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Trustworthy semi-supervised anomaly detection for online‐tooffline logistics business in merchant identification

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 544-556页

作者： Yong Li Shuhang Wang Shijie Xu Jiao yin Business School China University of Political Science and LawBeijingChina JD Logistics BeijingChina Southeast University NanjingChina Institute for Sustainable Industries and Liveable Cities Victoria UniversityMelbourneVictoriaAustralia

The rise of online-to-offline(O2O)e-commerce business has brought tremendous opportunities to the logistics *** the online-to-offline logistics business,it is essential to detect anomaly merchants with fraudulent shipping behaviours,such as sending other merchants'packages for profit with their low *** can help reduce the financial losses of platforms and ensure a healthy *** anomaly detection studies have mainly focused on online fraud behaviour detection,such as fraudulent purchase and comment behaviours in ***,these methods are not suitable for anomaly merchant detection in logistics due to the more complex online and offline operation of package-sending behaviours and the interpretable requirements of offline deployment in ***,a semi-supervised multiview fusion-based Anomaly Detection framework in online-to-offline logistics is proposed,which consists of a basic version SemiDet and an attention-enhanced multi-view fusion *** SemiDet,pair-wise data augmentation is first conducted to promote model robustness and address the challenge of limited labelled anomaly ***,SemiDet calculates the anomaly scoring of each merchant with an auto-encoder *** the multi-relationships among logistics merchants,a multi-view attention fusion-based anomaly detection network is further designed to capture merchants'mutual influences and improve the anomaly merchant detection performance.A post-hoc perturbation-based interpretation model is designed to output the importance of different views and ensure the trustworthiness of end-to-end anomaly *** framework based on an eight-month real-world dataset collected from one of the largest logistics platforms in China is evaluated,involving 6128 merchants and 16 million historical order consignor records in *** results show that the proposed model outperforms other baselines in both AUC-ROC and AUC-PR metrics.

关键词： artificial intelligence techniques data fusion deep learning

Rapid chemical recycling of waste polyester plastics catalyzed by recyclable catalyst

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Green Chemical Engineering 2024年第2期5卷 257-265页

作者： Yu-Ji Luo Jia-yin Sun Zhi Li School of Physical Science and Technology ShanghaiTech UniversityShanghai201210China

Waste plastics are serious environmental threats due to their low degradability and low recycling *** and efficient waste plastics recycling technologies are urgently demanded for a sustainable ***,we report a rapid,closed-loop,and streamlined process to convert polyesters such as poly(ethylene terephthalate)(PET)back to its purified *** trifluoromethanesulfonic acid or metal triflates as the recyclable catalyst,polyesters such as PET can be completely depolymerized by simple carboxylic acids within 1 *** coupling this acidolysis with a subsequent hydrogenolysis process,the consumed carboxylic acid was recovered and the closed-loop of PET depolymerization could be *** catalysts and depolymerization agents are fully recycled while only PET and hydrogen are consumed.

关键词： Chemical recycling Waste polyester plastics Acidolysis Recyclable catalyst

Study on detecting main ingredients of silicone rubber based on terahertz spectrum

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HIGH VOLTAGE 2024年第3期9卷 518-527页

作者： Mei, Hongwei Li, Lanxin yin, Fanghui Wang, Liming Farzaneh, Masoud Tsinghua Univ Shenzhen Int Grad Sch SIGS Shenzhen Guangdong Peoples R China Kunming Power Exchange Ctr Kunming Yunnan Peoples R China Univ Quebec Chicoutimi Dept Appl Sci DSA Chicoutimi PQ Canada

The authors investigated the ingredient detection technique of silicone rubber based on the Terahertz spectrum. For this purpose, 18 diverse high-temperature vulcanised silicone rubber (HTVSR) formulations were customised, 8 of which are used as calibration set while the rest 10 as prediction set. Based on the Beer-Lambert Law, the partial-least-square (PLS) regression model and the least-squares support-vector machines (LS-SVM) regression model were used to yield the relationships between the absorption spectrums and the content percentages of polydimethylsiloxane (PDMS), alumina trihydrate (ATH), and silica in HTVSR. The results showed that for the formulations tested, the prediction accuracy of all three main ingredients by the PLS regression model could be improved by changing the spectrum range from 0.2-4 to 0.5-2 THz. If the data were pre-processed by the Savitzky-Golay smoothing method or multiplicative scatter correction method, the prediction accuracy of PDMS could be further enhanced. However, this would lead to a slight decrease in the prediction accuracy of ATH. For the LS-SVM regression model, the radial basis function (RBF) kernel and the linear kernel were studied. It was found that the prediction accuracy of both kernels was better than that of the PLS regression model. With the LS-SVM regression model using the RBF kernel, the correlated coefficients of PDMS and ATH in the prediction set could be up to 0.9915 and 0.9742, respectively.

