It seems there are quite a few of us on here that still have a problem with TV's. We're the ones who, when walking past the electronics section of a Walmart/Target, are gritting our teeth due to the sensory overload of 50 brand new TV's emitting in the 16khz range.
I'm glad the parent and grandparent got modded up. It's incredibly difficult to convince people that you can actually hear the high pitch sound that the refresh rate of TV's emit-- they tend to look at you like you have two heads. It's so intense for me that I ended up having to give up watching TV's about 7 or 8 years ago.
Your comments are a bit black and white. I say this because I'm someone that leads a bit of a double life. When I do go out, I will randomly go up to people and ask them about their life. At work I'll ask almost every person how they are doing, strike up a random conversation with someone just to see how they are doing. I don't care how people feel towards me, I do it regardless. I don't have a need for people to care and love me, and I certainly don't mind if people don't like me. That's life.
At the same time, I enjoy being alone during the evenings. I usually sit in my room doing something quiet, perhaps play a game, or do some reading. While I have many people I talk and converse with, I have a select few friends whom I am quite close with. These are the people that I am quite close with, and would bend over backwards for. At the same time, if I am going out with a group of close friends, I will not hesitate to ask someone that I'm not close to come along with me. I don't get offended if people choose not to come, but I offer the friendly gesture anyways.
I used to be strictly an introvert. Why did I change? Because I found that the people I was closest with and got along the best with were also introverts, and being an introvert myself, that didn't leave me much of a chance to meet other introverts. So I changed, I decided I'd go out and be outgoing. What did I find out? That balancing my social and quiet time is far more satisifying in life then being an introvert, and I ended up meeting some great friends along the way.
(BTW, I won't look up the paper, but they actually did a study on college students to find out what makes them happy/sad-- and they found that the happiest students were the ones that had an active social life. As negative as you make it seem, being social and outgoing does have its pluses)
Perhaps NASA should investigate other ways for astronauts to "relieve" themselves on these missions then. They should look at http://www.realdoll.com/Real Doll (not work safe) and other sexual outlets instead.
While it might seem far fetched, during WW2, Hitler was looking at sex dolls as well as an outlet for soliders on the battlefields. While his interests were different (he was more worried of his soliders catching STD's from foreign prostitutes), it still was an approach to meet the sexual needs of his soliders so they would be in peak performance.
The 1 in 10 was actually from a preparing future faculty talk. Again, this is only one field. I think the best rates for positions to applicants is 1:2. Which is still pretty low. It's worse in the humanities than in the sciences though.
The 1/2 pay is somewhat common. It varies from university to university, but graduate stipends/post doc positions are usually capped.
The attrition rate, there are a bunch of links out there. Some universities will actually advertise their attrition rates. Here's one article on it, but you can google for it and find many. This one states more of a 50% attrition rate, but it combines science and humanities. Science is around 1 in 3.
http://www.gs.howard.edu/announcements/pr_feb14a_2 005.htm
Here's an interesting link covering a lot of what I was talking about. Came across it while trying to find your attrition stat. http://www.agu.org/eos_elec/97117e.html
It talks a lot about the perceptions of graduate students, future positions, etc. Also be sure to check out the perceived opionions of graduating Ph.D's on the job market. It also talks about how 36% had thought about droping out at some time(these are of the ones that made it through). How the number one reason for droping out was a poor job market. And how many of the students don't consider the job market when going to graduate school.
There is a glut of Ph.D's in the US creating an over-competitive environment that's drastically deflating the pay level. What really should be done, is restricting the Ph.D's that schools push out to help overcompensate for the over inflation. But this won't happen. Why? Grad students are cheap labor for PI's. Schools accept grad students not because they are interesting in training and bringing more qualified people into the field, but rather because they need them to work for PI's. A PI is only as good as his/her grad students. If you add in a post-doc period, you are looking at, in some cases, 10+ years (a figure nowadays that has been increasing as many people are having to do multiple post-docs) of getting paid 1/2 of what you would have gotten if you had just gone straight into industry. Mind you, this isn't a bread and butter time either. This is a period where (in most cases), people are spending ridiculous hours working weekends/nights trying desperately to get data. And for what? An even more competitive academic environment where the positions to applicants ratio is (in some fields) 1:10. We haven't even gotten to the whole tenure track part. Add in all these factors and it is not surprising that 1 in 3 of these students never even complete their graduate "training"--most fighting for a masters.
I hate to seem pessimistic, but this article is long overdue, and at the same time, disturbing. We are flooding the market with ambitious bright individuals with promises of great prestige and fortune.
I really think they need to make a "Sims:The rise to professor" game depicting the rather long and gruesome journey to professorship. It would have to be realistic, so on average, you should only be winning, say, 5% of the time. Most people don't realize how different the actual and perceived opinion of prospective graduate students is from the actual reality of academia. I'm actually quite surprised that only 4-5% of Ph.D's are working outside their field (mind you, this figure doesn't include people that wanted to be in academia but couldn't get a position and ended up in industry). Sadly, I know a few that are working in simple jobs as security guards.
(And before someone jumps down my throat saying that I am bitter because I had a bad experience--I actually haven't. However, I know many more that have, and while I can't empathize (as much) with them, I certainly sympathize).
Before there is a large debate in the ethics community, they (you) ought to get the facts straight.......the ability to order oligos on the web doesn't magically give someone the ability to hack out a super virus
The article also touches on some of the ethical issues and how to balance them with the progression of science.
Practical in time and money? Perhaps not, the article highlights how it took about 3 years to do, and how it's more pratical to modify a virus as you had mentioned. However, this is only with the technology we have available today. My guess is that eventually we won't have to build large DNA segments using their underlying oligios. This method also eliminates the need to actually have a working template of the virus in front of you. Right now we are under a self-delusion that keeping infectious disease locked in highly contained area's blocks the threat from them being used maliciously. Being able to assemble a virus genome just by knowing it's sequence breaks down these walls.
