55 research outputs found
Angular velocity and contact force simulation of the spiral bevel gear meshing based on the hertz contact theory
To obtain the change tendency of the wheel’s
angular velocity and tangential component of
contact force with time of the pinion under the step
input during spiral bevel gear meshing, the tooth
flank equation of spiral bevel gear was constructed
based on the Non-Uniform Rational B-splines
curve. The three-dimensional model of the pinion
and the wheel were built based on the tooth flank
equation. The calculation equation and relative
parameters set for the contact force of spiral bevel
gear meshing were done based on the Hertz
contact theory. A mating of spiral bevel gears was
taken as an example for dynamics simulation and
the simulation results show that the relative error
rate of the angular velocity between simulation and
theoretical calculation is 0.054%, and that the
relative error rate of tangential component of the
contact force between simulation and theoretical
calculation is 4.82%. These findings provide the
theoretical basis for dynamic characteristics
optimization of the spiral bevel gears
cuTS: Scaling Subgraph Isomorphism on Distributed Multi-GPU Systems Using Trie Based Data Structure
Subgraph isomorphism is a pattern-matching algorithm widely used in many domains such as chem-informatics, bioinformatics, databases, and social network analysis. It is computationally expensive and is a proven NP-hard problem. The massive parallelism in GPUs is well suited for solving subgraph isomorphism. However, current GPU implementations are far from the achievable performance. Moreover, the enormous memory requirement of current approaches limits the problem size that can be handled. This work analyzes the fundamental challenges associated with processing subgraph isomorphism on GPUs and develops an efficient GPU implementation. We also develop a GPU-friendly trie-based data structure to drastically reduce the intermediate storage space requirement, enabling large benchmarks to be processed. We also develop the first distributed sub-graph isomorphism algorithm for GPUs. Our experimental evaluation demonstrates the efficacy of our approach by comparing the execution time and number of cases that can be handled against the state-of-the-art GPU implementations
Significant Differences in Bacterial and Potentially Pathogenic Communities Between Sympatric Hooded Crane and Greater White-Fronted Goose
The gut microbiota of vertebrates play a crucial role in shaping the health of their hosts. However, knowledge of the avian intestinal microbiota has arguably lagged behind that of many other vertebrates. Here, we examine the intestinal bacterial communities of the hooded crane and the greater white-fronted goose at the Shengjin Lake of China, using high-throughput sequencing (Illumina Mi-Seq), and infer the potential pathogens associated with each species. Intestinal bacterial alpha-diversity in the greater white-fronted goose was significantly higher than that in hooded crane. The intestinal bacterial community compositions were significantly different between the two hosts, suggesting that host interactions with specific communities might have profound implications. In addition, potential pathogens were detected in both guts of the two hosts, suggesting that these wild birds might be at risk of disease and probably spread infectious disease to other sympatric vertebrates. The gut of hooded crane carried more potential pathogens than that of the greater white-fronted goose. The potentially pathogenic community compositions were also significantly different between the two hosts, suggesting the divergence of potentially pathogenic communities between hooded crane, and greater white-fronted goose. Finally, bacterial and potentially pathogenic structures showed strong evidence of phylogenic clustering in both hosts, further demonstrating that each host was associated with preferential and defined bacterial and potentially pathogenic communities. Our results argue that more attention should be paid to investigate avian intestinal pathogens which might increase disease risks for conspecifics and other mixed species, and even poultry and human beings
TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition
Tucker decomposition is one of the SOTA CNN model compression techniques.
However, unlike the FLOPs reduction, we observe very limited inference time
reduction with Tuckercompressed models using existing GPU software such as
cuDNN. To this end, we propose an efficient end-to-end framework that can
generate highly accurate and compact CNN models via Tucker decomposition and
optimized inference code on GPUs. Specifically, we propose an ADMM-based
training algorithm that can achieve highly accurate Tucker-format models. We
also develop a high-performance kernel for Tucker-format convolutions and
analytical performance models to guide the selection of execution parameters.