关键词： COMPOSITE INSULATORS

Global output feedback regulation of time-varying nonlinear systems via the dual-gain method

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Science China(Information Sciences) 2024年第5期67卷 333-334页

作者： Xian-Long yin Zong-Yao SUN Changyun WEN Institute of Automation Qufu Normal University School of Electrical and Electronic Engineering Nanyang Technological University

Notably, owing to the limited information available, the problem of output feedback stabilization/regulation for nonlinear systems has been explored based on state *** addition, the sensors accounting for state measurement could fail to detect the system states accurately due to the limitations of manufacturing techniques and instruments.

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Neurotoxicity of tetramethylammonium ion on larval and juvenile zebrafish:Effects on neurobehaviors and multiple biomarkers

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Journal of Environmental Sciences 2024年第9期143卷 138-147页

作者： Ruixin Zhang Rui Wang Jiajun Chang GDaniel Sheng Daqiang yin Key Laboratory of Yangtze River Water Environment Ministry of EducationCollege of Environmental Science and EngineeringTongji UniversityShanghai 200092China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China

Tetramethylammonium hydroxide(TMAH)is an important compound that utilized and released by the rapidly expanding semiconductor industry,which could hardly be removed by the conventional wastewater treatment *** a cholinergic agonist,the tetramethylammonium ion(TMA^(+))has been reported to induce toxicity to muscular and respiratory systems of mammals and human,however the toxicity on aquatic biota remains poorly *** investigated the neurotoxic effects of TMA^(+)exposure on zebrafish,based on neurobehavior tests and a series of *** inhibitions on the swimming distance of zebrafish larvae were observed when the exposure level exceeded 50 mg/L,and significant alterations on swimming path angles(straight and deflective movements)occurred even at 10 mg/*** tested neurobehavioral endpoints of zebrafish larvae were significantly positively correlated with reactive oxygen species(ROS)and malondialdehyde(MDA),significantly negatively related with the activities of antioxidant enzymes,but not significantly correlated with the level of acetylcholinesterase(AChE).Such relationship indicates that the observed neurotoxic effects on swimming behavior of zebrafish larvae is mainly driven by oxidative stress,rather than the alterations of *** the highest exposure concentration(200 mg/L),TMA^(+)evoked more severe toxicity on zebrafish juveniles,showing significantly stronger elevation on the MDA activity,and greater inhibitions on the activities of antioxidant enzymes and ACh E,suggesting juveniles were more susceptible to TMA^(+)exposure than larval zebrafish.

关键词： Tetramethylammonium Zebrafish Oxidative stress Acetylcholinesterase Neurobehavior

Bifunctional interstitial phosphorous doping strategy boosts platinum-zinc alloy for efficient ammonia oxidation reaction and hydrogen evolution reaction

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Nano Research 2024年第3期17卷 1182-1189页

作者： Tianqi Yu Kexin Tan Jia Wu Yongjin Zou Shibin yin Guangxi Key Laboratory of Electrochemical Energy Materials School of Chemistry and Chemical EngineeringGuangxi UniversityNanning 530004China Guangxi Key Laboratory of Information Materials Guilin University of Electronic TechnologyGuilin 541004China

It is still a lack of bifunctional catalysts for ammonia oxidation reaction(AOR)and hydrogen evolution reaction(HER)due to their different reaction *** this work,P is doped into PtZn alloy by calcination with NaH_(2)PO_(2) as P source to induce the lattice tensile strain of Pt and the electronic interaction between P and Zn,which optimizes the AOR and HER activity *** sample with the optimal P content can drive the AOR peak current density of 293.6 mA·mgPt^(-1),which is almost 2.7 times of *** HER,the overpotential at^(-1)0 mA·cm^(-2) is only 23 mV with Tafel slope of 34.1 mV·dec^(-1).Furthermore,only 0.59 V is needed to obtain 50 mA·mgPt^(-1) for ammonia electrolysis under a two-electrode ***,this work shows an ingenious method to design bifunctional catalysts for ammonia electrolysis.

