Laboratory Simulations of Suprauroral Mechanisms Leading to Perpendicular Ion Heating and Conic Formation

Laboratory experiments are presented simulating aspects of perpendicular ion heating and conic formation that are observed or hypothesized to occur in the terrestrial ionosphere and magnetosphere. Previous laboratory observations of ion conics in the presence of the current‐driven electrostatic ion cyclotron wave are reviewed. Field‐aligned ion beams, accompanied by beam‐generated electrostatic ion cyclotron modes, resulted in perpendicular energization of beam ions and also the heating of background plasma ions. Antenna‐launched broadband and narrow‐band lower hybrid waves produced considerable perpendicular ion heating and non‐Maxwellian “tail” formation. Laboratory results are discussed in light of in situ measurements by the S3‐3 satellite and the MARIE sounding rocket

Monitoring COVID-19 on social media: development of an end-to-end natural language processing pipeline using a novel triage and diagnosis approach

Background: The COVID-19 pandemic has created a pressing need for integrating information from disparate sources in order to assist decision makers. Social media is important in this respect; however, to make sense of the textual information it provides and be able to automate the processing of large amounts of data, natural language processing methods are needed. Social media posts are often noisy, yet they may provide valuable insights regarding the severity and prevalence of the disease in the population. Here, we adopt a triage and diagnosis approach to analyzing social media posts using machine learning techniques for the purpose of disease detection and surveillance. We thus obtain useful prevalence and incidence statistics to identify disease symptoms and their severities, motivated by public health concerns. Objective: This study aims to develop an end-to-end natural language processing pipeline for triage and diagnosis of COVID-19 from patient-authored social media posts in order to provide researchers and public health practitioners with additional information on the symptoms, severity, and prevalence of the disease rather than to provide an actionable decision at the individual level. Methods: The text processing pipeline first extracted COVID-19 symptoms and related concepts, such as severity, duration, negations, and body parts, from patients’ posts using conditional random fields. An unsupervised rule-based algorithm was then applied to establish relations between concepts in the next step of the pipeline. The extracted concepts and relations were subsequently used to construct 2 different vector representations of each post. These vectors were separately applied to build support vector machine learning models to triage patients into 3 categories and diagnose them for COVID-19. Results: We reported macro- and microaveraged F1 scores in the range of 71%-96% and 61%-87%, respectively, for the triage and diagnosis of COVID-19 when the models were trained on human-labeled data. Our experimental results indicated that similar performance can be achieved when the models are trained using predicted labels from concept extraction and rule-based classifiers, thus yielding end-to-end machine learning. In addition, we highlighted important features uncovered by our diagnostic machine learning models and compared them with the most frequent symptoms revealed in another COVID-19 data set. In particular, we found that the most important features are not always the most frequent ones. Conclusions: Our preliminary results show that it is possible to automatically triage and diagnose patients for COVID-19 from social media natural language narratives, using a machine learning pipeline in order to provide information on the severity and prevalence of the disease for use within health surveillance systems

Expression, maturation and turnover of DrrS, an unusually stable, DosR regulated small RNA in Mycobacterium tuberculosis

Mycobacterium tuberculosis depends on the ability to adjust to stresses encountered in a range of host environments, adjustments that require significant changes in gene expression. Small RNAs (sRNAs) play an important role as post-transcriptional regulators of prokaryotic gene expression, where they are associated with stress responses and, in the case of pathogens, adaptation to the host environment. In spite of this, the understanding of M. tuberculosis RNA biology remains limited. Here we have used a DosR-associated sRNA as an example to investigate multiple aspects of mycobacterial RNA biology that are likely to apply to other M. tuberculosis sRNAs and mRNAs. We have found that accumulation of this particular sRNA is slow but robust as cells enter stationary phase. Using reporter gene assays, we find that the sRNA core promoter is activated by DosR, and we have renamed the sRNA DrrS for DosR Regulated sRNA. Moreover, we show that DrrS is transcribed as a longer precursor, DrrS+, which is rapidly processed to the mature and highly stable DrrS. We characterise, for the first time in mycobacteria, an RNA structural determinant involved in this extraordinary stability and we show how the addition of a few nucleotides can lead to acute destabilisation. Finally, we show how this RNA element can enhance expression of a heterologous gene. Thus, the element, as well as its destabilising derivatives may be employed to post-transcriptionally regulate gene expression in mycobacteria in combination with different promoter variants. Moreover, our findings will facilitate further investigations into the severely understudied topic of mycobacterial RNA biology and into the role that regulatory RNA plays in M. tuberculosis pathogenesis

Measurement of multidimensional ion velocity distributions by optical tomography

We report the development of a new diagnostic capable of measuring plasma ion distributions as a function of all three velocity-space coordinates. The diagnostic makes use of laser-induced fluorescence (LIF) and computer-assisted image reconstruction techniques. LIF yields high-resolution, nonperturbing measurements of one-dimensional distributions that are integrated in two directions through three-dimensional velocity space. Computer tomography allows for the unambiguous determination of the complete ion velocity distribution. In addition to a description of the diagnostic, examples of recovered distributions obtained from experiments are given, and the effects of the major steps in the data processing are discussed

Laboratory observation of ion conics by velocity-space tomography of a plasma.

Laboratory experiments have examined particular elements of proposed mechanisms for ion conic formation seen in the Earth's auroral-zone magnetosphere. A laser-induced fluorescence diagnostic measured the ion distribution function at many angles in velocity space, allowing tomographic techniques to reconstruct the multidimensional ion distribution function. Ion conics, as well as drifting Maxwellians, were observed. © 1986 The American Physical Society

Optimizing microtubule arrangements for rapid cargo capture

Cellular functions such as autophagy, cell signaling, and vesicular trafficking involve the retrograde transport of motor-driven cargo along microtubules. Typically, newly formed cargo engages in slow undirected movement from its point of origin before attaching to a microtubule. In some cell types, cargo destined for delivery to the perinuclear region relies on capture at dynein-enriched loading zones located near microtubule plus ends. Such systems include extended cell regions of neurites and fungal hyphae, where the efficiency of the initial diffusive loading process depends on the axial distribution of microtubule plus ends relative to the initial cargo position. We use analytic mean first-passage time calculations and numerical simulations to model diffusive capture processes in tubular cells, exploring how the spatial arrangement of microtubule plus ends affects the efficiency of retrograde cargo transport. Our model delineates the key features of optimal microtubule arrangements that minimize mean cargo capture times. Namely, we show that configurations with a single microtubule plus end abutting the distal tip and broadly distributed other plus ends allow for efficient capture in a variety of different scenarios for retrograde transport. Live-cell imaging of microtubule plus ends in Aspergillus nidulans hyphae indicates that their distributions exhibit these optimal qualitative features. Our results highlight important coupling effects between the distribution of microtubule tips and retrograde cargo transport, providing guiding principles for the spatial arrangement of microtubules within tubular cell regions