Traveler: Navigating Task Parallel Traces for Performance Analysis.

Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings in terms of computational resource use. To aid performance analysis, developers may collect an execution trace-a chronological log of program activity during execution. As traces represent the full history, developers can discover a wide array of possibly previously unknown performance issues, making them an important artifact for exploratory performance analysis. However, interactive trace visualization is difficult due to issues of data size and complexity of meaning. Traces represent nanosecond-level events across many parallel processes, meaning the collected data is often large and difficult to explore. The rise of asynchronous task parallel programming paradigms complicates the relation between events and their probable cause. To address these challenges, we conduct a continuing design study in collaboration with high performance computing researchers. We develop diverse and hierarchical ways to navigate and represent execution trace data in support of their trace analysis tasks. Through an iterative design process, we developed Traveler, an integrated visualization platform for task parallel traces. Traveler provides multiple linked interfaces to help navigate trace data from multiple contexts. We evaluate the utility of Traveler through feedback from users and a case study, finding that integrating multiple modes of navigation in our design supported performance analysis tasks and led to the discovery of previously unknown behavior in a distributed array library.

HNN-core: A Python software for cellular and circuit-level interpretation of human MEG/EEG.

HNN-core is a library for circuit and cellular level interpretation of non-invasive human magneto-/electro-encephalography (MEG/EEG) data. It is based on the Human Neocortical Neurosolver (HNN) software (Neymotin et al., 2020), a modeling tool designed to simulate multiscale neural mechanisms generating current dipoles in a localized patch of neocortex. HNN's foundation is a biophysically detailed neural network representing a canonical neocortical column containing populations of pyramidal and inhibitory neurons together with layer-specific exogenous synaptic drive (Figure 1 left). In addition to simulating network-level interactions, HNN produces the intracellular currents in the long apical dendrites of pyramidal cells across the cortical layers known to be responsible for macroscopic current dipole generation.

The challenges of theory-software translation.

Background: Software is now ubiquitous within research. In addition to the general challenges common to all software development projects, research software must also represent, manipulate, and provide data for complex theoretical constructs. Ensuring this process of theory-software translation is robust is essential to maintaining the integrity of the science resulting from it, and yet there has been little formal recognition or exploration of the challenges associated with it. Methods: We thematically analyse the outputs of the discussion sessions at the Theory-Software Translation Workshop 2019, where academic researchers and research software engineers from a variety of domains, and with particular expertise in high performance computing, explored the process of translating between scientific theory and software. Results: We identify a wide range of challenges to implementing scientific theory in research software and using the resulting data and models for the advancement of knowledge. We categorise these within the emergent themes of design, infrastructure, and culture, and map them to associated research questions. Conclusions: Systematically investigating how software is constructed and its outputs used within science has the potential to improve the robustness of research software and accelerate progress in its development. We propose that this issue be examined within a new research area of theory-software translation, which would aim to significantly advance both knowledge and scientific practice.

Case Studies Using the Electroencephalogram to Monitor Anesthesia-Induced Brain States in Children.

For this child, at this particular moment, how much anesthesia should I give? Determining the drug requirements of a specific patient is a fundamental problem in medicine. Our current approach uses population-based pharmacological models to establish dosing. However, individual patients, and children in particular, may respond to drugs differently. In anesthesiology, we have the advantage that we can monitor our patients in real time and titrate drugs to the desired effect. Examples include blood pressure management or muscle relaxation. Although the brain is the primary site of action for sedative-hypnotic drugs, the brain is not routinely monitored during general anesthesia or sedation, a fact that would surprise many patients. One reason for this is that, until recently, physiologically principled approaches for anesthetic brain monitoring have not been articulated. In the past few years, our knowledge of anesthetic brain mechanisms has developed rapidly. We now know that anesthetic drug effects are clearly visible in the electroencephalogram (EEG) of adults and reflect underlying anesthetic pharmacology and brain mechanisms. Most recently, similar effects have been characterized in children. In this article, we describe how EEG monitoring could be used to guide anesthetic management in pediatric patients. We review previous evidence and present multiple case studies showing how drug-specific and dose-dependent EEG signatures seen in adults are visible in children and infants, including those with neurological disorders. We propose that the EEG can be used in the anesthetic care of children to enable anesthesiologists to better assess the drug requirements of individual patients in real time and improve patient safety and experience.

