High-resolution reconfigurable RF signal spectral processor.

Recent developments in microwave photonic filters (MPFs) offer superior properties for radio frequency (RF) signal processing, such as large instantaneous bandwidth, high resolution and multifunctional shapes. However, it is quite challenging to realize two or more characteristics simultaneously to meet the diverse needs in complex electromagnetic environment. In this paper, we propose a reconfigurable RF signal spectral processor with both large instantaneous bandwidth and high resolution. In the proposed spectral processor, sufficient taps supplied by an optical frequency comb (OFC) offer a large instantaneous bandwidth to process broadband RF signals. Flexible tap coefficients can be obtained by manipulating an optical spectral shaper (OSS), which provides excellent reconfigurability. This tap-by-tap manipulation is realized with a high resolution of hundreds of megahertz, allowing precise shape configuration of the response. In the experiment, we demonstrate a flat-top response with a wide bandwidth of 7.1 GHz. Reconfigurable features such as tunable bandwidth, adjustable center frequency and diverse shapes are also shown. In particular, the measured frequency resolution of 96.5 MHz demonstrates the ability for precise configuration.

Microfluidic on-demand engineering of longitudinal dynamic self-assembly of particles.

The lack of a simple operable method for on-demand engineering of longitudinal dynamic self-assembly of particles is one of the main problems in employing particle manipulation in biomedical research studies. Herein, a viscoelasticity-induced self-assembling microfluidic system is proposed to increase the maneuverability and orderliness of longitudinal dynamic self-assembly of particles, and achieve the on-demand control of interparticle spacings and frequencies of particles passing through an outlet. In our microfluidic system, two kinds of functional microstructures and a side-channel were designed to preprocess randomly distributed particles allowing them not to aggregate but rather to evenly distribute, and realize the on-demand control of the particle volume concentration. Randomly distributed particles could be focused into a line and become equally spaced on the center axis of a straight microchannel under transverse elastic force and longitudinal viscoelasticity-induced effective repulsive force. Besides, a finite element model was established to analyze the processes of particles flowing in each functional microstructure. Therefore, a step forward in the experimental method and realization of this microfluidic technology can provide opportunities for applications in biomedical engineering, materials science and beyond.

In vitro dentin tubule occlusion by an arginine-containing dentifrice.

PURPOSE: To evaluate the ability of an arginine-containing dentifrice to occlude dentin tubules. METHODS: Dentin discs were divided equally into premolar and molar groups, which were then utilized in three treatment groups: a blank control group (distilled water treatment), a negative control group (common dentifrice with calcium carbonate) and an experimental group [dentifrice with 8% (w/w) arginine]. Each dentin disk was brushed with the dentifrice twice daily for 7 consecutive days. After this period, each disc was separated into two equal halves. One half was used for scanning electron microscopy (SEM) and energy-dispersive spectrometer (EDS) examinations, while the other half was brushed with distilled water twice daily for another 7 days prior to SEM observation. RESULTS: The plugging rate in the arginine dentifrice group was significantly higher and more sustainable than in the negative control group. The surface deposition of calcium and phosphorus on the dentin discs in the arginine dentifrice group was also significantly higher. CLINICAL SIGNIFICANCE: This study provided evidence that using arginine as an active ingredient in dentifrice can improve its ability to occlude dentin tubules, thus supporting future efforts to improve dentin hypersensitivity.

Slow feature-based feature fusion methodology for machinery similarity-based prognostics.

Similarity-based prediction methods utilize degradation trend analysis based on degradation indicators (DIs). These methods are gaining prominence in industrial predictive maintenance because they effectively address prognostics for machines with unknown failure mechanisms. However, current studies often neglect the discrepancies in degradation trends when constructing DIs from multi-sensor data and lack automatic normalization of operating regimes during feature fusion. In this study, a feature fusion methodology based on a signal-to-noise ratio metric that leverages slow feature analysis (SFA) is proposed. This customized metric utilizes SFA to quantify degradation trend discrepancies of constructed DIs, while automatically filtering out the effects of multiple operating regimes during feature fusion. The effectiveness and superiority of the proposed method are demonstrated using publicly available aero-engine and rolling bearing datasets.

Hygeia: A Multilabel Deep Learning-Based Classification Method for Imbalanced Electrocardiogram Data.

