scholarly journals Identification of highly transformable wheat genotypes for mass production of fertile transgenic plants

Genome ◽  
2002 ◽  
Vol 45 (2) ◽  
pp. 421-430 ◽  
Author(s):  
A Pellegrineschi ◽  
L M Noguera ◽  
B Skovmand ◽  
R M Brito ◽  
L Velazquez ◽  
...  
Keyword(s):  
Transformation Efficiency ◽  
Transformation Process ◽  
Plant Genotype ◽  
Donor Plant ◽  
Genotype Effect ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Selection Medium ◽  
Callus Regeneration ◽  
Transformation Systems

The efficiency of wheat biolistic transformation systems strongly depends on the bombardment parameters, the condition of the donor plant, and the plant genotype chosen for the transformation process. This paper analyzes the transformation efficiency of the 129 wheat sister lines generically called 'Bobwhite', originally obtained from the cross 'Aurora'//'Kalyan'/'Bluebird 3'/'Woodpecker'. A number of factors influencing the transformation were examined, such as the ability to produce embryogenic callus, regeneration in selection medium, and overall transformation performance. Of the 129 genotypes evaluated, eight demonstrated transformation efficiencies above 60% (60 independent transgenic events per 100 immature embryos bombarded). Among the eight genotypes identified, we studied agronomic characteristics such as earliness to identify the most adaptable line(s) for different lab conditions. 'Bobwhite' SH 98 26 was identified as a super-transformable wheat line.Key words: wheat transformation, 'Bobwhite', genotype effect.

scholarly journals Optimizing Transformation Frequency of Cryptococcus neoformans and Cryptococcus gattii Using Agrobacterium tumefaciens

2021 ◽  
Vol 7 (7) ◽  
pp. 520
Author(s):  
Jianmin Fu ◽  
Nohelli E. Brockman ◽  
Brian L. Wickes
Keyword(s):  
Agrobacterium Tumefaciens ◽  
Yeast Cell ◽  
Transformation Efficiency ◽  
Transformation Frequency ◽  
Yeast Cells ◽  
Agar Concentration ◽  
Genetic Tool ◽  
Number Of Factors ◽  
Cryptococcus Spp ◽  
Transformation Systems

The transformation of Cryptococcus spp. by Agrobacterium tumefaciens has proven to be a useful genetic tool. A number of factors affect transformation frequency. These factors include acetosyringone concentration, bacterial cell to yeast cell ratio, cell wall damage, and agar concentration. Agar concentration was found to have a significant effect on the transformant number as transformants increased with agar concentration across all four serotypes. When infection time points were tested, higher agar concentrations were found to result in an earlier transfer of the Ti-plasmid to the yeast cell, with the earliest transformant appearing two h after A. tumefaciens contact with yeast cells. These results demonstrate that A. tumefaciens transformation efficiency can be affected by a variety of factors and continued investigation of these factors can lead to improvements in specific A. tumefaciens/fungus transformation systems.

Stock Market Prediction using Data Mining Techniques

2020 ◽  
pp. 310-313
Author(s):  
Karunesh Makker ◽  
Prince Patel ◽  
Hrishikesh Roy ◽  
Sonali Borse
Keyword(s):  
Neural Network ◽  
Stock Market ◽  
Prediction Model ◽  
Efficient Market Hypothesis ◽  
Deterministic System ◽  
Vast Number ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Using Data ◽  
Robust Prediction

Stock market is a very volatile in-deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding Technical indicators will guide the investor to minimize the risk and reap better returns.

scholarly journals SYSTEMATIC SUPPORT FOR THE DEVELOPMENT OF THE PEDAGOGICAL TEAM OF THE COLLEGE

2021 ◽  
pp. 45-52
Author(s):  
I. Bredikhina
Keyword(s):  
Educational Institution ◽  
Team Development ◽  
Clear Understanding ◽  
Team Members ◽  
Stage Of Development ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Successful Work ◽  
College Staff ◽  
The Impact

