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Cover Crop Influence on Soil Enzymes and Selected Chemical Parameters for a Claypan Corn–Soybean Rotation
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Cover crops (CC) improve soil quality, including soil microbial enzymatic activities and soil chemical parameters. Scientific studies conducted in research centers have shown positive effects of CC on soil enzymatic activities; however, studies conducted in farmer fields are lacking in the literature. The objective of this study was to quantify CC effects on soil microbial enzymatic activities (β-glucosidase, β-glucosaminidase, fluorescein diacetate hydrolase, and dehydrogenase) under a corn (Zea mays L.)–soybean (Glycine max (L.) Merr.) rotation. The study was conducted in 2016 and 2018 in Chariton County, Missouri, where CC were first established in 2012. All tested soil enzyme levels were significantly different between 2016 and 2018, irrespective of CC and no cover crop (NCC) treatments. In CC treatment, β-glucosaminidase activity was significantly greater at 0–10 cm depth in 2016 and at 10–20 and 20–30 cm in 2018. In contrast, dehydrogenase activity was significantly greater in NCC in 2018. Soil pH and organic matter (OM) content were found to be significantly greater in CC. Overall, CC have mixed effects on soil enzyme activities and positive effects on soil OM compared to NCC. This study highlights the short-term influence of CC and illustrates the high spatial and temporal variability of soil enzymes under farmer-managed fields.

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Feasibility Study of a Solar Flat Plate Collector for Domestic and Commercial Applications under Iraq Climate
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Publication Date
Sat Jul 08 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Highly Sensitive Kinetic-Spectrophotometric Method for the Assay of Carbamazepine in Pure and Commercial Tablet
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The study aimed to recommend a new spectrophotometric-kinetic method for determination of carbamazepine (CABZ) in its pure form and pharmaceutical forms. The proposed procedure based on the coupling of CABZ with diazotized sulfanilic acid in basic medium to yield a colored azo dye. Factors affecting the reaction yield were studied and the conditions were optimized. The colored product was followed spectrophotometrically via monitoring its absorbance at 396 nm. Under the optimized conditions, two method (the initial rate and fixed time (10 minute)) were applied for constructing the calibration graphs. The graphs were linear in concentration ranges 2.0 to 18.0 µg.mL-1 for both methods. The proposed was applied successfully in

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Electrical Engineering
A Method Combining Compressive Sensing-Based Method of Moment and LU Decomposition for Solving Monostatic RCS
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Publication Date
Thu Aug 04 2022
Journal Name
Contemporary Nurse
ICU nurses’ safety performance related to respect for safety and management commitment: A cross-sectional study
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
The The Use of Copper and Aluminum Electrodes for Energy Production in a Microbial Fuel Cell
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Microbial fuel cell is a device that uses the microorganism metabolism for the production of electricity under specific operating conditions. Double chamber microbial fuel cell was tested for the use of two cheap electrode materials copper and aluminum for the production of electricity under different operating conditions. The investigated conditions were concentration of microorganism (yeast) (0.5- 2 g/l), solutions temperature (33-45 oC) and concentration of glucose as a substrate (1.5- 6 g/l). The results demonstrated that copper electrode exhibit good performance while the performance of aluminum is poor. The electricity is generated with and without the addition of substrate. Addition of glucose substrate

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Publication Date
Sun Jul 01 2018
Journal Name
Computers & Mathematics With Applications
Analytical and numerical solutions for the nonlinear Burgers and advection–diffusion equations by using a semi-analytical iterative method
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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

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