Hierarchically Fusing Long and Short-Term User Interests for Click-Through Rate Prediction in Product Search

Estimating Click-Through Rate (CTR) is a vital yet challenging task in personalized product search. However, existing CTR methods still struggle in the product search settings due to the following three challenges including how to more effectively extract users' short-term interests with respect to multiple aspects, how to extract and fuse users' long-term interest with short-term interests, how to address the entangling characteristic of long and short-term interests. To resolve these challenges, in this paper, we propose a new approach named Hierarchical Interests Fusing Network (HIFN), which consists of four basic modules namely Short-term Interests Extractor (SIE), Long-term Interests Extractor (LIE), Interests Fusion Module (IFM) and Interests Disentanglement Module (IDM). Specifically, SIE is proposed to extract user's short-term interests by integrating three fundamental interests encoders within it namely query-dependent, target-dependent and causal-dependent interest encoder, respectively, followed by delivering the resultant representation to the module LIE, where it can effectively capture user long-term interests by devising an attention mechanism with respect to the short-term interests from SIE module. In IFM, the achieved long and short-term interests are further fused in an adaptive manner, followed by concatenating it with original raw context features for the final prediction result. Last but not least, considering the entangling characteristic of long and short-term interests, IDM further devises a self-supervised framework to disentangle long and short-term interests. Extensive offline and online evaluations on a real-world e-commerce platform demonstrate the superiority of HIFN over state-of-the-art methods.Comment: accpeted by CIKM'22 as a Full Pape

H2TNE: Temporal Heterogeneous Information Network Embedding in Hyperbolic Spaces

Temporal heterogeneous information network (temporal HIN) embedding, aiming to represent various types of nodes of different timestamps into low dimensional spaces while preserving structural and semantic information, is of vital importance in diverse real-life tasks. Researchers have made great efforts on temporal HIN embedding in Euclidean spaces and got some considerable achievements. However, there is always a fundamental conflict that many real-world networks show hierarchical property and power-law distribution, and are not isometric of Euclidean spaces. Recently, representation learning in hyperbolic spaces has been proved to be valid for data with hierarchical and power-law structure. Inspired by this character, we propose a hyperbolic heterogeneous temporal network embedding (H2TNE) model for temporal HINs. Specifically, we leverage a temporally and heterogeneously double-constrained random walk strategy to capture the structural and semantic information, and then calculate the embedding by exploiting hyperbolic distance in proximity measurement. Experimental results show that our method has superior performance on temporal link prediction and node classification compared with SOTA models.Comment: arXiv admin note: text overlap with arXiv:1705.08039 by other author

Investigating the Formation Process of Sn-Based Lead-Free Nanoparticles with a Chemical Reduction Method

Nanoparticles of a promising lead-free solder alloy (Sn3.5Ag (wt.%, SnAg) and Sn3.0Ag0.5Cu (wt.%, SAC)) were synthesized through a chemical reduction method by using anhydrous ethanol and 1,10-phenanthroline as the solvent and surfactant, respectively. To illustrate the formation process of Sn-Ag alloy based nanoparticles during the reaction, X-ray diffraction (XRD) was used to investigate the phases of the samples in relation to the reaction time. Different nucleation and growth mechanisms were compared on the formation process of the synthesized nanoparticles. The XRD results revealed different reaction process compared with other researchers. There were many contributing factors to the difference in the examples found in the literature, with the main focus on the formation mechanism of crystal nuclei, the solubility and ionizability of metal salts in the solvent, the solid solubility of Cu in Ag nuclei, and the role of surfactant on the growth process. This study will help define the parameters necessary for the control of both the composition and size of the nanoparticles

Preparation and Properties of Starch-Based Antibacterial Film with Orange Essential Oil Emulsified by Cellulose Nanocrystalline

Using corn starch (CS) as the film substrate, citric acid as the crosslinking agent, and Pickering emulsion prepared with cellulose nanocrystals (CNC)-emulsified orange peel essential oil (OPO) as the antibacterial agent, an antibacterial composite film (CS/CNC-OPO) was successfully prepared by the casting method. The effects of different contents of CNC and OPO on the mechanical strength, water vapor transmission rate, water contact angle and antibacterial properties of the composite film were analyzed, and the composite film was characterized by Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD) spectroscopy and scanning electron microscopy (SEM). The results showed that the performance of the CS/CNC-OPO antibacterial film was the best when 11% OPO was added and the CNC-to-OPO ratio was 1:11 (g/mL). The antibacterial film had the following properties: water vapor permeability, 1.03 × 10-3 g/(m·h·kPa); water contact angle, 74.53°; and tensile strength 6.01 MPa. The area of inhibition zone of the film against Escherichia coli and Staphylococcus aureus was up to 88.4 and 96.45 mm2, respectively. Therefore, the starch-based film has good strength, hydrophobic and antibacterial properties, and has broad application prospects in the field of food packaging

Non-invasive monitoring of cardiac function through Ballistocardiogram: an algorithm integrating short-time Fourier transform and ensemble empirical mode decomposition

The Ballistocardiogram (BCG) is a vibration signal that is generated by the displacement of the entire body due to the injection of blood during each heartbeat. It has been extensively utilized to monitor heart rate. The morphological features of the BCG signal serve as effective indicators for the identification of atrial fibrillation and heart failure, holding great significance for BCG signal analysis. The IJK-complex identification allows for the estimation of inter-beat intervals (IBI) and enables a more detailed analysis of BCG amplitude and interval waves. This study presents a novel algorithm for identifying the IJK-complex in BCG signals, which is an improvement over most existing algorithms that only perform IBI estimation. The proposed algorithm employs a short-time Fourier transform and summation across frequencies to initially estimate the occurrence of the J wave using peak finding, followed by Ensemble Empirical Mode Decomposition and a regional search to precisely identify the J wave. The algorithm’s ability to detect the morphological features of BCG signals and estimate heart rates was validated through experiments conducted on 10 healthy subjects and 2 patients with coronary heart disease. In comparison to commonly used methods, the presented scheme ensures accurate heart rate estimation and exhibits superior capability in detecting BCG morphological features. This advancement holds significant value for future applications involving BCG signals

