If I mention nuclear reactor accidents, you’d probably think of Three Mile Island, Fukushima, or maybe Chernobyl (or, now, Chornobyl). But there have been others that, for whatever reason, aren’t as well publicized. Did you know there is an International Nuclear Event Scale? Like the Richter scale, but for nuclear events. A zero on the scale is a little oopsie. A seven is like Chernobyl or Fukushima, the only two such events at that scale so far. Three Mile Island and the event you’ll read about in this post were both level five events. That other level five event? The Windscale fire incident in October of 1957.

If you imagine this might have something to do with the Cold War, you are correct. It all started back in the 1940s. The British decided they needed a nuclear bomb project and started their version of the Manhattan Project called “Tube Alloys.” But in 1943, they decided to merge the project with the American program.

The British, rightfully so, saw themselves as co-creators of the first two atomic bombs. However, in post-World War paranoia, the United States shut down all cooperation on atomic secrets with the 1946 McMahon Act.

We Are Not Amused

The British were not amused and knew that to secure a future seat at the world table, it would need to develop its own nuclear capability, so it resurrected Tube Alloys. If you want a detour about the history of Britan’s bomb program, the BBC has a video for you that you can see below.

youtube.com/embed/8WcMm31RbMw?…

Of course, post-war Britain wasn’t exactly flush with cash, so they had to limit their scope a bit. While the Americans had built bombs with both uranium and plutonium, the UK decided to focus on plutonium, which could create a stronger bomb with less material.

Of course, that also means you have to create plutonium, so they built two reactors — or piles, as they were known then. They were both in the same location near Seascale, Cumberland.

Inside a Pile

The Windscale Piles in 1951 (photo from gov.uk website).
The reactors were pretty simple. There was a big block of graphite with channels drilled through it horizontally. You inserted uranium fuel cartridges in one end, pushing the previous cartridge through the block until they fell out the other side into a pool of water.

The cartridges were encased in aluminum and had cooling fins. These things got hot! Immediately, though, practical concerns — that is, budgets — got in the way. Water cooling was a good idea, but there were problems. First, you needed ultra-pure water. Next, you needed to be close to the sea to dump radioactive cooling water, but not too close to any people. Finally, you had to be willing to lose a circle around the site about 60 miles in diameter if the worst happened.

The US facility at Hanford, indeed, had a 30-mile escape road for use if they had to abandon the site. They dumped water into the Columbia River, which, of course, turned out to be a bad idea. The US didn’t mind spending on pure water.

Since the British didn’t like any of those constraints, they decided to go with air cooling using fans and 400-foot-tall chimneys.

Our Heros

Most of us can relate to being on a project where the rush to save money causes problems. A physicist, Terence Price, wondered what would happen if a fuel cartridge split open. For example, one might miss the water pool on the other side of the reactor. There would be a fire and uranium oxide dust blowing out the chimney.

The idea of filters in each chimney was quickly shut down. Since the stacks were almost complete, they’d have to go up top, costing money and causing delays. However, Sir John Cockcroft, in charge of the construction, decided he’d install the filters anyway. The filters became known as Cockcroft’s Follies because they were deemed unnecessary.

So why are these guys the heroes of this story? It isn’t hard to guess.

A Rush to Disaster

The government wanted to quickly produce a bomb before treaties would prohibit them from doing so. That put them on a rush to get H-bombs built by 1958. There was no time to build more reactors, so they decided to add material to the fuel cartridges to produce tritium, including magnesium. The engineers were concerned about flammability, but no one wanted to hear it.

They also decided to make the fins of the cartridges smaller to raise the temperature, which was good for production. This also allowed them to stuff more fuel inside. Engineers again complained. Hotter, more flammable fuel. What could go wrong? When no one would listen, the director, Christopher Hinton, resigned.

The Inevitable

The change in how heat spread through the core was dangerous. But the sensors in place were set for the original patterns, so the increased heat went undetected. Everything seemed fine.

It was known that graphite tends to store some energy from neutron bombardment for later release, which could be catastrophic. The solution was to heat the core to a point where the graphite started to get soft, which would gradually release the potential energy. This was a regular part of operating the reactors. The temperature would spike and then subside. Operations would then proceed as usual.

By 1957, they’d done eight of these release cycles and prepared for a ninth. However, this one didn’t go as planned. Usually, the core would heat evenly. This time, one channel got hot and the rest didn’t. They decided to try the release again. This time it seemed to work.

