Recent progress in the JARVIS infrastructure for next-generation data-driven materials design

The Joint Automated Repository for Various Integrated Simulations (JARVIS) infrastructure at the National Institute of Standards and Technology (NIST) is a large-scale collection of curated datasets and tools with more than 80000 materials and millions of properties. JARVIS uses a combination of electronic structure, artificial intelligence (AI), advanced computation and experimental methods to accelerate materials design. Here we report some of the new features that were recently included in the infrastructure such as: 1) doubling the number of materials in the database since its first release, 2) including more accurate electronic structure methods such as Quantum Monte Carlo, 3) including graph neural network-based materials design, 4) development of unified force-field, 5) development of a universal tight-binding model, 6) addition of computer-vision tools for advanced microscopy applications, 7) development of a natural language processing tool for text-generation and analysis, 8) debuting a large-scale benchmarking endeavor, 9) including quantum computing algorithms for solids, 10) integrating several experimental datasets and 11) staging several community engagement and outreach events. New classes of materials, properties, and workflows added to the database include superconductors, two-dimensional (2D) magnets, magnetic topological materials, metal-organic frameworks, defects, and interface systems. The rich and reliable datasets, tools, documentation, and tutorials make JARVIS a unique platform for modern materials design. JARVIS ensures openness of data and tools to enhance reproducibility and transparency and to promote a healthy and collaborative scientific environment

Rural and regional Australian public accounting firm services : service provision, concerns and tensions

Public accounting firms provide a necessary and important service for rural and regional areas. However, the provision of high-quality services is hindered by a number of factors. This paper reports the findings from a large-scale survey of professional accounting firm practitioners located in rural and regional Australia, identifying factors causing concerns and tensions and quantifying their scope and importance. Prominent concerns and tensions identified include adverse effects arising from the employment market, communications technology developments and legislation such as the Corporate Law Economic Reform Program (Audit Reform and Corporate Disclosure) Act 2004 and the Financial Services Reform Act 2001

Tourism policy and destination marketing in developing countries: the chain of influence

Tourism marketers including destination marketing organisations (DMOs) and international tour operators play a pivotal role in destination marketing, especially in creating destination images. These images, apparent in tourist brochures, are designed to influence tourist decision-making and behaviour. This paper proposes the concept of a “chain of influence” in destination marketing and image-making, suggesting that the content of marketing materials is influenced by the priorities of those who design these materials, e.g. tour operators and DMOs. A content analysis of 2,000 pictures from DMO and tour operator brochures revealed synergies and divergence between these marketers. The brochure content was then compared to the South African tourism policy, concluding that the dominant factor in the chain of influence in the South African context is in fact its organic image

Anti-influenza Hyperimmune Immunoglobulin Enhances Fc-functional Antibody Immunity during Human Influenza Infection

BACKGROUND: New treatments for severe influenza are needed. Passive transfer of influenza-specific hyperimmune pooled immunoglobulin (Flu-IVIG) boosts neutralising antibody responses to past strains in influenza-infected subjects. The effect of Flu-IVIG on antibodies with Fc-mediated functions, which may target diverse influenza strains, is unclear. METHODS: We studied the capacity of Flu-IVIG, relative to standard IVIG, to bind to Fc receptors and mediate antibody-dependent cellular cytotoxicity in vitro. The effect of Flu-IVIG infusion, compared to placebo infusion, was examined in serial plasma samples from 24 subjects with confirmed influenza infection in the INSIGHT FLU005 pilot study. RESULTS: Flu-IVIG contains higher concentrations of Fc-functional antibodies than IVIG against a diverse range of influenza hemagglutinins. Following infusion of Flu-IVIG into influenza-infected subjects, a transient increase in Fc-functional antibodies was present for 1-3 days against infecting and non-infecting strains of influenza. CONCLUSIONS: Flu-IVIG contains antibodies with Fc-mediated functions against influenza virus and passive transfer of Flu-IVIG increases anti-influenza Fc-functional antibodies in the plasma of influenza-infected subjects. Enhancement of Fc-functional antibodies to a diverse range of influenza strains suggests that Flu-IVIG infusion could prove useful in the context of novel influenza virus infections, when there may be minimal or no neutralising antibodies in the Flu-IVIG preparation

Standardised data on initiatives—STARDIT: Beta version

Background and objective: There is currently no standardised way to share information across disciplines about initiatives, including fields such as health, environment, basic science, manufacturing, media and international development. All problems, including complex global problems such as air pollution and pandemics require reliable data sharing between disciplines in order to respond effectively. Current reporting methods also lack information about the ways in which different people and organisations are involved in initiatives, making it difficult to collate and appraise data about the most effective ways to involve different people. The objective of STARDIT (Standardised Data on Initiatives) is to address current limitations and inconsistencies in sharing data about initiatives. The STARDIT system features standardised data reporting about initiatives, including who has been involved, what tasks they did, and any impacts observed. STARDIT was created to help everyone in the world find and understand information about collective human actions, which are referred to as ‘initiatives’. STARDIT enables multiple categories of data to be reported in a standardised way across disciplines, facilitating appraisal of initiatives and aiding synthesis of evidence for the most effective ways for people to be involved in initiatives. This article outlines progress to date on STARDIT; current usage; information about submitting reports; planned next steps and how anyone can become involved. Method: STARDIT development is guided by participatory action research paradigms, and has been co-created with people from multiple disciplines and countries. Co-authors include cancer patients, people affected by rare diseases, health researchers, environmental researchers, economists, librarians and academic publishers. The co-authors also worked with Indigenous peoples from multiple countries and in partnership with an organisation working with Indigenous Australians. Results and discussion: Over 100 people from multiple disciplines and countries have been involved in co-designing STARDIT since 2019. STARDIT is the first open access web-based data-sharing system which standardises the way that information about initiatives is reported across diverse fields and disciplines, including information about which tasks were done by which stakeholders. STARDIT is designed to work with existing data standards. STARDIT data will be released into the public domain (CC0) and integrated into Wikidata; it works across multiple languages and is both human and machine readable. Reports can be updated throughout the lifetime of an initiative, from planning to evaluation, allowing anyone to be involved in reporting impacts and outcomes. STARDIT is the first system that enables sharing of standardised data about initiatives across disciplines. A working Beta version was publicly released in February 2021 (ScienceforAll.World/STARDIT). Subsequently, STARDIT reports have been created for peer-reviewed research in multiple journals and multiple research projects, demonstrating the usability. In addition, organisations including Cochrane and Australian Genomics have created prospective reports outlining planned initiatives. Conclusions: STARDIT can help create high-quality standardised information on initiatives trying to solve complex multidisciplinary global problems

Positive Selection Shaped the Convergent Evolution of Independently Expanded Kallikrein Subfamilies Expressed in Mouse and Rat Saliva Proteomes

We performed proteomics studies of salivas from the genome mouse (C57BL/6 strain) and the genome rat (BN/SsNHsd/Mcwi strain). Our goal was to identify salivary proteins with one or more of three characteristics that may indicate that they have been involved in adaptation: 1) rapid expansion of their gene families; 2) footprints of positive selection; and/or 3) sex-limited expression. The results of our proteomics studies allow direct comparison of the proteins expressed and their levels between the sexes of the two rodent species. Twelve members of the Mus musculus species-specific kallikrein subfamily Klk1b showed sex-limited expression in the mouse saliva proteomes. By contrast, we did not find any of the Rattus norvegicus species-specific kallikrein subfamily Klk1c proteins in male or female genome rat, nor transcripts in their submandibular glands. On the other hand, we detected expression of this family as transcripts in the submandibular glands of both sexes of Sprague-Dawley rats. Using the CODEML program in the PAML package, we demonstrate that the two rodent kallikrein subfamilies have apparently evolved rapidly under the influence of positive selection that continually remodeled the amino acid sites on the same face in the members of the subfamilies. Thus, although their kallikrein subfamily expansions were independent, this evolutionary pattern has occurred in parallel in the two rodent species, suggesting a form of convergent evolution at the molecular level. On the basis of this new data, we suggest that the previous speculative function of the species-specific rodent kallikreins as important solely in wound healing in males be investigated further. In addition to or instead of that function, we propose that their sex-limited expression, coupled with their rapid evolution may be clues to an as-yet-undetermined interaction between the sexes

Minimally invasive computer-navigated total hip arthroplasty, following the concept of femur first and combined anteversion: design of a blinded randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Impingement can be a serious complication after total hip arthroplasty (THA), and is one of the major causes of postoperative pain, dislocation, aseptic loosening, and implant breakage. Minimally invasive THA and computer-navigated surgery were introduced several years ago. We have developed a novel, computer-assisted operation method for THA following the concept of "femur first"/"combined anteversion", which incorporates various aspects of performing a functional optimization of the cup position, and comprehensively addresses range of motion (ROM) as well as cup containment and alignment parameters. Hence, the purpose of this study is to assess whether the artificial joint's ROM can be improved by this computer-assisted operation method. Second, the clinical and radiological outcome will be evaluated.</p> <p>Methods/Design</p> <p>A registered patient- and observer-blinded randomized controlled trial will be conducted. Patients between the ages of 50 and 75 admitted for primary unilateral THA will be included. Patients will be randomly allocated to either receive minimally invasive computer-navigated "femur first" THA or the conventional minimally invasive THA procedure. Self-reported functional status and health-related quality of life (questionnaires) will be assessed both preoperatively and postoperatively. Perioperative complications will be registered. Radiographic evaluation will take place up to 6 weeks postoperatively with a computed tomography (CT) scan. Component position will be evaluated by an independent external institute on a 3D reconstruction of the femur/pelvis using image-processing software. Postoperative ROM will be calculated by an algorithm which automatically determines bony and prosthetic impingements.</p> <p>Discussion</p> <p>In the past, computer navigation has improved the accuracy of component positioning. So far, there are only few objective data quantifying the risks and benefits of computer navigated THA. Therefore, this study has been designed to compare minimally invasive computer-navigated "femur first" THA with a conventional technique for minimally invasive THA. The results of this trial will be presented as soon as they become available.</p> <p>Trial registration number</p> <p>DRKS00000739</p

Large Scale Benchmark of Materials Design Methods

Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboar

JARVIS-Leaderboard: a large scale benchmark of materials design methods

Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many fields. Materials science, in particular, encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC), and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard