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largest decrease » marked decrease (Expand Search)
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larger decrease » marked decrease (Expand Search)
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High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles
Published 2025“…Furthermore, at 1100 °C, thermal conductivity decreased by 34.4%, and the density was only 242 kg/m<sup>3</sup>, the lowest density among SiO<sub>2</sub>-based aerogel composites. …”
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506
High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles
Published 2025“…Furthermore, at 1100 °C, thermal conductivity decreased by 34.4%, and the density was only 242 kg/m<sup>3</sup>, the lowest density among SiO<sub>2</sub>-based aerogel composites. …”
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507
High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles
Published 2025“…Furthermore, at 1100 °C, thermal conductivity decreased by 34.4%, and the density was only 242 kg/m<sup>3</sup>, the lowest density among SiO<sub>2</sub>-based aerogel composites. …”
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508
High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles
Published 2025“…Furthermore, at 1100 °C, thermal conductivity decreased by 34.4%, and the density was only 242 kg/m<sup>3</sup>, the lowest density among SiO<sub>2</sub>-based aerogel composites. …”
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509
High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles
Published 2025“…Furthermore, at 1100 °C, thermal conductivity decreased by 34.4%, and the density was only 242 kg/m<sup>3</sup>, the lowest density among SiO<sub>2</sub>-based aerogel composites. …”
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510
High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles
Published 2025“…Furthermore, at 1100 °C, thermal conductivity decreased by 34.4%, and the density was only 242 kg/m<sup>3</sup>, the lowest density among SiO<sub>2</sub>-based aerogel composites. …”
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511
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Cox risk curve.
Published 2025“…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
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516
Weather factor dummy variable.
Published 2025“…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
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517
Day factor dummy variable.
Published 2025“…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
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518
Desensitized original data.
Published 2025“…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
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519
Cox survival function curve.
Published 2025“…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”
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520
Data sample example.
Published 2025“…The study uses non-parametric and semi-parametric analysis methods in survival analysis to explore if and how weather conditions, parking tariffs, and temporal factors (weekdays, weekends, and short holidays) impact the parking duration. The parking data of a large commercial supermarket in Zhengzhou was collected over one month. …”