scholarly journals Enhancing Carbon Acid pKa Prediction by Augmentation of Sparse Experimental Datasets with Accurate AIBL (QM) Derived Values

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1048
Author(s):  
Jeffrey Plante ◽  
Beth A. Caine ◽  
Paul L. A. Popelier
Keyword(s):  
Experimental Data ◽  
Prediction Method ◽  
Structure Property ◽  
Computationally Efficient ◽  
Atom Type ◽  
Pka Prediction ◽  
High Performing ◽  
Carbon Acids ◽  
External Test ◽  
The Impact

The prediction of the aqueous pKa of carbon acids by Quantitative Structure Property Relationship or cheminformatics-based methods is a rather arduous problem. Primarily, there are insufficient high-quality experimental data points measured in homogeneous conditions to allow for a good global model to be generated. In our computationally efficient pKa prediction method, we generate an atom-type feature vector, called a distance spectrum, from the assigned ionisation atom, and learn coefficients for those atom-types that show the impact each atom-type has on the pKa of the ionisable centre. In the current work, we augment our dataset with pKa values from a series of high performing local models derived from the Ab Initio Bond Lengths method (AIBL). We find that, in distilling the knowledge available from multiple models into one general model, the prediction error for an external test set is reduced compared to that using literature experimental data alone.

scholarly journals Generalized Joint Hypermobility and Anxiety in Adolescents and Young Adults, the Impact on Physical and Psychosocial Functioning

Healthcare ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 525
Author(s):  
Janneke de Vries ◽  
Jeanine Verbunt ◽  
Janine Stubbe ◽  
Bart Visser ◽  
Stephan Ramaekers ◽  
...  
Keyword(s):  
Young Adults ◽  
Psychosocial Functioning ◽  
Negative Impact ◽  
Pain Catastrophizing ◽  
Joint Hypermobility ◽  
Adolescents And Young Adults ◽  
P Value ◽  
High Performing ◽  
Generalized Joint Hypermobility ◽  
The Impact

The purpose of this study was to study the association between the presence of generalized joint hypermobility (GJH) and anxiety within a non-clinical high performing group of adolescents and young adults. Second, to study the impact of GJH and/or anxiety on physical and psychosocial functioning, 168 adolescents and young adults (mean (SD) age 20 (2.9)) were screened. Joint (hyper)mobility, anxiety, and physical and psychosocial functioning were measured. In 48.8% of all high performing adolescents and young adults, GJH was present, whereas 60% had symptoms of anxiety. Linear models controlled for confounders showed that adolescents and young adults with GJH and anxiety had decreased workload (ß (95%CI) −0.43 (−0.8 to −0.08), p-value 0.02), increased fatigue (ß (95%CI) 12.97 (6.3–19.5), p-value < 0.01), and a higher level of pain catastrophizing (ß (95%CI) 4.5 (0.5–8.6), p-value 0.03). Adolescents and young adults with only anxiety had increased fatigue (ß (95%CI) 11 (4.9–19.5). In adolescents and young adults with GJH alone, no impact on physical and psychosocial functioning was found. Adolescents and young adults with the combination of GJH and anxiety were significantly more impaired, showing decreased physical and psychosocial functioning with decreased workload, increased fatigue, and pain catastrophizing. Presence of GJH alone had no negative impact on physical and psychosocial functioning. This study confirms the association between GJH and anxiety, but especially emphasizes the disabling role of anxiety. Screening for anxiety is relevant in adolescents and young adults with GJH and might influence tailored interventions.

SOME CHARACTERISTICS OF THE COMPOUND MULTIPLICITY IN HIGH-ENERGY NUCLEUS–NUCLEUS INTERACTIONS

2011 ◽  
Vol 20 (08) ◽  
pp. 1735-1754 ◽  
Author(s):  
M. MOHERY ◽  
M. ARAFA
Keyword(s):  
Experimental Data ◽  
Impact Parameter ◽  
Mass Number ◽  
Multiplicity Distribution ◽  
High Energy ◽  
Projectile Nucleus ◽  
Target Mass ◽  
Compound Multiplicity ◽  
Multiplicity Distributions ◽  
The Impact

The present paper deals with the interactions of 22 Ne and 28 Si nuclei at (4.1–4.5)A GeV /c with emulsion. Some characteristics of the compound multiplicity nc given by the sum of the number of shower particles ns and grey particles ng have been investigated. The present experimental data are compared with the corresponding ones calculated according to modified cascade evaporation model (MCEM). The results reveal that the compound multiplicity distributions for these two reactions are consistent with the corresponding ones of MCEM data. It can also be seen that the peak of these distributions shifts towards a higher value of nc with increasing projectile mass. It may further be seen that the compound multiplicity distributions becomes broader with increasing target size and its width increases with the size of the projectile nucleus. In addition, it has been found that the MCEM can describe the compound multiplicity characteristics of the different projectile, target and the correlation between different emitted particles. The values of average compound multiplicity increase with increasing mass of the projectile. Furthermore, it is observed that while the value of 〈nc〉 depends on the mass number of the projectile Ap and the target mass number At, the value of the ratio 〈nc〉/D(nc) seems to be independent of Ap and At. The impact parameter is found to affect the shape of the compound multiplicity distribution. Finally, the dependence of the average compound multiplicity on the numbers of grey and black particles, and the sum of them, is obvious. The values of the slope have been found to be independent of the projectile nucleus.

