LE-SSL-MOS: Self-Supervised Learning MOS Prediction with Listener Enhancement

Recently, researchers have shown an increasing interest in automatically predicting the subjective evaluation for speech synthesis systems. This prediction is a challenging task, especially on the out-of-domain test set. In this paper, we proposed a novel fusion model for MOS prediction that combines supervised and unsupervised approaches. In the supervised aspect, we developed an SSL-based predictor called LE-SSL-MOS. The LE-SSL-MOS utilizes pre-trained self-supervised learning models and further improves prediction accuracy by utilizing the opinion scores of each utterance in the listener enhancement branch. In the unsupervised aspect, two steps are contained: we fine-tuned the unit language model (ULM) using highly intelligible domain data to improve the correlation of an unsupervised metric - SpeechLMScore. Another is that we utilized ASR confidence as a new metric with the help of ensemble learning. To our knowledge, this is the first architecture that fuses supervised and unsupervised methods for MOS prediction. With these approaches, our experimental results on the VoiceMOS Challenge 2023 show that LE-SSL-MOS performs better than the baseline. Our fusion system achieved an absolute improvement of 13% over LE-SSL-MOS on the noisy and enhanced speech track. Our system ranked 1st and 2nd, respectively, in the French speech synthesis track and the challenge's noisy and enhanced speech track.Comment: accepted in IEEE-ASRU202

Towards additive manufacturing oriented geometric modeling using implicit functions

Surface-based geometric modeling has many advantages in terms of visualization and traditional subtractive manufacturing using computer-numerical-control cutting-machine tools. However, it is not an ideal solution for additive manufacturing because to digitally print a surface-represented geometric object using a certain additive manufacturing technology, the object has to be converted into a solid representation. However, converting a known surface-based geometric representation into a printable representation is essentially a redesign process, and this is especially the case, when its interior material structure needs to be considered. To specify a 3D geometric object that is ready to be digitally manufactured, its representation has to be in a certain volumetric form. In this research, we show how some of the difficulties experienced in additive manufacturing can be easily solved by using implicitly represented geometric objects. Like surface-based geometric representation is subtractive manufacturing-friendly, implicitly described geometric objects are additive manufacturing-friendly: implicit shapes are 3D printing ready. The implicit geometric representation allows to combine a geometric shape, material colors, an interior material structure, and other required attributes in one single description as a set of implicit functions, and no conversion is needed. In addition, as implicit objects are typically specified procedurally, very little data is used in their specifications, which makes them particularly useful for design and visualization with modern cloud-based mobile devices, which usually do not have very big storage spaces. Finally, implicit modeling is a design procedure that is parallel computing-friendly, as the design of a complex geometric object can be divided into a set of simple shape-designing tasks, owing to the availability of shape-preserving implicit blending operations

Blocking the formation of radiation–induced breast cancer stem cells

The goal of adjuvant (post-surgery) radiation therapy (RT) for breast cancer (BC) is to eliminate residual cancer cells, leading to better local tumor control and thus improving patient survival. However, radioresistance increases the risk of tumor recurrence and negatively affects survival. Recent evidence shows that breast cancer stem cells (BCSCs) are radiation-resistant and that relatively differentiated BC cells can be reprogrammed into induced BCSCs (iBCSCs) via radiation-induced re-expression of the stemness genes. Here we show that in irradiation (IR)-treated mice bearing syngeneic mammary tumors, IR-induced stemness correlated with increased spontaneous lung metastasis (51.7%). However, IR-induced stemness was blocked by targeting the NF-κB- stemness gene pathway with disulfiram (DSF)and Copper (Cu2+). DSF is an inhibitor of aldehyde dehydrogenase (ALDH) and an FDA-approved drug for treating alcoholism. DSF binds to Cu2+ to form DSF-Cu complexes (DSF/Cu), which act as a potent apoptosis inducer and an effective proteasome inhibitor, which, in turn, inhibits NF-κB activation. Treatment of mice with RT and DSF significantly inhibited mammary primary tumor growth (79.4%) and spontaneous lung metastasis (89.6%) compared to vehicle treated mice. This anti-tumor efficacy was associated with decreased stem cell properties (or stemness) in tumors. We expect that these results will spark clinical investigation of RT and DSF as a novel combinatorial treatment for breast cancer

Precise and Rapid Validation of Candidate Gene by Allele Specific Knockout With CRISPR/Cas9 in Wild Mice

