This study features a survey of the concentrations of aluminum (Al) and heavy metals (Mn, Pb, Cd, Hg, As, Cr, Ni, Cu, and Zn) in tea leaves and the corresponding cultivation soils (0–30 cm), carried out in Puan County (Guizhou Province, China). The average concentrations of Al, Mn, Pb, Cd, Hg, As, Cr, Ni, Cu, and Zn in the soil were 106 × 103, 214, 20.9, 0.09, 0.12, 17.5, 121, 27.8, 131.2, and 64 mg·kg−1, respectively. The heavy metals’ pollution indexes in the soil can be ranked as follows: Cu > Cr > Hg > As > Ni > Zn > Pb > Mn > Cd. The soil was moderately polluted by Cu because of the high geochemical background value of Cu in the area. The potential environment risk index (RI) showed that 7.69% out of the total sample sites were within the moderate level. Moreover, the ranges of Al, Mn, Pb, Cd, Hg, As, Cr, Ni, Cu, and Zn concentrations in young tea leaves were 250–660, 194–1130, 0.107–0.400, 0.012–0.092, 0.014–0.085, 0.073–0.456, 0.33–1.26, 6.33–14.90, 14.90–26.10, and 35.8–50.3 mg·kg−1, respectively. While in mature tea leaves, they were 4300–10,400, 536–4610, 0.560–1.265, 0.040–0.087, 0.043–0.089, 0.189–0.453, 0.69–2.91, 3.43–14.20, 6.17–16.25, and 9.1–20.0 mg·kg−1, respectively. Furthermore, the concentrations of Pb, Cu, As, Hg, Cd, and Cr in young tea leaves and mature tea leaves were all lower than the standard limit values (5.0, 30, 2.0, 0.3, 1.0, and 5.0 mg·kg−1 for Pb, Cu, As, Hg, Cd, and Cr, respectively) in China. Besides, the accumulation ability of tea leaves to Mn was the strongest, and the average bioconcentration factor (BCF) of Mn in mature tea leaves was 12.5. In addition, the average target hazard quotients (THQ) were all less than one for the young tea leaves and the average aggregate risk hazard index (HI) to adults was 0.272, indicating that there was not a potential health risk for adults through the consumption of the infusions brewed by young tea leaves. However, for mature tea leaves, the percentage which HI values were above one was 38.46%, and the risk to adults via the consumption of mature tea infusions were mainly contributed by Mn and Al.

This study aimed to construct objective and accurate geographical discriminant models for tea leaves based on multielement concentrations in combination with chemometrics tools. Forty mineral elements in 87 tea samples from three growing regions in Guizhou Province (China), namely Meitan and Fenggang (MTFG), Anshun (AS) and Leishan (LS) were analyzed. Chemometrics evaluations were conducted using a one-way analysis of variance (ANOVA), principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that the concentrations of the 28 elements were significantly different among the three regions (p < 0.05). The correct classification rates for the 87 tea samples were 98.9% for LDA and 100% for OPLS-DA. The variable importance in the projection (VIP) values ranged between 1.01–1.73 for 11 elements (Sb, Pb, K, As, S, Bi, U, P, Ca, Na, and Cr), which can be used as important indicators for geographical origin identification of tea samples. In conclusion, multielement analysis coupled with chemometrics can be useful for geographical origin identification of tea leaves.

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The feature extraction technique for an electronic nose (e-nose) applied in tobacco smell detection in an open country/outdoor environment with periodic background strong interference is studied in this paper. Principal component analysis (PCA), Independent component analysis (ICA), re-filtering and a priori knowledge are combined to separate and suppress background interference on the e-nose. By the coefficient of multiple correlation (CMC), it can be verified that a better separation of environmental temperature, humidity, and atmospheric pressure variation related background interference factors can be obtained with ICA. By re-filtering according to the on-site interference characteristics a composite smell curve was obtained which is more related to true smell information based on the tobacco curer’s experience.

In this paper we study the following nonlinear Hamiltonian elliptic system with gradient term −∆u + b(x) • ∇u + u + V (x)v = f (x, |z|)v, x ∈ R N , −∆v − b(x) • ∇v + v + V (x)u = f (x, |z|)u, x ∈ R N , where z = (u, v) ∈ R 2. Under some suitable conditions on the potential and nonlinearity, we obtain the existence of ground state solutions in periodic case and asymptotically periodic case via variational methods, respectively. Moreover, we also explore some properties of these ground state solutions, such as compactness of set of ground state solutions and exponential decay of ground state solutions.

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We study the following nonperiodic Hamiltonian systemż JH z t, z , whereWe introduce a new assumption on B t and prove that the corresponding Hamiltonian operator has only point spectrum. Moreover, by applying a generalized linking theorem for strongly indefinite functionals, we establish the existence of homoclinic orbits for asymptotically quadratic nonlinearity as well as the existence of infinitely many homoclinic orbits for superquadratic nonlinearity.

Studying the dynamic characteristics, species coexistence and biodiversity conservation mechanisms of subtropical forest ecosystems is important in the study of the quantitative characteristics and spatial gap distribution patterns. Based on census data from the 20 ha dynamics plot of the subtropical evergreen broad-leaved forest in Dinghushan in 2015, we analyzed the geometric characteristics and spatial distribution pattern of gaps in the plot by combining aerial image processing technology of unmanned aerial vehicles and GIS. Results show that the gap fraction is 13.72%, the gap density is 35.75 no./ha, and the average gap area is 38.37 m 2 . Results also show that: (1) The number of gaps in the area is negatively exponentially distributed with the increase of gap area, that is, the gap is small and the marginal effect is not significant. (2) The aver-age area of forest gaps in over-mature forest stands is larger than that in mature forests, while the mature forest is more likely to have more small gaps and fewer large gaps. (3) In different habitats, the distribution of gaps in each habitat shows the same pattern as that found in the whole plot. However, the difference in the valley is significant when compared with other habitats, and gap area and gap density in the valley are larger than other habitats. The ridge gap is also distinctive, and its gap density is lower than other habitats. (4) Gap area is significantly correlated with topographic factors. It was significantly negatively correlated with altitude and convexity, and had a significantly positive correlation with aspect and gradient. Based on these comparative analyses, a monitoring system of forest canopy changes and patterns can be established using drones, to dynamically monitor forest gaps and the undergrowth community.