Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements

The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed\u27s 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced

Modeling nitrogen loadings from agricultural soils in southwest China with modified DNDC

Degradation of water quality has been widely observed in China, and loadings of nitrogen (N) and other nutrients from agricultural systems play a key role in the water contamination. Process‐based biogeochemical models have been applied to quantify nutrient loading from nonpoint sources at the watershed scale. However, this effort is often hindered by the fact that few existing biogeochemical models of nutrient cycling are able to simulate the two‐dimensional soil hydrology. To overcome this challenge, we launched a new attempt to incorporate two fundamental hydrologic features, the Soil Conservation Service curve and the Modified Universal Soil Loss Equation functions, into a biogeochemistry model, Denitrification‐Decomposition (DNDC). These two features have been widely utilized to quantify surface runoff and soil erosion in a suite of hydrologic models. We incorporated these features in the DNDC model to allow the biogeochemical and hydrologic processes to exchange data at a daily time step. By including the new features, DNDC gained the additional ability to simulate both horizontal and vertical movements of water and nutrients. The revised DNDC was tested against data sets observed in a small watershed dominated by farmlands in a mountainous area of southwest China. The modeled surface runoff flow, subsurface drainage flow, sediment yield, and N loading were in agreement with observations. To further observe the behaviors of the new model, we conducted a sensitivity test with varied climate, soil, and management conditions. The results indicated that precipitation was the most sensitive factor determining the rate of N loading from the tested site. A Monte Carlo test was conducted to quantify the potential uncertainty derived by variations in four selected input parameters. This study demonstrates that it is feasible and effective to use enhanced biogeochemical models such as DNDC for quantifying N loadings by incorporating basic hydrological features into the model framework

Efficient removal of tetracycline from aqueous solution by K2CO3 activated penicillin fermentation residue biochar

In this study, biochar was prepared using penicillin fermentation residue (PR) as the raw material by different methods. The adsorption behavior and adsorption mechanism of biochar on tetracycline (TC) in an aqueous environment were investigated. The results showed that K2CO3 as an activator could effectively make porous structures, and that biochar with mesoporous or microporous could be prepared in a controlled manner with two kinds of different activation methods, the dry mixing method and the impregnation method. The dry mixing method could create more mesopores, while the impregnation method could prepare more micropores. Microporous biochar (IKBCH) with a high specific surface area could be prepared by the impregnation method combined with HCl soaking, which has an excellent adsorption effect on tetracycline. When the concentration of tetracycline was 200 mg/L, the removal rate of 99.91% could be achieved with the dosage of microporous biochar at 1 g/L. The adsorption process was in accordance with the Langmuir model and the pseudo-second-order model, respectively. The maximum adsorption capacity of IKBCH was 268.55 mg/g (25°C). The adsorption mechanisms were pore filling, π-π interaction, electrostatic adsorption, and hydrogen bond. Its stable and wide applicability adsorption process does not cause ecological pollution in the aqueous environment, and it is a promising biochar adsorbent

Protective effect of the curcumin-baicalein combination against macrovascular changes in diabetic angiopathy

Endothelial dysfunction is an early pathological event in diabetic angiopathy which is the most common complication of diabetes. This study aims to investigate individual and combined actions of Curcumin (Cur) and Baicalein (Bai) in protecting vascular function. The cellular protective effects of Cur, Bai and Cur+Bai (1:1, w/w) were tested in H2O2 (2.5 mM) impaired EA. hy926 cells. Wistar rats were treated with vehicle control as the control group, Goto-Kakizaki rats (n=5 each group) were treated with vehicle control (model group), Cur (150 mg/kg), Bai (150 mg/kg), or Cur+Bai (75 mg/kg Cur + 75 mg/kg Bai, OG) for 4 weeks after a four-week high-fat diet to investigate the changes on blood vessel against diabetic angiopathy. Our results showed that Cur+Bai synergistically restored the endothelial cell survival and exhibited greater effects on lowering the fasting blood glucose and blood lipids in rats comparing to individual compounds. Cur+Bai repaired the blood vessel structure in the aortic arch and mid thoracic aorta. The network pharmacology analysis showed that Nrf2 and MAPK/JNK kinase were highly relevant to the multi-targeted action of Cur+Bai which has been confirmed in the in vitro and in vivo studies. In conclusion, Cur+Bai demonstrated an enhanced activity in attenuating endothelial dysfunction against oxidative damage and effectively protected vascular function in diabetic angiopathy rats

Effect of Tanshinone IIA on gut microbiome in diabetes-induced cognitive impairment

