Dassault Systèmes (United States)

The objective of this paper is to develop a machine learning (ML)-aided cohesive zone model (CZM) for fatigue delamination. A viscodamage model is implemented in a string-based cohesive zone modeling framework to capture load- and path-dependent, pure and mixed mode fatigue delamination. An associated implicit integration scheme is developed and implemented in Abaqus/Standard to generate necessary training data. Subsequently, a series of ML models are trained as surrogates for computationally expensive finite element simulations required during model calibration, and these surrogates are implemented in the Dakota toolkit for parameterized and automated calibration. The present framework is validated by calibrating the present CZM via double cantilever beam and end-notched flexure tests on unidirectional E-glass fiber/E722 composite beams. The ML-aided calibration method is found to significantly enhance calibration efficiency while maintaining accuracy. The present CZM’s capability in handling mixed-mode delamination is demonstrated through simulating a series of mixed-mode bending tests. The present CZM can be implemented in a multiscale modeling framework for fatigue life prediction of composites.

Abstract Cavitation is a destructive phenomenon that reduces the hydraulic performance of the propeller and brings damage to the propeller blades. In this study, we numerically analyzed the cavitation phenomenon that occurs on a propeller using RANS approach on the 3DEXPERIENCE® platform. A Sliding Mesh approach was used to model rotating regions and a Volume of Fluid (VOF) method was used to model cavitation phenomenon. Transient simulations were executed under different cavitation conditions. The predicted cavitation distribution and thrust coefficient under cavitating condition correlate well with experimental observations.

Flat optical components, or metasurfaces, have transformed optical imaging, data storage, information processing, and biomedical applications by providing unprecedented control over light-matter interactions. These nano-engineered structures enable compact, multidimensional manipulation of light's amplitude, phase, polarization, and wavefront, producing scalar and vector beams with unique properties such as orbital angular momentum and knotted topologies. This flexibility has potential applications in optical communication and imaging, particularly in complex environments such as atmospheric turbulence and undersea scattering. However, designing metasurfaces for shorter wavelengths, such as visible and ultraviolet light, remains challenging due to fabrication limitations and material absorption. Here, we introduce an innovative concept called topology imprinting using judiciously designed all-dielectric nonlinear optical metasurfaces to replicate desired waveforms at fundamental and harmonic frequencies, opening promising avenues for advanced photonic applications.

8095 Background: Most clinical trials globally are not representative of a diverse patient population and 78% of trial participants remain White. This may limit the generalizability of trial results to the broader population, create an insufficient understanding of drugs’ safety and efficacy between different patient populations, and hinder equitable access to investigational drugs. We compare the racial and ethnic composition of US clinical trials sites for lung cancer to epidemiology data. Methods: The de-identified data was sourced from Medidata’s clinical trial database. The cohort included clinical trial participants enrolled in US sites in phase 1-3 interventional lung cancer studies conducted between 2016 and 2022. Lung cancer incidence estimates were taken from the National Cancer Institute’s incidence data. Sites were classified as at/above or below expected demographic composition based on a relative ratio calculation, RR = proportion of trial patients/proportion of population with lung cancer. RR ≥1 means site recruited at/above expected ratio for the demographic group and vice versa. A 10% tolerance was used to capture minor deviations. A Mann-Whitney U test was used to determine if the two site types have statistically different enrollment rates, with a p-value of 0.05 for significance. Results: The analysis cohort consisted of 6,988 lung cancer patients from 85 studies and 876 US sites. Most sites enrolled White non-Hispanic patients at/above the epidemiological threshold. Conversely, the majority of sites enrolled non-White patients below the threshold (Table 1). The overall enrollment performance of sites enrolling a representative cohort of Black, American Indian and White patients did not differ from their counterparts. However, sites enrolling at or above the epidemiological threshold of Asian non-Hispanic and Hispanic patients had a higher enrollment rate than sites underrepresenting these patient populations. Conclusions: The majority of US clinical trial sites underrepresent demographic subgroups except White non-Hispanic patients. Sites enrolling a representative pool of racial and ethnic demographic subgroups did not have a lower overall enrollment performance. Enrollment rate of sites recruiting at/above vs. below epidemiological threshold. Race/Ethnicity Sub-group Enrollment Rate (pts/site/month)Median (IQR) P-value Sites Enrolling At or Above Epidemiological Threshold Sites Enrolling Below Epidemiological Threshold N (%) sites Enrollment Rate N (%) sites Enrollment Rate Asian (non-Hispanic) 67 (13%) 0.11 (0.03 - 0.23) 439 (87%) 0.04 (0.02 - 0.08) <0.0001 Black (non-Hispanic) 96 (15%) 0.04 (0.02 - 0.08) 553 (85%) 0.04 (0.02 - 0.09) 0.99 American Indian (non-Hispanic) 6 (4%) 0.08 (0.06 - 0.12) 137 (96%) 0.04 (0.01 - 0.07) 0.19 White (non-Hispanic) 461 (59%) 0.04 (0.01 - 0.09) 326 (41%) 0.04 (0.02 - 0.07) 0.64 Hispanic 76 (14%) 0.07 (0.03 - 0.14) 447 (86%) 0.04 (0.02 - 0.08) 0.002

As semiconductor manufacturing continues to push the boundaries of pattern fidelity and manufacturability, curvilinear masks have emerged as a transformative technology. This special section of the Journal of Micro/Nanopatterning, Materials, and Metrology (JM3) brings together the latest research on curvilinear masks, covering their development, processing, verification, metrology, and practical applications, all enabled by advancements in multi-beam mask writer technology. The papers featured in the section, published in three parts in the

