Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Methods for Estimating Relationships in the Change Between Two Time Points for Latent Variables

Collection and analysis of longitudinal data is an important tool in understanding growth and development over time in a whole range of human endeavors. Ideally, researchers working in the longitudinal framework are able to collect data at more than two points in time, as this will provide them with the potential for a deeper understanding of the development processes under study and a much broader array of statistical modeling options. However, in some circumstances data collection is limited to only two time points, perhaps because of resource limitations, issues with the context in which the data are collected, or the nature of the trait under study. In such instances, researchers may still want to learn about complex relationships in the data, such as the correlation between changes in latent traits that are being measured. However, with only two data points, standard approaches for modeling such relationships, such as growth curve modeling, cannot be used. The current simulation study compares the performance of two methods for estimating the correlations among changes in latent variables between two points in time, the two-wave latent change score model and the latent difference factor model. Results of the simulation study showed that both methods yielded generally accurate estimates of the correlation between changes in a latent trait, with relatively small standard errors. Estimation bias and standard errors were lower with larger samples, larger factor loading magnitudes, and more indicators per factor. Further comparisons between the methods and implications of these results are discussed.
EVOLUTION OF A QUASI-STATIONARY STATE

To elucidate the time development of quasi-stationary states. a simple barrier penetrat'on problem has been studied. Both approximate expressions and numerical results for some parameters were obtained for the decay rate. First. irregular oscillations occur for a short time. Second, the exponential region follows. Third. further oscillations occur during which the decay rate dips to negative values. so that the probability of finding the undecayed system increases briefly at several times. Fourth and finally. the decay rate decreases like an inverse power of the time. (auth)
Analyzing contentious relationships and outlier genes in phylogenomics

Despite the wealth of evolutionary information available from genomic and transcriptomic data, recalcitrant relationships in phylogenomic studies remain throughout the tree of life. Recent studies have demonstrated that conflict is common among gene trees, and less than one percent of genes may ultimately drive species tree inference. In this study, we examined a plant and a vertebrate dataset where supermatrix and coalescent-based species trees conflict. Using a two-topology site-specific log-likelihood test, we identified two highly influential genes in each dataset. While the outlier genes in the vertebrate dataset have been shown to be the result of errors in orthology detection, we demonstrate that the outlier genes from the plant dataset may be the result of biological processes rather than model or methodological errors. When the outlier genes were removed from each supermatrix, the inferred trees matched the topologies obtained from coalescent analyses. While most tests of this nature limit the comparison to two trees, gene tree topologies generated under processes such as incomplete lineage sorting are unlikely to precisely match either topology in a two-topology test. We therefore examined bipartitions across a set of trees and recover more support for the resolution favored by coalescent analyses. These results suggest that by expanding beyond two-topology comparisons, we can dramatically improve our understanding of the underlying signal in phylogenomic datasets by asking more targeted edge-based questions.
An Open Source Emotional Speech Corpus for Human Robot Interaction Applications

For further understanding the wide array of emotions embedded in human speech, we are introducing a strictly-guided simulated emotional speech corpus. In contrast to existing speech corpora, this was constructed by maintaining an equal distribution of 4 long vowels in New Zealand English. This balance is to facilitate emotion related formant and glottal source feature comparison studies. Also, the corpus has 5 secondary emotions and 5 primary emotions. Secondary emotions are important in Human-Robot Interaction (HRI) to model natural conversations among humans and robots. But there are few existing speech resources to study these emotions, which has motivated the creation of this corpus. A large scale perception test with 120 participants showed that the corpus has approximately 70% and 40% accuracy in the correct classiﬁcation of primary and secondary emotions respectively. The reasons behind the differences in perception accuracies of the two emotion types is further investigated. A preliminary prosodic analysis of corpus shows signiﬁcant differences among the emotions. The corpus is made public at: github.com/tli725/JL-Corpus.
Triclustering Algorithms for Three-Dimensional Data Analysis

