Affective Music Information Retrieval

Much of the appeal of music lies in its power to convey emotions/moods and to evoke them in listeners. In consequence, the past decade witnessed a growing interest in modeling emotions from musical signals in the music information retrieval (MIR) community. In this article, we present a novel generative approach to music emotion modeling, with a specific focus on the valence-arousal (VA) dimension model of emotion. The presented generative model, called \emph{acoustic emotion Gaussians} (AEG), better accounts for the subjectivity of emotion perception by the use of probability distributions. Specifically, it learns from the emotion annotations of multiple subjects a Gaussian mixture model in the VA space with prior constraints on the corresponding acoustic features of the training music pieces. Such a computational framework is technically sound, capable of learning in an online fashion, and thus applicable to a variety of applications, including user-independent (general) and user-dependent (personalized) emotion recognition and emotion-based music retrieval. We report evaluations of the aforementioned applications of AEG on a larger-scale emotion-annotated corpora, AMG1608, to demonstrate the effectiveness of AEG and to showcase how evaluations are conducted for research on emotion-based MIR. Directions of future work are also discussed.Comment: 40 pages, 18 figures, 5 tables, author versio

Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection

Semi-supervised object detection is crucial for 3D scene understanding, efficiently addressing the limitation of acquiring large-scale 3D bounding box annotations. Existing methods typically employ a teacher-student framework with pseudo-labeling to leverage unlabeled point clouds. However, producing reliable pseudo-labels in a diverse 3D space still remains challenging. In this work, we propose Diffusion-SS3D, a new perspective of enhancing the quality of pseudo-labels via the diffusion model for semi-supervised 3D object detection. Specifically, we include noises to produce corrupted 3D object size and class label distributions, and then utilize the diffusion model as a denoising process to obtain bounding box outputs. Moreover, we integrate the diffusion model into the teacher-student framework, so that the denoised bounding boxes can be used to improve pseudo-label generation, as well as the entire semi-supervised learning process. We conduct experiments on the ScanNet and SUN RGB-D benchmark datasets to demonstrate that our approach achieves state-of-the-art performance against existing methods. We also present extensive analysis to understand how our diffusion model design affects performance in semi-supervised learning.Comment: Accepted in NeurIPS 2023. Code is available at https://github.com/luluho1208/Diffusion-SS3

Dual Associated Encoder for Face Restoration

Restoring facial details from low-quality (LQ) images has remained a challenging problem due to its ill-posedness induced by various degradations in the wild. The existing codebook prior mitigates the ill-posedness by leveraging an autoencoder and learned codebook of high-quality (HQ) features, achieving remarkable quality. However, existing approaches in this paradigm frequently depend on a single encoder pre-trained on HQ data for restoring HQ images, disregarding the domain gap between LQ and HQ images. As a result, the encoding of LQ inputs may be insufficient, resulting in suboptimal performance. To tackle this problem, we propose a novel dual-branch framework named DAEFR. Our method introduces an auxiliary LQ branch that extracts crucial information from the LQ inputs. Additionally, we incorporate association training to promote effective synergy between the two branches, enhancing code prediction and output quality. We evaluate the effectiveness of DAEFR on both synthetic and real-world datasets, demonstrating its superior performance in restoring facial details.Comment: Technical Repor

Potassium {4-[(3S,6S,9S)-3,6-dibenzyl-9-isopropyl-4,7,10-trioxo-11–oxa-2,5,8-triazadodecyl]phenyl}trifluoroborate

[[abstract]]The reported compound 4 was synthesized and fully characterized by 1H NMR, 13C NMR, 11B NMR, 19F NMR, and high resolution mass spectrometry.[[booktype]]電子版[[countrycodes]]CH

Using nomogram of the Barcelona Clinic Liver Cancer system for treatment selection in patients with stage C hepatocellular carcinoma

Abstract Background The nomogram of the Barcelona Clinic Liver Cancer (BCLC) for hepatocellular carcinoma (HCC) has been used for outcome prediction. Patients with BCLC stage C HCC often undergo anti-cancer therapy against current treatment guidelines in real world practice. We aimed to use the nomogram to provide guidance on treatment selection for BCLC stage C patients. Methods A total of 1317 patients with stage C HCC were retrospectively analyzed and divided into four groups by nomogram points. One-to-one matched pairs between patients receiving different treatments were generated by the propensity score with matching model within these groups. Survival analysis was performed by Kaplan-Meier method with log-rank test. Results Patients with higher nomogram points were more often treated with targeted or supportive therapies (p  15, there was no significant difference in survival between patients receiving two different treatment strategies. Conclusions The nomogram of BCLC system is a feasible tool to help stage C HCC patients to select primary anti-cancer treatment in pursuance of better overall survival.https://deepblue.lib.umich.edu/bitstream/2027.42/142787/1/12885_2018_Article_4202.pd

