Hasil untuk "Science (General)"

Raphael Vallat

Python is currently the fastest growing programming language in the world, thanks to its ease-of-use, fast learning curve and its numerous high quality packages for data science and machine-learning. Surprisingly however, Python is far behind the R programming language when it comes to general statistics and for this reason many scientists still rely heavily on R to perform their statistical analyses.

J. Nolan, C. Sandroni, B. Böttiger et al.

The European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) have collaborated to produce these post-resuscitation care guidelines for adults, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include the post-cardiac arrest syndrome, diagnosis of cause of cardiac arrest, control of oxygenation and ventilation, coronary reperfusion, haemodynamic monitoring and management, control of seizures, temperature control, general intensive care management, prognostication, long-term outcome, rehabilitation and organ donation.

Shirin Heidari, T. Babor, P. De Castro et al.

Sex and gender differences are often overlooked in research design, study implementation and scientific reporting, as well as in general science communication. This oversight limits the generalizability of research findings and their applicability to clinical practice, in particular for women but also for men. This article describes the rationale for an international set of guidelines to encourage a more systematic approach to the reporting of sex and gender in research across disciplines. A panel of 13 experts representing nine countries developed the guidelines through a series of teleconferences, conference presentations and a 2-day workshop. An internet survey of 716 journal editors, scientists and other members of the international publishing community was conducted as well as a literature search on sex and gender policies in scientific publishing. The Sex and Gender Equity in Research (SAGER) guidelines are a comprehensive procedure for reporting of sex and gender information in study design, data analyses, results and interpretation of findings. The SAGER guidelines are designed primarily to guide authors in preparing their manuscripts, but they are also useful for editors, as gatekeepers of science, to integrate assessment of sex and gender into all manuscripts as an integral part of the editorial process.

S. Leslie, Andrei Cimpian, Meredith Meyer et al.

A. Caspi, R. Houts, Daniel W Belsky et al.

Manuel J. Cobo, A. G. López-Herrera, E. Herrera-Viedma et al.

K. Imai, L. Keele, D. Tingley et al.

Identifying causal mechanisms is a fundamental goal of social science. Researchers seek to study not only whether one variable affects another but also how such a causal relationship arises. Yet commonly used statistical methods for identifying causal mechanisms rely upon untestable assumptions and are often inappropriate even under those assumptions. Randomizing treatment and intermediate variables is also insufficient. Despite these difficulties, the study of causal mechanisms is too important to abandon. We make three contributions to improve research on causal mechanisms. First, we present a minimum set of assumptions required under standard designs of experimental and observational studies and develop a general algorithm for estimating causal mediation effects. Second, we provide a method for assessing the sensitivity of conclusions to potential violations of a key assumption. Third, we offer alternative research designs for identifying causal mechanisms under weaker assumptions. The proposed approach is illustrated using media framing experiments and incumbency advantage studies.

G. Pilbratt, J. Riedinger, T. Passvogel et al.

Herschel was launched on 14 May 2009, and is now an operational ESA space observatory o ering unprecedented observational capabilities in the far-infrared and submillimetre spectral range 55 671 m. Herschel carries a 3.5 metre diameter passively cooled Cassegrain telescope, which is the largest of its kind and utilises a novel silicon carbide technology. The science payload comprises three instruments: two direct detection cameras/medium resolution spectrometers, PACS and SPIRE, and a very high-resolution heterodyne spectrometer, HIFI, whose focal plane units are housed inside a superfluid helium cryostat. Herschel is an observatory facility operated in partnership among ESA, the instrument consortia, and NASA. The mission lifetime is determined by the cryostat hold time. Nominally approximately 20,000 hours will be available for astronomy, 32% is guaranteed time and the remainder is open to the worldwide general astronomical community through a standard competitive proposal procedure.

P. Mucha, Thomas Richardson, K. Macon et al.

Network Notation Networks are often characterized by clusters of constituents that interact more closely with each other and have more connections to one another than they do with the rest of the components of the network. However, systematically identifying and studying such community structure in complicated networks is not easy, especially when the network interactions change over time or contain multiple types of connections, as seen in many biological regulatory networks or social networks. Mucha et al. (p. 876) developed a mathematical method to allow detection of communities that may be critical functional units of such networks. Application to real-world tasks—like making sense of the voting record in the U.S. Senate—demonstrated the promise of the method. A general mathematical method used to identify closely interacting groups can explain the behavior of complicated networks. Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities. We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices. This framework allows studies of community structure in a general setting encompassing networks that evolve over time, have multiple types of links (multiplexity), and have multiple scales.

