The SphK1 inhibitor development is of great importance for the treatment of non-small cell lung cancer (NSCLC). In this study, CHJ01 which has been previously shown anti-tumor effects was introduced to investigate the...
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The SphK1 inhibitor development is of great importance for the treatment of non-small cell lung cancer (NSCLC). In this study, CHJ01 which has been previously shown anti-tumor effects was introduced to investigate the detailed antitumor mechanism both in vitro and in vivo . CHJ01 inhibited the A549 cell proliferation, migration, and invasion significantly and showed cytotoxicity to A549. CHJ01 induced G0/G1 cell cycle arrest by increasing ceramide levels and altered the expression of TRAF2, Bcl-2, Bax and RELA. CHJ01 inhibited the TRAF2/ NF-κB signaling pathway and promoted apoptosis by downregulating Bcl-2 and upregulating Bax. In vivo anti-tumor effects were investigated using a nude mouse ectopic tumor model. CHJ01 reduced the volumes and weights of xenograft tumor in nude mice. CHJ01 induced apoptosis by HE staining and immunohistochemistry assay. These results indicated that CHJ01 can be a potential candidate for the treatment of NSCLC.
Forecasting the trajectories of traffic agents is essential for autonomous systems such as self-driving cars and social robots to guarantee safety in crowded scenarios. Capturing social interactions between agents and...
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Forecasting the trajectories of traffic agents is essential for autonomous systems such as self-driving cars and social robots to guarantee safety in crowded scenarios. Capturing social interactions between agents and generating informative future features bring great challenges to accurate trajectory prediction. To this end, this paper proposes a novel multi-agent trajectory prediction model called AGTFI based on the adaptive graph transformer and future interaction modeling. First, an adaptive graph transformer (AGT) proficient at extracting node and edge features is introduced to capture the complex social interactions between traffic agents. Moreover, a two-stage prediction approach is devised where the first stage is devoted to generating pre-estimated future motion features by bidirectional corrected GRU (BCGRU) and the second stage further incorporates future social interactions into BCGRU to reduce prediction errors. Quantitative and qualitative evaluations of AGTFI on benchmark datasets, including ETH-UCY, SDD, and INTERACTION demonstrate the effectiveness of our model. Ablation studies are conducted to verify the rationale behind the model components.
In the context of the rapid development of intelligent manufacturing, effective quality control has become the key to improving manufacturing efficiency and product quality. Traditional quality control methods are oft...
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In the context of the rapid development of intelligent manufacturing, effective quality control has become the key to improving manufacturing efficiency and product quality. Traditional quality control methods are often inadequate when faced with complex production data and changing manufacturing environments. Therefore, exploring new intelligent quality control technologies to cope with these challenges in intelligent manufacturing has become an important research direction. In view of this, the study proposed a quality control technology that combines association rules and fuzzy decision-making. Firstly, association rule mining methods are used to analyze production data and extract the relationships between key quality factors. Secondly, based on these association rules, fuzzy decision technology is used to adjust and optimize the production process, ultimately achieving quality control of products in the intelligent manufacturing production process. The data showed that when running on the training set and validation set, the research method reached a stable state at 18 and 46 iterations of the system, respectively, with a minimum cost loss function value. In both batch production lines, the detection efficiency under the operation of the research method remained at 2200 units per minute. During the process of repeating the system for 6 times, the research method consistently achieved maximum control accuracy and minimum time consumption. The satisfaction of the four experts with the operation of the research method in small batch production and large batch production was 9.32 and 9.2, respectively, significantly higher than other algorithms. The above results indicated that the proposed method can effectively improve the efficiency of product quality control, reduce production costs, and ultimately reduce the rate of defective products in the production process.
This paper focuses on kinematic calibration of a novel 5-DOF hybrid robot and attention is paid to the suppression of 'observation noise' impact caused by the measurement system and unconsidered source errors....
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This paper focuses on kinematic calibration of a novel 5-DOF hybrid robot and attention is paid to the suppression of 'observation noise' impact caused by the measurement system and unconsidered source errors. The proposed method that is pertinently developed to improve the accuracy of the targeted robot, is implemented as follows: with the aid of screw theory, a linear map between the pose error twist of the end effector and all possible geometric source errors of the hybrid machining robot is formulated. Following the measurement and solution of pose error twist, an extended Kalman filter (EKF) is then employed to obtain more reliable and stable identification results of geometric errors. A linearized error compensator is then proposed and used in calibration experiments. Compared with the least square method, the proposed EKF method is proved to be robust and has good compensation effect in the verification configurations. After kinematic calibration, the positional and angular errors of the robot are reduced to be less than 60.6 gm and 67.6 grad respectively. The results verify the effectiveness and general applicability of the proposed identification and compensation strategy.
In this paper, the zonotopic set-membership state estimation (SMSE) problem for nonlinear systems is investigated. To handle the nonlinear dynamics of the system, a semi-infinite programming (SIP) scheme based on zono...
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In this paper, the zonotopic set-membership state estimation (SMSE) problem for nonlinear systems is investigated. To handle the nonlinear dynamics of the system, a semi-infinite programming (SIP) scheme based on zonotope analysis is established and solved. The SIP scheme aims to obtain a tight zonotope to enclose the nonlinear dynamics of the system. Subsequently, the robustness performance of the estimation error system is analyzed based on the L performance. Sufficient design conditions are derived to guarantee that the state estimation results satisfy the preset L performance index. Finally, illustrative examples are given to demonstrate the effectiveness of the proposed method. (c) 2025 Published by Elsevier Ltd.
The diversity of the carrier transport mechanism in the resistive switching process remains a significant obstacle for the design and application of resistive random access memory (RRAM) devices. In this study, the in...
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The diversity of the carrier transport mechanism in the resistive switching process remains a significant obstacle for the design and application of resistive random access memory (RRAM) devices. In this study, the influence of annealing on the dielectric properties of the Ti/HfOx/Pt RRAM device and its associated carrier transport mechanism is investigated. The results reveal that the current conduction in both annealed and unannealed devices is primarily attributed to grain boundary (GB) relaxation, with only the GB acting as a depletion layer that induces dielectric relaxation. Furthermore, annealing decreases the interfacial polarization and changes the relaxation time at the GB. In addition, the charge carriers exhibit nearest-neighbor hopping conduction at a higher temperature in Ti/HfOx/Pt RRAM devices, whereas variable-range-hopping conduction occurs at lower temperatures. Long-range charge carrier transport also plays a significant role in the conduction process. To offer a deeper understanding of the conduction processes in the Ti/HfOx/Pt RRAM device, a carrier transport model is proposed, which provides valuable insights into the intricate mechanisms governing conduction in these devices.
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