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Chronique des luttes contre les violences policières depuis 2005
No full textInternational audienceVingt ans après les rébellions urbaines de 2005 qui ont suivi la mort de Zyed Benna et Bouna Traoré, le nombre connu d’interventions policières mortelles a fortement augmenté. Depuis plus de 50 ans, ce sont principalement des jeunes hommes noirs et arabes des quartiers populaires qui sont concernés. Parallèlement, depuis 10 ans, le nombre de mutilé·es par la répression de rassemblements ne cesse d’augmenter. Depuis les années 1970, dans la continuité des mobilisations des habitant·es des quartiers populaires et des héritier·ères de l’immigration post-coloniale, les luttes contre les violences policières sont toujours principalement portées par les Comités Vérité et justice
Bird Detection in the Field with the IA-Mask-RCNN
No full textInternational audienceIn recent times, field crop damage caused by birds, such as corvids and pigeons, has become crucial for many farmers. Damage can be as serious as the loss of a large part of the harvest. Several solutions have been proposed, but none are effective. An example is the use of scarecrows, but birds eventually adapt to them over time, and so they become ineffective.To study bird behavior and to propose a bird deterrent that would adapt to the presence of birds, we set up an experimental image-taking system on several plots of land over a period of 4-5 years. Around fifteen terabytes of images taken in the field were acquired. Our aim was to automatically detect these birds using deep learning methods and then to activate a real-time scarer. This work meets two challenges: the first is agroecological, as bird damage has become a major issue, and the second is IT, as it is difficult to detect birds in the field: the individuals are small because they are far from the camera lens, and field conditions are often less than optimal: darkness, confusion between the pigeons' colors and the ground, etc. The Mask-RCNN in its original configuration is not suited to detecting small individuals. We mainly focused on the model's hyperparameters to better adapt it to our study context. As a result, we improved the detection of small individuals using, among other things, appropriate anchor scales design and image processing techniques. At the same time, we built an original dataset focused on small individuals called BirdyDataset. The model can detect corvids and pigeons with an accuracy of 78% under real field conditions.</div
PANEL DISCUSSION: The Twin Transition Unpacked: Myths, Narratives, and Foundations of the Ecological and Digital – Transition & the EAD-ADERN Experienc
No full textInternational audienceSession Description: Drawing on examples from international agreements, business practices, emerging regulatory adaptations, and experiences from the Sorbonne Center for Artificial Intelligence, the panel will analyse the legal, commercial, and institutional frameworks necessary to scale the twin transition globally, with particular attention to the Global South, and explore how these developments might transform intellectual property and international law while translating high-level principes into operational, legally robust AI tools for climate action
CALIPSO Lidar Level 2 Vertical Feature Mask Data Description Document - Version 5.00
No full textThe CALIPSO lidar level 2 (L2) vertical feature mask (VFM) data product describes the vertical and horizontal distribution of cloud and aerosol layers observed by the CALIPSO lidar. The primary scientific data set (SDS) in the VFM files is the Feature Classification Flags. The Feature Classification Flags are stored as N × 5515 arrays of bit- mapped 16-bit integers, where N is the number of 15-shot (∼5 km along track) data segments in the granule. The data recorded in each 5515-element one-dimensional (1-D) array describes a vertical curtain that extends 5 km horizontally over an altitude range of 30.1 km down to –0.5 km. Each bit-mapped integer in these arrays characterizes the atmospheric state in exactly one of the range bins recorded in CALIOP’s downlinked data stream. Applying the Feature Classification Flags bit interpretations given in Table 3 yields a concise overview of the atmospheric sate within each range bin
Detectability of Gravitational-Wave Memory with LISA: A Bayesian Approach
No full textInternational audienceGravitational wave (GW) astronomy opens a new venue to explore the universe. Future observatories such as LISA, the Laser Interferometer Space Antenna, are expected to observe previously undetectable fundamental physics effects in signals predicted by General Relativity (GR).One particularly interesting such signal is associated to the displacement memory effect, which corresponds to a permanent deformation of spacetime due to the passage of gravitational radiation. In this work, we explore the ability of LISA to observe and characterize this effect. In order to do this, we use state-of-the-art simulations of the LISA instrument, and we perform a Bayesian analysis to assess the detectability and establish general conditions to claim detection of the displacement memory effect from individual massive black hole binary (MBHB) merger events in LISA. We perform parameter estimation both to explore the impact of the displacement memory effect and to reconstruct its amplitude. We discuss the precision at which such a reconstruction can be obtained thus opening the way to tests of GR and alternative theories. To provide astrophysical context, we apply our analysis to black hole binary populations models and estimate the rates at which the displacement memory effect could be observed within the LISA planned lifetime
Quasi-elastic scattering for the nuclear ground state structure: An intriguing case of Si
No full textInternational audienceQuasi-elastic (QEL) scattering measurements have been performed using the 28,30Si projectiles off the 90Zr target at energies around the Coulomb barrier. Coupled-channels (CC) calculations were carried out in a large parameter space of quadrupole and hexadecapole deformations for the N=Z, 28Si and N=Z+2, 30Si nuclei. 28Si at the N=Z line is observed to be uniquely oblate shaped in its ground state. In contrast, for 30Si with just two additional neutrons- oblate, prolate, and spherical CC descriptions are equally compatible with the measurements. To further investigate the nuclear structure evolution with varying neutron number, shell-model calculations were performed. These calculations reveal a sudden change in the nuclear structure aspects at 30Si in going from 28Si to 32Si. Combined reaction and structure analyses consistently indicate that 30Si does not possess a well-defined intrinsic shape, and it is a potential candidate for “shape fluctuations” in its ground state