Electrocardiogram (ECG) is a common diagnostic indicator of heart disease in hospitals. Because of the low price and noninvasiveness of ECG diagnosis, it is widely used for prescreening and physical examination of heart diseases. In several studies on ECG analysis, only rough diagnoses are made to determine whether ECGs are abnormal or on a few kinds of ECG. In actual scenarios, doctors must analyze ECG samples in detail, which is a multilabel classification problem. Herein, we propose Hygeia, a multilabel deep learning-based ECG classification method that can analyze and classify 55 types of ECG. First, a guidance model is constructed to transform the multilabel classification problem into multiple interrelated two-classification models. This method ensures the good performance of each ECG analysis model, and the relationship between various types of ECG can be used in the analysis. The imbalance of samples in ECG datasets makes it difficult to analyze abnormal ECGs with high sensitivity and accuracy. We used data generation and mixed sampling methods for 11 ECG types with imbalanced problems to improve the average accuracy, sensitivity, F1 value, and accuracy from 87.74%, 43.11%, 0.3929, and 0.3929, to 92.68%, 96.92, 0.9287, and 99.47%, respectively. The average accuracy, sensitivity, F1 value, and accuracy of 44 of the 55 tags of the abnormal ECG analysis model are 99.69%, 95.81%, 0.9758, and 99.72%, respectively.

A Highly Sensitive, Ultra-Durable, Eco-Friendly Ionic Skin for Human Motion Monitoring.

Ionic conductive hydrogels have shown great potential in areas such as wearable devices and electronic skins. Aiming at the sensitivity and biodegradability of the traditional flexible hydrogel electronic skin, this paper developed an ionic skin (S-iSkin) based on edible starch-sodium alginate (starch-SA), which can convert the external strain stimulus into a voltage signal without an external power supply. As an excellent ion conductive polymer, S-iSkin exhibited good stretchability, low hydrophilicity and outstanding electrochemical and sensing properties. Driven by sodium ions, the ion charge transfer resistance of S-iSkin is reduced by 4 times, the capacitance value is increased by 2 times and its conductivity is increased by 7 times. Additionally, S-iSkin has excellent sensitivity and linearity (R2 = 0.998), a long service life and good biocompatibility. Under the action of micro-stress, it can produce a voltage change ratio of 2.6 times, and its sensitivity is 52.04. The service life test showed that it can work stably for 2000 s and work more than 200 stress-voltage response cycles. These findings provide a foundation for the development of health monitoring systems and micro-stress sensing devices based on renewable biomass materials.

Multivariate time-series classification with hierarchical variational graph pooling.

In recent years, multivariate time-series classification (MTSC) has attracted considerable attention owing to the advancement of sensing technology. Existing deep-learning-based MTSC techniques, which mostly rely on convolutional or recurrent neural networks, focus primarily on the temporal dependency of a single time series. Based on this, complex pairwise dependencies among multivariate variables can be better described using advanced graph methods, where each variable is regarded as a node in the graph, and their dependencies are regarded as edges. Furthermore, current spatial-temporal modeling (e.g., graph classification) methodologies based on graph neural networks (GNNs) are inherently flat and cannot hierarchically aggregate node information. To address these limitations, we propose a novel graph-pooling-based framework, MTPool, to obtain an expressive global representation of MTS. We first convert MTS slices into graphs using the interactions of variables via a graph structure learning module and obtain the spatial-temporal graph node features via a temporal convolutional module. To obtain global graph-level representation, we design an "encoder-decoder"-based variational graph pooling module to create adaptive centroids for cluster assignments. Then, we combine GNNs and our proposed variational graph pooling layers for joint graph representation learning and graph coarsening, after which the graph is progressively coarsened to one node. Finally, a differentiable classifier uses this coarsened representation to obtain the final predicted class. Experiments on ten benchmark datasets showed that MTPool outperforms state-of-the-art strategies in the MTSC task.

High Throughput Fabrication of Flexible Top-Driven Sensing Probe.

In this work, considering the current status of conservative and complicated traditional thrombosis treatment methods, a kind of flexible intelligent probe (FIP) with a top-driven sensing strategy is proposed to realize the expected function of thrombosis accurate localization in a liquid flow environment. After throughput fabrication, we find that the FIP has excellent electrical conductivity and mechanical properties. Notable, our FIP with the principle of piezo-resistive sensing has a quasi-linear sensitivity (approx. 0.325 L per minute) to flow sensing in the low flow velocity range (0-1 L per minute). Via the well-designed magnetically driven method, our FIP has a maximum deflection output force of 443.264 mN, a maximum deflection angle of 43°, and a maximum axial force of 54.176 mN. We demonstrate that the FIP is capable of completing the specified command actions relatively accurately and has a good response to real-time sensing feedback performance, which has broad application prospects in thrombus localization detection.

