A cross-sectional study to assess medication safety,knowledge,attitude,and practices regarding nutrition and medication among pregnant women

Objective:To assess pregnant women's knowledge,attitude,and practice regarding nutrition and medication usage,analyse the prescribing pattern,and categorize them based on the Food and Drug Administration(FDA)guidelines.Methods:A cross-sectional study was conducted with 264 pregnant women in the obstetrics and gynaecology department of a tertiary care hospital from October 2022 to August 2023.A knowledge,attitude,and practice(KAP)questionnaire was prepared in English language by the researchers and validated by an expert panel consisting of 12 members.The validated questionnaire was then translated into regional languages,Kannada and Malayalam.The reliability of the questionnaire was assessed with test-retest method with a representative sample population of 30 subjects(10 subjects for each language).The subjects'knowledge,attitude,and practice were evaluated using the validated KAP questionnaire.The safety of the medication was assessed using the FDA drug safety classification for pregnancy.Results:The mean scores for nutritional and medication usage knowledge,attitude,and practice were 4.14±1.15,4.50±1.09,and 3.00±1.47,respectively.Among 30 prescribed medications,3 belong to category A(no risk in human studies),8 belong to category B(no risk in animal studies),18 belong to category C(risk cannot be ruled out)and 1 drug is not classified.A significant association was observed between medication knowledge and practice(r=0.159,P=0.010).Conclusions:Most of the study population knows the need to maintain good dietary and medication practices during pregnancy.Counselling pregnant women regarding diet and medication usage is crucial in maternal care.

A Dual-Task Learning Approach for Bearing Anomaly Detection and State Evaluation of Safe Region

Predictive maintenance has emerged as an effective tool for curbing maintenance costs,yet prevailing research predominantly concentrates on the abnormal phases.Within the ostensibly stable healthy phase,the reliance on anomaly detection to preempt equipment malfunctions faces the challenge of sudden anomaly discernment.To address this challenge,this paper proposes a dual-task learning approach for bearing anomaly detection and state evaluation of safe regions.The proposed method transforms the execution of the two tasks into an optimization issue of the hypersphere center.By leveraging the monotonicity and distinguishability pertinent to the tasks as the foundation for optimization,it reconstructs the SVDD model to ensure equilibrium in the model’s performance across the two tasks.Subsequent experiments verify the proposed method’s effectiveness,which is interpreted from the perspectives of parameter adjustment and enveloping trade-offs.In the meantime,experimental results also show two deficiencies in anomaly detection accuracy and state evaluation metrics.Their theoretical analysis inspires us to focus on feature extraction and data collection to achieve improvements.The proposed method lays the foundation for realizing predictive maintenance in a healthy stage by improving condition awareness in safe regions.

Study on the Safety and Prevention Technology of Coal Mining under the River in Xingyuan Coal Mine

Coal mining-induced surface subsidence poses significant ecological and infrastructural challenges, necessitating a comprehensive study to ensure safe mining practices, particularly in underwater conditions. This project aims to address the extensive impact of coal mining on the environment, infrastructure, and overall safety, focusing on the Shigong River area above the working face. The study employs qualitative and quantitative analyses, along with on-site engineering measurements, to gather data on crucial parameters such as coal seam characteristics, roof rock lithology, thickness, water resistance, and structural damage degree. The research encompasses a multidisciplinary approach, involving mining, geology, hydrogeology, geophysical exploration, rock mechanics, mine surveying, and computational mathematics. The importance of effective safety measures and prevention techniques is emphasized, laying the foundation for research focused on the Xingyun coal mine. The brief concludes by highlighting the potential economic and social benefits of this project and its contribution to valuable experience for future subsea coal mining.

