Class-level Structural Relation Modelling and Smoothing for Visual Representation Learning

Representation learning for images has been advanced by recent progress in more complex neural models such as the Vision Transformers and new learning theories such as the structural causal models. However, these models mainly rely on the classification loss to implicitly regularize the class-level data distributions, and they may face difficulties when handling classes with diverse visual patterns. We argue that the incorporation of the structural information between data samples may improve this situation. To achieve this goal, this paper presents a framework termed \textbf{C}lass-level Structural Relation Modeling and Smoothing for Visual Representation Learning (CSRMS), which includes the Class-level Relation Modelling, Class-aware Graph Sampling, and Relational Graph-Guided Representation Learning modules to model a relational graph of the entire dataset and perform class-aware smoothing and regularization operations to alleviate the issue of intra-class visual diversity and inter-class similarity. Specifically, the Class-level Relation Modelling module uses a clustering algorithm to learn the data distributions in the feature space and identify three types of class-level sample relations for the training set; Class-aware Graph Sampling module extends typical training batch construction process with three strategies to sample dataset-level sub-graphs; and Relational Graph-Guided Representation Learning module employs a graph convolution network with knowledge-guided smoothing operations to ease the projection from different visual patterns to the same class. Experiments demonstrate the effectiveness of structured knowledge modelling for enhanced representation learning and show that CSRMS can be incorporated with any state-of-the-art visual representation learning models for performance gains. The source codes and demos have been released at https://github.com/czt117/CSRMS

Smoking patterns and sociodemographic factors associated with tobacco use among Chinese rural male residents: a descriptive analysis

<p>Abstract</p> <p>Background</p> <p>Although evidence has shown high prevalence rates of tobacco use in the general urban populations in China, relatively little is known in its rural population. The purposes of this study were to examine smoking patterns and sociodemographic correlates of smoking in a sample of rural Chinese male residents.</p> <p>Methods</p> <p>The study employed a cross-sectional, multi-stage sampling design. Residents (N = 4,414; aged 15 years and older) were recruited from four geographic regions in China. Information on participants' tobacco use (of all forms), including their daily use, and sociodemographic characteristics were collected via survey questionnaires and the resultant data were analyzed using chi-square tests and logistic regression procedures.</p> <p>Results</p> <p>The overall smoking prevalence in the study sample was 66.8% (n = 2,950). Of these, the average use of tobacco products per day was 12.70 (SD = 7.99) and over 60% reported daily smoking of more than 10 cigarettes. Geographic regions of the study areas, age of the participants, marital status, ethnicity, education, occupation, and average personal annual income were found to be significantly associated with an increased likelihood of smoking among rural Chinese male residents.</p> <p>Conclusion</p> <p>There is a high smoking prevalence in the Chinese rural population and smoking behaviors are associated with important sociodemographic factors. Findings suggest the need for tobacco control and intervention policies aimed at reducing tobacco use in Chinese rural smoking populations.</p

Enhanced Photocatalytic Performance and Mechanism of Au@CaTiO₃ Composites with Au Nanoparticles Assembled on CaTiO₃ Nanocuboids

Using P25 as the titanium source and based on a hydrothermal route, we have synthesized CaTiO3 nanocuboids (NCs) with the width of 0.3–0.5 μm and length of 0.8–1.1 μm, and systematically investigated their growth process. Au nanoparticles (NPs) of 3–7 nm in size were assembled on the surface of CaTiO3 NCs via a photocatalytic reduction method to achieve excellent Au@CaTiO3 composite photocatalysts. Various techniques were used to characterize the as-prepared samples, including X-ray powder diffraction (XRD), scanning/transmission electron microscopy (SEM/TEM), diffuse reflectance spectroscopy (UV-vis DRS), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Rhodamine B (RhB) in aqueous solution was chosen as the model pollutant to assess the photocatalytic performance of the samples separately under simulated-sunlight, ultraviolet (UV) and visible-light irradiation. Under irradiation of all kinds of light sources, the Au@CaTiO3 composites, particularly the 4.3%Au@CaTiO3 composite, exhibit greatly enhanced photocatalytic performance when compared with bare CaTiO3 NCs. The main roles of Au NPs in the enhanced photocatalytic mechanism of the Au@CaTiO3 composites manifest in the following aspects: (1) Au NPs act as excellent electron sinks to capture the photoexcited electrons in CaTiO3, thus leading to an efficient separation of photoexcited electron/hole pairs in CaTiO3; (2) the electromagnetic field caused by localized surface plasmon resonance (LSPR) of Au NPs could facilitate the generation and separation of electron/hole pairs in CaTiO3; and (3) the LSPR-induced electrons in Au NPs could take part in the photocatalytic reactions

Emissions of Airport Monitoring with Solar Occultation Flux-Fourier Transform Infrared Spectrometer

