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A Study on Purchasing Behavior Analysis Method by Comparing Difference in Latent Class Distributions between Membership Stages

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Journal of Japan Industrial management Association 2022年第2期73卷 54-69页

作者： Yang, Tianxiang Yamashita, Haruka Goto, Masayuki Major of Industrial and Management Systems Engineering Graduate School of Creative Science and Engineering Waseda University Japan Department of Information and Communication Sciences Faculty of Science and Technology Sophia University Japan Department of Industrial and Management Systems Engineering School of Creative Science and Engineering Waseda University Japan

A marketing policy called the"Membership Stage System" is widely used in retail business. A membership stage provides benefits to customers such as shopping points when a customer's annual cumulative purchase amount exceeds a certain threshold and the customer's stage is raised a level. As a result, the company is not only able to promote the customer's willingness to purchase, but it can also obtain the purchasing history data, thereby enabling high-quality customer analysis. The most fundamental analysis is to infer the difference of purchasing characteristics between member stages and to construct different clustering models for each member stage. However, when the clustering models are learned independently for each membership stage, it is not possible to compare the obtained clusters between membership stages. In this study, we propose a new analytical method and its learning algorithm to analyze differences in cluster distribution between membership stages. Through demonstrating the proposed model applied to an actual data set of purchasing history data on a membership stage system, the effectiveness of our proposal is clarified. © 2022 Japan Industrial management Association. All rights reserved.

关键词： Sales

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Ionically conductive materials for energy-efficient succinic acid recovery towards electrified circular bioeconomy

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Bioresource Technology 2025年 430卷 132549页

作者： Pan, Shu-Yuan Liao, Yu-Lun Lin, Yu-I Tseng, Po-Chih Department of Bioenvironmental Systems Engineering College of Bioresources and Agriculture National Taiwan University No. 1 Section 4 Roosevelt Road Taipei City10617 Taiwan Agricultural Net-Zero Carbon Technology and Management Innovation Research Center College of Bioresources and Agriculture National Taiwan University No. 1 Section 4 Roosevelt Road Taipei City10617 Taiwan

In biorefineries, separation units for extracting valuable products from biomass often constitute a substantial portion of operational costs. Electrifying these separation units, such as through the use of bipolar membrane electrodeionization (BMEDI), has emerged as a key strategy to advance the circular bioeconomy. In this study, an ionically conductive material (ICM) was synthesized via sulfonation reactions under mild conditions and subsequently applied in BMEDI for the energy-efficient recovery of succinic acid. The ICM effectively alleviates the concentration polarization-induced limiting region in BMEDI, resulting in exceptional performance. The ICM-BMEDI system achieved a recovery efficiency of ∼91 %, a current efficiency of ∼90 %, a productivity of ∼0.55 kg/m2/h, and an energy consumption of ∼2.53 kWh per kg of succinic acid. Economic analysis revealed a strong benefit-cost ratio of 4.49 over a 2-year operational period. These findings highlight the potential of integrating ICM-BMEDI in biorefineries to achieve both energy-efficient and cost-effective bioproduction. © 2025 Elsevier Ltd

关键词： Cost benefit analysis

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Assessing disruptive potential of retail central bank digital currency and influence of design considerations: An open innovation approach in Thailand

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Journal of Open Innovation: Technology, Market, and Complexity 2025年第1期11卷

作者： Wathahong, Thanwa Ratanabanchuen, Roongkiat Israsena Na Ayudhya, Praima Tientanopajai, Kitt Technology Management and Innopreneurship Program Graduate School Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Banking and Finance Chulalongkorn Business School Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Industrial Design Faculty of Architecture Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Computer Engineering Faculty of Engineering Khon Kaen University Mittraphap Road Khon Kaen 40002 Thailand

Monetary authorities globally have studied central bank digital currency (CBDC) for wholesale and retail applications since the 1990s. Besides countering private cryptocurrencies' influence, central banks have also explored other benefits of CBDC, such as improving their financial oversight, enhancing digital payment systems, and reducing transaction fees and friction. For several years, the Bank of Thailand has also invested in research and development of CBDC, including retail use cases. However, an optimized design for an official launch of a retail CBDC in Thailand has yet to be determined, resembling fragmented progress observed among other central banks. This research has leveraged disruptive innovation theory to provide a fresh perspective on retail CBDC as potentially disruptive financial innovations. Additionally, it has proposed an open innovation-based methodology to determine industry preferences concerning twelve design considerations for retail CBDC and their impact on nine indicators of disruptive innovation. Data has been collected and analyzed from 98 respondents outside the Bank of Thailand, all possessing relevant expertise or experience in electronic payments. Crosstab and logistic regression analyses have indicated that retail CBDC in Thailand could embark on a disruptive innovation trajectory by adhering to defined design choices. Significantly, entering a new detached market has been identified as the most promising entry point, accompanied by explicit recommendations on nine out of twelve design considerations. © 2025 The Authors

