scholarly journals An Effective Workflow for Differentiating the Same Genus Herbs of Chrysanthemum morifolium Flower and Chrysanthemum Indicum Flower

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiao He ◽  
Qian Zhang ◽  
Cuiying Ma ◽  
Gabriel I. Giancaspro ◽  
Kaishun Bi ◽  
...  
Keyword(s):  
Binary Logistic Regression ◽  
Chrysanthemum Morifolium ◽  
Chemical Components ◽  
Hplc Fingerprint ◽  
Chrysanthemum Indicum ◽  
Statistical Data Mining ◽  
The Difference ◽  
Deep Profile ◽  
Logistic Regression Equation ◽  
Herbal Species

C. morifolium flower and C. indicum flower are two closely related herbal species with similar morphological and microscopic characteristics but are discriminated in edible and medicinal purpose. However, there is no effective approach to distinguish the two herbs. A novel workflow for quickly differentiating C. morifolium flower and C. indicum flower was developed. Firstly, the difference in anti-inflammatory effects for C. morifolium flower and C. indicum flower was characterized using lipopolysaccharide-treated rats. Then HPLC fingerprint analysis for 53 batches of C. morifolium flowers and 33 batches of C. indicum flower was carried out to deep profile the chemical components. The preliminary markers were screened out by OPLS-DA, identified by HPLC-ESI-QTOF-MS, and quantified by the improved SSDMC (single reference standard to determine multiple compounds) approach. Finally, multiple statistical data mining was performed to confirm the markers and a binary logistic regression equation was built to differentiate C. morifolium flower and C. indicum flower successfully. In general, the established workflow was rapid, effective and highly feasible, which would provide a powerful tool for herb identification.

scholarly journals The Uptake and Vaccination Willingness of COVID-19 Vaccine among Chinese Residents: Web-Based Online Cross-Sectional Study

Vaccines ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 90
Author(s):  
Yi Kong ◽  
Hao Jiang ◽  
Zhisheng Liu ◽  
Yi Guo ◽  
Dehua Hu
Keyword(s):  
Health Status ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Personal Health ◽  
Binary Logistic Regression Analysis ◽  
Snowball Sampling ◽  
Cross Sectional ◽  
Web Based ◽  
The Difference ◽  
High Level

Objective: To investigate the uptake and vaccination willingness of the COVID-19 vaccine among Chinese residents and analyze the difference and factors that impact vaccination. Methods: The snowball sampling method was used to distribute online questionnaires. Relevant sociodemographic data along with the circumstances of COVID-19 vaccination were collected from the respondents. The χ2 test, independent samples t test and binary logistic regression analysis were used to analyze the data. Results: Among 786 respondents, 84.22% had been vaccinated. Over 80% of the vaccinated population have completed all the injections because of supporting the national vaccination policies of China, while the unvaccinated population (23.91%) is mainly due to personal health status. Meanwhile, statistical analysis revealed that the main predictors of not being vaccinated were younger age (3 to 18 years old), personal health status, and lower vaccinated proportion of family members and close friends (p < 0.05). Conclusions: There was a high level of uptake of the COVID-19 vaccine in China, and people who have not been vaccinated generally had a low willingness to vaccinate in the future. Based on our results, it suggested the next work to expand the coverage of the COVID-19 vaccination should be concentrated on targeted publicity and education for people who have not been vaccinated.

The Difference in Sibling Birthweight and Neonatal Death: A Population-Based Cohort Study

2018 ◽  
Vol 36 (05) ◽  
pp. 498-504
Author(s):  
Maya Tabet ◽  
Louise Flick ◽  
Hong Xian ◽  
Jen Chang
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Neonatal Death ◽  
Binary Logistic Regression ◽  
Population Based ◽  
Growth Potential ◽  
Live Births ◽  
The Difference ◽  
Second Births ◽  
Half Sibling

