A Study on the Hazard and Identification Technique for Azo Compound as the Case of Explosive Fire of a Plant in Anseong

2020 ◽  
Vol 11 (4) ◽  
pp. 3-17
Author(s):  
Soon Young Kim ◽  
◽  
Soon Young Hong ◽  
Seong Woo Kang ◽  
Kyung Il Park
Keyword(s):  
Azo Compound ◽  
Identification Technique

Modelling and control of an alkaline water electrolysis process

2018 ◽  
Vol 1 (2) ◽  
pp. 9-14
Author(s):  
Marisol Cervantes-Bobadilla ◽  
Ricardo Fabricio Escobar Jiménez ◽  
José Francisco Gómez Aguilar ◽  
Tomas Emmanuel Higareda Pliego ◽  
Alberto Armando Alvares Gallegos
Keyword(s):  
Process Model ◽  
Water Electrolysis ◽  
Alkaline Water Electrolysis ◽  
Alkaline Water ◽  
Electrolysis Process ◽  
Linear Dynamic ◽  
Energy Current ◽  
Identification Technique ◽  
Nonlinear Static ◽  
And Control

In this research, an alkaline water electrolysis process is modelled. The electrochemical electrolysis is carried out in an electrolyzer composed of 12 series-connected steel cells with a solution 30% wt of potassium hydroxide. The electrolysis process model was developed using a nonlinear identification technique based on the Hammerstein structure. This structure consists of a nonlinear static block and a linear dynamic block. In this work, the nonlinear static function is modelled by a polynomial approximation equation, and the linear dynamic is modelled using the ARX structure. To control the current feed to the electrolyzer an unconstraint predictive controller was implemented, once the unconstrained MPC was simulated, some restrictions are proposed to design a constrained MPC (CMPC). The CMPC aim is to reduce the electrolyzer's energy consumption (power supply current). Simulation results showed the advantages of using the CMPC since the energy (current) overshoots are avoided.

scholarly journals COVID-19 pandemic: the implications of the natural history, challenges of diagnosis and management for care in sub-Saharan Africa

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Lawrence Omo-Aghoja ◽  
Emuesiri Goodies Moke ◽  
Kenneth Kelechi Anachuna ◽  
Adrian Itivere Omogbiya ◽  
Emuesiri Kohworho Umukoro ◽  
...  
Keyword(s):  
Public Health ◽  
Natural History ◽  
Low Income ◽  
Sub Saharan Africa ◽  
Low Income Countries ◽  
Diagnosis And Management ◽  
Severe Acute Respiratory Infection ◽  
Identification Technique ◽  
Sub Saharan ◽  
Policies And Programs

Abstract Background Coronavirus disease (COVID-19) is a severe acute respiratory infection which has afflicted virtually almost all nations of the earth. It is highly transmissible and represents one of the most serious pandemics in recent times, with the capacity to overwhelm any healthcare system and cause morbidity and fatality. Main content The diagnosis of this disease is daunting and challenging as it is dependent on emerging clinical symptomatology that continues to increase and change very rapidly. The definitive test is the very expensive and scarce polymerase chain reaction (PCR) viral identification technique. The management has remained largely supportive and empirical, as there are no officially approved therapeutic agents, vaccines or antiviral medications for the management of the disease. Severe cases often require intensive care facilities and personnel. Yet there is paucity of facilities including the personnel required for diagnosis and treatment of COVID-19 in sub-Saharan Africa (SSA). It is against this backdrop that a review of key published reports on the pandemic in SSA and globally is made, as understanding the natural history of a disease and the documented responses to diagnosis and management is usually a key public health strategy for designing and improving as appropriate, relevant interventions. Lead findings were that responses by most nations of SSA were adhoc, paucity of public health awareness strategies and absence of legislations that would help enforce preventive measures, as well as limited facilities (including personal protective equipment) and institutional capacities to deliver needed interventions. Conclusion COVID-19 is real and has overwhelmed global health care system especially low-income countries of the sub-Sahara such as Nigeria. Suggestions for improvement of healthcare policies and programs to contain the current pandemic and to respond more optimally in case of future pandemics are made herein.

