High-risk Zone Research Articles

Assessment of the Safety of Transport of the Natural Gas–Ammonia Mixture

The decarbonisation of many sectors of the economy, including primarily the energy sector, results in the gradual elimination of hydrocarbon fuels, especially coal. During the transition period, it will be possible to use natural gas, the combustion of which is associated with lower carbon dioxide emissions. Further reduction in this emission is possible with the use of mixtures of natural gas with other gases, e.g., ammonia. Ammonia, widely used in many industries, has recently been described as the emission-free fuel of the future. However, both of these gases are hazardous substances. Natural gas is a flammable gas and ammonia is a toxic gas. This paper presents an assessment of the transport safety of natural gas (methane) and its mixture with ammonia. The uncontrolled release of these substances from a damaged gas pipeline may cause a fire or a toxic hazard. This work presents hazard zones arising in the event of such a failure and determines the impact of various mixture compositions on the level of the potential hazard. The level of risk related to the uncontrolled release of a mixture of natural gas and ammonia was analysed. It has been estimated that for pipelines with a diameter of 400 mm and a low-pressure mixture of methane and ammonia in the proportion of 50/50 v/v, the danger zone with the risk of loss of life above 1 × 10−3 is approximately 50 m. In the case of the same pipelines transmitting the mixture of these high-pressure gases, the high-risk zone may extend to approximately 175 m.

An artificial intelligence based framework to analyze the landside risk of a mountainous highway

The present study entails an artificial intelligence-based framework for landslide risk analysis of a highway infrastructure in the Himalayan region. In total, 241 landslide polygons that were inventoried for the study area. The spatial component of landslide susceptibility map was prepared by incorporating drainage density, TWI, geology, elevation and slope gradient as major contributing factors, in the certainty factor–random forest (CF-RF) hybrid model with accuracy of 0.928. The landslide hazard analysis was carried out by multiplying landslide spatial and temporal probabilities. The landslide vulnerability analysis of the highway stretch was carried out by integrating the elements at risk. The built-up area was extracted by using U-Net deep learning algorithm with an accuracy of 0.964. The landslide risk map of the highway stretch prepared by the multiplication of landslide hazard and vulnerability maps depicts that 16.78% and 6.25% of the study area falls in high and very high-risk zones, respectively.

Significance of Serum Apelin Levels as a Biomarker for Gastric Cancer Diagnosis.

Gastric cancer (GC) is one of the common lethal disease and the most common cancers worldwide and in Iran. North of Iran is known as a common area of gastric cancer and a high-risk zone in Iran. Apelin is a biomolecule that plays roles in various types of cancers. This study was designed to investigate the serum apelin-12 levels in patients with gastric cancer as a predictive marker and affordable noninvasive alternative. In this case-control study, the case group included 42 patients with gastric cancer who were diagnosed by endoscopy and pathological findings. The participants in the case group were compared with the control group including 43 healthy individuals with no history of gastric cancer in their first-degree relatives and visiting the lab for routine tests. Apelin-12 serum level was assessed using ELISA kit. Data were analyzed in SPSS V16.0 applying Fisher's exact test, Mann-Whitney U test, and t-test. Serum apelin-12 in patients with gastric cancer was found to be statistically lower than that in healthy individuals (p< 0.05). There were no significant differences between clinicopathological characteristics and apelin-12 expression. The median survival time in experimental and control groups was 16.0 months. In the current study, serum levels of apelin were significantly different between cases and controls.

