The cytokinin two‐component signal transduction system (TCS) is involved in many biological processes, including hormone signal transduction and plant growth regulation. Although cytokinin TCS has ...been well characterized in Arabidopsis thaliana, its role in tomato remains elusive.
In this study, we characterized the diversity and function of response regulator (RR) genes, a critical component of TCS, in tomato. In total, we identified 31 RR genes in the tomato genome. These SlRR genes were classified into three subgroups (type‐A, type‐B and type‐C).
Various stress‐responsive cis‐elements were present in the tomato RR gene promoters. Their expression responses under pesticide treatment were evaluated by transcriptome analysis. Their expression under heat, cold, ABA, salinity and NaHCO3 treatments was further investigated by qRT‐PCR and complemented with the available transcription data under these treatments. Specifically, SlRR13 expression was significantly upregulated under salinity, drought, cold and pesticide stress and was downregulated under ABA treatment. SlRR23 expression was induced under salt treatment, while the transcription level of SlRR1 was increased under cold and decreased under salt stress.
We also found that GATA transcription factors played a significant role in the regulation of SlRR genes. Based on our results, tomato SlRR genes are involved in responses to abiotic stress in tomato and could be implemented in molecular breeding approaches to increase resistance of tomato to environmental stresses.
We identified 31 RR genes in tomato which were involved in response to abiotic stress and could be implemented in molecular breeding approaches to increase tomato environmental resistance.
This study aims to evaluate protective effects of brief repetitive bilateral arm ischemic preconditioning (BAIPC) on stroke recurrence in patients with symptomatic atherosclerotic intracranial ...arterial stenosis (IAS).
A total of 68 consecutive cases with symptomatic IAS, diagnosed by imaging, were enrolled in this prospective and randomized study. All patients received standard medical management. Patients in the BAIPC group (n = 38) underwent 5 brief cycles consisting of bilateral upper limb ischemia followed by reperfusion. The BAIPC procedure was performed twice daily over 300 consecutive days. Incidence of recurrent stroke and cerebral perfusion status in BAIPC-treated patients were compared with the untreated control group (n = 30).
In the control group, incidence of recurrent stroke at 90 and 300 days were 23.3% and 26.7%, respectively. In the BAIPC group, incidence of recurrent stroke was reduced to 5% and 7.9% at 90 and 300 days (p < 0.01), respectively. The average time to recovery (modified Rankin Scale score 0-1) was also shortened by BAIPC. Cerebral perfusion status, measured by SPECT and transcranial Doppler sonography, improved remarkably in BAIPC-treated brain than in control (p < 0.01).
This study provides a proof-of-concept that BAIPC may be an effective way to improve cerebral perfusion and reduce recurrent strokes in patients with IAS. Further investigation of this therapeutic approach is warranted as some patients were excluded after randomization.
Household chores service is one of the desirable functions for a service robot. Object classification is the most important function when searching for objects. We consider that the major concern is ...that the robot should not misclassify the object. If the robot misclassifies household object images, it will then perform the household tasks with the wrong object. This may cause serious damages to a service robot and to the user. This concept gives us the insight that the precision of the classification must be very high by setting a confidence threshold so that it then can claim a reliable service robot. By exploring this concept, we develop a more convincing indicator, Classification Reliability, to reveal the reliability of deep learning model. Moreover, we develop a fine-tune rule base to continuously regenerate more proper training dataset for the CNN model to increase reliability. Experimental results demonstrate that the CNN model fine-tuned by our closed-loop system achieves the reliability which is higher than the other similar effects such as DenseNet on the CIFAR-10 dataset.