Facile preparation and efficient MnxCoy porous nanosheets for the sustainable catalytic process of soot

The pursuit of high-performance is worth considerable effort in catalysis for energy efficiency and environmental sustainability. To develop redox catalysts with superior performance for soot combustion, a series of Mn_(x)Co_(y) oxides were synthesized using MgO template substitution.This method greatly improves the preparation and catalytic efficiency and is more in line with the current theme of green catalysts and sustainable development. The resulting Mn_(1)Co_(2.3) has a strong activation capability of gaseous oxygen due to a high concentration of Co^(3+) and Mn^(3+). The Mn doping enhanced the intrinsic activity by prompting oxygen vacancy formation and gaseous oxygen adsorption. The nanosheet morphology with abundant mesoporous significantly increased the solid–solid contact efficiency and improved the adsorption capability of gaseous reactants. The novel design of Mn_(1)Co_(2.3)oxide enhanced its catalytic performance through a synergistic effect of Mn doping and the porous nanosheet morphology, showing significant potential for the preparation of high-performance soot combustion catalysts.

An efficient and universal protoplast-based transient gene expression system for genome editing in Brassica crops

Protoplast-based transient gene expression system has been widely used in plant genome editing because of its simple operation and less time-consuming.In order to establish a universal protoplast-based transient transfection system for verifying activities of genome editing vectors containing targets in Brassica,we systematically optimized factors affecting protoplast isolation and transient gene expression.We established an efficient protoplast-based transient gene expression system(PTGE)in Chinese cabbage,achieving high protoplast yield of 4.9×10^(5)·g^(-1)FW,viability over 95%,and transfection efficiency of 76%.We showed for the first time that pretreatment of protoplasts with a hypotonic MMG could significantly enhance the transfection efficiency.Furthermore,protoplasts incubated at 37℃ for 6 min improved the transfection efficiency to 86%.We also demonstrated that PTGE worked well(more than 50%transfection efficiency)in multiple Brassica species including cabbage,Pak Choi,Chinese kale,and turnip.Finally,PTGE was used for validating the activities of CRISPR/Cas9 vectors containing targets in Chinese cabbage,cabbage,and pak choi,demonstrating the broad applicability of the established PTGE for genome editing in Brassica crops.

"Three-in-One" Ecological Development and Efficient Utilization Model of Aggregates

Green mining and the formation of an effective and efficient development model have become key issues that aggregates enterprises around the world need to solve urgently.On the basis of analyzing the development status of aggregates industry in Xiluodu area,the paper studied the main problems faced in the construction of green aggregates mines at present,and proposed a"three-in-one"ecological,intelligent and efficient green mine construction model for"ecological development","green logistics"and"solid waste recycling"of aggregates.The study has certain theoretical value and practical significance for the construction of green aggregates mine in Xiluodu area.

A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart agriculture.Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes.This paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks.The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies.The protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base station.The performance of the proposed protocol is evaluated through the network simulator NS3.40.For different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network lifetime.For 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.

Low rank optimization for efficient deep learning:making a balance between compact architecture and fast training

Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.

Efficiency and safety of laparoscopic left hemihepatectomy: A study of intrathecal vs extrathecal Glissonean pedicle techniques

