Dangerous Situations Research Articles

Risk Assessment for the Development of Emergency Scenarios for Tram Driver Training

(1) Background: This article presents research results from a project to develop a simulator and training program for tram drivers based on virtual reality tools. This article aims to present the research results on the risk assessment of adverse events to develop training scenarios for tram drivers. (2) Methods: The research methodology involved four steps, including the identification of adverse events based on interviews with experts, estimation of risk parameters, risk assessment using fuzzy logic, and risk evaluation to identify events recommended for the training program. (3) Results: Thirteen adverse events related to tram driving were identified and ranked according to the proposed classification. A risk assessment was then performed for the selected group of events using fuzzy logic models. The results made it possible to recommend situations that should be mapped in the virtual world as part of a tram driver training program. (4) Conclusions: The results made it possible to distinguish a group of events that should constitute the training area dedicated to tram drivers. Including the developed emergency scenarios in the training program allows employees to examine their reactions to stressful or dangerous situations and better prepare themselves for future duties.

SAVAGE: Simulation of Virtual Reality-Based for Building Fire Victim Rescue Learning Media

Airports are very dynamic and complex environments, making them high-risk places for incidents and accidents, both due to the aircraft's movement and to the building facilities or structures at the airport. Emergency service personnel must have high skills in emergency response, quick decision-making abilities, and a deep understanding of the various dangerous situations that may be encountered in the field. Continuous education and training are essential to ensure their readiness and ability to deal with emergencies. This study aims to develop Virtual Reality-based Search and Rescue learning media to improve the skills and understanding of training participants in search and rescue operations. This learning media is designed to provide a realistic and interactive simulation experience, allowing participants to practice rescue procedures in various dangerous scenarios without real risk. The development methods used in this study include the stages of needs analysis, design, development, implementation, and evaluation (ADDIE). At the analysis stage, the identification of training needs and competencies that must be achieved is carried out. The design stage involves designing Virtual Reality scenarios that cover various field conditions and rescue techniques. Effectiveness is evaluated by measuring the increase in skills and understanding of participants before and after using Virtual Reality media. The study results indicate that this learning media effectively improves the operational and decision-making skills of training participants in emergency situations. The feasibility assessment by media experts obtained an average score of 88.72%. Then, the feasibility assessment by material experts obtained an average score of 88.90%. After conducting a product trial on students, the evaluation results were 81.30%. Based on the results of the validation and trial of this product, Virtual Reality-based learning media can be recommended as an innovative and efficient training tool for Search and Rescue learning media.

Silver Nanoparticle-Decorated Cellulose Nanocrystal Reinforced Ionic Polymer Hydrogel With High Conductivity and Environmental Tolerance for Multifunctional Sensing and Emergency Alarm System.

Conductive hydrogels hold great promise for flexible electronics. However, the simultaneous achievement of satisfactory mechanical strength, outstanding environmental tolerance, high sensitivity, and multiple sensing applications in a single conductive hydrogel remains a significant challenge. Herein, ionic polymer-based hydrogels with a double conductive network consisting of [2-(methacryloyloxy)ethyl] trimethyl ammonium chloride (DMC), 2-hydroxyethyl acrylate (HEA) and silver nanoparticle decorated cellulose nanocrystal (CNC@Ag) are prepared by a facile one-pot method. The resultant hydrogel (CDH) exhibits high stretchability, satisfactory self-adhesion, excellent environment tolerance (from -60 to 60°C), long-term stability (60 days), effective UV-shielding, and strong antibacterial properties. Significantly, the CDH hydrogel displays high conductivity and rapid response due to its double conductive network of ionic polymer and CNC@Ag. Therefore, the CDH-assembled sensor can accurately detect signals from both strain and pressure deformations, exhibiting outstanding sensitivity and reliability for human motion detection, signal transmission, object recognition, and tactile sensing. More interestingly, collaborating with a development board, the CDH-based sensor can be developed as an emergency alarm to realize prompt alarms in dangerous situations. Overall, this work presents a strategy for the fabrication of conductive hydrogel with remarkable properties, making it possible for multifunctional sensing applications in wearable electronics.

