Profitable Retail Customer Identification Based on a Combined Prediction Strategy of Customer Lifetime Value

As a fundamental concept of customer relationship management, customer lifetime value (CLV) serves as a crucial metric to identify profitable retail customers. Various methods are available to predict CLV in different contexts. With the development of consumer big data, modern statistics and machine learning algorithms have been gradually adopted in CLV modeling. We introduce two machine learning algorithms—the gradient boosting decision tree (GBDT) and the random forest (RF)—in retail customer CLV modeling and compare their predictive performance with two classical models—the Pareto/NBD (HB) and the Pareto/GGG. To ensure CLV prediction and customer identification robustness, we combined the predictions of the four models to determine which customers are the most—or least—profitable. Using 43 weeks of customer transaction data from a large retailer in China, we predicted customer value in the future 20 weeks. The results show that the predictive performance of GBDT and RF is generally better than that of the Pareto/NBD (HB) and Pareto/GGG models. Because the predictions are not entirely consistent, we combine them to identify profitable and unprofitable customers

Structure-based self-supervised learning enables ultrafast prediction of stability changes upon mutation

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Measuring Customer Equity in Noncontractual Settings Using a Diffusion Model: An Empirical Study of Mobile Payments Aggregator

Customers are important intangible assets of firms. Customer equity (CE) and customer equity sustainability ratio (CESR) cannot only provide a crucial basis for measuring the growth potential of firms but also provide managers a reference standard to allocate the marketing resource. This empirical study discussed the CE measurement of a mobile payments aggregator. With the rapid development of mobile payment in China, it is very meaningful to calculate the CE of these aggregators as an emerging business pattern because calculating CE cannot only help the mobile payments aggregator evaluate its future business development but also help it to provide value-added services and generate service fee from its clients, i.e., the retailers. The main purpose of this paper is to calculate CE of a mobile payments aggregator generated from a specific retailer from the perspective of technology diffusion. Based on the Bass model and Rogers’ theory of innovation diffusion, we calculated CE and CESR for five segments, namely innovators, early adopters, early majorities, late majorities, and laggards. The results show that it is the early adopters and the early majorities who generate most of the profit and it is also these two segments that have the greatest growth potential in the future

Measuring Customer Equity in Noncontractual Settings Using a Diffusion Model: An Empirical Study of Mobile Payments

Customers are important intangible assets of firms. Customer equity (CE) and customer equity sustainability ratio (CESR) cannot only provide a crucial basis for measuring the growth potential of firms but also provide managers a reference standard to allocate the marketing resource. This empirical study discussed the CE measurement of a mobile payments aggregator. With the rapid development of mobile payment in China, it is very meaningful to calculate the CE of these aggregators as an emerging business pattern because calculating CE cannot only help the mobile payments aggregator evaluate its future business development but also help it to provide value-added services and generate service fee from its clients, i.e., the retailers. The main purpose of this paper is to calculate CE of a mobile payments aggregator generated from a specific retailer from the perspective of technology diffusion. Based on the Bass model and Rogers’ theory of innovation diffusion, we calculated CE and CESR for five segments, namely innovators, early adopters, early majorities, late majorities, and laggards. The results show that it is the early adopters and the early majorities who generate most of the profit and it is also these two segments that have the greatest growth potential in the future

Profitable Retail Customer Identification Based on a Combined Prediction Strategy of Customer Lifetime Value

As a fundamental concept of customer relationship management (CRM), customer lifetime value (CLV) serves as a crucial metric to identify profitable retail customers. Various methods are available to predict CLV in different contexts. With the development of consumer "big data," modern statistics and machine learning algorithms have been gradually adopted in CLV modeling. We introduce two machine learning algorithms – the gradient boosting decision tree (GBDT) and the random forest (RF) – in retail customer CLV modeling and compare their predictive performance with two classical models – the Pareto/NBD (HB) and the Pareto/GGG. To ensure CLV prediction and customer identification's robustness, we combined the predictions of the four aforementioned models to determine which customers are the most – or least – profitable. Using 43 weeks of customer transaction data from a large retailer in China, we predict customer value in the future 20 weeks. The results show that GBDT and RF's predictive performance is generally better than that of the Pareto/NBD (HB) and Pareto/GGG models. Since the predictions are not entirely consistent, we combine them to identify the profitable and unprofitable customer

Characterization of two Winter wheat varieties' responses to freezing in a frigid region of China

Cold stress is one of the main abiotic stresses faced by winter wheat, which results in significant yield loss, especially in the harsh winter of the Heilongjiang province. Glycine betaine (GB), an important osmolyte in higher plants, helps in stabilization of the plasma membrane and its protection from cold stress. In the present study, two winter wheat varieties, Dongnongdongmai1 (DM1) and Jimai22 (J22), which differ in their cold-resistance were planted under natural conditions and used for analyzing the relative electrical conductivity, malondialdehyde (MDA) content, betaine aldehyde dehydrogenase (BADH) activity, expression of BADH, and the content of GB. The cold-resistant variety, DM1, showed a greater increase in BADH activity and GB content and decreased MDA content than J22 under freezing conditions. GB was observed to have an obvious role in inhibiting the MDA content. This was reflected by the expression of BADH and enhanced tolerance to cold stress upon GB accumulation, which helped in membrane stabilization. The results of the present study confirmed the role of GB in conferring cold-resistance in the DM1 winter cultivar and could benefit other studies aimed at improving the tolerance of other wheat cultivars as well as other crops.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Overexpression of TaBADH increases the salt tolerance in Arabidopsis

