Graph Contrastive Learning with Multi-Objective for Personalized Product Retrieval in Taobao Search

In e-commerce search, personalized retrieval is a crucial technique for improving user shopping experience. Recent works in this domain have achieved significant improvements by the representation learning paradigm, e.g., embedding-based retrieval (EBR) and collaborative filtering (CF). EBR methods do not sufficiently exploit the useful collaborative signal and are difficult to learn the representations of long-tail item well. Graph-based CF methods improve personalization by modeling collaborative signal within the user click graph. However, existing Graph-based methods ignore user's multiple behaviours, such as click/purchase and the relevance constraint between user behaviours and items.In this paper, we propose a Graph Contrastive Learning with Multi-Objective (GCL-MO) collaborative filtering model, which solves the problems of weak relevance and incomplete personalization in e-commerce search. Specifically, GCL-MO builds a homogeneous graph of items and then optimizes a multi-objective function of personalization and relevance. Moreover, we propose a modified contrastive loss for multi-objectives graph learning, which avoids the mutual suppression among positive samples and thus improves the generalization and robustness of long-tail item representations. These learned item embeddings are then used for personalized retrieval by constructing an efficient offline-to-online inverted table. GCL-MO outperforms the online collaborative filtering baseline in both offline/online experimental metrics and shows a significant improvement in the online A/B testing of Taobao search

Responses of greenhouse-gas emissions to land-use change from rice to jasmine production in subtropical China

We studied the impacts of an increasingly common change in land use from paddy field to jasmine fields on the emission of greenhouse gases (GHGs), which have supposed the transformation of more than 1200 ha only in the last decade in the surroundings of Fuzhou city in response to economic changes. The possible increases that this can suppose constitutes and environmental concern in China. We studied areas dedicated to rice crop that have been partially converted to jasmine cultivation with some parts still kept as rice fields. Emissions of CO2, CH4 and N2O varied significantly among the seasons. CO2 and CH4 cumulative emissions and the global-warming potential (GWP) of these emissions were significantly lower in the jasmine than the paddy field. N2O emission, N2O cumulative emission, however, were higher in the jasmine than the paddy field, despite in some concrete studied periods the differences were not statistically significant. The total decrease in GHG emissions from the conversion from rice to jasmine production was strongly influenced by the indirect effects of various changes in soil conditions. The expected changes due to the great differences in water and fertilization use and management and organic matter input to soil between these two crops were in great part due to modified soil traits. According to structural equation models, the strong direct effects of the change from rice to Jasmine crop reducing the emissions of CO2 and N2O were partially decreased by the indirect effects of crop type change decreasing soil pH and soil [Fe2+] for CO2 emissions and by decreasing soil salinity and soil [Fe3+] for N2O emissions. The negative effects of the crop conversion on CH4 emissions were mostly due to the globally negative indirect effects on soil conditions, by decreases in soil salinity, water content and [Fe2+]. Soil salinity, water content, pH, [Fe2+], [Fe3+] and [total Fe] were significantly lower in the jasmine than the paddy field, but temperature had the opposite pattern. CO2 emissions were generally correlated positively with salinity, temperature, and water content and negatively with [Fe3+] and [total Fe] in both fields. CH4 emissions were positively correlated with salinity, temperature, water content and pH in both fields. N2O emissions were positively correlated with temperature and were negatively correlated with water content, pH, [Fe2+], [Fe3+] and [total Fe] in both fields. CO2 was the most important GHG for the GWPs, and the total GWP was significantly lower for the jasmine than for the rice cropland field. The change in the land use in this area of paddy fields will decreased the global GHG emission, and the effect on the GWPs was mostly due to changes in soil properties

Multi-Objective Personalized Product Retrieval in Taobao Search

In large-scale e-commerce platforms like Taobao, it is a big challenge to retrieve products that satisfy users from billions of candidates. This has been a common concern of academia and industry. Recently, plenty of works in this domain have achieved significant improvements by enhancing embedding-based retrieval (EBR) methods, including the Multi-Grained Deep Semantic Product Retrieval (MGDSPR) model [16] in Taobao search engine. However, we find that MGDSPR still has problems of poor relevance and weak personalization compared to other retrieval methods in our online system, such as lexical matching and collaborative filtering. These problems promote us to further strengthen the capabilities of our EBR model in both relevance estimation and personalized retrieval. In this paper, we propose a novel Multi-Objective Personalized Product Retrieval (MOPPR) model with four hierarchical optimization objectives: relevance, exposure, click and purchase. We construct entire-space multi-positive samples to train MOPPR, rather than the single-positive samples for existing EBR models.We adopt a modified softmax loss for optimizing multiple objectives. Results of extensive offline and online experiments show that MOPPR outperforms the baseline MGDSPR on evaluation metrics of relevance estimation and personalized retrieval. MOPPR achieves 0.96% transaction and 1.29% GMV improvements in a 28-day online A/B test. Since the Double-11 shopping festival of 2021, MOPPR has been fully deployed in mobile Taobao search, replacing the previous MGDSPR. Finally, we discuss several advanced topics of our deeper explorations on multi-objective retrieval and ranking to contribute to the community.Comment: 9 pages, 4 figures, submitted to the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Minin

Mesoscopic study on the effect of CFRP layers on the mechanical properties of coal circular-columns

