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Uncertainty estimation in marker-based motion capture of the tennis serve
No full textInternational audienceMarker-based motion capture (MoCap) systems are widely used to analyse human movement. However, they are affected by measurement uncertainties, particularly marker placement errors (MPE) and soft tissue artefacts (STA). Here, we quantify the individual and combined effects of these two sources of uncertainty on joint angles and angular velocities in the case of the tennis serve. A Monte-Carlo approach was used to simulate 3000 perturbed marker trajectories for each uncertainty source and their combination. We applied a random offset for MPE, while sinusoidal perturbations were used to simulate for STA. The resulting joint kinematics were compared across all degrees of freedom. Confidence intervals (5-95 %), root mean square deviation (RMSD) and Minimal Detectable Changes (MDC) were calculated for key biomechanical variables. Results showed that STA predominantly affected angular velocities, while MPE had a greater impact on joint angles. The combined simulation consistently produced the largest variability, with mean confidence intervals ranging from 5.1° to 30.8° for joint angles and from 70.5°.s-1 to 248.5°.s-1 for joint angular velocities, and RMSD values ranging from 1.6° to 8.4° for joint angles and from 16.8°.s-1 to 68.0°.s-1 for joint angular velocities. To our knowledge, this is the first quantification of MPE and STA effects on ballistic movement kinematics. These results provide critical reference values, enabling more accurate comparisons across subjects and studies while accounting for measurement uncertainties
Identification of miR-187 as a modulator of early oogenesis and female fecundity in medaka
No full textInternational audienceMicroRNAs (miRNAs) are known regulators of ovarian function in vertebrates, yet their physiological roles in fish reproduction remain poorly understood. Here, we identified miR-187 as one of the most ovarian-enriched miRNAs in medaka (Oryzias latipes) and we uncovered its function in vivo using CRISPR/Cas9-mediated gene inactivation. We showed that miR-187-3p is expressed in oocytes and granulosa cells in the ovary, and in discrete brain areas. Its loss-of-function lead to a significant reduction in female fecundity. High-resolution 3D imaging of whole ovaries revealed that mir-187 mutants accumulate early stage I follicles and show reduced progression to later stages, indicating a defect in early follicle recruitment and growth. Transcriptomic profiling of mutant ovaries revealed extensive gene-expression remodeling, including downregulation of key regulators of steroidogenesis, Wnt/β-catenin signaling, and TGF-β pathways, and upregulation of genes associated with early follicle activation and immature somatic cell states. Using an expression-based target-prediction pipeline, we identified several putative miR-187-3p targets, including nr6a1a (gcnf) and dpagt1, two genes previously implicated in oocyte differentiation and female fertility in mammals. Together, our results demonstrate that miR-187 acts as a previously unrecognized regulator of early folliculogenesis and female reproductive capacity in medaka, expanding the repertoire of miRNAs with essential in vivo roles in teleost oogenesis and female fecundity
Prediction of inclisiran efficacy in patients with established atherosclerotic cardiovascular disease: the SIRIUS In-Silico modelling of cardiovascular outcomes
No full textInternational audienceAims: Inclisiran, an siRNA-targeting hepatic PCSK9 mRNA, reduces low-density lipoprotein cholesterol (LDL-C), but its effect on major adverse cardiovascular event (MACE) remains unconfirmed. The SIRIUS in-silico modelling program aimed to predict the efficacy of inclisiran on MACE in virtual patients with atherosclerotic cardiovascular disease (ASCVD).Methods: The SIRIUS simulation (NCT05974345) used a validated mechanistic model of ASCVD and lipid-lowering therapy (LLT) effects in a virtual population with established ASCVD and LDL-C ≥70 mg/dL. Each virtual patient served as their own control to compare inclisiran versus placebo as an adjunct to high-intensity statin therapy, alone or with ezetimibe over 5 years. The model did not account for non-adherence, recurrent events, or adverse effects.Results: Among 204 691 virtual patients, inclisiran was predicted to reduce LDL-C by 49.7% versus placebo (from 91.1 to 48.3 mg/dL). Relative to placebo, inclisiran was predicted to lower 5 years risk of 3-point MACE by 25.2% (11.3% vs. 14.9%), myocardial infarction by 34.8% (5.7% vs. 8.6%; HR 0.65), ischaemic stroke by 26% (2.6% vs. 3.4%; HR 0.74), and major adverse limb event by 34.1% (0.5% vs. 0.8%; HR 0.66). A 7.1% relative reduction of cardiovascular death was predicted (4.2% vs. 4.5%; HR 0.93).Conclusions: SIRIUS is the first in-silico simulation using a knowledge-based mechanistic model to predict the efficacy of LLT on cardiovascular outcomes in ASCVD. These findings offer early model-based prediction of inclisiran's potential cardiovascular benefit ahead of phase 3 outcome trials
Convolutional neural networks to signal currency crises: From the Asian financial crisis to the Covid crisis