Comparison Between Methods of Choosing EEG Training Data in Epileptic Seizures Prediction Systems

Considering the large number of people that suffer with epilepsy, there is great interest in developing a system capable of predicting the occurrence of the seizures. Warning patients about the proximity of a seizure can help them to avoid dangerous situations. Many efforts in the development of this system have been placed using, basically, machine learning techniques. In most of these works, regardless of the technique employed, it is assumed that the system is able to learn when the patient’s brain signals, obtained from electroencephalogram (EEG), change from interictal to pre-ictal state. Some published works do not explicitly clarify the method of choosing training and test data. This means that good results may be due to the use of an inadequate method. That is, the EEG segments may have been temporarily mixed up during training, which would help the network correctly predict the seizure. However, this would not work from a real point of view. The objective of this work is to investigate, through experiments, the effect of the way of choosing the training and test data on the accuracy of a seizure prediction system. Experimental results showed that the accuracy of the systems increases when training is performed with windows close to the seizure used for testing.

Impact of Weight Loss on Olfaction in Patients Undergoing Bariatric Surgery.

Olfaction plays a vital role in regulating nutrition, avoiding potentially dangerous situations, and modulating behavior along with interpersonal relationships. Many common disorders can have a negative impact on olfaction; one of these is obesity. Bariatric surgery induces weight loss, and current evidence suggests that it can cause improvement in olfaction. However, more information is needed regarding this topic. One hundred eighty-five patients who underwent bariatric surgery and 184 age- and gender-matched control group who did not undergo any surgery have completed a questionnaire including items from the validated Self-Reported Mini Olfactory Questionnaire. Final analysis was based on 369 patients. There was a statistically significant difference between patients before and after surgery (p < 0.05). However, there was a statistically significant difference between people who underwent surgery with < 50% excess body weight loss and the control group but none with those > 50% excess body weight loss. No significant differences were found when comparing people with and without chronic illnesses, head and neck surgery, anti-allergy drug use, and COVID-19. Before surgery, there were statistically significant differences between patients with allergic rhinitis and polyps and those without, but no significant differences were observed after surgery. Patients had significantly improved olfactory scores post-surgery compared to before surgery. Patients who had > 50% excess body weight loss after surgery showed olfactory function as good as the general population represented by the control group. However, those with < 50% excess body weight loss had significantly worse olfactory scores compared to the general population.

Geo-Fenced Aerial Fire Response System

Purpose: We aim to create a prototype of a fire extinguisher drone equipped with advanced geo-fencing technology explicitly designed for use in high-rise buildings. This drone will be capable of both ground movement and flight, allowing it to quickly navigate narrow spaces and difficult-to-reach areas. Methodology: The study involves an in-depth analysis of various drones, features, and geo-fencing to develop a prototype for precise and targeted fire suppression. The aim is to minimize the damage caused by fires and improve overall safety by enabling swift intervention, particularly in confined or elevated locations where traditional firefighting methods may face challenges. Findings: The prototype drone, equipped with geo-fencing capabilities, has demonstrated its ability to be efficiently deployed within specific, pre-defined areas, significantly improving its precision and effectiveness in targeted fire suppression. This feature ensures that the drone operates only within designated zones, reducing the risk of interference or wandering into unsafe areas. The drone is controlled remotely, allowing it to fly freely and access hard-to-reach locations quickly. A small surveillance camera mounted on the drone enhances its effectiveness by providing real-time visuals of the fire's location and intensity. This capability allows operators to assess the situation more accurately and deploy the necessary response measures, making the drone a powerful tool for modern firefighting operations. Unique Contribution to Theory, Practice and Policy: The findings from this prototype provide valuable insights that can shape the future of fire response mechanisms and drone designs. The drones can target fires while minimizing risks to firefighting personnel, and they can potentially revolutionize emergency response strategies. The ability to remotely control drones, equipped with geo-fencing and surveillance capabilities, reduces the need for human intervention in dangerous situations and improves the speed and accuracy of fire suppression efforts. Furthermore, this technology can be applied to detect and combat wildfires, helping to minimize their destructive impact by enabling quicker detection and targeted responses in remote or difficult-to-access areas. These advancements pave the way for safer and more efficient firefighting methods in the future.

