Journal of Smart Science and Technology最新文献

筛选
英文 中文
Use of Selected Spectral Ratios to Assess the Response of Pineapple to Potassium Nutrition 利用选定的光谱比评价菠萝对钾营养的反应
Journal of Smart Science and Technology Pub Date : 2021-09-26 DOI: 10.24191/JSST.V1I1.11
S. K. Balasundram, Y. Chong
{"title":"Use of Selected Spectral Ratios to Assess the Response of Pineapple to Potassium Nutrition","authors":"S. K. Balasundram, Y. Chong","doi":"10.24191/JSST.V1I1.11","DOIUrl":"https://doi.org/10.24191/JSST.V1I1.11","url":null,"abstract":"Potassium (K) nutrition in pineapple grown on tropical peat can be problematic due to high precipitation which encourages leaching losses. Non-destructive tools that can assess K deficiency and the accompanying changes in biophysical and biochemical properties within pineapple is a good strategy to employ. In this study, we assessed the biophysical changes in pineapple (var. MD2) in response to different K rates by using a hyperspectral approach. K deficiency was detected at 171 days after planting. Shortage of K also exhibited a shift in red edge towards shorter wavelengths between 500-700 nm. In addition, spectral ranges of 430-680 nm, as well as 680-752 nm were found to be most effective in differentiating spectral response to varying K rates. Three vegetation indices, i.e. Normalized Pigment Chlorophyll Index (NPCI), Plant Senescence Index (PSRI) and Red-edge Vegetation Index (RVSI) were found to best describe K treatment effects on pineapple canopy reflectance. This study could be extended further to include pineapple varieties other than MD2, and also key nutrients, such as N and P, for better fertilizer management in peat-grown pineapple.","PeriodicalId":17117,"journal":{"name":"Journal of Smart Science and Technology","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89248219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Challenges and Way Forward for Implementing Green Roof in Construction Industry in Sarawak, Malaysia 马来西亚沙捞越州建筑行业实施绿色屋顶的挑战与未来
Journal of Smart Science and Technology Pub Date : 2021-09-26 DOI: 10.24191/JSST.V1I1.13
N. A. Rahim, A. Bohari, A. Adnan, N. Khalil, A. Olanipekun
{"title":"Challenges and Way Forward for Implementing Green Roof in Construction Industry in Sarawak, Malaysia","authors":"N. A. Rahim, A. Bohari, A. Adnan, N. Khalil, A. Olanipekun","doi":"10.24191/JSST.V1I1.13","DOIUrl":"https://doi.org/10.24191/JSST.V1I1.13","url":null,"abstract":"There is a growing global concern about the adverse effects of today's rapid economic growth and development, which impact the environment and deplete energy supply. A green roof may lower a building's energy consumption and minimise air pollution by reducing dust particles in the air. The primary impediment to green roof implementation in Malaysia lacks local knowledge and unskilled green roof specialists. As a result, there is a shortage of green roof installers and specialised firms in the country. This article discusses the problems and solutions of adopting green roofs in building projects based on construction industry experience in Sarawak. A survey utilising a questionnaire is used to obtain data for this research. The paper revealed the possible challenges of adopting a green roof for the construction industry. The study is critical in order to adopt green roof technology quickly in Malaysia.","PeriodicalId":17117,"journal":{"name":"Journal of Smart Science and Technology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89575531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Predicting AAK1/GAK Dual-Target Inhibitor against SARS-CoV-2 Viral Entry into Host Cells: An in silico Approach 预测AAK1/GAK双靶点抑制剂对SARS-CoV-2病毒进入宿主细胞的影响:一种计算机方法
Journal of Smart Science and Technology Pub Date : 2021-09-26 DOI: 10.24191/JSST.V1I1.14
Xavier Chee Wezen, Cl Wen, Li Ping, Yeong Kah Ho, K. Qing, Christopher Ha, Hwang Siaw San
{"title":"Predicting AAK1/GAK Dual-Target Inhibitor against SARS-CoV-2 Viral Entry into Host Cells: An in silico Approach","authors":"Xavier Chee Wezen, Cl Wen, Li Ping, Yeong Kah Ho, K. Qing, Christopher Ha, Hwang Siaw San","doi":"10.24191/JSST.V1I1.14","DOIUrl":"https://doi.org/10.24191/JSST.V1I1.14","url":null,"abstract":"Clathrin-mediated endocytosis (CME) is a normal biological process where cellular contents are transported into the cells. However, this process is often hijacked by different viruses to enter host cells and cause infections. Recently, two proteins that regulate CME – AAK1 and GAK – have been proposed as potential therapeutic targets for designing broad-spectrum antiviral drugs. In this work, we curated two compound datasets containing 83 AAK1 inhibitors and 196 GAK inhibitors each. Subsequently, machine learning methods, namely Random Forest, Elastic Net and Sequential Minimal Optimization, were used to construct Quantitative Structure Activity Relationship (QSAR) models to predict small molecule inhibitors of AAK1 and GAK. To ensure predictivity, these models were evaluated by using Leave-One-Out (LOO) cross validation and with an external test set. In all cases, our QSAR models achieved a q2LOO in range of 0.64 to 0.84 (Root Mean Squared Error; RMSE = 0.41 to 0.52) and a q2ext in range of 0.57 to 0.92 (RMSE = 0.36 to 0.61). Besides, our QSAR models were evaluated by using additional QSAR performance metrics and y-randomization test. Finally, by using a concensus scoring approach, nine chemical compounds from the Drugbank compound library were predicted as AAK1/GAK dual-target inhibitors. The electrostatic potential maps for the nine compounds were generated and compared against two known dual-target inhibitors, sunitinib and baricitinib. Our work provides the rationale to validate these nine compounds experimentally against the protein targets AAK1 and GAK.","PeriodicalId":17117,"journal":{"name":"Journal of Smart Science and Technology","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84333291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信