Both domestic and international aviation industries have experienced a boom, which results in a dramatic increase in emissions of the aviation industry in recent decades. Therefore, domestic and abroad scientists adopted different methods to measure emissions; however, there are no appropriate methods to measure the emissions of the whole airport. In order to provide data support for the relevant departments to take appropriate emission reduction measures, solar occultation flux-Fourier transform infrared spectrometer (SOF-FT-IR) is used to monitor the emissions of Beijing Capital International Airport. CO, CO2, C2H4, and CH2O are selected as the target gases and are quantitatively analyzed with the nonlinear least squares method to get the column concentration. Then, the flux can also be calculated by linking the wind velocity and direction with the column concentration. A comparison between the results measured by SOF-FT-IR and the results measured by the method published by the Intergovernmental Panel on Climate Change (IPCC) indicates that auxiliary power equipment and ground support equipment for the emission of the airport are also important emission sources besides the aircraft and the concentration distribution gives powerful and useful pieces of evidence to locate the emission sources. In order to decrease the contribution of the airport to the air pollution, the key point is to reduce the emissions of the APU and mobiles in the airport

sj-docx-1-asp-10.1177_00037028231183017 - Supplemental material for Parameter Estimation in Spectral Resolution Enhancement Based on Forward–Backward Linear Prediction Total Least Square Method

Supplemental material, sj-docx-1-asp-10.1177_00037028231183017 for Parameter Estimation in Spectral Resolution Enhancement Based on Forward–Backward Linear Prediction Total Least Square Method by Yusheng Qin, Xin Han, Xiangxian Li, Jingjing Tong and Minguang Gao in Applied Spectroscopy</p

Real-time monitoring of nucleic acid ligation in homogenous solutions using molecular beacons

Nucleic acids ligation is a vital process in the repair, replication and recombination of nucleic acids. Traditionally, it is assayed by denatured gel electrophoresis and autoradiography, which are not sensitive, and are complex and discontinuous. Here we report a new approach for ligation monitoring using molecular beacon DNA probes. The molecular beacon, designed in such a way that its sequence is complementary with the product of the ligation process, is used to monitor the nucleic acid ligation in a homogeneous solution and in real-time. Our method is fast and simple. We are able to study nucleic acids ligation kinetics conveniently and to determine the activity of DNA ligase accurately. We have studied different factors that influence DNA ligation catalyzed by T4 DNA ligase. The major advantages of our method are its ultrasensitivity, excellent specificity, convenience and real-time monitoring in homogeneous solution. This method will be widely useful for studying nucleic acids ligation process and other nucleic acid interactions

MEX3C interacts with adaptor-related protein complex 2 and involves in miR-451a exosomal sorting

<div><p>Some RNA species, especially microRNAs, are non-randomly sorted into exosomes, but how selectivity of RNA exosomal sorting is achieved is unknown. We found that all three variants of RNA-binding ubiquitin E3 ligase (MEX3C)–MEX3C-1, MEX3C-2, and MEX3C-3 –interact with adaptor-related protein complex 2 (AP-2), a cargo adaptor in clathrin-mediated endocytosis. MEX3C’s C-terminal RING finger domain and the hnRNP K homology (KH) domain shared by the three MEX3C variants are both necessary for MEX3C/AP-2 interaction. MEX3C associates with the endolysosomal compartment through an endocytosis-like process. siRNA-mediated inhibition of the MEX3C or AP-2 complex substantially decreased exosomal but not cellular microRNA miR-451a expression. Exosomal sorting is ceramide-dependent but not ESCRT-dependent in microRNA miR-451a. That RNA-binding protein associates with membrane trafficking machinery, and that its involvement in exosomal microRNA expression, suggest the existence of a mechanism for specific recruiting of RNA molecules to endosomes for subsequent exosomal sorting.</p></div

Engineering the Activity of Old Yellow Enzyme NemR-PS for Efficient Reduction of (<i>E</i>/<i>Z</i>)-Citral to (<i>S</i>)-Citronellol

The cascade catalysis of old yellow enzyme, alcohol dehydrogenase and glucose dehydrogenase has become a promising approach for one pot, two-step reduction of (E/Z)-citral to (S)-citronellol, serving as a chiral alcohol with rose fragrance. During the multi-enzymatic cascade catalysis, old yellow enzyme is responsible for the reduction of the conjugated C=C and the introduction of the chiral center, requiring high activity and (S)-enantioselectiviy. Herein, to improve the activity of the old yellow enzyme from Providencia stuartii (NemR-PS) with strict (S)-enantioselectivity, the semi-rational design on its substrate binding pocket was performed through a combination of homology modeling, molecular docking analysis, alanine scanning and iterative saturation mutagenesis. The NemR-PS variant D275G/F351A with improved activity was obtained and then purified for characterization, obeying the substrate inhibition kinetics. Compared with the wild type, the parameters Ki and Kcat/Km were increased from 39.79 mM and 2.09 s−1mM−1 to 128.50 mM and 5.01 s−1mM−1, respectively. Moreover, the variant D275G/F351A maintained strict (S)-enantioselectivity, avoiding the trade-off effect between activity and enantioselectivity. Either the enzyme NemR-PS or the variant D275G/F351A was co-expressed with alcohol dehydrogenase from Yokenella sp. WZY002 (YsADH) and glucose dehydrogenase from Bacillus megaterium (BmGDHM6). In contrast to the whole-cell biocatalyst co-expressing NemR-PS, that co-expressing the variant D275G/F351A shortened the reaction time from 36 h to 12 h in the reduction of 400 mM (E/Z)-citral. In the manner of substrate constant feeding, the accumulated product concentration reached up to 500 mM and completely eliminate the residual intermediate and by-product, suggesting the effectiveness of protein engineering and substrate engineering to improve catalytic efficiency