On the complexity measures of mutation hotspots in human TP53 protein

2020 ◽  
Vol 30 (7) ◽  
pp. 073118
Author(s):  
Yan Ding ◽  
Hongsheng Xue ◽  
Xinjia Ding ◽  
Yuqing Zhao ◽  
Zhilong Zhao ◽  
...  
Keyword(s):  
Complexity Measures ◽  
Tp53 Protein

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

scholarly journals Normalized Sombor Indices as Complexity Measures of Random Networks

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 976
Author(s):  
R. Aguilar-Sánchez ◽  
J. Méndez-Bermúdez ◽  
José Rodríguez ◽  
José Sigarreta
Keyword(s):  
Random Matrix ◽  
Adjacency Matrix ◽  
Matrix Theory ◽  
Computational Study ◽  
Random Networks ◽  
Geometric Graphs ◽  
Theory Approach ◽  
Complexity Measures ◽  
Random Geometric Graphs ◽  
Highly Correlated

We perform a detailed computational study of the recently introduced Sombor indices on random networks. Specifically, we apply Sombor indices on three models of random networks: Erdös-Rényi networks, random geometric graphs, and bipartite random networks. Within a statistical random matrix theory approach, we show that the average values of Sombor indices, normalized to the order of the network, scale with the average degree. Moreover, we discuss the application of average Sombor indices as complexity measures of random networks and, as a consequence, we show that selected normalized Sombor indices are highly correlated with the Shannon entropy of the eigenvectors of the adjacency matrix.

scholarly journals Crystal Chemical Relations in the Shchurovskyite Family: Synthesis and Crystal Structures of K2Cu[Cu3O]2(PO4)4 and K2.35Cu0.825[Cu3O]2(PO4)4

Crystals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 807
Author(s):  
Ilya V. Kornyakov ◽  
Sergey V. Krivovichev
Keyword(s):  
Crystal Structure ◽  
Crystal Structures ◽  
Structural Complexity ◽  
Crystal Chemical ◽  
X Ray Diffraction ◽  
Complexity Measures ◽  
X Ray ◽  
The Family ◽  
Similarities And Differences ◽  
Related Compounds

Single crystals of two novel shchurovskyite-related compounds, K2Cu[Cu3O]2(PO4)4 (1) and K2.35Cu0.825[Cu3O]2(PO4)4 (2), were synthesized by crystallization from gaseous phase and structurally characterized using single-crystal X-ray diffraction analysis. The crystal structures of both compounds are based upon similar Cu-based layers, formed by rods of the [O2Cu6] dimers of oxocentered (OCu4) tetrahedra. The topologies of the layers show both similarities and differences from the shchurovskyite-type layers. The layers are connected in different fashions via additional Cu atoms located in the interlayer, in contrast to shchurovskyite, where the layers are linked by Ca2+ cations. The structures of the shchurovskyite family are characterized using information-based structural complexity measures, which demonstrate that the crystal structure of 1 is the simplest one, whereas that of 2 is the most complex in the family.

scholarly journals Entropic measure unveils country competitiveness and product specialization in the World trade web

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gianluca Teza ◽  
Michele Caraglio ◽  
Attilio L. Stella
Keyword(s):  
Iterative Scheme ◽  
Entropy Function ◽  
Bipartite Networks ◽  
Complexity Measures ◽  
Wide Range ◽  
Self Consistent ◽  
Set Up ◽  
Technical Features ◽  
Country Competitiveness ◽  
Entropic Measure

AbstractWe show how the Shannon entropy function can be used as a basis to set up complexity measures weighting the economic efficiency of countries and the specialization of products beyond bare diversification. This entropy function guarantees the existence of a fixed point which is rapidly reached by an iterative scheme converging to our self-consistent measures. Our approach naturally allows to decompose into inter-sectorial and intra-sectorial contributions the country competitivity measure if products are partitioned into larger categories. Besides outlining the technical features and advantages of the method, we describe a wide range of results arising from the analysis of the obtained rankings and we benchmark these observations against those established with other economical parameters. These comparisons allow to partition countries and products into various main typologies, with well-revealed characterizing features. Our methods have wide applicability to general problems of ranking in bipartite networks.

The effects of topic familiarity on emotionality and linguistic complexity in EAP writing

2021 ◽  
pp. 136216882110335
Author(s):  
Mahmoud Abdi Tabari ◽  
Gavin Bui ◽  
Yizhou Wang
Keyword(s):  
Cognitive Complexity ◽  
Task Complexity ◽  
Assessment Tools ◽  
Automatic Assessment ◽  
Complexity Measures ◽  
Linguistic Complexity ◽  
Writing Performance ◽  
Topic Familiarity ◽  
Writing Courses ◽  
International Graduate

Focusing on the relationship between linguistic, cognitive, socioemotional factors in writing English for academic purposes (EAP), this study investigated whether topic familiarity as an important cognitive factor of task complexity influences different levels of emotionality and linguistic complexity in EAP writing and whether there are relationships between emotionality and linguistic complexity. To do so, 64 international graduate learners enrolled in EAP writing courses participated in the present study. Each wrote on familiar and unfamiliar topics determined via a questionnaire at the onset of the study. Their writings were then measured for textual emotionality and linguistic complexity using automatic assessment tools. Results showed that EAP writings differed systematically in terms of both emotionality and linguistic complexity due to the influence of topic familiarity. Unfamiliar topics led to writing performance with a significantly higher level of emotional negativity and significantly lower linguistic complexity levels as compared to familiar topics. A follow-up correlation analysis also revealed significant relationships between emotionality and linguistic complexity measures, indicating complex interactions between linguistic and socioemotional factors. Implications of these findings are discussed relative to deploying writing topics with varied levels of cognitive complexity for encouraging classroom engagement and improving L2 learners’ writing performance by effective task sequencing.

scholarly journals An Entropy-Based Formulation for Assessing the Complexity Level of a Mass Customization Industry 4.0 Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
César Martínez-Olvera
Keyword(s):  
Mass Customization ◽  
Industry 4.0 ◽  
Discrete Event ◽  
Complexity Measures ◽  
Event Simulation ◽  
Manufacturing Complexity ◽  
Original Contribution ◽  
Managerial Implications ◽  
Product Customization ◽  
System Operating

It has been stated that Industry 4.0’s goal is, among others, the sustainable success in a market characterized by exigent and informed consumers demanding personalized products and services, where the level of manufacturing complexity increases with level of product customization. Even though different manufacturing complexity measures have been developed, there seems to be a lack of a comprehensive metric that address both the mass customization variety-induced complexity, and the complexity derived from the adoption of the Industry 4.0 paradigm. The main original contribution of this paper is the development of an entropy-based (entropic) formulation to address this last issue. Its validity and usefulness is put to the test via a discrete-event simulation study of a mass customization production system operating within an Industry 4.0 context. Our findings show that the entropic formulation acts as a fairly good trend indicator of the system’s performance parameter increase/decrease, but not as an estimator of the final values. A discussion of the managerial implications of the obtained results is offered at the end of the paper.

scholarly journals Extending Bayesian concept learning to deal with representational complexity and adaptation

2001 ◽  
Vol 24 (4) ◽  
pp. 685-686
Author(s):  
Michael D. Lee
Keyword(s):  
Concept Learning ◽  
Learning Model ◽  
Fundamental Issue ◽  
Complexity Measures ◽  
Stimulus Representation ◽  
Hypothesis Space ◽  
Space Approach

While Tenenbaum and Griffiths impressively consolidate and extend Shepard's research in the areas of stimulus representation and generalization, there is a need for complexity measures to be developed to control the flexibility of their “hypothesis space” approach to representation. It may also be possible to extend their concept learning model to consider the fundamental issue of representational adaptation. [Tenenbaum & Griffiths]

Sign in / Sign up

Export Citation Format

Share Document