Microwave-assisted extraction and in situ clean-up for the determination of fluoroquinolone antibiotics in chicken breast muscle by LC-MS/MS.

A new method was developed for the determination of six fluoroquinolone antibiotics including fleroxacin, levofloxacin, ciprofloxacin, lomfloxacin, enrofloxacin, and sparfloxacin in chicken breast muscle, in which the extraction and clean-up were performed in one step by microwave irradiation. The mixture of ACN containing 0.3% v/v phosphoric acid/water pH 3 (70:30, v/v) was used as the extraction solution and hexane was used as the clean-up solution. The extract was analyzed by liquid chromatography-tandem mass spectrometry system. The RSDs of intra- and inter-day obtained are in the range of 1.0-10.4 and 3.8-13.6%, respectively. In the three fortified levels of chicken breast muscle (20, 100, and 500 ng/g), the recoveries of fluoroquinolone antibiotics ranging from 66.0 to 97.2% are obtained. The LODs are in the range of 2.7-6.7 ng/g. This method simplifies the process of the sample preparation and reduces the operation errors.

Influence of the "Inverted U Method" Nd: YAG Laser Posterior Capsulotomy on Anterior Segment Parameters, Decentration and Tilt of Intraocular Lens in Patients after Phaco-vitrectomy.

PURPOSE: To investigate the effects of the "inverted U method" Nd:YAG laser posterior capsulotomy on anterior segment parameters, decentration and tilt of intraocular lens (IOLs) and visual acuity in posterior capsular opacification (PCO) patients after combined phaco-vitrectomy. METHODS: Seventy-six patients (76 eyes) were enrolled in this study, who were diagnosed as PCO and underwent "inverted U method" Nd:YAG laser posterior capsulotomy. All patients had undergone previous combined phaco-vitrectomy for rhegmatogenous retinal detachment. The parameters including IOL decentration, angle of IOL tilt, anterior chamber angle (ACA), anterior chamber depth (ACD), anterior chamber volume (ACV), central corneal thickness (CCT), keratometry, pupil size, axial length (AL), intraocular pressure (IOP), refractive status, corrected distance visual acuity (CDVA), objective scattering index (OSI) and Chinese version of Visual Function 14 (VF-14) index were obtained before and 3 months after capsulotomy. RESULTS: After capsulotomy, the tilt angle and decentration of the IOLs at both vertical (tilt: p = .004, decentration: p = .029) and horizontal meridian (tilt: p = .001, decentration: p = .017) were significantly decreased, ACA increased (p = .015), CDVA (p = .000), VF-14 score (p = .000) and OSI (p = .000) were significantly improved. There were a significant decrease in cylindrical error (p = .001) and a myopic shift in spherical error (p = .001) after the capsulotomy. No significant differences in ACD, ACV, CCT, keratometry, pupil size, AL and IOP were detected (p > .05 for all). CONCLUSION: The "inverted U method" Nd: YAG laser posterior capsulotomy decreases tilt and decentration of the IOL, increases ACA and causes no change in ACD, ACV, CCT and IOP in patients after phaco-vitrectomy. These changes make a decrease in cylindrical error and a myopic shift in spherical error. Laser capsulotomy significantly improves visual acuity.

Improved object recognition using neural networks trained to mimic the brain's statistical properties.

The current state-of-the-art object recognition algorithms, deep convolutional neural networks (DCNNs), are inspired by the architecture of the mammalian visual system, and are capable of human-level performance on many tasks. As they are trained for object recognition tasks, it has been shown that DCNNs develop hidden representations that resemble those observed in the mammalian visual system (Razavi and Kriegeskorte, 2014; Yamins and Dicarlo, 2016; Gu and van Gerven, 2015; Mcclure and Kriegeskorte, 2016). Moreover, DCNNs trained on object recognition tasks are currently among the best models we have of the mammalian visual system. This led us to hypothesize that teaching DCNNs to achieve even more brain-like representations could improve their performance. To test this, we trained DCNNs on a composite task, wherein networks were trained to: (a) classify images of objects; while (b) having intermediate representations that resemble those observed in neural recordings from monkey visual cortex. Compared with DCNNs trained purely for object categorization, DCNNs trained on the composite task had better object recognition performance and are more robust to label corruption. Interestingly, we found that neural data was not required for this process, but randomized data with the same statistical properties as neural data also boosted performance. While the performance gains we observed when training on the composite task vs the "pure" object recognition task were modest, they were remarkably robust. Notably, we observed these performance gains across all network variations we studied, including: smaller (CORNet-Z) vs larger (VGG-16) architectures; variations in optimizers (Adam vs gradient descent); variations in activation function (ReLU vs ELU); and variations in network initialization. Our results demonstrate the potential utility of a new approach to training object recognition networks, using strategies in which the brain - or at least the statistical properties of its activation patterns - serves as a teacher signal for training DCNNs.

