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The incorporation of inorganic fillers into composite polymer electrolytes (CPEs) is a common strategy to improve ionic conductivity. However, the high surface energy of inorganic fillers typically aggravates poor interfacial contact with polymer chains. Herein, we develop a surface positive-charge modification strategy for enhancing the intermolecular interaction of poly(ethylene oxide) (PEO) electrolytes with inorganic fillers and optimizing lithium ion (Li

This review covers recent advances in understanding, designing, and exploring the defect in carbon toward energy-related applications, with the aim of referencing and guiding the large-scale and diverse applications of defect-rich carbon materials.

Despite the prevalence of nitrate reduction in groundwater, the biotransformation of per- and polyfluoroalkyl substances (PFAS) under nitrate-reducing conditions remains mostly unknown compared with aerobic or strong reducing conditions. We constructed microcosms under nitrate-reducing conditions to simulate the biotransformation occurring at groundwater sites impacted by aqueous film-forming foams (AFFFs). We investigated the biotransformation of 6:2 fluorotelomer thioether amido sulfonate (6:2 FtTAoS), a principal PFAS constituent of several AFFF formulations using both quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) and qualitative high-resolution mass spectrometry analyses. Our results reveal that the biotransformation rates of 6:2 FtTAoS under nitrate-reducing conditions were about 10 times slower than under aerobic conditions, but about 2.7 times faster than under sulfate-reducing conditions. Although minimal production of 6:2 fluorotelomer sulfonate and the terminal perfluoroalkyl carboxylate, perfluorohexanoate was observed, fluorotelomer thioether and sulfinyl compounds were identified in the aqueous samples. Evidence for the formation of volatile PFAS was obtained by mass balance analysis using the total oxidizable precursor assay and detection of 6:2 fluorotelomer thiol by gas chromatography-mass spectrometry. Our results underscore the complexity of PFAS biotransformation and the interactions between redox conditions and microbial biotransformation activities, contributing to the better elucidation of PFAS environmental fate and impact.

Semantic segmentation is an important task for scene understanding in self-driving cars and robotics, which aims to assign dense labels for all pixels in the image. Existing work typically improves semantic segmentation performance by exploring different network architectures on a target dataset. Little attention has been paid to build a unified system by simultaneously learning from multiple datasets due to the inherent distribution shift across different datasets. In this paper, we propose a simple, flexible, and general method for semantic segmentation, termed Cross-Dataset Collaborative Learning (CDCL). Our goal is to train a unified model for improving the performance in each dataset by leveraging information from all the datasets. Specifically, we first introduce a family of Dataset-Aware Blocks (DAB) as the fundamental computing units of the network, which help capture homogeneous convolutional representations and heterogeneous statistics across different datasets. Second, we present a Dataset Alternation Training (DAT) mechanism to facilitate the collaborative optimization procedure. We conduct extensive evaluations on diverse semantic segmentation datasets for autonomous driving. Experiments demonstrate that our method consistently achieves notable improvements over prior single-dataset and cross-dataset training methods without introducing extra FLOPs. Particularly, with the same architecture of PSPNet (ResNet-18), our method outperforms the single-dataset baseline by 5.65\%, 6.57\%, and 5.79\% mIoU on the validation sets of Cityscapes, BDD100K, CamVid, respectively. We also apply CDCL for point cloud 3D semantic segmentation and achieve improved performance, which further validates the superiority and generality of our method. Code and models will be released.

An oxygen-vacancy-rich Fe3O4/carbon nanosheets composite is fabricated from Fe3+-gluconate complex as precursor using a spontaneous foaming strategy. The composite has a unique 2D structure and exhibits superior microwave absorption capability.

Supplementary Material 1

Lithium metal is considered as a strongly attractive anode candidate for the high-energy-storage field, but its dreadful dendrite growth has haunted its commercialization progress. Herein, we develop a lithiophilic Nb2O5-embedded three-dimensional (3D) carbon nanofiber network (Nb2O5-CNF) as a scaffold to preload molten Li for the fabrication of dendrite-free composite anode. The in situ lithiation reaction between molten Li and Nb2O5 nanocrystals results in the formation of nanosize LixNbyO nanoparticles, which can serve as preferred sites that regulate nucleation/growth behavior of Li during the plating process. Besides, due to its high structural stability and abundant internal inner space, the 3D CNF network can function as a reservoir to confine the dimensional expansion of "hostless Li". The resulting Li composite anodes exhibit enlarged active areas and reduced interfacial energy barriers, delivering a prolonged cycling of 1000 h with an ultralow hysteresis of 52 mV and dendrite-free morphology in a symmetric cell (1.0 mA cm-2). Coupled with the LiFePO4 cathode, the Li@Nb2O5-CNF anode sustains a reversible capacity of 163 mAh g-1 with an excellent capacity retention of 93.0% after 370 cycles at 0.5C. This all-around strategy of lithiophilic sites coupled with a 3D conductive nanofiber matrix may shed light on promising applications of high-capacity and dendrite-free Li-metal batteries.