It's one thing to be on the side of not limiting science and free information on this debate (as am I), it's another to completly ignore it and pretend like it doesn't exist. The last time someone laughed at someone's approach to doing science, he went out and sequenced the entire genome before they did (Craig Venter).
It would also, of course, be interesting if you could use this to work backwards through the genome to a set point
There actually is research that looks at predicting the last common ancestor between two species. For example, given man and ape, you can make a prediction on what the man/ape gnome was before they diverged into two species (not to go into details, but a lot of species divergence is the result of some kind of large scale chromosome rearrangement that makes it impossible to sexually reproduce). Remember, we didn't evolve from an ape, we diverged from an ape. The man and ape have had the same amount of time to evolve their genomes to become the species that we are today. Most people assume that at one time in our past we looked exactly like present day apes, but then evolved into humans. Where in fact we(again, both man and ape) probably looked something like a cross between an ape and a human-- whatever that might be.
which the researchers then "back-translated" to create artificial genes.
i.e. they did a trivial replacement of single amino acid letters with three letter codons in silico, then generated the corresponding DNA sequence.
Entirely off subject, but I'd like to point out, that while ordering an entire gene might seem a little science fiction, you can basically order any sequence you want just by sending off a series of AGCT's through a web form today. In fact, it is entirely possible for someone to order the entire E. Coli virus in a large series of oligios and then reform the entire virus from the oligios themselves. There is a large debate in the ethics community on whether we should be censoring papers that discuss how individuals were able to transform a virus to make it more resistant to disease, take on new characteristics,etc. for fear that terrorists could use this data and engineer their own super-virus and wipe out humanity. While it might seem similar to the debate on whether having source code available to everyone makes software more secure than having the code unavailable, it's actually not-- we can't really patch humans with updates to fix the security flaws, and the whole pro movement is that even publishing data that terrorists could use is valuable to science and will help us in our understanding (and perhaps someday patch humans).
While I realize this news seems fascinating to some individuals, it is not something so entirely new that people in Computational Biology would consider it groundbreaking. Using the computer algorithms to generate new gene sequences is actually just a matter of running the gene finding algorithms you used to find these genes backwards (in fact, many people have been testing their gene finding algorithms by using their old algorithms to generate pseudo test sets). The only thing new about this paper is that people actually went forward and experimentally validated their results. An interesting find, however, the end result does not provide a huge leap to science.
Now, if people are really interesting in some neat ways of reengineering genes back onto themselves, then they should take a look at some of the work being done with synthetic circuits. The beauty of synthetic circuits is that since you already know how the genes will function, it's just a matter of setting the circuit up in the fashion that you want so that it produces the end result that you want. There really is no limit to what you can do with synthetic circuits (of course, researchers have a long way to go before they master and understand all the regulatory mechanisms). For example (and these are all very theoretical examples): building a cell circuit to release a drug into a body in a very time released fashion (and perhaps autonomously renewing, for example, building a circuit to release insulin into the body given the sugar level of the individual), designing a circuit to recognize and destroy tumors (or perhaps an even simpler form of designing a circuit to recognize and fluorescently label tumor cells in the body helping in removal/early detection). Of course, one could also build quite malicious synthetic circuits as well. For example, a circuit that would aggregate to the wall of the heart and, after a certain number of other cells accumulate, triggering a signal to all the malicious cells and destroy the heart in unison.
The other nice advantage of synthetic circuits is that the more we learn out regulatory mechanisms in species, the more we can use them for synthetic circuits. The more we use them for synthetic circuits, the more we understand about how exactly the underlying mechanism works (what causes them to break, how do they deal with differing toxic environments, etc). It creates a nice feedback loop with the progression of science.
There will come a day where it will be useful to generate new DNA/Proteins in combination with synthetic circuits, but, as noted in a previous post, we don't understand the relationship between protein sequence and structure/function enough for it to be a viable option (and this is just with how the protein folds, we haven't even gotten in to the problem of gene regulatory structures-- multiple gene splicing, chromosome structure elements, binding motifs, translational regulation, etc). In fact, this area is something we probably want to venture into as it provides us with an even finer control over the rate constants for synthetic circuits. But for now, the generation of randomly generated genes based on prior genes will go overlooked for quite some time.
Universities have evolved from public trusts into something closer to venture capital firms. What used to be a scientific community of free and open debate now often seems like a litigious scrum of data-hoarding and suspicion. And what's more, Americans are paying for it through the nose.
And who's to blame for that? Yup, the good old American system.
The fact of the matter is, America doesn't care about science. We worship things like actors and singers and sports figures and then snub our nose at scientists in academia and pay them crap. Business is the most popular major, not because it provides the most to society, but rather it is the most profitable. In other countries, scientists are looked up to and admired (for example, India).
In the US, the budgets have been cut drastically for academia (most grants are getting a 8% cut straight across the board this past year). Adjusting for inflation, the NIH and NSF budget's have actually shrunk over the past 10 years-- which is ridiculous considering the massive amounts of improvement in technology that have occured. With such a drastic decrease in available funds, researchers need to tighten their projects, search for alternative funding, and be wary of who they tell people what they are doing. Sharing data with someone you aren't collaborating with or on unpublished work is a sure way to find yourself out the door in academia. This is further being complicated by the fact that tenure reviews are starting to shift from the old paradigm of how many papers you published, to a newer paradigm of how much grant money you bring in (while this is usually correllated, it is not always the case).
It's not the scientists that have created the environment, it's the environment that has created the scientists. There's a reason why College Professors were listed as one of the top 5 undervalued professions in America. Patents are the one bone that academia gets and the writer seems to think that scientists are exploiting America. Academia is already losing a lot of great talent (and henceforth, progress) as it is in America due to lack of funding-- how do you think it would be if patents didn't exists?
Bah, it never was Einstein's theory in the first place, didn't you see the family guy episode?
Albert Einstein: And what is it you want to patent, Herr Smith? Herr Smith: I call it "Smith's Theory of Relativity." Albert Einstein: Hey, look at this. Herr Smith: What? Slams guys head with shutter and runs off with the theory
And the slope slickens (like that word? I think I invented it)
There's a reason that the slippery slope argument is a logical fallacy.
