OpenLLM-France/wikimedia huggingface dataset:
# CDIO/Rube Goldberg
## Problem Statement

Begin the process of creating a Rube Goldberg machine with a specific theme and size.

## Setting System Goals and Requirements
### Market/Customer needs

The customer, or, in this case, teacher, needs a functioning Rube Goldberg machine with a definite end result, and a clear theme.

### Factors that set the context of the requirements
##### Enterprise goals and capabilities

The goal of this Rube Goldberg machine, again, is not only to be functional, but to have a specific theme with various "tools." So the theme becomes a factor of the requirements. Since various tools must be used, a theme should be picked that will allow for a number of different tools to be used. For instance, if the theme was sports balls, there wouldn't be very many tools used. Just a different number of balls. The goal of this Rube Goldberg machine is to use multiple types of tools.

## Defining Function, Concept and Architecture
### System concepts

The basic concept of this Rube Goldberg machine is superheroes. Each step in the machine will have some correlation to different superheroes from the comic book and movie universe.

### Necessary system functions

The function of any Rube Goldberg machine is to take a very simple task and make it as complex as possible. Being complex means containing a lot of steps. The necessary function of this Rube Goldberg machine is to be able to make each step initiate at the end of the previous step. In other words, each step needs to cause the next step.

## Modeling of System and Ensuring Goals Can Be Met
### The plan of implementation and operations

Implementation will commence once the design process of the superhero Rube Goldberg machine is complete. After the entire machine is built, the operation of the machine will be tested.

## Development Project Management
### Project cost and schedule

The first week of the project consisted of just conceiving the different aspects of the Rube Goldberg machine. The second week will consist of the design process. The design process may continue into the third week. Once the design process is done, implementation will begin. If started, the implementation process will continue until the end of the project. Each process must be thorough to ensure success of the machine.
# Motivation and emotion/Assessment/Multimedia/Feedback/2023

This page summarises general feedback about the 2023 multimedia presentations. Detailed feedback about each individual presentation is available on its chapter talk page.

## Overall

* The overall quality of presentations was reasonably good, but there was a wide range.
* A surprising number of presentations went over time. Content beyond the maximum time limit was ignored for marking purposes. This often meant 0 or reduced marks for the Conclusion.

## Overview

* Overviews were often missing or too brief
* Start off by engaging audience interest (e.g., via an example)
* Display and narrate the title and sub-title (which should exactly match the title and sub-title for the book chapter)
* Provide some context about why the topic is important
* Consider presenting focus questions or at least an outline of what will be covered

## Content

* Content was generally well selected
* Content typically did a reasonably good job of synthesising relevant theory
* However, presentations typically did a poor ob of synthesising relevant research
* Greater use of examples would be useful

## Conclusion

* Conclusions generally did a good job of reinforcing one or more take-home messages

## Audio

* Audio narration was generally quite good
* Most presentations were well-paced
* Some presentations could be improved by being more selective about what to cover and slowing down
* Most presentations were well scripted and practiced

## Video

* Visual presentation was generally very good
* Most presentations did a pretty job of showing a small amount of key text per slide in large font, making it easy to read and listen at the same time
* Some presentations could have been improved by splitting content from a small number of visually busy slides into a larger number of slides each containing less visual information

## Meta-data

* A moderate number of presentations used the full title and sub-title (or an abbreviated version that fits within 100 characters) as the name of the presentation
* Detailed, informative descriptions of the presentation were rare
* Most presentations provided a link to the book chapter and a link from the book chapter to the presentation
* Some excellent presentations included time code links to specific sections

## Licensing

* Some presentations used copyright restricted images without permission
* Most presentations indicated a copyright license for the presentation
# Motivation and emotion/Assessment/Multimedia/Feedback

* General feedback about the 2024 multimedia presentations
* Detailed feedback about each individual presentation is available on its chapter talk page

## Overall

* The overall quality of presentations was reasonably good, but there was a wide range.
* A surprising number of presentations went over time. Content beyond the maximum time limit was ignored for marking purposes. This often meant 0 or reduced marks for the Conclusion.