scholarly journals Accuracy of the fluorescence-aided identification technique (FIT) for detecting tooth-colored restorations utilizing different fluorescence-inducing devices: an ex vivo comparative study

2021 ◽  
Author(s):  
W. Leontiev ◽  
E. Magni ◽  
C. Dettwiler ◽  
C. Meller ◽  
R. Weiger ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Ex Vivo ◽  
Predictive Values ◽  
Composite Restorations ◽  
Significant Difference ◽  
Identification Technique ◽  
Illumination Method ◽  
Sensitivity Specificity ◽  
Entire Procedure ◽  
Higher Sensitivity

Abstract Objectives The aim of the present study was to compare the accuracy of the conventional illumination method (CONV) and the fluorescence-aided identification technique (FIT) for distinguishing between composite restorations and intact teeth using different fluorescence-inducing devices commonly used for FIT. Materials and methods Six groups of six dentists equipped with one of six different FIT systems each independently attempted to identify composite restorations and intact teeth on a full-mouth model with 22 composite restorations using CONV and, 1 h later, FIT. The entire procedure was repeated 1 week later. Sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values, including 95% confidence intervals (CI), were calculated for CONV and FIT overall and for each device. The influence of examiner age, method, and device on each parameter was assessed by multivariate analysis of variance. Results The sensitivity (84%, CI 81–86%), specificity (94%, CI 93–96%), PPV (92%, CI 90–94%), and NPV (90%, CI 88–91%) of FIT was significantly higher than that of CONV (47%, CI 44–50%; 82%, CI 79–84%; 66%, CI 62–69%, and 69%, CI 68–71%, respectively; p<0.001). The differences between CONV and FIT were significant for all parameters and FIT systems except VistaCam, which achieved no significant difference in specificity. Examiners younger than 40 years attained significantly higher sensitivity and negative predictive values than older examiners. Conclusions FIT is more reliable for detecting composite restorations than the conventional illumination method. Clinical relevance FIT can be considered an additional or alternative tool for improving the detection of composite restorations.

scholarly journals 5-((8-Hydroxyquinolin-5-yl)diazenyl)-3-methyl-1H-pyrazole-4-carboxylic Acid

Molbank ◽  
10.3390/m1238 ◽  
2021 ◽  
Vol 2021 (2) ◽  
pp. M1238
Author(s):  
Ion Burcă ◽  
Valentin Badea ◽  
Calin Deleanu ◽  
Vasile-Nicolae Bercean
Keyword(s):  
Chemical Structure ◽  
Functional Group ◽  
Coupling Reaction ◽  
2D Nmr ◽  
Azo Coupling ◽  
2D Nmr Spectroscopy ◽  
Azo Compound ◽  
Ft Ir ◽  
New Compounds ◽  
Carboxylic Functional Group

A new azo compound was prepared via the azo coupling reaction between 4-(ethoxycarbonyl)-3-methyl-1H-pyrazole-5-diazonium chloride and 8-hydroxyquinoline (oxine). The ester functional group of the obtained compound was hydrolyzed and thus a new chemical structure with a carboxylic functional group resulted. The structures of the new compounds were fully characterized by: UV–Vis, FT-IR, 1D and 2D NMR spectroscopy, and HRMS spectrometry.

Spectrophotometric submicrodetermination of nitrites after double extraction of the azo compound produced

1970 ◽  
Vol 42 (14) ◽  
pp. 1809-1810 ◽  
Author(s):  
Giuseppe. Macchi ◽  
B. Cescon
Keyword(s):  
Azo Compound ◽  
Double Extraction

scholarly journals Intelligent Dynamic Identification Technique of Industrial Products in a Robotic Workplace

