Enhancing Topic Extraction in Recommender Systems with Entropy Regularization

In recent years, many recommender systems have utilized textual data for topic extraction to enhance interpretability. However, our findings reveal a noticeable deficiency in the coherence of keywords within topics, resulting in low explainability of the model. This paper introduces a novel approach called entropy regularization to address the issue, leading to more interpretable topics extracted from recommender systems, while ensuring that the performance of the primary task stays competitively strong. The effectiveness of the strategy is validated through experiments on a variation of the probabilistic matrix factorization model that utilizes textual data to extract item embeddings. The experiment results show a significant improvement in topic coherence, which is quantified by cosine similarity on word embeddings

A Novel Perspective to Look At Attention: Bi-level Attention-based Explainable Topic Modeling for News Classification

Many recent deep learning-based solutions have widely adopted the attention-based mechanism in various tasks of the NLP discipline. However, the inherent characteristics of deep learning models and the flexibility of the attention mechanism increase the models' complexity, thus leading to challenges in model explainability. In this paper, to address this challenge, we propose a novel practical framework by utilizing a two-tier attention architecture to decouple the complexity of explanation and the decision-making process. We apply it in the context of a news article classification task. The experiments on two large-scaled news corpora demonstrate that the proposed model can achieve competitive performance with many state-of-the-art alternatives and illustrate its appropriateness from an explainability perspective.Comment: Findings of ACL202

Topic-Centric Explanations for News Recommendation

News recommender systems (NRS) have been widely applied for online news websites to help users find relevant articles based on their interests. Recent methods have demonstrated considerable success in terms of recommendation performance. However, the lack of explanation for these recommendations can lead to mistrust among users and lack of acceptance of recommendations. To address this issue, we propose a new explainable news model to construct a topic-aware explainable recommendation approach that can both accurately identify relevant articles and explain why they have been recommended, using information from associated topics. Additionally, our model incorporates two coherence metrics applied to assess topic quality, providing measure of the interpretability of these explanations. The results of our experiments on the MIND dataset indicate that the proposed explainable NRS outperforms several other baseline systems, while it is also capable of producing interpretable topics compared to those generated by a classical LDA topic model. Furthermore, we present a case study through a real-world example showcasing the usefulness of our NRS for generating explanations.Comment: 20 pages, submitted to a journa

Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations

Precisely recommending candidate news articles to users has always been a core challenge for personalized news recommendation systems. Most recent works primarily focus on using advanced natural language processing techniques to extract semantic information from rich textual data, employing content-based methods derived from local historical news. However, this approach lacks a global perspective, failing to account for users' hidden motivations and behaviors beyond semantic information. To address this challenge, we propose a novel model called GLORY (Global-LOcal news Recommendation sYstem), which combines global representations learned from other users with local representations to enhance personalized recommendation systems. We accomplish this by constructing a Global-aware Historical News Encoder, which includes a global news graph and employs gated graph neural networks to enrich news representations, thereby fusing historical news representations by a historical news aggregator. Similarly, we extend this approach to a Global Candidate News Encoder, utilizing a global entity graph and a candidate news aggregator to enhance candidate news representation. Evaluation results on two public news datasets demonstrate that our method outperforms existing approaches. Furthermore, our model offers more diverse recommendations.Comment: 10 pages, Recsys 202

Blood-coated sensor for high-throughput ptychographic cytometry on a Blu-ray disc

Blu-ray drive is an engineering masterpiece that integrates disc rotation, pickup head translation, and three lasers in a compact and portable format. Here we integrate a blood-coated image sensor with a modified Blu-ray drive for high-throughput cytometric analysis of various bio-specimens. In this device, samples are mounted on the rotating Blu-ray disc and illuminated by the built-in lasers from the pickup head. The resulting coherent diffraction patterns are then recorded by the blood-coated image sensor. The rich spatial features of the blood-cell monolayer help down-modulate the object information for sensor detection, thus forming a high-resolution computational bio-lens with a theoretically unlimited field of view. With the acquired data, we develop a lensless coherent diffraction imaging modality termed rotational ptychography for image reconstruction. We show that our device can resolve the 435 nm linewidth on the resolution target and has a field of view only limited by the size of the Blu-ray disc. To demonstrate its applications, we perform high-throughput urinalysis by locating disease-related calcium oxalate crystals over the entire microscope slide. We also quantify different types of cells on a blood smear with an acquisition speed of ~10,000 cells per second. For in vitro experiment, we monitor live bacterial cultures over the entire Petri dish with single-cell resolution. Using biological cells as a computational lens could enable new intriguing imaging devices for point-of-care diagnostics. Modifying a Blu-ray drive with the blood-coated sensor further allows the spread of high-throughput optical microscopy from well-equipped laboratories to citizen scientists worldwide

Status of cardiovascular health among adults in a rural area of Northwest China: Results from a cross-sectional study.

The aim of this study was to assess the status of cardiovascular health among a rural population in Northwest China and to determine the associated factors for cardiovascular health.A population-based cross-sectional study was conducted in the rural areas of Hanzhong in Northwest China. Interview, physical examination, and fasting blood glucose and lipid measurements were completed for 2693 adults. The construct of cardiovascular health and the definitions of cardiovascular health metrics proposed by the American Heart Association were used to assess cardiovascular health. The proportions of subjects with cardiovascular health metrics were calculated, adjusting for age and sex. The multiple logistic regression model was used to evaluate the association between ideal cardiovascular health and its associated factors.Only 0.5% (0.0% in men vs 0.9% in women, P = 0.002) of the participants had ideal cardiovascular health, whereas 33.8% (18.0% in men vs 50.0% in women, P < 0.001) and 65.7% (82.0% in men vs 49.1% in women, P < 0.001) of the participants had intermediate and poor cardiovascular health, respectively. The prevalence of poor cardiovascular health increased with increasing age (P < 0.001 for trend). Participants fulfilled, on average, 4.4 (95% confidence interval: 4.2-4.7) of the ideal cardiovascular health metrics. Also, 22.2% of the participants presented with 3 or fewer ideal metrics. Only 19.4% of the participants presented with 6 or more ideal metrics. 24.1% of the participants had all 4 ideal health factors, but only 1.1% of the participants had all 4 ideal health behaviors. Women were more likely to have ideal cardiovascular health, whereas adults aged 35 years or over and those who had a family history of hypertension were less likely to have ideal cardiovascular health.The prevalence of ideal cardiovascular health was extremely low among the rural population in Northwest China. Most adults, especially men and the elderly, had a poor cardiovascular health status. To improve cardiovascular health among the rural population, efforts, especially lifestyle improvements, education and interventions to make healthier food choices, reduce salt intake, increase physical activities, and cease smoking, will be required at the individual, population, and social levels

An improved model to estimate trapping parameters in polymeric materials and its application on normal and aged low-density polyethylenes

Trapping parameters can be considered as one of the important attributes to describe polymeric materials. In the present paper, a more accurate charge dynamics model has been developed, which takes account of charge dynamics in both volts-on and off stage into simulation. By fitting with measured charge data with the highest R-square value, trapping parameters together with injection barrier of both normal and aged low-density polyethylene samples were estimated using the improved model. The results show that, after long-term ageing process, the injection barriers of both electrons and holes is lowered, overall trap depth is shallower, and trap density becomes much greater. Additionally, the changes in parameters for electrons are more sensitive than those of holes after ageing

Global land surface temperature influenced by vegetation cover and PM2.5 from 2001 to 2016

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 �g/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72�N and 48�S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature

Synchronization Time Division Multiplexing Bus Communication Method Using Serial Communication Interface

It provided a synchronization time division multiplexing bus communication method using serial communication interface, in which input and output data lines of a host and several slaves being connected with the bus. Then the detailed communication mode was stated. The method could be applied in all MCU, meanwhile meets the requirements of high speed for the real time performance, and solves the problem of bus communication between internal modules of a device and realizes controllable communication real time performance, reduced hardware circuit complexity as well as enhanced universality and reliability

Phytochemical and antiproliferative activity of proso millet.

The phytochemical content, antioxidant activity and antiproliferative properties of three diverse varieties of proso millet are reported. The free phenolic content ranged from 27.48 (Gumi 20) to 151.14 (Mi2504-6) mg gallic acid equiv/100 g DW. The bound phenolic content ranged from 55.95 (Gumi20) to 305.81 (Mi2504-6) mg gallic acid equiv/100 g DW. The percentage contribution of bound phenolic to the total phenolic content of genotype samples analyzed ranged between 62.08% and 67.05%. Ferulic acid and chlorogenic acid are the predominant phenolic acid found in bound fraction. Caffeic acid and p-coumaric acid were also detected. Syringic acid was detected only in the free fraction. The antioxidant activity was assessed using the hydrophilic peroxyl radical scavenging capacity (PSC) assay. The PSC antioxidant activity of the free fraction ranged from 57.68 (Mi2504-6) to 147.32 (Gumi20) µmol of vitamin C equiv/100 g DW. The PSC antioxidant activity of the bound fraction ranged from 95.38 (Mizao 52) to 136.48 (Gumi 20) µmol of vitamin C equiv/100 g DW. The cellular antioxidant activity (CAA) of the extract was assessed using the HepG2 model. CAA value ranged from 2.51 to 6.10 µmol equiv quercetin/100 g DW. Antiproliferative activities were also studied in vitro against MDA human breast cancer and HepG2 human liver cancer cells. Results exhibited a differential and possible selective antiproliferative property of the proso millet. These results may be used to direct the consumption of proso millet with improved health properties