Evolution of pore structure, submaceral composition and produced gases of two Chinese coals during thermal treatment

This research was funded by the Research Program for Excellent Doctoral Dissertation Supervisor of Beijing (grant no. YB20101141501), the Fundamental Research Funds for Central Universities (grant no. 35832015136) and Key Project of Coal-based Science and Technology in Shanxi Province-CBM accumulation model and reservoir evaluation in Shanxi province (grant no. MQ2014-01).Peer reviewedPostprin

Modeling Paying Behavior in Game Social Networks

Online gaming is one of the largest industries on the Internet, generating tens of billions of dollars in revenues annually. One core problem in online game is to find and convert free users into paying customers, which is of great importance for the sustainable development of almost all online games. Although much research has been conducted, there are still several challenges that remain largely unsolved: What are the fundamental factors that trigger the users to pay? How does users? paying behavior influence each other in the game social network? How to design a prediction model to recognize those potential users who are likely to pay? In this paper, employing two large online games as the basis, we study how a user becomes a new paying user in the games. In particular, we examine how users' paying behavior influences each other in the game social network. We study this problem from various sociological perspectives including strong/weak ties, social structural diversity and social influence. Based on the discovered patterns, we propose a learning framework to predict potential new payers. The framework can learn a model using features associated with users and then use the social relationships between users to refine the learned model. We test the proposed framework using nearly 50 billion user activities from two real games. Our experiments show that the proposed framework significantly improves the prediction accuracy by up to 3-11% compared to several alternative methods. The study also unveils several intriguing social phenomena from the data. For example, influence indeed exists among users for the paying behavior. The likelihood of a user becoming a new paying user is 5 times higher than chance when he has 5 paying neighbors of strong tie. We have deployed the proposed algorithm into the game, and the Lift_Ratio has been improved up to 196% compared to the prior strategy

Suppression of experimental arthritis through AMP-activated protein kinase activation and autophagy modulation

Autophagy plays a central role in various disease processes. However, its contribution to inflammatory arthritides such as rheumatoid arthritis (RA) is unclear. We observed that autophagy is engaged in the K/BxN serum transfer model of RA but autophagic flux is severely impaired. Metformin is an anti-diabetic drug that has been shown to stimulate autophagy. Induction of autophagic flux, through metformin-mediated AMP-activated protein kinase (AMPK) activation and interruption of mammalian target of rapamycin (mTOR) signaling mitigated the inflammation in experimental arthritis. Further investigation into the effects of metformin suggest that the drug directly activates AMPK and dose-dependently suppressed the release of TNF-α, IL-6, and MCP-1 by macrophages while enhancing the release of IL-10 in vitro. In vivo, metformin treatment significantly suppressed clinical arthritis and inflammatory cytokine production. Mechanistic studies suggest that metformin exerts its anti-inflammatory effects by correcting the impaired autophagic flux observed in the K/BxN arthritis model and suppressing NF-κB-mediated signaling through selective degradation of IκB kinase (IKK). These findings establish a central role for autophagy in inflammatory arthritis and argue that autophagy modulators such as metformin may represent potential therapeutic agents for the treatment of RA

2,2′,2′′,2′′′-[Pyridine-2,6-diylbis(methyl­ene­nitrilo)]tetra­ethanol

In the crystal structure of the title compound C15H27N3O4, the mol­ecule is located on a twofold axis and the asymmetric unit contains one half-mol­ecule, with one N and one C atom lying on the rotation axis. The pyridine ring is the hydrogen-bond acceptor, while two hydroxyl O atoms act as hydrogen-bond donors in intra­molecular O—H⋯N and intermolecular O—H⋯N and O—H⋯O hydrogen bonds, thereby forming a closed hydrogen-bonded cage

3,5-Dinitro­pyridin-4(1H)-one monohydrate

The three independent organic mol­ecules of 3,5-dinitro­pyridin-4(1H)-one monohydrate, C5H3N3O5·H2O, each feature an N—H⋯Owater hydrogen bond. Each water mol­ecule serves as hydrogen-bond donor to two carbonyl O atoms; these hydrogen bonds give rise to a layer motif. Two of the three formula units lie on special positions of site symmetry 2

Independent markers of nonalcoholic fatty liver disease in a gentrifying population‐based Chinese cohort

BackgroundPrevalence of nonalcoholic fatty liver disease (NAFLD) is increasing in developing countries, but its causes are not known. We aimed to ascertain the prevalence and determinants of NAFLD in a new largely unmedicated population‐based cohort from the rapidly gentrifying region of Pinggu, China.MethodsWe randomized cluster sampled 4002 Pinggu residents aged 26 to 76 years. Data from 1238 men and 1928 women without significant alcohol drinking or hepatitis virus B or C infection were analysed. NAFLD was defined using a liver‐spleen ratio (L/S ratio) ≤1.1 on unenhanced abdominal computed tomography (CT) scanning.ResultsOf men and women, 26.5% and 20.1%, respectively, had NAFLD. NAFLD prevalence was highest in younger men and older women. In multivariate logistic regression models, higher body mass index, waist circumference, serum triglyceride, alanine transaminase, and haemoglobin A1c independently increased the odds of NAFLD in both men and women separately. Higher annual household income and systolic blood pressure for men and higher serum uric acid and red meat intake and lower physical activity levels for women also independently associated with higher odds of NAFLD. Individuals with L/S ratio ≤1.1 had linearly increasing rates of obesity, diabetes, and metabolic syndrome that paralleled fatty liver increase.ConclusionsNAFLD is common in a gentrifying Chinese population particularly in younger men of high socioeconomic status and older women with sedentary behaviour who eat red meat. Demographic factors add independent risk of NAFLD above traditional metabolic risk factors. A CT L/S ratio of ≤1.1 identifies individuals at high risk of metabolic disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149708/1/dmrr3156_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149708/2/dmrr3156.pd

RNA-seq-based digital gene expression analysis reveals modification of host defense responses by rice stripe virus during disease symptom development in Arabidopsis

DEGs involved in protein phosphorylation at 14 dpi. (XLSX 52 kb

A Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare

Reinforcement learning (RL) has emerged as a powerful approach for tackling complex medical decision-making problems such as treatment planning, personalized medicine, and optimizing the scheduling of surgeries and appointments. It has gained significant attention in the field of Natural Language Processing (NLP) due to its ability to learn optimal strategies for tasks such as dialogue systems, machine translation, and question-answering. This paper presents a review of the RL techniques in NLP, highlighting key advancements, challenges, and applications in healthcare. The review begins by visualizing a roadmap of machine learning and its applications in healthcare. And then it explores the integration of RL with NLP tasks. We examined dialogue systems where RL enables the learning of conversational strategies, RL-based machine translation models, question-answering systems, text summarization, and information extraction. Additionally, ethical considerations and biases in RL-NLP systems are addressed