Search

Your search keyword '"Barreau P"' showing total 738 results
Start Over Author "Barreau P"
738 results on '"Barreau P"'

1. Robust time series generation via Schr\'odinger Bridge: a comprehensive evaluation

Author

Alouadi, Alexandre, Barreau, Baptiste, Carlier, Laurent, and Pham, Huyên

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

We investigate the generative capabilities of the Schr\"odinger Bridge (SB) approach for time series. The SB framework formulates time series synthesis as an entropic optimal interpolation transport problem between a reference probability measure on path space and a target joint distribution. This results in a stochastic differential equation over a finite horizon that accurately captures the temporal dynamics of the target time series. While the SB approach has been largely explored in fields like image generation, there is a scarcity of studies for its application to time series. In this work, we bridge this gap by conducting a comprehensive evaluation of the SB method's robustness and generative performance. We benchmark it against state-of-the-art (SOTA) time series generation methods across diverse datasets, assessing its strengths, limitations, and capacity to model complex temporal dependencies. Our results offer valuable insights into the SB framework's potential as a versatile and robust tool for time series generation., Comment: 11 pages

Published
2025

2. Optimal Sensor Placement in Power Transformers Using Physics-Informed Neural Networks

Author

Li, Sirui, Bragone, Federica, Barreau, Matthieu, Laneryd, Tor, and Morozovska, Kateryna

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

Our work aims at simulating and predicting the temperature conditions inside a power transformer using Physics-Informed Neural Networks (PINNs). The predictions obtained are then used to determine the optimal placement for temperature sensors inside the transformer under the constraint of a limited number of sensors, enabling efficient performance monitoring. The method consists of combining PINNs with Mixed Integer Optimization Programming to obtain the optimal temperature reconstruction inside the transformer. First, we extend our PINN model for the thermal modeling of power transformers to solve the heat diffusion equation from 1D to 2D space. Finally, we construct an optimal sensor placement model inside the transformer that can be applied to problems in 1D and 2D.

Published
2025

3. Accuracy and Robustness of Weight-Balancing Methods for Training PINNs

Author

Barreau, Matthieu and Shen, Haoming

Subjects
Computer Science - Machine Learning
Abstract

Physics-Informed Neural Networks (PINNs) have emerged as powerful tools for integrating physics-based models with data by minimizing both data and physics losses. However, this multi-objective optimization problem is notoriously challenging, with some benchmark problems leading to unfeasible solutions. To address these issues, various strategies have been proposed, including adaptive weight adjustments in the loss function. In this work, we introduce clear definitions of accuracy and robustness in the context of PINNs and propose a novel training algorithm based on the Primal-Dual (PD) optimization framework. Our approach enhances the robustness of PINNs while maintaining comparable performance to existing weight-balancing methods. Numerical experiments demonstrate that the PD method consistently achieves reliable solutions across all investigated cases, even in the low-data regime, and can be easily implemented, facilitating its practical adoption. The code is available at https://github.com/haoming-SHEN/Accuracy-and-Robustness-of-Weight-Balancing-Methods-for-Training-PINNs.git.

Published
2025

4. Data-Driven vs Traditional Approaches to Power Transformer's Top-Oil Temperature Estimation

Author

Tembo, Francis, Bragone, Federica, Laneryd, Tor, Barreau, Matthieu, and Morozovska, Kateryna

Subjects
Computer Science - Machine Learning
Abstract

Power transformers are subjected to electrical currents and temperature fluctuations that, if not properly controlled, can lead to major deterioration of their insulation system. Therefore, monitoring the temperature of a power transformer is fundamental to ensure a long-term operational life. Models presented in the IEC 60076-7 and IEEE standards, for example, monitor the temperature by calculating the top-oil and the hot-spot temperatures. However, these models are not very accurate and rely on the power transformers' properties. This paper focuses on finding an alternative method to predict the top-oil temperatures given previous measurements. Given the large quantities of data available, machine learning methods for time series forecasting are analyzed and compared to the real measurements and the corresponding prediction of the IEC standard. The methods tested are Artificial Neural Networks (ANNs), Time-series Dense Encoder (TiDE), and Temporal Convolutional Networks (TCN) using different combinations of historical measurements. Each of these methods outperformed the IEC 60076-7 model and they are extended to estimate the temperature rise over ambient. To enhance prediction reliability, we explore the application of quantile regression to construct prediction intervals for the expected top-oil temperature ranges. The best-performing model successfully estimates conditional quantiles that provide sufficient coverage.

Published
2025

5. MILP initialization for solving parabolic PDEs with PINNs

Author

Li, Sirui, Bragone, Federica, Barreau, Matthieu, and Morozovska, Kateryna

Subjects
Computer Science - Machine Learning
Abstract

Physics-Informed Neural Networks (PINNs) are a powerful deep learning method capable of providing solutions and parameter estimations of physical systems. Given the complexity of their neural network structure, the convergence speed is still limited compared to numerical methods, mainly when used in applications that model realistic systems. The network initialization follows a random distribution of the initial weights, as in the case of traditional neural networks, which could lead to severe model convergence bottlenecks. To overcome this problem, we follow current studies that deal with optimal initial weights in traditional neural networks. In this paper, we use a convex optimization model to improve the initialization of the weights in PINNs and accelerate convergence. We investigate two optimization models as a first training step, defined as pre-training, one involving only the boundaries and one including physics. The optimization is focused on the first layer of the neural network part of the PINN model, while the other weights are randomly initialized. We test the methods using a practical application of the heat diffusion equation to model the temperature distribution of power transformers. The PINN model with boundary pre-training is the fastest converging method at the current stage.

Published
2025

6. KKL Observer Synthesis for Nonlinear Systems via Physics-Informed Learning

Author

Niazi, M. Umar B., Cao, John, Barreau, Matthieu, and Johansson, Karl Henrik

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Machine Learning
Abstract

This paper proposes a novel learning approach for designing Kazantzis-Kravaris/Luenberger (KKL) observers for autonomous nonlinear systems. The design of a KKL observer involves finding an injective map that transforms the system state into a higher-dimensional observer state, whose dynamics is linear and stable. The observer's state is then mapped back to the original system coordinates via the inverse map to obtain the state estimate. However, finding this transformation and its inverse is quite challenging. We propose to sequentially approximate these maps by neural networks that are trained using physics-informed learning. We generate synthetic data for training by numerically solving the system and observer dynamics. Theoretical guarantees for the robustness of state estimation against approximation error and system uncertainties are provided. Additionally, a systematic method for optimizing observer performance through parameter selection is presented. The effectiveness of the proposed approach is demonstrated through numerical simulations on benchmark examples and its application to sensor fault detection and isolation in a network of Kuramoto oscillators using learned KKL observers.

Published
2025

7. Outcomes of mechanical thrombectomy in anticoagulated patients with acute distal and medium vessel stroke.

Author

Salim, Hamza, Musmar, Basel, Adeeb, Nimer, Yedavalli, Vivek, Lakhani, Dhairya, Grewal, Sahibjot, El Naamani, Kareem, Henninger, Nils, Sundararajan, Sri, Kühn, Anna, Khalife, Jane, Ghozy, Sherief, Scarcia, Luca, Tan, Benjamin, Regenhardt, Robert, Heit, Jeremy, Cancelliere, Nicole, Bernstock, Joshua, Rouchaud, Aymeric, Fiehler, Jens, Sheth, Sunil, Puri, Ajit, Dyzmann, Christian, Colasurdo, Marco, Barreau, Xavier, Renieri, Leonardo, Filipe, João, Harker, Pablo, Radu, Răzvan, Abdalkader, Mohamad, Klein, Piers, Marotta, Thomas, Spears, Julian, Ota, Takahiro, Mowla, Ashkan, Jabbour, Pascal, Biswas, Arundhati, Clarençon, Frédéric, Siegler, James, Nguyen, Thanh, Varela, Ricardo, Baker, Amanda, Essibayi, Muhammed, Altschul, David, Gonzalez, Nestor, Möhlenbruch, Markus, Costalat, Vincent, Gory, Benjamin, Stracke, Christian, Aziz-Sultan, Mohammad, Hecker, Constantin, Shaikh, Hamza, Liebeskind, David, Pedicelli, Alessandro, Alexandre, Andrea, Tancredi, Illario, Faizy, Tobias, Kalsoum, Erwah, Lubicz, Boris, Patel, Aman, Pereira, Vitor, Guenego, Adrien, and Dmytriw, Adam

Subjects
Stroke, anticoagulation, thrombectomy, Humans, Aged, Male, Female, Anticoagulants, Retrospective Studies, Ischemic Stroke, Aged, 80 and over, Thrombectomy, Treatment Outcome, Middle Aged, Stroke
Abstract

BACKGROUND: Stroke remains a major health concern globally, with oral anticoagulants widely prescribed for stroke prevention. The efficacy and safety of mechanical thrombectomy (MT) in anticoagulated patients with distal medium vessel occlusions (DMVO) are not well understood. METHODS: This retrospective analysis involved 1282 acute ischemic stroke (AIS) patients who underwent MT in 37 centers across North America, Asia, and Europe from September 2017 to July 2023. Data on demographics, clinical presentation, treatment specifics, and outcomes were collected. The primary outcomes were functional outcomes at 90 days post-MT, measured by modified Rankin Scale (mRS) scores. Secondary outcomes included reperfusion rates, mortality, and hemorrhagic complications. RESULTS: Of the patients, 223 (34%) were on anticoagulation therapy. Anticoagulated patients were older (median age 78 vs 74 years; p

Published
2024

8. Endovascular therapy versus medical management in isolated posterior cerebral artery acute ischemic stroke: A multinational multicenter propensity score-weighted study.

Author

Salim, Hamza, Pulli, Benjamin, Yedavalli, Vivek, Musmar, Basel, Adeeb, Nimer, Lakhani, Dhairya, Essibayi, Muhammed, El Naamani, Kareem, Henninger, Nils, Sundararajan, Sri, Kühn, Anna, Khalife, Jane, Ghozy, Sherief, Scarcia, Luca, Grewal, Inayat, Tan, Benjamin, Regenhardt, Robert, Heit, Jeremy, Cancelliere, Nicole, Bernstock, Joshua, Rouchaud, Aymeric, Fiehler, Jens, Sheth, Sunil, Puri, Ajit, Dyzmann, Christian, Colasurdo, Marco, Barreau, Xavier, Renieri, Leonardo, Filipe, João, Harker, Pablo, Radu, Răzvan, Abdalkader, Mohamad, Klein, Piers, Marotta, Thomas, Spears, Julian, Ota, Takahiro, Mowla, Ashkan, Jabbour, Pascal, Biswas, Arundhati, Clarençon, Frédéric, Siegler, James, Nguyen, Thanh, Varela, Ricardo, Baker, Amanda, Altschul, David, Gonzalez, Nestor, Möhlenbruch, Markus, Costalat, Vincent, Gory, Benjamin, Stracke, Christian, Aziz-Sultan, Mohammad, Hecker, Constantin, Shaikh, Hamza, Griessenauer, Christoph, Liebeskind, David, Pedicelli, Alessandro, Alexandre, Andrea, Tancredi, Illario, Faizy, Tobias, Kalsoum, Erwah, Lubicz, Boris, Patel, Aman, Pereira, Vitor, Wintermark, Max, Guenego, Adrien, and Dmytriw, Adam

Subjects
Acute ischemic stroke, endovascular therapy, medical management, posterior cerebral artery, propensity score analysis
Abstract

BACKGROUND: Despite the proven effectiveness of endovascular therapy (EVT) in acute ischemic strokes (AIS) involving anterior circulation large vessel occlusions, isolated posterior cerebral artery (PCA) occlusions (iPCAo) remain underexplored in clinical trials. This study investigates the comparative effectiveness and safety of EVT against medical management (MM) in patients with iPCAo. METHODS: This multinational, multicenter propensity score-weighted study analyzed data from the Multicenter Analysis of primary Distal medium vessel occlusions: effect of Mechanical Thrombectomy (MAD-MT) registry, involving 37 centers across North America, Asia, and Europe. We included iPCAo patients treated with either EVT or MM. The primary outcome was the modified Rankin Scale (mRS) at 90 days, with secondary outcomes including functional independence, mortality, and safety profiles such as hemorrhagic complications. RESULTS: A total of 177 patients were analyzed (88 MM and 89 EVT). EVT showed a statistically significant improvement in 90-day mRS scores (OR = 0.55, 95% CI = 0.30-1.00, p = 0.048), functional independence (OR = 2.52, 95% CI = 1.02-6.20, p = 0.045), and a reduction in 90-day mortality (OR = 0.12, 95% CI = 0.03-0.54, p = 0.006) compared to MM. Hemorrhagic complications were not significantly different between the groups. CONCLUSION: EVT for iPCAo is associated with better neurological outcomes and lower mortality compared to MM, without an increased risk of hemorrhagic complications. Nevertheless, these results should be interpreted with caution due to the studys observational design. The findings are hypothesis-generating and highlight the need for future randomized controlled trials to confirm these observations and establish definitive treatment guidelines for this patient population.

Published
2024

9. Learning and Verifying Maximal Taylor-Neural Lyapunov functions

Author

Barreau, Matthieu and Bastianello, Nicola

Subjects
Mathematics - Optimization and Control, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

We introduce a novel neural network architecture, termed Taylor-neural Lyapunov functions, designed to approximate Lyapunov functions with formal certification. This architecture innovatively encodes local approximations and extends them globally by leveraging neural networks to approximate the residuals. Our method recasts the problem of estimating the largest region of attraction - specifically for maximal Lyapunov functions - into a learning problem, ensuring convergence around the origin through robust control theory. Physics-informed machine learning techniques further refine the estimation of the largest region of attraction. Remarkably, this method is versatile, operating effectively even without simulated data points. We validate the efficacy of our approach by providing numerical certificates of convergence across multiple examples. Our proposed methodology not only competes closely with state-of-the-art approaches, such as sum-of-squares and LyZNet, but also achieves comparable results even in the absence of simulated data. This work represents a significant advancement in control theory, with broad potential applications in the design of stable control systems and beyond.

