The Royal Society of London is celebrating the 350th anniversary of its Philosophical Transactions, the world's oldest scientific journal. The journal has pioneered many of the features that we associate with scientific journal publishing, such as peer review, establishing priority, archiving, and dissemination. The journal evidently was founded in 1665 by the Society's secretary, Henry Oldenburg.
This Royal Society blog post by Julie McDougall-Waters provides some context to the celebration. DTLR joins in congratulating the Royal Society in celebrating this anniversary.
Tuesday, December 2, 2014
Thursday, November 6, 2014
Journals unite for reproducibility: DTLR is pleased!
Today Nature and Science posted joint editorials (here and here) endorsing a Proposed Principles and Guidelines for Reporting Preclinical Research, posted at the U.S. National Institutes of Health. It is the product of a June, 2014, workshop sponsored by NIH and the two journals, and endorsed by over 30 other biomedical journals. It provides a bare minimum list of criteria for good reporting practices of animal experiments in biomedical research. The list is less detailed than one given by Landis et al. (2012) which they cite.
DTLR joins in endorsing the proposed principles and congratulates all the participants for taking a major step forward in promoting reproducible research. It reflects a discipline-wide concern about the metastasis of non reproducible research across the spectrum of journals, as abundant evidence has made clear in recent years. The proposed principles emphasize study design issues such as randomization, blinding, sample size, and appropriate replication. Appropriately, such issues receive more space than analysis. (The use of the term "inclusion/exclusion criteria" is a little confusing here - in clinical research, this refers to patient enrolment criteria; but the authors here seem to use it to refer to selective reporting and data omission, certainly an important issue, but one I would have found other language to describe.) The sharing of data sets and the full disclosure of biological reagents are also welcome features. In general, materials and methods sections of papers really should be expanded such that an independent laboratory could reproduce the experiment and expect to obtain similar results.
DTLR does not believe that the proposed principles go far enough, however. For instance, the section on statistics requires a disclosure of "the statistical test used"; the fact that the emphasis here is on a statistical test rather than an estimation procedure is a serious oversight, in my view. The reporting of confidence intervals instead of tests provides a sense of magnitude and direction that is lacking in a p-value, allowing evaluation of both clinical and statistical significance. A statistical test outcome only communicates statistical significance. A confidence interval implicitly reports a test result when the confidence limits are compared with zero (for a conventional null hypothesis test). Other types of estimation (tolerance intervals, prediction intervals) may be more appropriate in some situations.
DTLR is glad to see a growing consensus in the scientific community that nonreproducible research is corrosive and must be reduced. This is a terrific step forward, but just one step. Now, individual laboratories must take these guidelines to heart and use them to improve the design, execution, analysis, and reporting of their studies.
Nature, vol. 515, p. 7 (2014).
Science, vol. 346, p. 679 (2014).
S. C. Landis, et al., 2012: A call for transparent reporting to optimize the predictive value of preclinical research. Nature, 490: 187-191.
DTLR joins in endorsing the proposed principles and congratulates all the participants for taking a major step forward in promoting reproducible research. It reflects a discipline-wide concern about the metastasis of non reproducible research across the spectrum of journals, as abundant evidence has made clear in recent years. The proposed principles emphasize study design issues such as randomization, blinding, sample size, and appropriate replication. Appropriately, such issues receive more space than analysis. (The use of the term "inclusion/exclusion criteria" is a little confusing here - in clinical research, this refers to patient enrolment criteria; but the authors here seem to use it to refer to selective reporting and data omission, certainly an important issue, but one I would have found other language to describe.) The sharing of data sets and the full disclosure of biological reagents are also welcome features. In general, materials and methods sections of papers really should be expanded such that an independent laboratory could reproduce the experiment and expect to obtain similar results.
DTLR does not believe that the proposed principles go far enough, however. For instance, the section on statistics requires a disclosure of "the statistical test used"; the fact that the emphasis here is on a statistical test rather than an estimation procedure is a serious oversight, in my view. The reporting of confidence intervals instead of tests provides a sense of magnitude and direction that is lacking in a p-value, allowing evaluation of both clinical and statistical significance. A statistical test outcome only communicates statistical significance. A confidence interval implicitly reports a test result when the confidence limits are compared with zero (for a conventional null hypothesis test). Other types of estimation (tolerance intervals, prediction intervals) may be more appropriate in some situations.