Three-dimensional data are increasingly prevalent across biomedical and social domains. Notable examples are gene-sample-time, individual-feature-time, or node-node-time data, generally referred to as observation-attribute-context data. The unsupervised analysis of three-dimensional data can be pursued to discover putative biological modules, disease progression profiles, and communities of individuals with coherent behavior, among other patterns of interest. It is thus key to enhance the understanding of complex biological, individual, and societal systems. In this context, although clustering can be applied to group observations, its relevance is limited since observations in three-dimensional data domains are typically only meaningfully correlated on subspaces of the overall space. Biclustering tackles this challenge but disregards the third dimension. In this scenario, triclustering—the discovery of coherent subspaces within three-dimensional data—has been largely researched to tackle these problems. Despite the diversity of contributions in this field, there still lacks a structured view on the major requirements of triclustering, desirable forms of homogeneity (including coherency, structure, quality, locality, and orthonormality criteria), and algorithmic approaches. This work formalizes the triclustering task and its scope, introduces a taxonomy to categorize the contributions in the field, provides a comprehensive comparison of state-of-the-art triclustering algorithms according to their behavior and output, and lists relevant real-world applications. Finally, it highlights challenges and opportunities to advance the field of triclustering and its applicability to complex three-dimensional data analysis.
From Numbers to Words: Reporting Statistical Results for the Social Sciences

Preface. Acknowledgements. 1. How to Use This Book. What This Book Is.and Is Not. Overview of the Book. What You Should Do if a Statistic of Interest Is Not Included. Writing for Publication. 2. Frequently Asked Questions About Reporting Statistics. What Is a Research Report? What Is a Results Section? What Should I Include in a Results Section? What Are Developing Trends in Reporting Results? What Is a Manipulation Check and How Should I Report It? How Should I Report the Results of the Test of My Hypotheses? What Exactly Should I Report in My Results Section? What Format Should I Use to Report Significance Levels(p value)? What if My Test Is Not Significant? "Are" or "Were" My Results Significant? What Is an "Effect Size" Indicator? Do I Have to Report the Effect Size? How Do I Report Effect Size? How Do I use Greek Symbols? Should Tables Be Used? If I Use Tables, Where Do I Put Them? Conclusion. 3. Descriptive Information. Frequencies and Percentages. Mean and Standard Deviation. 4. Reliabilities. Interitem: Cronbach's Alpha. Interrater. 5. Correlation. Correlation. 6. Nonparametric Statistics. Chi-Square Tests. Wilcoxon Rank Sum Test/ Mann-Whitney U Test. Kruskal-Wallis Test. McNemar's Repeated Measures Test. Cochran's Q. Wilcoxon Signed-Rank Test. Friedman Analysis of Variance by Ranks. 7. Parametric Statistics. z Test. t Test. Analysis of Variance (ANOVA). ANCOVA. Multivariate Analysis of Variance (MANOVA). MANCOVA. Regression and Multiple Regression. 8. Presenting Results Visually. Using Tables. Constructing Tables. Using Charts, Graphs, and Figures. Conclusion. 9. Conclusion. References. Summary Charts of Statistical Tests, What to Report, Abbreviations, and Suggested Syntax.
Communication Theories: Origins, Methods and Uses in the Mass Media

I. THE CHANGING MEDIA LANDSCAPE. 1. Introduction to Mass Communication Theory. II. SCIENTIFIC METHOD AND MODELS OF MASS COMMUNICATION. 2. Scientific Method. 3. Models in Mass Communication Research. III. PERCEPTION AND LANGUAGE ISSUES IN THE MASS MEDIA. 4. The Role of Perception in Communication. 5. Problems in Encoding. 6. Analysis of Propaganda: First Theories of Decoding and Effects. IV. THE SOCIAL-PSYCHOLOGICAL APPROACH. 7. Cognitive Consistency and Mass Communication. 8. Theories of Persuasion. 9. Groups and Communication. 10. Mass Media and Interpersonal Communication. V. MASS MEDIA EFFECTS AND USES. 11. Agenda Setting. 12. The Knowledge-Gap Hypothesis. 13. Effects of Mass Communication. 14. Uses of the Mass Media. VI. MEDIA CHANNELS. 15. Mass Media in Modern Society. 16. Media Chains and Conglomerates. 17. Theories of Cyber Communication. VII. BRINGING IT ALL TOGETHER. 18. The Overall Picture.
Woody Regeneration Response to Overstory Mortality Caused by the Hemlock Woolly Adelgid (Adelges tsugae) in the Southern Appalachian Mountains

