Throughput capacity of two-hop relay MANETs under finite buffers

Since the seminal work of Grossglauser and Tse [1], the two-hop relay algorithm and its variants have been attractive for mobile ad hoc networks (MANETs) due to their simplicity and efficiency. However, most literature assumed an infinite buffer size for each node, which is obviously not applicable to a realistic MANET. In this paper, we focus on the exact throughput capacity study of two-hop relay MANETs under the practical finite relay buffer scenario. The arrival process and departure process of the relay queue are fully characterized, and an ergodic Markov chain-based framework is also provided. With this framework, we obtain the limiting distribution of the relay queue and derive the throughput capacity under any relay buffer size. Extensive simulation results are provided to validate our theoretical framework and explore the relationship among the throughput capacity, the relay buffer size and the number of nodes

Natural Response Generation for Chinese Reading Comprehension

Machine reading comprehension (MRC) is an important area of conversation agents and draws a lot of attention. However, there is a notable limitation to current MRC benchmarks: The labeled answers are mostly either spans extracted from the target corpus or the choices of the given candidates, ignoring the natural aspect of high-quality responses. As a result, MRC models trained on these datasets can not generate human-like responses in real QA scenarios. To this end, we construct a new dataset called Penguin to promote the research of MRC, providing a training and test bed for natural response generation to real scenarios. Concretely, Penguin consists of 200k training data with high-quality fluent, and well-informed responses. Penguin is the first benchmark towards natural response generation in Chinese MRC on a relatively large scale. To address the challenges in Penguin, we develop two strong baselines: end-to-end and two-stage frameworks. Following that, we further design Prompt-BART: fine-tuning the pre-trained generative language models with a mixture of prefix prompts in Penguin. Extensive experiments validated the effectiveness of this design.Comment: 15 page

Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension

The conversational machine reading comprehension (CMRC) task aims to answer questions in conversations, which has been a hot research topic in recent years because of its wide applications. However, existing CMRC benchmarks in which each conversation is assigned a static passage are inconsistent with real scenarios. Thus, model's comprehension ability towards real scenarios are hard to evaluate reasonably. To this end, we propose the first Chinese CMRC benchmark Orca and further provide zero-shot/few-shot settings to evaluate model's generalization ability towards diverse domains. We collect 831 hot-topic driven conversations with 4,742 turns in total. Each turn of a conversation is assigned with a response-related passage, aiming to evaluate model's comprehension ability more reasonably. The topics of conversations are collected from social media platform and cover 33 domains, trying to be consistent with real scenarios. Importantly, answers in Orca are all well-annotated natural responses rather than the specific spans or short phrase in previous datasets. Besides, we implement three strong baselines to tackle the challenge in Orca. The results indicate the great challenge of our CMRC benchmark. Our datatset and checkpoints are available at https://github.com/nuochenpku/Orca.Comment: 14 page

Association between extremely high-density lipoprotein cholesterol and adverse cardiovascular outcomes: a systematic review and meta-analysis

BackgroundThe association between high-density lipoprotein cholesterol (HDL-C) and adverse cardiovascular outcomes is understudied. Based on cohort studies, the current study aimed to investigate the association of extremely high HDL-C with all-cause, atherosclerotic cardiovascular disease (CVD) mortality, and stroke risk.MethodsA systematic literature search in Embase, PubMed, Cochrane Library, and Web of Science was performed to collect relevant cohort studies published before August 20, 2022. A random-effects model was used to pool relative risks (RRs) and 95% confidence intervals (CIs).ResultsA total of 17 cohort studies involving 19,630,829 participants were included, encompassing 18,547,132 total deaths (1,328,036 CVD deaths). All-cause mortality, CVD mortality, and stroke risk in the extremely high HDL-C group were increased by 15% (RR = 1.15, 95% CI:1.05–1.25), 14% (RR = 1.14, 95% CI:0.96–1.35) and 14% (RR = 1.14, 95% CI:0.82–1.58), compared to the normal HDL-C group. In subgroup analyses, extremely high HDL-C was associated with a reduced risk of CVD mortality in women and a lower risk of stroke in men compared to normal HDL-C levels.ConclusionsThe extremely high levels of HDL-C were associated with elevated risks of all-cause mortality, CVD mortality, and stroke. More well-designed studies are needed to confirm our findings.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=370201, identifier: CRD42022370201

Emergent and robust ferromagnetic-insulating state in highly strained ferroelastic LaCoO3 thin films

