1,642 research outputs found
Bibliographics for the 983 eprints in the live archives of E-LIS : trends and status report up to 7th July 2004, based on author-self-archiving metadata
Get PDFThe priority for ideas and philosophy related to "Network Theory" have been traced back and documented by Braun(2004),and credit goes to Karinthy(1929).The IT has empowered to realise it, as the most practical phenomena and it is no more a humour. The OAI (Open Archives Initiatives)and ACIS (Academic Contributor Information System)are progressive in the direction ,which may lead to realise the "Collective Genius" at global level. Focus of present study is on Author-Self-Archiving (A-S-A)Metadata of the 983 Eprints in the Live Archives of the E-LIS (EPrints of Library and Information Science),which were approved till 7th July 2004.The A-S-A Metadata was used for librametric analysis. Self-explanatory bibliographics are illustrated.The highlights include: Conference papers (34%); highest approval, June 2004 (28%); published archives (76%);not refereed (52%); not in public domain (60%); highest self-archiving-author (De Robbio, Antonella).The Nos. of EPrints having single JITA domain specifications were: Theoretical and general aspects of libraries and information(27); Information use and sociology of information(80);Users,literacy and reading(13);Libraries as physical collections(30);Publishing and legal issues(57);Management(13);Industry, profession and education(36);Information sources, supports, channels(113) ; Information treatment for information services, Information functions and techniques (101); Technical services libraries, archives and museums(25); Housing technologies(1); Information technology and library technology(92); and Inter-domainery (395) i.e. having specifications of two or more than two JITA classes
A study on lower saturation voltage of dual-gate thin-film a-IGZO MOS transistors
No full textThis work focuses on an amorphous Indium-Gallium-Zinc Oxide (a-IGZO) thin-film transistor (TFT) model with lower saturation voltage for dual-gate (DG) TFTs compared to single-gate (SG) TFTs. The addition of a backgate in dual-gate TFTs saturates the drain current at one half of the V DS required for SG devices when front and backgate oxides are matched. This behaviour can be expected for various configurations of DG TFTs. TFTs with gate and backgate shorted, with gate or back-gate connected to source, and in diode load are discussed. The derived drain current equation for DG devices explains the lower saturation voltage and allows V DS,Sat extraction. The model has been verified by characterizing different configurations, and comparing them to the device model simulations
Scientometric Portrait of Homi Jehangir Bhabha: The Father of Indian Nuclear Research Programme
Get PDFQuantitative and qualitative analysis with graphic representation of the publication productivity of a scientist facilitates easy and clear perception about the work of a scientist. Bhabha’s scientific work spanned over more than three decades (1933-1967) during which he published 104 publications, which could be classified into nine fields: Interaction of Radiation with Matter (4), Quantum Electrodynamics (5), Mathematical Physics (2), Cosmic Ray Physics (18), Elementary Particle Physics (14), Field Theory (15), General Physics (2), Nuclear Physics (4) and General (40). The highest number of publications (6) were published in 1941, 1945 and 1964 respectively. The average number of publications published per year was 3.05. His productivity coefficient was 0.05 which is a clear indicates that his publication productivity was quite consistent throughout his scientific career. He was single author in 79 of his publications and the main author in 24 publications indicates that he always preferred to work himself and lead the team as ‘mentor’. Bhabha had 22 collaborators during the period. Team of research collaborators working with a successful scientist documents the sociological aspect of history of science while generating knowledge by a leader in a domain.
