STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis

The rapid evolution of large language models (LLMs) holds promise for reforming the methodology of spatio-temporal data mining. However, current works for evaluating the spatio-temporal understanding capability of LLMs are somewhat limited and biased. These works either fail to incorporate the latest language models or only focus on assessing the memorized spatio-temporal knowledge. To address this gap, this paper dissects LLMs' capability of spatio-temporal data into four distinct dimensions: knowledge comprehension, spatio-temporal reasoning, accurate computation, and downstream applications. We curate several natural language question-answer tasks for each category and build the benchmark dataset, namely STBench, containing 13 distinct tasks and over 60,000 QA pairs. Moreover, we have assessed the capabilities of 13 LLMs, such as GPT-4o, Gemma and Mistral. Experimental results reveal that existing LLMs show remarkable performance on knowledge comprehension and spatio-temporal reasoning tasks, with potential for further enhancement on other tasks through in-context learning, chain-of-though prompting, and fine-tuning. The code and datasets of STBench are released on https://github.com/LwbXc/STBench

An Economic and Disease Transmission Model of Human Papillomavirus and oropharyngeal Cancer in Texas

In 2017, 46,157 and 3,127 new oropharyngeal cancer (OPC) cases were reported in the U.S. and Texas, respectively. About 70% of OPC were attributed to human papillomavirus (HPV). However, only 51% of U.S. and 43.5% of Texas adolescents have completed the HPV vaccine series. Therefore, modeling the demographic dynamics and transmission of HPV and OPC progression is needed for accurate estimation of the economic and epidemiological impacts of HPV vaccine in a geographic area. An age-structured population dynamic model was developed for the U.S. state of Texas. With Texas-specific model parameters calibrated, this model described the dynamics of HPV-associated OPC in Texas. Parameters for the Year 2010 were used as the initial values, and the prediction for Year 2012 was compared with the real age-specific incidence rates in 23 age groups for model validation. The validated model was applied to predict 100-year age-adjusted incidence rates. The public health benefits of HPV vaccine uptake were evaluated by computer simulation. Compared with current vaccination program, increasing vaccine uptake rates by 50% would decrease the cumulative cases by 4403, within 100 years. The incremental cost-effectiveness ratio of this strategy was $94,518 per quality-adjusted life year (QALY) gained. Increasing the vaccine uptake rate by 50% can: (i) reduce the incidence rates of OPC among both males and females; (ii) improve the quality-adjusted life years for both males and females; (iii) be cost-effective and has the potential to provide tremendous public health benefits in Texas

An economic and disease transmission model of human papillomavirus and oropharyngeal cancer in Texas

In 2017, 46,157 and 3,127 new oropharyngeal cancer (OPC) cases were reported in the U.S. and Texas, respectively. About 70% of OPC were attributed to human papillomavirus (HPV). However, only 51% of U.S. and 43.5% of Texas adolescents have completed the HPV vaccine series. Therefore, modeling the demographic dynamics and transmission of HPV and OPC progression is needed for accurate estimation of the economic and epidemiological impacts of HPV vaccine in a geographic area. An age-structured population dynamic model was developed for the U.S. state of Texas. With Texas-specific model parameters calibrated, this model described the dynamics of HPV-associated OPC in Texas. Parameters for the Year 2010 were used as the initial values, and the prediction for Year 2012 was compared with the real age-specific incidence rates in 23 age groups for model validation. The validated model was applied to predict 100-year age-adjusted incidence rates. The public health benefits of HPV vaccine uptake were evaluated by computer simulation. Compared with current vaccination program, increasing vaccine uptake rates by 50% would decrease the cumulative cases by 4403, within 100 years. The incremental cost-effectiveness ratio of this strategy was $94,518 per quality-adjusted life year (QALY) gained. Increasing the vaccine uptake rate by 50% can: (i) reduce the incidence rates of OPC among both males and females; (ii) improve the quality-adjusted life years for both males and females; (iii) be cost-effective and has the potential to provide tremendous public health benefits in Texas

Multi-scale Modeling Dynamics of Marine Populations with Implications for Ecosystem Management of the Northern Gulf of Mexico

