Scientopia http://scientopia.org Thu, 01 Dec 2016 23:42:23 +0000 en-US hourly 1 76009644 Really, it's normal http://drugmonkey.scientopia.org/2016/12/01/really-its-normal/ Thu, 01 Dec 2016 23:42:23 +0000 http://drugmonkey.scientopia.org/?p=9478 It's okay. It's perfectly natural and healthy. Everyone does it, you know. I mean, it's not like anyone brags about it but they do it. Regularly. So go ahead and don't feel ashamed.

Go on over to Web of Science and see how your citations are coming along for the year.

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I blew it, here's the version of 21st Century Cures that was passed by the House http://drugmonkey.scientopia.org/2016/12/01/i-blew-it-heres-the-version-of-21st-century-cures-that-was-passed-by-the-house/ Thu, 01 Dec 2016 19:58:09 +0000 http://drugmonkey.scientopia.org/?p=9476 ooops.

I had the wrong version. Thanks to Jocelyn Kaiser of Science mag for alerting me.

The 21st Century Cures site is here and I think the right version of the bill is here in PDF form.

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On becoming an expert outside your direct area of expertise http://inbabyattachmode.scientopia.org/2016/12/01/on-becoming-an-expert-outside-your-direct-area-of-expertise/ Thu, 01 Dec 2016 07:54:52 +0000 http://inbabyattachmode.scientopia.org/?p=488 This week I received feedback that I need to act more confident in my role as expert. I recognize myself in this feedback, because often when I'm in a discussion about something neuroscience with someone who is not a neuroscientist, I come with all these nuances and considerations and find it hard to make very concrete statements. However, that is something that is needed when decisions need to be made about how to measure something or how to interpret literature.

This lead me to think about the difference of what you consider an expert on a topic in academia vs in industry (at least in my line of work).

img_7338

My interpretation of the difference between being an expert in academia vs in industry. Not drawn to scale. Also, the yellow is a drawing from Little Brother that I thought would not be visible but clearly is.

In academia, after having completed a PhD thesis and some time as a post-doc, you can consider yourself an expert in those topics (even if it feels like there are others who are even more expert). I definitely feel confident making statements about subjects in those incredibly tiny circles. However, now that I am in industry I am supposed to be an expert in much larger areas in a group of people who know even less about this topic (along the lines of: "In the land of the blind, the one-eyed man is king"). I have always been more of a generalist, so I like reading and thinking about these bigger areas (with dotted lines in the drawing because the areas change every now and then).

But I guess what comes next in this transition from the left circle to the right is to stand up in a meeting and either say:"I know that this is such and such and that's why I recommend this" or "I need to analyze this further and will come back to it". I need to figure out how much knowledge and analysis is needed to fulfill this role, because it is impossible to take the time to reach the expertise level from the left circle in my current job. And in academia, I feel I've been trained to withhold from any firm conclusions until you've looked at a topic from different viewpoints.

And I guess for a part it comes back to the question of how you become visible and get your opinion heard if you don't look like the prototype expert...?

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Overtime rules http://drugmonkey.scientopia.org/2016/11/30/overtime-rules/ Wed, 30 Nov 2016 16:12:37 +0000 http://drugmonkey.scientopia.org/?p=9467 So. A federal judge* managed to put a hold on Obama's move to increase the threshold for overtime exemption. Very likely any challenge to this will fail to succeed before a new Administration takes over the country. Most would bet there will be no backing for Obama's plans under the new regime.

NIH is planning to steam ahead with their NRSA salary guidelines that met the Obama rule. Workplaces are left in a quandary. Many have announced their policies and issued notification of raises to some employees. Now they are not being forced to do so, at the last hour.

My HR department has signaled no recent changes in plans. Postdocs will get raises up to the Obama threshold. There are some other categories affected but I've seen no announcement of any hold on those plans either.

How about you folks? What are your various HR departments going to do in light of the de facto halt on Obama's plans!

__
*activist judge

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Clearing the backlog http://genrepair.scientopia.org/2016/11/29/clearing-the-backlog/ Tue, 29 Nov 2016 03:23:31 +0000 http://genrepair.scientopia.org/?p=1702 I'm currently not able to spend a lot of time in lab (booo!) and stuck at my desk working on papers (yay!!!!). Papers good right? Yeah but too many manuscripts are coalescing at once. I'm staring at four drafts of papers from me (2 first authorships, 2 co-authorships) and I'm looking at my excel sheet and I have two more to write.