Identifying features of the stressed-strained state of a non-rigid roadbed along ascents and descents on highways

The object of this study is the asphalt-concrete layers of non-rigid roadbed on ascents and descents of highways before bridges. Asphalt-concrete layers of highways on approaches to bridges are one of the most important elements for providing the strength and durability of the entire structure of non-rigid roadbed. On the ascents and descents of approaches to bridges, where the speed of vehicles changes most often, the roadbed is exposed to more intense damage than in other areas. Practical experience shows that one of the most common root causes of the types of destruction of asphalt-concrete layers is disruption of their integrity in the form of cracks, which creates dangerous situations for road users due to premature and more intensive destruction of all road surfaces. This paper investigates features of the stressed-strained state of asphalt-concrete layers of roadbed on ascents and descents in the areas connecting bridges and overpasses with the embankment. A spatial finite-element model has been considered, which makes it possible to describe the stressed-strained state of each element in the road surface structure induced by the effect of traffic load on it. Quantitative and qualitative analysis of deformations, displacements, and stresses in asphalt-concrete layers of the structure of roadbed was carried out. Circumstances that can affect the premature formation of cracks and lead to a decrease in the durability of roadbed structures have been identified. This study makes it possible to identify and eliminate potential dangers that arise during the operation of roadbed. The results could be implemented in the design of roadbed in areas with difficult traffic in the area of ascent and descent, in particular before the bridge. Knowledge of features of the stressed-strained state of roadbed would contribute to the preservation of road infrastructure, could make it possible to improve the comfort and convenience when moving goods and passengers

Using H‐Convergence to Calculate the Numerical Errors for 1D Unsaturated Seepage Under Steady‐State Conditions

ABSTRACTUnsaturated zones are important for geotechnical design, geochemical reactions, and microbial reactions. The numerical analysis of unsaturated seepage is complex because it involves highly nonlinear partial differential equations. The permeability can vary by orders of magnitude over short vertical distances. This article defines and uses H‐convergence tests to quantify numerical errors made by uniform meshes with element size (ES) for 1D steady‐state conditions. The quantitative H‐convergence should not be confused with a qualitative mesh sensitivity study. The difference between numerical and mathematical convergences is stated. A detailed affordable method for an H‐convergence test is presented. The true but unknown solution is defined as the asymptote of the numerical solutions for all solution components when ES decreases to zero. The numerical errors versus ES are then assessed with respect to the true solution, and using a log–log plot, which indicates whether a code is correct or incorrect. If a code is correct, its results follow the rules of mathematical convergence in a mathematical convergence domain (MCD) which is smaller than the numerical convergence domain (NCD). If a code is incorrect, it has an NCD but no MCD. Incorrect algorithms of incorrect codes need to be modified and repaired. Existing codes are shown to converge numerically within large NCDs but generate large errors, up to 500%, in the NCDs, a dangerous situation for designers.

General practitioners’ views on inappropriate prescribing for older patients: a qualitative study through focus groups

