Hyperconjugation Involving Strained Carbon–Carbon Bonds. Structural Analysis of Ester and Ether Derivatives and One-Bond ¹³C–¹³C Coupling Constants of α- and... by Shinn Dee Yeoh (2001157)

“…These hyperconjugative interactions are manifested as a strong response of the C–OR bond distance to the electron demand of the OR substituent. …”

Hyperconjugation Involving Strained Carbon–Carbon Bonds. Structural Analysis of Ester and Ether Derivatives and One-Bond ¹³C–¹³C Coupling Constants of α- and... by Shinn Dee Yeoh (2001157)

“…These hyperconjugative interactions are manifested as a strong response of the C–OR bond distance to the electron demand of the OR substituent. …”

Hyperconjugation Involving Strained Carbon–Carbon Bonds. Structural Analysis of Ester and Ether Derivatives and One-Bond ¹³C–¹³C Coupling Constants of α- and... by Shinn Dee Yeoh (2001157)

“…These hyperconjugative interactions are manifested as a strong response of the C–OR bond distance to the electron demand of the OR substituent. …”

Cellular interaction network of proteins identified with dynamic MAM localization during RNA virus replication. by Stacy M. Horner (178713)

“…Previously described MAVS-interacting proteins (MAVS, MFN1, MFN2, C1QBP, AMFR, and TOMM70) are highlighted by large red circles. Nodes representing each protein were positioned on a cell map according to subcellular localization using annotation information from InnateDb.…”

Hyperconjugation Involving Strained Carbon–Carbon Bonds. Structural Analysis of Ester and Ether Derivatives and One-Bond ¹³C–¹³C Coupling Constants of α- and... by Shinn Dee Yeoh (2001157)

“…These hyperconjugative interactions are manifested as a strong response of the C–OR bond distance to the electron demand of the OR substituent. …”

The Role of Electrostatic Interactions in Binding of Histone H3K4me2/3 to the Sgf29 Tandem Tudor Domain by Bas J. G. E. Pieters (801824)

“…Herein, we report thermodynamic analyses for the recognition of histone H3K4me3 and H3K4me2 by the tandem tudor domain of Sgf29 and its recognition site variants. Small uncharged and large aromatic substitutions on the Asp266 site resulted in a significant decrease in binding affinities for both H3K4me3 and H3K4me2, demonstrating the role of the negative charge of Asp266 in the readout process by Sgf29. …”

Activity Monitor Intervention to Promote Physical Activity of Physicians-In-Training: Randomized Controlled Trial by Anne N. Thorndike (581111)

“…</p><p>Methods</p><p>We conducted a two-phase intervention among 104 medical residents at a large hospital in Boston, Massachusetts. …”

Muscle activities during walking and running at energetically optimal transition speed under normobaric hypoxia on gradient slopes by Daijiro Abe (797293)

“…<div><p>Energy cost of transport per unit distance (CoT; J·kg^-1·km^-1) displays a U-shaped fashion in walking and a linear fashion in running as a function of gait speed (<i>v</i>; km·h^-1). …”

Plasma and hepatic reaction to acute estrogen exposure. by Clémentine Chalmey (5657233)

“…*p<0.05 (two-way ANOVA, followed by Tukey test). <b>a</b> shows an increase from PND0, <b>b</b> shows a decrease from PND1, <b>c</b> shows a decrease from PND3 and <b>*</b> shows a difference from the age-matched control group.…”

Urodynamics. by Pauline M. L. Hennus (136676)

“…</p><p>Bladder hypocontractility = maximal detrusor pressure (Pdetmax)<20 cmH₂O.</p><p>Decreased BC = BC>20% smaller than expected BC for age.…”

DataSheet_1_Coral reef island shoreline change and the dynamic response of the freshwater lens, Huvadhoo Atoll, Maldives.docx by Lucy Carruthers (16398129)

“…The magnitudes and rates of reef island evolution were found to be highly site-specific, with island type found to be the only significant predictor of either net shoreline movement or weighted linear regression. Results suggest that freshwater lens volume was substantially impacted by shoreline change compared to changes in recharge whereby accretion and erosion led to large increases (up to 65.05%) decreases (up to -50.4%) in les volume, respectively. …”

The Trade-Off between Spatial and Temporal Variabilities in Reciprocal Upper-Limb Aiming Movements of Different Durations by Frederic Danion (482841)

“…<div><p>The spatial and temporal aspects of movement variability have typically been studied separately. As a result the relationship between spatial and temporal variabilities remains largely unknown. …”

Biodiversity Effects on Plant Stoichiometry by Maike Abbas (384938)

“…In addition to diversity effects on mean ratios, higher species richness consistently decreased the variance of chemical composition for all elemental ratios. …”

Cerebral Hemodynamics in Patients with Hemolytic Uremic Syndrome Assessed by Susceptibility Weighted Imaging and Four-Dimensional Non-Contrast MR Angiography by Ulrike Löbel (3325251)

“…TTP ranged from 3.7 to 10.2 frames (mean, 7.9 ± 1.4). Hemoglobin at the time of MRI (n = 35) was decreased in all patients (range, 5.0 to 12.6 g/dL; mean, 8.2 ± 1.4); hematocrit (n = 33) was abnormally low in all but a single patient (range, 14.3 to 37.2%; mean, 23.7 ± 4.2). …”

Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults by Salvatore Tedesco (6029417)

“…A large mean absolute percentage error (MAPE) was found for every monitor at slower walking speeds with the lowest reported MAPE at 2 km/h being 7.78%, increasing to 20.88% at 1.5 km/h, and 44.53% at 1 km/h. …”

Table_2_Early apixaban administration considering the size of infarction and functional outcome in acute ischemic stroke.DOCX by Min Hwan Lee (1657279)

“…Background and purpose<p>Atrial fibrillation-related stroke (AF-stroke) is associated with an adverse prognosis, characterized by a high incidence of progression, recurrence, and hemorrhagic transformation. …”

Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Suppression of Dendrite Formation in Lithium Metal Anodes by Zeeshan Ahmad (31617)

“…The machine-learning models are trained on purely structural features of the material, which do not require any first-principles calculations. We train a graph convolutional neural network on the shear and bulk moduli because of the availability of a large training data set with low noise due to low uncertainty in their first-principles-calculated values. …”

Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Suppression of Dendrite Formation in Lithium Metal Anodes by Zeeshan Ahmad (31617)

“…The machine-learning models are trained on purely structural features of the material, which do not require any first-principles calculations. We train a graph convolutional neural network on the shear and bulk moduli because of the availability of a large training data set with low noise due to low uncertainty in their first-principles-calculated values. …”

Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Suppression of Dendrite Formation in Lithium Metal Anodes by Zeeshan Ahmad (31617)

“…The machine-learning models are trained on purely structural features of the material, which do not require any first-principles calculations. We train a graph convolutional neural network on the shear and bulk moduli because of the availability of a large training data set with low noise due to low uncertainty in their first-principles-calculated values. …”

Table_1_Early apixaban administration considering the size of infarction and functional outcome in acute ischemic stroke.DOCX by Min Hwan Lee (1657279)

“…Background and purpose<p>Atrial fibrillation-related stroke (AF-stroke) is associated with an adverse prognosis, characterized by a high incidence of progression, recurrence, and hemorrhagic transformation. …”