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A comparative case study for fatigue lifetime predictors on EPDM rubber
No full textPrediction of lifetime for rubber-like materials subjected to uniaxial and multiaxial loads is an essential requirement in design of rubber components. The current state-of-art predictions rely on a range of stretch, stress, and energy metrics; each with its own formal definition. Strain-based methodologies include maximum principal stretches, Green-Lagrange strain, and the left Cauchy-Green tensor, while stress-based techniques encompass minimum stress and maximum principal stress, Cauchy stress, and Eshelby stress using configurational mechanics. To exemplify energy-based approaches, critical plane approach of Mars, utilizing cracking energy density, has also gained prominence as an influential method in this context. Despite the extensive literature available on these methods, a comprehensive comparative study on EPDM rubber has been conspicuously lacking. This study addresses this gap by conducting a review and comparison of several fatigue predictors through a numerical case study. The comparison is based on obtained lifetime of the benchmark geometry, a two-pipe bushing under multiaxial loading conditions, directly. The outcomes of this case study are expected to provide insights for lifetime prediction of rubber components
Relations among parenting stress, parent-teacher relationship and parent engagement: A mediation model
No full textExploiting Polynomial Chaos Expansion for Rapid Assessment of the Impact of Tissue Property Uncertainties in Low-Intensity Focused Ultrasound Stimulation
No full textNeuromodulation with low-intensity focused ultrasound (LIFUS) holds significant promise for noninvasive treatment of neurological disorders, but its success relies heavily on accurately targeting specific brain regions. Computational model predictions can be used to optimize LIFUS, but uncertain acoustic tissue properties can affect prediction accuracy. The Monte Carlo method is often used to quantify the impact of uncertainties, but many iterations are generally needed for accurate estimates. We studied a surrogate model based on polynomial chaos expansion (PCE) to quantify the uncertainty in the LIFUS acoustic intensity field caused by tissue acoustic property uncertainties. The PCE approach was benchmarked against Monte Carlo method for LIFUS in three different head models. We also investigated the effect of the number of PCE samples on the accuracy of the surrogate model. Our results show that the PCE surrogate model requires only 20 simulation samples to estimate the mean and standard deviation of the acoustic intensity field with high accuracy compared to 100 samples needed for Monte Carlo method. The root mean squared percentage error (RMSPE) in the mean acoustic intensity field was less than 1.5%, with a maximum error of less than 0.5 W/cm2 (< 1% of the focus peak intensity in water), while the RMSPE in the standard deviation was less than 9%, with a maximum error of less than 0.3 W/cm2. The accuracy of the PCE surrogate model, and the limited number of iterations it requires makes it a promising tool for quantifying the uncertainty in the acoustic intensity field in LIFUS applications
Mixed Layer Depth Measurement in Coastal Waters Utilizing Atmospheric Muons
No full textMixed layer (ML) in oceans is defined as the less dense upper region of the water column where turbulent mixing occurs and water exhibits almost uniform density profile. Mixed layer depth (MLD) is the depth of this region and shows diurnal and seasonal fluctuations as well as spatial variations in different regions of water. The determination of MLD is an important indicator for climate change in bodies of water, and the novel method proposed here would allow for a continuous monitoring of MLD. Atmospheric muon count is proportional to the density of water which can be measured by counting muons at the bottom and comparing with a shore-based or buoy-based muon counter. Combining this measurement with sea surface temperature (SST) and sea surface salinity (SSS) data from Earth-observing satellites, daily mean MLD can be estimated with an accuracy of 3% for down to 60-m depth. To determine MLD from muon count difference between surface and bottom detectors, a new method was introduced to calculate MLD using average density of water column. A Geant4 model was made to show the validity and limitations of the method. Unlike open ocean, the system can measure MLD in shallow coastal waters where muon count at the bottom is enough for daily based measurements. The proposed method can provide continuous in situ measurement of MLD in coastal shallow waters, and these data can be used to provide boundary conditions for hydrodynamic and ecosystem models. SIGNIFICANCE STATEMENT: In our work, we proposed a scintillator-based underwater muon detection system which can measure average water column density by counting surviving atmospheric muons at the bottom of the shallow coastal waters. Combining this measurement with the sea surface temperature, salinity, and altimetry data from Earth-observing satellites, MLD can be estimated. In accordance with UN-SDG-14: Life Below Water, the determination of MLD is an important indicator for climate change in bodies of water, and the novel method proposed here would allow for a continuous monitoring of MLD
Recent Developments in Glioblastoma-On-A-Chip for Advanced Drug Screening Applications
