Analysis and assessment of heavy metals pollution in soils around a Pb and Zn smelter in Baoji City,Northwest China

Soil heavy metal pollution from mining activities is potentially harmful to human health through the food chain. In this study, a total of 43 soil samples were collected from a depth of 0–20 cm from fields close to a Pb and Zn smelter. The samples were used to: 1) analyze the pollution level of heavy metals (Pb, Zn, Cr, and Cu) and spatial distribution pattern; 2) evaluate the degree of accumulation and enrichment, potential ecological risk, and human health risk; and 3) perform source apportionment in Fengxiang County, Shaanxi Province of China. The results showed that the concentration ranged from 43.67 to 189.55, 131.43 to 239.53, 74.77 to 112.25, and 24.69 to 37.71 mg·kg^?1 for Pb, Zn, Cr, and Cu, respectively, and the mean concentration for Pb, Zn, Cr, and Cu was 129.46, 192.85, 91.98 and 31.67 mg·kg^?1, respectively. The concentrations were greater than the Shaanxi Province background values, while they were lower than the second-level limits of Environmental Quality Standard for Soils of China (EQSS). The spatial distribution of heavy metal contents showed a banded in soil except Cu. The spatial distribution pattern and pollution assessment indexes (I_geo, EF) indicated that the investigated metals had been accumulated in the study areas, and implied significant influences from anthropogenic activities, local meteorological situation, and soil properties. The ecological risk assessment showed that the risks were relatively low (RI<150). Compared with the exposure risk for adults, that for children was significantly greater. The ingestion of heavy metals in the soils by humans was the main exposure pathway compared with the dermal exposure. There may be a risk of noncarcinogenic adverse health effects (HQ < 1, 0.377 ≤ HI≤1.553) on children, but the adults were unlikely to experience obvious adverse health effects (HQ < 1, HI < 1). The carcinogenic risk of Cr for adults and children was at an unacceptable level. The carcinogenic and noncarcinogenic risks were in the order of children > adults. The correlation analysis showed that Pb, Cr, and Cu have identical anthropogenic and natural sources, while Zn has another identical source. This study could provide a basis for the sustainable management of this region by reducing metal inputs and to protect soils from long-term heavy metal accumulation.     

Rare species habitat suitability assessment and reliability evaluation of an expert-based model: A case study of the insectivorous plant Pinguicula crystallina Sibth. et Smith subsp. hirtiflora (Ten.) Strid (Lentibulariaceae)

The development of habitat suitability models requires a large amount of data which are rarely available. In this case, researchers need to get information on the ecological features of the studied species, based on the opinion of experts or on the literature, to construct a qualitative model. However, such models cannot be rigorously evaluated, as in most cases absence points are not available. In this paper, we assess the habitat suitability for a vulnerable insectivorous plant, Pinguicula crystallina Sibth. et Smith subsp. hirtiflora (Ten.) Strid (Lentibulariaceae) in the Campania region. Our aim was to develop an expert-based, presence-only model in support of possible conservation actions. Topographic and geological features of this species suggested by the literature were used in our model. Both the Boyce index and field surveys were chosen to evaluate the model's reliability. During field surveys, 31 absence sites and 1 new presence site were identified, and differences between sites with regard to water chemistry and quality were investigated, water being an element in the species habitat. Factors that affect reliability of the model, such as the lack of a large amount of information on the species and the limited spatial resolution of geographical information system data, are discussed.     

Automatic detection of pulmonary nodules in CT images by incorporating 3D tensor filtering with local image feature analysis

Computer-aided detection (CAD) technology has been developed and demonstrated its potential to assist radiologists in detecting pulmonary nodules especially at an early stage. In this paper, we present a novel scheme for automatic detection of pulmonary nodules in CT images based on a 3D tensor filtering algorithm and local image feature analysis. We first apply a series of preprocessing steps to segment the lung volume and generate the isotropic volumetric CT data. Next, a unique 3D tensor filtering approach and local image feature analysis are used to detect nodule candidates. A 3D level set segmentation method is used to correct and refine the boundaries of nodule candidates subsequently. Then, we extract the features of the detected candidates and select the optimal features by using a CFS (Correlation Feature Selection) subset evaluator attribute selection method. Finally, a random forest classifier is trained to classify the detected candidates. The performance of this CAD scheme is validated using two datasets namely, the LUNA16 (Lung Nodule Analysis 2016) database and the ANODE09 (Automatic Nodule Detection 2009) database. By applying a 10-fold cross-validation method, the CAD scheme yielded a sensitivity of 79.3% at an average of 4 false positive detections per scan (FP/Scan) for the former dataset, and a sensitivity of 84.62% and 2.8 FP/Scan for the latter dataset, respectively. Our detection results show that the use of 3D tensor filtering algorithm combined with local image feature analysis constitutes an effective approach to detect pulmonary nodules.     

基于指标自动筛选的新疆开孔河流域生态健康评价

生态健康评价对了解区域生态健康状况和促进区域可持续发展具有重要意义,如何自动筛选出能反映生态系统特性的重要指标,是生态健康定量评估的关键问题。基于压力-状态-响应(PSR,Press-State-Response)框架和生态等级网络框架(EHN,Ecological Hierarchy Network),通过文献调研和因果分析建立要素层与指标层之间的交叉联系,构建了生态健康评价"网状"指标体系;在保证指标体系完备性基础上,通过结合主成分分析和熵权法的候选指标权重的客观计算,基于目标优化理论构建了评价指标的自动筛选模型,并基于中选指标计算了新疆开孔河流域2001—2017年生态健康指数(EHCI,Ecological Health Comprehensive Indexes),分析其空间分异和时间变化特征。结果表明:利用所建立的评价指标自动筛选模型,开孔河流域生态健康评价指标由31个候选指标自动筛选出了17个中选指标,用54.8%的指标表达了85.98%的信息,中选的17个指标在干旱/半干旱区域有关文献中应用较多,使用频次比例都在20%以上,其中归一化植被指数(NDVI,Normalized Difference Vegetation Index)、年降水量和植被覆盖度(FVC,Fractional Vegetation Coverage)3个指标的使用频次百分比均超过了50%,说明指标自动筛选模型的合理性;开孔河流域空间分布差异显著,总体上西北高、东南低,东南部和中部绿洲区外围生态健康状况较差,西北部河谷地带和中部两大绿洲区生态健康状况较好;17年来,流域生态质量整体趋于改善,显著改善区域占10.26%,远高于显著退化的1.61%,显著改善区域以孔雀河绿洲最为明显。开孔河流域生态健康的总体好转趋势说明区域生态综合治理取得一定成效。