BackgroundInappropriate prescribing (IP) is a common problem in the older population. Despite numerous attempts to tackle this issue, it remains a public health concern. In most European countries, general practitioners (GPs) are responsible for global primary care and are thus gatekeepers for the adequacy of medicines, specifically for older people. An in-depth analysis of the situation is necessary to understand why this phenomenon is still prevalent and to identify solutions that could help avoid IP in primary practice.MethodA qualitative study based on five focus groups (FG) comprising nine to thirteen general practitioners was conducted in the French-speaking part of Belgium. Participants were recruited among the Local Medical Evaluation Groups (LMEG) and selected to guarantee heterogeneity in working organisations, years of professional experience, gender and age. All interviews were recorded with prior agreement and transcribed in verbatims. The transcripts were coded and analysed to highlight the primary themes, considering dominant and marginal discourses.ResultsFifty four GPs participated in the study, with an average experience of 30 years. IPs are perceived as a significant problem in the older population, leading to dangerous health situations. The issue is associated with polypharmacy and multimorbidity, and GPs stated to manage IP using their clinical experience. Most of the study participants faced difficulties managing IP, mostly due to the specificity and complexity of elderly care. Indeed, managing an older patient is challenging due to medical complexity, poor adherence to drug regimes, or low medical literacy. In addition, the medical environment of general practice is challenging, with multiple providers, lack of time, prescribing routine and the absence of effective communication with specialists or other care providers. Additionally, the tools and support available to help medication management in primary care are inadequate. Enhancing collaboration with pharmacists is perceived as a strong potential facilitator.ConclusionThis article addresses the complex management of IP in the old age, from the point of view of GPs. Interesting clues were highlighted, like the need to clarify roles of healthcare providers, the better fit of tools to facilitate medication’s review with particularities of GPs needs and the empowerment of pharmacist collaboration.

On the influence of artificially distorted images in firearm detection performance using deep learning

Detecting people carrying firearms in outdoor or indoor scenes usually identifies (or avoids) potentially dangerous situations. Nevertheless, the automatic detection of these weapons can be greatly affected by the scene conditions. Commonly, in real scenes these firearms can be seen from different perspectives. They also may have different real and apparent sizes. Moreover, the images containing these targets are usually cluttered, and firearms can appear as partially occluded. It is also common that the images can be affected by several types of distortions such as impulse noise, image darkening or blurring. All these perceived variabilities could significantly degrade the accuracy of firearm detection. Current deep detection networks offer good classification accuracy, with high efficiency and under constrained computational resources. However, the influence of practical conditions in which the objects are to be detected has not sufficiently been analyzed. Our article describes an experimental study on how a set of selected image distortions quantitatively degrade the detection performance on test images when the detection networks have only been trained with images that do not present the alterations. The analyzed test image distortions include impulse noise, blurring (or defocus), image darkening, image shrinking and occlusions. In order to quantify the impact of each individual distortion on the firearm detection problem, we have used a standard YOLOv5 network. Our experimental results have shown that the increased addition of impulse salt-and-pepper noise is by far the distortion that affects the most the performance of the detection network.

Clinical-applied anatomy of the carpal tunnel regarding mini-invasive carpal tunnel release.

Carpal tunnel release is a widely performed procedure. Despite a high success rate, iatrogenic neurovascular injuries can occur which lead to a painful and unsatisfying outcome. This study conducted a detailed examination of the anatomy of the carpal tunnel and the proximity of neurovascular structures that are particularly susceptible to injury, especially in the context of minimally invasive carpal tunnel release procedures. The anatomy of the carpal tunnel of 104 wrists of 52 body donors was examined. The precise anatomical location and the presence of variations were recorded for the median nerve, ulnar nerve, ulnar artery and Berrettini branch. The distance between the median nerve, the ulnar artery, the ulnar nerve, and the Berrettini branch was measured in a proximo-distal and radio-ulnar direction in relation to the distal ulnar end of the carpal tunnel. The authors identified four main dangerous anatomical situations. (1) A proximal separation of the Long-Finger/Ring-Finger branch of the median nerve together with a narrow safe-zone; (2) an ulnar take-off of the recurrent muscle branch of the median nerve with a close radio-ulnar distance to the distal ulnar end of carpal tunnel; (3) an ulnar arterial arch lying close to the transverse carpal ligament; and (4) a proximal Berrettini branch also lying close to the latter. All situations are illustrated by photographs. Additionally, the authors present a sonographic carpal tunnel assessment protocol in order to reduce the risk of injury of any neurovascular structure in the proximity of the carpal tunnel. Certain patients may inherently face an increased risk of neurovascular injuries during minimally invasive carpal tunnel releases due to their anatomical variations. Four potentially risky scenarios were clearly illustrated. Consequently, one may consider conducting a preoperative ultrasound assessment of neurovascular structures at risk, when endoscopic or ultrasound-guided tunnel release are planned. In high-risk patients, open surgery should be preferred. II.

