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A robust statistical prediction model for late-summer heavy precipitation days in North China

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Science China Earth Sciences 2025年第1期68卷 158-171页

作者： Shunli JIANG Tingting HAN Xin ZHOU Huijun WANG Zhicong YIN Xiaolei SONG Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University for Information Science and Technology Nansen-Zhu International research centre Institute of Atmospheric Physics Chinese Academy of Sciences Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)

Recently, heavy precipitation(HP) events have occurred frequently in North China(NC), causing devastating economic losses and human fatalities. However, the short-term climate prediction of HP is quite limited. Combining year-to-year increment(DY) method and sliding correlations, we developed a robust seasonal prediction model for late-summer HP days(HPDs) in NC during 1982–2022, utilizing three independent predictors—February sea surface temperature(SST) in the Indian Ocean(SST＿IO), February snow depth over North Asia(SDE＿NA), and May melted snow depth in NC(MSDE＿NC). The SST＿IO anomalies affect NC's precipitation through the Pacific-Japan pattern. The SDE＿NA anomalies are associated with East Asian anomalous anticyclone by southeastern propagation of Rossby wave at Eurasia. The MSDE＿NC anomalies are followed by vertical motion and moisture anomalies in situ and thereby cause precipitation anomalies. This prediction model can well simulate the variations of the HPDs, with a correlation coefficient(CC) of 0.81(0.65) between the observed and predicted HPDs＿DY(HPDs＿anomaly). The percentage with the same sign for 15 extreme HPDs＿anomaly years(PSSE) is 100%.Moreover, in the cross-validation test during 1982–2022, the PSSE for HPDs＿anomaly is as high as 100%, along with a low rootmean-square error of 1.14. For independent hindcasts during 2013–2022, the CC between the observed and predicted HPDs＿DY(HPDs＿anomaly) is 0.93(0.83), together with high Nash-Sutcliffe efficiency(0.82) and agreement index(0.89). Specifically, the predictions are broadly consistent with the observations for 2015, 2016, 2017, 2021, and 2022, reflecting excellent performance of this prediction model of HPDs in NC.

关键词： Heavy precipitation at North China Year-to-year increment approach Robust seasonal prediction Sea surface temperature Snow depth

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Bicoid Signal Extraction with a Selection of Parametric and Nonparametric Signal Processing Techniques

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Genomics, Proteomics & Bioinformatics 2015年第3期13卷 183-191页

作者： Zara Ghodsi Emmanuel Sirimal Silva Hossein Hassani the statistical research centre Bournemouth University Institute for International Energy Studies (ⅡES)

The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraetion in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average.

关键词： Bicoid Drosophila melanogaster Signal extraction Signal processing

Gamma/hadron segregation for a ground based imaging atmospheric Cherenkov telescope using machine learning methods: Random Forest leads

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research in Astronomy and Astrophysics 2014年第11期14卷 1491-1503页

作者： Mradul Sharma Jitadeepa Nayak Maharaj Krishna Koul Smarajit Bose Abhas Mitra Astrophysical Sciences Division Bhabha Atomic Research Centre The Bayesian and Interdisciplinary research Unit Indian Statistical Institute

A detailed case study of γ-hadron segregation for a ground based atmo- spheric Cherenkov telescope is presented. We have evaluated and compared various supervised machine learning methods such as the Random Forest method, Artificial Neural Network, Linear Discriminant method, Naive Bayes Classifiers, Support Vector Machines as well as the conventional dynamic supercut method by simulating triggering events with the Monte Carlo method and applied the results to a Cherenkov telescope. It is demonstrated that the Random Forest method is the most sensitive machine learning method for γ-hadron segregation.

关键词： methods statistical -- telescopes

Ridge-Forward Quadratic Discriminant Analysis in High-Dimensional Situations

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Journal of Systems Science & Complexity 2016年第6期29卷 1703-1715页

作者： XIONG Cui ZHANG Jun LUO Xinchao School of Statistics East China Normal University College of Mathematics and Statistics Institute of Statistical SciencesShen Zhen-Hong Kong Joint Research Centre for Applied Statistical SciencesShenzhen University

Quadratic discriminant analysis is a classical and popular classification tool,but it fails to work in high-dimensional situations where the dimension p is larger than the sample size *** address this issue,the authors propose a ridge-forward quadratic discriminant(RFQD) analysis method via screening relevant predictors in a successive manner to reduce misclassification *** authors use extended Bayesian information criterion to determine the final model and prove that RFQD is selection *** Carlo simulations are conducted to examine its performance.