Published
2024

10. Outcomes of mechanical thrombectomy for medium vessel occlusion in acute ischemic stroke patients with ASPECTS 4–5 vs. 6–7: a retrospective, multicenter, and multinational study

Author

Musmar, Basel, Salim, Hamza Adel, Adeeb, Nimer, Yedavalli, Vivek, Lakhani, Dhairya, El Naamani, Kareem, Henninger, Nils, Sundararajan, Sri Hari, Kühn, Anna Luisa, Khalife, Jane, Ghozy, Sherief, Scarcia, Luca, Tan, Benjamin Y. Q., Regenhardt, Robert W., Heit, Jeremy J., Cancelliere, Nicole M., Bernstock, Joshua D., Rouchaud, Aymeric, Fiehler, Jens, Sheth, Sunil, Puri, Ajit S., Dyzmann, Christian, Colasurdo, Marco, Barreau, Xavier, Renieri, Leonardo, Filipe, João Pedro, Harker, Pablo, Radu, Răzvan Alexandru, Abdalkader, Mohamad, Klein, Piers, Marotta, Thomas R., Spears, Julian, Ota, Takahiro, Mowla, Ashkan, Jabbour, Pascal, Biswas, Arundhati, Clarençon, Frédéric, Siegler, James E., Nguyen, Thanh N., Varela, Ricardo, Baker, Amanda, Essibayi, Muhammed Amir, Altschul, David, Gonzalez, Nestor R., Möhlenbruch, Markus A., Costalat, Vincent, Gory, Benjamin, Stracke, Christian Paul, Aziz-Sultan, Mohammad Ali, Hecker, Constantin, Shaikh, Hamza, Liebeskind, David S., Pedicelli, Alessandro, Alexandre, Andrea M., Tancredi, Illario, Faizy, Tobias D., Kalsoum, Erwah, Lubicz, Boris, Patel, Aman B., Pereira, Vitor Mendes, Guenego, Adrien, and Dmytriw, Adam A.

Published
2025
Full Text
View/download PDF

11. BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos

Author

Duporge, Isla, Kholiavchenko, Maksim, Harel, Roi, Wolf, Scott, Rubenstein, Dan, Crofoot, Meg, Berger-Wolf, Tanya, Lee, Stephen, Barreau, Julie, Kline, Jenna, Ramirez, Michelle, and Stewart, Charles

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Using drones to track multiple individuals simultaneously in their natural environment is a powerful approach for better understanding group primate behavior. Previous studies have demonstrated that it is possible to automate the classification of primate behavior from video data, but these studies have been carried out in captivity or from ground-based cameras. To understand group behavior and the self-organization of a collective, the whole troop needs to be seen at a scale where behavior can be seen in relation to the natural environment in which ecological decisions are made. This study presents a novel dataset from drone videos for baboon detection, tracking, and behavior recognition. The baboon detection dataset was created by manually annotating all baboons in drone videos with bounding boxes. A tiling method was subsequently applied to create a pyramid of images at various scales from the original 5.3K resolution images, resulting in approximately 30K images used for baboon detection. The tracking dataset is derived from the detection dataset, where all bounding boxes are assigned the same ID throughout the video. This process resulted in half an hour of very dense tracking data. The behavior recognition dataset was generated by converting tracks into mini-scenes, a video subregion centered on each animal; each mini-scene was manually annotated with 12 distinct behavior types, resulting in over 20 hours of data. Benchmark results show mean average precision (mAP) of 92.62\% for the YOLOv8-X detection model, multiple object tracking precision (MOTA) of 63.81\% for the BotSort tracking algorithm, and micro top-1 accuracy of 63.97\% for the X3D behavior recognition model. Using deep learning to classify wildlife behavior from drone footage facilitates non-invasive insight into the collective behavior of an entire group., Comment: Dataset will be published shortly

Published
2024

12. Predictive value of follow-up infarct volume on functional outcomes in middle cerebral artery M2 segment vessel occlusion stroke treated with mechanical thrombectomy.

Author

Yedavalli, Vivek, Salim, Hamza, Musmar, Basel, Adeeb, Nimer, El Naamani, Kareem, Henninger, Nils, Sundararajan, Sri, Kühn, Anna, Khalife, Jane, Ghozy, Sherief, Scarcia, Luca, Tan, Benjamin, Regenhardt, Robert, Heit, Jeremy, Cancelliere, Nicole, Bernstock, Joshua, Rouchaud, Aymeric, Fiehler, Jens, Sheth, Sunil, Puri, Ajit, Dyzmann, Christian, Colasurdo, Marco, Barreau, Xavier, Renieri, Leonardo, Filipe, João, Harker, Pablo, Radu, Răzvan, Abdalkader, Mohamad, Klein, Piers, Marotta, Thomas, Spears, Julian, Ota, Takahiro, Mowla, Ashkan, Jabbour, Pascal, Biswas, Arundhati, Clarençon, Frédéric, Siegler, James, Nguyen, Thanh, Varela, Ricardo, Baker, Amanda, Essibayi, Muhammed, Altschul, David, Gonzalez, Nestor, Möhlenbruch, Markus, Costalat, Vincent, Gory, Benjamin, Stracke, Christian, Aziz-Sultan, Mohammad, Hecker, Constantin, Shaikh, Hamza, Liebeskind, David, Pedicelli, Alessandro, Alexandre, Andrea, Tancredi, Illario, Faizy, Tobias, Kalsoum, Erwah, Lubicz, Boris, Patel, Aman, Pereira, Vitor, Guenego, Adrien, and Dmytriw, Adam

Subjects
Stroke, follow-up infarct volume, mechanical thrombectomy, medium vessel occlusion
Abstract

BACKGROUND: Medium vessel occlusion (MeVO) strokes, particularly affecting the M2 segment of the middle cerebral artery, represent a critical proportion of acute ischemic strokes, posing significant challenges in management and outcome prediction. The efficacy of mechanical thrombectomy (MT) in MeVO stroke may warrant reliable predictors of functional outcomes. This study aimed to investigate the prognostic value of follow-up infarct volume (FIV) for predicting 90-day functional outcomes in MeVO stroke patients undergoing MT. METHODS: This multicenter, retrospective cohort study analyzed data from the Multicenter Analysis of primary Distal medium vessel occlusions: effect of Mechanical Thrombectomy (MAD-MT) registry, covering patients with acute ischemic stroke due to M2 segment occlusion treated with MT. We examined the relationship between 90-day functional outcomes, measured by the modified Rankin Scale (mRS), and follow-up infarct volume (FIV), assessed through CT or MRI within 12-36 h post-MT. RESULTS: Among 130 participants, specific FIV thresholds were identified with high specificity and sensitivity for predicting outcomes. A FIV ⩽5 ml was highly specific for predicting favorable and excellent outcomes. The optimal cut-off for both prognostications was identified at ⩽15 ml by the Youden Index, with significant reductions in the likelihood of favorable outcomes observed above a 40 ml threshold. Receiver Operator Curve (ROC) analyses confirmed FIV as a superior predictor of functional outcomes compared to traditional recanalization scores, such as final modified thrombolysis in cerebral infarction score (mTICI). Multivariable analysis further highlighted the inverse relationship between FIV and positive functional outcomes. CONCLUSIONS: FIV within 36 h post-MT serves as a potent predictor of 90-day functional outcomes in patients with M2 segment MeVO strokes. Establishing FIV thresholds may aid in the prognostication of stroke outcomes, suggesting a role for FIV in guiding post intervention treatment decisions and informing clinical practice. Future research should focus on validating these findings across diverse patient populations and exploring the integration of FIV measurements with other clinical and imaging markers to enhance outcome prediction accuracy.

Published
2024

13. Measurements of Chemical Potentials in Pb-Pb Collisions at sNN=5.02 TeV

Author

Acharya, S, Adamová, D, Rinella, G Aglieri, Aglietta, L, Agnello, M, Agrawal, N, Ahammed, Z, Ahmad, S, Ahn, SU, Ahuja, I, Akindinov, A, Al-Turany, M, Aleksandrov, D, Alessandro, B, Alfanda, HM, Molina, R Alfaro, Ali, B, Alici, A, Alizadehvandchali, N, Alkin, A, Alme, J, Alocco, G, Alt, T, Altamura, AR, Altsybeev, I, Alvarado, JR, Anaam, MN, Andrei, C, Andreou, N, Andronic, A, Andronov, E, Anguelov, V, Antinori, F, Antonioli, P, Apadula, N, Aphecetche, L, Appelshäuser, H, Arata, C, Arcelli, S, Aresti, M, Arnaldi, R, Arneiro, JGMCA, Arsene, IC, Arslandok, M, Augustinus, A, Averbeck, R, Azmi, MD, Baba, H, Badalà, A, Bae, J, Baek, YW, Bai, X, Bailhache, R, Bailung, Y, Bala, R, Balbino, A, Baldisseri, A, Balis, B, Banerjee, D, Banoo, Z, Barile, F, Barioglio, L, Barlou, M, Barman, B, Barnaföldi, GG, Barnby, LS, Barreau, E, Barret, V, Barreto, L, Bartels, C, Barth, K, Bartsch, E, Bastid, N, Basu, S, Batigne, G, Battistini, D, Batyunya, B, Bauri, D, Alba, JL Bazo, Bearden, IG, Beattie, C, Becht, P, Behera, D, Belikov, I, Hechavarria, ADC Bell, Bellini, F, Bellwied, R, Belokurova, S, Beltran, LGE, Beltran, YAV, Bencedi, G, Beole, S, Berdnikov, Y, Berdnikova, A, Bergmann, L, Besoiu, MG, Betev, L, Bhaduri, PP, Bhasin, A, and Bhat, MA

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Physical Sciences, ALICE Collaboration, Mathematical Sciences, Engineering, General Physics, Mathematical sciences, Physical sciences
Abstract

This Letter presents the most precise measurement to date of the matter-antimatter imbalance at midrapidity in Pb-Pb collisions at a center-of-mass energy per nucleon pair sqrt[s_{NN}]=5.02  TeV. Using the Statistical Hadronization framework, it is possible to obtain the value of the electric charge and baryon chemical potentials, μ_{Q}=-0.18±0.90  MeV and μ_{B}=0.71±0.45  MeV, with unprecedented precision. A centrality-differential study of the antiparticle-to-particle yield ratios of charged pions, protons, Ω baryons, and light (hyper)nuclei is performed. These results indicate that the system created in Pb-Pb collisions at the LHC is on average baryon-free and electrically neutral at midrapidity.

Published
2024

14. Outcomes with General Anesthesia Compared to Conscious Sedation for Endovascular Treatment of Medium Vessel Occlusions: Results of an International Multicentric Study

Author

Radu, Răzvan Alexandru, Costalat, Vincent, Romoli, Michele, Musmar, Basel, Siegler, James E., Ghozy, Sherief, Khalife, Jane, Salim, Hamza, Shaikh, Hamza, Adeeb, Nimer, Cuellar-Saenz, Hugo H., Thomas, Ajith J., Kadirvel, Ramanathan, Abdalkader, Mohamad, Klein, Piers, Nguyen, Thanh N., Heit, Jeremy J., Regenhardt, Robert W., Bernstock, Joshua D., Patel, Aman B., Rabinov, James D., Stapleton, Christopher J., Cancelliere, Nicole M., Marotta, Thomas R., Mendes Pereira, Vitor, El Naamani, Kareem, Amllay, Abdelaziz, Tjoumakaris, Stavropoula I., Jabbour, Pascal, Meyer, Lukas, Fiehler, Jens, Faizy, Tobias D., Guerreiro, Helena, Dusart, Anne, Bellante, Flavio, Forestier, Géraud, Rouchaud, Aymeric, Mounayer, Charbel, Kühn, Anna Luisa, Puri, Ajit S., Dyzmann, Christian, Kan, Peter T., Colasurdo, Marco, Marnat, Gaultier, Berge, Jérôme, Barreau, Xavier, Sibon, Igor, Nedelcu, Simona, Henninger, Nils, Ota, Takahiro, Dofuku, Shogo, Yeo, Leonard L. L., Tan, Benjamin YQ, Gopinathan, Anil, Martinez-Gutierrez, Juan Carlos, Salazar-Marioni, Sergio, Sheth, Sunil, Renieri, Leonardo, Capirossi, Carolina, Mowla, Ashkan, Chervak, Lina M., Vagal, Achala, Khandelwal, Priyank, Biswas, Arundhati, Clarençon, Frédéric, Elhorany, Mahmoud, Premat, Kevin, Valente, Iacopo, Pedicelli, Alessandro, Alexandre, Andrea M., Filipe, João Pedro, Varela, Ricardo, Quintero-Consuegra, Miguel, Gonzalez, Nestor R., YMD, Markus A., Jesser, Jessica, Weyland, Charlotte, ter Schiphorst, Adrien, Yedavalli, Vivek, Harker, Pablo, Aziz, Yasmin, Gory, Benjamin, Paul Stracke, Christian, Hecker, Constantin, Killer-Oberpfalzer, Monika, Griessenauer, Christoph J., Hsieh, Cheng-Yang, Liebeskind, David S., Tancredi, Illario, Fahed, Robert, Lubicz, Boris, Essibayi, Muhammed Amir, Baker, Amanda, Altschul, David, Scarcia, Luca, Kalsoum, Erwah, Dmytriw, Adam A., and Guenego, Adrien

