Velocomp has just released its latest product, the iBikeDash. The cycling computer requires an iPhone or iPod touch, as it’s largely an app (free) but also includes a Phone Booth housing for the Apple device that keeps it out of the worst the environment has to offer. It’s also shockproof and is bundled with an ANT+ speed sensor with optional sensors for cadence and heart rate.
The app includes 50 power-based and Heart Rate zone workouts and will measure speed, power, heart rate, wind speed, time, trip, elevation and calories to help users reach their fitness goals. It keeps users safe by helping riders be safe by helping them stay within the right zone.
There is also a power-based indoor trainer feature, a bike odometer and a calendar feature that keeps track of workouts, calories, miles and speed. There are also on-screen instructions and instructional videos included.
When calls come in, users can answer them and the ride data will continue to be collected in the background.
The iBike Dash computer is now shipping for the iPhone and iPod touch, priced at $200 for the basic version and $329 for the advanced model that has a cadence sensor, HR sensor, calorie measurement, battery and charger. Either version includes the Phone Booth holder, mount, wireless speed sensor, iBike app for iPhone or iPod touch, and iBike software for Mac OS X- and Windows-based computers.
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Via Engadget
Source: University of New South Wales
Achieving quantum teleportation opens the doors to ultra fast data transmission
Mark this day, folks, because the brainiacs have finally made a breakthrough in quantum teleportation: a team of scientists from Australia and Japan have successfully transferred a complex set of quantum data in light form.
You see, previously researchers had struggled with slow performance or loss of information, but with full transmission integrity achieved — as in blocks of qubits being destroyed in one place but instantaneously resurrected in another, without affecting their superpositions — we’re now one huge step closer to secure, high-speed quantum communication.
Needless to say, this will also be a big boost for the development of powerful quantum computing, and combine that with a more bedroom friendly version of the above teleporter, we’ll eventually have ourselves the best LAN party ever.
By John Timmer
Noam Chomsky: Understanding Language
Human languages are far more complex than any animal communication system we’re aware of, and yet young children can easily learn to master more than one language in an astonishingly short period of time. This has led a number of linguists, most notably Noam Chomsky, to suggest that there might be language universals, common features of all languages that the human brain is attuned to, making learning easier; others have looked for statistical correlations between languages. Now, a team of cognitive scientists has teamed up with an evolutionary biologist to perform a phylogenetic analysis of language families, and the results suggest that when it comes to the way languages order key sentence components, there are no rules.
The authors of the new paper point out just how hard it is to study languages. We’re aware of over 7,000 of them, and they vary significantly in complexity. There are a number of large language families that are likely derived from a single root, but a large number of languages don’t slot easily into one of the major groups. Against that backdrop, even a set of simple structural decisions—does the noun or verb come first? where does the preposition go?—become dizzyingly complex, with different patterns apparent even within a single language tree.
Linguists, however, have been attempting to find order within the chaos. Noam Chomsky helped establish the Generative school of thought, which suggests that there must be some constraints to this madness, some rules that help make a language easier for children to pick up, and hence more likely to persist. Others have approached this issue via a statistical approach (the authors credit those inspired by Joseph Greenberg for this), looking for word-order rules that consistently correlate across language families. This approach has identified a handful of what may be language universals, but our uncertainty about language relationships can make it challenging to know when some of these correlations are simply derived from a common inheritance.
For anyone with a biology background, having traits shared through common inheritance should ring a bell. Evolutionary biologists have long been able to build family trees of related species, called phylogenetic trees. By figuring out what species have the most traits in common and grouping them together, it’s possible to identify when certain features have evolved in the past. In recent years, the increase in computing power and DNA sequences to align, has led to some very sophisticated phylogenetic software, which can analyze every possible tree and perform a Bayesian statistical analysis to figure out which trees are most likely to represent reality.
By treating language features like subject-verb order as a trait, the authors were able to perform this sort of analysis on four different language families: 79 Indo-European languages, 130 Austronesian languages, 66 Bantu languages, and 26 Uto-Aztecan languages. Although we don’t have a complete roster of the languages in those families, they include over 2,400 languages that have been evolving for a minimum of 4,000 years.
The results are bad news for universalists: “most observed functional dependencies between traits are lineage-specific rather than universal tendencies,” according to the authors. The authors were able to identify 19 strong correlations between word order traits, but none of these appeared in all four families; only one of them appeared in more than two. Fifteen of them only occur in a single family. Specific predictions based on the Greenberg approach to linguistics also failed to hold up under the phylogenetic analysis. “Systematic linkages of traits are likely to be the rare exception rather than the rule,” the authors conclude.
If universal features can’t account for what we observe, what can? Common descent. “Cultural evolution is the primary factor that determines linguistic structure, with the current state of a linguistic system shaping and constraining future states.”
It’s important to emphasize that this study looked at a specific language feature (word order). Although a fairly significant one, it still leaves a lot of areas open for linguists to argue about. And the study did not build an exhaustive tree of any of the language families, in part because we probably don’t have enough information to classify all of them at this point.
Still, it’s hard to imagine any further details could overturn the gist of things, given how badly features failed to correlate across language families. And the work might be well received in some communities, since it provides an invitation to ask a fascinating question:
given that there aren’t obvious word order patterns across languages, how does the human brain do so well at learning the rules that are a peculiarity to any one of them?