Synthesis of chemical tools for targeted epigenetic modifications

DNA methylation is an important epigenetic modification that regulates gene expression, thereby playing a crucial role in biological processes including cellular development but also disease progression. Abnormal methylation patterns such as gene promoter hypermethylation are the most common molecular lesions found in cancer. Since DNA methylation is a reversible process, DNA methyltransferases (DNMTs) – the enzymes responsible for the maintenance of methylation patterns - are regarded as very attractive therapeutic targets. To date, several DNMT inhibitors have been developed to reverse DNA hypermethylation. The clinically approved azanucleosides 5-azacytidine and 5-aza-2′-deoxycytidine have high demethylating potency, but their use has remained limited due to their nonspecific activity and cytotoxic side-effects. The lack of techniques for targeted tissue-specific demethylation not only limits therapeutic potential but also restricts our understanding of the functional significance of DNA methylation in a number of biological processes, including cellular development and regeneration. The aim of this thesis was to develop small molecule tools that could achieve spatiotemporally targeted demethylation through light-based activation. We have used a photocaging strategy to synthesise six novel photocaged azanucleoside analogues. These analogues remained biologically inert until light illumination induced the release of active azanucleosides with moderate-to-high rates and efficiencies. It was found that the caging position strongly influenced the photochemical properties and aqueous stabilities of the photocaged analogues. The analogue with the fastest uncaging rate and best aqueous stability 3′-DEACMOC-dAC was evaluated for its biological performance in a number of cancer cell lines. Global DNA methylation analysis showed that the analogue achieved light-dependent demethylation at lower concentration treatments. However, at higher concentrations unexpected activity was observed in the absence of light, prompting further investigation using mass spectrometry analysis

ASEAN- Australia Trade Relations by Stages of Processing: Comparative Research

ASEAN and Australia became the dialogue partner in 1974. Over 46 years of cooperation and development, ASEAN- Australia relations have achieved many good results, especially in recent years when two sides participate in several free trade agreements (FTAs) at bilateral levels and multilateral levels. In 2014, Australia and ASEAN formally became strategic partners, recognizing the importance of the relationship in building mutual benefits. Participation in FTAs and relationship upgrading has helped bilateral trade growth. In 2018-2019, Australia was the seventh-largest trading partner of ASEAN and ASEAN was one of Australia's top three trading partner, however, the two sides face many challenges such as the difficulties after the global crisis since 2009, the "spaghetti bowl" phenomenon of joining many agreements at the same time. Thus, to solve these problems, the production and exporting of comparative advantage goods by the stages of processing to participate in an ideal regional supply chain are very important. Based on the comparative theory and supply chain perspectives The paper compared revealed comparative advantage indexes of ASEAN countries and Australia from 2009 through 2018 to find which country in ASEAN is Australia's suitable partner from which provided the ideal effective supply chain distribution. After that, through trade value comparison, the paper examed if ASEAN countries and Australia specialized in production by stages of processing. From the results, appropriate recommendations were provided to enhance the trade relations between ASEAN and Australia

Computation Offloading and Resource Allocation for Backhaul Limited Cooperative MEC Systems

In this paper, we jointly optimize computation offloading and resource allocation to minimize the weighted sum of energy consumption of all mobile users in a backhaul limited cooperative MEC system with multiple fog servers. Considering the partial offloading strategy and TDMA transmission at each base station, the underlying optimization problem with constraints on maximum task latency and limited computation resource at mobile users and fog servers is non-convex. We propose to convexify the problem exploiting the relationship among some optimization variables from which an optimal algorithm is proposed to solve the resulting problem. We then present numerical results to demonstrate the significant gains of our proposed design compared to conventional designs without exploiting cooperation among fog servers and a greedy algorithm

Investigation of the pollution status and the waste reusing ability in trade village Duong Lieu, Hoai Duc, Hanoi: Short communication

