The Intrinsic Structure of Nuclear Chemistry: A Scientometric Study

: In the last two decades, the research in nuclear chemistry has experienced a regular as well as voluminous structural changes and has grown notably with interaction from other fields in terms of theory building, methodology, and applications. This study focus a quantitative assessment of the scientific literature for mapping the intellectual structure of nuclear chemistry research and its scientific development over a 11-year period from 2008 till 2018. A total of 109281 publications were subjected to examination in order to draw statistics and depict dynamic changes to shed new light upon the growth, dispersion and structure of the studied domain. In general this work characterizes the papers, in terms of growth, institution, document type, prominent authors and institutions, and geographical distributio

A Scientometrics Analysis of World Vertigo Research Output with the reference of Web of science in 2001-2017

The study examines world publications on Vertigo research during 2001-2017, Scientometrics techniques are engaged to analyze the publications to identify the trend in publication. The total 7459 articles were taken up for study from Web of Science, a bibliographical and citation database offered by Clarivate Analytics which provides access to quality content. The articles pertaining to the area of vertigo and similar studies i.e. dizziness, Meniere’s disease, BBPV and related problems also includes. The result showed that the highest records 685 were published in 2015 and lowest 231 of records were published in 2002. Among all the listed sources ‘Article’ taken the first position with 6,036 records. The study also found that Cohe B. is active author, contributed above 134 numbers of articles has occupied the first position. The University of Munich was the top most contributed institution on Vertigo research with 266 records from Germany. In present study, Relative Growth Rate and Doubling Time also calculated

Rate-Based End-to-End Congestion Control of Multimedia Traffic in Packet Switched Networks

This paper proposes an explicit rate-based end-to-end congestion control mechanism to alleviate congestion of multimedia traffic in packet switched networks such as the Internet. The congestion is controlled by adjusting the transmission rates of the sources in response to the feedback information from destination such as the buffer occupancy, packet arrival rate and service rate at the outgoing link, so that a desired quality of service (QoS) can be met. The QoS is defined in terms of packet loss ratio, transmission delay, power, and network utilization. Comparison studies demonstrate the effectiveness of the proposed scheme over New-Reno TCP (a variant of AIMD: additive increase multiplicative decrease) technique during simulated congestion. Since it is end-to-end, no router support is necessary, the proposed methodology can be readily applied to today\u27s Internet, as well as for real-time video and voice data transfer in unicast networks

A Multi-Step Nonlinear Dimension-Reduction Approach with Applications to Bigdata

In this paper, a multi-step dimension-reduction approach is proposed for addressing nonlinear relationships within attributes. In this work, the attributes in the data are first organized into groups. In each group, the dimensions are reduced via a parametric mapping that takes into account nonlinear relationships. Mapping parameters are estimated using a low rank singular value decomposition (SVD) of distance covariance. Subsequently, the attributes are reorganized into groups based on the magnitude of their respective singular values. The group-wise organization and the subsequent reduction process is performed for multiple steps until a singular value-based user-defined criterion is satisfied. Simulation analysis is utilized to investigate the performance with five big data-sets

Direct Error Driven Learning for Deep Neural Networks with Applications to Bigdata

In this paper, generalization error for traditional learning regimes-based classification is demonstrated to increase in the presence of bigdata challenges such as noise and heterogeneity. To reduce this error while mitigating vanishing gradients, a deep neural network (NN)-based framework with a direct error-driven learning scheme is proposed. To reduce the impact of heterogeneity, an overall cost comprised of the learning error and approximate generalization error is defined where two NNs are utilized to estimate the costs respectively. To mitigate the issue of vanishing gradients, a direct error-driven learning regime is proposed where the error is directly utilized for learning. It is demonstrated that the proposed approach improves accuracy by 7 % over traditional learning regimes. The proposed approach mitigated the vanishing gradient problem and improved generalization by 6%

Optimal Adaptive Output Regulation of Uncertain Nonlinear Discrete-Time Systems using Lifelong Concurrent Learning

