Superespecialization is a (post)modern disease

Every scientist knows a colleague who is expert in some subject. Probably this person is an erudite in this subject, and is able to discuss this matter with the other experts in that matter in all world. This person is, however, unable to discuss any other subject. The Germans have a term for this: Fachidiot (translated as something like "idiot specialists").
The colleagues in Pedagogy usually blame (at least here in Brazil) the Napoleonic university reform for this state of affairs and state that it is post-modernism that is changing this.
I always doubted this. If we go back to the XIX century and see the biography of people like Euler, Rankine, Faraday, Darwin, we see that they were far from being specialists in just one subject. They were all polymaths.
I read recently an article about Heisenberg and discovered, not as far as the early XXth century, that he had a hard time getting his title (Dr rer nat) because he had problems with experimental physics. So he was expected to understand things other than the subject of his thesis to obtain the title.
I guess the superespecialization is a recent phenomenon. If you are a university professor like me and does not wish ending up as a "Fachidiot" here is my advice: try teaching something outside your area of expertise. You will find out it is funny to learn something new and that, with your intelligence, you will discover connections with yout own research field, perhaps even something innovative.

The Battle Between Zirconium Alloys and Stainless Steel as Cladding of Nuclear Reactor Components: Part One.

A worthy research has been performed at Escola Politécnica (EPUSP) of the University of São Paulo to process, compile, compare and advance the best literature data about metallurgical and physical properties of irradiated Zirconium alloys and austenitic Stainless Steels.

The nuclear reactor environment is very harmful to the cladding materials, pressure vessel and other major components present in its surroundings. Why? Fast and slow neutrons acts like a massive bullet when it impinges towards a crystalline structure. As effect of that collisions, the metal or alloy crystalline arrangement experiences a gradually degradation and the materials loses its main mechanical properties.

These efforts resulted in a new research group to integrate the several works that have been carried out at EPUSP in the field of Nuclear Materials: Advanced Nuclear Materials Research Center (NUCMAT).

In this blog we will share information about our research, results and data regarding studies that will be developed in the next months. The first paper is an upcoming work that we will publish in the congress of ABM (Associação Brasileira de Metalurgia, Materiais e Mineração) entitled: “Comparative Framework of Zirconium Alloys and Austenitic Stainless Steels Structural Integrity under Neutron Irradiation”.

We hope that you worldwide scientists post comment about our work giving suggestions for improvements.

Inertia: the hidden field

I was travelling in a bus on the streets of São Paulo, a living laboratory of inertial forces, and I was wondering about the weirdest of all Newton's laws: the first.
Imagine the following situation: a closed room with a subject inside (let us call him the Schrödinger's cat for simplicity's sake). Without his knowledge this room is in fact a vehicle, which is perfectly insulated from vibration and all forms of sound. The room starts moving and begins a curve.
The cat, inside the room, will sense mysterious force field acting over his body.
The strange nature of inertia arises, in my opinion, that this "field" has no source. Gravity is generated by mass, the Coulomb field is generated by charge, even the nuclear strong qnd weak forces have their own souces. Inertia doesn't. However, this becomes ever weirder.
Back in college I wrote my first paper (for the Physics Lab., equivalent to Experimental Physics 101) on the subject of the identity between inertial and gravitational mass.
Inertial mass is the ratio berween a force acting over a body and the acceleration it produces, which can be precisely determined in an elastic colision experiment. Gravitational mass is the ratio between gravitational force and gravity acceleration, which is related to the spacetime curvature, which can be precisely determined in a free fall experiments. There is no sensate reason to assume that both things are the same.
I remember when I wrote that paper (30 years ago) someone (I believe it was Einstein, but I am not sure) tried to justify this equality using Mach's principle, which, as far as I could understand, meant that inertia is created by the gravitational attraction of all mass im the Universe (the reference frame of the fixed stars).The problem is, after relativity we know that the fixed stars are not even there where we see them. I see another problem with this idea: there is no time delay between the change in movement and the onset of inercial forces. If inertia originates from the interaction between the body and faraway masses, shouldn't this imteraction obey the restriction of the light speed?
I know I'm writing about quite specialized things I didn't study, and worse, writing with the memory of a 1st year physics bachelor student of 30 years ago, but anyway I believe there is something very fundamental about Nature hidden in these weird properties of inertia.

Public opinion polls

There will be elections in Brazil in 2014. This time we will elect the president, the state governors, part of the senate, the congress and the state assemblies. Due to Brazilian law, open campaign is still prohibited, but some movement already started. For example, everybody knows that president Dilma Roussef will apply for reelection and there are two declared "opposition" candidates. In this context the public opinion polls acquire a great importance. According to these polls, President Dilma is frankly favorite  to win the election in the first turn and her adversaries barely reach  16%  and 12% of the "vote intentions".

A recently published poll gained considerable attention in Brazil. Two different polls organized by the same institute (IBOPE, short for "Brazilian Institute for Public Opinion Research") gave different results concerning the same population, in one of the polls Pres. Dilma would have about 43% of vote intentions, while in the second  this number would be 38%.

There was a fuzz in the social networks about this result, first because the News Services (which are in the majority supporting the opposition) published headlines like "President Dilma fell in the IBOPE poll!". There was an outcry from Pres. Dilma's supporters because they  insinuated political use of the result (which is obvious), because the former poll range extended for a longer period and ended after the second poll (which gained full coverage from the press).

Apart from the political use of such results, one should look at the problem with a scientific point of view. What is a public opinion poll?

The answer to this question is: a statistical inference measure.

