scholarly journals Research Progress and Prospects of Soil Pollution Assessment and Prediction Models

2019 ◽  
Vol 304 ◽  
pp. 052042
Author(s):  
Xiuxia Li ◽  
Wei Zhu ◽  
Yufang Qin ◽  
Fei Yin
Keyword(s):  
Soil Pollution ◽  
Prediction Models ◽  
Pollution Assessment ◽  
Research Progress

Soil pollution and soil organisms: an overview of research progress and perspectives

2015 ◽  
Vol 35 (20) ◽  
Author(s):  
陈保冬 CHEN Baodong ◽  
赵方杰 ZHAO Fangjie ◽  
张莘 ZHANG Xin ◽  
伍松林 WU Songlin ◽  
乔敏 QIAO Min ◽  
...  
Keyword(s):  
Soil Pollution ◽  
Research Progress ◽  
Soil Organisms

scholarly journals Applying Some Indices for Soil Pollution Assessment in Northern Industrial Area from Erbil Governorate

2021 ◽  
Vol 26 (4) ◽  
pp. 45-58
Author(s):  
Nashmeel Khudhur ◽  
Sidra Qubad Yassin ◽  
Ahmed Saman Hassan ◽  
Mortatha Nawzad Omar
Keyword(s):  
Heavy Metals ◽  
Soil Pollution ◽  
Surface Soil ◽  
Contamination Factor ◽  
Pollution Assessment ◽  
Industrial Area ◽  
Pollution Load Index ◽  
Growth Effect ◽  
Lepidium Sativum ◽  
Soil Site

Soil pollution by some heavy metals including: Cr, Mn, Fe, Ni, Cu, Zn, As, Mo, Cd and Pb from northern industrial area of Erbil City was assessed. The contamination indices including: geoaccumulation (Igeo), contamination factor (CF), enrichment factor (EF), degree of contamination (Cdeg), pollution load index (PLI) and element contamination index (ECI) were applied to assess soil pollution in Erbil North Industrial area at three sites (for both surface and sub-surface soils). Maximum Fe value 34243.6 ppm was recorded in sub-surface soil (site 2). Maximum values 265.4, 248.8, 98.23 and 397.45 ppm were recorded for Cr, Ni, Cu and Zn at sub-surface soil (site 3). Whereas, maximum values of 22.52, 5.36, 23.9, 6.12 and 65.67 ppm were recorded for As, Mo, Ag, Cd and Pb at surface soil (site 3). Results of analysed heavy metals for soil Cr, Mn, Fe, Ni, Cu, Zn, As, Mo, Ag, Cd and Pb have shown that the studied sites were severely contaminated with Cd, so the maximum detected Cd concentration was 6.12 ppm in surface soil (300 meters away from the industrial area). The soil pollution in the studied area was classified as moderate to strong surface and sub-surface soil contamination. Behavioral toxicity experiment showed slight growth effect on Lepidium sativum L.

scholarly journals Research Progress of Soil Water Infiltration

2020 ◽  
Vol 189 ◽  
pp. 01006
Author(s):  
Xia Qing ◽  
Han Haojie ◽  
Xiong Jinran ◽  
Zheng Caixia ◽  
Zhang Zhiliang ◽  
...  
Keyword(s):  
Soil Water ◽  
Agricultural Development ◽  
Prediction Models ◽  
Test Methods ◽  
Water Infiltration ◽  
Research Progress ◽  
Future Research ◽  
Research Development ◽  
Soil Water Infiltration ◽  
Development Direction

Soil water is an important link in the transformation of the “five waters”, which determines the growth and production of crops. Mastering the scientific infiltration law is a key link to promote agricultural development. Based on the existing research results, this paper systematically summarizes the basic theories, test methods, influencing factors, simulation equations, prediction models and other results of soil water infiltration research at home and abroad so far, and discusses the future research development direction.

Analyse of Agricultural Soil Heavy Metals Pollution

2015 ◽  
Vol 752-753 ◽  
pp. 1201-1205 ◽  
Author(s):  
Ružena Králiková ◽  
Miriam Andrejiová
Keyword(s):  
Soil Pollution ◽  
Metal Contamination ◽  
Agricultural Soil ◽  
Heavy Metal Contamination ◽  
Comprehensive Evaluation ◽  
Pollution Assessment ◽  
Land Resources ◽  
Soil Environment ◽  
Social Potential ◽  
Heavy Metals Pollution

Soil represents a decisive natural resource and economic and eco-social potential of the every country. Soil pollution is one of the biggest environmental problems. Contamination in the soil environment has a significant impact on the use of land resources and can cause high levels of exposure for people living near the site of contamination. Therefore, the risk elements soil pollution assessment is one of the most important resources for comprehensive evaluation of contaminated areas.The paper investigates the degree of heavy metal contamination of agricultural soil in selected Slovakian districts over a monitored period of time. Selected multidimensional statistical methods were applied to analyse and evaluate the degree of soil contamination.

Recent development of machine learning methods in sumoylation sites prediction

2021 ◽  
Vol 28 ◽  
Author(s):  
Yi-Wei Zhao ◽  
Shihua Zhang ◽  
Hui Ding
Keyword(s):  
Machine Learning ◽  
Molecular Mechanisms ◽  
Prediction Models ◽  
Computational Prediction ◽  
Research Progress ◽  
Post Translational Modification ◽  
Sumoylation Site ◽  
Cellular Processes ◽  
Online Tools ◽  
Experimental Approaches

: Sumoylation of proteins is an important reversible post-translational modification of proteins and mediates a variety of cellular processes. Sumo-modified proteins can change their subcellular localization, activity and stability. In addition, it also plays an important role in various cellular processes such as transcriptional regulation and signal transduction. The abnormal sumoylation is involved in many diseases, including neurodegeneration and immune-related diseases, as well as the development of cancer. Therefore, identification of the sumoylation site (SUMO site) is fundamental to understanding their molecular mechanisms and regulatory roles. In contrast to labor-intensive and costly experimental approaches, computational prediction of sumoylation sites in silico also attracted much attention for its accuracy, convenience and speed. At present, many computational prediction models have been used to identify SUMO sites, but these contents have not been comprehensively summarized and reviewed. Therefore, the research progress of relevant models is summarized and discussed in this paper. We will briefly summarize the development of bioinformatics methods on sumoylation site prediction. We will mainly focus on the benchmark dataset construction, feature extraction, machine learning method, published results and online tools. We hope the review will provide more help for wet-experimental scholars.

Interrill and Rill Erosion on Hillslope

2012 ◽  
Vol 170-173 ◽  
pp. 1344-1347
Author(s):  
Gang Liu ◽  
Wen Nian Xu ◽  
Qiong Zhang ◽  
Zhen Yao Xia
Keyword(s):  
Future Development ◽  
Prediction Models ◽  
Research Progress ◽  
Rill Erosion ◽  
Erosion Process ◽  
Erosion Processes ◽  
Erosion Prediction ◽  
Physically Based ◽  
The Relationship

Interrill and rill erosion are commonly observed erosion processes to coexist on hillslope. Understanding of the interrill and rill erosion process is the key for the development of physically-based erosion prediction models. This paper reviewed the research progress of interrill and rill erosion, and the relationship between them. The shortages were also put forward. Finally, the trends for future development and questions are also discussed.

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