Creep failure mode and sketch map of step-step fractured rock. by Dengke Yang (842532)

Creep failure mode and sketch map of slow-step fractured rock. by Dengke Yang (842532)

Endocardial and epicardial longitudinal strain and epicardial to endocardial longitudinal strain ratio at different gestational ages [in the square bracket the sample size]. Endoca... by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

On the top, strain rate curves with S, E and A peaks. by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

Relationship between axial strain and time curve. by Dengke Yang (842532)

Iron-Catalyzed Activation of Carbon–Halogen Bonds by Eveline H. Tiekink (19948324)

Subjects:

Equalisation of steady-state strain abundances for hCom2. by Tarun Mahajan (4815573)

AI KRegression by CHIN-CHENG CHU (20718575)

Endocardial to epicardial wall thickness ratio by histology. There was a progressive increase over gestational weeks (GW). by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

The ventricular myocardium was divided into seven layers to model the transmural variation of fiber orientation (A). by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

Left ventricular end diastolic diameter by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

Speckle tracking echocardiography. by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

Sagittal slices for assessment of layer thickness and fiber’s orientation. On the top, specimen in a 16 weeks of gestation fetus: the longitudinal endocardial layer is well represe... by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

Changes in fibers’ angulation during gestational age based on histology. by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

Relative wall thickness of endocardial by Biagio Castaldi (20673392)

Subjects: “…physiological maturation steps…”

Simulations show that microSLAM improves power and false positive rates. by Miriam Goldman (21433180)

A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”

Presents the bibliometric search results. by Yan She (8639796)

S1 Data. Bibliometric analysis. S2 Data. Estrogen level analysis. S3 Data. MicroCT quantification. S4 Data. Markers of bone metabolism. by Yan She (8639796)

Modeling results of 8-week-old female C57BL/6J mice. by Yan She (8639796)