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Efficacy and cost-effectiveness of lung cancer screening in France with low-dose computed tomography
No full textInternational audienceLung cancer is the third most frequent cancer in France. It has a poor prognosis when patients are diagnosed at advanced stages. Low-dose computed tomography (LDCT) can detect early-stage cancer. In addition, blood-based biomarkers could help select patients for lung cancer screening or manage indeterminate lung nodules. The objective of this study is to assess the efficacy and cost-effectiveness of lung cancer screening in the French context including LDCT and biomarkers. A microsimulation model calibrated for France was used to compare four strategies: no screening, biennial LDCT, biennial LDCT followed by biomarkers, and biennial screening with biomarkers followed by LDCT. Screening eligibility included age (50–74) and smoking history (>15 cigarettes/day over 25 years, or 10 cigarettes/day over 30 years, or former smokers who quit less than 10 years ago). A 25% participation rate was assumed. Direct medical costs were estimated from the perspective of the French health system. Cost and outcomes were discounted at 2.5%. Screening decreased lifetime lung cancer mortality from 2 to 12% depending on the participation rate, leading to an increase in both life years and quality-adjusted life years (QALY). Considering cost effectiveness, LDCT screening was associated with an incremental cost-effectiveness ratio of €7629 per QALY in comparison to the absence of screening. Sensitivity analyses were all favorable to LDCT-based screening strategies. Biennial LDCT screening could be an effective and cost-effective strategy in France even at a 25% participation rate
Dominant elites, dominated subalterns, nothing more? Analyzing the ambivalence of domination
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A Comprehensive Survey of Henry Gas Solubility Optimization Algorithm with its Theory, Variants, and Applications
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Optimization of Optical Network Units Placement Using Generalized Opposition Based-Learning Starfish Optimization Algorithm
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A binary multi-objective approach for solving the WMNs topology planning problem
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Tropical Cirrus Lifetime Estimated From Superpressure Balloon‐Borne Lidar Observations
No full textInternational audienceTropical tropopause layer (TTL) cirrus clouds play a key role in the Earth climate system. Yet the relative role of the various processes shaping them remains poorly known. Characterizing the temporal evolution of cloudy structures from observations is essential to address this issue but represents a challenge. Indeed, space‐ and airborne platforms move fast and mainly provide instantaneous snapshots. In boreal winter 2021–2022, two balloon‐borne lidars flew over the Equatorial Pacific Ocean, slowly drifting above the clouds. We use those unique nighttime observations to quantify the distribution of TTL cloud lifetime above this homogeneous region. This distribution is strongly asymmetric: half of the clouds live less than 1 hr, but their mean lifetime is about 6 hr. The few long‐lived clouds ( hr) dominate the cloud cover. Those results compare reasonably well with TTL cirrus lifetimes in the ERA5 reanalysis, although the modeled TTL cloud cover is largely underestimated
Noise Injection for Performance Bottleneck Analysis
No full textInternational audienceBottleneck evaluation plays a crucial part in performance tuning of HPC applications, as it directly influences the search for optimizations and the selection of the best hardware for a given code. In this paper, we introduce a new model-agnostic, instruction-accurate framework for bottleneck analysis based on performance noise injection. This method provides a precise analysis that complements existing techniques, particularly in quantifying unused resource slack. Specifically, we classify programs based on whether they are limited by computation, data access bandwidth,or latency by injecting additional noise instructions that target specific bottleneck sources. Our approach is built on the LLVM compiler toolchain, ensuring easy portability across different architectures and microarchitectures which constitutes an improvement over many state-of-the-art tools. We validate our framework on a range of hardware benchmarks and kernels, including a detailedstudy of a sparse-matrix–vector product (SPMXV) kernel, where we successfully detect distinct performance regimes. These insights further inform hardware selection, as demonstrated by our comparative evaluation between HBM and DDR memory systems
Disrupted self-perspective impact on episodic memory in individuals with self-disorders: A virtual investigation in the Latin Quarter of Paris
No full textInternational audienceVirtual reality (VR) provides a powerful framework for investigating how environmental factors interact with self-referential processes during episodic memory (EM) formation. This study examined whether adopting a selfperspective or another person's perspective while navigating a realistic simulation of the Latin Quarter of Paris differentially influenced EM in individuals at ultra-high risk (UHR) for psychosis (n = 22), patients with schizophrenia (SCZ; n = 20), and healthy controls (CTL; n = 28). Participants encoded specific events from either their own first-person perspective or an avatar's third-person perspective. After the navigation, they completed a free recall task assessing factual content, spatiotemporal context, and phenomenological details. Results showed that CTL exhibited a self-reference effect, recalling more details and demonstrating enhanced memory binding when encoding events from a self-perspective, compared to an other-perspective. In contrast, UHR and SCZ groups displayed pervasive EM deficits regardless of perspective and lacked this self-referential advantage. Deficits in self-perspective encoding correlated with neurological soft signs, while EM performance was associated with episodic mental time travel, executive functions, sense of presence and environmental familiarity, suggesting integrative processes between the environment, Self, and memory encoding. These findings support the theory of a disruption of minimal selfhood or ipseity in the SCZ spectrum, suggesting that core alterations in first-person anchoring compromise the encoding of experiences into coherent, spatially contextualised episodic memories. Furthermore, the results highlight the importance of naturalistic settings for uncovering how selfreferential and environmental factors jointly shape memory in psychosis. VR-based approaches may facilitate early identification of at-risk individuals and inform targeted interventions to promote engagement with the environment, enhancing EM and self-related processes in clinical populations