Published
2024
Full Text
View/download PDF

15. First observation of strange baryon enhancement with effective energy in pp collisions at the LHC

Author

Acharya, S., Agarwal, A., Aglieri Rinella, G., Aglietta, L., Agnello, M., Agrawal, N., Ahammed, Z., Ahmad, S., Ahn, S. U., Ahuja, I., Akindinov, A., Akishina, V., Al-Turany, M., Aleksandrov, D., Alessandro, B., Alfanda, H. M., Alfaro Molina, R., Ali, B., Alici, A., Alizadehvandchali, N., Alkin, A., Alme, J., Alocco, G., Alt, T., Altamura, A. R., Altsybeev, I., Alvarado, J. R., Alvarez, C. O. R., Anaam, M. N., Andrei, C., Andreou, N., Andronic, A., Andronov, E., Anguelov, V., Antinori, F., Antonioli, P., Apadula, N., Aphecetche, L., Appelshäuser, H., Arata, C., Arcelli, S., Arnaldi, R., Arneiro, J. G. M. C. A., Arsene, I. C., Arslandok, M., Augustinus, A., Averbeck, R., Averyanov, D., Azmi, M. D., Baba, H., Badalà, A., Bae, J., Baek, Y. W., Bai, X., Bailhache, R., Bailung, Y., Bala, R., Balbino, A., Baldisseri, A., Balis, B., Banoo, Z., Barbasova, V., Barile, F., Barioglio, L., Barlou, M., Barman, B., Barnaföldi, G. G., Barnby, L. S., Barreau, E., Barret, V., Barreto, L., Bartels, C., Barth, K., Bartsch, E., Bastid, N., Basu, S., Batigne, G., Battistini, D., Batyunya, B., Bauri, D., Bazo Alba, J. L., Bearden, I. G., Beattie, C., Becht, P., Behera, D., Belikov, I., Bell Hechavarria, A. D. C., Bellini, F., Bellwied, R., Belokurova, S., Beltran, L. G. E., Beltran, Y. A. V., Bencedi, G., Bensaoula, A., Beole, S., Berdnikov, Y., Berdnikova, A., Bergmann, L., Besoiu, M. G., Betev, L., Bhaduri, P. P., Bhasin, A., Bhattacharjee, B., Bianchi, L., Bielčík, J., Bielčíková, J., Bigot, A. P., Bilandzic, A., Biro, G., Biswas, S., Bize, N., Blair, J. T., Blau, D., Blidaru, M. B., Bluhme, N., Blume, C., Boca, G., Bock, F., Bodova, T., Bok, J., Boldizsár, L., Bombara, M., Bond, P. M., Bonomi, G., Borel, H., Borissov, A., Borquez Carcamo, A. G., Botta, E., Bouziani, Y. E. M., Bratrud, L., Braun-Munzinger, P., Bregant, M., Broz, M., Bruno, G. E., Buchakchiev, V. D., Buckland, M. D., Budnikov, D., Buesching, H., Bufalino, S., Buhler, P., Burmasov, N., Buthelezi, Z., Bylinkin, A., Bysiak, S. A., Cabanillas Noris, J. C., Cabrera, M. F. T., Cai, M., Caines, H., Caliva, A., Calvo Villar, E., Camacho, J. M. M., Camerini, P., Canedo, F. D. M., Cantway, S. L., Carabas, M., Carballo, A. A., Carnesecchi, F., Caron, R., Carvalho, L. A. D., Castillo Castellanos, J., Castoldi, M., Catalano, F., Cattaruzzi, S., Ceballos Sanchez, C., Cerri, R., Chakaberia, I., Chakraborty, P., Chandra, S., Chapeland, S., Chartier, M., Chattopadhay, S., Chattopadhyay, S., Chattopadhyay, S., Chen, M., Cheng, T., Cheshkov, C., Chibante Barroso, V., Chinellato, D. D., Chizzali, E. S., Cho, J., Cho, S., Chochula, P., Chochulska, Z. A., Choudhury, D., Christakoglou, P., Christensen, C. H., Christiansen, P., Chujo, T., Ciacco, M., Cicalo, C., Cifarelli, L., Ciupek, M. R., Clai, G., Colamaria, F., Colburn, J. S., Colella, D., Colelli, A., Colocci, M., Concas, M., Conesa Balbastre, G., Conesa del Valle, Z., Contin, G., Contreras, J. G., Coquet, M. L., Cortese, P., Cosentino, M. R., Costa, F., Costanza, S., Cot, C., Crochet, P., Cruz-Torres, R., Czarnynoga, M. M., Dainese, A., Dange, G., Danisch, M. C., Danu, A., Das, P., Das, S., Dash, A. R., Dash, S., De Caro, A., de Cataldo, G., de Cuveland, J., De Falco, A., De Gruttola, D., De Marco, N., De Martin, C., De Pasquale, S., Deb, R., Del Grande, R., Dello Stritto, L., Deng, W., Devereaux, K. C., Dhankher, P., Di Bari, D., Di Mauro, A., Di Ruzza, B., Diab, B., Diaz, R. A., Dietel, T., Ding, Y., Ditzel, J., Divià, R., Djuvsland, Ø., Dmitrieva, U., Dobrin, A., Dönigus, B., Dubinski, J. M., Dubla, A., Dupieux, P., Dzalaiova, N., Eder, T. M., Ehlers, R. J., Eisenhut, F., Ejima, R., Elia, D., Erazmus, B., Ercolessi, F., Espagnon, B., Eulisse, G., Evans, D., Evdokimov, S., Fabbietti, L., Faggin, M., Faivre, J., Fan, F., Fan, W., Fantoni, A., Fasel, M., Feliciello, A., Feofilov, G., Fernández Téllez, A., Ferrandi, L., Ferrer, M. B., Ferrero, A., Ferrero, C., Ferretti, A., Feuillard, V. J. G., Filova, V., Finogeev, D., Fionda, F. M., Flatland, E., Flor, F., Flores, A. N., Foertsch, S., Fokin, I., Fokin, S., Follo, U., Fragiacomo, E., Frajna, E., Fuchs, U., Funicello, N., Furget, C., Furs, A., Fusayasu, T., Gaardhøje, J. J., Gagliardi, M., Gago, A. M., Gahlaut, T., Galvan, C. D., Gami, S., Gangadharan, D. R., Ganoti, P., Garabatos, C., Garcia, J. M., García Chávez, T., Garcia-Solis, E., Gargiulo, C., Gasik, P., Gaur, H. M., Gautam, A., Gay Ducati, M. B., Germain, M., Gernhaeuser, R. A., Ghosh, C., Giacalone, M., Gioachin, G., Giri, S. K., Giubellino, P., Giubilato, P., Glaenzer, A. M. C., Glässel, P., Glimos, E., Goh, D. J. Q., Gonzalez, V., Gordeev, P., Gorgon, M., Goswami, K., Gotovac, S., Grabski, V., Graczykowski, L. K., Grecka, E., Grelli, A., Grigoras, C., Grigoriev, V., Grigoryan, S., Grosa, F., Grosse-Oetringhaus, J. F., Grosso, R., Grund, D., Grunwald, N. A., Guardiano, G. G., Guernane, R., Guilbaud, M., Gulbrandsen, K., Gumprecht, J. J. W. K., Gündem, T., Gunji, T., Guo, W., Gupta, A., Gupta, R., Gupta, R., Gwizdziel, K., Gyulai, L., Hadjidakis, C., Haider, F. U., Haidlova, S., Haldar, M., Hamagaki, H., Han, Y., Hanley, B. G., Hannigan, R., Hansen, J., Haque, M. R., Harris, J. W., Harton, A., Hartung, M. V., Hassan, H., Hatzifotiadou, D., Hauer, P., Havener, L. B., Hellbär, E., Helstrup, H., Hemmer, M., Herman, T., Hernandez, S. G., Herrera Corral, G., Herrmann, S., Hetland, K. F., Heybeck, B., Hillemanns, H., Hippolyte, B., Hobus, I. P. M., Hoffmann, F. W., Hofman, B., Hong, G. H., Horst, M., Horzyk, A., Hou, Y., Hristov, P., Huhn, P., Huhta, L. M., Humanic, T. J., Hutson, A., Hutter, D., Hwang, M. C., Ilkaev, R., Inaba, M., Innocenti, G. M., Ippolitov, M., Isakov, A., Isidori, T., Islam, M. S., Iurchenko, S., Ivanov, M., Ivanov, M., Ivanov, V., Iversen, K. E., Jablonski, M., Jacak, B., Jacazio, N., Jacobs, P. M., Jadlovska, S., Jadlovsky, J., Jaelani, S., Jahnke, C., Jakubowska, M. J., Janik, M. A., Janson, T., Ji, S., Jia, S., Jiang, T., Jimenez, A. A. P., Jonas, F., Jones, D. M., Jowett, J. M., Jung, J., Jung, M., Junique, A., Jusko, A., Kaewjai, J., Kalinak, P., Kalweit, A., Karasu Uysal, A., Karatovic, D., Karatzenis, N., Karavichev, O., Karavicheva, T., Karpechev, E., Karwowska, M. J., Kebschull, U., Keil, M., Ketzer, B., Keul, J., Khade, S. S., Khan, A. M., Khan, S., Khanzadeev, A., Kharlov, Y., Khatun, A., Khuntia, A., Khuranova, Z., Kileng, B., Kim, B., Kim, C., Kim, D. J., Kim, E. J., Kim, J., Kim, J., Kim, J., Kim, M., Kim, S., Kim, T., Kimura, K., Kirkova, A., Kirsch, S., Kisel, I., Kiselev, S., Kisiel, A., Kitowski, J. P., Klay, J. L., Klein, J., Klein, S., Klein-Bösing, C., Kleiner, M., Klemenz, T., Kluge, A., Kobdaj, C., Kohara, R., Kollegger, T., Kondratyev, A., Kondratyeva, N., Konig, J., Konigstorfer, S. A., Konopka, P. J., Kornakov, G., Korwieser, M., Koryciak, S. D., Koster, C., Kotliarov, A., Kovacic, N., Kovalenko, V., Kowalski, M., Kozhuharov, V., Kozlov, G., Králik, I., Kravčáková, A., Krcal, L., Krivda, M., Krizek, F., Krizkova Gajdosova, K., Krug, C., Krüger, M., Krupova, D. M., Kryshen, E., Kučera, V., Kuhn, C., Kuijer, P. G., Kumaoka, T., Kumar, D., Kumar, L., Kumar, N., Kumar, S., Kundu, S., Kurashvili, P., Kurepin, A., Kurepin, A. B., Kuryakin, A., Kushpil, S., Kuskov, V., Kutyla, M., Kuznetsov, A., Kweon, M. J., Kwon, Y., La Pointe, S. L., La Rocca, P., Lakrathok, A., Lamanna, M., Landou, A. R., Langoy, R., Larionov, P., Laudi, E., Lautner, L., Laveaga, R. A. N., Lavicka, R., Lea, R., Lee, H., Legrand, I., Legras, G., Lehrbach, J., Lejeune, A. M., Lelek, T. M., Lemmon, R. C., León Monzón, I., Lesch, M. M., Lesser, E. D., Lévai, P., Li, M., Li, P., Li, X., Liang-gilman, B. E., Lien, J., Lietava, R., Likmeta, I., Lim, B., Lim, S. H., Lindenstruth, V., Lippmann, C., Liu, D. H., Liu, J., Liveraro, G. S. S., Lofnes, I. M., Loizides, C., Lokos, S., Lömker, J., Lopez, X., López Torres, E., Lotteau, C., Lu, P., Lu, Z., Lugo, F. V., Luhder, J. R., Lunardon, M., Luparello, G., Ma, Y. G., Mager, M., Maire, A., Majerz, E. M., Makariev, M. V., Malaev, M., Malfattore, G., Malik, N. M., Malik, S. K., Malinina, L., Mallick, D., Mallick, N., Mandaglio, G., Mandal, S. K., Manea, A., Manko, V., Manso, F., Manzari, V., Mao, Y., Marcjan, R. W., Margagliotti, G. V., Margotti, A., Marín, A., Markert, C., Marquez, C. F. B., Martinengo, P., Martínez, M. I., Martínez García, G., Martins, M. P. P., Masciocchi, S., Masera, M., Masoni, A., Massacrier, L., Massen, O., Mastroserio, A., Matonoha, O., Mattiazzo, S., Matyja, A., Mazzaschi, F., Mazzilli, M., Melikyan, Y., Melo, M., Menchaca-Rocha, A., Mendez, J. E. M., Meninno, E., Menon, A. S., Menzel, M. W., Meres, M., Miake, Y., Micheletti, L., Mihai, D., Mihaylov, D. L., Mikhaylov, K., Minafra, N., Miśkowiec, D., Modak, A., Mohanty, B., Mohisin Khan, M., Molander, M. A., Monira, S., Mordasini, C., Moreira De Godoy, D. A., Morozov, I., Morsch, A., Mrnjavac, T., Muccifora, V., Muhuri, S., Mulligan, J. D., Mulliri, A., Munhoz, M. G., Munzer, R. H., Murakami, H., Murray, S., Musa, L., Musinsky, J., Myrcha, J. W., Naik, B., Nambrath, A. I., Nandi, B. K., Nania, R., Nappi, E., Nassirpour, A. F., Nastase, V., Nath, A., Nath, S., Nattrass, C., Naydenov, M. N., Neagu, A., Negru, A., Nekrasova, E., Nellen, L., Nepeivoda, R., Nese, S., Nicassio, N., Nielsen, B. S., Nielsen, E. G., Nikolaev, S., Nikulin, S., Nikulin, V., Noferini, F., Noh, S., Nomokonov, P., Norman, J., Novitzky, N., Nowakowski, P., Nyanin, A., Nystrand, J., Oh, S., Ohlson, A., Okorokov, V. A., Oleniacz, J., Onnerstad, A., Oppedisano, C., Ortiz Velasquez, A., Otwinowski, J., Oya, M., Oyama, K., Pachmayer, Y., Padhan, S., Pagano, D., Paić, G., Paisano-Guzmán, S., Palasciano, A., Panasenko, I., Panebianco, S., Pantouvakis, C., Park, H., Park, H., Park, J., Parkkila, J. E., Patley, Y., Patra, R. N., Paul, B., Pei, H., Peitzmann, T., Peng, X., Pennisi, M., Perciballi, S., Peresunko, D., Perez, G. M., Pestov, Y., Petersen, M. T., Petrov, V., Petrovici, M., Piano, S., Pikna, M., Pillot, P., Pinazza, O., Pinsky, L., Pinto, C., Pisano, S., Płoskoń, M., Planinic, M., Pliquett, F., Plociennik, D. K., Poghosyan, M. G., Polichtchouk, B., Politano, S., Poljak, N., Pop, A., Porteboeuf-Houssais, S., Pozdniakov, V., Pozos, I. Y., Pradhan, K. K., Prasad, S. K., Prasad, S., Preghenella, R., Prino, F., Pruneau, C. A., Pshenichnov, I., Puccio, M., Pucillo, S., Qiu, S., Quaglia, L., Radhakrishnan, A. M. K., Ragoni, S., Rai, A., Rakotozafindrabe, A., Ramello, L., Rami, F., Rasa, M., Räsänen, S. S., Rath, R., Rauch, M. P., Ravasenga, I., Read, K. F., Reckziegel, C., Redelbach, A. R., Redlich, K., Reetz, C. A., Regules-Medel, H. D., Rehman, A., Reidt, F., Reme-Ness, H. A., Reygers, K., Riabov, A., Riabov, V., Ricci, R., Richter, M., Riedel, A. A., Riegler, W., Riffero, A. G., Rignanese, M., Ripoli, C., Ristea, C., Rodriguez, M. V., Rodríguez Cahuantzi, M., Rodríguez Ramírez, S. A., Røed, K., Rogalev, R., Rogochaya, E., Rogoschinski, T. S., Rohr, D., Röhrich, D., Rojas Torres, S., Rokita, P. S., Romanenko, G., Ronchetti, F., Rosas, E. D., Roslon, K., Rossi, A., Roy, A., Roy, S., Rubini, N., Rudolph, J. A., Ruggiano, D., Rui, R., Russek, P. G., Russo, R., Rustamov, A., Ryabinkin, E., Ryabov, Y., Rybicki, A., Ryu, J., Rzesa, W., Sabiu, B., Sadovsky, S., Saetre, J., Šafařík, K., Saha, S., Sahoo, B., Sahoo, R., Sahoo, S., Sahu, D., Sahu, P. K., Saini, J., Sajdakova, K., Sakai, S., Salvan, M. P., Sambyal, S., Samitz, D., Sanna, I., Saramela, T. B., Sarkar, D., Sarma, P., Sarritzu, V., Sarti, V. M., Sas, M. H. P., Sawan, S., Scapparone, E., Schambach, J., Scheid, H. S., Schiaua, C., Schicker, R., Schlepper, F., Schmah, A., Schmidt, C., Schmidt, H. R., Schmidt, M. O., Schmidt, M., Schmidt, N. V., Schmier, A. R., Schotter, R., Schröter, A., Schukraft, J., Schweda, K., Scioli, G., Scomparin, E., Seger, J. E., Sekiguchi, Y., Sekihata, D., Selina, M., Selyuzhenkov, I., Senyukov, S., Seo, J. J., Serebryakov, D., Serkin, L., Šerkšnytė, L., Sevcenco, A., Shaba, T. J., Shabetai, A., Shahoyan, R., Shangaraev, A., Sharma, B., Sharma, D., Sharma, H., Sharma, M., Sharma, S., Sharma, S., Sharma, U., Shatat, A., Sheibani, O., Shigaki, K., Shimomura, M., Shin, J., Shirinkin, S., Shou, Q., Sibiriak, Y., Siddhanta, S., Siemiarczuk, T., Silva, T. F., Silvermyr, D., Simantathammakul, T., Simeonov, R., Singh, B., Singh, B., Singh, K., Singh, R., Singh, R., Singh, R., Singh, S., Singh, V. K., Singhal, V., Sinha, T., Sitar, B., Sitta, M., Skaali, T. B., Skorodumovs, G., Smirnov, N., Snellings, R. J. M., Solheim, E. H., Song, J., Sonnabend, C., Sonneveld, J. M., Soramel, F., Soto-hernandez, A. B., Spijkers, R., Sputowska, I., Staa, J., Stachel, J., Stan, I., Steffanic, P. J., Stellhorn, T., Stiefelmaier, S. F., Stocco, D., Storehaug, I., Strangmann, N. J., Stratmann, P., Strazzi, S., Sturniolo, A., Stylianidis, C. P., Suaide, A. A. P., Suire, C., Sukhanov, M., Suljic, M., Sultanov, R., Sumberia, V., Sumowidagdo, S., Szymkowski, M., Taghavi, S. F., Taillepied, G., Takahashi, J., Tambave, G. J., Tang, S., Tang, Z., Tapia Takaki, J. D., Tapus, N., Tarasovicova, L. A., Tarzila, M. G., Tassielli, G. F., Tauro, A., Tavira García, A., Tejeda Muñoz, G., Terlizzi, L., Terrevoli, C., Thakur, S., Thomas, D., Tikhonov, A., Tiltmann, N., Timmins, A. R., Tkacik, M., Tkacik, T., Toia, A., Tokumoto, R., Tomassini, S., Tomohiro, K., Topilskaya, N., Toppi, M., Torres, V. V., Torres Ramos, A. G., Trifiró, A., Triloki, T., Triolo, A. S., Tripathy, S., Tripathy, T., Trogolo, S., Trubnikov, V., Trzaska, W. H., Trzcinski, T. P., Tsolanta, C., Tu, R., Tumkin, A., Turrisi, R., Tveter, T. S., Ullaland, K., Ulukutlu, B., Upadhyaya, S., Uras, A., Urioni, M., Usai, G. L., Vala, M., Valle, N., van Doremalen, L. V. R., van Leeuwen, M., van Veen, C. A., van Weelden, R. J. G., Vande Vyvre, P., Varga, D., Varga, Z., Vargas Torres, P., Vasileiou, M., Vasiliev, A., Vázquez Doce, O., Vazquez Rueda, O., Vechernin, V., Vercellin, E., Vergara Limón, S., Verma, R., Vermunt, L., Vértesi, R., Verweij, M., Vickovic, L., Vilakazi, Z., Villalobos Baillie, O., Villani, A., Vinogradov, A., Virgili, T., Virta, M. M. O., Vodopyanov, A., Volkel, B., Völkl, M. A., Voloshin, S. A., Volpe, G., von Haller, B., Vorobyev, I., Vozniuk, N., Vrláková, J., Wan, J., Wang, C., Wang, D., Wang, Y., Wang, Y., Wang, Z., Wegrzynek, A., Weiglhofer, F. T., Wenzel, S. C., Wessels, J. P., Wiechula, J., Wikne, J., Wilk, G., Wilkinson, J., Willems, G. A., Windelband, B., Winn, M., Wright, J. R., Wu, W., Wu, Y., Xiong, Z., Xu, R., Yadav, A., Yadav, A. K., Yamaguchi, Y., Yang, S., Yano, S., Yeats, E. R., Yin, Z., Yoo, I.-K., Yoon, J. H., Yu, H., Yuan, S., Yuncu, A., Zaccolo, V., Zampolli, C., Zanone, F., Zardoshti, N., Zarochentsev, A., Závada, P., Zaviyalov, N., Zhalov, M., Zhang, B., Zhang, C., Zhang, L., Zhang, M., Zhang, M., Zhang, S., Zhang, X., Zhang, Y., Zhang, Z., Zhao, M., Zherebchevskii, V., Zhi, Y., Zhou, D., Zhou, Y., Zhu, J., Zhu, S., Zhu, Y., Zugravel, S. C., and Zurlo, N.