Background There has been a call for customized rather than population-based birthweight standards that would classify smallness based on an infant's own growth potential. Thus, this study aimed to examine the association between the difference in sibling birthweight and the likelihood of neonatal death among second births in a U.S. population. Study Design This was a population-based cohort study including 179,300 women who delivered their first two nonanomalous singleton live births in Missouri (1989–2005). We performed binary logistic regression to evaluate the association between being relatively smaller than the elder full- or half-sibling (i.e., smaller by at least 500 g) and neonatal death (i.e., deaths in the first 28 days of life) among second births after controlling for sociodemographic and pregnancy-related variables in the second pregnancy. Results The adjusted odds of neonatal death were 2.54-times higher among second births who were relatively smaller than their elder sibling. Among relatively small second births, every 100-g increase in the difference in sibling birthweight was associated with a 13% increase in the odds of neonatal death. Conclusion The deviation from the elder sibling's birthweight predicts neonatal death. Taking into consideration the elder sibling's birthweight may be warranted in clinical and research settings.

scholarly journals On a new approach to assessing the energy characteristics of substances

2019 ◽  
Vol 124 ◽  
pp. 01017
Author(s):  
O. S. Sirotkin ◽  
A. M. Pavlova ◽  
R. O. Sirotkin ◽  
A. E. Buntin
Keyword(s):  
Energy Production ◽  
Chemical Interaction ◽  
Heat Of Formation ◽  
Redox Properties ◽  
Chemical Components ◽  
Reaction Products ◽  
Energy Characteristics ◽  
New Approach ◽  
Production Technologies ◽  
The Difference

Within the unified model of chemical bonding and methods of quantitative assessment of components of mixed chemical interaction between the elements in compounds, developed by the authors, a new approach was developed to assess the structural and energy characteristics of substances and fuels. It comprises establishing a correlation between the difference of bonds’ chemical components of reactants and end products. Changes in the chemical bond components affect such characteristics of chemical reactions as the heat of formation of the reaction products, their redox properties, whether reaction is endoor exothermic, as well as the heat of fuel combustion reactions. This approach is an additional reserve for improving the methods for assessing the energy characteristics of fuels and increasing the efficiency of energy production technologies.

Performance simulations for categorical mediation: Analyzing khb estimates of mediation in ordinal regression models

2019 ◽  
Vol 19 (4) ◽  
pp. 913-930 ◽  
Author(s):  
E. Keith Smith ◽  
Michael G. Lacy ◽  
Adam Mayer
Keyword(s):  
Logistic Regression ◽  
Nonlinear Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Experimental Conditions ◽  
Logistic Regression Models ◽  
Nonlinear Regression Models ◽  
Size Number ◽  
Confidence Interval Coverage ◽  
The Difference

Standard mediation techniques for fitting mediation models cannot readily be translated to nonlinear regression models because of scaling issues. Methods to assess mediation in regression models with categorical and limited response variables have expanded in recent years, and these techniques vary in their approach and versatility. The recently developed khb technique purports to solve the scaling problem and produce valid estimates across a range of nonlinear regression models. Prior studies demonstrate that khb performs well in binary logistic regression models, but performance in other models has yet to be investigated. In this article, we evaluate khb‘s performance in fitting ordinal logistic regression models as an exemplar of the wider set of models to which it applies. We examined performance across 38,400 experimental conditions involving sample size, number of response categories, distribution of variables, and amount of mediation. Results indicate that under all experimental conditions, khb estimates the difference (mediation) coefficient and its associated standard error with little bias and that the nominal confidence interval coverage closely matches the actual. Our results suggest that researchers using khb can assume that the routine reasonably approximates population parameters.

scholarly journals ANALYSIS OF FARM CASSAVA PARTNERSHIP IN THE VILLAGE OF GREAT PUDDING BESAR DISTRICT OF BANGKA

2020 ◽  
Vol 2 (2) ◽  
pp. 91-104
Author(s):  
Yansah Yansah ◽  
Iwan Setiawan ◽  
Yudi Sapta Pranoto
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Binary Logistic Regression ◽  
T Test ◽  
Survey Method ◽  
Real Difference ◽  
Average Income ◽  
The Difference ◽  
Quota Sampling ◽  
The Village

