On the half-space or exterior problems of the 3D compressible elastic Navier-Stokes-Poisson equations

We study the three-dimensional compressible elastic Navier-Stokes-Poisson equations induced by a new bipolar viscoelastic model derived here, which model the motion of the compressible electrically conducting fluids. The various boundary conditions for the electrostatic potential including the Dirichlet and Neumann boundary conditions are considered. By using a unified energy method, we obtain the unique global $H^2$ solution near a constant equilibrium state in the half-space or exterior of an obstacle. The elasticity plays a crucial role in establishing the $L^2$ estimate for the electrostatic field.Comment: To appear in SIAM Journal on Mathematical Analysi

Dynamical magneto-rotational instability

Magneto-rotational instability (MRI) is an important instability mechanism for rotating flows with magnetic fields. In particular, when the strength of the magnetic field tends to zero, the stability criterion for rotating flows is generally different from the classical Rayleigh criterion for rotating flows without a magnetic field. MRI has wide applications in astrophysics, particularly to the turbulence and enhanced angular momentum transport in accretion disks. For the case of vertical magnetic fields, we give rigorous proof of linear MRI and a complete description of the spectra and semigroup growth of the linearized operator. Moreover, we prove nonlinear stability and instability from the sharp linear stability/instability criteria

Techno-invasion and job satisfaction in China: The roles of boundary preference for segmentation and marital status

BACKGROUND: While the intensive work-related use of information and communication technologies after working hours have led to increased techno-invasion, much less is known regarding whether and for whom techno-invasion influences job satisfaction. OBJECTIVE: Drawing on the conservation of resources theory and person-environment fit theory, this study examined the relationship between techno-invasion and decreased job satisfaction. Specific attention was paid to the moderating effect of boundary preference for segmentation and its joint influence with marital status on this relationship. METHODS: Questionnaire data were collected by an online survey of a nationwide and diverse sample of 472 employees from China. Data were analyzed using descriptive statistics, confirmatory factor analysis and hierarchical regression analysis. RESULTS: We found that techno-invasion negatively correlated with job satisfaction, which was strengthened by boundary preference for segmentation. Furthermore, the results of a three-way interaction effect suggested that the moderating role of boundary preference for segmentation on the relationship between techno-invasion and job satisfaction is stronger for unmarried employees than it is for married ones. CONCLUSIONS: The effect of techno-invasion on employees’ job satisfaction can be strengthened or weakened by their boundary preference for segmentation and marital status

MMOTU: A Multi-Modality Ovarian Tumor Ultrasound Image Dataset for Unsupervised Cross-Domain Semantic Segmentation

Ovarian cancer is one of the most harmful gynecological diseases. Detecting ovarian tumors in early stage with computer-aided techniques can efficiently decrease the mortality rate. With the improvement of medical treatment standard, ultrasound images are widely applied in clinical treatment. However, recent notable methods mainly focus on single-modality ultrasound ovarian tumor segmentation or recognition, which means there still lacks researches on exploring the representation capability of multi-modality ultrasound ovarian tumor images. To solve this problem, we propose a Multi-Modality Ovarian Tumor Ultrasound (MMOTU) image dataset containing 1469 2d ultrasound images and 170 contrast enhanced ultrasonography (CEUS) images with pixel-wise and global-wise annotations. Based on MMOTU, we mainly focus on unsupervised cross-domain semantic segmentation task. To solve the domain shift problem, we propose a feature alignment based architecture named Dual-Scheme Domain-Selected Network (DS2Net). Specifically, we first design source-encoder and target-encoder to extract two-style features of source and target images. Then, we propose Domain-Distinct Selected Module (DDSM) and Domain-Universal Selected Module (DUSM) to extract the distinct and universal features in two styles (source-style or target-style). Finally, we fuse these two kinds of features and feed them into the source-decoder and target-decoder to generate final predictions. Extensive comparison experiments and analysis on MMOTU image dataset show that DS2Net can boost the segmentation performance for bidirectional cross-domain adaptation of 2d ultrasound images and CEUS images. Our proposed dataset and code are all available at https://github.com/cv516Buaa/MMOTU_DS2Net.Comment: code: https://github.com/cv516Buaa/MMOTU_DS2Net paper:18 pages, 12 figures, 11 tables, 16 formula

