scholarly journals ENTERAL INSUFFICIENCY COURSE SEVERITY DEGREES DIAGNOSTICS IN PERITONITIS BY SMALL INTESTINAL MICROSCOPIC IMAGES PHASE MAPING

2021 ◽  
pp. 25-30
Author(s):  
V. P. Polyovyy ◽  
R. I. Sydorchuk ◽  
S. P. Polyova ◽  
A. S. Palianytsia ◽  
I. G. Chepega
Keyword(s):  
Small Intestine ◽  
Phase Measurement ◽  
Measurement Data ◽  
Statistical Parameters ◽  
Logical Scheme ◽  
Microscopic Images ◽  
Laboratory Rats ◽  
Histological Sections ◽  
Insufficiency Syndrome ◽  
Polarization Phase

Summary. The aim is to determine the efficiency of diagnostics of the enteric insufficiency syndrome severity in peritonitis by phase mapping of microscopic images of histological sections of the laboratory rats’ small intestine. Material and methods. Seventy-eight white nonlinear rats of both sexes were selected, weighing from 180 to 220 g, underwent simulated mild, moderate and severe experimental peritonitis according to the standard method. Samples of optically thin histological sections of the small intestine of rats with different severity of the course of peritonitis were used as the research object. Results. As a result of the study, a structural and logical scheme for studying the effectiveness of differential diagnosis of the severity of peritonitis by means of statistical analysis of the structure of the distribution of phases of microscopic images of biological preparations of rats was developed, which helped to determine the relationships between the distribution of statistical parameters of the 1st–4th orders, which characterize phase maps depending on the severity of the peritonitis course. Conclusion. The revealed changes in the statistical structure of phase maps fully correlate with the measurement data for the polarization phase manifestations of the properties of the polycrystalline component of histological sections, both in the case of the phase measurement of polycrystalline blood films and the wall of the small intestine.

scholarly journals Functional observability and target state estimation in large-scale networks

2021 ◽  
Vol 119 (1) ◽  
pp. e2113750119
Author(s):  
Arthur N. Montanari ◽  
Chao Duan ◽  
Luis A. Aguirre ◽  
Adilson E. Motter
Keyword(s):  
Large Scale ◽  
Phase Measurement ◽  
Scale Up ◽  
Measurement Data ◽  
State Observer ◽  
Sensor Nodes ◽  
Scalable Algorithms ◽  
Functional Observer ◽  
Full State ◽  
Large Scale Networks

The quantitative understanding and precise control of complex dynamical systems can only be achieved by observing their internal states via measurement and/or estimation. In large-scale dynamical networks, it is often difficult or physically impossible to have enough sensor nodes to make the system fully observable. Even if the system is in principle observable, high dimensionality poses fundamental limits on the computational tractability and performance of a full-state observer. To overcome the curse of dimensionality, we instead require the system to be functionally observable, meaning that a targeted subset of state variables can be reconstructed from the available measurements. Here, we develop a graph-based theory of functional observability, which leads to highly scalable algorithms to 1) determine the minimal set of required sensors and 2) design the corresponding state observer of minimum order. Compared with the full-state observer, the proposed functional observer achieves the same estimation quality with substantially less sensing and fewer computational resources, making it suitable for large-scale networks. We apply the proposed methods to the detection of cyberattacks in power grids from limited phase measurement data and the inference of the prevalence rate of infection during an epidemic under limited testing conditions. The applications demonstrate that the functional observer can significantly scale up our ability to explore otherwise inaccessible dynamical processes on complex networks.

scholarly journals Development and application of measurement data pre-processing tools for parameter identification considering q-axis voltage

2021 ◽  
Vol 2087 (1) ◽  
pp. 012068
Author(s):  
Dunxiang Sun ◽  
Lei Cui
Keyword(s):  
Parameter Identification ◽  
Extraction Method ◽  
Phase Measurement ◽  
Measurement Data ◽  
Positive Sequence ◽  
Model Accuracy ◽  
Model Parameter ◽  
Load Model ◽  
Measurement Units ◽  
Model Parameter Identification

Abstract At present, when model parameter identification is carried out, measurement data from phase measurement units or fault recorders are generally used directly. These two types of devices can directly provide the fundamental positive sequence quantities required for parameter identification, but cannot output the dq components. If these measurement data can be fully utilized for parameter identification, it is very beneficial to improve the model accuracy. In this paper, according to the engineering needs of load model parameter identification, the extraction method and variation law of dq components are studied, and the data pre-processing tool is developed and put into use.

scholarly journals Differential diagnostics of the presence of damage by the method of digital polarization mapping of microsocopy images of hystological sections of human organs

2021 ◽  
pp. 70-78
Author(s):  
Oleksandra Litvinenko ◽  
Oleh Vanchulyak ◽  
Irina Soltys ◽  
Olga Mikhailova ◽  
Artem Motrich
Keyword(s):  
Lung Tissue ◽  
Experimental Testing ◽  
Biological Tissues ◽  
Differential Diagnostics ◽  
Time Interval ◽  
Diagnostic Efficiency ◽  
Internal Organs ◽  
Microscopic Images ◽  
Histological Sections ◽  
Ellipticity Of Polarization