DTLR is glad to see a growing consensus in the scientific community that nonreproducible research is corrosive and must be reduced. This is a terrific step forward, but just one step. Now, individual laboratories must take these guidelines to heart and use them to improve the design, execution, analysis, and reporting of their studies.
References
Nature, vol. 515, p. 7 (2014).
Science, vol. 346, p. 679 (2014).
S. C. Landis, et al., 2012: A call for transparent reporting to optimize the predictive value of preclinical research. Nature, 490: 187-191.
Sunday, August 17, 2014
Evolution of airplanes: a follow-up
I thank Prof. Bejan for graciously replying to my critique of his work in a previous post. Permit me to follow up briefly here.
Bejan is correct that his earlier publications have cited Tennekes and the others. He is also right that the earlier writers did not include land and aquatic locomotion in their analyses. I was aware of Bejan's 2006 paper with Marden (which cites Tennekes only as a data source, not for analysis) but have not seen his 2000 book published by Cambridge U.P. I thank Prof. Bejan for clarifying these points, although my original post did make many of them already.
Nonetheless, Bejan's 2014 paper makes a specific point about the Concorde case, which Tennekes has discussed at length, as I showed. A citation in Bejan's 2014 paper in the context of the Concorde discussion would have been pertinent for readers. As it stands, the 2014 paper makes it seem that the 'outlying' nature of the Concorde on the diagram is a new finding, when it is not.
Bejan's comment also offers a very important distinction, one that I strongly affirm. A purely empirical analysis of observational data is a wholly different activity to first-principles modeling of such data, especially when the latter is then validated by empirical data. Many scientists indeed fail to appreciate this distinction. However, the quantitative predictive modeling in Bejan's 2014 paper seems to be based on basic aerodynamic scaling arguments. The link with evolution seems at best a metaphor; it is not clear to me that the evolutionary component of Bejan's work is predictive in any quantitative sense. I stand by my previous comments on interpreting data, particularly the pteranadon case. Being an outlier on the graph does not prevent the pteranadon for being fit for its ecological niche in its day. This would seem to limit the scope of the evolutionary metaphor when linked to specific aerodynamic scaling arguments. My methodological criticisms of correlation analysis also remain valid.
Bejan is correct that his earlier publications have cited Tennekes and the others. He is also right that the earlier writers did not include land and aquatic locomotion in their analyses. I was aware of Bejan's 2006 paper with Marden (which cites Tennekes only as a data source, not for analysis) but have not seen his 2000 book published by Cambridge U.P. I thank Prof. Bejan for clarifying these points, although my original post did make many of them already.
Nonetheless, Bejan's 2014 paper makes a specific point about the Concorde case, which Tennekes has discussed at length, as I showed. A citation in Bejan's 2014 paper in the context of the Concorde discussion would have been pertinent for readers. As it stands, the 2014 paper makes it seem that the 'outlying' nature of the Concorde on the diagram is a new finding, when it is not.
Bejan's comment also offers a very important distinction, one that I strongly affirm. A purely empirical analysis of observational data is a wholly different activity to first-principles modeling of such data, especially when the latter is then validated by empirical data. Many scientists indeed fail to appreciate this distinction. However, the quantitative predictive modeling in Bejan's 2014 paper seems to be based on basic aerodynamic scaling arguments. The link with evolution seems at best a metaphor; it is not clear to me that the evolutionary component of Bejan's work is predictive in any quantitative sense. I stand by my previous comments on interpreting data, particularly the pteranadon case. Being an outlier on the graph does not prevent the pteranadon for being fit for its ecological niche in its day. This would seem to limit the scope of the evolutionary metaphor when linked to specific aerodynamic scaling arguments. My methodological criticisms of correlation analysis also remain valid.
Tuesday, August 12, 2014
The "evolution" of airplanes: DTLR is not impressed
About three weeks ago, the Journal of Applied Physics
published a paper by Adrian Bejan and collaborators, “The evolution of
airplanes” (Bejan et al., 2014). Bejan
is a named professor of mechanical engineering and materials science at Duke
University, and author of well-known textbooks on heat transfer and
thermodynamics. His co-authors are a
Boeing engineer and Duke alum, Jordan Charles, and a French civil engineering professor, Sylvie Lorente, who is also an adjunct Duke professor. The publisher and Bejan’s university both
issued news releases about the paper, and Bejan wrote about his work at The
Conversation. Indeed, the paper has
received a lot of online press coverage.
The publisher’s own Inside Science news organ did include some critical
comments in its coverage; additional critical comments were also posted at The
Conversation in response to Bejan’s post.
