A statistical perspective on algorithm unrolling models for inverse problems

We consider inverse problems where the conditional distribution of the observation ${\bf y}$ given the latent variable of interest ${\bf x}$ (also known as the forward model) is known, and we have access to a data set in which multiple instances of ${\bf x}$ and ${\bf y}$ are both observed. In this context, algorithm unrolling has become a very popular approach for designing state-of-the-art deep neural network architectures that effectively exploit the forward model. We analyze the statistical complexity of the gradient descent network (GDN), an algorithm unrolling architecture driven by proximal gradient descent. We show that the unrolling depth needed for the optimal statistical performance of GDNs is of order $\log(n)/\log(\varrho_n^{-1})$, where $n$ is the sample size, and $\varrho_n$ is the convergence rate of the corresponding gradient descent algorithm. We also show that when the negative log-density of the latent variable ${\bf x}$ has a simple proximal operator, then a GDN unrolled at depth $D'$ can solve the inverse problem at the parametric rate $O(D'/\sqrt{n})$. Our results thus also suggest that algorithm unrolling models are prone to overfitting as the unrolling depth $D'$ increases. We provide several examples to illustrate these results

Soil Image Segmentation Based on Mask R-CNN

The complex background in the soil image collected in the field natural environment will affect the subsequent soil image recognition based on machine vision. Segmenting the soil center area from the soil image can eliminate the influence of the complex background, which is an important preprocessing work for subsequent soil image recognition. For the first time, the deep learning method was applied to soil image segmentation, and the Mask R-CNN model was selected to complete the positioning and segmentation of soil images. Construct a soil image dataset based on the collected soil images, use the EISeg annotation tool to mark the soil area as soil, and save the annotation information; train the Mask R-CNN soil image instance segmentation model. The trained model can obtain accurate segmentation results for soil images, and can show good performance on soil images collected in different environments; the trained instance segmentation model has a loss value of 0.1999 in the training set, and the mAP of the validation set segmentation (IoU=0.5) is 0.8804, and it takes only 0.06s to complete image segmentation based on GPU acceleration, which can meet the real-time segmentation and detection of soil images in the field under natural conditions. You can get our code in the Conclusions. The homepage is https://github.com/YidaMyth.Comment: 4 pages, 5 figures, Published in 2023 3rd International Conference on Consumer Electronics and Computer Engineerin

Ovarian preservation and prognosis in adnexal torsion surgery — a retrospective analysis

Objectives: This study aims to analyze the conditions of ovarian preservation during adnexal torsion surgery, and safetyof ovarian preservation.Material and methods: A retrospective analysis of 130 patients, who underwent surgery for ovarian benign tumor pedicletorsion in Fujian Provincial Maternal and Child Health Hospital from June 2013 to June 2018, was conducted. This studyanalyses the possible risk factors affecting the operation method using multiple logistic regression and analyses the complicationsand the recovery of ovarian function after the treatment of the ovarian preservation.Results: Among these patients, 58 received ovarian cystectomy, while 72 received ovariectomy. There was no significantdifference in terms of age, preoperative blood, operation time and surgical bleeding volume between the two groups(p > 0.05). However, there was a significant difference in preoperative adnexal blood flow, abdominal pain to the surgicalinterval, and a collection of torsion cycles (p < 0.05). There was an increased risk of ovarian resection in patients whose bloodflow of the annex disappeared, whose time of abdominal pain was long, and whose number of twists were significant. Forthe preservation group, there were no increases in postoperative complications.Conclusions: According to clinical indicators, such as preoperative adnexal blood flow, abdominal pain to the interval ofsurgery and the number of torsion cycles, it was determined whether it was feasible to keep the ovary. Retaining the ovaryis safe, effective and feasible in adnexal torsion

Asymmetric double-winged multi-view clustering network for exploring Diverse and Consistent Information

In unsupervised scenarios, deep contrastive multi-view clustering (DCMVC) is becoming a hot research spot, which aims to mine the potential relationships between different views. Most existing DCMVC algorithms focus on exploring the consistency information for the deep semantic features, while ignoring the diverse information on shallow features. To fill this gap, we propose a novel multi-view clustering network termed CodingNet to explore the diverse and consistent information simultaneously in this paper. Specifically, instead of utilizing the conventional auto-encoder, we design an asymmetric structure network to extract shallow and deep features separately. Then, by aligning the similarity matrix on the shallow feature to the zero matrix, we ensure the diversity for the shallow features, thus offering a better description of multi-view data. Moreover, we propose a dual contrastive mechanism that maintains consistency for deep features at both view-feature and pseudo-label levels. Our framework's efficacy is validated through extensive experiments on six widely used benchmark datasets, outperforming most state-of-the-art multi-view clustering algorithms

