Pesticides serve a crucial function in contemporary farming practices, safeguarding agricultural crops against pest infestations and boosting production outputs. However, indiscriminate use has caused environmental and human health damage. This study aimed to develop and validate a gas chromatography-flame ionization detection (GC-FID) methodology for the direct and routine analysis of spiromesifen residues in soil, leaves, and tomato fruits. The proposed method prioritizes simplicity by avoiding derivatization steps, offering advantages over existing approaches that utilize lengthy multi-step extraction or derivatization prior to GC analysis. A key novelty of this work is the development of a QuEChERS extraction coupled directly to GC-FID without further clean-up or chemical treatment steps, rendering the method more convenient and accessible for routine monitoring applications. Factors evaluated included: sample solvent; inlet and column temperature profiles; inlet type; sample volume; and injection technique. Recovery and matrix effect studies were conducted by fortifying tomato, leaf, and soil matrices at three different concentrations (0.5, 1, and 10 µg ml-1). Quadruplicate analyses (n = 4) yielded mean recoveries of 98.74% (fruits), 93.92% (leaves), and 94.18% (soil), confirming efficient extraction. Matrix effects were negligible at -7.9%, -7.8%, and -5.3%, respectively. The chromatographic linearity of the developed GC-FID method was excellent over the 0.002–20 µg ml-1 range with R2 > 0.9979. The method demonstrated good precision, with inter- and intra-day RSD% ranging from 0.06–1.8%, below the 3% limit. GC-MS analysis confirmed spiromesifen identification. Under greenhouse conditions, residual levels were 1.39 mg/kg in soil, 8.24 mg/kg in tomato, and 3.39 mg/kg in leaves. Dissipation followed first-order kinetics with a half-life of 1.6 days. The optimized GC-FID method is promising for monitoring spiromesifen usage and guiding agricultural practices. © (2024), (Iranian Chemical Society). All rights reserved.
The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th
... Show MoreAn efficient combination of Adomian Decomposition iterative technique coupled Elzaki transformation (ETADM) for solving Telegraph equation and Riccati non-linear differential equation (RNDE) is introduced in a novel way to get an accurate analytical solution. An elegant combination of the Elzaki transform, the series expansion method, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has
... Show MoreDue to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula
... Show MoreIn this work, we first construct Hermite wavelets on the interval [0,1) with it’s product, Operational matrix of integration 2^k M×2^k M is derived, and used it for solving nonlinear Variational problems with reduced it to a system of algebric equations and aid of direct method. Finally, some examples are given to illustrate the efficiency and performance of presented method.
The effect of the initial pressure upon the laminar flame speed, for a methane-air mixtures, has been detected paractically, for a wide range of equivalence ratio. In this work, a measurement system is designed in order to measure the laminar flame speed using a constant volume method with a thermocouples technique. The laminar burning velocity is measured, by using the density ratio method. The comparison of the present work results and the previous ones show good agreement between them. This indicates that the measurements and the calculations employed in the present work are successful and precise
The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the
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