44x42 for HP Deskjet 500PS
For spelman research day, the size is smaller.
margin ?
Bugs: I had some figures copy-pasted from WORD document, and it failed to print out on the poster. I resolved this problem by move the figure out of the WORD box.
Tuesday, June 30, 2015
SMB2015 Day 1
=>Lovchenko answers to pathway vs network. Depends on the contexts, depends on what we try to understand. Pathways can be convincingly defined when no crossovers occur in networks.
=> Voit:
mathematican turing coffee into theorems
showed a magician's work, turning coffee into coins.
biology challenge: how to weave snapshots into a movie?
dX = net change = influxes - efflexes
The values of the X are snapshots. The righthand are the mechanisms to infer
Case one, heat stress response in yeast, within minutes. (not affect by gene expression)
Immediate change of enzyme activities are Arrhenius effect.
Challenge of presentation: convey the key messages and why all these math equations are important.
=> chemical reactions, quasi-steady state approximation QSSA
reformat chemical reaction into state vectors.
https://en.wikibooks.org/wiki/Control_Systems/State-Space_Equations
difficulties: all possible states are very large
to reduce dimenson: identify fast invariants (nodes in the networks) that can reach quasi-steady states
/* This is similar to my rate-limiting approach for aging simulations */
the "slow manifold" is often the interest of experimental investigation. In ODE setting, set the fast reaction to zero.
Chemical master equations is often used to capture the stochasticity.
Often not solvable analytically, and studied by Gillespie algorithm based simulations. Fast reactions slows down Gillespie algorithms.
Propensity functions in stochastic simulations
Recently, some negative stories of QSSA were shown in stochastic systems.
Key ref: Rao and Arkin, JCP 2003.
Kim: slow manifold of stochastic systems is the conditional average. People have been using Michaellis-Menton to approximate the slow manifold.
Kim evaluate the difference between <conditional avearge> and the M-M deterministic value, using moment method. Kim conlcuded that 'low sensitivity' is necessary for accurate stochastic QSSA.
=> Robery Myers, quantitative reasoning
Quantitative Interpretation
RASCH analysis of task
https://en.wikipedia.org/wiki/Rasch_model
=>
=> E N Bodine, Rhode College
A math modeling class also emphasize scientific writing for sophomores and juniors.
Prereqquisite: differential equations. required for biomath majors.
Example in class: SIR model, slightly modified in different student groups
Two report milestones due in the course: a draft in midterm, a final report in the end.
Fall 2012, 2013 in MATLAB, 2014 switch to Mathematica (easier, also students use it in their previous courses).
About half of the coding and writing assignments are group assignments. Student peer-review using a rubric. The rubric seem to be generated by the students themselves.
=> Voit:
mathematican turing coffee into theorems
showed a magician's work, turning coffee into coins.
biology challenge: how to weave snapshots into a movie?
dX = net change = influxes - efflexes
The values of the X are snapshots. The righthand are the mechanisms to infer
Case one, heat stress response in yeast, within minutes. (not affect by gene expression)
Immediate change of enzyme activities are Arrhenius effect.
Challenge of presentation: convey the key messages and why all these math equations are important.
=> chemical reactions, quasi-steady state approximation QSSA
reformat chemical reaction into state vectors.
https://en.wikibooks.org/wiki/Control_Systems/State-Space_Equations
difficulties: all possible states are very large
to reduce dimenson: identify fast invariants (nodes in the networks) that can reach quasi-steady states
/* This is similar to my rate-limiting approach for aging simulations */
the "slow manifold" is often the interest of experimental investigation. In ODE setting, set the fast reaction to zero.
Chemical master equations is often used to capture the stochasticity.
Often not solvable analytically, and studied by Gillespie algorithm based simulations. Fast reactions slows down Gillespie algorithms.
Propensity functions in stochastic simulations
Recently, some negative stories of QSSA were shown in stochastic systems.
Key ref: Rao and Arkin, JCP 2003.
Kim: slow manifold of stochastic systems is the conditional average. People have been using Michaellis-Menton to approximate the slow manifold.
Kim evaluate the difference between <conditional avearge> and the M-M deterministic value, using moment method. Kim conlcuded that 'low sensitivity' is necessary for accurate stochastic QSSA.
=> Robery Myers, quantitative reasoning
Quantitative Interpretation
RASCH analysis of task
https://en.wikipedia.org/wiki/Rasch_model
=>
1. biofilm modeling
1D modeling? homogenous layer of aerobic microbes (10-20 μm think) biofilm in chronic injuries, such as wounds in diabetic patients.
experimental set up: microbes in a gel, by B. pitts using an indicate function to model microbes responses with resect to oxygen. Oxygen diffuses in biofilm
2. biometerology and ashma david quesada, south florida seasonal changes of asthma
heat stress vs cold stress
3. Lester Caudill, U of Richmod, integrated quantitative science
http://iqscience.richmond.edu Qin: from its, college students need to apply by July 8. The applications requires math courses in high school. So the students are highly selected. in its 6th years. funded by HHMI freshman level course emphasize big questions Java programming and computer simulation team taught by five faculty, one from each disci-
pline. there is an application process for students to register, 2008-9 first launched.
3.1. course organization. in 2008, one theme for fall and another in spring. Five dis- ciplines at all time (staffing and logistics nightmare) in 2014, death semester divived into 3 modules. each module has its own them, under the umbrella ’challenges of a changing planet’ 2-3 discipines per modules
3.2. staffing. in 2014, each faculty participated in 3 out of 6 modules Each modules take faculty 10 hours per week.
3.3. interdiplinary expereinces and assessment. in 2004, Exams are like five disci- pline exams stapled together. in 2014, take-home portion of each devoted to interdscipine pre- and post-course ID activities to measure ID-gain
3.4. computer science. in 2004, computer science lessons were scattered the entire year. Gaps between CS lesson led to memory loss of students.
in 2014, all computer science lessons are concentrated in the fall semester.
Q: Hope college: biology + computer science students Q: how do students adjust small class and large general courses. Q: big data aspect? A: some database aspect, depending on the CS instructor. Q: if student fail, which discipline do they fail?
1D modeling? homogenous layer of aerobic microbes (10-20 μm think) biofilm in chronic injuries, such as wounds in diabetic patients.
experimental set up: microbes in a gel, by B. pitts using an indicate function to model microbes responses with resect to oxygen. Oxygen diffuses in biofilm
2. biometerology and ashma david quesada, south florida seasonal changes of asthma
heat stress vs cold stress
3. Lester Caudill, U of Richmod, integrated quantitative science
http://iqscience.richmond.edu Qin: from its, college students need to apply by July 8. The applications requires math courses in high school. So the students are highly selected. in its 6th years. funded by HHMI freshman level course emphasize big questions Java programming and computer simulation team taught by five faculty, one from each disci-
pline. there is an application process for students to register, 2008-9 first launched.
3.1. course organization. in 2008, one theme for fall and another in spring. Five dis- ciplines at all time (staffing and logistics nightmare) in 2014, death semester divived into 3 modules. each module has its own them, under the umbrella ’challenges of a changing planet’ 2-3 discipines per modules
3.2. staffing. in 2014, each faculty participated in 3 out of 6 modules Each modules take faculty 10 hours per week.
3.3. interdiplinary expereinces and assessment. in 2004, Exams are like five disci- pline exams stapled together. in 2014, take-home portion of each devoted to interdscipine pre- and post-course ID activities to measure ID-gain
3.4. computer science. in 2004, computer science lessons were scattered the entire year. Gaps between CS lesson led to memory loss of students.
in 2014, all computer science lessons are concentrated in the fall semester.
Q: Hope college: biology + computer science students Q: how do students adjust small class and large general courses. Q: big data aspect? A: some database aspect, depending on the CS instructor. Q: if student fail, which discipline do they fail?
=> E N Bodine, Rhode College
A math modeling class also emphasize scientific writing for sophomores and juniors.