关键词： CBDC Central bank digital Currency Disruptive innovation Open Innovation Retail

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OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems

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Advanced Intelligent systems 2025年第3期7卷

作者： Chen, Po-Yuan Ko, Tai-Ming Institute of Bioinformatics and Systems Biology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei115 Taiwan Institute of Statistical Science Academia Sinica Taipei115 Taiwan Department of Biological Science and Technology College of Engineering Bioscience National Yang Ming Chiao Tung University Hsinchu300 Taiwan National Yang Ming Chiao Tung University Hsinchu300 Taiwan School of Pharmacy College of Pharmacy Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung807 Taiwan

Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) and antioxidants, plays a pivotal role in inflammatory responses associated with both chronic diseases and acute injuries. In this study, OXidative Stress PREDictor (OxSpred), a supervised learning model tailored to accurately annotate the oxidative stress state of innate immune cells at the single-cell level, is introduced. Compared to the traditional gene-set-variation-analysis-based enrichment method, OxSpred demonstrates superior accuracy with an area under the receiver operating characteristic curve of 0.89 and offers interpretable embeddings with significant biological relevance. Using the predicted ROS states, precise elucidation and interpretation of the roles of novel innate immune cell subtypes can be achieved. Overall, OxSpred enhances the utility of single-cell transcriptomic datasets by providing a robust in silico method for determining intracellular oxidative stress states, thereby enriching the understanding of innate immune cell functions during inflammation. © 2024 The Author(s). Advanced Intelligent systems published by Wiley-VCH GmbH.

关键词： Cells

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Very Short-Term Probabilistic Prediction Method for Wind Speed Based on ALASSO-Nonlinear Quantile Regression and Integrated Criterion

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CSEE Journal of Power and Energy systems 2023年第6期9卷 2121-2129页

作者： Yan Zhou Yonghui Sun Sen Wang Linquan Bai Dongchen Hou Rabea Jamil Mahfoud Peng Wang the College of Energy and Electrical Engineering Hohai UniversityNanjing 210098China Department of Systems Engineering and Engineering Management the University of North CarolinaCharlotte NC 28223USA

To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage and selection operator (ALASSO) and integrated criterion (IC) is proposed. The ALASSO method is studied for shrinkage of output weights and selection of variables. Furthermore, for the better performance of PIs, composite weighted linear programming (CWLP) is proposed to modify the conventional linear programming cost function of quantile regression (QR), by combining it with Bayesian information criterion (BIC) as an IC to optimize the coefficients of PIs. Then, the multiple fold cross model (MFCM) is utilized to improve the PIs performance. Multistep probabilistic prediction of 15-minute wind speed is performed based on the real wind farm data from the northeast of China. The effectiveness of the proposed approach is validated through the performances' comparisons with conventional methods.

关键词： Composite weighted linear programming least absolute shrinkage and selection operator integrated criterion wind speed

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How different spatial resolutions of digital models affects the geospatial distribution evaluation of the Index of Connectivity

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Journal of South American Earth Sciences 2025年 163卷

作者： Eberval Marchioro Geraldo André Rosseto Barreto Ialy Gomes Ferreira Adelsom Soares Filho Diogo Costa Buarque Department of Geography (DGEO) Graduate Program in Geography (PPGG) Federal University of Espírito Santo/Brazil (UFES) Coordinator of the Laboratory for Monitoring and Modeling Environmental Systems (Lamosa) Brazil Graduate Program in Management and Regulation of Water Resources (ProfÁgua/UFES) Brazil Graduate Program in Geography at UFES Brazil Graduate Program in Civil Engineering at UFV Brazil Department of Geography Graduate Program in Geography Federal University of Grande Dourados (UFGD) Brazil Department of Environmental Engineering Graduate Program in Environmental Engineering (PPGEA) Professional Master's in Water Resources Management and Regulation (ProfÁgua/UFES) Federal University of Espírito Santo/Brazil (UFES) Brazil

