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Left ventricle (LV) segmentation of cardiac magnetic resonance (MR) images is essential for evaluating cardiac function parameters and diagnosing cardiovascular diseases (CVDs). Accurate LV segmentation remains a challenge because of the large differences in cardiac structures in different research subjects. In this work, a network based on an encoder–decoder architecture for automatic LV segmentation of short-axis cardiac MR images is proposed. It combines UNet 3+ and Transformer to jointly predict the segmentation masks and signed distance maps (SDM). UNet 3+ can extract coarse-grained semantics and fine-grained details from full scales, while a Transformer is used to extract global features from cardiac MR images. It solves the problem of low segmentation accuracy caused by blurred LV edge information. Meanwhile, the SDM provides a shape-aware representation for segmentation. The performance of the proposed network is validated on the 2018 MICCAI Left Ventricle Segmentation Challenge dataset. The five-fold cross-validation evaluation was performed on 145 clinical subjects, and the average dice metric, Jaccard coefficient, accuracy, and positive predictive value reached 0.908, 0.834, 0.979, and 0.903, respectively, showing a better performance than that of other mainstream ones.

Cement and ionic curing agent were blended with iron tailings (ITS) and natural soil to prepare a new road base material. 7-d unconfined compressive strength (UCS) was selected as the evaluation index for determining the optimal mix ratio. The results reveal that the 7-d UCS always increases with the increase of cement content, and firstly increases with the increase of curing agent content and then tends to remain stable, exhibiting an increasing trend first and then dropping with the increase of ITS content. In lieu of this, the optimum ratio of iron tailings blended soil (ITBS) is determined as follows: ITS and soil are mixed in ratio of 50:50, and cement and soil curing agent account for 5% and 2% of the total mass, respectively. The results of splitting strength and flexural-tensile strength tests show that these strengths of the ITBS always increase with the curing age, and firstly increases and then decreases with the increase in ITS content. XRD and SEM analyses show that the ratio of ITS to soil significantly influences the micro-pore structure of the blended soil. At an ITS to soil ratio of 50%:50%, the combination of soil and ITS particles is the closest which results in the highest strength attainment.

A novel, simple and efficient anhydrous MgCO3 (AMC) synthesis method using ascorbic acid (ASA) has been developed based on the hydrothermal carbonization. In this process, ASA acts as both a CO2 source and a crystal modifier to regulate and control the crystallization of AMC. Furan derivatives, aldehydes and ketones from ascorbic acid play an unexpected role as a structure-directing agent. The effect of pH values of ASA, reaction time and the concentrations and types of Mg2+ were systematically investigated. Pure AMC with different morphology were successfully prepared.

Sleep staging is often applied to assess the quality of sleep and also be used to prevent and monitor psychiatric disorders caused by sleep. However, it remains a challenge to extract the discriminative features of salient waveforms in sleep EEG and enable the network to effectively classify sleep stages by emphasizing these crucial features, thus achieving higher accuracy. In this study, an end-to-end deep learning model based on DenseNet for automatic sleep staging is designed and constructed. In the framework, two convolutional branches are devised to extract the underlying features (Two-Frequency Feature) at various frequencies, which are then fused and input into the DenseNet module to extract salient waveform features. After that, the Coordinate Attention mechanism is employed to enhance the localization of salient waveform features by emphasizing the position of salient waveforms and the spatial relationship across the entire frequency spectrum. Finally, the obtained features are accessed to the fully connected for sleep staging. The model was validated with a 20-fold cross-validation procedure on two public available datasets, and the overall accuracy, kappa coefficient, and MF1 score reached 92.9%, 78.7, 0.86 and 90.0%, 75.8, 0.80 on Sleep-EDF-20 and Sleep-EDFx, respectively. Experimental results show that the proposed model achieves competitive performance for sleep staging compared with the reported approaches under the identical conditions.