Identifying Chinese Herbal Medicine Network for Endometriosis: Implications from a Population-Based Database in Taiwan

Background. Endometriosis is a common but bothersome gynecological disease, and Chinese herbal medicine (CHM) is used for treating endometriosis. The aim of this study is to explore CHM network and core treatments for endometriosis by analyzing nationwide CHM prescription database. Methods. From 1998 to 2013, the CHM prescriptions made primarily for endometriosis among women diagnosed with endometriosis (ICD-9-CM code: 671) by gynecologists during their reproductive age were collected. CHM network analysis was then carried out by using association rule mining and social network analysis. Results. A total of 12,986 CHM prescriptions made for endometriosis were analyzed. There were 556 kinds of CHM ever used, and, in average, each prescription was composed of 6.2 CHMs. Gui-Zhi-Fu-Ling-Wan (GZFLW) was used most frequently, followed by Cyperus rotundus (28.1% and 18.8% of all prescriptions, resp.). Additionally, the combination of Cyperus rotundus with GZFLW (8.0%) was the most frequently used combination of two CHMs. CHM network showed that GZFLW was the core CHM for endometriosis and graphically demonstrated the extensive coverage of TCM syndromes and pathogenesis of endometriosis. Conclusions. CHM network provides graphical demonstration and summary of commonly used CHMs for endometriosis, and further studies are warranted based on these findings

Case report: Ruptured internal carotid artery fusiform aneurysm mimicking pituitary apoplexy after stereotactic radiosurgery

Pituitary adenomas are benign tumors of the anterior pituitary gland for which surgery or pharmacological treatment is the primary treatment. When initial treatment fails, radiation therapy should be considered. There are several case reports demonstrating radiation-induced vascular injury. We report an adult patient who presented with headache and diplopia for 6 months and a sellar tumor with optic chiasm compression. The patient received transnasal surgery, and the tumor was partially removed, which demonstrated adenoma. Stereotactic radiosurgery (SRS) was arranged. However, owing to progressive tumor growth, the patient received further transnasal surgery and stereotactic radiosurgery (SRS). After 14 years, the patient reported the sudden onset of headache and diplopia, and a ruptured fusiform aneurysm from the left internal carotid artery with pituitary apoplexy was diagnosed. The patient received transarterial embolization of the aneurysm. There were no complications after embolization, and this patient was ambulatory on discharge with blindness in the left eye and cranial nerve palsies. Aneurysm formation may be a complication of SRS, and it may occur after several years. Further research is needed to investigate the pathogenesis of radiosurgery and the development of cerebral aneurysms

REG3A overexpression functions as a negative predictive and prognostic biomarker in rectal cancer patients receiving CCRT

Background. Concurrent chemoradiotherapy (CCRT) is suggested before resection surgery in the control of rectal cancer. Unfortunately, treatment outcomes are widely variable and highly patientspecific. Notably, rectal cancer patients with distant metastasis generally have a much lower survival rate. Accordingly, a better understanding of the genetic background of patient cohorts can aid in predicting CCRT efficacy and clinical outcomes for rectal cancer before distant metastasis. Methods. A published transcriptome dataset (GSE35452) (n=46) was utilized to distinguish prospective genes concerning the response to CCRT. We recruited 172 rectal cancer patients, and the samples were collected during surgical resection after CCRT. Immunohistochemical (IHC) staining was performed to evaluate the expression level of regenerating family member 3 alpha (REG3A). Pearson's chi-squared test appraised the relevance of REG3A protein expression to clinicopathological parameters. The Kaplan-Meier method was utilized to generate survival curves, and the log-rank test was performed to compare the survival distributions between two given groups. Results. Employing a transcriptome dataset (GSE35452) and focusing on the inflammatory response (GO: 0006954), we recognized that REG3A is the most significantly upregulated gene among CCRT nonresponders (log2 ratio=1.2472, p=0.0079). Following IHC validation, high immunoexpression of REG3A was considerably linked to advanced post-CCRT tumor status (p<0.001), post-CCRT lymph node metastasis (p=0.042), vascular invasion (p=0.028), and low-grade tumor regression (p=0.009). In the multivariate analysis, high immunoexpression of REG3A was independently correlated with poor disease-specific survival (DSS) (p=0.004) and metastasis-free survival (MeFS) (p=0.045). The results of the bioinformatic analysis also supported the idea that REG3A overexpression is implicated in rectal carcinogenesis. Conclusion. In the current study, we demonstrated that REG3A overexpression is correlated with poor CCRT effectiveness and inferior patient survival in rectal cancer. The predictive and prognostic utility of REG3A expression may direct patient stratification and decisionmaking more accurately for those patients