Coming Up for Air: Exploring an Intergenerational Perspective on Social Work.

From the late 1980s until now, scholars, educators and social workers have criticised the diminution of interest in the structural level of social problems. In this lament, former social work is beguiled, while critiques are targeted at the new generation of social workers. These critiques forewarn of important issues and problems, but at the same time they portray social work in a devolutionary way. It is argued that this one-sided debate conceals frictions between different generations of social workers. In reference to the work of Karl Mannheim, an intergenerational perspective is proposed that goes beyond nostalgic relishing of the past and calls on social work to actively engage with past remembrance and present evolutions.

Transcriptome Profiling of Beach Morning Glory (Ipomoea imperati) under Salinity and Its Comparative Analysis with Sweetpotato.

The response and adaption to salt remains poorly understood for beach morning glory [Ipomoea imperati (Vahl) Griseb], one of a few relatives of sweetpotato, known to thrive under salty and extreme drought conditions. In order to understand the genetic mechanisms underlying salt tolerance of a Convolvulaceae member, a genome-wide transcriptome study was carried out in beach morning glory by 454 pyrosequencing. A total of 286,584 filtered reads from both salt stressed and unstressed (control) root and shoot tissues were assembled into 95,790 unigenes with an average length of 667 base pairs (bp) and N50 of 706 bp. Putative differentially expressed genes (DEGs) were identified as transcripts overrepresented under salt stressed tissues compared to the control, and were placed into metabolic pathways. Most of these DEGs were involved in stress response, membrane transport, signal transduction, transcription activity and other cellular and molecular processes. We further analyzed the gene expression of 14 candidate genes of interest for salt tolerance through quantitative reverse transcription PCR (qRT-PCR) and confirmed their differential expression under salt stress in both beach morning glory and sweetpotato. The results comparing transcripts of I. imperati against the transcriptome of other Ipomoea species, including sweetpotato are also presented in this study. In addition, 6,233 SSR markers were identified, and an in silico analysis predicted that 434 primer pairs out of 4,897 target an identifiable homologous sequence in other Ipomoea transcriptomes, including sweetpotato. The data generated in this study will help in understanding the basics of salt tolerance of beach morning glory and the SSR resources generated will be useful for comparative genomics studies and further enhance the path to the marker-assisted breeding of sweetpotato for salt tolerance.

Power supply and impedance matching to drive technological radio-frequency plasmas with customized voltage waveforms.

We present a novel radio-frequency (RF) power supply and impedance matching to drive technological plasmas with customized voltage waveforms. It is based on a system of phase-locked RF generators that output single frequency voltage waveforms corresponding to multiple consecutive harmonics of a fundamental frequency. These signals are matched individually and combined to drive a RF plasma. Electrical filters are used to prevent parasitic interactions between the matching branches. By adjusting the harmonics' phases and voltage amplitudes individually, any voltage waveform can be approximated as a customized finite Fourier series. This RF supply system is easily adaptable to any technological plasma for industrial applications and allows the commercial utilization of process optimization based on voltage waveform tailoring for the first time. Here, this system is tested on a capacitive discharge based on three consecutive harmonics of 13.56 MHz. According to the Electrical Asymmetry Effect, tuning the phases between the applied harmonics results in an electrical control of the DC self-bias and the mean ion energy at almost constant ion flux. A comparison with the reference case of an electrically asymmetric dual-frequency discharge reveals that the control range of the mean ion energy can be significantly enlarged by using more than two consecutive harmonics.