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Summary : Fuel demand is shown to be influenced by fuel prices, people's income and motorization rates. We explore the effects of electric vehicle's rates in gasoline demand using this panel dataset. Files : dataset.csv - Panel dimensions are the Brazilian state ( i ) and year ( t ). The other columns are: gasoline sales per capita (ln_Sg_pc), prices of gasoline (ln_Pg) and ethanol (ln_Pe) and their lags, motorization rates of combustion vehicles (ln_Mi_c) and electric vehicles (ln_Mi_e) and GDP per capita (ln_gdp_pc). All variables are all under the natural log function, since we use this to calculate demand elasticities in a regression model. adjacency.csv - The adjacency matrix used in interaction with electric vehicles' motorization rates to calculate spatial effects. At first, it follows a binary adjacency formula: for each pair of states i and j, the cell (i, j) is 0 if the states are not adjacent and 1 if they are. Then, each row is normalized to have sum equal to one. regression.do - Series of Stata commands used to estimate the regression models of our study. dataset.csv must be imported to work, see comment section. dataset_predictions.xlsx - Based on the estimations from Stata, we use this excel file to make average predictions by year and by state. Also, by including years beyond the last panel sample, we also forecast the model into the future and evaluate the effects of different policies that influence gasoline prices (taxation) and EV motorization rates (electrification). This file is primarily used to create images, but can be used to further understand how the forecasting scenarios are set up. Sources: Fuel prices and sales: ANP (https://www.gov.br/anp/en/access-information/what-is-anp/what-is-anp) State population, GDP and vehicle fleet: IBGE (https://www.ibge.gov.br/en/home-eng.html?lang=en-GB) State EV fleet: Anfavea (https://anfavea.com.br/en/site/anuarios/)

This study examined the relationship between debt servicing and foreign exchange rate unification in Nigeria from 1995 to 2023, hypothesizing that a unified exchange rate policy would significantly impact the country's debt service-to-revenue ratio. Using annual time series data from sources such as the International Monetary Fund and World Development Indicators, the study employed an Autoregressive Distributed Lag (ARDL) model to analyze the relationship between the debt service-to-revenue ratio and factors including the official foreign exchange rate, GDP growth rate, inflation rate, and oil prices. The findings revealed several notable insights. Exchange rate unification was found to have a significant negative effect on the debt service-to-revenue ratio, suggesting that a unified exchange rate policy could help reduce Nigeria's debt service burden. Both current and lagged inflation rates showed a significant negative impact on the debt service-to-revenue ratio, indicating that higher inflation might be eroding the real value of debt or increasing nominal revenues faster than debt servicing costs. Lagged exchange rates were found to negatively affect the debt service-to-revenue ratio, implying that higher exchange rates in the previous period decrease the current ratio. Oil prices demonstrated mixed effects, with current prices positively impacting the debt service-to-revenue ratio while lagged prices had a negative effect. The study also revealed strong persistence in debt servicing behavior over time, as evidenced by the significant positive correlation between current and previous year's debt service ratios. These results offer significant implications for policymakers. The negative effect of exchange rate unification on the debt service-to-revenue ratio suggests that such a policy could improve efficiency in forex markets and reduce arbitrage opportunities, ultimately helping to reduce the debt service burden. The negative relationship between inflation and the debt service-to-revenue ratio indicates that higher inflation might be beneficial for debt servicing in the short term, though this should be interpreted cautiously given the potential negative consequences of high inflation. The mixed impact of oil prices reflects the complexity of Nigeria's oil-dependent economy, highlighting the need for economic diversification. The strong persistence in debt servicing commitments points to potential structural issues in debt management or lack of fiscal flexibility. Policymakers can use these findings to inform strategies for managing Nigeria's debt burden. The results suggest that pursuing exchange rate unification, carefully managing inflation, diversifying the economy to reduce oil dependence, and improving fiscal discipline could all contribute to better management of debt servicing costs. However, it's crucial to consider the lagged effects of economic variables on debt servicing when formulating long-term fiscal strategies.

Vector-format geologic maps for the upcoming (2024) publication of the same name in The Planetary Science Journal. Maps are provided at 1:1,000,000 and 1:3,000,000 scale (PDFs) as well as a zip file containing an ArcGIS project file.

Data for the article entitled "High-resolution mapping of on-road vehicle emissions with real-time traffic datasets based on big data".

This dataset includes codes and data to make results of empirical analysis in the paper "How firm resources affect responses to environmental regulation: Evidence from Korean manufacturing firms under an emission trading system".

The data used in this study on net inflows of FDI, technology readiness, innovation, and infrastructure were obtained from The World Bank (https://api.worldbank.org) using the Python API. The data on imports of intermediate goods were obtained from https://wits.worldbank.org/. However, accessing the WITS server proved to be challenging, and the Python code frequently received a 404 error message due to request timeouts. For convenience, we uploaded the data on imports of intermediate goods in CSV format. This data will be merged with the data on other variables collected using the Python API on demand. The Python code for data collection and processing is provided in this repository.

we developed a biomarker responsive AuNR-based Janus nanoprobe (AMCGL) by integrating MnO2 on one end of AuNRs and specific ligands on the other end. In the tumor microenvironment, highly expressed transglutaminase (TGase) facilitates the formation of isopeptide linkages between glutamine (Gln) and lysine (Lys), which in turn induces the aggregation of AuNRs. Meanwhile, the highly expressed glutathione (GSH) degrades MnO2 to trigger chemodynamic therapy. This in-situ aggregation approach amplifies the intensity of PA imaging, extends the time windows of PA imaging, and enhances the radiosensitization effect. The integrated strategy paves the way for AuNRs with specific responsive assembly and functional activation at the tumor site, facilitating PA imaging-guided enhanced radiosensitization and chemodynamic therapy of tumor.

Replication Code for 'Gig Labor: Trading Safety Nets for Steering Wheels'