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The number of countries that have adopted International Financial Reporting Standards (IFRS) in some form has grown each year. However, the existing literature generally ignores the varied types and the complex timing of IFRS adoption. Our paper provides a cross-reference of IFRS adoption dates and types for 195 countries and territories around the world. This definitive data, including an extensive online dataset, was developed to help researchers better identify IFRS adoption events in the samples used in their empirical studies. Additionally, we highlight potential challenges in identifying IFRS adoption types and dates as well as provide areas of future research that can benefit from our dataset, which can be accessed online https://about.illinoisstate.edu/mktrimb/song-trimble-2022-dataset/.
We present a thorough empirical analysis of market impact on the Bitcoin/USD exchange market using a complete dataset that allows us to reconstruct more than one million metaorders. We empirically confirm the “square-root law” for market impact, which holds on four decades in spite of the quasi-absence of statistical arbitrage and market marking strategies. We show that the square-root impact holds during the whole trajectory of a metaorder and not only for the final execution price. We also attempt to decompose the order flow into an “informed” and “uninformed” component, the latter leading to an almost complete long-term decay of impact. This study sheds light on the hypotheses and predictions of several market impact models recently proposed in the literature and promotes heterogeneous agent models as promising candidates to explain price impact on the Bitcoin market — and, we believe, on other markets as well.
In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago.
This paper focuses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project.
The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.
3D scanning technologies are deployed toward developing a digital 3D model for Additive Manufacturing (AM) applications. It collects data, turning it into a 3D model that uses designated 3D printing processes. Many scanners, ranging from low-cost alternatives to professional series that are far more accurate and reliable, are now available to assist in bringing designs to reality. 3D scanning solutions enable the appropriate measurement of 3D physical parts into the virtual world, allowing factory production teams and corporate offices to share critical design information. These techniques are utilized everywhere in the design process, including product design and development, reverse engineering, quality control and quality assurance. The manufacturing sector can decrease costs while accelerating time to market and resolving quality issues. This study investigates the metrological need as per the advancements of 3D scanners. The procedural steps of the 3D scanners, along with specific metrological components and soft tools for 3D scanning, are discussed briefly. Finally, various 3D scanning applications are identified and discussed in detail. Because of the overall relative advantages of these non-contact measurement techniques, 3D metrological tools are crucial for modern production. Almost every sector aims for smaller, more complex components, which are more vulnerable to contamination or injury from even the slightest touch with a probe. The market is driven by global Research and Development (R&D) investment to develop game-changing technologies and solutions. Precision inspection and quality control are significant market drivers for industry progress. Smart factories will have lifetime access to 3D metrological data, allowing them to enhance quality and gain a competitive advantage in the marketplace.
From Home to Hospital: Digitisation of Healthcare.
Microsoft with RingMD, Oneview Healthcare, Vital Images, Aruba, and Clinic to Cloud: The Ecosystem of Healthcare Solutions Providers in Asia.
Data Helps in Improving Nursing Practice, Making Better Decisions.
Launch of Asian Branch for QuintilesIMS Institute.
Strategic Environmental Assessment (SEA) is the process through which the impacts of plans and programmes on the environment are assessed. Objectives, targets and indicators are the tools through which these environmental impacts can be measured. The same objectives, targets and indicators may be used for all planning levels but it is also necessary to identify additional plan specific ones. We used a workshop based approach to provide an interface between planners and environmental scientists and to give examples of objectives, targets and indicators for biodiversity, water, air and climatic factors, which could be used in SEA for national, regional and local plans. In addition, we highlight the need for careful consideration during the selection process of these variables which will result in a more rigorous and robust SEA. This is a challenging process but once completed will maximise resources and reduce the workload later in the SEA process.
As biomedical research data grow, researchers need reliable and scalable solutions for storage and compute. There is also a need to build systems that encourage and support collaboration and data sharing, to result in greater reproducibility. This has led many researchers and organizations to use cloud computing [1]. The cloud not only enables scalable, on-demand resources for storage and compute, but also collaboration and continuity during virtual work, and can provide superior security and compliance features. Moving to or adding cloud resources, however, is not trivial or without cost, and may not be the best choice in every scenario. The goal of this workshop is to explore the benefits of using the cloud in biomedical and computational research, and considerations (pros and cons) for a range of scenarios including individual researchers, collaborative research teams, consortia research programs, and large biomedical research agencies / organizations.