Three Essays on Climate Change Adaptation and Impacts: Econometric Investigations

Climate change, biofuels, agricultural policies and other factors may well be changing farmer decisions and extreme events like wildfires. We use discrete choice models to examine how climate is influencing decisions on crop mix and land use choice along with natural wildfire incidence. Using panel data, we consider the effect of climate change across space on the censored choice of both major land uses and agricultural crop mix plus on the probability of wildfire. In terms of land use and crop mix, we use a two-step linearized spatial logit model to portray major land use transitions and a fractional dependent variable model to examine crop mix selection. The models include socioeconomic, environmental, and spatial factors. Our results indicate that climate significantly affects land use transitions and crop mix allocations. These results indicate that farm level adaptation to climate change is ongoing in a spatially heterogeneous manner. Generally crops are moving north and west plus up in elevation while climate change causes crop land to transition into grassland. For wildfire, we examine how wildfire risk is affected by climate and other factors using a fractional regression considering state unobserved factors. We examine risks of both human and naturally caused wildfires. We explore the importance of factors such as climate, demographics, and physical characteristics on fire risks. We find that climate conditions play a significant role in determining wildfire risks in the US but have regionally heterogeneous effects on human and naturally caused fires. This implies each caused fire can be better dealt with by using separate approaches

Identifying set-wise differential co-expression in gene expression microarray data

<p>Abstract</p> <p>Background</p> <p>Previous differential coexpression analyses focused on identification of differentially coexpressed gene pairs, revealing many insightful biological hypotheses. However, this method could not detect coexpression relationships between pairs of gene sets. Considering the success of many set-wise analysis methods for microarray data, a coexpression analysis based on gene sets may elucidate underlying biological processes provoked by the conditional changes. Here, we propose a differentially coexpressed gene sets (dCoxS) algorithm that identifies the differentially coexpressed gene set pairs between conditions.</p> <p>Results</p> <p>dCoxS is a two-step analysis method. In each condition, dCoxS measures the interaction score (IS), which represents the expression similarity between two gene sets using Renyi relative entropy. When estimating the relative entropy, multivariate kernel density estimation was used to model gene-gene correlation structure. Statistical tests for the conditional difference between the ISs determined the significance of differential coexpression of the gene set pair. Simulation studies supported that the IS is a representative measure of similarity between gene expression matrices. Single gene coexpression analysis of two publicly available microarray datasets detected no significant results. However, the dCoxS analysis of the datasets revealed differentially coexpressed gene set pairs related to the biological conditions of the datasets.</p> <p>Conclusion</p> <p>dCoxS identified differentially coexpressed gene set pairs not found by single gene analysis. The results indicate that set-wise differential coexpression analysis is useful for understanding biological processes induced by conditional changes.</p

Climate change influences on crop mix shifts in the United States

We examine the impact of current and future climate on crop mixes over space in the US. We find using historical data that temperature and precipitation are among the causal factors for shits in crop production location and mixes, with some crops being more sensitive than others. In particular, we find that when temperature rises, cotton, rice, sorghum and winter wheat are more likely to be chosen. We also find that barley, sorghum, winter wheat, spring wheat and hay are more likely to be chosen as regions become drier, and corn, cotton, rice and soybeans are more likely to be selected in wetter regions. Additionally, we assess how much of the observed crop mix shifts between 1970 and 2010 were contributed to by climate change. There we find climate explains about 7–50% of the shift in latitude, 20–36% in longitude and 4–28% of that in elevation. Finally, we estimate climate change impacts on future crop mix under CMIP5 scenarios. There we find shifts in US production regions for almost all major crops with the movement north and east. The estimates describe how the farmers respond to altering climate and can be used for planning future crop allocations

Nonflammable Lithium Metal Full Cells with Ultra-high Energy Density Based on Coordinated Carbonate Electrolytes

Coupling thin Li metal anodes with high-capacity/high-voltage cathodes such as LiNi0.8Co0.1Mn0.1O2 (NCM811) is a promising way to increase lithium battery energy density. Yet, the realization of high-performance full cells remains a formidable challenge. Here, we demonstrate a new class of highly coordinated, nonflammable carbonate electrolytes based on lithium bis(fluorosulfonyl)imide (UFSI) in propylene carbonate/fluoroethylene carbonate mixtures. Utilizing an optimal salt concentr ation (4 M LiFSI) of the electrolyte results in a unique coordination structure of Li+-FSI-solvent cluster, which is critical for enabling the formation of stable interfaces on both the thin Li metal anode and high-voltage NCM811 cathode. Under highly demanding cell configuration and operating conditions (Li metal anode = 35 mu m, areal capacity/charge voltage of NCM811 cathode = 4.8 mAh cm(-2)/4 .6 V, and anode excess capacity [relative to the cathode] = 0.83), the Li metal-based full cell provides exceptional electrochemical performance (energy densities = 679 Wh kg(cell)(-1)/1,024 Wh L-cell(-1)) coupled with nonflammability

Quantum dot-induced cell death involves Fas upregulation and lipid peroxidation in human neuroblastoma cells

BACKGROUND: Neuroblastoma, a frequently occurring solid tumour in children, remains a therapeutic challenge as existing imaging tools are inadequate for proper and accurate diagnosis, resulting in treatment failures. Nanoparticles have recently been introduced to the field of cancer research and promise remarkable improvements in diagnostics, targeting and drug delivery. Among these nanoparticles, quantum dots (QDs) are highly appealing due to their manipulatable surfaces, yielding multifunctional QDs applicable in different biological models. The biocompatibility of these QDs, however, remains questionable. RESULTS: We show here that QD surface modifications with N-acetylcysteine (NAC) alter QD physical and biological properties. In human neuroblastoma (SH-SY5Y) cells, NAC modified QDs were internalized to a lesser extent and were less cytotoxic than unmodified QDs. Cytotoxicity was correlated with Fas upregulation on the surface of treated cells. Alongside the increased expression of Fas, QD treated cells had increased membrane lipid peroxidation, as measured by the fluorescent BODIPY-C(11 )dye. Moreover, peroxidized lipids were detected at the mitochondrial level, contributing to the impairment of mitochondrial functions as shown by the MTT reduction assay and imaged with confocal microscopy using the fluorescent JC-1 dye. CONCLUSION: QD core and surface compositions, as well as QD stability, all influence nanoparticle internalization and the consequent cytotoxicity. Cadmium telluride QD-induced toxicity involves the upregulation of the Fas receptor and lipid peroxidation, leading to impaired neuroblastoma cell functions. Further improvements of nanoparticles and our understanding of the underlying mechanisms of QD-toxicity are critical for the development of new nanotherapeutics or diagnostics in nano-oncology

Fifteen Years After the Gozan-Dong Glass Fiber Outbreak, Incheon in 1995

Objectives: In 1995, an outbreak survey in Gozan-dong concluded that an association between fiberglass exposure in drinking water and cancer outbreak cannot be established. This study follows the subjects from a study in 1995 using a data linkage method to examine whether an association existed. The authors will address the potential benefits and methodological issues following outbreak surveys using data linkage, particularly when informed consent is absent. Methods: This is a follow-up study of 697 (30 exposed) individuals out of the original 888 (31 exposed) participants (78.5%) from 1995 to 2007 assessing the cancer outcomes and deaths of these individuals. The National Cancer Registry (KNCR) and death certificate data were linked using the ID numbers of the participants. The standardized incidence ratio (SIR) and standardized mortality ratio (SMR) from cancers were calculated by the KNCR. Results: The SIR values for all cancer or gastrointestinal cancer (GI) occurrences were the lowest in the exposed group (SIR, 0.73; 95% CI, 0.10 to 5.21; 0.00 for GI), while the two control groups (control 1: external, control 2: internal) showed slight increases in their SIR values (SIR, 1.18 and 1.27 for all cancers; 1.62 and 1.46 for GI). All lacked statistical significance. All-cause mortality levels for the three groups showed the same pattern (SMR 0.37, 1.29, and 1.11). Conclusions: This study did not refute a finding of non-association with a 13-year follow-up. Considering that many outbreak surveys are associated with a small sample size and a cross-sectional design, follow-up studies that utilize data linkage should become standard procedure.OAIID:oai:osos.snu.ac.kr:snu2011-01/102/0000040632/15SEQ:15PERF_CD:SNU2011-01EVAL_ITEM_CD:102USER_ID:0000040632ADJUST_YN:YEMP_ID:A077602DEPT_CD:902CITE_RATE:0FILENAME:fifteen years after the gozan-dong glass fiber outbreak, incheon in 1995..pdfDEPT_NM:보건학과CONFIRM: