Dangerous Hazards Research Articles

Computer vision based early fire-detection and firefighting mobile robots oriented for onsite construction

Fires are one of the most dangerous hazards and the leading cause of death in construction sites. This paper proposes a video-based firefighting mobile robot (FFMR), which is designed to patrol the desired territory and will constantly observe for fire-related events to make sure the camera without any occlusions. Once a fire is detected, the early warning system will send sound and light signals instantly and the FFMR moves to the right place to fight the fire source using the extinguisher. To improve the accuracy and speed of fire detection, an improved YOLOv3-Tiny (namely as YOLOv3-Tiny-S) model is proposed by optimizing its network structure, introducing a Spatial Pyramid Pooling (SPP) module, and refining the multi-scale anchor mechanism. The experiments show the proposed YOLOv3-Tiny-S model based FFMR can detect a small fire target with relatively higher accuracy and faster speed under the occlusions by outdoor environment. The proposed FFMR can be helpful to disaster management systems, avoiding huge ecological and economic losses, as well as saving a lot of human lives.

Modelling study on pedestrian evacuation dynamics considering exit selection behaviour under flood disaster

Flood spreading in metro stations is a dangerous hazard that frequently causes casualties and property losses. However, pedestrian evacuation under flood spreading scenarios has not been fully investigated. To fill this gap,we propose an extend Floor-Field model incorporating flood spreading and exit selection behaviour of individuals. In the model, the dynamic flood spreading process on metro platforms is expressed by using a simulation software named Mike21. The optimal exit selected by pedestrians in each step is decided on three factors, that is pedestrian density around the exit, pedestrian distance to the exit, and water depth at the exit. Meanwhile, the movement speed of pedestrain also changes with the water depth at each time step. Based on this, the transition probability to neighbor cell including static field, dynamic field, height field, and water flow field is calculated. This results in a flood evacuation model considering the pedestrian's behaviour when choosing an exit. The effects of flooding, pedestrian density, different exit selection behaviours, water flow field, and inlet flow on evacuation were thoroughly analysed. The analysis demonstrates that the likelihood of flooding significantly impacts the evacuation of pedestrians from the subway station; the more flooding is taken into account, the more influential the impact. In addition, the effect of inlet flow on evacuation is also noteworthy; considering exit selection behaviour can significantly increase the effectiveness of evacuation. The study's findings can be used to develop evacuation plans for flooded metro stations.

Landslide susceptibility and building exposure assessment using machine learning models and geospatial analysis techniques

Landslides are among the most dangerous hazards in Asia, posing a significant threat to human lives, infrastructure, and sustainable development. Landslide susceptibility maps provide useful insights into hazard potential but lack quantitative exposure assessments to develop targeted mitigation strategies and resource allocation. This study aims to propose an integrated approach for landslide hazards and exposure evaluation using machine learning models on the Google Earth Engine environment and geospatial analysis techniques. A geospatial database was established to predict hazards and evaluate exposure, including data on topography, geology, hydrology, climate features, land use, and building data. The landslide susceptibility map was created with advanced machine-learning algorithms, including Classification And Regression Tree (CART), Random Forest (RF), Gradient Boosting (GB), and Support Vector Machine (SVM). The ROC curve and the Wilcoxon signed-rank test were employed to evaluate the performance differences among the CART, GB, RF, and SVM models. The results indicated that the RF model demonstrated the highest performance, leading to its selection for creating a landslide susceptibility map. Landslide exposure was evaluated by overlaying the landslide susceptibility map with building data to quantify the number of affected houses by landslides across districts and communes. The analysis results identified the Cho Don district as the most exposed, with 46,237 households located in high and very high landslide susceptibility zones, followed by Ba Be district (39,631 households), Bac Kan city (37,266 households), Bach Thong district (28,495 households), Cho Moi district (28,436 households), Na Ri district (17,723 households), Ngan Son district (14,142 households), and Pac Nam district (13,034 households). These findings enable the identification of the potential consequences of landslides on infrastructure, human settlements, and livelihoods, contributing to the promotion of disaster reduction and prevention strategies.