GLOF hazard, exposure, vulnerability, and risk assessment of potentially dangerous glacial lakes in the Bhutan Himalaya

Deglaciation due to atmospheric warming has led to the formation and expansion of numerous glacial lakes, especially in the eastern Himalaya. Many of these glacial lakes are susceptible to glacial lake outburst floods (GLOFs), which can cause far-reaching impacts on downstream infrastructure and livelihoods. This study is a comprehensive assessment of GLOF susceptibility, hazard, exposure, vulnerability, and risk for four potentially dangerous glacial lakes (Bechung Tsho, Raphstreng Tsho, Thorthomi Tsho, and Lugge Tsho) located in the Lunana glacier complex of the Phochu basin in Bhutan. Exposure and risk assessments were based on modelled GLOF hydrodynamics, infrastructure data, population and housing census data. Among the four glacial lakes, Thorthormi Tsho and Lugge Tsho are relatively more susceptible to outburst floods than Raphstreng Tsho and Bechung Tsho. Outflow flood volumes from these lakes range between 6 × 105 and 3 × 108 m3 which can potentially impact over 16,000 people, two hydropower projects, numerous other infrastructures, and agricultural land up to 150 km downstream of the lakes. The GLOF exposed elements are largely in Punakha and Wangdue Phodrang districts, which are located 90 and 100 km downstream of the Lunana glacier complex respectively. Among 17 subdistrict blocks within the basin, one (Lunana) lies in a very high GLOF risk area, while 9 others are in the high GLOF risk zone. The study highlights the importance of multi-source data in improving the knowledge of downstream GLOF risk and serves as a base for improving GLOF risk reduction strategies in high mountain regions.

Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery

Floods are the natural disaster that occurs most frequently due to the weather and causes the most widespread destruction. The purpose of the proposed research is to analyze flood susceptibility mapping (FSM) in the Sulaymaniyah province of Iraq. This study employed a genetic algorithm (GA) to fine-tune parallel ensemble-based machine learning algorithms (random forest (RF) and bootstrap aggregation (Bagging)). Four machine learning algorithms (RF, Bagging, RF-GA, and Bagging-GA) were used to build FSM in the study area. To provide inputs into parallel ensemble-based machine learning algorithms, we gathered and processed data from meteorological (Rainfall), satellite image (flood inventory, normalized difference vegetation index (NDVI), aspect, land cover, altitude, stream power index (SPI), plan curvature, topographic wetness index (TWI), slope) and geographic sources (geology). For this research, Sentinel-1 synthetic aperture radar (SAR) satellite images were utilized to locate flooded areas and create an inventory map of floods. To train and validate the model, we employed 70 % and 30 % of 160 selected flood locations, respectively. Multicollinearity, frequency ratio (FR), and Geodetector methods were used for data preprocessing. Four metrics were utilized to assess the FSM performance: the root mean square error (RMSE), the area under the receiver-operator characteristic curve (AUC-ROC), the Taylor diagram, and the seed cell area index (SCAI). The results exhibited that all the suggested models have high accuracy of prediction, but the performance of Bagging-GA (RMSE (Train = 0.1793, Test = 0.4543)) was slightly better than RF-GA (RMSE (Train = 0.1803, Test = 0.4563)), Bagging (RMSE (Train = 0.2191, Test = 0.4566)), and RF (RMSE (Train = 0.2529, Test = 0.4724)). According to the ROC index, the Bagging-GA model (AUC = 0.935) was the most accurate in flood susceptibility modeling, followed by the RF-GA (AUC = 0.904), the Bagging (AUC = 0.872), and the RF (AUC = 0.847) models. The study's identification of high-risk flood zones and the most significant factors contributing to flooding make it a helpful resource for flood management.

Later Life as a Daring Experience: Factors Associated with Older Adults’ Risk Perception

ABSTRACT Risk perception refers to people’s subjective judgments about the possibility of negative occurrences and the extent to which they are concerned with them. Previous studies have found that older adults who were exposed to ongoing terror threats developed later-life and terror risk perceptions. These studies showed that high risk perception has negative psychological and physiological consequences. This study aimed to identify the factors associated with the development of both later-life risk perception and terror risk perception in later life. Data were collected via an online survey with 306 Internet users aged 50 years and over, half resided in a high-risk zone while the remainder lived in a low-risk zone. The Perceived Risk Scale, measures of depressive symptoms, life satisfaction, social support, spirituality, internet use, and personal background were applied. Low self-rated health was associated with terror and later-life risk perceptions, regardless of the risk zone. After controlling for personal background, only depressive symptoms significantly correlated with high risk perceptions. These findings suggest that older adults with poorer self-rated health, secular beliefs, and elevated depressive symptoms may be susceptible to developing high risk perceptions. Clinicians should encourage older adults to identify preserving resources to improve adjustment to late life stressors.