Crash dilemmas and the ethical design of self-driving vehicles: implications from metaethics and pragmatic road marks

AbstractHow should self-driving vehicles react when an accident can no longer be averted in dangerous situations? The complex issue of designing crash algorithms has been discussed intensively in recent research literature. This paper refines the discourse around a new perspective which reassesses the underlying dilemma structures in the light of a metaethical analysis. It aims at enhancing the critical understanding of both the conceptual nature and specific practical implications that relate to the problem of crash algorithms. The ultimate aim of the paper is to open up a way to building a bridge between the inherent structural issues of dilemma cases on the one hand and the characteristics of the practical decision context related to driving automation scenarios on the other. Based on a reconstruction of the metaethical structure of crash dilemmas, a pragmatic orientation towards the ethical design of crash algorithms is sketched and critically examined along two central particularities of the practical problem. Firstly, pertinent research on the social nature of crash dilemmas is found to be merely heuristic. Secondly, existing work from ethics of risk hardly offers explicit ethical solutions to relevant and urgent challenges. Further investigation regarding both aspects is ultimately formulated as a research desideratum.

A deep reinforcement learning framework for achieving super-human hazard perception in autonomous driving agents

Modeling driver behavior can significantly improve autonomous vehicles and intelligent driver assistance/training systems. Hazard perception (HP) is an essential driving skill for preventing driving accidents in potentially dangerous traffic situations. HP is not a Markov decision process, so modeling HP with reinforcement learning techniques is challenging. We introduce a framework for modeling HP scenarios using the soft actor-critic approach. Then, we use this framework to model HP in the emergence of a critical lateral hazard onto the road. The dual environments – the mirror environment for training and the target environment for usage – accelerate the learning process. The agent is employed in the target environment using an interpreter algorithm. The results show that the agent learns HP and outperforms the best human results by 2.6%. The training is implemented 40 times faster in the mirror environment. Evaluation tests show a driving experience similar to real-world scenarios rather than gaming simulations.

Current issues of conducting classes on fire training of police officers under martial law

The article addresses pertinent issues related to conducting firearms training sessions for police officers in conditions of a state of war. The authors analyze significant aspects of this activity, including teaching methods and techniques, personnel training specifics, as well as challenges and threats that may arise during armed conflicts. The main focus is on practical recommendations aimed at enhancing the effectiveness of police training for operating in conditions of a state of war. The article analyzes changes and modifications in the methodology of teaching and studying fire training in institutions of higher education with specific conditions of study, subordinated to the Ministry of Internal Affairs of Ukraine under martial law, which would take into account all aspects of the application and use of firearms and ensure high- quality training of students of higher education for actions in stressful and dangerous situations. The authors explore the practical-tactical possibilities of conducting firearms training sessions, comparing them with regulated and recommended regulatory acts. It is established that existing methods do not correspond to the real conditions of firearms application. Special attention is given to the issues of modern methods of firearms usage and changes in teaching methodology to increase proficiency. Features and methods of teaching fire training in higher education institutions with specific training conditions of the Ministry of Internal Affairs of Ukraine are outlined, as well as innovations in this field of training are indicated. A separate view is focused on the need for modern material and technical support, since the solution to the problem of police training requires a comprehensive approach, which includes the provision of the necessary resources for conducting specialized classes, both in closed rooms and on appropriately equipped modern training grounds, and support in the development of professional skills. Also, the authors emphasize the need to improve the legal training of personnel to provide them with a clear understanding of the laws and regulations related to the use of weapons.