## Overview

* Overviews were often missing or too brief
* Start off by engaging audience interest (e.g., via an example)
* Display and narrate the title and sub-title (which should exactly match the title and sub-title for the book chapter)
* Provide some context about why the topic is important
* Consider presenting focus questions or at least an outline of what will be covered

## Content

* Content was generally well selected
* Content typically did a reasonably good job of synthesising relevant theory
* However, presentations typically did a poor ob of synthesising relevant research
* Greater use of examples would be useful

## Conclusion

* Conclusions generally did a good job of reinforcing one or more take-home messages

## Audio

* Audio narration was generally quite good
* Most presentations were well-paced
* Some presentations could be improved by being more selective about what to cover and slowing down
* Most presentations were well scripted and practiced

## Video

* Visual presentation was generally very good
* Most presentations did a pretty job of showing a small amount of key text per slide in large font, making it easy to read and listen at the same time
* Some presentations could have been improved by splitting content from a small number of visually busy slides into a larger number of slides each containing less visual information

## Meta-data

* A moderate number of presentations used the full title and sub-title (or an abbreviated version that fits within 100 characters) as the name of the presentation
* Detailed, informative descriptions of the presentation were rare
* Most presentations provided a link to the book chapter and a link from the book chapter to the presentation
* Some excellent presentations included time code links to specific sections

## Licensing

* Some presentations used copyright restricted images without permission
* Most presentations indicated a copyright license for the presentation
# Evolving Money/Money – The Fundamentals

To broaden our thinking about how money systems can be reimagined, we can begin by clearly defining the problemmoney aims to solve.
   How can we facilitate the exchange of goods and services?
Here are some alternative solution approaches (presented in a format adapted from an attribute matrix) where a characteristic is followed by various alterative values:
Assuming exchanges take place, then options to consider include:
* Expectations of reciprocity: (none, optional, personal, barter, communal, private, public, immediate, deferred, material, symbolic, or reputational, …)
* Exchange of (similar) value: (now, promised future repayment, intrinsic value, symbolic value, good will, barter, …)
* Record keeping:
** There is no record of the transaction, or
** There is a record of the transaction
*** Private, our (the parties) memories only
*** Private, my written record only
*** Shared, we both get a copy of the written record
*** Exchange takes place in public, creating many witnesses to the exchange.
*** Third party retains a written record (privately)
*** Public record of the transaction
* Creating the money supply
** Tokens are earned, found, extracted, or manufactured
** Fiat money – Authority generates tokens
*** Various distribution protocols are possible to distribute these new tokens, such as to the banks, to the people, or to some agency.
* Cheating: theft, counterfeit, modifying records, delinquent repayments, externalities, (tragedy of) the commons,
* Ownership (and stewardship) of public goods such as land, minerals, ecosystem services, radio spectrum or internet channels, silence, clean air, wilderness, water, waterways, fish, game, wildlife, trees, attention, influence …
* Concern for future generations (none, only our sense of duty, environmental action, young people, proportional representation, … ) This leads to the following additional research question:
** How can future generations be fairly represented in today’s decision-making forums?
* Transfer (of wealth) (none, anything goes, regulated, …)
* Storage (of wealth) (none, increases in value, fee for storage, constant value, …)
* Paying for shared goods and services
** Voluntary contributions, charity, philanthropy
** Usage fees
** Tax
# Debt and money markets

Objectives
The main purpose of this topic is to help you:
* Understand what Equity and Debt markets are.
* Understand difference between Debt and Equity market.
* Know participants' and products in Debt market.
* analyze segments of Debt Market in India.

