A Translational Approach to Modeling Unique Aspects of Germ Cell Development During Self-Organization of the Primate Embryo

The specification of germ cells during embryonic development is vital not only for the development of an organism, but quite literally for the survival and propagation of its entire species. Recent work has demonstrated that several aspects of human primordial germ cell (hPGC) development are specific to primates, necessitating model systems and in vivo validation that is also species specific. In this work, a synthesis of in vitro and in vivo techniques is used to investigate hPGC specification within a human embryonic stem cell model of a gastrulating embryo known as a gastruloid. An hPGC transcriptomic signature that indicates migratory potential via canonical and novel mechanisms is indicated, raising several potential candidates for further investigation into the under-studied migratory phase of germ cell development. We seek to generate validation assays of hPGC function in an embryonic context by investigating migratory potential in grafts to the chick embryo, and demonstrate that despite significant differences between chick and human routes of migration in vivo, human in vitro-derived PGCs are in fact able to demonstrate migratory behavior in the chick, following chick migratory patterns and demonstrating a specific homing towards the chick mesonephros and gonad. These experiments not only provide a functional validation for in vitro-derived hPGCs that is complementary to molecular and epigenetic analysis, but also hint at the elements of hPGC development that are conserved throughout evolution. The gastruloid system is then used for further investigation into the hPGC niche. The power of this model system relies upon self-organization due to endogenous signaling in response to an exogenous BMP4 initiating signal, in a manner analogous to that found in the human embryo. We harness this power, using single cell image quantification and genetic tools including CRISPR-Cas9 to probe further into the signaling environment of the hPGC niche in the gastruloid model. We elucidate the role of each leg of the BMP4 – WNT – ACTIVIN/NODAL signaling cascade in development of this niche, which determines gastrulation events, in hPGC specification. These experiments not only demonstrate how BMP4 acts independently in addition to this cascade to directly specify hPGCs, but also how all three pathways work in harmony to generate self-organization of hPGCs within their gastruloid niche. By probing further into the ontogeny of hPGC specification, we find that upregulation of BLIMP1 alone, a canonical regulator of PGCs, is sufficient to induce later markers of hPGC fate, and surprisingly is also sufficient to downregulate SOX2 (a marker of epiblast and early ectodermal fate) and upregulate SOX17, which has been previously placed upstream of BLIMP1. Finally, we propose the marmoset as a good model of primate reproduction and embryogenesis, in an attempt to describe a non-human primate (NHP) system for validation of hPGC characteristics observed in vitro. We systematically investigate marmoset embryonic development in vivo using serial, high temporal and spatial resolution ultrasound imaging. We describe the morphological characteristics of implantation, gastrulation, neurulation, and organogenesis, as well as the curious marmoset phenotype of an elongated peri-gastrulation window, incorporating slowed embryonic growth and rapid extraembryonic development. In doing so, we generate an annotated ultrasound atlas of marmoset embryogenesis, and train models to identify developmental stages and predict fertilization ages from a single frame. In addition, we suggest that the extended peri-gastrulation window in the marmoset will provide a unique opportunity to perform in utero genetic editing, lineage tracing, and even allogenic transplantation to complement in vitro studies of hPGC development. This body of work provides a synthesis of culture techniques, genetic and molecular tools, and imaging systems that will provide a foundation for the exploration of not only human PGC development, but also hopefully a generalizable roadmap for translation between in vitro and in vivo studies early primate development

EFFECT OF BREAKING WAVE SHAPE ON IMPACT LOAD ON A MONOPILE STRUCTURE

A numerical model is derived to investigate the effect of breaking wave shape on impact load on a monopile structure. The derived model combines potential flow model with a Navier-Stokes/VOF solution. The analysis indicates that the breaking wave impact on a monopile structure results in an extremely rapid increase of pressure to high amplitudes. The peak impact pressure occurs in the region below the overturning wave jet. The breaking wave impact leads to extremely high slamming forces. It is observed that the slamming coefficient corresponding to the peak impact force approaches 2π. The area directly affected by the impact force is much higher than the impact area considered in engineering practice. Moreover, the analysis shows that the vertical load distribution is far more realistic than a rectangular shape distribution commonly applied in engineering practice. The results also show that the parameters of the rectangular shape distribution applied in engineering practice are complex function of the breaking wave shape and cannot be uniquely defined beforehand. This is because the vertical load distribution strongly depends on breaking wave shape and it is difficult to uniquely approximate such a complex load distribution by a rectangle. The derived results are compared with experimental data from laboratory experiments on irregular breaking wave loads on a monopile structure. Numerical results are in reasonable agreement with experimental data

Simulation of wave propagation in remote bonded FBG sensors using the spectral element method