If the average kid plays 1 hour of video games a day (probably too high), and watches 3 hours of TV (probably too low, much of it "sexy" primetime), and sees 2 big movies a year (violent, "sexy"), and more houses have TVs than video games (for obvious reasons), which medium will have the most effect on kids psyches?
If you're trying to make the argument that more houses have access to TV's and movies than to video games, then perhaps you are correct. However, judging strictly on the hours per day isn't accurate at all. TV, Movies and Video games are all forms of learning, however, only Video games fall into the category of being a "two-way literacy", while the formers are "one-way illiteracies". Two-way illiteracies have been shown to cause more metacognitive reasoning, which in turn leads to more understanding and learning than one way illiteracies. There is a movement in the learning/education community to try and restructure the traditional teaching methods used in schools systems to be more "two-way" to take advantage of the pervasiveness in learning that two-way illiteracies employ. In fact, some people have suggested that moving learning into being more game like would be more proper for people that have been growing up in the "digital age". There's an interesting book by James Paul Gee , where he highlights the tools that video games use to cause learning on the player, and how these principles can be used to further the educational and learning experience for society. What Video Games Have to Teach Us About Learning and Literacy
Whether anything anyone says is right or wrong, it's a matter of opinion first and foremost.
No, it's not.
Depends on the field. A large part of molecular biology/genetics deals with understanding mechanisms in the cell by doing a series of experiments that show that their theory is correct. You can't directly observe that something occurs, you can only imply that it occurs by a series of experiments that you have done. The point of the paper is then to win over a reviewer into believing that your hypothesis is correct.
Our biology provides us with excellent truth detectors: throughout most of primate evolution, if you were wrong about whether your food was poisonous or whether there was a lion hiding in the bushes, you didn't get to pass on your genes. You didn't get to debate social relativism with the lion before he made a tasty meal out of you.
Most of science is still ultimately about matters like that, matters that have good answers, at least in principle.
If a paper is discussing the regulation of a specific gene and it's pathway, I highly doubt you'll find a section that discusses the genes responsibility in the evolution of species and how it will help us in fighting off lions. Most average people won't care if gene X is downstream from gene Y, but it's a small peice of the puzzle in science that helps us understand how everything else in the cell works. I feel safe in saying that the people doing what you would consider the minority of science outweigh the others by at least 10:1.
Some science has veered off course, however. Every major scientific discipline (physics, biology, chemistry, etc.) has subareas where people start conflating experimental facts with opinion, aesthetics, and prejudice.
So, scientific truth is not a matter of opinion, but a lot of what is published in science is not about scientific truth.
The majority of "opinions" in science are left for the discussion section of a paper-- especially biology. However, what I will concede to you is the lack of researchers to publish the whole truth of their findings. Like I noted above, most of the time in molecular biology, researchers are trying to win over their hypothesis for the reviewers and get their paper published based on the evidence they have. In doing so, they often fail to mention or intentionally hide data that would comprimise their theory. But that's academia-- publish your research before someone else does and publish before there is evidence that contridicts it. While researchers are ultimately to blame for this one, the whole academia publish or perish, increasing competetion for faculty spots/tenure, and decreased funding from agencies is what is causing it to happen in the first place.
The only point I've demonstrated is thatsociety and technology are in a constant state of flux with each other. As it stands, marriage rates are falling and the average age of marriage is becoming older. In Japan itself (where this android originated from), divorce rates are increasing as married woman are beginning to realize that they do not want to deal with the traditional expectations of wives. People are too busy and stressed to deal with the demands that relationships press on them, and having some kind of android relationship might be exactly what they are looking for. You assume that it is the technology that is causing a societial change, where I would argue that it is the opposite.
I hope you and your robot enjoy growing old together.
Who are you to judge the decisions made by others? Because people enjoy primal urges more than others then they should be banished from society because it does not agree with the traditional monotomy that the church demands? Einstein-- who provided some of the greatest accomplishments to society -- was a large womanizer. He used to sneak out of his house in the middle of the night to meet woman and have affairs with them. And if that isn't enough, he even married his own cousin.
These are the same kind of arguments that society is dealing with now with the rights of gay marriage. Just because they can't reproduce, does not mean that they don't contribute to the benefit of society. I know a lot more gays that would have children more beneficial to society than a lot of the conservative politicans who enjoy making comparisons of gay marriage to beastiality.
Why are women always so worried about this? Trust me, weeding out the kind of guy who would rather go for a robot than a live woman can be nothing but a boon to you. It'd be nothing but a boon to society too. Darwinism is a good thing.
You assume that robots would only be a replacement instead of an improvement. I don't think it's far fetched to think that a robot could be designed to perform sex not only better than humans, but also with an uncanny ability to stimulate and perform in ways that would not possible by humans. As an example, take the large amount of people that go out on a weekend trying to get laid. Now imagine why someone would want to spend the night with a woman that a.) you have to buy drinks for b.) might not be good in the sack c.) have some kind of STD d.) has emotional commitments afterwards, when they can just go home and flip on their favorite quadruple jointed, soft skinned, beautiful, clean sexbot. Add in the complications of dating for the 60+ hour a week worker and the idea becomes more enticing.
The 10% that we consider useful is also the most useful in terms of comparative genetics. Coding regions tend to have the highest evolutionary selective pressure to not mutate/evolve in a fashion that is completly random or detrimental.
We are beginning to move into the era where non-coding regions are becoming important as well (enhancer, promoter regions, etc.), but they provide more fine tuned differences in the species (transcription factor binding efficiencies, etc.). (I use fine tuned in a very broad sense here, as it is entirely possible that one of these fined tuned process can cause an event where the gene gets entirely turned off permanantly-- as is the case with stem cell differentation)
One thing to consider is that genes are easy to compare and we understand coding regions better than non-coding regions in part because we can actually visualize how the coding DNA is going to work/look like in it's protein representation (translational suppression, etc. aside). We know that an insertion/deletion/mutation causes a change in the coding regions, which causes a change in the codon of the protein, which in turn causes a change in how the protein/folds and henceforth its function. Non-coding regions are difficult, they represent possible binding reactions between thousands of other transciption factors (genes), and there is a large lack of understanding in how the genes effect chromosome structure. We just don't know enough about the non-coding regions to understand how similarities/differences in the non-coding genome are affected in evolution.