Transcriptomic Analysis of circRNAs in the Peripheral Blood of Nonarteritic Anterior Ischemic Optic Neuropathy.

The aim of the study is to explore the expression profile variation of circular RNAs (circRNAs) in the peripheral blood of subjects with nonarteritic anterior ischemic optic neuropathy (NAION) and without NAION, to analyze the differential expression results, and to predict the role of circRNAs in disease development, providing novel ideas and methods for treatment and diagnosis. High-throughput sequencing to explore the expression profiles of RNAs in the peripheral blood of 6 NAION patients and 5 healthy controls was applied. Quality control obtained the advanced data from the original data by ticking out the unqualified data. Then, cluster analysis, volcano plot, coexpression network, and protein-protein interaction network (PPI) were performed. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to analyze the whole expressed genes. Lastly, the quantitative real-time Polymerase Chain Reaction (qRT-PCR) was used to verify those significantly differentially expressed circRNAs and do some bioinformatics analysis and prediction in 12 NAION patients and 12 controls. There were significant differences in the expression of 49 circRNAs in the peripheral blood of NAION patients, in which there were 24 upregulations and 25 downregulations (variation folds > 2 and P < 0.05), and it was confirmed that hsa_circ_0005583, hsa_circ_0003922, hsa_circ_0002021, and hsa_circ_0000462 were significantly downregulated (variation folds > 2 and P < 0.05), especially hsa_circ_0005583 which was the most significantly changed one (P < 0.001), and are related to processes such as neurodegeneration, oxidative stress, immunity, and metabolism. The expression profile of circRNAs in the peripheral blood of NAION patients is significantly changed, enriching our understanding of the disease.

On-line coupling of solid-phase extraction to liquid chromatography--a review.

Solid-phase extraction (SPE) is an effective sample preparation method for removal of interfering compound and enrichment of analyte. Liquid chromatography (LC) with various detectors is a main separation and detection technique used in the analytical field. This article reviews the literatures about the on-line coupling of SPE with LC. The advantages of on-line coupling are reduction of analysis time, sample contamination, and analyte losses, as well as improvement of precision and accuracy. The SPE sorbents including traditional materials, such as chemically bonded silica, ion-exchange and carbon-based materials, and some novel sorbents, such as restricted access material, molecularly imprinted polymer, immunosorbent, and monolithic material, used in the on-line analysis are discussed in detail. The on-line coupling of SPE-LC to other sample preparation techniques, such as supercritical fluid extraction, subcritical water extraction, microwave-assisted extraction, ultrasound-assisted extraction, and derivatization technique are also reviewed.

Dynamic ultrasound-assisted extraction coupled on-line with solid support derivatization and high-performance liquid chromatography for the determination of formaldehyde in textiles.

An on-line method was developed for the extraction, derivatization and determination of formaldehyde in textile samples. Formaldehyde was first extracted with water by ultrasound assisted, and directly introduced into a derivatization column which was packed with a moderately sulfonated cation-exchange resin. The resin used as solid support for the derivatization was charged with 2,4-dinitrophenylhydrazine (DNPH) previously. The formaldehyde DNPH derivative was eluted with the chromatographic mobile phase into an analytical column for the separation, and then monitored by UV detector. The maximum extraction yield was achieved when the extraction vessel was located at 10mm from the ultrasonic source and 10mg textile sample was extracted with 5mL pure water at a flow rate of 1.0mLmin(-1) at 50 degrees C. The detection limit of the proposed method was 0.06mgkg(-1). This method was applied to the determination of formaldehyde in different textile samples, and compared with the state standard method (off-line spectrophotometry) used in China. The similar contents of formaldehyde were obtained for most samples by the two methods, but little higher for some samples obtained by the proposed method. The average relative standard deviation (RSD) obtained by the on-line method was 3.2% which is lower than 29.5% obtained by the standard method.

