The Influence of the Oxygen Vacancies on the Pt/TiO2 Single-atom Catalyst – a DFT Study

The titanium dioxide (TiO2) surface is suitable as a substrate for single-atom catalysts(SACs). As a common defect on TiO2, oxygen vacancies may have a significant impact on the adsorption and activity of the adatoms. This work aims to investigate whether titanium dioxide containing surface oxygen vacancies is more suitable as a base material for SACs. This paper calculates the changes in the adsorption energy of Pt atom and the energy of the d-band center on the perfect surface and the surface containing oxygen vacancies. Concerning the perfect surface, the surface containing oxygen vacancies fixes the Pt atom more firmly, and increases the center energy of the d-band of Pt, thereby improving the performance of Pt atom as SACs. Consequently, the (110) surface of Rutile TiO2 with oxygen vacancies may be the best substrate for SACs.

Study of Allowable Interlaminar Normal Stress Based on the Time–Temperature Equivalence Principle in Automated Fiber Placement Process

Automatic fiber placement (AFP) is a type of labor-saving automatic technology for forming composite materials that are widely used in aviation and other fields. In this process, concave surface delamination is a common defect, as existing research on the conditions for this defect to occur is insufficient. To predict the occurrence of this defect, the concept of allowable interlaminar normal stress is proposed to define its occurrence conditions, and based on this concept, probe tests are carried out using the principle of time–temperature equivalence. Through the laying speed/allowable normal stress curve measured in the probe experiment, the physical meaning of allowable normal stress is discussed. At the same time, the measured curve is quantitatively analyzed, combined with viscoelastic theory and the molecular diffusion reptation model, and the dominating effect in the formation of a metal/prepreg layer and prepreg/prepreg layer is determined. Finally, the experimental data are used to guide the parameter selection in an automatic placement engineering case and prove its correctness.

Could Vitamin D3 Deficiency Influence Malocclusion Development?

The abnormal growth of the craniofacial bone leads to skeletal and dental defects, which result in the presence of malocclusions. Not all causes of malocclusion have been explained. In the development of skeletal abnormalities, attention is paid to general deficiencies, including of vitamin D3 (VD3), which causes rickets. Its chronic deficiency may contribute to skeletal malocclusion. The aim of the study was to assess the impact of VD3 deficiency on the development of malocclusions. The examination consisted of a medical interview, oral examination, an alginate impression and radiological imaging, orthodontic assessment, and taking a venous blood sample for VD3 level testing. In about 42.1% of patients, the presence of a skeletal defect was found, and in 46.5% of patients, dentoalveolar malocclusion. The most common defect was transverse constriction of the maxilla with a narrow upper arch (30.7%). The concentration of vitamin 25 (OH) D in the study group was on average 23.6 ± 10.5 (ng/mL). VD3 deficiency was found in 86 subjects (75.4%). Our research showed that VD3 deficiency could be one of an important factor influencing maxillary development. Patients had a greater risk of a narrowed upper arch (OR = 4.94), crowding (OR = 4.94) and crossbite (OR = 6.16). Thus, there was a link between the deficiency of this hormone and the underdevelopment of the maxilla.

Degassing Process Influence on Tensile Strength of Neat E132 Epoxy Polymeric Materials

During the composite’s fabrication process, one of the most common defect occurs is void. Numerous literatures have suggested that the presence of void negatively affect its mechanical properties and effective degassing process is one the solutions for such issue. In this study, experiments were carried out using neat E132 epoxy to investigate the effects of different degassing process (hot water, ultrasonic bath, and vacuum) on its tensile strength. The duration of its process was carried out from 5 – 9 minutes for hot water and ultrasonic bath where vacuum process was extended until 10 minutes to observed limiting behavior. It is found that the vacuum degassing method is the most effective. Vacuum degassing process displayed the least formation of bubble and micro voids even for 10 minutes. It is also revealed that vacuum degassing process resulted the highest average tensile strength at 48.8MPa. Such findings would facilitate the well bonded effective nanocomposite fabrication process.

The Optimal Tetralogy of Fallot Repair Using Generative Adversarial Networks

BackgroundTetralogy of Fallot (TOF) is a type of congenital cardiac disease with pulmonary artery (PA) stenosis being the most common defect. Repair surgery needs an appropriate patch to enlarge the narrowed artery from the right ventricular (RV) to the PA.MethodsIn this work, we proposed a generative adversarial networks (GANs) based method to optimize the patch size, shape, and location. Firstly, we built the 3D PA of patients by segmentation from cardiac computed tomography angiography. After that, normal and stenotic areas of each PA were detected and labeled into two sub-images groups. Then a GAN was trained based on these sub-images. Finally, an optimal prediction model was utilized to repair the PA with patch augmentation in the new patient.ResultsThe fivefold cross-validation (CV) was performed for optimal patch prediction based on GANs in the repair of TOF and the CV accuracy was 93.33%, followed by the clinical outcome. This showed that the GAN model has a significant advantage in finding the best balance point of patch optimization.ConclusionThis approach has the potential to reduce the intraoperative misjudgment rate, thereby providing a detailed surgical plan in patients with TOF.