Estimating Climate-Sensitive Wildfire Risk and Tree Mortality Models for Use in Broad-Scale U.S. Forest Carbon Projections

This study utilizes forest inventory and climate attributes as the basis for estimating models of wildfire risk and associated biomass loss (tree mortality) and then demonstrates how they can be applied in calculating CO2 emissions related to the incidence of wildfires from U.S. forests. First, we use the full set of over 150,000 FIA plots of national forest inventory and climatic parameters to estimate models of the annual probability of wildfire occurrence and loss of live tree biomass. Then, maps of the spatial allocation of both the model-derived probability of wildfire occurrences and tree mortality are presented at the national level. The probability of wildfire occurrences and tree mortality were defined by a complex non-linear association of climatic conditions and forest ownerships, available aboveground biomass, and the age of the stand. Then, we provide an example of how these models can estimate potential CO2 emissions from wildfires by using FIA inventory data. We estimated 6.10, 16.65, 22.75, and 31.01 million metric tons of annual CO2 emissions with low, medium, high, and catastrophic combustion rates, respectively, from forests due to wildfire in the continental U.S. The wildfire risk and biomass loss due to tree mortality maps can be used by landowners, managers, public agencies, and other stakeholders in identifying high-risk wildfire zones and the potential CO2 emissions. These equations can also help estimate fire risk and associated CO2 emissions for future climate conditions to provide insight into climate change-related wildfire occurrences.

Analysis of Spatial and Temporal Variation of Noise Level at Intersections of a Mid-Sized City in India

This study aims to determine spatial and temporal noise variation and acoustical climate at intersections. Data monitoring comprises measurement of peak and off-peak hour variations at 19 intersections between February 2020 to September 2021 in Kanpur, India. Kanpur was proposed as a smart city in 2015 under National Smart Cities Mission. This work has been part of a National Level Project "IMPRINT" to document ambient noise levels for a Tier 2 city with highly heterogeneous traffic. Noise variations are primarily influenced by traffic flow, geometric characteristics, classified volume, and honking events. Frequent stoppage of vehicles for boarding and alighting of passengers also significantly affect noise levels. The results suggest that spatial variation of noise is larger (more than15 dBA) than temporal variation (less than 5 dBA). Noise risk zones are identified based on noise level alongside intersections. Zones are classified as safe, tolerable, low risk, moderate risk, high risk, and extremely high risk zones. Noise level crosses tolerable limit at most study locations, and some locations fall in high-risk zones. The study has highlighted influence of different parameters on spatial and temporal noise variation at intersections and remedial action plans for traffic noise abatement.

Living with Floods Using State-of-the-Art and Geospatial Techniques: Flood Mitigation Alternatives, Management Measures, and Policy Recommendations

Flood, a distinctive natural calamity, has occurred more frequently in the last few decades all over the world, which is often an unexpected and inevitable natural hazard, but the losses and damages can be managed and controlled by adopting effective measures. In recent times, flood hazard susceptibility mapping has become a prime concern in minimizing the worst impact of this global threat; but the nonlinear relationship between several flood causative factors and the dynamicity of risk levels makes it complicated and confronted with substantial challenges to reliable assessment. Therefore, we have considered SVM, RF, and ANN—three distinctive ML algorithms in the GIS platform—to delineate the flood hazard risk zones of the subtropical Kangsabati river basin, West Bengal, India; which experienced frequent flood events because of intense rainfall throughout the monsoon season. In our study, all adopted ML algorithms are more efficient in solving all the non-linear problems in flood hazard risk assessment; multi-collinearity analysis and Pearson’s correlation coefficient techniques have been used to identify the collinearity issues among all fifteen adopted flood causative factors. In this research, the predicted results are evaluated through six prominent and reliable statistical (“AUC-ROC, specificity, sensitivity, PPV, NPV, F-score”) and one graphical (Taylor diagram) technique and shows that ANN is the most reliable modeling approach followed by RF and SVM models. The values of AUC in the ANN model for the training and validation datasets are 0.901 and 0.891, respectively. The derived result states that about 7.54% and 10.41% of areas accordingly lie under the high and extremely high flood danger risk zones. Thus, this study can help the decision-makers in constructing the proper strategy at the regional and national levels to mitigate the flood hazard in a particular region. This type of information may be helpful to the various authorities to implement this outcome in various spheres of decision making. Apart from this, future researchers are also able to conduct their research byconsidering this methodology in flood susceptibility assessment.

