183 research outputs found
Data & Scripts for Chu et al. (2016) Nature Communications
No full textThis data file includes data and R scripts used to fit the vital rates models and to run simulations (IBM and IPM) for Chu et al. (2016) Nature Communications
Association Between Artificial Intelligence Based Chest Computed Tomography and Clinical/Laboratory Characteristics with Severity and Mortality in COVID-19 Hospitalized Patients
No full textJiawei Ye,1,* Yingying Huang,2,* Caiting Chu,3 Juan Li,1 Guoxiang Liu,1 Wenjie Li,1 Chengjin Gao1 1Department of Emergency Medicine, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People’s Republic of China; 2Dementia Research Centre, Faculty of Medicine, Health and Human Sciences, Macquarie University Sydney, Australia; 3Department of Radiology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chengjin Gao; Wenjie Li, Email [email protected]; [email protected]: Some patients with COVID-19 rapidly develop respiratory failure or mortality, underscoring the necessity for early identification of those prone to severe illness. Numerous studies focus on clinical and lab traits, but only few attend to chest computed tomography. The current study seeks to numerically quantify pulmonary lesions using early-phase CT scans calculated through artificial intelligence algorithms in conjunction with clinical and laboratory helps clinicians to early identify the development of severe illness and death in a group of COVID-19 patients.Methods: From December 15, 2022, to January 30, 2023, 191 confirmed COVID-19 patients admitted to Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine were consecutively enrolled. All patients underwent chest CT scans and serum tests within 48 hours prior to admission. Variables significantly linked to critical illness or mortality in univariate analysis were subjected to multivariate logistic regression models post collinearity assessment. Adjusted odds ratio, 95% confidence intervals, sensitivity, specificity, Youden index, receiver-operator-characteristics (ROC) curves, and area under the curve (AUC) were computed for predicting severity and in-hospital mortality.Results: Multivariate logistic analysis revealed that myoglobin (OR = 1.003, 95% CI 1.001– 1.005), APACHE II score (OR = 1.387, 95% CI 1.216– 1.583), and the infected CT region percentage (OR = 113.897, 95% CI 4.939– 2626.496) independently correlated with in-hospital COVID-19 mortality. Prealbumin stood as an independent safeguarding factor (OR = 0.965, 95% CI 0.947– 0.984). Neutrophil counts (OR = 1.529, 95% CI 1.131– 2.068), urea nitrogen (OR = 1.587, 95% CI 1.222– 2.062), SOFA score(OR = 3.333, 95% CI 1.476– 7.522), qSOFA score(OR = 15.197, 95% CI 3.281– 70.384), PSI score(OR = 1.053, 95% CI 1.018– 1.090), and the infected CT region percentage (OR = 548.221, 95% CI 2.615– 114,953.586) independently linked to COVID-19 patient severity.Keywords: COVID-19, chest CT, artificial intelligence, mortality, severit
Data from: Large niche differences emerge at the recruitment stage to stabilize grassland coexistence
No full textNiche differences and average fitness differences jointly determine coexistence. However, little empirical information about the magnitude of these two mechanisms is available. Using multispecies population models fit to long-term demographic data for common, co-occurring species in five grassland and shrubland plant communities in western North America, we estimated the strength of stabilizing niche differences and average fitness differences. In all five communities, both pairwise and full community comparisons showed evidence for strong stabilizing mechanisms and relatively small average fitness differences. For a total of 17 species pairs, a measure of niche differences based on simulations of invasion growth rates ranged from 0.59 to 0.93 with a mean of 0.81, where 0 indicates complete niche overlap and 1 indicates zero niche overlap. A corresponding measure of average fitness differences ranged from 1.02 to 2.54 with a mean of 1.53, where 1 indicates identical fitness and a value of 2 indicates a four-fold difference in sensitivity to competition. Comparisons of full communities displayed similar patterns: niche differences ranged from 0.58 to 0.69 with a mean of 0.64, and the average fitness differences ranged from 1.42 to 1.63 with a mean of 1.47. In almost every case, the stabilizing mechanisms were much stronger than minimally necessary to prevent competitive exclusion. Considering that all but one of the species we studied are perennial grasses, which are often grouped in the same functional type, the magnitude of these niche differences is surprising. In all five communities, differences between intra- and interspecific effects at the recruitment stage contributed far more to stabilization than interactions affecting growth and survival. Our results indicate that for these abundant, co-occurring species 1) dynamics are far from neutral, with strong niche differences and weak fitness differences combining to stabilize coexistence, and 2) processes operating at early life stages account for a large proportion of the stabilizing effect. Given the limitations of our inductive approach, both these findings represent hypotheses in need of experimental testing
Long-term mapped data and R scripts
No full textThis file includes extracted demographic data used in our paper from five study sites in Western USA. It includes all R scripts for relevant analyses as well, such as conducting model selection and Integral Projection Model
The Use of High Rising Terminals in First- and Second-Generation Mandarin-Background Australians
No full textthe author deposited 22 July 2025This study investigated the use of High Rising Terminals (HRTs)—final rising pitch contours on declarative utterances—among three speaker groups in Australia: first-generation (Gen 1) Mandarin-background Australians, second-generation (Gen 2) Australians from Mandarin-speaking families, and Anglo-Celtic Australians. While HRTs have been widely studied in varieties such as Australian, New Zealand, and American English, their use for ethnolectal purposes remains underexplored. Drawing on spontaneous speech from sociolinguistic interviews, the study examined variation in HRT frequency across ethnic and generational lines, with preliminary analyses of phonetic realisation (rise excursion, rise alignment) and pragmatic function. Results showed that Gen 2 speakers exhibit the highest HRT frequency, followed by Gen 1 speakers, with Anglo speakers showing the lowest usage. A preliminary phonetic and pragmatic analysis revealed that while all groups deploy HRTs for similar discourse functions—such as engagement- and comprehension-checking, turn-holding, stance softening, and epistemic uncertainty—Gen 1 speakers showed greater variation in rise excursion. These findings suggested broad convergence in function but also underlined the role of migration history and identity in shaping suprasegmental patterns. In doing so, the study contributed to the understanding of how prosody, ethnicity, and migrant generation interact in the evolving soundscape of Australian English
Appendix H. Matrices of interaction coefficients for the vital rate regressions.
No full textMatrices of interaction coefficients for the vital rate regressions
Appendix I. Observed and simulated spatial patterns.
No full textObserved and simulated spatial patterns
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