A STUDY ON SPECTRUM OF CONGENITALANOMALIES DELIVERED IN A TERTIARY CARE CENTER

INTRODUCTION: Congenital anomaliesaccount for 9% of neonatal deaths in India. Prevalence of birth anomalies in India is 6-7%. AIMS AND OBJECTIVES: The objective was to determine proportion and clinical spectrum of congenital anomalies and maternal and perinatal risk factors associated with congenital anomalies in live newborns in our area. MATERIALS AND METHODS: Neonates born in ALLURI SITARAMA RAJU ACADEMY OF MEDICAL SCIENCES hospital during study period with documented congenital anomalies are included. All still-borns and gestational age <22wks & birth weight <400gm were excluded. Retrospective hospital-based study, conducted between January 2019 to December 2019 in ASRAM Hospital. RESULTS: The total number of births is 1132 during this one year of which, 106 newborns had congenital anomalies. In this study we found that major anomalies (80.2%) , Minor anomalies (19.8%).In this study we found that most of the anomalies were major and mostly involved cardiovascular system. In minor anomalies the most common defect was sacral dimple. CONCLUSION: Congenital anomalies can be reduced with in-utero surgeries, and necessary preventive measures which are becoming feasible.

The Influence of Tri-Defects of Epitaxial Layers on the Performance of 4H-Sic Diodes

The triangular defect is a common defect in the 4H-SiC epitaxy, which is also one of the killer defects to the 4H-SiC devices. In this paper, the 4H-SiC epitaxial wafer was grown by chemical vapor deposition (CVD). The formation mechanism of triangular defects in silicon carbide epitaxy was analyzed, and the solutions were proposed. Then, the diodes were fabricated on the wafer, and the influence of triangular defects on the forward and reverse I-V characteristics of 4H-SiC diodes was analyzed by tracking the defects map. The results show that the presence of triangular defects can lead to the reduction of the reverse voltage by about 40%, an increase of the leakage current by four orders of magnitude, and an increase of the forward conduction resistance.

EVALUATION OF COATINGS TENDENCY TO THE PORES AND NON-METAL INCLUSIONS FORMATION IN A WELD

The task of welding steel elements painted with various coatings is found in a number of industries at the stages of factory assembly and installation of large-sized structures, as well as during repair and restoration work. The porosity of the welded metal is the most common defect in electric arc welding without removing the coating, and the tendency to pore formation is a normalized parameter in the certification of interoperable primers (EN ISO 17652-2: 2003). The studies carried out cover wide-spread polyacrylate, alkyd, epoxy, polyvinyl butyral primers in an extended working thicknesses range. In addition, the evaluation technique is used for zinc-filled and organosilicate protective coat-ings. Based on the study of the nonmetallic inclusions composition in a weld by energy dispersive X-ray spectroscopy and using a scanning electron microscope, the behavior features of the coatings de-struction products and their derivatives during physical and chemical transformations under welding are described. The technological features of welding without coating removing are noted: stability of the mode parameters, resistance to metal spraying and coating burnout activity in the areas adjacent to a weld.

Pointer Defect Detection Based on Transfer Learning and Improved Cascade-RCNN

To meet the practical needs of detecting various defects on the pointer surface and solve the difficulty of detecting some defects on the pointer surface, this paper proposes a transfer learning and improved Cascade-RCNN deep neural network (TICNET) algorithm for detecting pointer defects. Firstly, the convolutional layers of ResNet-50 are reconstructed by deformable convolution, which enhances the learning of pointer surface defects by feature extraction network. Furthermore, the problems of missing detection caused by internal differences and weak features are effectively solved. Secondly, the idea of online hard example mining (OHEM) is used to improve the Cascade-RCNN detection network, which achieve accurate classification of defects. Finally, based on the fact that common pointer defect dataset and pointer defect dataset established in this paper have the same low-level visual characteristics. The network is pre-trained on the common defect dataset, and weights are transferred to the defect dataset established in this paper, which reduces the training difficulty caused by too few data. The experimental results show that the proposed method achieves a 0.933 detection rate and a 0.873 mean average precision when the threshold of intersection over union is 0.5, and it realizes high precision detection of pointer surface defects.