In order to study the effect of CFRP layers on the mechanical properties of coal cylinders. A discrete-continuous coupled meso-mechanical numerical model of CFRP passively confined coal cylinders was developed using a three-dimensional FLAC-PFC coupling method. The validity of the model was verified with experimental data of 0-2 layers of CFRP passively confined coal cylinders. On this basis, studies of the influence of 3-7 layers on mechanical properties and energy evolution of CFRP confined coal cylinders was carried out. The results show that the yield limit and the peak of the coal cylinders gradually coincide with the increase of CFRP layers, showing a state of yielding or failure without warning. With the increase of CFRP layers, the increment in the peak strength of coal cylinders first increases and then decreases. A function is obtained to characterize the evolution of the peak strength increment of CFRP confined coal cylinders under different layers. The increment in the peak strain shows a behavior of first increasing and then decreasing, and then increasing and decreasing again. When the elastic strain energy is constant, the axial strain of the coal cylinders has no correlation with CFRP layers, but its peak strain and ultimate strain both increase with the increase of CFRP layers. The dissipative energy conversion ratio at peak point increases first and then decreases with the increase of CFRP layers. A function is established to characterize the evolution of the dissipative energy conversion ratio of CFRP confined coal cylinders with different layers. The ductility characteristics of stress-strain curves, peak strength increment, peak strain increment, dissipative energy conversion ratio and total energy increment of coal cylinders are considered comprehensively, and taking into account the principles of economic cost and winding level, the three layers are determined as the optimal winding layers for CFRP confined coal circular-columns

Forebrain NR2B Overexpression Facilitating the Prefrontal Cortex Long-Term Potentiation and Enhancing Working Memory Function in Mice

Prefrontal cortex plays an important role in working memory, attention regulation and behavioral inhibition. Its functions are associated with NMDA receptors. However, there is little information regarding the roles of NMDA receptor NR2B subunit in prefrontal cortical synaptic plasticity and prefrontal cortex-related working memory. Whether the up-regulation of NR2B subunit influences prefrontal cortical synaptic plasticity and working memory is not yet clear. In the present study, we measured prefrontal cortical synaptic plasticity and working memory function in NR2B overexpressing transgenic mice. In vitro electrophysiological data showed that overexpression of NR2B specifically in the forebrain region resulted in enhancement of prefrontal cortical long-term potentiation (LTP) but did not alter long-term depression (LTD). The enhanced LTP was completely abolished by a NR2B subunit selective antagonist, Ro25-6981, indicating that overexpression of NR2B subunit is responsible for enhanced LTP. In addition, NR2B transgenic mice exhibited better performance in a set of working memory paradigms including delay no-match-to-place T-maze, working memory version of water maze and odor span task. Our study provides evidence that NR2B subunit of NMDA receptor in prefrontal cortex is critical for prefrontal cortex LTP and prefrontal cortex-related working memory

Curcumin Enhances Neurogenesis and Cognition in Aged Rats: Implications for Transcriptional Interactions Related to Growth and Synaptic Plasticity

Background: Curcumin has been demonstrated to have many neuroprotective properties, including improvement of cognition in humans and neurogenesis in animals, yet the mechanism of such effects remains unclear. Methodology: We assessed behavioural performance and hippocampal cell proliferation in aged rats after 6- and 12-week curcumin-fortified diets. Curcumin enhanced non-spatial and spatial memory, as well as dentate gyrate cell proliferation as compared to control diet rats. We also investigated underlying mechanistic pathways that might link curcumin treatment to increased cognition and neurogenesis via exon array analysis of cortical and hippocampal mRNA transcription. The results revealed a transcriptional network interaction of genes involved in neurotransmission, neuronal development, signal transduction, and metabolism in response to the curcumin treatment. Conclusions: The results suggest a neurogenesis- and cognition-enhancing potential of prolonged curcumin treatment i

Joint algorithm for peak-to-average power reduction of NC-OFDM system

This paper examines the problem of reducing the peak-to-average power ratio (PAPR) occurring in non-contiguous OFDM (NC-OFDM) systems proposed for cognitive radio. The PAPR analysis for NC-OFDM is unlike that of contiguous OFDM and so mitigation schemes must be modified. We propose an algorithm that combines phase adjustment, interleaving and power back-off in a way that is tailored for NC-OFDM. The proposed algorithm exploits the agility of cognitive radio technology to rapidly choose and employ the appropriate PAPR reduction approach from a set of possibilities to achieve a significant decrease PAPR to a setting threshold. The simulation results show that the proposed algorithm achieves a large decrease in PAPR, and calculation complexity is low

A Vehicular Service-Oriented Dynamical Routing Searching Algorithm in Software-Defined BusNet

With the development of the vehicular network, BusNet-based service is of great interest to both bus companies and public users. How to provide service and ensure service quality is considered as key points for the promotion of such kinds of applications. In this paper, a system architecture, which is designed based on multiaccess edge computing (MEC) architecture and software-defined network (SDN), is proposed. Moreover, considering the problem of the dynamicity of the network, a new routing path optimization algorithm, SPSO (serial particle swarm optimization), is proposed, while a dynamic weight matrix is used to improve routing performance. The comprehensive simulation results demonstrate that the proposed method can well adapt to the dynamic change of network topology and improve communication performance significantly