The Impact of Stationarity, Regularity, and Context on the Predictability of Individual Human Mobility

2021 ◽  
Vol 7 (4) ◽  
pp. 1-24
Author(s):  
Douglas Do Couto Teixeira ◽  
Aline Carneiro Viana ◽  
Jussara M. Almeida ◽  
Mrio S. Alvim
Keyword(s):  
State Of The Art ◽  
Human Mobility ◽  
Contextual Information ◽  
Prediction Method ◽  
Mobility Prediction ◽  
Mobility Patterns ◽  
Distinct Cell ◽  
Inherent Nature ◽  
The One ◽  
The Impact

Predicting mobility-related behavior is an important yet challenging task. On the one hand, factors such as one’s routine or preferences for a few favorite locations may help in predicting their mobility. On the other hand, several contextual factors, such as variations in individual preferences, weather, traffic, or even a person’s social contacts, can affect mobility patterns and make its modeling significantly more challenging. A fundamental approach to study mobility-related behavior is to assess how predictable such behavior is, deriving theoretical limits on the accuracy that a prediction model can achieve given a specific dataset. This approach focuses on the inherent nature and fundamental patterns of human behavior captured in that dataset, filtering out factors that depend on the specificities of the prediction method adopted. However, the current state-of-the-art method to estimate predictability in human mobility suffers from two major limitations: low interpretability and hardness to incorporate external factors that are known to help mobility prediction (i.e., contextual information). In this article, we revisit this state-of-the-art method, aiming at tackling these limitations. Specifically, we conduct a thorough analysis of how this widely used method works by looking into two different metrics that are easier to understand and, at the same time, capture reasonably well the effects of the original technique. We evaluate these metrics in the context of two different mobility prediction tasks, notably, next cell and next distinct cell prediction, which have different degrees of difficulty. Additionally, we propose alternative strategies to incorporate different types of contextual information into the existing technique. Our evaluation of these strategies offer quantitative measures of the impact of adding context to the predictability estimate, revealing the challenges associated with doing so in practical scenarios.

The penetration and ricochet of ogive-nosed rigid projectiles obliquely impacting metallic targets

2021 ◽  
pp. 204141962110377
Author(s):  
Yaniv Vayig ◽  
Zvi Rosenberg
Keyword(s):  
Experimental Data ◽  
Numerical Simulations ◽  
Dynamic Pressure ◽  
Oblique Impacts ◽  
Simulation Results ◽  
The Impact ◽  
Penetration Depths ◽  
Resistance To Penetration ◽  
Good Agreement

A large number of 3D numerical simulations were performed in order to follow the trajectory changes of rigid CRH3 ogive-nosed projectiles, impacting semi-infinite metallic targets at various obliquities. These trajectory changes are shown to be related to the threshold ricochet angles of the projectile/target pairs. These threshold angles are the impact obliquities where the projectiles end up moving in a path parallel to the target’s face. They were found to depend on a non-dimensional entity which is equal to the ratio between the target’s resistance to penetration and the dynamic pressure exerted by the projectile upon impact. Good agreement was obtained by comparing simulation results for these trajectory changes with experimental data from several published works. In addition, numerically-based relations were derived for the penetration depths of these ogive-nosed projectiles at oblique impacts, which are shown to agree with the simulation results.

Dynamics of Trust in Automation and Interactive Decision Making during Driving Simulation Tasks

2021 ◽  
Vol 65 (1) ◽  
pp. 786-790
Author(s):  
Lucero Rodriguez Rodriguez ◽  
Carlos Bustamante Orellana ◽  
Jayci Landfair ◽  
Corey Magaldino ◽  
Mustafa Demir ◽  
...  
Keyword(s):  
Decision Making ◽  
Automated System ◽  
Automated Driving ◽  
Safety And Efficacy ◽  
High Performing ◽  
Interactive Decision Making ◽  
Driving Task ◽  
Preliminary Study ◽  
Self Driving Cars ◽  
The Impact

As technological advancements and lowered costs make self-driving cars available to more people, it becomes important to understand the dynamics of human-automation interactions for safety and efficacy. We used a dynamical approach to examine data from a previous study on simulated driving with an automated driving assistant. To maximize effect size in this preliminary study, we focused the current analysis on the two lowest and two highest-performing participants. Our visual comparisons were the utilization of the automated system and the impact of perturbations. Low-performing participants toggled and maintained reliance either on automation or themselves for longer periods of time. Decision making of high-performing participants was using the automation briefly and consistently throughout the driving task. Participants who displayed an early understanding of automation capabilities opted for tactical use. Further exploration of individual differences and automation usage styles will help to understand the optimal human-automation-team dynamic and increase safety and efficacy.