We numerically investigate the effects of disorder on the quantum Hall effect (QHE) and the quantum phase transitions in silicene based on a lattice model. It is shown that for a clean sample, ...silicene exhibits an unconventional QHE near the band center, with plateaus developing at ν=0, ±2, ±6,…, and a conventional QHE near the band edges. In the presence of disorder, the Hall plateaus can be destroyed through the float-up of extended levels toward the band center, in which higher plateaus disappear first. However, the center ν=0 Hall plateau is more sensitive to disorder and disappears at a relatively weak disorder strength. Moreover, the combination of an electric field and the intrinsic spin-orbit interaction (SOI) can lead to quantum phase transitions from a topological insulator to a band insulator at the charge neutrality point (CNP), accompanied by additional quantum Hall conductivity plateaus.
We previously identified and characterized a novel p53-regulated gene in mouse prostate cancer cells that was homologous to a human gene that had been identified in brain cancers and termed RTVP-1 or ...GLIPR. In this report, we document that the human RTVP-1 gene is also regulated by p53 and induces apoptosis in human prostate cancer cell lines. We show that the expression of the human RTVP-1 gene is down-regulated in human prostate cancer specimens compared with normal human prostate tissue at the mRNA and protein levels. We further document epigenetic changes consistent with RTVP-1 being a tumor suppressor in human prostate cancer.
With recent development of robotic technology, it is increasingly common that robot coexist with human, in which humans and robots share a common workspace and work in close proximity. To maintain ...efficiency and ensure safety under these circumstances, robot should have the ability to predict the future human motion based on the observed on-going motion. In this paper, we present a methodology for on-line inference of human intention and prediction of human hand motion. The proposed framework is built using Probabilistic Dynamic Movement Primitive (PDMP). In the off-line stage, a set of PDMPs is constructed based on the recorded demonstrations and they will then be used for inferring human intention and predicting human hand motion in the on-line stage. A proof of concept evaluation is carried out in a tabletop manipulation task. Experimental result shows the proposed framework achieve high performance in human intention inference and in the trajectory similarity between the predicted and the actual hand movement under the normally defined environment. We also show the proposed framework can adapt and generalize to the newly defined environment.
In this paper, we propose a leg compliance method and strategies for ZMP-based bipedal walking robot on continuous uneven terrain without gyro sensor by combining soft joint, impedance, force and ...position control. We divide biped robot into support leg and swing leg to apply different control methods, and distinguish period of swing leg into four procedures, which adopt different strategies. By this way, robot achieves walking on uneven slope. Besides, when robot walks on normal flat ground, the proposed compliant landing method can also decrease the impact of ground reaction force (GRF) and reinforce stability during transition from single support phase (SSP) to double support phase (DSP). The validity of the proposed approach and strategies are verified and achieved with experiment biped robot in our lab.
In this paper, we propose a modularized architecture for a robot arm object fetching system integrated with 3D CAD-model based object recognition system that can cope with objects in random types and ...poses. The interface and the core functionality of each module in the architecture are discussed in detail. Implementation of each module is also conducted. Furthermore, the assumptions and the working conditions behind each module are carefully examined. We develop the system based on our previous work and enhance the recognition module. To proof the feasibility of our architecture, 3D object recognition and fetching demonstration are successfully implemented, and the result of object recognition, teaching by touching, and fast grasp synthesis are successfully demonstrated.
Internet-based robotic systems have received much attention in the past years. In this paper, we review the networked mobile robot systems and suggest taxonomy based on the three levels of control ...commands. The performance analysis result shows that direct control has potential difficulty for implementation due to the unpredicted transmission delay of the network. To attack this problem, we have suggested the behavior-programming control concept to avoid disturbances of the Internet latency. For this purpose, primitive local intelligence of the mobile robot is grouped into motion planner, motion executor, and motion assistant, where each of a group is treated as an agent. They are integrated by centralized control architecture based on multiagent concept, communicated through a center information memory. The event-driven concept is applied on the robot to switch the behaviors to accommodate the unpredicted mission autonomously. We have successfully demonstrated experimentally the feasibility and reliability for system through a performance comparison with direct remote control. The behavior-programming control of the networked robot can be extended to explore the unknown environment and to perform remote learning through linguistic interaction.
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