Adelges tsugae Annand (hemlock woolly adelgid, HWA, an invasive insect native to Japan), which causes defoliation and death of Tsuga canadensis (L.) Carrière (eastern hemlock), was introduced to the United States in the early 1950s and has spread throughout much of the range of T. canadensis causing widespread mortality. In 2016 and 2017, we resampled long-term vegetation monitoring plots across five forest types (ecogroups) within Great Smoky Mountains National Park that contained T. canadensis in 2003 (prior to the spread of HWA within the park) to examine changes in the species composition and diversity of the regeneration layer. We hypothesized that compositional changes in the seedling and sapling strata would be driven primarily by the pre-HWA importance value of T. canadensis and relative dominance of Rhododendron maximum L. (rosebay rhododendron), and that species diversity metrics would differ across year depending on ecogroup and the relative dominance of R. maximum. Non-metric multi-dimensional scaling (NMDS) revealed that the seedling and sapling strata of plots with greater pre-HWA importance of T. canadensis and lower basal area of R. maximum generally exhibited greater compositional change between 2003 and 2017. Topo-edaphic variables were also significant in both NMDS ordinations and were associated with the distribution of multiple hardwood species. Species richness, evenness, and Shannon-Wiener diversity varied with strata following the loss of T. canadensis, with the degree and direction of change varying with the dominance of R. maximum.
Handbook of Research Methods in Social and Personality Psychology: Author Index

Introduction to the second edition Harry T. Reis and Charles M. Judd 1. Scratch an itch with a brick: why we do research Susan T. Fiske Part I. Design and Inference Considerations: 2. Research design and issues of validity Marilynn B. Brewer and William D. Crano 3. Research design Eliot R. Smith 4. Causal inference and generalization in field settings: experimental and quasi-experimental designs Stephen G. West, Heining Cham and Yu Liu 5. Field research methods Elizabeth Levy Paluck and Robert B. Cialdini Part II. Procedural Possibilities: 6. Using physiological indexes in social psychological research Jim Blascovich 7. Research methods in social and affective neuroscience Eliot T. Berkman, William A. Cunningham and Matthew D. Lieberman 8. Behavior genetic research methods: testing quasi-causal hypotheses using multivariate twin data Erica Turkheimer and K. Paige Harden 9. Methods of small group research Norbert L. Kerr and R. Scott Tindale 10. Inducing and measuring emotion and affect: tips, tricks, and secrets Karen S. Quigley, Kristen A. Lindquist and Lisa Feldman Barrett 11. Complex dynamical systems in social and personality psychology: theory, modeling, and analysis Michael J. Richardson, Rick Dale and Kerry L. Marsh 12. Implicit measures in social and personality psychology Bertram Gawronski and Jan De Houwer 13. The mind in the middle: a practical guide to priming and automaticity research John A. Bargh and Tanya L. Chartrand 14. Behavioral observation and coding Richard E. Heyman, Michael F. Lorber, J. Mark Eddy and Tessa V. West 15. Methods for studying everyday experience in its natural context Harry T. Reis, Shelley L. Gable and Michael R. Maniaci 16. Survey research Jon A. Krosnick, Paul L. Lavrakas and Nuri Kim 17. Conducting research on the Internet Michael R. Maniaci and Ronald D. Rogge Part III. Data Analytic Strategies: 18. Measurement, reliability, construct validation, and scale construction Oliver P. John and Veronica Benet-Martinez 19. Exploring causal and noncausal hypotheses in nonexperimental data Leandre R. Fabrigar and Duane T. Wegener 20. Advanced psychometrics: confirmatory factor analysis, item response theory, and the study of measurement invariance Keith F. Widaman and Kevin J. Grimm 21. Multilevel and longitudinal modeling Alexander M. Schoemann, Mijke Rhemtulla and Todd D. Little 22. The design and analysis of data from dyads and groups David A. Kenny and Deborah A. Kashy 23. Nasty data: unruly, ill-mannered observations can ruin your analysis Gary H. McClelland 24. Missing data analysis Gina L. Mazza and Craig K. Enders 25. Meditation and moderation Charles M. Judd, Vincent Y. Yzerbyt and Dominique Muller 26. Meta-analysis of research in social and personality psychology Blair T. Johnson and Alice H. Eagly.
Role of 24-Hour Intraocular Pressure Monitoring in Glaucoma Management