Three-Dimensional Rockslide Analysis Using Unmanned Aerial Vehicle and LiDAR: The Castrocucco Case Study, Southern Italy

Rockslides are one of the most dangerous hazards in mountainous and hilly areas. In this study, a rockslide that occurred on 30 November 2022 in Castrocucco, a district located in the Italian municipality of Maratea (Potenza province) in the Basilicata region, was investigated by using pre- and post-event high-resolution 3D models. The event caused a great social alarm as some infrastructures were affected. The main road to the tourist hub of Maratea was, in fact, destroyed and made inaccessible. Rock debris also affected a beach club and important boat storage for sea excursions to Maratea. This event was investigated by using multiscale and multisensor close-range remote sensing (LiDAR and SfM) to determine rockslide characteristics. The novelty of this work lies in how these data, although not originally acquired for rockslide analysis, have been integrated and utilized in an emergency at an almost inaccessible site. The event was analyzed both through classical geomorphological analysis and through a quantitative comparison of multi-temporal DEMs (DoD) in order to assess (i) all the morphological features involved, (ii) detached volume (approximately 8000 m3), and (iii) the process of redistributing and reworking the landslide deposit in the depositional area.

Structuring and Development of Poultry Sectors in Algeria: Limits of Modernization Policies: The Case of the “Turkey” Sector (2000-2020)

Background: The Algerian poultry industry has had the biggest growth in the country. The purpose of this study is to demonstrate that the modernization of the poultry industry, driven by the policies pertaining to poultry that Algeria enacted between 2000 and 2020, did not result in the creation of governance structures that were in line with the demands of improving the performance of these industries. This theory is supported by the “Turkey” sector example. Methods: In order to explain Algeria’s poor governance of the poultry industry, the new institutional economy (NIE) invests within the framework of the “Sector” approach. The 1,288 units of turkey farms dispersed among 38 wilayas, or 80% of all the wilayats in the nation representing all possible production regions, were the subject of surveys conducted on turkey farms between 2015 and 2017. Result: The “atomized” breeding structures, the importance of “independent” breeding, the lack of economies of scale, the low level of development of integrated production and the absence of hybrid institutional arrangements are what set the “Turkey” sector apart, according to an analysis of its organizational structures. All of these things contribute to high production and transaction costs. Nonetheless, the “turkey” sector’s lack of coordination mechanisms continues to be a serious problem that causes abrupt changes and volatility in producer pricing, which in turn causes cyclical crises. These crises are a source of uncertainty and dangerous hazards, especially for small farms.

A Model generation method and iteration algorithm for optimising fire protection thickness

With temperatures rising above 1000 °C within 5 min, hydrocarbon fire causes rapid strength degradation of structural steel members. It is among the most dangerous hazards, such as boiling liquid expanding vapour explosion (BLEVE) in the oil and gas industry. Intumescent coating as passive protection is widely adopted to prevent the steel structure from material property reduction. However, when optimising fire protection with heat transfer simulation, repetitive modelling work and lacking recalculation principle hinder productivity improvement. This method is developed to generate steel beam models and provides an effective algorithm to optimise coating thickness considering the temperature of a specific region. The main functions of the method include:•Providing section dimensions, initial insulation thickness, target temperature and heating time, temperature allowance and mesh size as variables.•Automatically generating the Abaqus steel beam model under 3-side heating conditions.•Effective iteration algorithm to modify fire protection thickness: test containing 38 Universal beam sections with a 5 °C allowance below target shows that 55.2% were completed within five iterations and 76.3% were completed within eight iterations.

Navigating precarious foodscapes: discourses and everyday practices of eating chicken meat in Japan

ABSTRACT As consumers grow distanced from food production, prominent discourses increasingly emphasize the importance of ethical food. These dynamics are indicative of precarious foodscapes, a concept that I delve into through a case study of discourses and everyday practices of eating chicken in Japan. For discourses, I contrast the media’s treatment of two incidents: a 2016 domestic food incident in which scores were poisoned scores that received scant media coverage and a 2014 foreign incident in which meat was mishandled in a Chinese factory that received extensive media coverage as a food scandal. For everyday practices, I analyze 22 focus groups in which participants discussed the strategies and motivations that they draw on to navigate Japanese foodscapes. Participants strongly preferred domestic chicken over imported chicken. Raw chicken emerged as an alluring delicacy for some and a dangerous hazard for others. Prominent discourses informed participant’s embodied sense of trust and shaped the factors they perceived to be (un)important when buying food. I argue that discourses of ethical food and consumer strategies for navigating precarious foodscapes vary based on context. Close attention to context is necessary to navigate the barriers introduced by precarious foodscapes and continue to build transformative linkages across food systems.