As the core started to cool as expected, there was an anomaly. One part of the core was rising instead, reaching up to 400C. They sped up the fans and the radiation monitors determined that they had a leak up the chimney.

Memories

Remember the filters? Cockcroft”s Follies? Well, radioactive dust had gone up the chimney before. In fact, it had happened pretty often. As predicted, the fuel would miss the pool and burst.

With the one spot getting hotter, operators assumed a cartridge had split open in the core. They were wrong. The cartridge was on fire. The Windscale reactor was on fire.

Of course, speeding up the fans just made the fire worse. Two men donned protective gear and went to peek at an inspection port near the hot spot. They saw four channels of fuel glowing “bright cherry red”. At that point, the reactor had been on fire for two days. The Reactor Manager suited up and climbed the 80 feet to the top of the reactor building so he could assess the backside of the unit. It was glowing red also.

Fight Fire with ???

The fans only made the fire worse. They tried to push the burning cartridges out with metal poles. They came back melted and radioactive. The reactor was now white hot. They then tried about 25 tonnes of carbon dioxide, but getting it to where it was needed proved to be too difficult, so that effort was ineffective.

By the 11th of October, an estimated 11 tonnes of uranium were burning, along with magnesium in the fuel for tritium production. One thermocouple was reading 3,100C, although that almost had to be a malfunction. Still, it was plenty hot. There was fear that the concrete containment building would collapse from the heat.

You might think water was the answer, and it could have been. But when water hits molten metal, hydrogen gas results, which, of course, is going to explode under those conditions. They decided, though, that they had to try. The manager once again took to the roof and tried to listen for any indication that hydrogen was building up. A dozen firehoses pushed into the core didn’t make any difference.

Sci Fi

If you read science fiction, you probably can guess what did work. Starve the fire for air. The manager, a man named Tuohy, and the fire chief remained and sent everyone else out. If this didn’t work, they were going to have to evacuate the nearby town anyway.

They shut off all cooling and ventilation to the reactor. It worked. The temperature finally started going down, and the firehoses were now having an effect. It took 24 hours of water flow to get things completely cool, and the water discharge was, of course, radioactive.

If you want a historical documentary on the even, here’s one from Spark:

youtube.com/embed/S0DXndsQ0H4?…

Aftermath

The government kept a tight lid on the incident and underreported what had been released. But there was much less radioactive iodine, cesium, plutonium, and polonium release because of the chimney filters. Cockcroft’s Folly had paid off.

While it wasn’t ideal, official estimates are that 240 extra cancer cases were due to the accident. Unofficial estimates are higher, but still comparatively modest. Also, there had been hushed-up releases earlier, so it is probably that the true number due to this one accident is even lower, although if it is your cancer, you probably don’t care much which accident caused it.

Milk from the area was dumped into the sea for a while. Today, the reactor is sealed up, and the site is called Sellafield. It still contains thousands of damaged fuel elements within. The site is largely stable, although the costs of remediating the area have been, and will continue to be staggering.

This isn’t the first nuclear slip-up that could have been avoided by listening to smart people earlier. We’ve talked before about how people tend to overestimate or sensationalize these kinds of disasters. But it still is, of course, something you want to avoid.

Featured image: “HD.15.003” by United States Department of Energy

hackaday.com/2025/10/29/this-r…

Over on YouTube [CuriousMarc] and [TubeTimeUS] team up for a multi-part series E&L MMD-1 Mini-Micro Designer Restoration.

The E&L MMD-1 is a microcomputer trainer and breadboard for the Intel 8080. It’s the first ever single-board computer. What’s more, they mention in the video that E&L actually invented the breadboard with the middle trench for the ICs which is so familiar to us today; their US patent 228,136 was issued in August 1973.

The MMD-1 trainer has support circuits providing control logic, clock, bus drivers, voltage regulator, memory decoder, memory, I/O decoder, keyboard encoder, three 8-bit ports, an octal keyboard, and other support interconnects. They discuss in the video the Intel 1702 which is widely accepted as the first commercially available EPROM, dating back to 1971.

In the first video they repair the trainer then enter a “chasing lights” assembly language program for testing and demonstration purposes. This program was found in 8080 Microcomputer Experiments by Howard Boyet on page 76. Another book mentioned is The Bugbook VI by David Larsen et al.