BACKGROUND Selective hemihepatic vascular occlusion is utilized in both right and left hemihepatectomies to preserve blood supply to the intact lobe,maintain hemo-dynamic stability,and mitigate surgical risks.While this technique encompasses both intrathecal and extrathecal Glissonean pedicle transection methods,there is a lack of systematic comparative reports on these two approaches.AIM To retrospectively analyze the clinical data of patients with hepatocellular carcinoma(HCC)undergoing laparoscopic anatomical hepatectomy in our hospital to explore the feasibility,safety,and short-and long-term efficacy of extrathecal and intrathecal Glissonean pedicle transection methods in laparo-scopic left hemihepatectomy.METHODS A retrospective study was performed to analyze the clinical data of 49 HCC patients who underwent laparoscopic left hemihepatectomy from January 2019 to December 2022 in our hospital.These patients were divided into extrathecal Glissonean pedicle transection(EGP)group(n=24)and intrathecal Glissonean pedicle transection(IGP)group(n=25)according to the different approaches used for selective hemihepatic vascular occlusion.The perioperative indicators,liver function indexes,complications,and follow-up findings were compared between these two groups.RESULTS The surgeries were smooth in both groups,and no perioperative death was noted.The hepatic pedicle transection time and the operation time were(16.1±2.3)minutes and(129.6±19.0)minutes,respectively,in the EGP group,which were significantly shorter than those in the IGP group[(25.5±2.4)minutes and(184.8±26.0)minutes,respectively],both P<0.01.There were no significant differences in intraoperative blood loss,time to anal exhaust,hospital stay,drain indwelling time,and postoperative liver function between the two groups(all P>0.05).The incidence of postoperative complications showed no significant difference[16.67%(4/24)vs 16.0%(4/25),P>0.05].All the 49 HCC patients were followed up after surgery(range:11.2-53.3 months;median:36.4 months).The overall survival rate and disease-free survival rate were not significantly different(both P>0.05).CONCLUSION Both extrathecal and intrathecal Glissonean pedicle approaches are effective and safe hepatic inflow occlusion techniques in laparoscopic left hemihepatectomy for HCC.However,the extrathecal approach simplifies the hepatic pedicle transection,shortens the operation time,and increases the surgical efficiency,making it a more feasible technique.

Establishment of NaLuF_(4):15%Tb-based low dose X-PDT agent and its application on efficient antitumor therapy

X-ray excited photodynamic therapy(X-PDT)is the bravo answer of photodynamic therapy(PDT)for deep-seated tumors,as it employs X-ray as the irradiation source to overcome the limitation of light penetration depth.However,high X-ray irradiation dose caused organ lesions and side effects became the major barrier to X-PDT application.To address this issue,this work employed a classic-al co-precipitation reaction to synthesize NaLuF_(4):15%Tb^(3+)(NLF)with an average particle size of(23.48±0.91)nm,which was then coupled with the photosensitizer merocyanine 540(MC540)to form the X-PDT system NLF-MC540 with high production of singlet oxygen.The system could induce antitumor efficacy to about 24%in relative low dose X-ray irradiation range(0.1-0.3 Gy).In vivo,when NLF-MC540 irradiated by 0.1 Gy X-ray,the tumor inhibition percentage reached 89.5%±5.7%.The therapeutic mechanism of low dose X-PDT was found.A significant increase of neutrophils in serum was found on the third day after X-PDT.By immunohistochemical staining of tumor sections,the Ly6G^(+),CD8^(+),and CD11c^(+)cells infiltrated in the tumor microenvironment were studied.Utilizing the bilat-eral tumor model,the NLF-MC540 with 0.1 Gy X-ray irradiation could inhibit both the primary tumor and the distant tumor growth.De-tected by enzyme linked immunosorbent assay(ELISA),two cytokines IFN-γand TNF-αin serum were upregulated 7 and 6 times than negative control,respectively.Detected by enzyme linked immune spot assay(ELISPOT),the number of immune cells attributable to the IFN-γand TNF-αlevels in the group of low dose X-PDT were 14 and 6 times greater than that in the negative control group,respectively.Thus,it conclude that low dose X-PDT system could successfully upregulate the levels of immune cells,stimulate the secretion of cy-tokines(especially IFN-γand TNF-α),activate antitumor immunity,and finally inhibit colon tumor growth.

Increasing realism in modelling energy losses in railway vehicles and their impact to energy-efficient train control

The reduction of energy consumption is an increasingly important topic of the railway system.Energy-efficient train control(EETC)is one solution,which refers to mathematically computing when to accelerate,which cruising speed to hold,how long one should coast over a suitable space,and when to brake.Most approaches in literature and industry greatly simplify a lot of nonlinear effects,such that they ignore mostly the losses due to energy conversion in traction components and auxiliaries.To fill this research gap,a series of increasingly detailed nonlinear losses is described and modelled.We categorize an increasing detail in this representation as four levels.We study the impact of those levels of detail on the energy optimal speed trajectory.To do this,a standard approach based on dynamic programming is used,given constraints on total travel time.This evaluation of multiple test cases highlights the influence of the dynamic losses and the power consumption of auxiliary components on railway trajectories,also compared to multiple benchmarks.The results show how the losses can make up 50%of the total energy consumption for an exemplary trip.Ignoring them would though result in consistent but limited errors in the optimal trajectory.Overall,more complex trajectories can result in less energy consumption when including the complexity of nonlinear losses than when a simpler model is considered.Those effects are stronger when the trajectory includes many acceleration and braking phases.