I'm super happy with all the work I've been doing but I'm not going to lie this is daunting as hell. I want to get at least two of the papers out the door in the next week and a half or lets face it, they won't be going out until early January.

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Commercial airlines now refusing to transport lab mice http://drugmonkey.scientopia.org/2016/11/28/commercial-airlines-now-refusing-to-transport-lab-mice/ Mon, 28 Nov 2016 16:42:55 +0000 http://drugmonkey.scientopia.org/?p=9465 Via ScienceMag:

Twenty-nine transgenic mice that two Spanish airlines had refused to transport hitched a ride to the Canary Islands on a military plane Friday and are now at their final destination

Y'all looked away when they stopped shipping purpose bred non-human primate laboratory subjects. "Oh please", you thought, "there is no way anyone gives a care about genetic mouse models".

Guess what? You were wrong and Niemöller's principle rules the day.

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On reading http://mistressoftheanimals.scientopia.org/2016/11/28/on-reading/ Mon, 28 Nov 2016 14:55:06 +0000 http://mistressoftheanimals.scientopia.org/?p=2938 This morning I was reading a great article in the NYTimes magazine. It was about a cook, a person who is a chef at their own restaurant, putting together a meal for friends, a meal at which she could sit down and enjoy. The recipes are interesting, and some of them maybe worth trying.

But what hit me, when I was done, was the writing. This chef runs some fancy-pants restaurant in New York. I probably couldn't get a reservation there. But when I was reading this, I felt that I'd like to know this woman. I felt that she had opened up a part of herself, and that I understood some of those parts. I could make the leap from chef to scientist and see things about myself in what she said about herself.

I know lots of people who "don't have time for reading". Reading in it and of itself is just a stand-in for getting information, knowledge, stuff flowing into your head. Reading is just an efficient way to do that. To cut oneself off from that flow, to limit that flow to things that one already knows, to things in one's own narrow sphere, is to cut one's self off from life.

We do not know where our ideas come from (for the most part). We do not know what will nudge us one way or the other, in our professional lives, in our personal lives. But if we do not read, we will certainly miss out on many opportunities to be nudged. To grow. To change. Change is good. It is life itself.

 

 

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Why did you just throw away my box of memories, Microsoft? http://inbabyattachmode.scientopia.org/2016/11/28/why-did-you-just-throw-away-my-box-of-memories-microsoft/ Mon, 28 Nov 2016 08:03:53 +0000 http://inbabyattachmode.scientopia.org/?p=484 Dear Microsoft,

I am the kind of person that likes to keep little boxes with memories. At my parents’ house, I have a box with letters that my grandmother sent to me when I was studying or working abroad. When she passed away, she had a box with the letters I wrote to her, so now I have a slightly bigger box that contains both our correspondence. I have a similar box with letters from friends in high school. And a box with pictures from the time before digital photography.

My Hotmail account was a box like that. I started using it in the late nineties just before I went to college and continued to use it for almost 10 years, until I switched to gmail. I never deleted anything, except for in the early days when Hotmail only allowed you so much storage and I had to make the difficult decision of which of those precious emails to delete.

I hadn’t logged into my Hotmail account for over a year, and then when I did yesterday, it had switched to being outlook, and to my horror my inbox said: ”You’re all caught up” and it was empty, except for the image of a winner cup. What have you done, Microsoft? Did you just throw away my box of memories?! A quick google search shows me I’m not the only one, but that Microsoft has been an overachieving Marie Kondo for everybody and apparently decided that none of those emails were sparking joy and therefore could all just be deleted.

So now I’ve been preoccupied since yesterday with trying to remember what was in those ten years of emails: the entire electronic correspondence with the person I had a relationship with for more than half of that decade, the email from his mom around the time we broke up about how I needed to make decisions for myself – an email that really upset me when I received it, but that when I re-read it years later finally understood the warmth behind it. Also, emails from my friend when she was abroad for a year when we were 18. Sent emails from myself when I was abroad for work or studying. Very precious emails from the first person I ever dated when I was 14: email did not exist back then for me, but we later found each other back – in an email that kind of changed my life afterwards (yes – dramatic, but that is the case when you’re adolescent right?). Also: pictures from before the digital era that people had scanned and emailed. And probably many other things that I couldn’t remember, but that were in that box as well.

