OpenLLM-France/wikimedia huggingface dataset:
# Talagang

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# Tabla
## Introduction

Welcome to the Tabla pages. Somebody who knows more than I do about the Tabla can write this intro.

## The Tabla

The Tabla is actually a set of two drums, the Tabla and the Bayan (or Dugga). The Bayan is placed on the left under the left hand, and the Tabla goes under the right hand. The drums should touch each other, and this point between the drums should be on your body's centreline. Sit in half-lotus position. While this may be uncomfortable at first, the player will find that this position actually keeps the back straighter than plain crossed legs. It means you can play longer and with less back pain... though your foot may fall asleep.
Each drum sits on a cloth ring to keep it stable. The Bayan should be more or less flat, with its head parallel to the ground. The Tabla should be tilted slightly forward, so it is easier for your hand to rest while playing.

## Diagrams for ease in learning

I've put together a couple diagrams of the drum heads to better show where given notes are placed.
PLEASE: if you know Devnagari, correct these charts!
The two diagrams :
| The Dayan (Tabla) | The outside rim of the head is woven rawhide, called the Gajara. The black spot in the middle of the drum is called the Syahi. The syahi is a ball of hide glue, ink, and weight that is pressed onto the drum to improve its resonance. |
| The Bayan (Dugga) | On the outer edge of the head but inside the Gajira is another ring of rawhide called the Chat. This improves the tensile strength of the threading. The skin itself is called a Maidan. The narrow bit of Maidan showing between the Dugga's offset Syahi and the edge of the drum is the Luv. |
And here are some hand placement diagrams for the specific hand positions.
Bayan hand positions :
| Name | Devnagari Script | Singhalese Script | Description |
| Ge | ग | ग | Strike the Luv soundly with tips of both the middle and ring fingers. The heel of the hand should come off the drum to allow resonation, and the fingers should be clawed back towards the palm in a single fluid motion after coming off the strike. |
| Ge-Ge | ग | ग | When doing many Ge strikes in succession, they alternate between the basic above and the index finger strike, done the same as above only with the index finger alone. |
| Kat/Ki/Ke | क | ක | Slap the hand down onto the drum. This should not resonate. The palm should cover the Syahi. |
Dayan hand positions :
| Name | Devnagari Script | Singhalese Script | Description |
| Ti (The) | ती(ट) | ති(ට) | later! |
| Te (Ri) | ट(र) | ත(රි) | later! |
| Na (Ta) | ना/ता | නා(තා) | later! |
| Tin | तीं | තිං | later! |
| Tat | ता | තාත් | later! |
| Thun | तूं | later! | later! |
| D | ? | later! | later! |
| N | न | later! | later! |
| Dhe | धे | later! | later! |
| R | ? | later! | later! |
Combined hand positions :
| Name | Devnagari Script | Singhalese Script | Description |
| Dha | धा | ධ | later! |
| Dhin | धिं | ධිං | later! |
| Dhi | धि | ධි | later! |
| Dhit | ? | ධත් | later! |
# Taking powers/R/Minimum or not/Exercise

Determine directly, for which $n\in \mathbb {N}$ the power function
    $\mathbb {R} \longrightarrow \mathbb {R} ,x\longmapsto x^{n},$
# Nonlinear finite elements/Homework 11/Solutions

