Reliability analysis of multiplex control system of subsea blowout preventer based on stochastic Petri net

Višestruki (MUX − multiplex) upravljački sustav za sprečavanje podmorske erupcije bušotine (BOP − blowout preventer) ima bitnu ulogu u stvaranju sigurnih radnih uvjeta kod podmorskih aktivnosti bušenja. U skladu s radnim stanjima i kritičnim načinima kvara višestrukog upravljačkog sustava, u radu se predstavlja njegov stohastički model Petri mreža (SPN), uzimajući u obzir nesavršenu sposobnost otkrivanja greške. Predlaže se metoda numeričke analize temeljena na istolikom (izomorfnom) trajnom Markovljevom lancu modela. Istraživani su i uspoređivani pokazatelji pouzdanosti, odnosno pouzdanost, raspoloživost i MTTF višestrukog (MUX) upravljačkog sustava i probnog hidrauličkog upravljačkog sustava. Uz to, istraživani su učinci faktora prikrivenosti grešaka na vjerojatnosti stanja i dostupnost MUX upravljačkog sustava, a izvršena je i analiza nesigurnosti brzina paljenja u odnosu na MTTF.The multiplex (MUX) control system of subsea blowout preventer (BOP) plays a vital role in providing safe working conditions for the subsea drilling activities. According to the working states and critical failure modes of the MUX control system, this paper presents its stochastic Petri nets (SPN) model, taking into account the imperfect fault detection capacity. The numerical analysis method is proposed based on the isomorphic continuous-time Markov chain of the model. The reliability indexes, namely reliability, availability and MTTF of the MUX control system and pilot hydraulic control system are obtained and compared. In addition, the effects of fault coverage factor on state probabilities and availability of the MUX control system are researched and the uncertainty analysis of the firing rates related to MTTF is also performed

Glomerular capillary C3 deposition as a risk factor for unfavorable renal outcome in pediatric primary focal segmental glomerular sclerosis

IntroductionSome patients with primary focal segmental sclerosis (FSGS) demonstrate complement 3 (C3) deposition in glomerular capillary loops (Cap-C3) and/or mesangial area (Mes-C3). The clinicopathological and prognostic significance of C3 deposition remains incompletely investigated, especially in the pediatric cohort.MethodsWe retrospectively analyzed 264 children of biopsy-proven primary FSGS between January 2003 and December 2020. The correlation between Cap-C3 and renal outcome was evaluated by the Kaplan-Meier method and Cox multivariate regression analysis. Renal end-point event was defined as the development of end-stage renal disease, death for renal disease, or an estimated glomerular filtration rate reduction by at least 50% from baseline.ResultsAmong the 264 patients, 30 (11.4%) had Cap-C3. Kaplan-Meier analysis showed that patients with Cap-C3 had significantly lower renal survival rates than patients without Cap-C3 (60.17% vs. 84.71% at 5 years, 39.49% vs. 65.55% at 10 years, P < 0.01). Cox multivariate regression analysis showed that Cap-C3 was an independent risk factor for poor renal outcome (HR 3.53, 95% CI 1.22–10.19, P = 0.02).ConclusionGlomerular capillary C3 deposition was an independent risk factor for unfavorable renal outcome in children with primary FSGS

Decision-Feedback Multiuser Detection in Multicell Multicarrier DS-CDMA Systems with/without BS Cooperation

Abstract—In this contribution, we investigate the signal detection in the multicarrier direct-sequence code-division multiple-access (DS-CDMA) systems employing both time (T)-domain and frequency (F)-domain spreading, which are referred to as the TF/MC DS-CDMA systems. A multicell scenario with universal frequency reuse is considered, where signals experience frequency-selective Rayleigh fading. A decision-feedback multiuser detector (MUD), which represents the extension of a so-called receiver multiuser diversity aided multi-stage minimum mean-square error MUD (RMD/MS-MMSE MUD), is employed to cope with both the intracell multiuser interference (MUI) and intercell interference (ICI), when base-station (BS) cooperation is or is not assumed. Furthermore, when BS cooperation is assumed, symbols detected at different BSs are interchangedand combined to enhance the detection performance. Our studies and performance results demonstrate that the RMD/MS-MMSE MUD constitutes one of the promising multicell processing (MCP) schemes, making it possible for each cell to support heavily overloaded users, even when a frequency-reuse factor one is applied

When selection pays: Structured public goods game with a generalized interaction mode

