Radical-Enhanced Chinese Character Embedding

We present a method to leverage radical for learning Chinese character embedding. Radical is a semantic and phonetic component of Chinese character. It plays an important role as characters with the same radical usually have similar semantic meaning and grammatical usage. However, existing Chinese processing algorithms typically regard word or character as the basic unit but ignore the crucial radical information. In this paper, we fill this gap by leveraging radical for learning continuous representation of Chinese character. We develop a dedicated neural architecture to effectively learn character embedding and apply it on Chinese character similarity judgement and Chinese word segmentation. Experiment results show that our radical-enhanced method outperforms existing embedding learning algorithms on both tasks.Comment: 8 pages, 4 figure

Self-Supervised Multi-Modal Sequential Recommendation

With the increasing development of e-commerce and online services, personalized recommendation systems have become crucial for enhancing user satisfaction and driving business revenue. Traditional sequential recommendation methods that rely on explicit item IDs encounter challenges in handling item cold start and domain transfer problems. Recent approaches have attempted to use modal features associated with items as a replacement for item IDs, enabling the transfer of learned knowledge across different datasets. However, these methods typically calculate the correlation between the model's output and item embeddings, which may suffer from inconsistencies between high-level feature vectors and low-level feature embeddings, thereby hindering further model learning. To address this issue, we propose a dual-tower retrieval architecture for sequence recommendation. In this architecture, the predicted embedding from the user encoder is used to retrieve the generated embedding from the item encoder, thereby alleviating the issue of inconsistent feature levels. Moreover, in order to further improve the retrieval performance of the model, we also propose a self-supervised multi-modal pretraining method inspired by the consistency property of contrastive learning. This pretraining method enables the model to align various feature combinations of items, thereby effectively generalizing to diverse datasets with different item features. We evaluate the proposed method on five publicly available datasets and conduct extensive experiments. The results demonstrate significant performance improvement of our method

A centering correction method for GNSS antenna diversity theory and implementation using a software receiver

GPS is performing well in open sky situation. However, severe attenuation or blockage of signals by high buildings may leads to an insufficient number of received satellites. Antenna diversity scheme is viewed as a method to alleviate signal attenuation and enhance the performance of GNSS positioning in the harsh environments. This paper introduces an antenna diversity system, composed of two spatially separated antennas. If relative geometry of two antennas is known, the carrier phase measurement outputs from these two antennas can be combined with Centering Correction Method (CCM). Even each antenna may not able to acquire more than four satellites this antenna diversity system can still precisely estimate each antenna’s location with centimeter-level accuracy, as long as the sum of the captured satellites by two separate antennas is no less than four

An Optimal Rate Control and Routing Scheme for Multipath Networks

This paper considers optimal rate control and routing schemes for multipath networks which can be formulated as multipath network utility maximization problems. In these schemes, maximizing the aggregated user utility over the network with multipath routes under the link capacity constraints is the objective of utility maximization problems. By adopting the Lagrangian method, sub-problems for users and paths are deduced and interpreted from an economic point of view. In order to obtain the optimal rate allocation, a novel distributed primal-dual algorithm is proposed, and the performance is evaluated through simulations under two different fairness concepts. Moreover, window-based flow control scheme is also presented since it is more convenient to realize in practical end-to-end implementation than the rate control scheme

Molecular and biochemical investigations of the anti-fatigue effects of tea polyphenols and fruit extracts of Lycium ruthenicum Murr. on mice with exercise-induced fatigue

Background: The molecular mechanisms regulating the therapeutic effects of plant-based ingredients on the exercise-induced fatigue (EIF) remain unclear. The therapeutic effects of both tea polyphenols (TP) and fruit extracts of Lycium ruthenicum (LR) on mouse model of EIF were investigated.Methods: The variations in the fatigue-related biochemical factors, i.e., lactate dehydrogenase (LDH), superoxide dismutase (SOD), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-2 (IL-2), and interleukin-6 (IL-6), in mouse models of EIF treated with TP and LR were determined. The microRNAs involved in the therapeutic effects of TP and LR on the treatment of mice with EIF were identified using the next-generation sequencing technology.Results: Our results revealed that both TP and LR showed evident anti-inflammatory effect and reduced oxidative stress. In comparison with the control groups, the contents of LDH, TNF-α, IL-6, IL-1β, and IL-2 were significantly decreased and the contents of SOD were significantly increased in the experimental groups treated with either TP or LR. A total of 23 microRNAs (21 upregulated and 2 downregulated) identified for the first time by the high-throughput RNA sequencing were involved in the molecular response to EIF in mice treated with TP and LR. The regulatory functions of these microRNAs in the pathogenesis of EIF in mice were further explored based on Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses with a total of over 20,000–30,000 target genes annotated and 44 metabolic pathways enriched in the experimental groups based on GO and KEGG databases, respectively.Conclusion: Our study revealed the therapeutic effects of TP and LR and identified the microRNAs involved in the molecular mechanisms regulating the EIF in mice, providing strong experimental evidence to support further agricultural development of LR as well as the investigations and applications of TP and LR in the treatment of EIF in humans, including the professional athletes

The association between serum phosphorus and common carotid artery intima–media thickness in ischemic stroke patients

PurposeAn elevated concentration of phosphorus is associated with an increased risk of atherosclerosis and cardiovascular diseases. Common carotid artery intima–media thickness (cIMT) is an imaging marker of atherosclerosis. However, data on the relationship between phosphorus and cIMT in ischemic stroke are scarce. We aimed to evaluate the association between serum phosphorus levels and cIMT in patients who had experienced ischemic stroke.Patients and methodsA total of 1,450 ischemic stroke patients were enrolled. Participants were divided into four groups (quartiles) according to baseline serum phosphorus level. Carotid atherosclerosis was identified by measurement of cIMT; abnormal cIMT was defined as a maximum cIMT or mean cIMT ≥ 1 mm. Multivariable logistic regression models were used to assess the association between serum phosphorus level and the presence of abnormal cIMT.ResultsIn the multivariable adjusted analysis, falling into the highest quartile for serum phosphorus (Q4) was associated with a 2.00-fold increased risk of having abnormal maximum cIMT [adjusted odds ratio (OR) 2.00; 95% confidence interval (CI) 1.44–2.79] and a 1.76-fold increased risk of having abnormal mean cIMT (adjusted OR 1.76; 95% CI 1.22–2.53) in comparison to Q1. Furthermore, the association between serum phosphorus and abnormal cIMT was confirmed in analyses treating serum phosphorus as a continuous variable and in subgroup analyses.ConclusionIn acute ischemic stroke patients, baseline elevated serum phosphorus level was found to be independently associated with carotid atherosclerosis, as measured by cIMT

A guideline for economic evaluations of vaccines and immunization programs in China.

This study aimed to develop a consensus framework for economic evaluations of vaccines as a national guideline in China. Some unique and important aspects were particularly emphasized. Nineteen Chinese experts in the field of health economics and immunization decision-making were nominated to select and discuss relevant aspects of vaccine economic evaluations in China. A workshop attended by external experts was held to summarize unique and important aspects and formulate consensus recommendations. There were ten unique and/or important aspects identified for economic evaluations of vaccines in China, including study perspectives, comparator strategies, analysis types, model choices, costing approaches, utility measures, discounting, uncertainty, equity, and evaluation purposes. Background information and expert recommendations were provided for each aspect. Economic evaluations of vaccines should play an important role in China's immunization policy-making. This guideline can help improve the quality of economic evaluations as a good practice consensus

Pleiotropic genes for metabolic syndrome and inflammation

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation