scholarly journals Predictive Chromatography of Leaf Extracts Through Encoded Environmental Forcing on Phytochemical Synthesis

2021 ◽  
Vol 12 ◽  
Author(s):  
Junelle Rey C. Bacong ◽  
Drandreb Earl O. Juanico
Keyword(s):  
Neural Network ◽  
Adaptive Response ◽  
Growth Conditions ◽  
Data Representation ◽  
Training Algorithm ◽  
Leaf Extracts ◽  
Environmental Forcing ◽  
Plant Environment ◽  
Phytochemical Profile ◽  
First Time

Environment fluctuations can influence a plant's phytochemical profile via phenotypic plasticity. This adaptive response ensures a plant's survival under fluctuating growth conditions. However, the resulting plant extract composition becomes unpredictable, which is a problem for highly standardized medicinal applications. Here we demonstrate, for the first time, the feasibility of tracking the changes in the phytochemical profile based on real-time measurements of a few environment and extract-preparation variables. As a result, we predicted the chromatograms of Blumea balsamifera extracts through an imputation-augmented convolutional neural network, which uses the image-transformed temporal measurements of the variables. We developed a sensor network that collected data in a greenhouse and a training algorithm that concurrently generated a data representation of the implicit plant-environment interactions leading to the mutable chromatograms of leaf extracts. We anticipate the generic applicability of the method for any plant and recognize its potential for addressing the standardization problems in plant therapeutics.

scholarly journals Phytochemical Profile and Biological Properties of Colchicum triphyllum (Meadow Saffron)

Foods ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 457 ◽  
Author(s):  
Biancamaria Senizza ◽  
Gabriele Rocchetti ◽  
Murat Ali Okur ◽  
Gokhan Zengin ◽  
Evren Yıldıztugay ◽  
...  
Keyword(s):  
High Performance ◽  
Biological Activities ◽  
Reducing Power ◽  
Extraction Methods ◽  
Biological Properties ◽  
Leaf Extracts ◽  
Antioxidant Power ◽  
Phytochemical Profile ◽  
First Time

In this work, the phytochemical profile and the biological properties of Colchicum triphyllum (an unexplored Turkish cultivar belonging to Colchicaceae) have been comprehensively investigated for the first time. Herein, we focused on the evaluation of the in vitro antioxidant and enzyme inhibitory effects of flower, tuber, and leaf extracts, obtained using different extraction methods, namely maceration (both aqueous and methanolic), infusion, and Soxhlet. Besides, the complete phenolic and alkaloid untargeted metabolomic profiling of the different extracts was investigated. In this regard, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) allowed us to putatively annotate 285 compounds when considering the different matrix extracts, including mainly alkaloids, flavonoids, lignans, phenolic acids, and tyrosol equivalents. The most abundant polyphenols were flavonoids (119 compounds), while colchicine, demecolcine, and lumicolchicine isomers were some of the most widespread alkaloids in each extract analyzed. In addition, our findings showed that C. triphyllum tuber extracts were a superior source of both total alkaloids and total polyphenols, being on average 2.89 and 10.41 mg/g, respectively. Multivariate statistics following metabolomics allowed for the detection of those compounds most affected by the different extraction methods. Overall, C. triphyllum leaf extracts showed a strong in vitro antioxidant capacity, in terms of cupric reducing antioxidant power (CUPRAC; on average 96.45 mg Trolox Equivalents (TE)/g) and ferric reducing antioxidant power (FRAP) reducing power (on average 66.86 mg TE/g). Interestingly, each C. triphyllum methanolic extract analyzed (i.e., from tuber, leaf, and flower) was active against the tyrosinase in terms of inhibition, recording the higher values for methanolic macerated leaves (i.e., 125.78 mg kojic acid equivalent (KAE)/g). On the other hand, moderate inhibitory activities were observed against AChE and α-amylase. Strong correlations (p < 0.01) were also observed between the phytochemical profiles and the biological activities determined. Therefore, our findings highlighted, for the first time, the potential of C. triphhyllum extracts in food and pharmaceutical applications.

