The Celestial Frame and the Weighting of the Celestial Pole Offsets in the Computation of VLBI-Based Corrections for the Main Lunisolar Nutation Terms

Very long baseline interferometry (VLBI) is the only technique in space geodesy that can determine directly the celestial pole offsets (CPO). In this paper, we make use of the CPO derived from global VLBI solutions to estimate empirical corrections to the main lunisolar nutation terms included in the IAU 2006/2000A precession–nutation model. In particular, we pay attention to two factors that affect the estimation of such corrections: the celestial reference frame used in the production of the global VLBI solutions and the stochastic model employed in the least-squares adjustment of the corrections. In both cases, we have found that the choice of these aspects has an effect of a few μas in the estimated corrections.

Near-infrared Supernova Ia Distances: Host Galaxy Extinction and Mass-step Corrections Revisited

We present optical and near-infrared (NIR, Y-, J-, H-band) observations of 42 Type Ia supernovae (SNe Ia) discovered by the untargeted intermediate Palomar Transient Factory survey. This new data set covers a broad range of redshifts and host galaxy stellar masses, compared to previous SN Ia efforts in the NIR. We construct a sample, using also literature data at optical and NIR wavelengths, to examine claimed correlations between the host stellar masses and the Hubble diagram residuals. The SN magnitudes are corrected for host galaxy extinction using either a global total-to-selective extinction ratio, R V = 2.0, for all SNe, or a best-fit R V for each SN individually. Unlike previous studies that were based on a narrower range in host stellar mass, we do not find evidence for a “mass step,” between the color- and stretch-corrected peak J and H magnitudes for galaxies below and above log ( M * / M ⊙ ) = 10 . However, the mass step remains significant (3σ) at optical wavelengths (g, r, i) when using a global R V , but vanishes when each SN is corrected using their individual best-fit R V . Our study confirms the benefits of the NIR SN Ia distance estimates, as these are largely exempted from the empirical corrections dominating the systematic uncertainties in the optical.

High precision evaluation of the combustion enthalpy by ab-intio computations

Accurate evaluation of combustion enthalpy is of high scientific and industrial importance. Although via ab-initio computation of heat of reactions, as one of the promising and well-established approaches in computational chemistry, this goal should in principle be achievable, examples of reliable and precise evaluation of heat of combustion by ab-initio methods has surprisingly not yet been reported. A handful of works carried out for this purpose report significant inconsistencies between the ab-initio evaluated and experimentally determined combustion enthalpies and suggest empirical corrections to improve the accuracy of predicted data. With this background, the main aims of the present study is to investigate the reasons behind those reported inconsistencies and propose guidelines for highly accurate evaluation of combustion enthalpy via ab-initio computations. Through the provided guidelines, the most accurate results ever reported, with average absolute deviation, mean unsigned error and correlation coefficient of 1.556 kJ/mole, 0.072% and 0.99999, respectively, is achieved for theoretically computed combustion enthalpies of 40 studied hydrocarbons.

Understanding Conformational Entropy in Small Molecules

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

HYDRAULIC CHARACTERISTICS OF INJECTION FLOW REGULATORS

The effi ciency of the irrigation system can be increased by reducing unproductive waterdischarges from channels. Hydrodynamic fl ow regulators control water supply on demandand are activated when water consumption in the downstream of the structure is reducedbelow the design value. Many works have been devoted to the theoretical and experimentalstudy of the hydraulic characteristics of the structures under consideration, but no universaldependence has yet been obtained for directly determining the amount of fl ow rates thatmerge in the regulator and the accuracy of water supply. The generally accepted schemefor merging fl ows in the regulator was the fl ow scheme in the exhaust tee, which later requiredmaking empirical corrections to align the theoretical dependencies with experimental data.In this paper, a fundamentally new approach to the calculation of hydrodynamic regulatorsis proposed – consideration of their operation as injection devices and the applicationof appropriate computational dependencies. The results of theoretical calculations arecompared with the existing data of experimental study of several versions of the fl ow partof the regulators. The output section of all structures was made in the form of a pyramidaldiffuser with a continuous fl ow. The fl ow coming from the upstream to the downstream wasinjecting, the fl ow circulating between the mixing chamber and the outlet section of the diffuserwas injectable. Comparison of experimental data and the obtained theoretical curve showeda good match. As a result of the research, it was found out that the accuracy of regulation canbe set by purposefully maintaining the necessary water horizon in the space above the diffuserand linking it with the amount of fl ow coming from the downstream through the spillway.

SAMPL7 Challenge Overview: Assessing the Reliability of Polarizable and Non-Polarizable Methods for Host-Guest Binding Free Energy Calculations

The SAMPL challenges focus on testing and driving progress of computational methods to help guide pharmaceutical drug discovery. However, assessment of methods for predicting binding affinities is often hampered by computational challenges such as conformational sampling, protonation state uncertainties, variation in test sets selected, and even lack of high quality experimental data. SAMPL blind challenges have thus frequently included a component focusing on host-guest binding, which removes some of these challenges while still focusing on molecular recognition. Here, we report on the results of the SAMPL7 blind prediction challenge for host-guest affinity prediction. In this study, we focused on three different host-guest categories -- a familiar deep cavity cavitand series which has been featured in several prior challenges (where we examine binding of a series of guests to two hosts), a new series of cyclodextrin derivatives which are monofunctionalized around the rim to add amino acid-like functionality (where we examine binding of a two guests to a series of hosts), and binding of a series of guests to a new acyclic TrimerTrip host which is related to previous cucurbituril hosts. Many predictions used methods based on molecular simulations, and overall success was mixed, though several methods stood out. As in SAMPL6, we find that one strategy for achieving reasonable accuracy here was to make empirical corrections to binding predictions based on previous data for host categories which have been studied well before, though this can be of limited value when new systems are included. Additionally, we found that methods using the AMOEBA polarizable force field had considerable success for the two host categories in which they participated. The new TrimerTrip system was also found to introduce some sampling problems, because multiple conformations may be relevant to binding and interconvert only slowly. Overall, results in this challenge tentatively suggest that further investigation of polarizable force fields for these challenges may be warranted.

Understanding Conformational Entropy in Small Molecules

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

Understanding Conformational Entropy in Small Molecules

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

Recovering λR and V/σ from seeing-dominated IFS data

ABSTRACT Observers experience a series of limitations when measuring galaxy kinematics, such as variable seeing conditions and aperture size. These effects can be reduced using empirical corrections, but these equations are usually applicable within a restrictive set of boundary conditions (e.g. Sérsic indices within a given range) that can lead to biases when trying to compare measurements made across a full kinematic survey. In this work, we present new corrections for two widely used kinematic parameters, λR and V/σ, that are applicable across a broad range of galaxy shapes, measurement radii, and ellipticities. We take a series of mock observations of N-body galaxy models and use these to quantify the relationship between the observed kinematic parameters, structural properties, and different seeing conditions. Derived corrections are then tested using the full catalogue of galaxies, including hydrodynamic models from the eagle simulation. Our correction is most effective for regularly rotating systems, yet the kinematic parameters of all galaxies – fast, slow, and irregularly rotating systems – are recovered successfully. We find that λR is more easily corrected than V/σ, with relative deviations of 0.02 and 0.06 dex, respectively. The relationship between λR and V/σ, as described by the parameter κ, also has a minor dependence on seeing conditions. These corrections will be particularly useful for stellar kinematic measurements in current and future integral field spectroscopic surveys of galaxies.