How dangerous is the situation in the West Bank? What does survival look like inside Gaza City? The Gaza-bound Global Sumud Flotilla (GSF) says a drone has struck its main ship in the Tunisian port of Sidi Bou Said, causing a fire, but that all its passengers and crew were safe. A spokesman for the GSF blamed Israel for the incident, which occurred late on Monday, but the Tunisian National Guard said reports of a drone attack were "completely unfounded". The GSF, however, insisted the incident was a drone attack and said it would provide more details on Tuesday morning.

Olive production is an important tree crop in Mediterranean climates. However, olive yield varies significantly due to climate change. Accurately estimating yield using remote sensing and machine learning remains a complex challenge. In this study, we developed a streamlined pipeline for olive yield estimation in the Kairouan and Sousse governorates of Tunisia. We extracted features from multispectral reflectance bands, vegetation indices derived from Landsat-8 OLI and Landsat-9 OLI-2 satellite imagery, along with digital elevation model data. These spatial features were combined with ground-based field survey data to form a structured tabular dataset. We then developed an automated ensemble learning framework, implemented using AutoGluon to train and evaluate multiple machine learning models, select optimal combinations through stacking, and generate robust yield predictions using five-fold cross-validation. The results demonstrate strong predictive performance from both sensors, with Landsat-8 OLI achieving R2 = 0.8635 and RMSE = 1.17 tons per ha, and Landsat-9 OLI-2 achieving R2 = 0.8378 and RMSE = 1.32 tons per ha. This study highlights a scalable, cost-effective, and accurate method for olive yield estimation, with potential applicability across diverse agricultural regions globally.

The AAAI/SIGAI Doctoral Consortium provides an opportunity for a group of PhD students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. This year, 30 students were selected for this programme, and we've been hearing from them about their research. In this interview, Amine Barrak, tells us about his work speeding up machine learning by using serverless computing. My focus is on speeding up machine learning by using serverless computing. My research is about finding a way to do machine learning training efficiently in small serverless settings.

We describe how interpretable boosting algorithms based on ridge-regularized generalized linear models can be used to analyze high-dimensional environmental data. We illustrate this by using environmental, social, human and biophysical data to predict the financial vulnerability of farmers in Chile and Tunisia against climate hazards. We show how group structures can be considered and how interactions can be found in high-dimensional datasets using a novel 2-step boosting approach. The advantages and efficacy of the proposed method are shown and discussed. Results indicate that the presence of interaction effects only improves predictive power when included in two-step boosting. The most important variable in predicting all types of vulnerabilities are natural assets. Other important variables are the type of irrigation, economic assets and the presence of crop damage of near farms.

Russia's savage, imperialistic and childish war on Ukraine has been said by democracies to be a battle between democracies and autocracies, the free world and the the unfree. And it is the opening of the battle to come between two very different sets of values. The other, more subtle, nefarious, insidious and perhaps deadlier in some ways, war is that of Artificial Intelligence. The abuse of AI has the capability to destroy human agency, take away any sense of free will, devastate human rights, divide societies and turn people under its thumb into automatons to serve the elites of corrupt, autocratic and dictatorial countries. To see how autocracies will use AI to subjugate and destroy any sense of human agency in their populations, we only have to look at how they've done so with social media.

Israeli settlers rampage through Palestinian villages, Syria's president is getting friendly with several Arab states, and attacks against African migrants in Tunisia. Here's your round up of our coverage, written by Abubakr Al-Shamahi, Al Jazeera Digital's Middle East and North Africa editor. With the backing of the United States, Israeli and Palestinian officials met at a Jordanian resort on Sunday in an attempt to reach a deal to end more than a year of intense violence. By the end of it, the two sides said they had agreed to work closely together, to bring about a "de-escalation on the ground". And, according to a joint statement, Israel even said it would suspend the building of any new settlement units in the occupied West Bank.

Machine learning and statistical modeling methods were used to analyze the impact of climate change on financial wellbeing of fruit farmers in Tunisia and Chile. The analysis was based on face to face interviews with 801 farmers. Three research questions were investigated. First, whether climate change impacts had an effect on how well the farm was doing financially. Second, if climate change was not influential, what factors were important for predicting financial wellbeing of the farm. And third, ascertain whether observed effects on the financial wellbeing of the farm were a result of interactions between predictor variables. This is the first report directly comparing climate change with other factors potentially impacting financial wellbeing of farms. Certain climate change factors, namely increases in temperature and reductions in precipitation, can regionally impact self-perceived financial wellbeing of fruit farmers. Specifically, increases in temperature and reduction in precipitation can have a measurable negative impact on the financial wellbeing of farms in Chile. This effect is less pronounced in Tunisia. Climate impact differences were observed within Chile but not in Tunisia. However, climate change is only of minor importance for predicting farm financial wellbeing, especially for farms already doing financially well. Factors that are more important, mainly in Tunisia, included trust in information sources and prior farm ownership. Other important factors include farm size, water management systems used and diversity of fruit crops grown. Moreover, some of the important factors identified differed between farms doing and not doing well financially. Interactions between factors may improve or worsen farm financial wellbeing.

The world is facing enormous challenges, ranging from climate change to extreme poverty. The 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs)a were adopted by United Nations Member States in 2015 as an operational framework to address these challenges. The SDGs include No Poverty, Quality Education, Gender Equality, Peace, Justice and Strong Institutions, among others, as well as a meta goal on Partnerships for the Goals. Despite limitations,7 the SDGs form a rare global consensus of all 193 UN member states on where we should collectively be heading. Goals are meaningless without a way to track their progress. Data on the SDGs and the associated indicatorsb are often outdated or unavailable, hindering progress during the Decade of Action leading up to 2030.c

The price of oil has hit $70 a barrel for the first time since 2014. Brent crude, the international benchmark for oil prices, jumped after the Organisation of Petroleum Exporting Countries (OPEC) said it would continue to limit supplies.

American surveillance drones have been flying over the Tunisia-Libya border to tackle threats by the Islamic State group, also known as ISIS, Tunisian President Beji Caid Essebsi said late Tuesday. He said that the drones will use his country's military bases for Tunisia's benefit. In a local television interview, Essebsi said that the U.S. drones were unarmed and they were flying over the border on Tunisia's request. It remained unclear that whether the aircraft flew across Libyan territory. Last month U.S. government sources told Reuters that American drones have started flying missions into Libya from a Tunisian air base.