ABSTRACT
Deep Unfolding Networks (DUNs) serve as a predominant approach for Compressed Sensing (CS) reconstruction algorithms by harnessing optimization. However, a notable constraint within the DUN framework is the restriction to single-channel inputs and outputs at each stage during gradient descent computations. This constraint compels the feature maps of the proximal mapping module to undergo multi-channel to single-channel dimensionality reduction, resulting in limited feature characterization capabilities. Furthermore, most prevalent reconstruction networks rely on single-scale structures, neglecting the extraction of features from different scales, thereby impeding the overall reconstruction network's performance. To address these limitations, this paper introduces a novel CS reconstruction network termed the Multi-channel and Multi-scale Unfolding Network (MMU-Net). MMU-Net embraces a multi-channel approach, featuring the incorporation of Adap-SKConv with an attention mechanism to facilitate the exchange of information between gradient terms and enhance the feature map's characterization capacity. Moreover, a Multi-scale Block is introduced to extract multi-scale features, bolstering the network's ability to characterize and reconstruct the images. Our study extensively evaluates MMU-Net's performance across multiple benchmark datasets, including Urban100, Set11, BSD68, and the UC Merced Land Use Dataset, encompassing both natural and remote sensing images. The results of our study underscore the superior performance of MMU-Net in comparison to existing state-of-the-art CS methods.
ABSTRACT
OBJECTIVE: To assess the efficacy and safety of Wuji Powder (WP) and a small dose aripiprazole in treatment of antipsychotic drug-induced phlegm dampness type amenorrhea. METHODS: Seventy female schizophrenic patients with antipsychotic drug-induced galactorrhea-amenorrhea syndrome (GAS) were recruited and randomly assigned to the treatment group and the control group, 35 in each group. All patients received antipsychotic drug therapy. Patients in the treatment group additionally took WP, while those in the control group took aripiprazole (at the daily dose of 5 mg, once daily). The therapeutic course for all was 4 weeks. Prolactin levels and obesity indices[body weight, waist aircumstance, body mass index (BMI) and waist-hit ratio (WHR)] were determined before and after treatment. The efficacy was evaluated. RESULTS: The treatment course was completed in 95.71% of patients. The total effective rate of the 33 patients of the treatment group was 93.94% (31/33), while it was 91.18% (31/34) in the 34 patients of the control group. There was no difference in the total effective rate between the two groups (P > 0.05). Prolactin levels in both group after treatment were significantly lower than those of the baseline (P < 0.01). There was no significant difference in prolactin levels between the two groups after treatment (P > 0.05). Compared with before treatment, body weight, BMI, waist circumstance, and waist-hip ratio obviously decreased after treatment, showing significant difference when compared with the control group (P < 0.05). There was no significant difference in body weight, BMI, waist circumstance, and waist-hip ratio in the control group between before and after treatment (P > 0.05). CONCLUSIONS: Both WP and aripiprazole could lower high prolactin levels of schizophrenics with phlegm dampness type amenorrhea. They showed equivalent efficacy. But WP showed more obvious effect in reducing obesity indices.