Methods for evaluation the manufacturability of a vehicle

2020 ◽  
pp. 152-160
Keyword(s):  
Neural Network ◽  
Initial Data ◽  
Comparative Data ◽  
Training Algorithm ◽  
Neural Network Method ◽  
The Neural Network ◽  
Network Method ◽  
Calculation Results ◽  
Production And Operation

Methods for evaluation the manufacturability of a vehicle in the field of production and operation based on an energy indicator, expert estimates and usage of a neural network are stated. By using the neural network method the manufacturability of a car in a complex and for individual units is considered. The preparation of the initial data at usage a neural network for predicting the manufacturability of a vehicle is shown; the training algorithm and the architecture for calculating the manufacturability of the main units are given. According to the calculation results, comparative data on the manufacturability vehicles of various brands are given.

scholarly journals Thermal-wet model of knitted double jersey based on backpropagation algorithm of neural network

2020 ◽  
Vol 15 ◽  
pp. 155892501990083
Author(s):  
Xintong Li ◽  
Honglian Cong ◽  
Zhe Gao ◽  
Zhijia Dong
Keyword(s):  
Neural Network ◽  
Water Vapor ◽  
Thermal Resistance ◽  
Resistance Test ◽  
Training Algorithm ◽  
Backpropagation Algorithm ◽  
Optimal Network ◽  
Resistance Model ◽  
Hidden Layer ◽  
The Relationship

In this article, thermal resistance test and water vapor resistance test were experimented to obtain data of heat and humidity performance. Canonical correlation analysis was used on determining influence of basic fabric parameters on heat and humidity performance. Thermal resistance model and water vapor resistance model were established with a three-layered feedforward-type neural network. For the generalization of the network and the difficulty of determining the optimal network structure, trainbr was chosen as training algorithm to find the relationship between input factors and output data. After training and verification, the number of hidden layer neurons in the thermal resistance model was 12, and the error reached 10−3. In the water vapor resistance model, the number of hidden layer neurons was 10, and the error reached 10−3.

Preparation and Growth of Pb2Sr2Y0.5Ca0.5Cu3O8+δ Thin Film Superconductors

1992 ◽  
Vol 285 ◽  
Author(s):  
S.H.H. Naqvi ◽  
M. Vickers ◽  
S. Tarling ◽  
P. Barnes ◽  
I.W. Boyd
Keyword(s):  
Thin Film ◽  
Pulsed Laser ◽  
Growth Conditions ◽  
Laser Deposition ◽  
Ex Situ ◽  
Dc Resistivity ◽  
Basic Set ◽  
Zero Resistance ◽  
Van Der Pauw ◽  
First Time

ABSTRACTThe lead based superconductor Pb2Sr2Y0.5Ca0.5Cu3O8+δ is a most complex material. If any oxygen is present in the PbO-CuOδ-PbO sandwich layer (i.e. if δ>0) the superconductivity deteriorates. This is also a most difficult material to grow not only because of the large number of cation stoichiometries which have to be precisely balanced but also because of the tendency for multiple phases to form. Pulsed laser deposition (PLD) has been applied to prepare thin films of the 2213-phase on MgO (100) single crystal substrates at low temperature (300°C) in low oxidizing atmospheres. A basic set of ex-situ growth conditions has been determined which produce for the first time good quality films of this material as characterized by DC resistivity using the Van der Pauw method, as well as EDX and XRD. The layers are reasonably c-axis oriented and display a superconducting onset transition temperature of 79K and zero resistance at 65K after subsequent annealing in a nitrogen ambient.

scholarly journals Optimization of Green Synthesis of Silver Nanoparticles from Leaf Extracts ofPimenta dioica(Allspice)

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Akshay Rajeev Geetha ◽  
Elizabeth George ◽  
Akshay Srinivasan ◽  
Jameel Shaik
Keyword(s):  
Silver Nanoparticles ◽  
Green Synthesis ◽  
Leaf Extract ◽  
Synthesis Method ◽  
Leaf Extracts ◽  
Synthesis Of Nanoparticles ◽  
Hot Air ◽  
Vis Spectroscopy ◽  
Pimenta Dioica ◽  
First Time

Production of silver nanoparticles from the leaf extracts ofPimenta dioicais reported for the first time in this paper. Three different sets of leaves were utilized for the synthesis of nanoparticles—fresh, hot-air oven dried, and sun-dried. These nanoparticles were characterized using UV-Vis spectroscopy and AFM. The results were diverse in that different sizes were seen for different leaf conditions. Nanoparticles synthesized using sun-dried leaves (produced using a particular ratio (1 : 0.5) of the leaf extract sample and silver nitrate (1 mM), resp.) possessed the smallest sizes. We believe that further optimization of the current green-synthesis method would help in the production of monodispersed silver nanoparticles having great potential in treating several diseases.

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