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Identification of the Diffusion Coefficients of Pollutants ( N O 3 - and Mn2+) through the Walls of Concrete Tank and Vulnerability of the Stored Water Quality

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Engineering（科研） 2024年第9期16卷 246-274页

作者： Narcisse Malanda Bienvenu Ebata Ndion Christian Tathy Thibault Mongo Paul Louzolokimbembe nation school superior polytechnic Marien Ngouabi University Brazzaville Republic of Congo superior Institute Architecture Town Planning Building and Public Works University of Dnis Sassou Nguesso Kintl Republic of Congo

The populations of urban centers in Congo-Brazzaville have decided to develop various methods of water storage (concrete or masonry underground tanks) for domestic use, due to shortages in the distribution of water through the public network. However, questions remain as to the physico-chemical quality of the water stored in these tanks, when these structures are built in wet and relatively polluted areas. This paper presents a model of pollutant diffusion through the cementitious matrix (concrete) of tank walls simulated at a buried reservoir. The results of the experimental and numerical simulations show that certain concrete parameters, such as porosity, permeability and diffusivity, have a significant influence on the transfer of pollutants through the concrete walls, thus altering the physico-chemical quality of the stored water. The numerical models (1D) used to predict pollutant transfer and the quality of the stored water are consistent with those of the optimal control for identifying the diffusion coefficient. Major ion concentrations appear to be correlated with system porosity and diffusion coefficient. Nevertheless, the identification of the diffusion coefficient from the optimal control method, based on an explicit numerical resolution of a finite volume PDE for the approximation of the experiment, is not consistent with that of the optimal control method.

关键词： Buried Tank Water Concrete Modelling Optimal Control Diffusion Coefficient

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Biocatalytic enhancement of laccase immobilized on ZnFe_(2)O_(4) nanoparticles and its application for degradation of textile dyes

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Chinese Journal of Chemical Engineering 2024年第4期68卷 216-223页

作者： Yuhang Wei Qingpeng Zhu Weiwei Xie Xinyue Wang Song Li Zhiming Chen school of Chemical and Environmental Engineering Anhui Laboratory of Functional Coordinated Complexes for Materials Chemistry and ApplicationAnhui Polytechnic UniversityWuhu 241000China school of Biology and Food Engineering Anhui Polytechnic UniversityWuhu 241000China

Efficient and convenient treatment of industrial dyeing wastewater is of great significance to guarantee human and animal *** work presented the enhanced catalytic activity at pH 3.0 of laccase immobilized on amino-functionalized ZnFe_(2)O_(4) nanoparticles(ZnFe_(2)O_(4)-laccase)and its application for the degradation of textile *** to the existence of a large number of oxygen vacancies on the surface of the ZnFe_(2)O_(4) nanoparticles,negative ions accumulated on the magnetic carriers,which resulted in a harsh optimal pH value of the ZnFe_(2)O_(4)-*** activity assays revealed that the ZnFe_(2)O_(4)-laccase possessed superior pH and thermal stabilities,excellent reusability,and noticeable organic solvent ***,the ZnFe_(2)O_(4) laccase presented efficient and sustainable degradation of high concentrations of textile *** initial decoloration efficiencies of malachite green(MG),brilliant green(BG),azophloxine,crystal violet(CV),reactive blue 19(RB19),and procion red MX-5B were approximately 99.1%,95.0%,93.3%,87.4%,86.1%,and 85.3%,*** 10 consecutive reuses,the degradation rates of the textile dyes still maintained about 98.2%,92.5%,83.2%,81.5%,79.8%and 65.9%,*** excellent dye degradation properties indicate that the ZnFe_(2)O_(4)-laccase has a technical application in high concentrations of dyestuff treatment.

