Spatio-Temporal AU Relational Graph Representation Learning For Facial Action Units Detection

This paper presents our Facial Action Units (AUs) recognition submission to the fifth Affective Behavior Analysis in-the-wild Competition (ABAW). Our approach consists of three main modules: (i) a pre-trained facial representation encoder which produce a strong facial representation from each input face image in the input sequence; (ii) an AU-specific feature generator that specifically learns a set of AU features from each facial representation; and (iii) a spatio-temporal graph learning module that constructs a spatio-temporal graph representation. This graph representation describes AUs contained in all frames and predicts the occurrence of each AU based on both the modeled spatial information within the corresponding face and the learned temporal dynamics among frames. The experimental results show that our approach outperformed the baseline and the spatio-temporal graph representation learning allows our model to generate the best results among all ablated systems. Our model ranks at the 4th place in the AU recognition track at the 5th ABAW Competition

A New Approach to Extract Fetal Electrocardiogram Using Affine Combination of Adaptive Filters

The detection of abnormal fetal heartbeats during pregnancy is important for monitoring the health conditions of the fetus. While adult ECG has made several advances in modern medicine, noninvasive fetal electrocardiography (FECG) remains a great challenge. In this paper, we introduce a new method based on affine combinations of adaptive filters to extract FECG signals. The affine combination of multiple filters is able to precisely fit the reference signal, and thus obtain more accurate FECGs. We proposed a method to combine the Least Mean Square (LMS) and Recursive Least Squares (RLS) filters. Our approach found that the Combined Recursive Least Squares (CRLS) filter achieves the best performance among all proposed combinations. In addition, we found that CRLS is more advantageous in extracting FECG from abdominal electrocardiograms (AECG) with a small signal-to-noise ratio (SNR). Compared with the state-of-the-art MSF-ANC method, CRLS shows improved performance. The sensitivity, accuracy and F1 score are improved by 3.58%, 2.39% and 1.36%, respectively.Comment: 5 pages, 4 figures, 3 table

ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation

Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional layer with the local receptive field, which makes it difficult to learn global shape information from the limited information provided by scribble annotations. To address this issue, this paper proposes a new CNN-Transformer hybrid solution for scribble-supervised medical image segmentation called ScribFormer. The proposed ScribFormer model has a triple-branch structure, i.e., the hybrid of a CNN branch, a Transformer branch, and an attention-guided class activation map (ACAM) branch. Specifically, the CNN branch collaborates with the Transformer branch to fuse the local features learned from CNN with the global representations obtained from Transformer, which can effectively overcome limitations of existing scribble-supervised segmentation methods. Furthermore, the ACAM branch assists in unifying the shallow convolution features and the deep convolution features to improve model’s performance further. Extensive experiments on two public datasets and one private dataset show that our ScribFormer has superior performance over the state-of-the-art scribble-supervised segmentation methods, and achieves even better results than the fully-supervised segmentation methods. The code is released at https://github.com/HUANGLIZI/ScribFormer

Electroplating lithium transition metal oxides.

Materials synthesis often provides opportunities for innovation. We demonstrate a general low-temperature (260°C) molten salt electrodeposition approach to directly electroplate the important lithium-ion (Li-ion) battery cathode materials LiCoO2, LiMn2O4, and Al-doped LiCoO2. The crystallinities and electrochemical capacities of the electroplated oxides are comparable to those of the powders synthesized at much higher temperatures (700° to 1000°C). This new growth method significantly broadens the scope of battery form factors and functionalities, enabling a variety of highly desirable battery properties, including high energy, high power, and unprecedented electrode flexibility

A cohort study of the efficacy and safety of immune checkpoint inhibitors plus anlotinib versus immune checkpoint inhibitors alone as the treatment of advanced non-small cell lung cancer in the real world