    Given:
    For small strains, the strain tensor is given by
    ${\boldsymbol {\varepsilon }}={\frac {1}{2}}\left[{\boldsymbol {\nabla }}\mathbf {u} +({\boldsymbol {\nabla }}\mathbf {u} )^{T}\right]\qquad {\text{or}}\qquad \varepsilon _{ij}={\frac {1}{2}}(u_{i,j}+u_{j,i})~.$
    In classical (small strain) rate-independent plasticity we start off with an additive decomposition :of the strain tensor
    ${\boldsymbol {\varepsilon }}={\boldsymbol {\varepsilon }}^{e}+{\boldsymbol {\varepsilon }}^{p}\qquad {\text{or}}\qquad \varepsilon _{ij}=\varepsilon _{ij}^{e}+\varepsilon _{ij}^{p}~.$
    Assuming linear elasticity, we have the following elastic stress-strain law
    ${\boldsymbol {\sigma }}={\boldsymbol {\mathsf {C}}}:{\boldsymbol {\varepsilon }}^{e}\qquad {\text{or}}\qquad \sigma _{ij}=C_{ijkl}\varepsilon _{kl}^{e}~.$
    Let us assume that the $J_{2}$ theory applies during plastic deformation of the material. :Hence, the material obeys an associated flow rule
    ${\text{(1)}}\qquad {\dot {\boldsymbol {\varepsilon }}}^{p}={\dot {\gamma }}{\frac {\partial f({\boldsymbol {\sigma }},\alpha ,T)}{\partial {\boldsymbol {\sigma }}}}$
    where ${\dot {\gamma }}$ is the plastic flow rate, $f$ is the yield function, $T$ is the temperature, and $\alpha$ is an internal variable.
** Problem 1: Part 1: Evolution rule for plastic flow
** Problem 1: Part 2: Energy equation
** Problem 1: Part 3: Rate form constitutive relation
** Problem 1: Part 4: Consistency condition
** Problem 1: Part 5: Consistency condition - 1
** Problem 1: Part 6: Continuum elastic-plastic tangent modulus
** Problem 1: Part 7: Flow rule
** Problem 1: Part 8: Consistency condition - 2
** Problem 1: Part 9: Elastic-plastic tangent modulus
** Problem 1: Part 10: Discrete evolution equations
** Problem 1: Part 11: Discrete Kuhn-Tucker
** Problem 1: Part 12: Trial elastic stress - 1
** Problem 1: Part 13: Trial elastic stress - 2
** Problem 1: Part 14: Return mapping
** Problem 1: Part 15: Plastic flow parameter
** Problem 1: Part 16: Newton iterations
* Problem 2: Billet Upset Forging
* Problem 3: Taylor Impact Tests
# Nonlinear finite elements/Homework 11/Solutions/Problem 1/Part 3
## Problem 1: Part 3: Rate form constitutive relation

Write down the rate form of the elastic stress-strain law. Assume that deformations are small so that objectivity of the rates is not a concern.
The rate form of the elastic constitutive equation is
    ${\dot {\boldsymbol {\sigma }}}={\boldsymbol {\mathsf {C}}}:{\dot {\boldsymbol {\varepsilon }}}^{e}={\boldsymbol {\mathsf {C}}}:({\dot {\boldsymbol {\varepsilon }}}-{\dot {\boldsymbol {\varepsilon }}}^{p})$
Plugging in the expression for ${\dot {\boldsymbol {\varepsilon }}}^{p}$ we get
    ${\dot {\boldsymbol {\sigma }}}={\boldsymbol {\mathsf {C}}}:\left({\dot {\boldsymbol {\varepsilon }}}-{\dot {\gamma }}{\frac {\partial f}{\partial {\boldsymbol {\sigma }}}}\right)$
# Nonlinear finite elements/Homework 11/Solutions/Problem 1/Part 12
## Problem 1: Part 12: Trial elastic stress