## EQUITY MARKET

Publicly traded equities form a significant source of capital for firms, and equity markets are a key part of the process of allocating capital among competing uses in our country.
# Effects of Late or Non-payments/Bad Debt Value

| Unit 3.3-Effects of Late or Non-payments | Introduction | Tenets of Risk Assessment | Risk and Reward | "Eight C's" | 5 "C's" | 3 "C's" | Applying the "C's" | Impact of Nonpayment | Identifying Costs | Bad Debt Value | Interest | Cost and Capital | Administrative | Summary | Resources | Activities | Assessment Go to Unit 3.1 | Unit 3.2 | Unit 3.3 | Unit 3.4 | Unit 3.5 Return to Trade Finance Module 3: Commercial Risk |

## Bad Debt Value

Bad debts are obligations that are not collectible for a variety of reasons such as lack of cash flow from a buyer to remit, misunderstanding of terms and conditions and a resulting inability of a buyer and seller to agree on those differences. Bad debts, under the tax laws of the US, can only be written off as an expense by sellers if they can demonstrate, usually through hiring of a collection agency or lawyer, that every effort has been made to make the collection.
In a survey of over 5,000 businesses in manufacturing, distribution and retail, the National Association of Credit Management found that each dollar of accounts past due is worth the following:
| Three Months | Six Months | One Year | Two Years |
| $.90 | $.50 | $.25 | $.00 |
# Quizbank/Debt crisis

The graph to the right understates the student loan problem because home mortgages are uniquely safe investments, primarily because the debt can often be erased by selling the property. You cannot sell your education. And while the value of real estate tends to grow, the relative value of your education falls as your carreer developes to the point where employers are more interested in your current skill set than in your education. A graph that more dramatically illustrates the crisis can be found at bloomberg.com:The student loan debt crisis is about to get worse
# Linearly independent/(3,3,3), (0,4,5), (4,8,9)/Example

The three vectors
    ${\begin{pmatrix}3\\3\\3\end{pmatrix}},\,\,{\begin{pmatrix}0\\4\\5\end{pmatrix}},\,{\text{ and }}\,{\begin{pmatrix}4\\8\\9\end{pmatrix}}$
are linearly dependent. The equation
    $4{\begin{pmatrix}3\\3\\3\end{pmatrix}}+3{\begin{pmatrix}0\\4\\5\end{pmatrix}}-3{\begin{pmatrix}4\\8\\9\end{pmatrix}}={\begin{pmatrix}0\\0\\0\end{pmatrix}}\,$
is a nontrivial representation of the null vector.
# Linearly independent/System of linear equations/Remark

The vectors $v_{1}={\begin{pmatrix}a_{11}\\\vdots \\a_{m1}\end{pmatrix}},\ldots ,v_{n}={\begin{pmatrix}a_{1n}\\\vdots \\a_{mn}\end{pmatrix}}\in K^{m}$ are linearly dependent if and only if the homogeneous linear system
    ${\begin{matrix}a_{11}x_{1}+a_{12}x_{2}+\cdots +a_{1n}x_{n}&=&0\\a_{21}x_{1}+a_{22}x_{2}+\cdots +a_{2n}x_{n}&=&0\\\vdots &\vdots &\vdots \\a_{m1}x_{1}+a_{m2}x_{2}+\cdots +a_{mn}x_{n}&=&0\end{matrix}}$
has a nontrivial solution.
# Vector space/Basis/Polynomials/Introduction/Section
## Definition

Let $K$ be a field, and let $V$ be a $K$-vector space. Then a linearly independent generating system $v_{i}\in V$, $i\in I$,
$V$
$V$

## Example

The standard vectors in $K^{n}$ form a basis. The linear independence was shown in example. To show that they also form a generating system, let
    $v={\begin{pmatrix}b_{1}\\b_{2}\\\vdots \\b_{n}\end{pmatrix}}\in K^{n}\,$
be an arbitrary vector. Then we have immediately
    $v=\sum _{i=1}^{n}b_{i}e_{i}\,.$
Hence, we have a basis, which is called the standard basis of $K^{n}$.

