Sulfonamide Per- and Polyfluoroalkyl Substances Can Impact Microorganisms Used in Aromatic Hydrocarbon and Trichloroethene Bioremediation.

Per- and polyfluoroalkyl substances (PFASs) from aqueous film forming foams (AFFFs) can hinder bioremediation of co-contaminants such as trichloroethene (TCE) and benzene, toluene, ethylbenzene, and xylene (BTEX). Anaerobic dechlorination can require bioaugmentation of Dehalococcoides, and for BTEX, oxygen is often sparged to stimulate in situ aerobic biodegradation. We tested PFAS inhibition to TCE and BTEX bioremediation by exposing an anaerobic TCE-dechlorinating coculture, an aerobic BTEX-degrading enrichment culture, and an anaerobic toluene-degrading enrichment culture to n-dimethyl perfluorohexane sulfonamido amine (AmPr-FHxSA), perfluorohexane sulfonamide (FHxSA), perfluorohexanesulfonic acid (PFHxS), or nonfluorinated surfactant sodium dodecyl sulfate (SDS). The anaerobic TCE-dechlorinating coculture was resistant to individual PFAS exposures but was inhibited by >1000× diluted AFFF. FHxSA and AmPr-FHxSA inhibited the aerobic BTEX-degrading enrichment. The anaerobic toluene-degrading enrichment was not inhibited by AFFF or individual PFASs. Increases in amino acids in the anaerobic TCE-dechlorinating coculture compared to the control indicated stress response, whereas the BTEX culture exhibited lower concentrations of all amino acids upon exposure to most surfactants (both fluorinated and nonfluorinated) compared to the control. These data suggest the main mechanisms of microbial toxicity are related to interactions with cell membrane synthesis as well as protein stress signaling.

Elucidating adsorption mechanisms of benzalkonium chlorides (BACs) on polypropylene and polyethylene terephthalate microplastics (MPs): Effects of BACs alkyl chain length and MPs characteristics.

Since the onset of the COVID-19 pandemic, there has been an increase in the use of disposable plastics and disinfectants. This study systematically investigated the adsorption behavior and mechanisms of benzalkonium chlorides (BACs), commonly used disinfectants, on polypropylene (PP) and polyethylene terephthalate (PET) microplastics (MPs), considering various factors, such as characteristics of MPs, alkyl chain length of BACs, and environmental conditions. Our results demonstrated a higher adsorption capacity for PP-MPs with relatively hydrophobic properties compared to PET-MPs, where longer alkyl chains in BACs (i.e., higher octanol-water partition coefficients, Kow) significantly enhanced adsorption through hydrophobic interactions. The inverse relationship between particle size of MPs and adsorption was evident. While changes in pH minimally affected adsorption on PP-MPs, adsorption on PET-MPs increased with rising pH, highlighting the influence of pH on electrostatic interactions. Moreover, MP aging with UV/H2O2 amplified BAC adsorption on PP-MPs due to surface oxidation and fragmentation, whereas the properties of PET-MPs remained unaltered, resulting in unchanged adsorption capacities. Spectroscopy studies and density functional theory (DFT) calculations confirmed hydrophobic and electrostatic interactions as the primary adsorption mechanisms. These findings improve our understanding of MPs and BACs behavior in the environment, providing insights for environmental risk assessments related to combined pollution.

A multifactorial fall risk assessment system for older people utilizing a low-cost, markerless Microsoft Kinect.

Falls among older people are a major health concern. This study aims to develop a multifactorial fall risk assessment system for older people using a low-cost, markerless Microsoft Kinect. A Kinect-based test battery was designed to comprehensively assess major fall risk factors. A follow-up experiment was conducted with 102 older participants to assess their fall risks. Participants were divided into high and low fall risk groups based on their prospective falls over a 6-month period. Results showed that the high fall risk group performed significantly worse on the Kinect-based test battery. The developed random forest classification model achieved an average classification accuracy of 84.7%. In addition, the individual's performance was computed as the percentile value of a normative database to visualise deficiencies and targets for intervention. These findings indicate that the developed system can not only screen out 'at risk' older individuals with good accuracy, but also identify potential fall risk factors for effective fall intervention.Practitioner summary: Falls are the leading cause of injuries in older people. We newly developed a multifactorial fall risk assessment system for older people utilising a low-cost, markerless Kinect. Results showed that the developed system can screen out 'at risk' individuals and identify potential risk factors for effective fall intervention.

