Alcohol-induced fatalities and crude rates in the United States at the county level. by Tony Wong (779773)

Alcohol-related monthly crude rates for ages 15 and older between 2018 and 2024, stratified by gender and race. by Tony Wong (779773)

Percent change in yearly crude rates (between 2019 and 2021 and between 2019 and 2024) by gender and state. by Tony Wong (779773)

Male-to-female ratios of yearly crude rates. by Tony Wong (779773)

“…The crude rates of male and female alcohol deaths used to calculate these ratios are shown in <a href="/article/info:doi/10.1371/journal.pgph.0004623#pgph.0004623.g001" target="_blank">Fig 1</a>.…”

Yearly crude rates stratified by age from 1999 to 2024 and by race from 1999 to 2020. by Tony Wong (779773)

Yearly crude rates normalized by their 1999 value. by Tony Wong (779773)

“…<p>Values below 1 indicate crude rate decreases relative to their 1999 value, those above 1 indicate increases. …”

Maps of alcohol-induced crude rates in the United States at the county level for 1999, 2021, 2024. by Tony Wong (779773)

Crude rates in select US counties between 1999 and 2024. by Tony Wong (779773)

Supporting information file corresponding to Fig 7. by Oswaldo Maillard (20660661)

Supporting information file corresponding to Fig 3. by Oswaldo Maillard (20660661)

Supporting information file corresponding to Fig 5. by Oswaldo Maillard (20660661)

Supporting information file corresponding to Fig 8. by Oswaldo Maillard (20660661)

Supplementary Materials for 'Association between gastric rhythm and gastroesophageal reflux defined by simultaneous body surface gastric mapping and 24-hour pH testing' by William Xu (22345150)

Satellite-Based Monitoring of Methane Emissions from China’s Rice Hub by Ruosi Liang (14018604)

“…Our satellite-based estimation finds a rice methane emission of 0.85 (0.69–1.03) Tg a^–1 from the province or an average emission factor of 22.0 (17.8–26.6) g m^–2 a^–1 when normalized by rice paddy areas. …”

Distribution of AQI and Air pollutants indicators by provinces. by Weixin Chen (138569)

Influencing factors of APCA. by Wenping Ning (19871091)

“…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”

Temporal trends in APCA. by Wenping Ning (19871091)

“…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”

Traditional Markov transfer probability matrices. by Wenping Ning (19871091)

“…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”

Spatial Markov transfer probability matrix. by Wenping Ning (19871091)

“…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”

Three-dimensional kernel density of APCA. by Wenping Ning (19871091)

“…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”