Published
2025
Full Text
View/download PDF

16. Incidence and clinical outcomes of perforations during mechanical thrombectomy for medium vessel occlusion in acute ischemic stroke: A retrospective, multicenter, and multinational study.

Author

Dmytriw, Adam, Musmar, Basel, Salim, Hamza, Ghozy, Sherief, Siegler, James, Kobeissi, Hassan, Shaikh, Hamza, Khalife, Jane, Abdalkader, Mohamad, Klein, Piers, Nguyen, Thanh, Heit, Jeremy, Regenhardt, Robert, Cancelliere, Nicole, Bernstock, Joshua, Naamani, Kareem, Amllay, Abdelaziz, Meyer, Lukas, Dusart, Anne, Bellante, Flavio, Forestier, Géraud, Rouchaud, Aymeric, Saleme, Suzana, Mounayer, Charbel, Fiehler, Jens, Kühn, Anna, Puri, Ajit, Dyzmann, Christian, Kan, Peter, Colasurdo, Marco, Marnat, Gaultier, Berge, Jérôme, Barreau, Xavier, Sibon, Igor, Nedelcu, Simona, Henninger, Nils, Marotta, Thomas, Stapleton, Christopher, Rabinov, James, Ota, Takahiro, Dofuku, Shogo, Yeo, Leonard, Tan, Benjamin, Gopinathan, Anil, Martinez-Gutierrez, Juan, Salazar-Marioni, Sergio, Sheth, Sunil, Renieri, Leonardo, Capirossi, Carolina, Mowla, Ashkan, Chervak, Lina, Vagal, Achala, Adeeb, Nimer, Cuellar-Saenz, Hugo, Tjoumakaris, Stavropoula, Jabbour, Pascal, Khandelwal, Priyank, Biswas, Arundhati, Clarençon, Frédéric, Elhorany, Mahmoud, Premat, Kevin, Valente, Iacopo, Pedicelli, Alessandro, Filipe, João, Varela, Ricardo, Quintero-Consuegra, Miguel, Gonzalez, Nestor, Möhlenbruch, Markus, Jesser, Jessica, Costalat, Vincent, Ter Schiphorst, Adrien, Yedavalli, Vivek, Harker, Pablo, Aziz, Yasmin, Gory, Benjamin, Stracke, Christian, Hecker, Constantin, Kadirvel, Ramanathan, Killer-Oberpfalzer, Monika, Griessenauer, Christoph, Thomas, Ajith, Hsieh, Cheng-Yang, Liebeskind, David, Alexandru Radu, Răzvan, Alexandre, Andrea, Tancredi, Illario, Faizy, Tobias, Fahed, Robert, Weyland, Charlotte, Lubicz, Boris, Patel, Aman, Pereira, Vitor, and Guenego, Adrien

Subjects
AIS, MT, MeVo, Stroke, mechanical thrombectomy, perforation, Humans, Ischemic Stroke, Male, Retrospective Studies, Female, Aged, Middle Aged, Incidence, Thrombectomy, Treatment Outcome, Aged, 80 and over
Abstract

BACKGROUND: Mechanical thrombectomy (MT) has revolutionized the treatment of acute ischemic stroke (AIS) due to large vessel occlusion (LVO), but its efficacy and safety in medium vessel occlusion (MeVO) remain less explored. This multicenter, retrospective study aims to investigate the incidence and clinical outcomes of vessel perforations (confirmed by extravasation during an angiographic series) during MT for AIS caused by MeVO. METHODS: Data were collected from 37 academic centers across North America, Asia, and Europe between September 2017 and July 2021. A total of 1373 AIS patients with MeVO underwent MT. Baseline characteristics, procedural details, and clinical outcomes were analyzed. RESULTS: The incidence of vessel perforation was 4.8% (66/1373). Notably, our analysis indicates variations in perforation rates across different arterial segments: 8.9% in M3 segments, 4.3% in M2 segments, and 8.3% in A2 segments (p = 0.612). Patients with perforation had significantly worse outcomes, with lower rates of favorable angiographic outcomes (TICI 2c-3: 23% vs 58.9%, p

Published
2024

17. First pass effect as an independent predictor of functional outcomes in medium vessel occlusions: An analysis of an international multicenter study.

Author

Radu, Răzvan, Costalat, Vincent, Fahed, Robert, Ghozy, Sherief, Siegler, James, Shaikh, Hamza, Khalife, Jane, Abdalkader, Mohamad, Klein, Piers, Nguyen, Thanh, Heit, Jeremy, Sweid, Ahmad, El Naamani, Kareem, Regenhardt, Robert, Diestro, Jose, Cancelliere, Nicole, Amllay, Abdelaziz, Meyer, Lukas, Dusart, Anne, Bellante, Flavio, Forestier, Géraud, Rouchaud, Aymeric, Saleme, Suzana, Mounayer, Charbel, Fiehler, Jens, Kühn, Anna, Puri, Ajit, Dyzmann, Christian, Kan, Peter, Colasurdo, Marco, Marnat, Gaultier, Berge, Jérôme, Barreau, Xavier, Sibon, Igor, Nedelcu, Simona, Henninger, Nils, Kyheng, Maéva, Marotta, Thomas, Stapleton, Christopher, Rabinov, James, Ota, Takahiro, Dofuku, Shogo, Yeo, Leonard, Tan, Benjamin, Martinez-Gutierrez, Juan, Salazar-Marioni, Sergio, Sheth, Sunil, Renieri, Leonardo, Capirossi, Carolina, Mowla, Ashkan, Tjoumakaris, Stavropoula, Jabbour, Pascal, Khandelwal, Priyank, Biswas, Arundhati, Clarençon, Frédéric, Elhorany, Mahmoud, Premat, Kevin, Valente, Iacopo, Pedicelli, Alessandro, Pedro Filipe, João, Varela, Ricardo, Quintero-Consuegra, Miguel, Gonzalez, Nestor, Möhlenbruch, Markus, Jesser, Jessica, Tancredi, Illario, Ter Schiphorst, Adrien, Yedavalli, Vivek, Harker, Pablo, Chervak, Lina, Aziz, Yasmin, Gory, Benjamin, Paul Stracke, Christian, Hecker, Constantin, Killer-Oberpfalzer, Monika, Griessenauer, Christoph, Thomas, Ajith, Hsieh, Cheng-Yang, Liebeskind, David, Alexandre, Andrea, Faizy, Tobias, Weyland, Charlotte, Patel, Aman, Pereira, Vitor, Lubicz, Boris, Dmytriw, Adam, and Guenego, Adrien

Subjects
MeVO, Stroke, outcomes research, reperfusion, thrombectomy, Humans, Stroke, Brain Ischemia, Retrospective Studies, Thrombectomy, Treatment Outcome, Intracranial Hemorrhages
Abstract

INTRODUCTION: First pass effect (FPE), achievement of complete recanalization (mTICI 2c/3) with a single pass, is a significant predictor of favorable outcomes for endovascular treatment (EVT) in large vessel occlusion stroke (LVO). However, data concerning the impact on functional outcomes and predictors of FPE in medium vessel occlusions (MeVO) are scarce. PATIENTS AND METHODS: We conducted an international retrospective study on MeVO cases. Multivariable logistic modeling was used to establish independent predictors of FPE. Clinical and safety outcomes were compared between the two study groups (FPE vs non-FPE) using logistic regression models. Good outcome was defined as modified Rankin Scale 0-2 at 3 months. RESULTS: Eight hundred thirty-six patients with a final mTICI ⩾ 2b were included in this analysis. FPE was observed in 302 patients (36.1%). In multivariable analysis, hypertension (aOR 1.55, 95% CI 1.10-2.20) and lower baseline NIHSS score (aOR 0.95, 95% CI 0.93-0.97) were independently associated with an FPE. Good outcomes were more common in the FPE versus non-FPE group (72.8% vs 52.8%), and FPE was independently associated with favorable outcome (aOR 2.20, 95% CI 1.59-3.05). 90-day mortality and intracranial hemorrhage (ICH) were significantly lower in the FPE group, 0.43 (95% CI, 0.25-0.72) and 0.55 (95% CI, 0.39-0.77), respectively. CONCLUSION: Over 2/3 of patients with MeVOs and FPE in our cohort had a favorable outcome at 90 days. FPE is independently associated with favorable outcomes, it may reduce the risk of any intracranial hemorrhage, and 3-month mortality.

Published
2024

18. Investigating strangeness enhancement with multiplicity in pp collisions using angular correlations

Author

Acharya, S, Adamová, D, Agarwal, A, Aglieri Rinella, G, Aglietta, L, Agnello, M, Agrawal, N, Ahammed, Z, Ahmad, S, Ahn, SU, Ahuja, I, Akindinov, A, Akishina, V, Al-Turany, M, Aleksandrov, D, Alessandro, B, Alfanda, HM, Alfaro Molina, R, Ali, B, Alici, A, Alizadehvandchali, N, Alkin, A, Alme, J, Alocco, G, Alt, T, Altamura, AR, Altsybeev, I, Alvarado, JR, Alvarez, COR, Anaam, MN, Andrei, C, Andreou, N, Andronic, A, Andronov, E, Anguelov, V, Antinori, F, Antonioli, P, Apadula, N, Aphecetche, L, Appelshäuser, H, Arata, C, Arcelli, S, Aresti, M, Arnaldi, R, Arneiro, JGMCA, Arsene, IC, Arslandok, M, Augustinus, A, Averbeck, R, Azmi, MD, Baba, H, Badalà, A, Bae, J, Baek, YW, Bai, X, Bailhache, R, Bailung, Y, Bala, R, Balbino, A, Baldisseri, A, Balis, B, Banerjee, D, Banoo, Z, Barbasova, V, Barile, F, Barioglio, L, Barlou, M, Barman, B, Barnaföldi, GG, Barnby, LS, Barreau, E, Barret, V, Barreto, L, Bartels, C, Barth, K, Bartsch, E, Bastid, N, Basu, S, Batigne, G, Battistini, D, Batyunya, B, Bauri, D, Bazo Alba, JL, Bearden, IG, Beattie, C, Becht, P, Behera, D, Belikov, I, Bell Hechavarria, ADC, Bellini, F, Bellwied, R, Belokurova, S, Beltran, LGE, Beltran, YAV, Bencedi, G, Bensaoula, A, Beole, S, Berdnikov, Y, Berdnikova, A, and Bergmann, L

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Physical Sciences, Hadron-Hadron Scattering, Particle and Resonance Production, Particle Correlations and Fluctuations, Mathematical Physics, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Quantum Physics, Nuclear & Particles Physics, Mathematical physics, Nuclear and plasma physics, Particle and high energy physics
Abstract

A study of strange hadron production associated with hard scattering processes and with the underlying event is conducted to investigate the origin of the enhanced production of strange hadrons in small collision systems characterised by large charged-particle multiplicities. For this purpose, the production of the single-strange meson KS0 and the double-strange baryon Ξ± is measured, in each event, in the azimuthal direction of the highest-pT particle (“trigger” particle), related to hard scattering processes, and in the direction transverse to it in azimuth, associated with the underlying event, in pp collisions at s = 5.02 TeV and s = 13 TeV using the ALICE detector at the LHC. The per-trigger yields of KS0 and Ξ± are dominated by the transverse-to-leading production (i.e., in the direction transverse to the trigger particle), whose contribution relative to the toward-leading production is observed to increase with the event charged-particle multiplicity. The transverse-to-leading and the toward-leading Ξ±/KS0 yield ratios increase with the multiplicity of charged particles, suggesting that strangeness enhancement with multiplicity is associated with both hard scattering processes and the underlying event. The relative production of Ξ± with respect to KS0 is higher in transverse-to-leading processes over the whole multiplicity interval covered by the measurement. The KS0 and Ξ± per-trigger yields and yield ratios are compared with predictions of three different phenomenological models, namely Pythia8.2 with the Monash tune, Pythia8.2 with ropes and EPOS LHC. The comparison shows that none of them can quantitatively describe either the transverse-to-leading or the toward-leading yields of KS0 and Ξ±.

