Transient Two-Phase Flow in Porous Media: A Literature Review and Engineering Application in Geotechnics

This work reviews the transient two-phase flow in porous media with engineering applications in Geotechnics. It initially overviews constitutive relationships, conventional theories, and experiments. Then, corresponding limitations are discussed according to conflicting observations and multiphase interfacial dynamics. Based on those findings, the dynamic nonequilibrium effects were so defined, which could also be abbreviated as dynamic/transient effects. Four advanced theories have already been developed to resolve these effects. This review collects them and discusses their pros and cons. In addition, this work further reviews the state-of-art in terms of experimental methods, influential factors in dynamic/transient effects, and modelling performance, as well as micromodel and numerical methods at pore-scale. Last, the corresponding geotechnical applications are reviewed, discussing their applicability in effective stress, shear strength, and deformation. Finally, the entire review is briefed to identify research gaps in Geotechnics.

Evaluation of CRISPR gene-editing tools in zebrafish

Background Zebrafish have practical features that make them a useful model for higher-throughput tests of gene function using CRISPR/Cas9 editing to create ‘knockout’ models. In particular, the use of G0 mosaic mutants has potential to increase throughput of functional studies significantly but may suffer from transient effects of introducing Cas9 via microinjection. Further, a large number of computational and empirical tools exist to design CRISPR assays but often produce varied predictions across methods leaving uncertainty in choosing an optimal approach for zebrafish studies. Methods To systematically assess accuracy of tool predictions of on- and off-target gene editing, we subjected zebrafish embryos to CRISPR/Cas9 with 50 different guide RNAs (gRNAs) targeting 14 genes. We also investigate potential confounders of G0-based CRISPR screens by assaying control embryos for spurious mutations and altered gene expression. Results We compared our experimental in vivo editing efficiencies in mosaic G0 embryos with those predicted by eight commonly used gRNA design tools and found large discrepancies between methods. Assessing off-target mutations (predicted in silico and in vitro) found that the majority of tested loci had low in vivo frequencies (< 1%). To characterize if commonly used ‘mock’ CRISPR controls (larvae injected with Cas9 enzyme or mRNA with no gRNA) exhibited spurious molecular features that might exacerbate studies of G0 mosaic CRISPR knockout fish, we generated an RNA-seq dataset of various control larvae at 5 days post fertilization. While we found no evidence of spontaneous somatic mutations of injected larvae, we did identify several hundred differentially-expressed genes with high variability between injection types. Network analyses of shared differentially-expressed genes in the ‘mock’ injected larvae implicated a number of key regulators of common metabolic pathways, and gene-ontology analysis revealed connections with response to wounding and cytoskeleton organization, highlighting a potentially lasting effect from the microinjection process that requires further investigation. Conclusion Overall, our results provide a valuable resource for the zebrafish community for the design and execution of CRISPR/Cas9 experiments.

Application of ASAS method to PAMELA calorimeter

In this paper, we propose a method that makes it possible to to improve energy reconstruction for data obtained via thin heterogeneous calorimeters for direct measurements of cosmic rays with energies of TeV and higher. Despite the large number of modern experimental complexes, the primary energy of cosmic nuclei with energies above 1 TeV is determined with large errors associated with fluctuations in the development of the cascade. For heterogeneous calorimeters, transient effects give an additional negative effect. In this paper we analyze the main causes of fluctuations and discuss a method for reducing the effect of fluctuations on the results of primary energy reconstruction. The method of accumulation of signal along the spectrum (ASAS) is used to reduce fluctuations associated with transient effects. The method was tested using the heterogeneous calorimeter of the PAMELA collaboration. It is shown that the proposed approach makes it possible to correctly determine the energy of slowly developing showers, the maxima of which are not measured.