Anthrax bio-surveillance of livestock in Arua District, Uganda, 2017–2018

Anthrax, caused by Bacillus anthracis, is a widespread zoonotic disease with many human cases, especially in developing countries. Even with its global distribution, anthrax is a neglected disease with scarce information about its actual impact on the community level. Due to the ecological dynamics of anthrax transmission at the wildlife-livestock interface, the Sub-Saharan Africa region becomes a high-risk zone for maintaining and acquiring the disease. In this regard, some subregions of Uganda are endemic to anthrax with regular seasonal trends. However, there is scarce data about anthrax outbreaks in Uganda. Here, we confirmed the presence of B. anthracis in several livestock samples after a suspected anthrax outbreak among livestock and humans in Arua District. Additionally, we explored the potential risk factors of anthrax through a survey within the community kraals. We provide evidence that the most affected livestock species during the Arua outbreak were cattle (86%) compared to the rest of the livestock species present in the area. Moreover, the farmers’ education level and the presence of people's anthrax cases were the most critical factors determining the disease's knowledge and awareness. Consequently, the lack of understanding of the ecology of anthrax may contribute to the spread of the infection between livestock and humans, and it is critical to reducing the presence and persistence of the B. anthracis spores in the environment. Finally, we discuss the increasingly recognized necessity to strengthen global capacity using a One Health approach to prevent, detect, control, and respond to public threats in Uganda.

Exploring Spatio-Temporal Variations of Ecological Risk in the Yellow River Ecological Economic Belt Based on an Improved Landscape Index Method.

Intense human activities have led to profound changes in landscape patterns and ecological processes, generating certain ecological risks that seriously threaten human wellbeing. Ecological risk assessment from a landscape perspective has become an important tool for macroecosystem landscape management. This research improves the framework and indices of the ecological risk assessment from a landscape perspective, evaluates the land use pattern and landscape ecological risk dynamics in the Yellow River Ecological Economic Belt (YREEB), analyzes the spatiotemporal variation, and identifies key areas for ecological risk management. The results indicate the following: The main land use types in the region are grassland and cropland, but the area of cropland and grassland decreased during the study period, and with the accelerated urbanization, urban land is the only land use type that continued to increase over the 20-year period. The ecological risk in the YREEB tended to decrease, the area of low ecological risk zones increased, while the area of high ecological risk zones gradually decreased. Most areas are at medium risk level, but the risk in central Qinghai and Gansu is obviously higher, and there is a dispersed distribution of local high- and low-risk zones. A total of 37.7% of the study area is identified as critical area for future risk management, and the potential for increased risk in these areas is high. These results can provide a basis for sustainable development and planning of the landscape and the construction of ecological civilization in ecologically fragile areas.

Age-dependent potential health risk assessment due to radioactive radon-222 in the environs of highly populated Durgapur industrial zone and nearby Bakreswar hot spring, India.