Published
2024

19. Measurement of beauty-quark production in pp collisions at s = 13 TeV via non-prompt D mesons

Author

Acharya, S, Adamová, D, Agarwal, A, Aglieri Rinella, G, Aglietta, L, Agnello, M, Agrawal, N, Ahammed, Z, Ahmad, S, Ahn, SU, Ahuja, I, Akindinov, A, Akishina, V, Al-Turany, M, Aleksandrov, D, Alessandro, B, Alfanda, HM, Alfaro Molina, R, Ali, B, Alici, A, Alizadehvandchali, N, Alkin, A, Alme, J, Alocco, G, Alt, T, Altamura, AR, Altsybeev, I, Alvarado, JR, Anaam, MN, Andrei, C, Andreou, N, Andronic, A, Andronov, E, Anguelov, V, Antinori, F, Antonioli, P, Apadula, N, Aphecetche, L, Appelshäuser, H, Arata, C, Arcelli, S, Aresti, M, Arnaldi, R, Arneiro, JGMCA, Arsene, IC, Arslandok, M, Augustinus, A, Averbeck, R, Azmi, MD, Baba, H, Badalà, A, Bae, J, Baek, YW, Bai, X, Bailhache, R, Bailung, Y, Bala, R, Balbino, A, Baldisseri, A, Balis, B, Banerjee, D, Banoo, Z, Barile, F, Barioglio, L, Barlou, M, Barman, B, Barnaföldi, GG, Barnby, LS, Barreau, E, Barret, V, Barreto, L, Bartels, C, Barth, K, Bartsch, E, Bastid, N, Basu, S, Batigne, G, Battistini, D, Batyunya, B, Bauri, D, Bazo Alba, JL, Bearden, IG, Beattie, C, Becht, P, Behera, D, Belikov, I, Bell Hechavarria, ADC, Bellini, F, Bellwied, R, Belokurova, S, Beltran, LGE, Beltran, YAV, Bencedi, G, Bensaoula, A, Beole, S, Berdnikov, Y, Berdnikova, A, Bergmann, L, Besoiu, MG, and Betev, L

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Mathematical Physics, Mathematical Sciences, Physical Sciences, Hadron-Hadron Scattering, Heavy Quark Production, QCD, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Quantum Physics, Nuclear & Particles Physics, Mathematical physics, Nuclear and plasma physics, Particle and high energy physics
Abstract

The pT-differential production cross sections of non-prompt D0, D+, and Ds+ mesons originating from beauty-hadron decays are measured in proton–proton collisions at a centre-of-mass energy s = 13 TeV. The measurements are performed at midrapidity, |y| < 0.5, with the data sample collected by ALICE from 2016 to 2018. The results are in agreement with predictions from several perturbative QCD calculations. The fragmentation fraction of beauty quarks to strange mesons divided by the one to non-strange mesons, fs/(fu + fd), is found to be 0.114 ± 0.016 (stat.) ± 0.006 (syst.) ± 0.003 (BR) ± 0.003 (extrap.). This value is compatible with previous measurements at lower centre-of-mass energies and in different collision systems in agreement with the assumption of universality of fragmentation functions. In addition, the dependence of the non-prompt D meson production on the centre-of-mass energy is investigated by comparing the results obtained at s = 5.02 and 13 TeV, showing a hardening of the non-prompt D-meson pT-differential production cross section at higher s. Finally, the bb¯ production cross section per unit of rapidity at midrapidity is calculated from the non-prompt D0, D+, Ds+, and Λc+ hadron measurements, obtaining dσ/dy=75.2±3.2stat.±5.2syst.−3.2+12.3extrap. μb.

Published
2024

20. Multiplicity dependence of charged-particle intra-jet properties in pp collisions at s = 13 TeV

Author

Acharya, S, Adamová, D, Rinella, G Aglieri, Aglietta, L, Agnello, M, Agrawal, N, Ahammed, Z, Ahmad, S, Ahn, SU, Ahuja, I, Akindinov, A, Al-Turany, M, Aleksandrov, D, Alessandro, B, Alfanda, HM, Molina, R Alfaro, Ali, B, Alici, A, Alizadehvandchali, N, Alkin, A, Alme, J, Alocco, G, Alt, T, Altamura, AR, Altsybeev, I, Alvarado, JR, Anaam, MN, Andrei, C, Andreou, N, Andronic, A, Andronov, E, Anguelov, V, Antinori, F, Antonioli, P, Apadula, N, Aphecetche, L, Appelshäuser, H, Arata, C, Arcelli, S, Aresti, M, Arnaldi, R, Arneiro, JGMCA, Arsene, IC, Arslandok, M, Augustinus, A, Averbeck, R, Azmi, MD, Baba, H, Badalà, A, Bae, J, Baek, YW, Bai, X, Bailhache, R, Bailung, Y, Bala, R, Balbino, A, Baldisseri, A, Balis, B, Banerjee, D, Banoo, Z, Barile, F, Barioglio, L, Barlou, M, Barman, B, Barnaföldi, GG, Barnby, LS, Barreau, E, Barret, V, Barreto, L, Bartels, C, Barth, K, Bartsch, E, Bastid, N, Basu, S, Batigne, G, Battistini, D, Batyunya, B, Bauri, D, Alba, JL Bazo, Bearden, IG, Beattie, C, Becht, P, Behera, D, Belikov, I, Bell Hechavarria, ADC, Bellini, F, Bellwied, R, Belokurova, S, Beltran, LGE, Beltran, YAV, Bencedi, G, Beole, S, Berdnikov, Y, Berdnikova, A, Bergmann, L, Besoiu, MG, Betev, L, Bhaduri, PP, Bhasin, A, and Bhat, MA

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Physical Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Quantum Physics, Nuclear & Particles Physics, Astronomical sciences, Atomic, molecular and optical physics, Particle and high energy physics
Abstract

The first measurement of the multiplicity dependence of intra-jet properties of leading charged-particle jets in proton–proton (pp) collisions is reported. The mean charged-particle multiplicity and jet fragmentation distributions are measured in minimum-bias and high-multiplicity pp collisions at center-of-mass energy s = 13 TeV using the ALICE detector. Jets are reconstructed from charged particles produced in the midrapidity region (|η|

Published
2024

21. Multicenter evaluation of mechanical thrombectomy for distal medium vessel occlusions with National Institute of Health Stroke Scale Scores ≥ 6 and ≤ 6

Author

Kühn, Anna Luisa, Puri, Ajit S., Salim, Hamza Adel, Musmar, Basel, Ghozy, Sherief, Siegler, James, Shaikh, Hamza, Khalife, Jane, Abdalkader, Mohamad, Klein, Piers, Nguyen, Thanh N., Heit, Jeremy J., Regenhardt, Robert W., Diestro, Jose Danilo Bengzon, Cancelliere, Nicole M., Sweid, Ahmad, Naamani, Kareem El, Hasan, Zuha, Gopinathan, Anil, Amllay, Abdelaziz, Meyer, Lukas, Dusart, Anne, Bellante, Flavio, Forestier, Géraud, Rouchaud, Aymeric, Saleme, Suzana, Mounayer, Charbel, Fiehler, Jens, Dyzmann, Christian, Kan, Peter T., Singh, Jasmeet, Colasurdo, Marco, Marnat, Gaultier, Berge, Jérôme, Barreau, Xavier, Sibon, Igor, Nedelcu, Simona, Henninger, Nils, Marotta, Thomas R., Stapleton, Christopher J., Rabinov, James D., Ota, Takahiro, Dofuku, Shogo, Yeo, Leonard LL., Tan, Benjamin Y. Q., Martinez-Gutierrez, Juan Carlos, Salazar-Marioni, Sergio, Sheth, Sunil, Renieri, Leonardo, Capirossi, Carolina, Mowla, Ashkan, Tjoumakaris, Stavropoula I., Jabbour, Pascal, Khandelwal, Priyank, Biswas, Arundhati, Clarençon, Frédéric, Elhorany, Mahmoud, Premat, Kevin, Valente, Iacopo, Pedicelli, Alessandro, Filipe, João Pedro, Varela, Ricardo, Quintero-Consuegra, Miguel, Gonzalez, Nestor R., Möhlenbruch, Markus A., Jesser, Jessica, Costalat, Vincent, ter Schiphorst, Adrien, Yedavalli, Vivek, Harker, Pablo, Chervak, Lina, Aziz, Yasmin, Gory, Benjamin, Stracke, Christian Paul, Hecker, Constantin, Killer-Oberpfalzer, Monika, Griessenauer, Christoph J., Thomas, Ajith, Hsieh, Cheng-Yang, Liebeskind, David S., Radu, Răzvan Alexandru, Alexandre, Andrea M., Fahed, Robert, Tancredi, Illario, Faizy, Tobias D., Weyland, Charlotte, Lubicz, Boris, Patel, Aman B., Pereira, Vitor Mendes, Guenego, Adrien, and Dmytriw, Adam A.

Published
2024
Full Text
View/download PDF

22. Adaptive Collaborative Filtering with Personalized Time Decay Functions for Financial Product Recommendation

Author

Ghiye, Ashraf, Barreau, Baptiste, Carlier, Laurent, and Vazirgiannis, Michalis

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning, Quantitative Finance - Computational Finance, Statistics - Machine Learning
Abstract

Classical recommender systems often assume that historical data are stationary and fail to account for the dynamic nature of user preferences, limiting their ability to provide reliable recommendations in time-sensitive settings. This assumption is particularly problematic in finance, where financial products exhibit continuous changes in valuations, leading to frequent shifts in client interests. These evolving interests, summarized in the past client-product interactions, see their utility fade over time with a degree that might differ from one client to another. To address this challenge, we propose a time-dependent collaborative filtering algorithm that can adaptively discount distant client-product interactions using personalized decay functions. Our approach is designed to handle the non-stationarity of financial data and produce reliable recommendations by modeling the dynamic collaborative signals between clients and products. We evaluate our method using a proprietary dataset from BNP Paribas and demonstrate significant improvements over state-of-the-art benchmarks from relevant literature. Our findings emphasize the importance of incorporating time explicitly in the model to enhance the accuracy of financial product recommendation., Comment: 10 pages, 1 figure, 2 tables, to be published in the Seventeenth ACM Conference on Recommender Systems (RecSys '23)

Published
2023
Full Text
View/download PDF

23. Correction: Perinatal foodborne titanium dioxide exposure-mediated dysbiosis predisposes mice to develop colitis through life

Author

Carlé, Caroline, Boucher, Delphine, Morelli, Luisa, Larue, Camille, Ovtchinnikova, Ekaterina, Battut, Louise, Boumessid, Kawthar, Airaud, Melvin, Quaranta-Nicaise, Muriel, Ravanat, Jean-Luc, Dietrich, Gilles, Menard, Sandrine, Eberl, Gérard, Barnich, Nicolas, Mas, Emmanuel, Carriere, Marie, Al Nabhani, Ziad, and Barreau, Frédérick

