Data - willing to pay of dog owners. by Fentahun Mengie (20862454)

“…Male dog owners and dog owners belonging to lower age groups had significantly higher AT towards leashing dogs. Sixty two percent of dog owners were WTP for the suggested price bid amounts; but, in general, their number decreased when price of the vaccine increased. …”

Data - intention of dog owners. by Fentahun Mengie (20862454)

“…Male dog owners and dog owners belonging to lower age groups had significantly higher AT towards leashing dogs. Sixty two percent of dog owners were WTP for the suggested price bid amounts; but, in general, their number decreased when price of the vaccine increased. …”

Map of the study area (shaded in gray). by Fentahun Mengie (20862454)

“…Male dog owners and dog owners belonging to lower age groups had significantly higher AT towards leashing dogs. Sixty two percent of dog owners were WTP for the suggested price bid amounts; but, in general, their number decreased when price of the vaccine increased. …”

DataSheet1_Prognostic significance of fludeoxyglucose positron emission tomography delta radiomics following bridging therapy in patients with large B-cell lymphoma undergoing CAR... by Colton Ladbury (19768281)

Stability differences between condition 1 and other conditions across participants on the non-hemiparetic side (NHP) side. by Hyung Suk Yang (20442438)

Stability differences between condition 1 and other conditions across participants on the hemiparetic (HP) side. by Hyung Suk Yang (20442438)

Mapping of the change of nightlight radiance in Afghanistan. by Till Raphael Saenger (20427744)

CCI - Chlorophyll Content Index. by Dominika Radzikowska-Kujawska (14439076)

Comparison of data after the experiment. by Neng Pan (5262032)

Top predictive variables for KDIGO stage ≥ 3 identified by the final Random Forest model. by Julian Müller-Kühnle (22265248)

Chlorophyll fluorescence: (A) Yield - quantum yield of the photochemical reaction in PSII, (C) ETR – electron transport rate, (E) NPQ - Non - Photochemical Quenching, (B) F0 - init... by Dominika Radzikowska-Kujawska (14439076)

Balance test results. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

Mechanism analysis results. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

Endogenous test results. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

Heterogeneity analysis results. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

Robustness test results. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

Baseline results of the impact of RLM on HWSW. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

The influencing factors of RLM. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

Variable definitions and basic statistics. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”

Average and marginal effects of RLM on HWSW. by Yi Yu (28902)

“…Specifically, with every 1% increase in RLM, the likelihood of rural residents’ HWSW will decrease by 3.5%. This effect remains significant after a series of robustness checks. …”