8,038 research outputs found
In vitro regeneration of Basella alba L
Basella alba L. is a tropical vine used as a vegetable in some Asian and African countries. It has potential as a nontraditional crop for small family farms. A short day plant, it blooms during the fall, provided the temperatures are mild. In the southeastern U.S., the short days of fall are associated with subfreezing temperatures, and plants are killed before blooming. Attempts were made to regenerate the plant using tissue culture techniques. Several trials were conducted with different media, hormones, and explants. It was found that nodal segments on Gamborg medium regenerated shoots. Interaction studies of auxins and cytokinins indicated that its endogeneous auxin content might be high because callus proliferated in almost all treatments and roots initiated even when the medium was not supplemented with an auxin
Optical Photometry and Spectroscopy of the Suspected Cool Algol AV Delphini: Determination of the Physical Properties
We present new spectroscopic and BVRI photometric observations of the double-lined eclipsing binary AV Del ( period = 3:85 days) conducted over six observing seasons. A detailed radial velocity and light-curve analysis of the optical data shows the system to be most likely semidetached, with the less massive and cooler star filling its Roche lobe. The system is probably a member of the rare class of ‘‘cool Algol’’ systems, which are distinguished from the ‘‘classical’’ Algol systems in that the mass-gaining component is also a late-type star rather than a B- or A-type star. By combining the spectroscopic and photometric analyses, we derive accurate absolute masses for the components of M1 = 1.453 + 0.028 M and M2 = 0.705 + 0.014 M and radii of R1 = 2.632 + 0.030 R and R2 = 4.233 + 0.060 R, as well as effective temperatures of 6000 + 200 and 4275 + 150 K for the primary and secondary, respectively. There are no obvious signs of activity (spottedness) in the optical light curve of the binary
Risk of uterine rupture after the partographic \u27alert\u27 line is crossed--an additional dimension in the quest towards safe motherhood in labour following caesarean section
To determine if prolonged active phase of labour is associated with increased risk of uterine scar rupture in labour following previous lower segment caesarean section, a retrospective cohort study (1988-91) was done to analyse active phase partographs of 236 patients undergoing trial of labour following caesarean section, 7 (3%) of whom had scar rupture. After onset of active phase (3 cm cervical dilatation), a 1 cm/h line was used to indicate alert . A zonal partogram was developed by dividing the active phase partographs into 5 time zones: A (area to the left of alert line), B (0-1 h after alert line), C (1-2 h after alert line), D (2-3 h after alert line) and EF (\u3e 3 h after alert line). The relative risk of uterine scar rupture was calculated for different partographic time zones. The relative risk of uterine scar rupture was 10.5 (95% confidence interval 1.3-85.5, p = 0.01) at 1 hour after crossing the alert line; 8.0 (95% confidence interval 1.6-40.3, p = 0.009) at 2 hours after crossing the alert line; and 7.0 (95% confidence interval 1.6-29, p = 0.02) at 3 hours after crossing the alert line. In women undergoing trial of labour following caesarean section, prolonged active phase of labour is associated with increased risk of uterine rupture. A zonal partogram may be helpful in assessing this risk in actively labouring women who cross the partographic alert line
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RMP Evaluations, Course Easiness, and Grades: Are they Related?
This paper investigates the relationship between the student evaluations of the instructors at the RateMyProfessors.com (RMP) website and the average grades awarded by those instructors. As of Spring 2012, the RMP site included evaluations of 538 full-and part-time instructors at the College of Staten Island (CSI). We selected the evaluations of the 419 instructors who taught at CSI for at least two semesters from Fall 2009 to Spring 2011 and had at least ten evaluations. This research indicates that there is a strong correlation between RMP’s overall evaluation and easiness scores. However, the perceived easiness of an instructor/course does not always result in higher grades for students. Furthermore, we found that the instructors who received high overall evaluation and easiness scores (4.0 to 5.0) at the RMP site do not necessarily award high grades. This is a very important finding as it disputes the argument that instructors receive high evaluations because they are easy or award high grades. On the other hand, instructors of the courses that are perceived to be difficult (RMP easiness score of 3.0 or less) are likely to be tough graders. However, instructors who received moderate overall evaluation and easiness scores (between 3.0 and 4.0) the RMP site had a high correlation between these scores and average grade awarded by those instructors. Finally, our research shows that the instructors in non-STEM disciplines award higher grades than the instructors in STEM disciplines. Non-STEM instructors also received higher overall evaluations than their STEM counterparts and non-STEM courses were perceived easier by the students than STEM courses. Accessed 3,007 times on https://pareonline.net from October 12, 2015 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right
Prediction of Heart Disease using Machine Learning Algorithms: A Survey
According to recent survey by WHO organisation 17.5 million people dead each year. It will increase to 75 million in the year 2030[1].Medical professionals working in the field of heart disease have their own limitation, they can predict chance of heart attack up to 67% accuracy[2], with the current epidemic scenario doctors need a support system for more accurate prediction of heart disease. Machine learning algorithm and deep learning opens new door opportunities for precise predication of heart attack. Paper provideslot information about state of art methods in Machine learning and deep learning. An analytical comparison has been provided to help new researches’ working in this field
Source code embedded (SCEM) security framework
Security in the Software Development Life Cycle (SDLC) has become imperative due to the variety of threats posed during and after system design. In this paper we have studied the security in system design in general and software development in particular, and have proposed strategies for integration of security in the SDLC. The paper highlights the needs of embedding security right from the earlier processes in the SDLC because patches and controls after the software delivery are more expensive to fix. We propose Source Code EMbedded (SCEM) security framework to improve the design of security policies and standards for the software development process to ensure the security and reliability in government departments such as taxation, auditing, national security, social security, and immigration. It is also envisaged that the implementation of SCEM security framework will ensure commercial and public trust in the software development process within Australia and worldwide, saving enormous redevelopment costs
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