June 2022 Across the world, video cameras have become an accepted feature of urban life. Many cities in China now have dense networks of them, and London and New Delhi aren't far behind. Now France is playing catch-up. Concerns have been raised throughout the country. But the surveillance rollout has met special resistance in Marseille, France's second-biggest city. It's unsurprising, perhaps, that activists are fighting back against the cameras, highlighting the surveillance system's overreach and underperformance.

Since the first conference In Marseille in 1982, the International Conference on Logic Programming (ICLP) has been the premier international event for presenting research in logic programming. These proceedings include technical communications about, and abstracts for presentations given at the 40th ICLP held October 14-17, in Dallas Texas, USA. The papers and abstracts in this volume include the following areas and topics. Formal and operational semantics: including non-monotonic reasoning, probabilistic reasoning, argumentation, and semantic issues of combining logic with neural models. Language design and programming methodologies such as answer set programming. inductive logic programming, and probabilistic programming. Program analysis and logic-based validation of generated programs. Implementation methodologies including constraint implementation, tabling, Logic-based prompt engineering, and the interaction of logic programming with LLMs.

Counterfactual analysis is an essential method in machine learning, policy evaluation, economics and causal inference. It involves reasoning about "what could have happened" under alternative scenarios, providing insights into causality and decision-making effectiveness. An example could be the concept of counterfactual fairness, as introduced by Kusner et al. (2017), that ensures fairness by evaluating how decisions would change under alternative, counterfactual conditions. Counterfactual fairness focuses on mitigating bias by ensuring that sensitive attributes, such as race, gender, or socioeconomic status, do not unfairly influence outcomes. Agathe Fernandes Machado acknowledges that the project leading to this publication has received funding from OBVIA. Arthur Charpentier acknowledges funding from the SCOR Foundation for Science and the National Sciences and Engineering Research Council (NSERC) for funding (RGPIN-2019-07077). Ewen Gallic acknowledges funding from the French government under the "France 2030" investment plan managed by the French National Research Agency (reference: ANR-17-EURE-0020) and from Excellence Initiative of Aix-Marseille University - A*MIDEX.

In recent years, machine learning techniques have accelerated and innovated research in numerous fields, including neuroscience. By identifying patterns in experimental data, these models could for instance predict the neural processes associated with specific experiences or with the processing of sensory stimuli. Researchers at CNRS and Université Aix-Marseille and Maastricht University recently tried to use computational models to predict how the human brain transforms sounds into semantic representations of what is happening in the surrounding environment. Their paper, published in Nature Neuroscience, shows that some deep neural network (DNN)-based models might be better at predicting neural processes from neuroimaging and experimental data. "Our main interest is to make numerical predictions about how natural sounds are perceived and represented in the brain, and to use computational models to understand how we transform the heard acoustic signal into a semantic representation of the objects and events in the auditory environment," Bruno Giordano, one of the researchers who carried out the study, told Medical Xpress.

Scientists have developed a theory that can explain how flying insects determine the gravity direction without using accelerometers. It also forms a substantial step in the creation of tiny, autonomous drones. Scientists have discovered a novel manner for flying drones and insects to estimate the gravity direction. Whereas drones typically use accelerometers to this end, the way in which flying insects do this has until now been shrouded in mystery, since they lack a specific sense for acceleration. In an article published in Nature, scientists from TU Delft and Aix Marseille Université / CNRS in France have shown that drones can estimate the gravity direction by combining visual motion sensing with a model of how they move.

The regions of Alpes-Maritimes, Var, Bouches-du-Rhône, Ardèche, Rhône, Haute-Savoie, Vendée, Maine-et-Loire and Morbihan were part of the trial - but tax officials say it may now be rolled out nationwide.

The regions of Alpes-Maritimes, Var, Bouches-du-Rhône, Ardèche, Rhône, Haute -Savoie, Vendée, Maine-et-Loire and Morbihan were part of the trial - but tax officials say it may now be rolled out nationwide.

Across the world, video cameras have become an accepted feature of urban life. Many cities in China now have dense networks of them, and London and New Delhi aren't far behind. Now France is playing catch-up. Since 2015, the year of the Bataclan terrorist attacks, the number of cameras in Paris has increased fourfold. The police have used such cameras to enforce pandemic lockdown measures and monitor protests.

MARSEILLE, France and PROVIDENCE, R.I., April 27, 2022 (GLOBE NEWSWIRE) -- Volta Medical, a pioneering medtech startup advancing novel artificial intelligence (AI) algorithms to treat cardiac arrhythmias, today announced it will participate at Heart Rhythm 2022, where Volta VX1 digital AI companion technology will be featured in several venues, including a poster session, podium presentation, Rhythm Theater program and the Volta exhibit booth. VX1 is a machine and deep learning-based algorithm designed to assist operators in the real-time manual annotation of 3D anatomical and electrical maps of the human atria during atrial fibrillation (AF) or atrial tachycardia. It is the first FDA cleared AI-based tool in interventional cardiac electrophysiology (EP). On Friday, April 29, VX1 will be highlighted in two scientific sessions: session DH-202, "Machine Learning Applications for Arrhythmia Detection and Treatment" from 10:30-11:30 a.m. Volta's Rhythm Theater presentation, "Can AI Solve the Persistent AF Paradigm?," will be held Saturday, April 30 from 10:00-11:00 a.m.

This position will investigate the application of a range of supervised learning techniques, representations and data augmentation strategies to the discovery of bioactive molecules in ultra-large libraries for selected therapeutic targets. The project will exploit large volumes of protein structure data, including recently available Alphafold2 structures. Selection criteria - Essential • A PhD awarded in an area relevant to the project. The CRCM is also affiliated to the private cancer hospital Institut Paoli Calmettes, the CNRS and Aix-Marseille University. The successful candidate will have a 3-year contract with a gross monthly salary of up to €2,900 gross monthly (depending on experience).