Inverse Analysis Research Articles

Impact of more than one distal anastomosis on the same territory in three-vessel disease patients

BACKGROUNDPrevious studies defined complete revascularization as the placement of at least one bypass graft to each diseased coronary territory. This study was conducted to evaluate whether putting more than one graft to each diseased coronary territory is beneficial for patients with three-vessel disease (3VD) who underwent coronary artery bypass grafting (CABG). METHODSAmong 1,859 patients who underwent primary isolated CABG, 1008 patients (male:female=841:239, 67.0±9.3 years) who underwent off-pump CABG for 3VD and in whom complete revascularization was achieved were retrospectively enrolled. Complete revascularization was defined as at least one graft to each coronary artery territory. The median follow-up duration was 86.6 months [interquartile range, 53.0-126.9]. RESULTSEight hundred and twenty nine patients (82.2%) had more than 3 distal anastomoses whereas the other 179 patients had 3 distal anastomoses. Hypertension (n=729, 72.3%) and diabetes (n=556, 55.2%) were the most common comorbidities without any intergroup differences. Early mortality rate was 1.0% (n=10). Late death occurred in 337 out of 998 early survivors. Five- and 10-year all-cause mortality rates were 18.0% and 36.0%, respectively. Cumulative incidences of cardiac deaths were 5.2% and 9.2%, respectively. The inverse probability treatment weighting-adjusted multivariate analyses showed that more than 3 distal anastomoses was associated with lower all-cause mortality and cardiac death (hazard ratio [95% confidence interval] = 0.76 [0.57-0.99] and = 0.50 [0.31-0.83], respectively). CONCLUSIONSGrafting more than one diseased-vessel in each diseased coronary territory during CABG might be beneficial for patients with 3VD in terms of all-cause mortality and cardiac death.

Determination of the Gurson-Tvergaard-Needleman damage model parameters for simulating small punch tests of heat-resistant alloys

The small punch (SP) test is utilized to assess the mechanical characteristics and damage progression of heat-resistant alloys. The inverse finite element analysis method incorporating SP tests is a parameter identification method based on adjusting the accuracy of the simulated load-displacement curves. In this paper, the elastoplastic parameters of the Hollomon model and the damage parameters of the Gurson-Tvergaard-Needleman (GTN) model are determined based on the undamaged and damaged stages of the load-displacement curves, respectively. The whole stress-strain curves of the tested materials are then built using the results of finite element simulations of the tensile specimens of ZG15Cr2Mo1, P91, 316H, and Hastelloy X at room and elevated temperatures. Comparison with uniaxial tensile tests indicates that the simulated stress-strain curves closely resemble the experimental data from the tensile testing. In addition, the simulated damage evolution characteristics of the SP specimens are consistent with the mechanical model based on the actual deformation behavior. It is possible to comprehend the damage evolution process by analyzing the SP specimens’ stress and strain change characteristics.

Inclusion of Surgery in Multimodality Treatment is Predictive of Better Survival in Stage IIIA Non-small Cell Lung Cancer: an Inverse Probability Treatment-Weighting Analysis

