Learning Segmentation Masks with the Independence Prior

An instance with a bad mask might make a composite image that uses it look fake. This encourages us to learn segmentation by generating realistic composite images. To achieve this, we propose a novel framework that exploits a new proposed prior called the independence prior based on Generative Adversarial Networks (GANs). The generator produces an image with multiple category-specific instance providers, a layout module and a composition module. Firstly, each provider independently outputs a category-specific instance image with a soft mask. Then the provided instances' poses are corrected by the layout module. Lastly, the composition module combines these instances into a final image. Training with adversarial loss and penalty for mask area, each provider learns a mask that is as small as possible but enough to cover a complete category-specific instance. Weakly supervised semantic segmentation methods widely use grouping cues modeling the association between image parts, which are either artificially designed or learned with costly segmentation labels or only modeled on local pairs. Unlike them, our method automatically models the dependence between any parts and learns instance segmentation. We apply our framework in two cases: (1) Foreground segmentation on category-specific images with box-level annotation. (2) Unsupervised learning of instance appearances and masks with only one image of homogeneous object cluster (HOC). We get appealing results in both tasks, which shows the independence prior is useful for instance segmentation and it is possible to unsupervisedly learn instance masks with only one image.Comment: 7+5 pages, 13 figures, Accepted to AAAI 201

The feasibility of Sn, In, or Al doped ZnSb thin film as candidates for phase change material

The potentials of Sn, In, or Al doped ZnSb thin film as candidates for phase change materials have been studied in this paper. It was found that the Zn-Sb bonds were broken by the addition of the dopants and homopolar Zn-Zn bonds and other heteropolar bonds, such as Sn-Sb, In-Sb, and Al-Sb, were subsequently formed. The existence of homopolar Sn-Sn and In-In bonds in Zn₅₀Sb₃₆Sn₁₄ and Zn₄₁Sb₃₆In₂₃ films, but no any Al-Al bonds in Zn₃₅Sb₃₀Al₃₅ film, was confirmed. All these three amorphous films crystallize with the appearance of crystalline rhombohedral Sb phase, and Zn₃₅Sb₃₅Al₃₅ film even exhibits a second crystallization process where the crystalline AlSb phase is separated out. The Zn₃₅Sb₃₀Al₃₅ film exhibits a reversible phase change behavior with a larger Ea ( 4.7 eV), higher Tc (~ 245ᴼ C), better 10-yr data retention (~ 182ᴼ C), less incubation time (20 ns at 70 mW), and faster complete crystallization speed (45 ns at 70 mW). Moreover, Zn₃₅Sb₃₀Al₃₅ film shows the smaller root-mean-square (1.654 nm) and less change of the thickness between amorphous and crystalline state (7.5%), which are in favor of improving the reliability of phase change memory.This work was financially supported by the Natural Science Foundation of China (Grant Nos. 61306147, 61377061), the Public Project of Zhejiang Province (Grant No.2014C31146), the Young Leaders of academic climbing project of the Education Department of Zhejiang Province (pd2013092), the Natural Science Foundation of Zhejiang Province (Grant No. LQ15F040002), the Scientific Research Foundation of Graduate School of Ningbo University, and sponsored by K. C. Wong Magna Fund in Ningbo University

Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression

In this paper, we propose a progressive learning paradigm for transformer-based variable-rate image compression. Our approach covers a wide range of compression rates with the assistance of the Layer-adaptive Prompt Module (LPM). Inspired by visual prompt tuning, we use LPM to extract prompts for input images and hidden features at the encoder side and decoder side, respectively, which are fed as additional information into the Swin Transformer layer of a pre-trained transformer-based image compression model to affect the allocation of attention region and the bits, which in turn changes the target compression ratio of the model. To ensure the network is more lightweight, we involves the integration of prompt networks with less convolutional layers. Exhaustive experiments show that compared to methods based on multiple models, which are optimized separately for different target rates, the proposed method arrives at the same performance with 80% savings in parameter storage and 90% savings in datasets. Meanwhile, our model outperforms all current variable bitrate image methods in terms of rate-distortion performance and approaches the state-of-the-art fixed bitrate image compression methods trained from scratch

