What Technical and Professional Skills are Needed for Cybersecurity Roles?

The Cybersecurity Skills Survey was designed to respond to the high-demand for cybersecurity professionals, noted by the findings of SIM (Society for Information Management) IT Trends and Issues Study (2017, 2018, 2019, 2020, 2021). The findings of the IT Trends and Issues Study are based upon input from over 1,000 IT leaders representing 37 SIM Chapters. The goals of the cybersecurity skills survey were to identify: (1) What technical skills are needed for entry-level professionals in cybersecurity jobs? (2) What professional skills are needed for entry level professionals in cybersecurity jobs? (3) What technical skills are needed for early-career professionals in cybersecurity jobs? and (4) What professional skills are needed for early-career professionals in cybersecurity jobs? The survey findings provide key insights into in-demand skills and “difficult-to-find” competencies. This paper reports on 99 responses captured from IT leaders representing the SIM Chapters in St. Louis, Austin, Milwaukee, and Phoenix

Bivariate modelling of precipitation and temperature using a non-homogeneous hidden Markov model

Aiming to generate realistic synthetic times series of the bivariate process of daily mean temperature and precipitations, we introduce a non-homogeneous hidden Markov model. The non-homogeneity lies in periodic transition probabilities between the hidden states, and time-dependent emission distributions. This enables the model to account for the non-stationary behaviour of weather variables. By carefully choosing the emission distributions, it is also possible to model the dependance structure between the two variables. The model is applied to several weather stations in Europe with various climates, and we show that it is able to simulate realistic bivariate time series

First results from the IllustrisTNG simulations: A tale of two elements -- chemical evolution of magnesium and europium

The distribution of elements in galaxies provides a wealth of information about their production sites and their subsequent mixing into the interstellar medium. Here we investigate the distribution of elements within stars in the IllustrisTNG simulations. In particular, we analyze the abundance ratios of magnesium and europium in Milky Way-like galaxies from the TNG100 simulation (stellar masses ${\log} (M_\star / {\rm M}_\odot) \sim 9.7 - 11.2$). As abundances of magnesium and europium for individual stars in the Milky Way are observed across a variety of spatial locations and metallicities, comparison with the stellar abundances in our more than $850$ Milky Way-like galaxies provides stringent constraints on our chemical evolutionary methods. To this end we use the magnesium to iron ratio as a proxy for the effects of our SNII and SNIa metal return prescription, and a means to compare our simulated abundances to a wide variety of galactic observations. The europium to iron ratio tracks the rare ejecta from neutron star -- neutron star mergers, the assumed primary site of europium production in our models, which in turn is a sensitive probe of the effects of metal diffusion within the gas in our simulations. We find that europium abundances in Milky Way-like galaxies show no correlation with assembly history, present day galactic properties, and average galactic stellar population age. In general, we reproduce the europium to iron spread at low metallicities observed in the Milky Way, with the level of enhancement being sensitive to gas properties during redshifts $z \approx 2-4$. We show that while the overall normalization of [Eu/Fe] is susceptible to resolution and post-processing assumptions, the relatively large spread of [Eu/Fe] at low [Fe/H] when compared to that at high [Fe/H] is very robust.Comment: 18 pages, 14 figures, accepted to MNRA