LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee's Advertisement Recommendation

Graph Neural Network (GNN) is the trending solution for item retrieval in recommendation problems. Most recent reports, however, focus heavily on new model architectures. This may bring some gaps when applying GNN in the industrial setup, where, besides the model, constructing the graph and handling data sparsity also play critical roles in the overall success of the project. In this work, we report how GNN is applied for large-scale e-commerce item retrieval at Shopee. We introduce our simple yet novel and impactful techniques in graph construction, modeling, and handling data skewness. Specifically, we construct high-quality item graphs by combining strong-signal user behaviors with high-precision collaborative filtering (CF) algorithm. We then develop a new GNN architecture named LightSAGE to produce high-quality items' embeddings for vector search. Finally, we design multiple strategies to handle cold-start and long-tail items, which are critical in an advertisement (ads) system. Our models bring improvement in offline evaluations, online A/B tests, and are deployed to the main traffic of Shopee's Recommendation Advertisement system

Optical excitation and detection of neuronal activity

Optogenetics has emerged as an exciting tool for manipulating neural activity, which in turn, can modulate behavior in live organisms. However, detecting the response to the optical stimulation requires electrophysiology with physical contact or fluorescent imaging at target locations, which is often limited by photobleaching and phototoxicity. In this paper, we show that phase imaging can report the intracellular transport induced by optogenetic stimulation. We developed a multimodal instrument that can both stimulate cells with high spatial resolution and detect optical pathlength changes with nanometer scale sensitivity. We found that optical pathlength fluctuations following stimulation are consistent with active organelle transport. Furthermore, the results indicate a broadening in the transport velocity distribution, which is significantly higher in stimulated cells compared to optogenetically inactive cells. It is likely that this label-free, contactless measurement of optogenetic response will provide an enabling approach to neuroscience.Comment: 20 pages, 5 figure

Effect of Inclination Angle on the Response of Double-row Retaining Piles: Experimental and Numerical Investigation

The excavation depth of foundation pits has been increasing along with the continuous development of underground space and high-rise buildings. As a result, traditional double-row vertical piles cannot meet the ground settlement and deflection requirements. This study proposed a double-row pile optimization method to extend the suitability of double-row retaining piles to greater excavation depth. The optimization model was established by adjusting the inclination angle of the front and rear piles. Physical scale model tests were performed to analyze the effect of the inclination angle on the pile head displacements and bending moments during excavations and step loadings using three schemes, namely, traditional double-row piles with vertical piles, double-row contiguous retaining piles with batter pile in the front row, and double-row contiguous retaining piles with batter pile in both rows. Numerical simulations were also conducted to verify the effectiveness of the inclination angle adjustment in optimizing the double-row piles. Results indicate that the increase in the displacement and bending moment of the double-row contiguous retaining batter piles is not evident during excavation and step loading when compared with those of the double-row vertical piles and the double-row contiguous retaining piles with batter pile in the front row. Thus, double-row contiguous retaining batter piles can be used in deep foundation pits. The tilt angle is also excessively small to reduce the lateral displacement of the foundation pit, and the optimal tilt angle is 8° – 16°. Although the embedment depth can influence the deformation of the double-row contiguous retaining batter piles significantly, a critical embedment depth may be reached. The findings of this study can provide references for the optimization of double-row piles in foundation pits

PHF8 and REST/NRSF co-occupy gene promoters to regulate proximal gene expression

Chromatin regulators play an important role in the development of human diseases. In this study, we focused on Plant Homeo Domain Finger protein 8 (PHF8), a chromatin regulator that has attracted special concern recently. PHF8 is a histone lysine demethylase ubiquitously expressed in nuclei. Mutations of PHF8 are associated with X-linked mental retardation. It usually functions as a transcriptional co-activator by associating with H3K4me3 and RNA polymerase II. We found that PHF8 may associate with another regulator, REST/NRSF, predominately at promoter regions via studying several published PHF8 chromatin immunoprecipitation-sequencing (ChIP-Seq) datasets. Our analysis suggested that PHF8 not only activates but may also repress gene expression

Regulation of high-fat diet-induced microglial metabolism by transient receptor potential vanilloid type 1

Objective·Transcriptomic and lipidomic analysis techniques were used to investigate the role of transient receptor potential vanilloid type 1 (TRPV1) channel activation in the regulation of high-fat diet-induced microglial metabolism.Methods·Eight-week-old C57BL/6J mice (WT) and Trpv1-/- (KO) mice were used as experimental animals, and fed high-fat diet (HFD) for 3 days, 7 days, and 8 weeks to induce modelling (WT and KO groups, n = 3; WT-HFD and KO-HFD groups, n = 4). TRPV1 channel expression and cellular localisation were measured by immunofluorescence in the brains of mice in the WT-HFD and KO-HFD group. RNA sequencing and liquid chromatography-mass spectrometry were performed to determine the brain phenotype of mice in the WT-HFD and KO-HFD groups.Results·The expression level of Trpv1 mRNA in microglia was significantly increased in mice in the WT-HFD group compared to mice in the WT group. The expression levels of genes related to brain lipid metabolism, mitochondrial function, glucose transfer, and glycolysis were down-regulated in the KO-HFD group of mice compared with the WT-HFD group of mice. Lipidomic analysis showed that although lipids accumulated in the brain tissue of mice in the KO-HFD group, Trpv1 knockdown attenuated HFD-induced microglia activation, and in addition the TRPV1 agonist capsaicin attenuated palmitate-induced depolarisation of mitochondrial membrane potential in vitro.Conclusion·Together, these findings suggest that TRPV1 regulates lipid and glucose metabolism in microglia via fuel availability driven by a mitochondrial mechanism

ReCo: Region-Controlled Text-to-Image Generation

Recently, large-scale text-to-image (T2I) models have shown impressive performance in generating high-fidelity images, but with limited controllability, e.g., precisely specifying the content in a specific region with a free-form text description. In this paper, we propose an effective technique for such regional control in T2I generation. We augment T2I models' inputs with an extra set of position tokens, which represent the quantized spatial coordinates. Each region is specified by four position tokens to represent the top-left and bottom-right corners, followed by an open-ended natural language regional description. Then, we fine-tune a pre-trained T2I model with such new input interface. Our model, dubbed as ReCo (Region-Controlled T2I), enables the region control for arbitrary objects described by open-ended regional texts rather than by object labels from a constrained category set. Empirically, ReCo achieves better image quality than the T2I model strengthened by positional words (FID: 8.82->7.36, SceneFID: 15.54->6.51 on COCO), together with objects being more accurately placed, amounting to a 20.40% region classification accuracy improvement on COCO. Furthermore, we demonstrate that ReCo can better control the object count, spatial relationship, and region attributes such as color/size, with the free-form regional description. Human evaluation on PaintSkill shows that ReCo is +19.28% and +17.21% more accurate in generating images with correct object count and spatial relationship than the T2I model

TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

Artificial Intelligence (AI) has made incredible progress recently. On the one hand, advanced foundation models like ChatGPT can offer powerful conversation, in-context learning and code generation abilities on a broad range of open-domain tasks. They can also generate high-level solution outlines for domain-specific tasks based on the common sense knowledge they have acquired. However, they still face difficulties with some specialized tasks because they lack enough domain-specific data during pre-training or they often have errors in their neural network computations on those tasks that need accurate executions. On the other hand, there are also many existing models and systems (symbolic-based or neural-based) that can do some domain-specific tasks very well. However, due to the different implementation or working mechanisms, they are not easily accessible or compatible with foundation models. Therefore, there is a clear and pressing need for a mechanism that can leverage foundation models to propose task solution outlines and then automatically match some of the sub-tasks in the outlines to the off-the-shelf models and systems with special functionalities to complete them. Inspired by this, we introduce TaskMatrix.AI as a new AI ecosystem that connects foundation models with millions of APIs for task completion. Unlike most previous work that aimed to improve a single AI model, TaskMatrix.AI focuses more on using existing foundation models (as a brain-like central system) and APIs of other AI models and systems (as sub-task solvers) to achieve diversified tasks in both digital and physical domains. As a position paper, we will present our vision of how to build such an ecosystem, explain each key component, and use study cases to illustrate both the feasibility of this vision and the main challenges we need to address next

Mapping the path towards novel treatment strategies: a bibliometric analysis of Hashimoto’s thyroiditis research from 1990 to 2023

BackgroundHashimoto’s thyroiditis (HT), a common form of thyroid autoimmunity, is strongly associated with deteriorating clinical status and impaired quality of life. The escalating global prevalence, coupled with the complexity of disease mechanisms, necessitates a comprehensive, bibliometric analysis to elucidate the trajectory, hotspots, and future trends in HT research.ObjectiveThis study aims to illuminate the development, hotspots, and future directions in HT research through systematic analysis of publications, institutions, authors, journals, references, and keywords. Particular emphasis is placed on novel treatment strategies for HT and its complications, highlighting the potential role of genetic profiling and immunomodulatory therapies.MethodsWe retrieved 8,726 relevant documents from the Web of Science Core Collection database spanning from 1 January 1990 to 7 March 2023. Following the selection of document type, 7,624 articles were included for bibliometric analysis using CiteSpace, VOSviewer, and R software.ResultsThe temporal evolution of HT research is categorized into three distinct phases: exploration (1990-1999), rapid development (1999-2000), and steady growth (2000-present). Notably, the United States, China, Italy, and Japan collectively contributed over half (54.77%) of global publications. Among the top 10 research institutions, four were from Italy (4/10), followed by China (2/10) and the United States (2/10). Recent hotspots, such as the roles of gut microbiota, genetic profiling, and nutritional factors in HT management, the diagnostic dilemmas between HT and Grave’s disease, as well as the challenges in managing HT complicated by papillary thyroid carcinoma and type 1 diabetes mellitus, are discussed.ConclusionAlthough North America and Europe have a considerable academic impact, institutions from emerging countries like China are demonstrating promising potential in HT research. Future studies are anticipated to delve deeper into the differential diagnosis of HT and Grave’s disease, the intricate relationship between gut microbiota and HT pathogenesis, clinical management of HT with papillary thyroid carcinoma or type 1 diabetes, and the beneficial effects of dietary modifications and micronutrients supplementation in HT. Furthermore, the advent of genetic profiling and advanced immunotherapies for managing HT offers promising avenues for future research