关键词： ZnFe_(2)O_(4)-laccase Catalytic activity Stability and reusability Degradation of textile dye

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A Fault Detection Method for Electric Vehicle Battery System Based on Bayesian Optimization SVDD Considering a Few Faulty Samples

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Energy Engineering 2024年第9期121卷 2543-2568页

作者： Miao Li Fanyong Cheng Jiong Yang Maxwell Mensah Duodu Hao Tu school of Electronics and Electrical Engineering Anhui Polytechnic UniversityWuhu241000China

Accurate and reliable fault detection is essential for the safe operation of electric *** vector data description(SVDD)has been widely used in the field of fault ***,constructing the hypersphere boundary only describes the distribution of unlabeled samples,while the distribution of faulty samples cannot be effectively described and easilymisses detecting faulty data due to the imbalance of sample ***,selecting parameters is critical to the detection performance,and empirical parameterization is generally timeconsuming and laborious and may not result in finding the optimal ***,this paper proposes a semi-supervised data-driven method based on which the SVDD algorithm is improved and achieves excellent fault detection *** incorporating faulty samples into the underlying SVDD model,training deals better with the problem of missing detection of faulty samples caused by the imbalance in the distribution of abnormal samples,and the hypersphere boundary ismodified to classify the samplesmore *** Bayesian Optimization NSVDD(BO-NSVDD)model was constructed to quickly and accurately optimize hyperparameter *** the experiments,electric vehicle operation data with four common fault types are used to evaluate the performance with other five models,and the results show that the BO-NSVDD model presents superior detection performance for each type of fault data,especially in the imperceptible early and minor faults,which has seen very obvious ***,the strong robustness of the proposed method is verified by adding different intensities of noise in the dataset.

关键词： Fault detection vehicle battery system lithium batteries fault samples

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Room-temperature Self-healing and Recyclable PDMS Elastomers with superior Mechanical Properties for Triboelectric Nanogenerators

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Chinese Journal of Polymer Science 2024年第10期42卷 1566-1577页

作者： Shu-Juan Wang Lu Wang Hong-Zhe Su Zhi-Cheng Wu Qiao-Gen Zhang Wei Fan Xin-Li Jing school of Chemistry Joint Innovation Center of Thermal Protection Materials Xi'an Jiaotong University school of Electrical Engineering Xi'an Jiaotong University school of Textile Science and Engineering Xi'an Polytechnic University

Polydimethylsiloxane (PDMS) is an electron-withdrawing material that is widely used in triboelectric nanogenerators (TENGs). However, PDMS has poor mechanical properties after curing and is easily damaged when subjected to long-term workloads. Thus, the long-term stable operation of TENGs under mechanical deformation cannot be guaranteed. In this work, multiple hydrogen bonds and aromatic disulfide bonds were introduced into PDMS elastomers. These elastomers exhibited high toughness (a tensile strength of 1.91 MPa and an elongation at break of 340%), good recyclability, and room-temperature self-healing properties (healing efficiency of 96.4%in 24 h). Recyclable sandwich-like triboelectric nanogenerators with excellent electrical output performance (13.5 V) and room-temperature self-healing performance (24 h, 98% recovery of self-generating performance) were prepared by utilizing the hydrogen bonding between the PDMS elastomer and MXene. The work reported herein offers theoretical guidance and a compelling strategy for developing high-performance TENG negative friction layers.

关键词： Aromatic disulfide bonds Hydrogen bonds Polydimethylsiloxane Room temperature self-healing Triboelectric nanogenerator

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Weakly-supervised instance co-segmentation via tensor-based salient co-peak search

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Frontiers of Computer Science 2024年第2期18卷 83-92页

作者： Wuxiu QUAN Yu HU Tingting DAN Junyu LI Yue ZHANG Hongmin CAI school of Computer Science Guangdong Polytechnic Normal UniversityGuangzhou 510665China school of Computer Science and Engineering South China University of TechnologyGuangzhou 510006China

Instance co-segmentation aims to segment the co-occurrent instances among two *** task heavily relies on instance-related cues provided by co-peaks,which are generally estimated by exhaustively exploiting all paired candidates in point-to-point ***,such patterns could yield a high number of false-positive co-peaks,resulting in over-segmentation whenever there are mutual *** tackle with this issue,this paper proposes an instance co-segmentation method via tensor-based salient co-peak search(TSCPS-ICS).The proposed method explores high-order correlations via triple-to-triple matching among feature maps to find reliable co-peaks with the help of co-saliency *** proposed method is shown to capture more accurate intra-peaks and inter-peaks among feature maps,reducing the false-positive rate of co-peak *** having accurate co-peaks,one can efficiently infer responses of the targeted *** on four benchmark datasets validate the superior performance of the proposed method.

