scholarly journals A Discussion of the Favorable Factors for the Economic System’s Utility Growth Rate

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Lunhan Luo ◽  
Jianan Fang
Keyword(s):  
Growth Rate ◽  
Utility Function ◽  
Group Size ◽  
Growth Rates ◽  
Small World ◽  
Economic Systems ◽  
Network Structures ◽  
Small World Network ◽  
Proper Volume

Some virtual economic systems are constructed. The agents in the systems are linked crossover by different network structures and endowed with goods and the same symmetric Cobb-Douglas utility function. Their Cobb-Douglas utility growth rates (UGR) are compared with each other after the systems reach their eventual equilibriums. We try to discover how the network structures and how the endowments affect the UGR. Furthermore, the possible factors including group size, trade sequence, turnover, and number of trades are taken into account. Some but not all of the factors listed above may impact the UGR. The aim of this paper is to select the effective ones and try to improve the UGR by manipulating these factors. We discovered that the small-world network surpasses other networks to achieve the highest UGR. Besides, another way to improve UGR is to endow the agents with proper volume of goods.

scholarly journals How Does the Heterogeneity of Members Affect the Evolution of Group Opinions?

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
An Lu ◽  
Haifeng Ling ◽  
Zhengping Ding
Keyword(s):  
Decision Making ◽  
Random Network ◽  
Small World ◽  
Important Influence ◽  
The Other ◽  
Network Structures ◽  
Small World Network ◽  
Average Amount ◽  
Regular Network ◽  
The Impact

Understanding the impact of heterogeneity on the evolution of group opinions can enlighten us on how to effectively organize, redesign, and improve decision-making efficiency. This article explores mainly the effects of heterogeneity on the evolution of group opinions. It is found that the heterogeneity of individuals’ openness has an important influence on the ability to aggregate group opinions. According to the average amount of clusters and Herfindahl–Hirschman Index (HHI) under different network structures, heterogeneity often improves the ability. In addition, for the small-world network and random network, there is little difference in the aggregation ability from both the average amount of clusters and the Herfindahl–Hirschman Index. While for the regular network, the ability is obviously weaker than that of the other two. This result also shows that the randomness of interaction between members will enhance the cohesion of a group.

scholarly journals A Study of How the Watts-Strogatz Model Relates to an Economic System’s Utility

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Lunhan Luo ◽  
Jianan Fang
Keyword(s):  
Growth Rate ◽  
Economic System ◽  
Group Size ◽  
System Performance ◽  
Small World ◽  
System Structure ◽  
Equal Size ◽  
Small World Networks ◽  
Growth Ratio ◽  
Size Number

Watts-Strogatz model is a main mechanism to construct the small-world networks. It is widely used in the simulations of small-world featured systems including economic system. Formally, the model contains a parameters set including three variables representing group size, number of neighbors, and rewiring probability. This paper discusses how the parameters set relates to the economic system performance which is utility growth rate. In conclusion, it is found that, regardless of the group size and rewiring probability, 2 to 18 neighbors can help the economic system reach the highest utility growth rate. Furthermore, given the range of neighbors and group size of a Watts-Strogatz model based system, the range of its edges can be calculated too. By examining the containment relationship between that range and the edge number of an actual equal-size economic system, we could know whether the system structure has redundant edges or can achieve the highest utility growth ratio.

Analysis of Oncogene Protein Structure Using Small World Network Concept

2020 ◽  
Vol 15 (7) ◽  
pp. 732-740
Author(s):  
Neetu Kumari ◽  
Anshul Verma
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
Degree Distribution ◽  
Protein Structures ◽  
Small World ◽  
Extreme Condition ◽  
Centrality Measures ◽  
Small World Network ◽  
Network Concept ◽  
Oncogene Protein

