Antibacterial activities of the extracts of Mimosa pudica L. an in-vitro study

Mimosa pudica L., also called sensitive plant or touch-me-not, belongs to the genus Mimosa (Family: Mimosaceae). This plant grows as a weed in nearly every parts of Vietnam and is used as a traditional medicine for the treatment of some diseases. This study aims to evaluate the antibacterial activity of the water and ethanol extracts of this plant by using disc diffusion method. The total flavonoid as quercetin equivalent (QE) per gram (dry weight) of these two extracts was also estimated. The result of tests for in-vitro antibacterial activity indicates that the ethanol extract showed significant activity against E.coli, S.aureus, B.subtilis and S.typhi with the zone of inhibition was 11mm, 19mm, 17mm and 16mm respectively. The water extract only inhibited the growth of S.aureus (14mm) and B.subtilis (15mm) and there was no resistance against E.coli and S.typhi. The analysis of total flavonoid content found that the ethanol extract contains higher amount of flavonoid than water extract and flavonoid is responsible mainly for the antibacterial activity of Mimosa pudica L

Ultrasonic-Assisted Cathodic Plasma Electrolysis Approach for Producing of Graphene Nanosheets

In this chapter, we review on the production of graphene by ultrasonic-assisted cathodic plasma electrolysis approach which involves a combination process of conventional electrolysis and plasma at ambient pressure and moderate temperature. Firstly, we review on the techniques for electrochemical preparation of graphene. Then, we briefly describe plasma electrolysis approach for producing of graphene. The mechanism, advantages, and disadvantages of this technique are discussed in detail

BoMb-OT: On Batch of Mini-batches Optimal Transport

Mini-batch optimal transport (m-OT) has been successfully used in practical applications that involve probability measures with intractable density, or probability measures with a very high number of supports. The m-OT solves several sparser optimal transport problems and then returns the average of their costs and transportation plans. Despite its scalability advantage, the m-OT does not consider the relationship between mini-batches which leads to undesirable estimation. Moreover, the m-OT does not approximate a proper metric between probability measures since the identity property is not satisfied. To address these problems, we propose a novel mini-batching scheme for optimal transport, named Batch of Mini-batches Optimal Transport (BoMb-OT), that finds the optimal coupling between mini-batches and it can be seen as an approximation to a well-defined distance on the space of probability measures. Furthermore, we show that the m-OT is a limit of the entropic regularized version of the BoMb-OT when the regularized parameter goes to infinity. Finally, we carry out extensive experiments to show that the BoMb-OT can estimate a better transportation plan between two original measures than the m-OT. It leads to a favorable performance of the BoMb-OT in the matching and color transfer tasks. Furthermore, we observe that the BoMb-OT also provides a better objective loss than the m-OT for doing approximate Bayesian computation, estimating parameters of interest in parametric generative models, and learning non-parametric generative models with gradient flow.Comment: 36 pages, 20 figure

Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data

Modern deep neural networks have achieved impressive performance on tasks from image classification to natural language processing. Surprisingly, these complex systems with massive amounts of parameters exhibit the same structural properties in their last-layer features and classifiers across canonical datasets when training until convergence. In particular, it has been observed that the last-layer features collapse to their class-means, and those class-means are the vertices of a simplex Equiangular Tight Frame (ETF). This phenomenon is known as Neural Collapse ($\mathcal{NC}$). Recent papers have theoretically shown that $\mathcal{NC}$ emerges in the global minimizers of training problems with the simplified ``unconstrained feature model''. In this context, we take a step further and prove the $\mathcal{NC}$ occurrences in deep linear networks for the popular mean squared error (MSE) and cross entropy (CE) losses, showing that global solutions exhibit $\mathcal{NC}$ properties across the linear layers. Furthermore, we extend our study to imbalanced data for MSE loss and present the first geometric analysis of $\mathcal{NC}$ under bias-free setting. Our results demonstrate the convergence of the last-layer features and classifiers to a geometry consisting of orthogonal vectors, whose lengths depend on the amount of data in their corresponding classes. Finally, we empirically validate our theoretical analyses on synthetic and practical network architectures with both balanced and imbalanced scenarios.Comment: 93 pages, 20 figures, 4 tables. Hien Dang and Tho Tran contributed equally to this wor

M^2UNet: MetaFormer Multi-scale Upsampling Network for Polyp Segmentation

Polyp segmentation has recently garnered significant attention, and multiple methods have been formulated to achieve commendable outcomes. However, these techniques often confront difficulty when working with the complex polyp foreground and their surrounding regions because of the nature of convolution operation. Besides, most existing methods forget to exploit the potential information from multiple decoder stages. To address this challenge, we suggest combining MetaFormer, introduced as a baseline for integrating CNN and Transformer, with UNet framework and incorporating our Multi-scale Upsampling block (MU). This simple module makes it possible to combine multi-level information by exploring multiple receptive field paths of the shallow decoder stage and then adding with the higher stage to aggregate better feature representation, which is essential in medical image segmentation. Taken all together, we propose MetaFormer Multi-scale Upsampling Network (M$^2$UNet) for the polyp segmentation task. Extensive experiments on five benchmark datasets demonstrate that our method achieved competitive performance compared with several previous methods

Lecane (Rotifera: Lecanidae) community in psammon habitat in Central Coast Vietnam: Diversity and relation to environmental condition

Characteristics of the Lecane (Rotifera) community in psammon in Central Coast Vietnam were investigated. A total of 50 taxa were identified in samples collected at hygropsammon zones of temporary pools, contributing 4 new species to rotifers' record of Vietnam. Psammonxenic species accounted for the largest percentage of Lecane community with 82%, followed by psammophiles (12%) and psammonbionts (6%). Influences of some environmental factors on the distribution of psammic lecanids were also observed. This group of organisms showed a slight tendency towards sand with grain sizes larger than 125 µm. Besides, other abiotic factors including pH, total phosphorus (TP) and total dissolved solids (TDS) were also found to significantly related to the distribution of some common Lecane species

Foreign direct investment in Vietnam: Is there any evidence of technological spillover effects

In the context of integrating more deeply into the world economy the Vietnamese policy makers have undertaken several measures to attract foreign direct investment to the country, with the culmination of FDI inflows in 2007 reaching over USD 20 billion, an increase of 69% over 2006. The policy has been taken on the ground that the FDI inflows will create employment and bring along the much needed technological advances, which will spill over to domestic firms. In this paper, we use a firm-level panel data constructed from the Census 2000-2005 to investigate not only the horizontal spillovers but also the backward and forward linkages. Adding to the current literature which focused mainly on the spillovers in the manufacturing sector, our paper provide the first estimates of the spillover effects in the service sector (at least in the context of developing countries). We also distinguish between the horizontal output spillovers (which capture demonstration effects and competition effects) and the horizontal employment spillover (which captures the labour mobility effect). The results obtained from our regression models are mixed. Different channels of spillovers are at work for the manufacturing and the service sectors. We find evidence of the positive backward technological spillovers for the manufacturing and positive horizontal spillovers for the service sector