Researchers who lead the trends

Xuan-Hung Doan, Phuong-Tram T. Nguyen, Viet-Phuong La, Hong-Kong T. Nguyen (2019). Chapter 5. Researchers who lead the trends. In Quan-Hoang Vuong, Trung Tran (Eds.), The Vietnamese Social Sciences at a Fork in the Road (pp. 98–120). Warsaw, Poland: De Gruyter. DOI:10.2478/9783110686081-010 Online ISBN: 9783110686081 © 2019 Sciend

Advancing Wound Filling Extraction on 3D Faces: A Auto-Segmentation and Wound Face Regeneration Approach

Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications. In this paper, we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network. Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions. To achieve accurate segmentation, we conducted thorough experiments and selected a high-performing model from the trained models. The selected model demonstrates exceptional segmentation performance for complex 3D facial wounds. Furthermore, based on the segmentation model, we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous study. Our method achieved a remarkable accuracy of 0.9999986\% on the test suite, surpassing the performance of the previous method. From this result, we use 3D printing technology to illustrate the shape of the wound filling. The outcomes of this study have significant implications for physicians involved in preoperative planning and intervention design. By automating facial wound segmentation and improving the accuracy of wound-filling extraction, our approach can assist in carefully assessing and optimizing interventions, leading to enhanced patient outcomes. Additionally, it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue implants. Our source code is available at \url{https://github.com/SIMOGroup/WoundFilling3D}

The regularity and exponential decay of solution for a linear wave equation associated with two-point boundary conditions

This paper is concerned with the existence and the regularity of global solutions to the linear wave equation associated with two-point type boundary conditions. We also investigate the decay properties of the global solutions to this problem by the construction of a suitable Lyapunov functional.Comment: 18 page

Existence, blow-up and exponential decay estimates for a nonlinear wave equation with boundary conditions of two-point type

This paper is devoted to study a nonlinear wave equation with boundary conditions of two-point type. First, we state two local existence theorems and under suitable conditions, we prove that any weak solutions with negative initial energy will blow up in finite time. Next, we give a sufficient condition to guarantee the global existence and exponential decay of weak solutions. Finally, we present numerical resultsComment: 2

Application of Self-Supervised Learning to MICA Model for Reconstructing Imperfect 3D Facial Structures

In this study, we emphasize the integration of a pre-trained MICA model with an imperfect face dataset, employing a self-supervised learning approach. We present an innovative method for regenerating flawed facial structures, yielding 3D printable outputs that effectively support physicians in their patient treatment process. Our results highlight the model's capacity for concealing scars and achieving comprehensive facial reconstructions without discernible scarring. By capitalizing on pre-trained models and necessitating only a few hours of supplementary training, our methodology adeptly devises an optimal model for reconstructing damaged and imperfect facial features. Harnessing contemporary 3D printing technology, we institute a standardized protocol for fabricating realistic, camouflaging mask models for patients in a laboratory environment

Role of GmNAC019 transcription factor in salinity and drought tolerance of transgenic Arabidopsis thaliana

Increasingly severe drought and salinity stress due to global climate change have made these stresses bigger threats to ecosystem and agriculture. Previous studies reported that GmNAC019, a soybean NAC transcription factor - encoding gene, displayed induced expression upon drought treatment in wild-type cultivars. In this study, drought and salinity stresses were applied on GmNAC019-overexpressing Arabidopsis plants to verify the contribution of GmNAC019 in regulating plant response to the stress conditions. Results from the water loss rate and survival rate assays revealed that the transgenic line conferred improved tolerance to drought stress as evidenced by lower leaf water loss and significantly higher rate of survival than seen in the wild-type plants. Similarly, the survival rate assay for testing salinity effects on plants by growing the plants on MS medium supplemented with different NaCl concentrations also indicated that the transgenic plants had a better tolerance to salt stress as they displayed lower rate of root growth inhibition and higher survival rate. Taken these results altogether, it is suggested that GmNAC019 might play important role in aiding plant response to drought and salinity stresses. Specific functions of this gene should be elaborated in future studies to evaluate its potential application for crop improvement