A statistical analysis on the relationship between thunderstorms and the sporadic E Layer over Rome

2013 ◽  
Vol 334 (9) ◽  
pp. 968-971 ◽  
Author(s):  
V. Barta ◽  
C. Scotto ◽  
M. Pietrella ◽  
V. Sgrigna ◽  
L. Conti ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Sporadic E Layer ◽  
Sporadic E ◽  
The Relationship

A statistical analysis of sporadic E layer occurrence in the midlatitude China region

2017 ◽  
Vol 122 (3) ◽  
pp. 3617-3631 ◽  
Author(s):  
Chen Zhou ◽  
Qiong Tang ◽  
Xiaoxiao Song ◽  
Haiyin Qing ◽  
Yi Liu ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Sporadic E Layer ◽  
Sporadic E ◽  
China Region

Statistical analysis and modelling of sporadic E layer over Europe

2019 ◽  
Vol 64 (6) ◽  
pp. 1243-1255 ◽  
Author(s):  
N.Y. Zaalov ◽  
E.V. Moskaleva
Keyword(s):  
Statistical Analysis ◽  
Sporadic E Layer ◽  
Sporadic E

scholarly journals BMI-1 Expression Heterogeneity in Endometriosis-Related and Non-Endometriotic Ovarian Carcinoma

2021 ◽  
Vol 22 (11) ◽  
pp. 6082
Author(s):  
Ludmila Lozneanu ◽  
Raluca Anca Balan ◽  
Ioana Păvăleanu ◽  
Simona Eliza Giuşcă ◽  
Irina-Draga Căruntu ◽  
...  
Keyword(s):  
Stem Cells ◽  
Statistical Analysis ◽  
Ovarian Carcinoma ◽  
Clinicopathological Characteristics ◽  
Cell Phenotype ◽  
Epithelial Tumor ◽  
Normal Organ ◽  
Ovarian Carcinogenesis ◽  
Cellular Signaling Pathway ◽  
The Relationship

BMI-1 is a key component of stem cells, which are essential for normal organ development and cell phenotype maintenance. BMI-1 expression is deregulated in cancer, resulting in the alteration of chromatin and gene transcription repression. The cellular signaling pathway that governs BMI-1 action in the ovarian carcinogenesis sequences is incompletely deciphered. In this study, we set out to analyze the immunohistochemical (IHC) BMI-1 expression in two different groups: endometriosis-related ovarian carcinoma (EOC) and non-endometriotic ovarian carcinoma (NEOC), aiming to identify the differences in its tissue profile. Methods: BMI-1 IHC expression has been individually quantified in epithelial and in stromal components by using adapted scores systems. Statistical analysis was performed to analyze the relationship between BMI-1 epithelial and stromal profile in each group and between groups and its correlation with classical clinicopathological characteristics. Results: BMI-1 expression in epithelial tumor cells was mostly low or negative in the EOC group, and predominantly positive in the NEOC group. Moreover, the stromal BMI-1 expression was variable in the EOC group, whereas in the NEOC group, stromal BMI-1 expression was mainly strong. We noted statistically significant differences between the epithelial and stromal BMI-1 profiles in each group and between the two ovarian carcinoma (OC) groups. Conclusions: Our study provides solid evidence for a different BMI-1 expression in EOC and NEOC, corresponding to the differences in their etiopathogeny. The reported differences in the BMI-1 expression of EOC and NEOC need to be further validated in a larger and homogenous cohort of study.

scholarly journals Noni fruit’s water spot appearance on the second day of harvest: a trade-off between resistance and energy

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Tian Wu ◽  
Danyan Hu ◽  
Qingfen Wang
Keyword(s):  
Statistical Analysis ◽  
Molecular Level ◽  
Morinda Citrifolia ◽  
Transcriptome Data ◽  
Trade Off ◽  
Kegg Pathways ◽  
Available Energy ◽  
Climacteric Fruit ◽  
The Relationship ◽  
Insight Into

Abstract Background Noni (Morinda citrifolia Linn.) is a tropical tree that bears climacteric fruit. Previous observations and research have shown that the second day (2 d) after harvest is the most important demarcation point when the fruit has the same appearance as the freshly picked fruit (0 d); however, they are beginning to become water spot appearance. We performed a conjoint analysis of metabolome and transcriptome data for noni fruit of 0 d and 2 d to reveal what happened to the fruit at the molecular level. Genes and metabolites were annotated to KEGG pathways and the co-annotated KEGG pathways were used as a statistical analysis. Results We found 25 pathways that were significantly altered at both metabolic and transcriptional levels, including a total of 285 differentially expressed genes (DEGs) and 11 differential metabolites through an integrative analysis of transcriptomics and metabolomics. The energy metabolism and pathways originating from phenylalanine were disturbed the most. The upregulated resistance metabolites and genes implied the increase of resistance and energy consumption in the postharvest noni fruit. Most genes involved in glycolysis were downregulated, further limiting the available energy. This lack of energy led noni fruit to water spot appearance, a prelude to softening. The metabolites and genes related to the resistance and energy interacted and restricted each other to keep noni fruit seemingly hard within two days after harvest, but actually the softening was already unstoppable. Conclusions This study provides a new insight into the relationship between the metabolites and genes of noni fruit, as well as a foundation for further clarification of the post-ripening mechanism in noni fruit.

