scholarly journals Measuring Component Importance for Network System Using Cellular Automata

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Li He ◽  
Qiyan Cao ◽  
Fengjun Shang
Keyword(s):  
Growth Factor ◽  
Cellular Automata ◽  
Numerical Experiments ◽  
Importance Measure ◽  
Network System ◽  
Failure Rates ◽  
Random Series ◽  
Component Importance ◽  
The Impact ◽  
Computing Method

This paper concentrates on the component importance measure of a network whose arc failure rates are not deterministic and imprecise ones. Conventionally, a computing method of component importance and a measure method of reliability stability are proposed. Three metrics are analyzed first: Birnbaum measurement, component importance, and component risk growth factor. Based on them, the latter can measure the impact of the component importance on the reliability stability of a system. Examples in some typical structures illustrate how to calculate component importance and reliability stability, including uncertain random series, parallel, parallel-series, series-parallel, and bridge systems. The comprehensive numerical experiments demonstrate that both of these methods can efficiently and accurately evaluate the impact of an arc failure on the reliability of a network system.

scholarly journals Analysis of Network Reliability Characteristics and Importance of Components in a Communication Network

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1347
Author(s):  
Soni Bisht ◽  
Akshay Kumar ◽  
Nupur Goyal ◽  
Mangey Ram ◽  
Yury Klochkov
Keyword(s):  
Communication Network ◽  
Growth Factor ◽  
Network Reliability ◽  
Importance Measure ◽  
Average Risk ◽  
Reliability Indices ◽  
Reliability Characteristics ◽  
Critical Components ◽  
Component Failures ◽  
The Impact

Network reliability is one of the most important concepts in this modern era. Reliability characteristics, component significance measures, such as the Birnbaum importance measure, critical importance measure, the risk growth factor and average risk growth factor, and network reliability stability of the communication network system have been discussed in this paper to identify the critical components in the network, and also to quantify the impact of component failures. The study also proposes an efficient algorithm to compute the reliability indices of the network. The authors explore how the universal generating function can work to solve the problems related to the network using the exponentially distributed failure rate. To illustrate the proposed algorithm, a numerical example has been taken.

scholarly journals Importance Measures for NFV Data Center: An Availability Evaluation

2018 ◽  
Author(s):  
Rafael Souza ◽  
Marcelo Santos ◽  
Stênio Fernandes
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Network Function Virtualization ◽  
Importance Measure ◽  
Substantial Impact ◽  
Network Function ◽  
Component Importance ◽  
Importance Analysis ◽  
Reliability Block Diagrams ◽  
The Impact

Data center infrastructures need to provide high availability of their services. Unexpected spikes of downtime in data centers lead to financial losses. Besides, there are intangible costs such as damaged reputation, low employee satisfaction, and reduced customer retention. In this context, Network Function Virtualization (NFV) emerged as a paradigm that assists data centers in becoming more dynamic and flexible. This paper presents an availability evaluation and importance analysis under the redundancy of NFV in data centers. The NFV data center component importance is represented by using Reliability Block Diagrams (RBD). The proposed models have identified the availability importance and critical devices in an NFV data center. This research also suggests alternatives for device redundancy to reach higher availability and proposes a new importance measure for analyzing the impact of NFV factors on data center availability. The measure can evaluate the degree of the impact of a failure on the data center, therefore, help to identify the factors with a substantial impact on data center availability.

scholarly journals Protein Tyrosine Kinases: Their Roles and Their Targeting in Leukemia

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 184
Author(s):  
Kalpana K. Bhanumathy ◽  
Amrutha Balagopal ◽  
Frederick S. Vizeacoumar ◽  
Franco J. Vizeacoumar ◽  
Andrew Freywald ◽  
...  
Keyword(s):  
Growth Factor ◽  
Protein Kinase ◽  
Tyrosine Kinase ◽  
Protein Kinases ◽  
Tyrosine Kinases ◽  
Treatment Options ◽  
Growth Factor Receptor ◽  
Tyrosine Protein Kinase ◽  
Mesenchymal Epithelial Transition Factor ◽  
The Impact

