Low Penetration Research Articles

Gradient 2D re-entrant cores for sandwich structures under low-velocity impact

Auxetic metamaterials, known for their unusual properties, are being explored as cores for sandwich structures to improve impact resistance. This study investigated the low-velocity impact response of sandwich panels with various core designs using finite element method (FEM) and experiments on 3D-printed specimens. These cores include pure honeycomb, pure auxetic, and gradient variations with controlled gradients of Poisson’s ratio, transitioning from negative to positive (NTP), positive to negative (PTN), negative-to-positive-to-negative (NTPTN), and positive-to-negative-to-positive (PTNTP). These gradients were achieved by adjusting the unit cell angle within the core. Under quasi-static indentation, the gradient PTN design improved energy absorption by 26% compared to the honeycomb structure, while the gradient NTP structure showed a 9% improvement over the auxetic core. As for the impact tests, the gradient NTP and PTN structures significantly enhanced the indentation resistance of auxetic and honeycomb structures by 21.3% and 6.5%, respectively. Interestingly, while the optimal core for peak energy absorption varied with impact velocity, gradient structures generally provided superior energy absorption, particularly at lower velocities. FEM results at initial impact velocities of 10, 15, 20 m/s confirmed that structures having negative Poisson’s ratio at their top layer exhibited the lowest penetration depth. Additionally, gradient structures, particularly NTP and NTPTN, demonstrated superior energy absorption capability compared to purely auxetic or honeycomb structures, especially at lower velocities. The study highlights the benefits of utilizing gradient auxetic metamaterial cores in high-performance sandwich structures for impact resistance applications. These structures showed minimal localized damage, reduced densification risk due to uniform crushing, and lower penetration depth.

Genetic heterogeneity in familial forms of genetic generalized epilepsy: from mono- to oligogenism

Genetic generalized epilepsy (GGE) including childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy (JME), and GGE with tonic–clonic seizures (TCS) (GGE-TCS), is genetically influenced with a two- to four- fold increased risk in the first-degree relatives of patients. Since large families with GGE are very rare, international studies have focused on sporadic GGE patients using whole exome sequencing, suggesting that GGE are highly genetically heterogeneous and rather involve rare or ultra-rare variants. Moreover, a polygenic mode of inheritance is suspected in most cases. We performed SNP microarrays and whole exome sequencing in 20 families from Sudan, focusing on those with at least four affected members. Standard genetic filters and Endeavour algorithm for functional prioritization of genes selected likely susceptibility variants in FAT1, DCHS1 or ASTN2 genes. FAT1 and DCHS1 are adhesion transmembrane proteins interacting during brain development, while ASTN2 is involved in dendrite development. Our approach on familial forms of GGE is complementary to large-scale collaborative consortia studies of sporadic cases. Our study reinforces the hypothesis that GGE is genetically heterogeneous, even in a relatively limited geographic area, and mainly oligogenic, as supported by the low familial penetrance of GGE and by the Bayesian algorithm that we developed in a large pedigree with JME. Since populations with founder effect and endogamy are appropriate to study autosomal recessive pathologies, they would be also adapted to decipher genetic components of complex diseases, using the reported bayesian model.Graphical

Impact of Titanium Cranial Implants on the Electric Field and SAR Distribution Induced by Mobile Phones Within the User’s Head

The purpose of this study was to determine the impact of a titanium cranial implant on the electric field distribution and the amount of energy absorbed from a cell phone within the human head. Three-dimensional lifelike models of the head of the mobile phone user, a titanium cranial implant, and a smartphone model was built. The head model consisted of sixteen homogeneous, isotropic domains, with permittivity and conductivity parameters taken from the literature. Numerical calculations were performed at the mobile communication frequency of 2600 MHz for a head model with and without a titanium cranial implant, in order to determine a field perturbation introduced by the implant. Our results show that in the presence of a titanium cranial implant, the electric field amplitude and SAR (Specific Absorption Rate) are increased within the layers close to the outer surface of the model (skin, fat tissue, and muscle). On the other hand, a cranial implant leads to a lower penetration depth, decreasing the electric field amplitude and SAR inside the skull, cerebrospinal fluid, and brain.