Blocking of inflammatory heparan sulfate domains by specific antibodies is not protective in experimental glomerulonephritis

Glomerulonephritis is an acquired serious glomerular disease, which involves the interplay of many factors such as cytokines, chemokines, inflammatory cells, and heparan sulfate (HS). We previously showed that blocking of inflammatory heparan sulfate domains on cultured glomerular endothelium by specific anti-HS single chain antibodies reduced polymorphonuclear cell (PMN) adhesion and chemokine binding. We hypothesized that injection of anti-HS antibodies in PMN-driven experimental glomerulonephritis should reduce glomerular influx of PMNs and thereby lead to a better renal outcome. In contrast to our hypothesis, co-injection of anti-HS antibodies did not alter the final outcome of anti-glomerular basement membrane (anti-GBM)-induced glomerulonephritis. Glomerular PMN influx, normally peaking 2 hours after induction of glomerulonephritis with anti-GBM IgG was not reduced by co-injection of anti-HS antibodies. Four days after induction of glomerulonephritis, albuminuria, renal function, glomerular hyalinosis and fibrin deposition were similar in mice treated and not treated with anti-HS antibodies. Interestingly, we observed transient effects in mice co-injected with anti-HS antibodies compared to mice that did not receive anti-HS antibodies: (i) a decreased renal function 2 hours and 1 day after induction of glomerulonephritis; (ii) an increased albuminuria after 2 hours and 1 day; (iii) an increased glomerular fibrin deposition after 1 day; (iv) a reduced glomerular macrophage influx after 1 day; (v) a sustained glomerular presence of PMNs at day 1 and 4, accompanied by an increased renal expression of IL-6, CXCL1, ICAM-1, L-selectin, CD11b and NF-κB. The mechanism underlying these observations induced by anti-HS antibodies remains unclear, but may be explained by a temporarily altered glycocalyx and/or altered function of PMNs due to the binding of anti-HS antibodies. Nevertheless, the evaluated anti-HS antibodies do not show therapeutic potential in anti-GBM-induced glomerulonephritis. Future research should evaluate other strategies to target HS domains involved in inflammatory processes during glomerulonephritis.

Transient evolution of basal drag during glacier slip

Glacier slip is usually described using steady-state sliding laws that relate drag, slip velocity and effective pressure, but where subglacial conditions vary rapidly transient effects may influence slip dynamics. Here we use results from a set of laboratory experiments to examine the transient response of glacier slip over a hard bed to velocity perturbations. The drag and cavity evolution from lab experiments are used to parameterize a rate-and-state drag model that is applied to observations of surface velocity and ice-bed separation from the Greenland ice sheet. The drag model successfully predicts observed lags between changes in ice-bed separation and sliding speed. These lags result from the time (or displacement) required for cavities to evolve from one steady-state condition to another. In comparing drag estimates resulting from applying rate-and-state and steady-state slip laws to transient data, we find the peaks in drag are out of phase. This suggests that in locations where subglacial conditions vary on timescales shorter than those needed for cavity adjustment transient slip processes control basal drag.

THE TRANSIENT EFFECTS OF FLOOD WATER ON A WARSHIP IN CALM WATER IMMEDIATELY FOLLOWING DAMAGE

The safety of a ship which is damaged below the waterline will depend on the way water floods into the internal compartments. The water will cause the ship to take on an angle of heel and trim which will further affect the flooding into the compartments. The ship’s equilibrium position in calm water can be predicted using hydrostatic theory, however at present it is difficult to predict the transient behaviour between the initial upright position of the ship and its final equilibrium. In some cases, the transient motion may cause a capsize prior to a possible equilibrium position being reached. This paper describes an investigation of this phenomenon using a model of a warship with simplified, typical internal geometry. With the model initially stationary, a rapid damage event was generated, and the global motions measured, along with the water levels in some of the internal compartments, as functions of time. Immediately after the damage occurred the model rolled to starboard (towards the damage). It then rolled to port (away from the damage) before eventually returning to starboard and settling at its equilibrium value. In all the tests conducted the equilibrium heel angle was less than that reached during the initial roll to starboard. This implies that the roll damping, and the way in which the water floods into the model immediately following the damage, could both have a very important influence on the likelihood of survival.