Holistic Approach to Safety and Operational Stability: Analyzing VVER-1200 Reactor Dynamics in SGTR and AC Power Loss

VVER-1200 (Water-Water Energetic Reactor) represents a significant advancement in nuclear power generation, emphasizing the continuous analysis and enhancement of safety systems for reliable operation. The proposed study focuses on simulating combined scenarios involving steam generator tube rupture (SGTR) and AC power loss using core algorithms and models within personal computer transient analyzer (PCTRAN). Reactor kinetic equations, thermal-hydraulic balance, and safety system models are discussed to elucidate their role in simulating SGTR and AC power loss. Safety criteria, boundaries and initial conditions are outlined to provide a comprehensive understanding of the simulation framework. The analysis delves into dynamic behavior of VVER-1200, placing emphasis on thermal-hydraulic implications, essential reactor parameters, and radiation monitoring to facilitate impact evaluation. Continuous monitoring and maintenance of safety systems are underscored to ensure stable core cooling, particularly during proposed transient conditions. Through meticulous analysis and comparison with established benchmarks, this study contributes to bolstering the safety and reliability of VVER-1200 reactors by identifying vulnerabilities, assessing mitigation strategies, and refining emergency response protocols. Practical implications of this study offer a crucial understanding of reactor behavior, safety system performance, and emergency response strategies, thereby improving safety, optimizing operational practices, and reducing risks in nuclear reactor accidents.

An Efficient and Lightweight YOLOv8s Strawberry Maturity Detection Model

The manual picking of strawberries is inefficient and costly,limiting scalability and economic benefits.Mechanizing this process reduces labor demands,improves working conditions,and modernizes the strawberry industry.Target detection technology,crucial for mechanized picking,must accurately determine strawberry maturity.This study presents an enhanced YOLOv8s model addressing current machine learning issues like accuracy,parameters,and complexity.The improved model replaces the Bottleneck structure in C2f with the FasterNet network,integrates an efficient multi-scale attention mechanism,and uses the Ghost module in the backbone to reduce computational load while maintaining performance.It also introduces Wise-IoU for bounding box regression loss,improving recognition accuracy.The YOLOv8s-FEGW model achieves a 93.8%mAP in detecting strawberry ripeness,with significant reductions in parameters(36.8%),complexity(34.6%),and model size(37.7%),alongside a 12.7% Frames Per Second(FPS)boost.These enhancements result in excellent detection capabilities,supporting agricultural automation and intelligence.

Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems

The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation services.With the expansion of the railway networks,enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation.In light of the prevailing application of artificial intelligence technologies within railway systems,this study leverages large model technology characterized by robust learning capabilities,efficient associative abilities,and linkage analysis to propose an Artificial-intelligent(AI)-powered railway control and dispatching system.This system is elaborately designed with four core functions,including global optimum unattended dispatching,synergetic transportation in multiple modes,high-speed automatic control,and precise maintenance decision and execution.The deployment pathway and essential tasks of the system are further delineated,alongside the challenges and obstacles encountered.The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system,ensuring a more effective alignment between transportation services and passenger demands.

Application and Effect Evaluation of the Integrated“5A and 3+3”Management Model in the Safe Medication Use for Chemotherapy Patients

Objective:To explore the application and effect evaluation of the integrated“5A and 3+3”management model in ensuring safe medication use for chemotherapy patients.Methods:A total of 100 intravenous chemotherapy patients admitted to the oncology department of Shaanxi Provincial People’s Hospital were randomly divided into two groups using a random number list method.Both groups received conventional nursing management during chemotherapy,while the study group additionally received the integrated“5A and 3+3”safety management model.The nursing intervention effects between the two groups were compared.Results:After the intervention,the study group showed higher levels of self-management ability,compliance,and nursing satisfaction compared to the control group.The overall incidence of adverse events during hospitalization was lower in the study group,with statistically significant differences(P<0.05).The knowledge scores of medical staff in the study group,related to the prevention and treatment of chemotherapy drug side effects,daily symptom management,and daily life management,were higher than those in the control group,with statistically significant differences(P<0.05).Conclusion:Implementing the integrated“5A and 3+3”model in the safe medication management of intravenous chemotherapy patients can effectively enhance patients’self-management abilities and compliance,improve medical staff’s ability to safely administer chemotherapy drugs,reduce adverse events caused by chemotherapy,and increase patient satisfaction.

Trimming the Degrees of Freedom via a K^(+) Flux Rectifier for Safe and Long‑Life Potassium‑Ion Batteries

High degrees of freedom(DOF)for K^(+)movement in the electrolytes is desirable,because the resulting high ionic conductivity helps improve potassium-ion batteries,yet requiring support from highly free and flammable organic solvent molecules,seriously affecting battery safety.Here,we develop a K^(+)flux rectifier to trim K ion’s DOF to 1 and improve electrochemical properties.Although the ionic conductivity is compromised in the K^(+)flux rectifier,the overall electrochemical performance of PIBs was improved.An oxidation stability improvement from 4.0 to 5.9 V was realized,and the formation of dendrites and the dissolution of organic cathodes were inhibited.Consequently,the K||K cells continuously cycled over 3,700 h;K||Cu cells operated stably over 800 cycles with the Coulombic efficiency exceeding 99%;and K||graphite cells exhibited high-capacity retention over 74.7%after 1,500 cycles.Moreover,the 3,4,9,10-perylenetetracarboxylic diimide organic cathodes operated for more than 2,100 cycles and reached year-scale-cycling time.We fabricated a 2.18 Ah pouch cell with no significant capacity fading observed after 100 cycles.

Surface Passivation Toward Efficient and Stable Perovskite Solar Cells

Although metal halide perovskites are increasingly popular for the next generation of efficient photovoltaic devices,the inevitable defects from the preparation process have become the notorious barrier to further improvement of performance,which increases non-radiative recombination and lowers the power conversion efficiency of solar cells.Surface passivation strategies have been affirmed as one of the most practical approaches to suppress these defects.Therefore,it is necessary to have a detailed review on the surface passivation to reveal the improvements of the devices.Herein,the mechanism and recent advances of surface passivation have been systematically summarized with respect to various passivation approaches,including the Lewis acid–base,the low-dimensional perovskite,inorganic molecules,and polymers.Finally,the review also offers the research trend and prospects of surface passivation.

Determining safe yield and mapping water level zoning in groundwater resources of the Neishabour Plain

Groundwater is a crucial sources of water supply,especially in arid and semi-arid areas around the world.With uncontrolled withdrawals and limited availability of these resources,it is essential to determine the safe yield of these valuable resources.The Hill method approach was used in this study to determine the safe yield the Neishabour aquifer in Khorasan Razvi province in Iran.The results showed that the safe yield in the Neishabour aquifer is 60%lower than the current pumping amounts during the study period,indicating that further overdrafts could result in the destruction of this aquifer.This highlights the importance of using the Hill method to estimate the permitted exploitation from other aquifers,thus preventing problems caused by over-extraction and maintaining stability of global groundwater levels.