Background: The basic building block of a body is protein which is a complex system whose structure plays a key role in activation, catalysis, messaging and disease states. Therefore, careful investigation of protein structure is necessary for the diagnosis of diseases and for the drug designing. Protein structures are described at their different levels of complexity: primary (chain), secondary (helical), tertiary (3D), and quaternary structure. Analyzing complex 3D structure of protein is a difficult task but it can be analyzed as a network of interconnection between its component, where amino acids are considered as nodes and interconnection between them are edges. Objective: Many literature works have proven that the small world network concept provides many new opportunities to investigate network of biological systems. The objective of this paper is analyzing the protein structure using small world concept. Methods: Protein is analyzed using small world network concept, specifically where extreme condition is having a degree distribution which follows power law. For the correct verification of the proposed approach, dataset of the Oncogene protein structure is analyzed using Python programming. Results: Protein structure is plotted as network of amino acids (Residue Interaction Graph (RIG)) using distance matrix of nodes with given threshold, then various centrality measures (i.e., degree distribution, Degree-Betweenness correlation, and Betweenness-Closeness correlation) are calculated for 1323 nodes and graphs are plotted. Conclusion: Ultimately, it is concluded that there exist hubs with higher centrality degree but less in number, and they are expected to be robust toward harmful effects of mutations with new functions.

Comparison of copper sulphate pentahydrate growth rates determined by different methods

1990 ◽  
Vol 55 (7) ◽  
pp. 1691-1707 ◽  
Author(s):  
Miloslav Karel ◽  
Jiří Hostomský ◽  
Jaroslav Nývlt ◽  
Axel König
Keyword(s):  
Growth Rate ◽  
Crystal Growth ◽  
Fluidized Bed ◽  
Growth Rates ◽  
Copper Sulphate ◽  
Crystal Growth Rate ◽  
Effect Of Temperature ◽  
Rotating Disc ◽  
Shape Factors ◽  
Data Treatment

Crystal growth rates of copper sulphate pentahydrate (CuSO4.5 H2O) determined by different authors and methods are compared. The methods included in this comparison are: (i) Measurement on a fixed crystal suspended in a streaming solution, (ii) measurement on a rotating disc, (iii) measurement in a fluidized bed, (iv) measurement in an agitated suspension. The comparison involves critical estimation of the supersaturation used in measurements, of shape factors used for data treatment and a correction for the effect of temperature. Conclusions are drawn for the choice of values to be specified when data of crystal growth rate measurements are published.

Measurement of growth rates for single crystals and pressed tablets of CuSO4.5 H2O on a rotating disc

1989 ◽  
Vol 54 (11) ◽  
pp. 2951-2961 ◽  
Author(s):  
Miloslav Karel ◽  
Jaroslav Nývlt
Keyword(s):  
Growth Rate ◽  
Single Crystal ◽  
Single Crystals ◽  
Growth Rates ◽  
Diffusion Coefficients ◽  
Preferred Orientation ◽  
Rotating Disc ◽  
Dissolution Rates ◽  
Rates Of Growth ◽  
Good Agreement

Measured growth and dissolution rates of single crystals and tablets were used to calculate the overall linear rates of growth and dissolution of CuSO4.5 H2O crystals. The growth rate for the tablet is by 20% higher than that calculated for the single crystal. It has been concluded that this difference is due to a preferred orientation of crystal faces on the tablet surface. Calculated diffusion coefficients and thicknesses of the diffusion and hydrodynamic layers in the vicinity of the growing or dissolving crystal are in good agreement with published values.

scholarly journals Accuracy of State-Level Surveillance during Emerging Outbreaks of Respiratory Viruses: A Model-Based Assessment

2021 ◽  
pp. 0272989X2110222
Author(s):  
Yuwen Gu ◽  
Elise DeDoncker ◽  
Richard VanEnk ◽  
Rajib Paul ◽  
Susan Peters ◽  
...  
Keyword(s):  
Growth Rate ◽  
Data Collection ◽  
Disease Progression ◽  
Health Care Providers ◽  
Growth Rates ◽  
State Level ◽  
Future Research ◽  
Care Providers ◽  
State Surveillance ◽  
First Come First Serve

