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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
Pub Date : 2021-09-26 DOI: 10.24191/JSST.V1I1.11
S. K. Balasundram, Y. Chong
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.
在热带泥炭上生长的菠萝的钾(K)营养可能会出现问题,因为高降水会促进淋失。非破坏性的工具可以评估缺钾和伴随的菠萝生物物理和生化特性的变化是一个很好的策略。在这项研究中,我们利用高光谱方法评估了菠萝(品种MD2)对不同钾率的生物物理变化。植后171 d出现缺钾现象。缺K也表现出红边向500-700 nm之间较短波长偏移。此外,430 ~ 680 nm和680 ~ 752 nm的光谱范围是区分不同K速率下光谱响应的最有效波段。归一化色素叶绿素指数(NPCI)、植物衰老指数(PSRI)和红边植被指数(RVSI)三个植被指数最能描述钾处理对菠萝冠层反射率的影响。这项研究可以进一步扩展到MD2以外的菠萝品种,以及关键的营养成分,如氮和磷,以更好地管理泥炭菠萝。
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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
Pub Date : 2021-09-26 DOI: 10.24191/JSST.V1I1.13
N. A. Rahim, A. Bohari, A. Adnan, N. Khalil, A. Olanipekun
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.
当今快速的经济增长和发展对环境造成了影响并消耗了能源供应,全球对这种不利影响日益感到关切。绿色屋顶可以降低建筑物的能源消耗,并通过减少空气中的灰尘颗粒来减少空气污染。马来西亚实施绿色屋顶的主要障碍是缺乏当地知识和不熟练的绿色屋顶专家。因此,该国缺乏绿色屋顶安装人员和专业公司。本文结合沙捞越建筑行业的经验,探讨了在建筑项目中采用绿色屋顶存在的问题及解决方法。本研究采用问卷调查的方式来获取数据。这篇论文揭示了建筑行业采用绿色屋顶可能面临的挑战。这项研究对于马来西亚迅速采用绿色屋顶技术至关重要。
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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
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
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.
网格蛋白介导的内吞作用(CME)是细胞内容物被转运到细胞内的正常生物过程。然而,这一过程经常被不同的病毒劫持,进入宿主细胞并引起感染。最近,两种调节CME的蛋白——AAK1和GAK——被认为是设计广谱抗病毒药物的潜在治疗靶点。在这项工作中,我们整理了两个化合物数据集,每个数据集包含83个AAK1抑制剂和196个GAK抑制剂。随后,采用随机森林(Random Forest)、弹性网络(Elastic Net)和顺序最小优化(Sequential Minimal Optimization)等机器学习方法构建定量结构活性关系(Quantitative Structure - Activity Relationship, QSAR)模型,预测AAK1和GAK的小分子抑制剂。为了确保预测性,这些模型通过使用Leave-One-Out (LOO)交叉验证和外部测试集进行评估。在所有情况下,我们的QSAR模型在0.64至0.84的范围内实现了q2LOO(均方根误差;RMSE = 0.41至0.52),q2ext的范围为0.57至0.92 (RMSE = 0.36至0.61)。此外,我们的QSAR模型通过使用附加的QSAR性能指标和y随机化检验进行评估。最后,通过一致性评分方法,从Drugbank化合物文库中预测9个化合物为AAK1/GAK双靶点抑制剂。生成了九种化合物的静电电位图,并与两种已知的双靶点抑制剂舒尼替尼和巴西替尼进行了比较。我们的工作为验证这9种化合物在AAK1和GAK蛋白靶点上的实验效果提供了理论依据。
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引用次数: 0
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Journal of Smart Science and Technology
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