IntroductionStage IIIA non-small cell lung cancers (NSCLC) are treated with surgical based multimodality approach or definitive chemoradiation therapy plus durvalumab consolidation. It is not clear whether surgery-based multimodality therapy has any survival advantage over definitive chemoradiation plus immunotherapy consolidation. MethodNational Cancer Database (NCDB) was used to identify NSCLC patients at stage IIIA (AJCC8, T3N1/T4N0-1 or T1N2/T2N2) who are treated with surgery-based multimodality approach or definitive chemoradiation plus durvalumab. Survival between groups were compared using inverse probability of treatment weighting (IPTW)-adjusted Kaplan Meier curves and Cox proportional hazards regression analysis. Results were independently confirmed by Landmark Inverse and Clone Censor Weight analyses to address immortal time bias. ResultsFrom 2017 to 2019, 24,170 patients are identified as potentially resectable stage IIIA (T3N1, T4N0-1, T1N2/T2N2). Among them, 2,615 (10.8%) received surgery-based multi-modality therapy and 2,985 (12.4%) received definitive chemoradiation plus durvalumab. Surgery based multimodality approach had significant survival advantage over definitive chemoradiation plus durvalumab (HR 0.74; 95% CI 0.69-0.79, P<0.001). The median overall survival (mOS) for the definitive chemoradiation plus durvalumab group was 48.59 m whereas mOS was not reached for surgery-based multimodality group. This trend persisted in both N2 negative and positive tumors. Neoadjuvant chemotherapy was just as effective as adjuvant chemotherapy and delay of immunotherapy consolidation to 12 weeks after initiation of chemoradiation did not negatively affect survival outcome. ConclusionFor stage IIIA NSCLC patients, surgery-based multimodality treatment outperformed chemoradiation plus durvalumab in survival. DisclosureZH reports grant from Bayer Inc, BMS, Merck, AMG, Legend biotech, BeiGene, Novartis and OncC4. No disclosure from all other authors. MicroAbstractResectable stage IIIA non-small cell lung cancer treated with multi-disciplinary approach with surgical resection survive longer than those who were treated with concurrent chemoradiation therapy plus consolidation durvalumab. Chemotherapy can be given as adjuvant or as neoadjuvant with no survival difference. Delay of immunotherapy consolidation to more than 12 weeks after starting radiation does not compromise survival outcome.

Association Between Gallstones and Depressive Symptoms: Results from NHANES and Mendelian Randomization Study.

Prior research has suggested a correlation between gallstones and depressive symptoms, yet the specifics of this relationship remain unclear. This study aims to explore the association between gallstones and depressive symptoms among adults. Initially, we conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) 2017 - March 2020. After propensity score matching (PSM) for participants with gallstones and those without gallstones, multivariate logistic regression analysis was used to explore the potential association between gallstones and depressive symptoms. This was followed by Mendelian randomization (MR) analysis to further elucidate the causal relationship between them. Using the genome-wide association study database, we extracted instrumental variables and performed bidirectional univariate and multivariate MR analyses. In the cross-sectional study of NHANES 2017 - March 2020, 835 pairs of participants with comparable characteristics, both with and without gallstones, were identified after PSM. The multivariate adjusted logistic regression analyses revealed a significant association between gallstones and depressive symptoms [fully adjusted model: OR=1.821 (95% CI, 1.181-2.808), P=0.007]. Subsequent MR analyses further clarified the causal relationship, indicating that genetically determined gallstones significantly increase the risk of developing depressive symptoms [forward univariate MR analysis: OR=1.04 (95% CI, 1.01-1.06), P=0.002; multivariate MR analysis: OR=1.03 (95% CI, 1.01-1.05), P=0.009], with no evidence of reverse causation [inverse univariate MR analysis: OR=1.28 (95% CI, 0.90-1.83), P=0.17]. Gallstones are a risk factor for depressive symptoms among adults. Hence, we recommend timely depression screening for patients diagnosed with gallstones, facilitating early detection and effective treatment of depressive symptoms, thus alleviating its impact on both individuals and society.

Inverse Chance-Constrained Dynamic Data Envelopment Analysis under Natural and Managerial Disposability: Concerning Renewable Energy Efficiency and Potentials

The performance of dynamic systems with specific data has been examined in some data envelopment analysis (DEA) studies. However, in many real-life situations, dealing with dynamic systems becomes challenging because of random factors. So, in this paper, a chance-constrained dynamic DEA approach under managerial and natural disposability is first proposed to analyze the dynamic renewable energy efficacy of processes in the presence of random performance measures. Then, the potentials of some performance metrics are addressed for changes of others using the introduced inverse chance-constrained dynamic DEA models. The chance-constrained dynamic DEA techniques and their inverse dynamic stochastic problems are converted into linear problems. The introduced approaches are applied to probe the renewable energy efficiency and potentials of some OECD countries in a span of time. The results show stochastic dynamic DEA and inverse stochastic dynamic DEA provided are practical tools for making the best choices, when there is uncertainty.

