http://stdj.scienceandtechnology.com.vn/index.php/stdj/issue/feed Science and Technology Development Journal 2022-05-11T20:41:14+00:00 Phuc Van Pham pvphuc@vnuhcm.edu.vn Open Journal Systems http://stdj.scienceandtechnology.com.vn/index.php/stdj/article/view/3802 The suitable distribution area of artichoke (Cynara scolymus L.) in the Hoang Lien Son Mountain range (Lao Cai Province) 2022-05-11T03:14:58+00:00 Truong Ngoc Kiem kiemtn@vnu.edu.vn Nguyen Ngoc Cong congdng.nb914@gmail.com <p>Hoang Lien Son is a high, rugged mountain range in the northwest region of Vietnam where many ethnic minorities gather, and due to socioeconomic characteristics, the life of the people here still faces many difficulties. Artichoke is a medicinal plant with high economic value and favorable growth in temperate climates and is one of the options for sustainable economic development for people in mountainous areas. The study used a multicriteria analysis method on AHP to analyze the influence of ecological factors of the Hoang Lien Son area (Lao Cai Province) on the growth and development of artichokes. The weights from the AHP model are used to establish ecological adaptation maps through geographic information system (GIS) software. The research results show that the most suitable areas (S1 and S2) for the development of artichokes have an area of 125,642.72 hectares, accounting for 34.41% of the study area. However, the area with the highest adaptability (S1) for growing artichokes is not large, located at an altitude of over 1000 m, mainly at 1700 m in the territory of Sapa town and some communes in Bat Xat district. The results provide the scientific basis for planning potential planting areas and exploiting and developing artichokes to improve livelihoods and people's lives, contributing to biodiversity conservation and sustainable development.</p> 2022-05-11T00:00:00+00:00 ##submission.copyrightStatement## http://stdj.scienceandtechnology.com.vn/index.php/stdj/article/view/3890 DFT insight into the high stability of single Pt atoms on the CeO2(111) surface 2022-05-11T06:33:33+00:00 Thang Viet Ho hvthang@dut.udn.vn Hop Quy Van vanquyhop97@gmail.com Thong Le Minh Pham phamleminhthong@gmail.com <p><strong>Introduction</strong>: Single Pt atom catalysts supported on CeO2(111) surfaces have attracted considerable attention in recent years due to their high reactivity and selectivity in important reactions, such as water–gas shift reactions for hydrogen production and CO oxidation. However, the geometrical and electronic structure of Pt/CeO2(111) at the atomic level is still not clearly understood. In this study, we aim to gain insight into the geometrical and electronic structure of a single Pt atom on the CeO2(111) surface.</p> <p><strong>Methodology</strong>: Various single Pt atom species, including (Pt)ads, (PtOH)ads, (PtO)ads, (PtO2H2)ads, (PtO2)ads, (Pt)subCe, and (Pt)subO, deposited on the CeO2(111) surface were investigated by the DFT+U method with dispersion corrections. Furthermore, the CO molecule was adopted to evaluate the electronic structures of these single Pt atoms. In addition, the supported Pt3 cluster was applied as a metallic model to distinguish it from single Pt atom models.</p> <p><strong>Results</strong>: By comparing the CO adsorption properties of single Pt atom models and Pt3 cluster models to those of experimental observations in the literature, the stretching frequency of CO on (PtO2)ads species agrees well with the experimental results, while the frequencies of CO on other single Pt atom structures and on Pt3 clusters largely differ from the experimental results.</p> <p><strong>Conclusion</strong>: Based on the DFT calculated results, we conclude that the activity and high stability of single Pt atom species that were observed from the experiment are formed via the interaction between Pt and two extra O atoms on the CeO2(111) surface.</p> 2022-05-11T00:00:00+00:00 ##submission.copyrightStatement## http://stdj.scienceandtechnology.com.vn/index.php/stdj/article/view/3896 Chemical constituents of the lichen Usnea lapponica Vain., Parmeliaceae 2022-05-11T06:37:34+00:00 Nguyen Huu Tri trihuunguyen@sgu.edu.vn Dung Thi My Nguyen nguyenthimydung121285@gmail.com <p><strong>Introduction</strong>: The lichen Usnea lapponica Vain. belonging to the Usnea genus (family Parmeliaceae) grow hanging from tree branches in the damp forest at Bidoup Nui Ba National Park, Dam Rong district, Lam Dong province. In addition, this lichen has not yet been chemically and biologically studied. The primary goal of the present work was to study the chemical constituents of the lichen Usnea lapponica Vain.