Semantic-Enhanced Differentiable Search Index Inspired by Learning Strategies

Recently, a new paradigm called Differentiable Search Index (DSI) has been proposed for document retrieval, wherein a sequence-to-sequence model is learned to directly map queries to relevant document identifiers. The key idea behind DSI is to fully parameterize traditional ``index-retrieve'' pipelines within a single neural model, by encoding all documents in the corpus into the model parameters. In essence, DSI needs to resolve two major questions: (1) how to assign an identifier to each document, and (2) how to learn the associations between a document and its identifier. In this work, we propose a Semantic-Enhanced DSI model (SE-DSI) motivated by Learning Strategies in the area of Cognitive Psychology. Our approach advances original DSI in two ways: (1) For the document identifier, we take inspiration from Elaboration Strategies in human learning. Specifically, we assign each document an Elaborative Description based on the query generation technique, which is more meaningful than a string of integers in the original DSI; and (2) For the associations between a document and its identifier, we take inspiration from Rehearsal Strategies in human learning. Specifically, we select fine-grained semantic features from a document as Rehearsal Contents to improve document memorization. Both the offline and online experiments show improved retrieval performance over prevailing baselines.Comment: Accepted by KDD 202

Three Dimensional Reconfigurable Optical Singularities in Bilayer Photonic Crystals

Metasurfaces and photonic crystals have revolutionized classical and quantum manipulation of light, and opened the door to studying various optical singularities related to phases and polarization states. However, traditional nanophotonic devices lack reconfigurability, hindering the dynamic switching and optimization of optical singularities. This paper delves into the underexplored concept of tunable bilayer photonic crystals (BPhCs), which offer rich interlayer coupling effects. Utilizing silicon nitride-based BPhCs, we demonstrate tunable bidirectional and unidirectional polarization singularities, along with spatiotemporal phase singularities. Leveraging these tunable singularities, we achieve dynamic modulation of bound-state-in-continuum states, unidirectional guided resonances, and both longitudinal and transverse orbital angular momentum. Our work paves the way for multidimensional control over polarization and phase, inspiring new directions in ultrafast optics, optoelectronics, and quantum optics

Data science: connotation, methods, technologies, and development

The rapid development of big data breeds data science. Understanding and mastering the internal pattern of the value generation of big data is important for improving digitization and the covergence of data science with management science, computer science, and other disciplines. In this study, we discuss the significance of data science for the development of science and technology and social progress. Based on the interpretation of the connotation of data science, we introduce the definition of data science and review its formation by summarizing the major progress of related disciplines. We also discuss the research methodologies, development patterns and trends, and technical directions of data science. Finally, we make suggestions for data science to promote the development of data-based science and technology

A novel scheme for domain-transfer problem in the context of sentiment analysis

In this work, we attempt to tackle domain-transfer problem by combining old-domain labeled examples with new-domain unlabeled ones. The basic idea is to use old-domain-trained classifier to label some informative unlabeled examples in new domain, and retrain the base classifier over these selected examples. The experimental results demonstrate that proposed scheme can significantly boost the accuracy of the base sentiment classifier on new domain

Journal of the Copyright Society of the USA

The snaking of strip in the continuous annealing furnace affects both the process stability of production line significantly and the quality of final products. This paper for the first time proposed the self-centering ability of tapered hearth roll on initial flatness of strip travelling in the furnace and a FEM model that coupling the strip and furnace roll is constructed to simulate the traveling process of strip in the furnace. The self-centering ability is quite different with respect to the different initial flatness waves of strip traveling in the furnace and can be used for optimization of initial flatness of strip for stability improvement

Study on the Flow Behavior of Wellbore Fluids of a Natural Gas Hydrate Well with the Combined Depressurization and Heat Injection Method

