Innovation and night light in large and small cities. by Saul Estrin (8629173)

The Throttle Effect in Metal–Organic Frameworks for Distinguishing Water Isotopes by Xiao Xiao (99147)

“…We believe that the throttle effect with small-molecule loading could provide a universal design principle for MOF-based applications, especially for isotope separation.…”

The Throttle Effect in Metal–Organic Frameworks for Distinguishing Water Isotopes by Xiao Xiao (99147)

“…We believe that the throttle effect with small-molecule loading could provide a universal design principle for MOF-based applications, especially for isotope separation.…”

Effect by world bank income classification. by Stephan Dietrich (6979985)

“…Suprisingly, we find that income pathways accounts for only a small proportion of wellbeing damages caused by extreme temperatures. …”

Marginal effect of HTD on income and SWB. by Stephan Dietrich (6979985)

“…Suprisingly, we find that income pathways accounts for only a small proportion of wellbeing damages caused by extreme temperatures. …”

<b>Nest mass in forest tits </b><b><i>Paridae</i></b><b> </b><b>increases with elevation and decreasing body mass, promoting reproductive success</b> by Clara Wild (19246606)

“…Nest boxes were installed along an elevational gradient of approximately 1000 m a.sl., either in forest gaps with fluctuating microclimatic conditions or in closed forests with buffered microclimates. We found that nest mass increased by ~ 60% along the elevational gradient, but the effect of canopy openness on nest mass was not significant, while nest mass decreased along the ranked species from the smallest <i>Periparus ater</i> to the medium-sized <i>Cyanistes caeruleus</i> and the largest <i>Parus major</i>. …”

Patient enrollment and inclusion information. by Ruitian Song (11045127)

“…During chemotherapy, PVS decreased significantly from 3M to 12M. Subsequently, from 12M to FollowUp, PVS increased again. …”

Marginal effect of additional hot day on SWB. by Stephan Dietrich (6979985)

“…Suprisingly, we find that income pathways accounts for only a small proportion of wellbeing damages caused by extreme temperatures. …”

Summary of previous work. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

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

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

YOLO11. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

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

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

Comparative experimental results. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

Algorithm operation steps. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

SCI-YOLO11. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

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

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

YOLOV8. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

Faster-RCNN. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

Results of ablation experiments. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”

Structure diagram of SPDConv. by Junyan Wang (4738518)

“…Specifically, to tackle the difficulties associated with small object detection, we replace conventional convolutions in the Backbone with SPDConv modules to enhance feature capture capabilities for small targets and low-resolution images while reducing computational overhead. …”