It is well known that exposure to a high concentration of radon-222 causes severe health effects, including cancer. The present article includes a survey on radon-222 in the water bodies of the city Durgapur [non-geothermal area] and nearby Bakreswar hot spring [geothermal province], India. The possible sources of radon from natural radionuclides and industries have been discussed in the article. Durgapur is a densely populated [~ 3680 persons/km2] industrial city with a population of 0.57 million. On the other hand, many tourists and pilgrims usually visit Bakreswar throughout the year. Age-dependent potential health risk assessments of the dwellers at Durgapur and Bakreswar due to radon exposure were performed for the first time. The present work is the first attempt to estimate the mean ingestion /and inhalation dose per annum, total effective dose [TED] per annum and the health risk assessment for cancer in adults, children and infants due to radon exposure at Durgapur and Bakreswar. In some cases, the values of TED exceed the permissible limit of 100 micro Sievert per year [µSv/y] as recommended by EUC and WHO. The radiation profile maps relating to radon concentration and associated contour maps of health risk factors [HRF] for the adults, children and infants were also prepared for the first time. Some areas were identified as high-risk zones, and the dwellers are prone to a high risk of cancer. The article also proposed several techniques to reduce radon in water and buildings. The authors also recommended banning some water sources to protect people from radon risk. This study will help scientists, policymakers, industrialists, farmers, government agencies and public health departments.

Effects of blood hematocrit on performance of endovascular coiling for treatment of middle cerebral artery (MCA) aneurysms: Computational study

Aneurysms with saccular cervical aneurysms are often treated with coiling embolism to prevent rupture and hemorrhage. This study attempted to examine the effects of coiling embolism on blood hemodynamics and bleeding from Middle cerebral artery (MCA) aneurysms. The pulsatile blood stream inside the heart is modeled using computational fluid dynamics by solving Reynolds Average Navier-stocks (RANS) equations. In this study, pressure, oscillatory shear index (OSI), and wall shear stress (WSS) on the sac wall are compared to reveal the high-risk zone at different times during the blood cycle. We also examine the role of coiling porosity in three different conditions of peak systolic blood hematocrit. The WSS value reaches its maximum near the neck of the sac, while the OSI value reaches its maximum near the dome of the aneurysm. Coiling also reduces OSI while having a limited impact on WSS near the neck, according to our results.

A novel methodological framework for risk zonation and source–sink response concerning heavy-metal contamination in agroecosystems

The accurate identification of high-risk zones and risk source–sink responses for heavy-metal (HM) contamination of agroecosystems remains challenging due to involving multiple environmental media such as soils, dustfall, and crops and a wide range of evaluation criteria and constraints. This study established a novel evaluation model based on the integration of Geographical Information Systems (GIS) and multi-criteria decision analysis (MCDA) to assess agroecosystem risk in the Lihe River watershed, China. Bivariate local indicators of spatial association (LISA) were adopted to explore the spatial interaction of risk sources and sinks with outputs ranging from 0.0003 (no risk) to 0.83 (high risk). Areas with moderate, considerable, and high risk constituted 67.4 % of the total land area, and only 1.8 % of the area was classed as low risk. Central urban and eastern areas around Taihu Lake were risk accumulation regions that needed more remedial attention. Risk cluster zones in the central urban area involved significant source–sink response relationships with the spatial distribution of industries, whereas eastern zones were linked to vehicular traffic distribution, accounting for 27.5 % and 16.5 % of the total area, respectively. This study provides a new methodological framework for the assessment of environmental risk, risk zonation, and risk source–sink spatial interaction in agroecosystems.

Resonant column and cyclic torsional shear tests on Sutlej river sand subjected to the seismicity of Himalayan and Shivalik hill ranges: A case study

The study of site-specific dynamic properties of soil holds vital importance in many geotechnical engineering problems for the region holding high active seismicity. The Sutlej River basin, a valley and high-risk seismic zone in the north-eastern part of the Punjab state, has been considered for the study. The site-specific shear modulus reduction curves and material damping ratio curves for a range of shear strain amplitudes have been developed under varying experimental conditions of confining pressure, relative density, and loading frequency using the resonant column (RC) tests and cyclic torsional shear (CTS) tests. The study addresses the usage of two testing approaches, i.e., resonant column test (RC) and cyclic torsional shear test (CTS), for the estimation of shear modulus and damping ratio values at varying shear strain amplitudes. The regression analysis has been performed for the two testing techniques viz. RC and CTS to study the sensitivity of shear modulus values and material damping ratio values towards varying experimental conditions. The shear modulus and damping ratio values determined from cyclic torsional shear tests were observed to have great dependency on the frequency of loading. The knowledge of site-specific dynamic properties will support practical interpretation for the geotechnical engineering problems in the region.