关键词： weakly-supervised co-segmentation co-peak tensormatching deep network instance segmentation

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RepDNet:A re-parameterization despeckling network for autonomous underwater side-scan sonar imaging with prior-knowledge customized convolution

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Defence Technology（防务技术） 2024年第5期35卷 259-274页

作者： Zhuoyi Li Zhisen Wang Deshan Chen Tsz Leung Yip Angelo P.Teixeira Department of Logistics and Maritime Studies The Hong Kong Polytechnic UniversityChina State Key Laboratory of Maritime Technology and Safety Wuhan University of TechnologyChina school of Transportation and Logistics Engineering Wuhan University of TechnologyChina national Engineering Research Center for Water Transport Safety Wuhan University of TechnologyChina Centre for Marine Technology and Ocean Engineering(CENTEC) Instituto Superior TecnicoUniversidade de LisboaPortugal

Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined ***,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise *** approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain *** address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is *** DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle *** training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing *** inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing *** DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit *** on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.

关键词： Side-scan sonar Sonar image despeckling Domain knowledge Re-parameterization

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Principle for the Installation of Accommodation for Sick guards in Public Health Establishments in Brazzaville in the Republic of Congo

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Journal of Environmental Science and Engineering(B) 2024年第2期13卷 70-79页

作者： Alain Symphorien Ndongo Destin Gemetone Etou Christian Tathy Laboratory of Energetic Mechanics and Engineering(LMEI) National Polytechnic SchoolMarien Ngouabi UniversityBP 69BrazzavilleCongo national superior polytechnic school(ENSP) University Marien NgouabiBP 69BrazzavilleCongo Higher Normal school(ENS) University Marien Ngouabi BP 69Brazzaville Congo

The results of scientific studies of human social facts in the field of health show that the management of a patient should involve the patient’s entourage,whatever the status or size of the health *** healthcare establishments in the Congo,the following are recognised as being responsible for medical care:specialist doctors,doctors,midwives,nurses and care *** patient’s family and close friends are responsible for looking after the patient and financing *** hospital infrastructure does not provide any space for the patient warden who accompany the patient during reception and *** makes Congolese hospitals inefficient for patient *** can we integrate the function of the Sick guard and the assistance of the family,in order to reduce the mortality rate and repair the harm caused to patients requiring the presence of relatives during their stay in hospital,which is considered to be a dangerous place?This article examines the functional principles for configuring the space that patient warden would occupy in the patient care *** the basis of a documentary analysis of sociological and architectural studies of existing facilities,this article proposes a typical accommodation model with the spaces needed to ensure the well-being and effectiveness of the patient warden with the *** are rooms with minimum space for 2 to 4 individual beds,equipped with toilets and *** accommodation has a dining area,kitchen and laundry *** the future,this accommodation will become part of the hospital estate and may be occupied by orderlies and patient warden recruited by the hospital administration.

关键词： Sick guard patient public health establishment accommodation Republic of Congo

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Development of MoS_(2)-stainless steel catalyst by 3D printing for efficient destruction of organics via peroxymonosulfate activation

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Journal of Environmental Sciences 2024年第1期135卷 108-117页

作者： Yufeng Liu Jianhui Xu Xin Fu Pengxu Wang Dan Li Yunfei Zhang Shenggui Chen Chunhui Zhang Peng Liu school of Environment and Civil Engineering Dongguan University of TechnologyDongguan 523808China school of Art and Design Guangzhou Panyu PolytechnicGuangzhou 511483China Dongguan Institute of Science and Technology Innovation Dongguan University of TechnologyDongguan 523808China school of Mechanical Engineering Dongguan University of TechnologyDongguan 523808China

