Software Citation in HEP: Current State and Recommendations for the Future

In November 2022, the HEP Software Foundation (HSF) and the Institute for Research and Innovation for Software in High-Energy Physics (IRIS-HEP) organized a workshop on the topic of Software Citation and Recognition in HEP. The goal of the workshop was to bring together different types of stakeholders whose roles relate to software citation and the associated credit it provides in order to engage the community in a discussion on: the ways HEP experiments handle citation of software, recognition for software efforts that enable physics results disseminated to the public, and how the scholarly publishing ecosystem supports these activities. Reports were given from the publication board leadership of the ATLAS, CMS, and LHCb experiments and HEP open source software community organizations (ROOT, Scikit-HEP, MCnet), and perspectives were given from publishers (Elsevier, JOSS) and related tool providers (INSPIRE, Zenodo). This paper summarizes key findings and recommendations from the workshop as presented at the 26th International Conference on Computing In High Energy and Nuclear Physics (CHEP 2023).Comment: 7 pages, 2 listings. Contribution to the Proceedings of the 26th International Conference on Computing In High Energy and Nuclear Physics (CHEP 2023

Applying laboratory thermal desorption data in an interstellar context: sublimation of methanol thin films

Methods by which experimental measurements of thermal desorption can be applied in astrophysical environments have been developed, using the sublimation of solid methanol as an example. The temperature programmed desorption of methanol from graphitic, amorphous silica and polycrystalline gold substrates was compared, with the kinetic parameters of desorption extracted by either a leading edge analysis or by fitting using a stochastic integration method. At low coverages, the desorption shows a substrate-dependent fractional order. However, at higher coverages methanol desorption is zeroth order with kinetic parameters independent of substrate. Using a kinetic model based on the stochastic integration analyses, desorption under astrophysically relevant conditions can be simulated. We find that the chemical and morphological nature of the substrate has relatively little impact on the desorption temperature of solid methanol, and that the substrate independent zeroth-order kinetics can provide a satisfactory model for desorption in astrophysical environments. Uncertainties in the heating rate and the distribution of grain sizes will have the largest influence on the range of desorption temperature. These conclusions are likely to be generally applicable to all species in dust grain ice mantles

Software Citation in HEP: Current State and Recommendations for the Future

In November 2022, the HEP Software Foundation and the Institute for Research and Innovation for Software in High-Energy Physics organized a workshop on the topic of Software Citation and Recognition in HEP. The goal of the workshop was to bring together different types of stakeholders whose roles relate to software citation, and the associated credit it provides, in order to engage the community in a discussion on: the ways HEP experiments handle citation of software, recognition for software efforts that enable physics results disseminated to the public, and how the scholarly publishing ecosystem supports these activities. Reports were given from the publication board leadership of the ATLAS, CMS, and LHCb experiments and HEP open source software community organizations (ROOT, Scikit-HEP, MCnet), and perspectives were given from publishers (Elsevier, JOSS) and related tool providers (INSPIRE, Zenodo). This paper summarizes key findings and recommendations from the workshop as presented at the 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)

Wholly Rickettsia! Reconstructed Metabolic Profile of the Quintessential Bacterial Parasite of Eukaryotic Cells

Reductive genome evolution has purged many metabolic pathways from obligate intracellular Rickettsia (Alphaproteobacteria; Rickettsiaceae). While some aspects of host-dependent rickettsial metabolism have been characterized, the array of host-acquired metabolites and their cognate transporters remains unknown. This dearth of information has thwarted efforts to obtain an axenic Rickettsia culture, a major impediment to conventional genetic approaches. Using phylogenomics and computational pathway analysis, we reconstructed the Rickettsia metabolic and transport network, identifying 51 host-acquired metabolites (only 21 previously characterized) needed to compensate for degraded biosynthesis pathways. In the absence of glycolysis and the pentose phosphate pathway, cell envelope glycocon- jugates are synthesized from three imported host sugars, with a range of additional host-acquired metabolites fueling the tricarboxylic acid cycle. Fatty acid and glycero- phospholipid pathways also initiate from host precursors, and import of both iso- prenes and terpenoids is required for the synthesis of ubiquinone and the lipid car- rier of lipid I and O-antigen. Unlike metabolite-provisioning bacterial symbionts of arthropods, rickettsiae cannot synthesize B vitamins or most other cofactors, accen- tuating their parasitic nature. Six biosynthesis pathways contain holes (missing en- zymes); similar patterns in taxonomically diverse bacteria suggest alternative en- zymes that await discovery. A paucity of characterized and predicted transporters emphasizes the knowledge gap concerning how rickettsiae import host metabolites, some of which are large and not known to be transported by bacteria. Collectively, our reconstructed metabolic network offers clues to how rickettsiae hijack host met- abolic pathways. This blueprint for growth determinants is an important step toward the design of axenic media to rescue rickettsiae from the eukaryotic cell

Common DNA Variants Accurately Rank an Individual of Extreme Height

Polygenic scores (or genetic risk scores) quantify the aggregate of small effects from many common genetic loci that have been associated with a trait through genome-wide association. Polygenic scores were first used successfully in schizophrenia and have since been applied to multiple phenotypes including multiple sclerosis, rheumatoid arthritis, and height. Because human height is an easily-measured and complex polygenic trait, polygenic height scores provide exciting insights into the predictability of aggregate common variant effect on the phenotype. Shawn Bradley is an extremely tall former professional basketball player from Brigham Young University and the National Basketball Association (NBA), measuring 2.29 meters (7′6″, 99.99999th percentile for height) tall, with no known medical conditions. Here, we present a case where a rare combination of common SNPs in one individual results in an extremely high polygenic height score that is correlated with an extreme phenotype. While polygenic scores are not clinically significant in the average case, our findings suggest that for extreme phenotypes, polygenic scores may be more successful for the prediction of individuals

Conscious monitoring and control (reinvestment) in surgical performance under pressure.

Research on intraoperative stressors has focused on external factors without considering individual differences in the ability to cope with stress. One individual difference that is implicated in adverse effects of stress on performance is "reinvestment," the propensity for conscious monitoring and control of movements. The aim of this study was to examine the impact of reinvestment on laparoscopic performance under time pressure

Evaluation of a national universal coverage campaign of long-lasting insecticidal nets in a rural district in north-west Tanzania.

\ud \ud Insecticide-treated nets (ITN) are one of the most effective measures for preventing malaria. Mass distribution campaigns are being used to rapidly increase net coverage in at-risk populations. This study had two purposes: to evaluate the impact of a universal coverage campaign (UCC) of long-lasting insecticidal nets (LLINs) on LLIN ownership and usage, and to identify factors that may be associated with inadequate coverage. In 2011 two cross-sectional household surveys were conducted in 50 clusters in Muleba district, north-west Tanzania. Prior to the UCC 3,246 households were surveyed and 2,499 afterwards. Data on bed net ownership and usage, demographics of household members and household characteristics including factors related to socio-economic status were gathered, using an adapted version of the standard Malaria Indicator Survey. Specific questions relating to the UCC process were asked. The proportion of households with at least one ITN increased from 62.6% (95% Confidence Interval (CI) = 60.9-64.2) before the UCC to 90.8% (95% CI = 89.0-92.3) afterwards. ITN usage in all residents rose from 40.8% to 55.7%. After the UCC 58.4% (95% CI = 54.7-62.1) of households had sufficient ITNs to cover all their sleeping places. Households with children under five years (OR = 2.4, 95% CI = 1.9-2.9) and small households (OR = 1.9, 95% CI = 1.5-2.4) were most likely to reach universal coverage. Poverty was not associated with net coverage. Eighty percent of households surveyed received LLINs from the campaign. The UCC in Muleba district of Tanzania was equitable, greatly improving LLIN ownership and, more moderately, usage. However, the goal of universal coverage in terms of the adequate provision of nets was not achieved. Multiple, continuous delivery systems and education activities are required to maintain and improve bed net ownership and usage.\ud \u

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)

Using BOX-PCR to exclude a clonal outbreak of melioidosis

Background Although melioidosis in endemic regions is usually caused by a diverse range of Burkholderia pseudomallei strains, clonal outbreaks from contaminated potable water have been described. Furthermore B. pseudomallei is classified as a CDC Group B bioterrorism agent. Ribotyping, pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) have been used to identify genetically related B. pseudomallei isolates, but they are time consuming and technically challenging for many laboratories. Methods We have adapted repetitive sequence typing using a BOX A1R primer for typing B. pseudomallei and compared BOX-PCR fingerprinting results on a wide range of well-characterized B. pseudomallei isolates with MLST and PFGE performed on the same isolates. Results BOX-PCR typing compared favourably with MLST and PFGE performed on the same isolates, both discriminating between the majority of multilocus sequence types and showing relatedness between epidemiologically linked isolates from various outbreak clusters. Conclusion Our results suggest that BOX-PCR can be used to exclude a clonal outbreak of melioidosis within 10 hours of receiving the bacterial strains