Ozone Production With Plasma Discharge: Comparisons Between Activated Air and Activated Fuel/Air Mixture

2021 ◽  
Author(s):  
Ghazanfar Mehdi ◽  
Maria Grazia De Giorgi ◽  
Donato Fontanarosa ◽  
Sara Bonuso ◽  
Antonio Ficarella
Keyword(s):  
Experimental Data ◽  
Plasma Chemistry ◽  
Kinetic Scheme ◽  
Plasma Discharge ◽  
Chemical Kinetic ◽  
Ozone Production ◽  
Air Plasma ◽  
Flammability Limits ◽  
Combustion Enhancement ◽  
The Impact

Abstract This study focused on the comparative analysis about the production of ozone and active radicals in presence of nanopulsed plasma discharge on air and on fuel/air mixture to investigate its effect on combustion enhancement. This analysis is based on numerical modeling of air and methane/air plasma discharge with different repetition rates (100 Hz, 1000 Hz and 10000 Hz). To this purpose, a two-step approach has been proposed based on two different chemistry solvers: a 0-D plasma chemistry solver (ZDPlasKin toolbox) and a combustion chemistry solver (CHEMKIN software suite). Consequently, a comprehensive chemical kinetic scheme was generated including both plasma excitation reactions and gas phase reactions. Validation of air and methane/air mechanisms was performed with experimental data. Kinetic models of both air and methane/air provides good fitting with experimental data of O atom generation and decay process. ZDPlasKin results were introduced in CHEMKIN in order to analyze combustion enhancement. It was found that the concentrations of O3 and O atom in air are higher than the methane/air activation. However, during the air activation peak concentration of ozone was significantly increased with repetition rates and maximum was observed at 10000 Hz. Furthermore, ignition timings and flammability limits were also improved with air and methane/air activation but the impact of methane/air activation was comparatively higher.

Abstract P457: Systems Analysis To Understand The Impact Of The CDK Module On Cardiomyocyte Proliferation

2021 ◽  
Vol 129 (Suppl_1) ◽  
Author(s):  
Bryana N Harris ◽  
Laura Woo ◽  
Jeffrey J Saucerman
Keyword(s):  
Experimental Data ◽  
Cell Cycle ◽  
Transcription Factor ◽  
Dna Synthesis ◽  
Current Knowledge ◽  
Cycle Phase ◽  
Cyclin D ◽  
Cardiomyocyte Proliferation ◽  
The Core ◽  
The Impact

Rationale: Heart failure is caused by the inability of adult mammalian hearts to overcome the loss of cardiomyocytes (CMs). This is due partly to the limited proliferative capacity of CMs, which exit the cell cycle and do not undergo cell division. Current knowledge in cardiac regeneration lacks an understanding of the molecular regulatory networks that determine whether CMs will progress through the cell cycle to proliferate. Our goal is to use computational modeling to understand the expression and activation levels of the core cell cycle network, specifically cyclins and cyclin-cyclin-dependent kinase (CDK) complexes. Methods: A model of core cell cycle dynamics was curated using previously published studies of CM proliferation regulators. This model incorporates those regulators known to stimulate G1/S and G2/M transitions through the core CDKs. The activity of each of the 22 network nodes (22 reactions) was predicted using a logic-based differential equation approach. The CDK model was then coupled with a minimal ODE model of cell cycle phase distributions and validated based on descriptions and experimental data from the literature. To prioritize key nodes for experimental validation, we performed a sensitivity analysis by stimulating individual knockdown for every node in the network, measuring the fractional activity of all nodes. Results: Our model confirmed that the knockdown of p21 and Rb protein and the overexpression of E2F transcription factor and cyclinD-cdk4 showed an increase in cells going through DNA synthesis and entering mitosis. A combined knockdown of p21 and p27 showed an increase of cells entering mitosis. Cyclin D-cdk4 and p21 overexpression showed a decrease and increase of Rb expression, respectively. Of the 14 model predictions, 12 agreed with experimental data in the literature. A comprehensive knockdown of the model nodes suggests that E2F (a key transcription factor driving DNA synthesis) is positively regulated by cyclin D while negatively regulated by GSK3B, SMAD3, and pRB. Conclusion: This model enables us to predict how cardiomyocytes respond to stimuli in the CDK network and identify potential therapeutic regulators that induce cardiomyocyte proliferation.

