Generating Text Sequence Images for Recognition

Recently, methods based on deep learning have dominated the field of text recognition. With a large number of training data, most of them can achieve the state-of-the-art performances. However, it is hard to harvest and label sufficient text sequence images from the real scenes. To mitigate this issue, several methods to synthesize text sequence images were proposed, yet they usually need complicated preceding or follow-up steps. In this work, we present a method which is able to generate infinite training data without any auxiliary pre/post-process. We tackle the generation task as an image-to-image translation one and utilize conditional adversarial networks to produce realistic text sequence images in the light of the semantic ones. Some evaluation metrics are involved to assess our method and the results demonstrate that the caliber of the data is satisfactory. The code and dataset will be publicly available soon

Relationship of arterial tonometry and exercise in patients with chronic heart failure: a systematic review with meta-analysis and trial sequential analysis

Background: Arterial stiffness is a common characteristic in patients with chronic heart failure (CHF), and arterial tonometric technologies related to arterial stiffness are novel and effective methods and have an important value in the diagnosis and prognosis of CHF. In terms of ameliorating arterial stiffness in patients with CHF, exercise training is considered an adjuvant treatment and also an effective means in the diagnosis and judgment of prognosis. However, there are huge controversies and inconsistencies in these aspects. The objective of this meta-analysis was to systematically test the connection of arterial tonometry and exercise in patients with CHF. Methods: Databases, including MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, were accessed from inception to 7 March 2022. The meta-analysis was then conducted, and trial sequential analysis (TSA) was performed jointly to further verify our tests and reach more convincing conclusions by using RevMan version 5.4 software, STATA version 16.0 software, and TSA version 0.9.5.10 Beta software. Results: Eighteen articles were included, with a total of 876 participants satisfying the inclusion criteria. The pooling revealed that flow-mediated dilation (FMD) was lower in basal condition [standardized mean difference (SMD): - 2.28%, 95% confidence interval (CI) - 3.47 to - 1.08, P < 0.001] and improved significantly after exercise (SMD: 5.96%, 95% CI 2.81 to 9.05, P < 0.001) in patients with heart failure with reduced ejection fraction (HFrEF) compared with healthy participants. The high-intensity training exercise was more beneficial (SMD: 2.88%, 95% CI 1.78 to 3.97, P < 0.001) than the moderate-intensity training exercise to improve FMD in patients with CHF. For augmentation index (AIx), our study indicated no significant differences (SMD: 0.50%, 95% CI - 0.05 to 1.05, P = 0.074) in patients with heart failure with preserved ejection fraction (HFpEF) compared with healthy participants. However, other outcomes of our study were not identified after further verification using TSA, and more high-quality studies are needed to reach definitive conclusions in the future. Conclusions: This review shows that FMD is lower in basal condition and improves significantly after exercise in patients with HFrEF compared with healthy population; high-intensity training exercise is more beneficial than moderate-intensity training exercise to improve FMD in patients with CHF; besides, there are no significant differences in AIx in patients with HFpEF compared with the healthy population. More high-quality studies on this topic are warranted

Bilateral back-projection for single image super resolution

In this paper, a novel algorithm for single image super resolution is proposed. Back-projection [1] can minimize the reconstruction error with an efficient iterative procedure. Although it can produce visually appealing result, this method suffers from the chessboard effect and ringing effect, especially along strong edges. The underlining reason is that there is no edge guidance in the error correction process. Bilateral filtering can achieve edge-preserving image smoothing by adding the extra information from the feature domain. The basic idea is to do the smoothing on the pixels which are nearby both in space domain and in feature domain. The proposed bilateral back-projection algorithm strives to integrate the bilateral filtering into the back-projection method. In our approach, the back-projection process can be guided by the edge information to avoid across-edge smoothing, thus the chessboard effect and ringing effect along image edges are removed. Promising results can be obtained by the proposed bilateral back-projection method efficiently. 1

Methyl 4-(4-methyl­benzamido)-2-sulfamoylbenzoate

The title compound, C16H16N2O5S, is a potent new fungicide. There are two mol­ecules in the asymmetric unit which are linked by C—H⋯π inter­actions, forming a dimer. The two phenyl rings in each mol­ecules are almost coplanar, with C—N—C—C torsion angles of 177.6 (2) and −172.5 (2)°. There are inter­molecular and intra­molecular N—H⋯O hydrogen bonds in the crystal structure