Published
2024
Full Text
View/download PDF

24. Measurement of beauty production via non-prompt charm hadrons in p–Pb collisions at sNN = 5.02 TeV

Author

Acharya, S., Adamová, D., Agarwal, A., Aglieri Rinella, G., Aglietta, L., Agnello, M., Agrawal, N., Ahammed, Z., Ahmad, S., Ahn, S. U., Ahuja, I., Akindinov, A., Akishina, V., Al-Turany, M., Aleksandrov, D., Alessandro, B., Alfanda, H. M., Alfaro Molina, R., Ali, B., Alici, A., Alizadehvandchali, N., Alkin, A., Alme, J., Alocco, G., Alt, T., Altamura, A. R., Altsybeev, I., Alvarado, J. R., Alvarez, C. O. R., Anaam, M. N., Andrei, C., Andreou, N., Andronic, A., Andronov, E., Anguelov, V., Antinori, F., Antonioli, P., Apadula, N., Aphecetche, L., Appelshäuser, H., Arata, C., Arcelli, S., Arnaldi, R., Arneiro, J. G. M. C. A., Arsene, I. C., Arslandok, M., Augustinus, A., Averbeck, R., Averyanov, D., Azmi, M. D., Baba, H., Badalà, A., Bae, J., Baek, Y. W., Bai, X., Bailhache, R., Bailung, Y., Bala, R., Balbino, A., Baldisseri, A., Balis, B., Banerjee, D., Banoo, Z., Barbasova, V., Barile, F., Barioglio, L., Barlou, M., Barman, B., Barnaföldi, G. G., Barnby, L. S., Barreau, E., Barret, V., Barreto, L., Bartels, C., Barth, K., Bartsch, E., Bastid, N., Basu, S., Batigne, G., Battistini, D., Batyunya, B., Bauri, D., Bazo Alba, J. L., Bearden, I. G., Beattie, C., Becht, P., Behera, D., Belikov, I., Bell Hechavarria, A. D. C., Bellini, F., Bellwied, R., Belokurova, S., Beltran, L. G. E., Beltran, Y. A. V., Bencedi, G., Bensaoula, A., Beole, S., Berdnikov, Y., Berdnikova, A., Bergmann, L., Besoiu, M. G., Betev, L., Bhaduri, P. P., Bhasin, A., Bhattacharjee, B., Bianchi, L., Bielčík, J., Bielčíková, J., Bigot, A. P., Bilandzic, A., Biro, G., Biswas, S., Bize, N., Blair, J. T., Blau, D., Blidaru, M. B., Bluhme, N., Blume, C., Boca, G., Bock, F., Bodova, T., Bok, J., Boldizsár, L., Bombara, M., Bond, P. M., Bonomi, G., Borel, H., Borissov, A., Borquez Carcamo, A. G., Botta, E., Bouziani, Y. E. M., Bratrud, L., Braun-Munzinger, P., Bregant, M., Broz, M., Bruno, G. E., Buchakchiev, V. D., Buckland, M. D., Budnikov, D., Buesching, H., Bufalino, S., Buhler, P., Burmasov, N., Buthelezi, Z., Bylinkin, A., Bysiak, S. A., Cabanillas Noris, J. C., Cabrera, M. F. T., Cai, M., Caines, H., Caliva, A., Calvo Villar, E., Camacho, J. M. M., Camerini, P., Canedo, F. D. M., Cantway, S. L., Carabas, M., Carballo, A. A., Carnesecchi, F., Caron, R., Carvalho, L. A. D., Castillo Castellanos, J., Castoldi, M., Catalano, F., Cattaruzzi, S., Ceballos Sanchez, C., Cerri, R., Chakaberia, I., Chakraborty, P., Chandra, S., Chapeland, S., Chartier, M., Chattopadhay, S., Chattopadhyay, S., Chattopadhyay, S., Chen, M., Cheng, T., Cheshkov, C., Chibante Barroso, V., Chinellato, D. D., Chizzali, E. S., Cho, J., Cho, S., Chochula, P., Chochulska, Z. A., Choudhury, D., Christakoglou, P., Christensen, C. H., Christiansen, P., Chujo, T., Ciacco, M., Cicalo, C., Ciupek, M. R., Clai, G., Colamaria, F., Colburn, J. S., Colella, D., Colocci, M., Concas, M., Conesa Balbastre, G., Conesa del Valle, Z., Contin, G., Contreras, J. G., Coquet, M. L., Cortese, P., Cosentino, M. R., Costa, F., Costanza, S., Cot, C., Crochet, P., Cruz-Torres, R., Cui, P., Czarnynoga, M. M., Dainese, A., Dange, G., Danisch, M. C., Danu, A., Das, P., Das, P., Das, S., Dash, A. R., Dash, S., De Caro, A., de Cataldo, G., de Cuveland, J., De Falco, A., De Gruttola, D., De Marco, N., De Martin, C., De Pasquale, S., Deb, R., Del Grande, R., Dello Stritto, L., Deng, W., Devereaux, K. C., Dhankher, P., Di Bari, D., Di Mauro, A., Diab, B., Diaz, R. A., Dietel, T., Ding, Y., Ditzel, J., Divià, R., Djuvsland, Ø., Dmitrieva, U., Dobrin, A., Dönigus, B., Dubinski, J. M., Dubla, A., Dupieux, P., Dzalaiova, N., Eder, T. M., Ehlers, R. J., Eisenhut, F., Ejima, R., Elia, D., Erazmus, B., Ercolessi, F., Espagnon, B., Eulisse, G., Evans, D., Evdokimov, S., Fabbietti, L., Faggin, M., Faivre, J., Fan, F., Fan, W., Fantoni, A., Fasel, M., Feliciello, A., Feofilov, G., Fernández Téllez, A., Ferrandi, L., Ferrer, M. B., Ferrero, A., Ferrero, C., Ferretti, A., Feuillard, V. J. G., Filova, V., Finogeev, D., Fionda, F. M., Flatland, E., Flor, F., Flores, A. N., Foertsch, S., Fokin, I., Fokin, S., Follo, U., Fragiacomo, E., Frajna, E., Fuchs, U., Funicello, N., Furget, C., Furs, A., Fusayasu, T., Gaardhøje, J. J., Gagliardi, M., Gago, A. M., Gahlaut, T., Galvan, C. D., Gangadharan, D. R., Ganoti, P., Garabatos, C., Garcia, J. M., García Chávez, T., Garcia-Solis, E., Gargiulo, C., Gasik, P., Gaur, H. M., Gautam, A., Gay Ducati, M. B., Germain, M., Gernhaeuser, R. A., Ghosh, C., Giacalone, M., Gioachin, G., Giri, S. K., Giubellino, P., Giubilato, P., Glaenzer, A. M. C., Glässel, P., Glimos, E., Goh, D. J. Q., Gonzalez, V., Gordeev, P., Gorgon, M., Goswami, K., Gotovac, S., Grabski, V., Graczykowski, L. K., Grecka, E., Grelli, A., Grigoras, C., Grigoriev, V., Grigoryan, S., Grosa, F., Grosse-Oetringhaus, J. F., Grosso, R., Grund, D., Grunwald, N. A., Guardiano, G. G., Guernane, R., Guilbaud, M., Gulbrandsen, K., Gumprecht, J. J. W. K., Gündem, T., Gunji, T., Guo, W., Gupta, A., Gupta, R., Gupta, R., Gwizdziel, K., Gyulai, L., Hadjidakis, C., Haider, F. U., Haidlova, S., Haldar, M., Hamagaki, H., Han, Y., Hanley, B. G., Hannigan, R., Hansen, J., Haque, M. R., Harris, J. W., Harton, A., Hartung, M. V., Hassan, H., Hatzifotiadou, D., Hauer, P., Havener, L. B., Hellbär, E., Helstrup, H., Hemmer, M., Herman, T., Hernandez, S. G., Herrera Corral, G., Herrmann, S., Hetland, K. F., Heybeck, B., Hillemanns, H., Hippolyte, B., Hobus, I. P. M., Hoffmann, F. W., Hofman, B., Hong, G. H., Horst, M., Horzyk, A., Hou, Y., Hristov, P., Huhn, P., Huhta, L. M., Humanic, T. J., Hutson, A., Hutter, D., Hwang, M. C., Ilkaev, R., Inaba, M., Innocenti, G. M., Ippolitov, M., Isakov, A., Isidori, T., Islam, M. S., Iurchenko, S., Ivanov, M., Ivanov, M., Ivanov, V., Iversen, K. E., Jablonski, M., Jacak, B., Jacazio, N., Jacobs, P. M., Jadlovska, S., Jadlovsky, J., Jaelani, S., Jahnke, C., Jakubowska, M. J., Janik, M. A., Janson, T., Ji, S., Jia, S., Jiang, T., Jimenez, A. A. P., Jonas, F., Jones, D. M., Jowett, J. M., Jung, J., Jung, M., Junique, A., Jusko, A., Kaewjai, J., Kalinak, P., Kalweit, A., Karasu Uysal, A., Karatovic, D., Karatzenis, N., Karavichev, O., Karavicheva, T., Karpechev, E., Karwowska, M. J., Kebschull, U., Keidel, R., Keil, M., Ketzer, B., Khade, S. S., Khan, A. M., Khan, S., Khanzadeev, A., Kharlov, Y., Khatun, A., Khuntia, A., Khuranova, Z., Kileng, B., Kim, B., Kim, C., Kim, D. J., Kim, E. J., Kim, J., Kim, J., Kim, J., Kim, M., Kim, S., Kim, T., Kimura, K., Kirkova, A., Kirsch, S., Kisel, I., Kiselev, S., Kisiel, A., Kitowski, J. P., Klay, J. L., Klein, J., Klein, S., Klein-Bösing, C., Kleiner, M., Klemenz, T., Kluge, A., Kobdaj, C., Kohara, R., Kollegger, T., Kondratyev, A., Kondratyeva, N., Konig, J., Konigstorfer, S. A., Konopka, P. J., Kornakov, G., Korwieser, M., Koryciak, S. D., Koster, C., Kotliarov, A., Kovacic, N., Kovalenko, V., Kowalski, M., Kozhuharov, V., Kozlov, G., Králik, I., Kravčáková, A., Krcal, L., Krivda, M., Krizek, F., Krizkova Gajdosova, K., Krug, C., Krüger, M., Krupova, D. M., Kryshen, E., Kučera, V., Kuhn, C., Kuijer, P. G., Kumaoka, T., Kumar, D., Kumar, L., Kumar, N., Kumar, S., Kundu, S., Kurashvili, P., Kurepin, A., Kurepin, A. B., Kuryakin, A., Kushpil, S., Kuskov, V., Kutyla, M., Kuznetsov, A., Kweon, M. J., Kwon, Y., La Pointe, S. L., La Rocca, P., Lakrathok, A., Lamanna, M., Landou, A. R., Langoy, R., Larionov, P., Laudi, E., Lautner, L., Laveaga, R. A. N., Lavicka, R., Lea, R., Lee, H., Legrand, I., Legras, G., Lehrbach, J., Lejeune, A. M., Lelek, T. M., Lemmon, R. C., León Monzón, I., Lesch, M. M., Lesser, E. D., Lévai, P., Li, M., Li, X., Liang-gilman, B. E., Lien, J., Lietava, R., Likmeta, I., Lim, B., Lim, S. H., Lindenstruth, V., Lindner, A., Lippmann, C., Liu, D. H., Liu, J., Liveraro, G. S. S., Lofnes, I. M., Loizides, C., Lokos, S., Lömker, J., Lopez, X., López Torres, E., Lotteau, C., Lu, P., Lu, Z., Lugo, F. V., Luhder, J. R., Lunardon, M., Luparello, G., Ma, Y. G., Mager, M., Maire, A., Majerz, E. M., Makariev, M. V., Malaev, M., Malfattore, G., Malik, N. M., Malik, Q. W., Malik, S. K., Malinina, L., Mallick, D., Mallick, N., Mandaglio, G., Mandal, S. K., Manea, A., Manko, V., Manso, F., Manzari, V., Mao, Y., Marcjan, R. W., Margagliotti, G. V., Margotti, A., Marín, A., Markert, C., Martinengo, P., Martínez, M. I., Martínez García, G., Martins, M. P. P., Masciocchi, S., Masera, M., Masoni, A., Massacrier, L., Massen, O., Mastroserio, A., Matonoha, O., Mattiazzo, S., Matyja, A., Mazuecos, A. L., Mazzaschi, F., Mazzilli, M., Mdhluli, J. E., Melikyan, Y., Melo, M., Menchaca-Rocha, A., Mendez, J. E. M., Meninno, E., Menon, A. S., Menzel, M. W., Meres, M., Miake, Y., Micheletti, L., Mihaylov, D. L., Mikhaylov, K., Minafra, N., Miśkowiec, D., Modak, A., Mohanty, B., Mohisin Khan, M., Molander, M. A., Monira, S., Mordasini, C., Moreira De Godoy, D. A., Morozov, I., Morsch, A., Mrnjavac, T., Muccifora, V., Muhuri, S., Mulligan, J. D., Mulliri, A., Munhoz, M. G., Munzer, R. H., Murakami, H., Murray, S., Musa, L., Musinsky, J., Myrcha, J. W., Naik, B., Nambrath, A. I., Nandi, B. K., Nania, R., Nappi, E., Nassirpour, A. F., Nath, A., Nath, S., Nattrass, C., Naydenov, M. N., Neagu, A., Negru, A., Nekrasova, E., Nellen, L., Nepeivoda, R., Nese, S., Nicassio, N., Nielsen, B. S., Nielsen, E. G., Nikolaev, S., Nikulin, S., Nikulin, V., Noferini, F., Noh, S., Nomokonov, P., Norman, J., Novitzky, N., Nowakowski, P., Nyanin, A., Nystrand, J., Oh, S., Ohlson, A., Okorokov, V. A., Oleniacz, J., Onnerstad, A., Oppedisano, C., Ortiz Velasquez, A., Otwinowski, J., Oya, M., Oyama, K., Pachmayer, Y., Padhan, S., Pagano, D., Paić, G., Paisano-Guzmán, S., Palasciano, A., Panebianco, S., Pantouvakis, C., Park, H., Park, H., Park, J., Parkkila, J. E., Patley, Y., Patra, R. N., Paul, B., Pei, H., Peitzmann, T., Peng, X., Pennisi, M., Perciballi, S., Peresunko, D., Perez, G. M., Pestov, Y., Petersen, M. T., Petrov, V., Petrovici, M., Piano, S., Pikna, M., Pillot, P., Pinazza, O., Pinsky, L., Pinto, C., Pisano, S., Płoskoń, M., Planinic, M., Pliquett, F., Plociennik, D. K., Poghosyan, M. G., Polichtchouk, B., Politano, S., Poljak, N., Pop, A., Porteboeuf-Houssais, S., Pozdniakov, V., Pozos, I. Y., Pradhan, K. K., Prasad, S. K., Prasad, S., Preghenella, R., Prino, F., Pruneau, C. A., Pshenichnov, I., Puccio, M., Pucillo, S., Qiu, S., Quaglia, L., Ragoni, S., Rai, A., Rakotozafindrabe, A., Ramello, L., Rami, F., Rasa, M., Räsänen, S. S., Rath, R., Rauch, M. P., Ravasenga, I., Read, K. F., Reckziegel, C., Redelbach, A. R., Redlich, K., Reetz, C. A., Regules-Medel, H. D., Rehman, A., Reidt, F., Reme-Ness, H. A., Rescakova, Z., Reygers, K., Riabov, A., Riabov, V., Ricci, R., Richter, M., Riedel, A. A., Riegler, W., Riffero, A. G., Rignanese, M., Ripoli, C., Ristea, C., Rodriguez, M. V., Rodríguez Cahuantzi, M., Rodríguez Ramírez, S. A., Røed, K., Rogalev, R., Rogochaya, E., Rogoschinski, T. S., Rohr, D., Röhrich, D., Rojas Torres, S., Rokita, P. S., Romanenko, G., Ronchetti, F., Rosas, E. D., Roslon, K., Rossi, A., Roy, A., Roy, S., Rubini, N., Rudolph, J. A., Ruggiano, D., Rui, R., Russek, P. G., Russo, R., Rustamov, A., Ryabinkin, E., Ryabov, Y., Rybicki, A., Ryu, J., Rzesa, W., Sabiu, B., Sadovsky, S., Saetre, J., Šafařík, K., Saha, S. K., Saha, S., Sahoo, B., Sahoo, R., Sahoo, S., Sahu, D., Sahu, P. K., Saini, J., Sajdakova, K., Sakai, S., Salvan, M. P., Sambyal, S., Samitz, D., Sanna, I., Saramela, T. B., Sarkar, D., Sarma, P., Sarritzu, V., Sarti, V. M., Sas, M. H. P., Sawan, S., Scapparone, E., Schambach, J., Scheid, H. S., Schiaua, C., Schicker, R., Schlepper, F., Schmah, A., Schmidt, C., Schmidt, H. R., Schmidt, M. O., Schmidt, M., Schmidt, N. V., Schmier, A. R., Schotter, R., Schröter, A., Schukraft, J., Schweda, K., Scioli, G., Scomparin, E., Seger, J. E., Sekiguchi, Y., Sekihata, D., Selina, M., Selyuzhenkov, I., Senyukov, S., Seo, J. J., Serebryakov, D., Serkin, L., Šerkšnytė, L., Sevcenco, A., Shaba, T. J., Shabetai, A., Shahoyan, R., Shangaraev, A., Sharma, B., Sharma, D., Sharma, H., Sharma, M., Sharma, S., Sharma, S., Sharma, U., Shatat, A., Sheibani, O., Shigaki, K., Shimomura, M., Shin, J., Shirinkin, S., Shou, Q., Sibiriak, Y., Siddhanta, S., Siemiarczuk, T., Silva, T. F., Silvermyr, D., Simantathammakul, T., Simeonov, R., Singh, B., Singh, B., Singh, K., Singh, R., Singh, R., Singh, R., Singh, S., Singh, V. K., Singhal, V., Sinha, T., Sitar, B., Sitta, M., Skaali, T. B., Skorodumovs, G., Smirnov, N., Snellings, R. J. M., Solheim, E. H., Song, J., Sonnabend, C., Sonneveld, J. M., Soramel, F., Soto-hernandez, A. B., Spijkers, R., Sputowska, I., Staa, J., Stachel, J., Stan, I., Steffanic, P. J., Stellhorn, T., Stiefelmaier, S. F., Stocco, D., Storehaug, I., Strangmann, N. J., Stratmann, P., Strazzi, S., Sturniolo, A., Stylianidis, C. P., Suaide, A. A. P., Suire, C., Sukhanov, M., Suljic, M., Sultanov, R., Sumberia, V., Sumowidagdo, S., Szymkowski, M., Taghavi, S. F., Taillepied, G., Takahashi, J., Tambave, G. J., Tang, S., Tang, Z., Tapia Takaki, J. D., Tapus, N., Tarasovicova, L. A., Tarzila, M. G., Tassielli, G. F., Tauro, A., Tavira García, A., Tejeda Muñoz, G., Telesca, A., Terlizzi, L., Terrevoli, C., Thakur, S., Thomas, D., Tikhonov, A., Tiltmann, N., Timmins, A. R., Tkacik, M., Tkacik, T., Toia, A., Tokumoto, R., Tomassini, S., Tomohiro, K., Topilskaya, N., Toppi, M., Torres, V. V., Torres Ramos, A. G., Trifiró, A., Triloki, T., Triolo, A. S., Tripathy, S., Tripathy, T., Trubnikov, V., Trzaska, W. H., Trzcinski, T. P., Tsolanta, C., Tu, R., Tumkin, A., Turrisi, R., Tveter, T. S., Ullaland, K., Ulukutlu, B., Upadhyaya, S., Uras, A., Urioni, M., Usai, G. L., Vala, M., Valle, N., van Doremalen, L. V. R., van Leeuwen, M., van Veen, C. A., van Weelden, R. J. G., Vande Vyvre, P., Varga, D., Varga, Z., Vargas Torres, P., Vasileiou, M., Vasiliev, A., Vázquez Doce, O., Vazquez Rueda, O., Vechernin, V., Vercellin, E., Vergara Limón, S., Verma, R., Vermunt, L., Vértesi, R., Verweij, M., Vickovic, L., Vilakazi, Z., Villalobos Baillie, O., Villani, A., Vinogradov, A., Virgili, T., Virta, M. M. O., Vodopyanov, A., Volkel, B., Völkl, M. A., Voloshin, S. A., Volpe, G., von Haller, B., Vorobyev, I., Vozniuk, N., Vrláková, J., Wan, J., Wang, C., Wang, D., Wang, Y., Wang, Y., Wegrzynek, A., Weiglhofer, F. T., Wenzel, S. C., Wessels, J. P., Wiechula, J., Wikne, J., Wilk, G., Wilkinson, J., Willems, G. A., Windelband, B., Winn, M., Wright, J. R., Wu, W., Wu, Y., Xiong, Z., Xu, R., Yadav, A., Yadav, A. K., Yamaguchi, Y., Yang, S., Yano, S., Yeats, E. R., Yin, Z., Yoo, I.-K., Yoon, J. H., Yu, H., Yuan, S., Yuncu, A., Zaccolo, V., Zampolli, C., Zanone, F., Zardoshti, N., Zarochentsev, A., Závada, P., Zaviyalov, N., Zhalov, M., Zhang, B., Zhang, C., Zhang, L., Zhang, M., Zhang, M., Zhang, S., Zhang, X., Zhang, Y., Zhang, Z., Zhao, M., Zherebchevskii, V., Zhi, Y., Zhou, D., Zhou, Y., Zhu, J., Zhu, S., Zhu, Y., Zugravel, S. C., and Zurlo, N.