Estimation of Arterial Path Flow Considering Flow Distribution Consistency: A Data-Driven Semi-Supervised Method

To implement fine-grained progression signal control on arterial, it is essential to have access to the time-varying distribution of the origin–destination (OD) flow of the arterial. However, due to the sparsity of automatic vehicle identification (AVI) devices and the low penetration of connected vehicles (CVs), it is difficult to directly obtain the distribution pattern of arterial OD flow (i.e., path flow). To solve this problem, this paper develops a semi-supervised arterial path flow estimation method considering the consistency of path flow distribution by combining the sparse AVI data and the low permeability CV data. Firstly, this paper proposes a semi-supervised arterial path flow estimation model based on multi-knowledge graphs. It utilizes graph neural networks to combine some arterial AVI OD flow observation information with CV trajectory information to infer the path flow of AVI unobserved OD pairs. Further, to ensure that the estimation results of the multi-knowledge graph path flow estimation model are consistent with the distribution of path flow in real situations, we introduce a generative adversarial network (GAN) architecture to correct the estimation results. The proposed model is extensively tested based on a real signalized arterial. The results show that the proposed model is still able to achieve reliable estimation results under low connected vehicle penetration and with less observed label data.

New perspective on the role of grain boundaries for hot‐corrosion studies on sintered 3YSZ ceramic

AbstractThe hot‐corrosion behavior of sintered 3 mol.% yttria‐stabilized zirconia (3YSZ) ceramic with significant (1:4 in ratio) variation in grain sizes was investigated. Contrary to the popular perception of the role of grain boundaries, ceramics with smaller grains portrayed remarkable hot‐corrosion resistance despite having ∼450% more grain boundaries compared to their counterpart. The mechanism behind a rather ‘unusual’ role of the grain boundary in deciding the corrosion pathways for 3YSZ ceramic systems was examined. The affinity of NaVO3 to react with Y2O3 was found to be a crucial step for the initiation of corrosion and this process had no potential influence on the fraction of grain boundaries in the system. A phase transformation (tetragonal to monoclinic) induced porosity created easy path for the molten liquid to flow inside the ZrO2 matrix. The ceramic with a smaller grain size resisted such a transformation and resulted in a much lower penetration depth for the corrosion to proceed further inside the matrix. Although grain boundaries are usually portrayed as weak points for corrosion, this study illustrates an alternate pathway using which corrosion can be averted in a fine grained 3YSZ ceramic.

Abstract B030: Productive T-cell-mediated immunoediting of developing sarcomas by distinct mechanisms

Abstract Immunoediting is the process where developing tumors are shaped by cells of the immune system. Tumors with low immunogenicity are likely to emerge after neoantigen-specific T cells eliminate the most immunogenic cell populations. However, direct interrogation of mechanisms by which this occurs has not possible due to the pre-emergent nature before the disease is verifiably established. By modifying a mouse model of soft-tissue sarcoma where emergent tumors are consistently edited, we developed a system to examine mechanisms underlying how T cells interact with pre-emergent tumor cell populations to suppress tumor emergence. This system involves production of neoantigen-expressing autochthonous tumors with a fluorescent reporter to define neoantigen-expression status of individual cells. Tumors emerge with lower penetrance and delayed onset in T cell-sufficient mice, while every tumor from T cell-deficient mice contain a significant fraction of neoantigen-negative tumor cells. Yet, ∼53% of T cell-sufficient mice never developed, which suggests that neoantigen silencing was necessary, but not sufficient for tumor emergence. Consistent with this, genetic removal of the neoantigen after malignant transformation shows that tumor development is only rescued when neoantigen loss occurs prior to the peak T cell response, occurring around 8 days post transformation. Moreover, clonality studies reveal the presence of T cells reduces the number clones that contribute to tumor emergence down to 1-2 clones per emerged tumor. Mechanistically, blockade of the T cell effector cytokine, IFNgamma, rescues the neoantigen-negative, but not neoantigen-expressing tumor cells, demonstrating that T cells control early tumors via at least two distinct mechanisms: IFNgamma-dependent suppression of neoantigen-negative tumors cells and IFNgamma-independent suppression of neoantigen-expressing cells. Thus, our findings support that neoantigen-negative cells are subjected to cytokine-mediated suppression from T cells responding to the neoantigen-positive population in the pre-emergent tumor microenvironment. This bystander suppression can prevent tumor emergence despite non-homogeneity in neoantigen expression. Citation Format: Brian G Hunt, Julie F. Cheung, Srividhya Venkatesan, Jennifer L. Loza, Kelli A. Connolly, Shudipto Wahed, Elaine Cheng, Ishan Bansal, Emily Borr, Wei Wei, Ivana William, Brittany Fitzgerald, Nikhil Joshi. Productive T-cell-mediated immunoediting of developing sarcomas by distinct mechanisms [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B030.