Digital Terrain Models (DTM) and Digital Elevation Models (DEM) are important for obtaining the Index of Connectivity, as they provide valuable information to assess the possibility of sediments reaching the riverbed in watershed basins. This is crucial for proactive management, as it allows the adoption of preventive and mitigating measures. Therefore, this study aims to analyze the effect of the spatial resolution of DEMs with resolutions of 5 m and 2 m, and between the DTM and DEM at 2 m, in determining the Index of Connectivity (IC). Additionally, it was investigated whether it is possible to use only one spatial resolution of digital models to assess the geospatial distribution of IC for all hydrogeomorphological landscapes of the Duas Bocas River watershed, located in the Metropolitan Region of Greater Vitória, in the state of Espírito Santo, Southeast Brazil. For this study, the Borselli Index of Connectivity model (et al., 2008) was used, originally developed for rural areas of Italy and widely applied in different regions worldwide. The data used, including Digital Elevation and Terrain Models and land use and cover information, were obtained from the Integrated Geospatial Base System of the State of Espírito Santo (Brazil), which is publicly *** results indicate that a better geospatial representation of IC occurs when changing the spatial resolution of DEMs from a 5 m pixel to a 2 m pixel and when using the 2 m DTM instead of the 2 m DEM. When analyzing the relationship between IC and the hydrogeomorphological landscapes in the basin, it was observed that, in the absence of models with an even finer pixel resolution, the 2 m DTM is the most suitable option, as it presented IC values consistent within and between landscapes in the Escalated Terraces of Southern Espírito Santo, Coastal Hills and Massifs, and Coastal Plateaus sectors. The exception was the fluvio-lagoon plain, which requires an even finer pixel resolution, necessitating further st

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A comprehensive study on butanolysis of furfuryl alcohol to butyl levulinate using tungstated zirconia and sulfonated carbon catalysts

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Carbon Resources Conversion 2021年第1期4卷 111-121页

作者： Upender Rao Thuppati C.Choi H.Machida K.Norinaga Department of Chemical Systems Engineering Graduate School of EngineeringNagoya UniversityAichi 464-8603Japan

This work presents the formation of butyl levulinate,a potential fuel additive,and an excellent renewable chemical obtained by the butanolysis of furfuryl alcohol(FAL)over a solid acid *** butanolysis of furfuryl alcohol reaction is a strong function of acidity for which tungstated zirconia(WO_(3)-ZrO_(2)),a robust solid acid catalyst,and a sulfonated carbon catalyst were employed to produce high yields of butyl levulinate targeting a lower initial molar ratio of butanol to FAL.A maximum of 28 mol%yield of butyl levulinate was obtained with tungstated zirconia *** prepared sulfonated carbon catalyst at high reaction temperatures facilitated the complete conversion of reaction intermediate,2-butoxymethylfuran(2-BMF)through which butyl levulinate was formed,and as high as 80 mol%of butyl levulinate yield was produced at an initial mole ratio of 8.5:1 of butanol to *** better results of sulfonated carbon catalyst could be attributed to the presence of-SO3H,carboxylic acid,and phenolic OH groups on the carbon surface.

关键词： Butanolysis Tungstated zirconia Sulfonated carbon And butyl levulinate

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Deep Learning-Enhanced Hand-Driven Microfluidic Chip for Multiplexed Nucleic Acid Detection Based on RPA/CRISPR

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Advanced Science 2025年第0期 e2414918页

作者： Xu, Tao Zhang, Ying Li, Shunji Dai, Chenxi Wei, Hongguo Chen, Dongjuan Zhao, Yunjun Liu, He Li, Deliang Chen, Peng Liu, Bi-Feng Tian, Ye College of Medicine and Biological Information Engineering Northeastern University Shenyang110169 China The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory Systems Biology Theme Department of Biomedical Engineering College of Life Science and Technology Huazhong University of Science and Technology Wuhan430074 China Department of Laboratory Medicine Maternal and Child Health Hospital of Hubei Province Tongji Medical College Huazhong University of Science and Technology Wuhan430070 China Foshan Graduate School of Innovation Northeastern University Foshan528300 China