Enhanced thermal stability and electrical behavior of Zn-doped Sb2Te films for phase change memory application

Zn-doped Sb₂Te films are proposed to present the feasibility for phase-change memory application. Zn atoms are found to significantly increase crystallization temperature of Zn x (Sb₂Te)1−x films and be almost linearly with the wide range of Zn-doping concentration from x = 0 to 29.67 at.%. Crystalline resistances are enhanced by Zn-doping, while keeping the large amorphous/crystalline resistance ratio almost constant at ∼10⁵. Especially, the Zn 26.07 (Sb₂Te)73.93 and Zn 29.67 (Sb₂Te)70.33 films exhibit a larger resistance change, faster crystallization speed, and better thermal stability due to the formation of amorphous Zn-Sb and Zn-Te phases as well as uniform distribution of Sb₂Te crystalline grains

Improved phase-change characteristics of Zn-doped amorphous Sb₇Te₃ films for high-speed and low-power phase change memory

The superior performance of Zn-doped Sb₇Te₃ films might be favorable for the application in phase change memory. It was found that Zn dopants were able to suppress phase separation and form single stable Sb2Te crystal grain, diminish the grain size, and enhance the amorphous thermal stability of Sb₇Te₃ film. Especially, Zn 30.19(Sb₇Te₃)69.81 film has higher crystallization temperature (∼258 °C), larger crystallization activation energy (∼4.15 eV), better data retention (∼170.6 °C for 10 yr), wider band gap (∼0.73 eV), and higher crystalline resistance. The minimum times for crystallization of Zn 30.19(Sb₇Te₃)69.81 were revealed to be as short as ∼10 ns at a given proper laser power of 70 mW.This work was financially supported by the International Science & Technology Cooperation Program of China (Grant No. 2011DFA12040), the National Program on Key Basic Research Project (973 Program) (Grant No. 2012CB722703), the Natural Science Foundation of China (Grant Nos. 61008041 and 60978058), the CAS Special Grant for Postgraduate Research, Innovation and Practice, the Program for Innovative Research Team of Ningbo city (Grant No. 2009B21007), and sponsored by K. C. Wong Magna Fund in Ningbo University

Transient low T3 syndrome in patients with COVID-19: a new window for prediction of disease severity

ObjectiveTo investigate the relationship of low T3 syndrome with disease severity in patients with COVID-19.MethodsThe clinical data of 145 patients with COVID-19 were retrospectively collected, and patients were divided into a low T3 group and a normal T3 group. Logistic regression models were used to assess predictive performance of FT3. Receiver operating characteristic (ROC) analysis was used to evaluate the use of low T3 syndrome in predicting critical disease. Kaplan-Meier analysis was used to analyze the impact of low T3 syndrome on mortality.ResultsThe prevalence of low T3 level among COVID-19 patients was 34.48%. The low T3 group was older, and had lower levels of hemoglobin, lymphocytes, prealbumin, and albumin, but higher levels of white blood cells, neutrophils, CRP, ESR, and D-dimer (all p<0.05). The low T3 group had greater prevalences of critical disease and mortality (all p <0.05). Multivariate logistic regression analysis showed that the Lymphocytes, free T3 (FT3), and D-dimer were independent risk factors for disease severity in patients with COVID-19. ROC analysis showed that FT3, lymphocyte count, and D-dimer, and all three parameters together provided reliable predictions of critical disease. Kaplan-Meier analysis showed the low T3 group had increased mortality (p<0.001). Six patients in the low T3 group and one patient in the normal T3 group died. All 42 patients whose T3 levels were measured after recovery had normal levels after discharge.ConclusionPatients with COVID-19 may have transient low T3 syndrome at admission, and this may be useful for predicting critical illness

Femoral neck system vs. cannulated screws on treating femoral neck fracture: a meta-analysis and system review