In the radial return algorithm, we define a trial elastic state as
    ${\text{(2)}}\qquad {\boldsymbol {\sigma }}_{n+1}^{\text{trial}}={\boldsymbol {\sigma }}_{n}+{\boldsymbol {\mathsf {C}}}:({\boldsymbol {\varepsilon }}_{n+1}-{\boldsymbol {\varepsilon }}_{n})$
where ${\boldsymbol {\sigma }}_{n},{\boldsymbol {\varepsilon }}_{n}$ are the stress and strain at $t=t_{n}$ and ${\boldsymbol {\sigma }}_{n+1},{\boldsymbol {\varepsilon }}_{n+1}$ are the values at $t=t_{n+1}$. Show that, if the elastic response of the material is linear, equation (2) can be written as
    ${\text{(3)}}\qquad {\boldsymbol {\sigma }}_{n+1}^{\text{trial}}=[\lambda ~{\text{tr}}({\boldsymbol {\varepsilon }}_{n+1})~{\boldsymbol {\mathit {1}}}+2~\mu ~{\boldsymbol {\varepsilon }}_{n+1}]-[\lambda ~{\text{tr}}({\boldsymbol {\varepsilon }}_{n}^{p})~{\boldsymbol {\mathit {1}}}+2~\mu ~{\boldsymbol {\varepsilon }}_{n}^{p}]~.$
From equation (2)
    ${\boldsymbol {\sigma }}_{n+1}^{\text{trial}}={\boldsymbol {\sigma }}_{n}+{\boldsymbol {\mathsf {C}}}:({\boldsymbol {\varepsilon }}_{n+1}-{\boldsymbol {\varepsilon }}_{n})={\boldsymbol {\mathsf {C}}}:{\boldsymbol {\varepsilon }}_{n}^{e}+{\boldsymbol {\mathsf {C}}}:({\boldsymbol {\varepsilon }}_{n+1}-{\boldsymbol {\varepsilon }}_{n}^{e}-{\boldsymbol {\varepsilon }}_{n}^{p})={\boldsymbol {\mathsf {C}}}:({\boldsymbol {\varepsilon }}_{n+1}-{\boldsymbol {\varepsilon }}_{n}^{p})$
Therefore,
    ${{\boldsymbol {\sigma }}_{n+1}^{\text{trial}}==(\lambda ~{\boldsymbol {\mathit {1}}}\otimes {\boldsymbol {\mathit {1}}}+2~\mu ~{\boldsymbol {\mathsf {I}}}):({\boldsymbol {\varepsilon }}_{n+1}-{\boldsymbol {\varepsilon }}_{n}^{p})=\lambda ~{\text{tr}}({\boldsymbol {\varepsilon }}_{n+1})+2~\mu ~{\boldsymbol {\varepsilon }}_{n+1}-\lambda ~{\text{tr}}({\boldsymbol {\varepsilon }}_{n}^{p})-2~\mu ~{\boldsymbol {\varepsilon }}_{n}^{p}~.}$
Hence shown.
# Nonlinear finite elements/Homework 11/Solutions/Problem 1/Part 11
## Problem 1: Part 11: Discrete Kuhn-Tucker

The Kuhn-Tucker loading-unloading conditions are
    ${\dot {\gamma }}\geq 0~,~~f({\boldsymbol {\sigma }},\alpha ,T)\leq 0~;~~{\dot {\gamma }}f({\boldsymbol {\sigma }},\alpha ,T)=0~.$
Write down a discrete form of the Kuhn-Tucker conditions.
The discrete form of the Kuhn-Tucker conditions is
    ${\begin{aligned}\Delta \gamma &\geq 0\\f({\boldsymbol {\sigma }}_{n+1},\alpha _{n+1},T_{n+1})&\leq 0\\\Delta \gamma ~f({\boldsymbol {\sigma }}_{n+1},\alpha _{n+1},T_{n+1})&=0\end{aligned}}$
# Nonlinear finite elements/Homework 11/Solutions/Problem 2
## Problem 2: Billet upset forging

Given:
* Compression of cylindrical billet with rigid dies.
* No-slip contact between billet and dies.
* $r_{0}$ = 10 mm; $l_{0}$ = 30 mm.
* $\mu$ = 384.6 MPa; $K$ = 833.3 MPa.
* Yield stress given by
    $\sigma _{y}=\sigma _{0}+H~\varepsilon _{p}~.$
* $\sigma _{0}$ = 1 MPa; $H$ = 3 MPa.
* Compressive force of 1 KN applied to die.