Heterogeneous nucleation of pure Al on MgO single crystal substrate accompanied by a MgAl2O4 buffer layer

This paper investigates the correlations between interfacial reaction, crystallographic orientation relationship on the interface and the required undercooling for nucleation on different crystallographic planes of MgO. Thermal analysis and high resolution transmission electron microscopy were used to study the nucleation behavior of liquid, high-purity Al droplet on single crystal MgO substrates using a DSC with an integrated image capture system and a sessile drop apparatus. The results showed that the original substrate MgO would be completely replaced by the reaction product MgAlO at the interface owing to the chemical reaction between liquid Al and the MgO substrates. In addition, the same crystal structure with the original MgO substrate is achieved in the new MgAlO layer. The orientation relationship between MgAlO and Al is consistent with the theoretical prediction according to the Bramfitt's lattice misfit theory and Edge-to-Edge model. Consequently, the generated MgAlO significantly influences the detected undercooling

Emerging trends and focus of research on the relationship between traumatic brain injury and gut microbiota: a visualized study

BackgroundTraumatic brain injury (TBI) is one of the most serious types of trauma and imposes a heavy social and economic burden on healthcare systems worldwide. The development of emerging biotechnologies is uncovering the relationship between TBI and gut flora, and gut flora as a potential intervention target is of increasing interest to researchers. Nevertheless, there is a paucity of research employing bibliometric methodologies to scrutinize the interrelation between these two. Therefore, this study visualized the relationship between TBI and gut flora based on bibliometric methods to reveal research trends and hotspots in the field. The ultimate objective is to catalyze progress in the preclinical and clinical evolution of strategies for treating and managing TBI.MethodsTerms related to TBI and gut microbiota were combined to search the Scopus database for relevant documents from inception to February 2023. Visual analysis was performed using CiteSpace and VOSviewer.ResultsFrom September 1972 to February 2023, 2,957 documents published from 98 countries or regions were analyzed. The number of published studies on the relationship between TBI and gut flora has risen exponentially, with the United States, China, and the United Kingdom being representative of countries publishing in related fields. Research has formed strong collaborations around highly productive authors, but there is a relative lack of international cooperation. Research in this area is mainly published in high-impact journals in the field of neurology. The “intestinal microbiota and its metabolites,” “interventions,” “mechanism of action” and “other diseases associated with traumatic brain injury” are the most promising and valuable research sites. Targeting the gut flora to elucidate the mechanisms for the development of the course of TBI and to develop precisely targeted interventions and clinical management of TBI comorbidities are of great significant research direction and of interest to researchers.ConclusionThe findings suggest that close attention should be paid to the relationship between gut microbiota and TBI, especially the interaction, potential mechanisms, development of emerging interventions, and treatment of TBI comorbidities. Further investigation is needed to understand the causal relationship between gut flora and TBI and its specific mechanisms, especially the “brain-gut microbial axis.

Different Chemotherapy Regimens in the Management of Advanced or Metastatic Urothelial Cancer: a Bayesian Network Meta-Analysis of Randomized Controlled Trials

Background/Aims: Urothelial cancer (UC) as a chemotherapy-sensitive tumor, has achieved remarkable progresses in therapeutic paradigm, particularly in the advanced/metastatic stages. However, both clinicians and patients are confused when it comes to choosing the optimal chemotherapy. Hence, this article was aimed to conduct a comprehensive comparison of different chemotherapy regimens for advanced or metastatic UC in terms of survival benefits or adverse events. Methods: The online databases PubMed, EMBASE and Web of Science were searched systematically and comprehensively for randomized controlled trials (RCTs) up to September 15, 2017. The pooled hazard ratios (HRs) or odds ratios (ORs) with 95% credible interval (CrI) were calculated by Markov chain Monte Carlo methods. The effectiveness and safety of included regimens were conducted to provide a hierarchy by means of rank probabilities with the help of “R-3.4.0” software and the “gemtc-0.8.2” package. The surface under the cumulative ranking curve (SUCRA) was also incorporated in our analysis for ranking the corresponding chemotherapy regimens. Results: Ten different chemotherapy regimens involved in this article were predominantly of trials in a first-line setting, and eight clinical outcomes were ultimately analyzed in this study. In terms of Overall response rate (ORR), Overall survival (OS) or Progression-free survival (PFS)/Time to progression (TTP), the rank probabilities and SUCRA indicated that Paclitaxel/cisplatin/gemcitabine (PCG) was superior to gemcitabine/cisplatin (GC) or methotrexate/vinblastine/doxorubicin/cisplatin (MVAC), the traditional first-line treatment for advanced/metastatic UC. In the case of ORR or PFS/TTP, GC+sorafenib also displayed its superiority in comparison with GC or MVAC. Despite their survival benefits, PCG or GC+sorafenib presented a relatively higher incidence of adverse events. Conclusion: Our results revealed that by adding a paclitaxel or sorafenib into the first-line GC, it could yield a better survival benefit, but also worsen adverse events for advanced/ metastatic UC. Clinically, physicians should weigh the merits of these approaches to maximize the survival benefits of eligible patients