Why did you just throw away my box of memories, Microsoft?

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Getting article metadata from MS Academic: some R code http://christinaslisrant.scientopia.org/2016/11/27/getting-article-metadata-from-ms-academic-some-r-code/ Sun, 27 Nov 2016 23:20:35 +0000 http://christinaslisrant.scientopia.org/?p=1235 As promised, I went back and did this myself instead of relying on a partner in crime (earlier referred to as an SME but he outed himself). It's funny because I had his code, but he did things differently than I do them so I needed to do it myself.

First mostly successful run I ended up with about 44% of the rows missing the metadata. I discovered fairly quickly that using TM's removePunctuation was, of course (in retrospect), closing up instead of leaving a space for intraword dashes. You can have it ignore those, but you can't have it go ahead and leave a space. I first did some finding and replacing in Excel but that got me down to 32%. Then I was like, duh, just do the gsub for [[:punct:]] and see if that's better. I hope I haven't used my quota!

Here's the code. Sign up for your key here. Also note: not affiliated, not endorsing.

#microsoft academic to try to find affiliations for article titles

library("httr", lib.loc="~/R/win-library/3.3")

library("tm", lib.loc="~/R/win-library/3.3")
library("jsonlite", lib.loc="~/R/win-library/3.3")

setwd("~/DataScienceResearchInitiative")

#don't forget the following or you will regret it
options(stringsAsFactors = FALSE)

# api info https://dev.projectoxford.ai/docs/services/56332331778daf02acc0a50b/operations/565d753be597ed16ac3ffc03

# https://api.projectoxford.ai/academic/v1.0/evaluate[?expr][&model][&count][&offset][&orderby][&attributes]

#keys:
msakey1<-"put yours here"
msakey2<-"put yours here"

apiurl<-"https://api.projectoxford.ai/academic/v1.0/evaluate?expr="
searchexpr<-"Ti='improving short text classification by learning vector representations of both words and hidden topics'"
apiattrib<-"Ti,Y,AA.AuN,AA.AfN,C.CN,J.JN,E"

#test on one to see how it works
testcite query = list(expr = searchexpr,count = 1, attributes = apiattrib), add_headers("Ocp-Apim-Subscription-Key"= msakey1))

#get the json out into usable format
#could look for errors first
testcite$status_code

#comes out raw so need to make into text
testciteContent

test<-fromJSON(testciteContent)
test$entities$AA
test$entities$AA[[1]]$AuN
#this will get a ; separated vector
paste(test$entities$AA[[1]]$AuN, collapse = ';')

test$entities$AA[[1]]$AfN
test$entities$J$JN
test$entities$Y
test$entities$Ti

# initiate a dataframe
# for each title, go out and search using that title
# could add in a warn_for_status(r) when status is not 200 (happy)
# if status !200 go to the next one, if status ==200
# extract ti, y, authors (paste), affil (paste), jn, cn, and out of entities VFN, V, FP LP DOI D
# write them to the data frame

#initiated a data frame the length of the list of titles

CitesOut y = integer(1904),
au = rep(NA,1904),
af = rep(NA,1904),
jn = rep(NA,1904),
cn = rep(NA,1904),
vfn = rep(NA,1904),
v = rep(NA,1904),
fp = rep(NA,1904),
lp = rep(NA,1904),
doi = rep(NA,1904),
abs = rep(NA,1904),
stringsAsFactors = FALSE)

#note all the different chances to deal with missing values
#some should have been missing because there were journal articles, conference papers, who knows what else combined

getMScites apiurl<-"https://api.projectoxford.ai/academic/v1.0/evaluate?expr="
searchexpr apiattrib<-"Ti,Y,AA.AuN,AA.AfN,C.CN,J.JN,E"
holding<-GET(apiurl,
query = list(expr = searchexpr,count = 1, attributes = apiattrib),
add_headers("Ocp-Apim-Subscription-Key"= msakey1))
print(paste("cite number", citeNo,"status is:", holding$status_code))
print(holding$headers$`content-length`)
holdingContent holdC<-fromJSON(holdingContent)
cciterow<-data.frame(
ti=ifelse(is.null(holdC$entities$Ti),NA,holdC$entities$Ti),
y=ifelse(is.null(holdC$entities$Y),NA,as.integer(holdC$entities$Y)),
au=ifelse(is.null(holdC$entities$AA[[1]]$AuN),NA,paste(holdC$entities$AA[[1]]$AuN, collapse = ';')),
af=ifelse(is.null(holdC$entities$AA[[1]]$AfN),NA,paste(holdC$entities$AA[[1]]$AfN, collapse = ';')),
jn=ifelse(is.null(holdC$entities$J$JN),NA,holdC$entities$J$JN),
cn=ifelse(is.null(holdC$entities$C$CN),NA,holdC$entities$C$CN))
print(cciterow)
if(is.null(holdC$entities$E)){
eciterow<-data.frame(
vfn=NA,
v=NA,
fp=NA,
lp=NA,
doi=NA,
abs=NA)
} else {
holdE<-fromJSON(holdC$entities$E)
eciterow<-data.frame(
vfn=ifelse(is.null(holdE$VFN),NA,holdE$VFN),
v=ifelse(is.null(holdE$V),NA,holdE$V),
fp=ifelse(is.null(holdE$FP),NA,holdE$FP),
lp=ifelse(is.null(holdE$LP),NA,holdE$LP),
doi=ifelse(is.null(holdE$DOI),NA,holdE$DOI),
abs=ifelse(is.null(holdE$D),NA,holdE$D)
)
}
print(eciterow)
citerow<-cbind(cciterow,eciterow, stringsAsFactors=FALSE)
print("this is citerow")
print(citerow)
return(citerow)
}

#troubleshooting
apiurl<-"https://api.projectoxford.ai/academic/v1.0/evaluate?expr="
searchexpr apiattrib<-"Ti,Y,AA.AuN,AA.AfN,C.CN,J.JN,E"
troubleshoot<-GET(apiurl,
query = list(expr = searchexpr,count = 1, attributes = apiattrib),
add_headers("Ocp-Apim-Subscription-Key"= msakey1))

troubleshoot$status_code
troubleshoot$headers$`content-length`

troubleshootcontent<-rawToChar(troubleshoot$content)
troubleC<-fromJSON(troubleshootcontent)
troubleE<-fromJSON(troubleC$entities$E)

## IMPORTANT - all the titles have to be lower case and there can't be any punctuation
TitlesToFind

TitlesToFindl<-apply(TitlesToFind,1,tolower)

TitlesToFindf

head(TitlesToFindf)

#don't do this way
CitesOut<-rbind(CitesOut,getMScites(3))

#note the delay of 2 seconds so you don't start getting that kind of error
for (i in 21:1904){
temp<-getMScites(i)
CitesOut[i,]<-temp
Sys.sleep(2)}
write.csv(CitesOut,"MSdsCites.csv")

#some missing, how bad is it?
length(which(is.na(CitesOut$ti)))
length(which(is.na(CitesOut$abs)))

#used the following for after I fixed the space in the middle of the document
missCites<-which(is.na(CitesOut$ti))

for (i in 1:length(missCites)) {
temp<-getMScites(i)
CitesOut[i,]<-temp
Sys.sleep(2)
}

[/sourcecode ]

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Giving Thanks http://drugmonkey.scientopia.org/2016/11/24/giving-thanks/ Thu, 24 Nov 2016 14:32:08 +0000 http://drugmonkey.scientopia.org/2016/11/24/giving-thanks/ On this day in the US we celebrate the things for which we are thankful.

I am thankful for the support of the taxpayers of this country who fund scientific research grants so that we all can advance knowledge and improve health.

I am thankful for the hard work of all of the science technicians who anchor the laboratories.

I am thankful for all of the support staff that let research Universities, hospitals and Institutes operate.

I am thankful for all of the scientific trainees who pour their intellects and energy into discovery. 

I am thankful for the Professors and Principle Investigators who struggle mightily to keep all the balls in the air so that the science they love can advance in their own laboratories.

I am also thankful for you, Dear Readers. Thanks for another fun year of discussions on the blog.

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