All-sky search for continuous gravitational-wave signals from unknown neutron stars in binary systems in the first part of the fourth LIGO-Virgo-KAGRA observing run
No full textInternational audienceWe present the results of a blind all-sky search for continuous gravitational-wave signals from neutron stars in binary systems using data from the first part of the fourth observing run (O4a) using LIGO detectors data. Rapidly rotating, non-axisymmetric neutron stars are expected to emit continuous gravitational waves, whose detection would significantly improve our understanding of the galactic neutron star population and matter under extreme conditions, while also providing valuable tests of general relativity. Neutron stars in binary systems likely constitute a substantial fraction of the unobserved galactic population and, due to potential mass accretion, may emit stronger gravitational-wave signals than their isolated counterparts. This search targets signals from neutron stars with frequencies in the 100-350 Hz range, with orbital periods between 7 and 15 days and projected semi-major axes between 5 and 15 light-seconds. The analysis employs the GPU-accelerated fasttracks pipeline. No credible astrophysical signals were identified, and, in the absence of a detection, we report search sensitivity estimates on the population of neutron stars in binary systems in the Milky Way
GWTC-4.0: Population Properties of Merging Compact Binaries
No full textInternational audienceWe detail the population properties of merging compact objects using 158 mergers from the cumulative Gravitational-Wave Transient Catalog 4.0, which includes three types of binary mergers: binary neutron star, neutron star--black hole binary, and binary black hole mergers. We resolve multiple over- and under-densities in the black hole mass distribution: features persist at primary masses of and with a possible third feature at . These are departures from an otherwise power-law-like continuum that steepens above . Binary black holes with primary masses near are more likely to have less massive secondaries, with a mass ratio distribution peaking at , potentially a signature of stable mass transfer during binary evolution. Black hole spins are inferred to be non-extremal, with 90% of black holes having , and preferentially aligned with binary orbits, implying many merging binaries form in isolation. However, we find a significant fraction, 0.24-0.42, of binaries have negative effective inspiral spins, suggesting many could be formed dynamically in gas-free environments. We find evidence for correlation between effective inspiral spin and mass ratio, though it is unclear if this is driven by variation in the mode of the distribution or the width. (Abridged
Extension of the Total Carbon Column Observing Network (TCCON) over the Eastern Mediterranean and Middle East: the Nicosia site in Cyprus
No full textInternational audienceAbstract. Long-term greenhouse gas (GHG) measurements are essential for understanding the carbon cycle, detecting trends in atmospheric composition, and assessing the efficiency of climate change mitigation strategies. However, observational gaps over large geographic areas such as the Eastern Mediterranean and Middle East (EMME), a well-known regional GHG hotspot, are likely to increase uncertainties in estimations of their sources and sinks. Here, we describe a new Total Carbon Column Observing Network (TCCON) observatory for solar absorption spectroscopy measurements that has been operating in Nicosia, Cyprus, since September 2019. The site helps bridge a regional observational gap in the EMME, a strategic location at the crossroads of air masses from Europe, Asia, and Africa. Using near-infrared (NIR, InGaAs detector) solar absorption spectra, TCCON-Nicosia measures total column average dry-air mole fractions (Xgas) of key trace gases, including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), carbon monoxide (CO), hydrogen fluoride (HF), water vapor (H2O), and semi-heavy water (HDO). These continuous observations, spanning more than 4 years, are presented along with a description of the quality control procedures, compliant with the TCCON standards, to ensure total column atmospheric data with minimal errors. In 2023, observations were extended into the mid-infrared (MIR) spectral region with the addition of a liquid-nitrogen-cooled InSb (LN2-InSb) detector enabling the retrieval of additional trace gases such as formaldehyde (HCHO), carbonyl sulfide (OCS), nitrogen monoxide (NO), nitrogen dioxide (NO2), and ethane (C2H6), herewith further contributing to the global Network for the Detection of Atmospheric Composition Change (NDACC). To tie the TCCON Nicosia with the WMO reference scale, an AirCore (AC) campaign conducted in June 2020 over Cyprus provided vertical in situ profiles, which were converted into total column quantities (AC.Xgas) and compared to TCCON observations (Xgas). The TCCON/in situ comparison showed agreement well within their respective uncertainty budget
The Deleuzian representation hypothesis
No full textInternational audienceWe propose an alternative to sparse autoencoders (SAEs) as a simple and effective unsupervised method for extracting interpretable concepts from neural networks. The core idea is to cluster differences in activations, which we formally justify within a discriminant analysis framework. To enhance the diversity of extracted concepts, we refine the approach by weighting the clustering using the skewness of activations. The method aligns with Deleuze's modern view of concepts as differences. We evaluate the approach across five models and three modalities (vision, language, and audio), measuring concept quality, diversity, and consistency. Our results show that the proposed method achieves concept quality surpassing prior unsupervised SAE variants while approaching supervised baselines, and that the extracted concepts enable steering of a model's inner representations, demonstrating their causal influence on downstream behavior