We further propose a co-design framework to determine the proper Tucker ranks
driven by practical inference time (rather than FLOPs). Our evaluation on five
modern CNNs with A100 demonstrates that our compressed models with our
optimized code achieve up to 3.14X speedup over cuDNN, 1.45X speedup over TVM,
and 4.57X over the original models using cuDNN with up to 0.05% accuracy loss.Comment: 12 pages, 8 figures, 3 tables, accepted by PPoPP '2
Multi - mechanism coalescence design and matrix expression of logic action sequences of the over-turn nursing robot Part I: Functions and coalescence design
In order to effectively solve the problem in over-turn of a bedridden person with the assistance of external force, a double bed face- three embedded leave over-turn nursing robot with the flexible compensation was put forward, with the abstraction of the bedridden person as an organism. This robot, on the basis of concept gesture of the person in bed and the state of the robot supporting and proving the gesture with the actions and combination of the two bed faces, held the complete function of over-turn nursing with 7 states corresponding to 5 gestures of the bedridden person obeying the fundamental requirements of safety, rapidity, and comport. The design method of "PS-MM-KD" was proposed for multi-mechanism coalescent system with related specific tasks induced from the original problems with Systems Engineering. Mechanics and Mechanisms, then applied in the concrete sub-system design followed by analysis and verification of both the scheme and the sub-systems in the design, using the Kinematics and Dynamics, implementing the gears, chain wheel, slewing mechanism, screw nut and mortise and tenon joint type clutch mechanism design successfully. Based on those above, a "two-bed face/three-leaf embedded flexible compensation nursing robot" was designed adopting to all ages, people of various kinds of body geometry. PLC, sensor and logic algorithm were used to carry out the control and operation of 7 state-5 posture sequences for realization of the automation and intelligent over-turning in safety, comfort, and convenience
Multi - mechanism coalescence design and matrix expression of logic action sequences of the over-turn nursing robot Part II: Gesture-state in sets and matrix
As is expressed in Part I, Functions and coalescence design of the over-turn nursing robot, the performance and requirements have been put forward with systematic design of several mechanisms. Here, in order to control and function well the over-turn nursing robot, the three-dimensional and five-dimensional Euclidean space with the real number were adopted in terms of sets for gesture of the bedridden person and the corresponding state of the robot, respectively. The matrix method was employed to define and describe the gestures-robot performance and its transition path. The gesture-state sequence matrix not only accurately and clearly expressed the gesture series, state sequence and their corresponding relations, but also laid a theoretical and technical foundation for the path planning from the current gesture to the target one. The control and operation of 7 states and 5 gestures were done to realize the automation and intelligent over-turning safely, comfortably and conveniently
Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning
We present a reinforcement learning (RL) framework that enables quadrupedal
robots to perform soccer goalkeeping tasks in the real world. Soccer
goalkeeping using quadrupeds is a challenging problem, that combines highly
dynamic locomotion with precise and fast non-prehensile object (ball)
manipulation. The robot needs to react to and intercept a potentially flying
ball using dynamic locomotion maneuvers in a very short amount of time, usually
less than one second. In this paper, we propose to address this problem using a
hierarchical model-free RL framework. The first component of the framework
contains multiple control policies for distinct locomotion skills, which can be
used to cover different regions of the goal. Each control policy enables the
robot to track random parametric end-effector trajectories while performing one
specific locomotion skill, such as jump, dive, and sidestep. These skills are
then utilized by the second part of the framework which is a high-level planner
to determine a desired skill and end-effector trajectory in order to intercept
a ball flying to different regions of the goal. We deploy the proposed
framework on a Mini Cheetah quadrupedal robot and demonstrate the effectiveness
of our framework for various agile interceptions of a fast-moving ball in the
real world.Comment: First two authors contributed equally. Accompanying video is at
https://youtu.be/iX6OgG67-Z
Small extracellular vesicles derived from four dimensional-culture of mesenchymal stem cells induce alternatively activated macrophages by upregulating IGFBP2/EGFR to attenuate inflammation in the spinal cord injury of rats
Effectively reducing the inflammatory response after spinal cord injury (SCI) is a challenging clinical problem and the subject of active investigation. This study employed a porous scaffold-based three dimensional long-term culture technique to obtain human umbilical cord mesenchymal stem cell (hUC-MSC)-derived Small Extracellular Vesicles (sEVs) (three dimensional culture over time, the “4D-sEVs”). Moreover, the vesicle size, number, and inner protein concentrations of the MSC 4D-sEVs contained altered protein profiles compared with those derived from 2D culture conditions. A proteomics analysis suggested broad changes, especially significant upregulation of Epidermal Growth Factors Receptor (EGFR) and Insulin-like Growth Factor Binding Protein 2 (IGFBP2) in 4D-sEVs compared with 2D-sEVs. The endocytosis of 4D-sEVs allowed for the binding of EGFR and IGFBP2, leading to downstream STAT3 phosphorylation and IL-10 secretion and effective induction of macrophages/microglia polarization from the pro-inflammatory M1 to anti-inflammatory M2 phenotype, both in vitro and in the injured areas of rats with compressive/contusive SCI. The reduction in neuroinflammation after 4D-sEVs delivery to the injury site epicenter led to significant neuroprotection, as evidenced by the number of surviving spinal neurons. Therefore, applying this novel 4D culture-derived Small Extracellular Vesicles could effectively curb the inflammatory response and increase tissue repair after SCI
Prevalence and prognosis of molecularly defined familial hypercholesterolemia in patients with acute coronary syndrome
BackgroundFamilial hypercholesterolemia (FH) can elevate serum low-density lipoprotein cholesterol (LDL-C) levels, which can promote the progression of acute coronary syndrome (ACS). However, the effect of FH on the prognosis of ACS remains unclear.MethodsIn this prospective cohort study, 223 patients with ACS having LDL-C ≥ 135.3 mg/dL (3.5 mmol/L) were enrolled and screened for FH using a multiple-gene FH panel. The diagnosis of FH was defined according to the ACMG/AMP criteria as carrying pathogenic or likely pathogenic variants. The clinical features of FH and the relationship of FH to the average 16.6-month risk of cardiovascular events (CVEs) were assessed.ResultsThe prevalence of molecularly defined FH in enrolled patients was 26.9%, and coronary artery lesions were more severe in patients with FH than in those without (Gensini score 66.0 vs. 28.0, respectively; P < 0.001). After lipid lowering, patients with FH still had significantly higher LDL-C levels at their last visit (73.5 ± 25.9 mg/dL vs. 84.7 ± 37.1 mg/dL; P = 0.013) compared with those without. FH increased the incidence of CVEs in patients with ACS [hazard ratio (HR): 3.058; 95% confidence interval (CI): 1.585–5.900; log-rank P < 0.001].ConclusionFH is associated with an increased risk of CVEs in ACS and is an independent risk factor for ACS. This study highlights the importance of genetic testing of FH-related gene mutations in patients with ACS
- …