Bhabha became a citable author in 1937. Bhabha received 1211 citations to his 30 publications out of 104 publications. Out of 104, 74 publications did not receive any citations. Out of 74 publications, 40 publications dealt subjects mainly of general interest. Bhabha’s 86.66 percent of cited publications received their first citations within four years of their publication indicates that his publications were noticed immediately and had direct impact among the fellow researchers working all over the world. His overall citation rate was 11.64 per cited publication. The highest citations 389 were received to the domain ‘Cosmic ray physics’. The highest number of citations received were 45 in 1938. His self-citations were only 24 (1.98%) and citations by others were 1187 (98.02%). The highest self citations were six in 1946. Bhabha’s mean diachronous self-citation rate was 1.98. The highest citation rate 28.4 was to the domain ‘Quantum electrodynamics. His single authored publications have received the highest number 863 (71.26%) of citations. Bhabha’s five publications have been cited more than 100 times each. His publications have been cited by the authors working in various diverse fields like nuclear physics, mathematical physics, instrumentation, optics, geophysics and geochemistry, condensed matter physics, applied physics, electrical and electronic engineering, mechanical engineering etc., indicating a very diverse influence and impact of Bhabha’s publications. Bhabha’s publications have also been cited by the Nobel laureates like V. L. Ginzberg, Wolfgang Pauli, H. A. Bethe, M. Born, W. Bothe, E. P. Wigner, H. Yukawa, P. M. S. Blackett and C. N. Yang which is an indication of his originality of ideas and high quality of publications
Scientometric portrait of Nobel laureate Leland H. Hartwell
Get PDFLeland H. Hartwell was honoured with the Nobel Prize in Physiology or Medicine (2001) at his 62 years age and at 41 years of research publishing career. The first contribution of the author was in 1961 at the age of 22. The number of his contributions in a year peaked in 1997 when it touched 8. He had 108 publications during 1961 – 2001 in domains: Molecular Biology of Cell Cycle Regulation (43), Genetics of Cell Division (48), Genomic Re-arrangement and DNA Repair (9), Molecular Genetics of Yeast Cell Fission (5), and Drug Target Interaction (3) which were analysed for authorship pattern with his 101 collaborators. Most active researchers having number of publications with Leland H. Hartwell were : Weinert, T. A. (10), Garvik, B. M. (8), McLaughlin, C. S. (8), Jenness, D. D. (5). His productivity coefficient was 0.76 which clearly indicates that his productivity increased after 50 percentile age. Highest collaboration coefficient (1) for Leland H. Hartwell was found during 1963-1965, 1968-1969, 1977, 1981-1983, 1985-1990, 1996 and 1998-2001. Journals have been the most preferred channel of communication where, as many as 96 papers out of 108 have been published. The core journals publishing his papers were: Cell (14), Genetics (12), Mol. Cell Biol. (8), J. Bactariol. (7), J. Cell Biol. ( 7), Science (7) J. Mol. Biol.(6), Exp. Cell Res. (5), and Proc. Nat. Acad. Sci.(5). Publication density is 2.63 and Publication concentration is 14.63. Most prolific keywords in titles of publications were: Saccharomyces cerevisiae , Yeast , Cell division cycle , RAD9, DNA Damage , Genes , Cell cycle, Genetic control , Check point (s) , Cell division , Mutant of Yeast
Equation of state for dense matter from finite nuclei to neutron star mergers
No full textDocumentos apresentados no âmbito do reconhecimento de graus e diplomas estrangeirosEquation of state (EOS) of dense matter has been constrained from the experimental data available on the properties of finite nuclei and neutron stars. Towards this purpose, a diverse set of nuclear energy density functionals based on relativistic and non-relativistic mean field models have been employed.
These EOSs are so chosen that they are consistent with the bulk properties of the finite nuclei.
The values of various nuclear matter parameters which predominantly govern the behaviour of the EOS are determined through their correlations with the properties of the neutron stars such as radii, tidal deformability and maximum mass of the neutron stars. The nuclear matter parameters considered are incompressibility, symmetry energy and their density derivatives which appear in the expansion of the EOS around the saturation density. The radii and tidal deformability of the neutron star with
the canonical mass display strong correlations with the linear combinations of slopes of the incompressibility and symmetry energy coefficients. Similar correlations with the curvature of the symmetry energy coefficient are also obsvered indicating that the properties of the neutron stars are sensitive to the high density behaviour of the symmetry energy. It is also shown that the giant resonances in nuclei are instrumental in limiting the tidal deformability parameter and the radius of a neutron star in
somewhat narrower bounds. The outcomes of the present thesis is important in view of the fact that the accurate values of the various neutron star observables as considered are expected to be available in near future
To accelerate the battery simulation process for crash and impact tests using machine learning
No full textAn investigation into the prediction of thermal runaway in lithium-ion batteries subjected
to abusive mechanical loading is comparable to a crash or impact test and a crucial safety
measure that can prevent catastrophic events. Using an explicit crash simulation method, it
is possible to simulate the indentation test model and predict the thermal runaway. However,
it is important to note that this approach is associated with a significant time investment.
State-of-the-art technologies that involve machine learning for prediction of thermal runaway
can be utilised for faster predictions.
The research conducted in this thesis focuses on a cell model that simulates an indentation
test and a machine learning model that predicts the thermal runaway. This model successfully
captures the behavior of an internal short circuit and is verified using experimental data from
existing literature. Additionally, a workflow is generated in Altair Hyperstudy to produce
data essential for training the machine learning model using an automated process. This data
created is based on the design variables of the indenter (impacting body). This facilitates
comprehension of potential deformation, damage and related patterns. The machine learning
model is created using the Altair Physics AI tool and subsequently trained by the provided
dataset. Data, as foundational resource is used to train the machine learning model. These
datasets must be available in adequate quantities and of high quality for neural network training
to discover the relationship between input and output. The outcomes of this Machine
learning model yield an adequate degree of accuracy. The accuracy of these results is highly
dependent on the model, quality of data derived from this dataset and the Hyperparameters
used for the model training. Insights of the predicted results by ML model are of great use
for Design consideration and validation of lithium-ion batteries. The outcomes of conducting
the indentation test simulation on the cell jellyroll model provides insights on the potential
time in which a thermal runaway will occur, which could potentially lead to the occurrence of
a fire or explosion. Moreover, the development of a comprehensive scaled model incorporating
relevant data holds significant implications for future battery regulations.Outgoin
Journal of Natural Rubber Research 1987-1996: A ten-year bibliometric study
Get PDFThe Journal of Natural Rubber Research, published by the Rubber Research Institute of Malaysia since 1929, has played a key role in the dissemination of natural rubber information all over the world. This paper analyses the authorship pattern, the range and frequency of references cited, the extent of acknowledgement and appendix or appendices being included in research articles of natural rubber, the types of collaborative research in natural rubber and the international collaboration scenario as portrayed in the Journal. Results indicated that the trend is towards multi-authorship and a high degree of collaboration between natural rubber researchers
To accelerate the battery simulation process for crash and impact tests using machine learning
Get PDFAn investigation into the prediction of thermal runaway in lithium-ion batteries subjected
to abusive mechanical loading is comparable to a crash or impact test and a crucial safety
measure that can prevent catastrophic events. Using an explicit crash simulation method, it
is possible to simulate the indentation test model and predict the thermal runaway. However,
it is important to note that this approach is associated with a significant time investment.