The public goods game is a broadly used paradigm for studying the evolution of cooperation in structured populations. According to the basic assumption, the interaction graph determines the connections of a player where the focal actor forms a common venture with the nearest neighbors. In reality, however, not all of our partners are involved in every game. To elaborate this observation, we propose a model where individuals choose just some selected neighbors from the complete set to form a group for public goods. We explore the potential consequences by using a pair-approximation approach in a weak selection limit. We theoretically analyze how the number of total neighbors and the actual size of the restricted group influence the critical enhancement factor where cooperation becomes dominant over defection. Furthermore, we systematically compare our model with the traditional setup and show that the critical enhancement factor is lower than in the case when all players are present in the social dilemma. Hence, the suggested restricted interaction mode offers a better condition for the evolution of cooperation. Our theoretical findings are supported by numerical calculations

A novel bionic gripper based on the front tarsi of scutigers

Based on the biological structure of scutigers’ front tarsi, a novel bionic gripper with bristles was designed, and its simulation model was established. It was verified that proposed bionic gripper not only achieved the expected gripping action, but also completed pinching motion, with better grasping performance. The related parameters such as displacement, velocity, acceleration, force and torque were also analyzed. The friction contact finite element analysis on the gripper bionic with bristles structure was performed by ABAQUS, and compared with the control group. The finite element results displayed that bristles could effectively improve the capture efficiency of bionic grippers. The diameter and bristle density of bristles in bionic grippers were optimized and analyzed their influences on the gripping efficiency. This work provided a reference for the structural design of bionic gripper and the practical application of bionic non-smooth surfaceThe accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Design of Bionic Buffering and Vibration Reduction Foot for Legged Robots

When legged robots walk on rugged roads, they would suffer from strong impact from the ground. The impact would cause the legged robots to vibrate, which would affect their normal operation. Therefore, it is necessary to take measures to absorb impact energy and reduce vibration. As an important part of a goat’s foot, the hoof capsule can effectively buffer the impact from the ground in the goat’s running and jumping. The structure of the hoof capsules and its principle of buffering and vibration reduction were studied. Inspired by the unique shape and internal structure of the hoof capsules, a bionic foot was designed. Experimental results displayed that the bionic foot could effectively use friction to consume impact energy and ensured the stability of legged robot walking. In addition, the bionic foot had a lower natural vibration frequency, which was beneficial to a wide range of vibration reduction. This work brings a new solution to the legged robot to deal with the ground impact, which helps it adapt to a variety of complex terrain

Prediction of knee joint pain in Tai Chi practitioners: a cross-sectional machine learning approach

Objective To build a supervised machine learning-based classifier, which can accurately predict whether Tai Chi practitioners may experience knee pain after years of exercise.Design A prospective approach was used. Data were collected using face-to-face through a self-designed questionnaire.Setting Single centre in Shanghai, China.Participants A total of 1750 Tai Chi practitioners with a course of Tai Chi exercise over 5 years were randomly selected.Measures All participants were measured by a questionnaire survey including personal information, Tai Chi exercise pattern and Irrgang Knee Outcome Survey Activities of Daily Living Scale. The validity of the questionnaire was analysed by logical analysis and test, and the reliability of this questionnaire was mainly tested by a re-test method. Dataset 1 was established by whether the participant had knee pain, and dataset 2 by whether the participant’s knee pain affected daily living function. Then both datasets were randomly assigned to a training and validating dataset and a test dataset in a ratio of 7:3. Six machine learning algorithms were selected and trained by our dataset. The area under the receiver operating characteristic curve was used to evaluate the performance of the trained models, which determined the best prediction model.Results A total of 1703 practitioners completed the questionnaire and 47 were eliminated for lack of information. The total reliability of the scale is 0.94 and the KMO (Kaiser-Meyer-Olkin measure of sampling adequacy) value of the scale validity was 0.949 (>0.7). The CatBoost algorithm-based machine-learning model achieved the best predictive performance in distinguishing practitioners with different degrees of knee pain after Tai Chi practice. ‘Having knee pain before Tai Chi practice’, ‘knee joint warm-up’ and ‘duration of each exercise’ are the top three factors associated with pain after Tai Chi exercise in the model. ‘Having knee pain before Tai Chi practice’, ‘Having Instructor’ and ‘Duration of each exercise’ were most relevant to whether pain interfered with daily life in the model.Conclusion CatBoost-based machine learning classifier accurately predicts knee pain symptoms after practicing Tai Chi. This study provides an essential reference for practicing Tai Chi scientifically to avoid knee pain