Mobile Internet Access Patterns for Travel: Comparison of Desktops, Tablets, and Phones

This study investigated information access patterns on desktops, tablets, and phones of a few different travel related websites through web log analysis. The results show that the three types of devices have different ratios of search traffic, referral traffic, and direct traffic. With a smaller screen on mobile devices, users visit fewer pages per visit, stay less time on the website per session, and have higher bounce rates. Content analysis revealed that travelers requested more specific information on mobile devices and general information on desktop computers, indicating information needs in late decision making stages on mobile devices

Adaptive Admittance Control Strategy for a Robotic Knee Exoskeleton With a Nonlinear Variable Stiffness Actuator

This article presents the design and control of a robotic knee exoskeleton for gait rehabilitation of patients with knee joint impairments. First, the hardware design of the exoskeleton is presented, including the mechanical structure, actuator design and configuration, and electronic system. Based on the nonlinear characteristics of human muscles, a nonlinear variable stiffness actuator (NLVSA) is designed for the actuation system of the exoskeleton. Next, the modeling of the NLVSA is described. In addition, an adaptive admittance control strategy comprising a sparrow search optimization algorithm-based long short-term memory neural network model and an adaptive admittance control algorithm based on the radial basis function neural network (RBFAAC) is proposed for the exoskeleton. Finally, a pilot study is conducted to demonstrate the effectiveness of the robotic knee exoskeleton. The experimental results validate the effectiveness of the designed NLVSA, and the exoskeleton has the potential for human knee rehabilitation by providing effective assistance with the proposed control strategy. With the proposed RBFAAC algorithm, the average root mean square error between the reference and actual knee joint angles is 1.24° at different walking speeds

Fish species-specific TRIM gene FTRCA1 negatively regulates interferon response through attenuating IRF7 transcription

In mammals and fish, emerging evidence highlights that TRIM family members play important roles in the interferon (IFN) antiviral immune response. Fish TRIM family has undergone an unprecedented expansion leading to generation of finTRIM subfamily, which is exclusively specific to fish. Our recent results have shown that FTRCA1 (finTRIM C. auratus 1) is likely a fish species-specific finTRIM member in crucian carp C. auratus and acts as a negative modulator to downregulate fish IFN response by autophage-lysosomal degradation of protein kinase TBK1. In the present study, we found that FTRCA1 also impedes the activation of crucian carp IFN promoter by IRF7 but not by IRF3. Mechanistically, FTRCA1 attenuates IRF7 transcription levels likely due to enhanced decay of IRF7 mRNA, leading to reduced IRF7 protein levels and subsequently reduced fish IFN expression. E3 ligase activity is required for FTRCA1 to negatively regulate IRF7-mediated IFN response, because ligase-inactive mutants and the RING-deleted mutant of FTRCA1 lose the ability to block the activation of crucian carp IFN promoter by IRF7. These results together indicate that FTRCA1 is a multifaceted modulator to target different signaling factors for shaping fish IFN response in crucian carp.</p

Robotic Assembly Control Reconfiguration Based on Transfer Reinforcement Learning for Objects with Different Geometric Features

Robotic force-based compliance control is a preferred approach to achieve high-precision assembly tasks. When the geometric features of assembly objects are asymmetric or irregular, reinforcement learning (RL) agents are gradually incorporated into the compliance controller to adapt to complex force-pose mapping which is hard to model analytically. Since force-pose mapping is strongly dependent on geometric features, a compliance controller is only optimal for current geometric features. To reduce the learning cost of assembly objects with different geometric features, this paper is devoted to answering how to reconfigure existing controllers for new assembly objects with different geometric features. In this paper, model-based parameters are first reconfigured based on the proposed Equivalent Theory of Compliance Law (ETCL). Then the RL agent is transferred based on the proposed Weighted Dimensional Policy Distillation (WDPD) method. The experiment results demonstrate that the control reconfiguration method costs less time and achieves better control performance, which confirms the validity of proposed methods