Parts of what could be a Russian drone fell on Romanian territory, Romania's Defence Minister Angel Tilvar says, two days after Ukraine said Russian drones had detonated on the NATO member's land. Romanian officials had earlier denied reports of drones falling on Romanian territory and said Russian attacks in neighbouring Ukraine did not cause a direct threat. Tilvar told local news channel Antena 3 CNN on Wednesday that parts of what was most likely a drone were discovered in the eastern Tulcea county, an area of the Danube that forms a natural border between Romania and war-torn Ukraine. "I confirm that in this area, pieces that may be of a drone were found," he said, adding that the pieces did not pose a threat. He said the area had not been evacuated because there was nothing to suggest that the parts were dangerous and said the pieces would be analysed to confirm their origin.

Almost six billion tonnes of sand and other sediment are extracted from the world's seas and oceans every year on average, according to the United Nations. The UN Environment Programme (UNEP) warned on Tuesday of the devastating toll on biodiversity and coastal communities, adding that the scale of dredging was growing, with dire consequences. "The scale of environmental impacts of shallow sea mining activities and dredging is alarming," said Pascal Peduzzi, who heads UNEP's analytics centre GRID-Geneva. He pointed to the effects on biodiversity, as well as on water turbidity, and noise effects on marine mammals. The UNEP launched a global data platform on sediment extraction in marine environments, Marine Sand Watch, which uses artificial intelligence to track and monitor dredging activities of sand, clay, silt, gravel and rock in the world's marine environment.

Geographical location is a crucial element of humanitarian response, outlining vulnerable populations, ongoing events, and available resources. Latest developments in Natural Language Processing may help in extracting vital information from the deluge of reports and documents produced by the humanitarian sector. However, the performance and biases of existing state-of-the-art information extraction tools are unknown. In this work, we develop annotated resources to fine-tune the popular Named Entity Recognition (NER) tools Spacy and roBERTa to perform geotagging of humanitarian texts. We then propose a geocoding method FeatureRank which links the candidate locations to the GeoNames database. We find that not only does the humanitarian-domain data improves the performance of the classifiers (up to F1 = 0.92), but it also alleviates some of the bias of the existing tools, which erroneously favor locations in the Western countries. Thus, we conclude that more resources from non-Western documents are necessary to ensure that off-the-shelf NER systems are suitable for the deployment in the humanitarian sector.

Russia launched a drone attack on Ukraine's Danube River port of Izmail, leading to widespread damage to infrastructure, according to the region's governor. The attack came hours ahead of talks between Russian President Vladimir Putin and his Turkish counterpart, Recep Tayyip Erdogan, which were expected to touch on ways to revive the Black Sea grain deal that Moscow abandoned in July. Ukraine and Romania disagreed over whether the attack on Izmail hit Romanian territory on the other side of the river. Foreign Minister Dmytro Kuleba said Ukraine had visual evidence of the incident. Romanian Foreign Minister Luminita Odobescu condemned the "cynical" Russian attack on Ukrainian infrastructure but said no Russian drones or debris had fallen on Romanian territory.

Debris rained from the Kyiv night sky as Russia launched air attacks on early Wednesday, killing at least two people in the Ukrainian capital, Mayor Vitali Klitschko wrote on the Telegram messaging app. Ukraine and Russia made their boldest drone and missile strikes in months on each other, with a strike in Kyiv killing two people while a strike on ships in the Black Sea and an airport near the border lasted for hours, according to local reports. "While the Russians have been retaliating brutally against Ukraine, Kyiv's incremental escalation has prevented a massive conventional (or nuclear attack) that would have obliterated Ukraine," Rebekah Koffler, president of Doctrine & Strategy Consulting and a former Defense Intelligence Agency officer, told Fox News Digital. "It's quite witty," she said. "Will this win the war for Ukraine? But it might gradually wear down the Russian people's morale."