Transient Hyperglycemia and Hypoxia Induce Memory Effects in AngiomiR Expression Profiles of Feto-Placental Endothelial Cells

Gestational diabetes (GDM) and preeclampsia (PE) are associated with fetal hyperglycemia, fetal hypoxia, or both. These adverse conditions may compromise fetal and placental endothelial cells. In fact, GDM and PE affect feto-placental endothelial function and also program endothelial function and cardiovascular disease risk of the offspring in the long-term. MicroRNAs are short, non-coding RNAs that regulate protein translation and fine tune biological processes. A group of microRNAs termed angiomiRs is particularly involved in the regulation of endothelial function. We hypothesized that transient hyperglycemia and hypoxia may alter angiomiR expression in feto-placental endothelial cells (fpEC). Thus, we isolated primary fpEC after normal, uncomplicated pregnancy, and induced hyperglycemia (25 mM) and hypoxia (6.5%) for 72 h, followed by reversal to normal conditions for another 72 h. Current vs. transient effects on angiomiR profiles were analyzed by RT-qPCR and subjected to miRNA pathway analyses using DIANA miRPath, MIENTURNET and miRPathDB. Both current and transient hypoxia affected angiomiR profile stronger than current and transient hyperglycemia. Both stimuli altered more angiomiRs transiently, i.e., followed by 72 h culture at control conditions. Pathway analysis revealed that hypoxia significantly altered the pathway ‘Proteoglycans in cancer’. Transient hypoxia specifically affected miRNAs related to ‘adherens junction’. Our data reveal that hyperglycemia and hypoxia induce memory effects on angiomiR expression in fpEC. Such memory effects may contribute to long-term adaption and maladaption to hyperglycemia and hypoxia.

Managing and Utilizing Big Data in Atmospheric Monitoring Systems for Underground Coal Mines

Underground coal mining Atmospheric Monitoring Systems (AMS) have been implemented for real-time or near real-time monitoring and evaluation of the mine atmosphere and related parameters such as gas concentration (e.g., CH4, CO, O2), fan performance (e.g., power, speed), barometric pressure, ambient temperature, humidity, etc. Depending on the sampling frequency, AMS can collect and manage a tremendous amount of data, which mine operators typically consult for everyday operations as well as long-term planning and more effective management of ventilation systems. The raw data collected by AMS need considerable pre-processing and filtering before they can be used for analysis. This paper discusses different challenges related to filtering raw AMS data in order to identify and remove values due to sensor breakdowns, sensor calibration periods, transient values due to operational considerations, etc., as well as to homogenize time series for different variables. The statistical challenges involve the removal of faulty values and outliers (due to systematic problems) and transient effects, gap-filling (by means of interpolation methods), and homogenization (setting a common time reference and time step) of the respective time series. The objective is to derive representative and synchronous time series values that can subsequently be used to estimate summary statistics of AMS and to infer correlations or nonlinear dependence between different data streams. Identification and modeling of statistical dependencies can be further exploited to develop predictive equations based on time series models.

Machine Learning in Computer Vision Software for Geomechanics Modeling

AI-GEM (Artificial Intelligence of Geomechanics Earth Modelling) tool aims to detect the geomechanical features, especially the elastic parameters and stresses. Characterizing the wellbore instability issues is one of the factors increases cost of drilling and creating an AI-based tool will enhance and present a real-time solution for wellbore instability. These features are usually interpreted manually, depending on the experience and usually impacted by inconsistencies due to biased or unexperienced interpreters. Therefore, there is a need for a robust automatic or semiautomatic approach to reduce time, manual efficiency and consistency. The range of Geomechanics issues is wide and interfaces with many other upstream disciplines (e.g., Petrophysics, Geophysics, Production Geology, Drilling and Reservoir Engineering). Safe and effective field operation is built on the understanding and implementation of the subsurface in-situ stress state throughout the life of the field; the quantification of key subsurface uncertainties through well thought-out data gathering and characterization programs. The integration with appropriate Geomechanics modelling and the field surveillance /monitoring strategy. There are two major aspects that must be addressed during the design phase of any Geomechanics project. The first and most important is developing a realistic estimate of the expected mechanical behaviour of the rocks and its potential response as a result of drilling. The second is to design an economic, safe well and support method for the determined rocks behaviour. The design process begins with the feasibility study followed by preliminary design, the detail design, tender design and throughout the construction. The design is constantly updated during each phase as more information becomes available and this requires the involvement of Geologists, Engineers and Subject Matter Expert throughout the phases of a project. A central concern for all geomechanical designs is the well-rock interaction, which is not only includes the final state but also the transient effects of the well processes as well as time and stress of the dependent rock properties. The end-to-end workflow to achieve the mechanical earth model is automated, guided and orchestrated with the help of machine learning framework such as recommendation engine for offset well data, prediction of well logs, and optimization for all calibration with existing test results, enabling end users to run sensitivity and scenario analysis so on and so forth.