The criticisms focus on the overall logic and philosophy of the
paper. I strongly sympathize with these
criticisms. Here, however, I will provide an additional perspective beyond those aired by others thus far.
The paper presents a number of
simple analyses including basic aerodynamic scaling arguments, compared favorably
with empirical data about aircraft geometry and performance. A
particularly vivid graph in the paper shows empirical data comparing the body
mass and velocity of airplanes with those of running, flying, and swimming
animals. The diagram (the paper’s Fig.
2) is reproduced below.
The Ref. 1 in the caption is Bejan and Marden (2006). The authors make the point that the Concorde is an outlier
in this diagram, and further comment as follows.
Looking at the graphs of this paper, we see that there is an outlier, the Concorde, which was perhaps the most radical departure from the traditional swept wing commercial airplane. The Concorde’s primary goal was to fly fast. In chasing an “off the charts” speed rating the Concorde deviated from the evolutionary path traced by successful airplanes that preceded it. It was small, had limited passenger capacity, long fuselage, short wingspan, massive engines, and poor fuel economy relative to the airplanes that preceded it. Even when it was in service, the Concorde did not sell, and only 20 units were ever produced (whereas successful Boeing and Airbus models were produced by the thousands). Eventually, due to lack of demand and safety concerns, the Concorde was retired in 2003. (Bejan, et al., 2014, p. 6.)
Except for the remark about the "evolutionary path", all of this is factual. However, many of these observations are not
original. In a book published originally
in Dutch in 1992, Henk Tennekes (2009) presents the following graph (his Fig.
2) comparing cruise speed and body weight; in the graph he tacitly ties cruise
speed to wing loading (weight divided by wing surface area). Although it does not include running and
swimming animals, the graph is otherwise similar in spirit to Bejan et al.’s graph.
Tennekes attributes this sort of analysis to the former
DuPont company head, Crawford H. Greenewalt, and later scholars, including Colin J. Pennycuick. Greenewalt’s
original analysis was published in 1962; see Tennekes (2009) for citations and
sources of data. Tennekes also derives a
simple scaling formula relating wing loading to cruise speed. The equation 2 referred to in the caption is a version of this scaling formula.
What does Tennekes have to say about the Concorde? In Chapter 1, he writes the following.
Wasn’t it supposed to fly at about 1,300 miles per hour? How come it didn’t have higher wing loading and therefore smaller wings? The answer is that the Concorde suffered from conflicting design specifications. Small wings suffice at high speeds, but large wings are needed for taking off and landing at speeds comparable to those of other airliners. If it could not match the landing speed of other airliners, the Concorde would have needed special, longer runways. The plane’s predicament was that it has to drag oversize wings along when cruising in the stratosphere at twice the speed of sound. It could compensate somewhat for that handicap by flying extremely high, at 58,000 feet. Still, its fuel consumption was outrageous. (Tennekes, p. 18)
And in the preface, Tennekes writes:
The Concorde went out with a bang. A fiery crash near Paris on July 25, 2000, signaled the end of its career….In retrospect, the Concorde was a fluke, more so that anyone could have anticipated. From an evolutionary perspective it was a mutant. It was a very elegant mutant, but it was only marginally functional. The fate of the Concorde inspired me to draw parallels between biological evolution and its technological counterpart wherever appropriate. (Tennekes, p. xii)
Tennekes has more extensive comments on the Concorde in
Chapter 6. At his doctoral thesis
defense, he argued “that supersonic airliners would be a step backward in the history
of aviation” (p. 165). He explains that with
supersonic flight, the aircraft would have to generate shock waves in the air,
which requires “a lot of energy” (p. 166). On the same page,
Although Concorde passengers didn’t notice anything as their plane penetrated the sound barrier, the economic barrier was real enough. If you want to exceed March 1, it will cost you 3 times as much as staying below the speed of sound. For the aircraft industry, supersonic flight was indeed a step in the wrong direction. Time and again, before aeronautical engineers started dabbling with supersonic flight, they had managed to reach higher speeds and lower costs. The Concorde broke that trend.
I think it is unfortunate that both Bejan and Tennekes are
tempted by the evolutionary metaphor; the critical comments I alluded to in my
opening paragraph zero in precisely on this aspect of the work, as well as
Bejan’s “constructal law” which he also purports to be at work here. (I won’t bother to discuss that aspect further.) Nonetheless the authors are correct that the
empirical data and aerodynamic scaling relationships are consistent with each
other, and possibly of limited use and interest. They should not, however, be used to narrow one’s thinking. For instance,
in Tennekes’ plot, a number of animals show up as more severe ‘outliers’ than
the Concorde. Tennekes states that deviations
from the trend line may be justified.
