RESUMEN
Kongyu Gold Mining Area is located in the northern margin of the Sichuan-Yunnan tectonic belt. This area has gone through two large tectonic cycles of Mesoproterozoic, Neoproterozoic and Phanerozoic. The strata are accompanied by a large number of tensile cracks, shear cracks and microfissures. The voidage, permeability and transitional effect of the rock are increased, and the transformation between surface water and groundwater is enhanced. On the other hand, tectonic movement controls the distributions and allocations of elements in the earth's crust, resulting in directional geochemical changes in crustal materials and rules. Driven by the tectonic force, the elements are reallocated. The ion content and ion compressibility of those elements increase and decrease inversely. The manifestations of rocks and minerals under directional pressure can be characterized by the flow and puncture of plastic minerals and the fragmentation of hard and brittle minerals. In the process of leaching, the pollutant elements precipitate from the deposits of different granular ores, and most are absorbed by the soil column; thus, the mass fraction of polluting elements in the soil column obviously increases. The variability is the largest when the leachate passes through the fine ore. The rate of change of the element mass fraction from high to low is Ni, Zn, Cu, Cd, Pb, As and Cr. A small part migrated from the soil column to the collection fluid, and the leaching effect is related to the rate of change of soil mass fraction, the ion radius of elements and the compressibility.
Asunto(s)
Metales/análisis , Contaminantes del Suelo/análisis , Suelo/química , China , Monitoreo del Ambiente/métodos , Fenómenos Geológicos , Oro , Agua Subterránea/química , Minerales/análisis , Minería , Ríos , Contaminantes Químicos del Agua/análisisRESUMEN
Sixty-nine total suspended particle (TSP) samples, paired with forty-eight surface soil samples, covering four seasons from January 2021 to November 2021, were collected from the Three Gorges Reservoir Region (TGRR). Twenty per- and poly-fluoroalkyl substances (PFASs) were analyzed to evaluate their contamination characteristics and understand the role of atmospheric deposition on the environmental loads in TGRR. The annual average concentrations of PFASs in TSP and soil were 37.2 ± 1.22 pg·m-3 and 0.798 ± 0.134 ng·g-1, respectively. For TSP, concentrations were highest in spring and lowest in summer. For soil, it was in autumn and winter, respectively. The seasonality was more influenced by anthropogenic activities than by meteorological conditions or physicochemical parameters of the soil. Positive matrix fractionation (PMF) indicated that, based on annual averages, PFOA-based products (40.2 %) were the major sources of PFASs in TSP, followed by PFOS-based products (25.2 %) and precursor degradation (34.6 %). The highest source contributor for PFASs in spring was precursor degradation (40.9 %), while in other three seasons, it was PFOA-based products (39.9 %, 40.9 % and 52.0 %, respectively). The mean atmospheric dry and wet deposition fluxes of PFASs were estimated at 4.38 ng·m-2·day-1 and 23.5 ng·m-2·day-1, respectively. The contribution of atmospheric deposition to the inventory mass of PFASs in the surface soil was 22.3 %. These findings fill a gap in knowledge regarding the processes and mechanisms of the occurrence, sources and atmospheric deposition of PFASs in the TGRR.
RESUMEN
The sex ratio is an important factor affecting the economic benefits of duck groups in the process of hemp duck breeding. However, the current manual counting method is inefficient, and the results are not always accurate. On the one hand, ducks are in constant motion, and on the other hand, the manual counting method relies on manpower; thus, it is difficult to avoid repeated and missed counts. In response to these problems, there is an urgent need for an efficient and accurate way of calculating the sex ratio of ducks to promote the farming industry. Detecting the sex ratio of ducks requires accurate counting of male ducks and female ducks. We established the world's first manually marked sex classification dataset for hemp ducks, including 1663 images of duck groups; 17,090 images of whole, individual duck bodies; and 15,797 images of individual duck heads, which were manually captured and had sex information markers. Additionally, we used multiple deep neural network models for the target detection and sex classification of ducks. The average accuracy reached 98.68%, and with the combination of Yolov5 and VovNet_27slim, we achieved 99.29% accuracy, 98.60% F1 score, and 269.68 fps. The evaluation of the algorithm's performance indicates that the automation method proposed in this paper is feasible for the sex classification of ducks in the farm environment, and is thus a feasible tool for sex ratio estimation.