A Synthesis Program: Reducing Uncertainties of the Terrestrial Biosphere Carbon Cycle at Various Spatio Temporal Scales

The terrestrial biosphere plays an important role in the global carbon cycle, and disturbance fire and climate extreme drought have strong direct and indirect impacts on the carbon fluxes. In addition, the lateral dissolved organic carbon (DOC) flux from soils to inland waters represents an important component of the terrestrial biosphere carbon cycle. Fires play an important role in the terrestrial biosphere carbon cycle, not only through direct carbon release but also contributing to a potential long-term storage as pyrogenic carbon (PyC). PyC is formed through fires, and because it may resist further biological and chemical degradation, is more stable in soil and sediment than original biomass. Chapter 1 presents estimates of global PyC production. Worldwide, droughts are becoming more frequent with increasing weather extremes, resulting in substantial impacts on land-atmosphere carbon exchange. However, the patterns of carbon fluxes in response to droughts differ across biomes and time scales due to variations in the adaptation and resilience of different plant species, soil properties, and available water and nutrients. In chapter 2, I examined the biome-scale spatial patterns in the response of carbon fluxes to droughts at different time scales. The export of dissolved organic carbon (DOC) from a watershed is a critical flux of terrestrial biosphere carbon cycles. Advanced understanding of how environmental factors drive the temporal patterns of this biogeochemical process and their relative magnitudes of impacts is necessary to accurately model and evaluate terrestrial carbon storage and fluxes. In chapter 3, I examined the impacts of environmental factors on the temporal patterns of DOC export and their relative magnitudes, as well as the autocorrelation of DOC export. The lateral flux of dissolved organic carbon (DOC) from soils to inland waters and ultimately delivered to the ocean represents a fundamental component of the global carbon cycle. To estimate the production, delivery and potential fates of DOC flux from terrestrial through aquatic ecosystems to the ocean, I developed a process-based terrestrial-aquatic DOC fluxes model (TAF-DOC), which has the ability to estimate the spatial and temporal dynamics of DOC flux through incorporating various environmental factors

Using Large Language Model to Solve and Explain Physics Word Problems Approaching Human Level

Our work demonstrates that large language model (LLM) pre-trained on texts can not only solve pure math word problems, but also physics word problems, whose solution requires calculation and inference based on prior physical knowledge. We collect and annotate the first physics word problem dataset-PhysQA, which contains over 1000 junior high school physics word problems (covering Kinematics, Mass&Density, Mechanics, Heat, Electricity). Then we use OpenAI' s GPT3.5 to generate the answer of these problems and found that GPT3.5 could automatically solve 49.3% of the problems through zero-shot learning and 73.2% through few-shot learning. This result demonstrates that by using similar problems and their answers as prompt, LLM could solve elementary physics word problems approaching human level performance. In addition to solving problems, GPT3.5 can also summarize the knowledge or topics covered by the problems, provide relevant explanations, and generate new physics word problems based on the input. Our work is the first research to focus on the automatic solving, explanation, and generation of physics word problems across various types and scenarios, and we achieve an acceptable and state-of-the-art accuracy. This underscores the potential of LLMs for further applications in secondary education.Comment: 9 pages, 6 figure

Hurricanes Substantially Reduce the Nutrients in Tropical Forested Watersheds in Puerto Rico

Because nutrients including nitrogen and phosphorus are generally limited in tropical forest ecosystems in Puerto Rico, a quantitative understanding of the nutrient budget at a watershed scale is required to assess vegetation growth and predict forest carbon dynamics. Hurricanes are the most frequent disturbance in Puerto Rico and play an important role in regulating lateral nitrogen and phosphorus exports from the forested watershed. In this study, we selected seven watersheds in Puerto Rico to examine the immediate and lagged effects of hurricanes on nitrogen and phosphorous exports. Our results suggest that immediate surges of heavy precipitation associated with hurricanes accelerate nitrogen and phosphorus exports as much as 297 ± 113 and 306 ± 70 times than the long-term average, respectively. In addition, we estimated that it requires approximately one year for post-hurricane riverine nitrogen and phosphorus concentrations to recover to pre-hurricane levels. During the recovery period, the riverine nitrogen and phosphorus concentrations are 30 ± 6% and 28 ± 5% higher than the pre-hurricane concentrations on average

Genetic variants in ELOVL2 and HSD17B12 predict melanoma‐specific survival

Fatty acids play a key role in cellular bioenergetics, membrane biosynthesis and intracellular signaling processes and thus may be involved in cancer development and progression. In the present study, we comprehensively assessed associations of 14,522 common single‐nucleotide polymorphisms (SNPs) in 149 genes of the fatty‐acid synthesis pathway with cutaneous melanoma disease‐specific survival (CMSS). The dataset of 858 cutaneous melanoma (CM) patients from a published genome‐wide association study (GWAS) by The University of Texas M.D. Anderson Cancer Center was used as the discovery dataset, and the identified significant SNPs were validated by a dataset of 409 CM patients from another GWAS from the Nurses’ Health and Health Professionals Follow‐up Studies. We found 40 noteworthy SNPs to be associated with CMSS in both discovery and validation datasets after multiple comparison correction by the false positive report probability method, because more than 85% of the SNPs were imputed. By performing functional prediction, linkage disequilibrium analysis, and stepwise Cox regression selection, we identified two independent SNPs of ELOVL2 rs3734398 T>C and HSD17B12 rs11037684 A>G that predicted CMSS, with an allelic hazards ratio of 0.66 (95% confidence interval = 0.51–0.84 and p = 8.34 × 10−4) and 2.29 (1.55–3.39 and p = 3.61 × 10−5), respectively. Finally, the ELOVL2 rs3734398 variant CC genotype was found to be associated with a significantly increased mRNA expression level. These SNPs may be potential markers for CM prognosis, if validated by additional larger and mechanistic studies

Genetic code expansion in \u3ci\u3ePseudomonas putida\u3c/i\u3e KT2440

Pseudomonas putida KT2440 is an emerging microbial chassis for bio-based chemical production from renewable feedstocks and environmental bioremediation. However, tools for studying, engineering, and modulating protein complexes and biosynthetic enzymes in this organism are largely underdeveloped. Genetic code expansion for the incorporation of unnatural amino acids (unAAs) into proteins can advance such efforts and, furthermore, enable additional controls of biological processes of the strain. In this work, we established the orthogonality of two widely used archaeal tRNA synthetase and tRNA pairs in KT2440. Following the optimization of decoding systems, four unAAs were incorporated into proteins in response to a UAG stop codon at 34.6-78% efficiency. In addition, we demonstrated the utility of genetic code expansion through the incorporation of a photocrosslinking amino acid, p-benzoyl-L-phenylalanine (pBpa), into glutathione S-transferase (GstA) and a chemosensory response regulator (CheY) for protein-protein interaction studies in KT2440. This work reported the successful genetic code expansion in KT2440 for the first time. Given the diverse structure and functions of unAAs that have been added to protein syntheses using the archaeal systems, our research lays down a solid foundation for future work to study and enhance the biological functions of KT2440