Failure Propagation Modeling and Analysis Via System Interfaces

Safety-critical systems must be shown to be acceptably safe to deploy and use in their operational environment. One of the key concerns of developing safety-critical systems is to understand the system behaves in the presence of failures, regardless of whether that failure is triggered by the external envi- ronment, or caused by internal errors. Safety assessment at the early stages of system development involves analysis of potential failures and their conse- quences. Increasingly, for complex systems, model-based safety assessment is becoming more widely used. In this paper we propose an approach for safety analysis based on system interface models. By extending interaction models on the system interface level with failure modes as well as relevant portions of the physical system to be controlled, automated support could be provided for much of the failure analysis. We focus on fault modeling and on how to compute minimal cut sets. Particularly, we explore state space reconstruction strategy and bounded searching technique to reduce the number of states that need to be analyzed, which remarkably improves the efficiency of cut sets searching algorithm

A Non-Intrusive Pressure Sensor by Detecting Multiple Longitudinal Waves

Pressure vessels are widely used in industrial fields, and some of them are safety-critical components in the system - for example, those which contain flammable or explosive material. Therefore, the pressure of these vessels becomes one of the critical measurements for operational management. In the paper, we introduce a new approach to the design of non-intrusive pressure sensors, based on ultrasonic waves. The model of this sensor is built based upon the travel-time change of the critically refracted longitudinal wave (LCR wave) and the reflected longitudinal waves with the pressure. To evaluate the model, experiments are carried out to compare the proposed model with other existing models. The results show that the proposed model can improve the accuracy compared to models based on a single wave

Semisupervised hypergraph discriminant learning for dimensionality reduction of hyperspectral image.

Semisupervised learning is an effective technique to represent the intrinsic features of a hyperspectral image (HSI), which can reduce the cost to obtain the labeled information of samples. However, traditional semisupervised learning methods fail to consider multiple properties of an HSI, which has restricted the discriminant performance of feature representation. In this article, we introduce the hypergraph into semisupervised learning to reveal the complex multistructures of an HSI, and construct a semisupervised discriminant hypergraph learning (SSDHL) method by designing an intraclass hypergraph and an interclass graph with the labeled samples. SSDHL constructs an unsupervised hypergraph with the unlabeled samples. In addition, a total scatter matrix is used to measure the distribution of the labeled and unlabeled samples. Then, a low-dimensional projection function is constructed to compact the properties of the intraclass hypergraph and the unsupervised hypergraph, and simultaneously separate the characteristics of the interclass graph and the total scatter matrix. Finally, according to the objective function, we can obtain the projection matrix and the low-dimensional features. Experiments on three HSI data sets (Botswana, KSC, and PaviaU) show that the proposed method can achieve better classification results compared with a few state-of-the-art methods. The result indicates that SSDHL can simultaneously utilize the labeled and unlabeled samples to represent the homogeneous properties and restrain the heterogeneous characteristics of an HSI

ChatGPT is a Potential Zero-Shot Dependency Parser

Pre-trained language models have been widely used in dependency parsing task and have achieved significant improvements in parser performance. However, it remains an understudied question whether pre-trained language models can spontaneously exhibit the ability of dependency parsing without introducing additional parser structure in the zero-shot scenario. In this paper, we propose to explore the dependency parsing ability of large language models such as ChatGPT and conduct linguistic analysis. The experimental results demonstrate that ChatGPT is a potential zero-shot dependency parser, and the linguistic analysis also shows some unique preferences in parsing outputs.Comment: 10 page

Pressure measurement based on multi-waves fusion algorithm

Measuring the pressure of a pressure vessel accurately is one of fundamental requirements of the operation of many complex engineering systems. Ultrasonic technique has been proposed to be a good alteration of non-intrusive measurement. Based on the study of acoustoelastic effect and thin-shell theory, it has been identified that the travel-time changes of the critically refracted longitudinal wave (LCR wave) and other reflected longitudinal waves are all proportional to the inner pressure. Considering the information redundancy in these waves, we proposed an approach for pressure measurement by using the information fusion algorithm on multiple reflected longitudinal waves. In the paper, we discussed the fusion algorithm in details and proposed a pressure measurement model, which represents an accurate relationship between the pressure and the travel-time changes of multiple waves. Through the experiment, the analysis of data collected from experiment system showed that the pressure measurement based on the multi-wave model is notably more accurate than the one based on the single-wave model (the average relative error (ARE) can be less than 7.24% and the root-mean-square error (RMSE) can be lower than 0.3MPa)

