The effects of timbre on neural responses to musical emotion

Timbre is an important factor that affects the perception of emotion in music. To date, little is known about the effects of timbre on neural responses to musical emotion. To address this issue, we used ERPs to investigate whether there are different neural responses to musical emotion when the same melodies are presented in different timbres. With a cross-modal affective priming paradigm, target faces were primed by affectively congruent or incongruent melodies without lyrics presented in violin, flute, and the voice. Results showed a larger P3 and a larger left anterior distributed LPC in response to affectively incongruent versus congruent trials in the voice version. For the flute version, however, only the LPC effect was found, which was distributed over centro-parietal electrodes. Unlike the voice and flute versions, an N400 effect was observed in the violin version. These findings revealed different patterns of neural responses to emotional processing of music when the same melodies were presented in different timbres, and provide evidence to confirm the hypothesis that there are specialized neural responses to the human voice

Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display

ITM(inverse tone-mapping) converts SDR (standard dynamic range) footage to HDR/WCG (high dynamic range /wide color gamut) for media production. It happens not only when remastering legacy SDR footage in front-end content provider, but also adapting on-theair SDR service on user-end HDR display. The latter requires more efficiency, thus the pre-calculated LUT (look-up table) has become a popular solution. Yet, conventional fixed LUT lacks adaptability, so we learn from research community and combine it with AI. Meanwhile, higher-bit-depth HDR/WCG requires larger LUT than SDR, so we consult traditional ITM for an efficiency-performance trade-off: We use 3 smaller LUTs, each has a non-uniform packing (precision) respectively denser in dark, middle and bright luma range. In this case, their results will have less error only in their own range, so we use a contribution map to combine their best parts to final result. With the guidance of this map, the elements (content) of 3 LUTs will also be redistributed during training. We conduct ablation studies to verify method's effectiveness, and subjective and objective experiments to show its practicability. Code is available at: https://github.com/AndreGuo/ITMLUT.Comment: Accepted in CVMP2023 (the 20th ACM SIGGRAPH European Conference on Visual Media Production

Trajectory similarity learning with auxiliary supervision and optimal matching

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EyelashNet: A Dataset and A Baseline Method for Eyelash Matting

Eyelashes play a crucial part in the human facial structure and largely affect the facial attractiveness in modern cosmetic design. However, the appearance and structure of eyelashes can easily induce severe artifacts in high-fidelity multi-view 3D face reconstruction. Unfortunately it is highly challenging to remove eyelashes from portrait images using both traditional and learning-based matting methods due to the delicate nature of eyelashes and the lack of eyelash matting dataset. To this end, we present EyelashNet, the first eyelash matting dataset which contains 5,400 high-quality eyelash matting data captured from real world and 5,272 virtual eyelash matting data created by rendering avatars. Our work consists of a capture stage and an inference stage to automatically capture and annotate eyelashes instead of tedious manual efforts. The capture is based on a specifically-designed fluorescent labeling system. By coloring the eyelashes with a safe and invisible fluorescent substance, our system takes paired photos with colored and normal eyelashes by turning the equipped ultraviolet (UVA) flash on and off. We further correct the alignment between each pair of photos and use a novel alpha matte inference network to extract the eyelash alpha matte. As there is no prior eyelash dataset, we propose a progressive training strategy that progressively fuses captured eyelash data with virtual eyelash data to learn the latent semantics of real eyelashes. As a result, our method can accurately extract eyelash alpha mattes from fuzzy and self-shadow regions such as pupils, which is almost impossible by manual annotations. To validate the advantage of EyelashNet, we present a baseline method based on deep learning that achieves state-of-the-art eyelash matting performance with RGB portrait images as input. We also demonstrate that our work can largely benefit important real applications including high-fidelity personalized avatar and cosmetic design

Extracellular RNA in melanoma: Advances, challenges, and opportunities

Melanoma, a malignant mass lesion that originates in melanocytes and has a high rate of malignancy, metastasis, and mortality, is defined by these characteristics. Malignant melanoma is a kind of highly malignant tumor that produces melanin and has a high mortality rate. Its incidence accounts for 1%–3% of all malignant tumors and shows an obvious upward trend. The discovery of biomolecules for the diagnosis and treatment of malignant melanoma has important application value. So far, the exact molecular mechanism of melanoma development relevant signal pathway still remains unclear. According to previous studies, extracellular RNAs (exRNAs) have been implicated in tumorigenesis and spread of melanoma. They can influence the proliferation, invasion and metastasis of melanoma by controlling the expression of target genes and can also influence tumor progression by participating in signal transduction mechanisms. Therefore, understanding the relationship between exRNA and malignant melanoma and targeting therapy is of positive significance for its prevention and treatment. In this review, we did an analysis of extracellular vesicles of melanoma which focused on the role of exRNAs (lncRNAs, miRNAs, and mRNAs) and identifies several potential therapeutic targets. In addition, we discuss the typical signaling pathways involved in exRNAs, advances in exRNA detection and how they affect the tumor immune microenvironment in melanoma

A Drive to Driven Model of Mapping Intraspecific Interaction Networks.

Community ecology theory suggests that an individual\u27s phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities

Prediction of Ground Surface Settlements Induced by EPB Shield Tunneling in Water-Rich Soft Strata

The main goal of this study is to enhance the prediction of ground surface settlements induced by Earth pressure balance (EPB) shield tunneling. In the setting of Changzhou, China, a comprehensive database of long-term ground-displacement findings from Metro Lines No. 1 and No. 2 was analyzed with the goal of assessing the parameters characterizing the settlement, i.e., volume loss, trough width parameter. For the metro lines in the water-rich soft strata of Changzhou, the ground loss Vl is usually in the range of 0.1–0.75%, and the trough width parameter K is usually in the range from 0.3 to 0.7. A superposition analytical method is proposed to estimate the short-term ground settlements induced by shield tunneling, with attention given to ground loss as well as shield working loads. The suggested analytical approach was found to be in good agreement with the field measurements in the case of EPB shield tunneling. This study can provide a reliable assessment of the long-term as well as short-term ground surface settlements for tunnel design

Prediction of Ground Surface Settlements Induced by EPB Shield Tunneling in Water-Rich Soft Strata

The main goal of this study is to enhance the prediction of ground surface settlements induced by Earth pressure balance (EPB) shield tunneling. In the setting of Changzhou, China, a comprehensive database of long-term ground-displacement findings from Metro Lines No. 1 and No. 2 was analyzed with the goal of assessing the parameters characterizing the settlement, i.e., volume loss, trough width parameter. For the metro lines in the water-rich soft strata of Changzhou, the ground loss Vl is usually in the range of 0.1–0.75%, and the trough width parameter K is usually in the range from 0.3 to 0.7. A superposition analytical method is proposed to estimate the short-term ground settlements induced by shield tunneling, with attention given to ground loss as well as shield working loads. The suggested analytical approach was found to be in good agreement with the field measurements in the case of EPB shield tunneling. This study can provide a reliable assessment of the long-term as well as short-term ground surface settlements for tunnel design