Gene expression pattern of K transporter GhHAK5 gene of potassium efficient and in-efficient cotton cultivars based on morphological physiognomies as affected by potassium nutrition and reduced irrigation

Background Under K deficiency the uptake and distribution pattern in plant cells is mediated through different transport proteins and channels which were controlled by specific gene family.Therefore,a hydroponic experiment was conducted under control condition for testing the gene expression pattern of the K transporter under adequate and low K supply levels.After that,a 2-year field experiment was conducted to evaluate five selected cotton cultivars(four K-efficient cultivars,viz.,CIM-554,CYTO-124,FH-142,IUB-2013,and one K non-efficient,BH-212) screened from the initial hydroponics culture experiment and two levels of potassium(0 K_(2)O kg·ha^(-1) and 50 K_(2)O kg·ha^(-1)) were tested under reduced irrigation(50% available water content;50 AWC) and normal irrigation conditions(100% available water content;100 AWC).Result Results revealed that the transcript levels of GhHAK5aD in roots were significantly higher in K^(+) efficient cultivars than that in K^(+) non-efficient cultivars.The GhHAK5aD expression upon K^(+) deficiency was higher in roots but lower in shoots,indicating that GhHAK5aD could have a role in K^(+) uptake in roots,instead of transport of K^(+) from root to shoot.Similarly,under field conditions the cultivar FH-142 showed an increase of 22.3%,4.9%,2.4%,and 1.4% as compared with BH-212,IUB-2013,CYTO-124,and CIM-554,respectively,in seed cotton yield(SCY) with K application under reduced irrigation conditions.With applied K,the FH-142 showed an increase in net photosynthetic rate by 57.3% as compared with the rest of the cultivars under reduced irrigation over K control.However,the overall performance indicators of K-efficient cultivars like FH-142,CYTO-124,CIM-554,and IUB-2013 were better than BH-212(K in-efficient) under reduced irrigation conditions with applied K at 50 kg·ha^(-1).Fiber quality trait improved significantly with K application under water deficit.The increase in micronaire was 3.6%,4.7%,7.8%,3.4%,and 6.7% in BH-212,IUB-2013,CIM-554,CYTO-124,and FH-142,respectively,with K application at 50 kg·ha^(-1) over without K application under reduced irrigation conditions during the cotton growing season.Similarly,the cultivars FH-142 increased by 12% with K application under reduced irrigation as compared with other cultivars.The performance of K-efficient cultivars under reduced irrigation conditions was 30% better in SCY and quality traits with the application of K at 50 kg·ha^(-1) as compared with K-non-efficient cultivars.Similarly,water use efficiency(WUE)(40.1%) and potassium use efficiency(KUE)(20.2%) were also noted higher in case of FH-142 as compared with other cultivar with K application under reduced conditions.Conclusion Higher expression of GhHAK5aD gene was observed in K-efficient cultivars as compared with K-nonefficient cultivars in roots indicates that GhHAK5aD may be contributing to genotypic differences for K^(+) efficiency in cotton.K-efficient cotton cultivars can be used for the low-K environments and can also be recommended for general cultivars.

Highly Selective Electrocatalytic CuEDTA Reduction by MoS_(2) Nanosheets for Efficient Pollutant Removal and Simultaneous Electric Power Output

Electrocatalytic reduction of ethylenediamine tetraacetic acid copper(CuEDTA),a typical refractory heavy metal complexation pollutant,is an environmental benign method that operates at mild condition.Unfortunately,the selective reduction of CuEDTA is still a big challenge in cathodic process.In this work,we report a MoS_(2) nanosheet/graphite felt(GF)cathode,which achieves an average Faraday efficiency of 29.6%and specific removal rate(SRR)of 0.042 mol/cm^(2)/h for CuEDTA at−0.65 V vs SCE(saturated calomel electrode),both of which are much higher than those of the commonly reported electrooxidation technology-based removal systems.Moreover,a proofof-concept CuEDTA/Zn battery with Zn anode and MoS_(2)/GF cathode is demonstrated,which has bifunctions of simultaneous CuEDTA removal and energy output.This is one of the pioneer studies on the electrocatalytic reduction of heavy metal complex and CuEDTA/Zn battery,which brings new insights in developing efficient electrocatalytic reduction system for pollution control and energy output.