27 research outputs found
A biobibliometric study on Prof. B. N. Koley, an eminent physiologist
No full text74-82This biobibliometric study is based on 251 papers of Prof. B. N. Koley published during 1958-2001. On the basis of collecteddata, this study examines year-wise distribution of papers, research group of the scientist and scattering of papers in differentcommunication channels. In addition, it finds out author productivity, spectrum of research activity through analysis of the titlekeywords, and productivity of Koley's research group. Finally, it shows that the data set does not follow Bradford distribution
Social Capital as Engagement and Belief Revision
No full textSocial Capital or “goodwill” is an essential ingredient of any collective activity – be it commercial, cultural or administrative activity. In online environments, several models have been pursued for recording and utilizing social capital based on signals including likes or upvotes. Such explicitly stated signals are susceptible to impulsive behavior and hyperinflation. In this paper, we develop an implicit model for social capital based on the extent of engagement generated by any participant’s activities, and the way this engagement leads to a belief revision about the participant from other members of the community. Two kinds of social capital measures are proposed: an authority score that indicates engagement, and a citizenship score that calibrates value-addition made by a user as a result of engaging with others’ content. The proposed model is implemented in two online communities showing different kinds of content authorities, supported by a strong community of engaged citizens
The Internet is creating Net-States
No full textA nation-state is a geopolitical entity with the cultural entity of a nation, from which it aims to derive its political legitimacy to rule. A few key features of the nation-state are:
A Sovereign Government
Exclusive/Semi-exclusive Citizenship
Territorial Integrity or Territorial Impermeability
Nationalism as the core Philosophy
The Web and Internet are two of the most significant technologies that are currently shaping our world. The increased Internet penetration and cheap access has spawned a whole lot of very popular web based services: search and advertising services like those offered by Google, social networks like Facebook, Twitter, Instagram; video stores like YouTube and others.
An individual generates tremendous amount of data pertaining to his or her activities throughout the day, using these services. This data acts as a user’s identity or a “Data Double” on the Web with the service provider often being considered as the guarantor of the authenticity of the user. Our profiles at Facebook, Instagram, LinkedIn, Uber are such identities. And they are trusted albeit only to a certain extent.
Also each of these Web Giants have their own governance style, characterised by their rules and regulations which are determined by both policy and the algorithms that run these platforms. Adding to that, the web is increasingly encouraging more cross-border exchanges of goods and services, allowing users and firms to bypass national borders.
These phenomena raises the question of: Are these Web Giants a different kind of nation-state themselves? Is the Internet helping shape Net-States? To answer these questions, we use the theory of sociomateriality
Non-uniqueness of Hölder continuous solutions for Inhomogeneous Incompressible Euler flows
No full textWe consider the inhomogeneous (or density dependent) incompressible Euler equations in a three-dimensional periodic domain. We construct density and velocity such that, for any , both of them are -Hölder continuous and is a weak solution to the underlying equations. The proof is based on typical convex integration techniques using Mikado flows as building blocks. As a main novelty with respect to the related literature, our result produces a Hölder continuous density.41 pages. arXiv admin note: text overlap with arXiv:2006.06482, arXiv:2101.09278 by other author
Non-uniqueness of Hölder continuous solutions for stochastic Euler and Hypodissipative Navier-Stokes equations
No full textHere we construct infinitely many Hölder continuous global-in-time and stationary solutions to the stochastic Euler and hypodissipative Navier-Stokes equations in the space for , with and respectively. A modified stochastic convex integration scheme, using Beltrami flows as building blocks and propagating inductive estimates both pathwise and in expectation, plays a pivotal role to improve the regularity of Hölder continuous solutions for the underlying equations. As a main novelty with respect to the related literature, our result produces solutions with noteworthy Hölder exponents.38 pages. arXiv admin note: substantial text overlap with arXiv:2401.09894 by other author
INDIAN JOURNAL OF PHYSIOLOGY AND ALLIED SCIENCES: AN ANALYSIS OF CITATION PATTERN
No full text23-26The present study covers 457 citations appended to 26 research articles published in the four issues of the quarterly Indian Journal of Physiology and Allied Sciences,vol. 55(200 1). The articles are contributed by 75 authors (74 - Indian). From the citation count it appears that the solo research in physiology is quite substantial (about 24%). Though about 77% of the work is the result of team research, the team size is found to be small ranging from 2 to 5. Of the citations, 76.81 per cent relate to journal articles, 18.59 to monographs, and the rest to conference papers, theses, etc. The ratio of Indian to foreign citations is found to be almost 1:6. Of the total citations, 4.59 percent are author self citations, and 2.84 percent are journal self citations. Of the citing articles one is single- authored,10 are two-authored, 9 three-authored, 4 four-authored, and one each five- authored and six-authored. No collaboration was noticed in the case of 23 citing articles.The remaining 3 articles were the results of two-institution collaboration
