Equivariant Hypergraph Diffusion Neural Operators

Hypergraph neural networks (HNNs) using neural networks to encode hypergraphs provide a promising way to model higher-order relations in data and further solve relevant prediction tasks built upon such higher-order relations. However, higher-order relations in practice contain complex patterns and are often highly irregular. So, it is often challenging to design an HNN that suffices to express those relations while keeping computational efficiency. Inspired by hypergraph diffusion algorithms, this work proposes a new HNN architecture named ED-HNN, which provably represents any continuous equivariant hypergraph diffusion operators that can model a wide range of higher-order relations. ED-HNN can be implemented efficiently by combining star expansions of hypergraphs with standard message passing neural networks. ED-HNN further shows great superiority in processing heterophilic hypergraphs and constructing deep models. We evaluate ED-HNN for node classification on nine real-world hypergraph datasets. ED-HNN uniformly outperforms the best baselines over these nine datasets and achieves more than 2\%$\uparrow$ in prediction accuracy over four datasets therein.Comment: Code: https://github.com/Graph-COM/ED-HN

Saturated Linkers in Two-Dimensional Covalent Organic Frameworks Boost Their Luminescence

The development of highly luminescent two-dimensional covalent organic frameworks (COFs) for sensing applications remains challenging. To suppress commonly observed photoluminescence quenching of COFs, we propose a strategy involving interrupting the intralayer conjugation and interlayer interactions using cyclohexane as the linker unit. By variation of the building block structures, imine-bonded COFs with various topologies and porosities are obtained. Experimental and theoretical analyses of these COFs disclose high crystallinity and large interlayer distances, demonstrating enhanced emission with record-high photoluminescence quantum yields of up to 57% in the solid state. The resulting cyclohexane-linked COF also exhibits excellent sensing performance for the trace recognition of Fe3+ ions, explosive and toxic picric acid, and phenyl glyoxylic acid as metabolites. These findings inspire a facile and general strategy to develop highly emissive imine-bonded COFs for detecting various molecules.journal articl

Predictive model for diabetic retinopathy under limited medical resources: A multicenter diagnostic study

BackgroundComprehensive eye examinations for diabetic retinopathy is poorly implemented in medically underserved areas. There is a critical need for a widely available and economical tool to aid patient selection for priority retinal screening. We investigated the possibility of a predictive model for retinopathy identification using simple parameters.MethodsClinical data were retrospectively collected from 4, 159 patients with diabetes admitted to five tertiary hospitals. Independent predictors were identified by univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and a nomogram was developed based on a multivariate logistic regression model. The validity and clinical practicality of this nomogram were assessed using concordance index (C-index), area under the receiver operating characteristic curve (AUROC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).ResultsThe predictive factors in the multivariate model included the duration of diabetes, history of hypertension, and cardiovascular disease. The three-variable model displayed medium prediction ability with an AUROC of 0.722 (95%CI 0.696-0.748) in the training set, 0.715 (95%CI 0.670-0.754) in the internal set, and 0.703 (95%CI 0.552-0.853) in the external dataset. DCA showed that the threshold probability of DR in diabetic patients was 17-55% according to the nomogram, and CIC also showed that the nomogram could be applied clinically if the risk threshold exceeded 30%. An operation interface on a webpage (https://cqmuxss.shinyapps.io/dr_tjj/) was built to improve the clinical utility of the nomogram.ConclusionsThe predictive model developed based on a minimal amount of clinical data available to diabetic patients with restricted medical resources could help primary healthcare practitioners promptly identify potential retinopathy

Soil Salt Distribution and Tomato Response to Saline Water Irrigation under Straw Mulching.