It is a tempting goal to identify causative genes underlying phenotypic differences among inbred strains of mice, which is a huge reservoir of genetic resources to understand mammalian pathophysiology. In particular, the wild-derived mouse strains harbor enormous genetic variations that have been acquired during evolutionary divergence over 100s of 1000s of years. However, validating the genetic variation in non-classical strains was extremely difficult, until the advent of CRISPR/Cas9 genome editing tools. In this study, we first describe a T cell phenotype in both wild-derived PWD/PhJ parental mice and F1 hybrids, from a cross to C57BL/6 (B6) mice, and we isolate a genetic locus on Chr2, using linkage mapping and chromosome substitution mice. Importantly, we validate the identification of the functional gene controlling this T cell phenotype, Cd44, by allele specific knockout of the PWD copy, leaving the B6 copy completely intact. Our experiments using F1 mice with a dominant phenotype, allowed rapid validation of candidate genes by designing sgRNA PAM sequences that only target the DNA of the PWD genome. We obtained 10 animals derived from B6 eggs fertilized with PWD sperm cells which were subjected to microinjection of CRISPR/Cas9 gene targeting machinery. In the newborns of F1 hybrids, 80% (n = 10) had allele specific knockout of the candidate gene Cd44 of PWD origin, and no mice showed mistargeting of the B6 copy. In the resultant allele-specific knockout F1 mice, we observe full recovery of T cell phenotype. Therefore, our study provided a precise and rapid approach to functionally validate genes that could facilitate gene discovery in classic mouse genetics. More importantly, as we succeeded in genetic manipulation of mice, allele specific knockout could provide the possibility to inactivate disease alleles while keeping the normal allele of the gene intact in human cells

Beam test of a 180 nm CMOS Pixel Sensor for the CEPC vertex detector

The proposed Circular Electron Positron Collider (CEPC) imposes new challenges for the vertex detector in terms of pixel size and material budget. A Monolithic Active Pixel Sensor (MAPS) prototype called TaichuPix, based on a column drain readout architecture, has been developed to address the need for high spatial resolution. In order to evaluate the performance of the TaichuPix-3 chips, a beam test was carried out at DESY II TB21 in December 2022. Meanwhile, the Data Acquisition (DAQ) for a muti-plane configuration was tested during the beam test. This work presents the characterization of the TaichuPix-3 chips with two different processes, including cluster size, spatial resolution, and detection efficiency. The analysis results indicate the spatial resolution better than 5 $\mu m$ and the detection efficiency exceeds 99.5 % for both TaichuPix-3 chips with the two different processes

Research and Application of Variable Rate Fertilizer Applicator System Based on a DC Motor

International audienceWith the aim to simplify the electrical component structure of the present variable rate fertilizer applicator system, a kind of variable rate fertilizer applicator control system was developed. It is based on low voltage DC motor. The working voltage of this system is not higher than 12V DC, which can be supplied by the tractor’s storage battery directly. With the encoder measuring the motor speed, it could response the running state of the motor in real time. A kind of control model based on PID algorithm was built. With this model, the influence of load variation on the motor speed could reduce. As a result, the control accuracy of this system could be improved. Field experiment has been conducted using this system. Experiment showed that when the travel speed was 3.60km/h, the maximum fertilizer rate could be 850 kg / hm2. When the fertilizer rate was 200 ~ 600 kg/ hm2, the mean error of this system was 1.71% while the maximum error was 2.56%

Effects of stocking density on growth performance, digestive function and immune performance of Matou goats

The objective of this study was to examine the effects of different stocking densities on Matou goats. Thirty-six female Matou goats were randomly assigned into three experimental treatments including the low density (LD, 0.67 goat/m2), the medium density (MD, 1 goat/m2) and the high density (HD, 2 goats/m2) group. Compared with LD group, the average daily weight gain (ADG) of HD group decreased (p < .05). The length of duodenal and ileal villi in HD group was significantly lower than that in LD group (p < .05). The rumen pH and concentration of total volatile fatty acid (VFA), propionate butyrate and ammonia-nitrogen increased in HD group (p < .05). The acetate/propionate ratio was the highest in MD group (p < .05). The mRNA expression level of agouti-related protein gene (AgRP) in hypothalamus of LD was higher than that in HD group (p < 0.05). Proopiomelanocortin (POMC) mRNA expression level was the highest in MD group (p<.05) and the lowest in HD group (p < .05). An increase in growth hormone receptor (GHR), insulin-like growth factor 1 (IGF1) and claudin-1 mRNA expression level were noticed in HD group (p<.05). Compared with LD group, the serum total protein (TP), albumin (Alb), globulin (Glb) IgA and IgG levels in HD group decreased (p < .05). Glucocorticoid (GCS), β-endorphin (β-EP) and cortisol levels in serum were also significantly increased in HD group compared with LD group (p < .05). These results showed that stocking density affected rumen environment and high stocking density resulted in a decrease in growth, digestive and immune function of Matou goats