Personalizing the shoulder rhythm in a computational upper body model improves kinematic tracking in high range-of-motion arm movements

Musculoskeletal models of the shoulder are needed to understand the mechanics of overhead motions. Existing models implementing the shoulder rhythm are generic and might not accurately represent an individual’s scapular kinematics. We introduce a method to personalize the shoulder rhythm of a computational model of the upper body that defines the orientations of the clavicle and scapula based on glenohumeral joint angles. During five static calibration poses, we palpate and measure the orientation of the scapula. We explore the importance of representing shoulder elevation by introducing clavicle elevation as a degree of freedom that is independent of the glenohumeral angles. For ten subjects, we record the five calibration poses, ten additional static poses, and dynamic arm raises covering the participants’ full range of motion in each body plane using optical motion capture. We examine the data using a dynamically-constrained inverse kinematics analysis. Shoulder rhythm personalization, independent clavicle elevation, and both in combination reduce the average upper body marker tracking error compared to the generic model in the static poses (26 mm to 17–20 mm) and in the dynamic trials (22 mm to 14–17 mm). Only personalization reduces the average scapula marker error (51 mm to 36–38 mm) and scapula axis-angle error (15° to 10°) compared with the palpated ground truth measurements in the static poses, and in the dynamic trials at instances that best match the static poses (53 mm to 37–40 mm, 15° to 9°). Our results show that personalizing upper body models improves kinematic tracking. We provide our experimental data, model, and methods to allow researchers to reproduce and build upon our results.

Investigation on flooding dynamic response and mitigation measure of river bridge

Flood-induced failure of river bridges is intense due to frequently extreme and undesigned precipitation for global climate change. To reveal the dynamic characteristics and failure mechanism of bridges, flooding dynamic analysis is fully investigated via fluid–structure interaction simulation and Arbitrary Lagrangian-Eulerian method. Parametric analysis of different fluids and bridge configurations and pre-ballast mitigation measure are further conducted based on a simply-supported box-girder bridge. This study reveals several significant findings: the narrow channel can accelerate downstream flood velocity of the bridge piers to over double that of the upstream flow; moreover, unsubmerged piers experience vertical downward wave force surpassing buoyancy; the box girders exhibit three flood-response states, i.e., intact, slip and collapse, dependent on the hydraulic loading and bridge resistance capacity. Maximum horizontal wave force and displacement increase exponentially with the depth of water storage. Post-slip damage, bearing stress on the wave-facing side tends towards zero, while the wave-backing side presents a twofold increase. Maximum horizontal displacement (Xmax) distinguishes the failure states, such as 0 m ≤ Xmax ≤ 0.03 m (intact), 0.03 m < Xmax ≤ 1.39 m (slip), Xmax > 1.39 m (collapse), whose relation to the maximum horizontal wave force has been proposed for design reference and the inversion analysis of the bridge force. Applying a pre-ballast equivalent to 75 % of girder weight reduces Xmax by up to 91.5 %, shifting failure from collapse to slip. These insights offer crucial guidance for enhancing bridge safety amidst escalating flood risks.

Parameter Calibration of Chaboche Kinematic Hardening Model by Inverse Analysis Using Different Optimization Methods in the Case of Pipe Bending

Drag link is one of the important parts in steering system used in automotive. The ball joint, ball joint housing, and pipe compose the drag link. In this study, finite element analysis is used to simulate the deformation process. St 52 steel material is used. A yield criterion, an associated flow rule, and Chaboche’s kinematic hardening rule were used in the finite ele-ment simulations of processes involving high plastic deformation. A series of low-cycle ten-sile/compression tests is performed to determine the parameters of Chaboche’s kinematic hardening rule. The success of the simulation results depends on the more accuracy of the finding parameters. Some optimization methods are used in the calibration progression of these parameters and the results are compared. For the purpose of optimization, the angle of the pipe after bending is set as 16.6 as soon as possible. As design variables, the Chaboche kinematic hardening rule parameters were adjusted. Consequently, calibrated parameters were obtained for St52 pipe bending. By analysing and verifying the candidate points, opti-mization methods are compared. The optimum parameters are determined as YS=350 MPa, C=2984.3 MPa, and =100 while their initial values are YS=373.806 MPa, C=4016 MPa, and =94. It is concluded that the optimization process gives more consistency in the bending process.