The U.S. northern Gulf of Mexico (GoM) coastal waters provide invaluable ecosystem functions and services for human welfare. However, GoM ecosystems have been disrupted by decades of anthropogenic activities in conjunction with climate change. While understanding anthropogenic and climate-induced impacts has become a consensus towards ecosystem-based management, the obstacle that lies ahead is how to tease apart confounding interactions in ecosystem dynamics. This dissertation used multi-scale modeling approaches to address existing challenges in understanding ecosystem dynamics in the GoM. This dissertation begins with a large-scale population study focusing on the bloom dynamics of jellyfish (Aurelia spp.) over the GoM continental shelf from 1995 to 2010. The spatio-temporal variations in jellyfish abundance and biomass were simulated by using an Individual-Based Model (IBM). The model simulation disclosed the potential bloom areas including coastal waters off South Texas, East Louisiana, and nearby the Mississippi Sound, driven by distinct oceanographic processes. In addition, the statistical analysis based on model simulation highlighted the bottom-up effects of zooplankton on triggering GoM jellyfish outbreaks. The second focus of this dissertation tackles a problem in understanding the recruitment dynamics of oysters in response to hurricane disturbance at the estuarine scale. Specifically, a Dynamic Energy Budget Model (DEBM) was applied under “post-hurricane” and “baseline” scenarios to partition the relative impacts of hurricanes on the recruitment of planktonic oyster larvae in the Galveston Bay System. The results indicated a strong post-disaster resilience of oyster larvae. Salinity had profound effects on oyster larval recruitment shaping the spatial patterns of recovery. The planktonic habitat suitability model for oyster larvae showed the optimal habitats in lower Galveston Bay and West Bay and the least optimal habitats in upper Galveston Bay and East Bay. The third focus of this dissertation was given to identifying underlying mechanisms by which humans act on estuarine ecosystems under climate change. Specifically, an Empirical Dynamic Modeling (EDM) approach was used to study the dynamics and stability of two biogeographically similar estuarine systems in Texas with different levels of urbanization. The results highlighted the role human plays in magnifying the fluctuation in biological populations and decoupling interspecies interaction. Although human intervention destabilized the ecosystem, making it vulnerable to climate change, biodiversity and species interaction exerted buffering effects to maintain ecosystem functions and services. Overall, this dissertation highlights the utility of heuristic modeling approaches in multi-scale ecological studies ranging from estuaries to coastal waters, and from populations to an ecosystem. The findings of this dissertation contribute to the assessment and management of estuarine and coastal marine ecosystems subjected to human and natural disturbances in the face of climate change

Discrete Simulation of Vibratory Roller Compaction of Field Rockfills

Vibratory roller compaction is a well-known method in improving the mechanical properties of field rockfills. However, the meso mechanism of rockfill densification under vibratory roller compaction has not been understood clearly. This paper presents a discrete numerical method to simulate the vibratory roller compaction of field rockfills. Firstly, rockfill particles were modeled by irregular and stochastic clusters, which can be breakable. In addition, the segregation of field rockfills was replicated in a practical manner. Then, a new model of the vibratory roller was presented, in which the frame inertia was considered. Finally, the developed method was applied to simulate the vibratory roller compaction of field rockfills in the Shui Buya Project. Results show that (1) the numerical simulations of vibratory roller compaction of field rockfills agree well with the field experiments; thus, the feasibility and rationality of the developed simulation method are verified; (2) the dynamic response of field rockfills under vibratory roller compaction can be predicted by the presented numerical method with calibrated model and parameters; (3) the new roller model with frame inertia considered is much more accurate than the roller models in early studies. Thus, the developed discrete numerical method can be further adopted to explore the meso mechanism of rockfill densification under vibratory roller compaction in the future

Discrete Simulation of Vibratory Roller Compaction of Field Rockfills

Vibratory roller compaction is a well-known method in improving the mechanical properties of field rockfills. However, the meso mechanism of rockfill densification under vibratory roller compaction has not been understood clearly. This paper presents a discrete numerical method to simulate the vibratory roller compaction of field rockfills. Firstly, rockfill particles were modeled by irregular and stochastic clusters, which can be breakable. In addition, the segregation of field rockfills was replicated in a practical manner. Then, a new model of the vibratory roller was presented, in which the frame inertia was considered. Finally, the developed method was applied to simulate the vibratory roller compaction of field rockfills in the Shui Buya Project. Results show that (1) the numerical simulations of vibratory roller compaction of field rockfills agree well with the field experiments; thus, the feasibility and rationality of the developed simulation method are verified; (2) the dynamic response of field rockfills under vibratory roller compaction can be predicted by the presented numerical method with calibrated model and parameters; (3) the new roller model with frame inertia considered is much more accurate than the roller models in early studies. Thus, the developed discrete numerical method can be further adopted to explore the meso mechanism of rockfill densification under vibratory roller compaction in the future.</jats:p