No full textGlioblastoma (GBM) is an aggressive form of cancer, comprising ≈80% of malignant brain tumors. However, there are no effective treatments for GBM due to its heterogeneity and the presence of the blood-brain barrier (BBB), which restricts the delivery of therapeutics to the brain. Despite in vitro models contributing to the understanding of GBM, conventional 2D models oversimplify the complex tumor microenvironment. Organ-on-a-chip (OoC) models have emerged as promising platforms that recapitulate human tissue physiology, enabling disease modeling, drug screening, and personalized medicine. There is a sudden increase in GBM-on-a-chip models that can significantly advance the knowledge of GBM etiology and revolutionize drug development by reducing animal testing and enhancing translation to the clinic. In this review, an overview of GBM-on-a-chip models and their applications is reported for drug screening and discussed current challenges and potential future directions for GBM-on-a-chip models
THE ROLE OF TECHNOLOGY DISCOURSE IN AUTHORITARIANISM AND POPULISM: THE CASE OF TURKEY AFTER 2018
No full textExamining Coal Rib Stability Using Mechanical Bolts: Experimental and Numerical Study
No full textIn the underground coal mines of US, mechanical bolts are employed alongside other bolt types to mitigate rib deformation and enhance the stability of coal ribs. The performance of mechanical bolts within coal ribs has received limited research attention to date. This paper presents an integrative approach that combines numerical modeling and experimental methods to propose a comprehensive methodology for supporting coal ribs using mechanical bolts. Standard pullout tests were conducted to establish the load-response behavior of mechanical rib bolts. Subsequently, these load-response characteristics were calibrated through numerical models and applied to larger-scale supported coal rib simulations. The coal rib models were compared and validated with a case study to pursue the studies with more realistic numerical models. The validated models serve as the foundation for the models employed in parametric studies. A support approach tailored to mechanical bolt applications was developed based on these comprehensive studies. The key findings of this paper are as follows: Mechanical bolts exhibit a trilinear force-displacement response with critical points providing crucial insights into their characteristics, such as stiffness and yield capacity of the bolt. Bolt length was found to be less influential than the number of bolts during the design of the mechanical bolts. The bolts' placement within the rib structure arose as another critical factor. Generally, stronger coal units do not necessitate additional support, whereas medium-strength and weaker coal require support in most scenarios. Specific support design approaches were proposed for various mining conditions, including coal strength, overburden depth, and mining height. The combined results of numerical simulations and experimental tests underscore the pivotal role of proper mechanical bolt application in ensuring stable coal rib conditions, with several noteworthy contributions setting this study apart
OPTIMAL PORTFOLIO ALLOCATION UNDER FRACTAL THEORY
No full textThe efficient market hypothesis (EMH) has been dominating the literature of finance for a long time. Meanwhile, the problematic assumptions and inappropriateness of EMH in explaining real-life financial markets have dictated the significance of developing new theories and approaches. On the other hand, the Fractal Market Hypothesis postulates that financial markets are structured as fractals, they exhibit statistical self-similarity, and long-term memory in their time series. The portfolio applications to this hypothesis are quite limited in the literature. In this study, a portfolio optimization approach based on Fractal Market Hypothesis is developed. This paper suggests a portfolio optimization method, the Mean-MFTWXDFA which is based on multifractal temporally weighted cross-correlation analysis. The suggested method is also compared with those of classical portfolio applications such as the Mean-Variance, Mean-Value at Risk, and Mean-Conditional Value at Risk methods. Applications of the fractal-based portfolio perform reasonably well into out-of-sample analyses of a portfolio including the cryptocurrency market and three diversifying assets: oil, clean energy, and equity, outperforming conventional ones
Uncoupled Damage Modeling in Flow Forming Processes: An Assessment of Failure Mechanisms
No full textHow Women and Men Should (Not) Be: Gender Rules and Their Alignment With Status Beliefs Across Nations
No full textGender rules, that is, prescriptive and proscriptive gender stereotypes, dictate how women and men should and should not be, and thereby perpetuate the gender hierarchy that privileges men over women. Across seven nations that span the continuum of gender equality, we investigated gender status norms by identifying the extent to which gender rules correspond with social status beliefs. As expected, in all investigated nations, participants (N = 4,327) believed that men should not show low-status traits reflecting weakness (e.g., weak, naive) but should show high-status traits reflecting agency (e.g., leadership ability, ambitious). Correlational analyses found that the more gender-equal a nation, the more men's agency prescriptions were aligned with high-status and their weakness proscriptions with low-status characteristics. Moreover, participants believed that women should not show high-status traits reflecting dominance (e.g., dominant, demanding) in the United States, Turkey, India, and Ghana-that is, in the relatively less gender-equal nations. Yet, no trait was proscribed for women in the relatively more gender-equal nations of Switzerland and Sweden. The status alignment of women's prescriptions and proscriptions did not relate to nations' achieved gender equality. We discuss how the alignment of men's gender rules with status beliefs represents a hidden barrier to achieving full gender equality