Let us consider what is in fact a poll. This process probes one population (the country voters) extracting a small sample and probes one question. Let us remain simple, let us suppose the question is binary, having only two possible outcomes. As every math, physics, engineering student learns, this problem is equivalent to probing a box containing a large number of pebbles colored black and white. Supposing the fraction of white peebles is p, that the sample size is N, the number n of white pebbles in the sample will be given by the Binomial probability distribution:

Let us look what this means for a typical sample size used in these polls (N=2600) and let us assume p=0.38 (that is, the population is composed of 38% of white pebbles). The result is given by the red line in the figure below.

 The fact that we measured p=0.38 means that we actually drew 988 white pebbles in the 2600 sized sample, but let us come back a little and ask before the measure what would be the probability to draw 988 pebbles provided p=0.38. This number is f=0.01612 (that is 1.6212%). Let us suppose now our measure of p is wrong and it is actually larger (it could be smaller too). I plotted in the figure (blue line) what would be the result if p=0.40. The probability to draw 988 white pebbles in this case would be f=0.00182 (or 0.182%). It looks small, but it is actually more than 1/10 of the ideal value. In fact, if we drew 100 N=2600 samples out of the box, any result between ~960 and ~1020 would be likely obtained in p=0.38.

Everybody who works with statistical inference knows this fact. In a statistical measure we will never be fully confident in the result. We will always run into the possibility to commit two types of errors, the first error, called "type I" error means that you accepts as true a proposition that is actually false, in the present case, that assuming p=0.38 is wrong. This is the origin of the "confidence interval" concept, which most laymen know as "error margin". There is, however, the type II error, which is rejecting a statement which is actually true, in the present case, rejecting p=0.40 after drawing 988 white pebbles. The type II error is more difficult to control and one could easily loose track of it if one tries to circumscribe the type I error to low probability values.

The determination of the confidence interval to this problem usually requires approximating the binomial distribution by the normal distribution (which is a good hypothesis in the present case) or maybe using more sophisticated methods, like using bayesian inference, but one should take care not to use the central limit theorem here, since the number of samples is actually 1.

Therefore the result of a public opinion poll is simply a (educated) guess. Its results must be analysed with care and never in the way described above (the "conclusion" that president Dilma is falling in the public preference). This use of statistics is simply political misuse. Naturally all this analysis is based on one premise, namely, that the sample is extracted from an homogeneous population. In my opinion this is one of the largest failures in the public opinion polls. I believe it is possible to fraud a public opinion poll by carefully choosing the place and the time in which the interviews are made. Naturally there are protocols which have to be followed, but even so, I believe one can direct the answers depending on the will of the institute. Naturally in a civilized country, a public opinion institute which resorts to this kind of strategy would end up loosing credibility, but the one sided nature of the Brazilian Press will surely ensure that any misuse of the public opinion polls will be unpunished.

Multicausal failures

We all are aware of failures that are caused by a single event. From the point o view of engineering these are lucky cases, since controlling these events, the failure can be prevented. Engineering project usually assumes this hypothesis for this purpose. For example, the maximum stress level of a structure is calculated based on the yield or fracture stress of the individual components, some parts in airplanes are designed such that the cyclic stress intensity factor does not exceed the fatigue threshold level measured in a Paris plot.
There are, however, cases in which the failure is caused by multiple critical events happening in series or in parallel simmutaneously or not. The most famous example was the fire in the Kiss club in Santa Maria-RS, Brazil, last year. The causes ranged from corrupt city officials and firemen, who alloed the place to open without minimal safety conditions, greed by the owners, which led to bad material's selection of the foam used for acoustic insulation,which produced HCN when burnt, and the stupidity of the band members, who lit inappropriate fireworks in a closed space. Any of these events, if they were avoided, would prevent the tragedy too.This went surely through the mind of all people involved, but they surely decided that the probability of everything going wrong in the right sequence in the right time was too low to consider. The tragedy is there to prove they were wrong.
In fracture as Prof. Bažant teaches, this leads to two different failure propability distributions. In case of a single critical event (as in cleavage), the probability is described by the Weibull distribution. In the case the failure is a consequence of infinite individual critical events, like ductile fracture by microvoid coalescence, this leads to the gaussian distribution. There are also intermediate cases. The point here is to remind that multicausal failures do exist. They require nonlinear thinking by the engineer, who is forced to consider not only what could go wrong, but also in which sequence and in which time.
Worse, as I repeat to exhaustion to my students, when you decrese the probability of the unicausal failure, the multicausal failure becomes increasingly more probable.

Science or mysticism?

We are always criticising opinions and interpretations which lack the rigour of the scientific method, but how do we defend science to theordinary public? I remember reading in a book (don't remember which) the following critiscism: everyone of us believes in the first law of thermodynamics, because we were told it holds the most careful tests made until today, but only a handful scientists in the whole world are able to understand and interpret these tests. The majority of the population feels confortable with believing in science just because someone with a lab coat said it is science.

The h index

I was explaining to a.colleague how to calculate.the h index of our department, since he got surprized that an emmeritus professor of our department (who does not publish too much) appears three times in the list of the 34 most quoted papers. I explained that this is a problem of the h index (if II remember well, Hirch pointed to this in his paper): it gives too much value to old published papers, which, due to their long lives, received lots of citations. Then I got the idea of using a time-dependent h index, let us say, based on the list of papers published in a given time span (for example, the last three years). This will give a best estimate of the citation strength os a set of researchers. Of course, this time-dependent h index may be artificially inflated by the own researcher citing his own papers, thefore I suggest introducing a secondary index, which I call the citation strengrh, which is the number of citations (full) divided by the citations excluding self-citations. In my opinipn this index computes the probability that an article published by that author is cited by someone else. I would like to hear your opinion about this idea.