Nobel Laureate Anthony J Leggett: A scientometric portrait
No full textThis paper attempts to analyse the publication productivity of Anthony J. Leggett, the 2003 Nobel Prize winner in physics. His contributions peaked in 1987, 1994, and 1998 with 10 papers each. He had 194 publications during 1964 - 2004 in domains like Superfluid 3He (65), Foundations of Quantum Mechanics (36), Dissipative Quantum Systems (24), Atomic Alkali Gases (18), and Miscellaneous (51)which were analysed for authorship pattern with his 70 collaborators. Most active collaborators with Anthony J Leggett were: A. Garg with six papers and A. O. MCaldeira, D. M. Ginsberg, D. J. Vanharlingen , F. Sols, S.Takagi and D. A. Wollman with five papers each. His productivity coefficient was 0.60 which clearly indicates that his productivity
increased after 50 percentile age. The highest degree of collaboration (1) for Anthony J. Leggett was found during 1964, 1971 and 1983. Journals have been the most preferred channel of communication, where as many as 139 papers out of 194 have been published. The core journals publishing his papers were: Phys. Rev. Leu. (42), Phys. Rev. B (9), J. Low Temp. Phys. (8),Phys. Rev. A (7), Ann. Phys. (6), Foundations of physics (6), J. Phys.(5), Prog. Theor: Phys. (5), and Rev. Mod. Phys. (5).Publication density was 3.02 and publication concentration was 3.59
Enhancing Biogas Production Through the Co-Digestion of Fish Waste (FW) and Water Hyacinth (WH) Using Cow Dung as an Inoculum: Effect of FW/WH Ratio
No full textThe current investigation explores biogas production from water hyacinth (WH) and fish waste (FW) with cow dung (CD) as an inoculum source in two scenarios. In the first scenario, the optimization of mono-digestion was performed where the effect of WH/FW (substrates) with CD (inoculum) in varied ratios of 1:1, 1:2, 2:1, and 3:1 was observed to enhance the biogas production. In the second scenario, the optimization of co-digestion using both FW and WH as substrates in different ratios (1:1, 1:2, and 2:1) with a fixed amount of inoculum was studied. The experiments were conducted in 500 mL digesters in duplicate under mesophilic conditions. Under mono-digestion conditions for FW, the digester operating with FW/CD in a 1:2 ratio demonstrated the highest biogas yield of 970 ± 14.1 mL/g VS, containing 610 CH4 mL/g VS, while in WH, the WH/CD ratio of 1:1 exhibited the highest biogas yield of 925 ± 49.4 mL/g VS, with a methane content of 440 CH4 mL/g VS. The co-digestion of the WH/FW ratio (1:1) showcased the highest biogas production of 1655 ± 91.92 mL/g VS, accompanied by 890 ± 70.7 CH4 mL/g VS. This was followed by the 1:2 and 2:1 ratio, yielding 1400 ± 56.5 and 1140 ± 169.7 mL/g VS. of biogas and 775 and 585 CH4 mL/g VS, respectively. The CD and WH mixture at a 1:1 ratio demonstrated the most significant decrease in chemical oxygen demand (COD), reaching 91.68%. COD reductions over 80% in all combinations were observed in all instances. Anaerobic digestion (AD) simulations were validated using the Gompertz model, with high correlation coefficient values (R-squared) above 0.99 for all of the studied ratios, depicting a significant correlation between experimental data and model predictions. The propionic to acetic acid ratio did not cross the threshold level, indicating no inhibition of methane production. ANOVA analysis of biogas production between the co-digestion and mono-digestion of substrates showed non-significant results (p > 0.310 and p > 0.824, respectively), while overall digestion was significant (p < 0.024), indicating efficiency variations among substrates. Paired sample t-tests revealed substantial differences between co-digestion ratios, which were also significant
Generative Maximum Entropy Learning for Multiclass Classification
No full textMaximum entropy approach to classification is very well studied in applied statistics and machine learning and almost all the methods that exists in literature are discriminative in nature. In this paper, we introduce a maximum entropy classification method with feature selection for large dimensional data such as text datasets that is generative in nature. To tackle the curse of dimensionality of large data sets, we employ conditional independence assumption (Naive Bayes) and we perform feature selection simultaneously, by enforcing a `maximum discrimination' between estimated class conditional densities. For two class problems, in the proposed method, we use Jeffreys (J) divergence to discriminate the class conditional densities. To extend our method to the multi-class case, we propose a completely new approach by considering a multi-distribution divergence: we replace Jeffreys divergence by Jensen-Shannon (JS) divergence to discriminate conditional densities of multiple classes. In order to reduce computational complexity, we employ a modified Jensen-Shannon divergence (JS(GM)), based on AM-GM inequality. We show that the resulting divergence is a natural generalization of Jeffreys divergence to a multiple distributions case. As far as the theoretical justifications are concerned we show that when one intends to select the best features in a generative maximum entropy approach, maximum discrimination using J-divergence emerges naturally in binary classification. Performance and comparative study of the proposed algorithms have been demonstrated on large dimensional text and gene expression datasets that show our methods scale up very well with large dimensional datasets
