The influence of parenting style in childhood on adult depressed patients’ interpersonal relationships in the period of youth

ObjectiveThe objective of this study was to explore the mediating effect of adolescent self and courage on the relationship between parenting style in childhood and adult depressed patients’ interpersonal relationships in the period of youth.MethodsThe study analyzed data from 651 depressed individuals using the Wang Weidong memory-tracing personality developmental inventory (WMPI) from the psychology department of Guang’anmen Hospital.ResultsThe results of the study show a significant positive correlation between parenting style in childhood, adolescent self, courage, and adult depressed patients’ interpersonal relationships in the period of youth. Parenting style in childhood has a direct positive predictive effect on adult depressed patients’ interpersonal relationships in the period of youth. It also has an indirect effect on interpersonal relationships in the period of youth through three indirect pathways: the independent mediating effect of adolescent self, the independent mediating effect of adolescent courage, and the chain mediating effect of adolescent self and courage.ConclusionThe findings of this study suggest that parenting style in childhood plays an important role in shaping adult depressed patients’ interpersonal relationships in the period of youth. The relationship between parenting style in childhood and interpersonal relationships in the period of youth is influenced by the independent mediating effect of adolescent self and courage, as well as the chain mediating effect of adolescent self and courage. These findings have implications for the development of interventions and programs aimed at improving the mental health and well-being of depressed patients

MATERIAL PROCESSING AND DEVICE APPLICATIONS OF ORGANIC AND METAL OXIDE SEMICONDUCTOR MATERIALS

Ph.DDOCTOR OF PHILOSOPH

Organic Field-Effect Transistor: Device Physics, Materials, and Process

Organic field-effect transistors have received much attention in the area of low cost, large area, flexible, and printable electronic devices. Lots of efforts have been devoted to achieve comparable device performance with high charge carrier mobility and good air stability. Meanwhile, in order to reduce the fabrication costs, simple fabrication conditions such as the printing techniques have been frequently used. Apart from device optimization, developing novel organic semiconductor materials and using thin-film alignment techniques are other ways to achieve high-performance devices and functional device applications. It is expected that by combining proper organic semiconductor materials and appropriate fabrication techniques, high-performance devices for various applications could be obtained. In this chapter, the organic field-effect transistor in terms of device physics, organic materials, device process, and various thin-film alignment techniques will be discussed

Microstructure Engineering of Metal-Halide Perovskite Films for Efficient Solar Cells

Photovoltaic (PV) devices with metal-halide perovskite films, namely perovskite solar cells, have become a rapidly rising star due to low cost of raw materials, simple solution processability, and swiftly increased power conversion efficiency (PCE). The PCEs so far certified have gone beyond 22% for perovskite solar cells and 23.6% for tandem devices with single crystalline silicon solar cells, which offer a promising PV technology for practical applications. In principle, performance of perovskite solar cells are largely dominated by the optoelectronic properties and stability of metal-halide perovskite films, which are determined by the microstructure features of the films in turns. In this chapter, we will describe the recently developed strategies on microstructure engineering of metal-halide perovskite films for efficient perovskite solar cells

Hierarchical temperature imaging using pseudoinversed convolutional neural network aided TDLAS tomography

As an in situ combustion diagnostic tool, Tunable Diode Laser Absorption Spectroscopy (TDLAS) tomography has been widely used for imaging of two-dimensional temperature distributions in reactive flows. Compared with the computational tomographic algorithms, Convolutional Neural Networks (CNNs) have been proofed to be more robust and accurate for image reconstruction, particularly in case of limited access of laser beams in the Region of Interest (RoI). In practice, flame in the RoI that requires to be reconstructed with good spatial resolution is commonly surrounded by low-temperature background. Although the background is not of high interest, spectroscopic absorption still exists due to heat dissipation and gas convection. Therefore, we propose a Pseudo-Inversed CNN (PI-CNN) for hierarchical temperature imaging that (a) uses efficiently the training and learning resources for temperature imaging in the RoI with good spatial resolution, and (b) reconstructs the less spatially resolved background temperature by adequately addressing the integrity of the spectroscopic absorption model. In comparison with the traditional CNN, the newly introduced pseudo inversion of the RoI sensitivity matrix is more penetrating for revealing the inherent correlation between the projection data and the RoI to be reconstructed, thus prioritising the temperature imaging in the RoI with high accuracy and high computational efficiency. In this paper, the proposed algorithm was validated by both numerical simulation and lab-scale experiment, indicating good agreement between the phantoms and the high-fidelity reconstructions.Comment: Submitted to IEEE Transactions on Instrumentation and Measuremen

CSTNet: A Dual-Branch Convolutional Network for Imaging of Reactive Flows using Chemical Species Tomography

Chemical Species Tomography (CST) has been widely used for in situ imaging of critical parameters, e.g. species concentration and temperature, in reactive flows. However, even with state-of-the-art computational algorithms the method is limited due to the inherently ill-posed and rank-deficient tomographic data inversion, and by high computational cost. These issues hinder its application for real-time flow diagnosis. To address them, we present here a novel CST-based convolutional neural Network (CSTNet) for high-fidelity, rapid, and simultaneous imaging of species concentration and temperature. CSTNet introduces a shared feature extractor that incorporates the CST measurement and sensor layout into the learning network. In addition, a dual-branch architecture is proposed for image reconstruction with crosstalk decoders that automatically learn the naturally correlated distributions of species concentration and temperature. The proposed CSTNet is validated both with simulated datasets, and with measured data from real flames in experiments using an industry-oriented sensor. Superior performance is found relative to previous approaches, in terms of robustness to measurement noise and millisecond-level computing time. This is the first time, to the best of our knowledge, that a deep learning-based algorithm for CST has been experimentally validated for simultaneous imaging of multiple critical parameters in reactive flows using a low-complexity optical sensor with severely limited number of laser beams.Comment: Submitted to IEEE Transactions on Neural Networks and Learning System

Cloning, Heterologous Expression, and Characterization of a βκ-Carrageenase From Marine Bacterium Wenyingzhuangia funcanilytica: A Specific Enzyme for the Hybrid Carrageenan–Furcellaran

Carrageenan is a group of important food polysaccharides with high structural heterogeneity. Furcellaran is a typical hybrid carrageenan, which contains the structure consisted of alternative beta-carrageenan and kappa-carrageenan motifs. Although several furcellaran-hydrolyzing enzymes have been characterized, their specificity for the glycosidic linkage was still unclear. In this study, we cloned, expressed, and characterized a novel GH16_13 furcellaran-hydrolyzing enzyme Cgbk16A_Wf from the marine bacterium Wenyingzhuangia fucanilytica CZ1127. Cgbk16A_Wf exhibited its maximum activity at 50 degrees C and pH 6.0 and showed high thermal stability. The oligosaccharides in enzymatic products were identified by liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) and nuclear magnetic resonance (NMR) spectroscopy. It was confirmed that Cgbk16A_Wf specifically cleaves the beta-1,4 linkages between beta-carrageenan and kappa-carrageenan motifs from non-reducing end to reducing end. Considering the structural heterogeneity of carrageenan and for the unambiguous indication of the specificity, we recommended to name the furcellaran-hydrolyzing activity represented by Cgbk16A as beta kappa-carrageenase instead of furcellaranase

Absolute frequency measurement of the 87Sr optical lattice clock at NTSC using International Atomic Time

We report the absolute frequency measurement of the 5s2 1S0-5s5p 3P0 transition in 87Sr optical lattice clock (Sr1) at National Time Service Center (NTSC). Its systematic frequency shifts are evaluated carefully with a total relative uncertainty of 5.1E10-17. The measured absolute frequency is 429 228 004 229 872.91(18) Hz with a relative uncertainty of 4.13E10-16, with reference to the ensemble of primary and secondary frequency standards published in the Circular T bulletin by BIPM through a global navigation satellite system (GNSS) link