Determination of sulfonamides in soil samples based on alumina-coated magnetite nanoparticles as adsorbents.

In this study, alumina-coated magnetite nanoparticles (Fe(3)O(4)/Al(2)O(3) NPs) were synthesized, and they were applied to the analysis of sulfonamides (SAs) including sulfadiazine (SDZ), sulfamerazine (SMR), sulfamethoxazole (SMX), sulfamonomethoxine (SMM), sulfamethoxydiazine (SMD), sulfadimethoxine (SDM) and sulfaquinoxaline (SQX) in different soil samples based on magnetic solid-phase extraction (MSPE). The extraction and concentration process was carried out in a single step by mixing the extraction solvent, magnetic adsorbents and soil sample under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. The SAs desorbed from the adsorbents were determined by liquid chromatography-tandem mass spectrometry. Compared with traditional methods, the MSPE method simplified the operation procedure and reduced the analysis time. Under the optimum conditions, the recoveries of SDZ, SMR, SMX, SMM, SMD and SDM by analyzing the five spiked soil samples were between 71% and 93% except for SQX (42-60%). This may be due to the stronger hydrophobic property of SQX. Detection limits of SAs were between 0.37 and 6.74 ng g(-1). It was also found that the "aging" effect of SAs contaminated soil could cause the recoveries to decrease.

Preparation of magnetic strong cation exchange resin for the extraction of melamine from egg samples followed by liquid chromatography-tandem mass spectrometry.

In the work, magnetic strong cation exchange (MSCX) resins were prepared using hydrophobic Fe(3)O(4) magnetite as the magnetically susceptible component, styrene and divinylbenzene as polymeric matrix components, acetyl sulfonate as the sulfonation agent. The resins were successfully applied to the extraction of melamine (MEL) from egg samples. The extraction procedure was carried out in a single step by blending and stirring the sample, extraction solvent and the magnetic resins. The MEL was extracted from the sample matrix then adsorbed onto the resins directly through ion-exchange interaction. When the extraction was completed, the resins with adsorbed analyte were easily separated from the sample matrix by applying an appropriate magnetic field. Main factors affecting the extraction of MEL such as the amount of MSCX resins, extraction time, washing and eluting conditions were optimized. The MEL eluted from the resins was determined by liquid chromatography-tandem mass spectrometry. The linearity of quantification obtained by analyzing matrix-matched standards is in the range of 10-1000 ng g(-1). The limit of detection and quantification obtained are 2.6 and 8.8 ng g(-1), respectively. The relative standard deviations of intra- and inter-day ranging from 1.6% to 6.5% and from 2.1% to 7.2% are obtained. The recoveries of MEL are in the range of 77.2-99.3%. The proposed method was successfully applied to determine MEL in eggs obtained from different local markets. MEL was detectable with the contents of 43.5 and 234.1 ng g(-1) in two samples.

A green method using micellar system for determination of sulfonamides in soil.

A green and simple method was developed for determination of sulfonamides (SAs) in soil samples. The procedure was based on the microwave-assisted extraction (MAE) of SAs from soil using non-ionic surfactant Triton X-114 as the extraction medium. Then sodium chloride was added into the MAE extract and the mixture was equilibrated for some time at high temperature. The analytes in the surfactant-rich phase were concentrated with the help of centrifugation and directly analyzed by high performance liquid chromatography with UV detection. None of potentially hazardous organic solvents was used in the whole sample preparation procedure. The significant variables for the performance of extraction and concentration were studied. The limits of detection of SAs obtained are in the range of 3.2-5.7 ng g(-1). The relative standard deviations of intra- and inter-day tests ranging from 3.5% to 7.7% and from 4.6% to 9.5% are obtained, respectively. This method was applied to the determination of SAs in some soil samples with different characteristics. The SAs recoveries obtained at fortified level of 100 ng g(-1) for these samples are in the range of 81.2-93.7%. The effect of ageing time of spiked soil samples on the SAs recoveries was examined by the proposed method and a method reported in the literature. The recoveries of SAs decreased when the ageing time changed from 1 day to 4 weeks.

Preparation of alumina-coated magnetite nanoparticle for extraction of trimethoprim from environmental water samples based on mixed hemimicelles solid-phase extraction.

