Search for: All records

The HH 24 complex harbors five collimated jets emanating from a small protostellar multiple system. We have carried out a multiwavelength study of the jets, their driving sources, and the cloud core hosting the embedded stellar system, based on data from the Hubble Space Telescope, Gemini, Subaru, Apache Point Observatory 3.5 m, Karl G. Jansky Very Large Array, and Atacama Large Millimeter/submillimeter Array (ALMA) telescopes. The data show that the multiple system, SSV 63, contains at least 7 sources, ranging in mass from the hydrogen-burning limit to proto-Herbig Ae stars. The stars are in an unstable nonhierarchical configuration, and one member, a borderline brown dwarf, is moving away from the protostellar system with 25 km s⁻¹, after being ejected ∼5800 yr ago as an orphaned protostar. Five of the embedded sources are surrounded by small, possibly truncated, disks resolved at 1.3 mm with ALMA. Proper motions and radial velocities imply jet speeds of 200–300 km s⁻¹. The two main HH 24 jets, E and C, form a bipolar jet system that traces the innermost portions of parsec-scale chains of Herbig–Haro and H₂shocks with a total extent of at least 3 pc. H₂CO and C¹⁸O observations show that the core has been churned and continuously fed by an infalling streamer.¹³CO and¹²CO trace compact, low-velocity, cavity walls carved by the jets and an ultracompact molecular outflow from the most embedded object. ChaoticN-body dynamics likely will eject several more of these objects. The ejection of stars from their feeding zones sets their masses. Dynamical decay of nonhierarchical systems can thus be a major contributor to establishing the initial mass function.

 

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease‐specific biomarkers in human serum using bottom‐up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%–19% variation in protein identification among the kits. Immunocapturing‐based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non‐antibody‐based methods (i.e., kits using ion exchange resins) and kits leveraging a multi‐antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom‐up proteomic results revealed that different SAPD kits enrich distinct disease‐ and pathway‐specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

 

Data literacy has taken a front seat in present day conversations on education reform primarily due to the need for education on disruptive technologies such as Artificial Intelligence and Internetof- Things that are rapidly transforming the future of work and life. School systems worldwide have already included data literacy several years ago in their curriculum, still the definition of data and the activities utilized to teach data handling are verily outdated and seek change to reflect the new relationship we are starting to form with data. This paper discusses a workshop conducted for data literacy education in schools. The hands-on activity based approach taken in the workshop seeks to offer a broad definition to data along the lines of real world application in terms of our human sensory perception of audition, vision, and haptics. 

Context.3C 84 is a nearby radio source with a complex total intensity structure, showing linear polarisation and spectral patterns. A detailed investigation of the central engine region necessitates the use of very-long-baseline interferometry (VLBI) above the hitherto available maximum frequency of 86 GHz.

Aims.Using ultrahigh resolution VLBI observations at the currently highest available frequency of 228 GHz, we aim to perform a direct detection of compact structures and understand the physical conditions in the compact region of 3C 84.

Methods.We used Event Horizon Telescope (EHT) 228 GHz observations and, given the limited (u, v)-coverage, applied geometric model fitting to the data. Furthermore, we employed quasi-simultaneously observed, ancillary multi-frequency VLBI data for the source in order to carry out a comprehensive analysis of the core structure.

Results.We report the detection of a highly ordered, strong magnetic field around the central, supermassive black hole of 3C 84. The brightness temperature analysis suggests that the system is in equipartition. We also determined a turnover frequency ofν_m = (113 ± 4) GHz, a corresponding synchrotron self-absorbed magnetic field ofB_SSA = (2.9 ± 1.6) G, and an equipartition magnetic field ofB_eq = (5.2 ± 0.6) G. Three components are resolved with the highest fractional polarisation detected for this object (m_net = (17.0 ± 3.9)%). The positions of the components are compatible with those seen in low-frequency VLBI observations since 2017–2018. We report a steeply negative slope of the spectrum at 228 GHz. We used these findings to test existing models of jet formation, propagation, and Faraday rotation in 3C 84.

Conclusions.The findings of our investigation into different flow geometries and black hole spins support an advection-dominated accretion flow in a magnetically arrested state around a rapidly rotating supermassive black hole as a model of the jet-launching system in the core of 3C 84. However, systematic uncertainties due to the limited (u, v)-coverage, however, cannot be ignored. Our upcoming work using new EHT data, which offer full imaging capabilities, will shed more light on the compact region of 3C 84.