Two-stage stochastic multi-criteria group decision making for wind-photovoltaic-hydropower scheduling

Scheduling of wind-photovoltaic-hydropower systems is a complex multi-objective collaborative problem which requires multi-criteria decision making (MCDM) to assist in formulating the most-preferred scheduling scheme. There are uncertainties existing in criteria weights (CWs) due to the limitations of the knowledge level of decision makers and the subjectivity of preferences. This paper proposes a two-stage stochastic multi-criteria group decision making model considering the uncertainties in the decision making environment and the progression of the decision making process. For the prophase decision making (the first stage), the stochastic multi-criteria acceptability analysis (SMAA) theory and the MCDM model VIKOR are combined to construct a SMAA-VIKOR model for inverse weight space analysis on the situation that the initial CW information is completely unknown. In the second stage of decision making, the decision makers are allowed to express their fuzzy preferences based on the information provided in the first stage by coupling the intuitionistic fuzzy analytic hierarchy process (IFAHP) into the SMAA-VIKOR model to obtain the final scheme. The wind-photovoltaic-hydropower system in Yalong River Basin is selected as the case study. Results show that among the 12 alternative schemes, scheme A2 is ranked first with the probability of 0.69 in the first stage while the probability of taking the first ranking in the second stage is increased to 1. More explicit ranking results are obtained based on the results of the first stage, which effectively enhances the confidence of decision makers and improves decision making efficiency.

The influence of insulin on diabetic retinopathy and retinal vessel parameters in diabetes

AimTo investigate the associations between insulin use and diabetic retinopathy (DR), and retinal vascular parameters in type 2 diabetes (T2DM).MethodsA total of 6,374 T2DM patients, consisting of 2,231 patients receiving insulin alone and 4143 patients without any hypoglycemic medication, were included in cross-sectional analyses. Among those without DR at baseline, 791 patients were followed for three years in longitudinal analyses. Fundus photography was taken to diagnose DR and calculate central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE), arteriolar-to-venular ratio (AVR), and vascular tortuosity. Inverse probability treatment-weighted analyses were performed.ResultsAfter adjusting for gender, age, body mass index, blood pressure, blood glucose, T2DM duration, smoking, and alcohol use, insulin users showed a higher risk of DR (odds ratio (OR) = 2.27, 95% confidence interval (95%CI) = 2.08–2.48, P < 0.001), larger CRVE (β = 3.92, 95%CI = 2.46–5.37, P < 0.001), smaller AVR (β=-0.0083, 95%CI=-0.0121- -0.0046, P < 0.001), and larger vascular curvature (β = 0.19, 95%CI = 0.05–0.33, P = 0.008). After 3 years, insulin users had a higher risk of developing DR (OR = 1.94; 95% CI = 1.37–2.73, P = 0.002), and greater change in CRVE (β = 3.92, 95%CI = 0.96–6.88, P = 0.009).ConclusionsThe impact of insulin on the retinal microvasculature provides support for linking insulin to the increased risk of DR, as well as cardiovascular events in T2DM.

Deep learning-aided inverse analysis framework to accelerate the exploration of DP steel microstructures

Materials development requires numerous numbers of trial and error experiments. To reduce the experimental cost, numerical simulations which predict material microstructures and mechanical properties have a great potential to estimate the microstructures that should be produced for obtaining materials with the desired properties. There is a need to develop dual-phase (DP) steel with higher strength and ductility because DP steel is widely used due to its significant mechanical properties. DP steel consists of a soft phase (ferrite) and a hard phase (martensite), and the mechanical properties depend on the ratio of the two phases. The mechanical properties of DP steels are affected by the spatial distribution of martensite and ferrite, which requires a comprehensive consideration of a variety of microstructures. The problem is how to estimate microstructures of DP steel with the desired mechanical property because a comprehensive investigation of microstructures makes computational cost significantly expensive. For the purpose of reduction of the computational costs, we aim to develop a framework with low computational cost. The developed framework finds the optimal microstructure of DP steel by repeated random searches for a model that combines a generative adversarial network (GAN), which generates microstructures, and a convolutional neural network (CNN), which predicts the maximum stress and working limit strain from microstructures. Due to a low-dimensional search space provided by a latent variable of GAN, the proposed framework enables an efficient search for microstructures possible. To explore the desired microstructures under complex deformation modes, the multiple deformation modes are considered in this study. This framework is applicable not only for the microstructure of DP steel but also any other material microstructures. We are exhaustively able to explore the microstructure with desired properties of metallic or other composite materials in low-dimensional space thanks to this framework and contributes to accelerating materials development.