Strong Electronic Interaction of Amorphous Fe2O3 Nanosheets with Single‐Atom Pt toward Enhanced Carbon Monoxide Oxidation

Platinum‐based catalysts are critical to several chemical processes, but their efficiency is not satisfying enough in some cases, because only the surface active‐site atoms participate in the reaction. Henceforth, catalysts with single‐atom dispersions are highly desirable to maximize their mass efficiency, but fabricating these structures using a controllable method is still challenging. Most previous studies have focused on crystalline materials. However, amorphous materials may have enhanced performance due to their distorted and isotropic nature with numerous defects. Here reported is the facile synthesis of an atomically dispersed catalyst that consists of single Pt atoms and amorphous Fe2O3 nanosheets. Rational control can regulate the morphology from single atom clusters to sub‐nanoparticles. Density functional theory calculations show the synergistic effect resulted from the strong binding and stabilization of single Pt atoms with the strong metal‐support interaction between the in situ locally anchored Pt atoms and Fe2O3 lead to a weak CO adsorption. Moreover, the distorted amorphous Fe2O3 with O vacancies is beneficial for the activation of O2, which further facilitates CO oxidation on nearby Pt sites or interface sites between Pt and Fe2O3, resulting in the extremely high performance for CO oxidation of the atomic catalyst.An atomically Pt dispersed catalyst on amorphous Fe2O3 nanosheets is developed. The size effect of Pt and phase effect of support are explored. The synergistic effect results from the strong metal‐support interactions between the single Pt atoms and the amorphous Fe2O3 structure supports lead to an enhanced CO oxidation performance.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151833/1/adfm201904278-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151833/2/adfm201904278.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151833/3/adfm201904278_am.pd

SARS-CoV-2 spike-reactive naïve B cells and pre-existing memory B cells contribute to antibody responses in unexposed individuals after vaccination

IntroductionSince December 2019, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has presented considerable public health challenges. Multiple vaccines have been used to induce neutralizing antibodies (nAbs) and memory B-cell responses against the viral spike (S) glycoprotein, and many essential epitopes have been defined. Previous reports have identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-reactive naïve B cells and preexisting memory B cells in unexposed individuals. However, the role of these spike-reactive B cells in vaccine-induced immunity remains unknown.MethodsTo elucidate the characteristics of preexisting SARS-CoV-2 S-reactive B cells as well as their maturation after antigen encounter, we assessed the relationship of spike-reactive B cells before and after vaccination in unexposed human individuals. We further characterized the sequence identity, targeting domain, broad-spectrum binding activity and neutralizing activity of these SARS-CoV-2 S-reactive B cells by isolating monoclonal antibodies (mAbs) from these B cells.ResultsThe frequencies of both spike-reactive naïve B cells and preexisting memory B cells before vaccination correlated with the frequencies of spike-reactive memory B cells after vaccination. Isolated mAbs from spike-reactive naïve B cells before vaccination had fewer somatic hypermutations (SHMs) than mAbs isolated from spike-reactive memory B cells before and after vaccination, but bound SARS-CoV-2 spike in vitro. Intriguingly, these germline-like mAbs possessed broad binding profiles for SARS-CoV-2 and its variants, although with low or no neutralizing capacity. According to tracking of the evolution of IGHV4-4/IGKV3-20 lineage antibodies from a single donor, the lineage underwent SHMs and developed increased binding activity after vaccination.DiscussionOur findings suggest that spike-reactive naïve B cells can be expanded and matured by vaccination and cocontribute to vaccine-elicited antibody responses with preexisting memory B cells. Selectively and precisely targeting spike-reactive B cells by rational antigen design may provide a novel strategy for next-generation SARS-CoV-2 vaccine development

