Is veal white, pink, or red?

This is the big question of the week in Switzerland, as on the first of September the new law for the humane treatment of calves enters into effect.

When I was in the third school year, our teacher Egidio Bernasconi took us to visit the stable of our classmate Rita Spizzi. Her father was in charge of food at the private clinic Moncucco in Coremmo, just behind our school building. Besides the large vegetable garden, he also had half a dozen cows, and that was the topic of the lesson.

We learned about agribusiness. In the self-sustenance times, a farmer in the Prealps would have one or two cows to provide the proteins for his family. Spizzi's operation was larger, because it had to sustain a clinic instead of just a family.

A cow's main product was its milk, which had a shelf life of only a couple of days. The cream would be skimmed off and cultured for a few days to make butter, which had about a week of shelf life. The excess milk would be used to make yogurt, which had a longer shelf life. When there was a lot of excess milk, it would be used to make cheese, which depending on the type could last for a whole season.

When a cow would no longer produce milk due to her age, Mr. Spizzi would sell her to the slaughterhouse. This explains why the typical beef dish of the region is brasato: the meat had to be stewed for hours in a red wine sauce because it was very tough, coming from old cows.

Mr. Spizzi always needed enough cows to feed the patients and staff. Every spring he would walk his cows to the outskirts of town to visit a bull. Half of the off-spring would be female, and that was good, because Mr. Spizzi could select one to raise to replace the next old cow; the other cows would be raised to be sold at the fair. This is why Mr. Spizzi spend a little more money to use a select bull, as its offspring would fetch a higher price at the market.

For the male offspring there was not much use, because only few bulls are required. Mr. Spizzi would keep them as long as they can live on their mother's milk, then sell them to the slaughterhouse. Because these calves were young and milk-fed, their meat was whitish. By the way, this is why in the Insubrian culture the fancy meat is veal scaloppine.

This was a long time ago and in modern agribusiness a farmer has an order of magnitude more cows. Also, much progress has been made in cattle feed, so the farmer can make more money by feeding his calves for a longer time, yielding more meat.

This is where the animal protection groups come in and the new law for veal comes into play. When the calves are kept alive for a longer time, they would naturally eat hay and grass, roaming on the Alps. Their meat would become reddish. Although taste and nutritional value are the same, for centuries people have known that the whiter the veal, the more it was tender. Before the new law, a farmer would have been paid less per kilo if the veal was redder.

To keep the veal whiter, the contemporary farmer would keep his animals on milk and indoors, but this means that the calves are anemic and therefore tortured.

The current debate is on whether veal should be red, pink, or white. This is where color science comes into play. Instead of using color terms, the experts want to sound more authoritative by using numbers rather than words. Instead of red, pink, white, they use 38, 42, 48. They never mention a unit, so what are these numbers? Is there a new redness scale?

It turns out that the new law also introduces a new standardized method to determine the color of veal. The carcass is measured at a specified location near the shoulder with a Minolta colorimeter. The first number on the colorimeter is the color number for the carcass.

Zooming in on the pictures reveals that the colorimeter is displaying CIELAB data, so the first number is L*. Therefore, what the gastronome takes for red, pink, white, a color scientist would take for dark, medium, light.

Newspaper article on the debate (in German): Kalbfleisch-Knatsch in der Fleischbranche.

Generating your publication list

It is often necessary to compile one's bibliography. For example to apply for a grant or a job. One approach is to keep a text file and update it as you publish. However, unstructured data is a pain to update when you fall behind, and you anyway already have your publications in your bibliography database. Is there a quick and simple way to generate a publication list?

For those using BibDesk to manage their bibliography, the answer is Jürgen Spitzmüller's biblatex-publist package. It generates correct citations leaving out your name, sorts them by date, and allows grouping by publication type.

In the preamble you just add three items:

• \usepackage[bibstyle=publist]{biblatex}
• \omitname[your first name]{your last name}
• \addbibresource{biblio.bib}

In the document part you just add a block like below for each publication type:

• \section{Patents}
• \begin{refsection}[biblio]
• \nocite{*}
• \printbibliography[heading=none, filter=mine, type=patent]
• \end{refsection}

The citation result will look like this when set into type:

Aug. 2006 (with Audrius J. Budrys). “Multi-component iconic representation of file characteristics”. 7,086,011. Hewlett-Packard Development Company.

If you are still using BibTeX, this is a good time to update your engine. BibTeX has been obsolete for many years and is no longer used these days. People now use biblatex, and publist is just a style file for biblatex. Actually, biblatex still uses BibTeX, so you want to switch your engine to Biber.

The make the switch, in the TexShop preferences go in the Engine tab and replace the BibTeX engine bibtex with biber. It may be necessary to run the TeX Live utility to update all the packages, as there has been a bug fix in the last week.

Extra tip: Option-Go to the folder ∼/Library/TeXShop/Engines/Inactive/Latexmk/ where you find the file Latexmk For TeXShop.pdf with the instructions on how to typeset your documents with a single mouse click.