Abstract 4127919: Disease-associated variants in DSP -encoded desmoplakin are common, yet low penetrant alleles associated with development of myocarditis and cardiomyopathy at a population level

Intro: DSP- encoded desmoplakin is implicated in a distinct form of arrhythmic cardiomyopathy (ACM), often involving the LV and characterized by myocardial inflammation. Conventional ACM diagnostic criteria has poor sensitivity for DSP -associated ACM, thus highlighting the need to identify the full spectrum of phenotypic risk associated with disease-associated DSP variants. Objective: To analyze the genotypic and phenotypic spectrum of DSP -mediated disease at a large population level. Methods: UK Biobank participants with exome sequencing (ES) were included. Variants were filtered by gene evidence category, yielding 3 groups: predicted deleterious (pDel); subset with predicted loss of function (LOF); and ultra-filtered subset by ClinVar 2* pathogenic/likely pathogenic (P/LP). Phenotypic penetrance was analyzed with DSP -neg individuals as control. Variant location analysis assessed LOFs by susceptibility to nonsense mediated decay region and missenses by amino acid sequence to identify mutational hotspots where P/LPs localize. Results: Out of 200,580 with ES, 1407 DSP carriers had pDel, 168 with LOF, and 44 with ClinVar 2* P/LP. DSP carriers had higher burden of myocarditis, cardiomyopathy (CM), and heart failure. A progressive enrichment in myocarditis and CM was observed by more stringent variant filtering in DSP carriers compared to control. A higher proportion of DSP carriers had myocarditis – 0.28% (4) of the pDels, 1.8% (3) of LOFs, and 4.5% (2) compared to control 0.07% (p<0.05). A parallel trend noted the proportion of DSP carriers with CM growing from 1.4% (19) to 5.4% (9) and 6.8% (3) in the pDel, LOF, and ClinVar 2* P/LPs respectively compared to 0.6% in the control group (p<0.01). Location analysis of missense variants revealed that P/LPs localized in higher proportions (74%) to key domains compared to non-P/LPs (50%; p<0.001), highlighting prognostic value of predicting pathogenicity of missense DSP variants by mutation hotspots. Conclusions: While DSP variants are relatively common in the population, variant presence is associated with low penetrance. Enhancing clinical penetrance with increasingly stringent filtering of DSP variants emphasizes the importance of variant evaluation in clinical risk assessment. This first-in-kind population study of DSP provides insights into novel risk prediction factors, allowing us to predict pathogenicity by type and location of mutation and using variant filtering strategy to better assess phenotypic penetrance.

Abstract 4120763: Predicting Disease Risk Among Variants in Cardiomyopathy-Associated Genes Across Diverse Genetic Ancestries

Background: Many cases of cardiomyopathy (CM) are genetically inherited, and the expansion of broad genomic sequencing has opened the door for predicting those at risk for developing disease. However, genetic tools that help determine variant pathogenicity employ genetic data from predominantly European genetic ancestries. Understanding the full diversity of genetic variants in cardiomyopathy genes is central to identifying which variants will cause disease. Hypothesis: Participants of non-European genetic ancestry will have a higher burden of cardiomyopathy gene variants with "VUS" designation in ClinVar but will have equivalent/less penetrance of clinical cardiomyopathy compared to a European ancestry group. Methods: Participants in the AllofUs database with exome sequencing (ES) were queried and a cohort of 230,013 participants were retained after sample quality control filters. Participant genetic ancestry was based on the designated ancestry group determined via AllofUs as previously described (1). Participants were queried for variants in genes with definitive or moderate evidence of hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and arrhythmogenic cardiomyopathy (ACM) in ClinGen. Variants were filtered by ClinVar status (1* and above P/LP, 1* and above B/LB, and VUS). Participant CM disease status was determined via ICD-9/10 code. Results: For each ancestry group, prevalence of cardiomyopathy ranged from 0.34% in the Latino/admixed American ancestry group to 1.09% in the African group, with an average prevalence of 0.91% across all groups. The European group had a statistically significant lower percentage of ClinVar VUS variants at 26%, while all other non-European ancestry groups had a combined VUS prevalence rate of 35% (****p<0.0001). The penetrance of CM in participants with CM VUS variants was lower in combined non-European ancestry groups (0.84%) than European ancestry (1.02%) (*p=0.0156). Conclusion: Prevalence of ClinVar VUS variants varies across different genetic ancestry groups, with European ancestry having a lower burden of VUS variants compared to non-European groups. However, non-European ancestry groups with increased burden of VUS variants have lower disease penetrance. Citations: (1) The All of Us Research Program Genomics Investigators. Genomic data in the All of Us Research Program. Nature 627 , 340–346 (2024). https://doi.org/10.1038/s41586-023-06957-x

DDEL-16. MICROMESH FOR REVAMPING THE ‘COLD’ TUMOR MICROENVIRONMENT IN GLIOBLASTOMA IMMUNOTHERAPY

Abstract High-grade gliomas have poor prognoses with limited treatment options, typically maximal safe resection and adjuvant radiochemotherapy. Novel therapies often face challenges due to low brain penetrance and poor bioavailability. To address these issues, a conformable, compartmentalized polymeric implant called microMESH has been developed. microMESH provides localized, sustained release of drugs, small inhibitors, antibodies, and nanomedicines, enabling novel therapeutic combinations. When applied to the tumor margins, microMESH adheres to the tissue, releasing its therapeutic cargo over weeks and reducing systemic toxicity. Its biocompatibility, cytotoxicity, and anti-tumor efficacy were tested on murine cancer cells (CT-2A) and orthotopic glioblastoma syngeneic models. Exposing primary bone marrow-derived monocytes (BMDM) to CT-2A conditioned medium increased the expression of anti-inflammatory cytokines (IL-10 and IL-4) by 2 times without significantly affecting the pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6), indicating that CT-2A cells tend to establish an immunosuppressive ‘cold’ tumor microenvironment. Next, the co-incubation of CT-2A cells with BMDM followed by the administration of the immune checkpoint inhibitor aCD47 resulted in a cancer cell viability drop by 50% already at 50 μg/ml aCD47 after 1 day. Additionally, pre-treatment with docetaxel (DTXL) further decreased cell viability, suggesting a synergism between aCD47 and the chemotherapeutic drug. Flow cytometry showed that 50 nM DTXL at 3 days post-incubation was responsible for a strong translocation of the ‘immunogenic dell death’ protein calreticulin on the cell membrane, potentially explaining the synergism. Over 2 months, the intracranially deployed microMESH biodegraded without inducing any toxic effect. In orthotopic CT-2A tumors, aCD47/DTXL–microMESH (0.75 mg/kg, single intracranial application) showed a 40-day survival compared to 22 days for iv DTXL (3 mg/kg qod), 24 days for ip aCD47 (5 mg/kg qod), and 18 days for untreated mice. microMESH helped identify and enabled novel combination therapies directly at the tumor bed, demonstrating superior efficacy over systemic therapies.

ASSESSING THE DEVELOPMENT OF THE BRAZILIAN ELECTRIC VEHICLES MARKET: A STUDY INTEGRATING A STRUCTURE-CONDUCT-PERFORMANCE (SCP) MODEL AND A PESTEL ANALYSIS

Climate change is one of the biggest political and economic challenges faced by global economy. To slow down climate change, mitigation actions and greenhouse gas (GHG) emission targets have been adopted, promoting electric vehicles (EVs) globally. In Brazil, however, emission reduction strategies for the transport sector are based on the broad use of biofuels. This paper studies the Brazilian light-duty vehicle EVs market investigating the reasons behind its current state. A Structure-Conduct-Performance Model with a PESTEL Analysis and the Herfindahl–Hirschman Index integrated to the structure analysis was used. The Brazilian EV market has grown in the period from 2019 to 2023, albeit timidly and restricted to a luxury market. The lack of actions promoting electric mobility, a less than promising economic scenario, the challenges in implementing a charging infrastructure and the conduct of the incumbent firm in the market – investing in high priced hybrid models – contribute to low penetration of EVs in the market and the dominance of hybrids amongst them. In the light of these findings, this study highlights that the Brazilian EVs market would benefit from public policies developed to promote electric mobility, and investment of private companies to develop EV models with more competitive prices.

A novel method for rapidly simulating X-ray pulsar signals at a spacecraft

This paper addresses the challenges posed by the low photon flux and limited atmospheric penetration capabilities of X-ray pulsar signals, which are further exacerbated by technical, economic, and temporal constraints during in-orbit observations. These challenges result in a lack of continuous and high-fidelity data support for ground-based X-ray pulsar navigation (XPNAV) research and validation. To overcome these obstacles, we propose an innovative method for the efficient and rapid simulation of X-ray pulsar signals as received by spacecraft. Building on the physical process that, although the arrival times of the same pulsar signal differ between the spacecraft and the Solar System Barycenter (SSB), these times can be calibrated to the same phase at the SSB using a timing model, we leverage the relationship between the pulsar signal’s arrival rate at the SSB and its arrival phase. Using the Order Statistical Method (OSM), we directly and effectively generate the arrival phase series of pulsar signals received by the spacecraft, which follow a non-homogeneous Poisson process (NHPP). Subsequently, from these phase series, we derive the arrival time series of spacecraft-received pulsar signals, incorporating multiple physical effects based on a relationship model between arrival time series and phases. This method significantly reduces the required simulation time while maintaining high accuracy, thereby greatly enhancing simulation efficiency. Validation against data from the Rossi X-ray Timing Explorer (RXTE) and the Neutron Star Interior Composition Explorer (NICER) shows that the correlation coefficients between the accumulated profiles of simulated and measured data exceed 0.99. Furthermore, our method reduces the simulation time of high-flux pulsar signals by 25.7 %, high spin frequency signals by 40.8 %, and long observation duration signals by 25.38 % compared to the latest fast simulation techniques, highlighting its advantages in accuracy, speed, and versatility for simulating pulsar signals across varying flux rates, spin frequencies, and observation durations. This approach provides continuous and effective data support for XPNAV research, significantly advancing theoretical and practical developments in the field.

Association of Postpartum Temperature Exposure with Postpartum Depression: A Retrospective Cohort Study in Southern California.

