Function combination map of the PLES in Duolun County, Inner Mongolia. by A ruhan (20489164)

Spatial variation diagram of coupling degree and coupling coordination degree of carrying capacity between ecological and production space. by A ruhan (20489164)

The coupling degree and coupling capacity scheduling change curve of the PLES in Duolun County. by A ruhan (20489164)

Distribution map of production space carrying capacity in Duolun County, Inner Mongolia. by A ruhan (20489164)

Index system and index weight of the PLES carrying capacity in Duolun County. by A ruhan (20489164)

Spatial variation diagram of coupling degree and coupling coordination degree of carrying capacity between ecological and living space. by A ruhan (20489164)

Obstacle degree of the PLES carrying capacity criterion layer in Duolun County. by A ruhan (20489164)

Spatial differentiation of coupling degree and coupling coordination degree of carrying capacity in PLES. by A ruhan (20489164)

Stepwise transitions during low-pH induced structural transitions mediated by lyssavirus G. by Fanli Yang (404970)

Structure of MOKV-G at pH-4.0. by Fanli Yang (404970)

Preparation of lyssavirus glycoproteins. by Fanli Yang (404970)

Characterization of the interactions between CTR and PHD-FD of RABV-G in solution at the indicated pHs. by Fanli Yang (404970)

Comparison of the lyssavirus G structures reported in this study with previously reported RABV-G structures in intermediate states. by Fanli Yang (404970)

General characteristics of study subjects. by Soo-Hee Hwang (17767519)

“…COVID-19 did not affect inpatient mortality (p = 0.9608), but in-hospital mortality decreased from 12% to 7% in the medical aid group.</p><p>Conclusion</p><p>Overall, we found that COVID-19 had an impact on admission rates of patients with AMI but did not have a significant impact on in-hospital mortality. …”

(a) Changes of SOC (Soil organic matter) content during acification of black soil. The control group (0Y) received no fertilization, while the treatment groups included soils that... by Xiaoxu Zhu (11764430)

Importance of random forest model. by Yu Zhang (12946)

“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”

Schematic of the Baidu SVI collection. by Yu Zhang (12946)

“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”

Map of the study area. by Yu Zhang (12946)

“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”

Research framework. by Yu Zhang (12946)

“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”

Perception type distribution and typical images. by Yu Zhang (12946)

“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”