Energy footprint of the digital economy

Back in 2009 we looked at the carbon footprint of ripping color documents for digital presses and published the result in the EI 2010 paper "Font rendering on a GPU-based raster image processor." Assuming the raster image processor is run at maximum capacity, the state of the art system at the time consumed 38,723 KWh and generated 23,234 Kg of CO₂. By using GPUs, we were able to rip the same data with 10,804 KWh respectively 6,483 Kg of CO₂. At the time we thought saving 16,751 Kg of CO₂ per year per RIP was a pretty cool result, but at the end the product never shipped, despite — or maybe because — it was much lower cost. (See the paper for the details of the calculations.)

This month the Digital Power Group published the white-paper "The cloud begins with coal: big data, big networks, big infrastructure, and big power." The work was sponsored by the National Mining Association and the American Coalition for Clean Coal Electricity, which explains why some of the numbers appear a little optimistic in terms of the coal needed to keep the smart phones running and serving contents, but even if we divide the numbers by 5 to make them a little more realistic, the numbers are quite staggering when we add everything up. It turns out, that a smart phone requires as much coal as a small refrigerator. Cloud computing will consume an ever increasing fraction of our total energy consumption. This is a good reason to work on more efficient and greener storage systems.

Data Privacy

During the ascent of Nazism in Europe in the decade before world war II, the Swiss banks introduced secret bank accounts to hide the identity of persecuted customers from infiltrated spies working at the banks or loitering in their lobbies. After the war, this mechanism was abused by the banks to assist tax evaders and consequently has been largely dismantled.

Apparently, the Swiss have been able to maintain their reputation as a discreet country. An echo effect of the leak of an American agency's penchant for snooping everybody's data, is that more entities are now storing their data in Switzerland, although data storage in Switzerland is about 25% more expensive than in the neighboring EU countries. "Our customers know that money can be replaced — but sensitive data can not," says Mateo Meier of Artmotion, a data center in Zürich. Switzerland's know-how, political stability and adequate infrastructure are ideal conditions to store data securely, he says.

History does not repeat itself, and the Swiss have learned from the mistakes related to bank secrecy: there are no privacy rights for suspected felons and their data.

Newspaper article: Schweizer Datentresore sind nicht sicher

Color can prevent shark attack

A Western Australian company has used pioneering research by leading University of WA shark experts to develop wetsuits designed to confuse sharks or render surfers invisible to the predators. The world-first shark repellent suits are based on discoveries by Associate Professor Nathan Hart and Winthrop Professor Shaun Collin, from UWA's Oceans Institute and School of Animal Biology, about how predatory sharks see and detect prey. The suits use a specific combination of colours and patterns to deter the creatures. One design — known as the ‘cryptic' wetsuit — allows the wearer to effectively blend with background colours in the water, making it difficult for a shark to detect or focus on the wearer. The other design — the ‘warning' wetsuit — makes the user appear highly visible by using disruptive and high contrast banding patterns to make them appear totally unlike any normal prey, or even as an unpalatable or dangerous option. The designs also come in the form of stickers for the undersides of surfboards. While the company Shark Attack Mitigation Systems could not claim the suits were a failsafe protection against shark attacks, results from initial testing of the wetsuits in the ocean with wild sharks had been ‘extraordinary'.

Original article: UWA science leads to world-first anti-shark suits

See also Why are animals colourful? Sex and violence, seeing and signals

Skin-Whitening

In Japanese culture a white skin is an important component of female aesthetics. In the old days, maikos applied a thick white base mask that was made with lead, but after the discovery that it poisoned the skin and caused terrible skin and back problems for the older geisha towards the end of the Meiji Era, it was replaced with rice powder.

At the end of 2007 it appeared that the cosmetics industry had finally invented a skin whitening product that is both safe and convenient, as we reported in this blog in a whiter shade of pale. Unfortunately it now appears this Rhododenol product is unsafe after all.

2,250 users of Kanebo Cosmetics Inc. skin-whitening cosmetics have reported developing serious symptoms such as white blotches on their skin. Serious effects of the products include depigmentation in an area of at least 5 cm and depigmentation in three or more areas of the body, as well as clearly visible depigmentation in parts of the face. In total, the company has received more than 100,000 inquiries in connection with the recall.

The product in question is named "Rhododenol." Kanebo earlier said it has been marketing cosmetics that use the ingredient as an active substance since 2008 via various retail outlets. The company said it has secured the cooperation of the Japanese Dermatological Association in getting a list of medical facilities which will treat the symptoms posted on the association's website. Kanebo Cosmetics Inc.'s voluntary recall of its skin-whitening line is likely to deal a crippling blow not only to its brand image but also to its parent Kao Corp. It will not be easy to restore the image of the damaged brand. The recall became more damaging due to Kanebo's delayed response.

NIH To Fund Big Data Projects

Biomedical research is increasingly data-intensive, with researchers routinely generating and using large, diverse datasets. Yet the ability to manage, integrate and analyze such data, and to locate and use data generated by others, is often limited due to a lack of tools, accessibility, and training. The National Institutes of Health announced that it will provide up to $24 million per year for the new Big Data to Knowledge (BD2K) Centers of Excellence. This initiative supports research, implementation, and training in data science that will enable biomedical scientists to capitalize on the transformative opportunities that large datasets provide.

Press release: NIH commits $24 million annually for Big Data Centers of Excellence

Web site: NIH Big Data to Knowledge (BD2K)