ObjectiveThis meta-analysis aimed to compare the relative safety and efficacy of cannulated compression screw (CCS) and femoral neck system (FNS) in treating patients with femoral neck fractures and to provide evidence-based medical evidence for FNS in treating femoral neck fractures.MethodsPubMed, Embase, Cochrane, and China National Knowledge Infrastructure databases were searched to collect outcomes related to femoral neck fractures treated with FNS and CCS, including time to fracture healing, incidence of non-union, incidence of osteonecrosis of the femoral head, incidence of failure of internal fixation, rate of femoral neck shortening, Harris hip score, Barthel index, operative time, intraoperative blood loss, fluoroscopy frequency, and complications. A meta-analysis was performed using RevManv5.4 (The Cochrane Collaboration) and Stata v14.0 software.ResultsThis analysis included 21 studies involving 1,347 patients. The results showed that FNS was superior to CCS in terms of fracture healing time [mean difference (MD) = −0.75, 95% CI = (−1.04, −0.46), P < 0.05], incidence of bone non-union [odds ratio (OR) = 0.53, 95% CI = (0.29, 0.98), P = 0.04], incidence of osteonecrosis of the femoral head [OR = 0.49, 95% CI = (0.28, 0.86), P = 0.01], incidence of internal fixation failure [OR = 0.30, 95% CI = (0.18, 0.52), P < 0.05], rate of femoral neck shortening [OR = 0.38, 95% CI = (0.27, 0.54), P > 0.05], Harris hip score [MD = 3.31, 95% CI = (1.99, 4.63), P < 0.001], Barthel index [MD =  4.31, 95% CI = (3.02, 5.61), P < 0.05], intraoperative bleeding [MD = 14.72, 95% CI = (8.52, 20.92), P < 0.05], fluoroscopy frequency [OR = 0.53, 95% CI = (0.29, 0.98), P = 0.04], and complications [OR = 0.31, 95% CI = (0.22, 0.45), P < 0.05]. The difference between FNS and CCS in operative time was not statistically significant [MD = −2.41, 95% CI = (−6.88, 2.05), P = 0.29].ConclusionFNS treatment of femoral neck fracture can shorten the fracture healing time; reduce the incidence and translucent rate of bone non-union, osteonecrosis of the femoral head, and internal fixation failure; reduce intraoperative blood loss and postoperative complications; and improve hip joint function and activity. We are confident in the findings that FNS, an effective and safe procedure for internal fixation of femoral neck fractures, is superior to CCS

Effect of Sow Intestinal Flora on the Formation of Endometritis

Endometritis is the main cause of decreased reproductive performance of sows, while one of the most important factors in the etiology of sow endometritis is an aberration of birth canal microbiota. Therefore, people began to pay attention to the microbiota structure and composition of the birth canal of sows with endometritis. Interestingly, we found that the risk of endometritis was increased in the sows with constipation in clinical practice, which may imply that the intestinal flora is related to the occurrence of endometritis. Therefore, understanding the relationship between birth canal microbiota and intestinal microbiota of the host has become exceptionally crucial. In this study, the microbiota of birth canal secretions and fresh feces of four healthy and four endometritis sows were analyzed via sequencing the V3 + V4 region of bacterial 16S ribosomal (rDNA) gene. The results showed a significant difference between endometritis and healthy sows birth canal flora in composition and abundance. Firmicutes (74.36%) and Proteobacteria were the most dominant phyla in birth canal microbiota of healthy sows. However, the majority of beneficial bacteria that belonging to Firmicutes phylum (e.g., Lactobacillus and Enterococcus) declined in endometritis sow. The abundance of Porphyromonas, Clostridium sensu stricto 1, Streptococcus, Fusobacterium, Actinobacillus, and Bacteroides increased significantly in the birth canal microbiota of endometritis sows. Escherichia–Shigella and Bacteroides were the common genera in the birth canal and intestinal flora of endometritis sows. The abundance of Escherichia–Shigella and Bacteroides in the intestines of sows suffering from endometritis were significantly increased than the intestinal microbiota of the healthy sows. We speculated that some intestinal bacteria (such as Escherichia–Shigella and Bacteroides) might be bound up with the onset of sow endometritis based on intestinal microbiota analysis in sows with endometritis and healthy sows. The above results can supply a theoretical basis to research the pathogenesis of endometritis and help others understand the relationship with the microbiota of sow's birth canal and gut