H. Radder

Practicing and studying automated experimentation may benefit from philosophical reflection on experimental science in general. This paper reviews the relevant literature and discusses central issues in the philosophy of scientific experimentation. The first two sections present brief accounts of the rise of experimental science and of its philosophical study. The next sections discuss three central issues of scientific experimentation: the scientific and philosophical significance of intervention and production, the relationship between experimental science and technology, and the interactions between experimental and theoretical work. The concluding section identifies three issues for further research: the role of computing and, more specifically, automating, in experimental research, the nature of experimentation in the social and human sciences, and the significance of normative, including ethical, problems in experimental science.

T. Richardson, R. Urbanke

R. Carey

Ian Niles, A. Pease

J. Westgard

L. Hooghe, G. Marks

L. Hartwell, J. Hopfield, S. Leibler et al.

Saku Mantere, M. Ketokivi

Keichi Takahashi, Tomonori Hayami, Yu Mukaizono et al.

mdx II is an Infrastructure-as-a-Service (IaaS) cloud platform designed to accelerate data science research and foster cross-disciplinary collaborations among universities and research institutions in Japan. Unlike traditional high-performance computing systems, mdx II leverages OpenStack to provide customizable and isolated computing environments consisting of virtual machines, virtual networks, and advanced storage. This paper presents a comprehensive performance evaluation of mdx II, including a comparison to Amazon Web Services (AWS). We evaluated the performance of a 16-vCPU VM from multiple aspects including floating-point computing performance, memory throughput, network throughput, file system and object storage performance, and real-world application performance. Compared to an AWS 16-vCPU instance, the results indicated that mdx II outperforms AWS in many aspects and demonstrated that mdx II holds significant promise for high-performance data analytics (HPDA) workloads. We also evaluated the virtualization overhead using a 224-vCPU VM occupying an entire host. The results suggested that the virtualization overhead is minimal for compute-intensive benchmarks, while memory-intensive benchmarks experienced larger overheads. These findings are expected to help users of mdx II to obtain high performance for their data science workloads and offer insights to the designers of future data-centric cloud platforms.

F. Abbate, A. Carleo, S. Chatterjee et al.

The detection of a pulsar closely orbiting our Galaxy's supermassive black hole - Sagittarius A* - is one of the ultimate prizes in pulsar astrophysics. The relativistic effects expected in such a system could far exceed those currently observable in compact binaries such as double neutron stars and pulsar white dwarfs. In addition, pulsars offer the opportunity to study the magneto-ionic properties of Earth's nearest galactic nucleus in unprecedented detail. For these reasons, and more, a multitude of pulsar searches of the Galactic Centre have been undertaken, with the outcome of just seven pulsar detections within a projected distance of 100 pc from Sagittarius A*. It is currently understood that a larger underlying population likely exists, but it is not until observations with the SKA have started that this population can be revealed. In this paper, we look at important updates since the publication of the last SKAO science book and offer a focused view of observing strategies and likely outcomes with the updated SKAO design.

Karl Stapelfeldt, Eric Mamajek

The Exoplanet Exploration Program (ExEP) is chartered by the NASA Astrophysics Division to carry out science, research, and technology tasks that advance NASA's science goals for exoplanets. The ExEP Science Gap List is a compilation of "science gaps", defined as either: 1) The difference between knowledge needed to define requirements for specified future NASA exoplanet missions and the current state of the art, or 2) Knowledge which is needed to enhance the exoplanet science return of current and future NASA exoplanet missions. It is annually updated and input is solicited from the exoplanet community via ExoPAG. Current gaps are: 1) Spectroscopic observations of the atmospheres of small exoplanets, 2) Modeling exoplanet atmospheres, 3) Spectral signature retrieval, 4) Planetary system architectures: occurrence rates for exoplanets of all sizes, 5) Occurrence rates and uncertainties for temperate rocky planets, 6) Yield estimation for exoplanet direct imaging missions, 7) Intrinsic properties of known exoplanet host stars, 8) Mitigating stellar jitter as a limitation to sensitivity of dynamical methods to detect small temperate exoplanets and measure their masses and orbits, 9) Dynamical confirmation of exoplanet candidates and determination of their masses and orbits, 10) Observations and analyses of direct imaging targets, 11) Understanding the abundance and distribution of exozodiacal dust, 12) Measurements of accurate transiting planet radii, 13) Properties of atoms, molecules and aerosols in exoplanet atmospheres, 14) Exoplanet interior structure and material properties, 15) Quantify and mitigate the impacts of stellar contamination on transmission spectroscopy for measuring the composition of exoplanet atmospheres, 16) Complete the inventory of remotely observable exoplanet biosignatures and their false positives, 17) Understanding planet formation and disk properties.