Dry, leeward regions support Colonization Period sites: Stratigraphy, dating, and geomorphological setting of one of the earliest habitations in the Hawaiian Islands

The earliest archaeological sites anchor discussions of the timing, speed, and direction of colonization of continents, single archipelagos, and individual islands, and new discoveries of the oldest sites often cause reevaluations of settlement models and culture-histories at various scales. Consequently, the oldest sites have continued to garner great interest amongst archaeologists worldwide. Here we report a suite of 21 AMS radiocarbon age determinations from a deeply stratified sandy mound habitation situated at an environmentally diverse “hot-spot” along the south-central leeward shore of Moloka‘i, Hawaiian Islands. Despite its ecological position in a dry leeward region – what some have called “high risk zones” – the ease of access and concentration of vital resources, including potable water, nutrient-rich gardening soils, and marine and freshwater biota was a magnet for early colonists. The faunal content, site stratigraphy, and geomorphological context of the Kawela Mound is described documenting rapid change in the dynamic landscape over several centuries. A Bayesian analysis of the Kawela Mound radiocarbon dates places earliest habitation at a modeled age of AD 1121–1262 (median AD 1210) making it one of the earliest habitations in the Hawaiian Islands. We provide a model for discovering early sites on leeward coastal Moloka‘I, which should be applicable elsewhere.

Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

The landscape of Pakistan is vulnerable to flood and periodically affected by floods of different magnitudes. The aim of this study was aimed to assess the flash flood susceptibility of district Jhelum, Punjab, Pakistan using geospatial model and Frequency Ratio and Analytical Hierarchy Process. Also, the study considered eight most influential flood-causing parameters are Digital Elevation Model, slop, distance from the river, drainage density, Land use/Land cover, geology, soil resistivity (soil consisting of different rocks and soil formation) and rainfall deviation. The rainfall data was collected from weather stations in the vicinity of the study area. Estimated weight was allotted to each flood-inducing factors with the help of AHP and FR. Through the use of the overlay analysis, each of the factors were brought together, and the value of drainage density was awarded the maximum possible score. According to the study several areas of the region based on the parameters have been classified in flood zones viz, very high risk, high risk, moderate risk, low risk, and very low risk. In the light of the results obtained, 4% of the study area that accounts for 86.25 km2 is at high risk of flood. The areas like Bagham, Sohawa, Domeli, Turkai, Jogi Tillas, Chang Wala, Dandot Khewra were located at the very high elevation. Whereas Potha, Samothi, Chaklana, Bagrian, Tilla Jogian, Nandna, Rawal high-risk zones and have been damaged badly in the flood history of the area. This study is the first of its kind conducted on the Jhelum District and provides guidelines for disaster management authorities and response agencies, infrastructure planners, watershed management, and climatologists.

A Global-Scale Ecological Niche Modeling of the Emerging Pathogen Serratia marcescens to Aid in its Spatial Ecology.

Serratia marcescensis a big emerging concern for human health and coral biodiversity. Spatial ecology and the influencing factors on pathogen ecology, however, remain unknown. The study forms the first global risk assessment ofS. marcescens. MaxEnt niche modeling was applied using two biotic and sixteen abiotic variables. The world was classified into five risk-level categories based on the pathogen ecology, and the world population exposed toS. marcescensinfection was then quantified. The prepared model showed an area under the curve value of 0.918 ± 0.028, implying excellent prediction ability. The highly and moderately suitable areas occupied around 0.52% and 17.9% of the total global land area. The order of probability of havingS. marcescens-related infections was Asia > North America > South America > Europe > Africa > Australia. Human population density and temperature were the most influential factors in the distribution. The moderate to high transmission risk zones contained 0.20% (1.61 billion people) of the human population. In brief, these results give novel insights into its spatial ecology and provide the risk maps that can be utilized to plan targeted strategic control measures against future invasions of this emerging pathogen.

