Discussion for Titanium Peroxides and Their Application for Dealing with Zombie Shrimp Issue
Food safety was an important issue recently. Today sodium percarbonate was used to fake the vitality of shrimps to earn a good sell. However, it may cause harm to health because of the peroxides left over. To handle this problem, we set up two goals to achieve: detecting them and then removing them. In the past, the titration skill was an easy method for determining the concentration of H2O2. It not only spent too much time but also resulted in errors commonly. In this research, titanium sulfate and citric acid were used to prepare the colorimetric reagent. To measure the peroxides in water, several factors were controlled and the SOP for detecting and the calibration line for peroxides finally established. In practical, we turned the colorimetric reagent into the fast test paper which was easily for use. The other part of this research was to clear up the peroxides in water. We use titanium sulfate, hydrogen peroxide and citric acid as starting material via hot-bath method to prepare the nano-photocatalyst of titanium dioxide. Since the powder was inconvenient to deal with large amount of water. The powder-like TiO2 was further made into ball-shaped TiO2 in favor of water treatment and reuse. It was found that the photocatalytic performance of ball-shaped TiO2 was effective to be on duty for removal of the peroxides. In summary, this research provided two techniques to deal with the zombie shrimp. The novel method for synthesis of TiO2 catalyst and the preparation of colorimetric reagent for fast test paper were all in low cost. They had great potential to develop in marketing demand.
An Efficient and Accurate Super-Resolution Approach to Low-Field MRI via U-Net Architecture With Logarithmic Loss and L2 Regularization
Low-field (LF) MRI scanners have the power to revolutionize medical imaging by provid- 27 ing a portable and cheaper alternative to high-field MRI scanners. However, such scanners are usu- 28 ally significantly noisier and lower quality than their high-field counterparts. This prevents them 29 from appealing to global markets. The aim of this paper is to improve the SNR and overall image quality of low-field MRI scans (called super-resolution) to improve diagnostic capability and, as a result, make it more accessible. To address this issue, we propose a Nested U-Net neural network architecture super-resolution algorithm that outperforms previously suggested super-resolution deep learning methods with an average PSNR of 78.83 ± 0.01 and SSIM of 0.9551 ± 0.01. Our ANOVA paired t-test and Post-Hoc Tukey test demonstrate significance with a p-value < 0.0001 and no other network demonstrating significance higher than 0.1. We tested our network on artificial noisy downsampled synthetic data from 1500 T1 weighted MRI images through the dataset called the T1- mix. Four board-certified radiologists scored 25 images (100 image ratings total) on the Likert scale (1-5) assessing overall image quality, anatomical structure, and diagnostic confidence across our architecture and other published works (SR DenseNet, Generator Block, SRCNN, etc.). Our algo- rithm outperformed all other works with the highest MOS, 4.4 ± 0.3. We also introduce a new type of loss function called natural log mean squared error (NLMSE), outperforming MSE, MAE, and MSLE on this specific SR task. Additionally, we ran inference on actual Hyperfine scan images with successful qualitative results using a Generator RRDB block. In conclusion, we present a more ac- curate deep learning method for single image super-resolution applied to low-field MRI via a 45 Nested U-Net architecture.
In silico identification and physicochemical analysis of potential novel antimicrobial peptides from Momordica charantia L.
The emergence of antibacterial resistance has necessitated the development of alternative treatments, such as antimicrobial peptides (AMPs). AMPs are part of the innate immune systems of various organisms such as Momordica charantia L., a known medicinal plant in Southeast Asia. In this study, potential novel AMPs from M. charantia were derived in silico to provide prospective antibiotic alternatives using promising plant-based peptides. M. charantia protein sequences that were 500 amino acids long were digested using proteolytic enzymes, resulting in 3,621 peptides. Each resulting sequence was characterized as either AMP or Non-AMP using four statistical analysis tools, and those identified as AMPs were analyzed. This led to 102 AMPs, 53 of which were unregistered on the Data Repository for Antimicrobial Peptides, indicating that they have yet to be derived from other species. Six of the eight studied physicochemical properties show strong correlations with each other, suggesting that subsequent AMP design studies may focus on these six properties. As such, M. charantia may be a rich source of potential AMPs and, thereby, alternative antibiotics. The in vitro examination of these novel AMPs is also recommended to further understand their potential as alternative antibiotics sourced from locally available plants.
Study of regenerative and ontogenetic processes under the influence of EHF EMR.
The increased sensitivity of aquatic organisms to the effects of EMF has been proven by numerous experimental studies. It has been repeatedly noted that exposure to EMF of certain frequencies and intensities leads to disruption of physiological functions, orientation in time and space, changes in the behavior of organisms, suppression of motor activity. Other ranges of electromagnetic radiation, on the contrary, can cause the effects of increased regeneration, growth rate and survival. In connection with these trends, the purpose of our research is to analyze the effects of the influence of electromagnetic radiation of extremely high frequency on the development of the Xenopus laevis and the regeneration of newts and planarians