## Example

We consider the $K$-linear subspace $U\subset K^{n}$ given by
    $U={\left\{v\in K^{n}\mid \sum _{i=1}^{n}v_{i}=0\right\}}\,.$
A basis for $U$ is given by the $n-1$ vectors
    $u_{1}=(1,-1,0,0,\ldots ,0),\,u_{2}=(0,1,-1,0,\ldots ,0),\,,\ldots ,u_{n-1}=(0,0,\ldots ,0,1,-1),\,.$
These vectors belong evidently to $U$. The linear independence can be checked in $K^{n}$. From an equation
    $\sum _{i=1}^{n-1}a_{i}u_{i}=0\,$
we can deduce step by step $a_{1}=0$, $a_{2}=0$, etc. That the system is a generating system follows from
    ${\begin{pmatrix}v_{1}\\v_{2}\\v_{3}\\\vdots \\v_{n-1}\\v_{n}\end{pmatrix}}=v_{1}{\begin{pmatrix}1\\-1\\0\\\vdots \\0\\0\end{pmatrix}}+(v_{1}+v_{2}){\begin{pmatrix}0\\1\\-1\\\vdots \\0\\0\end{pmatrix}}+(v_{1}+v_{2}+v_{3}){\begin{pmatrix}0\\0\\1\\-1\\\vdots \\0\end{pmatrix}}+\cdots +(v_{1}+v_{2}+v_{3}+\cdots +v_{n-1}){\begin{pmatrix}0\\0\\0\\\vdots \\1\\-1\end{pmatrix}}\,,$
where the equality in the last row rests on the condition
    $\sum _{i=1}^{n}v_{i}=0\,.$
For the complex numbers, the elements $1,{\mathrm {i} }$ form a real basis. In the space of all $m\times n$-matrices, that is, $\operatorname {Mat} _{m\times n}(K)$, those matrices where exactly one entry is $1$, and all other entries are $0$, form a basis, see exercise.

## Example

In the polynomial ring $K[X]$ over a field $K$, the powers $X^{n}$, $n\in \mathbb {N}$, form a basis. By definition, every polynomial
    $a_{n}X^{n}+a_{n-1}X^{n-1}+\cdots +a_{2}X^{2}+a_{1}X+a_{0}$
is a linear combination of the powers $X^{0}=1,X^{1}=X,\ldots ,X^{n}$. Moreover, these powers are linearly independent. For if
    $a_{n}X^{n}+a_{n-1}X^{n-1}+\cdots +a_{2}X^{2}+a_{1}X+a_{0}=0\,,$
then all coefficients equal $0$ (this is part of the concept of a polynomial).
# Vector space/Characterizations of basis/Maximal/Minimal/Fact

Let $K$ be a field, and let $V$ be a $K$-vector space. Let $v_{1},\ldots ,v_{n}\in V$ be a family of vectors. Then the following statements are equivalent.
* The family is a basis of $V$.
* The family is a minimal generating system; that is, as soon as we remove one vector $v_{i}$, the remaining family is not a generating system any more.
* For every vector $u\in V$, there is exactly one representation
    $u=s_{1}v_{1}+\cdots +s_{n}v_{n}\,.$
* The family is maximally linearly independent; that is, as soon as some vector is added, the family is not linearly independent any more.
# Vector space/Linearly independent/Finite index set/Definition

Let $K$ be a field, and let $V$ be a $K$-vector space. A family of vectors $v_{i}$, $i\in I$, (where $I$ denotes a finite index set) is called linearly independent if an equation of the form
    $\sum _{i\in I}s_{i}v_{i}=0{\text{ with }}s_{i}\in K$
is only possible when $s_{i}=0$ for all $i$.
# Vectors/Linearly independent/Explanations/Remark