Postpartum depression (PPD) has been associated with biological, emotional, social, and environmental factors. However, evidence regarding the effect of temperature on PPD is extremely limited. We aimed to examine the associations between postpartum temperature exposure and PPD. We conducted a retrospective cohort study using data from Kaiser Permanente Southern California electronic health records from 1 January 2008 through 31 December 2018. PPD was first assessed using the Edinburgh Postnatal Depression Scale (score ) during the first year of the postpartum period and further identified by using both diagnostic codes and prescription medications. Historical daily ambient temperatures were obtained from the resolution gridMET dataset (https://www.climatologylab.org/gridmet.html) and linked to participants' residential addresses at delivery. Postpartum temperature exposures were measured by calculating various temperature metrics during the period from delivery to PPD diagnosis date. A time-to-event approach with a discrete-time logistic regression was applied to estimate the association between temperature exposure and time to PPD. Effect modification by maternal characteristics and other environmental factors was examined. There were 46,114 (10.73%) PPD cases among 429,839 pregnancies ( age y). Increased PPD risks were positively associated with exposure to higher mean temperature [adjusted odds ratio (aOR) per interquartile range increment: 1.07; 95% confidence interval (CI): 1.05, 1.09] and diurnal temperature range (; 95% CI: 1.06, 1.10); the associations were stronger for maximum temperature compared with minimum temperature. The temperature-related PPD risks were greater among African American, Asian, and Hispanic mothers and among mothers years of age compared with their counterparts. We also observed higher effects of temperature on PPD among mothers exposed to higher air pollution or lower green space levels and among mothers with lower air conditioning penetration rates. Maternal exposure to higher temperature and diurnal temperature variability during the postpartum period was associated with an increased risk of PPD. Effect modification by maternal age, race/ethnicity, air pollution, green space, and air conditioning penetration was identified. https://doi.org/10.1289/EHP14783.

NFC Tag Awareness and Its Visual Implementation on Food Packaging: Case Study in Slovenia

Many companies are using smart packaging to provide consumers with more information about their products. The goal of our case study is to access the Near Field Communication (NFC) tag knowledge, as well as getting insights into tag positioning in food package design for better visibility in order to develop some guidelines for future tag implementations. A preliminary survey of professionals provided an overview of NFC tag usage, followed by an online survey that assessed knowledge and visibility of tag placements. These findings were further discussed in focus groups and measured using eye-tracking technology. For placement visibility assessments, well-known and fictitious packaging designs of milk were used. The results show that, due to the NFC tag’s low market penetration, consumer recognition is low, with only generations Y and Z being familiar with the NFC tag. Knowledge of the NFC tag does not significantly vary based on education level. When considering the use of NFC tags, it is crucial to define and understand the target market. If the target is younger generations, the potential to increase engagement with the product can be achieved. Additionally, to boost consumer interaction, NFC tags or other smart elements should include an activation prompt, positioned on the central right section of the packaging and distinguished by a distinct color. The influence of the design on tag visibility is essential to ensure its effectiveness.

Experimental Study on Liquid Jet Trajectory in Cross Flow of Swirling Air at Elevated Pressure Condition

Abstract Motivated by fuel atomization applications in gas turbine combustors, this paper presents an experimental examination of liquid jet trajectory and spray dynamics in crossflow of swirling air, at elevated pressure conditions. The study was conducted within an annular passage and was focused on momentum flux ratio and swirl number as the main parameters. The momentum flux ratio was varied from 2 to 25 through incremental adjustments to the liquid injection velocity and the swirl number values of 0.42 and 0.74 were used, representing typical gas turbine fuel atomization conditions. Jet trajectories were captured by imaging the three-dimensional helical path traced by the liquid jet using two mutually perpendicular optical windows. Radial penetration was quantified by solving the equations of a helix. The key findings revealed that radial penetration of the liquid jet is larger for higher momentum flux ratios and is influenced by the helical arc length. Notably, the radial penetration observed at low momentum flux ratios was larger for crossflow with lower swirl number and the radial penetration observed at high momentum flux ratios was more for crossflows with higher swirl number. In comparison to the spray characteristics in swirling crossflows at atmospheric pressure, condition of elevated gaseous pressure resulted in lower radial penetration, jet spread and jet area. Jet trajectory correlations for elevated pressure conditions are additionally presented, developed using curve fitting to the experimental data, which will be useful to the industry for estimation of spray trajectory in swirling crossflows at high pressure conditions.

