jerven

Working on the uniprot services that might be used from the connector it would be nice to learn if this uses public resources or if there is a private anthropic copy of certain uniprot data sets.

And the Swiss CFF also thinks it is under spending on maintenance. Track maintenance last year was nearly 20% from its target.

Funnily enough, for a long time the lakes of Switzerland had been stuffed into a database table of municipalities at SwissTopo for 2 decades before that was refactored out. Or at least I recall having heard this story.

Yes, and no, maybe ;) the economic incentives are designed to always provide enough power and no more at the cheapest possible point for that time slot. The market (if free enough) searches for that point over time. One possible solution may be peaker plants (this was financially so in the burn fuel age) another maybe overbuilding (e.g. your home backup or off-site generator power that are sized at peak load/demand, not the actual demand). All constrained by what is physically possible on a grid.

Peaker plants gamble that there are going to be peaks (sure financially plan for but they are not guaranteed to make their profits).

In the peaker plant categories the storage options are different from the spin options because the incentives are slightly different. Specifically battery storage is not just a peak plant exercise it is a grid connection optimization exercise. Grid connections limit how much power one can sell from a generator. A battery system can be placed on the grid or between the grid and the generator. In the case of between grid and generator, it allows a generator to run at it's optimal speeds more often than not, and sell more because one can guarantee a wider range of output for a longer amount of time.

Some of the first battery storage systems were sold to gas peaker plants because it allowed them more time to react. i.e. idle at a more efficient level their gas turbines or even shut them off and start them on demand.

The plants that are willing to give supply for the most negative price are the ones that will not be curtailed. So market forces. Basically at such points power plants are paying for the privilege to be allowed to supply power. This is dominated by restart costs and as such is often paid by classic "baseload" plants such as nuclear ones. i.e. they will accept losing money during one part of the day/week so that they can make money during a different part of the day/week.

Primary energy compared to electricity as energy. The first adds energy used in driving, chemical industry etc. the second is just the amount of electricity generated.

I was wondering how the existing case law of translated works, from one language to an other works here. It would at suggest that this is an infringement of the license especially because of the lack of creativity. But IANAL and of course no idea of applicable case law.

There is a significant fine to be paid by the non delivering supplier. This still happens and that is why there is also an auction for reserve power. Oversupply is fined even higher as that is also bad for grid stability.

RDFa/Microdata is more interesting for people whom sell objects instead of content. e.g. marking up that a page is about a kitchen cabinet that is 60cm wide and in the color white might lead to more sales in the long run. As people whom are looking for 60cm wide cabinets might get to your page instead of one about one 36 inch wide.

I am partial to the approach in https://www.expasy.org/about-chat ;) so yes I can think it can help. Mostly though the use case becomes interesting when you deal with multiple graph databases e.g. UniProt + WikiData etc.

If it is just to query one single dataset that is already in one tool it is less compelling.

Yes, it is super sad :( a real pity that a cheap but useful resource gets taken out almost by accident.

I would like to state that good bike lanes and trains also have induced demand. The Netherlands and Switzerland, have demand for more of both (as well as more demand for car lanes as well)

It is just that trains and bikes are much more efficient in terms of land use.

The 3 lane road in front of my house is "good" for 16,000 cars a day. The 2 lane train line a 5 minutes walk from my house is "good" for 120,000 passengers a day. A train line can carry about 10x the traffic of a car lane (in practice) with similar ground usage.

So when a train system has more demand/use than expected (e.g. leman express in the geneva region) there are more options to increase throughput (in the leman express case double level trains) that require less new infrastructure to be build.

When new infrastructure is required, limitations of space mean that a 15 year period from plan to implementation is normal. Which means infrastructure which has more head-room is preferred over quickly saturated ones.

To add the adding of one lane to the A1 for 18KM costs half the total of the leman express infrastructure. But has significantly less benefits in total transit capacity.

4 people, for a short term stay is about where it starts to make sense to ride share. Long term, you would have an longer term pass, vastly reducing the cost of a busride, and you would often travel in smaller groups. So in my experience there are times when bus/tram can be much faster and convenient than a car. Of course there are many cases where it is the other way round (and going out of the cities that ratio changes dramatically for a car). Good city design tends to favor a ratio in favor of public transport over cars.

Yes, in theory, but your process control would be terrible, thus your product would also be terrible. Unless you invent something very clever.

Is it a current trend? my Mom does this and she picked it up in the 70's on typewriters.