Protein kinases constitute a large group of enzymes catalysing protein phosphorylation and controlling multiple signalling events. The human protein kinase superfamily consists of 518 members and represents a complicated system with intricate internal and external interactions. Protein kinases are classified into two main families based on the ability to phosphorylate either tyrosine or serine and threonine residues. Among the 90 tyrosine kinase genes, 58 are receptor types classified into 20 groups and 32 are of the nonreceptor types distributed into 10 groups. Tyrosine kinases execute their biological functions by controlling a variety of cellular responses, such as cell division, metabolism, migration, cell–cell and cell matrix adhesion, cell survival and apoptosis. Over the last 30 years, a major focus of research has been directed towards cancer-associated tyrosine kinases owing to their critical contributions to the development and aggressiveness of human malignancies through the pathological effects on cell behaviour. Leukaemia represents a heterogeneous group of haematological malignancies, characterised by an uncontrolled proliferation of undifferentiated hematopoietic cells or leukaemia blasts, mostly derived from bone marrow. They are usually classified as chronic or acute, depending on the rates of their progression, as well as myeloid or lymphoblastic, according to the type of blood cells involved. Overall, these malignancies are relatively common amongst both children and adults. In malignant haematopoiesis, multiple tyrosine kinases of both receptor and nonreceptor types, including AXL receptor tyrosine kinase (AXL), Discoidin domain receptor 1 (DDR1), Vascular endothelial growth factor receptor (VEGFR), Fibroblast growth factor receptor (FGFR), Mesenchymal–epithelial transition factor (MET), proto-oncogene c-Src (SRC), Spleen tyrosine kinase (SYK) and pro-oncogenic Abelson tyrosine-protein kinase 1 (ABL1) mutants, are implicated in the pathogenesis and drug resistance of practically all types of leukaemia. The role of ABL1 kinase mutants and their therapeutic inhibitors have been extensively analysed in scientific literature, and therefore, in this review, we provide insights into the impact and mechanism of action of other tyrosine kinases involved in the development and progression of human leukaemia and discuss the currently available and emerging treatment options based on targeting these molecules.

scholarly journals Landscape pattern and economic factors’ effect on prediction accuracy of cellular automata-Markov chain model on county scale

2020 ◽  
Vol 12 (1) ◽  
pp. 626-636
Author(s):  
Wang Song ◽  
Zhao Yunlin ◽  
Xu Zhenggang ◽  
Yang Guiyan ◽  
Huang Tian ◽  
...  
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Markov Model ◽  
Prediction Accuracy ◽  
Driving Mechanism ◽  
Economic Factors ◽  
Chain Model ◽  
The Impact ◽  
County Scale

AbstractUnderstanding and modeling of land use change is of great significance to environmental protection and land use planning. The cellular automata-Markov chain (CA-Markov) model is a powerful tool to predict the change of land use, and the prediction accuracy is limited by many factors. To explore the impact of land use and socio-economic factors on the prediction of CA-Markov model on county scale, this paper uses the CA-Markov model to simulate the land use of Anren County in 2016, based on the land use of 1996 and 2006. Then, the correlation between the land use, socio-economic data and the prediction accuracy was analyzed. The results show that Shannon’s evenness index and population density having an important impact on the accuracy of model predictions, negatively correlate with kappa coefficient. The research not only provides a reference for correct use of the model but also helps us to understand the driving mechanism of landscape changes.

scholarly journals The Impact of Dental Implant Length on Failure Rates: A Systematic Review and Meta-Analysis

Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 3972
Author(s):  
Maha Abdel-Halim ◽  
Dalia Issa ◽  
Bruno Ramos Chrcanovic
Keyword(s):  
Treatment Plan ◽  
Meta Analysis ◽  
Implant Failure ◽  
Failure Rates ◽  
Manual Search ◽  
Short Implants ◽  
The Many ◽  
The Impact ◽  
Implant Length