In the second video they wire in some Hewlett-Packard HP 5082-7300 displays which they use to report on values in memory.

A third episode is promised, so stay tuned for that! If you’re interested in the 8080 you might like to read about its history or even how to implement one in an FPGA!

youtube.com/embed/eCAp3K7yTlQ?…

youtube.com/embed/Sfe18oyRvGk?…

hackaday.com/2025/10/29/restor…

We’ll be honest. If you had told us a few decades ago we’d teach computers to do what we want, it would work some of the time, and you wouldn’t really be able to explain or predict exactly what it was going to do, we’d have thought you were crazy. Why not just get a person? But the dream of AI goes back to the earliest days of computers or even further, if you count Samuel Butler’s letter from 1863 musing on machines evolving into life, a theme he would revisit in the 1872 book Erewhon.

Of course, early real-life AI was nothing like you wanted. Eliza seemed pretty conversational, but you could quickly confuse the program. Hexapawn learned how to play an extremely simplified version of chess, but you could just as easily teach it to lose.

But the real AI work that looked promising was the field of expert systems. Unlike our current AI friends, expert systems were highly predictable. Of course, like any computer program, they could be wrong, but if they were, you could figure out why.

Experts?

As the name implies, expert systems drew from human experts. In theory, a specialized person known as a “knowledge engineer” would work with a human expert to distill his or her knowledge down to an essential form that the computer could handle.

This could range from the simple to the fiendishly complex, and if you think it was hard to do well, you aren’t wrong. Before getting into details, an example will help you follow how it works.

From Simple to Complex

One simple fake AI game is the one where the computer tries to guess an animal you think of. This was a very common Basic game back in the 1970s. At first, the computer would ask a single yes or no question that the programmer put in. For example, it might ask, “Can your animal fly?” If you say yes, the program guesses you are thinking of a bird. If not, it guesses a dog.

Suppose you say it does fly, but you weren’t thinking of a bird. It would ask you what you were thinking of. Perhaps you say, “a bat.” It would then ask you to tell it a question that would distinguish a bat from a bird. You might say, “Does it use sonar?” The computer will remember this, and it builds up a binary tree database from repeated play. It learns how to guess animals. You can play a version of this online and find links to the old source code, too.

Of course, this is terrible. It is easy to populate the database with stupid questions or ones you aren’t sure of. Do ants live in trees? We don’t think of them living in trees, but carpenter ants do. Besides, sometimes you may not know the answer or maybe you aren’t sure.

So let’s look at a real expert system, Mycin. Mycin, from Stanford, took data from doctors and determined what bacteria a patient probably had and what antibiotic would be the optimal treatment. Turns out, most doctors you see get this wrong a lot of the time, so there is a lot of value to giving them tools for the right treatment.

This is really a very specialized animal game where the questions are preprogrammed. Is it gram positive? Is it in a normally sterile site? What’s more is, Mycin used Bayesian math so that you could assign values to how sure you were of an answer, or even if you didn’t know. So, for example, -1 might mean definitely not, +1 means definitely, 0 means I don’t know, and -0.5 means probably not, but maybe. You get the idea. The system ran on a DEC PDP-10 and had about 600 rules.

The system used LISP and could paraphrase rules into English. For example:
(defrule 52
if (site culture is blood)
(gram organism is neg)
(morphology organism is rod)
(burn patient is serious)
then .4
(identity organism is pseudomonas))
Rule 52:
If
1) THE SITE OF THE CULTURE IS BLOOD
2) THE GRAM OF THE ORGANISM IS NEG
3) THE MORPHOLOGY OF THE ORGANISM IS ROD
4) THE BURN OF THE PATIENT IS SERIOUS
Then there is weakly suggestive evidence (0.4) that
1) THE IDENTITY OF THE ORGANISM IS PSEUDOMONAS

In practice, the program did as well as real doctors, even specialists. Of course, it was never used in practice because of ethical concerns and the poor usability of entering data into a timesharing terminal. You can see a 1988 video about Mycin below.

youtube.com/embed/a65uwr_O7mM?…

Under the Covers

Mycin wasn’t the first or only expert system. Perhaps the first was SID. In 1982, SID produced over 90% of the VAX 9000’s CPU design, although many systems before then had dabbled in probabilities and other similar techniques. For example, DENDRAL from the 1960s used rules to interpret mass spectrometry data. XCON started earlier than SID and was DEC’s way of configuring hardware based on rules. There were others, too. Everyone “knew” back then that expert systems were the wave of the future!

