Applications of Magnetic Microbubbles for Theranostics

Compared with other diagnostic methods, ultrasound is proven to be a safe, simple, non-invasive and cost-effective imaging technique, but the resolution is not comparable to that of magnetic resonance imaging (MRI). Contrast-enhanced ultrasound employing microbubbles can gain a better resolution and is now widely used to diagnose a number of diseases in the clinic. For the last decade, microbubbles have been widely used as ultrasound contrast agents, drug delivery systems and nucleic acid transfection tools. However, microbubbles are not fairly stable enough in some conditions and are not well administrated distributed in the circulation system. On the other hand, magnetic nanoparticles, as MRI contrast agents, can non-specifically penetrate into normal tissues because of their relatively small sizes. By taking advantage of these two kinds of agents, the magnetic microbubbles which couple magnetic iron oxides nanoparticles in the microbubble structure have been explored. The stability of microbubbles can be raised by encapsulating magnetic nanoparticles into the bubble shells and with the guidance of magnetic field, magnetic microbubbles can be delivered to regions of interest, and after appropriate ultrasound exposure, the nanoparticles can be released to the desired area while the magnetic microbubbles collapse. In this review, we summarize magnetic microbubbles used in diagnostic and therapeutic fields, and predict the potential applications of magnetic microbubbles in the future

Chemical Abundances of Planetary Nebulae in the Substructures of M31

We present deep spectroscopy of planetary nebulae (PNe) that are associated with the substructures of the Andromeda Galaxy (M31). The spectra were obtained with the OSIRIS spectrograph on the 10.4 m GTC. Seven targets were selected for the observations, three in the Northern Spur and four associated with the Giant Stream. The most distant target in our sample, with a rectified galactocentric distance >100 kpc, was the first PN discovered in the outer streams of M31. The [O III] 4363 auroral line was well detected in the spectra of all targets, enabling electron temperature determination. Ionic abundances are derived based on the [O III] temperatures, and elemental abundances of helium, nitrogen, oxygen, neon, sulfur, and argon are estimated. The relatively low N/O and He/H ratios as well as abundance ratios of alpha-elements indicate that our target PNe might belong to populations as old as ~2 Gyr. Our PN sample, including the current seven and the previous three observed by Fang et al., have rather homogeneous oxygen abundances. The study of abundances and the spatial and kinematical properties of our sample leads to the tempting conclusion that their progenitors might belong to the same stellar population, which hints at a possibility that the Northern Spur and the Giant Stream have the same origin. This may be explained by the stellar orbit proposed by Merrett et al. Judging from the position and kinematics, we emphasize that M32 might be responsible for the two substructures. Deep spectroscopy of PNe in M32 will help to assess this hypothesis.Comment: Accepted for publication in the ApJ. 23 pages, including 13 figures and 7 table

Application of Fast Deviation Correction Algorithm Based on Shape Matching Algorithm in Component Placement

For contradiction PC template matching between accuracy and speed, combined with the advantages of FPGA high speed parallel computing. This paper presents a FPGA-based rapid correction shape matching algorithm. Mainly in the FPGA, using shape matching and least squares method to calculate the angular deviation chip components. Use single instruction stream algorithm acceleration. Experimental results show that compared with traditional PC template matching algorithms, this algorithm to further improve the correction accuracy and greatly reducing correction time. And SMT machine vision correction can be obtained in a stable and efficient use

A Finite Element Mesh Aggregating Approach to Multiple-Source Reconstruction in Bioluminescence Tomography

A finite element mesh aggregating approach is presented to reconstruct images of multiple internal bioluminescence sources. Rather than assuming independence between mesh nodes, the proposed reconstruction strategy exploits spatial structure of nodes and aggregation feature of density distribution on the finite element mesh to adaptively determine the number of sources and to improve the quality of reconstructed images. With the proposed strategy integrated in the regularization-based reconstruction process, reconstruction algorithms need no a priori knowledge of source number; even more importantly, they can automatically reconstruct multiple sources that differ greatly in density or power

ReRoGCRL: Representation-based Robustness in Goal-Conditioned Reinforcement Learning

While Goal-Conditioned Reinforcement Learning (GCRL) has gained attention, its algorithmic robustness against adversarial perturbations remains unexplored. The attacks and robust representation training methods that are designed for traditional RL become less effective when applied to GCRL. To address this challenge, we first propose the Semi-Contrastive Representation attack, a novel approach inspired by the adversarial contrastive attack. Unlike existing attacks in RL, it only necessitates information from the policy function and can be seamlessly implemented during deployment. Then, to mitigate the vulnerability of existing GCRL algorithms, we introduce Adversarial Representation Tactics, which combines Semi-Contrastive Adversarial Augmentation with Sensitivity-Aware Regularizer to improve the adversarial robustness of the underlying RL agent against various types of perturbations. Extensive experiments validate the superior performance of our attack and defence methods across multiple state-of-the-art GCRL algorithms. Our tool ReRoGCRL is available at https://github.com/TrustAI/ReRoGCRL.Comment: This paper has been accepted in AAAI24 (https://aaai.org/aaai-conference/