Computer Modeling of Carotid Endarterectomy With the Different Shape Patches and Prediction of the Atherosclerotic

Objective: The article describes a method for constructing geometric models of the carotid bifurcation and computer simulation of endarterectomy surgery with the patches of various configurations. The purpose of this work is to identify the areas of the greatest risk of restenosis in the constructed models and to conduct a comparative analysis of risk factors when using the patches of different widths and shapes. Methods: The method is demonstrated on a reconstructed model of a healthy vessel. Its building is based on a preoperative computed tomography study of a particular patient's affected vessel. The flow in the vessel is simulated by computational fluid dynamics using data from the patient's ultrasound Doppler velocimetry. Risk factors are assessed through the hemodynamic indices on the vessel wall associated with Wall Shear Stress. Results: The distribution of risk zones in the healthy vessel, presumably leading to its observed lesion (plaque), is analyzed. Comparative evaluation of 10 various patches implantation results is carried out and the optimal variant is determined. The proposed method can be used to predict the hemodynamic results of surgery using patches of various sizes and shapes.

Mapping the Forest Fire Risk Zones Using Artificial Intelligence with Risk Factors Data

Geographical information system data has been used in forest fire risk zone mapping studies commonly. However, forest fires are caused by many factors, which cannot be explained only by geographical and meteorological reasons. Human-induced factors also play an important role in occurrence of forest fires and these factors depend on various social and economic conditions. This article aims to prepare a fire risk zone map by using a data set consisting of nine human-induced factors, three natural factors, and a temperature factor causing forest fires. Moreover, an artificial intelligence method, k-means, clustering algorithm was employed in preparation of the fire risk zone map. Turkey was selected as the study area as there are social and economic varieties among its zones. Therefore, the forestry zones in Turkey were separated into three groups as low, moderate, and high-risk categories and a map was provided for these risk zones. The map reveals that the forestry zones on the west coast of Turkey are under high risk of forest fire while the moderate risk zones mostly exist in the southeastern zones. The zones located in the interior parts, in the east, and on the north coast of Turkey have comparatively lower forest fire risks.

Counteraction to misfeasance in taxation as a defense mechanism in the issue of tax fairness

The issue of counteraction to misfeasance in taxation as a defense mechanism of tax fairness is researched in the paper. The main objective of the state tax policy is determined that consists of the creation of a mechanism capable of counteracting misfeasance in taxation. It has been established that the state authorities should define clear, available and proper mechanisms that prevent misfeasance of taxation which violate the principles of taxation fairness. It is stated that the main security feature of fair taxation is monitoring and auditing activities, which considered as efficient measures. It was determined that completely new; previously unknown concepts and institutions related to counteracting misfeasance in taxation were introduced into the national tax legislation. The system for on-site inspections was also revised and the concept of the planned monitoring system was developed, which defines the criteria for tax risks, according to which audits are carried out and taxpayers are selected the field tax audits are planned for. These measures are aimed not only at increasing the effectiveness of monitoring work, but also at protection and promotion of conscientious taxpayers’ rights. The application of a simplified taxation system is indicated, as experience of reality shows, it allows not only to achieve a legal reduction in the tax burden, but also to use a special tax regime for illegal minimization of the tax burden on business. It is established that a key for increasing the efficiency of counteraction to misfeasance in taxation by taxpayers is the development of a tax monitoring methodology capable of identifying tax risk zones that indicate the use of taxpayers' schemes for their payment evasion. It is determined that the misfeasance by taxpayer has negative impact on national tax system. Such activity definitely violates the concept of taxation fairness as it is aimed at creating an illegal reduction in the tax burden. A number of measures have been identified in the Tax Code of Ukraine that can increase the effectiveness of counteraction to misfeasance in taxation.

ecological system of the digital educational environment as a new definition of modern education in the view of teachers

