Distributed Uncertainty Quantification of Kernel Interpolation on Spheres

For radial basis function (RBF) kernel interpolation of scattered data, Schaback in 1995 proved that the attainable approximation error and the condition number of the underlying interpolation matrix cannot be made small simultaneously. He referred to this finding as an "uncertainty relation", an undesirable consequence of which is that RBF kernel interpolation is susceptible to noisy data. In this paper, we propose and study a distributed interpolation method to manage and quantify the uncertainty brought on by interpolating noisy spherical data of non-negligible magnitude. We also present numerical simulation results showing that our method is practical and robust in terms of handling noisy data from challenging computing environments.Comment: 24 pages,6 figure

CoCoFormer: A controllable feature-rich polyphonic music generation method

This paper explores the modeling method of polyphonic music sequence. Due to the great potential of Transformer models in music generation, controllable music generation is receiving more attention. In the task of polyphonic music, current controllable generation research focuses on controlling the generation of chords, but lacks precise adjustment for the controllable generation of choral music textures. This paper proposed Condition Choir Transformer (CoCoFormer) which controls the output of the model by controlling the chord and rhythm inputs at a fine-grained level. In this paper, the self-supervised method improves the loss function and performs joint training through conditional control input and unconditional input training. In order to alleviate the lack of diversity on generated samples caused by the teacher forcing training, this paper added an adversarial training method. CoCoFormer enhances model performance with explicit and implicit inputs to chords and rhythms. In this paper, the experiments proves that CoCoFormer has reached the current better level than current models. On the premise of specifying the polyphonic music texture, the same melody can also be generated in a variety of ways

Referring Multi-Object Tracking

Existing referring understanding tasks tend to involve the detection of a single text-referred object. In this paper, we propose a new and general referring understanding task, termed referring multi-object tracking (RMOT). Its core idea is to employ a language expression as a semantic cue to guide the prediction of multi-object tracking. To the best of our knowledge, it is the first work to achieve an arbitrary number of referent object predictions in videos. To push forward RMOT, we construct one benchmark with scalable expressions based on KITTI, named Refer-KITTI. Specifically, it provides 18 videos with 818 expressions, and each expression in a video is annotated with an average of 10.7 objects. Further, we develop a transformer-based architecture TransRMOT to tackle the new task in an online manner, which achieves impressive detection performance and outperforms other counterparts. The dataset and code will be available at https://github.com/wudongming97/RMOT.Comment: Accpeted by CVPR 2023. The dataset and code will be available at https://github.com/wudongming97/RMO

Effects of surface modification, carbon nanofiber concentration, and dispersion time on the mechanical properties of carbon-nanofiber–polycarbonate composites

The time effect of ultrasonication was investigated for dispersing carbon nanofibers (CNFs) into a polycarbonate (PC) matrix on the mechanical properties of thus-produced composites. The effects of CNF surface modification by plasma treatment and the CNF concentration in composites on their mechanical properties were also explored. The plasma coating was characterized by HRTEM and FT-IR. Furthermore, the plasma polymerization (10 w) treatment on the CNF enhanced the CNF dispersion in the polymer matrix. The mechanical properties of the CNF–PC composites varied with the dispersion time, at first increasing to a maximum value and then dropping down. After a long ultrasonic treatment (24 h), the properties increased again. At a high concentration, the CNF-PC suspension became difficult to disperse. Additionally, the possible mechanisms for these behaviors are simply proposed. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 3792–3797, 2007Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55871/1/25112_ftp.pd

B serum proteome profiles revealed dysregulated proteins and mechanisms associated with insomnia patients: A preliminary study

BackgroundInsomnia is a clinical problem of significant public health importance; however, the underlying pathogenesis of this disorder is not comprehensively understood.MethodsTo identify potential treatment targets and unfold one of the gaps that were involved in insomnia pathological mechanisms, we employed a tandem mass tag-based (TMT) quantitative proteomics technology to detect differentially expressed proteins (DEPs) in serum from patients with insomnia and controls. DEPs were further analyzed by bioinformatics platforms. In addition, parallel reaction monitoring (PRM) was used to verify the TMT results.ResultsPatients with insomnia had poorer sleep quality compared with healthy controls. A total of 106 DEPs were identified among patients with insomnia and controls. They were mainly enriched in immune and inflammation-related biological functions and signaling pathways. Using the protein–protein interaction network, we screened the 10 most connected proteins as key DEPs. We predicted that four key DEPs were subject to targeted regulation by natural compounds of herbs. Eight key DEPs were validated using PRM in an additional 15 patients with insomnia and 15 controls, and the results also supported the experimental findings.ConclusionWe identified aberrantly expressed proteins in insomnia that may be involved in the immune-inflammatory response. The 10 key DEPs screened may be potential targets for insomnia, especially FN1, EGF, HP, and IGF1. The results of this study will broaden our understanding of the pathological mechanisms of insomnia and provide more possibilities for pharmacotherapy

Hydrodynamic Delivery of Chitosan-Folate-DNA Nanoparticles in Rats with Adjuvant-Induced Arthritis

50 kDa chitosan was conjugated with folate, a specific tissue-targeting ligand. Nanoparticles such as chitosan-DNA and folate-chitosan-DNA were prepared by coacervation process. The hydrodynamic intravenous injection of nanoparticles was performed in the right posterior paw in normal and arthritic rats. Our results demonstrated that the fluorescence intensity of DsRed detected was 5 to 12 times more in the right soleus muscle and in the right gastro muscle than other tissue sections. β-galactosidase gene expression with X-gal substrate and folate-chitosan-plasmid nanoparticles showed best coloration in the soleus muscle. Treated arthritic animals also showed a significant decrease in paw swelling and IL-1β and PGE2 concentration in serum compared to untreated rats. This study demonstrated that a nonviral gene therapeutic approach using hydrodynamic delivery could help transfect more efficiently folate-chitosan-DNA nanoparticles in vitro/in vivo and could decrease inflammation in arthritic rats