</p> <p><strong>Methods</strong>: A dried powder of thalli Usnea lapponica Vain. was extracted by maceration with MeOH at ambient temperature to prepare the crude MeOH extract. This crude extract was subjected to silica gel column chromatography with gradient polar solvent including n-hexane, CHCl3, EtOAc, and MeOH to separate into different polar fractions. The chemical structures of the isolated compounds were elucidated through the interpretation of their 1D and 2D NMR and HRESIMS data.</p> <p><strong>Results</strong>: In this paper, we reported the isolation of six known compounds, including two depsides lecanorin (1) and isolecanoric acid (2), two depsidones norstictic acid (3) and methylstictic acid (4), an ergosterol, 22E,24R-5α,6α-epoxyergosta-8,22-diene-3β,7α-diol (5), and lupeol (6).</p> <p><strong>Conclusion</strong>: This is the first time that these compounds have been reported from Usnea lapponica Vain.</p> 2022-05-11T00:00:00+00:00 ##submission.copyrightStatement## http://stdj.scienceandtechnology.com.vn/index.php/stdj/article/view/3895 Omicron: Flighty factor challenging global vaccine campaigns or the ending signal of the COVID-19 pandemic 2022-05-02T21:55:22+00:00 http://stdj.scienceandtechnology.com.vn/public/journals/2/article_3895_cover_en_US.png Giang Thi Kim Lien phamvanphuc2308@gmail.com Nguyen Thi Bao Anh phamvanphuc2308@gmail.com Le Nguyen Thien Han phamvanphuc2308@gmail.com Le Tu Manh Huy phamvanphuc2308@gmail.com Le Thi Ngoc Tam phamvanphuc2308@gmail.com Nguyen Tran Phuoc Thuan phamvanphuc2308@gmail.com Hien Minh Nguyen nmhien@medvnu.edu.vn <p>Coronavirus disease 2019 (COVID-19) has been a great global public health issue for two years. In November 2021, a new variant, B.1.1.529, of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified in South Africa and caused a rapid rise in COVID-19 cases. On 26 November 2021, the World Health Organization (WHO) named this variant Omicron and classified it as a variant of concern (VoC). The spike protein of this variant contains a high number of mutations, raising concerns about viral transmissibility, pathogenicity, immune evasion, and neutralization by antibodies. When the early Omicron surge occurred, preliminary data showed that the transmission of this variant was extremely fast, but the number of patients with severe symptoms was low. This review will describe the characteristics of the Omicron variant and compare the mutations of the spike in the five VoCs. We also look over research and opinions on the Omicron variant and evaluate epidemiological data from the Omicron wave and the Delta wave. In the review discussion, we will discuss Omicron whether it is a challenge for global vaccine campaigns, whether it is a sign of a waning pandemic, and how we acknowledge the new variant and future of the COVID-19 pandemic.</p> 2022-05-02T21:55:21+00:00 ##submission.copyrightStatement## http://stdj.scienceandtechnology.com.vn/index.php/stdj/article/view/3894 Breast cancer diagnosis based on detecting lymph node metastases using deep learning 2022-05-11T20:41:14+00:00 Bich Ha Thach Nguyen hatuny97@gmail.com Bich Ngoc Le lnbich@hcmiu.edu.vn Trinh Ngoc Huynh hntrinh@ump.edu.vn Hai Thanh Le lthai@hcmut.edu.vn Thu Hien Thu Pham ptthien@hcmiu.edu.vn <p><strong>Introduction</strong>: Automated detection of metastatic breast cancer from whole slide images of lymph nodes utilizing a deep convolutional neural network was proposed in this study.</p> <p><strong>Methods</strong>: The dataset is taken from the PatchCamelyon subset, which contains 220,025 images divided into training, validation, and testing sets at a ratio of 60:20:20. The pretrained ResNet50 model was utilized, and transfer learning was subsequently applied to adjust the weights of the model. To elevate the model performance, the evaluation metrics were assessed by the accuracy score, confusion matrix, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) score.</p> <p><strong>Results</strong>: As a result, the proposed algorithm obtained high performance, with scores over 95% in all the evaluation methods, especially the AUC score, which achieved 0.989. Moreover, the model is validated in a testing set with the test-time augmentation (TTA) technique to enhance prediction quality and reduce generalization error.</p> <p><strong>Conclusion</strong>: Overall, the proposed model achieves high accuracy when applying transfer learning. The results prove that the trained Resnet50 model can extract useful information from small cells in histopathologic images for breast cancer detection.</p> 2022-05-12T00:00:00+00:00 ##submission.copyrightStatement##