The valorization of rice husk biochar obtained by pyrolysis was studied by production high quality activated carbon. Activated carbon (AC) chemically treated by K 2 CO 3 , was used as sorbent phase in bar adsorptive microextraction followed by comprehensive two-dimensional gas chromatography coupled to a quadrupole mass spectrometer analysis (BAµE/GC×GC-qMS) for trace analysis of carbazole in commercial diesel. The prepared AC was characterized by N 2 adsorption, SEM-EDS and pH PZC. Assays of nitrogen adsorption isotherm demonstrated that the AC presented microporosity and the Density Functional Theory Calculation was applied to obtain information concerning the micropore size distribution. The BET surface area and total pore volume were 1850 m 2 g-1 and 0.83 cm 3 g-1 , respectively. AC from rice huskpyrolysis (RH) showed an acceptable adsorption capacity for Carbazole in diesel matrices allowed us to obtain average recoveries of 91.0 % and convenient analytical parameters. From the data obtained, the proposed methodology proved to be a suitable sorption-based static microextraction alternative for monitoring trace levels of carbazole in commercial diesel.
The Ca River basin has an area of 27,200 km2 distributed across the territories of two countries: Vietnam (65.2%) and Lao PDR (34.8%). Spatial and temporal variations in suspended sediment (SS) and dissolved nutrients (PO43-, NO3-, SiO2) were determined in two hydrological stations located along the Ca River 4–6 times per month in the rainy season and 1–4 times per month in the dry season, between the months of August 2017 and July 2018. A loading–discharge (L–Q) curve was used to analyze the correlation among water physicochemical parameters with seasonal river discharge. The results indicate that SS was higher in upstream flows compared to downstream flows, which is primarily due to erosion. Seasonal SSs and dissolved phosphate have an inverse correlation trend to that of dissolved silica. Results revealed that the concentration of phosphate and suspended sediments was higher in the rainy season than in the dry season. This finding proves that rain washes particulate matter from the surface runoff into the Ca River basin. Significant correlations between discharge and dissolved nutrient load were observed. This study provides useful information regarding variations of SS and water physicochemical parameters with seasonal water discharge in the Ca River.
Attribute reduction is a critical problem in the data preprocessing step with the aim of minimizing redundant attributes to improve the efficiency of data mining models. The fuzzy rough set theory is considered an effective tool to solve the attribute reduction problem directly on the original decision system, without data preprocessing. With the current digital transformation trend, decision systems are larger in size and updated. To solve the attribute reduction problem directly on change decision systems, a number of recent studies have proposed incremental algorithms to find reducts according to fuzzy rough set approach to reduce execution time. However, the proposed algorithms follow the traditional filter approach. Therefore, the obtained reduct is not optimal in both criteria: the number of attribute of the reducts and the accuracy of classification model. In this paper, we propose incremental algorithms that find reducts following filter-wrapper approach using fuzzy distance measure in the case of adding and deleting attribute set. The experimental results on the sample datasets show that the proposed algorithms significantly reduce the number of attributes in reduct and improve the classification accuracy compared to other algorithms using filter approach
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