Structural vibration testing is an effective guarantee for the Structural Health Monitoring (SHM) of large-scale civil engineering. Traditional vibration testing has drawbacks such as difficulties in wiring and picking up low-frequency signals, low communication speed, and susceptibility to testing site conditions. In order to improve the universality of wireless vibration sensors, this article develops a wireless vibration sensor, introduces the module composition and basic principles of the sensor, and conducts standard vibration table performance comparison tests between wired acceleration sensors and wireless vibration sensors, verifying the accuracy of wireless vibration sensors. In order to further explore the feasibility of wireless vibration sensor applications, the wired acceleration sensor and wireless vibration sensor were used to analyze the structural dynamic characteristics of the four-layer steel frame structure model in the laboratory, and the comparison was made based on ABAQUS finite element simulation. Finally, the field vibration test was carried out outdoors. The results show that the natural frequency identification results of the wireless vibration sensor and the wired acceleration sensor for the four-story steel frame structure through fast Fourier transform, short-time Fourier transform, and wavelet transform are basically the same, the half-power bandwidth method and logarithmic decrement rate method are used to identify the damping, and wavelet transform is used to identify the vibration mode with minimal error and high accuracy. It shows that the wireless vibration sensor is feasible in practical engineering, has stable and reliable transmission capacity, and can provide certain reference values for earthquake monitoring, building Structural Health Monitoring, etc.

Terminal sialic acids (Sia) on soluble glycoprotein of saliva play an important role in the clearance of influenza virus. The aim of this study is to investigate the alteration of sialylation on the salivary proteins of women during the lactation period and its effect on the saliva binding ability to virus. In total, 210 saliva samples from postpartum women with and without breastfeeding were collected, and the expression level of α2-3/6-linked Sia on the whole salivary proteins and specific glycoproteins of IgA and MUC5B from different groups were tested and verified using lectin microarray, blotting analysis and ELISA based method. The H1N1 vaccine and three strains of Avian influenza virus (AIV) were used for the saliva binding assay. Results showed that the variation in salivary expression level of α2-3-linked Sia was much more obvious than the α2-6-linked Sia, which was up-regulated significantly in the breastfeeding groups compared to the non-breastfeeding groups at the same postpartum stage. Furthermore, the binding abilities of salivary glycoproteins to AIV strains and H1N1 vaccine were increased in breastfeeding groups accordingly. This finding adds new evidence for the maternal benefit of breastfeeding and provides new thinking to protect postpartum women from AIV infection.

More and more research on left ventricle quantification skips segmentation due to its requirement of large amounts of pixel-by-pixel labels. In this study, a framework is developed to directly quantify left ventricle multiple indices without the process of segmentation. At first, DenseNet is utilized to extract spatial features for each cardiac frame. Then, in order to take advantage of the time sequence information, the temporal feature for consecutive frames is encoded using gated recurrent unit (GRU). After that, the attention mechanism is integrated into the decoder to effectively establish the mappings between the input sequence and corresponding output sequence. Simultaneously, a regression layer with the same decoder output is used to predict multi-indices of the left ventricle. Different weights are set for different types of indices based on experience, and l2-norm is used to avoid model overfitting. Compared with the state-of-the-art (SOTA), our method can not only produce more competitive results but also be more flexible. This is because the prediction results in our study can be obtained for each frame online while the SOTA only can output results after all frames are analyzed.

Background: In contrast to traditional static cold preservation of donor livers, normothermic machine perfusion (NMP) may reduce preservation injury, improve graft viability and potentially allows ex vivo assessment of graft viability before transplantation. The polymerized porcine hemoglobin is a kind of hemoglobin oxygen carrier prepared by crosslinking porcine hemoglobin by glutaraldehyde to form a polymer. The pPolyHb has been proved to have the ability of transporting oxygen which could repair the organ ischemia-reperfusion injury in rats. Objective: In order to evaluate the effectiveness of rat liver perfusion in vitro based on pPolyHb, we established the NMP system, optimized the perfusate basic formula and explored the optimal proportion of pPolyHb and basal perfusate. Methods: The liver was removed and perfused for 6 h at 37°C. We compared the efficacy of liver perfusion with different ratios of pPolyHb. Subsequently, compared the perfusion effect using Krebs Henseleit solution and pPolyHb perfusate of the optimal proportion, and compared with the liver preserved with UW solution. At 0 h, 1 h, 3 h and 6 h after perfusion, appropriate samples were collected for blood gas analysis and liver injury indexes detection. Some tissue samples were collected for H&E staining and TUNEL staining to observe the morphology and detect the apoptosis rate of liver cells. And we used Western Blot test to detect the expression of Bcl-2 and Bax in the tissues. Results: According to the final results, the optimal addition ratio of pPolyHb was 24%. By comparing the values of Bcl-2/Bax, the apoptosis rate of pPolyHb group was significantly reduced. Under this ratio, the results of H&E staining and TUNEL staining showed that the liver morphology was well preserved without additional signs of hepatocyte ischemia, biliary tract injury, or hepatic sinusoid injury, and hepatocyte apoptosis was relatively mild. Conclusion: Through the above-mentioned study we show that within 6 h of perfusion based on pPolyHb, liver physiological and biochemical activities may essentially be maintained in vitro . This study demonstrates that a pPolyHb-based perfusate is feasible for NMP of rat livers. This opens up a prospect for further research on NMP.

In this paper, β-diketone boron complex (BF2-TPE) was first used as an ultraviolet (UV) absorber for polyvinyl chloride (PVC), and then a series of PVC/BF2-TPE composite films were prepared by solvent casting method. UV accelerated aging experiment was conducted to evaluate the effect of BF2-TPE on the photooxidative degradation of PVC, the structure and properties of the composite films in the UV aging process were characterized by ultraviolet-visible absorption spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric analysis, dynamic mechanical analysis and mechanical property analysis. The results show that BF2-TPE can absorb UV light in the wavelength range of 220-450 nm. The yield strength of the PVC/BF2-TPE composite film with 0.5% BF2-TPE (PVC/BF2-TPE0.5) decreases from 10.5 MPa to 7.8 MPa after 1200 h of UV irradiation, and its retention ratio is much higher compared with that of pure PVC film, indicating that BF2-TPE can inhibit the photooxidative degradation PVC. The PVC/BF2-TPE0.5 composite film shows higher temperature of onset decomposition, indicating that BF2-TPE can also enhance the thermal stability of PVC/BF2-TPE composite films.

Background Germline mutations in PTEN are associated with the PTEN hamartoma tumor syndrome (PHTS), an umbrella term used to describe a spectrum of autosomal‐dominant disorders characterized by variable phenotypic manifestations associated with cell or tissue overgrowth. We report a boy who developed severe progressive abdominal distention due to a dramatic adipose mass from the age of 7 months and developed recurrent hypoinsulinemic hypoglycemia that led to seizures at the age of 4 years. Methods Trio‐based whole‐genome sequencing was performed by using blood DNA from the child and his parents. The possible pathogenic variants were verified by Sanger sequencing. Functional characterization of the identified variant was completed by western blot. Results The child inherited a single‐nucleotide deletion NM_000314.6:c.849delA (p.Glu284Argfs) in the tumor suppressor gene PTEN from his father. The paternal family members have a history of cancer. It is conceivable that PTEN loss‐of‐function induced the adipose tumor growth and hypoglycemia, although the proband did not meet the usual diagnosis criteria of Cowden syndrome or Bannayan–Riley–Ruvalcaba syndrome that are characterized by germline mutations of PTEN. Conclusion This case underlines the variability of phenotypes associated with PTEN germline mutations and provides useful information for diagnosis and genetic counseling of PTEN‐related diseases for pediatric patients. We report a unique combination of drastic phenotypes from a pediatric patient who presented with massive abdominal distention and severe hypoglycemia that led to recurrent seizures. Trio‐based sequencing analysis identified a heterozygous germline single‐nucleotide deletion mutation in the coding region of the tumor suppressor gene PTEN.