Published
2024
Full Text
View/download PDF

25. Sensor Fault Detection and Isolation in Autonomous Nonlinear Systems Using Neural Network-Based Observers

Author

Cao, John, Niazi, Muhammad Umar B., Barreau, Matthieu, and Johansson, Karl Henrik

Subjects
Mathematics - Optimization and Control, Computer Science - Machine Learning, Mathematics - Dynamical Systems
Abstract

This paper presents a novel observer-based approach to detect and isolate faulty sensors in nonlinear systems. The proposed sensor fault detection and isolation (s-FDI) method applies to a general class of nonlinear systems. Our focus is on s-FDI for two types of faults: complete failure and sensor degradation. The key aspect of this approach lies in the utilization of a neural network-based Kazantzis-Kravaris/Luenberger (KKL) observer. The neural network is trained to learn the dynamics of the observer, enabling accurate output predictions of the system. Sensor faults are detected by comparing the actual output measurements with the predicted values. If the difference surpasses a theoretical threshold, a sensor fault is detected. To identify and isolate which sensor is faulty, we compare the numerical difference of each sensor meassurement with an empirically derived threshold. We derive both theoretical and empirical thresholds for detection and isolation, respectively. Notably, the proposed approach is robust to measurement noise and system uncertainties. Its effectiveness is demonstrated through numerical simulations of sensor faults in a network of Kuramoto oscillators.

Published
2023

26. Core-excited states of SF6 probed with soft-x-ray femtosecond transient absorption of vibrational wave packets

Author

Barreau, Lou, Ross, Andrew D, Kimberg, Victor, Krasnov, Pavel, Blinov, Svyatoslav, Neumark, Daniel M, and Leone, Stephen R

Subjects
Physical Sciences, Chemical Sciences, Atomic, Molecular and Optical Physics, Physical Chemistry, Chemical sciences, Mathematical sciences, Physical sciences
Abstract

A vibrational wavepacket in Formula Presented is created by impulsive stimulated Raman scattering with a few-cycle infrared pulse and mapped simultaneously onto five sulfur core-excited states using table-top soft x-ray transient absorption spectroscopy between 170 to 200 eV. The femtosecond vibrations induce real-time energy shifts of the x-ray absorption, whose amplitude depend strongly on the nature of the core-excited state. The pump laser intensity is used to control the number of vibrational states in the superposition, thereby accessing core-excited levels for various extensions of the S-F stretching motion. This enables the determination of the relative core-level potential energy gradients for the symmetric stretching mode, in good agreement with TDDFT calculations. This experiment demonstrates a new means of characterizing core-excited potential energy curves.

Published
2023

27. Use of the pRESET LITE thrombectomy device in combined approach for medium vessel occlusions: A multicenter evaluation

Author

Wang, Maud, Henkes, Hans, Ghozy, Sherief, Siegler, James E., Shaikh, Hamza, Khalife, Jane, Abdalkader, Mohamad, Klein, Piers, Nguyen, Thanh N., Heit, Jeremy J., Sweid, Ahmad, Naamani, Kareem El, Regenhardt, Robert W., Diestro, Jose Danilo Bengzon, Cancelliere, Nicole M., Amllay, Abdelaziz, Meyer, Lukas, Dusart, Anne, Bellante, Flavio, Forestier, Géraud, Rouchaud, Aymeric, Saleme, Suzana, Mounayer, Charbel, Fiehler, Jens, Kühn, Anna Luisa, Puri, Ajit S., Dyzmann, Christian, Kan, Peter T., Colasurdo, Marco, Marnat, Gaultier, Berge, Jérôme, Barreau, Xavier, Sibon, Igor, Nedelcu, Simona, Henninger, Nils, Weyland, Charlotte, Marotta, Thomas R., Stapleton, Christopher J., Rabinov, James D., Ota, Takahiro, Dofuku, Shogo, Yeo, Leonard LL., Tan, Benjamin Y. Q., Martinez-Gutierrez, Juan Carlos, Salazar-Marioni, Sergio, Sheth, Sunil, Renieri, Leonardo, Capirossi, Carolina, Mowla, Ashkan, Tjoumakaris, Stavropoula I., Jabbour, Pascal, Khandelwal, Priyank, Biswas, Arundhati, Clarençon, Frédéric, Elhorany, Mahmoud, Premat, Kevin, Valente, Iacopo, Pedicelli, Alessandro, Filipe, João Pedro, Varela, Ricardo, Quintero-Consuegra, Miguel, Gonzalez, Nestor R., Möhlenbruch, Markus A., Jesser, Jessica, Costalat, Vincent, ter Schiphorst, Adrien, Yedavalli, Vivek, Harker, Pablo, Chervak, Lina M., Aziz, Yasmin, Gory, Benjamin, Stracke, Christian Paul, Hecker, Constantin, Killer-Oberpfalzer, Monika, Griessenauer, Christoph J., Thomas, Ajith J., Hsieh, Cheng-Yang, Liebeskind, David S., Radu, Răzvan Alexandru, Alexandre, Andrea M., Tancredi, Illario, Faizy, Tobias D., Patel, Aman B., Pereira, Vitor Mendes, Fahed, Robert, Lubicz, Boris, Dmytriw, Adam A., and Guenego, Adrien

Published
2024
Full Text
View/download PDF

28. Core-excited states of SF$_{6}$ probed with soft X-ray femtosecond transient absorption of vibrational wavepackets

Author

Barreau, Lou, Ross, Andrew D., Kimberg, Victor, Krasnov, Pavel, Blinov, Svyatoslav, Neumark, Daniel M., and Leone, Stephen R.

Subjects
Physics - Chemical Physics, Physics - Atomic Physics
Abstract

A vibrational wavepacket in SF$_6$, created by impulsive stimulated Raman scattering with a few-cycle infrared pulse, is mapped onto five sulfur core-excited states using table-top soft X-ray transient absorption spectroscopy between 170-200 eV. The amplitudes of the X-ray energy shifts of the femtosecond oscillations depend strongly on the nature of the state. The prepared wavepacket is controlled with the pump laser intensity to probe the core-excited levels for various extensions of the S-F stretching motion. This allows the determination of the relative core-level potential energy gradients, in good agreement with TDDFT calculations. This experiment demonstrates a new means of characterizing core-excited potential energy surfaces.

Published
2022
Full Text
View/download PDF

29. Stress, Anxiety, and School Burnout Post COVID-19: A Study of French Adolescents

Author

Simoës-Perlant, Aurélie, Barreau, Marion, and Vezilier, Caroline

Abstract

This study examined the symptoms of exhaustion, school stress and anxious school refusal from a comparative developmental perspective in French adolescents enrolled in public and private general, technological and vocational schools. It is particularly important to consider academic stress levels, anxiety and school burnout in middle and high school students as they are linked to many mental health problems, such as depression or suicidal thoughts. In this study, four hundred and ninety-three adolescents completed an online questionnaire consisting of the School Burnout Inventory, the Echelle Toulousaine de Stress Scolaire perçu and the School refusal evaluation was developed. The results show a very high percentage of suffering among teenagers. The young people most affected are high school students and more particularly students in 10th and 12th grade, with nearly three-quarters of them suffering from school burnout and/or high school stress, without any distinction between the sexes or the type of schooling.

Published
2023
Full Text
View/download PDF

30. Physics-informed Learning for Identification and State Reconstruction of Traffic Density

Author

Barreau, Matthieu, Aguiar, Miguel, Liu, John, and Johansson, Karl Henrik

Subjects
Mathematics - Optimization and Control
Abstract

We consider the problem of traffic density reconstruction using measurements from probe vehicles (PVs) with a low penetration rate. In other words, the number of sensors is small compared to the number of vehicles on the road. The model used assumes noisy measurements and a partially unknown first-order model. All these considerations make the use of machine learning to reconstruct the state the only applicable solution. We first investigate how the identification and reconstruction processes can be merged and how a sparse dataset can still enable a good identification. Secondly, we propose a pre-training procedure that aids the hyperparameter tuning, preventing the gradient descent algorithm from getting stuck at saddle points. Examples using numerical simulations and the SUMO traffic simulator show that the reconstructions are close to the real density in all cases., Comment: 7 pages, 3 figures, conference paper (CDC 2021)

Published
2021

31. Lyapunov Stability Analysis of a Mass-Spring system subject to Friction

Author

Barreau, Matthieu, Tarbouriech, Sophie, and Gouaisbaut, Frederic

Subjects
Mathematics - Optimization and Control
Abstract

This paper deals with the stability analysis of a mass-spring system subject to friction using Lyapunov-based arguments. As the described system presents a stick-slip phenomenon, the mass may then periodically sticks to the ground. The objective consists of developing numerically tractable conditions ensuring the global asymptotic stability of the unique equilibrium point. The proposed approach merges two intermediate results: The first one relies on the characterization of an attractor around the origin, to which converges the closed-loop trajectories. The second result assesses the regional asymptotic stability of the equilibrium point by estimating its basin of attraction. The main result relies on conditions allowing to ensure that the attractor issued from the first result is included in the basin of attraction of the origin computed from the second result. An illustrative example draws the interest of the approach.

Published
2021

32. History-Augmented Collaborative Filtering for Financial Recommendations

Author

Barreau, Baptiste and Carlier, Laurent

Subjects
Computer Science - Machine Learning, Quantitative Finance - Computational Finance, Statistics - Machine Learning
Abstract

In many businesses, and particularly in finance, the behavior of a client might drastically change over time. It is consequently crucial for recommender systems used in such environments to be able to adapt to these changes. In this study, we propose a novel collaborative filtering algorithm that captures the temporal context of a user-item interaction through the users' and items' recent interaction histories to provide dynamic recommendations. The algorithm, designed with issues specific to the financial world in mind, uses a custom neural network architecture that tackles the non-stationarity of users' and items' behaviors. The performance and properties of the algorithm are monitored in a series of experiments on a G10 bond request for quotation proprietary database from BNP Paribas Corporate and Institutional Banking.

Published
2021
Full Text
View/download PDF

33. Learning-based State Reconstruction for a Scalar Hyperbolic PDE under noisy Lagrangian Sensing

Author

Barreau, M., Liu, J., and Johansson, K. H.

Subjects
Mathematics - Optimization and Control
Abstract

The state reconstruction problem of a heterogeneous dynamic system under sporadic measurements is considered. This system consists of a conversation flow together with a multi-agent network modeling particles within the flow. We propose a partial-state reconstruction algorithm using physics-informed learning based on local measurements obtained from these agents. Traffic density reconstruction is used as an example to illustrate the results and it is shown that the approach provides an efficient noise rejection.