The best analogy I can give is it's like comparing two different car. The coding regions would be things that are very tractable for us, the color, the number of doors, the type of car, the engine, etc. The non coding regions would be like trying to understand the wiring/programming behind the engine with knowing very little engineering. Sure, how it's wired and programmed is important, but saying that two red wires seem to be connected in a similar fashion means that they must function similarly often falls short. You don't know where those wires run to , and you don't fully understand how the components that they connect to fit into the big picture of how the engine works.
I wouldn't be suprised if in time these non-coding regions become more important for comparative genomics in the long run, but it will take some time before we get to that point.
Next, genetic testing before an insurance company will sell you health insurance.
This is actually unlawful. A few years ago a company out in the midwest I believe got in trouble for doing genetic testing on employees. It turns out the employees were suing the company saying the work caused permanent damage to to their hands, while the company tried to use genetic testing to say they were predisposed to the condition. Somewhere along the lines the court stepped in and said they can't test their employees like that as it violates their privacy.
There's a great movie you should watch that covers some of these points, it's called Gattaca
http://us.imdb.com/title/tt0119177/ . It's a movie about a guy born into a society, where on birth, you're given an expected lifespan and the diseases you will get. He's born into the society right before they start genetically screening-- as would be expected, he wasn't perfect. He spends his life trying to compete in a society where job interviews are based on DNA tests, and all along the way he is constantly being pushed down by people because he was labeled as having bad genes-- especially by his brother, who was born several years after him perfect. Eventually he steals the identity of someone who is perfect and tries to conquer his dream of flying into a space. It's a very interesting and touching movie given the topic, and I would suggest that everyone watch it.
Of course, we can always ask Watson what he thinks about the situation:
"People say it would be terrible if we made all girls pretty. I think it would be great."
http://www.newscientist.com/article.ns?id=dn3451/
I think we are in a bit of a gray area here. The Wiki article talks about how the comparison to Hitler is unnacceptable as nothing should compare to the atrocities that Hitler brought about. The wiki article tends to focus on what the Nazi's did during WW2 (as it talks a lot about the holocaust, etc.), what it doesn't talk about is the rise of power of the Nazi's in the 30's. For example, I don't see the article mentioning anything about the persecuation and flight of Thomas Mann from the Nazis. However, what we are talking about, is the fact that GW and his administration have displayed many of the characteristics which give rise to a leader such as Hitler and a facist regime
If that doesn't work, then perhaps we can use the fact that there are some here who are supporting GW and his ways. From which, we can fall back on this exception (quoted from the wiki description):
When discussing with actual neo-Nazis, Godwin's law should not typically apply
There used to be a navy dive tank at the subbase in Groton, CT that they would train on. I can't remember the exact conditions, but they used to keep the tank at about 92 degrees F for training purposes. After around 4 hours or so of training in the tank, they had to take a break to warm up. Water syphons heat away from the body much faster than air does-- I'm not sure there's any spot where he could swim across at where he wouldn't need some kind of wetsuit for.
There is an interesting memory approach called Image streaming that deals with conjuring memories that you didn't think ever happened. The odd thing about it is that many times the things you forgot actually get remembered(and not fake memories). It makes one wonder if indeed we actually ever forgotten them at all or just misplaced them.
You can laugh and not believe it at all, but Image Streaming is remarkeably effective in remembering events you think you had forgoten. For you can start with an old childhood memory of a person but not remember exactly what they looked like. After a period of time streaming and describing what they looked like you can build up the image of the person that you thought you had forgotten. It's like putting together the peices of a jigsaw-puzzle. You start off with a little bit, but you slowly add peices to the puzzle. As time goes on and you see more of the puzzle you find peices that you thought you lost. Eventually, you get to see the whole puzzle.
It is also quite effective in creativity and random guessing. I was actually quite suprised at how much easier it is for me to come up with ideas or solutions that I would never have thought of before. Once you really get into it you'd be suprised how effective it actually is, and following the mental progression of images to some solution is quite remarkeable. If you don't believe me, check your local library and pick up the book and read the first few chapters. Try it for a week or two, and if you still don't believe it put it down. I bought the book more for shits and giggles between undergrad and grad but was quite suprised with the results and my creativity afterwards.
Possible interactions (direct interactions that is) might decrease, but the complexity of the network has increased. Take the following:
A B \/ C D \/ E | F
Knocking out A would disrupt C, E, F. But C is the only direct product of A-- E, and F are downstream of A. There is a difference between being directly connected to a gene in a gene regulatory network and just being downstream of a gene. The problem is that by decreasing the genes you'e increased the length of the downstream interactions. Which means that knocking out a certain gene can have adverse effects on a large number of other genes that just happen to be downstream of it. You know that A affects other genes but by how much, and how further downstream is that gene? Add in varying kinetic rates and thousands of other sub-networks and you have a very messy picture.
When there are a lot of genes, knock outs aren't too bad as the genes only interact with a select few other genes and you don't have such a large downstream cascade. The real problem lies in the fact that we don't have the biological tools to collect the data that we need to actually figure out how these networks are composed. It's a very cumbersome process. And even when we have had simulated data of what we actually need, 90% of the expression levels you analyze aren't even relevant to your subnetwork, and you get a lot of false positives due to pure randomness in other genes.
The problem is that having many downstream genes increases the complexity of the biologist to gather meaningful data to be analyzed. Bioinformatics/Computational Biology rely on the biologist to provide the data. Since the biologist's job just got harder, so also did the Bioinformatasist/Computational Biologist's.