Natural gas hydrate (NGH) is a kind of clean energy with great potential because of its huge reserves. There are several effective methods for exploiting hydrate sediments such as depressurization, thermal excitation, inhibitor injection and displacement, etc. Among these methods, the combined depressurization and heat injection method is considered a very promising method, which solves the problem of insufficient heat supply during the depressurization process. In this paper, the mechanism of combined depressurization and heat injection exploitation of NGH is analyzed, and the multiphase flow models of the injection well and production well are established, respectively, for the parallel horizontal NGH well production system with this combined method. The multiphase flow laws of fluids in a wellbore were obtained, and the factors affecting the temperature and pressure distributions in the wellbore were analyzed. The results of this study show that gas and water are produced simultaneously in the process of exploitation with this combined depressurization and heat injection method. The electric submersible pump has a great influence on the flow of the fluids in the wellbore, and there are sudden skips of the temperature and pressure at the pump position. Increasing the depth and working frequency of the pump will reduce the risk of continuous discharge of water from the annulus. Increasing the injection rate and injection temperature can both improve the effect of heat injection. This study provides theoretical guidance for the combined extraction with depressurization and heat injection method and production optimization of NGH

Identification of Three Small Molecules That Can Selectively Influence Cellular Manganese Levels in a Mouse Striatal Cell Model

Manganese (Mn) is a biologically essential metal, critical as a cofactor for numerous enzymes such a glutamine synthetase and kinases such as ataxia-telangiectasia mutated (ATM). Similar to other essential metals such as iron and zinc, proper levels of Mn need to be achieved while simultaneously being careful to avoid excess levels of Mn that can be neurotoxic. A lifetime of occupational exposure to Mn can often lead to a Parkinsonian condition, also known as “manganism”, characterized by impaired gait, muscle spasms, and tremors. Despite the importance of its regulation, the mechanisms underlying the transport and homeostasis of Mn are poorly understood. Rather than taking a protein or gene-targeted approach, our lab recently took a high-throughput-screening approach to identify 41 small molecules that could significantly increase or decrease intracellular Mn in a neuronal cell model. Here, we report characterization of these small molecules, which we refer to as the “Mn toolbox”. We adapted a Fura-2-based assay for measuring Mn concentration and for measuring relative concentrations of other divalent metals: nickel, copper, cobalt, and zinc. Of these 41 small molecules, we report here the identification of three that selectively influence cellular Mn but do not influence the other divalent metals tested. The patterns of activity across divalent metals and the discovery of Mn-selective small molecules has potential pharmacological and scientific utility

Modulation of Gut Microbiota by Lactobacillus casei Fermented Raspberry Juice In Vitro and In Vivo

The aim of this study was to investigate the modulation of gut microbiota by fermented raspberry juice (FRJ) both in vitro and in vivo. Results showed that total phenolic content and antioxidant activities of FRJ reached the highest after fermentation for 42 h. Seventeen phenolic compounds were contained in FRJ, mainly including ellagic acid (496.64 ± 2.91 μg/g) and anthocyanins (total concentration: 387.93 μg/g). FRJ modulated the gut microbiota into a healthy in vitro status, with increase of valeric and isovaleric acids production. In healthy mice, all FRJ treatments improved the production of acetic, butyric and isovaleric acids as well as the gene expression of ZO-1, Claudin-1, Claudin-4, Ocdudin, E-cadherin and Muc-2. Moreover, variable gut microbial compositions were found among the groups fed diet-supplemented the different doses of FRJ, within low and median doses of FRJ may regulate the microbiota to a healthier state compared to the high dose supplementation. This study indicated that fermentation is a potential way to produce plant-based juices, which could reshape the gut microbiota and improve the host health

Gut microbiota reshapes cancer immunotherapy efficacy: Mechanisms and therapeutic strategies

Abstract Gut microbiota is essential for maintaining local and systemic immune homeostasis in the presence of bacterial challenges. It has been demonstrated that microbiota play contrasting roles in cancer development as well as anticancer immunity. Cancer immunotherapy, a novel anticancer therapy that relies on the stimulation of host immunity, has suffered from a low responding rate and incidence of severe immune‐related adverse events (irAEs). Previous studies have demonstrated that the diversity and composition of gut microbiota were associated with the heterogeneity of therapeutic effects. Therefore, alteration in microbiota taxa can lead to improved clinical outcomes in immunotherapy. In this review, we determine whether microbiota composition or microbiota‐derived metabolites are linked to responses to immunotherapy and irAEs. Moreover, we discuss various approaches to improve immunotherapy efficacy or reduce toxicities by modulating microbiota composition