scholarly journals Studying the Impact of Radioactive Charging on the Microphysical Evolution and Transport of Radioactive Aerosols with the TOMAS-RC v1 framework

2017 ◽  
Author(s):  
Petros Vasilakos ◽  
Yong-Ηa Kim ◽  
Jeffrey R. Pierce ◽  
Sotira Yiacoumi ◽  
Costas Tsouris ◽  
...  
Keyword(s):  
Background Radiation ◽  
Atmospheric Transport ◽  
Long Range Transport ◽  
Radioactive Aerosol ◽  
Computationally Efficient ◽  
Radioactive Aerosols ◽  
Model Studies ◽  
Aerosol Mass ◽  
Range Transport ◽  
The Impact

Abstract. Radioactive charging can significantly impact the way radioactive aerosols behave, and as a result their lifetime, but such effects are neglected in predictive model studies of radioactive plumes. The objective of this work is to determine the influence of radioactive charging on the vertical transport of radioactive aerosols in the atmosphere, through its effect on coagulation and deposition, as well as quantifying the impact of this charging on aerosol lifetime. The TwO-Moment Aerosol Sectional (TOMAS) microphysical model was extended to account for radioactive charging effects on coagulation in a computationally efficient way. The expanded model, TOMAS-RC (TOMAS with Radioactive Charging effects), was then used to simulate the microphysical evolution and deposition of radioactive aerosol (containing the isotopes 131I and 137Cs) in a number of idealized atmospheric transport experiments. Results indicate that radioactive charging can facilitate or suppress coagulation of radioactive aerosols, thus influencing the deposition patterns and total amount of radioactive aerosol mass available for long-range transport. Sensitivity simulations to uncertain parameters affirm the potential importance of radioactive charging effects. An important finding is that charging of neutral, coarse mode aerosol from background radiation can reduce coagulation rates and extend its lifetime in the atmosphere by up to a factor of 2.

Experimental and Simulation of a Cam and Translated Roller Follower Over a Range of Speeds

2016 ◽  
Author(s):  
Louay S. Yousuf ◽  
Dan B. Marghitu
Keyword(s):  
Experimental Data ◽  
Lyapunov Exponent ◽  
High Resolution ◽  
Lyapunov Exponents ◽  
Planar Motion ◽  
Largest Lyapunov Exponents ◽  
Set Up ◽  
The Impact ◽  
Impact With Friction

In this study a cam and follower mechanism is analyzed. There is a clearance between the follower and the guide. The mechanism is analyzed using SolidWorks simulations taking into account the impact and the friction between the roller follower and the guide. Four different follower guide’s clearances have been used in the simulations like 0.5, 1, 1.5, and 2 mm. An experimental set up is developed to capture the general planar motion of the cam and follower. The measures of the cam and the follower positions are obtained through high-resolution optical encoders (markers). The effect of follower guide’s clearance is investigated for different cam rotational speeds such as 100, 200, 300, 400, 500, 600, 700 and 800 R.P.M. Impact with friction is considered in our study to calculate the Lyapunov exponent. The largest Lyapunov exponents for the simulated and experimental data are analyzed and selected.

scholarly journals A New Model Approach for Convective Wall Heat Losses in DQMOM-IEM Simulations for Turbulent Reactive Flows

2018 ◽  
Vol 141 (5) ◽  
Author(s):  
Yeshaswini Emmi ◽  
Andreas Fiolitakis ◽  
Manfred Aigner ◽  
Franklin Genin ◽  
Khawar Syed
Keyword(s):  
Experimental Data ◽  
Heat Losses ◽  
Reacting Flow ◽  
Jet Flame ◽  
New Model ◽  
Turbulent Reactive Flows ◽  
Novel Method ◽  
The One ◽  
The Impact ◽  
Model Approach

A new model approach is presented in this work for including convective wall heat losses in the direct quadrature method of moments (DQMoM) approach, which is used here to solve the transport equation of the one-point, one-time joint thermochemical probability density function (PDF). This is of particular interest in the context of designing industrial combustors, where wall heat losses play a crucial role. In the present work, the novel method is derived for the first time and validated against experimental data for the thermal entrance region of a pipe. The impact of varying model-specific boundary conditions is analyzed. It is then used to simulate the turbulent reacting flow of a confined methane jet flame. The simulations are carried out using the DLR in-house computational fluid dynamics code THETA. It is found that the DQMoM approach presented here agrees well with the experimental data and ratifies the use of the new convective wall heat losses model.

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