Oral squamous cell carcinoma (OSCC) is the predominant histological type of the head and neck squamous cell carcinoma (HNSCC). By comparing the differentially expressed genes (DEGs) in OSCC-TCGA patients with copy number variations (CNVs) that we identify in OSCC-OncoScan dataset, we herein identified 37 dysregulated candidate genes. Among these potential candidate genes, 26 have been previously reported as dysregulated proteins or genes in HNSCC. Among 11 novel candidates, the overall survival analysis revealed that melanotransferrin (MFI2) is the most significant prognostic molecular in OSCC-TCGA patients. Another independent Taiwanese cohort confirmed that higher MFI2 transcript levels were significantly associated with poor prognosis. Mechanistically, we found that knockdown of MFI2 reduced cell viability, migration and invasion via modulating EGF/FAK signaling in OSCC cells. Collectively, our results support a mechanistic understanding of a novel role for MFI2 in promoting cell invasiveness in OSCC.

Graduate student scholar/artists Sydney Erlikh, Maggie Bridger, and Sandie Yi reflect on their experiences of having attended VIBE: Challenging Ableism and Audism Through the Arts. The three were struck by the diversity and range of unique experiences reflected in the work of the presenting artists. Each author takes the lead on one of three themes they collectively identified: what constitutes disability art, how community shapes artistic and scholarly practice, and how boundaries of the field are evolving. The article explores the ways in which disabled artists are defining creative processes and aesthetic approaches outside of the mainstream art world and its ableist productivity demands. They also take note of how artists with non- apparent disabilities are actively moving the field in new directions. Finally, they examine the ethical dimensions of artistic “ownership” in the collaboration between artists with and without disabilities, particularly around those with intellectual disabilities and their allies. The authors ultimately offer a description of a new wave of disability art that is pushing the field to think through questions of process, collaboration, ethics, visibility, creative scholarship, and relationship to disability studies. This new work, they argue, is creating space for a more sustainable, community-based practice.

Sites impacted by aqueous film-forming foam (AFFF) contain co-contaminants that can stimulate biotransformation of polyfluoroalkyl substances. Here, we compare how microbial enrichments from AFFF-impacted soil amended with diethyl glycol monobutyl ether (found in AFFF), aromatic hydrocarbons (present in co-released fuels), acetate, and methane (substrates used or formed during bioremediation) impact the aerobic biotransformation of an AFFF-derived six-carbon electrochemical fluorination (ECF) precursor

Sample assignment plays a prominent part in modern object detection approaches. However, most existing methods rely on manual design to assign positive / negative samples, which do not explicitly establish the relationships between sample assignment and object detection performance. In this work, we propose a novel dynamic sample assignment scheme based on hyper-parameter search. We first define the number of positive samples assigned to each ground truth as the hyper-parameters and employ a surrogate optimization algorithm to derive the optimal choices. Then, we design a dynamic sample assignment procedure to dynamically select the optimal number of positives at each training iteration. Experiments demonstrate that the resulting HPS-Det brings improved performance over different object detection baselines. Moreover, We analyze the hyper-parameter reusability when transferring between different datasets and between different backbones for object detection, which exhibits the superiority and versatility of our method.

Due to the COVID-19 pandemic, most employees face increasing career-related stress, particularly those who work in multinational corporations (MNCs), because the international travel constraints prevent them from going back to their families. Hence, it is imperative to investigate the critical impact of employees’ occupational burnout (OB) on career-related outcomes. In response, this research explores the moderating effect of OB on the relationships between career competencies (CCs) and career sustainability (CS). To achieve a more comprehensive understanding of relevant issues, we adopted a mixed-method research design that includes both qualitative and quantitative analyses. Findings indicate that all the three dimensions of CCs (i.e., reflective, communicative, and behavioral career competencies; RC, CC, and BC) were positively related to CS; moreover, OB negatively moderated the individual relationships of CC and BC with CS. The main contribution of this study is to enrich the existing career literature by addressing the critical moderating role of OB in the links of CC and BC individually with CS. Practical implications are also discussed in this study.