The pteranadon, for instance, was a soaring animal. In prehistoric times there were no polar ice
caps, reducing the atmospheric temperature gradient between the poles and
equator, compared to today. As a result
there was less wind back then. He
presents other examples, including aircraft.
More generally, just because the bulk of the data fall along a trend
line or curve, data away from that trend should not necessarily be
deprecated. Furthermore, correlation
should not be confused with causation. Bejan
et al. (2014) offer no such nuances or caveats in their discussion. Consequently they exaggerate the importance and implications of their findings.
It is also of great concern that Bejan et al. (2014) do not
cite, either in the main paper or their supplemental information, Tennekes' work, particularly in the context of the Concorde discussion. This is unusually poor
scholarship. (Bejan does cite Greenewalt and Pennycuik in an earlier paper, Bejan and Marden, 2006.) Bejan et al. (2014) also
make pointless, tautologous statements such as “Small or large, airplanes are
evolving such that they look more and more like airplanes, not like birds” and
then in the next paragraph, “Small or large, airplanes are evolving such that
they look the same.” Their abstract ends
with the non-sequitur, “The view that emerges is that the evolution phenomenon
is broader than biological evolution.
The evolution of technology, river basins, and animal design is one phenomenon,
and it belongs in physics.” Such statements are unjustified, unhelpful, and provide heat rather than light to the discussion.
A technical point should also be made: at one point, Bejan et al. (2014) comment on
their data analysis that “the correlation is statistically meaningful because
its P-value is 0.0001, and it is less than 0.05 so that the null hypothesis can
be rejected”. This is a fairly naive and
unimpressive statement. The 0.05
threshold is conventional but totally arbitrary; moreover, the null hypothesis
is one of no correlation at all, which is an incredibly low bar to establish a “meaningful”
relationship between two variables.
Statistical significance does not necessarily convey practical
significance. For instance, it is possible to make a relationship with a negligibly small slope "statistically significant" if the sample size is large enough. Reporting any kind of statistical inference (the p-value) on observational, non-randomly sampled data is itself questionable. Moreover, as Loh (1987)
noted, the correlation coefficient does not actually measure the closeness of
the data to the best fit line. The
fitted equation and coefficient of determination, which the authors do provide,
are more meaningful measures of the strength of the relationship between two
variables. The great statistician John Tukey (1954) stated that "most correlation coefficients should never be calculated."
To conclude, the publication of Bejan et al. (2014) in the
Journal of Applied Physics is questionable.
The work should instead have been submitted for review at an
aerodynamics or aerospace engineering journal. I suspect it might
not have impressed reviewers in that community.
Moreover, the authors should have cited Tennekes (2009) who provides a more detailed and nuanced discussion of the Concorde case, and they should increase the care with which they interpret
correlations in empirical data. I think the rhetoric about evolution is superfluous and distracting from the authors' primary technical findings, and should have been dispensed with. Other critics have focused their views on this last point, so I've not dwelt on it here.
References
A. Bejan and J. H. Marden, 2006: Unifying constructal theory for scale effects in running, swimming, and flying. Journal of Experimental Biology, 209: 238-248.
A. Bejan, J. D. Charles, and S. Lorente, 2014: The evolution of airplanes. Journal of Applied Physics, 116: 044901 (6 pages).
Wei-Yin Loh, 1987: Does the correlation coefficient really measure the degree of clustering around a line? Journal of Educational Statistics, 12: 235-239.
Henk Tennekes, 2009: The Simple Science of Flight: From Insects to Jumbo Jets. Revised and expanded edition. MIT Press (Cambridge, MA).
John Tukey, 1954: Causation, regression, and path analysis. In Statistics and Mathematics in Biology, edited by O. Kempthorne, T. A. Bancroft, J. W. Gowen, and J. L. Lush. Iowa State College Press (Ames), 35-66.
Thursday, July 3, 2014
Congratulations to Alvin
Last month, the Deep Submergence Vessel (DSV) Alvin celebrated its 50th anniversary of service to oceanographic research. As Humphris et al. (2014) note, Alvin is "the world's first deep-diving submarine and the only one dedicated to scientific research in the United States." Named after geophysicist Allyn Vine, the half-century old submarine is returning to service after a major upgrade this year. I recommend the article by Humphris et al. (2014) for readers interested in learning about the history of this unique vessel.
S. E. Humphris, C. R. German, and J. P. Hickey, 2014: Fifty years of deep ocean exploration with the DSV Alvin. Eos, Transactions, American Geophysical Union, 95 (22): 181-182.
Reference
S. E. Humphris, C. R. German, and J. P. Hickey, 2014: Fifty years of deep ocean exploration with the DSV Alvin. Eos, Transactions, American Geophysical Union, 95 (22): 181-182.
Nobel laureates and fluid dynamics research
Do Nobel laureates do research in fluid
dynamics? As far as I can tell, the Nobel Prize has been awarded
specifically for achievements in fluid dynamics exactly once, to
Hannes Alfven (Physics, 1970) “for fundamental work and discoveries
in magnetohydro-dynamics with fruitful applications in different
parts of plasma physics.” An argument could be made for
Pierre-Gilles de Gennes (Physics, 1991) who was awarded for his work
on liquid crystals, and Ilya Prigogine (Chemistry, 1977) who was
awarded for his contributions to non-equilibrium thermodynamics and
dissipative structures. These fields are at least adjacent to fluid
dynamics, with considerable overlap. However, other Nobel laureates,
who won the award for other achievements, have often either dabbled
or even made substantial contributions to fluid dynamics research.
Perhaps the most accomplished was Lord
Rayleigh (Physics, 1904), who won the prize for studies of the
densities of gases, as well as for the discovery of Argon. He made
immense contributions to the theories of fluid dynamics and
acoustics, particularly in the field of hydrodynamic instabilities.
In the latter field we find his name attached to the Rayleigh-Taylor
instability, the Plateau-Rayleigh instability, and Rayleigh-Benard
convection (not to mention the Rayleigh number). Rayleigh's
monograph on the Theory of Sound is a landmark publication in the
history of acoustics. Another Nobel laureate, astrophysicist
Subramanyan Chandrasekhar (Physics, 1983), also contributed to the
theory of hydrodynamic instability, authoring the similarly landmark
monograph, Hydrodynamic and Hydromagnetic Stability. As far as I
know, Chandraskehar is the only Nobel laureate to have served on the
executive committee of the American Physical Society's Division of
Fluid Dynamics (1954-1957, as chair in 1955; long before he won the
Nobel Prize).
The theory of turbulence is said to
concern the greatest unsolved problem of classical physics. Werner
Heisenberg (Physics, 1932) and Lars Onsager (Chemistry, 1968), both
developed turbulence theories analogous to the famous
Kolmogorov-Obukhov -5/3 law. Heisenberg, whose doctoral dissertation
was in fluid dynamics, developed his theory while detained at Farm
Hall after WWII, with Karl von Weizsacker. Lev Landau (Physics,
1962) had his own theory of turbulence, and his monograph with E. M.
Lifshitz on Fluid Mechanics is one of the best known volumes of their
Course of Theoretical Physics.
Other Nobel Laureates dabbled in
hydrodynamic research. Edward M. Purcell (Physics, 1952) wrote a
famous paper, “Life at Low Reynolds Number” (1977), and T. D. Lee
(Physics, 1957) wrote “On some statistical properties of
hydrodynamical and magneto-hydrodynamical fields” (1952). Albert
Einstein proposed a new airfoil design in 1916, although it was not
successful. Richard Feynman lectured eloquently about fluid dynamics
in two chapters of the Feynman Lectures, but as far as I know he did
not pursue research in the field.
The above musings were prompted by an
article in last week's issue of Science, co-authored by Ahmed H.
Zewail (Chemistry, 1999). The paper (Lorenz and Zewail, 2014)
concerns measurements of the motion of molten lead in a single zinc
oxide nanotube, using electron microscopy. The work is a
contribution to the young and growing field of nanofluidics.
Readers, do you know of other Nobel
laureates who have contributed to fluid dynamics or related fields?
Please leave your comments if you do.
Reference
Ulrich J. Lorenz and Ahmed H. Zewail, 2014: Observing liquid flow in nanotubes by 4D electron microscopy. Science, 344: 1496-1500.
Wednesday, May 28, 2014
Efimov trimers: a discovery in molecular physics
Quanta Magazine has an interesting feature article by Natalie Wolchover about the discovery of Efimov trimers, predicted in 1970 by Vitaly Efimov. The first reported experimental result was in 2006, but it was not considered definitive. Evidently three different groups now have posted their results, with the first paper published and the other two currently in peer review. Take a look at Wolchover's article.
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