Table 3_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 1_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 4_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 5_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Calculation FFR, IMR and CFR. by Ainhoa Pérez-Guerrero (21377457)

“…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”

Definition of events. by Ainhoa Pérez-Guerrero (21377457)

“…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”

Eligibility criteria. by Ainhoa Pérez-Guerrero (21377457)

“…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”

Secondary endpoints. by Ainhoa Pérez-Guerrero (21377457)

“…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”

Flowchart of BWEMFO. by Jingjing Ma (419752)

“…The scalability of the algorithm is confirmed through benchmark functions. …”

Various MFOs from three mechanisms. by Jingjing Ma (419752)

“…The scalability of the algorithm is confirmed through benchmark functions. …”

The flowchart of MFO. by Jingjing Ma (419752)

“…The scalability of the algorithm is confirmed through benchmark functions. …”

Parameters. by Jingjing Ma (419752)

“…The scalability of the algorithm is confirmed through benchmark functions. …”

Riemann Hypothesis Solution: A Structured Hilbert-Polya Operator Realization via Entropy Geometry by Jennifer Bulyaki (22283308)

Video 5_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

Video 8_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

Video 6_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

Video 1_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

Supplementary file 1_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.docx by Hannah James (6551678)

Video 9_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)