Query-LIFE: Query-aware Language Image Fusion Embedding for E-Commerce Relevance

Relevance module plays a fundamental role in e-commerce search as they are responsible for selecting relevant products from thousands of items based on user queries, thereby enhancing users experience and efficiency. The traditional approach models the relevance based product titles and queries, but the information in titles alone maybe insufficient to describe the products completely. A more general optimization approach is to further leverage product image information. In recent years, vision-language pre-training models have achieved impressive results in many scenarios, which leverage contrastive learning to map both textual and visual features into a joint embedding space. In e-commerce, a common practice is to fine-tune on the pre-trained model based on e-commerce data. However, the performance is sub-optimal because the vision-language pre-training models lack of alignment specifically designed for queries. In this paper, we propose a method called Query-LIFE (Query-aware Language Image Fusion Embedding) to address these challenges. Query-LIFE utilizes a query-based multimodal fusion to effectively incorporate the image and title based on the product types. Additionally, it employs query-aware modal alignment to enhance the accuracy of the comprehensive representation of products. Furthermore, we design GenFilt, which utilizes the generation capability of large models to filter out false negative samples and further improve the overall performance of the contrastive learning task in the model. Experiments have demonstrated that Query-LIFE outperforms existing baselines. We have conducted ablation studies and human evaluations to validate the effectiveness of each module within Query-LIFE. Moreover, Query-LIFE has been deployed on Miravia Search, resulting in improved both relevance and conversion efficiency

Molecular dynamics simulations of oil recovery from dolomite slit nanopores enhanced by CO2 and N2 injection

Shale oil reservoirs are dominated by micro-and nanopores, which greatly impede the oil recovery rates. CO2 and N2 injection have proven to be highly effective approaches to enhance oil recovery from low-permeability shale reservoirs, and also represent great potential for CO2 sequestration. Therefore, a better understanding of the mechanism of shale oil recovery enhanced by CO2 and N2 is of great importance to achieve maximum shale oil productivity. In this paper, the adsorption behavior of shale oil and the mechanism of enhancing shale oil recovery by CO2 and N2 flooding in dolomite slit pores are investigated by performing nonequilibrium molecular dynamics simulations. Considering the shale oil adsorption behavior, mass density distribution is analyzed and the results indicate that a symmetric density distribution of the oil regarding the center in the slit pore along the x-axis can be obtained. The maximum density of the adsorbed layer nearest to the slit wall is 1.310 g/cm3 for C8H18 , which is about 2.0 times of that for bulk oil density in the middle area of slit pore. The interaction energy and radial distribution functions (between oil and CO2 , and between oil and N2 ) are calculated to display the displacement behavior of CO2 and N2 flooding. It is found that CO2 and N2 play different roles: CO2 has strong solubility, diffusivity and a higher interaction energy with dolomite wall, and the oil displacement efficiency of CO2 reaches 100% after 1 ns of flooding; however, during N2 flooding, the oil displacement efficiency is 87.3% after 4 ns of flooding due to the lower interaction energy between N2 and dolomite and that between N2 and oil.Cited as: Guo, H., Wang, Z., Wang, B., Zhang, Y., Meng, H., Sui H. Molecular dynamics simulations of oil recovery from dolomite slit nanopores enhanced by CO2 and N2 injection. Advances in Geo-Energy Research, 2022, 6(4): 306-313. https://doi.org/10.46690/ager.2022.04.0

Platinum-based chemotherapy plus cetuximab first-line for Asian patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck: Results of an open-label, single-arm, multicenter trial

Background The purpose of this study was to assess the efficacy, safety, and pharmacokinetics of cisplatin-based chemotherapy plus cetuximab as first-line treatment in Chinese and Korean patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN). Methods Patients (n = 68) received cetuximab weekly plus 3-week cycles of cisplatin/5-fluorouracil (5-FU) chemotherapy for up to 6 cycles. The primary endpoint was overall response rate. Results The overall response rate was 55.9%, including 2 complete responses (CRs). Median overall survival (OS) was 12.6 months and median progression-free survival (PFS) was 6.6 months. Grade 3/4 adverse events (AEs) were reported in 41 (60.3%) patients. The safety profile was in line with previous clinical experience. The pharmacokinetic profile was in line with that observed with cetuximab in white and Japanese patients. Conclusion The efficacy, safety, and pharmacokinetic findings from this study support the use of first-line platinum-based chemotherapy plus cetuximab in Chinese and Korean patients with recurrent and/or metastatic SCCHN (ClinicalTrials.gov NCT01177956). © 2014 The Authors Head & Neck Published by Wiley Periodicals, Inc. Head Neck 37: 1081–1087, 201

Buddhist Vegetarian Restaurants and the Changing Meanings of Meat in Urban China

This article charts the changing meanings of meat in contemporary urban China and explores the role played by Buddhist vegetarian restaurants in shaping these changes. In Kunming, meat has long been a sign of prosperity and status. Its accessibility marked the successes of the economic reforms. Yet Kunmingers were increasingly concerned about excessive meat consumption and about the safety and quality of the meat supply. Buddhist vegetarian restaurants provided spaces where people could share meat-free meals and discuss and develop their concerns about meat-eating. While similar to and influenced by secular, Western vegetarianisms, the central role of Buddhism was reflected in discourses on karmic retribution for taking life and in a non-confrontational approach that sought to accommodate these discourses with the importance of meat in Chinese social life. Finally, the vegetarian restaurants spoke to middle-class projects of self-cultivation, and by doing so potentially challenged associations between meat-eating and social status

