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[Display omitted] • Cotton fiber was used as the normal-phase adsorbent for zearalenone extraction. • Extraction was conducted by applying pull–push operations to the syringe plunger. • Extraction zearalenone from cereal crops/traditional Chinese medicines was effective. • The extraction method was simple, low-cost, and labor/time-saving. • Coupled with LC-MS/MS, quantitative analysis of zearalenone in corn was validated. Here, an in-syringe cotton fiber solid-phase extraction (CF-SPE) method for the effective pretreatment of zearalenone (ZEA) in cereal crops and traditional Chinese medicines was developed. In this method, a syringe tube is packed with degreasing cotton, which serves as the normal-phase adsorbent for extracting ZEA from the nonpolar solvent extract of samples. The entire extraction process, including activation, sampling, washing, and elution steps, can be conveniently performed by employing a series of pull–push operations to force the solution to pass through the degreasing cotton. Optimal extraction recoveries were achieved using 200 mg of degreasing cotton as the adsorbent, a 3 mL volume of sampling solution, a desorption solution consisting of 2 mL of acetonitrile, and 4 pull–push times for both sampling and desorption. Coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS), quantification of ZEA in corns was achieved by validating matrix-matched calibration curves in the range of 0.1–100.0 ng/g with satisfactory linearity (R2 = 0.9996). The limit of detection (LOD) was calculated to be 0.025 ng/g with a signal-to-noise ratio (S/N) of 3. The intra-/inter-day relative recoveries and relative standard deviations were calculated to be in the ranges of 93.8%–110.4% and 3.2%–9.3%, respectively, which were satisfactory for quantitative analysis. The proposed in-syringe CF-SPE-LC-MS/MS method is simple, cheap, and labor/time-saving. [ABSTRACT FROM AUTHOR]

• Natural feather fibers were used as support materials for SLE for the first time. • A novel FF-SLE method was proposed for convenient oil sample preparation. • The FF-SLE device was easy to constructed with low cost (∼0.5 CNY). • The oil sample was directly used without any pretreatment including dilution. • FF-SLE proved to be green for extracting synthetic antioxidants from edible oils. The current study proposed a novel feather fiber-supported liquid extraction (FF-SLE) method for extracting analytes from oil samples. The natural feather fibers were used as the oil support material and directly loaded in the plastic tube of a disposable syringe to construct the low-cost extraction device (∼0.5 CNY). The edible oil without any pretreatment including dilution was added directly to the extraction device, followed by the addition of the green extraction solvent of ethanol. As an example, the proposed method was applied to extract nine synthetic antioxidants from edible oils. The optimized extraction conditions for processing 0.5 g of oil were obtained when the syringe dimension was 5 mL, the extraction solvent was 0.5 mL of ethanol, the amount of feather fibers was 200 mg of duck feather fibers and the static extraction time was 10 min. The applications to seven kinds of feathers and seven kinds of edible oils all indicated the excellent oil removal efficiencies (>98.0%). Combined with high-performance liquid chromatography-ultraviolet, a quantification method was validated with satisfied linearity (R2≥0.994), accuracy (95.8–114.6%) and precision (≤8.3%) with the limits of detection ranging from 50 to 100 ng/g. The proposed FF-SLE method was simple, effective, convenient, low-cost, green and environmental-friendly for the extraction of analytes from oil samples prior to instrument analysis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Natural feathers were employed as the support medium of an oily extraction solvent. • In-pipette-tip extraction device was constructed with the cost less than 0.1 CNY. • Extraction can be conducted by simply drawing solution in/out. • The method is simple, convenient, rapid, green, low-cost, and easy to automate. • Coupled with HPLC-UV, quantification of antidepressants in urines was achieved. In this study, a novel in-pipette-tip natural-feather-supported liquid microextraction (NF-SLME) method was developed for conveniently extracting hydrophobic compounds in aqueous samples. Natural feathers were used as the support medium of an oily extraction solvent and an in-pipette-tip extraction device was simply constructed with the cost less than 0.1 CNY. The whole extraction process could be conveniently conducted with a pipettor. As a proof of concept, the in-pipette-tip NF-SLME method was applied to extract antidepressants in urines. The best extraction recoveries were obtained when the extraction solvent was 15 μL of n -octanol, the pH of the sampling solution was 10.0, the desorption solution was 200 μL of acetonitrile, and the numbers of cycles of drawing solution in/out for extraction and elution were 5 and 2, respectively. Coupled with high-performance liquid chromatography–ultraviolet, a quantification method was validated in ranges of 0.05–10 μg/mL with satisfactory linearities (R2 ≥ 0.988). The limits of quantification were calculated to range from 0.032 to 0.048 μg/mL, which is adequate for antidepressant analysis in urine. The potential of the in-pipette-tip NF-SLME method was further illustrated by the successful extraction of triazole pesticides and androgenic steroids with good recoveries. [ABSTRACT FROM AUTHOR]