BackgroundPreoperative stereotactic planning of deep brain stimulation (DBS) using computed tomography (CT) imaging in patients with Parkinson's disease (PD) is of clinical interest. However, frame-induced metal artifacts are common in clinical practice, which can be challenging for neurosurgeons to visualize brain structures.ObjectivesTo evaluate the image quality and radiation exposure of patients with stereotactic frame brain CT acquired using a dual-source CT (DSCT) system in single- and dual-energy modes.Materials and MethodsWe included 60 consecutive patients with Parkinson's disease (PD) and randomized them into two groups. CT images of the brain were performed using DSCT (Group A, an 80/Sn150 kVp dual-energy mode; Group B, a 120 kVp single-energy mode). One set of single-energy images (120 kVp) and 10 sets of virtual monochromatic images (50–140 keV) were obtained. Subjective image analysis of overall image quality was performed using a five-point Likert scale. For objective image quality evaluation, CT values, image noise, signal-to-noise ratio (SNR), and contrast-to-noise (CNR) were calculated. The radiation dose was recorded for each patient.ResultsThe mean effective radiation dose was reduced in the dual-energy mode (1.73 mSv ± 0.45 mSv) compared to the single-energy mode (3.16 mSv ± 0.64 mSv) (p < 0.001). Image noise was reduced by 46–52% for 120–140 keV VMI compared to 120 kVp images (both p < 0.01). CT values were higher at 100–140 keV than at 120 kVp images. At 120–140 keV, CT values of brain tissue showed significant differences at the level of the most severe metal artifacts (all p < 0.05). SNR was also higher in the dual-energy mode 90–140 keV compared to 120 kVp images, showing a significant difference between the two groups at 120–140 keV (all p < 0.01). The CNR was significantly better in Group A for 60–140 keV VMI compared to Group B (both p < 0.001). The highest subjective image scores were found in the 120 keV images, while 110–140 keV images had significantly higher scores than 120 kVp images (all p < 0.05).ConclusionDSCT images using dual-energy modes provide better objective and subjective image quality for patients with PD at lower radiation doses compared to single-energy modes and facilitate brain tissue visualization with stereotactic frame DBS procedures.

Recently, self-attention mechanisms have shown impressive performance in various NLP and CV tasks, which can help capture sequential characteristics and derive global information. In this work, we explore how to extend self-attention modules to better learn subtle feature embeddings for recognizing fine-grained objects, e.g., different bird species or person identities. To this end, we propose a dual cross-attention learning (DCAL) algorithm to coordinate with self-attention learning. First, we propose global-local cross-attention (GLCA) to enhance the interactions between global images and local high-response regions, which can help reinforce the spatial-wise discriminative clues for recognition. Second, we propose pair-wise cross-attention (PWCA) to establish the interactions between image pairs. PWCA can regularize the attention learning of an image by treating another image as distractor and will be removed during inference. We observe that DCAL can reduce misleading attentions and diffuse the attention response to discover more complementary parts for recognition. We conduct extensive evaluations on fine-grained visual categorization and object re-identification. Experiments demonstrate that DCAL performs on par with state-of-the-art methods and consistently improves multiple self-attention baselines, e.g., surpassing DeiT-Tiny and ViT-Base by 2.8% and 2.4% mAP on MSMT17, respectively., Comment: Accepted by CVPR 2022

Sparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features. In this work, we propose to improve Sparse R-CNN with two dynamic designs. First, Sparse R-CNN adopts a one-to-one label assignment scheme, where the Hungarian algorithm is applied to match only one positive sample for each ground truth. Such one-to-one assignment may not be optimal for the matching between the learned proposal boxes and ground truths. To address this problem, we propose dynamic label assignment (DLA) based on the optimal transport algorithm to assign increasing positive samples in the iterative training stages of Sparse R-CNN. We constrain the matching to be gradually looser in the sequential stages as the later stage produces the refined proposals with improved precision. Second, the learned proposal boxes and features remain fixed for different images in the inference process of Sparse R-CNN. Motivated by dynamic convolution, we propose dynamic proposal generation (DPG) to assemble multiple proposal experts dynamically for providing better initial proposal boxes and features for the consecutive training stages. DPG thereby can derive sample-dependent proposal boxes and features for inference. Experiments demonstrate that our method, named Dynamic Sparse R-CNN, can boost the strong Sparse R-CNN baseline with different backbones for object detection. Particularly, Dynamic Sparse R-CNN reaches the state-of-the-art 47.2% AP on the COCO 2017 validation set, surpassing Sparse R-CNN by 2.2% AP with the same ResNet-50 backbone., Accepted by CVPR 2022