Association with Combined Occupational Hazards Exposure and Risk of Metabolic Syndrome: A Workers' Health Examination Cohort 2012-2021.

Background: This study aimed to evaluate the association between exposure to occupational hazards and the metabolic syndrome. A secondary objective was to analyze the additive and multiplicative effects of exposure to risk factors. Methods: This retrospective cohort was based on 31,615 health examinees at the Pusan National University Yangsan Hospital in Republic of Korea from 2012-2021. Demographic and behavior-related risk factors were treated as confounding factors, whereas three physical factors, 19 organic solvents and aerosols, and 13 metals and dust were considered occupational risk factors. Time-dependent Cox regression analysis was used to calculate hazard ratios. Results: The risk of metabolic syndrome was significantly higher in night shift workers (hazard ratio = 1.45: 95% confidence interval = 1.36-1.54) and workers who were exposed to noise (1.15:1.07-1.24). Exposure to some other risk factors was also significantly associated with a higher risk of metabolic syndrome. They were dimethylformamide, acetonitrile, trichloroethylene, xylene, styrene, toluene, dichloromethane, copper, antimony, lead, copper, iron, welding fume, and manganese. Among the 28 significant pairs, 19 exhibited both positive additive and multiplicative effects. Conclusions: Exposure to single or combined occupational risk factors may increase the risk of developing metabolic syndrome. Working conditions should be monitored and improved to reduce exposure to occupational hazards and prevent the development of the metabolic syndrome.

Mineralization of a Fully Halogenated Organic Compound by Persulfate under Conditions Relevant to in Situ Reduction and Oxidation: Reduction of Hexachloroethane by Ethanol Addition Followed by Oxidation.

Fully halogenated compounds are difficult to remediate by in situ chemical oxidation (ISCO) because carbon-halogen bonds react very slowly with the species that typically initiate contaminant transformation: sulfate radical (SO4•-) and hydroxyl radical (•OH). To enable the remediation of this class of contaminants by persulfate (S2O82-)-based ISCO, we employed a two-phase process to dehalogenate and oxidize a representative halogenated compound (i.e., hexachloroethane). In the first phase, a relatively high concentration of ethanol (1.8 M) was added, along with concentrations of S2O82- that are typically used for ISCO (i.e., 450 mM). Hexachloroethane underwent rapid dehalogenation when carbon-centered radicals produced by the reaction of ethanol and radicals formed during S2O82- decomposition reacted with carbon-halogen bonds. Unlike conventional ISCO treatment, hexachloroethane transformation and S2O82- decomposition took place on the time scale of days without external heating or base addition. The presence of O2, Cl-, and NO3- delayed the onset of hexachloroethane transformation when low concentrations of S2O82- (10 mM) were used, but these solutes had negligible effects when S2O82- was present at concentrations typical of in situ remediation (450 mM). The second phase of the reaction was initiated after most of the ethanol had been depleted when thermolytic S2O82- decomposition resulted in production of SO4•- that oxidized the partially dehalogenated transformation products. With proper precautions, S2O82--based ISCO with ethanol could be a useful remediation technology for sites contaminated with fully halogenated compounds.

Automated Laser-Fiber Coupling Module for Optical-Resolution Photoacoustic Microscopy.

Photoacoustic imaging has emerged as a promising biomedical imaging technique that enables visualization of the optical absorption characteristics of biological tissues in vivo. Among the different photoacoustic imaging system configurations, optical-resolution photoacoustic microscopy stands out by providing high spatial resolution using a tightly focused laser beam, which is typically transmitted through optical fibers. Achieving high-quality images depends significantly on optical fluence, which is directly proportional to the signal-to-noise ratio. Hence, optimizing the laser-fiber coupling is critical. Conventional coupling systems require manual adjustment of the optical path to direct the laser beam into the fiber, which is a repetitive and time-consuming process. In this study, we propose an automated laser-fiber coupling module that optimizes laser delivery and minimizes the need for manual intervention. By incorporating a motor-mounted mirror holder and proportional derivative control, we successfully achieved efficient and robust laser delivery. The performance of the proposed system was evaluated using a leaf-skeleton phantom in vitro and a human finger in vivo, resulting in high-quality photoacoustic images. This innovation has the potential to significantly enhance the quality and efficiency of optical-resolution photoacoustic microscopy.

C2RL: Convolutional-Contrastive Learning for Reinforcement Learning Based on Self-Pretraining for Strong Augmentation.

Reinforcement learning agents that have not been seen during training must be robust in test environments. However, the generalization problem is challenging to solve in reinforcement learning using high-dimensional images as the input. The addition of a self-supervised learning framework with data augmentation in the reinforcement learning architecture can promote generalization to a certain extent. However, excessively large changes in the input images may disturb reinforcement learning. Therefore, we propose a contrastive learning method that can help manage the trade-off relationship between the performance of reinforcement learning and auxiliary tasks against the data augmentation strength. In this framework, strong augmentation does not disturb reinforcement learning and instead maximizes the auxiliary effect for generalization. Results of experiments on the DeepMind Control suite demonstrate that the proposed method effectively uses strong data augmentation and achieves a higher generalization than the existing methods.

Improved Likelihood Probability in MIMO Systems Using One-Bit ADCs.

This study considers an improved likelihood probability in multi-input multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs). MIMO systems using one-bit ADCs are known to exhibit from performance degradation because of inaccurate likelihood probabilities. To overcome this degradation, the proposed method leverages the detected symbols to estimate the true likelihood probability by combining the initial likelihood probability. An optimization problem is formulated to minimize the mean-squared error between the true and combined likelihood probabilities, and a solution is derived using the least-squares method. Simulation results show that the proposed method obtains a signal-to-noise gain of approximately 0.3 dB to achieve a frame error rate of 10-1 compared to conventional methods. This improvement in performance is attributed to the enhanced reliability of the likelihood probability.

Reinforcement Learning-Aided Channel Estimator in Time-Varying MIMO Systems.

This paper proposes a reinforcement learning-aided channel estimator for time-varying multi-input multi-output systems. The basic concept of the proposed channel estimator is the selection of the detected data symbol in the data-aided channel estimation. To achieve the selection successfully, we first formulate an optimization problem to minimize the data-aided channel estimation error. However, in time-varying channels, the optimal solution is difficult to derive because of its computational complexity and the time-varying nature of the channel. To address these difficulties, we consider a sequential selection for the detected symbols and a refinement for the selected symbols. A Markov decision process is formulated for sequential selection, and a reinforcement learning algorithm that efficiently computes the optimal policy is proposed with state element refinement. Simulation results demonstrate that the proposed channel estimator outperforms conventional channel estimators by efficiently capturing the variation of the channels.

Non-Orthogonal Multiple Access with One-Bit Analog-to-Digital Converters Using Threshold Adaptation.

In digital communication systems featuring high-resolution analog-to-digital converters (ADCs), the utilization of successive interference cancellation and detection can enhance the capacity of a Gaussian multiple access channel (MAC) by combining signals from multiple transmitters in a non-orthogonal manner. Conversely, in systems employing one-bit ADCs, it is exceedingly difficult to eliminate non-orthogonal interference using digital signal processing due to the considerable distortion present in the received signal when employing such ADCs. As a result, the Gaussian MAC does not yield significant capacity gains in such cases. To address this issue, we demonstrate that, under a given deterministic interference, the capacity of a one-bit-quantized channel becomes equivalent to the capacity without interference when an appropriate threshold value is chosen. This finding suggests the potential for indirect interference cancellation in the analog domain, facilitating the proposition of an efficient successive interference cancellation and detection scheme. We analyze the achievable rate of the proposed scheme by deriving the mutual information between the transmitted and received signals at each detection stage. The obtained results indicate that the sum rate of the proposed scheme generally outperforms conventional methods, with the achievable upper bound being twice as high as that of the conventional methods. Additionally, we have developed an optimal transmit power allocation algorithm to maximize the sum rate in fading channels.

Epidemiology of occupational injuries in construction workers between 2009 and 2018 in South Korea.

BACKGROUND: This study aimed to investigate the characteristics of occupational injuries based on fatality, sex, and classification of occupations among construction workers using workers' compensation (WC) insurance data in South Korea. METHODS: We collected WC insurance data from the Korea Workers' Compensation & Welfare Service for all construction workers between 2009 and 2018. Data from 158,947 accepted claims for occupational injury were extracted, and the demographic features, occupational injury types, and annual trends were analyzed for fatal and nonfatal cases. The annual incidence and mortality trends of occupational injury were estimated using negative binomial regression and Poisson regression models, for injury incidence and mortality respectively. RESULTS: Among a total of 158,947 occupational injury cases, there were 155,772 (98%) nonfatal injuries and 3175 (2%) fatal injuries. For all occupational injuries, Construction Elementary Workers (6th Korean Standard Classification of Occupations (KSCO) 910; 45.7%) was the most frequent occupation, followed by Construction-Related Technical Workers (6th KSCO 772; 39.2%). The most frequent injury type was a fracture, followed by ruptures or lacerations and contusions. The incidence of all occupational injuries increased from 700.36 per 100,000 persons in 2009 to 1,195.98 per 100,000 persons in 2018. Further, deaths from injuries at work followed a significantly increasing annual trend [mortality rate ratio 1.04 (95% CI: 1.03-1.05)] from 2009 to 2018. CONCLUSION: The over two-thirds increased incidence of occupational injuries and significantly increasing mortality trends for occupational injuries during the last 10 years indicate the need for aggressive intervention in occupational safety and health management within the Korean construction industry.

Cooperative DF Protocol for MIMO Systems Using One-Bit ADCs.

This study considers a detection scheme for cooperative multi-input-multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs) in a decode-and-forward (DF) relay protocol. The use of one-bit ADCs is a promising technique for reducing the power consumption, which is necessary for supporting future wireless systems comprising a large number of antennas. However, the use of a large number of antennas remains still limited to mobile devices owing to their size. Cooperative communication using a DF relay can resolve this limitation; however, detection errors at the relay make it difficult to employ cooperative communication directly. This difficulty is more severe in a MIMO system using one-bit ADCs due to its nonlinear nature. To efficiently address the difficulty, this paper proposes a detection scheme that mitigates the error propagation effect. The upper bound of the pairwise error probability (PEP) of one-bit ADCs is first derived in a weighted Hamming distance form. Then, using the derived PEP, the proposed detection for the DF relay protocol is derived as a single weighted Hamming distance. Finally, the complexity of the proposed detection is analyzed in terms of real multiplications. The simulation results show that the proposed detection method efficiently mitigates the error propagation effect but has a relatively low level of complexity when compared to conventional detection methods.

Spherical-Cap Approximation of Vector Quantization for Quantization-Based Combining in MIMO Broadcast Channels with Limited Feedback.

The spherical-cap approximation of vector quantization (SCVQ) is an analytical model used for the mathematical analysis of multiple-input multiple-output (MIMO) systems with limited feedback. SCVQ closely emulates the distribution of the quantization error induced by the finite-rate quantization of a channel using a simple and analytically tractable approach. However, the conventional SCVQ model is not applicable when antenna-combining schemes such as quantization-based combining (QBC) are considered. Because QBC is an effective antenna-combining method that minimizes channel quantization errors, it can be adopted for various practical MIMO broadcast systems. Nevertheless, evaluating the performance of QBC-based MIMO systems with an explicit codebook can be extremely difficult, depending on the system complexity. To resolve this, this study generalizes the conventional SCVQ to be compatible with the QBC. The proposed generalized version of the SCVQ effectively emulates the quantization error obtained using QBC, while enabling a simple simulation independent of the number of feedback bits and mathematically tractable analysis. We validate the effectiveness of the proposed model by presenting a wireless communication application based on a dense cellular network.

Effectiveness and Usability of a Novel Kinect-Based Tailored Interactive Fall Intervention System for Fall Prevention in Older People: A Preliminary Study.