Published
2020

34. Learning-based Traffic State Reconstruction using Probe Vehicles

Author

Liu, John, Barreau, Matthieu, Cicic, Mladen, and Johansson, Karl H.

Subjects
Mathematics - Optimization and Control
Abstract

This article investigates the use of a model-based neural-network for the traffic reconstruction problem using noisy measurements coming from probe vehicles. The traffic state is assumed to be the density only, modeled by a partial differential equation. There exist various methods for reconstructing the density in that case. However, none of them perform well with noise and very few deal with lagrangian measurements. This paper introduces a method that can reduce the processes of identification, reconstruction, prediction, and noise rejection into a single optimization problem. Numerical simulations, based either on a macroscopic or a microscopic model, show good performance for a moderate computational burden., Comment: 7 pages, 8 figures

Published
2020

35. Numerical Investigation of Traffic State Reconstruction and Control Using Connected Automated Vehicles

Author

Cicic, Mladen, Barreau, Matthieu, and Johansson, Karl Henrik

Subjects
Mathematics - Optimization and Control
Abstract

In this paper we present a numerical study on control and observation of traffic flow using Lagrangian measurements and actuators. We investigate the effect of some basic control and observation schemes using probe and actuated vehicles within the flow. The aim is to show the effect of the state reconstruction on the efficiency of the control, compared to the case using full information about the traffic. The effectiveness of the proposed state reconstruction and control algorithms is demonstrated in simulations. They show that control using the reconstructed state approaches the full-information control when the gap between the connected vehicles is not too large, reducing the delay by more than $60\%$ when the gap between the sensor vehicles is $1.25$~km on average, compared to a delay reduction of almost $80\%$ in the full-information control case. %It shows that the reconstruction is well achieved if the distance between two connected and autonomous vehicles is not too large (more than 1 vehicle per kilometer). %We also show that it is possible to further improve the control performance by employing a simple adaptive probe vehicle selection scheme. Moreover, we propose a simple scheme for selecting which vehicles to use as sensors, in order to reduce the communication burden. Numerical simulations demonstrate that %It also demonstrates that it is possible to reduce the communication burden using a triggering mechanism with with this triggering mechanism, the delay is reduced by around $65\%$, compared to a reduction of $72\%$ if all connected vehicles are communicating at all times.

Published
2020

36. Attosecond photoionization dynamics in the vicinity of the Cooper minima in argon

Author

Alexandridi, C., Platzer, D., Barreau, L., Busto, D., Zhong, S., Turconi, M., Neoričić, L., Laurell, H., Arnold, C. L., Borot, A., Hergott, J. -F., Tcherbakoff, O., Lejman, M., Gisselbrecht, M., Lindroth, E., L'Huillier, A., Dahlström, J. M., and Salières, P.

Subjects
Physics - Atomic Physics
Abstract

Using a spectrally resolved electron interferometry technique, we measure photoionization time delays between the $3s$ and $3p$ subshells of argon over a large 34-eV energy range covering the Cooper minima in both subshells. The observed strong variations of the $3s-3p$ delay difference, including a sign change, are well reproduced by theoretical calculations using the Two-Photon Two-Color Random Phase Approximation with Exchange. Strong shake-up channels lead to photoelectrons spectrally overlapping with those emitted from the $3s$ subshell. These channels need to be included in our analysis to reproduce the experimental data. Our measurements provide a stringent test for multielectronic theoretical models aiming at an accurate description of inter-channel correlation.

Published
2020
Full Text
View/download PDF

37. Dynamic Traffic Reconstruction using Probe Vehicles

Author

Barreau, Matthieu, Selivanov, Anton, and Johansson, Karl Henrik

Subjects
Mathematics - Optimization and Control, Mathematics - Analysis of PDEs
Abstract

This article deals with the observation problem in traffic flow theory. The model used is the semilinear viscous Burgers equation. Instead of using the traditional fixed sensors to estimate the state of the traffic at given points, the measurements here are obtained from Probe Vehicles (PVs). We propose then a moving dynamic boundary observer whose boundaries are defined by the trajectories of the PVs. The main result of this article is the exponential convergence of the observation error, and, in some cases, its finite-time convergence. Finally, numerical simulations show that it is possible to observe the traffic in the congested, free-flow, and mixed regimes provided that the number of PVs is large enough., Comment: 6 pages, 3 figures, CDC conference paper

Published
2020

38. Revealing electronic state-switching at conical intersections in alkyl iodides by ultrafast XUV transient absorption spectroscopy

Author

Chang, Kristina F., Reduzzi, Maurizio, Wang, Han, Poullain, Sonia M., Kobayashi, Yuki, Barreau, Lou, Prendergast, David, Neumark, Daniel M., and Leone, Stephen R.

Subjects
Physics - Chemical Physics, Physics - Atomic and Molecular Clusters
Abstract

Conical intersections between electronic states often dictate the chemistry of photoexcited molecules. Recently developed sources of ultrashort extreme ultraviolet (XUV) pulses tuned to element-specific transitions in molecules allow for the unambiguous detection of electronic state-switching at a conical intersection. Here, the fragmentation of photoexcited iso-propyl iodide and tert-butyl iodide molecules (i-C$_{3}$H$_{7}$I and t-C$_{4}$H$_{9}$I) through a conical intersection between $^{3}$Q$_{0}$/$^{1}$Q$_{1}$ spin-orbit states is revealed by ultrafast XUV transient absorption measuring iodine 4d core-to-valence transitions. The electronic state-sensitivity of the technique allows for a complete mapping of molecular dissociation from photoexcitation to photoproducts. In both molecules, the sub-100 fs transfer of a photoexcited wave packet from the $^{3}$Q$_{0}$ state into the $^{1}$Q$_{1}$ state at the conical intersection is captured. The results show how differences in the electronic state-switching of the wave packet in i-C$_{3}$H$_{7}$I and t-C$_{4}$H$_{9}$I directly lead to differences in the photoproduct branching ratio of the two systems.

Published
2020

40. Integral Quadratic Constraints on Linear Infinite-dimensional Systems for Robust Stability Analysis

Author

Matthieu, Barreau, W., Scherer Carsten, Frederic, Gouaisbaut, and Alexandre, Seuret

Subjects
Mathematics - Optimization and Control, Mathematics - Analysis of PDEs
Abstract

This paper proposes a framework to assess the stability of an ordinary differential equation which is coupled to a 1D-partial differential equation (PDE). The stability theorem is based on a new result on Integral Quadratic Constraints (IQCs) and expressed in terms of two linear matrix inequalities with a moderate computational burden. The IQCs are not generated using dissipation inequalities involving the whole state of an infinite-dimensional system, but by using projection coefficients of the infinite-dimensional state. This permits to generalize our robustness result to many other PDEs. The proposed methodology is applied to a time-delay system and numerical results comparable to those in the literature are obtained.

Published
2020

41. Efficient table-top dual-wavelength beamline for ultrafast transient absorption spectroscopy in the soft X-ray region

Author

Barreau, Lou, Ross, Andrew D., Garg, Samay, Kraus, Peter M., Neumark, Daniel M., and Leone, Stephen R.

Subjects
Physics - Optics, Physics - Chemical Physics
Abstract

We present a table-top beamline providing a soft X-ray supercontinuum extending up to 350 eV from high-order harmonic generation with sub-13 fs 1300 nm driving pulses and simultaneous production of sub-5 fs pulses centered at 800 nm. Optimization of the high harmonic generation in a long and dense gas medium yields a photon flux of ~2 x 10^7 photons/s/1% bandwidth at 300 eV. The temporal resolution of X-ray transient absorption experiments with this beamline is measured to be 11 fs for 800 nm excitation. This dual-wavelength approach, combined with high flux and high spectral and temporal resolution soft X-ray absorption spectroscopy, is a new route to the study of ultrafast electronic dynamics in carbon-containing molecules and materials at the carbon K-edge.

Published
2019
Full Text
View/download PDF

42. Deep Prediction of Investor Interest: a Supervised Clustering Approach

Author

Barreau, Baptiste, Carlier, Laurent, and Challet, Damien

Subjects
Computer Science - Machine Learning, Quantitative Finance - Computational Finance, Statistics - Machine Learning
Abstract

We propose a novel deep learning architecture suitable for the prediction of investor interest for a given asset in a given time frame. This architecture performs both investor clustering and modelling at the same time. We first verify its superior performance on a synthetic scenario inspired by real data and then apply it to two real-world databases, a publicly available dataset about the position of investors in Spanish stock market and proprietary data from BNP Paribas Corporate and Institutional Banking.

Published
2019
Full Text
View/download PDF

43. Practical Stability Analysis of a Drilling Pipe under Friction with a PI-Controller

Author

Barreau, Matthieu, Gouaisbaut, Frédéric, and Seuret, Alexandre

Subjects
Mathematics - Optimization and Control, Mathematics - Analysis of PDEs
Abstract

This paper deals with the exponential stability of a drilling pipe controlled by a PI controller. The model used leads to a coupled ODE / PDE and is consequently of infinite dimension. Using recent advances in time-delay systems, we derive a new Lyapunov functional based on an state extension made up of projections of the Riemann coordinates. Two cases will be considered. First, we will provide an exponential stability result expressed using the LMI framework. This result is dedicated to a linear version of the torsional dynamic. On a second hand, the nonlinear terms in the initial model, that generates the well-known stick-slip phenomenon is captured through a new stability theorem. Numerical simulations show the effectiveness of the method and that the stick-slip oscillations cannot be weaken using a PI controller., Comment: Published in: IEEE Transactions on Control Systems Technology

Published
2019
Full Text
View/download PDF

44. Perinatal foodborne titanium dioxide exposure-mediated dysbiosis predisposes mice to develop colitis through life

Author

Carlé, Caroline, Boucher, Delphine, Morelli, Luisa, Larue, Camille, Ovtchinnikova, Ekaterina, Battut, Louise, Boumessid, Kawthar, Airaud, Melvin, Quaranta-Nicaise, Muriel, Ravanat, Jean-Luc, Dietrich, Gilles, Menard, Sandrine, Eberl, Gérard, Barnich, Nicolas, Mas, Emmanuel, Carriere, Marie, Al Nabhani, Ziad, and Barreau, Frédérick

Published
2023
Full Text
View/download PDF

46. Proenkephalin deletion in hematopoietic cells induces intestinal barrier failure resulting in clinical feature similarities with irritable bowel syndrome in mice

Author

Mas-Orea, Xavier, Rey, Lea, Battut, Louise, Bories, Cyrielle, Petitfils, Camille, Abot, Anne, Gheziel, Nadine, Wemelle, Eve, Blanpied, Catherine, Motta, Jean-Paul, Knauf, Claude, Barreau, Frederick, Espinosa, Eric, Aloulou, Meryem, Cenac, Nicolas, Serino, Matteo, Mouledous, Lionel, Fazilleau, Nicolas, and Dietrich, Gilles

Published
2023
Full Text
View/download PDF

47. Adipose tissue is a source of regenerative cells that augment the repair of skeletal muscle after injury

Author

Sastourné-Arrey, Quentin, Mathieu, Maxime, Contreras, Xavier, Monferran, Sylvie, Bourlier, Virginie, Gil-Ortega, Marta, Murphy, Enda, Laurens, Claire, Varin, Audrey, Guissard, Christophe, Barreau, Corinne, André, Mireille, Juin, Noémie, Marquès, Marie, Chaput, Benoit, Moro, Cédric, O’Gorman, Donal, Casteilla, Louis, Girousse, Amandine, and Sengenès, Coralie

Published
2023
Full Text
View/download PDF

48. Revealing electronic state-switching at conical intersections in alkyl iodides by ultrafast XUV transient absorption spectroscopy.

Author

Chang, Kristina F, Reduzzi, Maurizio, Wang, Han, Poullain, Sonia M, Kobayashi, Yuki, Barreau, Lou, Prendergast, David, Neumark, Daniel M, and Leone, Stephen R

Subjects
physics.chem-ph, physics.atm-clus
Abstract

Conical intersections between electronic states often dictate the chemistry of photoexcited molecules. Recently developed sources of ultrashort extreme ultraviolet (XUV) pulses tuned to element-specific transitions in molecules allow for the unambiguous detection of electronic state-switching at a conical intersection. Here, the fragmentation of photoexcited iso-propyl iodide and tert-butyl iodide molecules (i-C3H7I and t-C4H9I) through a conical intersection between 3Q0/1Q1 spin-orbit states is revealed by ultrafast XUV transient absorption measuring iodine 4d core-to-valence transitions. The electronic state-sensitivity of the technique allows for a complete mapping of molecular dissociation from photoexcitation to photoproducts. In both molecules, the sub-100 fs transfer of a photoexcited wave packet from the 3Q0 state into the 1Q1 state at the conical intersection is captured. The results show how differences in the electronic state-switching of the wave packet in i-C3H7I and t-C4H9I directly lead to differences in the photoproduct branching ratio of the two systems.

Published
2020

49. Efficient table-top dual-wavelength beamline for ultrafast transient absorption spectroscopy in the soft X-ray region.

Author

Barreau, Lou, Ross, Andrew D, Garg, Samay, Kraus, Peter M, Neumark, Daniel M, and Leone, Stephen R

Subjects
physics.optics, physics.chem-ph
Abstract

We present a table-top beamline providing a soft X-ray supercontinuum extending up to 370 eV from high-order harmonic generation with sub-13 fs 1300 nm driving pulses and simultaneous production of sub-5 fs pulses centered at 800 nm. Optimization of high harmonic generation in a long and dense gas medium yields a photon flux of  ~ 1.4 × 106 photons/s/1% bandwidth at 300 eV. The temporal resolution of X-ray transient absorption experiments with this beamline is measured to be 11 fs for 800 nm excitation. This dual-wavelength approach, combined with high flux and high spectral and temporal resolution soft X-ray absorption spectroscopy, is a new route to the study of ultrafast electronic dynamics in carbon-containing molecules and materials at the carbon K-edge.

Published
2020

50. FAB10: a user-oriented bandwidth-tunable extreme ultraviolet lightsource for investigations of femtosecond to attosecond dynamics in gas and condensed phases

Author

Bresteau, D., Spezzani, C., Tcherbakoff, O., Hergott, J.-F., Lepetit, F., D’Oliveira, P., Salières, P., Géneaux, R., Luttmann, M., Vadillo-Torre, I., Lenfant, J., Weber, S. J., Dehlinger, M., Meltchakov, E., Delmotte, F., Bourassin-Bouchet, C., Im, J., Chen, Z., Caillaux, J., Zhang, J., Marsi, M., Barreau, L., Poisson, L., Dowek, D., Fanciulli, M., Heckmann, O., Richter, M. C., Hricovini, K., Sebdaoui, M., Dennetiere, D., Polack, F., and Ruchon, T.

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results