The early detection of high-risk human papillomavirus (HR-HPV) is crucial for the assessment and improvement of prognosis in cervical cancer. However, existing PCR-based screening methods suffer from inadequate accessibility, which dampens the enthusiasm for screening among grassroots populations, especially in resource-limited areas, and contributes to the persistently high mortality rate of cervical cancer. Here, a portable system is proposed for multiplexed nucleic acid detection, termed R-CHIP, that integrates Recombinase polymerase amplification (RPA), CRISPR detection, Hand-driven microfluidics, and an artificial Intelligence Platform. The system can go from sample pre-processing to results readout in less than an hour with simple manual operation. Optimized for sensitivity of 10−17 M for HPV-16 and 10−18 M for HPV-18, R-CHIP has an accuracy of over 95% in 300 tests on clinical samples. In addition, a smartphone microimaging system combined with the ResNet-18 deep learning model is used to improve the readout efficiency and convenience of the detection system, with initial prediction accuracies of 96.0% and 98.0% for HPV-16 and HPV-18, respectively. R-CHIP, as a user-friendly and intelligent detection platform, has great potential for community-level HR-HPV screening in resource-constrained settings, and contributes to the prevention and early diagnosis of other diseases. © 2025 The Author(s). Advanced Science published by Wiley-VCH GmbH.

关键词： Risk assessment

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Chlorogenic acid simultaneously enhances the oxidative protection and anti-digestibility of porous starch

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International Journal of Biological Macromolecules 2025年 312卷 143949页

作者： Wu, Yongtai He, Dong Wu, Yi He, Ni Li, Lin Zhang, Xia Xing, Xinhui Li, Bing School of Food Science and Engineering Guangdong Provincial Key Laboratory of Green Processing of Natural Products and Product Safety Engineering Research Center of Starch and Plant Protein Deep Processing Ministry of Education South China University of Technology 381 Wushan Road Tianhe District Guangzhou510640 China School of Chemical Engineering and Light Industry Guangdong University of Technology No. 100 Waihuan Xi Road Panyu District Guangzhou510006 China School of Biological and Chemical Engineering Zhejiang University of Science and Technology Hangzhou310023 China School of Chemical Engineering and Energy Technology Dongguan University of Technology College Road 1 Dongguan523808 China Key Laboratory for Industrial Biocatalysis of the Ministry of Education Center for Synthetic and Systems Biology Institute of Biochemical Engineering Department of Chemical Engineering Tsinghua University Beijing247117 China Institute of Biopharmaceutical and Health Engineering Key Laboratory of Active Proteins and Peptides Green Biomanufacturing of Guangdong Higher Education Institutes Tsinghua Shenzhen International Graduate School Shenzhen518055 China

Porous starch (PS) has been utilized as an oral protective carrier to enhance the oxidative stability of liposoluble nutrients. However, PS releases more glucose during digestion, thereby increasing the risk of chronic diseases. Chlorogenic acid (CA) has excellent antioxidant properties and enhances the starch digestion resistance. To simultaneously enhance the oxidative protection and anti-digestibility, PS was blended with CA. Morphological analysis revealed that PSs with pores absorbed liposoluble substances. Surface area, total pore volume, and oxidative stability analyses demonstrated that rice starch (RS) enzymatically hydrolyzed for 12 h (PS12) loaded more substances and exerted a better protective effect in cooperation with CA. Simulated digestion confirmed that PS12-CA1 had the best anti-digestibility among PS12-CAs and a similar digestibility as RS. Additionally, CA treatment resulted in more anti-digestive V-type crystals in PSs, which resisted digestion. This study showed that the combination of PS and CA simultaneously enhanced oxidative protection and reduced the digestibility of PS. Thus, CA treatment makes PS a better oral nutrient delivery. © 2025

关键词： Chlorogenic acid Oxidative protection and anti-digestibility Porous starch

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Towards a Predictive Approach for Omni-channel Retailing Supply Chains

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IFAC-PapersOnLine 2019年第13期52卷 844-850页

作者： Pereira, Marina Meireles Frazzon, Enzo Morosini Graduate Program in Production Engineering Industrial and Systems Engineering Department Technology Center Federal University of Santa Catarina Florianópolis Santa Catarina Brazil

The adoption of omni-channel strategy has changed the relation between retailers and customers and brought more complexity to the retailing supply chains. To address the increasing complexity, it is necessary to adopt innovative approaches based on information technologies and intelligent decision methods. The challenges to retailers are improving the accuracy of offline and online channels demand forecasting, better managing offline and online customer's needs, thus reducing the uncertainties of the omni-channel retailing supply chain. In this context, this research paper aims to propose a predictive approach for omni-channel retailing supply chain combining clustering with artificial neural network to handle demand uncertainty. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Neural networks Complex networks Learning systems Sales Supply chain management Channel strategies Clustering Demand forecasting Demand uncertainty Innovative approaches Intelligent decisions Omni channel Retail supply chain

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