Falls are prevalent among older people and can lead to serious health problems. We newly developed a novel Kinect-based tailored interactive fall intervention system, which seamlessly integrates multifactorial fall risk assessment and tailored intervention programs to prevent falls in older people. This preliminary study aimed to examine the effectiveness and usability of this developed system for fall prevention in older people. Thirty community-dwelling older women participated in this experiment; they were allocated to an intervention group (IG) or a control group (CG) for a quasi-randomized trial (15 people each). Participants in IG followed an 8-week tailored intervention (40 min/session × 2 sessions/week × 8 weeks) using the Kinect-based interactive fall intervention system, while participants in CG maintained their habitual activities. Various outcome measures were evaluated at baseline (Week 0), interim (Week 4), and post-intervention (Week 8). Experimental results showed that IG led to significant improvements in TUG-Timed Up and Go (p = 0.010), BBS-Berg Balance Scale (p = 0.011), and Montreal Cognitive Assessment-MoCA (p = 0.022) between baseline and post-intervention. In comparison to the baseline, TUG and BBS were even significantly improved at interim (p = 0.004 and 0.047, respectively). There were no significant changes in static balance-related performance outcomes and the Short Falls Efficacy Scale-SFES after the intervention. Whereas in CG, most performance measures did not show significant changes during the 8-week period, TUG completion time became significantly longer at post-intervention in comparison to interim (p = 0.028) and fear of falling was also significantly higher at post-intervention than baseline (p = 0.021). These findings suggest that the Kinect-based 8-week tailored interactive fall interventions effectively improved older people's physical and cognitive abilities. Regarding the usability of the developed system, the average System Usability Scale (SUS) score was 83.5 out of 100, indicating excellent system usability. The overall mean Computer Literacy Scale (CLS) score was 2.5 out of 26, showing that older participants in this study had very limited experience with computers. No significant correlation between SUS and CLS scores demonstrated that newly developed Kinect-based tailored interactive fall intervention system was easy to use for older people, regardless of their computer experience. This novel system should help health professionals and older people proactively manage the risk of falls.

A Low-Complexity Algorithm for a Reinforcement Learning-Based Channel Estimator for MIMO Systems.

This paper proposes a low-complexity algorithm for a reinforcement learning-based channel estimator for multiple-input multiple-output systems. The proposed channel estimator utilizes detected symbols to reduce the channel estimation error. However, the detected data symbols may include errors at the receiver owing to the characteristics of the wireless channels. Thus, the detected data symbols are selectively used as additional pilot symbols. To this end, a Markov decision process (MDP) problem is defined to optimize the selection of the detected data symbols. Subsequently, a reinforcement learning algorithm is developed to solve the MDP problem with computational efficiency. The developed algorithm derives the optimal policy in a closed form by introducing backup samples and data subblocks, to reduce latency and complexity. Simulations are conducted, and the results show that the proposed channel estimator significantly reduces the minimum-mean square error of the channel estimates, thus improving the block error rate compared to the conventional channel estimation.

Degradation of iopromide during the UV-LED/chlorine reaction: Effect of wavelength, radical contribution, transformation products, and toxicity.

Three different UV-LED wavelengths (265, 310, and 365 nm) were used in the UV-LED/chlorine reaction to investigate the degradation mechanism of iopromide (IPM) at different wavelengths, a representative iodinated contrast media compound. The degradation rate (k'IPM) increased from pH 6-8 at 265 nm, but, decreased as the pH increased up to 9 at 310 nm and 365 nm. Radical scavenging experiments showed that reactive chlorine species (RCS) are the dominant radical species at all wavelengths, but a higher contribution of OH• was observed at lower pH and longer wavelengths. The contribution of RCS decreased but the contribution of OH• increased as the wavelength increased. Among RCS, the largest contribution was found to be ClO•. Total nine transformation products (TPs) were identified by LC-QTOF-MS during the UV-LED/chlorine reaction at 265 nm. Based on the identified TPs and their time profiles, we proposed a degradation pathway of IPM during UV-LED/chlorine reaction. The Microtox test using V. fischeri showed that no significant increase in toxicity was observed at all wavelengths. The synergistic effect of UV-LED and chlorine was greater at a higher wavelength by the electrical efficiency per order (EEO) calculation.

Hyaluronan Synthase 1: A Novel Candidate Gene Associated With Late-Onset Non-syndromic Hereditary Hearing Loss.

OBJECTIVES: Hyaluronan synthase 1 (HAS1) is a membrane-bound protein that is abundant in the epidermis and dermis, and it is important for skin function. However, its association with hearing loss has not yet been studied. Herein, we sought to evaluate the potential contribution of HAS1: c.1082G>A to genetic hearing loss. METHODS: We used whole-exome sequencing to analyze blood DNA samples of six patients of a family with autosomal dominant familial late-onset progressive hearing loss, which was revealed to be related to a variant of the HAS1 gene. Confirmatory Sanger sequencing was performed with samples from 10 members. A missense variant was detected in HAS1 (c.1082 G>A, p.Cys361Tyr). In silico analyses predicted this variant to result in the functional loss of HAS1. Immunostaining was conducted using wild-type mouse samples to verify HAS1 expression. RESULTS: Has1 was detected in an otocyst at E10.5. In the pup, Has1 expression was localized in the stria vascularis (SV), hair cells, supporting cells of the organ of Corti, and some spiral ganglion neurons. SV marginal cells markedly expressed Has1 in the adult stage. The hearing threshold in the Has1-depleted condition was investigated by accessing the International Mouse Phenotyping Consortium's Auditory Brainstem Response (ABR) data. ABR of Has1 knock-out mice showed threshold elevations at 6, 12, and 18 kHz in young male adults. CONCLUSION: HAS1 may have a close relationship with auditory function and genetic hearing loss. Further investigation is needed to reveal the precise role of HAS1 in the auditory system. HAS1 is a candidate gene for future hereditary hearing loss genetic testing.