Clinical impact of visceral adiposity on long-term mortality in patients undergoing coronary artery bypass grafting

Introduction and objectivesAlthough visceral adiposity increases cardiovascular risk in the general population, the obesity paradox has been reported in critically ill patients. However, evidence for its prognostic role in patients undergoing coronary artery bypass grafting (CABG) is limited. This study evaluated the prognostic implications of visceral adiposity in patients who underwent CABG using computed tomography-based measurement of visceral fat. MethodsA total of 2810 patients who underwent CABG from 2007 to 2017 were analyzed. The study population was classified into 3 groups according to visceral fat area index (VFAI) tertiles. VFAI was calculated as visceral fat area (cm2)/height2 (m2) at the L3 level. The primary outcome was all-cause mortality during follow-up. ResultsPatients in the low VFAI group (lowest tertile) were younger and had a lower body mass index and less subcutaneous fat than those in the high VFAI group (highest tertile). During a median 8.7-year follow-up, VFAI was significantly associated with the risk of mortality in restricted cubic spline curve analysis (HR, 0.94 per 10 increases; 95%CI, 0.91-0.97; P<.001). Patients in the low VFAI group had a higher incidence of long-term mortality than those in the intermediate and high VFAI groups (T1 36.1%, T2 27.2%, and T3 29.1%; T1 vs T2; adjusted HR, 1.36; 95%CI, 1.15-1.61; P<.001; T1 vs T; adjusted HR, 1.37; 95%CI, 1.16-1.62; P<.001). Similar results were obtained after inverse probability treatment-weighting analysis. ConclusionsLow visceral adiposity was associated with an increased risk of long-term mortality in patients who underwent CABG.

Type 2 diabetes mellitus has a positive role in osteomyelitis: A Mendelian randomization analysis.

According to clinical evidence, type 2 diabetes mellitus (T2D) and osteomyelitis (OM) are currently the 2 major causes of mortality and morbidity in humans. Despite accounts of their coexistence, there is still no understanding of their fundamental connection. We attempted to assess the causal effect of T2D on OM using the two-sample Mendelian randomization method. The whole gene-wide association study's aggregate data were examined. Single-nucleotide polymorphisms, which have a substantial correlation with T2D, were used as instrumental variables in a two-sample Mendelian randomization (MR) analysis to assess the causal relationship between T2D and OM risk using the inverse variance weighting, MR-egger regression, and weighted median approaches, respectively. A total of 114 single-nucleotide polymorphism were used as instrumental variables in this analysis. The inverse variance-weighted analysis showed a significant causal relationship between T2D and OM, indicating that T2D has a detrimental effect on OM risk. The odds ratio for the causal effect of T2D on OM was 1.317, with a 95% confidence interval of (1.140, 1.522) (P < .001). To assess heterogeneity, Cochran Q test statistics and MR-Egger regression were applied in the inverse variance-weighted technique. The P-value of .737 indicated a considerable level of heterogeneity was not absent in the data. This study used Mendelian randomization analysis to establish a causal relationship between T2D and OM. The findings suggest that T2D may increase the risk of OM.

Histone-modifying enzymes and gastric cancer: Search for potential biomarkers and therapeutic targets based on Mendelian randomization

