Graves being prepared for the victims of an airstrike on a school in Minab in southern Iran, 2 March 2026. Graves being prepared for the victims of an airstrike on a school in Minab in southern Iran, 2 March 2026. A photo of Iran's bombed schoolgirl graveyard went around the world. T he graves, freshly dug, lie in neat rows of 20 across. More than 60 have already been carved out of the earth, with a few clusters of people standing gathered around them.

Neolithic period to the Industrial Revolution and includes information reviewed and assembled by history experts and graduate research assistants.

Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge present in both visual and textual data.

Indonesian rescuers have recovered wreckage from a missing plane that is believed to have crashed with 11 people on board while approaching a mountainous region on Sulawesi island during cloudy conditions. The discovery on Sunday comes after the small plane - on its way from Yogyakarta on Indonesia's main island of Java to Makassar, the capital city of South Sulawesi province - vanished from radar on Saturday. Rescuers on the ground then retrieved larger debris consistent with the main fuselage and tail scattered on a steep northern slope, Anwar told a news conference. "The discovery of the aircraft's main sections significantly narrows the search zone and offers a crucial clue for tightening the search area," Anwar said. "Our joint search and rescue teams are now focusing on searching for the victims, especially those who might still be alive." The plane, a turboprop ATR 42-500, was operated by Indonesia Air Transport and was last tracked in the Leang-Leang area of Maros, a mountainous district of South Sulawesi province.

Indonesia's government has filed multiple lawsuits seeking more than $200m in damages against six firms, after deadly floods wreaked havoc across Sumatra, killing more than 1,000 people last year, although environmentalists criticised the moves as inadequate. Environmentalists, experts and the government pointed the finger at deforestation for its role in last year's disaster that washed torrents of mud and wooden logs into villages across the northwestern part of the island. The sum represents both fines for damage and the proposed monetary value of recovery efforts. The suits were filed to courts on Thursday in Jakarta and North Sumatra's Medan, the ministry added. "We firmly uphold the principle of polluter pays," Environment Minister Hanif Faisol Nurofiq said in a statement.

Explainable machine learning techniques have gained increasing attention in engineering applications, especially in aerospace design and analysis, where understanding how input variables influence data-driven models is essential. Partial Dependence Plots (PDPs) are widely used for interpreting black-box models by showing the average effect of an input variable on the prediction. However, their global sensitivity metric can be misleading when strong interactions are present, as averaging tends to obscure interaction effects. To address this limitation, we propose a global sensitivity metric based on Individual Conditional Expectation (ICE) curves. The method computes the expected feature importance across ICE curves, along with their standard deviation, to more effectively capture the influence of interactions. We provide a mathematical proof demonstrating that the PDP-based sensitivity is a lower bound of the proposed ICE-based metric under truncated orthogonal polynomial expansion. In addition, we introduce an ICE-based correlation value to quantify how interactions modify the relationship between inputs and the output. Comparative evaluations were performed on three cases: a 5-variable analytical function, a 5-variable wind-turbine fatigue problem, and a 9-variable airfoil aerodynamics case, where ICE-based sensitivity was benchmarked against PDP, SHapley Additive exPlanations (SHAP), and Sobol' indices. The results show that ICE-based feature importance provides richer insights than the traditional PDP-based approach, while visual interpretations from PDP, ICE, and SHAP complement one another by offering multiple perspectives.

We present a non-linear AI-model designed to reconstruct monthly mean anomalies of the European temperature and precipitation based on the Euro-Atlantic Weather regimes (WR) indices. WR represent recurrent, quasi-stationary, and persistent states of the atmospheric circulation that exert considerable influence over the European weather, therefore offering an opportunity for sub-seasonal to seasonal forecasting. While much research has focused on studying the correlation and impacts of the WR on European weather, the estimation of ground-level climate variables, such as temperature and precipitation, from Euro-Atlantic WR remains largely unexplored and is currently limited to linear methods. The presented AI model can capture and introduce complex non-linearities in the relation between the WR indices, describing the state of the Euro-Atlantic atmospheric circulation and the corresponding surface temperature and precipitation anomalies in Europe. We discuss the AI-model performance in reconstructing the monthly mean two-meter temperature and total precipitation anomalies in the European winter and summer, also varying the number of WR used to describe the monthly atmospheric circulation. We assess the impact of errors on the WR indices in the reconstruction and show that a mean absolute relative error below 80% yields improved seasonal reconstruction compared to the ECMWF operational seasonal forecast system, SEAS5. As a demonstration of practical applicability, we evaluate the model using WR indices predicted by SEAS5, finding slightly better or comparable skill relative to the SEAS5 forecast itself. Our findings demonstrate that WR-based anomaly reconstruction, powered by AI tools, offers a promising pathway for sub-seasonal and seasonal forecasting.