Earlier in the year many scientists who analyzed Bush's proposed budget expected him to cut areas of research by 8% while increasing DOD funding in an effort in balance the budget. It seems by these charts that we have actually increased funding. Most of which goes into DoD and Homeland security, but suprisingly even NSF, NIH had some increases. Not enough to really compensate for the amount of underpaid post-docs/graduate students who get tired of the rat race and dog-eat-dog world of academia and leave, but modest nonetheless.
Slashdot Mirror
Where they will go on to the lucrative career of creating doll replicas of themselves...
It seems there are quite a few of us on here that still have a problem with TV's. We're the ones who, when walking past the electronics section of a Walmart/Target, are gritting our teeth due to the sensory overload of 50 brand new TV's emitting in the 16khz range.
I'm glad the parent and grandparent got modded up. It's incredibly difficult to convince people that you can actually hear the high pitch sound that the refresh rate of TV's emit-- they tend to look at you like you have two heads. It's so intense for me that I ended up having to give up watching TV's about 7 or 8 years ago.
Your comments are a bit black and white. I say this because I'm someone that leads a bit of a double life. When I do go out, I will randomly go up to people and ask them about their life. At work I'll ask almost every person how they are doing, strike up a random conversation with someone just to see how they are doing. I don't care how people feel towards me, I do it regardless. I don't have a need for people to care and love me, and I certainly don't mind if people don't like me. That's life.
At the same time, I enjoy being alone during the evenings. I usually sit in my room doing something quiet, perhaps play a game, or do some reading. While I have many people I talk and converse with, I have a select few friends whom I am quite close with. These are the people that I am quite close with, and would bend over backwards for. At the same time, if I am going out with a group of close friends, I will not hesitate to ask someone that I'm not close to come along with me. I don't get offended if people choose not to come, but I offer the friendly gesture anyways.
I used to be strictly an introvert. Why did I change? Because I found that the people I was closest with and got along the best with were also introverts, and being an introvert myself, that didn't leave me much of a chance to meet other introverts. So I changed, I decided I'd go out and be outgoing. What did I find out? That balancing my social and quiet time is far more satisifying in life then being an introvert, and I ended up meeting some great friends along the way.
(BTW, I won't look up the paper, but they actually did a study on college students to find out what makes them happy/sad-- and they found that the happiest students were the ones that had an active social life. As negative as you make it seem, being social and outgoing does have its pluses)
Perhaps NASA should investigate other ways for astronauts to "relieve" themselves on these missions then. They should look at http://www.realdoll.com/Real Doll (not work safe) and other sexual outlets instead. While it might seem far fetched, during WW2, Hitler was looking at sex dolls as well as an outlet for soliders on the battlefields. While his interests were different (he was more worried of his soliders catching STD's from foreign prostitutes), it still was an approach to meet the sexual needs of his soliders so they would be in peak performance.
The 1 in 10 was actually from a preparing future faculty talk. Again, this is only one field. I think the best rates for positions to applicants is 1:2. Which is still pretty low. It's worse in the humanities than in the sciences though. The 1/2 pay is somewhat common. It varies from university to university, but graduate stipends/post doc positions are usually capped. The attrition rate, there are a bunch of links out there. Some universities will actually advertise their attrition rates. Here's one article on it, but you can google for it and find many. This one states more of a 50% attrition rate, but it combines science and humanities. Science is around 1 in 3. http://www.gs.howard.edu/announcements/pr_feb14a_2 005.htm
Here's an interesting link covering a lot of what I was talking about. Came across it while trying to find your attrition stat. http://www.agu.org/eos_elec/97117e.html
It talks a lot about the perceptions of graduate students, future positions, etc. Also be sure to check out the perceived opionions of graduating Ph.D's on the job market. It also talks about how 36% had thought about droping out at some time(these are of the ones that made it through). How the number one reason for droping out was a poor job market. And how many of the students don't consider the job market when going to graduate school.
There is a glut of Ph.D's in the US creating an over-competitive environment that's drastically deflating the pay level. What really should be done, is restricting the Ph.D's that schools push out to help overcompensate for the over inflation. But this won't happen. Why? Grad students are cheap labor for PI's. Schools accept grad students not because they are interesting in training and bringing more qualified people into the field, but rather because they need them to work for PI's. A PI is only as good as his/her grad students. If you add in a post-doc period, you are looking at, in some cases, 10+ years (a figure nowadays that has been increasing as many people are having to do multiple post-docs) of getting paid 1/2 of what you would have gotten if you had just gone straight into industry. Mind you, this isn't a bread and butter time either. This is a period where (in most cases), people are spending ridiculous hours working weekends/nights trying desperately to get data. And for what? An even more competitive academic environment where the positions to applicants ratio is (in some fields) 1:10. We haven't even gotten to the whole tenure track part. Add in all these factors and it is not surprising that 1 in 3 of these students never even complete their graduate "training"--most fighting for a masters.
I hate to seem pessimistic, but this article is long overdue, and at the same time, disturbing. We are flooding the market with ambitious bright individuals with promises of great prestige and fortune.
I really think they need to make a "Sims:The rise to professor" game depicting the rather long and gruesome journey to professorship. It would have to be realistic, so on average, you should only be winning, say, 5% of the time. Most people don't realize how different the actual and perceived opinion of prospective graduate students is from the actual reality of academia. I'm actually quite surprised that only 4-5% of Ph.D's are working outside their field (mind you, this figure doesn't include people that wanted to be in academia but couldn't get a position and ended up in industry). Sadly, I know a few that are working in simple jobs as security guards.
(And before someone jumps down my throat saying that I am bitter because I had a bad experience--I actually haven't. However, I know many more that have, and while I can't empathize (as much) with them, I certainly sympathize).
Before there is a large debate in the ethics community, they (you) ought to get the facts straight....
http://www.msnbc.msn.com/id/8715760/site/newsweek
The article also touches on some of the ethical issues and how to balance them with the progression of science.