Ultrasonic guided waves (GW) due to their ability to monitor large areas with few sensors, are commonly employed for structural health monitoring (SHM) in aerospace, civil, and mechanical industries. The FBG sensors in the edge filtering setup are re-emerging as a favored technique for GW sensing. The FBG sensors offer embeddability, ability to be multiplexed, small size, and immunity to electric and magnetic fields. To enhance the sensitivity of these sensors, these sensors are deployed in the so-called remote bonding configuration where the optical fiber is bonded to the structure while the FBG sensor is free. This configuration not only enhances the sensitivity but also opens up possibility of self-referencing. In this setup the GW in the structure is coupled to the fiber and converted into fiber modes. These modes propagate along the fiber and then are sensed at the FBG. The conversion of the plate modes to fiber modes is a phenomenon which is still being studied. The effect of the adhesive layer and the material properties of the adhesive on the coupling are still not known. Furthermore the directional nature of this coupling and its marked difference from the directly bonded configuration needs to be studied in detail. For this detailed study a computationally efficient model which captures the physics of the coupling is necessary. Hence, in this research we develop a numerical model based on the spectral element method (SEM) for the modeling of the remote bonded configuration of the FBG. The model comprises four meters long optical fiber bonded to the center of the plate by the adhesive layer and the piezoelectric disc (PZT) used for wave excitation. The ability of the SEM model to capture the effect of the adhesive and the remote bonding as well as the directional nature of the coupling has been studied in this paper. The model is validated with analytical and experimental results. It has been shown that the SEM model captures the physics of the coupling and is computationally more efficient than other methods using conventional finite element software

Vibration-based damage growth monitoring in beam-like structures

Damage growth monitoring plays an important role in providing early warning of structural failure. The existing methods for damage growth monitoring are mainly local inspection methods, such as acoustic emission. These methods need a priori knowledge of accessible damage vicinity, which may not be realized in practice. Hence, vibration-based global approach is adopted to overcome these difficulties. Natural frequency, as a global modal parameter, can be measured easily and is used for vibration-based damage growth monitoring in this study. A concept of damage-induced relative natural frequency change (RNFC) curve is defined first and its relation with mode shape is then derived analytically, giving a good way to approximate RNFC curves. For monitoring damage growth, a damage growth indicator is proposed based on RNFCs between two damaged stages of a beam. The effectiveness of the indicator for damage growth monitoring is proved by both numerical and experimental cases in beam-like structures

Multi step structural health monitoring approaches in debonding assessment in a sandwich honeycomb composite structure using ultrasonic guided waves

This paper aims to investigate the use of ultrasonic guided wave (GW) propagation mechanism and the assessment of debonding in a sandwich composite structure (SCS) using a multi-step approach. Towards this, a series of GW propagation-based laboratory experiments and numerical simulations have been carried out on the SCS sample. The debonding regions of variable size and locations were assessed using a pre-defined network of piezoelectric lead zirconate transducers (PZT). Besides, several artificial masses were also placed in the SCS to validate the multi-step structural health monitoring (SHM) strategy. The SHM approach uses a proposed quick damage identification matrix maps and an improved elliptical wave processing (EWP) strategy of the registered GW signals to detect the locations of debonding and other damages in the SCS. The benefit of the proposed damage identification map is to locate the damaged area (sectors) quickly. This identification step is followed by applying the damage localization step using the improved EWP only on the previously identified damage sector region. The proposed EWP has shown the potential to effectively locate the hidden multiple debonding regions and damages in the SCS with a reduced number of calculations using a step-wise approach that uses only a selected number of grid points. The paper shows the effectiveness of the proposed approach based on data gathered from numerical simulations and experimental studies. Thus, using the above-mentioned SHM strategy debondings and damages present within and outside the sensor network are localized. The results were cross verified with nondestructive testing (NDT) methods such as infrared thermography and laser Doppler vibrometry

A global-local damage localization and quantification approach in composite structures using ultrasonic guided waves and active infrared thermography

The paper emphasizes an effective quantification of hidden damage in composite structures using ultrasonic guided wave (GW) propagation-based structural health monitoring (SHM) and an artificial neural network (ANN) based active infrared thermography (IRT) analysis. In recent years, there has been increased interest in using a global-local approach for damage localization purposes. The global approach is mainly used in identifying the damage, while the local approach is quantifying. This paper presents a proof-of-study to use such a global-local approach in damage localization and quantification. The main novelties in this paper are the implementation of an improved SHM GW algorithm to localize the damages, a new pixel-based confusion matrix to quantify the size of the damage threshold, and a newly developed IRT-ANN algorithm to validate the damage quantification. From the SHM methodology, it is realized that only three sensors are sufficient to localize the damage, and an ANN- IRT imaging algorithm with only five hidden neurons in quantifying the damage. The robust SHM methods effectively identified, localized, and quantified the different damage dimensions against the non-destructive testing-IRT method in different composite structures

DEEP LEARNING BASED SURROGATE MODELLING OF WAVE PROPAGATION AND DAMAGE DETECTION IN CRACKED ROD

Guided wave-based Structural Health Monitoring (SHM) tools utilize the guided wave responses to interrogate damage in structures. This research demonstrates the use of various objective functions in single (mono) objective and multi-objective genetic algorithms for damage identification in isotropic 1D structures. The time domain spectral element method and a deep-learning-based surrogate is utilized for simulating wave propagation in an isotropic cracked rod. The genetic algorithms employ results ('numerical experiment') obtained from the spectral element model and the deep-learning-based surrogate to determine the optimized crack locations and crack depths as output parameters. The obtained optimized parameters from genetic algorithms are compared in terms of errors for various objective functions

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Kalman Filter Based Load Monitoring in Beam Like Structures Using Fibre-Optic Strain Sensors

The paper presents a proof of concept of a new methodology for the load estimation in beam-like structures under complex loading. The paper customizes a Kalman Filter (KF) based estimation technique which is shown to be robust to the presence of measurement noise as well as the changing condition of the beam for estimation of loads in beam-like structures. The methodology was validated using numerical as well as experimental data. The initial studies indicate that the proposed methodology has promise for applications where monitoring and classification of the strains is necessary, such as those in continuous welded rails