Thermal recoil force, telemetry, and the Pioneer anomaly

Precision navigation of spacecraft requires accurate knowledge of small forces, including the recoil force due to anisotropies of thermal radiation emitted by spacecraft systems. We develop a formalism to derive the thermal recoil force from the basic principles of radiative heat exchange and energy-momentum conservation. The thermal power emitted by the spacecraft can be computed from engineering data obtained from flight telemetry, which yields a practical approach to incorporate the thermal recoil force into precision spacecraft navigation. Alternatively, orbit determination can be used to estimate the contribution of the thermal recoil force. We apply this approach to the Pioneer anomaly using a simulated Pioneer 10 Doppler data set.Comment: 10 pages, 3 figures. Published versio

Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types

Background:There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually.Methods:In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data.Results:We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap.Conclusions:Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the inter-active knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs

New and extended parameterization of the thermodynamic model AIOMFAC: calculation of activity coefficients for organic-inorganic mixtures containing carboxyl, hydroxyl, carbonyl, ether, ester, alkenyl, alkyl, and aromatic functional groups

We present a new and considerably extended parameterization of the thermodynamic activity coefficient model AIOMFAC (Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients) at room temperature. AIOMFAC combines a Pitzer-like electrolyte solution model with a UNIFAC-based group-contribution approach and explicitly accounts for interactions between organic functional groups and inorganic ions. Such interactions constitute the salt-effect, may cause liquid-liquid phase separation, and affect the gas-particle partitioning of aerosols. The previous AIOMFAC version was parameterized for alkyl and hydroxyl functional groups of alcohols and polyols. With the goal to describe a wide variety of organic compounds found in atmospheric aerosols, we extend here the parameterization of AIOMFAC to include the functional groups carboxyl, hydroxyl, ketone, aldehyde, ether, ester, alkenyl, alkyl, aromatic carbon-alcohol, and aromatic hydrocarbon. Thermodynamic equilibrium data of organic-inorganic systems from the literature are critically assessed and complemented with new measurements to establish a comprehensive database. The database is used to determine simultaneously the AIOMFAC parameters describing interactions of organic functional groups with the ions H^+, Li^+, Na^+, K^+, NH_(4)^+, Mg^(2+), Ca^(2+), Cl^−, Br^−, NO_(3)^−, HSO_(4)^−, and SO_(4)^(2−). Detailed descriptions of different types of thermodynamic data, such as vapor-liquid, solid-liquid, and liquid-liquid equilibria, and their use for the model parameterization are provided. Issues regarding deficiencies of the database, types and uncertainties of experimental data, and limitations of the model, are discussed. The challenging parameter optimization problem is solved with a novel combination of powerful global minimization algorithms. A number of exemplary calculations for systems containing atmospherically relevant aerosol components are shown. Amongst others, we discuss aqueous mixtures of ammonium sulfate with dicarboxylic acids and with levoglucosan. Overall, the new parameterization of AIOMFAC agrees well with a large number of experimental datasets. However, due to various reasons, for certain mixtures important deviations can occur. The new parameterization makes AIOMFAC a versatile thermodynamic tool. It enables the calculation of activity coefficients of thousands of different organic compounds in organic-inorganic mixtures of numerous components. Models based on AIOMFAC can be used to compute deliquescence relative humidities, liquid-liquid phase separations, and gas-particle partitioning of multicomponent mixtures of relevance for atmospheric chemistry or in other scientific fields

Numerical Capture and Validation of a Massively Separated Bluff-Body Wake

A flow over a bluff-body is numerically investigated and validated using a Detached-Eddy Simulation (DES) technique at Re=21,400. An incompressible solver that is nominally second-order accurate employing an implicit constant backward time-stepping scheme with blended upwind-central differencing spatial discretization is used to study the massively separated wake that is generated. Measurements are taken up to 6 downstream characteristic lengths, evaluating the wake time-averaged first- and second-moment statistics alongside near-wall boundary layer quantities and surface-force integrals. Results advocate the use of DES methods, which are found to be significantly more accurate for capturing wake statistics, compared to two different Reynolds-Averaged (RANS) models calibrated with an identical grid. Although comparative accuracy can be obtained with the RANS techniques for the boundary layer and surface-forces, these techniques are unsuitable for modeling wake statistics as they are inherently dissipative, evident through early velocity recovery when evaluated against experimental data

Laboratory investigation of lateral dispersion within dense arrays of randomly distributed cylinders at transitional Reynolds number

Published versio

Efficient Characterization and Modelling of the Nonlinear Behaviour of LFT for Crash Simulations

Modeling the nonlinear material behaviour of long fiber reinforced thermoplastics (LFT) presents a challenging task since local inhomogeneities and nonlinear effects must be taken into account also on the microscale. We present a computational method with which we can predict the nonlinear material response of a composite material using only standard DMA measurements on the pure polymer matrix material. The material models considered include plasticity, damage, viscoelasticity, and viscoplasticity as described in [1]. These models can be combined similar to the model from [2] and extended to the composite by assigning linear elastic properties to the fibers. The mechanical response of the composite is computed using an FFT-based technique [3]. The geometry of the composite, in particular the fiber orientation, can be characterized using injection molding simulations or micro CT scans. We create virtual models of the composite using the algorithm of [4]. We show that with this method, the material behaviour of the composite can be predicted while the experimental complexity needed for the material characterization is low

Surface Tension of Seawater

New measurements and a reference correlation for the surface tension of seawater at atmospheric pressure are presented in this paper. Surface tension of seawater was measured across a salinity range of 20 ⩽ S ⩽ 131 g/kg and a temperature range of 1 ⩽ t ⩽ 92 °C at atmospheric pressure using the Wilhelmy plate method. The uncertainty within measurements varied from 0.18 to 0.37 mN/m with the average uncertainty being 0.22 mN/m. The experimental procedures were validated with tests conducted on ACS reagent grade water and aqueous sodium chloride solutions. Literature data and present measurements were evaluated and a reference correlation was developed expressing surface tension of seawater as a function of temperature and salinity. The average absolute percentage deviation between measurements and the correlation was 0.19% while the maximum deviation was 0.60%.Center for Clean Water and Clean Energy at MIT and KFUPM (Project R13-CW-10

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome

Phospho.ELM: a database of phosphorylation sites—update 2011

The Phospho.ELM resource (http://phospho.elm.eu.org) is a relational database designed to store in vivo and in vitro phosphorylation data extracted from the scientific literature and phosphoproteomic analyses. The resource has been actively developed for more than 7 years and currently comprises 42 574 serine, threonine and tyrosine non-redundant phosphorylation sites. Several new features have been implemented, such as structural disorder/order and accessibility information and a conservation score. Additionally, the conservation of the phosphosites can now be visualized directly on the multiple sequence alignment used for the score calculation. Finally, special emphasis has been put on linking to external resources such as interaction networks and other databases