354 research outputs found
Salycilic Acid Induces Exudation of Crocin and Phenolics in Saffron Suspension-Cultured Cells
No full textAbstract: The production of crocin, an uncommon and valuable apocarotenoid with strong biological activity, was obtained in a cell suspension culture of saffron (Crocus sativus L.) established from style-derived calli to obtain an in-vitro system for metabolite production. Salycilic acid (SA) was used at different concentrations to elicit metabolite production, and its effect was analyzed after a 4 days of treatment. HPLC-DAD analysis was used for total crocin quantification while the Folin-Ciocâlteu method was applied for phenolic compounds (PC) content. Interestingly, despite cell growth inhibition, a considerable exudation was observed when the highest SA concentration was applied, leading to a 7-fold enhanced production of crocin and a 4-fold increase of phenolics compared to mock cells. The maximum antioxidant activity of cell extracts was evidenced after SA 0.1 mM elicitation. Water-soluble extracts of saffron cells at concentrations of 1, 0.5, and 0.1 μg mL−1 showed significant inhibitory effects on MDA-MB-231 cancer cell viability. The heterologous vacuolar markers RFP-SYP51, GFPgl133Chi, and AleuRFP, were transiently expressed in protoplasts derived from the saffron cell suspensions, revealing that SA application caused a rapid stress effect, leading to cell death. Cell suspension elicitation with SA on the 7th day of the cell growth cycle and 24 h harvest time was optimized to exploit these cells for the highest increase of metabolite production in saffron cells
A COMMON FIXED POINT FOR WEAK φ-CONTRACTIONS ON <i>b</i>-METRIC SPACES
No full textaydi, hassen/0000-0003-4606-7211; Moradi, Sirous/0000-0002-8640-7252; , Hassen/0000-0003-3896-3809In this paper, we give a common fixed point result, for single-valued and multi-valued mappings satisfying a weak phi-contraction in b-metric spaces. Presented theorems extend, generalize and improve some existing results in the literature. Some examples are also given.Romanian National Authority for Scientific Research, CNCS UEFISCDI [PN-II-ID-PCE-2011-3-0094]The second author is partially supported by a grant of the Romanian National Authority for Scientific Research, CNCS UEFISCDI, project number PN-II-ID-PCE-2011-3-0094.Science Citation Index Expande
A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography
No full textAssessment of cultural heritage assets is now extremely important all around the world. Non-destructive inspection is essential for preserving the integrity of artworks while avoiding the loss of any precious materials that make them up. The use of Infrared Thermography is an interesting concept since surface and subsurface faults can be discovered by utilizing the 3D diffusion inside the object caused by external heat. The primary goal of this research is to detect defects in artworks, which is one of the most important tasks in the restoration of mural paintings. To this end, machine learning and deep learning techniques are effective tools that should be employed properly in accordance with the experiment’s nature and the collected data. Considering both the temporal and spatial perspectives of step-heating thermography, a spatiotemporal deep neural network is developed for defect identification in a mock-up reproducing an artwork. The results are then compared with those of other conventional algorithms, demonstrating that the proposed approach outperforms the others
Design and Development of E-learning Content Based on Gagne’s Model of Instructional Design and its Impact on Motivation and Academic Achievement
No full textIntroduction: The purpose of this study was to design and develop e-learning content for medical microbiology course based on Gagne’s model of instructional design and assess its impact on motivation and academic achievement among students of Aja University of Medical Sciences.
Methods: This study was a quasi-experimental research with a pretest-posttest control group design. The population consisted of all male students of Aja University of Medical Sciences in 2015-16 academic years, of whom 60 students were selected by convenience sampling and randomly divided into control and experimental groups. Data were collected using a researcher-made academic achievement test and Harter’s standard questionnaire. The experimental group received e-Learning content for six 60-minute sessions and the control group received lectures. The data were analyzed by means of descriptive statistics and ANCOVA.
Results: The results of ANCOVA demonstrates that the use of Gagne's model of instructional design in designing and producing electronic and educational content based on this method is effective on academic achievement of students (p <0.01). Furthermore, the univariate analysis of variance for analyzing motivation showed an increase in academic motivation of the experimental group following the intervention (p<0.01).