State-of-the-art technologies that involve machine learning for prediction of thermal runaway
can be utilised for faster predictions.
The research conducted in this thesis focuses on a cell model that simulates an indentation
test and a machine learning model that predicts the thermal runaway. This model successfully
captures the behavior of an internal short circuit and is verified using experimental data from
existing literature. Additionally, a workflow is generated in Altair Hyperstudy to produce
data essential for training the machine learning model using an automated process. This data
created is based on the design variables of the indenter (impacting body). This facilitates
comprehension of potential deformation, damage and related patterns. The machine learning
model is created using the Altair Physics AI tool and subsequently trained by the provided
dataset. Data, as foundational resource is used to train the machine learning model. These
datasets must be available in adequate quantities and of high quality for neural network training
to discover the relationship between input and output. The outcomes of this Machine
learning model yield an adequate degree of accuracy. The accuracy of these results is highly
dependent on the model, quality of data derived from this dataset and the Hyperparameters
used for the model training. Insights of the predicted results by ML model are of great use
for Design consideration and validation of lithium-ion batteries. The outcomes of conducting
the indentation test simulation on the cell jellyroll model provides insights on the potential
time in which a thermal runaway will occur, which could potentially lead to the occurrence of
a fire or explosion. Moreover, the development of a comprehensive scaled model incorporating
relevant data holds significant implications for future battery regulations.Outgoin
Ananda K. Coomaraswamy, Benoy Kumar Sarkar, and the Śukranīti
Get PDFThe English-raised Ananda K. Coomaraswamy, the twentieth century’s leading historian of Indian art, is well known for prizing tradition and anonymity and for upholding the position that visualization exercises were an essential part of the creative process. The first part of this article addresses the role of the English Arts and Crafts Movement and of such lesser-known figures as Sister Nivedita and Lionel de Fonseka in shaping Coomaraswamy’s views. The middle part consists of a discussion of the passages in the nineteenth-century Sanskrit treatise the Śukranīti that Coomaraswamy depended upon to support his opinions. The final part of the article is devoted to the writings of the sociologist Benoy Kumar Sarkar, author of the standard translation of the Śukranīti. As an opponent of the over-spiritualisation of Indian civilisation, he constructed a universal grammar of art. In this enterprise, he was heavily influenced by the American painter Max Weber
Heterogeneous sub-continuum ionic transport in statistically isolated graphene nanopores
No full textGraphene and other two-dimensional materials offer a new class of ultrathin membranes that can have atomically defined nanopores with diameters approaching those of hydrated ions1, 2, 3, 4, 5, 6, 7. These nanopores have the smallest possible pore volumes of any ion channel, which, due to ionic dehydration8 and electrokinetic effects9, places them in a novel transport regime and allows membranes to be created that combine selective ionic transport10 with ultimate permeance11, 12, 13 and could lead to separations14, 15 and sensing16 applications. However, experimental characterization and understanding of sub-continuum ionic transport in nanopores below 2 nm is limited17, 18. Here we show that isolated sub-2 nm pores in graphene exhibit, in contrast to larger pores, diverse transport behaviours consistent with ion transport over a free-energy barrier arising from ion dehydration and electrostatic interactions. Current–voltage measurements reveal that the conductance of graphene nanopores spans three orders of magnitude8 and that they display distinct linear, voltage-activated or rectified current–voltage characteristics and different cation-selectivity profiles. In rare cases, rapid, voltage-dependent stochastic switching is observed, consistent with the presence of a dissociable group in the pore vicinity19. A modified Nernst–Planck model incorporating ion hydration and electrostatic effects quantitatively matches the observed behaviours.United States. Department of Energy. Office of Basic Energy Sciences (award no. DE-SC0008059)National Science Foundation (U.S.) (award no. DMR-0819762
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