It is long perceived that the more data collection, the more knowledge emerges about the real disease progression. During emergencies like the H1N1 and the severe acute respiratory syndrome coronavirus 2 pandemics, public health surveillance requested increased testing to address the exacerbated demand. However, it is currently unknown how accurately surveillance portrays disease progression through incidence and confirmed case trends. State surveillance, unlike commercial testing, can process specimens based on the upcoming demand (e.g., with testing restrictions). Hence, proper assessment of accuracy may lead to improvements for a robust infrastructure. Using the H1N1 pandemic experience, we developed a simulation that models the true unobserved influenza incidence trend in the State of Michigan, as well as trends observed at different data collection points of the surveillance system. We calculated the growth rate, or speed at which each trend increases during the pandemic growth phase, and we performed statistical experiments to assess the biases (or differences) between growth rates of unobserved and observed trends. We highlight the following results: 1) emergency-driven high-risk perception increases reporting, which leads to reduction of biases in the growth rates; 2) the best predicted growth rates are those estimated from the trend of specimens submitted to the surveillance point that receives reports from a variety of health care providers; and 3) under several criteria to queue specimens for viral subtyping with limited capacity, the best-performing criterion was to queue first-come, first-serve restricted to specimens with higher hospitalization risk. Under this criterion, the lab released capacity to subtype specimens for each day in the trend, which reduced the growth rate bias the most compared to other queuing criteria. Future research should investigate additional restrictions to the queue.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

scholarly journals StalGrowth—A Program to Estimate Speleothem Growth Rates and Seasonal Growth Variations

Geosciences ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 187
Author(s):  
Rolf Vieten ◽  
Francisco Hernandez
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Environmental Parameters ◽  
Ion Concentration ◽  
Radiometric Dating ◽  
Seasonal Growth ◽  
Climate Signal ◽  
Show Evidence ◽  
Cave Monitoring ◽  
Calcium Ion Concentration

Speleothems are one of the few archives which allow us to reconstruct the terrestrial paleoclimate and help us to understand the important climate dynamics in inhabited regions of our planet. Their time of growth can be precisely dated by radiometric techniques, but unfortunately seasonal radiometric dating resolution is so far not feasible. Numerous cave environmental monitoring studies show evidence for significant seasonal variations in parameters influencing carbonate deposition (calcium-ion concentration, cave air pCO2, drip rate and temperature). Variations in speleothem deposition rates need to be known in order to correctly decipher the climate signal stored in the speleothem archive. StalGrowth is the first software to quantify growth rates based on cave monitoring results, detect growth seasonality and estimate the seasonal growth bias. It quickly plots the predicted speleothem growth rate together with the influencing cave environmental parameters to identify which parameter(s) cause changes in speleothem growth rate, and it can also identify periods of no growth. This new program has been applied to multiannual cave monitoring studies in Austria, Gibraltar, Puerto Rico and Texas, and it has identified two cases of seasonal varying speleothem growth.

scholarly journals Effect of Light Intensity and Quality on Growth Rate and Composition of Chlorella vulgaris

Plants ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 31 ◽  
Author(s):  
Maria N. Metsoviti ◽  
George Papapolymerou ◽  
Ioannis T. Karapanagiotidis ◽  
Nikolaos Katsoulas
Keyword(s):  
Growth Rate ◽  
Light Intensity ◽  
Chlorella Vulgaris ◽  
Lipid Content ◽  
Growth Rates ◽  
Solar Irradiance ◽  
White Led ◽  
Microalgal Biomass ◽  
Nm Range ◽  
Effect Of Light

In this research, the effect of solar irradiance on Chlorella vulgaris cultivated in open bioreactors under greenhouse conditions was investigated, as well as of ratio of light intensity in the 420–520 nm range to light in the 580–680 nm range (I420–520/I580–680) and of artificial irradiation provided by red and white LED lamps in a closed flat plate laboratory bioreactor on the growth rate and composition. The increase in solar irradiance led to faster growth rates (μexp) of C. vulgaris under both environmental conditions studied in the greenhouse (in June up to 0.33 d−1 and in September up to 0.29 d−1) and higher lipid content in microalgal biomass (in June up to 25.6% and in September up to 24.7%). In the experiments conducted in the closed bioreactor, as the ratio I420–520/I580–680 increased, the specific growth rate and the biomass, protein and lipid productivities increased as well. Additionally, the increase in light intensity with red and white LED lamps resulted in faster growth rates (the μexp increased up to 0.36 d−1) and higher lipid content (up to 22.2%), while the protein, fiber, ash and moisture content remained relatively constant. Overall, the trend in biomass, lipid, and protein productivities as a function of light intensity was similar in the two systems (greenhouse and bioreactor).

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