Practical in time and money? Perhaps not, the article highlights how it took about 3 years to do, and how it's more pratical to modify a virus as you had mentioned. However, this is only with the technology we have available today. My guess is that eventually we won't have to build large DNA segments using their underlying oligios. This method also eliminates the need to actually have a working template of the virus in front of you. Right now we are under a self-delusion that keeping infectious disease locked in highly contained area's blocks the threat from them being used maliciously. Being able to assemble a virus genome just by knowing it's sequence breaks down these walls.
It's one thing to be on the side of not limiting science and free information on this debate (as am I), it's another to completly ignore it and pretend like it doesn't exist. The last time someone laughed at someone's approach to doing science, he went out and sequenced the entire genome before they did (Craig Venter).
It would also, of course, be interesting if you could use this to work backwards through the genome to a set point
There actually is research that looks at predicting the last common ancestor between two species. For example, given man and ape, you can make a prediction on what the man/ape gnome was before they diverged into two species (not to go into details, but a lot of species divergence is the result of some kind of large scale chromosome rearrangement that makes it impossible to sexually reproduce). Remember, we didn't evolve from an ape, we diverged from an ape. The man and ape have had the same amount of time to evolve their genomes to become the species that we are today. Most people assume that at one time in our past we looked exactly like present day apes, but then evolved into humans. Where in fact we(again, both man and ape) probably looked something like a cross between an ape and a human-- whatever that might be.
While I realize this news seems fascinating to some individuals, it is not something so entirely new that people in Computational Biology would consider it groundbreaking. Using the computer algorithms to generate new gene sequences is actually just a matter of running the gene finding algorithms you used to find these genes backwards (in fact, many people have been testing their gene finding algorithms by using their old algorithms to generate pseudo test sets). The only thing new about this paper is that people actually went forward and experimentally validated their results. An interesting find, however, the end result does not provide a huge leap to science.
Now, if people are really interesting in some neat ways of reengineering genes back onto themselves, then they should take a look at some of the work being done with synthetic circuits. The beauty of synthetic circuits is that since you already know how the genes will function, it's just a matter of setting the circuit up in the fashion that you want so that it produces the end result that you want. There really is no limit to what you can do with synthetic circuits (of course, researchers have a long way to go before they master and understand all the regulatory mechanisms). For example (and these are all very theoretical examples): building a cell circuit to release a drug into a body in a very time released fashion (and perhaps autonomously renewing, for example, building a circuit to release insulin into the body given the sugar level of the individual), designing a circuit to recognize and destroy tumors (or perhaps an even simpler form of designing a circuit to recognize and fluorescently label tumor cells in the body helping in removal/early detection). Of course, one could also build quite malicious synthetic circuits as well. For example, a circuit that would aggregate to the wall of the heart and, after a certain number of other cells accumulate, triggering a signal to all the malicious cells and destroy the heart in unison.
The other nice advantage of synthetic circuits is that the more we learn out regulatory mechanisms in species, the more we can use them for synthetic circuits. The more we use them for synthetic circuits, the more we understand about how exactly the underlying mechanism works (what causes them to break, how do they deal with differing toxic environments, etc). It creates a nice feedback loop with the progression of science.
There will come a day where it will be useful to generate new DNA/Proteins in combination with synthetic circuits, but, as noted in a previous post, we don't understand the relationship between protein sequence and structure/function enough for it to be a viable option (and this is just with how the protein folds, we haven't even gotten in to the problem of gene regulatory structures-- multiple gene splicing, chromosome structure elements, binding motifs, translational regulation, etc). In fact, this area is something we probably want to venture into as it provides us with an even finer control over the rate constants for synthetic circuits. But for now, the generation of randomly generated genes based on prior genes will go overlooked for quite some time.
From TFA
Universities have evolved from public trusts into something closer to venture capital firms. What used to be a scientific community of free and open debate now often seems like a litigious scrum of data-hoarding and suspicion. And what's more, Americans are paying for it through the nose.
And who's to blame for that? Yup, the good old American system.
The fact of the matter is, America doesn't care about science. We worship things like actors and singers and sports figures and then snub our nose at scientists in academia and pay them crap. Business is the most popular major, not because it provides the most to society, but rather it is the most profitable. In other countries, scientists are looked up to and admired (for example, India).
In the US, the budgets have been cut drastically for academia (most grants are getting a 8% cut straight across the board this past year). Adjusting for inflation, the NIH and NSF budget's have actually shrunk over the past 10 years-- which is ridiculous considering the massive amounts of improvement in technology that have occured. With such a drastic decrease in available funds, researchers need to tighten their projects, search for alternative funding, and be wary of who they tell people what they are doing. Sharing data with someone you aren't collaborating with or on unpublished work is a sure way to find yourself out the door in academia. This is further being complicated by the fact that tenure reviews are starting to shift from the old paradigm of how many papers you published, to a newer paradigm of how much grant money you bring in (while this is usually correllated, it is not always the case).
It's not the scientists that have created the environment, it's the environment that has created the scientists. There's a reason why College Professors were listed as one of the top 5 undervalued professions in America. Patents are the one bone that academia gets and the writer seems to think that scientists are exploiting America. Academia is already losing a lot of great talent (and henceforth, progress) as it is in America due to lack of funding-- how do you think it would be if patents didn't exists?
Bah, it never was Einstein's theory in the first place, didn't you see the family guy episode?
Albert Einstein: And what is it you want to patent, Herr Smith?
Herr Smith: I call it "Smith's Theory of Relativity."
Albert Einstein: Hey, look at this.
Herr Smith: What?
Slams guys head with shutter and runs off with the theory
Bah, ignore my "illiteracies". Spell checker(and indirectly me) did a replace all with the wrong word, should be "literacy's".
But next it will be music.
Then movies.
Then TV.
And the slope slickens (like that word? I think I invented it)
There's a reason that the slippery slope argument is a logical fallacy.
If the average kid plays 1 hour of video games a day (probably too high), and watches 3 hours of TV (probably too low, much of it "sexy" primetime), and sees 2 big movies a year (violent, "sexy"), and more houses have TVs than video games (for obvious reasons), which medium will have the most effect on kids psyches?