The present review aimed to evaluate the impact of implant length on failure rates between short (<10 mm) and long (≥10 mm) dental implants. An electronic search was undertaken in three databases, as well as a manual search of journals. Implant failure was the outcome evaluated. Meta-analysis was performed in addition to a meta-regression in order to verify how the risk ratio (RR) was associated with the follow-up time. The review included 353 publications. Altogether, there were 25,490 short and 159,435 long implants. Pairwise meta-analysis showed that short implants had a higher failure risk than long implants (RR 2.437, p < 0.001). There was a decrease in the probability of implant failure with longer implants when implants of different length groups were compared. A sensitivity analysis, which plotted together only studies with follow-up times of 7 years or less, resulted in an estimated increase of 0.6 in RR for every additional month of follow-up. In conclusion, short implants showed a 2.5 times higher risk of failure than long implants. Implant failure is multifactorial, and the implant length is only one of the many factors contributing to the loss of an implant. A good treatment plan and the patient’s general health should be taken into account when planning for an implant treatment.

scholarly journals Comprehensive Analytical Modelling of an Absolute pH Sensor

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5190
Author(s):  
Cristina Medina-Bailon ◽  
Naveen Kumar ◽  
Rakshita Pritam Singh Dhar ◽  
Ilina Todorova ◽  
Damien Lenoble ◽  
...  
Keyword(s):  
Silicon Dioxide ◽  
Numerical Experiments ◽  
Ph Sensor ◽  
Hafnium Dioxide ◽  
Matlab Code ◽  
Oxide Degradation ◽  
Depletion Width ◽  
Ion Activity ◽  
The Absolute ◽  
The Impact

In this work, we present a comprehensive analytical model and results for an absolute pH sensor. Our work aims to address critical scientific issues such as: (1) the impact of the oxide degradation (sensing interface deterioration) on the sensor’s performance and (2) how to achieve a measurement of the absolute ion activity. The methods described here are based on analytical equations which we have derived and implemented in MATLAB code to execute the numerical experiments. The main results of our work show that the depletion width of the sensors is strongly influenced by the pH and the variations of the same depletion width as a function of the pH is significantly smaller for hafnium dioxide in comparison to silicon dioxide. We propose a method to determine the absolute pH using a dual capacitance system, which can be mapped to unequivocally determine the acidity. We compare the impact of degradation in two materials: SiO2 and HfO2, and we illustrate the acidity determination with the functioning of a dual device with SiO2.

Fibroblast growth factor 21 (FGF-21) in obese children: no relationship to growth, IGF-1, and IGFBP-3

2016 ◽  
Vol 30 (2) ◽  
Author(s):  
Thomas Reinehr ◽  
Christian L. Roth ◽  
Joachim Woelfle
Keyword(s):  
Weight Loss ◽  
Growth Factor ◽  
Fibroblast Growth Factor ◽  
Critical Role ◽  
Fibroblast Growth Factor 21 ◽  
Fibroblast Growth ◽  
Obese Children ◽  
Pubertal Stage ◽  
The Impact ◽  
Igfbp 3

AbstractBackground:Fibroblast growth factor 21 (FGF-21) is a hepatic protein that plays a critical role in liver, adipose tissue, and bone metabolism. Animal models reported an increase of FGF-21 and associated growth disturbances in undernutrition. Therefore, we studied the impact of weight loss in obese children on growth, FGF-21, and insulin-like factor 1 (IGF-1) concentrations.Methods:We analyzed height, serum concentrations of FGF-21, IGF-1, IGFBP-3, leptin, and insulin at baseline and 1 year later in 30 obese children with substantial weight loss (reduction >0.5 BMI-SDS) and in 30 obese children of similar age, gender, and pubertal stage with stable BMI-SDS. All children participated in a 1-year lifestyle intervention. Height and IGF-1 was transformed to standard deviation score (SDS). Multiple linear regression analyses adjusted for age, gender, and pubertal stage were performed.Results:At baseline, height-SDS was significantly related to IGF-1-SDS (β-coefficient 0.68 95% confidence interval (95% CI)±0.49; p=0.008) and leptin (β-coefficient 0.042 95% CI±0.030; p=0.008), but not to FGF-21 or insulin. FGF-21 was not significantly associated with IGF-1 or IGFBP-3. In longitudinal analysis, changes of FGF-21 were not significantly related to changes of height, IGF-1-SDS or IGFBP-3. However, in the subgroup of 30 children with substantial BMI-SDS reduction, FGF-21, leptin, insulin, and HOMA decreased significantly.Conclusion:As there was no significant association between FGF-21 and growth or IGF-1 both in cross-sectional and longitudinal analyses, these findings do not support the hypothesis that FGF-21 is involved in growth of obese children. Further studies are necessary to understand the multiple alterations in the growth hormone (GH) axis in obese children.