Diabetes-induced cognitive impairment (DCI) presents a major public health risk among the aging population. Previous clinical attempts on known therapeutic targets for DCI, such as depleted insulin secretion, insulin resistance, and hyperglycaemia have delivered poor patient outcomes. However, recent evidence has demonstrated that the gut microbiome plays an important role in DCI by modulating cognitive function through the gut–brain crosstalk. The bioactive compound tanshinone IIA (TAN) has shown to improve cognitive and memory function in diabetes mellitus models, though the pharmacological actions are not fully understood. This study aims to investigate the effect and underlying mechanism of TAN in attenuating DCI in relation to regulating the gut microbiome. Metagenomic sequencing analyses were performed on a group of control rats, rats with diabetes induced by a high-fat/high-glucose diet (HFD) and streptozotocin (STZ) (model group) and TAN-treated diabetic rats (TAN group). Cognitive and memory function were assessed by the Morris water maze test, histopathological assessment of brain tissues, and immunoblotting of neurological biomarkers. The fasting blood glucose (FBG) level was monitored throughout the experiments. The levels of serum lipopolysaccharide (LPS) and tumor necrosis factor-α (TNF-α) were measured by enzyme-linked immunoassays to reflect the circulatory inflammation level. The morphology of the colon barrier was observed by histopathological staining. Our study confirmed that TAN reduced the FBG level and improved the cognitive and memory function against HFD- and STZ-induced diabetes. TAN protected the endothelial tight junction in the hippocampus and colon, regulated neuronal biomarkers, and lowered the serum levels of LPS and TNF-α. TAN corrected the reduced abundance of Bacteroidetes in diabetic rats. At the species level, TAN regulated the abundance of B. dorei, Lachnoclostridium sp. YL32 and Clostridiodes difficile. TAN modulated the lipid metabolism and biosynthesis of fatty acids in related pathways as the main functional components. TAN significantly restored the reduced levels of isobutyric acid and butyric acid. Our results supported the use of TAN as a promising therapeutic agent for DCI, in which the underlying mechanism may be associated with gut microbiome regulation

Biotransformation of rare earth oxide nanoparticles eliciting microbiota imbalance

Background Disruption of microbiota balance may result in severe diseases in animals and phytotoxicity in plants. While substantial concerns have been raised on engineered nanomaterial (ENM) induced hazard effects (e.g., lung inflammation), exploration of the impacts of ENMs on microbiota balance holds great implications. Results This study found that rare earth oxide nanoparticles (REOs) among 19 ENMs showed severe toxicity in Gram-negative (G−) bacteria, but negligible effects in Gram-positive (G+) bacteria. This distinct cytotoxicity was disclosed to associate with the different molecular initiating events of REOs in G− and G+ strains. La2O3 as a representative REOs was demonstrated to transform into LaPO4 on G− cell membranes and induce 8.3% dephosphorylation of phospholipids. Molecular dynamics simulations revealed the dephosphorylation induced more than 2-fold increments of phospholipid diffusion constant and an unordered configuration in membranes, eliciting the increments of membrane fluidity and permeability. Notably, the ratios of G−/G+ reduced from 1.56 to 1.10 in bronchoalveolar lavage fluid from the mice with La2O3 exposure. Finally, we demonstrated that both IL-6 and neutrophil cells showed strong correlations with G−/G+ ratios, evidenced by their correlation coefficients with 0.83 and 0.92, respectively. Conclusions This study deciphered the distinct toxic mechanisms of La2O3 as a representative REO in G− and G+ bacteria and disclosed that La2O3-induced membrane damages of G− cells cumulated into pulmonary microbiota imbalance exhibiting synergistic pulmonary toxicity. Overall, these findings offered new insights to understand the hazard effects induced by REOs

Совершенствование маркетинговой деятельности промышленного предприятия (на примере РУП «Белоруснефть-Особино»)

We report a detailed computational and experimental study of the interaction of single-walled carbon nanotubes (SWCNTs) with the drug-metabolizing cytochrome P450 enzyme, CYP3A4. Dose-dependent inhibition of CYP3A4-mediated conversion of the model compound, testosterone, to its major metabolite, 6β-hydroxy testosterone was noted. Evidence for a direct interaction between SWCNTs and CYP3A4 was also provided. The inhibition of enzyme activity was alleviated when SWCNTs were pre-coated with bovine serum albumin. Furthermore, covalent functionalization of SWCNTs with polyethylene glycol (PEG) chains mitigated the inhibition of CYP3A4 enzymatic activity. Molecular dynamics simulations suggested that inhibition of the catalytic activity of CYP3A4 is mainly due to blocking of the exit channel for substrates/products through a complex binding mechanism. This work suggests that SWCNTs could interfere with metabolism of drugs and other xenobiotics and provides a molecular mechanism for this toxicity. Our study also suggests means to reduce this toxicity, eg., by surface modification

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe