Predicting binding energies of astrochemically relevant molecules via machine learning

The behaviour of molecules in space is to a large extent governed by where they freeze out or sublimate. The molecular binding energy is thus an important parameter for many astrochemical studies. This parameter is usually determined with time-consuming experiments, computationally expensive quantum chemical calculations, or the inexpensive, but inaccurate, linear addition method. In this work we propose a new method based on machine learning for predicting binding energies that is accurate, yet computationally inexpensive. A machine learning model based on Gaussian Process Regression is created and trained on a database of binding energies of molecules collected from laboratory experiments presented in the literature. The molecules in the database are categorized by their features, such as mono- or multilayer coverage, binding surface, functional groups, valence electrons, and H-bond acceptors and donors. The performance of the model is assessed with five-fold and leave-one-molecule-out cross validation. Predictions are generally accurate, with differences between predicted and literature binding energies values of less than $\pm$20\%. The validated model is used to predict the binding energies of twenty one molecules that have recently been detected in the interstellar medium, but for which binding energy values are not known. A simplified model is used to visualize where the snowlines of these molecules would be located in a protoplanetary disk. This work demonstrates that machine learning can be employed to accurately and rapidly predict binding energies of molecules. Machine learning complements current laboratory experiments and quantum chemical computational studies. The predicted binding energies will find use in the modelling of astrochemical and planet-forming environments.Comment: Accepted in astronomy and astrophysic

Serum galectin-1 in patients with multiple myeloma: associations with survival, angiogenesis, and biomarkers of macrophage activation

Galectin-1 (Gal-1) is known to regulate cell signaling within the immune system and may be a target for new anticancer immune therapy. In patients with chronic lymphocytic leukemia (CLL) and classical Hodgkin lymphoma (cHL), high levels of Gal-1 within the tumor microenvironment were associated with worse disease state or poor outcome. Gal-1 can be secreted from cells by an unknown mechanism, and levels in blood samples were associated with high tumor burden and worse disease state in cHL and CLL patients. However, serum levels of Gal-1 have never been investigated in patients with multiple myeloma (MM). We measured serum Gal-1 levels in samples from patients with treatment demanding MM at the time of diagnosis (n=102) and after treatment (n=24) and examined associations of serum Gal-1 with clinicopathological information obtained from patient medical records, as well as data on bone marrow angiogenesis and the macrophage activation biomarkers soluble CD163 (sCD163) and soluble mannose receptor. Serum Gal-1 levels were not elevated in patients with MM at diagnosis compared with healthy donors (median values 8.48 vs 11.93 ng/mL, P=0.05), which is in contrast to results in cHL and CLL. Furthermore, Gal-1 levels did not show association with bone marrow angiogenesis, clinicopathological parameters, overall survival, or response to treatment. There was a statically significant association between Gal-1 and sCD163 levels (R=0.24, P=0.02), but not with soluble mannose receptor (P=0.92). In conclusion, our results indicate that Gal-1 is not an important serum biomarker in MM, which is in contrast to data from patients with cHL and CLL. However, the association with sCD163 is in line with previous data showing that Gal-1 may be involved in alternative (M2-like) activation of macrophages

If Practice Makes Perfect, Where do we Stand?

Practitioners have played an important role in the information system (IS) field’s development since its beginnings. In the 1970s, IS researchers’ integration with practitioners was high with Society for Information Management members receiving copies of the MIS Quarterly, practitioners funding the ICIS Doctoral Consortium, and submissions receiving at least one practitioner review. Today, however, the integration between practitioners and researchers appears more distant. Given that almost 50 years have passed since the field’s development, we believe that we need to reflect on the past, present, and future relationship between IS research and IS practice. Has the distance between academics and practitioners become too great? Is our relevance too low to expect practitioners to join AIS and attend our conferences? How might we increase the integration? At a panel at ICIS 2018, several panelists provided position statements about those issues

IS 2009: Changing the Course for Undergraduate IS Model Curricula

In this panel, the joint AIS / ACM Information Systems undergraduate model curriculum task force members together with other curriculum experts will be presenting and discussing the IS 2009 Curriculum Guidelines for Undergraduate Degree Programs in Information Systems document and soliciting IS community feedback regarding ongoing IS curriculum development efforts. As such, the panel discussion will center on the significant components embedded in the newly revised curriculum document. This includes: 1) an introduction to the key principles that guided the development of the document, 2) a list of features incorporated into the new model curricula, 3) the future of curriculum development efforts, and 4) proposed mechanism to solicit feedback from the academy

Model for the low-temperature magnetic phases observed in doped YBa_2Cu_3O_{6+x}

A classical statistical model for the antiferromagnetic (AFM) ordering of the Cu-spins in the CuO_2 planes of reduced YBa_2Cu_3O_{6+x} type materials is presented. The magnetic phases considered are the experimentally observed high-temperature AFI phase with ordering vector Q_I=(1/2,1/2,0), and the low-temperature phases: AFII with Q_II=(1/2,1/2,1/2) and intermediate TA (Turn Angle) phases TAI, TAII and TAIII with components of both ordering vectors. It is shown that the AFII and TA phases result from an effective ferromagnetic (FM) type coupling mediated by free spins in the CuO_x basal plane. Good agreement with experimental data is obtained for realistic model parameters.Comment: 11 pages, 2 Postscript figures, Submitted to Phys.Rev.Let

Measurement of unique magnetic and superconducting phases in oxygen-doped high-temperature superconductors La_2-xSr_xCuO_4+y

We present a combined magnetic neutron scattering and muon spin rotation study of the nature of the magnetic and superconducting phases in electronically phase separated La(2-x)Sr(x)CuO(4+y), x = 0.04, 065, 0.09. For all samples, we find long-range modulated magnetic order below T_N ~ T_c = 39 K. In sharp contrast wit oxygen-stoichiometric La(2-x)Sr(x)CuO(4), we find that the magnetic propagation vector as well as the ordered magnetic moment is independent of Sr content and consistent with that of the 'striped' cuprates. Our study provides direct proof that superoxygenation in La(2-x)Sr(x)CuO(4+y) allows the spin stripe ordered phase to emerge and phase separate from superconducting regions with the hallmarks of optimally doped oxygen-stoichiometric La(2-x)Sr(x)CuO(4)