Fireworks algorithm (FA) is a relatively new swarm-based metaheuristic for global optimization. The algorithm is inspired by the phenomenon of fireworks display and has a promising performance on a number of benchmark functions. However, in the sense of swarm intelligence, the individuals including fireworks and sparks are not well-informed by the whole swarm. In this paper we develop an improved version of the FA by combining with differential evolution (DE) operators: mutation, crossover, and selection. At each iteration of the algorithm, most of the newly generated solutions are updated under the guidance of two different vectors that are randomly selected from highly ranked solutions, which increases the information sharing among the individual solutions to a great extent. Experimental results show that the DE operators can improve diversity and avoid prematurity effectively, and the hybrid method outperforms both the FA and the DE on the selected benchmark functions. [ABSTRACT FROM AUTHOR]

[Display omitted] • A one-pot derivatization/extraction method of furfurals was proposed. • PBH and MWCNTs were used for derivatization and extraction, respectively. • The derivatization extraction and steps were integrated into a single step. • On-pot simultaneous derivatization and extraction of three furfurals were realized. • The detection selectivity and accuracy were greatly improved. Furfurals (5-hydroxymethylfurfural, furfural and 5-methyl furfural) have potential toxic effects to humans. This study developed a simple and rapid one-pot derivatization/extraction procedure for effective sample preparation of furfurals in complex samples prior to instrument analysis. The sample solution was incubated with 1-pyrenebutyric hydrazide (PBH) and hydroxyl-functionalized multi-walled carbon nanotubes (MWCNTs-OH) in a vial for 3 min. During this process, the furfurals were effectively derivatized by PBH and the furfural-PBH derivatives were selectively captured by MWCNTs-OH simultaneously. The detection selectivity and accuracy were greatly improved for the following liquid chromatography-tandem mass spectrometry analysis. Quantifying furfurals was validated over the 0.5–500 ng/mL concentration range with satisfactory linearities (R2 >0.99), accuracies (84.7%–119.0%) and precisions (<9.0%). The limits of quantification of 0.30, 0.36 and 0.20 ng/mL for 5-hydroxymethylfurfural, furfural and 5-methyl furfural, respectively, were achieved. Finally, the validated method was successfully applied to determine furfurals concentrations in various samples. [ABSTRACT FROM AUTHOR]

• Natural kapok fiber was used as an oil support material for SLE. • For the first time, the SLE technique was applied to process oil samples. • The extraction device was easy to constructed and cost as low as 0.5 CNY. • The new KF-SLE method is simple, convenient, low-cost and easy to automate. In this study, a novel kapok fiber-supported liquid extraction (KF-SLE) method was developed for conveniently extracting analytes from oil samples. Natural kapok fiber without any pretreatment was directly used as an oil support medium. The extraction device was conveniently constructed by directly packing some kapok fibers into a syringe tube. Due to the fibrous property of the kapok fiber, no filter plate was needed. The cost of a KF-SLE device was as low as 0.5 CNY. The KF-SLE process was conveniently conducted using a simple three-step protocol: (1) the oil sample without any pretreatment including dilution was added directedly; (2) then, the oil-immiscible extractant was added; (3) after waiting a certain time for static extraction, the extractant was eluted out by pressing the kapok fibers with the syringe plunger. The extractant could be directly transferred for subsequent instrumental detection. For the feasibility and proof-of-concept study, the method was applied to quantify four synthetic flavor chemicals in edible oils. Satisfied quantification results were obtained with the correlation coefficient (R2) being greater than 0.996, the relative recoveries ranging from 92.90% to 107.53% and intra- and inter-day RSDs being less than 7.56%. All in all, for the first time, the SLE technique was expanded to process oil samples and the method has the characteristics of low cost, environmental friendliness, high sample processing throughput and ease of automation, offering a promising approach for edible oil sample preparations. [ABSTRACT FROM AUTHOR]

GNN-based social recommendation aims to use social network information to improve recommendation performance of traditional user–item interaction network (U–I network). However, in graph neural network information aggregation, both social networks and U–I networks inevitably have noise, which affects accuracy of recommendation results. To reduce the noise impact of network data, we propose Robust Social Recommendation based on Contrastive Learning and Dual-Stage Graph Neural Network (CLDS). First, considering instability of social networks, we propose the social preference network. It is robust and retains only social friend relationships with common preferences. Based on it and U–I network, we construct a social recommendation pre-training model. Next, we propose self-contrastive learning method. The method initializes multiple social network node representations through Gaussian distribution, pre-training and random disturbance, respectively. Then, it uses contrastive learning on the generated multiple node representations to enhance the robustness of node representation. Finally, CLDS avoids directly capturing potentially user–user and item–item information in U–I networks which is incomplete and untrusted. And instead, it only extracts user–item information to reduce the noise generated by GNN-based U–I network information aggregation. We conduct experiments under the open-source real network dataset. The experimental results show that CLDS outperforms state-of-art methods in social recommendation. The code is available at: https://github.com/Andrewsama/CLDS-master. [ABSTRACT FROM AUTHOR]