Titanium dioxide (TiO2) nanoparticles are efficient photocatalysis for treating organic pollutants in water. Immobilizing TiO2 nanoparticles not only enables the reuse of nanoparticles but also prevents the harmful impact of releasing nanoparticles into the aquatic environment. In this study, a porous composite microfiber membrane based on polyacrylonitrile (PAN) with TiO2 nanoparticles has been synthesized by electrospinning technique. The new membrane system has exhibited excellent adsorptive-photocatalytic property to degrade Methylene blue (MB). Using the nonlinear form of the pseudo-first-order, pseudo-second-order, Elovich, and Intra-particle diffusion models, the adsorption mechanism was analyzed. Coupling with adsorption and photocatalysis, the efficiency of this membrane system was illustrated via the multistage linear form of the pseudo-first-order kinetic; and the electrical energy per order (EEO) confirmed the lowest energy requirements to transfer selected pollutants. Combining the results of SEM, BET, FTIR, XRD and TGA, it revealed the relationship of microstructure, composition, and MB decomposition performance. The finding presents new knowledge for material design and evaluation of polymers/oxides membrane systems for remediating organic pollutants in water.

The cryogenic performance of multinanoscale CMOS transistors with a standard 55-nm Si-bulk technology is systematically investigated by dc measurements. In contrast to 300 K, the cryogenic drain saturation current ( ${I}_{\text {dsat}}$ ) gain significantly enhances from 54% to 167% with the increasing channel length and has a relatively weak response to width change. In addition, the degraded subthreshold swing (SS) due to the short channel effect is alleviated at lower temperatures. The merits of a typical nMOS transistor ( ${W}/{L} = 0.6~\mu \text{m}$ /60 nm) worked at 4.2 K are associated with an improved ${I}_{\text {dsat}}$ (~1.3 times), decreased drain leakage current with three orders of magnitude, and 2/3 reduced SS. However, the cryogenic ${I}_{\text {dsat}}$ tends to saturate below 10 K and the threshold voltage increases, as well as barrier lowering induced by drain voltage, starts to deteriorate. The detailed analyses on these MOSFET (deep) cryogenic characteristics are implemented based on the comprehensive semiconductor physics images, including energy band change, temperature/geometry-dependent scattering, band-to-band tunneling process, and depletion width influence. Our findings will be beneficial for the community to design ultralow temperature-integrated circuits.

The complete mitochondrial genome (mtgenome) was determined from the emerged-pupa shell (Noninvasive sampling) of T. aureus wuyiensis Lee. It was 15,234 base pairs in length and contained 13 protein-coding genes (PCGs), 2 rRNA genes, 22 tRNA genes, and a control region. By taking Meandrusa sciron and Teinopalpus imperialis as outgroups, a maximum-likelihood phylogenetic tree was constructed among five geographical populations of Teinopalpus aureus based on 13 PCGs and two rRNA genes. Our results showed that the WYS, MHS and PS populations, locating at or closing to Wuyishan Mountain-range, were in one cluster; while the JLS (locating at Nanling Mountain-range) and DYS (locating at Dayaoshan Mountain closing to Nanling Mountain-range) populations belonged to another cluster. It supported well the subspecies of T. aureus wuyiensis, and suggested that the genetic relationship between T. a. guangxiensis and the nominal subspecies of T. a. aureus were closer enough to combine into one subspecies.