Durable superhydrophobic polyvinylidene fluoride membranes via facile spray-coating for effective membrane distillation

Membrane wetting and fouling substantially limits application and deployment of membrane distillation process. Designing high-performance superhydrophobic membranes offers an effective solution to solve the challenge. In this work, a highly durable superhydrophobic surface (water contact angle of 170.8 ± 1.3°) was constructed via a facile and rapid spray-coating of extremely hydrophobic SiO2 nanoparticles onto a porous polyvinylidene fluoride (PVDF) substrate for membrane distillation. The superhydrophobic membrane coated by fluorinated SiO2 nanoparticles exhibited a superior physicochemical stability in a wide range of extreme environments (i.e., NaOH, HCl, hot water, rust water, humic acid solution, ultrasonication, and high-speed water scouring). During 8-h continuous membrane distillation desalination experiment, the coated superhydrophobic membrane experienced a consistently stable water vapor flux (ca. 19.1 kg·m−2·h−1) and desalination efficiency (99.99 %). Additionally, such a stable superhydrophobicity endowed the spray-coated PVDF membrane to overcome membrane wetting and fouling during membrane distillation of highly saline solutions containing foulants (i.e., humic acid and rust). Results reported in this study provides a useful concept and strategy in facile construction of robust superhydrophobic membranes via spray-coating for effective membrane distillation.</p

Attempted Depletion of Passenger Leukocytes by Irradiation in Pigs

Allograft/xenograft rejection is associated with “passenger leukocyte” migration from the organ into recipient lymph nodes. In Study 1, we attempted to deplete leukocytes from potential kidney “donor” pigs, using two regimens of total body irradiation. A dose of 700 cGy was administered, followed by either 800 cGy (“low-dose”) or 1,300 cGy (“high dose”) with the kidneys shielded. Neither regimen was entirely successful in depleting all leukocytes, although remaining T and 8 cell numbers were negligible. Study 2 was aimed at providing an indication of whether near-complete depletion of leukocytes had any major impact on kidney allograft survival. In non-immunosuppressed recipient pigs, survival of a kidney from a donor that received high-dose irradiation was compared with that of a kidney taken from a non-irradiated donor. Kidney graft survival was 9 and 7 days, respectively, suggesting that depletion had little impact on graft survival. The lack of effect may have been related to (i) inadequate depletion of passenger leukocytes, thus not preventing a direct T cell response, (ii) the presence of dead or dying leukocytes (antigens), thus not preventing an indirect T cell response, or (iii) constitutive expression of MHC class II and B7 molecules on the porcine vascular endothelium, activating recipient T cells

Achieving high-quality silver sintered joint for highly-reliable schottky barrier diodes via pressureless method

The fabrication of silver joints was done using the pressureless sintering technology to suit the demand of high-reliability schottky barrier diodes (SBD). Porosity of 10.6% and shear strength of 39.6 MPa were reached under the optimized parameters of 290°C sintering temperature and 40 min residence time. The sintered joint demonstrated good mechanical/thermal/electrical performance in the ultimate reliability assessment testing, including the temperature cycling test, second sintering test, steady-state lifetime test, and intermittent lifetime test. This study demonstrated the viability of pressureless sintering of silver joints with good high-temperature reliability, which has significant application potential for aeronautical high-reliability power electronics

COVID-19 Epidemic Peer Support and Crisis Intervention Via Social Media

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.This article describes a peer support project developed and carried out by a group of experienced mental health professionals, organized to offer peer psychological support from overseas to healthcare professionals on the frontline of the COVID-19 outbreak in Wuhan, China. This pandemic extremely challenged the existing health care systems and caused severe mental distress to frontline healthcare workers. The authors describe the infrastructure of the team and a novel model of peer support and crisis intervention that utilized a popular social media application on smartphone. Such a model for intervention that can be used elsewhere in the face of current global pandemic, or future disaster response