If you're trying to make the argument that more houses have access to TV's and movies than to video games, then perhaps you are correct. However, judging strictly on the hours per day isn't accurate at all. TV, Movies and Video games are all forms of learning, however, only Video games fall into the category of being a "two-way literacy", while the formers are "one-way illiteracies". Two-way illiteracies have been shown to cause more metacognitive reasoning, which in turn leads to more understanding and learning than one way illiteracies. There is a movement in the learning/education community to try and restructure the traditional teaching methods used in schools systems to be more "two-way" to take advantage of the pervasiveness in learning that two-way illiteracies employ. In fact, some people have suggested that moving learning into being more game like would be more proper for people that have been growing up in the "digital age". There's an interesting book by James Paul Gee , where he highlights the tools that video games use to cause learning on the player, and how these principles can be used to further the educational and learning experience for society.
What Video Games Have to Teach Us About Learning and Literacy
Whether anything anyone says is right or wrong, it's a matter of opinion first and foremost.
No, it's not.
Depends on the field. A large part of molecular biology/genetics deals with understanding mechanisms in the cell by doing a series of experiments that show that their theory is correct. You can't directly observe that something occurs, you can only imply that it occurs by a series of experiments that you have done. The point of the paper is then to win over a reviewer into believing that your hypothesis is correct.
Our biology provides us with excellent truth detectors: throughout most of primate evolution, if you were wrong about whether your food was poisonous or whether there was a lion hiding in the bushes, you didn't get to pass on your genes. You didn't get to debate social relativism with the lion before he made a tasty meal out of you.
Most of science is still ultimately about matters like that, matters that have good answers, at least in principle.
If a paper is discussing the regulation of a specific gene and it's pathway, I highly doubt you'll find a section that discusses the genes responsibility in the evolution of species and how it will help us in fighting off lions. Most average people won't care if gene X is downstream from gene Y, but it's a small peice of the puzzle in science that helps us understand how everything else in the cell works. I feel safe in saying that the people doing what you would consider the minority of science outweigh the others by at least 10:1.
Some science has veered off course, however. Every major scientific discipline (physics, biology, chemistry, etc.) has subareas where people start conflating experimental facts with opinion, aesthetics, and prejudice.
So, scientific truth is not a matter of opinion, but a lot of what is published in science is not about scientific truth.
The majority of "opinions" in science are left for the discussion section of a paper-- especially biology. However, what I will concede to you is the lack of researchers to publish the whole truth of their findings. Like I noted above, most of the time in molecular biology, researchers are trying to win over their hypothesis for the reviewers and get their paper published based on the evidence they have. In doing so, they often fail to mention or intentionally hide data that would comprimise their theory. But that's academia-- publish your research before someone else does and publish before there is evidence that contridicts it. While researchers are ultimately to blame for this one, the whole academia publish or perish, increasing competetion for faculty spots/tenure, and decreased funding from agencies is what is causing it to happen in the first place.
Thank you, sir, for demonstrating my point.
The only point I've demonstrated is thatsociety and technology are in a constant state of flux with each other. As it stands, marriage rates are falling and the average age of marriage is becoming older. In Japan itself (where this android originated from), divorce rates are increasing as married woman are beginning to realize that they do not want to deal with the traditional expectations of wives. People are too busy and stressed to deal with the demands that relationships press on them, and having some kind of android relationship might be exactly what they are looking for. You assume that it is the technology that is causing a societial change, where I would argue that it is the opposite.
I hope you and your robot enjoy growing old together.
Who are you to judge the decisions made by others? Because people enjoy primal urges more than others then they should be banished from society because it does not agree with the traditional monotomy that the church demands? Einstein-- who provided some of the greatest accomplishments to society -- was a large womanizer. He used to sneak out of his house in the middle of the night to meet woman and have affairs with them. And if that isn't enough, he even married his own cousin.
These are the same kind of arguments that society is dealing with now with the rights of gay marriage. Just because they can't reproduce, does not mean that they don't contribute to the benefit of society. I know a lot more gays that would have children more beneficial to society than a lot of the conservative politicans who enjoy making comparisons of gay marriage to beastiality.
Why are women always so worried about this? Trust me, weeding out the kind of guy who would rather go for a robot than a live woman can be nothing but a boon to you. It'd be nothing but a boon to society too. Darwinism is a good thing.
You assume that robots would only be a replacement instead of an improvement. I don't think it's far fetched to think that a robot could be designed to perform sex not only better than humans, but also with an uncanny ability to stimulate and perform in ways that would not possible by humans. As an example, take the large amount of people that go out on a weekend trying to get laid. Now imagine why someone would want to spend the night with a woman that a.) you have to buy drinks for b.) might not be good in the sack c.) have some kind of STD d.) has emotional commitments afterwards, when they can just go home and flip on their favorite quadruple jointed, soft skinned, beautiful, clean sexbot. Add in the complications of dating for the 60+ hour a week worker and the idea becomes more enticing.
The 10% that we consider useful is also the most useful in terms of comparative genetics. Coding regions tend to have the highest evolutionary selective pressure to not mutate/evolve in a fashion that is completly random or detrimental.
We are beginning to move into the era where non-coding regions are becoming important as well (enhancer, promoter regions, etc.), but they provide more fine tuned differences in the species (transcription factor binding efficiencies, etc.). (I use fine tuned in a very broad sense here, as it is entirely possible that one of these fined tuned process can cause an event where the gene gets entirely turned off permanantly-- as is the case with stem cell differentation)
One thing to consider is that genes are easy to compare and we understand coding regions better than non-coding regions in part because we can actually visualize how the coding DNA is going to work/look like in it's protein representation (translational suppression, etc. aside). We know that an insertion/deletion/mutation causes a change in the coding regions, which causes a change in the codon of the protein, which in turn causes a change in how the protein/folds and henceforth its function. Non-coding regions are difficult, they represent possible binding reactions between thousands of other transciption factors (genes), and there is a large lack of understanding in how the genes effect chromosome structure. We just don't know enough about the non-coding regions to understand how similarities/differences in the non-coding genome are affected in evolution.