Performance analysis for subsea blind shear ram preventers subject to testing strategies

In a subsea blowout preventer system, a subsea blind shear ram preventer (BSRP) plays as a crucial safety barrier by cutting off the drill pipe and sealing the wellhead to prevent serious accidents. Testing and repairs of BSRPs are the main issues in operation and maintenance activities. It is important to assess BSRPs unavailability during proof and partial testing phases in order to ensure their safety functions. This paper presents a newly state-based approach for unavailability analysis by incorporating testing activities of BSRPs into multiphase Markov process. In the approach, states waiting for repair are taken into consideration. Analytical formulas for evaluation of time-dependent unavailability and average unavailability for BSRPs are developed. In addition, the non-periodic characteristics and effects of degradation are also taken into account in proof testing. The effects of testing errors and postponed repairs on the tendency of unavailability in partial testing phases are checked in the proposed models. Performance analyses for BSRPs configurations, scenarios and cases considered in the paper are carried out to demonstrate the application of the proposed models. Monte Carlo models for both proof and partial testing are developed and simulated. Different comparisons are performed for validation of the set of the derived formulations

A DBN-based risk assessment model for prediction and diagnosis of offshore drilling incidents

Drilling operations of offshore oil and gas fields are characterized by high technical complexity, high risks, and high costs, since they are always in harsh environments with complicated geological factors. Lost circulation or well “kick” is a typically hazardous event that may occur while drilling wells and it also may develop into a blowout accident without being well handled. It is necessary to identify and analyze the root causes of these events and their consequences, in order to prevent serious accidents from happening. In a drilling operation, the risk of blowout may change with time, depending on the operation stage, and such kind of dynamics should be captured in risk assessment. This paper presents an approach for determining the conditional probabilities of hazardous events and their consequences. The approach includes models that take into account the influence of degradation and (if applicable) new real-time information which represents the changing model parameters (such as state change of mud density). Such an approach is based on the Dynamic Bayesian Network (DBN) theory and then incorporates additional nodes to address the model uncertainties and parameter uncertainties. In addition, the effect of equipment degradation, which had been ignored in the existing researches, also is considered for modeling. Given that a hazardous event has occurred, this presented model can be used to predict the risk evolution, as well to reason its root causes during offshore drilling operation. A bowtie model is established to link the potential incident scenarios with the pressure regimes and formation load capacity, and then the model is translated into a DBN. DBN inference is adapted to perform prediction and diagnosis for dynamic risk assessment, and then a sensitivity analysis is carried out to find the relative importance of each root cause. A case study with focusing on lost circulation during three drilling scenarios is adapted to illustrate the feasibility of the proposed approach

Reliability modeling of subsea SISs partial testing subject to delayed restoration

Subsea oil and gas production has always involved the challenging task of determining the overall reliability of safeguarding systems, such as safety instrumented systems (SISs). Partial testing and delayed restoration of SISs are the main issues in operation and maintenance activities. This paper proposes a novel reliability-modeling methodology for subsea SISs subject to partial testing and delayed restoration. The proposed methodology incorporates an increasing failure rate in conjunction with dangerous undetected failures for the final elements. Approximation formulas for evaluating the average probability of failure on demand are derived for SISs in the low-demand operating mode. In addition, the effects of degradation are modeled by following Weibull rules in different subsequent partial testing intervals. In contrast to previous works, the present research accounts for delayed restoration after detecting failures and also considers the repair time for different scenarios. The proposed formulas are compared with the existing ones for partial verification. A case study on the shutdown valves of a subsea high-integrity pressure protection system is presented to illustrate the feasibility of the proposed methodology. It is also proven that the proposed approximation offers a robust opportunity for testing strategy optimization and performance improvement of SISs