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1797
Author(s):  
Ján Vachálek ◽  
Dana Šišmišová ◽  
Pavol Vašek ◽  
Jan Rybář ◽  
Juraj Slovák ◽  
...  
Keyword(s):  
Machine Learning ◽  
Control Charts ◽  
Nearest Neighbor ◽  
Learning Algorithm ◽  
Conveyor Belt ◽  
Standard Uncertainty ◽  
K Nearest Neighbor ◽  
Industrial Products ◽  
Dynamic Identification ◽  
Identification Technique

The article deals with aspects of identifying industrial products in motion based on their color. An automated robotic workplace with a conveyor belt, robot and an industrial color sensor is created for this purpose. Measured data are processed in a database and then statistically evaluated in form of type A standard uncertainty and type B standard uncertainty, in order to obtain combined standard uncertainties results. Based on the acquired data, control charts of RGB color components for identified products are created. Influence of product speed on the measuring process identification and process stability is monitored. In case of identification uncertainty i.e., measured values are outside the limits of control charts, the K-nearest neighbor machine learning algorithm is used. This algorithm, based on the Euclidean distances to the classified value, estimates its most accurate iteration. This results into the comprehensive system for identification of product moving on conveyor belt, where based on the data collection and statistical analysis using machine learning, industry usage reliability is demonstrated.

scholarly journals Identification of Brain Electrical Activity Related to Head Yaw Rotations

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3345
Author(s):  
Enrico Zero ◽  
Chiara Bersani ◽  
Roberto Sacile
Keyword(s):  
Electrical Activity ◽  
Electrical Stimulus ◽  
Head Movements ◽  
Brain Electrical Activity ◽  
Output Function ◽  
Input Output ◽  
Eeg Signals ◽  
Head Turning ◽  
Identification Technique ◽  
The Brain

Automatizing the identification of human brain stimuli during head movements could lead towards a significant step forward for human computer interaction (HCI), with important applications for severely impaired people and for robotics. In this paper, a neural network-based identification technique is presented to recognize, by EEG signals, the participant’s head yaw rotations when they are subjected to visual stimulus. The goal is to identify an input-output function between the brain electrical activity and the head movement triggered by switching on/off a light on the participant’s left/right hand side. This identification process is based on “Levenberg–Marquardt” backpropagation algorithm. The results obtained on ten participants, spanning more than two hours of experiments, show the ability of the proposed approach in identifying the brain electrical stimulus associate with head turning. A first analysis is computed to the EEG signals associated to each experiment for each participant. The accuracy of prediction is demonstrated by a significant correlation between training and test trials of the same file, which, in the best case, reaches value r = 0.98 with MSE = 0.02. In a second analysis, the input output function trained on the EEG signals of one participant is tested on the EEG signals by other participants. In this case, the low correlation coefficient values demonstrated that the classifier performances decreases when it is trained and tested on different subjects.

scholarly journals Overview of Popular Techniques of Raman Spectroscopy and Their Potential in the Study of Plant Tissues

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1537
Author(s):  
Aneta Saletnik ◽  
Bogdan Saletnik ◽  
Czesław Puchalski
Keyword(s):  
Raman Spectroscopy ◽  
Cell Walls ◽  
Structural Changes ◽  
Spatial Information ◽  
Technological Development ◽  
Analytical Techniques ◽  
High Sensitivity ◽  
Plant Tissues ◽  
Wide Range ◽  
Identification Technique

Raman spectroscopy is one of the main analytical techniques used in optical metrology. It is a vibration, marker-free technique that provides insight into the structure and composition of tissues and cells at the molecular level. Raman spectroscopy is an outstanding material identification technique. It provides spatial information of vibrations from complex biological samples which renders it a very accurate tool for the analysis of highly complex plant tissues. Raman spectra can be used as a fingerprint tool for a very wide range of compounds. Raman spectroscopy enables all the polymers that build the cell walls of plants to be tracked simultaneously; it facilitates the analysis of both the molecular composition and the molecular structure of cell walls. Due to its high sensitivity to even minute structural changes, this method is used for comparative tests. The introduction of new and improved Raman techniques by scientists as well as the constant technological development of the apparatus has resulted in an increased importance of Raman spectroscopy in the discovery and defining of tissues and the processes taking place in them.

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