关键词： Extended BIC quadratic discriminant analysis ridge-forward selection consistency.

Major Soil Chemical Properties of the Major Tea-Growing Areas in India

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Pedosphere 2015年第2期25卷 316-328页

作者： Tanmoy KARAK Ranjit Kumar PAUL Romesh Kumar BORUAH Indira SONAR Biswajyoti BORDOLOI Amrit Kumar DUTTA Borsha BORKOTOKY Upper Assam Advisory centre Tea Research Association Division of statistical Genetics Indian Agricultural Statistics Research Institute Arunachal Advisory centre Tea Research AssociationDirectorate of Trade and CommerceGovernment of Arunachal Pradesh

Major chemical properties of tea-growing soils are of paramount importance for better management in a sustainable ***,this study was carried out to understand the major soil chemical properties of major tea(Camellia sinensis L.)-growing areas,Dibrugarh and Tinsukia districts,in the state of Assam,India.A total of 991 surface soil samples were collected from 15 large tea estates(TEs) for analysis of their major chemical *** pH ranged from 3.61 to *** organic carbon and total nitrogen ranged from 2.4 to 47.3 and 0.24 to 3.60 g kg^(-1),*** soils were sufficiently rich in plant-available potassium(as K_2O),which ranged from 127.71 to 252.33 mg kg^(-1),exceeding the amount prescribed for optimum tea yield of > 100 mg kg^(-1).Plant-available sulfur among soil samples widely varied from 4 to 129 mg kg^(-1).Results of hierarchical clustering analysis for homogenous grouping of the 15 TEs based on soil chemical properties showed that the 15 TEs could be classified into three distinct groups which consisted of6,8 and 1 TEs,*** on the Kolmogorov-Smirnov(K-S) test,the best fitted theoretical probability distributions were found out for different soil chemical *** could be concluded that a balanced fertilizer application would be needed as a part of tea improvement program using soil chemical test.

关键词： organic carbon plant-available potassium plant-available sulfur probability distribution soil pH tea estates total nitrogen

Transient chemical-mediated epigenetic modulation confers unrestricted lineage potential on human primed pluripotent stem cells

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Science China Life Sciences 2025年

作者： Shi Chen Yuanyuan He Lejun Lv Bei Liu Cheng Li Hongkui Deng Jun Xu Department of Cell Biology School of Basic Medical Sciences Peking University Stem Cell Research Center Peking University Health Science Center Peking University Academy of Advanced Interdisciplinary Studies Peking University BeiCell Therapeutics School of Life Sciences Center for Bioinformatics Center for Statistical Science Peking University MOE Engineering research Center of Regenerative Medicine School of Basic Medical Sciences State Key Laboratory of Natural and Biomimetic Drugs Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation College of Life Sciences Peking-Tsinghua Center for Life Sciences Peking University

Human primed pluripotent stem cells are capable of generating all the embryonic ***,their extraembryonic trophectoderm potentials are *** remains unclear how to expand their developmental potential to trophectoderm *** we show that transient treatment with a cocktail of small molecule epigenetic modulators imparts trophectoderm lineage potentials to human primed pluripotent stem cells while preserving their embryonic *** chemically treated cells can generate trophectoderm-like cells and downstream trophoblast stem cells,diverging into syncytiotrophoblast and extravillous trophoblast *** and CUT&Tag analyses reveal that these induced cells share transcriptional profiles with in vivo trophectoderm and cytotrophoblast,and exhibit reduced H3K27me3 modification at gene loci specific to trophoblast lineages compared with primed pluripotent *** exploration highlighted the critical roles of epigenetic modulators HDAC2,EZH1/2,and KDM5s in the activation of trophoblast lineage *** findings demonstrate that transient epigenetic resetting activates unrestricted lineage potential in human primed pluripotent stem cells,and offer new mechanistic insights into human trophoblast lineage specification and in vitro models for studying placental development and related disorders.