Features of the Course of Various types of Stroke in Patients Exposed to Low-dose Radiation

BACKGROUND: There is limited number of studies about peculiarities of cardiovascular diseases in population of different region by the zone of radiation exposure risk. AIM: The aim of the study was to study the effect of radiation factor on the pathogenesis of stroke. MATERIALS AND METHODS: To study the in influence of radiation factor on pathogenesis of stroke, 358 stroke patients were distributed based on the place of their residence into corresponding zones of radiation risk: 53 patients lived in zone of extremely high radiation level (488–100 cSV, zone I): 75 - from the zone of maximal radiation exposure (35–100 cSV, zone II), 158 - from zone with high radiation exposure (35–7 cSV, zone III), and 72 patients were the residents of minimal radiation risk (1–7 cSV, zone IV). RESULTS: The study of coagulation hemostasis had revealed the significant increase of fibrinogen level in patients from zone I: 4.7 ± 0.14% versus 3.2 ± 0.11%, in patients living in minimal radiation risk zone (p &lt; 0.01). The patients from extremely high radiation risk had significant decrease in fibrinolysis time in comparison to patients from zone IV (p &lt; 0.05). The primary APS was diagnosed in 24 (6.7%) patients in total group of stroke patients (11 males and 13 females), from which 21 patients with ischemic stroke and 3 with hemorrhagic stroke. Leiden Va defect was found significantly more often in patients lived in high radiation risk zone (9.4%), in 13.5% stroke patients from zone II, in 13.2% patients lived in zone I, in comparison to 6.9% patients lived in zone IV. The patients from zone I had significantly higher level of plasma homocysteine in comparison to patients from other zones, (p &lt; 0.01). Furthermore, the significantly higher levels of plasma homocysteine were found in the group with maximal and high radiation exposure, in comparison to the group of patients from minimal risk zone (p &lt; 0.05). CONCLUSIONS: We can see the presence of indirect evidences of modifying influence of radiation factor on pathogenic mechanisms of stroke.

Formation of the near-face stress field under the influence of natural and technological factors

The mine face is a high-risk zone, where a loss of stability, an occurrence of dynamic and gas-dynamic processes, and an increase in the content of harmful gases are possible. All these negative consequences to certain extent depend on the near-face stress field. This article presents the results of numerical study of the peculiarities of its time-dependent formation in rocks with different properties, when using such means of reducing the outburst hazard as water injection and unloading cavities. It is shown that with the course of time in the rocks around the mine working, the area of increased difference of the stress tensor components spreads, which leads to the formation of cracks of varying degrees of intensity. The maximum component of the stress tensor increases; the abutment pressure zone is formed in the near-face region. The simultaneous increase of vertical stress in the abutment pressure zone and unloading of horizontal stress leads to displacement of the coal seam in the mine working and loss of the mine face stability. If the mine working is driven through hard rocks, Q* parameter values, as well as the maximum vertical stresses in the abutment pressure zone, are significantly increased. The zone of inelastic deformations begins to form with a long delay and has noticeably smaller dimensions. Hard rocks can withstand greater difference of the stress tensor components and greater vertical loads without breaking. Coal moistening leads to a significant decrease in the difference of the stress tensor components in the near-face zone of the coal seam. Values of Q* parameter in moistened coal in the three-meter near-face zone is 1.5–5 times lower than in the coal seam with a natural moisture content. The growth of the abutment pressure zone in moistened coal slows down; the zone of inelastic deformations becomes somewhat larger. The near-face stresses in the mine working with the unloading cavity is radically different from the previous cases. The peak values of Q* parameter and maximum stress are moved to the depth of unloading cavity. At the same time, both the difference of the stress tensor components and the maximum stress remain at a low level, which corresponds to moistened coal and in a long time interval ensures deformation of the near-face zone in the elastic mode. Unloading of this zone from rock pressure occurs in two directions: in the direction of the mine face and in the direction of the unloading cavity.