Glaucoma is the leading cause of irreversible blindness worldwide and the prevalence is on the rising trend. Intraocular pressure (IOP) reduction is the mainstay of treatment. The current practice of IOP monitoring is based on spot measurements during clinic visits during office hours. However, there are up to 50% of glaucoma patients who had normal initial IOP, while some treated patients continued to have progressive glaucomatous optic nerve damage even with a low IOP. Recent studies have shown that the IOP of glaucoma patients fluctuated during the day with different patterns, and some of them had peak IOP outside office hours. These findings provided us with new insights on the role of 24-hour IOP monitoring in managing normal tension glaucoma and patients with progressive deterioration despite apparently well-controlled IOP. Nevertheless, results to date are rather inconsistent, and there is no consensus yet. In this review, we briefly highlighted the current modalities of 24-hour IOP monitoring and summarized the characteristic 24-hour IOP pattern and the clinical relevance of IOP parameters in predicting glaucomatous progression in different glaucoma subtypes. We also discussed the therapeutic efficacy of current glaucoma treatment modalities with respect to the mentioned 24-hour IOP profiles, so as to strengthen the role of 24-hour IOP monitoring in identifying and stratifying the risks of progression in glaucoma patients, as well as optimizing treatments according to their IOP profiles.
Fg-index: towards verification-free query processing on graph databases

Graphs are prevalently used to model the relationships between objects in various domains. With the increasing usage of graph databases, it has become more and more demanding to efficiently process graph queries. Querying graph databases is costly since it involves subgraph isomorphism testing, which is an NP-complete problem. In recent years, some effective graph indexes have been proposed to first obtain a candidate answer set by filtering part of the false results and then perform verification on each candidate by checking subgraph isomorphism. Query performance is improved since the number of subgraph isomorphism tests is reduced. However, candidate verification is still inevitable, which can be expensive when the size of the candidate answer set is large. In this paper, we propose a novel indexing technique that constructs a nested inverted-index, called FG-index, based on the set of Frequent subGraphs (FGs). Given a graph query that is an FG in the database, FG-index returns the exact set of query answers without performing candidate verification. When the query is an infrequent graph, FG-index produces a candidate answer set which is close to the exact answer set. Since an infrequent graph means the graph occurs in only a small number of graphs in the database, the number of subgraph isomorphism tests is small. To ensure that the index fits into the main memory, we propose a new notion of δ-Tolerance Closed Frequent Graphs (δ-TCFGs), which allows us to flexibly tune the size of the index in a parameterized way. Our extensive experiments verify that query processing using FG-index is orders of magnitude more efficient than using the state-of-the-art graph index.
Mature vessel networks in engineered tissue promote graft–host anastomosis and prevent graft thrombosis