Ukraine's forces advanced on the southern and eastern fronts during the 79th week of the country's war with Russia, reaching what experts believe to be the rear of Russia's first line of defence. But they also faced a Russian advance in the northeast that created a dilemma about where to field available troops. Ukrainian forces driving towards occupied Melitopol confirmed their recapture of Robotyne, an important Russian stronghold in western Zaporizhia, which they entered on August 20. Southern forces spokesman Oleksandr Shtupun said on August 28 that forces were busy demining the area, securing their positions and winning more territory southeast of the settlement. Geolocated footage placed them 5km (3.1 miles) southeast of Robotyne.

Ukraine bade farewell to legendary fighter pilot Andriy Pilshchykov, known by his call sign "Juice", who was killed with two other pilots during a training flight last week. A Ukrainian flag was draped over 29-year-old Pilshchykov's coffin and his cap placed on top. Russian forces shot down two Ukrainian drones over the Black Sea, the Russian state RIA news agency reported citing the Ministry of Defence. The mission of Ukraine's president in Russian-occupied Crimea said that Moscow was preparing to start a new round of mobilisation for the Russian army in the territory. The United Kingdom's defence ministry said Russia had boosted salaries and benefits for its soldiers making military service "increasingly lucrative".

Russian air defences shot down three Ukrainian drones flying over the Russian regions of Tula and Belgorod, the Ministry of Defence has reported, in the latest attempted attacks on targets inside Russian territory. Two drones "were destroyed" by air defences over the Tula region south of Moscow, the defence ministry said in a statement on the Telegram messaging app early on Tuesday morning. Another drone was "destroyed by air defence forces" over the Belgorod region, which borders Ukraine, at about 11pm Moscow time (20:00 GMT) on Monday, the ministry said in a separate statement. The ministry did not say whether there had been damage or casualties as a result of the drone raids. Moscow and other Russian regions have been hit by a barrage of Ukrainian drone attacks in recent weeks with Ukrainian President Volodymyr Zelenskyy saying late last month that the war would be returning to Russia.

Russia's defence ministry has said its air defence forces destroyed a large-scale Ukrainian-launched drone attack on the Crimean Peninsula, which Moscow annexed from Ukraine in 2014. Crimea has been targeted by Kyiv since Moscow launched its full-scale invasion of Ukraine in February 2022, but has come under more intense, increased attacks in recent weeks. The Russian Ministry of Defence said early on Friday its forces shot down nine drones, while 33 others "were suppressed by electronic warfare and crashed without reaching the target". It did not elaborate on whether there had been any damage or casualties. It added that it had also shot down a Ukraine-launched missile over the Kaluga region, which borders the Moscow region.

Logs are valuable information for oil and gas fields as they help to determine the lithology of the formations surrounding the borehole and the location and reserves of subsurface oil and gas reservoirs. However, important logs are often missing in horizontal or old wells, which poses a challenge in field applications. In this paper, we utilize data from the 2020 machine learning competition of the SPWLA, which aims to predict the missing compressional wave slowness and shear wave slowness logs using other logs in the same borehole. We employ the NGBoost algorithm to construct an Ensemble Learning model that can predicate the results as well as their uncertainty. Furthermore, we combine the SHAP method to investigate the interpretability of the machine learning model. We compare the performance of the NGBosst model with four other commonly used Ensemble Learning methods, including Random Forest, GBDT, XGBoost, LightGBM. The results show that the NGBoost model performs well in the testing set and can provide a probability distribution for the prediction results. In addition, the variance of the probability distribution of the predicted log can be used to justify the quality of the constructed log. Using the SHAP explainable machine learning model, we calculate the importance of each input log to the predicted results as well as the coupling relationship among input logs. Our findings reveal that the NGBoost model tends to provide greater slowness prediction results when the neutron porosity and gamma ray are large, which is consistent with the cognition of petrophysical models. Furthermore, the machine learning model can capture the influence of the changing borehole caliper on slowness, where the influence of borehole caliper on slowness is complex and not easy to establish a direct relationship. These findings are in line with the physical principle of borehole acoustics.