Preparation and In Vitro Evaluation of Tacrolimus-Loaded Ethosomes

The main objective of the present work was to prepare and assess dermal delivery of tacrolimus-loaded ethosomes versus classic liposomes. Both delivery systems were characterized for particle size, polydispersity index, and entrapment efficiency (EE), by dynamic laser diffraction and ultrafiltration or dialysis methods, respectively. The results indicated that presence of ethanol in the formulations affected the particle size. In addition, ultrafiltration method was selected to determine EE due to relatively short period as compared with dialysis method. Ethosomes exhibited a significant higher EE and amount of drug in dermis in contrast to classic liposomes suggesting that ethosomes with higher entrapment capacity prompted more amount of tacrolimus to permeate through stratum corneum and reach the target of atopic dermatitis (AD). Physical stability was very well for tacrolimus-loaded ethosomes under storage condition (4°C). Our results demonstrated that the ethosomal system might be a promising candidate for dermal delivery of tacrolimus for AD

LncRNA CERS6-AS1, sponging miR-6838-5p, promotes proliferation and invasion in cervical carcinoma cells by upregulating FOXP2

Cervical cancer (CC) is a common disease in women characterized by high recurrence rate. LncRNA ceramide synthase 6 antisense RNA 1 (CERS6-AS1) has been found to play a crucial role in the progression of breast cancer and pancreatic cancer. Nevertheless, the regulatory role of CERS6-AS1 in CC remains largely unclear. Here, we found that the expression of CERS6- AS1 was upregulated in CC tissues and cell lines compared with adjacent tissues and normal human cervical epithelial cells. CERS6-AS1 overexpression promoted proliferation and invasion, and inhibited apoptosis in CC cells, while silencing of CERS6-AS1 led to the opposite results. CERS6-AS1 was verified as a sponge of miR-6838-5p by RNA pull-down and luciferase reporter gene assays. Functional investigations revealed that CERS6-AS1 knockdown inhibited proliferation and invasion, and promoted apoptosis in CC cells, which was reversed by miR-6838-5p inhibitor. Furthermore, forkhead box P2 (FOXP2) was identified as a target for miR-6838-5p, and overexpression of miR6838-5p decreased the expression level of FOXP2. Besides, CERS6-AS1 was able to sponge miR-6838-5p to accelerate CC cell proliferation and invasion and inhibited cell apoptosis through upregulating FOXP2 expression. In general, CERS6-AS1 was able to regulate CC cell proliferation, invasion and apoptosis by the miR-6838-5p/FOXP2 axis, which suggested that CERS6-AS1 may be a potential target for the treatment of CC

Metabolomic profiles of myocardial ischemia under treatment with salvianolic acid B

<p>Abstract</p> <p>Background</p> <p><it>Radix Salvia miltiorrhiza </it>(<it>Danshen</it>) has been used as a principal herb in treating cardiovascular diseases in Chinese medicine. Salvianolic acid B (SA-B), a water-soluble active component of <it>Danshen</it>, was found to have anti-myocardial ischemia (anti-MI) effect. This study aims to investigate mechanisms of SA-B on MI.</p> <p>Methods</p> <p>Five conventional Western medicines (isosorbide dinitrate, verapamil, propranolol, captopril and trimethazine) with different mechanisms for treating cardiovascular diseases were selected as positive references to compare with SA-B in changing of the metabolomic profiles in MI rats under treatment. Potential mechanisms of SA-B were further investigated in H9C2 cell line.</p> <p>Results</p> <p>The metabolomic profiles between SA-B- and propranolol-treated MI rats were similar, since there was a big overlap between the two groups in the PLS-DA score plot. Finally, it was demonstrated that SA-B exhibited a protective effect on MI mainly by decreasing the concentration of cyclic adenosine monophosphate (cAMP) and Ca²⁺and inhibiting protein kinase A (PKA).</p> <p>Conclusion</p> <p>SA-B and propanolol exhibited similar metabolomic profiles, indicating that the two drugs might have a similar mechanism.</p