Особливості формування безпекових компетентностей в умовах воєнного стану

An urgent task, both under martial law and in the post-war period, is to develop safety competencies among higher education students by increasing their awareness of hazards and risk factors. According to the results of two sociological surveys conducted in December 2020 and December 2022, it was revealed that under martial law, young peoples’ assessment of hazards and risk factors is more unanimous compared to the pre-war period, and the refined indicator of awareness of hazards and risk factors is somewhat higher. Continuous threats to the safety of young people caused by military actions have enhanced the motivation to increase awareness of dangers in everyday life. The analysis of the results of a statistical assessment of the awareness of modern environment hazards and risk factors among young people indicates certain changes that follow naturally from the actual state of the country at war. A new wartime reality for Ukrainians resulted in the expected highest awareness rate and, simultaneously, the highest level of unanimity in its assessment. Moreover, the coronavirus disease (COVID-19) is recognized as one of the most dangerous hazards, but the unanimity in its assessment is much lower. It was also determined that the most dangerous and safest factors are perceived more unanimously. Human behavior generally depends on a set of existing hazards and risk factors, and their adequate awareness. Distortion of awareness of certain factors’ danger would lower the level of personal safety. Therefore, a balanced and adequate awareness of existing hazards and risk factors is an essential point in forming safety competencies among higher education students. Further development of the approaches to form higher education students’ safety competencies in wartime conditions is essential to increase the efficiency of the educational process in the post-war period. Keywords: safety competencies, level of danger, awareness of hazards and risk factors, risk-oriented approach, assessment.

An efficient diagnostic strategy for intermittent faults in electronic circuit systems by enhancing and locating local features of faults

Due to their short duration, concealability, and random occurrence, intermittent faults have become the most dangerous hazard in electronic circuit systems. However, existing intelligent diagnostic methods often struggle to provide substantial effectiveness for such objects. This article proposes a scheme to enhance the output signal of electronic circuits to make the features more intuitive and facilitate fault feature mining, and designs a scheme to mine tiny fault features from global signals. First, the circuit’s output signal undergoes an S-transform to obtain its time-frequency domain characteristics. Next, a sequence and excitation networks attention module is employed to allocate weights to different channels. Finally, the aforementioned output is used as input to the Swin transformer framework to thoroughly explore fault features. Three electronic circuits are used as experimental circuits to test the proposed method. The experiment shows that the proposed diagnostic method is fast and has an accuracy of over 97%. Therefore, the effectiveness of the designed strategy that includes multiple attention mechanisms in mining intermittent fault features in electronic circuit systems has been demonstrated.

Laser-assisted direct coating of Graphene-Based films on plastic substrates with bactericidal properties

Bacterial growth on surfaces is a substantial problem in medical equipment, fresh food storage, and water supply industries. Antibacterial coatings offer a preferred method to prevent this dangerous hazard. However, to provide a complete solution, the developed coating must not only efficiently prevent bacterial growth and consist of cost-effective, stable, and bio-friendly materials but also offer a simple coating method. In this work, we use novel laser processing that offers significant advancements, including (1) fast, single-step, and waste-free synthesis, (2) allowing direct printing of graphene over any substrate, including thermal-sensitive materials (i.e., polymers), and (3) micron-resolution patterning of the coated materials. We use an intense laser beam to fabricate metal-oxide/graphene nanoparticle composite films directly on plastic surfaces. The metal-oxide nanoparticles (cobalt and copper) are tested for antibacterial activity. Due to the combined formation, the metal-oxide nanoparticles are highly dispersed and firmly adhered to the graphene matrix. Notably, the structure and properties of the laser product, such as the nanoparticle's size and the graphitization level, can be controlled by tuning laser parameters. The composite coatings demonstrate excellent antibacterial activity. Studying substrates coated with different metal compositions found that 4.5–5 % of metal contents have antibacterial activity (percentage inhibition) by 89 % (PBS). Additionally, leaching studies demonstrate that the fabricated substrates are stable in different pH solutions.

