Recognition of mortar pumpability via computer vision and deep learning

The mortar pumpability is essential in the construction industry,which requires much labor to estimate manually and always causes material waste.This paper proposes an effective method by combining a 3-dimensional convolutional neural network(3D CNN)with a 2-dimensional convolutional long short-term memory network(ConvLSTM2D)to automatically classify the mortar pumpability.Experiment results show that the proposed model has an accuracy rate of 100%with a fast convergence speed,based on the dataset organized by collecting the corresponding mortar image sequences.This work demonstrates the feasibility of using computer vision and deep learning for mortar pumpability classification.

Development and application of hepatocellular carcinoma risk prediction model based on clinical characteristics and liver related indexes

BACKGROUND Hepatocellular carcinoma(HCC)is difficult to diagnose with poor therapeutic effect,high recurrence rate and has a low survival rate.The survival of patients with HCC is closely related to the stage of diagnosis.At present,no specific serolo-gical indicator or method to predict HCC,early diagnosis of HCC remains a challenge,especially in China,where the situation is more severe.AIM To identify risk factors associated with HCC and establish a risk prediction model based on clinical characteristics and liver-related indicators.METHODS The clinical data of patients in the Affiliated Hospital of North Sichuan Medical College from 2016 to 2020 were collected,using a retrospective study method.The results of needle biopsy or surgical pathology were used as the grouping criteria for the experimental group and the control group in this study.Based on the time of admission,the cases were divided into training cohort(n=1739)and validation cohort(n=467).Using HCC as a dependent variable,the research indicators were incorporated into logistic univariate and multivariate analysis.An HCC risk prediction model,which was called NSMC-HCC model,was then established in training cohort and verified in validation cohort.RESULTS Logistic univariate analysis showed that,gender,age,alpha-fetoprotein,and protein induced by vitamin K absence or antagonist-II,gamma-glutamyl transferase,aspartate aminotransferase and hepatitis B surface antigen were risk factors for HCC,alanine aminotransferase,total bilirubin and total bile acid were protective factors for HCC.When the cut-off value of the NSMC-HCC model joint prediction was 0.22,the area under receiver operating characteristic curve(AUC)of NSMC-HCC model in HCC diagnosis was 0.960,with sensitivity 94.40%and specificity 95.35%in training cohort,and AUC was 0.966,with sensitivity 90.00%and specificity 94.20%in validation cohort.In early-stage HCC diagnosis,the AUC of NSMC-HCC model was 0.946,with sensitivity 85.93%and specificity 93.62%in training cohort,and AUC was 0.947,with sensitivity 89.10%and specificity 98.49%in validation cohort.CONCLUSION The newly NSMC-HCC model was an effective risk prediction model in HCC and early-stage HCC diagnosis.

Theoretical study on martensitic-type transformation path from rutile phase to α-PbO2 phase of TiO2

The martensitic-type phase transformation paths from the rutile to theα-PbO2 phase of TiO2 are studied with linear interpolation and NEB/G-SSNEB methods based on first-principles calculations.Its potential energy surface and the lowest energy path are revealed.Our results indicate that the titanium atoms of the rutile phase shuffle along the[0-11]rut crystal direction to form theα-PbO2 phase.During the phase transition,the oxygen atoms are dragged by the heavier titanium atoms and then reach their new equilibrium positions.The barrier of phase transition from nudged elastic band theory is about 231 meV,which is qualitatively consistent with previous theoretical calculations from the monoclinic phase to the tetragonal phase for ZrO2 and HfO2.Debye model can also be successfully used to predict the pressure and temperature of the phase transformation.

Development and prospects of cervical laminoplasty

Cervical laminoplasty surgery is an alternative to laminectomy. It can increase the space of the spinal cord available by raising the lamina, and achieve the indirect decompression effect to treat cervical spondylosis. Various techniques of laminoplasty have since been developed after two prototype techniques: Hirabayashi's open-door laminoplasty and Kurokawa's double-door laminoplasty. Several studies report superior biomechanical stability of the cervical spine after laminoplasty compared with laminectomy. Recent development in laminoplasty is preservation of muscle attachment, which enabled dynamic and static stabilization of the cervical spine by neck extensor muscles. After treatment with new laminoplasty techniques with active postoperative neck muscle exercises, postoperative instability, kyphosis, axial neck pain, and loss of ROM become minimal. The development,complications and future trends of cervical laminoplasty are summarized below.