Tap water contains some heavy metals and bio-organic substances with variety of concentration and these cannot be treated using regular physicochemical processes. So the present study, aims at evaluating the effectiveness of the sterilization using electrocatalytic technique with Escherichia coli (E. coli) as the observed index. The operational parameters such as anode material, voltage, inflow method, and electrode number are studied to understand the variation of pH, conductivity, E. coli, and residual chlorine of tap water. The outcome reveals that the maximum sterilization efficiency of E. coli is obtained using the titanium dioxide electrode, followed by ruthenium dioxide and graphite. A disinfection efficiency of 98% can be easily achieved. Also, the appropriate increase in the operating voltage can increase the sterilization efficiency and decrease the treatment time. The sterilization efficiency of the E. coli can reach 100% under the continuous inflow of tap water and the voltage of 60 V for 1 min, which meets the conventional standard of drinking water (6 CFU/100ml). The estimated operating cost of treatment of 1 ton of tap water is NTD 1.7.

Solid polymer electrolytes (SPEs) with good flexibility and low cost are very promising for all-solid-state lithium metal batteries, but they suffer from the trade-off between ionic conductivity at room temperature and mechanical stability. Herein, a robust composite polymer electrolyte is prepared by thermal lamination of PEO polymer electrolyte films onto a lithiated organic nanofiber membrane (LOF), which could combine the merits of 3D Li-ion conduction highways for high ionic conductivity and nanofiber-reinforced networks for good mechanical properties. The intimate combination between the nanofibers and the PEO matrix endows the LOF-reinforced PEO composite (LOF-CPE) with homogeneous structure, leading to an enhanced ultimate tensile stress of 8.9 MPa. Furthermore, the introduction of the LOF significantly decreases the crystallinity of the polymer matrix, which accelerates polymer segmental motion. The well-designed LOF also constructs an interfacial percolation network with additional active Li+, resulting in the formation of high-speed Li-ion conduction pathways. Therefore, the as-prepared LOF-CPE delivers an excellent ionic conductivity of 7.41 × 10−5 S cm−1 at 30 °C. While used as a SPE in LiFePO4|Li solid-state batteries, the batteries exhibit good cyclability with a capacity retention of 82% after 500 cycles under 0.5C. This work provides a very promising strategy for solid polymer electrolytes to simultaneously achieve high ionic conductivity and excellent mechanical properties towards high-performance solid-state lithium metal batteries.

Live-attenuated rotavirus vaccine has shown low protection in underdeveloped or developing countries. However, the inactivated rotavirus vaccine may have the potential to overcome some of these challenges. In the present study, the immunogenicity and protective efficacy of a bivalent inactivated rotavirus vaccine by parenteral administration were elevated in a neonatal rhesus monkey model. A bivalent inactivated rotavirus vaccine containing G1P[8] (ZTR-68 strain) and G9P[8] (ZTR-18 strain) was administered to pregnant rhesus monkeys twice at an interval of 14 days. Neutralizing antibodies against RV strains ZTR-68, ZTR-18, SA11, WA, UK, and Gottfried emerged in pregnant rhesus monkeys and were transplacentally transmitted to the offspring. In the vaccine group, clinical symptoms of diarrhea, viral load in the gut tissue and histopathological changes were significantly reduced in the neonatal rhesus monkeys following oral challenge with the SA11 strain.

Aqueous film-forming foams (AFFFs) are important sources of per- and polyfluoroalkyl substances (PFASs) in soil, groundwater, and surface water. Soil microorganisms can convert polyfluorinated substances into persistent perfluoroalkyl acids, but the understanding of co-contaminant stimulation or inhibition of PFASs biotransformation is limited. In this study, we investigate how aerobic biotransformation of polyfluorinated substances was affected by common AFFF co-contaminants, such as gasoline aromatics: benzene, toluene, ethylbenzene, and

An observation model is introduced for accurate positioning of the ionospheric field-aligned irregularities (FAIs). The model is applied to the Hainan coherent scatter phased array radar (HCOPAR) in the Hainan island of China and constructed based on the International Geomagnetic Reference Field (IGRF) model. Compared with the original centerline method, the model method has higher accuracy at a higher altitude and larger azimuth. In the observation of the E-region irregularities, the model can be used to position the sidelobe echoes under certain conditions. Thus, the zonal observation range of the radar can be extended.

Generative adversarial network (GAN) has become a research hotspot in generation model, since it can generate realistic images. To cope with the problem that the GAN cannot effectively capture the dependency between local and global features of the image and the dependency between different classes, this paper proposes a new generation model, named twins attention mechanism based generative adversarial network (TAGAN). Driven by twins attention mechanism, the real natural image is modeled by simulating the dependencies between local and global features and the dependencies between categories to create realistic fake images. TAGAN has feature attention and channel attention. The feature attention learns the correlation between similar features by selectively aggregating features. The channel attention learns the internal dependencies of each channel by integrating the relevant features of each channel dimension. The experiments implemented on the MNIST, CIFAR10 and CelebA64 datasets demonstrate that the proposed model is effective.