In situ detection of lithium-ion batteries by ultrasonic technologies

Overcharging is one of the most frequent and dangerous hazards in lithium-ion batteries, which not only increases the risk of battery failure but also causes thermal runaway and catastrophic outcomes. In this work, we combine the A-scan and 2D/3D Total Focusing Method (TFM) ultrasonic detecting technologies to in situ monitor and image the battery's abnormal behavior under overcharging. The ultrasound wave behavior during the charge/discharge process at various current densities and cut-off voltages is demonstrated first to obtain a general comprehension of its relations to the lithiation/de-lithiation, volume changes, concentration polarization, and temperature elevation process. Moreover, the early-warning characteristic of ultrasonic detecting has been proven in overcharging. The onset and location of side reactions can be precisely and facilely detected by ultrasonic detecting technologies as early as 102% SoC after the overcharging begins, and various overcharged states can be differentiated with an accuracy of 0.4% SoC. The astonishing precision of ultrasonic detecting technologies allows a timely remedy to be applied to batteries, thus elongating batteries’ lifespan. In conclusion, the ultrasonic detecting technique is excellent at not only accurately detecting the battery state but also acting as an alarm for latent danger.

Phytotoxicity of Rich Oxygenated Terpenes Essential Oil of Prosopis farcta against the Weed Dactyloctenium aegyptium

Weeds are considered the main reason for crop yield loss in the world. Weed control and management include various treatments such as cultural, physical, chemical, and biological methods. Chemical control of weeds is the most common method; however, the application of commercial synthetic herbicides caused several dangerous hazards in the environment including the appearance of resistant weed biotypes. Prosopis farcta (Banks & Sol.) J.F.Macbr. (Family: Fabaceae), is a common weed plant in the Middle East, where it is hard to eliminate due to its deep and overlapped roots. On the other side, it has many traditional uses around the world. Herein, the essential oil (EO) of P. farcta above-ground parts was extracted via hydrodistillation techniques and then analyzed using gas chromatography-mass spectroscopy (GC-MS). From the GC-MS analysis, 47 compounds were identified with a relative concentration of 98.02%, including terpenes as the main components (95.08%). From overall identified compounds, cubenol (19.07%), trans-chrysanthenyl acetate (17.69%), torreyol (8.28%), davana ether (3.50%), camphor (3.35%), and farnesyl acetone (3.13%) represented the abundant constituents. Furthermore, the phytotoxic activity of the P. farcta EO was assessed against the weed Dactyloctenium aegyptium (L.) Willd. The EO of P. farcta, at a concentration of 100 µL L−1, significantly inhibited the germination, seedling shoot growth, and seedling root growth by 64.1, 64.0, and 73.4%, respectively. The results exhibited that the seedling root growth is the most affected followed by the seed germination and seedling shoot growth with respective IC50 at 64.5, 80.5, and 92.9 µL L−1. It can be concluded that weeds are not absolutely harmful, but they may have beneficial uses, such as, for example as a source of phytochemicals with application in weed control practices (bioherbicides). It is advised to conduct additional research to characterize the allelopathic action of the major chemicals in their pure form, either alone or in combination, against a variety of weeds.

Impact of disposable mask microplastics pollution on the aquatic environment and microalgae growth.

The COVID-19 pandemic has mandated people to use medical masks to protect the public. However the improper management of disposable mask waste has led to the increase of marine pollution, in terms of water quality, and the decline in aquatic microorganisms. The aim of this research was to investigate the impact of disposable mask waste on fresh water and microalgae biomass quality. Disposable masks (untreated or treated with Enterococcus faecalis) were placed in 10-L glass reactors containing fresh water or water containing algal Chlorella sp. and its growth supplements (Chlorella medium) (four 10-L reactors in total) and kept in controlled conditions for 3months. Water and biomass yield quality were evaluated using water quality analysis, spectroscopy, scanning electron microscopy (SEM), and proximate lipid and protein analysis. Disposable masks, incubated in either fresh water or Chlorella medium, affected several water quality parameters such as chemical oxygen demand (COD), biological oxygen demand (BOD), dissolved oxygen (DO), and pH. Microplastic identification revealed that some fibers were present in the water following a 100-day treatment process. Fourier transform-infrared spectroscopy (FTIR) analysis was used to determine the change in important, organic functional groups and highlighted the disappearance of a peak at 1530cm-1 corresponding to the primary protein (C-N) and the appearance of new peaks at 1651cm-1 and 1270cm-1 corresponding to methyl alcohol (CH2OH) and ketone (C = O), respectively. This indicated the detrimental effect of disposable mask fragmentation on the biomass quality. The SEM investigation has shown a damage to the surface membrane of Chlorella sp. cells. Altogether, disposable masks decreased the water quality and damaged microalgae by inhibiting their growth. Therefore, the disposable mask contaminated by various microbes, after being used by a human, may be one of the most dangerous hazards to the environment.

Numerical study of water wave generation by granular-liquid mixture collapse using two-phase material point method

Debris flow sliding with high-speed and its possible interactions with a confined water body may lead to dangerous hazard. Therefore, it is important in practical applications to accurately predict the granular-liquid flows and their possible interactions with the water body. A two-phase material point method (MPM) with double-point formulation was applied in this paper to simulate the generation of the water wave by granular-liquid mixtures collapse into water. In our study, the debris flow was idealized as a granular-liquid mixture, the liquid phase was considered as a compressible viscous fluid, the granular response was modeled using the Mohr–Coulomb yield criterion and the granular-liquid interaction forces including viscous drag force and buoyancy force. Two experimental tests of dam-breaking flow and the wave generation by a dry granular column collapse were simulated, the accuracy and effectiveness of the proposed approach has been proven by comparing the numerical results with experimental data. We performed an experiment of saturated granular column collapsed into water and the test results were used to validate the proposed method, then applied the validated method to simulate the water wave generation by granular-liquid mixture collapse into water and investigate the effects of the initial degree of saturation defined as the initial depth ratio of water to granular material on the time evolution of the granular front and the amplitude of leading wave.

“Scour bed morphology caused by partially free and submerged flow at pipe culvert”

ABSTRACT Scour is the most dangerous hazard that can affect waterways, since it is responsible for more than sixty percent of the failures that have been reported, including the scour that is caused by floods at water structures. The influence of partially free and submerged flow at a pipe culvert on scour bed morphology was experimentally studied. In addition, three different diameters of the pipe culverts that were used with four Froude numbers for seven different water depths upstream of the culverts were included. The results show that at low Froude number for different heights of water, upstream and downstream are slightly different regarding the height of the water. To illustrate, at high Froude numbers, the height of the water has a very slight difference upstream, whereas there is a large and noticeable decrease in water heights and an increase in velocity downstream. When the height of water increases, the scour depth increases upstream and downstream. The increase downstream is more noticeable. That is because the scour increases when the submergence ratio and water velocity increase, in addition to the water depths with high submergence ratios cause a larger scour hole.

Varying genesis and landfall locations for North Atlantic tropical cyclones in a warmer climate

Tropical cyclones (TCs) are one of the most dangerous hazards that threaten U.S. coastlines. They can be particularly damaging when they occur in densely populated areas, such as the U.S. Northeast. Here, we investigate seasonal-scale variations in TC genesis and subsequent first landfall locations of > 37,000 synthetic TCs that impact the U.S. Northeast from the pre-industrial era (prior to 1800) through a very high emissions future (RCP8.5; 2080–2100). TC genesis in the Main Development Region decreases across all parts of the season from the pre-industrial to the future, with the greatest decreases in the proportion of genesis (up to 80.49%) occurring in the early and late seasons. Conversely, TC genesis in a region near the U.S. southeast coast increases across all parts of the season from the pre-industrial to the future, with the greatest increases in the proportion of genesis (up to 286.45%) also occurring in the early and late seasons. Impacts of changing TC genesis locations are highlighted by variations in where TCs make their first landfall over the same time periods, with an increase in landfalls along the mid-Atlantic seaboard from Delaware to North Carolina during all parts of the season from the pre-industrial to the future.