The article states that in order to create a competitive educational institution, management needs to use team management technologies. The research considers the issue of creating systematic support for pedagogical teams, namely assessment and analysis of a number of factors influencing the successful work of the pedagogical team and the formation of systematic support for team development using retrospective techniques and team adjustments. According to the results of the research, which is based on the Michigan model of leadership, the existing difficulties in the functioning of college teams were analyzed. The survey identified that at this stage of development, not all members of the college staff teams have a clear understanding of the overall goal (86.9 %) and the impact of teamwork on the overall result (78.2 %). Their unequal contribution to achieving the goal was also noted (73.9 %). The survey indicates that not all teams have a combination of skills at the highest level, and team members who have certain skills are not always interested in helping colleagues (82.6 %). Teams are quite high spirited and motivated even in difficult periods (82.6 %), the teams hold constructive discussions about misunderstandings and problems, regularly find new opportunities to find information and solve complex problems, appreciate the achievements of colleagues (86.9 %). Thus, it turned out that team leaders motivate not all team members to successfully implement projects (78.2 %), but provide management and prompt feedback, consult with team members to remove obstacles and difficulties in the work and ensure team progress (86.9 %). Given the identified weak spots of the pedagogical teams of the college and the factors influencing their work, systematic support, which consists in the formation of psychological security, constant analysis of team development and retrospectives, swell as models of adjustment for team development to improve their efficiency were created.

scholarly journals Effect of Gold Nanoparticles Size Capped with Surfactant on the Transformation of Plasmid into Escherichia coli Bacteria

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Amr D ◽  
◽  
Attia N ◽  
Seufi A ◽  
Galal A ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Gold Nanoparticles ◽  
Heat Shock ◽  
Transformation Efficiency ◽  
Transformation Process ◽  
Bacterial Cells ◽  
Bacterial Transformation ◽  
Foreign Genes ◽  
Escherichia Coli Bacteria ◽  
Convenient Technique

Bacterial transformation has great importance in molecular biology, as it is used for introduction of foreign genes into bacterial cells either chemical or physical ways. Using calcium chloride to prepare competent cells and heat shock is the most widely used method for bacterial transformation. This method is an efficient and convenient technique but it has in some extent low transformation efficiency. Here we report the use of nanoparticles that significantly improve the transformation efficiency up to 10 times higher than the standard heat shock method by the assistance of (˜ 15, 25 nm) SDS capped gold nanoparticles in the transformation process that leads to the formation of temporary nano-channels across the bacterial cell wall to deliver plasmids into cells. Transformation of bacteria with plasmid was examined using Β-galactosidase assay.

Exploring the Factors Influencing Acceptance of Mobile Phone

2018 ◽  
pp. 156-179
Author(s):  
Renatus Michael Mushi
Keyword(s):  
Mobile Phone ◽  
Conceptual Model ◽  
Mobile Phones ◽  
Key Factors ◽  
Mobile Money ◽  
Mobile Phone Technology ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Perceived Values ◽  
Usage Context

This chapter describes how the adoption and usage of technologies is influenced by a number of factors. Such factors tend to affect the perception of people to accept or reject a technology in their usage context. Mobile phone technology has gained popularity as a dependable tool in SMEs. In Tanzania, for example, it is used to accomplish activities such as marketing, communication and mobile money transactions. This chapter highlights the key factors which influence the acceptance of mobile phones as they are used by individual peoples in the SMEs. The conceptual model shows that TAM can be extended by factors such as perceived values in explaining the acceptance of mobile phone technology in Tanzanian SMEs.

The Margin of Appreciation

2020 ◽  
pp. 67-96
Author(s):  
Jan Zglinski
Keyword(s):  
Statistical Analysis ◽  
Theory And Practice ◽  
European Court Of Justice ◽  
Free Movement ◽  
Domestic Institutions ◽  
Factors Influencing ◽  
Court Of Justice ◽  
European Court ◽  
Number Of Factors ◽  
Margin Of Appreciation

This chapter examines the application of the margin of appreciation in free movement cases. It identifies the doctrine’s legal scope and investigates the scenarios in which the European Court of Justice defers to national authorities. A statistical analysis suggests that there is a significant gap between theory and practice, with only a small number of factors influencing the way in which the margin of appreciation is used. The results show how much regulatory autonomy Member States retain in free movement law. They also expose which concerns the Court prioritizes in its jurisprudence and which decisions it feels safe, or forced, to delegate to domestic institutions.

scholarly journals Building a Persuasive Virtual Dietitian

Informatics ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 27
Author(s):  
Luca Anselma ◽  
Alessandro Mazzei
Keyword(s):  
Data Interpretation ◽  
Perceived Usefulness ◽  
Language Generation ◽  
Content Selection ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Persuasive Power ◽  
Diet Management ◽  
Selection For ◽  
Numeric Data

