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Magnaldehyde D

$730

  • Brand : BIOFRON

  • Catalogue Number : AV-B02969

  • Specification : 95%

  • CAS number : 93753-33-4

  • Formula : C16H14O3

  • Molecular Weight : 254.28

  • PUBCHEM ID : 5319189

  • Volume : 5mg

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Catalogue Number

AV-B02969

Analysis Method

HPLC,NMR,MS

Specification

95%

Storage

2-8°C

Molecular Weight

254.28

Appearance

Powder

Botanical Source

Structure Type

Lignans

Category

Standards;Natural Pytochemical;API

SMILES

C=CCC1=CC(=C(C=C1)O)C2=C(C=CC(=C2)C=O)O

Synonyms

5'-Allyl-2',6-dihydroxy-3-biphenylcarbaldehyde/[1,1'-Biphenyl]-3-carboxaldehyde, 2',6-dihydroxy-5'-(2-propen-1-yl)-

IUPAC Name

4-hydroxy-3-(2-hydroxy-5-prop-2-enylphenyl)benzaldehyde

Applications

Density

1.2±0.1 g/cm3

Solubility

Soluble in Chloroform,Dichloromethane,Ethyl Acetate,DMSO,Acetone,etc.

Flash Point

222.9±25.2 °C

Boiling Point

421.5±45.0 °C at 760 mmHg

Melting Point

InChl

InChI=1S/C16H14O3/c1-2-3-11-4-6-15(18)13(8-11)14-9-12(10-17)5-7-16(14)19/h2,4-10,18-19H,1,3H2

InChl Key

KDWYPRNOEMXUNA-UHFFFAOYSA-N

WGK Germany

RID/ADR

HS Code Reference

Personal Projective Equipment

Correct Usage

For Reference Standard and R&D, Not for Human Use Directly.

Meta Tag

provides coniferyl ferulate(CAS#:93753-33-4) MSDS, density, melting point, boiling point, structure, formula, molecular weight etc. Articles of coniferyl ferulate are included as well.>> amp version: coniferyl ferulate

No Technical Documents Available For This Product.

PMID

32050596

Abstract

Background The purpose of this study was to evaluate the prevalence of position-dependent obstructive sleep apnea (POSA) in elderly patients (≥65 years old). Adult (range 19-65 years old) and elderly patients were also compared in order to show differences in the incidence of POSA between these two groups of patients. Methods A prospective bi-center study was performed between January 2018 and May 2019. A total of 434 participants underwent polysomnography (PSG) study at home (Embletta MPR). Body position during the PSG recordings was determined. Patients were subdivided in two groups: those aged between 19 and 65 years old (adult patients) and ≥65 years old (elderly patients). POSA patients were defined using Cartwright’s system, Bignold classification, and the new Amsterdam Positional OSA Classification (APOC). Results The prevalence of POSA in elderly patients differed according to the classification system used: 49.3% using Cartwright’s classification system, 20.5% with the Bignold classification, and 22.6%, 38.9%, and 5.4% of APOC 1, APOC 2, and APOC3 sub-classes were respectively identified for the APOC classification system. No difference between adult and elderly patients regarding the prevalence of POSA was observed. No statistical differences emerged between the two groups of patients in terms of supine (p = 0.9) and non-supine AHI (p = 0.4). Conclusions A significant number of elderly patients could be considered treatable with positional therapy according to the APOC classification. However, the efficacy and applicability of positional therapy in elderly patients must be confirmed by further research.

KEYWORDS

obstructive sleep apnea, positional sleep apnea, aging effects, polysomnography

Title

Positional Obstructive Sleep Apnea Syndrome in Elderly Patients

Author

Giannicola Iannella,1,2,* Giuseppe Magliulo,1 Cristina Anna Maria Lo Iacono,3 Giulia Bianchi,4 Antonella Polimeni,5 Antonio Greco,1 Andrea De Vito,2 Giuseppe Meccariello,2 Giovanni Cammaroto,2 Riccardo Gobbi,2 Marco Brunori,3 Milena Di Luca,6 Filippo Montevecchi,7 Annalisa Pace,1 Irene Claudia Visconti,1 Claudia Milella,1 Carmen Solito,1 Stefano Pelucchi,4 Luca Cerritelli,4 and Claudio Vicini2,4

Publish date

2020 Feb;

PMID

26214691

Abstract

This paper assesses the potentiality of certainty factor models (CF) for the best suitable causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata Prefecture, Japan. To test the applicability of CF, a landslide inventory map provided by National Research Institute for Earth Science and Disaster Prevention (NIED) was split into two subsets: (i) 70% of the landslides in the inventory to be used for building the CF based model; (ii) 30% of the landslides to be used for the validation purpose. A spatial database with fifteen landslide causative factors was then constructed by processing ALOS satellite images, aerial photos, topographical and geological maps. CF model was then applied to select the best subset from the fifteen factors. Using all fifteen factors and the best subset factors, landslide susceptibility maps were produced using statistical index (SI) and logistic regression (LR) models. The susceptibility maps were validated and compared using landslide locations in the validation data. The prediction performance of two susceptibility maps was estimated using the Receiver Operating Characteristics (ROC). The result shows that the area under the ROC curve (AUC) for the LR model (AUC = 0.817) is slightly higher than those obtained from the SI model (AUC = 0.801). Further, it is noted that the SI and LR models using the best subset outperform the models using the fifteen original factors. Therefore, we conclude that the optimized factor model using CF is more accurate in predicting landslide susceptibility and obtaining a more homogeneous classification map. Our findings acknowledge that in the mountainous regions suffering from data scarcity, it is possible to select key factors related to landslide occurrence based on the CF models in a GIS platform. Hence, the development of a scenario for future planning of risk mitigation is achieved in an efficient manner.

Title

Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan

Author

Jie Dou, 1 ,* Dieu Tien Bui, 2 Ali P. Yunus, 1 Kun Jia, 3 Xuan Song, 4 ,* Inge Revhaug, 5 Huan Xia, 6 and Zhongfan Zhu 7

Publish date

2015

PMID

30696101

Abstract

Urbanization has brought notable benefits for cities, but has also resulted in severe and diverse challenges in China. Previous studies have contributed to the definitions and evaluation of urbanization. However, there remain a great deal of ambiguities regarding urban comprehensive carrying capacity, and its measurable indicators still need further exploration given the urban development. This study aims to explore a model for evaluating urban comprehensive carrying capacity and thus to promote urban development. A total of 48 indicators which fell into 8 subsystems were identified to evaluate the urban comprehensive carrying capacity through literature reviews and interviews. The indicator set was developed for evaluation indicator selecting. Meanwhile, the dynamic system was explored, and an evaluation model based on the entire array polygon method was designed to evaluate urban comprehensive carrying capacity. Finally, a case study was conducted to provide suggestions for the decision-maker to implement the evaluation model. The results of this study show that the evaluation indicator system was dynamic due to urban development. Meanwhile, the model of the entire array polygon method was able to effectively evaluate urban comprehensive carrying capacity through the case study. Furthermore, this study found that there is an imbalance among subsystems in urban development according to the standard deviation. The findings are useful for setting up a benchmark framework for urban sustainability and providing an evaluation and monitoring model for decision maker to improve the urban carrying capacity.

KEYWORDS

sustainability, urbanization, urban comprehensive carrying capacity, entire array polygon method

Title

An Evaluation Model for Urban Comprehensive Carrying Capacity: An Empirical Case from Harbin City

Author

Yikun Su,1 Hong Xue,2,* and Huakang Liang2

Publish date

2019 Feb