Supplementary Material for: Longitudinal Decrease in Left Ventricular Size with Age: Impact on Mortality and Cardiovascular Hospitalization by figshare admin karger (2628495)

“…Participants were categorized by LVEDD change from baseline: No Change (<5 mm), Decreased (≥5 mm), and Increased (≥5 mm). Results: A decrease in LVEDD was observed in 24% of participants (mean change -9±3 mm) and was significantly associated with older age, female sex, decreased volumes, concentric remodeling and diastolic dysfunction. …”

<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>. …”

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

<b>The loss of insulin-positive cell clusters precedes the decrease of islet frequency and beta cell area in type 1 diabetes</b> by Denise M. Drotar (21679539)

“…Moreover, changes in endocrine composition also occurred in mAAb+ donors, including a significant decrease in the INS+ islet fraction. These data suggest preferential loss of INS+ small endocrine objects early in type 1 diabetes development.…”

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. …”

Wise-IOU regression diagram. 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. …”

Visualization of detection 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. …”

Structure diagram of the SE attention mechanism. 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. …”

Flow chart of participants selection. by Linjia Duan (13276989)

“…</p><p>Conclusions</p><p>Among older adults with cognitive impairment in China, the risk of all-cause mortality significantly decreased as both the frequency and number of cognitive activities increased. …”