No full textInternational audienceCurrency crises are recurrent events in economic history. They were particularly frequent during the 1980s and 1990s, reflecting diverse underlying causes, and have continued to occur in the early decades of the 21st century. This paper proposes a unified model to examine recent crises across 60 countries between the Asian crisis and the Covid-19 pandemic, including the 2008 global financial crisis and the 2014-2016 commodity-related tensions. The objective is to develop a robust early warning system capable of identifying potential currency crises within a two-year horizon, regardless of their origins. We assess several state-of-theart machine-learning architectures used in financial forecasting, going beyond conventional econometric benchmarks. For the first time in this literature, particular attention is given to convolutional neural networks, originally designed for image recognition, offering an innovative perspective for the analysis of macro-financial vulnerabilities. The results indicate that CNNs generate more accurate warning signals than other competitive models, such as long short-term memory networks, detecting 24 out of 27 crises in the sample. Moreover, the convolutionalbased analysis replicates well-established empirical regularities, assigning varying importance to indicators across subperiods. While the collapses observed between 2014 and 2016 appear primarily driven by domestic macro-financial deterioration, the 2008 and Covid-19 crises are more closely linked to global or US factors
Multiseasonal modeling of pesticide resistance in maize stalk borer
No full textInternational audienceThis study presents a comprehensive approach to modelling the infestation of maize by the maize stalk borer (Busseola fusca) using both chemical control and cultural practices consisting of post-harvest residue management. Two distinct mathematical models are developed: a semi-discrete integro-differential model and a semi-discrete differential model, each addressing different aspects of pest resistance. The integro-differential model captures the dynamics of quantitative resistance, considering resistance as a continuous variable from fully sensitive to fully resistant. The second model, on the other hand, accounts for qualitative resistance by incorporating discrete genetic mutations. Both models consider key factors such as pesticide decay rates, fitness costs associated with resistance, and the impact of integrated pest management (IPM) strategies. Our findings highlight the critical role of fitness costs in delaying resistance development and demonstrate the enhanced effectiveness of IPM techniques over conventional chemical control. This dual-model approach provides a robust framework for designing sustainable pest management practices in agriculture
ICU-acquired infections and thrombo-embolic events in critically ill patients receiving platelet transfusion: a prospective multicenter observational study.
No full textInternational audienceBackground: Platelet transfusion is relatively common in patients hospitalized in intensive care units (ICU). Both ICU-acquired infections and thromboembolic events have been reported after platelet transfusion. We sought to explore risk-factors of these complications.Materials and methods: We conducted a ancillary analysis of a multicenter prospective observational study including critically ill patients who received at least one platelet transfusion in one of the 9 participating ICUs. Patients' characteristics were compared according to the occurrence of post platelet transfusion ICU-acquired infections (blood stream infections and ventilator-associated pneumonia) and thromboembolic events. Factors associated with those outcomes were assessed by univariable and multivariable Fine and Gray regression.Results: Of the 310 included patients, 64 patients (20.6%) and 14 patients (4.5%) experienced at least one ICU-acquired infection and a thromboembolic event after platelet transfusion, respectively. Fifty patients (78.1%) developed blood stream infection (BSI), 32 (50%) experienced ventilator associated pneumonia (VAP) and 18 (28.1%) had both VAP and BSI. Independent risk factors for post platelet transfusion ICU-acquired infection included a platelet count at ICU admission <109/L (protective) (subdistribution Harard Ratio (sHR) 0.52 95% CI [0.31-0.89] p=0.016), multiple platelet transfusion prior to infection occurrence (sHR 2.15 [1.25-3.71] p=0.005) and a Simplified Acute Physiology Score (SAPS) II>50 (sHR 3.67 [2.16-6.25] p<0.001). While, the unique variable independently associated with thrombotic event occurring after platelet transfusion in adjusted Fine-Gray regression was a SAPS II >50 (sHR 4.27 [1.18-15.39] p=0.027).Discussion: In this prospective multicenter study, the risk of hospital-acquired infection after platelet transfusion increased in patients receiving multiple platelet transfusions and with patient severity at ICU admission
Reachability in multi-agent transfer systems
No full textInternational audienceThis paper introduces collaborative reachability games with energy constraints. In the considered arenas, agents can spend or gain energy during moves, or share it with their peers if their current position allows it. We study several variants of energy reachability games where agents move either synchronously or asynchronously, and with/without constraints on energy transfers among peers. We show that these problems have dierent complexities ranging from NP to EXPSPACE
Do Municipal Mergers Undermine Democratic Participation ?
