Correlative Channel-Aware Fusion for Multi-View Time Series Classification

Multi-view time series classification (MVTSC) aims to improve the performance by fusing the distinctive temporal information from multiple views. Existing methods mainly focus on fusing multi-view information at an early stage, e.g., by learning a common feature subspace among multiple views. However, these early fusion methods may not fully exploit the unique temporal patterns of each view in complicated time series. Moreover, the label correlations of multiple views, which are critical to boost-ing, are usually under-explored for the MVTSC problem. To address the aforementioned issues, we propose a Correlative Channel-Aware Fusion (C2AF) network. First, C2AF extracts comprehensive and robust temporal patterns by a two-stream structured encoder for each view, and captures the intra-view and inter-view label correlations with a graph-based correlation matrix. Second, a channel-aware learnable fusion mechanism is implemented through convolutional neural networks to further explore the global correlative patterns. These two steps are trained end-to-end in the proposed C2AF network. Extensive experimental results on three real-world datasets demonstrate the superiority of our approach over the state-of-the-art methods. A detailed ablation study is also provided to show the effectiveness of each model component

Frame Flexible Network

Existing video recognition algorithms always conduct different training pipelines for inputs with different frame numbers, which requires repetitive training operations and multiplying storage costs. If we evaluate the model using other frames which are not used in training, we observe the performance will drop significantly (see Fig.1), which is summarized as Temporal Frequency Deviation phenomenon. To fix this issue, we propose a general framework, named Frame Flexible Network (FFN), which not only enables the model to be evaluated at different frames to adjust its computation, but also reduces the memory costs of storing multiple models significantly. Concretely, FFN integrates several sets of training sequences, involves Multi-Frequency Alignment (MFAL) to learn temporal frequency invariant representations, and leverages Multi-Frequency Adaptation (MFAD) to further strengthen the representation abilities. Comprehensive empirical validations using various architectures and popular benchmarks solidly demonstrate the effectiveness and generalization of FFN (e.g., 7.08/5.15/2.17% performance gain at Frame 4/8/16 on Something-Something V1 dataset over Uniformer). Code is available at https://github.com/BeSpontaneous/FFN.Comment: Accepted by CVPR202

catena-Poly[[[diaqua­terbium(III)]-μ-6-carboxy­nicotinato-μ-pyridine-2,5-di­carboxyl­ato] dihydrate]

The title compound, {[Tb(C7H3NO4)(C7H4NO4)(H2O)2]·2H2O}n, is isotypic with the analogous TmIII compound [Li, Zhang, Wang & Bai (2009). Acta Cryst. E65, m411]. The TbIII atom is octa­coordinated by two water mol­ecules and by four carboxyl­ate O atoms and two pyridyl N atoms from two pyridine-2,5-dicarboxyl­ate (2,5-pydc) and two 6-carboxy­nicotinate (2,5-Hpydc) ligands. The 2,5-pydc and 2,5-Hpydc ligands bridge TbIII atoms, generating helical coordination polymers along [001]. An extensive network of O—H⋯O hydrogen bonds is formed between the coordination polymers and the uncoordinated water mol­ecules. The refined Flack parameter of 0.54 (2) suggests inversion twinning

MnF 2

Magnetically recyclable materials should be ideal support in photocatalytic system because they permit the photocatalysts to be recovered rapidly and efficiently by applying an external magnetic field such as, MnF2. In this paper, MnF2 and SiO2 layers constitute a one-dimensional quasiperiodic photonic crystal according to Fibonacci. When the electromagnetic wave irradiates obliquely, the transmission peak moves to higher frequency direction with the angle increasing. Both the number of transmission peaks and the transmission peaks of double-forked structure increase with the increase of structural progression. We also found that the polarization of electromagnetic waves has influence on the transmission properties; TM wave transmission peak half wide is significantly greater than TE wave transmission peak half wide. The band gap near antiferromagnetic (AF) resonance frequency becomes narrow as the intensity of the applied static magnetic field increases. The as-prepared photonic crystal has tremendous potential practical use to eliminate organic pollutants from wastewater

Tetra­aqua­bis(2-oxo-1,2-dihydro­quinoline-4-carboxyl­ato-κO 4)nickel(II)

In the title compound, [Ni(C10H6NO3)2(H2O)4], the central NiII atom is located on an inversion center and coordinated in a slightly distorted octa­hedral geometry by two O atoms from two 2-oxo-1,2-dihydro­quinoline-4-carboxyl­ate ligands and four water mol­ecules, all of which act as monodentate ligands. The crystal structure features an extensive network of inter­molecular hydrogen-bonding inter­actions (O—H⋯O and N—H⋯O) and offset face-to-face π–π stacking inter­actions [centroid–centroid distances = 3.525 (3) and 3.281 (5) Å]

Preoperative controlling nutritional status score (CONUT) predicts postoperative complications of patients with bronchiectasis after lung resections

BackgroundThe Controlled Nutritional Status (CONUT) score is a valid scoring system for assessing nutritional status and has been shown to correlate with clinical outcomes in many surgical procedures; however, no studies have reported a correlation between postoperative complications of bronchiectasis and the preoperative CONUT score. This study aimed to evaluate the value of the CONUT score in predicting postoperative complications in patients with bronchiectasis.MethodsWe retrospectively analyzed patients with localized bronchiectasis who underwent lung resection at our hospital between April 2012 and November 2021. The optimal nutritional scoring system was determined by receiver operating characteristic (ROC) curves and incorporated into multivariate logistic regression. Finally, independent risk factors for postoperative complications were determined by univariate and multivariate logistic regression analyses.ResultsA total of 240 patients with bronchiectasis were included, including 101 males and 139 females, with an average age of 49.83 ± 13.23 years. Postoperative complications occurred in 59 patients (24.6%). The incidence of complications, postoperative hospital stay and drainage tube indwelling time were significantly higher in the high CONUT group than in the low CONUT group. After adjusting for sex, BMI, smoking history, lung function, extent of resection, intraoperative blood loss, surgical approach and operation time, multivariate analysis showed that the CONUT score remained an independent risk factor for postoperative complications after bronchiectasis.ConclusionsThe preoperative CONUT score is an independent predictor of postoperative complications in patients with localized bronchiectasis