Conclusion: A pivotal issue in e-learning is paying attention to structure and quality in developing educational contents according to principles of instructional design. Given the improvement of motivation and academic achievement through implementation of e-content based on Gagne’s model of instructional design, it is suggested that organizations and universities administering e-learning pay due attention to instructional design and application of scientific approaches
A Fountain of Sasanian Age from Ardashir Khwarrah, with a note on the Archaeometric Investigations by Maria Letizia Amadori
No full textThe author describes a peculiar stone object preserved in the stores of Firuzabad UNESCO site base, and tries to interpet and date it as a fountain of the Sasanian period
Erratum to: Cold Atmosphere Plasma Modification on Beta-Carotene-Loaded Nanofibers to Enhance Osteogenic Differentiation (Fibers and Polymers, (2022), 23, 1, (18-27), 10.1007/s12221-021-0033-y)
No full text2981The article Cold Atmosphere Plasma Modification on Beta-Carotene-Loaded Nanofibers to Enhance Osteogenic Differentiation, written by Yasamin Moradi, Seyed Alireza Atyabi, Ali Ghiassadin, Hadi Bakhshi, Shiva Irani, Seyed Mohammad Atyabi, and Neda Dadgar, was mistakenly originally published without open access. After publication in Vol.23, No.1, page 18–27 this was corrected and the article was made an open access publication. Therefore, the copyright of the article has been changed to and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License (https://doi.org/10.1007/s12221-021-0033-y), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The original article has been corrected.231
Automated detection of prostate cancer using wavelet transform features of ultrasound RF time series
No full textThe aim of this research was to investigate the performance of wavelet transform based features of ultrasound radiofrequency (RF) time series for automated detection of prostate cancer tumors in transrectal ultrasound images. Sequential frames of RF echo signals from 35 extracted prostate specimens were recorded in parallel planes, while the ultrasound probe and the tissue were fixed in position in each imaging plane. The sequence of RF echo signal samples corresponding to a particular spot in tissue imaging plane constitutes one RF time series. Each region of interest (ROI) of ultrasound image was represented by three groups of features of its time series, namely, wavelet, spectral and fractal features. Wavelet transform approximation and detail sequences of each ROI were averaged and used as wavelet features. The average value of the normalized spectrum in four quarters of the frequency range along with the intercept and slope of a regression line fitted to the values of the spectrum versus normalized frequency plot formed six spectral features. Fractal dimension (FD) of the RF time series were computed based on the Higuchi's approach. A support vector machine (SVM) classifier was used to classify the ROIs. The results indicate that combining wavelet coefficient based features with previously proposed spectral and fractal features of RF time series data would increase the area under ROC curve from 93.1% to 95.0%, respectively. Furthermore, the accuracy, sensitivity, and specificity increases to 91.7%, 86.6%, and 94.7%, from 85.7%, 85.2%, and 86.1%, respectively, using only spectral and fractal features. [ABSTRACT FROM AUTHOR]Peer reviewedFinal article publishe
The Relation between Treated Maternal Urinary Tract Infection and Adverse Maternal, Prenatal Outcomes in Pregnant Women of Ardabil, Iran
No full textBackground and Objective: Urinary tract infection is one of the most common bacterial infections during pregnancy and has also been implicated as a risk factor for adverse maternal and prenatal outcomes. The aim of our study was to determine the relation between maternal urinary tract infection and adverse maternal, prenatal outcomes in pregnant women of Ardabil, Iran.
Material and Methods: This retrospective-case-control study was conducted on prenatal file records of pregnant women in Ardabil (2011). The pregnant women who had a positive urine culture in their prenatal files (N= 211) were considered as a case group and 232 ones without urinary tract infection as a control. Using a research- made questionnaire, the data related to present pregnancy and prenatal information was collected and analyzed by KrusKal Wallis, Chi- Square and Fisher statistical tests.
Results: Maternal age of under 25 (%61.6 vs. 56.5), body mass index of more than 30 (%18.3 vs. 15.6), primigravida (%55 vs. 48.8), hypertension (%2.4 vs. 1.3), hyperemesis Gravidarum (%14.8 vs. 12.6), frequency and dysuria (%1.9 vs. 0.9), low birth weight (%95.4 vs. 93.2), congenital malformation (%3.5 vs. 1.8), artificial milk feeding (%6.5 vs. 2.7), neonatal death (%0.9 vs. 0.0) are higher in urinary infection group, however the differences are not statistically significant. Other maternal and prenatal adverse outcomes such as diabetes, pre-eclampsia , hemoglobin level, prematurity, abortion and stillbirth have not significant relation with urinary infection.
Conclusion: Because of low level of adverse maternal or prenatal outcomes reported in our study, we conclude that screening and treatment of urinary tract infection in Ardabil health service is appropriate; therefore, no change is needed for present screening or treatment processes
Open data portals as part of the open data ecosystem?: Lessons learned from geoportal research
No full textMany countries and also cities have their own open data portal, which provide geographic data that can be used even by citizens. One of the current challenges is to satisfy user needs to ensure that the data that is provided through the portal isactually used. This paper provides insights in the findability of datasets through of a special kind of portal: the geoportal. It presents the main findings of research accomplished on the findability, attainability and usability of geoportals through anassessment of the transaction costs involved.OLD Geo-information and Land Developmen
Developing health indicators for composite structures based on a two-stage semi-supervised machine learning model using acoustic emission data
No full textComposite structures are highly valued for their strength-to-weight ratio, durability, and versatility, making them ideal for a variety of applications, including aerospace, automotive, and infrastructure. However, potential damage scenarios like impact, fatigue, and corrosion can lead to premature failure and pose a threat to safety. This highlights the importance of monitoring composite structures through structural health monitoring (SHM) and prognostics and health management (PHM) to ensure their safe and reliable operation. SHM provides information on the current state of the structure, while PHM predicts its future behavior and determines necessary maintenance. Health indicators (HIs) play a crucial role in both SHM and PHM, providing information on structural health and behavior, but accurate determination of these indicators can be challenging due to the complexity of material behavior and multiple sources of damage in composite structures. In the present work, a model containing a developed adaptive standardization, a dimension reduction sub-model, a time-independent sub-model, and a time-dependent sub-model is introduced to address this challenge. First, the raw data collected by the acoustic emission technique monitoring composite structures under fatigue loading is processed to provide plenty of statistical features. The extracted features are adaptively standardized according to the available data until the current time. Then, the principal component analysis algorithm is employed to reconstruct a few yet highly informative features out of those statistical features. An artificial neural network is used to regress the principal components to the HI that meets the prognostic criteria. Finally, the last sub-model takes into account the time dependency of HI values during fatigue loading. In comparison to other models, the results show superior performance.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Structural Integrity & Composite
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