scholarly journals Lack of Obvious Influence of PLLA Nanofibers on the Gene Expression of BMP-2 and VEGF during Growth and Differentiation of Human Mesenchymal Stem Cells

2009 ◽  
Vol 9 ◽  
pp. 313-319 ◽  
Author(s):  
Markus D. Schofer ◽  
S. Fuchs-Winkelmann ◽  
C. Wack ◽  
M. Rudisile ◽  
R. Dersch ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Factor ◽  
Time Course ◽  
Negative Impact ◽  
Fracture Repair ◽  
Bone Morphogenetic Protein 2 ◽  
Vegf Gene ◽  
Down Regulation ◽  
Artificial Graft ◽  
The Impact

Growth factors like bone morphogenetic protein 2 (BMP-2) and vascular endothelial growth factor (VEGF) play an important role in bone remodeling and fracture repair. Therefore, with respect to tissue engineering, an artificial graft should have no negative impact on the expression of these factors. In this context, the aim of this study was to analyze the impact of poly(L-lactic acid) (PLLA) nanofibers on VEGF and BMP-2 gene expression during the time course of human mesenchymal stem cell (hMSC) differentiation towards osteoblasts. PLLA matrices were seeded with hMSCs and cultivated over a period of 22 days under growth and osteoinductive conditions, and analyzed during the course of culture, with respect to gene expression of VEGF and BMP-2. Furthermore, BMP-2–enwoven PLLA nanofibers were used in order to elucidate whether initial down-regulation of growth factor expression could be compensated. Although there was a great interpatient variability with respect to the expression of VEGF and BMP-2, PLLA nanofibers tend to result in a down-regulation in BMP-2 expression during the early phase of cultivation. This effect was diminished in the case of VEGF gene expression. The initial down-regulation was overcome when BMP-2 was directly incorporated into the PLLA nanofibers by electrospinning. Furthermore, the incorporation of BMP-2 into the PLLA nanofibers resulted in an increase in VEGF gene expression. Summarized, the results indicate that the PLLA nanofibers have little effect on growth factor production. An enhancement in gene expression of BMP-2 and VEGF can be achieved by an incorporation of BMP-2 into the PLLA nanofibers.

Practical Optimization of Industrial Gravel Size in Gravel Packed Well

2011 ◽  
Vol 201-203 ◽  
pp. 383-387
Author(s):  
Jin Gen Deng ◽  
Yu Chen ◽  
Li Hua Wang ◽  
Wen Long Zhao ◽  
Ping Li
Keyword(s):  
Design Method ◽  
Control Measures ◽  
Control Effect ◽  
Gravel Layer ◽  
Gravel Size ◽  
Sand Control ◽  
Gravel Packing ◽  
Gravel Pack ◽  
The Impact ◽  
Computing Method

In the design of gravel packing sand control, the reasonable selection of gravel size is one of the keys to implementing sand control measures successfully. Aiming at the defects of commonly used methods of gravel size design and the characteristic that the gravel used in field operation is actually a mixture of gravel with multiple grain diameters, this paper builds a model of pore structure in gravel layer through researching the gravel pack structure caused by the gravel of two grain diameters mixed under actual packing conditions, calculates and analyzes the pore sizes in gravel layer. Ultimately, based on Saucier method, this paper presents a new gravel size optimization idea for gravel packing sand control with multiple grain diameters mixed, which agrees with the actual situation of industrial gravel, and gives the idea’s computing method. Considering the ideality of the model in this paper, the author has modified the computing method to make it more fit for the actual packing situation. This gravel size design method also gives consideration to the impact of formation sand uniformity on sand control effect, so it have the characteristics of good practicability, wide applicability and more accurate than other conventional methods.

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