No full textThis paper contributes to the existing literature on municipal mergers by highlighting heterogeneous political consequences associated with territorial reforms. The study evidences that municipal mergers reduce by 8 percentage points voter turnout, aligning with broader empirical trends. Employing a Difference-in-Differences approach and data from French municipalities from 2008, 2014 and 2020, the analysis reveals that mergers have a stronger negative effect on voter turnout in rural, less populated areas and in large-scale consolidations. The decline is also more pronounced in municipalities with limited electoral competition. The effect is mitigated by an increase in the number of polling stations and changes in the political color of the majority of the chief town municipality after the elections
Impact of Cardiac Resynchronization Therapy in Patients With Left Ventricular Assist Devices: A Systematic Review and Meta-analysis
No full textInternational audienceBackground:Many patients with left ventricular assist devices (LVADs) have cardiac resynchronization therapy (CRT). However, the impact of CRT on their clinical and hemodynamic outcomes remains unclear.Methods:We conducted a systematic review and meta-analysis to evaluate CRT's impact on survival in LVAD patients. We searched PUBMED, EMBASE, and Cochrane databases from inception through April 30, 2025, for studies reporting outcomes in LVAD patients with CRT. The primary outcome was all-cause mortality in patients with versus without CRT. Secondary clinical outcomes included ventricular arrhythmias (VAs) and shocks delivered. Hemodynamic outcomes included heart rate, right atrial pressure, mean pulmonary artery pressure, pulmonary capillary wedge pressure, thermodilution cardiac output, pulmonary artery saturation, right ventricular stroke work index, and left ventricular end-diastolic diameter.Results:13 studies including 3,665 patients were analyzed. CRT did not demonstrate any significant survival benefit, whether comparing CRT-D versus ICD (OR 1.12 [0.85–1.48]), CRT on versus CRT off (OR 1.48 [0.87–2.53]), CRT versus no device (OR 0.99 [0.61–1.59]), or CRT versus no device or ICD (OR 1.00 [0.16–6.31]). Similarly, none of the tested comparisons showed significant differences in VAs incidence or shock rates. Biventricular pacing demonstrated no advantage for any hemodynamic outcomes, whether compared to right ventricular pacing or intrinsic rhythm.Conclusion:In this meta-analysis, CRT was not associated with overall survival benefit in LVAD recipients, nor with hemodynamic improvement. Future randomized trials may be warranted to definitively establish CRT's value in this population and refine patient selection criteria for optimal outcomes
Efficient Threshold ML-DSA
No full textInternational audienceThreshold signature schemes allow a group of users to jointly generate a digital signature, providing resilience against faults and enhancing decentralization. With the advent of post-quantum cryptography, lattice-based threshold signatures have gained attention as viable PQ-threshold solutions. Nevertheless, existing constructions are limited in terms of their scalability, robustness. Worse, none is compatible with standardized schemes, particularly with the NIST-selected and standardized Module-Lattice-based Digital Signature Algorithm (ML-DSA) algorithm.In this work, we present the first threshold signature scheme that is fully compatible with ML-DSA, supporting secure and efficient signing for a small number of parties, with an average communication per party upper bounded by 1 MB up to 6 parties. Our construction leverages advanced short secret sharing techniques and integrates optimized rejection sampling to achieve a favorable balance between communication efficiency and correctness in distributed environments. We implement our construction in Go and evaluate its performance across local, LAN, and WAN network settings. Our benchmarks demonstrate that our threshold ML-DSA scheme is not only practically deployable but also well-suited for real-world applications, including multi-device cryptocurrency wallets, threshold-based TLS authentication, and for Tor's directory authorities