S1 Dataset - by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

Mineral content of raw materials. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

Technical parameters of ultrafine cement. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

Technical parameters of PVA fiber. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

Sample preparation and testing flow chart. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

XRD patterns of MUCG at different curing age. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

FTIR spectra of MUCG at different curing age. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

Description of fitting models. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

Mineral composition of UFC, B, and SF. by Junxia Zhou (14381598)

“…BET and SEM analyses demonstrated that the specific surface area and porosity (most probable pore size) gradually decreased over time. At various ages, mesopores (cumulative pore diameter, median pore diameter) initially increased and then decreased. …”

Estimates of recent population sizes for eight populations sampled in the 1000 Genomes Project. by Zhendong Huang (390367)

Summary of previous work. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Comparison of MAP@0.5 results from experiments. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

YOLO11. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Structure of the SCI-YOLO11 network. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Comparative experimental results. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Algorithm operation steps. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

SCI-YOLO11. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Dataset for insulator defect detection. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

YOLOV8. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Faster-RCNN. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”