Espensenduncan7056

Sampling is a critical step in pesticide atmospheric analysis. Passive sampling offers advantages of inexpensive and convenient air monitoring. Polyethylene films (PE) were used as a passive sampler at multiple heights in greenhouse and agricultural field for 15 days to trap atmospheric chlorothalonil and lambda-cyhalothrin in the months of May and July. Among the two PE film thicknesses (20 and 80 μm), 20 μm PE was the most effective at absorbing target pesticides from air and attains equilibrium stage earlier than 80 μm PE film. After approximately 240 h of PE exposure in greenhouse and fields, chlorothalonil and lambda-cyhalothrin reached an equilibrium stage of partitioning between air and PE. Atmospheric concentrations of chlorothalonil (p less then 0.01) and lambda-cyhalothrin (p less then 0.001) at 1.5 m height were higher with the concentrations of 1855.59 ± 243.85 ng/m3 and 3682.11 ± 316.71 ng/m3, respectively, in the month of May as compared to the other three respective heights. The concentrations of chlorothalonil in air at 2 m height (1587.27 ± 284.19 ng/m3) were slightly higher than 0.5 m (1392.28 ± 205.09 ng/m3). Atmospheric concentrations of lambda-cyhalothrin at 2 m (3178.26 ± 299.29 ng/m3) were significantly lower than the other heights (p less then 0.05). The greenhouse air concentrations of chlorothalonil and lambda-cyhalothrin in the months of May (1855.59 ± 243.85 and 3682.11 ± 316.71 ng/m3, respectively) and July (1749.33 ± 378.61 and 3445.08 ± 390.32 ng/m3, respectively) were higher than fields. The results indicate the usability of PE films to monitor chlorothalonil and lambda-cyhalothrin and potential other semi-volatile pesticides in agricultural fields.Pharmaceuticals, such as dipyrone (DIP), paracetamol (PCT), and propranolol (PPN), are widely used analgesics and beta-blockers with the greatest presence in wastewaters and, consequently, in natural waters. The present work evaluated solar light-driven photocatalyst from petrochemical industrial waste (PW) as a strategy for the degradation of three pharmaceuticals in different water matrices (distilled water-DW, simulated wastewater-SWW, and real hospital wastewater-RHWW). All experiments were carried out in a solar photo-reactor with a capacity of 1 L and the experimental condition employed was a catalyst concentration of 350 mg L-1 at pH 5.0; these conditions were selected considering the Doehlert design validation spreadsheet and the desirability function. All materials prepared were conveniently characterized by zeta potential, small-angle X-ray scattering (SAXS), diffuse reflectance ultraviolet-visible (DRUV), and infrared spectroscopy. According to the results of the characterization, significant diffe8%). Furthermore, 20 transformation products (TPs) generated throughout the treatment were identified by LC-QTOF MS using a customized TPs database. According to quantitative structure activity relationship (Q)SAR analysis, more than 75% of the TPs identified were not biodegradable. About 35% of them have oral toxicity characteristics indicated by Cramer's rules, and the DIP TPs represent high toxicity for different trophic levels.Landscape plants have both ecological and aesthetic value and may also represent ideal candidates for phytoremediation. In the present study, one round of hydroponic culture for 14 days with different cadmium (Cd) concentrations (0, 0.5, 1, and 2 mg L-1 Cd) was carried out to test whether Hydrocotyle vulgaris L. is a Cd-tolerant plant. Furthermore, physiological parameters, including pigment concentrations, photosynthesis, antioxidant enzyme activities (AEAs), and nutrient uptake, were also examined to determine the tolerance of H. vulgaris to Cd exposure. https://www.selleckchem.com/products/otx015.html The results showed that H. vulgaris could grow normally under all Cd supply levels. The Cd removal efficiency reached 100% at Cd concentrations ≤1.0 mg L-1. The concentrations of Cd in roots and shoots increased (P less then 0.05) with Cd supplementation. The maximum concentrations of Cd reached 26.4 and 118 mg kg-1 in shoots and roots, respectively. The translocation factor values were similar under all Cd treatments. The highest mean daily increase in biomass (MDIB) was obtained under 1 mg L-1 Cd exposure, which increased by 69.86% compared to that in the control, which may be due to the increased photosynthetic pigments, photosynthetic rate, and the consistent nutrient concentrations under this Cd level, as there were positive relationships between these parameters and MDIB. Moreover, the activities of AEA also generally explicated highest among all Cd levels. All these results indicate that the above physiological parameters play a positive role in promoting plant growth and alleviating Cd stress. In summary, H. vulgaris was verified as a potential Cd-tolerant plant, providing new information for Cd phytoremediation. Furthermore, given its extensive habitat distribution, this species might be tested for phytoremediation of contaminated soils in future work.High-strength concrete (HSC) is defined as concrete that meets a special combination of uniformity and performance requirements, which cannot be attained routinely via traditional constituents and normal mixing, placing, and curing procedures. It is a complex material since modeling its behavior is a difficult task. This paper intends to show the feasible applicability of optimized convolutional neural networks (CNN) for predicting the slump in HSC. The following are the parameters that given as the input for the prediction of slump cement (kg/m3), slag (kg/m3), fly ash (kg/m3), water (kg/m3), super-plasticizer (kg/m3), coarse aggregate (kg/m3), and fine aggregate (kg/m3). In order to make the prediction more accurate, the design of CNN is assisted with optimization logic by making some fine-tuned filter size of the convolutional layer. For this optimization purpose, this work presents a new "hybrid" algorithm that incorporates the concept of sea lion optimization algorithm (SLnO) and dragonfly algorithm (DA) and is named as Levy updated-sea lion optimization algorithm (LU-SLnO). Finally, the performance of the proposed work is compared and proved over the state-of-the-art models with respect to error measure and convergence analysis.