Simulation and experiment research of vibration characteristic on star compressor

Aiming at the vibration defects of star compressor, simulation and experiment are carried out to investigate the compressor. By drilling holes in the valve stem, the pressure changes of each cylinder are measured without damaging the cylinder block. The dynamic model of crank-connecting rod mechanism is established. After the measured cylinder pressure loaded on the dynamic model, the force acting on the main motion pair is obtained. The finite element model of the compressor is established for the first time, the force of the motion pair is loaded on the finite element model by MPC coupling method, and the vibration acceleration of the machine base is tested. The result shows that the main modal shapes between 50-150 Hz are body deformation, modal shapes between 150-200 Hz are base deformation, the simulation acceleration of the base is higher than that of the experiment, and the main working frequency and frequency doubling can correspond. The conclusions provide reference for vibration isolation design of star compressor

Multi-objective optimization design of ship propulsion shafting based on the multi-attribute decision making

The expression of field transfer matrix of a ship propulsion shafting is deduced based on the modified Timoshenko beam theory using the transfer matrix method. Moreover, the power flow of each bearing of the propulsion shafting is carried out numerically. The Pareto optimal solution set is obtained by selecting the aft stern bearing stiffness, front stern bearing stiffness, thrust bearing stiffness and the bearing spacing length as the optimization design variables and selecting the sum of the power flow of each bearing of the propulsion shafting as the optimization objectives. Then, the Pareto optimal solution set is sorted by the TOPSIS method and MADM approach. The analysis results show that it is feasible and effective to avoid the blindness of selecting optimization results by optimizing the propulsion shafting multi-objectives based on the TOPSIS method and MADM approach

Crucial Role of Drosophila Neurexin in Proper Active Zone Apposition to Postsynaptic Densities, Synaptic Growth and Synaptic Transmission

Trans-synaptic adhesion molecules, a family of cell adhesion molecules that mediate the coordinated interactions between pre- and postsynaptic membrane, are thought to mediate target recognition, initiate synapse formation and alignment, maintain the integrity of synapse, and regulate synaptic function during synapse development and remodeling. Among these, neurexins-a family of highly conserved neuron-specific transmembrane proteins have been proposed to act as a key synapse organizer required for synapse formation and neurotransmitter release. However, their in vivo functions remain elusive, particularly due to the complexity and redundancy of mammalian neurexin genes. Here, we report the cloning and characterization of the Drosophila homolog of neurexin genes. In contrast to the presence of 3 neurexin genes in mammals, we found that the Drosophila genome contains a single neurexin gene, which we named Drosophila neurexin (dnrx). In situ hybridization and immunohistochemical analyses revealed that dnrx is expressed in neurons of central nervous system (CNS) and localized to CNS synaptic regions, axons and glutamatergic neuromuscular junctions (NMJs) during development. At larval NMJ, DNRX is concentrated at active zones, but also extends into periactive zones within synaptic boutons. We have obtained null mutations in the single dnrx gene. Using Drosophila NMJs, an excellent in vivo synapse model system, we demonstrate that dnrx loss of function prevents the normal proliferation of synaptic boutons, while dnrx gain of function in neurons has the opposite effect. Synaptic vesicle and active zone component markers are mislocalized along dnrx mutant axons, suggesting that DNRX is required for the proper recruitment and localization of key synaptic components during presynaptic differentiation. Postsynaptically, the distribution of postsynaptic density (PSD) proteins is enlarged. Conspicuously, dnrx null mutants display striking defects in synaptic ultrastructure with the presence of detachments between pre- and postsynaptic membranes, abnormally long active zones, and increased number of T-bars. These abnormalities result in corresponding alterations in synaptic transmission with reduced neurotransmitter release. Together, our results provide compelling evidence for an in vivo role of neurexins in the control of synapse growth, the modulation of synaptic architecture and adhesive interactions between pre- and postsynaptic compartments in vivo

Exploring Explanation Effects on the Usage of Artificial Intelligence in Recruitment: Human Resources Professionals\u27 Perspective

Artificial intelligence (AI) is increasingly used in recruitment for its data handling and decision consistency, but human resources professionals (HRPs) remain skeptical about predictive accuracy and potential biases (e.g., only hiring males), influencing the justice of AI’s decision. Meanwhile, such advanced capabilities of AI may make HRPs worry that AI could replace their roles and threaten their identity. To address such concerns and improve the acceptance of AI, it is essential to increase the explainability of the AI. Thus, we propose classifying AI explanations into input, process, and output. Our study will determine the effect of explanation on HRPs’ reliance of AI and will explore how organizational justice and threat to identity influence HRPs’ reliance on AI usage. This research aims to clarify the psychological mechanisms affecting AI acceptance in hiring, contributing to the human-machine interaction and HR management literature

A Bayesian Network-Based Framework for Personalization in Mobile Commerce Applications

Providing personalized services for mobile commerce (m-commerce) can improve user satisfaction and merchant profits, which are important to the success of m-commerce. This paper proposes a Bayesian network (BN)-based framework for personalization in m-commerce applications. The framework helps to identify the target mobile users and to deliver relevant information to them at the right time and in the right way. Under the framework, a personalization model is generated using a new method and the model is implemented in an m-commerce application for the food industry. The new method is based on function dependencies of a relational database and rough set operations. The framework can be applied to other industries such as movies, CDs, books, hotel booking, flight booking, and all manner of shopping settings

Holospectrum analysis for bearing cage behaviour

In this paper, the holospectrum is introduced to analyse bearing cage behaviour. Through data fusion on radial vibration displacements, one type of frequency domain analysis, holospectrum, is applied to reflect the detailed characteristics of cage dynamic behaviour. Several typical bearing cage running conditions, such as unbalance, misalignment, impact and friction, are discussed in the investigation, and the corresponding characteristics in the holospectrum are identified. The holospectrum has intuitive and understandable characteristics for the analysis of cage whirling motion. The experimental results show that the holospectrum analysis has the potential to deeply assess bearing cage behaviour