Prereqquisite: differential equations. required for biomath majors.
Example in class: SIR model, slightly modified in different student groups
Two report milestones due in the course: a draft in midterm, a final report in the end.
Fall 2012, 2013 in MATLAB, 2014 switch to Mathematica (easier, also students use it in their previous courses).
About half of the coding and writing assignments are group assignments. Student peer-review using a rubric. The rubric seem to be generated by the students themselves.
Friday, June 26, 2015
blacklight jobs and SUs = wall-time-minutes/4
At XSEDE user portal, choose jobs.
It seems SUs = wall-time-minutes/4
It seems SUs = wall-time-minutes/4
Thursday, June 25, 2015
unison on blacklight (not working)
https://portal.xsede.org/psc-blacklight
"Blacklight runs an enhanced version of the SuSE Linux operating system."
I download a Linux binary unison to blacklight frontend.
http://www.cs.haifa.ac.il/~shuly/unison/
On byte
unison tmp1 ssh://hqin2@blacklight.psc.xsede.org/tmp1
OK, it is not trivial to setup unison on blacklight.
"Blacklight runs an enhanced version of the SuSE Linux operating system."
I download a Linux binary unison to blacklight frontend.
http://www.cs.haifa.ac.il/~shuly/unison/
hqin2@tg-login1:~> ll
total 1376
lrwxrwxrwx 1 hqin2 mc48o9p 27 2015-06-25 16:06 unison -> unison-2.27.47-linux32.text
-rwxr-x--x 1 hqin2 mc48o9p 1348789 2015-06-25 16:05 unison-2.27.47-linux32.text
-rw------- 1 hqin2 mc48o9p 315 2015-06-25 16:13 unison.log
Byte-2:demo hqin$ unison tmp1 ssh://hqin2@blacklight.psc.xsede.org/tmp1
Contacting server...
hqin2@blacklight.psc.xsede.org's password:
bash: unison: command not found
Fatal error: Lost connection with the server
OK, it is not trivial to setup unison on blacklight.
vertical strips on 17in mac pro laptop
Today, my 17inch mac pro laptop (5 years old now, hostname "ace") has a vertical strip in the middle. (It occurred once in the spring 2015, but went away on its own).
After some online research, I pressed the glass screen for a few second, and restart by holding CMMD+Ctrl+P+R. The vertical strip went away.
Pressing the glass screen was mentioned at
https://www.ifixit.com/Answers/View/17589/MacBook+suddenly+has+inverted-flickering+vertical+strip+on+the+screen
CMMD+Ctrl+P+R was mentioned at
http://www.cnet.com/forums/discussions/macbook-pro-screen-problems-strip-screen-then-shutdown-588409/
Later in the afternoon, the same vertical strip come back again, after some overheated use.
I tried press the glass and CMMD+Ctrl+P+R again. The vertical strip was still there.
After some online research, I pressed the glass screen for a few second, and restart by holding CMMD+Ctrl+P+R. The vertical strip went away.
Pressing the glass screen was mentioned at
https://www.ifixit.com/Answers/View/17589/MacBook+suddenly+has+inverted-flickering+vertical+strip+on+the+screen
CMMD+Ctrl+P+R was mentioned at
http://www.cnet.com/forums/discussions/macbook-pro-screen-problems-strip-screen-then-shutdown-588409/
Later in the afternoon, the same vertical strip come back again, after some overheated use.
I tried press the glass and CMMD+Ctrl+P+R again. The vertical strip was still there.
Wednesday, June 24, 2015
First markdown try
First markdown
h qin
June 24, 2015
When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
summary(cars)## speed dist
## Min. : 4.0 Min. : 2.00
## 1st Qu.:12.0 1st Qu.: 26.00
## Median :15.0 Median : 36.00
## Mean :15.4 Mean : 42.98
## 3rd Qu.:19.0 3rd Qu.: 56.00
## Max. :25.0 Max. :120.00
Note that the
echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.
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