Effect of Hunting on the Reproduction of the Sable Population

Russian Journal of Ecology - Analysis of hunting samples of the Kamchatka sable population for 2001–2013 has revealed changes in the reproductive parameters of females over the period from...     

Global Warming-Related Dynamics of Infection by Eubothrium rugosum (Plathelminthes,Cestoda) in the Burbot from the Rybinsk Reservoir

Russian Journal of Ecology - Abstract—Long-term observations (1968–2019) on the dynamics of infection by the cestode Eubothrium rugosum in the burbot (Lota lota) have been performed in...     

内窥镜检查在电站锅炉内部检验中的应用

工业内窥镜是电站锅炉内部检验中不可或缺的设备,主要用来对集箱、减温器、受热面管等内部人眼无法观察到的地方进行检验,从而确定承压部件内部是否存在严重影响锅炉安全运行的缺陷.本文通过对锅炉内窥实例进行分析和总结,阐述内窥镜检查在锅炉内检中的重要性并给相关工作人员提供借鉴与参考.     

宁波月湖的水质改善与生态修复

随着浙江"五水共治"工作的深化,宁波作为浙江"五水共治"的中坚力量,始终把"五水共治"作为全市工作的首要任务和突破重点。自1999年进行清淤后,月湖水质得到短期改善,然而治标不治本的治理措施,并没有让月湖水质得到根本改善。因此,对月湖进行科学有效的生态修复,针对性地处理水污染问题,使之重新焕发活力具有十分重要的意义。     

地铁站附属地下餐饮空间噪声特征分析

利用专业噪声测量设备及噪声频谱分析设备,对地铁站附属地下餐饮空间区域噪声进行监测,绘制噪声小时频谱。经分析发现地铁附属地下餐饮空间声环境会受到客流、空间位置及餐铺建筑结构影响,因此在该类空间进行降噪设计中应充分考虑这些因素的影响。     

“互联网+”智慧环保生态环境多元感知体系发展分析

在大数据技术以及信息化快速稳定持续发展的实践背景之下,"互联网+"智慧环保发展时代的悄然来临,使得对"互联网+"智慧环保多元感知体系的研究与发展工作,逐步被提升到了极其重要的地位。文章结合雄安新区生态环境智慧监测体系建设项目,展开了简要的阐释分析。     

基层环境统计年报中的问题及建议

环境统计工作是环境保护工作中的基础,是各级政府和环境保护行政主管部门制定环境保护政策和计划、加强环境监督管理和污染防治的重要依据。本文结合日常工作经验,就目前基层环境统计工作中存在的问题进行探讨,并提出一些建议。     

Metagenomic analysis reveals the effects of cotton straw–derived biochar on soil nitrogen transformation in drip-irrigated cotton field

Environmental Science and Pollution Research - Biochar has been widely accepted as a soil amendment to improve nitrogen (N) use efficiency, but the effect of biochar on N transformation metabolic...     

Towards saving freshwater: halophytes as unconventional feedstuffs in livestock feed: a review

Water represents 71% of all earth area and about 97% of this water is salty water. So, only 3% of the overall world water quantity is freshwater. Human can benefit only from 1% of this water and the remaining 2% freeze at both poles of earth. Therefore, it is important to preserve the freshwater through increasing the plants consuming salty water. The future prosperity of feed resources in arid and semi-arid countries depends on economic use of alternative resources that have been marginalized for long periods of time, such as halophytic plants, which are one such potential future resource. Halophyte plants can grow in high salinity water and soil and to some extent during drought. The growth of these plants depends on the contact of the salted water with plant roots as in semi-desert saline water, mangrove swamps, marshes, and seashores. Halophyte plants need high levels of sodium chloride in the soil water for growth, and the soil water must also contain high levels of salts, as sodium hydroxide or magnesium sulfate. There are many uses for halophyte plants, including feed for animals, vegetables, drugs, sand dune stabilizers, wind shelter, soil cover, wetland cultivation, laundry detergents, and paper production. This paper will focus on the use of halophytes as a feed additive for animals. In spite of the good nutritional value of halophytes, some anti-nutritional factors as nitrates, nitrite complexes, tannins, glycosides, phenolic compounds, saponins, oxalates, and alkaloids may be present in some of them. The presence of such anti-nutritional agents makes halophytes unpalatable to animals, which tends to reduce feed intake and nutrient use. Therefore, the negative effects of these plants on animal performance are the only objection against using halophytes in animal feed diets. This review article highlights the beneficial impact of considering halophytes in animal feeding on saving freshwater and illustrates its nutritive value for livestock from different aspects.     

Air Quality Modeling Using the PSO-SVM-Based Approach,MLP Neural Network,and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

The main aim of this study was to construct several regression models of air quality using techniques based on the statistical learning, in the metropolitan area of Oviedo, in northern Spain. In this research, a hybrid particle swarm optimization-based evolutionary support vector regression is implemented to predict the air quality from the experimental dataset (specifically, nitrogen oxides, carbon monoxide, sulfur dioxide, ozone, and dust) collected from 2013 to 2015 in the metropolitan area of Oviedo. Furthermore, a multilayer perceptron network (MLP) and the M5 model tree were also fitted to the experimental dataset for comparison purposes. Finally, the predicted results show that the hybrid proposed model is more robust than the MLP and M5 model tree prediction methods in terms of statistical estimators and testing performances.