Gastric cancer, a common and severe malignancy, is associated with unfavorable outcomes and limited therapeutic options. The exploration of the potential link between plasma histone-modifying enzymes and gastric cancer through Mendelian randomization (MR) analysis offers an opportunity to identify new therapeutic targets and biomarkers. In this study, data on plasma histone-modifying enzymes were obtained from the International Working Unit Open genome-wide association studies project, and summary statistics of gastric cancer from the FinnGen study were analyzed. Forward and inverse MR were performed to determine the causal relationship between plasma histone-modifying enzymes and gastric cancer. The principal methodology for MR is the inverse variance weighted (IVW) method. Additionally, a sensitivity analysis was performed to determine the robustness of the findings. Finally, bioinformatics was used for the preliminary functional analysis. Our forward MR analysis revealed that the plasma Set1/Ash2 histone methyltransferase complex subunit ASH2 (ASH2L) was positively associated with gastric cancer risk, and the histone-lysine N-methyltransferase SETMAR (SETMAR) was negatively associated. Inverse MR analysis revealed that gastric cancer incidence was negatively correlated with the expression of plasma histone acetyltransferase KAT6A (KAT6A). These findings were consistent across different statistical methods and were deemed unlikely to have been distorted by horizontal pleiotropy. Furthermore, bioinformatics analysis indicated that ASH2L, SETMAR, and KAT6A are differentially expressed in various tumors and are significantly correlated with both the prognosis of gastric cancer and the infiltration of various immune cells. Thus, plasma histone-modifying enzymes may be causally linked to gastric cancer, and ASH2L, SETMAR, and KAT6A could play crucial roles as biomarkers and therapeutic targets in managing gastric cancer.

A clinical investigation of force plate drift error on predicted joint kinetics during gait

Inverse dynamic analysis is a technique used during gait analysis to estimate intersegmental forces and net joint moments. Inverse dynamic calculations are susceptible to various forms of error. One such error is force plate drift, often produced by humidity condensing within the input connectors and electronics, causing an undesired change in output over time. This can be particularly concerning for movement laboratories where inverse dynamics are considered in clinical decision-making processes. Manufacturers will provide tolerance levels for drift. However, levels of acceptable drift are rarely considered from a clinical perspective. Therefore, this study aims to establish clinically acceptable limits of force plate drift error, induced by applying systematic errors to force plate channels, on predicted lower limb joint moments during gait. Gait data of 10 children with typical development were analysed and induced errors of 0.5 N, 1 N, 1.5 N, 3 N, 6 N and 12 N were incrementally applied to the horizontal and vertical force channels. Data were recalculated for each increment and mean profiles compared to an error free mean (±1SD) band. Error was deemed clinically significant when moments fell outside the mean (±1SD) band. Induced error at 6 N and above was sufficient to cause a clinically significant change. Sagittal and coronal plane moments at the hip were most affected, followed by the knee and then the ankle. While manufacturer guidelines for acceptable drift are usually well below 6 N, care is needed when using force plates over several minutes or more as drift may eventually exceed clinically acceptable limits.

Development of a Six-Degree-of-Freedom Deep-Sea Water-Hydraulic Manipulator

With the advancement of deep-sea exploration, the demand for underwater manipulators capable of long-duration heavy-duty operations has intensified. Water-hydraulic systems exhibit less viscosity variation with increasing depth than oil-based systems, offering better adaptability to deep-sea conditions. Using seawater as the driving medium inherently eliminates issues such as oil contamination by water, frequent maintenance limiting underwater operation time, and environmental pollution caused by oil leaks. This paper introduces a deep-sea manipulator directly driven by seawater from the deep-sea environment. To address the challenges of weak lubrication and high corrosion associated with water hydraulics, a reciprocating plunger seal was adopted, and a water-hydraulic actuator was developed. The installation positions of actuator hinges and maximum output force requirements were optimized using particle swarm optimization (PSO), effectively reducing the manipulator’s self-weight. Through kinematic and inverse kinematic analyses and joint performance tests, a six-degree-of-freedom water-hydraulic manipulator was designed with a maximum reach of 2.5 m, a lifting capacity of 5000 N, and end-effector positioning accuracy within 18 mm.

Inverse modeling of 2010–2022 satellite observations shows that inundation of the wet tropics drove the 2020–2022 methane surge

Atmospheric methane concentrations rose rapidly over the past decade and surged in 2020-2022 but the causes have been unclear. We find from inverse analysis of GOSAT satellite observations that emissions from the wet tropics drove the 2010-2019 increase and the subsequent 2020-2022 surge, while emissions from northern mid-latitudes decreased. The 2020-2022 surge is principally contributed by emissions in Equatorial Asia (43%) and Africa (30%). Wetlands are the major drivers of the 2020-2022 emission increases in Africa and Equatorial Asia because of tropical inundation associated with La Niña conditions, consistent with trends in the GRACE terrestrial water storage data. In contrast, emissions from major anthropogenic emitters such as the United States, Russia, and China are relatively flat over 2010-2022. Concentrations of tropospheric OH (the main methane sink) show no long-term trend over 2010-2022 but a decrease over 2020-2022 that contributed to the methane surge.

