... is key to scalability and long-term success for projects in the global health informatics (GHI) domain. This paper presents key strategies for incorporating principles of health equity in the GHI project lifecycle. Materials and Methods The American Medical Informatics Association (AMIA) GHI Working...

... fibrils on the adherend when Dahlquist criterion (i.e. E <1 MPa) is satisfied. (ii) Strong and scalable adhesion in the DMT-like regime. After attachment, the adhesive fibrils become stiff when transitioning into the glass-phase upon reverse stimulation. When loaded in the stiff-state...

... waiting queue to avoid the failure of transaction caused by channel congestion, improving transaction throughput. However, nodes in Spider need to maintain the global network state, and the scalability could be better. However, Hide&Seek [ 15 ] is the latest rebalancing mechanism, which maximizes...

...) to infer large networks in parallel without compromising original quality. We implement the proposed generic parallel framework and seamlessly integrate 15 publicly available inference methods. We assess the scalability of 15 state-of-the-art inference methods together with their performance using...

..., we highlighted key initiatives in genomics research and efforts to address health challenges facing the diverse and fast-growing populations on the continent. We explore the scalability of genomic tools and techniques to tackle a broader range of infectious diseases in Africa, a continent...

... is conducive to evaluating feasibility and scalability of implementation strategies on a national level. In previous work evaluating implementation of three EBPs for older Veterans (hospital-based walking, caregiver skills training, group physical therapy), we found facilities varied in their need...

.../standard_publication_model ) Abstract Integration of accumulative large-scale single-cell transcriptomes requires scalable batch-correction approaches. Here we propose Fugue, a simple and efficient batch-correction method that is scalable for integrating super large-scale single-cell transcriptomes from diverse sources...

... it scalable to handle ’big data’. On the other hand, the robustness property is less explored and there exists only limited theoretical results. Motivated by the need of handling such data, recently we proposed a novel spectral embedding algorithm, which we coined Robust and Scalable Embedding...

... across inputs from different technologies. Findings Here, we present spacemake, a modular, robust, and scalable spatial transcriptomics pipeline built in Snakemake and Python. Spacemake is designed to handle all major spatial transcriptomics data sets and can be readily configured for other...

... and schedule, and scalability outcomes of their respective space missions. Our reference class dataset consists of 203 space missions spanning 1963–2021, of which 181 missions belong to NASA and 22 belong to SpaceX. We find that SpaceX’s platform strategy was 10X cheaper and 2X faster than NASA’s bespoke...

... log n ) , which allows for scalability to previously unimplementable data sizes. The NNGP is a well-defined spatial process, with sparse precision matrices available in closed form enabling the aforementioned computation gains. However, this sparsity guarantees the approximating covariance...

... the separation of control and data for realizing decentralized data flows between atomic services, in order to efficiently support environments that generate huge volumes of data continuously. Furthermore, existing approaches only consider vertical and horizontal scalability. It is important to mention...

... results; (ii) high scalability—the algorithm should easily scale to massive datasets; (iii) universality—the algorithm should be effective for various tasks without any prior assumption; and (iv) user friendliness—the algorithm should be very easy to use in practice. National Key Research and Development...

... a considerable computational challenge and are carried out by large scientific groups under great expenditure of time and personnel. Automating these processes requires highly efficient and scalable methods and software, but so far there is no workflow solution to easily process 1 million GWAS samples...

... for almost any application. However, with the growth of the Internet in recent decades, both in the number of users and in the amount of information, those centralized models began to suffer availability and scalability issues. To address those issues, the use of decentralized architectures and alternative...

...Patrick Erik Bradley; Markus Wilhelm Jahn Corresponding author: [email protected] This article has a similar aim as [ 15 ] in that the scalability of the Hilbert curve should be exploited to produce a scalable index whose local precision adapts to the local density of the point cloud...

... to bioinformaticians. In the same way that cloud computing has democratized access to distributed systems engineering for generalist software engineers, access to scalable and reproducible bioinformatic engineering can be democratized for generalist bioinformaticians and biologists. We present solutions, based on our...

... at addressing the node storage scalability problem. Adopting the VBG model, each node only needs to store part of block data and saves the VBG storage index to distributed hash table by taking block data as a resource, thus improving the query efficiency of block data. With the incentive mechanism of block data...

... Scalability Shrinkage Variable selection Suppose, for each observational unit , we have a multivariate response on variables of interest, along with information on possible predictors , a subset of which are assumed to be important in predicting the responses. Let denote...

..., three conditions must be met to label as an ‘elementary flux mode’ or ‘elementary pathway’: The biggest challenge in EFM analysis is its scalability to allow for the analysis of genome-scale models. From a computational complexity perspective, the lack of scaling is understandable. A problem...