Public Health Preparedness for Extreme Heat Events.

Heat is a dangerous hazard that causes acute heat illness, chronic disease exacerbations, adverse pregnancy outcomes, and a range of injuries. Risks are highest during extreme heat events (EHEs), which challenge the capacity of health systems and other critical infrastructure. EHEs are becoming more frequent and severe, and climate change is driving an increasing proportion of heat-related mortality, necessitating more investment in health protection. Climate-resilient health systems are better positioned for EHEs, and EHE preparedness is a form of disaster risk reduction. Preparedness activities commonly take the form of heat action plans (HAPs), with many examples at various administrative scales. HAP activities can be divided into primary prevention, most important in the pre-event phase; secondary prevention, key to risk reduction early in an EHE; and tertiary prevention, important later in the event phase. After-action reports and other postevent evaluation activities are central to adaptive management of this climate-sensitive hazard. Expected final online publication date for the Annual Review of Public Health, Volume 44 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Fire Detection Approach Using A Deep Learning Approach

Fire destroys everything on its way. It is the most dangerous hazard that causes disasters. It can be started from a small ignition which could lead to a big loss or unwanted disaster. People lose their lives from fires. According to National Fire Protection Association (NFPA), the reported fire cases were nearly 1,400,000 in 2020 while those cases caused almost 3,500 civilian deaths. In addition, the number of civilians injured from fires is around 15,000 and the estimated properties damage is around 21 billion in US Dollars. Thus, detection of fire has become a very important topic especially due to the rapid and evolving of technology. In this paper, a simple, fast and accurate method of fire detection using deep learning is proposed. This method is developed based on image processing techniques. If the fire is not detected early, then the Oxygen level decreases which leads to suffocation. So, this method can help us by detecting fires at an early stage. This approach filters an image into pixels based on thresholds according to some features such as colors, immobility source and flame texture with its reflection. MATLAB is used as a simulation tool to conduct several experiments to verify the effectiveness of the proposed method. The obtained results show that the accuracy was over 97% when applied on more than 700 images for training and testing purposes.

Review of Vibration Control Strategies of High-Rise Buildings.

Since the early ages of human existence on Earth, humans have fought against natural hazards for survival. Over time, the most dangerous hazards humanity has faced are earthquakes and strong winds. Since then and till nowadays, the challenges are ongoing to construct higher buildings that can withstand the forces of nature. This paper is a detailed review of various vibration control strategies used to enhance the dynamical response of high-rise buildings. Hence, different control strategies studied and used in civil engineering are presented with illustrations of real applications if existing. The main aim of this review paper is to provide a reference-rich document for all the contributors to the vibration control of structures. This paper will clarify the applicability of specific control strategies for high-rise buildings. It is worth noting that not all the studied and investigated methods are applicable to high-rise buildings; a few of them remain limited by many parameters such as cost-effectiveness and engineering-wise installation and maintenance.

Seismic Performance of Multi Story Building with Different Base Isolators

Abstract: Earthquakes are one of nature's most dangerous hazards; throughout history, they have resulted in substantial loss of life and serious property damage, particularly to man-made structures. Seismic activity of large magnitude is a major source of risk for all types of constructions. We apply unique methodologies based on performance-based seismic design to protect structures from earthquakes. One way for reducing the influence of large-scale vibration created during an earthquake is the base isolation method. Seismic isolation can be used to give an efficient solution for a variety of seismic design difficulties according to well-established practices that have been examined by several researchers. It compares the performance of two types of isolators: Lead Rubber Bearing (LRB) and Friction Pendulum Bearing (FPB). G+12 R.C structure is taken in this study & Time History analysis is performed with ETABS software. Story drift and Story force are compared for the building with the base isolator against the building with the fixed base. In comparison with a fixed base building, parameters are changed in each direction due to the presence of an isolator. The analysis examines the characteristics and the effects of base isolation on structures with the Uttarkashi earthquake.