Vietnam has about 2,000 trade villages locating mainly in the north. Duong Lieu village in Hoai Duc, Hanoi, is one of the key areas of agricultural production and food processing. However, this area is affected by serious environmental pollution, particularly caused by solid waste and wastewater. Solid wastes of the starch production process from arrowroot are disposed in large amounts and represent the main reason for environmental pollution in Duong Lieu village. These wastes are present anywhere in this village, for example on the main road, in gardens, event fill in ponds and ditches. The components of the dried arrowroot waste are mainly carbon-rich substances such as starch (5%), cellulose (90%) and N, P, K (0.5%; 0.11%; 0.16%, respectively). The fresh arrowroot waste has humidity of up to 80%. This substrate is suitable for culture of straw mushroom and oyster mushroom. The mushrooms use cellulose as carbon source for their growth. Therefore, waste from arrowroot that can be recycled efficiently by the biological method for culturing mushrooms. This treatment method is suitable to the conditions of Vietnam because it does not only reduce waste residues but also is environmentally friendly.Việt nam có khoảng 2000 làng nghề và tập trung chủ yếu ở miền Bắc. Dương Liễu là một trong những vùng trọng điểm chế biến nông sản thực phẩm. Song hiện tại khu vực này đang bị ô nhiễm môi trường nghiêm trọng,đặc biệt ô nhiễm rác thải và nước thải. Chất thải rắn của quá trình chế biến tinh bột từ củ dong là rất lớn. Nó có mặt khắp nơi từ trong nhà ra ngoài ngõ thậm chí lấp đầy cống rãnh, ao hồ. Đây chính là nguyên nhân gây nên ô nhiễm môi trường vùng làng nghề. Thành phần của bã dong rất giàu cellulose (90%), tinh bột (5%) và có cả nitơ, photpho, kali tương với 0,5%, 0,11% và 0,16%; độ ẩm của bã dong tươi lên tới 80%. Cơ chất này thích hợp để trồng nấm rơm và nấm sò. Bởi các loại nấm này sử dụng cellulose là nguồn cung cấp cacbon chính để sinh trưởng. Do vậy, bã thải từ củ dong có thể được tái sử dụng hiệu quả bằng phương pháp sinh học như là dùng trồng nấm. Đây là một sự lựa chọn phù hợp với điều kiện Việt Nam, vừa giảm thiểu chất thải dư thừa vừa thân thiện với môi trường

The Impact of Education on Child Abuse Prevention

This research investigates the impact of education on child abuse prevention in Vietnam by using Vietnamese government's reports (2012 – 2019) on child abuse. In order to analyze the impact of education on child abuse prevention, this study focuses on reviewing the previous policies in preventing child abuse, surveying three main determinants of parents, teachers and children and testing the data collected from the survey. The result shows that education plays an important role in improving the ability to take actions against child abuse. Some recommendations to parents, teachers, children and the government are also proposed for encouraging improvements in child abuse prevention education. Keywords: Child Abuse Prevention, Education, Vietnam DOI: 10.7176/EJBM/12-20-09 Publication date:July 31st 202

Batch Clipping and Adaptive Layerwise Clipping for Differential Private Stochastic Gradient Descent

Each round in Differential Private Stochastic Gradient Descent (DPSGD) transmits a sum of clipped gradients obfuscated with Gaussian noise to a central server which uses this to update a global model which often represents a deep neural network. Since the clipped gradients are computed separately, which we call Individual Clipping (IC), deep neural networks like resnet-18 cannot use Batch Normalization Layers (BNL) which is a crucial component in deep neural networks for achieving a high accuracy. To utilize BNL, we introduce Batch Clipping (BC) where, instead of clipping single gradients as in the orginal DPSGD, we average and clip batches of gradients. Moreover, the model entries of different layers have different sensitivities to the added Gaussian noise. Therefore, Adaptive Layerwise Clipping methods (ALC), where each layer has its own adaptively finetuned clipping constant, have been introduced and studied, but so far without rigorous DP proofs. In this paper, we propose {\em a new ALC and provide rigorous DP proofs for both BC and ALC}. Experiments show that our modified DPSGD with BC and ALC for CIFAR-$10$ with resnet-$18$ converges while DPSGD with IC and ALC does not.Comment: 20 pages, 18 Figure

Generalizing DP-SGD with Shuffling and Batch Clipping

Classical differential private DP-SGD implements individual clipping with random subsampling, which forces a mini-batch SGD approach. We provide a general differential private algorithmic framework that goes beyond DP-SGD and allows any possible first order optimizers (e.g., classical SGD and momentum based SGD approaches) in combination with batch clipping, which clips an aggregate of computed gradients rather than summing clipped gradients (as is done in individual clipping). The framework also admits sampling techniques beyond random subsampling such as shuffling. Our DP analysis follows the $f$-DP approach and introduces a new proof technique which allows us to derive simple closed form expressions and to also analyse group privacy. In particular, for $E$ epochs work and groups of size $g$, we show a $\sqrt{g E}$ DP dependency for batch clipping with shuffling.Comment: Update disclaimer