Tuning into musicians’ wellbeing: Research on music performance anxiety (MPA)

Tuning into musicians' wellbeing: Research on music performance anxiety (MPA) The Music and Mental Health Research Clinic (MMHRC) at the University of Ottawa's Institute of Mental Health Research (IMHR) at The Royal is investigating how to reduce music performance anxiety (MPA) and the benefits of specific coping strategies for musicians. The audience cheers, and smiles are on every face. The music performance was incredible; it emotionally moved the audience, got their toes tapping, and made them forget their worries. On the other hand, the musicians are thinking about the note they missed or their tempo not being quite perfect. The audience does not see the musicians worrying before the performance, the state of anxiety during the performance, or the negative rumination that will occur afterwards. Biologically wired with an innate tendency to default to negative assumptions to avoid dangerous situations, our bodies react to stressors as if our lives are at stake (Baumeister, 2001; Rozin &amp; Royzman, 2001; Ito &amp; Cacioppo, 2005). This negativity bias is a key reason why changing our habits, behaviours, and thought patterns is so challenging. It often results in automatic negative thoughts, such as underestimating available opportunities and resources, and increased sensitivity to perceived threats.

Kappa-opioid receptor blockade in the inferior colliculus of prey threatened by pit vipers decreases anxiety and panic-like behaviour.

The dorsal midbrain comprises dorsal columns of the periaqueductal grey matter and corpora quadrigemina. These structures are rich in beta-endorphinergic and leu-enkephalinergic neurons and receive GABAergic inputs from substantia nigra pars reticulata. Although the inferior colliculus (IC) is mainly involved in the acoustic pathways, the electrical and chemical stimulation of central and pericentral nuclei of the IC elicits a vigorous defensive behaviour. The defensive immobility and escape elicited by IC activation is commonly related to panic-like emotional states. To investigate the role of κ-opioid receptor of the IC in the antiaversive effects of endogenous opioid receptor blockade in a dangerous situation, male Wistar rats were pretreated in the IC with the κ-opioid receptor-selective antagonist nor-binaltorphimine at different concentrations and submitted to the non-enriched polygonal arena for a snake panic test in the presence of a rattlesnake and, after 24 h, prey were resubmitted to the experimental context. The snakes elicited in prey a set of antipredatory behaviours, such as the anxiety-like responses of defensive attention and risk assessment, and the panic-like reactions of defensive immobility and either escape or active avoidance during the elaboration of unconditioned and conditioned fear-related responses. Pretreatment of the IC with microinjections of nor-binaltorphimine at higher concentrations significantly decreased the frequency and duration of both anxiety- and panic-attack-like behaviours. These findings suggest that κ-opioid receptor blockade in the IC causes anxiolytic- and panicolytic-like responses in threatening conditions, and that kappa-opioid receptor-selective antagonists can be a putative coadjutant treatment for panic syndrome treatment.

Designing effective warning sounds: psychoacoustical considerations

Warning sounds are designed to get attention and prompt immediate action in dangerous situations. This paper examines the psychoacoustical factors that affect the effectiveness of warning sounds by looking at urgency perception and annoyance. Two listening tests were conducted, each designed to investigate the effects of different parameters on warning sound perception. For the first set of tests, three parameters were manipulated: predominant frequency component, wave shape, and roughness perception. The second trial looked at the influences of frequency, specifications in the German standards (DIN) for the warning sounds, effect of pulse rates, and musical tones. The results of the study demonstrate the importance of carefully considering psychoacoustical factors when designing warning sounds to ensure they are effective in alerting individuals to potential hazards.

Artificial intelligence-based prediction of pathogen emergence and evolution in the world of synthetic biology.