Digital technologies and products are a new reality of modern education, but the degree of their influence on the ecology of the digital educational environment has not been fully studied. The article examines teachers' ideas about a new definition of education - the ecology of the digital educational environment; about the impact of digital educational products on the cognitive, personal and activity sphere of students. Implement the tasks set, an anonymous online survey of teachers of secondary schools in Moscow, the Moscow region, Voronezh, Nizhny Novgorod, Samara was conducted using the Google form. The article, based on the analysis of teachers' ideas about the ecology of the digital educational environment, risk zones and their impact on the cognitive, personal and activity spheres of students are identified; criteria for assessing the impact of digital educational products on cognitive processes, personal qualities and motivation of students learning activities are determined; indicators for each type of criteria are considered. The article shows, in the view of teachers, digital educational products have an ambivalent impact on the development of a student: they act as a resource, a means of development, and at the same time, they are risky for the development of a student.

Karst Collapse Risk Zonation and Evaluation in Wuhan, China Based on Analytic Hierarchy Process, Logistic Regression, and InSAR Angular Distortion Approaches

The current study presents a detailed assessment of risk zones related to karst collapse in Wuhan by analytical hierarchy process (AHP) and logistic regression (LR) models. The results showed that the LR model was more accurate with an area under the receiver operating characteristic (ROC) curve of 0.911 compared to 0.812 derived from the AHP model. Both models performed well in identifying high-risk zones with only a 3% discrepancy in area. However, for the medium- and low-risk classes, although the spatial distribution of risk zoning results were similar between two approaches, the spatial extent of the risk areas varied between final models. The reliability of both methods were reduced significantly by excluding the InSAR-based ground subsidence map from the analysis, with the karst collapse presence falling into the high-risk zone being reduced by approximately 14%, and karst collapse absence falling into the karst area being increased by approximately 6.5% on the training samples. To evaluate the practicality of using only results from ground subsidence maps for the risk zonation, the results of AHP and LR are compared with a weighted angular distortion (WAD) method for karst risk zoning in Wuhan. We find that the areas with relatively large subsidence horizontal gradient values within the karst belts are generally spatially consistent with high-risk class areas identified by the AHP- and LR-based approaches. However, the WAD-based approach cannot be used alone as an ideal karst collapse risk assessment model as it does not include geological and natural factors into the risk zonation.

"This is Calabar South; shine your eyes" : Urbanization and Insecurity in Nigeria, case study of Calabar metropolis and its effects on state- society relations

It is common to describe some parts (especially the satellite zones) in the metropolitan areas of Nigeria as hot spots for crimes or high-risk zones: Ikorodu in Lagos, Ikwere in Rivers State, Warri in Delta State, etc. From this context, it is obvious that some areas possess characteristics that encourage or entrench crime and violence. This paper focuses on one of such contemporary high-risk zones in Cross River State, Nigeria: the Calabar South. We argue that the accelerated growth of urbanization has amplified the demand for key services in Calabar metropolis and that the provision of shelter and basic services such as water and sanitation, education, public health, employment, and transport has not kept pace with this increasing demand. Therefore, accelerated and poorly managed urbanization has resulted in various types of atmospheric, land and water pollution, and violent crimes which in turn jeopardize human security in the area and creates hate-sentiments between the dwellers of Calabar South and the administrative authorities. We utilize qualitative research methodology. Oral interviews and questionnaires serve as primary sources utilized while an extensive literature represents the secondary sources utilized here-in. We arrived at the conclusion that the increased environmental, social and economic problems associated with rapid urbanization are the causes of high-risk zones.

