Transforming medical equipment management in digital public health: a decision-making model for medical equipment replacement

IntroductionIn the rapidly evolving field of digital public health, effective management of medical equipment is critical to maintaining high standards of healthcare service levels and operational efficiency. However, current decisions to replace large medical equipment are often based on subjective judgments rather than objective analyses and lack a standardized approach. This study proposes a multi-criteria decision-making model that aims to simplify and enhance the medical equipment replacement process.MethodsThe researchers developed a multi-criteria decision-making model specifically for the replacement of medical equipment. The model establishes a system of indicators for prioritizing and evaluating the replacement of large medical equipment, utilizing game theory to assign appropriate weights, which uniquely combines the weights of the COWA and PCA method. In addition, which uses the GRA method in combination with the TOPSIS method for a more comprehensive decision-making model.ResultsThe study validates the model by using the MRI equipment of a tertiary hospital as an example. The results of the study show that the model is effective in prioritizing the most optimal updates to the equipment. Significantly, the model shown a higher level of differentiation compared to the GRA and TOPSIS methods alone.DiscussionThe present study shows that the multi-criteria decision-making model presented provides a powerful and accurate tool for optimizing decisions related to the replacement of large medical equipment. By solving the key challenges in this area as well as giving a solid basis for decision making, the model makes significant progress toward the field of management of medical equipment

Optomechanical effects in nanocavity-enhanced resonant Raman scattering of a single molecule

In this paper, we address the optomechanical effects in surface-enhanced resonant Raman scattering (SERRS) from a single molecule in a nanoparticle on mirror (NPoM) nanocavity by developing a quantum master-equation theory, which combines macroscopic quantum electrodynamics and electron-vibration interaction within the framework of open quantum system theory. We supplement the theory with electromagnetic simulations and time-dependent density functional theory calculations in order to study the SERRS of a methylene blue molecule in a realistic NPoM nanocavity. The simulations allow us not only to identify the conditions to achieve conventional optomechanical effects, such as vibrational pumping, nonlinear scaling of Stokes and anti-Stokes scattering, but also to discovery distinct behaviors, such as the saturation of exciton population, the emergence of Mollow triplet side bands, and higher-order Raman scattering. All in all, our study might guide further investigations of optomechanical effects in resonant Raman scattering.This work is supported by the Projects No. 12004344 and No. 21902148 from the National Nature Science Foundation of China, joint Project No. 21961132023 from the NSFC-DPG, Project No. PID2019-107432GB-I00 from the Spanish Ministry of Science and Innovation, and Grant No. IT1526-22 for consolidated groups of the Basque University, through the Department of Education, Research, and Universities of the Basque Government.Peer reviewe

Natural Coevolution of Tumor and Immunoenvironment in Glioblastoma.

Isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) has a dismal prognosis. A better understanding of tumor evolution holds the key to developing more effective treatment. Here we study GBM\u27s natural evolutionary trajectory by using rare multifocal samples. We sequenced 61,062 single cells from eight multifocal IDH wild-type primary GBMs and defined a natural evolution signature (NES) of the tumor. We show that the NES significantly associates with the activation of transcription factors that regulate brain development, including MYBL2 and FOSL2. Hypoxia is involved in inducing NES transition potentially via activation of the HIF1A-FOSL2 axis. High-NES tumor cells could recruit and polarize bone marrow-derived macrophages through activation of the FOSL2-ANXA1-FPR1/3 axis. These polarized macrophages can efficiently suppress T-cell activity and accelerate NES transition in tumor cells. Moreover, the polarized macrophages could upregulate CCL2 to induce tumor cell migration. SIGNIFICANCE: GBM progression could be induced by hypoxia via the HIF1A-FOSL2 axis. Tumor-derived ANXA1 is associated with recruitment and polarization of bone marrow-derived macrophages to suppress the immunoenvironment. The polarized macrophages promote tumor cell NES transition and migration. This article is highlighted in the In This Issue feature, p. 2711

3D Reconstruction and Measurement Analysis of a Dense Point Cloud Fused with a Depth Image

To solve the problems of holes, noise, and texture information missing in the traditional incremental reconstruction of complex surface objects, a 3D reconstruction method of depth image fusion surface dense point clouds is proposed, and texture feature creation is combined to obtain a 3D reconstruction model that takes into account the main body and details of the reconstructed object. First, the mechanism of surface dense reconstruction based on the patch-based multiview stereo (PMVS) algorithm is analyzed. Combined with the principle of view angle selection of stereo images, surface point cloud density reconstruction is performed. Then, the depth value is optimized by the region growing method, and the optimization model is established. The depth image is fused into a dense surface, and the reconstructed part is supplemented by the depth information. Finally, the Markov random field (MRF) is introduced to describe the richness of image details, and combined with the calculating method of the area coordinate, the texture coordinates are accurately calculated to reproduce the texture details of the 3D reconstruction model. 3D reconstruction experiments are performed on multiple indoor and outdoor model surfaces, and the experimental results show that the proposed method can achieve complete and accurate reconstruction of complex surface objects. Our method provides technical support for complex surface topography detection and has industrial practical significance

Optimal Investment of DC Pension Plan under Incentive Schemes and Loss Aversion

We investigate the DC pension manager’s portfolio problem when the manager is remunerated through two schemes for DC pension managerial compensation under loss aversion and minimum guarantee. We apply the concavification technique and a static Lagrangian technique to solve the problem and derive the closed-form representation of the optimal wealth and portfolio processes. Theoretical and numerical results show that the incentive schemes can significantly impact the distribution of the optimal terminal wealth