An Enhanced Affine Projection Algorithm Based on the Adjustment of Input-Vector Number.

An enhanced affine projection algorithm (APA) is proposed to improve the filter performance in aspects of convergence rate and steady-state estimation error, since the adjustment of the input-vector number can be an effective way to increase the convergence rate and to decrease the steady-state estimation error at the same time. In this proposed algorithm, the input-vector number of APA is adjusted reasonably at every iteration by comparing the averages of the accumulated squared errors. Although the conventional APA has the constraint that the input-vector number should be integer, the proposed APA relaxes that integer-constraint through a pseudo-fractional method. Since the input-vector number can be updated at every iteration more precisely based on the pseudo-fractional method, the filter performance of the proposed APA can be improved. According to our simulation results, it is demonstrated that the proposed APA has a smaller steady-state estimation error compared to the existing APA-type filters in various scenarios.

Smart Skin: Vision-Based Soft Pressure Sensing System for In-Home Hand Rehabilitation.

We introduce a novel in-home hand rehabilitation system for monitoring hand motions and assessing grip forces of stroke patients. The overall system is composed of a sensing device and a computer vision system. The sensing device is a lightweight cylindrical object for easy grip and manipulation, which is covered by a passive sensing layer called "Smart Skin." The Smart Skin is fabricated using soft silicone elastomer, which contains embedded microchannels partially filled with colored fluid. When the Smart Skin is compressed by grip forces, the colored fluid rises and fills in the top surface display area. Then, the computer vision system captures the image of the display area through a red-green-blue camera, detects the length change of the liquid through image processing, and eventually maps the liquid length to the calibrated force for estimating the gripping force. The passive sensing mechanism of the proposed Smart Skin device works in conjunction with a single camera setup, making the system simple and easy to use, while also requiring minimum maintenance effort. Our system, on one hand, aims to support home-based rehabilitation therapy with minimal or no supervision by recording the training process and the force data, which can be automatically conveyed to physical therapists. In contrast, the therapists can also remotely instruct the patients with their training prescriptions through online videos. This study first describes the design, fabrication, and calibration of the Smart Skin, and the algorithm for image processing, and then presents experimental results from the integrated system. The Smart Skin prototype shows a relatively linear relationship between the applied force and the length change of the liquid in the range of 0-35 N. The computer vision system shows the estimation error <4% and a relatively high stability in estimation under different hand motions.

Adsorption of benzalkonium chlorides onto polyethylene microplastics: Mechanism and toxicity evaluation.

Usage of disposable plastic products and disinfectants has been skyrocketing due to the COVID-19 pandemic. The random disposal of plastic products may result in greater microplastic pollution. Benzalkonium chloride is known as one of the most common ingredients of disinfectants. In this study, the adsorption behavior of benzalkonium chlorides (BAC12, BAC14, BAC16) on polyethylene microplastics (PE-MPs) and the combined toxic effects were investigated using batch adsorption experiment and Daphnia magna. The results showed that PE-MPs had strong adsorption capacity for BACs and the adsorption capacity increased (11.03-22.77 mg g-1) with their octanol-water distribution coefficients. The effect of pH was negligible while dissolved organic matter inhibited the adsorption. A slightly inverse relationship between particle size of PE-MPs and adsorption was observed. Additionally, the MP aging with UV/H2O2 increased the adsorption of BAC12 but decreased that of relatively hydrophobic BAC14 and BAC16. The survival rate of Daphnia magna increased up to 100% in the presence of PE-MPs depending upon their adsorption capacities, suggesting that PE-MPs do not act as a carrier but rather as a scavenger for BACs. This study provides important information necessary for environmental risk assessment with regard to the combined pollution of MPs and toxic chemicals.