Surface functionalised nano magnetic particles for waste water treatment: Removal of heavy metal

Master'sMASTER OF ENGINEERIN

Studying livestock breeding wastewater treatment with bentonite adsorbent

The possibility of using adsorbents (bentonite, diatomite and kaolinite) for obtaining adsorptive materials effective in livestock breeding wastewater treatment has been assessed. It has been shown on the example of ions of ammonia (NH4) and phosphate (PO43) that particles of bentonite have relatively high adsorption capacity. The data about adsorption kinetics have been processed with the use of first and second-order kinetic models. It has been revealed that the second-order kinetic model described better adsorption of ammonia and phosphate from aqueous solutions by particles of bentonit

A discretized point-hyperplane incidence bound in Rd\mathbb{R}^d

Let $P$ be a $\delta$-separated $(\delta, s, C_P)$-set of points in $B(0, 1)\subset \mathbb{R}^d$ and $\Pi$ be a $\delta$-separated $(\delta, t, C_\Pi)$-set of hyperplanes intersecting $B(0, 1)$ in $\mathbb{R}^d$. Define $$I_{C\delta}(P, \Pi)=\#\{(p, \pi)\in P\times \Pi\colon p\in \pi(C\delta)\}.$$ Suppose that $s, t\ge \frac{d+1}{2}$, then we have $I_{C\delta}(P, \Pi)\lesssim \delta |P||\Pi|$. The main ingredient in our argument is a measure theoretic result due to Eswarathansan, Iosevich, and Taylor (2011) which was proved by using Sobolev bounds for generalized Radon transforms. Our result is essentially sharp, a construction will be provided and discussed in the last section.Comment: 14 page

Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media

Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels. This kind of data makes the existing works suffer from many difficulties to handle, especially ones using deep learning approaches. In this paper, we propose an approach to handle this problem. This work is extended from our previous work, in which we proposed to combine the typical deep learning technique of Convolutional Neural Networks with domain knowledge. The combination is used for acquiring additional training data augmentation and a more reasonable loss function. In this work, we further improve our architecture by various substantial enhancements, including negation-based data augmentation, transfer learning for word embeddings, the combination of word-level embeddings and character-level embeddings, and using multitask learning technique for attaching domain knowledge rules in the learning process. Those enhancements, specifically aiming to handle short and informal messages, help us to enjoy significant improvement in performance once experimenting on real datasets.Comment: A Preprint of an article accepted for publication by Inderscience in IJCVR on September 201

Vietnam’s Accession to the World Trade Organization: Economic Projections to 2020

This study presents a set of assessments of the long term economic effects of Vietnam’s accession to the WTO. Generally speaking, our results indicate that Vietnam would benefit from accelerating its participation in more open multilateralism. However, it is also clear from our analysis that these benefits will remain modest in the absence of comprehensive and complementary domestic economic reforms. Passive external liberalization, even when coupled with determined domestic reform, is inferior to WTO participation combined with negotiated market access and other activist multilateral agreements. Finally, our analysis shows that capital insufficiency is a very serious constraint on Vietnamese economic growth and diversification. Capital market reform can play an essential role in dynamic and sustained economic development for the country.Vietnam, WTO, Trade

Applications of Mach-Zehnder Interferometry to Studies on Local Deformation of Polymers Under Photocuring

A Mach‐Zehnder interferometer (MZI) was built and modified to in situ monitor the deformation of polymers during the photocuring process. In this review, the working principle and method of operation of this MZI were explained together with the method of data analysis. As the examples for the utilization of this modified MZI, measurements of the deformation induced by photopolymerization was demonstrated for three different types of samples: homopolymer in the bulk state, miscible polymer blends and phase‐separated polymer blends. Finally, a concluding remark is provided for the usage of MZI in polymer research

EmbryosFormer: Deformable Transformer and Collaborative Encoding-Decoding for Embryos Stage Development Classification

The timing of cell divisions in early embryos during the In-Vitro Fertilization (IVF) process is a key predictor of embryo viability. However, observing cell divisions in Time-Lapse Monitoring (TLM) is a time-consuming process and highly depends on experts. In this paper, we propose EmbryosFormer, a computational model to automatically detect and classify cell divisions from original time-lapse images. Our proposed network is designed as an encoder-decoder deformable transformer with collaborative heads. The transformer contracting path predicts per-image labels and is optimized by a classification head. The transformer expanding path models the temporal coherency between embryo images to ensure monotonic non-decreasing constraint and is optimized by a segmentation head. Both contracting and expanding paths are synergetically learned by a collaboration head. We have benchmarked our proposed EmbryosFormer on two datasets: a public dataset with mouse embryos with 8-cell stage and an in-house dataset with human embryos with 4-cell stage. Source code: https://github.com/UARK-AICV/Embryos.Comment: Accepted at WACV 202

Genetic diversity of gac [Momordica cochinchinensis (Lour.) Spreng] accessions collected from Mekong delta of Vietnam revealed by RAPD markers

Abstract Gac (Momordica cochinchinensis (Lour.) Spreng) (2n = 28) belongs to the Cucurbitaceae family. It is indigenous throughout in Vietnam as well as in South East Asia. To estimate the genetic diversity, 20 gac accessions collected in Mekong river delta were analyzed using 10 RAPD primers. Total of 126 fragments were obtained from ten RAPD primers, with 114 polymorphic fragments, and average of 11.4 fragments per primer. The high level of polymorphism (90.4%) was found across 20 gac accessions. The high est Nei's gene diversity value among gac accessions was H = 0.40, and the lowest was H = 0.29 with a mean of 0.36. The highest Shannon diversity index value among gac accessions was H' = 0.58 and the lowest was H' = 0.46 with an average of 0.53. Cluster analysis for genetic relationship between accessions displayed that 20 gac accessions grouped into four main clusters which genetic distance coefficient ranged from 0.29 to 0.64 and with an average of 0.54. There were defined groups according to their locations. According to these results, RAPD technique can be useful tool in genetic diversity evaluation of gac. The information achieved could also be useful for gac breeding program, cultivar differentiation and conservation