This study aims to describe the implementation of the partnership farming Cassava Village Pudding Besar District of pudding Big Bangka, analyze the differences in average income that is obtained by farmers from various partnership schemes cassava in the village Pudding Besar District of pudding Big Bangka, analyzed the factors - factors that influence farmers' decision in choosing partners and not partner with partnership cassava farm in the village of Great pudding pudding Large District of Bangka. This study was conducted in January 2019 until January 2020 in the village of Great Pudding Pudding Large District of Bangka. The method used is survey method. Penrikan method used example is a method of quota sampling with a sample of two groups of 40 people and the partnering farmers do not partner 40 people. Methods of data analysis using descriptive qualitative, quantitative analsisis (independent sample t-test, binary logistic regression). The results showed the implementation of partnership farming patterns occurring in the village of Great Pudding is a partnership with the name intiplasma KSR Program (Cassava People's Gardens). There is a real difference but not significant, the average income of Rp 32,384,718 partner farmers, while the non- partner farmers Rp 36,751,056 with the difference in the average income of farmers partner and non- partner Rp 4,366,388 per year. Factors that significantly affect farmers' decisions in partnering and partnering as age and availability of capital.

scholarly journals Identification betweenStephania tetrandraS. Moore andStephania cepharanthaHayata by CWT–FTIR–RBFNN

2008 ◽  
Vol 22 (5) ◽  
pp. 371-386 ◽  
Author(s):  
Chang-Jiang Zhang ◽  
Cun-Gui Cheng
Keyword(s):  
Neural Network ◽  
Feature Vector ◽  
Recognition Rate ◽  
Total Reflection ◽  
Chemical Components ◽  
Continuous Wavelet ◽  
Feature Extracting ◽  
Training Samples ◽  
The Difference ◽  
Stephania Tetrandra

Horizontal attenuation total reflection–Fourier transform infrared spectroscopy (HATR–FTIR) is used to measure the FTIR ofStephania tetrandraS. Moore andStephania cepharanthaHayata. Because they belong to the same family and the same genus Chinese traditional medicinal materials, their chemical components are very similar. In order to extrude the difference betweenStephania tetrandraS. Moore andStephania cepharanthaHayata, continuous wavelet transform (CWT) is used to decompose the FTIR ofStephania tetrandraS. Moore andStephania cepharanthaHayata. Three main scales are selected as the feature extracting space in the CWT domain. According the distribution of FTIR ofStephania tetrandraS. Moore andStephania cepharanthaHayata, three feature regions are determined at every spectra band at selected three scales in the CWT domain. Thus nine feature parameters form the feature vector. The feature vector is input to the radius basis function neural network (RBFNN) to train so as to accurately classify theStephania tetrandraS. Moore andStephania cepharanthaHayata. 128 couples of FTIR are used to train and test the proposed method, where 78 couples of data are used as training samples and 50 couples of data are used as testing samples. Experimental results show that the accurate recognition rate betweenStephania tetrandraS. Moore andStephania cepharanthaHayata is respectively 99.8 and 99.9% by using the proposed method.

scholarly journals Cloning and Functional Characterization of Dihydroflavonol 4-Reductase Gene Involved in Anthocyanin Biosynthesis of Chrysanthemum

2020 ◽  
Vol 21 (21) ◽  
pp. 7960
Author(s):  
Sun-Hyung Lim ◽  
Bora Park ◽  
Da-Hye Kim ◽  
Sangkyu Park ◽  
Ju-Hee Yang ◽  
...  
Keyword(s):  
Developmental Stages ◽  
Anthocyanin Biosynthesis ◽  
Functional Characterization ◽  
Flower Color ◽  
Chrysanthemum Morifolium ◽  
C Terminus ◽  
Reductase Gene ◽  
The Difference ◽  
Chrysanthemum Morifolium Ramat