Study on the application of LSTM-LightGBM Model in stock rise and fall prediction

This paper proposes a hybrid financial time series forecast model based on LSTM and LightGBM, namely LSTM_LightGBM model. Use the LightGBM model to train the processed stock historical data set, and save the training results. Then the opening price, closing price, highest price, lowest price, trading volume and adjusted closing price are separately input into the LSTM model for prediction. The prediction result of each attribute is used as the test set of the prediction after LightGBM training. Constantly adjust the parameters of each model, and finally get the optimal stock price forecast model. The model is validated with the rise and fall of AAPL stock. Through the comparison of evaluation index root mean square error RMSE, mean absolute error MAE, prediction accuracy Accuracy and f1_score. It is found that the LSTM_LightGBM model exhibits stable and better prediction performance in the stock prediction. That is to say, the LSTM_LightGBM model proposed in this paper is stable and feasible in the stock price fluctuation forecast

Coastal Wetlands Play an Important Role in the Ecological Security Pattern of the Coastal Zone

The construction of an ecological security pattern can effectively overcome the contradiction between regional human exploitation and ecological protection in the coastal zone. Taking the Xiangshan Bay (XSB) basin as an example, this study identified ecological source areas from three aspects, namely ecosystem services’ importance, ecological sensitivity, and landscape connectivity, and then constructed ecological resistance surfaces, identified ecological corridors, and constructed an ecological security pattern. The results show that the natural reserves in the XSB basin were all located in the identified primary ecological source areas, thus indicating the feasibility and reliability of the “importance–connectivity–sensitivity” ecological source identification mechanism in this study. The ecological corridor in the coastal wetland area accounts for about 40% of the total corridor length, which is the link connecting other ecological sources, revealing the important role of coastal wetlands in the coastal ecosystem. Through the ecological security pattern of the XSB basin and field investigation, we put forward suggestions such as clearing Spartina alterniflora, restoring salt marsh wetland vegetation, and strengthening follow-up monitoring for the restoration of coastal wetlands. This study is expected to provide reference and guidance for the improvement of coastal zone ecological protection and restoration

Coastal Wetlands Play an Important Role in the Ecological Security Pattern of the Coastal Zone

The construction of an ecological security pattern can effectively overcome the contradiction between regional human exploitation and ecological protection in the coastal zone. Taking the Xiangshan Bay (XSB) basin as an example, this study identified ecological source areas from three aspects, namely ecosystem services’ importance, ecological sensitivity, and landscape connectivity, and then constructed ecological resistance surfaces, identified ecological corridors, and constructed an ecological security pattern. The results show that the natural reserves in the XSB basin were all located in the identified primary ecological source areas, thus indicating the feasibility and reliability of the “importance–connectivity–sensitivity” ecological source identification mechanism in this study. The ecological corridor in the coastal wetland area accounts for about 40% of the total corridor length, which is the link connecting other ecological sources, revealing the important role of coastal wetlands in the coastal ecosystem. Through the ecological security pattern of the XSB basin and field investigation, we put forward suggestions such as clearing Spartina alterniflora, restoring salt marsh wetland vegetation, and strengthening follow-up monitoring for the restoration of coastal wetlands. This study is expected to provide reference and guidance for the improvement of coastal zone ecological protection and restoration

Far-infrared transparent conductors

Abstract The long-standing challenge in designing far-infrared transparent conductors (FIRTC) is the combination of high plasma absorption edge (λ p ) and high conductivity (σ). These competing requirements are commonly met by tuning carrier concentration or/and effective carrier mass in a metal oxide/oxonate with low optical dielectric constant (ε opt  = 2–7). However, despite the high σ, the transparent band is limited to mid-infrared (λ p   15 and λ p  > 15 μm. These FIRTC crystals are mainly octahedrally-coordinated heavy-metal chalcogenides and their solid solutions with shallow-level defects. Their high ε opt relies on the formation of electron-deficiency multicenter bonds resulting in the great electron-polarization effect. The new FIRTC enables us to develop the first “continuous film” type far-infrared electromagnetic shielder that is unattainable using traditional materials. Therefore, this study may inaugurate a new era in far-infrared optoelectronics

BoMW: Bag of Manifold Words for One-shot Learning Gesture Recognition from Kinect

In this paper, we study one-shot learning gesture recognition on RGB-D data recorded from Microsoft’s Kinect. To this end, we propose a novel bag of manifold words (BoMW) based feature representation on sysmetric positive definite (SPD) manifolds. In particular, we use covariance matrices to extract local features from RGB-D data due to its compact representation ability as well as the convenience of fusing both RGB and depth information. Since covariance matrices are SPD matrices and the space spanned by them is the SPD manifold, traditional learning methods in the Euclidean space such as sparse coding can not be directly applied to them. To overcome this problem, we propose a unified framework to transfer the sparse coding on SPD manifolds to the one on the Euclidean space, which enables any existing learning method can be used. After building BoMW representation on a video from each gesture class, a nearest neighbour classifier is adopted to perform the one-shot learning gesture recognition. Experimental results on the ChaLearn gesture dataset demonstrate the outstanding performance of the proposed one-shot learning gesture recognition method compared against state-of-the-art methods. The effectiveness of the proposed feature extraction method is also validated on a new RGB-D action recognition dataset