BACKGROUND: Anlotinib is a new multi-target tyrosine kinase inhibitor (TKI) and has been shown to have antitumor effects and synergistic antitumor effects with immunotherapy only in animal studies and in the 2nd-line treatment in small clinical trials. A real-world study with large sample to compare the efficacy and safety of anlotinib plus immune checkpoint inhibitors (ICIs) with ICIs alone in the multiline treatment of advanced non-small cell lung cancer (NSCLC) was urgently needed. METHODS: The data of 535 advanced NSCLC patients were collected from January 1, 2018, to December 31, 2021. The patients were divided into 2 groups: (I) ICI monotherapy (230 patients); (II) ICI + anlotinib (305 patients). After propensity-score matching (PSM) to reduce the effects of biases and confounding variables, the progression-free survival time (PFS), occurrence of adverse events, disease control rate (DCR), and objective response rate (ORR) of the 2 groups were compared. The effects of clinical factors, including age, gender, gene mutations, tumor proportion score, metastases, and combined radiotherapy, were also analyzed. RESULTS: After PSM, the baseline clinical characteristics were well balanced and the 2 group had a good comparability. Patients in the ICI + anlotinib group had significantly longer median PFS in both the 2nd-line treatment (7.73 vs. 4.70 months; P=0.003) and 3rd-line treatment (5.90 vs. 3.37 months; P=0.020), but the difference lacked statistical significance in the 1st-line treatment (8.40 vs. 5.20 months; P=0.229). The overall median PFS of patients in the ICI + anlotinib group was also much longer than that of patients in the ICI monotherapy group (6.37 vs. 3.90 months; P<0.001). The ICI + anlotinib group also tended to have a higher DCR, a higher ORR, and a higher probability of severe adverse drug reactions during the treatment than the ICI monotherapy group, but the differences were not statistically significant. Combining ICI + anlotinib could improve the outcomes of patients with bone metastasis. CONCLUSIONS: Anlotinib + ICI therapy could have greater efficacy in the treatment of advanced NSCLC patients than ICI monotherapy. The probability of adverse events might increase in the combined treatment, but could be controlled

Searching for the nano-Hertz stochastic gravitational wave background with the Chinese Pulsar Timing Array Data Release I

Observing and timing a group of millisecond pulsars (MSPs) with high rotational stability enables the direct detection of gravitational waves (GWs). The GW signals can be identified from the spatial correlations encoded in the times-of-arrival of widely spaced pulsar-pairs. The Chinese Pulsar Timing Array (CPTA) is a collaboration aiming at the direct GW detection with observations carried out using Chinese radio telescopes. This short article serves as a `table of contents' for a forthcoming series of papers related to the CPTA Data Release 1 (CPTA DR1) which uses observations from the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Here, after summarizing the time span and accuracy of CPTA DR1, we report the key results of our statistical inference finding a correlated signal with amplitude \log A_{\rm c}= -14.4 \,^{+1.0}_{-2.8} for spectral index in the range of $\alpha\in [-1.8, 1.5]$ assuming a GW background (GWB) induced quadrupolar correlation. The search for the Hellings-Downs (HD) correlation curve is also presented, where some evidence for the HD correlation has been found that a 4.6-$\sigma$ statistical significance is achieved using the discrete frequency method around the frequency of 14 nHz. We expect that the future International Pulsar Timing Array data analysis and the next CPTA data release will be more sensitive to the nHz GWB, which could verify the current results.Comment: 18 pages, 6 figures, submitted to "Research in astronomy and astrophysics" 22nd March 202

Traditional Chinese medicine residues promote the growth and quality of Salvia miltiorrhiza Bunge by improving soil health under continuous monoculture

Continuous monoculture of crops has resulted in reduced yields and quality, as well as soil deterioration. Although traditional Chinese medicine residues (TCMRs) are known to promote plant growth and soil health, few studies have investigated their effectiveness in continuous monoculture soils. Here, we studied the impact of chemical fertilizers (CF) and four TCMRs with antibacterial activities on the growth of S. miltiorrhiza (a widely used medicinal plant in China), accumulation of active ingredients in plants, and soil health under continuous monoculture conditions. Compared with no fertilizer (CK) and CF, fermented Sophora flavescens radix residue (SFRf) and fermented and unfermented Moutan cortex residue (MCRf and MCRu, respectively) resulted in a reduction of the disease index of root rot, while CF did not. The CF and four TCMR treatments increased the accumulation of nitrogen (N) (42.8-124.6% and 17.0-101.7%), phosphorous (P) (19.8-74.7% and 8.3-27.4%), and potassium (K) (104.1-212.0% and 9.3-51.8%) in shoots and roots compared to CK. The differences in nutrient accumulation between the CF and TCMR treatments were statistically insignificant, excepted for the N accumulation in the roots. All fertilization treatments increased plant biomass compared to CK, with increases of 25.57-89.86% and 2.62-35.28% in shoots and roots, respectively. The SFRf treatment exhibited the most significant enhancement in both shoot and root biomass. CF significantly reduced the accumulation of seven active ingredients in roots by 23.90-78.95% compared to CK, whereas each TCMR increased accumulation of certain active ingredients. The TCMR treatments effectively improved the health of deteriorated soil by enhancing soil physicochemical properties, restoring the balance of the microbial community, recruiting beneficial bacteria, and reducing the relative abundance of the pathogen Fusarium. The SFRf treatment exhibited superior performance in improving soil health than other treatments. Overall, the TCMRs outperformed CF in restoring soil health and promoting the yield and quality of S. miltiorrhiza. These findings offer guidance for improving the health of continuous cropping soil and recycling TCMRs