Hasil untuk "History (General)"

P. Hirst, Grahame F. Thompson, S. Bromley

L. Murray

T. E. Martin

W. J. Hutchins, H. Somers

R. Cattell

C. King

P. Laslett

R. Bhaskar

Susan E. Stothard, M. Snowling, D. V. M. Bishop et al.

Mona Baker, G. Saldanha

E. Nevo, A. Beiles, R. Ben-Shlomo

Heinrich von Stackelberg

H. Call, I. Mücke

Rani Mohanraj, Shuba Kumar, Sylvia Jayakumar et al.

Polished white rice (WR), high in refined carbohydrates, the main staple in South India is associated with enhanced risk of diabetes. Brown Rice (BR), with lower glycemic load, high fibre content and micronutrients, is a healthier choice. Two hundred and twelve Persons with Diabetes (PwD) attending a tertiary diabetes care centre in a city in South India responded to a questionnaire documenting types, frequency and reasons for rice consumption, awareness and beliefs about BR. A sub-set of 10, participated in qualitative interviews, which additionally, explored the influence of traditional beliefs on and consumption patterns of rice, barriers to BR consumption and willingness to accept it in their diet. Ninety-three percent reported consuming WR with traditional usage (97 %) being the main reason for its preference. Brand image, grain size, texture and taste, of rice were other decisional considerations. Awareness about health benefits of BR was limited, with 69 % and 51 % believing it to be nutritious and helping to reduce blood sugar respectively. Appearance, texture, taste and cost were deterrents to its use. Over half agreed to switch to BR if they believed it would improve their health. Participants with a shorter duration of diabetes were more willing to change to BR. The study highlights the need to promote greater literacy regarding health benefits of BR and other forms of less polished rice. Larger trials examining the effectiveness of BR viz-a viz other types of less polished rice on blood glucose levels, metabolic factors and nutritional content among PwD are needed.

N. Thin, M. Gadgil, R. Guha

Donald C. Chang

Science is about facts and truth. Yet sometimes the truth and facts are not obvious. For example, in the field of MRI (Magnetic Resonance Imaging), there has been a long-lasting debate about who were the major contributors in its development. Particularly, there was a strong dispute between the followers of two scientists, R. Damadian and P. Lauterbur. In this review, we carefully trace the major developments in applying NMR for cancer detection starting almost 50 years ago. The research records show that the truth was beyond the claims of either research camps. The development of NMR for cancer detection involved multiple research groups, who made critical contributions at different junctures.

M. Weissman, P. Wickramaratne, P. Adams et al.

Tri Nguyen, Chirag Modi, L. Y. Aaron Yung et al.

The mass assembly history (MAH) of dark matter halos plays a crucial role in shaping the formation and evolution of galaxies. MAHs are used extensively in semi-analytic and empirical models of galaxy formation, yet current analytic methods to generate them are inaccurate and unable to capture their relationship with the halo internal structure and large-scale environment. This paper introduces FLORAH, a machine-learning framework for generating assembly histories of ensembles of dark matter halos. We train FLORAH on the assembly histories from the GUREFT and VSMDPL N-body simulations and demonstrate its ability to recover key properties such as the time evolution of mass and concentration. We obtain similar results for the galaxy stellar mass versus halo mass relation and its residuals when we run the Santa Cruz semi-analytic model on FLORAH-generated assembly histories and halo formation histories extracted from an N-body simulation. We further show that FLORAH also reproduces the dependence of clustering on properties other than mass (assembly bias), which is not captured by other analytic methods. By combining multiple networks trained on a suite of simulations with different redshift ranges and mass resolutions, we are able to construct accurate main progenitor branches (MPBs) with a wide dynamic mass range from $z=0$ up to an ultra-high redshift $z \approx 20$, currently far beyond that of a single N-body simulation. FLORAH is the first step towards a machine learning-based framework for planting full merger trees; this will enable the exploration of different galaxy formation scenarios with great computational efficiency at unprecedented accuracy.

Miguel Jaramago

Analizamos en el presente trabajo una estatua del tipo convencionalmente denominado Orante sumerio, depositada en el Museo Arqueológico Nacional (Madrid), y expuesta actualmente en sus salas de Egipto, Nubia y Oriente Próximo. Revisaremos la pieza en detalle, comentando sus características y estado de conservación, haremos una breve referencia al significado que pudo tener en la sociedad en que surgió, y finalmente nos plantearemos su posible origen geográfico y su cronología, así como ciertos elementos que tal vez podrían ser indicios de una discutible antigüedad.

Niels C. M. Martens, Miguel Ángel Carretero Sahuquillo, Erhard Scholz et al.

Editorial of a special issue on dark matter & modified gravity, distributed across the journals Studies in History and Philosophy of Modern Physics and Studies in History and Philosophy of Science. Published version of the open access editorial (in SHPS) available here: https://doi.org/10.1016/j.shpsa.2021.08.015. The six papers are collected here: https://www.sciencedirect.com/journal/studies-in-history-and-philosophy-of-science-part-b-studies-in-history-and-philosophy-of-modern-physics/special-issue/10CR71RJLWM.