Expert systems generally fall into two categories: forward chaining and backward chaining. Mycin was a backward chaining system.

What’s the difference? You can think of each rule as an if statement. Just like the example, Mycin knew that “if the site is in the blood and it is gram negative and…. then….” A forward chaining expert system will try to match up rules until it finds the ones that match.

Of course, you can make some assumptions. So, in the sample, if a hypothetical forward-chaining Mycin asked if the site was the blood and the answer was no, then it was done with rule 52.

However, the real Mycin was backward chaining. It would assume something was true and then set out to prove or disprove it. As it receives more answers, it can see which hypothesis to prioritize and which to discard. As rules become more likely, one will eventually emerge.

If that’s not clear, you can try a college lecture on the topic from 2013, below.

youtube.com/embed/ZhTt-GG7PiQ?…

Of course, in a real system, too, rules may trigger more rules. There were probably as many actual approaches as there were expert systems. Some, like Mycin, were written in LISP. Some in C. Many used Prolog, which has some features aimed at just the kind of things you need for an expert system.

What Happened?

Expert systems are actually very useful for a certain class of problems, and there are still examples of them hanging around (for example, Apache Drools). However, some problems that expert systems tried to solve — like speech recognition — were much better handled by neural networks.

Part of the supposed charm of expert systems is that — like all new technology — it was supposed to mature to the point where management could get rid of those annoying programmers. That really wasn’t the case. (It never is.) The programmers just get new titles as knowledge engineers.

Even NASA got in on the action. They produced CLIPS, allowing expert systems in C, which was available to the public and still is. If you want to try your hand, there is a good book out there.

Meanwhile, you can chat with Eliza if you don’t want to spend time chatting with her more modern cousins.

hackaday.com/2025/10/29/expert…

Per la seconda volta negli ultimi mesi, Google è stata costretta a smentire le notizie di una massiccia violazione dei dati di Gmail. La notizia è stata scatenata dalle segnalazioni di un “hacking di 183 milioni di account” diffuse online, nonostante non vi sia stata alcuna violazione o incidente reale che abbia coinvolto i server di Google.

Come hanno spiegato i rappresentanti dell’azienda, non si tratta di un nuovo attacco, ma piuttosto di vecchi database di login e password raccolti dagli aggressori tramite infostealer e altri attacchi degli ultimi anni.

“Le segnalazioni di una ‘violazione di Gmail che ha interessato milioni di utenti’ sono false. Gmail e i suoi utenti sono protetti in modo affidabile”, hanno dichiarato i rappresentanti di Google. L’azienda ha inoltre sottolineato che la fonte delle voci di una fuga di dati importante era un database contenente i log degli infostealer, nonché credenziali rubate durante attacchi di phishing e altri attacchi.

Il fatto è che questo database è stato recentemente reso pubblico tramite la piattaforma di analisi delle minacce Synthient ed è stato poi aggiunto all’aggregatore di perdite Have I Been Pwned (HIBP).

Il creatore di HIBP, Troy Hunt, ha confermato che il database di Synthient contiene circa 183 milioni di credenziali, inclusi login, password e indirizzi web su cui sono state utilizzate. Secondo Hunt, non si tratta di una singola fuga di dati: queste informazioni sono state raccolte nel corso degli anni da canali Telegram, forum, dark web e altre fonti. Inoltre, questi account non sono correlati a una singola piattaforma, ma a migliaia, se non milioni, di siti web e servizi diversi.

Inoltre, il 91% dei record era già apparso in altre fughe di notizie ed era presente nel database HIBP, mentre solo 16,4 milioni di indirizzi erano nuovi.

I rappresentanti di Synthient hanno confermato che la maggior parte dei dati nel database non è stata ottenuta tramite attività di hacking, ma infettando i sistemi dei singoli utenti con malware. In totale, i ricercatori hanno raccolto 3,5 TB di informazioni (23 miliardi di righe), inclusi indirizzi email, password e indirizzi di siti web esposti in cui sono state utilizzate le credenziali compromesse.

Google sottolinea che l’azienda scopre e utilizza regolarmente tali database per i controlli di sicurezza, aiutando gli utenti a reimpostare le password trapelate e a proteggere nuovamente i propri account.