Working for an open-data project, I am starting to believe that the AI companies are basically criminal enterprises. If I did this kind of thing to them they would call the cops and say I am a criminal for breaking TOS and doing a DDOS, therefore they are likely to be criminal organizations and their CEOs should be in Alcatraz.

MilleniumDB is an interesting engine, as is Qlever mentioned in other comments. I think both are good candidates at making RDF graphs one or two orders of magnitude cheaper to host as sparql endpoints.

Both seem to have arrived at the stage of transitioning from research to production code.

Very exiting for those of us providing our data in RDF and exposing Sparql.

AWs Neptune analytics is also very interesting, allowing Cypher on RDF graphs. Even the Oracle inbuilt RDF+Sparql seems to have improved greatly in 23ai.

There was a microsoft prototype for more stack allocation in OpenJDK (https://archive.fosdem.org/2020/schedule/event/reducing_gc_t...). I recall that being put on hold because of how it would interact with project Loom fast stack copying. But I don't know the current status.

GO has a non moving GC and I understand, that the cost of introducing safe moving GC is considered high. If one has a moving GC which the serious java one's are read/write barriers are already required, especially if they are concurrent like ZGC, C4 or Shenadoah. ZGc, C4 and Shenadoah all started out as non generational GC implementations, which gained them later, because in most cases they do increase performance/reduce overhead.

Valhalla makes objects denser, and reduces overhead of identity which is great. Reducing the difference in memory layout between java objects and nested go structs.

Go with arena's reduce the GC de-allocation costs. Something that the ZGC team is looking at in relation to loom/virtual threads. (but I can't find the reference for that right now)

Java AOT has come a long way, and is not so rare as it used to be. Native binaries with GraalVM AOT are becoming more a common way to ship CLI tools written in JVM languages.

I must say when ever I have the chance I do really enjoy the Cff/sbb dining cars on the swiss network. A real sense of luxury to see the Alps go by drinking a ok coffee or decent beer in a nice environment. Feels nicer than bussiness class on a plane.

Run the UniProt sparql service on it ;) I was lucky to test the yarcdata implementation of sparql on an xmt machine around 2012, super UI but single user.

Could you expand upon this? sounds like an interesting opinion/experience that is worth sharing in more detail.

I think that GO with GO-CAM is definitely going that way. Basic GO is rather simple and can't infer that much (as in GO by itself has low classification or inference logic build in). Uberon, for anatomy, does use a lot of OWL power and shows that the logic-based inference can help a lot.

Reactome, is a graph, because that is the domain. But technically it does little with that fact (In my disappointed opinion).

Given that GO and Reactome are also relatively small academic efforts in general...

Just use the browser dev tools to change it to what ever you want. And then take the screenshot.

Just want to note that there is a lot of non GPL software in RHEL. e.g. Apache licensed or MIT. For which they do not have an obligation to provide the sources.

Nice classification of graph dataset size. I just think that XXL is the wrong size for a 1Tb dataset. Datasets like wikidata, UniProt, omabrowser etc. as a graph are really not XXL when decently funded (i.e. if they could afford the memgraph cloud pricing). I would have shifted them so that medium would be XS and then continue to the 1 trillion edges+nodes to get to the XXL size.

In 2014 I was at Oracle Open World. A 3rd party hardware vendor was saying (and having customers) for Hadoop "clusters" that had 8 cpu cores. Basically their pitch was that Oracle Hardware (ex sun) started at a dense full rack of about a 1 million USD or so, but with the 3d party you could have a hadoop "cluster" in 2U and for 20K. The oracle thing was actually quite price competitive at the time, if you needed hadoop. The 3rd party thing was overpriced for what it was. Yet, I am sure that 3rd party hardware vendor made out like bandits.

I just want to note, that reliability becomes an issue at scale as well. C can be the first to crash making it's "faster speed" useless. An example: there was a benchmark game for DNA GC counting. C was the fastest at beginning (a vectorized rust version has taken over). However, the C version in the lead at that time was the only version that could not count the GC ratio in human Chromosome X. Due to segfault/integer overflow. So in practical terms the C version was really infinitely slow even if the top ranker in the benchmark.

On a person note: I am dealing with C segfault ruining 261 hours of compute, which will probably need about a 1000 or so more to debug :(

Me too! it is funny having done it a few times I got used to it but I would love to get rid of it.

and often don't even capture the molecule pose as it would appear in biology.

Mapping between ligands in PDB and cognate ligands as being annotated in UniProt is improving :) my UniProt curator colleagues are working hard on this. Though a lot was made possible by re-annotating all cognate ligands with ChEBI.