Soil salinization is an important threat to wheat growth and production. Previous transcriptome analysis showed that the expression of the betaine aldehyde dehydrogenase (BADH) gene differed significantly between the cultivars with strong and weak salinity tolerance. Herein, the BADH gene from the wheat cultivar Dongnongdongmai 1 was cloned and transformed into the wild-type Arabidopsis to identify its function in salt tolerance. The root length was detected respectively at 0 mM, 50 mM, 100 mM, 150 mM and 20mM Nacl for 7d. The relative electrolytic leakage (REL), GB content and BADH activity were measured at 150 mM Nacl for1d and 3 d . The result, the BADH activity and GB content of TaBADH -overexpressed transgenic (TaBADHOE) lines were significantly higher than the wild type. Salt stress analysis showed that the root length of TaBADHOE lines 4, line 18, and line 19 were 0.44cm, 0.54cm and 0.35cm, respectively, which were significantly longer than 0.24cm of wild type in the media containing 150 mM NaCl for 7d. In addition, the REL of transgenic line 4, line 18 and line 19 respectively were 0.37, 0.33, 0.42, respectively, which significantly lower than 0.63 of wild type in media containing 150 mM NaCl for 3d. These results demonstrate that TaBADH significantly increased plant salt tolerance, indicating genetic transformation of TaBADH may be an effective and sustainable breeding method for increasing salt tolerance in wheat cultivars.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Transcriptome Profiling of Maize (Zea mays L.) Leaves Reveals Key Cold-Responsive Genes, Transcription Factors, and Metabolic Pathways Regulating Cold Stress Tolerance at the Seedling Stage

Cold tolerance is a complex trait that requires a critical perspective to understand its underpinning mechanism. To unravel the molecular framework underlying maize (Zea mays L.) cold stress tolerance, we conducted a comparative transcriptome profiling of 24 cold-tolerant and 22 cold-sensitive inbred lines affected by cold stress at the seedling stage. Using the RNA-seq method, we identified 2237 differentially expressed genes (DEGs), namely 1656 and 581 annotated and unannotated DEGs, respectively. Further analysis of the 1656 annotated DEGs mined out two critical sets of cold-responsive DEGs, namely 779 and 877 DEGs, which were significantly enhanced in the tolerant and sensitive lines, respectively. Functional analysis of the 1656 DEGs highlighted the enrichment of signaling, carotenoid, lipid metabolism, transcription factors (TFs), peroxisome, and amino acid metabolism. A total of 147 TFs belonging to 32 families, including MYB, ERF, NAC, WRKY, bHLH, MIKC MADS, and C2H2, were strongly altered by cold stress. Moreover, the tolerant lines’ 779 enhanced DEGs were predominantly associated with carotenoid, ABC transporter, glutathione, lipid metabolism, and amino acid metabolism. In comparison, the cold-sensitive lines’ 877 enhanced DEGs were significantly enriched for MAPK signaling, peroxisome, ribosome, and carbon metabolism pathways. The biggest proportion of the unannotated DEGs was implicated in the roles of long non-coding RNAs (lncRNAs). Taken together, this study provides valuable insights that offer a deeper understanding of the molecular mechanisms underlying maize response to cold stress at the seedling stage, thus opening up possibilities for a breeding program of maize tolerance to cold stress

Resveratrol Reestablishes Mitochondrial Quality Control in Myocardial Ischemia/Reperfusion Injury through Sirt1/Sirt3-Mfn2-Parkin-PGC-1α Pathway

Resveratrol is a natural polyphenol found in various plants. It has been widely studied on cardiovascular disorders. It is known that resveratrol can activate Sirtuin proteins and participate in cellular energy metabolism through a Sirtuin-dependent pathway. Here, we hypothesized that resveratrol may protect against myocardial ischemia/reperfusion injury (MIRI) through the target of Sirt1/Sirt3 on mitochondrial dynamics, cardiac autophagy, bioenergetics and oxidative damage in hypoxia/reoxygenation (H/R)-induced neonatal rat cardiomyocytes. We observed that resveratrol could activate the Sirt1/Sirt3-FoxO pathway on myocardial mitochondria in H/R cardiomyocytes. Subsequently, we found that resveratrol repaired the fission–fusion balance, autophagic flux and mitochondrial biosynthesis compared by H/R group. These changes were followed by increased functional mitochondrial number, mitochondrial bioenergetics and a better mitochondrial antioxidant enzyme system. Meanwhile, these effects were antagonized by co-treatment with Selisistat (Ex527), a Sirtuin inhibitor. Together, our findings uncover the potential contribution of resveratrol in reestablishing a mitochondrial quality control network with Parkin, Mfn2 and PGC-1α as the key nodes

Computational redesign of a hydrolase for nearly complete PET depolymerization at industrially relevant high-solids loading

Abstract Biotechnological plastic recycling has emerged as a suitable option for addressing the pollution crisis. A major breakthrough in the biodegradation of poly(ethylene terephthalate) (PET) is achieved by using a LCC variant, which permits 90% conversion at an industrial level. Despite the achievements, its applications have been hampered by the remaining 10% of nonbiodegradable PET. Herein, we address current challenges by employing a computational strategy to engineer a hydrolase from the bacterium HR29. The redesigned variant, TurboPETase, outperforms other well-known PET hydrolases. Nearly complete depolymerization is accomplished in 8 h at a solids loading of 200 g kg−1. Kinetic and structural analysis suggest that the improved performance may be attributed to a more flexible PET-binding groove that facilitates the targeting of more specific attack sites. Collectively, our results constitute a significant advance in understanding and engineering of industrially applicable polyester hydrolases, and provide guidance for further efforts on other polymer types