Dihydroflavonol 4-reductase (DFR) catalyzes a committed step in anthocyanin and proanthocyanidin biosynthesis by reducing dihydroflavonols to leucoanthocyanidins. However, the role of this enzyme in determining flower color in the economically important crop chrysanthemum (Chrysanthemum morifolium Ramat.) is unknown. Here, we isolated cDNAs encoding DFR from two chrysanthemum cultivars, the white-flowered chrysanthemum “OhBlang” (CmDFR-OB) and the red-flowered chrysanthemum “RedMarble” (CmDFR-RM) and identified variations in the C-terminus between the two sequences. An enzyme assay using recombinant proteins revealed that both enzymes catalyzed the reduction of dihydroflavonol substrates, but CmDFR-OB showed significantly reduced DFR activity for dihydrokaempferol (DHK) substrate as compared with CmDFR-RM. Transcript levels of anthocyanin biosynthetic genes were consistent with the anthocyanin contents at different flower developmental stages of both cultivars. The inplanta complementation assay, using Arabidopsis thaliana dfr mutant (tt3-1), revealed that CmDFR-RM, but not CmDFR-OB, transgenes restored defective anthocyanin biosynthesis of this mutant at the seedling stage, as well as proanthocyanidin biosynthesis in the seed. The difference in the flower color of two chrysanthemums can be explained by the C-terminal variation of CmDFR combined with the loss of CmF3H expression during flower development.

scholarly journals The Healthy e-Elderly People Assessment (HEPA) application

2019 ◽  
Vol 33 (1) ◽  
pp. 14-23
Author(s):  
Wachiraporn Wilaiwan ◽  
Wattasit Siriwong
Keyword(s):  
Health Effects ◽  
Elderly People ◽  
Binary Logistic Regression ◽  
The Elderly ◽  
Cross Sectional ◽  
Content Type ◽  
The Difference ◽  
Rest Breaks ◽  
Self Administered Questionnaire ◽  
Elderly Users

Purpose The purpose of this paper is to evaluate health effects and determine the factors associated with health effects from smartphone and tablet use among the elderly in Thailand. Design/methodology/approach This study was a cross-sectional descriptive study. The participants comprised 490 elderly people. A self-administered questionnaire was used for data collection via the Healthy e-Elderly People Assessment mobile application in the Android operating system by Google which consists of five parts of a questionnaire. The variables were analyzed using SPSS such as frequency, percentage, mean and binary logistic regression. Findings Altogether, the participants were 223 males and 267 females; mean age=64.9±5.4. The average time spent using a mobile device was 2.8±1.9 h/day. Participants recorded that after use of either device, 59.0 percent experienced eye pain, 52.7 percent experienced dim eyes, 30.2 percent experienced tiredness, and 28.0 percent experienced moodiness. Socially, 26.8 percent recorded changes in social interaction. Periods of time using devices, time consumed in device usage (hours/day), the type of application, and the difference in times of use, place of usage and time spent in rest breaks from smartphone or tablet usage were significantly associated with health effects (p<0.05). Originality/value The elderly users may be at risk of several health effects from smartphone and tablet use. The potential gap in knowledge conceals some of the risk factors for the current health effects. Practical intervention to reduce health effects from the use of smartphones and tablets should be considered.

A Study on the Difference of Urban and Rural Resilience under Climate Change- A Case Study of Chiayi County

2020 ◽  
Author(s):  
Shin-En Pai ◽  
Hsueh-Sheng Chang
Keyword(s):  
Climate Change ◽  
Rural Areas ◽  
Binary Logistic Regression ◽  
International Strategy ◽  
Sendai Framework ◽  
Resilience Index ◽  
The Face ◽  
The Difference ◽  
Urban And Rural Areas ◽  
The Impact

&lt;p&gt;In recent years, the impact of climate change has caused critical risks to urban and rural systems, how to mitigate the damage caused by extreme climate events has become a topic of considerable concern in various countries in recent years. The United Nations International Strategy for Disaster Reduction (UNISDR) mentioned in the Hyogo Framework for Action (HFA) and the Sendai Framework for Disaster Risk Reduction 2015-2030 (Sendai Framework) that improving community resilience will help to deal with the harm caused by climate change. However, most of the previous research on resilience have only focused solely on urban or rural only, and have failed to clearly identify the differences in resilience between urban and rural areas. In fact, if we can understand the difference in resilience between urban and rural in the face of climate change, it will provide planners with better planning strategies or resource allocation. Based on this, the study first developed the resilience index through literature review, and then filtered and screened the index through Principle Component Analysis (PCA). After that, the resilience index was applied to empirical areas, and the spatial correlation of resilience was explored through Local Indicators of Spatial Autocorrelation (LISA). Finally, the binary logistic regression is used to analyze the difference in resilience of urban or rural under climate change.&lt;/p&gt;

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