The article presents the results of experimental testing of methods of azimuthal-invariant polarization mapping of microscopic images of samples of histological sections of the myocardium and lung tissue; time monitoring of changes in the magnitude of statistical moments of the 1-4th orders, characterizing the distributions of the azimuth and ellipticity of polarization of microscopic images of myocardial and lung tissue samples with different age of damage; determination of the diagnostic efficiency (time interval and accuracy) of establishing the age of damage to human internal organs by digital histological methods of mapping azimuth maps and polarization ellipticity of microscopic images. Aim of the work. Development of a digital histology technique for samples of human internal organs. Materials and methods. The object of the study was the histology of samples of human internal organs (myocardium, lung tissue) with different duration of damage from 1 hour to 120 hours. For control, we used BT samples from those who died from coronary artery disease with different duration of damage from 1 hour to 120 hours. The studies were carried out using the method of digital polarization mapping of microscopic images of histological sections of biological tissues of human internal organs. Results. Revealed the following ranges ramp variation quantity statistics polarizing digital histology and accuracy of the limitation of damage: a. Arts azimuth polarization microscopic image of a magnification ×40 (asymmetry – 12 hours, kurtosis – 12 hours, accuracy – 55-60 min), maps of ellipticity of polarization of microscopic images with a magnification of ×40 (asymmetry – 12 hours, kurtosis – 12 hours, accuracy – 65-75 min). Conclusions. Scenarios of changes in the statistical structure of maps of azimuth and ellipticity of polarization of microscopic images of histological sections of human internal organs have been determined - with an increase in the duration of damage, the value of the mean and variance decreases, the asymmetry and kurtosis increase.

Studies on the distribution and site location ofNippostrongylus brasiliensiswithin the small intestine of laboratory rats

Parasitology ◽  
1970 ◽  
Vol 61 (3) ◽  
pp. 449-460 ◽  
Author(s):  
Thomas J. W. Alphey
Keyword(s):  
Small Intestine ◽  
Primary Infection ◽  
Sexual Attraction ◽  
Adult Population ◽  
Migratory Behaviour ◽  
Fourth Stage ◽  
Site Location ◽  
Laboratory Rats ◽  
Anterior Half ◽  
Normal Site

The distribution ofN. brasiliensiswithin the small intestine of rats, following a primary infection, is described.The fourth stage larvae were found to inhabit the sections later parasitized by the adult population.Both the larval and adult worms were found to be confined to the anterior half of the small intestine. This aggregation is believed to be under the influence of stimuli (factor(s) 1), present in the lumen of the host gut.The adult worms also clumped within the already confined worm population. This behaviour is thought to be due to intrinsic behaviour patterns of the worm, sexual attraction and thigmokinesis.Larval and adult worms were surgically transferred to points, at varying distance from the ‘normally’ inhabited region, in the small intestine of fresh recipient rats. The resulting migratory behaviour of the worms was studied.The worm populations resulting from both the larval and the adult transfers showed the ability to recognize that they were in the wrong position of the small intestine and to be able to orientate, migrate and locate the ‘normal’ site.

A Study of the Forces on the Small Intestine From a Novel Suction Based Approach for Robotic Endoscopic Locomotion

2009 ◽  
Author(s):  
Roberto Montane ◽  
Mihir S. Wagh ◽  
Carl D. Crane
Keyword(s):  
Small Intestine ◽  
Small Bowel ◽  
Tissue Damage ◽  
Measurement Data ◽  
Vacuum Pressure ◽  
Maximum Force ◽  
In Situ Experiments ◽  
Measured Force

Many studies have been published regarding robotic endoscopes, however, very little has been done to quantify their effects on the intestine [1]. Here, the use of suction to hold onto the small intestine is investigated. These results will be used to develop an endoscope that is capable of being advanced deep into the small bowel. Prototype suction devices have been designed and various rigid suction tips tested on swine cadaveric intestines. Testing consisted of applying vacuum pressure to suction tips within the intestine. Suction tips were pulled in a shearing method against segments of swine intestine. Measurement data acquired determined parameters which generated the greatest amount of holding force while minimizing tissue damage. Vacuum pressures from 64 kPa–85 kPa were applied to suction tips. The measured force increased from 1.62 Newton (6 oz) to 3.89 Newton (14 oz) with increasing vacuum pressure. Even at the highest vacuum pressure employed (85 kPa) there were no visible signs of intestinal trauma. A maximum force of 3.89 Newton (14 oz) could be attained from a single tip. During in-situ experiments this method advanced the endoscope 25cm into the small intestine.

scholarly journals SPATIO-TEMPORAL SALINITY MONITORING OF THE GHAGHARA RIVER USING LANDSAT TIME-SERIES IMAGERY AND MULTIPLE REGRESSION ANALYSIS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 401-405
Author(s):  
M. Gašparović ◽  
S. K. Singh
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Critical Role ◽  
Measurement Data ◽  
Environmental Research ◽  
Water Salinity ◽  
P Value ◽  
Degree Polynomial ◽  
Statistical Parameters

Abstract. Nowadays, water has become one of the most important environmental issues for our ecosystem and is facing major challenges today. During the COVID-19 pandemic, the world has understood the need for good quality of water for sanitation and hygiene. Earth observing satellites plays a critical role in near-real-time detection and monitoring of land and water change and quality. This research presents a methodology for modeling and mapping water salinity in high spatial resolution. Data for modeling were measured on the five monitoring stations (Ayodhya, Basti, Birdghat, Paliakalan, and Turtipar) along the Ghagraha River Basin in India, during the period of 28 years (1985–2013). In this research, Electrical Conductivity (EC) as water salinity parameter modeled by means of Landsat 5 satellite imagery. All available Landsat 5 imagery were acquired on the same date as the ground measurement data was utilized for the modeling. Modeling was done based on linear, 2nd and 3rd polynomial multiple regression analysis. All statistical parameters for accuracy assessment show that 3rd degree polynomial performs better EC prediction capability than 2nd degree polynomial and linear regression. The 3rd degree polynomial multiple regression model RMSE, R2, MAE, p-value were 8.682, 0.993, 6.493, 0.008, respectively. The developed algorithm provides new knowledge that can be widely applied in various environmental research mapping and monitoring like water salinity. Also, this method allows rapid detection of water pollution, which has an important impact on human health, agriculture, and the environment.

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