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Interstitial lung disease (ILD) is a heterogeneous group of diseases characterized by lung injury caused by lung fibroblast proliferation, interstitial inflammation, and fibrosis. Different cell signal transduction pathways are activated in response to various proinflammatory or fibrotic cytokines, such as IL-6, and these cytokines are increased in different ILDs. The overexpressed cytokines and growth factors in ILD can activate TGF-β/Smad2/3/4, NF-κB, and JAK/STAT signal transduction pathways, promote the activation of immune cells, increase the release of pro-inflammatory and pro-fibrotic factors, differentiate fibroblasts into myofibroblasts, and promote the occurrence and development of ILD. This finding suggests the importance of signal transduction pathways in patients with ILD. Recent evidence suggests that resveratrol (RSV) attenuates excessive inflammation and pulmonary fibrosis by inhibiting the TGF-β/Smad2/3/4, NF-κB, and JAK/STAT signal transduction pathways and overactivation of immune cells. In this review, advances in lung protection and the underlying mechanisms of RSV are summarized, and the potential efficacy of RSV as a promising treatment option for ILD is highlighted.

In the field of music information retrieval (MIR), cover song identification (CSI) is a challenging task that aims to identify cover versions of a query song from a massive collection. Existing works still suffer from high intra-song variances and inter-song correlations, due to the entangled nature of version-specific and version-invariant factors in their modeling. In this work, we set the goal of disentangling version-specific and version-invariant factors, which could make it easier for the model to learn invariant music representations for unseen query songs. We analyze the CSI task in a disentanglement view with the causal graph technique, and identify the intra-version and inter-version effects biasing the invariant learning. To block these effects, we propose the disentangled music representation learning framework (DisCover) for CSI. DisCover consists of two critical components: (1) Knowledge-guided Disentanglement Module (KDM) and (2) Gradient-based Adversarial Disentanglement Module (GADM), which block intra-version and inter-version biased effects, respectively. KDM minimizes the mutual information between the learned representations and version-variant factors that are identified with prior domain knowledge. GADM identifies version-variant factors by simulating the representation transitions between intra-song versions, and exploits adversarial distillation for effect blocking. Extensive comparisons with best-performing methods and in-depth analysis demonstrate the effectiveness of DisCover and the and necessity of disentanglement for CSI.

Additional file 1: Supplementary Figure 1. Association between dietary folate (log transformed) and serum folate (log transformed). The solid red line represents the relation between the variables, the blue punctate lines indicate a 95% confidence interval, and the black bars show frequency. Adjust for: age, gender, race, education level, BMI, energy intake, total fat intake, dietary fiber intake, smoking habits, alcohol consumption, diabetes, hypertension. Supplementary Table 1. Threshold effect analysis of dietary folate on serum folate, using the segmented regression model.

Supplementary Material 1

To observe the intervention effect of auricular point sticking on dry eye in myopia patients after small-incision lenticule extraction (SMILE) surgery. This was a prospective randomized controlled study conducted among the myopia patients who received SMILE surgery at Eye and ENT Hospital of Fudan University. The post-SMILE operation patients who screened by the inclusion and exclusion criteria were randomized into a control group and a treatment group. Patients in the control group were given 0.1% fluorometholone and 0.5% carboxymethylcellulose sodium eye drops, while the treatment group was given additional unilateral auricular point sticking for 1 month. The patients were estimated using ocular surface disease index (OSDI), Schirmer tear test-1 (STT-1), tear film break-up time (TF-BUT), corneal fluorescein staining (CFS) score, corneal sensitivity (CS) and visual quality (VQ) at 1 d, 1 week and 1 month after surgery; the changes in anxiety and depression were also observed in the patients. Compared with the first day after operation, CS in the nasal region was improved in the treatment group, and the VQ score increased in the control group patients at 1 week after operation (both P

In the distributed multi-target tracking system, the local sensors often begin working at different time and provide tracks at different rates with different communication delays. As a result, the local tracks from different sensors are usually asynchronous. The current solution is time registration before track association which leads to track synchronization. However, when synchronizing, the estimation error increases. This affects performance of track-to-track association. In this paper, tracks are treated as time series, and using dynamic time warping method (DTW) measures the distance between any two tracks. DTW is a much more robust distance measure for time series, allowing similar shapes to match even if they are out of phase in the time axis. Considering track-to-track association problems, and confining the search area of DTW when optimizing, a fast algorithm is obtained. This is a post-processing technique of tracks. In order to make track-to-track association more accurately after obtaining the track data from sensors, the algorithm is proposed so that track fusion can be implemented next. Simulation results show that the presented method can effectively solve the asynchronous track-to-track association problem.

This paper presents the state estimation problem of discrete-time Markovian jump linear systems (MJLSs) with stochastic coefficient matrices (SCMs) and one-step randomly delayed measurements (RODs). Here, the SCMs are modeled as the randomly weighted sum of a series known basis matrices while the RODs are represented by a sequence of independent Bernoulli random variables. The proposed system is the MJLS with multiple stochastic parameters, including stochastic system matrices leading the uncertainty coupling between system matrices and state/noises, and ranndom Bernoulli variables leading the real measurement correlated with that at previous instant. By geometry augmentation, the state coupled with mode uncertainty is estimated instead of estimating the original state directly. Then, the linear minimum-mean-square error (LMMSE) estimator is derived in a recursive structure according to the orthogonality principle. A numerical simulation is presented to testify the proposed method.

Talking aboutSmarandache power function, Smarandache totient function, convergence.

In this paper, one uses the elementary method to study the convergence of theSmarandache alternate consecutive, reverse Fibonacci sequence and Smarandache multiplesequence.