Image_3_Tucumã Oil Shifted Ruminal Fermentation, Reducing Methane Production and Altering the Microbiome but Decreased Substrate Digestibility Within a RUSITEC Fed a Mixed Hay – Co... by Aline F. O. Ramos (5473229)

“…Addition of tucumã oil linearly decreased (P < 0.01) dry matter disappearance. …”

Image_5_Tucumã Oil Shifted Ruminal Fermentation, Reducing Methane Production and Altering the Microbiome but Decreased Substrate Digestibility Within a RUSITEC Fed a Mixed Hay – Co... by Aline F. O. Ramos (5473229)

“…Addition of tucumã oil linearly decreased (P < 0.01) dry matter disappearance. …”

Image_2_Tucumã Oil Shifted Ruminal Fermentation, Reducing Methane Production and Altering the Microbiome but Decreased Substrate Digestibility Within a RUSITEC Fed a Mixed Hay – Co... by Aline F. O. Ramos (5473229)

“…Addition of tucumã oil linearly decreased (P < 0.01) dry matter disappearance. …”

(A) Side image of epoxy resin-made abutment-analog base and prosthesis; (B) Front image of epoxy resin-made abutment-analog base and prosthesis. by Long Li (6555)

Listed in this table are the models used to assess the meteorological, spatial, and temporal variables in a series of logistic regressions. by Andrea J. Ayala (3120333)

Multiple linear regression models (a - p) of environmental response variables regressed against the habitat transformation variables (predictors), given the spatio-temporal covaria... by Matthew S. Bird (522478)

Table_1_Non-linear association between serum spermidine and mild cognitive impairment: Results from a cross-sectional and longitudinal study.DOCX by Jiahui Xu (3156327)

“…Restricted cubic spline models show that there is a non-linear association between SPD and MCI. In line with cross-sectional findings, the longitudinal study showed that a high SPD concentration may indicate a lower risk of MCI [ORs (95% CIs) for the third tertile of 0.62 (0.39, 0.99)].…”

Tack of Entangled Molecular Bottlebrushes by Carlos R. López-Barrón (1723549)

“…We assess the tack performance of α-olefin molecular bottlebrushes having an elastic modulus from 4 to 30 times lower than a linear polyolefin (polypropylene). Monotonic increases of the tack parameters are observed as the bottlebrush side chain length (<i>N</i>_sc) increases and the modulus decreases. …”

Tack of Entangled Molecular Bottlebrushes by Carlos R. López-Barrón (1723549)

“…We assess the tack performance of α-olefin molecular bottlebrushes having an elastic modulus from 4 to 30 times lower than a linear polyolefin (polypropylene). Monotonic increases of the tack parameters are observed as the bottlebrush side chain length (<i>N</i>_sc) increases and the modulus decreases. …”

Tack of Entangled Molecular Bottlebrushes by Carlos R. López-Barrón (1723549)

“…We assess the tack performance of α-olefin molecular bottlebrushes having an elastic modulus from 4 to 30 times lower than a linear polyolefin (polypropylene). Monotonic increases of the tack parameters are observed as the bottlebrush side chain length (<i>N</i>_sc) increases and the modulus decreases. …”

Tack of Entangled Molecular Bottlebrushes by Carlos R. López-Barrón (1723549)

“…We assess the tack performance of α-olefin molecular bottlebrushes having an elastic modulus from 4 to 30 times lower than a linear polyolefin (polypropylene). Monotonic increases of the tack parameters are observed as the bottlebrush side chain length (<i>N</i>_sc) increases and the modulus decreases. …”

A total of 116 ORFs were annotated as functional genes. by Xuemei Duan (6901601)

The impact of a breast cancer diagnosis on health-related quality of life. A prospective comparison among middle-aged to elderly women with and without breast cancer by Randi V. Karlsen (2545756)

“…</p> <p><b>Results</b> Women with breast cancer reported significantly larger decreases in HQoL from before to after diagnosis than those who remained breast cancer-free (physical component summary, −2.0; 95% CI −2.8; −1.2, mental component summary, −1.5, 95% CI −2.3; −0.6). …”

Linear and back-splicing alterations correlate with mis-regulation of post-transcriptional regulators. by Dilara Ayyildiz (17145143)

“…<p>The schematic (created using <a href="http://Biorender.com" target="_blank">Biorender.com</a>) presents a possible model of action of mutant huntingtin, affecting directly or indirectly (through miRNAs) the expression of post-transcriptional regulators, eventually leading to increased alternative linear splicing and decreased circRNAs biogenesis. …”

Latencies are linear functions of pheromone dose with different parameter values in each neuron. by Jean-Pierre Rospars (44871)

Supplementary Material for: Modelling Childhood Growth Using Fractional Polynomials and Linear Splines by Tilling K. (4145887)

“…Here, we demonstrate multilevel models for childhood growth either as a smooth function (using fractional polynomials) or a set of connected linear phases (using linear splines). …”

Structure diagram of ensemble model. by Hongqi Wang (2208238)

“…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”

Fitting formula parameter table. by Hongqi Wang (2208238)

“…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”

Test plan. by Hongqi Wang (2208238)

“…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”

Fitting surface parameters. by Hongqi Wang (2208238)

“…Furthermore, we quantitatively analyze the specific influence of water content and other factors on the thermal conductivity of stabilized soil and construct a comprehensive prediction model encompassing BP neural network, gradient boosting decision tree, and linear regression models. …”