If a family is not linearly independent, then it is called linearly dependent. A linear combination $\sum _{i\in I}s_{i}v_{i}=0$ is called a representation of the null vector. It is called the trivial representation if all coefficients $s_{i}$ equal $0$ and, if at least one coefficient is not $0$, a nontrivial representation of the null vector. A family of vectors is linearly independent if and only if one can represent with the family the null vector only in the trivial way. This is equivalent with the property that no vector of the family can be expressed as a linear combination by the others.
# Vector space/Linearly independent/Definition

Let $K$ be a field, and let $V$ be a $K$-vector space. Then a family of vectors $v_{i}$, $i\in I$, in $V$ is called linearly independent if an equation
    $\sum _{i\in J}s_{i}v_{i}=0{\text{ with }}s_{i}\in K{\text{ for a finite subset }}J\subseteq I$
is only possible if $s_{i}=0$ for all $i$.
# Vector space/Characterizations of basis/Maximal/Minimal/Fact/Proof

Proof by ring closure. $(1)\Rightarrow (2)$. The family is a generating system. Let us remove a vector, say $v_{1}$, from the family. We have to show that the remaining family, that is $v_{2},\ldots ,v_{n}$, is not a generating system anymore. So suppose that it is still a generating system. Then, in particular, $v_{1}$ can be written as a linear combination of the remaining vectors, and we have
    $v_{1}=\sum _{i=2}^{n}s_{i}v_{i}\,.$
But then
    $v_{1}-\sum _{i=2}^{n}s_{i}v_{i}=0\,$
is a nontrivial representation of $0$, contradicting the linear independence of the family. $(2)\Rightarrow (3)$. Due to the condition, the family is a generating system, hence every vector can be represented as a linear combination. Suppose that for some $u\in V$, there is more than one representation, say
    $u=\sum _{i=1}^{n}s_{i}v_{i}=\sum _{i=1}^{n}t_{i}v_{i}\,,$
where at least one coefficient is different. Without loss of generality, we may assume $s_{1}\neq t_{1}$. Then we get the relation
    ${\left(s_{1}-t_{1}\right)}v_{1}=\sum _{i=2}^{n}{\left(t_{i}-s_{i}\right)}v_{i}\,$
Because of $s_{1}-t_{1}\neq 0$, we can divide by this number and obtain a representation of $v_{1}$ using the other vectors. In this situation, due to exercise, also the family without $v_{1}$ is a generating system of $V$, contradicting the minimality. $(3)\Rightarrow (4)$. Because of the unique representability, the zero vector has only the trivial representation. This means that the vectors are linearly independent. If we add a vector $u$, then it has a representation
    $u=\sum _{i=1}^{n}s_{i}v_{i}\,,$
and, therefore,
    $0=u-\sum _{i=1}^{n}s_{i}v_{i}\,$
is a non-trivial representation of $0$, so that the extended family $u,v_{1},\ldots ,v_{n}$ is not linearly independent. $(4)\Rightarrow (1)$. The family is linearly independent, we have to show that it is also a generating system. Let $u\in V$. Due to the condition, the family $u,v_{1},\ldots ,v_{n}$ is not linearly independent. This means that there exists a non-trivial representation
    $0=su+\sum _{i=1}^{n}s_{i}v_{i}\,.$
Here $s\neq 0$, because otherwise this would be a non-trivial representation of $0$ with the original family $v_{1},\ldots ,v_{n}$. Hence, we can write
    $u=-\sum _{i=1}^{n}{\frac {s_{i}}{s}}v_{i}\,,$
yielding a representation for $u$.
# Basis/Unique representation/Coordinates/Bijection/Remark

Let a basis ${\mathfrak {v}}=v_{1},\ldots ,v_{n}$ of a $K$-vector space $V$ be given. Due to fact (3), this means that for every vector $u\in V$, there exists a unique representation (a linear combination)
    $u=s_{1}v_{1}+s_{2}v_{2}+\cdots +s_{n}v_{n}\,.$
Here, the uniquely determined elements $s_{i}\in K$ (scalars) are called the coordinates of $u$ with respect to the given basis. This means that for a given basis, there is a correspondence between vectors and coordinate tuples $(s_{1},s_{2},\ldots ,s_{n})\in K^{n}$. We say that a basis determines a linear coordinate system of $V$. To paraphrase, a basis gives, in particular, a bijective mapping
    $\Psi _{\mathfrak {v}}\colon K^{n}\longrightarrow V,{\begin{pmatrix}s_{1}\\\vdots \\s_{n}\end{pmatrix}}\longmapsto s_{1}v_{1}+s_{2}v_{2}+\cdots +s_{n}v_{n}.$
The inverse mapping
    ${\left(\Psi _{\mathfrak {v}}\right)}^{-1}\colon V\longrightarrow K^{n}$
is also called the coordinate mapping.
# Vector space/Finitely generated/Basis/Fact/Proof

Let $v_{i}$, $i\in I$, be a finite generating system of $V$ with a finite index set $I$. We argue with the characterization from fact (2). If the family is minimal, then we have a basis. If not, then there exists some $k\in I$ such that the remaining family, where $v_{k}$ is removed, that is, $v_{i}$, $i\in I\setminus \{k\}$, is also a generating system. In this case, we can go on with this smaller index set. With this method, we arrive at a subset $J\subseteq I$ such that $v_{i}$, $i\in J$, is a minimal generating set, hence a basis.
# Coordinates/Linear and curvy/Remark

Linear coordinates give a bijective relation between points and number tuples. Due to linearity, such a bijection respects addition and scalar multiplication. In many different contexts, also nonlinear (curvilinear) coordinates are important. These put points of a space and number tuples into a bijective relation. Examples are polar coordinates, cylindrical coordinates, and spherical coordinates. By choosing suitable coordinates, mathematical problems, like the computation of volumes, can be simplified.
# Vector space/Arbitrary/Theorem of Hamel/Remark

In general, the Theorem of Hamel says that every vector space has a basis. The proof of this theorem uses strong set-theoretical methods, in particular the axiom of choice and the Lemma of Zorn. This is the reason why many statements about finite-dimensional vector spaces pass over to vector spaces of infinite dimension. In this course, we will concentrate on the finite-dimensional case.
# Vector space/Basis/Exchange lemma/Fact

Let $K$ denote a field, let $V$ denote a $K$-vector space, and let a basis $v_{1},\ldots ,v_{n}$ of $V$ be given. Let $w\in V$ be a vector with a representation
    $w=\sum _{i=1}^{n}s_{i}v_{i}\,,$
where $s_{k}\neq 0$ for some fixed $k$.
    $v_{1},\ldots ,v_{k-1},w,v_{k+1},\ldots ,v_{n}$
$V$
# Vector space/Basis/Exchange theorem/Fact

Let $K$ denote a field, let $V$ denote a $K$-vector space, and let a basis $b_{1},\ldots ,b_{n}$ of $V$ be given. Let
    $u_{1},\ldots ,u_{k}$
denote a family of linearly independent vectors in $V$.
    $J=\{i_{1},i_{2},\ldots ,i_{k}\}\subseteq \{1,\ldots ,n\}=I\,$
such that the family
    $u_{1},\ldots ,u_{k},b_{i},i\in I\setminus J,$
$V$
In particular, $k\leq n$.
# Vector space/Finitely generated/Dimension/Definition

Let $K$ be a field, and let $V$ be a $K$-vector space with a finite generating system. Then the number of vectors in any basis of $V$ is called the dimension of $V$, written
    $\dim _{K}{\left(V\right)}.$
# Standard space/K^n/Dimension n/Fact

Let $K$ be a field, and $n\in \mathbb {N}$.
standard space $K^{n}$ has the
$n$