Herein,a novel MoS_(2)-stainless steel composite material was first synthetized via a 3D printing method(3DP MoS_(2)-SS)for peroxymonosulfate(PMS)activation and organics *** with MoS_(2)-SS powder/PMS system(0.37 g/(m^(2)/min)),4.3-fold higher k_(FLO)/S_(BET)value was obtained in 3DP MoS_(2)-SS/PMS system(1.60 g/(m^(2)/min),resulting from the superior utilization of active *** observed that 3DP MoS_(2)-SS significantly outperformed the 3DP SS due to the enhanced electron transfer rate and increased active ***,Mo^(4+)facilitated the Fe^(2+)/Fe^(3+)cycle,resulting in the rapid degradation of florfenicol(FLO).Quenching experiments and electron paramagnetic resonance spectra indicated that·OH,SO_(4)·^(-),O_(2)·^(-)and^(1)O_(2)were involved in the degradation of *** effect of influencing factors on the degradation of FLO were evaluated,and the optimized degradation efficiency of 98.69%was achieved at 1 mM PMS and pH of *** degradation products were detected by UPLC/MS analyses and several possible degradation pathways were proposed to be the cleavage of C-N bonds,dechlorination,hydrolysis,defluorination and *** addition,3DP MoS_(2)-SS/PMS system also demonstrated superior degradation performance for 2-chlorophenol,acetaminophen,ibuprofen and *** study provided deep insights into the MoS_(2)-SS catalyst prepared by 3DP technology for PMS activation and FLO-polluted water treatment.

关键词： 3D printing Stainless steel MoS_(2) Peroxymonosulfate activation Degradation mechanism

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Deep Learning for Financial Time Series Prediction:A State-of-the-Art Review of Standalone and HybridModels

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 187-224页

作者： Weisi Chen Walayat Hussain Francesco Cauteruccio Xu Zhang school of Software Engineering Xiamen University of TechnologyXiamen361024China Peter Faber Business school Australian Catholic UniversityNorth Sydney2060Australia Department of Information Engineering Polytechnic University of MarcheAncona60121Italy

Financial time series prediction,whether for classification or regression,has been a heated research topic over the last *** traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction ***,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and *** review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other *** illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related *** the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only *** remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency *** principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and t

关键词： Financial time series prediction convolutional neural network long short-term memory deep learning attention mechanism finance

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Solid solution strategy modulated defects engineering of(Cr_(1-x)V_(x))_(2)AlC MAX phase toward superior electromagnetic wave absorption

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Rare Metals 2024年第7期43卷 3205-3219页

作者： Ji-Lin Gou Yu-Kai Chang Shu Liu Peng-Hui Li Ping-Hao Cui Qian-Ku Hu Li-Bo Wang Xin Zhang Jun-Kai Wang Qi-Xun Xia Ai-Guo Zhou school of Materials Science and Engineering Henan Polytechnic UniversityJiaozuo 454003China Key Laboratory for Microstructural Material Physics of Hebei Province School of ScienceYanshan UniversityQinhuangdao 066004China State Key Laboratory of Metastable Materials Science and Technology Yanshan UniversityQinhuangdao 066004China

Defects engineering is an effective strategy for manipulating electromagnetic parameters and enhancing electromagnetic wave(EMW)absorption ***,the relationship between them is not clear,especially in solid solution *** this work,a series of(Cr_(1-x)V_(x))_(2)AlC MAX phase solid solutions with layered structure were prepared via tuning the ratio of Cr and V to explore their EMW absorption *** experimental results indicated that the doping of V atoms at the M-site could effectively regulate its impedance matching and EMW absorption properties by introducing appropriate numbers of defects in the crystal,such as twin boundaries,dislocations and lattice *** them,if Cr:V=3:1,Cr_(1.5)V_(0.5)AlC,as radar absorption materials,could reach a strong reflection loss of-51.8 dB at the frequency of 12.8 GHz under an ultra-thin thickness of 1.3 *** reflection loss value could attain-10 dB in a wide frequency range of 2.7-18 GHz and thickness range of 1-5 *** addition,after high temperature and acid-alkali immersion treatment,this sample still had good EMW absorption capability,and the effective absorption bandwidth was enhanced from 2.3 to 2.6 GHz after concentrated acid immersion or 3.1 GHz after concentrated alkali *** work has great reference significance for the research and development of high-performance MAX-based EMW absorption materials in harsh environments.

关键词： MAX phases Solid solution Defects engineering Electromagnetic wave absorption Harsh environments

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