In this study, a new type of alumina-coated magnetite nanoparticles (Fe(3)O(4)/Al(2)O(3) NPs) modified by the surfactant sodium dodecyl sulfate (SDS) has been successfully synthesized and applied for extraction of trimethoprim (TMP) from environmental water samples based on mixed hemimicelles solid-phase extraction (MHSPE). The coating of alumina on Fe(3)O(4) NPs not only avoids the dissolving of Fe(3)O(4) NPs in acidic solution, but also extends their application without sacrificing their unique magnetization characteristics. Due to the high surface area of these new sorbents and the excellent adsorption capacity after surface modification by SDS, satisfactory concentration factor and extraction recoveries can be produced with only 0.1g Fe(3)O(4)/Al(2)O(3) NPs. Main factors affecting the adsolubilization of TMP such as the amount of SDS, pH value, standing time, desorption solvent and maximal extraction volume were optimized. Under the selected conditions, TMP could be quantitatively extracted. The recoveries of TMP by analyzing the four spiked water samples were between 67 and 86%, and the relative standard deviation (RSD) ranged from 2 to 6%. Detection and quantification limits of the proposed method were 0.09 and 0.24 microg L(-1), respectively. Concentration factor of 1000 was achieved using this method to extract 500 mL of different environmental water samples. Compared with conventional SPE methods, the advantages of this new Fe(3)O(4)/Al(2)O(3) NPs MHSPE method still include easy preparation and regeneration of sorbents, short times of sample pretreatment, high extraction yields, and high breakthrough volumes. It shows great analytical potential in preconcentration of organic compounds from large volume water samples.

Microwave-assisted extraction coupled online with derivatization, restricted access material cleanup, and high-performance liquid chromatography for determination of formaldehyde in aquatic products.

A rapid technique based on microwave-assisted extraction (MAE) coupled online with derivatization, restricted access material cleanup, and high-performance liquid chromatography (HPLC) was developed for the determination of formaldehyde in aquatic products. Formaldehyde was first extracted with water under the action of microwaves and then directly introduced into a derivatization reservoir containing 2,4-dinitrophenylhydrazine (DNPH). The formaldehyde-DNPH derivative (100 µL) was loaded into a restricted access material (RAM) precolumn for online cleanup. Subsequently, the analyte was transferred from the precolumn to an analytical column and determined by UV absorption spectrum at 352 nm. The limit of detection (LOD) was 0.27 mg kg(-1). The intraday and interday precisions expressed as RSDs were 3.5% and 5.0%, respectively. This method was applied to determine the presence of formaldehyde in various aquatic products. The results were in agreement with those obtained by the state standard method (steam-distillation and offline HPLC analysis) used in China and higher than those obtained by the online ultrasound-assisted extraction (UAE) method. The recoveries obtained by analyzing 11 spiked aquatic products were in the range of 70.0%-105.0%. The online technique was demonstrated to be rapid with little consumption of samples and reagents.

Analysis of sulfonamides in environmental water samples based on magnetic mixed hemimicelles solid-phase extraction coupled with HPLC-UV detection.

The magnetic mixed hemimicelles solid-phase extraction (MMHSPE), based on the adsorption of cation surfactant octadecyltrimethylammonium bromide (OTMABr) onto magnetite nanoparticles (Fe(3)O(4) NPs) to form mixed hemimicelles, was proposed for the preconcentration of several sulfonamides (SAs) compounds including sulfamethoxazole (SMX), sulfamethoxydiazine (SMD), sulfadimethoxine (SDM) and sulfaquinoxaline (SQX) from environmental water samples. This method avoided the time-consuming column-passing process of loading large volume samples in traditional SPE through the rapid isolation of OTMABr-coated Fe(3)O(4) NPs with an adscititious magnet. Mixed hemimicelles formed on the surface of Fe(3)O(4) NPs by OTMABr showed great adsorptive tendency towards analytes. The OTMABr-coated Fe(3)O(4) NPs adsorbents were easy to be prepared, low cost and environmentally friendly. A comprehensive study on the adsorption conditions such as the amount of the surfactant, the solution pH, the desorption condition and the maximum extraction sample volume were optimized. A concentration factor of 1000 was achieved by the extraction of 500 mL of environmental water samples using MMHSPE. Detection limits obtained for SMX, SMD, SDM and SQX were 0.026, 0.024, 0.033 and 0.030 microg L(-1), respectively. Good recoveries (70-102%) with low relative standard deviations (1-6%) were achieved in analyzing spiked water samples. Low concentration of SQX was found in hospital primary and final sewage effluent sample.