### Solution
#### Part 1

Plot of final shape of billet.
This problem is solved using ANSYS 8.0. Plane182 (2-D 4-node axisymmetric element) is used to model a quarter of the billet and the die. Contac48 (2-D contact element) is used for the node to surface contact. The final shape of the billet is shown in Fig 4.
* Figure 4. Deformed shape of the billet at the final load step.

#### Part 2

Compare final shape with that given in Simo and Hughes.
The die moves less in the ANSYS simulation than it does in the plot shown in Simo and Hughes (p. 325, Fig. 9.8 (b)). In Simo and Hughes, the die stroke is around 20.5 mm. In our simulation, the die stroke is around 19 mm.
The top of the billet shows an undulation that indicates that contact is not being done correctly. The billet material appears to be moving through the die during deformation. Simo and Hughes do not show such an effect.

#### Part 3

Plot die force (N) vs. die stroke (mm).
A plot of the die force vs. the displacement at the center of the billet is shown in Fig 5. The die stroke is (30 - $u$) mm where $u$ is the displacement shown in the plot.
* Figure 5. Billet force-displacement plot.

#### Part 4

Compare plot of force vs. stroke with Simo and Hughes.
See Fig 9.8 (c) in Simo and Hughes. Our simulation shows a smaller displacement for the same load when compared with Simo and Hughes.

#### Part 5

Comment on volumetric locking.
The smaller displacement observed in our simulation may be an indication of volumetric locking when fully integrated PLANE182 elements are used. Underintegrated elements or assumed strain elements may alternatively be used to confirm that possibility.
# The concept of irreducible complexity/video workshop
## Figure 4 - ribozyme activity

An animated ribozyme. The video needs to illustrate motion in the structure of the ribozyme during substrate binding/unbinding and during catalysis. The video will show movement of a substrate into and out of the active site of the ribozyme.
A decision has to be made about the level of structural detail in the molecules. Maybe there should be a preliminary video that illustrates both a detailed molecular structure of a ribozyme and a more diagrammatic structural model. During the "ribozyme activity" video it might be useful to have a "zoom in" part that shows more detail during the actual chemical reaction.
substrate: a choice needs to be made for the exact substrate to use for the initial ribozyme "R". The choice should make a useful point about a type of reaction that would be useful in the RNA world.

## Figure 5 - amino acid binding

So what peptide/amino acids should be used to illustrate allosteric regulation of ribozyme "R"? How much molecular detail is needed to show that binding of the amino acids can couple to conformational change at the active site? Can the animation just show faster catalysis? Is it useful to show both an original, slow, non-amino acid-binding ribozyme and a newly evolved, faster version of the ribozyme that does bind amino acids?
Are there other ways that amino acid binding to 'R" could be beneficial besides an allosteric enhancement of enzyme activity? Maybe just protection from destruction of the ribozyme? Any evidence that amino acid/peptide binding can stabilize ribozmes?
There might be some useful results and theory about positively-charged amino acids that bind non-covalently to the phosphate backbones of RNA molecules. ribonuclease P as a model system? Also, there may be a relevant type of covalent amino acid-RNA interaction. (ADP-ribosylation? uridylylation?)
Nuclear ADP-Ribosylation Reactions in Mammalian Cells: Where Are We Today and Where Are We Going?
Does the non-biological origin of amino acids need to be illustrated? Would cells have biosynthesized amino acids before having a translation system?
# The dynamics and social organization of innovation in the field of oncology/Bibliography
## Papers and resources
### General