This Paper Addresses Neural Network (NN) based Optimal Adaptive Regulation of Uncertain Nonlinear Discrete-Time Systems in Affine Form using Output Feedback Via Lifelong Concurrent Learning. First, an Adaptive NN Observer is Introduced to Estimate Both the State Vector and Control Coefficient Matrix, and its NN Weights Are Adjusted using Both Output Error and Concurrent Learning Term to Relax the Persistency Excitation (PE) Condition. Next, by Utilizing an Actor-Critic Framework for Estimating the Value Functional and Control Policy, the Critic Network Weights Are Tuned Via Both Temporal Different Error and Concurrent Learning Schemes through a Replay Buffer. the Actor NN Weights Are Tuned using Control Policy Errors. to Attain Lifelong Learning for Performing Effectively during Multiple Tasks, an Elastic Weight Consolidation Term is Added to the Critic NN Weight Tuning Law. the State Estimation, Regulation, and the Weight Estimation Errors of the Observer, Actor and Critic NNs Are Demonstrated to Be Bounded When Performing Tasks by using Lyapunov Analysis. Simulation Results Are Carried Out to Verify the Effectiveness of the Proposed Approach on a Vander Pol Oscillator. Finally, Extension to Optimal Tracking is Given Briefly

Synthesis, anti-inflammatory and analgesic activity of 4-(substituted benzylamino)-5-substituted phenyl-3-amino-1,2,4-triazole derivatives

A novel series of 4-(substituted benzylamino)-5-substituted phenyl-3-amino-1, 2, 4-triazole derivatives were synthesized by reaction of 5-substituted phenyl-3,4-diamino-1,2,4-triazole with different aromatic aldehydes. The structures of the compounds were synthesized and characterised by elemental analysis, 1H NMR, Mass and IR Spectra. The title compounds were investigated for anti-inflammatory and analgesic activities using carrageenan induced rat paw edema and acetic induced writhing test, respectively. All the test compounds exhibited significant activity, compounds IVg, IVh and IVb showed more potent anti-inflammatory activity when compared with standard (Ibuprofen). All the test compounds were significantly (p < 0.05) reduced writhings induced by the acetic acid in mice.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Synthesis, anti-inflammatory and analgesic activity of 4-(substituted benzylamino)-5-substituted phenyl-3-amino-1,2,4-triazole derivatives

A novel series of 4-(substituted benzylamino)-5-substituted phenyl-3-amino-1, 2, 4-triazole derivatives were synthesized by reaction of 5-substituted phenyl-3,4-diamino-1,2,4-triazole with different aromatic aldehydes. The structures of the compounds were synthesized and characterised by elemental analysis, 1H NMR, Mass and IR Spectra. The title compounds were investigated for anti-inflammatory and analgesic activities using carrageenan induced rat paw edema and acetic induced writhing test, respectively. All the test compounds exhibited significant activity, compounds IVg, IVh and IVb showed more potent anti-inflammatory activity when compared with standard (Ibuprofen). All the test compounds were significantly (p < 0.05) reduced writhings induced by the acetic acid in mice.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Dynamic disorder in receptor-ligand forced dissociation experiments

Recently experiments showed that some biological noncovalent bonds increase their lifetimes when they are stretched by an external force, and their lifetimes will decrease when the force increases further. Several specific quantitative models have been proposed to explain the intriguing transitions from the "catch-bond" to the "slip-bond". Different from the previous efforts, in this work we propose that the dynamic disorder of the force-dependent dissociation rate can account for the counterintuitive behaviors of the bonds. A Gaussian stochastic rate model is used to quantitatively describe the transitions observed recently in the single bond P-selctin glycoprotein ligand 1(PSGL-1)$-$P-selectin force rupture experiment [Marshall, {\it et al.}, (2003) Nature {\bf 423}, 190-193]. Our model agrees well to the experimental data. We conclude that the catch bonds could arise from the stronger positive correlation between the height of the intrinsic energy barrier and the distance from the bound state to the barrier; classical pathway scenario or {\it a priori} catch bond assumption is not essential.Comment: 4 pages, 2 figure

The Realities of Evaluating Educational Technology in School Settings

\ua9 2024 Copyright held by the owner/author(s).HCI researchers are increasingly interested in the evaluation of educational technologies in context, yet acknowledge that challenges remain regarding the logistical, material and methodological constraints of this approach to research [18, 53].Through the analysis of the authors\u27 contributed thematic research vignettes, the following article exposes the practical realities of evaluating educational technologies in school settings. This includes insights into the planning stages of evaluation, the relationship between the researcher and the school environment, and the impact of the school context on the data collection process.We conclude by providing an orientation for the design of HCI educational technology research undertaken in school contexts, providing guidance such as considering the role of modular research design, clarifying goals and expectations with school partners, and reporting researcher positionality