Significance Rapid graft revascularization, while critical for graft survival, is often not seen in current grafts due to poor basal vascularization. In the present work, we assessed the effect of engineered vessel network assembly and maturation in pre-vascularized constructs prior to implantation on the dynamics of graft integration and perfusion. Grafts bearing highly complex and mature vessel networks were rapidly invaded by host vasculature, which anastomosed with the engineered vessels, promoting their perfusion and reducing blood clot accumulation in the graft. The implantation of grafts with highly mature engineered vessels promises to improve graft integration with the host vasculature and its overall survival. Graft vascularization remains one of the most critical challenges facing tissue-engineering experts in their attempt to create thick transplantable tissues and organs. In vitro prevascularization of engineered tissues has been suggested to promote rapid anastomosis between the graft and host vasculatures; however, thrombotic events have been reported upon graft implantation. Here, we aimed to determine whether in vitro vessel maturation in transplantable grafts can accelerate vascular integration and graft perfusion and prevent thrombotic events in the grafts. To this end, endothelial cells and fibroblasts were cocultured on 3D scaffolds for 1, 7, or 14 d to form vasculature with different maturation degrees. Monitoring graft–host interactions postimplantation demonstrated that the 14-d in vitro-cultured grafts, bearing more mature and complex vessel networks as indicated by elongated and branched vessel structures, had increased graft–host vessel anastomosis; host vessel penetration into the graft increased approximately eightfold, and graft perfusion increased sixfold. The presence of developed vessel networks prevented clot accumulation in the grafts. Conversely, short-term cultured constructs demonstrated poor vascularization and increased thrombus formation. Elevated expression levels of coagulation factors, von Willebrand factor (vWF), and tissue factor (TF), were demonstrated in constructs bearing less mature vasculature. To conclude, these findings demonstrate the importance of establishing mature and complex vessel networks in engineered tissues before implantation to promote anastomosis with the host and accelerate graft perfusion.
Filaments and striations: anisotropies in observed, supersonic, highly magnetized turbulent clouds

Stars form in highly magnetized, supersonic turbulent molecular clouds. Many of the tools and models that we use to carry out star formation studies rely upon the assumption of cloud isotropy. However, structures like high-density filaments in the presence of magnetic fields and magnetosonic striations introduce anisotropies into the cloud. In this study, we use the two-dimensional power spectrum to perform a systematic analysis of the anisotropies in the column density for a range of Alfvén Mach numbers ($\operatorname{\mathcal {M}_{\text{A}}}=0.1{\! -\! 10}$) and turbulent Mach numbers ($\operatorname{\mathcal {M}}=2{\! -\! 20}$), with 20 high-resolution, three-dimensional turbulent magnetohydrodynamic simulations. We find that for cases with a strong magnetic guide field, corresponding to $\operatorname{\mathcal {M}_{\text{A}}}\lt 1$, and $\operatorname{\mathcal {M}}\lesssim 4$, the anisotropy in the column density is dominated by thin striations aligned with the magnetic field, while for $\operatorname{\mathcal {M}}\gtrsim 4$ the anisotropy is significantly changed by high-density filaments that form perpendicular to the magnetic guide field. Indeed, the strength of the magnetic field controls the degree of anisotropy and whether or not any anisotropy is present, but it is the turbulent motions controlled by $\operatorname{\mathcal {M}}$ that determine which kind of anisotropy dominates the morphology of a cloud.
Prescription stimulant use among young adult college students: Who uses, why, and what are the consequences?

Abstract Objective To examine prescription stimulant use among college students, particularly use with versus without prescriptions or attention deficit hyperactive disorder (attention-deficit/hyperactivitydisorder (ADHD)) diagnoses. Participants: Data were drawn from a diverse sample of college students from seven colleges/universities in Georgia participating. Methods: Measures assessed ADHD-specific factors, prescription stimulant use, access, motives, side effects, and covariates. Results: Of the 219 students reporting prescription stimulant use (average age 20.72 years, 54.8% female, 82.1% White), 45.7% did not have prescriptions or ADHD diagnoses. Correlates of use without prescriptions/diagnoses included lower parental education, attending private school, not having depression- or anxiety-related diagnoses, and past 30-day marijuana and tobacco use. Those without prescriptions/diagnoses were more likely to use to stay awake longer, to have more enjoyable time, and to party longer; they also reported fewer adverse side effects. Conclusions: Campuses should educate students about ADHD, facilitate screening and treatment, and emphasize adverse consequences of recreational use.