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I’m Nervous about Sharing This Secret with You:Youtube Influencers Generate Strong Parasocial Interactions by Discussing Personal Issues

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Journal of Data and Information Science 2022年第2期7卷 31-56页

作者： Mike Thelwall Emma Stuart Amalia Mas-Bleda Meiko Makita Mahshid Abdoli statistical Cybermetrics research Group University of WolverhamptonUK

Purpose:Performers may generate loyalty partly through eliciting illusory personal connections with their audience,parasocial relationships(PSRs),and individual illusory exchanges,parasocial interactions(PSIs).On social media,semi-PSIs are real but imbalanced exchanges with audiences,including through comments on influencers’videos,and strong semi-PSIs are those that occur within *** article introduces and assesses an automatic method to detect videos with strong PSI ***/methodology/approach:Strong semi-PSIs were hypothesized to occur when commenters used a variant of the pronoun“you”,typically addressing the *** on the videos of UK female influencer channels were used to test whether the proportion of you pronoun comments could be an automated indicator of strong PSI potential,and to find factors associating with the strong PSI potential of influencer *** highest and lowest strong PSI potential videos for 117 influencers were classified with content analysis for strong PSI potential and evidence of factors that might elicit ***:The you pronoun proportion was effective at indicating video strong PSI potential,the first automated method to detect any type of *** at the camera,head and shoulders framing,discussing personal issues,and focusing on the influencer associated with higher strong PSI potential for influencer *** social media factors found include requesting feedback and discussing the channel *** limitations:Only one country,genre and social media platform was *** implications:The method can be used to automatically detect YouTube videos with strong PSI potential,helping influencers to monitor their ***/value:This is the first automatic method to detect any aspect of PSI or PSR.

关键词： Parasocial interaction Parasocial relationships Influencers YouTube Social media semi-PSI

“My ADHD Hellbrain”: A Twitter Data Science Perspective on a Behavioural Disorder

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Journal of Data and Information Science 2021年第1期6卷 13-34页

作者： Mike Thelwall Meiko Makita Amalia Mas-Bleda Emma Stuart statistical Cybermetrics research Group University of WolverhamptonUK

Purpose: Attention deficit hyperactivity disorder(ADHD) is a common behavioural condition. This article introduces a new data science method, word association thematic analysis, to investigate whether ADHD tweets can give insights into patient concerns and online communication needs. Design/methodology/approach: Tweets matching "my ADHD"(n=58,893) and 99 other conditions(n=1,341,442) were gathered and two thematic analyses conducted. Analysis 1: A standard thematic analysis of ADHD-related tweets. Analysis 2: A word association thematic analysis of themes unique to ***: The themes that emerged from the two analyses included people ascribing their brains agency to explain and justify their symptoms and using the concept of neurodivergence for a positive self-image. research limitations: This is a single case study and the results may differ for other *** implications: Health professionals should be sensitive to patients' needs to understand their behaviour, find ways to justify and explain it to others and to be positive about their ***/value: Word association thematic analysis can give new insights into the(self-reported) patient perspective.

关键词： ADHD Word association thematic analysis Social behaviour Social web Twitter

Male, Female, and Nonbinary Differences in UK Twitter Self-descriptions: A Fine-grained Systematic Exploration

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Journal of Data and Information Science 2021年第2期6卷 1-27页

作者： Mike Thelwall Saheeda Thelwall Ruth Fairclough statistical Cybermetrics research Group University of WolverhamptonUK

Purpose: Although gender identities influence how people present themselves on social media, previous studies have tested pre-specified dimensions of difference, potentially overlooking other differences and ignoring nonbinary ***/methodology/approach: Word association thematic analysis was used to systematically check for fine-grained statistically significant gender differences in Twitter profile descriptions between 409,487 UK-based female, male, and nonbinary users in 2020. A series of statistical tests systematically identified 1,474 differences at the individual word level, and a follow up thematic analysis grouped these words into ***: The results reflect offline variations in interests and in jobs. They also show differences in personal disclosures, as reflected by words, with females mentioning qualifications, relationships, pets, and illnesses much more, nonbinaries discussing sexuality more, and males declaring political and sports affiliations more. Other themes were internally imbalanced, including personal appearance(e.g. male: beardy;female: redhead), selfevaluations(e.g. male: legend;nonbinary: witch;female: feisty), and gender identity(e.g. male: dude;nonbinary: enby;female: queen).research limitations: The methods are affected by linguistic styles and probably underreport nonbinary *** implications: The gender differences found may inform gender theory, and aid social web communicators and ***/value: The results show a much wider range of gender expression differences than previously acknowledged for any social media site.

关键词： Twitter Online self-presentation Gender Nonbinary genders Twitter bios