'My skin was peeling' - the African women tricked into making Russian drones On her first day of work, Adau realised she had made a big mistake. We got our uniforms, not even knowing exactly what we were going to do. From the first day of work we were taken to the drones factory. We stepped in and we saw drones everywhere and people working. Then they took us to our different work stations.

How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? On Sunday, Russia launched its largest drone and missile attack since the war began, firing a total of 823 projectiles into Ukraine. The attack killed at least four people, wounded 44, and caused damage to a key building in Kyiv's government district, making it the first on the site since the full-fledged war began in February 2022.

In the three months before August last year, Russia fired a total of 1,100, according to a report by Ukraine's general staff. A steep rise followed, with 818 drones recorded in August, 1,410 in September and more than 2,000 in October. But the numbers just keep going up. In May, for the first time, the number of drones exceeded 4,000. This month is likely to set a new record.

Ukrainian drones struck multiple military airbases deep inside Russia on Sunday in a major operation a day before the neighbours held peace talks in Istanbul. The Russian Defence Ministry said Ukraine had launched drone strikes targeting Russian military airfields across five regions, causing several aircraft to catch fire. The attacks occurred in the Murmansk, Irkutsk, Ivanovo, Ryazan, and Amur regions. Air defences repelled the assaults in all but two regions – Murmansk and Irkutsk, the ministry said. "In the Murmansk and Irkutsk regions, the launch of FPV drones from an area in close proximity to airfields resulted in several aircraft catching fire," the Defence Ministry said.

Ukraine's Air Force claimed it shot down 93 of 141 drones Russia launched in attacks overnight. The Air Force also said that 47 of the drones were "lost" while two returned to Russia. Russia said it destroyed 31 Ukrainian drones which had primarily targeted industrial sites in Russia's Tatarstan region, located about 1,000km (about 600 miles) from the Ukrainian border. No victims or damage have been reported. The governor of Russia's Bryansk region, Alexander Bogomaz, said 14 Ukrainian drones were neutralised in the region, which borders Ukraine.

Attacks on underwater cables running through strategically significant bodies of water in both the Baltic Sea and the South China Sea by Russia and China, respectively, in recent months has top officials concerned they are not "mere coincidence." Maritime sabotage efforts in both regions of the world appear to have been on the rise over the last several years, with a notable spike in recent months after at least three separate attacks occurred in as many months, beginning in November, and the top suspects are Russia and China. "The Kremlin has been running a hybrid campaign against Europe for years, ranging from spreading disinformation and cyberattacks to weaponizing energy supplies. Since Russia's full-scale invasion of Ukraine, these efforts have intensified dramatically," EU High Representative Kaja Kallas told Fox News Digital. "However, Russia is not the only challenge we face."

Russia's Ministry of Defence said the army gained control of the settlement of Shevchenko, near the logistical centre of Pokrovsk, a key target in its advance through Ukraine's eastern Donetsk region. Ukraine has yet to acknowledge the loss of the town. Ukraine's General Staff of the Armed Forces said it repelled 46 of 56 Russian attacks around a dozen towns in the Pokrovsk sector and several clashes were ongoing. A Ukrainian drone hit one of Russia's largest oil refineries – in Taneko, Tatarstan – according to Russian Telegram channel ASTRA. Fuel oil that spilled from wrecked Russian tankers has spread into the Sea of Azov and reached the shores of Ukraine's partly Russian-occupied Zaporizhia region, a Moscow-installed official said.

Russian President Vladimir Putin has pledged retaliation after Ukrainian drones struck residential buildings in the city of Kazan in Russia's Tatarstan region. Putin made the comments via videolink on Sunday while addressing the local leader of Tatarstan in a road-opening ceremony. "Whoever, and however much they try to destroy, they will face many times more destruction themselves and will regret what they are trying to do in our country," Putin said. On Saturday morning, six Ukrainian drones hit residential buildings in Kazan and a seventh struck an industrial facility. No injuries from the attack were officially reported, while media reports indicated that three people suffered cuts from shattered window glass.

Ukrainian drones have hit residential buildings in the Russian city of Kazan, more than 1,000 kilometres (600 miles) from the front line, bringing the war deep into the heart of Russia. The Russian Ministry of Defence said the city, located some 800km (500 miles) east of Moscow, was attacked by three waves of drones between 7:40am and 9:20am (04:40 and 06:20 GMT) on Saturday. Eight drones were used in the attack, according to the press service of the Tatarstan regional government. Six hit residential buildings, one hit an industrial facility and another was shot down over a river, it said in a statement. Local authorities said there were no casualties.

Topic modeling is a key method in text analysis, but existing approaches are limited by assuming one topic per document or fail to scale efficiently for large, noisy datasets of short texts. We introduce Semantic Component Analysis (SCA), a novel topic modeling technique that overcomes these limitations by discovering multiple, nuanced semantic components beyond a single topic in short texts which we accomplish by introducing a decomposition step to the clustering-based topic modeling framework. We evaluate SCA on Twitter datasets in English, Hausa and Chinese. It achieves competetive coherence and diversity compared to BERTopic, while uncovering at least double the semantic components and maintaining a noise rate close to zero. Furthermore, SCA is scalable and effective across languages, including an underrepresented one.