L’azienda sottolinea inoltre che, anche se Gmail non è stato hackerato, i vecchi nomi utente e password già trapelati potrebbero comunque rappresentare una minaccia. Per mitigare questi rischi, Google consiglia di abilitare l’autenticazione a più fattori o di passare alle passkey, che sono più sicure delle password tradizionali.

Ricordiamo che, nel settembre 2025, Google aveva già smentito le segnalazioni di una massiccia violazione dei dati degli utenti di Gmail. All’epoca, erano emersi resoconti sui media secondo cui Google avrebbe inviato una notifica di massa a tutti gli utenti di Gmail (circa 2,5 miliardi di persone) per chiedere loro di cambiare urgentemente le password e abilitare l’autenticazione a due fattori. I rappresentanti di Google hanno poi negato la veridicità di tale notizia.

L'articolo 183 milioni di account Gmail hackerati! E’ falso: era solo una bufala proviene da Red Hot Cyber.

Nvidia non ha sviluppato un proprio computer quantistico, ma il CEO Jensen Huang scommette che l’azienda avrà un ruolo chiave nel futuro della tecnologia. Nel suo discorso di apertura alla Global Technology Conference (GTC) di Nvidia a Washington, D.C., martedì, Huang ha annunciato NVQLink, una tecnologia di interconnessione che collega i processori quantistici ai supercomputer di intelligenza artificiale di cui hanno bisogno per funzionare efficacemente.

Ha affermato: “NVQLink è la chiave per collegare i supercomputer quantistici e quelli classici”. I processori quantistici rappresentano un modo completamente nuovo di fare calcolo, utilizzando i principi della fisica quantistica per risolvere problemi che gli attuali computer classici non sono in grado di risolvere.

Le loro applicazioni sono vaste, dalla scoperta scientifica alla finanza. Tuttavia, per fornire risultati significativi per aziende e ricercatori, devono essere integrati con computer classici ad alte prestazioni, che eseguono calcoli che non sono in grado di completare e correggono gli errori naturali nelle loro risposte, un processo noto come correzione degli errori.

Tim Costa, General Manager di Ingegneria Industriale e Quantum di NVIDIA, ha affermato che nel settore esiste un consenso generale sulla necessità di questa infrastruttura ibrida che coinvolge processori quantistici (QPU) e chip di intelligenza artificiale come le GPU NVIDIA, in parte perché l’esecuzione di una correzione completa degli errori richiede l’intelligenza artificiale.

Costa ha affermato che alcune aziende hanno già tentato di integrare processori quantistici con supercomputer di intelligenza artificiale, ma queste tecnologie non sono riuscite a fornire la velocità e la scalabilità necessarie per ottenere una correzione degli errori rapida e scalabile. NVIDIA afferma che la sua nuova tecnologia di interconnessione è la prima soluzione a fornire la velocità e la scalabilità necessarie per realizzare la vera promessa del calcolo quantistico su larga scala.

A tal fine, NVIDIA sta collaborando con oltre una dozzina di diverse aziende quantistiche, tra cui IonQ, Quantumuum e Infleqtion, nonché con diversi laboratori nazionali, tra cui i Sandia National Laboratories, l’Oak Ridge National Laboratory e il Fermi Laboratory. Questa tecnologia di interconnessione si basa su un’architettura aperta ed è adatta a diverse modalità quantistiche, tra cui ioni intrappolati, superconduttori e fotoni. Costa ha affermato che questa apertura è cruciale, il che significa che i laboratori nazionali saranno ora in grado di sviluppare supercomputer per utilizzare le capacità quantistiche non appena saranno disponibili.

Costa ha affermato che in futuro “ogni supercomputer utilizzerà processori quantistici per ampliare la gamma di problemi che può elaborare, e ogni processore quantistico si affiderà ai supercomputer per funzionare correttamente”. Quando vedremo le tecnologie quantistiche generare un valore commerciale significativo? Costa di Nvidia ha affermato che qualsiasi risposta potesse dare sarebbe sbagliata.

L'articolo Nvidia lancia NVQLink per il calcolo quantistico proviene da Red Hot Cyber.

What has the EDRi network been up to over the past few weeks? Find out the latest digital rights news in our bi-weekly newsletter. In this edition: we're pondering digital fairness, budget cuts for the Austrian DPA and more.

The post EDRi-gram, 29 October 2025 appeared first on European Digital Rights (EDRi).