To investigate better saline water irrigation scheme for tomatoes that scheduling with the compromise among yield (Yt), quality, irrigation water use efficiency (IWUE) and soil salt residual, an experiment with three irrigation quotas and three salinities of irrigation water was conducted under straw mulching in northern China. The irrigation quota levels were 280 mm (W1), 320 mm (W2) and 360 mm (W3), and the salinity levels were 1.0 dS/m (F), 3.0 dS/m (S1) and 5.0 dS/m (S2). Compared to freshwater, saline water irrigations decreased the maximum leaf area index (LAIm) of tomatoes, and the LAIm presented a decline tendency with higher salinity and lower irrigation quota. The best overall quality of tomato was obtained by S2W1, with the comprehensive quality index of 3.61. A higher salinity and lower irrigation quota resulted in a decrease of individual fruit weight and an increase of the blossom-end rot incidence, finally led to a reduction in the tomato Yt and marketable yield (Ym). After one growth season of tomato, the mass fraction of soil salt in plough layer under S2W1 treatment was the highest, and which presented a decline trend with an increasing irrigation quota. Moreover, compared to W1, soil salts had a tendency to move to the deeper soil layer when using W2 and W3 irrigation quota. According to the calculation results of projection pursuit model, S1W3 was the optimal treatment that possessed the best comprehensive benefit (tomato overall quality, Yt, Ym, IWUE and soil salt residual), and was recommended as the saline water irrigation scheme for tomatoes in northern China

Fault diagnosis for temperature, flow rate and pressure sensors in VAV systems using wavelet neural network

Wavelet neural network, the integration of wavelet analysis and neural network, is presented to diagnose the faults of sensors including temperature, flow rate and pressure in variable air volume (VAV) systems to ensure well capacity of energy conservation. Wavelet analysis is used to process the original data collected from the building automation first. With three-level wavelet decomposition, the series of characteristic information representing various operation conditions of the system are obtained. In addition, neural network is developed to diagnose the source of the fault. To improve the diagnosis efficiency, three data groups based on several physical models or balances are classified and constructed. Using the data decomposed by three-level wavelet, the neural network can be well trained and series of convergent networks are obtained. Finally, the new measurements to diagnose are similarly processed by wavelet. And the well-trained convergent neural networks are used to identify the operation condition and isolate the source of the fault.Wavelet analysis Neural network Fault diagnosis Sensor Variable air volume

Comparison of anther and microspore culture in androgenic embryogenesis and regeneration of broccoli (Brassica oleracea L. var. italica P.)

The aim of this study was to compare the efficiency of broccoli anther and microspore culture methods for doubled haploid (DH) lines production. We evaluated the main influencing factors and optimized the culture methods to improve embryo induction and plant regeneration for efficient doubled haploid production in broccoli breeding. Six broccoli hybrids were used in this study. Our results show that generally, the efficiency of androgenic embryogenesis and regeneration in microspore culture is higher than that in the anther culture. Moreover, the microspore culture eliminated the possibility of plantlets coming from diploid tissue. In this study, the four-day cold pre-treatment yielded the highest number of embryos in both anther and microspore culture methods; the embryo yield at 32.5°C for 24 h was the highest in anther and microspore culture. Optimal plating densities were 30 anthers per dish in anther culture and 4×105 microspores per ml in microspore culture. In androgenic embryo production, the PG-96 medium proved to be more effective than NLN medium. Sucrose concentration at 10% for anther culture and 13% (w/v) for microspore culture was recommended. A total of 70 regenerants were obtained from three genotypes including doubled haploids, haploids and aneuploids.Keywords: Anther, broccoli, doubled haploid, microspore, plant regeneratio

A Fast and Robust Key Frame Extraction Method for Video Copyright Protection

The paper proposes a key frame extraction method for video copyright protection. The fast and robust method is based on frame difference with low level features, including color feature and structure feature. A two-stage method is used to extract accurate key frames to cover the content for the whole video sequence. Firstly, an alternative sequence is got based on color characteristic difference between adjacent frames from original sequence. Secondly, by analyzing structural characteristic difference between adjacent frames from the alternative sequence, the final key frame sequence is obtained. And then, an optimization step is added based on the number of final key frames in order to ensure the effectiveness of key frame extraction. Compared with the previous methods, the proposed method has advantage in computation complexity and robustness on several video formats, video resolution, and so on