The average path length of a network is an important index reflecting the network transmission efficiency. In this paper, we propose a new method of decreasing the average path length by adding edges. A new indicator is presented, incorporating traffic flow demand, to assess the decrease in the average path length when a new edge is added during the optimization process. With the help of the indicator, edges are selected and added into the network one by one. The new method has a relatively small time computational complexity in comparison with some traditional methods. In numerical simulations, the new method is applied to some synthetic spatially embedded networks. The result shows that the method can perform competitively in decreasing the average path length. Then, as an example of an application of this new method, it is applied to the road network of Hangzhou, China. [ABSTRACT FROM AUTHOR]

• Commercially available pyrene-1-boronic acid was effective to label catecholamines. • On-tissue labeling strategy was developed to label catecholamines in-situ. • The strategy succeeded in imaging catecholamines in adrenal gland tissue sections. • The strategy proved to be robust, easy-to-use and low-cost. • Distributions of catecholamines obtained by MALDI-MSI matched well optical images. In this study, an on-tissue chemical labeling - matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) method was developed for visualization of the distribution of three catecholamine (CA) compounds (dopamine, epinephrine and norepinephrine) in porcine adrenal gland. Commercially available pyrene-1-boronic acid (PBA) was employed as an effective in situ derivatizing reagent dissolved in acetonitrile containing 0.1% pyridine for the chemical labeling and the matrix coating. Without extra matrix coating, the tissue section was directly analyzed by MALDI-MS. The detection specificity and sensitivity were greatly improved with the on-tissue PBA labeling and successful imaging of the three CAs in porcine adrenal gland was achieved. Compared with previously reported methods for MALDI-MSI of the CAs, the analytical strategy proposed in the study provided a robust, easy-to-use and low-cost on-tissue chemical derivatization method that facilitated simultaneous molecular imaging of the three compounds. [ABSTRACT FROM AUTHOR]

• Natural cotton fiber was used as a water supporting material for LPME. • In-syringe extraction device was constructed to facilitate the extraction process. • Extraction can be conducted by simply pulling/pushing the syringe plunger. • Coupled with GC-MS/MS, the method was validated with high sensitivity. • The method is sensitive, simple, convenient, low-cost and easy to automate. In the current study, natural cotton fiber was served as the supporter of water, and the water acted as an extractant for liquid-phase microextraction of polar components in low-polar edible oils. An in-syringe extraction device was constructed to facilitate the extraction process by simply loading a certain amount of cotton fibers between the syringe needle and the plastic syringe tube. Then, the extraction process can be conveniently conducted by pull-push the syringe plunger. It can be regarded as a new type of dynamic liquid-phase microextraction method while operated more convent. For the feasibility study, the novel in-syringe cotton fiber-supported liquid extraction (CF-SLECF-SLE) pretreatment method was applied to extract free 3-mono-chloropropane-1,2-diol (3-MCPD) in edible oils. Specifically, the cotton fibers supported a certain amount of water by successfully pulling-pushing 1 mL of water and 1 mL of HEX in/out twice, respectively. Then, 2.0 mL of diluted oil sample (containing 0.4 g oil) was loaded in and out four times for extraction, during which process 3-MCPD was extracted into the supported water. The extracted 3-MCPD was desorbed with 1 mL of ethyl acetate (EA), derivatized with trimethyl silane imidazole (TMSI), and analyzed by gas chromatography-tandem mass spectrometry (GC-MS/MS). For three different spiked edible oils, the internal standard normalized matrix effect (IS-normalized ME) values were in ranges of 96.3–104.8% with RSD being 4.3%, benefiting the accurate quantitative analysis. The limit of quantification (LOQ) was calculated to be 2 ng/g, which met the regular determination requirement of 3-MCPD in edible oils. Satisfied linearity was obtained in 2–500 ng/g, with correlation coefficients (R2) being 0.998. The relative recoveries were in the ranges of 96.9–110.5%. The intra-/inter-day RSDs were less than 8.2% and 10.2%, respectively. The proposed method provides an efficient, simple, low-cost, and easy to automate strategy for determining free 3-MCPD in edible oils. [ABSTRACT FROM AUTHOR]