In vitro mutagenesis of Cymbidium La bell “Anna Belle” by γ-rays irradiation and oligochitosan interaction

The optimum media for multiplication of protocorm like bodies (PLBs) and shoot buds of Cymbidium La bell “Anna Belle” were studied in order to prepare the in vitro samples for irradiation. The values of LD50 (lethal dose of 50% samples) of PLBs, shoot buds and plantlets of tested Cymbidium after cultivation of 4 months were also determined about 35.0, 41.0 and 83.1 Gy, respectively. The addition of oligochitosan played as an very important trigger for promotion on the generation of shoot bud from PLBs after irradiation. The in vitro variations have been generated by γ-rays irradiation of PLBs with doses in range of 20 - 50 Gy. The highest mutant frequency (3.83‰) of C. La bell was found by the irradiation of PLB samples at 30 Gy. The different properties of obtained in vitro variations compared to wild types were found to be chlorophyll, short leaves, long leaves, and violet pericardium variations. The genetic relationships among generated variant lines in M1V4 and wild type were analyzed using RAPD techniques

Rate of convergence in the Smoluchowski-Kramers approximation for mean-field stochastic differential equations

In this paper we study a second-order mean-field stochastic differential systems describing the movement of a particle under the influence of a time-dependent force, a friction, a mean-field interaction and a space and time-dependent stochastic noise. Using techniques from Malliavin calculus, we establish explicit rates of convergence in the zero-mass limit (Smoluchowski-Kramers approximation) in the $L^p$-distances and in the total variation distance for the position process, the velocity process and a re-scaled velocity process to their corresponding limiting processes

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}

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

An Investigation of Barriers to Adopt Green Innovation Among Manufacturing Organizations in Vietnam

This research aims to identify the main barriers to green innovation in Vietnam manufacturing organizations. This study began by reviewing the relevant literature and providing a solid theoretical framework to understand the determinants of green innovation for manufacturing firms in the global context. It also helps internal and external stakeholders figure out what influence and how to implement green innovation more efficiently by removing all impediments. Additionally, this article is considered a valuable and rational evidence for prioritizing and directing innovation policies in the manufacturing industry. Based on numerical data from 143 employees at middleand upper-level managers among manufacturing companies around Vietnam, the study found that deficiency of financial resources primarily significantly impacts green innovation adoption, followed by the uncertainty of market demand and lack of government support. However, with limited observations, the investigation did not observe the dynamic effect of green innovation over periods and only focused on the manufacturing sector instead of different industries for generalizing the research results. Moreover, the circumstances of green innovation would be diverse in other nations. Keywords: green innovation, manufacturing organizations, government supports, financial barriers, market barrier

A breakthrough dynamic-osmotic membrane bioreactor/nanofiltration hybrid system for real municipal wastewater treatment and reuse.

This study designed a Dynamic-Osmotic membrane bioreactor/nanofiltration (OsMBR/NF) system for municipal wastewater treatment and reuse. Results indicated that a continuously rotating FO module with 60 RPM in Dynamic-OsMBR system could enhance shear stress and reduce cake layer of foulants, leading to higher flux (50%) compared to Traditional-OsMBR during a 40-operation day. A negligible specific reverse salt flux (0.059 G/L) and a water flux of 2.86 LMH were recorded when a mixture of 0.1 M EDTA-2Na/0.1 M Na2CO3/0.9 mM Triton114 functioned as draw solution (DS). It was found that the Dynamic-OsMBR/NF hybrid system could effectively remove pollutants (∼98% COD, ∼99% PO43-P, ∼93% NH4+-N, > 99% suspended solids) from wastewater. In short, this developed system can be considered a breakthrough technology as it successfully minimizes membrane fouling by shear force, and achieves high water quality for reuse by two membrane- barriers

Inverse kinematic control algorithm for a welding robot - positioner system to trace a 3D complex curve

The welding robots equipped with rotary positioners have been widely used in several manufacturing industries. However, for welding a 3D complex weld seam, a great deal of points should be created to ensure the weld path smooth. This is a boring job and is a great challenge - rotary positioner system since the robot and the positioner must move simultaneously at the same time. Therefore, in this article, a new inverse kinematics solution is proposed to generate the movement codes for a six DOFs welding robot incorporated with a rotary positioner. In the algorithm, the kinematic error is minimized, and the actual welding error is controlled so that it is always less than an allowable limit. It has shown that the proposed algorithm is useful in developing an offline CAD-based programming tool for robots when welding complex 3D paths. The use of the algorithm increases the accuracy of the end-effector positioning and orientation, and reduces the time for teaching a welding robot - positioner system. Simulation scenarios demonstrate the potency of the suggested method