Role of common variants and new genes associated with arrhythmogenic cardiomyopathy

Abstract Introduction Arrhythmogenic Cardiomyopathy (ACM) is an inherited cardiac disease, predominantly affecting males, characterized by fibro-fatty myocardial replacement mainly in the right ventricle. It leads to 5% sudden cardiac death in affected young adults (<25 yo) without an implantable cardioverter defibrillator. Early diagnosis is crucial for appropriate clinical management to reduce mortality and prevent disease progression. Rare variants in desmosomal genes (PKP2,DSC2,DSG2,DSP and JUP) are found in 50% of cases. However, challenges persist since we observe a low penetrance in relatives (28-58%) and a high variability in expressivity and severity annihilating any preventive strategy. Objective We aim to decipher the genetic architecture of ACM by investigating the role of common variants in disease susceptibility/severity and to idendify new genes associated to ACM. Method A Genome Wide Association Study (GWAS) was performed on 1079 ACM index patients and 7305 controls, followed by conditional analysis. New candidate genes were knocked out (KO) in Zebrafish and/or hiPSC using CRISPR/Cas9. Impedance and external field potential measurements were performed on hiPSC derived cardiomyocytes (CM-hiPSC). Results The GWAS identified 5 significant loci (Figure 1, P<5.10-8), including 2 desmosomal genes (PKP2 a n d DSG2) and 3 new candidates (KLF12, CTNNA3, and ARL17B/WNT3). Conditional analysis revealed 3 additional loci with suggestive p-values (P<1.10-6), highlighting 3 new susceptible loci. Among them, we uncovered key non-coding regulatory regions near desmosomal genes (DSC2 and DSG2). Initial findings in PKP2-KO zebrafish present hearts with structural defects, while CM-hiPS KLF12-KO(-/-) exhibited altered interbeat interval and relaxation time compared to isogenic controls. Conclusion Our findings reveal ACM's complex genetic architecture, implicating common variants in disease susceptibility. A polygenic risk score will be implemented to improve patient risk stratification. Three novel loci/genes for ACM as well as specific regulatory regions of desmosomal genes have been highlighted. Their functional studies in isogenic hiPSC and Zebrafish models will offer new insights in ACM underlying molecular mechanism and potential therapeutic targets.

Quantifying motion blur by imaging shock front propagation with broadband and narrowband X-ray sources

Time-integrated radiography using MeV Bremsstrahlung X-ray sources is the norm for imaging during system-level testing of components and structures under dynamic condition. One source of error in the analysis of the time-integrated radiography data sets stems from motion blur which smears out sharp interfaces to a greater degree with longer exposure times, which become necessary to provide sufficient signal-to-noise with low X-ray penetration of objects of interest. To quantify motion blur, a 1D shock wave through PMMA was investigated experimentally at The Dynamic Compression Sector at The Advanced Photon Source (DCS@APS) with tapered broadband and 25.46 ± 1.06 keV narrowband X-rays. Four cameras with different exposure times were used for each experiment to compare the effect that exposure time has on motion blur. In addition, our methodology to accurately simulate motion blur in terms of transmission and shape is presented and compared to our experimental results and quantified. There is a high level of agreement between the experimental and simulation results across the range of data sets investigated in this study with a percent difference range of 0.29–1.31% for the four shots. The methodology of this work serves as a steppingstone towards a physically validated model that could be used in conjunction with experimental results to deconvolve physical parameters, densities, and interfaces of interest in a way that would not be possible with experimental results alone.

Transferability of real-time EVT safety models: an investigation using autonomous vehicles data

Recent research has shown that data from autonomous vehicles (AVs) enables proactive, real-time road safety management. However, with low AV market penetration, it's crucial to assess the transferability of AV-based safety models to other locations. This study transfers real-time safety models from a data-rich to a data-scarce environment using vehicular conflict data collected by AVs. Multi-site Bayesian hierarchical Extreme Value Theory models are developed in two cities, with model transfer evaluated using informative priors and parameter recalibration. Both approaches produce reliable results, though the transferability index favors the informed prior method, while predictive deviance shows similar performance for both. Model sensitivity to temporal data limitations is assessed, revealing that the recalibration approach is more sensitive to block size, whereas the informed prior method remains stable. A novel method mimicking data limitations shows transferred models perform well with data utilizations above 20%, promoting transferability to mitigate data inadequacy.