This paper describes the Multimedia Application for Diet Management (MADiMan), a system that supports users in managing their diets while admitting diet transgressions. MADiMan consists of a numerical reasoner that takes into account users’ dietary constraints and automatically adapts the users’ diet, and of a natural language generation (NLG) system that automatically creates textual messages for explaining the results provided by the reasoner with the aim of persuading users to stick to a healthy diet. In the first part of the paper, we introduce the MADiMan system and, in particular, the basic mechanisms related to reasoning, data interpretation and content selection for a numeric data-to-text NLG system. We also discuss a number of factors influencing the design of the textual messages produced. In particular, we describe in detail the design of the sentence-aggregation procedure, which determines the compactness of the final message by applying two aggregation strategies. In the second part of the paper, we present the app that we developed, CheckYourMeal!, and the results of two human-based quantitative evaluations of the NLG module conducted using CheckYourMeal! in a simulation. The first evaluation, conducted with twenty users, ascertained both the perceived usefulness of graphics/text and the appeal, easiness and persuasiveness of the textual messages. The second evaluation, conducted with thirty-nine users, ascertained their persuasive power. The evaluations were based on the analysis of questionnaires and of logged data of users’ behaviour. Both evaluations showed significant results.

scholarly journals Understanding Why Clinicians Answer or Ignore Clinical Decision Support Prompts

2012 ◽  
Vol 03 (03) ◽  
pp. 309-317 ◽  
Author(s):  
V. Anand ◽  
S. M. Downs ◽  
A.E. Carroll
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Health Improvement ◽  
Key Factors ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Computer Automation ◽  
Computer Decision Support

Summary Introduction: The identification of key factors influencing responses to prompts and reminders within a computer decision support system (CDSS) has not been widely studied. The aim of this study was to evaluate why clinicians routinely answer certain prompts while others are ignored. Methods: We utilized data collected from a CDSS developed by our research group – the Child Health Improvement through Computer Automation (CHICA) system. The main outcome of interest was whether a clinician responded to a prompt. Results: This study found that, as expected, some clinics and physicians were more likely to address prompts than others. However, we also found clinicians are more likely to address prompts for younger patients and when the prompts address more serious issues. The most striking finding was that the position of a prompt was a significant predictor of the likelihood of the prompt being addressed, even after controlling for other factors. Prompts at the top of the page were significantly more likely to be answered than the ones on the bottom. Conclusions: This study detailed a number of factors that are associated with physicians following clinical decision support prompts. This information could be instrumental in designing better interventions and more successful clinical decision support systems in the future.

scholarly journals Factors Influencing Prescribing Decisions of Physicians: A Review

1970 ◽  
Vol 28 (6) ◽  
Author(s):  
Majid Davari ◽  
Elahe Khorasani ◽  
Bereket Molla Tigabu
Keyword(s):  
Negative Impact ◽  
Healthcare Spending ◽  
Practice Variation ◽  
Personal Attributes ◽  
Factors Affecting ◽  
Prescribing Behavior ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Pharmaceutical Industries ◽  
Promotion Strategies

BACKGROUND: The pharmaceutical bill is increasing at an alarming rate. The physician practice variation has a pronounced effect on healthcare spending. A number of factors can influence the prescribing behavior of physicians. The aim of this review was to identify the factors affecting the prescribing decision of physicians.METHODS: Electronic databases including Scopus, PubMed/MEDLINE CENTRAL, Cochrane Libraries and Google scholar were searched systematically for literatures on factors influencing prescribing decisions of physicians from 2000 to 2016. There was no restriction on the study designs.RESULTS: Thirty-three studies met the inclusion criteria from 1122 search results. A total of 33 factors were identified. The most frequent factors were patients’ clinical condition, pharmaceutical industries, physician attributes, patient preference and cost of medicine.CONCLUSION: Physicians’ personal attributes, cost of the medicine and pharmaceutical industries’ marketing and promotion strategies were mostly mentioned to influence prescribing decision. The identified factors showed that prescribing is not only geared for patient benefit, but also towards personal interest. The use of valid and reliable practice guidelines could reduce the negative impact of wide ranges of factors and promote the rational prescribing effectively. 

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