Elastokinetics modeling and characteristic analysis of the parallel robot mechanism

This paper focuses a new 4-UPS-RPS five degree of freedom (DOF) spatial parallel robot mechanism with independent intellectual property rights obtained. Based on KED method and together with finite element method, Lagrange equation and substructure modeling method, the elastokinetics analytical model of this parallel robot mechanism is established under the ideal situation. Subsequently, the research results, such as elastokinetics model, stress and frequency characteristic analysis, are obtained. Combined with typical examples, key design parameters which significantly influence the dynamic characteristics of the system, are explicated. The work done in this paper lays a solid foundation for the dynamic optimum design of parallel robot mechanism and the physical prototype development

(2E,6E)-2,6-Bis(2,5-difluoro­benzyl­idene)cyclo­hexa­none

In the title compound, C20H14F4O, a derivative of curcumin, the dihedral angle between the two aromatic rings is 27.19 (13)°. The C=C double bonds have an E configuration

Analysis of 116 cases of rectal cancer treated by transanal local excision

BACKGROUND: The purpose of this research was to evaluate the therapeutic effects and prognostic factors of transanal local excision (TAE) for rectal cancer. METHODS: We retrospectively analyzed 116 cases that underwent TAE for rectal cancer from 1995 to 2008. A Cox regression analysis was used to analyze prognostic factors. RESULTS: The survival times for the patients were from 14 to 160.5 months (median time, 58.5 months). The 5-year and 10-year overall survival rates were 72% and 53%, respectively. In all 16 cases experienced local recurrence (13.8%). Pathological type, recurrence or metastasis, and depth of infiltration (T stage) were the prognostic factors according to the univariate analysis, and the latter two were independent factors affecting patient prognosis. For patients with T1 stage who underwent adjuvant radiotherapy, there was no local recurrence; for those in T2 stage, the local recurrence rate was 14.6%. In addition, there was no difference between the patients who received radiotherapy and those who did not (T1: P = 0.260, T2: P = 0.262 for survival rate and T1: P = 0.480, T2: P = 0.560 for recurrence). CONCLUSIONS: The result of TAE for rectal cancer is satisfactory for T1 stage tumors, but it is not suitable for T2 stage tumors

Numerical Analysis of Partial Abrasion of the Straddle-type Monorail Vehicle running Tyre

The finite element model of the running tyre and the pre-stressed concrete (PC) track beam are created in the study. The wheel-rail contact status under the conditions such as acceleration or braking, lateral deviation, and roll is analysed. The wear law of the running tyre under the operating condition of driving on winding roads is discussed. The results show that the running tyre will unevenly wear when driving on the winding road; the smaller curve radius and the faster speed result in heavier and more uneven wear. There is a larger slip between the running tyre on the inner side of the curve and the rail surface, and this tyre has more uneven wear than the running tyre on the outer side of the curve. The research findings provide a theoretical basis for solving the problem of reducing the uneven wear of the running tyre

Implications of Virtual Reality on Environmental Sustainability in Manufacturing Industry: A Case Study

Research on Virtual Reality (VR) in manufacturing is rarely driven by environmental sustainability. This paper explores the feasibility of developing VR technologies to reduce environmental impact, drawing from a case study in an automotive company. We developed a VR demo to support the communication for design review between the technology centre in Sweden and the manufacturing site in China, thus reducing travel frequencies. This reduction was verified through user experience and feedback from focus group discussion and questionnaire. The results show a reduction of travel frequencies for design review, therefore contributing to environmental sustainability