Prediction of TBM cutter wear in heterogeneous ground under high ambient pressure

To prevent tunnel face collapse in heterogeneous ground, the applied face pressure in the excavation chamber can be increased to stabilise the tunnel face, which may hinder cutter rotation during tunnel boring machine (TBM) tunnelling. This study proposes a TBM cutter wear prediction model that considers the impact of the variation in the cutter normal force on the cutterhead owing to the high applied face pressure and low penetration rate. First, the cutter motion mode in heterogeneous ground is investigated. The cutter is found to slide when cutting soft rock based on an analysis of the field data. The evolution process of the cutter wear morphology under heterogeneous ground conditions is summarised. A method for calculating the cutter normal force when the cutter slides on the tunnel face is proposed by referring to the cutting mechanism of the drag bits. The cutter hardness is measured on-site using a portable hardness tester. A semi-empirical model considering the variation in the cutter normal force on the cutterhead is proposed to predict the cutter wear in heterogeneous ground. Wear prediction is compared with other predictive models and field data for validation, and the discrepancies between the different models are discussed. The results show that the proposed model is effective for predicting TBM cutter wear under complex geological conditions.

How Connected Cars Could Capture Cloud Dynamics for Solar Forecasting—Evidence from Two Simulation Scenarios

The rapidly increasing share of fluctuating electricity from photovoltaics calls for accurate approaches to estimate cloud motion, the primary source for the varying power supply. While local sensor networks are prominent in targeting forecast horizons too short for image‐based methods, they have minimal spatial coverage. This work presents the first step towards expanding those approaches to spatially scalable sensor networks: With the motivation of using automotive light sensors as a sensor network, two excerpts from a microscopic traffic simulation serve as simulative sensor networks. A fractal‐based cloud shadow pattern passes the sensor network areas with defined velocities and directions, which shall be estimated using the cumulative mean absolute error method. The evaluation results indicate that the more extensive observation areas compensate for the dynamics in the sensor network when compared to a reference work with a static sensor grid. Furthermore, this work shows how the estimates deteriorate with lower vehicle penetration rates (PR) and longer building shadows due to a lower solar elevation angle. At a penetration rate of 40%, the root mean square errors for both sensor networks are still below 5 ms−1. In conclusion, the spatiotemporal characteristics of a vehicle network offer a potential for estimating cloud movements.

Analytical Solutions for Composite Foundations Reinforced by Partially Penetrated Stone Columns and Vertical Drains

ABSTRACTWhen stone columns or vertical drains are applied to improve soils, it is common to face situations where the soft soil layer is too thick to be penetrated completely. Although consolidation theories for soils with partially penetrated vertical drains or stone columns are comprehensive, consolidation theories for impenetrable composite foundations containing both two types of drainage bodies have been few reported in the existing literature. Equations governing the consolidation of the reinforced zone and unreinforced zone are established, respectively. Analytical solutions for consolidation of such composite foundations are obtained under permeable top with impermeable bottom (PTIB) and permeable top with permeable bottom (PTPB), respectively. The correctness of proposed solutions is verified by comparing them with existing solutions and finite element analyses. Then, extensive calculations are performed to analyze the consolidation behaviors at different penetration rates, including the total average consolidation degree defined by strain or stress and the distribution of the average excess pore water pressure (EPWP) along the depth. The results show that the total average consolidation rate increases as the penetration rate increases; for some composite foundations with a low penetration rate, the consolidation of the unreinforced zone cannot be ignored. Finally, according to the geological parameters provided by an actual project, the obtained solution is used to calculate the settlement, and the results obtained by the proposed solution are in reasonable agreement with the measured data.