Use of absrtacts
* Assessing the Eventual Publication of Clinical Trial Abstracts Submitted to a Large Annual Oncology Meeting
Document tagging and other text-mining
* OpenMinTeD, European text-mining infrastructure
* NCBI text mining web services
* EuropePMC text mined annotations
Funding data
* Funding Data from Publication Acknowledgements: Coverage, Uses and Limitations
Innovation dynamics
* A triple helix model of medical innovation: Supply, demand, and technological capabilities in terms of Medical Subject Headings
Topical burst detection
* Bursty and Hierarchical Structure in Streams, implementations in C, python
* Mapping topics and topic bursts in PNAS
Name disambiguation
* Author name disambiguation, a recent review
* Exploiting citation networks for large-scale author name disambiguation, a recent paper from ppl at ETH-Zurich
Ontologies
* Disease Ontology
Evolving communities
* Evolving network structure of academic institutions

### Word embedding

Algorithm and improvements
* king - man + woman is queen; but why?
* What are some interesting Word2Vec results?
* Linguistic Regularities in Sparse and Explicit Word Representations
* Document Classification by Inversion of Distributed Language Representations
* A Dual Embedding Space Model for Document Ranking
Changes in meaning
* Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
* Statistically Significant Detection of Linguistic Change

### Stochastic block models and description length minimization

* Inferring the mesoscale structure of layered, edge-valued and time-varying networks
* Hierarchical Block Structures and High-Resolution Model Selection in Large Networks
* Model Selection and Hypothesis Testing for Large-Scale Network Models with Overlapping Groups

### Visualizations

* Visualizing genomic testing in the cancer clinical trials portfolio

### Medical ontologies

* The NCI has a dictionary of cancer terms with 8,389 terms
* The NCI has a drug dictionary
* the NCI has a dictionary of genetics terms
* See also the NCI list of cancer types
There are also more sophisticated ontologies:
* For instance, there is an NCI Thesaurus
* BioPortal keeps a database of ontologies

## News

Social media buzz
* Social (Media) Oncology Project
Core set hypothesis
* A Countdown: Top 10 Problems With NCI-Designated Cancer Centers, item 2.
Transparency
Sanofi, Novartis, NCI, Ranbaxy top missing data list as Shire most transparent
ASCO and ESMO
ESMO's not what it used to be—and that's a good thing, executives say

## Research Seminars
#### Gabriel Varela

* BRCA Patients and Clinical Collectives: New Configurations of Action in Cancer Genetics Practices Pascale Bourret
# The dynamics and social organization of innovation in the field of oncology/Editorial boards

Jonah has been working on collecting the names and positions of researchers in the editorial boards of oncology journals throughout their existence.

## Journals

(document what journals interest us, perhaps even a list stating the progress and links)
We have to date completed a Pilot study of the top ten journals by IF, selected from our larger sample of 52 journals (we selected the top one hundred journals for the period 1990-2015, ordered by total cites, extracted those classed as 'oncology' by WoS, then selected the top ten oncology journals from the subsequent list by impact factor).
This pilot includes (in alphabetical order):
* British Journal of Cancer
* Cancer
* Cancer Research
* Clinical Cancer Research
* International Journal of Cancer
* International Journal of Radiation Oncology Biology and Physics
* Journal of Clinical Oncology
* Journal of the National Cancer Institute
* Nature Reviews Cancer
* Oncogene
A more detailed overview of the progress of accessing and collecting the editorial board info will be uploaded at a later date. In brief, however, the information was collected from several different source:
* the websites of the journals / journal publishers, which in some cases include front matter or editorial rosters in their online archives
* the Internet Archive 'WayBack Machine', which takes snapshots of webpages over time and can be used to access some of the old journal website urls displaying ed rosters
* PubMed Central
* Physical perodical holdings at McGill
* Physical holdings at other universities (in this case, UdeM has proven to have the most useful / extensive collection)
In spite of this diversity of sources, it has not been possible to achieve full coverage, and we are still missing editorial information for several journals across several years (most notably the Int J Rad Onco, due to limited physical holdings and a website that has proven 'uncrawlable' by the WayBackMachine).