The emergence of new techniques in both microbial biotechnology and artificial intelligence (AI) is opening up a completely new field for monitoring and sometimes even controlling the evolution of pathogens. However, the now famous generative AI extracts and reorganizes prior knowledge from large datasets, making it poorly suited to making predictions in an unreliable future. In contrast, an unfamiliar perspective can help us identify key issues related to the emergence of new technologies, such as those arising from synthetic biology, whilst revisiting old views of AI or including generative AI as a generator of abduction as a resource. This could enable us to identify dangerous situations that are bound to emerge in the not-too-distant future, and prepare ourselves to anticipate when and where they will occur. Here, we emphasize the fact that amongst the many causes of pathogen outbreaks, often driven by the explosion of the human population, laboratory accidents are a major cause of epidemics. This review, limited to animal pathogens, concludes with a discussion of potential epidemic origins based on unusual organisms or associations of organisms that have rarely been highlighted or studied.

A Formalism for Scalable Maritime Traffic Monitoring and Explainable Anomaly Detection and Resolution at Vessel Traffic Services

Abstract Vessel traffic service (VTS) centres around the globe monitor and manage the ship traffic in their areas of responsibility and respond to arising unsafe or inefficient situations. Decision support tools (DST) help vessel traffic service operators (VTSO) to enhance their situational awareness and decision-making process, thus to recognise and assess dangerous situations. However, current DST have unsophisticated features and require manual configuration by the operator. Firstly, triggers for alerts are mostly based on the creation of geographical polygons for spatial-dependent assignment of rules, thresholds, ranges and limits for specific features. Secondly, calculations for the detection of safety-critical situations rely on measurements based on the closest point of approach (CPA) without taking contextual information into account. Thirdly, trajectory predictions are performed considering a constant velocity model (CVM) which does not depict reality. Due to these and other peculiarities, current DST are prone to false alerts. This results into a high workload where unsafe situations may be overlooked. In this paper, we propose a hierarchical formalism as foundation for an anomaly detection and resolution which generates less false alerts. The formalism consists of three hierarchical layers which represent, objects, measurements and situations. The formalism ensures adaptability and extensibility to various VTS areas and traffic patterns. Moreover, due to the given structure, the presented formalism is easily implementable, adaptable and scalable taking the currently available technological capabilities at VTS centres into account. We demonstrate the feasibility of this formalism by implementing a proof-of-concept and assessing it with realistic scenarios. Our implementation utilizes a rule-based system as central framework and it is configured through statistical methods, e.g. machine learning. Given this hybrid approach, the implementation provides reasonable and explainable results. This enables comprehensibility and verifiability by authorities and operators which is crucial for acceptance.

Psychological aspects of aggression among police personnel

The article presents psychological aspects of aggression in the context of professional activity of police personnel. The nature and manifestations of aggression in the working environment of police officers are investigated, the factors that cause aggressive behaviour are considered, and its impact on the efficiency and safety of performance of official duties is analysed. The theoretical analysis has shown that everyday stress and dangerous situations in wartime create a favourable environment for the development of aggressive tendencies, which can negatively affect the quality of official duties performance. It has been found that aggression among police personnel can take various forms such as verbal conflict and physical force, which calls into question the credibility of law enforcement agencies and can have serious legal and ethical consequences. The purpose of the study is to examine and analyse various manifestations of aggression among police personnel in order to identify possible differences in their characteristics and ability to display such behaviour. The sample consisted of 200 police officers, divided into two groups by gender, 100 in each group. The first group was represented by men, the second by women. The study used the “Aggression Level Questionnaire” by A. Bass and A. Darky. Mathematical and statistical processing of the results was carried out using Student’s t-test for independent samples and Fisher's angular transformation criterion (φ). An empirical study of aggression among police officers of different gender groups has revealed significant differences in the manifestation of aggressive behaviour. Male police officers are more likely to use physical force and verbal aggression compared to female police officers. At the same time, both groups have a similar tendency to indirect aggression and negativism, which indicates a general tendency towards indirect forms of aggression and oppositional behaviour among police personnel. Female police officers show a higher level of irritability, suspicion and resentment, which may affect their interaction with others and their overall psychological state.