director of Policy & Community Engagement (United Ways of Texas),
Austin, TX