Transition metal oxides are promising candidates for the next generation of spintronic devices due to their fascinating properties that can be effectively engineered by strain, defects, and microstructure. An excellent example can be found in ferroelastic LaCoO3 with paramagnetism in bulk. In contrast, unexpected ferromagnetism is observed in tensile-strained LaCoO3 films, however, its origin remains controversial. Here we simultaneously reveal the formation of ordered oxygen vacancies and previously unreported long-range suppression of CoO6 octahedral rotations throughout LaCoO3 films. Supported by density functional theory calculations, we find that the strong modification of Co 3d-O 2p hybridization associated with the increase of both Co-O-Co bond angle and Co-O bond length weakens the crystal-field splitting and facilitates an ordered high-spin state of Co ions, inducing an emergent ferromagnetic-insulating state. Our work provides unique insights into underlying mechanisms driving the ferromagnetic-insulating state in tensile-strained ferroelastic LaCoO3 films while suggesting potential applications toward low-power spintronic devices

Beclin1 Controls the Levels of p53 by Regulating the Deubiquitination Activity of USP10 and USP13

Autophagy is an important intracellular catabolic mechanism that mediates the degradation of cytoplasmic proteins and organelles. We report a potent small molecule inhibitor of autophagy named “spautin-1” for specific and potent autophagy inhibitor-1. Spautin-1 promotes the degradation of Vps34 PI3 kinase complexes by inhibiting two ubiquitin-specific peptidases, USP10 and USP13, that target the Beclin1 subunit of Vps34 complexes. Beclin1 is a tumor suppressor and frequently monoallelically lost in human cancers. Interestingly, Beclin1 also controls the protein stabilities of USP10 and USP13 by regulating their deubiquitinating activities. Since USP10 mediates the deubiquitination of p53, regulating deubiquitination activity of USP10 and USP13 by Beclin1 provides a mechanism for Beclin1 to control the levels of p53. Our study provides a molecular mechanism involving protein deubiquitination that connects two important tumor suppressors, p53 and Beclin1, and a potent small molecule inhibitor of autophagy as a possible lead compound for developing anticancer drugs

Design of Flight Control System for a Novel Tilt-Rotor UAV

This paper presents the control system design process of a novel tilt-rotor unmanned aerial vehicle (TRUAV). First, a new configuration scheme with the tilting rotors is designed. Then, the detailed nonlinear mathematical model is established, and the parameters are acquired from designed experiments and numerical analyses. For control design purposes, the dynamics equation is linearized around the hovering equilibrium point, and a control allocation method based on trim calculation is developed. To deal with the actuator saturation and uncertain disturbance problems for the novel TRUAV, an improved flight control law based on the combination of the robust servo linear quadratic regulator (RSLQR) optimal control and the extended state observer (ESO) is proposed. The designed flight control law has a simple structure with a high reliability in engineering. Simulations and hovering flight tests are carried out to verify the effectiveness of the mathematical model and the proposed control strategy

Aerodynamics Optimization of a Ducted Coaxial Rotor in Forward Flight Using Orthogonal Test Design

To investigate the aerodynamic complexities involved in the combination of freestream and propeller’s suction flow field of ducted coaxial rotors system in forward flight, an orthogonal L16(43) test design has been applied to optimize the design parameters including forward speed, pitch angle, and axial spacing between rotors. Multiblock grids and Multiple Frame of Reference (MFR) method are adopted for calculating aerodynamic performance of the system, hover characteristic was compared with experimental data obtained from the test stand, and the thrust performance is well predicted for various rotor spacing and a range of rpm. This solution approach is developed for the analytical prediction of forward flight and the simulation results indicated that the design parameters influenced lift, drag, and torque reduced in the order: wind speed > rotor spacing > pitch angle, wind speed > pitch angle, and rotor spacing > wind speed > pitch angle, respectively. The optimal rotor spacing and pitch angle were determined to maximize the aerodynamic performance considering high lift, low drag, and trimmed torque

A Numerical-Experimental Method for Drop Impact Analysis of Composite Landing Gear

The special material performance, manufacturing process, machining behavior, and operating condition of composite materials cause uncertainties to inevitably appear in the mechanical properties of composite structures. Therefore, variability in mechanical properties must be considered in a mechanical response analysis of composite structures. A method is proposed in this paper to predict the dynamic performance of composite landing gear with uncertainties using experimental modal analysis data and nonlinear static test data. In this method, the nonlinear dynamic model of the composite landing gear is divided into two parts, the linear and the nonlinear parts. An experimental modal analysis is employed to predict the linear parameters with a frequency response function, and the nonlinear parameters caused by large deflection are identified by a nonlinear static test with the nonlinear least squares method. To check the accuracy and practicability of the method, it is applied to drop impact simulations and tests of composite landing gear. The results of the simulations are in good agreement with the test results, which shows that the proposed method is perfectly suited for the dynamic analysis of composite landing gear