DNA methylation age acceleration is associated with incident cognitive impairment in the Health and Retirement Study.

DNA methylation clocks have emerged as promising biomarkers for cognitive impairment and dementia. Longitudinal studies exploring the link between DNA methylation clocks and cognitive decline have been constrained by limited sample sizes and a lack of diversity. Our study aimed to investigate the longitudinal associations between DNA methylation clocks and incident cognitive impairment using a larger sample size encompassing a US nationally representative sample from the Health and Retirement Study. We measured DNA methylation age acceleration in 2016 by comparing the residuals of DNA methylation clocks, including GrimAge, against chronological age. Cognitive decline was determined by the change in Langa-Weir cognition status from 2016 to 2018. Using multivariable logistic regression, we evaluated the link between DNA methylation age acceleration and cognitive decline, adjusting for cell-type proportions, demographic, and health factors. We also conducted an inverse probability weighting analysis to address potential selection bias from varying loss-to-follow-up rates. The analytic sample (N=2,713) at baseline had an average of 68 years old, and during the two years of follow-up, 12% experienced cognitive decline. Participants who experienced cognitive decline during follow-up had higher baseline GrimAge (mean = 1.2 years) acceleration compared to those who maintained normal cognitive function (mean = -0.8 years, p < 0.001). A one-year increase in GrimAge acceleration was associated with 1.05 times higher adjusted and survey-weighted odds of cognitive decline during follow-up (95% CI: 1.01-1.10). This association was consistent after accounting for loss-to-follow-up (OR = 1.07, 95% CI: 1.04-1.11). Our study offers insights into DNA methylation age acceleration associated with cognitive decline, suggesting avenues for improved prevention, diagnosis, and treatment.

Experimental analysis of a beam with a 2D triangular substructure

AbstractThe aim of this study is to determine experimentally the higher material parameter of a metamaterial with a triangular substructure and to verify a higher‐gradient elasticity model for beams with internal substructures or microstructures. The investigations of the higher‐gradient elasticity models of Bernoulli‐Euler and Timoshenko beams with a periodic triangular substructure in Khakalo et al. show that the bending stiffness strongly depends on the geometrical parameters of the lattice structure. To achieve this goal, beams with triangular substructures were additively manufactured using fused deposition modeling and stereolithography. They were experimentally investigated in tensile and bending tests. Three different types of beams with triangular substructures were produced, consisting of one, two and four layers of triangular beams, using two different materials: Polylactide and epoxy resin. The higher material parameter g was quantitatively determined based on the experimental results using inverse analysis. The results are valid for these specific variations of the substructure and can adequately represent the elastic size effects. In addition, this study investigates the relationship between the bending stiffness and the geometric parameters of the lattice structure as well as the influence of the curing time on the elastic properties of epoxy resin. The experiments involved testing the triangular beams under tensile and bending loads. The numerical and experimental results were compared using digital image correlation. Based on the experimental data, a higher gradient material parameter representing the geometric structure of the lattice was determined.

Near Real-time Leak Location by Inverse Analysis Integrating Measurement Uncertainty

AbstractThis paper presents a novel model-based method for near real-time pipe burst location in water distribution networks by integrating measurement uncertainty into inverse analysis. The method accounts for expected errors between measured and computed values, providing a pipe burst location area whose size varies according to the expected error level and the burst size. The proposed method is demonstrated and compared with the traditional inverse approach using a real case study with artificial bursts of different sizes and with different pressure signal noise levels. The performance of both methods is also assessed and discussed considering the effect of seasonal water demands. The traditional inverse analysis fails to accurately locate the pipe burst events, and depending on the expected error level and pipe burst size, the obtained locations may be significantly further away from the real burst location. Conversely, the proposed method does not point to the exact burst location but provides an approximated area in which step-testing can be carried out to pinpoint the exact burst location; the size of this area can be larger or smaller depending on the burst flow rate and signal uncertainty.