Risk and Vulnerability Assessment: A Case Study of Pakistan

Climate change has put the planet earth on high risk due to flash, riverine flooding and droughts. Unprecedented frequent flooding, hurricanes, droughts and heavy snowfalls can be witnessed in the past few decades. Now no country can declare itself safe from the negative impacts of changing climate. To reduce the risk of potential damages, vulnerability and risk assessment can give a clear picture of a particular region regarding a specific hazard. It will help the administration to address those areas which are highly at risk due to a certain hazard so as to minimize collateral damages in future. In Khyber Pukhtoonkhwa, Nowshera was one of the most affected districts. It has destroyed building stock, livestock and crops in most parts of the district. To minimize these losses in future, this research has been carried out to assess the current condition of building stock in Nowshera Cantt and Nowshera City area. This research explores in detail the building stock vulnerability and associated risk. This research has found that the flood reoccurrence time period is 7 years for zone 1and 7. While other zones 2, 3,4,5,6,8 and 9 have 81 years of reoccurrence time period. Based on the physical vulnerability, this research found that there are five types of buildings in the study area. Vulnerability of Type 1 to 5 are varying from strong to weak according to its structures having RCC roof, strong walls, plain concrete / tiles floor. Flood risk map has been produced on the basis of flood frequency and typology of high frequency structures in that particular area. The research explicitly shows different areas in risk map according to the level of risk i.e. from low to high risk zones. This research has found that binding material is the major factor in structural damages in the study area.

A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data

(1) Background: Hurricane events are expected to increase as a consequence of climate change, increasing their intensity and severity. Destructive hurricane activities pose the greatest threat to coastal communities along the U.S. Gulf of Mexico and Atlantic Coasts in the conterminous United States. This study investigated the historical extent of hurricane-related damage, identifying the most at-risk areas of hurricanes using geospatial big data. As a supplement to analysis, this study further examined the overall population trend within the hurricane at-risk zones. (2) Methods: The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model and the HURRECON model were used to estimate the geographical extent of the storm surge inundation and wind damage of historical hurricanes from 1950 to 2018. The modeled results from every hurricane were then aggregated to a single unified spatial surface to examine the generalized hurricane patterns across the affected coastal counties. Based on this singular spatial boundary coupled with demographic datasets, zonal analysis was applied to explore the historical population at risk. (3) Results: A total of 777 counties were found to comprise the “hurricane-prone coastal counties” that have experienced at least one instance of hurricane damage over the study period. The overall demographic trends within the hurricane-prone coastal counties revealed that the coastal populations are growing at a faster pace than the national average, and this growth puts more people at greater risk of hurricane hazards. (4) Conclusions: This study is the first comprehensive investigation of hurricane vulnerability encompassing the Atlantic and Gulf Coasts stretching from Texas to Maine over a long span of time. The findings from this study can serve as a basis for understanding the exposure of at-risk populations to hurricane-related damage within the coastal counties at a national scale.

A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China

Rapid urban expansion has brought new challenges to firefighting, with the speed of firefighting rescue being crucial for the safety of property and life. Thus, fire prevention and rescuing people in distress have become more challenging for city managers and emergency responders. Unfortunately, existing research does not consider the negative effects of the current spatial distribution of fire-risk areas, land cover, location, and traffic congestion. To address these shortcomings, we use multiple methods (including geographic information system, multi-criterion decision-making, and location–allocation (L-A)) and multi-source geospatial data (including land cover, point-of-interest, drive time, and statistical yearbooks) to identify suitable areas for fire brigades. We propose a method for identifying potential fire-risk areas and to select suitable fire brigade zones. In this method, we first remove exclusion criteria to identify spatially undeveloped zones and use kernel density methods to evaluate the various fire-risk zones. Next, we use analytic hierarchy processes (AHPs) to comprehensively evaluate the undeveloped areas according to the location, orography, and potential fire-risk zones. In addition, based on the multi-time traffic situation, the average traffic speed during rush hour of each road is calculated, a traffic network model is established, and the travel time is calculated. Finally, the L-A model and network analysis are used to map the spatial coverage of the fire brigades, which is optimized by combining various objectives, such as the coverage rate of high-fire-risk zones, the coverage rate of building construction, and the maintenance of a sub-five-minute drive time between the proposed fire brigade and the demand point. The result shows that the top 50% of fire-risk zones in the central part of Wuhan are mainly concentrated to the west of the Yangtze River. Good overall rescue coverage is obtained with existing fire brigades, but the fire brigades in the north, south, southwest, and eastern areas of the study area lack rescue capabilities. The optimized results show that, to cover the high-fire-risk zones and building constructions, nine fire brigades should be added to increase the service coverage rate from 93.28% to 99.01%. The proposed method combines the viewpoint of big data, which provides new ideas and technical methods for the fire brigade site-selection model.