The shutdown of the facial recognition cameras at the Václav Havel Airport in Prague came after years of criticism from EDRi member IuRe. The legitimacy of the criticism was confirmed by the Czech Office for Personal Data Protection. However, the Czech police continue to systematically violate the law in further processing of biometric data.

The post Czech police forced to turn off facial recognition cameras at the Prague airport thanks to the AI Act appeared first on European Digital Rights (EDRi).

Despite its growing responsibilities, the Austrian Data Protection Authority continues to be impaired by budget cuts. epicenter.works and noyb are filing a complaint with the European Commission about Austria not fulfilling its obligations of sufficiently funding its data protection authority and leaving millions of Austrians to deal with consequences of limited access to the fundamental right to data protection.

The post Budget cuts incapacitate Austrian DPA: NGOs complaint to the EU Commission appeared first on European Digital Rights (EDRi).

noblogo.org/transit/fiano-o-de…

Transit

2025-10-29 08:41:50

Fiano, o delle distinzioni di comodo.

(173)

Brevi e probabilmente banali considerazioni dopo l'ascolto di Emanuele Fiano oggi sui fatti accaduti a “Cà Foscari”.

Per chi segue il dibattito social, la posizione di Emanuele Fiano e “Sinistra per Israele” tende a sostenere che l’ #antisionismo sia una forma di #antisemitismo, cioè che l’opposizione al movimento sionista o alle politiche di Israele coincida sempre con l’odio verso gli ebrei. Questa visione semplifica e confonde due piani profondamente diversi.​

L’antisemitismo è ostilità verso gli ebrei in quanto persone, religione o popolo: pogrom, discriminazioni, teorie del complotto e “Shoah” ne sono espressioni drammatiche. L’antisionismo invece è la critica dell’ideologia sionista e delle politiche dello Stato di Israele: non nasce per definizione come discorso d’odio, ma come posizione politica, spesso alimentata da ragioni storiche, etiche o di difesa dei diritti dei palestinesi.​

Ci sono sempre stati ebrei antisionisti: gruppi religiosi o laici che non si riconoscono nello Stato di #Israele o ne criticano l’esistenza, a prescindere da ogni odio antiebraico. Anzi, la discussione critica tra ebrei su sionismo e Israele fa parte della storia stessa dell’ebraismo moderno. Equiparare ogni antisionismo all’antisemitismo cancella questa pluralità e nega il diritto a dissentire, dentro e fuori dalla comunità ebraica.​

Una critica anche aspra al governo israeliano, alla sua politica verso i palestinesi o al progetto sionista in sé non implica odio per gli ebrei. Così come criticare la Russia di Putin, la Cina di Xi o l’America di Biden non significa odiare russi, cinesi o americani. Dire il contrario è una forma di propaganda che soffoca il dibattito, bolla ogni dissenso come intolleranza e serve spesso a zittire movimenti per i diritti umani o campagne di solidarietà internazionale.​

Chi sostiene che antisionismo e antisemitismo siano la stessa cosa rischia di banalizzare davvero l’antisemitismo: se tutto è odio antiebraico, niente lo è più davvero. E si finisce per colpire chi magari lotta contro razzismi e colonalismi ma è a favore dei diritti di palestinesi, israeliani ed ebrei.​ Banalizzazione che fanno, alla luce del sole, Fiano e i componenti di “Sinistra per Israele.” Antisionismo e antisemitismo sono cose diverse e confonderle fa male sia alla lotta contro le discriminazioni, sia alla libertà di dibattito politico.

Non ho scritto cose nuove, me ne rendo conto, ma continuare a “tenere il punto”, in giorni disperanti come questi, mi aiuta a considerare le cose per come dovrebbero essere, non per come vogliamo che siano.

#Blog #Antisemitismo #Antisionismo #Opinioni #Italia #Politics #Politica

Mastodon: @alda7069@mastodon.unoTelegram: t.me/transitblogFriendica: @danmatt@poliverso.orgBio Site (tutto in un posto solo, diamine): bio.site/danielemattioli

Gli scritti sono tutelati da “Creative Commons” (qui)

Tutte le opinioni qui riportate sono da considerarsi personali. Per eventuali problemi riscontrati con i testi, si prega di scrivere a: corubomatt@gmail.com

Transit

Il blog di Alessandra Corubolo & Daniele Mattioli. On line -in varie forme- dal 2005.

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