## Record format

(document how are structuring the data, the different proposals we had and issues we ran into)
Currently the editorial board info is in Excel spreadsheet format, with one spreadsheet per journal, broken up by column into First Name, Middle Initial, Last Name, Editorial Position, Editorial Subcategory, Year.
The files are available in a Dropbox folder.
# The dynamics and social organization of innovation in the field of oncology/Guidelines

Guidelines reflect the established consensus of certain health care collectives.

### GIN

Guidelines International Network provides a searchable library of guidelines
# The dynamics and social organization of innovation in the field of oncology

This page documents the progress and serves as collaboration space for parts of the research project "Oncology's metaknowledge networks: an investigation of the collective dynamics of bio-clinical innovation", funded by the Canadian Institutes of Health Research.
The project is a joint effort of four groups split between Chicago, Marseille, Montreal and Paris, coordinated by Alberto Cambrosio (Montreal).
Project discussion takes place in meetings, calls, e-mail, wiki talk pages and a dedicated forum.

## About

We are working to deploy an approach that links digital archives and new computational tools to qualitative and historical investigation of oncology’s emergence and development. We will trace research teams and collaboration networks, investigative and clinical technologies, the myriad recombinant elements under investigation — tissues, cells, genes, proteins, biomarkers — and the changing landscape of institutions that hosts them. To provide us with insight, these traces will then be analysed through natural language processing, machine learning, network analysis and probabilistic modeling. Together, these tools and data will allow us unprecedented, integrative insight into how oncology “thinks”, how it followed its particular path of innovation, and the possible consequences of that path for biomedical research and human health.

## Data sources

* Oncology conference abstracts
* Oncology editorial boards
* Oncology articles in Pubmed
* Project funding databases
* Clinical trials databases
* Patient records
* Guidelines

## Instruments

The project will use and develop several research instruments.

## Data analysis

* Co-occurrence likelihoods
* Stochastic block models
# Spiders

Spiders are abundant terrestrial arthropods. Actually more than 40,000 species are known (World Spider Catalog, 2015). They produce venom for defense and prey capture and only a few species are dangerous for humans. They succeed in almost every terrestrial environment and are regulators of insect populations for their abundance (Haddad et al. 2004, Chatterjee et al. 2009). Spiders are very important in ecological studies as environment quality indicators and as biologic control agents in agroecosystems, therefore they are ideal organisms for biological monitoring (Pearce & Venier 2006, Cristofoli et al. 2010). Almost all arachnids are good ecosystem degradation indicators, because they are very sensitive to environmental changes caused by human activity. They are closely associated with environmental conditions and vegetation. Most spiders have specific ecological requirements, making them useful indicators of spatial and temporal variation in terrestrial ecosystems (Pearce & Venier 2006). They are important in trophic networks as predators, as well as because of their abundance, biomass and species diversity (Wise 1993, 2006). They feed on all kinds of invertebrates, especially insects, and some little vertebrates and they are eaten by birds, reptiles, amphibians and several groups of mammals.

### Spiders in Agroecosystems

In the last decades there has been an important increase in the number of studies focusing on the use of spiders as biological control agents (Riechert and Lockley, 1984, Young and Edwards, 1990; Sunderland, 1999). They are highlighted for their abundance, biomass and species richness and for their participation in the control of phytophagous species, decomposition and pollination.
It has been mentioned that spiders in the field usually consume about one appropriate-sized insect per day (Nyffeler and Benz, 1987), however they will kill many more insects than they consume (Maupin and Riechert, 2001). In conjunction with other natural enemies (parasitoids, pathogens and other predators) spiders may tip the balance in biological control (Sunderland, 1999), particularly those species called “agrobiont” spiders by Luczak (1979). These spiders have life history characteristics that allow them to reach adulthood and reproduce during the main crop vegetation period, exhibiting high dominance in strong abiotically driven and frequently disturbed habitat types, like agroecosystems (Luczak, 1979, Nyffeler and Benz, 1987, Samu and Szinetár, 2002).

## Subpages

Special:Prefixindex/Spiders/

## See Also

* Topic:Arachnology