关键词： PtZn alloy phosphorous doping ammonia oxidation reaction hydrogen evolution reaction bifunctional catalyst

Preparation and performance improvement of a dual-component microcapsule self-healing system for silicone rubber insulating material

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High Voltage 2024年第2期9卷 453-465页

作者： Mingzhe Li Bin Cao Fanghui yin Hongwei Mei Liming Wang Engineering Laboratory of Power Equipment Reliability in Complicated Coastal Environments Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenChina

A key factor limiting the development of silicone rubber insulating materials is their short service life in harsh operating *** establishment of a self-healing system is desired to improve the long-term operational performance of silicone rubber and effectively extend its service *** this study,poly(urea-formaldehyde)microcapsules containing polydimethylsiloxane healing agents are prepared and a dual-component microcapsule self-healing system for silicone rubber material is established and *** addition,the key factors affecting the self-healing performance(such as microcapsule size,rupture rate,and microcapsule doping amount)are *** is found that when SYLGARDTM 184 is used as the healing agent and matrix,with a 4:6(A:B)doping ratio of dual-component microcapsules and 20 phr doping amount,the self-healing efficiency is approximately 51%.Furthermore,increasing the microcapsule rupture rate and the interface strength between the healing agent and the matrix can effectively improve the self-healing *** relationships between key factors and self-healing performance are theoretically *** on the relationships,the microcapsule self-healing system can be appropriately *** results of this paper can provide a reference for the development of long-life silicone rubber insulating materials.

关键词： service rubber performance

Planning method of droplet fusion scheduling based on mixedinteger programming

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Science China(Technological Sciences) 2024年第1期67卷 157-171页

作者： XIONG JiaCong CHEN JianKui WANG YiXin yin ZhouPing LI YiQun State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

The emergence of new display devices,such as organic light-emitting diodes,has brought about numerous advantages,including high material utilization,low cost,and high *** devices are manufactured using inkjet printing and possess the potential to become a key technology for display ***,a challenge in achieving this is the display effect that reveals uneven brightness and darkness,which can be avoided by controlling the volume of ink solution in a pixel to within 5%.Currently,the volume difference among the nozzles of commercial printheads does not meet the requirements for volume uniformity,thus challenging the printing ***,designing a suitable printing method that allows for the fusion of different volumes of ink droplets,ultimately reducing the error of the post fusion process,is *** this study,we propose a print display droplet fusion scheduling method comprising two main ***,we use a dichotomous trust domain algorithm to obtain a feasible range of printhead docking point spacings for different nozzle and pixel panel ***,we model the printing process as a droplet fusion scheduling model based on mixed integer programming,with the optimization objective of achieving intra pixel volume uniformity via ensuring the volume uniformity of ink droplets within all *** verified this method through numerical simulations and printing experiments using 394 pixels per inch(ppi)pixel panels and successfully reduced the volume uniformity error among pixels to within 5%.

关键词： printing display droplet fusion mixed-integer programming dichotomous trust domain

SWG: an architecture for sparse weight gradient computation

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Science China(Information Sciences) 2024年第2期67卷 302-321页

作者： Weiwei WU Fengbin TU Xiangyu LI Shaojun WEI Shouyi yin School of Integrated Circuits Tsinghua University Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology

On-device training for deep neural networks(DNN) has become a trend due to various user preferences and scenarios. The DNN training process consists of three phases, feedforward(FF), backpropagation(BP), and weight gradient(WG) update. WG takes about one-third of the computation in the whole training process. Current training accelerators usually ignore the special computation property of WG and process it in a way similar to FF/BP. Besides, the extensive data sparsity existing in WG, which brings opportunities to save computation, is not well explored. Nevertheless, exploiting the optimization opportunities would meet three underutilization problems, which are caused by(1) the mismatch between WG data dimensions and hardware parallelism,(2) the full sparsity, i.e., the sparsity of feature map(Fmap),error map(Emap), and gradient, and(3) the workload imbalance resulting from irregular sparsity. In this paper, we propose a specific architecture for sparse weight gradient(SWG) computation. The architecture is designed based on hierarchical unrolling and sparsity-aware(HUSA) dataflow to exploit the optimization opportunities of the special computation property and full data sparsity. In HUSA dataflow, the data dimensions are unrolled hierarchically on the hardware architecture. A valid-data trace(VDT) mechanism is embedded in the dataflow to avoid the underutilization caused by the two-sided input sparsity. The gradient is unrolled in PE to alleviate the underutilization induced by output sparsity while maintaining the data reuse opportunities. Besides, we design an intra-and inter-column balancer(IIBLC) to dynamically tackle the workload imbalance problem resulting from the irregular sparsity. Experimental results show that with HUSA dataflow exploiting the full sparsity, SWG achieves a speedup of 12.23× over state-of-the-art gradient computation architecture, Train Ware. SWG helps to improve the energy efficiency of the state-of-the-art training accelerator LNPU from

关键词： CNN training gradient computation sparsity architecture