Symmetric Subspace Motion Generators

When moving an object endowed with continuous symmetry, an ambiguity arises in its underlying rigid body transformation, induced by the arbitrariness of the portion of motion that does not change the overall body shape. The functional redundancy caused by continuous symmetry is ubiquitously present in a broad range of robotic applications, including robot machining and haptic interface (revolute symmetry), remote center of motion devices for minimal invasive surgery (line symmetry), and motion modules for hyperredundant robots (plane symmetry). In this paper, we argue that such functional redundancy can be systematically resolved by resorting to symmetric subspaces (SSs) of the special Euclidean group SE(3), which motivates us to systematically investigate the structural synthesis of SS motion generators. In particular, we develop a general synthesis procedure that allows us to generate a wide spectrum of novel mechanisms for use in the applications mentioned

Synthesis and singularity analysis of N-UU parallel wrists: A symmetric space approach

We report some recent advances in kinematics and singularity analysis of the mirrorsymmetric N-UU parallel wrists using symmetric space theory. We show that both the finite displacement and infinitesimal singularity kinematics of a N-UU wrist are governed by the mirror symmetry property and half-angle property of the underlying motion manifold, which is a symmetric submanifold of the special Euclidean group SE(3). Our result is stronger than and may be considered a closure of Hunt's argument for instantaneous mirror symmetry in his pioneering exposition of constant velocity shaft couplings. Moreover, we show that the wrist can, to some extent, be treated as a spherical mechanism, even though dependent translation exists, and the singularity-free workspace of a N-UU wrist may be analytically derived. This leads to a straightforward optimal design for maximal singularity-free workspace

The Power of Words in Crowdfunding

In this chapter, the authors first provide an overview of the crowdfunding phenomenon. Through the literature review of crowdfunding success factors in the four models, the authors then summarize that the current entrepreneurial research focused on success factors has failed to sufficiently examine how the power of words would affect crowdfunding. Therefore, the authors propose that non-verbal and verbal cues are crucial to entrepreneurial financing success. Based on the insufficient research related with those cues, especially the non-verbal ones, the authors open an area of study on non-verbal and verbal cues in the entrepreneurial financing process by conducting and writing this chapter

Adaptive Backstepping Controller Design for Stochastic Jump Systems

In this technical note, we improve the results in a paper by Shi et al., in which problems of stochastic stability and sliding mode control for a class of linear continuous-time systems with stochastic jumps were considered. However, the system considered is switching stochastically between different subsystems, the dynamics of the jump system can not stay on each sliding surface of subsystems forever, therefore, it is difficult to determine whether the closed-loop system is stochastically stable. In this technical note, the backstepping techniques are adopted to overcome the problem in a paper by Shi et al.. The resulting closed-loop system is bounded in probability. It has been shown that the adaptive control problem for the Markovian jump systems is solvable if a set of coupled linear matrix inequalities (LMIs) have solutions. A numerical example is given to show the potential of the proposed techniques

The devil is in the details: The effect of nonverbal cues on crowdfunding success

Many reward-based crowdfunding platforms encourage entrepreneurs to introduce their projects and make a personal appeal with a video clip. In this study, we investigate the impact of such a pitch video on financing outcomes. Grounded in social perception literature, we propose that effective use of nonverbal cues in a pitch video increases funding success. We coded and analyzed videos of crowdfunding campaigns and found that an entrepreneur could improve the funding outcomes by gazing less, appearing early, and reducing speech hesitations in a pitch video. We also found that smiling has no impact on funding success

Socio-demographic, Clinical, and Genetic Determinants of Quality of Life in Lung Cancer Patients.

Patient reported health-related quality of life (QOL) is a major component of the overall well-being of cancer patients, with links to prognosis. In 6,420 lung cancer patients, we identified patient characteristics and genetic determinants of QOL. Patient responses from the SF-12 questionnaire was used to calculate normalized Physical Component Summary (PCS) and Mental Component Summary (MCS) scores. Further, we analyzed 218 single nucleotide polymorphisms (SNPs) in the p38 MAPK signaling pathway, a key mediator of response to cellular and environmental stress, as genetic determinants of QOL in a subset of the study population (N = 641). Trends among demographic factors for mean PCS and MCS included smoking status (PCS Ptrend < 0.001, MCS Ptrend < 0.001) and education (PCS Ptrend < 0.001, MCS Ptrend < 0.001). Similar relationships were seen for MCS. The homozygous rare genotype of MEF2B: rs2040562 showed an increased risk of a poor MCS (OR: 3.06, 95% CI: 1.05-8.92, P = 0.041). Finally, survival analysis showed that a low PCS or a MCS was associated with increased risks of five-year mortality (HR = 1.63, 95% CI: 1.51-1.77, HR = 1.23, 95% CI: 1.16-1.32, respectively) and there was a significant reduction in median survival time (Plog-rank < 0.001). These findings suggest that multiple factors contribute to QOL in lung cancer patients, and baseline QOL can impact survival

Large-eddy simulations of the inlet grid-generated turbulence

In this paper, a new technique of turbulence generation in large eddy simulation (LES) is studied and verified. In order to generate turbulence similar to the wind tunnel test, the proposed grid inlet technique places the grid on the Inlet boundary to achieve the following effects: changing the grid size controls the turbulence integral length scale and changing the distance from inlet controls the turbulence intensity. The purpose of this paper is to explore the domain requirements of grid-inlet technology by studying the turbulence characteristics of three different grid inlets. In particular, this paper further studies the effects of domain sizes on the lateral correlation of fluctuating wind by arranging the transverse positions of monitoring points irregularly and in equal proportion. Meanwhile, the isotropic hypothesis of gird-generated turbulence is verified by power spectrum. The results show that the turbulence intensity is unaffected by the domain sizes, the larger calculation domain corresponds to the gentler changing trend of the lateral correlation of the fluctuating wind and the flow fields under the three different domain sizes basically satisfy the isotropic hypothesis. The above results are helpful for the further application of the grid inlet technique

Adaptive Resource Allocation for Workflow Containerization on Kubernetes

In a cloud-native era, the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes. However, when encountering continuous workflow requests and unexpected resource request spikes, the engine is limited to the current workflow load information for resource allocation, which lacks the agility and predictability of resource allocation, resulting in over and under-provisioning resources. This mechanism seriously hinders workflow execution efficiency and leads to high resource waste. To overcome these drawbacks, we propose an adaptive resource allocation scheme named ARAS for the Kubernetes-based workflow engines. Considering potential future workflow task requests within the current task pod's lifecycle, the ARAS uses a resource scaling strategy to allocate resources in response to high-concurrency workflow scenarios. The ARAS offers resource discovery, resource evaluation, and allocation functionalities and serves as a key component for our tailored workflow engine (KubeAdaptor). By integrating the ARAS into KubeAdaptor for workflow containerized execution, we demonstrate the practical abilities of KubeAdaptor and the advantages of our ARAS. Compared with the baseline algorithm, experimental evaluation under three distinct workflow arrival patterns shows that ARAS gains time-saving of 9.8% to 40.92% in the average total duration of all workflows, time-saving of 26.4% to 79.86% in the average duration of individual workflow, and an increase of 1% to 16% in CPU and memory resource usage rate