The best analogy I can give is it's like comparing two different car. The coding regions would be things that are very tractable for us, the color, the number of doors, the type of car, the engine, etc. The non coding regions would be like trying to understand the wiring/programming behind the engine with knowing very little engineering. Sure, how it's wired and programmed is important, but saying that two red wires seem to be connected in a similar fashion means that they must function similarly often falls short. You don't know where those wires run to , and you don't fully understand how the components that they connect to fit into the big picture of how the engine works.
I wouldn't be suprised if in time these non-coding regions become more important for comparative genomics in the long run, but it will take some time before we get to that point.
Next, genetic testing before an insurance company will sell you health insurance.
This is actually unlawful. A few years ago a company out in the midwest I believe got in trouble for doing genetic testing on employees. It turns out the employees were suing the company saying the work caused permanent damage to to their hands, while the company tried to use genetic testing to say they were predisposed to the condition. Somewhere along the lines the court stepped in and said they can't test their employees like that as it violates their privacy.
There's a great movie you should watch that covers some of these points, it's called Gattaca http://us.imdb.com/title/tt0119177/ . It's a movie about a guy born into a society, where on birth, you're given an expected lifespan and the diseases you will get. He's born into the society right before they start genetically screening-- as would be expected, he wasn't perfect. He spends his life trying to compete in a society where job interviews are based on DNA tests, and all along the way he is constantly being pushed down by people because he was labeled as having bad genes-- especially by his brother, who was born several years after him perfect. Eventually he steals the identity of someone who is perfect and tries to conquer his dream of flying into a space. It's a very interesting and touching movie given the topic, and I would suggest that everyone watch it.
Of course, we can always ask Watson what he thinks about the situation:
"People say it would be terrible if we made all girls pretty. I think it would be great."
http://www.newscientist.com/article.ns?id=dn3451/
I think we are in a bit of a gray area here. The Wiki article talks about how the comparison to Hitler is unnacceptable as nothing should compare to the atrocities that Hitler brought about. The wiki article tends to focus on what the Nazi's did during WW2 (as it talks a lot about the holocaust, etc.), what it doesn't talk about is the rise of power of the Nazi's in the 30's. For example, I don't see the article mentioning anything about the persecuation and flight of Thomas Mann from the Nazis. However, what we are talking about, is the fact that GW and his administration have displayed many of the characteristics which give rise to a leader such as Hitler and a facist regime
If that doesn't work, then perhaps we can use the fact that there are some here who are supporting GW and his ways. From which, we can fall back on this exception (quoted from the wiki description):
When discussing with actual neo-Nazis, Godwin's law should not typically apply
Either way, I think we're safe.
There used to be a navy dive tank at the subbase in Groton, CT that they would train on. I can't remember the exact conditions, but they used to keep the tank at about 92 degrees F for training purposes. After around 4 hours or so of training in the tank, they had to take a break to warm up. Water syphons heat away from the body much faster than air does-- I'm not sure there's any spot where he could swim across at where he wouldn't need some kind of wetsuit for.
There is an interesting memory approach called Image streaming that deals with conjuring memories that you didn't think ever happened. The odd thing about it is that many times the things you forgot actually get remembered(and not fake memories). It makes one wonder if indeed we actually ever forgotten them at all or just misplaced them.
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http://www.geocities.com/Athens/Forum/6243/imstri
You can laugh and not believe it at all, but Image Streaming is remarkeably effective in remembering events you think you had forgoten. For you can start with an old childhood memory of a person but not remember exactly what they looked like. After a period of time streaming and describing what they looked like you can build up the image of the person that you thought you had forgotten. It's like putting together the peices of a jigsaw-puzzle. You start off with a little bit, but you slowly add peices to the puzzle. As time goes on and you see more of the puzzle you find peices that you thought you lost. Eventually, you get to see the whole puzzle.
It is also quite effective in creativity and random guessing. I was actually quite suprised at how much easier it is for me to come up with ideas or solutions that I would never have thought of before. Once you really get into it you'd be suprised how effective it actually is, and following the mental progression of images to some solution is quite remarkeable. If you don't believe me, check your local library and pick up the book and read the first few chapters. Try it for a week or two, and if you still don't believe it put it down. I bought the book more for shits and giggles between undergrad and grad but was quite suprised with the results and my creativity afterwards.
Knocking out A would disrupt C, E, F. But C is the only direct product of A-- E, and F are downstream of A. There is a difference between being directly connected to a gene in a gene regulatory network and just being downstream of a gene. The problem is that by decreasing the genes you'e increased the length of the downstream interactions. Which means that knocking out a certain gene can have adverse effects on a large number of other genes that just happen to be downstream of it. You know that A affects other genes but by how much, and how further downstream is that gene? Add in varying kinetic rates and thousands of other sub-networks and you have a very messy picture.
When there are a lot of genes, knock outs aren't too bad as the genes only interact with a select few other genes and you don't have such a large downstream cascade. The real problem lies in the fact that we don't have the biological tools to collect the data that we need to actually figure out how these networks are composed. It's a very cumbersome process. And even when we have had simulated data of what we actually need, 90% of the expression levels you analyze aren't even relevant to your subnetwork, and you get a lot of false positives due to pure randomness in other genes.
The problem is that having many downstream genes increases the complexity of the biologist to gather meaningful data to be analyzed. Bioinformatics/Computational Biology rely on the biologist to provide the data. Since the biologist's job just got harder, so also did the Bioinformatasist/Computational Biologist's.
I was suprised by this article actually:
http://www.aaas.org/spp/rd/caprev04.htm
Earlier in the year many scientists who analyzed Bush's proposed budget expected him to cut areas of research by 8% while increasing DOD funding in an effort in balance the budget. It seems by these charts that we have actually increased funding. Most of which goes into DoD and Homeland security, but suprisingly even NSF, NIH had some increases. Not enough to really compensate for the amount of underpaid post-docs/graduate students who get tired of the rat race and dog-eat-dog world of academia and leave, but modest nonetheless.