We demonstrate through comprehensive analysis and empirical evidence the inherent advantages of pixel-based computing for curvilinear photomasks when using a graphics processing unit (GPU)-based platform. The Single Instruction, Multiple Data nature of GPUs enables fast pixel-based computations. We study the advantages of using GPU acceleration for pixel-based computing in various mask processing and verification steps. We highlight the natural runtime predictability of pixel-based computing, which is in the order of number of pixels, or O(p), irrespective of the complexity of the mask shapes. We also emphasize that pixel dose equivalence and information theory provide a mathematical basis for the practical accuracy of a pixel-based approach toward mask data preparation. The Nyquist limit guides the mask rules for masks written using multi-beam writers as the mask is essentially sampled into pixels. This sampling acts as a low-pass filter. We also perform a case study of smooth shapes to show how bandlimited shapes enabled by pixel-based multi-beam writers are more manufacturable. We conclude that the O(p) approach for GPU acceleration enables accurate and practical data processing for curvy masks governed by information theory as we leap into an increasingly complex curvy world.

It is unknown whether Medicaid expansion under the Affordable Care Act (ACA) or state-level policies mandating Medicaid coverage of the routine costs of clinical trial participation have ameliorated longstanding racial and ethnic disparities in cancer clinical trial enrollment. We conducted a retrospective, cross-sectional difference-in-differences analysis examining the effect of Medicaid expansion on rates of enrollment for Black or Hispanic nonelderly adults in nonobservational, US cancer clinical trials using data from Medidata's Rave platform for 2012-2019. We examined heterogeneity in this effect on the basis of whether states had pre-existing mandates requiring Medicaid coverage of the routine costs of clinical trial participation. The study included 47,870 participants across 1,353 clinical trials and 344 clinical trial sites. In expansion states, the proportion of participants who were Black or Hispanic increased from 16.7% before expansion to 17.2% after Medicaid expansion (0.5 percentage point [PP] change [95% CI, -1.1 to 2.0]). In nonexpansion states, this proportion increased from 19.8% before 2014 (when the first states expanded eligibility under the ACA) to 20.4% after 2014 (0.6 PP change [95% CI, -2.3 to 3.5]). These trends yielded a nonsignificant difference-in-differences estimate of 0.9 PP (95% CI, -2.6 to 4.4). Medicaid expansion was associated with a 5.3 PP (95% CI, 1.9 to 8.7) increase in the enrollment of Black or Hispanic participants in states with mandates requiring Medicaid coverage of the routine costs of trial participation, but not in states without mandates (-0.3 PP [95% CI, -4.5 to 3.9]). Medicaid expansion was not associated with a significant increase in the proportion of Black or Hispanic oncology trial participants overall, but was associated with an increase specifically in states that mandated Medicaid coverage of the routine costs of trial participation.

TOR (target of rapamycin), a ubiquitous protein kinase central to cellular homeostasis maintenance, fundamentally regulates ribosome biogenesis in part by its target La-related protein 1 (LARP1). Among other target transcripts, LARP1 specifically binds TOP (terminal oligopyrimidine) mRNAs encoding all 80 ribosomal proteins in a TOR-dependent manner through its C-terminal region containing the DM15 module. Though the functional implications of the LARP1 interaction with target mRNAs is controversial, it is clear that the TOP-LARP1-TOR axis is critical to cellular health in humans. Its existence and role in evolutionarily divergent animals remain less understood. We focused our work on expanding our knowledge of the first arm of the axis: the connection between LARP1-DM15 and the 5' TOP motif. We show that the overall DM15 architecture observed in humans is conserved in fruit fly and zebrafish. Both adopt familiar curved arrangements of HEAT-like repeats that bind 5' TOP mRNAs on the same conserved surface, although molecular dynamics simulations suggest that the N-terminal fold of the fruit fly DM15 is predicted to be unstable and unfold. We demonstrate that each ortholog interacts with TOP sequences with varying affinities. Importantly, we determine that the ability of the DM15 region to bind some TOP sequences but not others might amount to the context of the RNA structure, rather than the ability of the module to recognize some sequences but not others. We propose that TOP mRNAs may retain similar secondary structures to regulate LARP1 DM15 recognition.

Abstract The use of systems engineering has proven effective in managing complexity and improving system design. Model based system engineering utilizing the Systems Modeling Language (SysML) especially helps in multidisciplinary environments where engineering data needs to be transformed and integrated between environments. Manufacturing is another discipline same as systems engineering is on active digitalization transformation. In the paper, we propose method and solution to apply Model based system engineering (MBSE) for improvement of process planning of assembly lines leveraging model based approach. SysML modeling and execution enable automation of analysis activities as trade‐off, where the behavior of various assembly scenarios of an assembly line can be captured using SysML behavioral diagrams and compared based on various evaluation criteria. However, relying solely on descriptive SysML system models without integrating the virtual representation of the assembly line is insufficient to verify all aspects of system behavior, such as ergonomics and collision avoidance. The main objective of this work is to present a concept for transforming SysML assembly scenarios into the process and resources models of the computer‐aided design and manufacturing (CAD/CAM) environment. This yields a holistic view that serves as a foundation for further production‐related simulations and analyses, enhancing efficiency, ergonomic design, factory layout, and material flow, ensuring effective assembly workstation design optimized at systems engineering level.