scholarly journals Equatorial E Region Electric Fields and Sporadic E Layer Responses to the Recovery Phase of the November 2004 Geomagnetic Storm

2017 ◽  
Vol 122 (12) ◽  
pp. 12,517-12,533 ◽  
Author(s):  
J. Moro ◽  
L. C. A. Resende ◽  
C. M. Denardini ◽  
J. Xu ◽  
I. S. Batista ◽  
...  
Keyword(s):  
Geomagnetic Storm ◽  
Electric Fields ◽  
Recovery Phase ◽  
E Region ◽  
Sporadic E Layer ◽  
Sporadic E

Civil engineers’ personal values/demographics linkage in project team building

2017 ◽  
Vol 24 (6) ◽  
pp. 1337-1349 ◽  
Author(s):  
Atilla Damci ◽  
David Arditi ◽  
Gul Polat
Keyword(s):  
Statistical Analysis ◽  
Work Experience ◽  
Personal Values ◽  
Team Building ◽  
Project Teams ◽  
Team Leaders ◽  
Content Type ◽  
First Time ◽  
The Relationship ◽  
Civil Engineers

Purpose The purpose of this paper is to explore the relationship between civil engineers’ demographics (e.g. age, marital status, education, work experience) and their personal values. The objective was to predict civil engineers’ personal values based on their demographics. Design/methodology/approach A questionnaire survey was administered to civil engineers to collect data on their demographics and their personal values. Statistical analysis was performed to verify whether a significant statistical relationship exists between civil engineers’ demographics and their personal values. Findings The most important and the least important personal values were identified for civil engineers. Statistical analysis indicated that civil engineers’ values do vary based on their demographics. Research limitations/implications The results of this study cannot be generalized, because individuals’ personal values and demographics are, by definition, local. Location and culture may affect the personal values of civil engineers. Practical implications Team leaders normally have access to information about the demographics of the engineers they employ; based on the results of this study, they should be able to predict their personal values, and to make more informed decisions when appointing them to particular positions on project teams. Originality/value The research presented in this paper, establishes for the first time, that a linkage exists between civil engineers’ personal values and their demographics, and makes it easier for team leaders to make assignment decisions.

INSTAGRAM SEBAGAI MEDIA EDUKASI PENINGKATAN PENGETAHUAN KESEHATAN GIGI DAN MULUT

2021 ◽  
Vol 8 (2) ◽  
pp. 51-56
Author(s):  
Ratna Sari Dyah ◽  
Lies Elina
Keyword(s):  
Comparative Analysis ◽  
Statistical Analysis ◽  
Dental Health ◽  
Sampling Technique ◽  
Online Media ◽  
Hygiene Behavior ◽  
Increasing Knowledge ◽  
Quota Sampling ◽  
The Relationship ◽  
Oral Hygiene Behavior

Knowledge of how to maintain proper dental health will greatly affect the incidence of dental caries, brushing and rinsing teeth - gargling is one of the behaviors to maintain oral hygiene. behavior based on correct knowledge will last longer than behavior that is not based on knowledge, an effort to increase knowledge is through health education. Online media is one of the educational media to increase knowledge of dental and oral health. The type of research in this study is a comparative comparative analysis or "causal-comparative". Quota sampling technique sampling, the research location was conducted in SMA N 3 Bandar Lampung ..as many as 100 people. The research variable was the online media instagram in increasing knowledge of caries. Statistical analysis used the T-test to see the relationship between Instagram in increasing knowledge. The results showed instagram can that there was a role for online media education in increasing knowledge of cavities.

Risks of Using Statistical Analysis Tools in Project Management Environments

2020 ◽  
Vol 7 (2) ◽  
pp. 1-19
Author(s):  
Brian J. Galli
Keyword(s):  
Risk Management ◽  
Project Management ◽  
Statistical Analysis ◽  
Common Type ◽  
Systematic Search ◽  
Statistical Tools ◽  
Early Stages ◽  
Analysis Tools ◽  
The Common ◽  
The Relationship

The purpose of this study is to examine the risks of using statistical tools in a project basis. A systematic search of certain academic databases has been conducted for this study. Statistical tools could be used in a project, and they should be properly planned and designed. Statistical tools include major activities, such as collecting and analyzing data, providing meaningful interpretation, and reporting findings. When dealing with statistical tools, there are several risks that may exist and impact the project either positively or negatively. This study covers a brief outline of the risk management, statistical tools, and the relationship between the two concepts. Finally, a discussion of the common type of risks that are initiated by using statistical analysis tools are provided, which could be planned, identified, and analyzed in the early stages of the project.

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