Nonlinear characteristic analysis of high-speed spatial parallel mechanism

In order to grasp the nonlinear characteristic of high-speed spatial parallel mechanism, the analysis of nonlinear characteristics for spatial parallel mechanism is investigated. The nonlinear elastic dynamic equation of 4-UPS-UPU high-speed spatial parallel mechanism is derived by kineto-elastodynamics theory, the dynamic equation is solved by numerical method, the nonlinear characteristic of the parallel mechanism is analyzed by phase diagram. Numerical results show that 4-UPS-UPU high-speed spatial parallel mechanism exhibits typical nonlinear characteristic during exercise, the factors, such as the motion trajectory of parallel mechanism, the material of driving limbs, the diameter of driving limbs and the mass of moving platform, are also have effect on nonlinear characteristics of parallel mechanism. Therefore the reasonable choice of the above factors can weaken the chaos motion. This researches provide important theoretical base of the chaos suppression for spatial parallel mechanism

Comparison of dynamic changes of endogenous hormones between calli derived from mature and immature embryos of maize

Mature and immature embryos of maize inbred lines 87-1 and 137 were used as explants to induce callus on improved N6 medium. The contents of endogenous hormones abscisic acid (ABA), indoleacetic acid (IAA), gibberellic acid (GA3) and cytokinins (ZR) of immature, mature embryos and their corresponding calli were detected by method of enzyme-linked immunosorbant assay (ELISA). At the beginning of culture, IAA and GA3 levels decreased rapidly and reached their lowest levels at day 7, indicating that large amounts of IAA and GA3 are needed for germination. Levels of IAA and GA3 were highest at the beginning of embryonic callus formation from immature embryos, suggesting high levels of IAA and GA3 were beneficial to induction of embryonic callus from immature embryos (CIME). The IAA, GA3 and ABA contents and ration of IAA to ABA (IAA/ABA), GA3 to ABA (GA3/ABA) in callus of mature embryos (CME) were higher than those of CIME after the 14th day from culture initiation and the changes of ratios IAA/ABA and GA3/ABA increased rapidly in CME while they remained low in CIME during the whole experimental period. This inferred that high levels of IAA, GA3 or ABA and large increases in IAA/ABA and GA3/ABA might hinder the induction and maintenance of embryonic calli from mature embryos

Analysis of Roadway Traffic Accidents Based on Rough Sets and Bayesian Networks

The paper integrates Rough Sets (RS) and Bayesian Networks (BN) for roadway traffic accident analysis. RS reduction of attributes is first employed to generate the key set of attributes affecting accident outcomes, which are then fed into a BN structure as nodes for BN construction and accident outcome classification. Such RS-based BN framework combines the advantages of RS in knowledge reduction capability and BN in describing interrelationships among different attributes. The framework is demonstrated using the 100-car naturalistic driving data from Virginia Tech Transportation Institute to predict accident type. Comparative evaluation with the baseline BNs shows the RS-based BNs generally have a higher prediction accuracy and lower network complexity while with comparable prediction coverage and receiver operating characteristic curve area, proving that the proposed RS-based BN overall outperforms the BNs with/without traditional feature selection approaches. The proposed RS-based BN indicates the most significant attributes that affect accident types include pre-crash manoeuvre, driver’s attention from forward roadway to centre mirror, number of secondary tasks undertaken, traffic density, and relation to junction, most of which feature pre-crash driver states and driver behaviours that have not been extensively researched in literature, and could give further insight into the nature of traffic accidents.</p

Vehicle Driving Risk Prediction Based on Markov Chain Model

A driving risk status prediction algorithm based on Markov chain is presented. Driving risk states are classified using clustering techniques based on feature variables describing the instantaneous risk levels within time windows, where instantaneous risk levels are determined in time-to-collision and time-headway two-dimension plane. Multinomial Logistic models with recursive feature variable estimation method are developed to improve the traditional state transition probability estimation, which also takes into account the comprehensive effects of driving behavior, traffic, and road environment factors on the evolution of driving risk status. The “100-car” natural driving data from Virginia Tech is employed for the training and validation of the prediction model. The results show that, under the 5% false positive rate, the prediction algorithm could have high prediction accuracy rate for future medium-to-high driving risks and could meet the timeliness requirement of collision avoidance warning. The algorithm could contribute to timely warning or auxiliary correction to drivers in the approaching-danger state