VILNIUS/WARSAW - Lithuania is planning defenses against military drones at a key future power grid substation linking the Baltic states with western Europe, in an area intelligence sources say Russia could target with a false-flag attack. The construction plans include fencing strong enough to resist an explosives-laden truck, sensors searching for possible tunnels dug by hostile actors, and concrete "sarcophagi" for transformers to withstand any drone attack, according to Litgrid CEO Andrius Semeskevicius. "Previously, when designing our grid, we planned for natural disasters. Now, we think about all possible hybrid and nonhybrid threats", he said in an interview. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Lithuania ready to'fight back' but has evacuation plans in face of Russia threats, PM tells BBC To play this video you need to enable JavaScript in your browser. Figure caption, 'We will fight back' if Russia attacks, Lithuanian PM says Lithuania's prime minister has told the BBC his country has made evacuation plans in the face of threats from Russia, but added they will not surrender if attacked. Prime Minister Mindaugas Sinkevičius told Newsnight that Lithuanians feel constantly threatened by Russia, in part because of drones entering the nation's airspace. He told Newsnight if his country was attacked, we will fight back... we will engage. But he said there were plans for a variety of scenarios and used an example of getting elderly citizens out of cities smoothly and avoiding traffic jams.

Is the war entering a new phase? An Italian fighter jet flying for NATO has brought down what officials said was a suspected Russian drone in Lithuanian airspace. According to Lithuania's national crisis management centre, the drone entered the country's airspace on Tuesday from Belarus and was shot down near the small settlement of Pratkunai in central Lithuania, just north of the country's second-largest city, Kaunas. Debris from the device was being examined to determine if it was from Russia or another country. The intervention by the Italian fighter jet demonstrated "the value of the Atlantic alliance" and "what it means to be an ally", Kaunas said after meeting crews who were at the scene.

Is the war entering a new phase? NATO downs drone over Lithuania, 'probably' launched by Russia NATO downs drone over Lithuania, 'probably' launched by Russia A NATO fighter jet shot down a drone in southern Lithuania shortly after midnight on Tuesday, which Italian Defence Minister Guido Crosetto says "probably originated from Russia". Share NATO downs drone over Lithuania, 'probably' launched by Russia on social media Who is NFL billionaire Robert Kraft? Athletes share'what women in sport look like' to rebut Sydney Sweeney ad Millions line up for'sacred henna' at Indian temple

NATO scrambled two Italian Eurofighter Typhoons to shoot down a drone over Lithuania that officials say likely entered from Belarus, marking a first for the Baltic nation.

Nato fighter pilots have shot down a drone that entered Lithuania's airspace overnight, the Lithuanian president said. Authorities said the drone likely entered southern Lithuania, near the second-largest city of Kaunas, from neighbouring Belarus shortly after midnight on Tuesday. Lithuanian President Gitanas Nausėda wrote in a statement on X: A drone that just entered Lithuanian airspace was destroyed by NATO fighter jets. The origins of the drone are yet to be determined, a spokesperson for the Lithuanian national crisis management centre said. Drone alerts sounded across the capital Vilnius and surrounding region earlier on Tuesday.

Recent incidents heighten anxieties that hybrid warfare tactics could trigger military confrontation with Russia. Lithuanian armed special forces and members of the Lithuanian Riflemen's Union take part in a military exercise in central Lithuania [File: Nils Adler/Al Jazeera] A member of the Lithuanian Riflemen's Union joins in military exercises in central Lithuania [File: Nils Adler/Al Jazeera] Along the forests and marshlands that separate the Baltic states from Russia and Belarus, workers are digging anti-tank ditches, pouring concrete bunkers and erecting rows of dragon's teeth - jagged concrete obstacles designed to slow and channel advancing armour - to buy precious time in the event of an attack. Russia's full-scale invasion of Ukraine in 2022 reignited old fears in Estonia, Latvia and Lithuania, where memories of Soviet rule remain close to the surface. In the years since, those fears have been channelled into preparation. Defence budgets have surged, military exercises have intensified, and new fortifications have emerged even as daily life largely continues as normal.

VILNIUS/STOCKHOLM/LONDON - Ukrainian drones have strayed into Baltic countries' airspace in recent weeks, sowing confusion and raising tensions with Russia at a time when U.S. commitment to NATO's collective security is in question. The airspace incursions have occurred as Ukraine, seeking to land heavier blows on Russia four years after Moscow's full-scale invasion, uses exploding drones to hit Russian Baltic ports that handle nearly 40% of national oil and gas exports. In most cases, Kyiv and the Baltic states have confirmed the stray drones are Ukrainian but have blamed Russia for causing them to deviate from their flight path with the use of electronic defenses that jam or spoof signals. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

Online health communities (OHCs) are vital for fostering peer support and improving health outcomes. Support groups within these platforms can provide more personalized and cohesive peer support, yet traditional support group formation methods face challenges related to scalability, static categorization, and insufficient personalization. To overcome these limitations, we propose two novel machine learning models for automated support group formation: the Group specific Dirichlet Multinomial Regression (gDMR) and the Group specific Structured Topic Model (gSTM). These models integrate user generated textual content, demographic profiles, and interaction data represented through node embeddings derived from user networks to systematically automate personalized, semantically coherent support group formation. We evaluate the models on a large scale dataset from MedHelp, comprising over 2 million user posts. Both models substantially outperform baseline methods including LDA, DMR, and STM in predictive accuracy (held out log likelihood), semantic coherence (UMass metric), and internal group consistency. The gDMR model yields group covariates that facilitate practical implementation by leveraging relational patterns from network structures and demographic data. In contrast, gSTM emphasizes sparsity constraints to generate more distinct and thematically specific groups. Qualitative analysis further validates the alignment between model generated groups and manually coded themes, showing the practical relevance of the models in informing groups that address diverse health concerns such as chronic illness management, diagnostic uncertainty, and mental health. By reducing reliance on manual curation, these frameworks provide scalable solutions that enhance peer interactions within OHCs, with implications for patient engagement, community resilience, and health outcomes.