An endophytic member of the genus Trichoderma was isolated from the root of a healthy 3-year-old Panax notoginseng in Yunnan province, PR China. The results of phylogenetic analyses based on a combined of ITS, tef1 and rpb2 indicated that this isolate was distinct from other species of the genus Trichoderma and closely related to Trichoderma songyi. It can be distinguished from T. songyi by its slower growth rates on PDA and colony morphology. The novel isolate formed conidia in thick white pustules scattered mostly at the margin. Its conidiophores tended to be regularly verticillium-like, little branched, sometimes substituted by phialides singly or in whorls. Conidia are smooth, mostly broadly subglobose to ellipsoidal. In combination with the genotypic and phenotypic characteristics, all data demonstrated that the fungus studied represented a unique and distinguishable novel species of the genus Trichoderma, for which the name Trichoderma panacis sp. nov. is proposed.

BACKGROUND: Long before the outbreak of COVID-19, chatbots had been playing an increasingly crucial role and gaining growing popularity in healthcare. In the current omicron waves of this pandemic when the most resilient healthcare systems at the time are increasingly being overburdened, these conversational agents (CA) are being resorted to as preferred alternatives for healthcare information. For many people, especially the adolescent and middle-aged, mobile phones are the most favored source of information. As a result of this, it is more important than ever to investigate the user experience of and satisfaction with chatbots on mobile phones. OBJECTIVE: The objective of this study was twofold: (i) Informed by Deneche & Warren's evaluation framework, Zhu, Janssen, Wang & Liu's measures of variables, and the Theory of Consumption Values, we designed a new assessment model for evaluating the user experience of and satisfaction with chatbots on mobile phones; and (ii) we aimed to validate the newly-developed model and use it to gain an understanding of the user experience of and satisfaction with the popular healthcare chatbots that are available for use by young people aged between 17 and 35 in southeast China in self-diagnosis and acquiring information about COVID-19 and virus variants that are currently spreading. METHODS: First, in order to assess user experience and satisfaction, we identified the assessment model based on relevant literature and the Theory of Consumption Values. Second, the chatbots were pre-screened and selected for investigation. Subsequently, 413 informants were recruited from Nantong University, China. This was followed by a questionnaire survey soliciting the participants' experience of and satisfaction with the selected healthcare chatbots via an Internet questionnaire survey platform (https://www.wjx.cn/). Finally, quantitative and qualitative analyses were made to find the informants' perception. RESULTS: The data collected were highly reliable (cronbach α=0.986) and valid (communalities=0.632~0.823, KMO=0.980, percentage of cumulative variance (rotated)=75.257%, P

Lithium metal is considered as a strongly attractive anode candidate for the high-energy-storage field, but its dreadful dendrite growth has haunted its commercialization progress. Herein, we develop a lithiophilic Nb

Dibutyl phthalate (DBP) in the presence of a wastewater system is harmful to the environment and interferes with the human’s endocrine system. For wastewater treatment, DBP is very difficult to be decomposed by biotechniques and many catalytic processes have been developed. Among them, the electrocatalytic oxidation (EO) technique has been proven to possess high degradation efficiency of various organic compounds in wastewater. In this study, an electrocatalytic electrode of iridium-tantalum/titanium (IrO2-Ta2O5/Ti) was employed as the anode and graphite as the cathode to decompose DBP substances in the water. According to experimental results, the high removal efficiency of DBP and total organic carbon (TOC) of 90% and 56%, respectively, could be obtained under a voltage gradient of 10 V/cm for 60 min. Compared with other photocatalysis degradation, the IrO2-Ta2O5/Ti electrode could shorten about half the treatment time and electric power based on the same removal efficiency of DBP (i.e., photocatalysis requires 0.225~0.99 KWh). Results also indicated that the production of hydroxyl radical (•OH) in the electrocatalytic electrode played a key role for decomposing the DBP. Moreover, the pH and conductivity of water containing DBP were slightly changed and eventually remained in a stable state during the EO treatment. In addition, the removal efficiency of DBP could still remain about 90% after using the IrO2-Ta2O5/Ti electrode three times and the surface structure of the IrO2-Ta2O5/Ti electrode was stable.