Search Results (218)

Background/Objectives: The extension of euthanasia and physician-assisted suicide to individuals with mental disorders presents a profound ethical, clinical, and legal challenge. While increasingly accepted in some jurisdictions, their application in psychiatric contexts—particularly in cases of depression—raises concerns about diagnostic precision, therapeutic adequacy, and the validity of informed consent. This study examines two controversial Belgian cases to explore the complexities of euthanasia for psychological suffering. Methods: A qualitative case analysis was conducted through a qualitative analysis of publicly available media sources. The cases were examined through clinical, psychoanalytic, and medico-legal lenses to assess diagnostic clarity, treatment history, and ethical considerations. No access to official medical records was available. Case Presentation: The first case involved a young woman whose depressive symptoms were reportedly linked to trauma from a terrorist attack. The second concerned a middle-aged woman convicted of infanticide and later diagnosed with Major Depression. Discussion: In both cases, euthanasia was granted on the grounds of “irreversible psychological suffering.” However, the absence of detailed clinical documentation, potential unresolved trauma, and lack of psychodynamic assessment raised doubts about the robustness of the evaluations and the validity of informed consent. Conclusions: These findings highlight the need for a more rigorous, multidisciplinary, and ethically grounded approach to psychiatric euthanasia. This study underscores the importance of precise diagnostic criteria, comprehensive treatment histories, and deeper exploration of unconscious and existential motivations. Safeguarding clinical integrity and ethical standards is essential in end-of-life decisions involving mental illness. Full article

The current global energy crisis is one of the most pressing challenges of the 21st century, it highlights the fragility of an old power system based on fossil fuels, geopolitical dependencies and often the precariousness and age of equipment and installations, affecting the economy, security and social stability on a national, regional and world scale. The risk of blackout thus becomes not only a technological threat, but a symbol of the need for a paradigm shift. The energy future must be sustainable, collaborative and adaptable—to guarantee not only the continuity of services with electricity, but also the stability of modern society. This paper provides an intrinsic interdisciplinary analysis on the causes, implications and possible solutions related to major imbalances in contemporary power systems, emphasizing the growing risk of blackout (large power outages). The main causes of crises are analyzed interdisciplinary, such as: insecurity in the functioning of the National Power System, terrorist attack on the National Power System, extreme weather condition, natural calamity, energy insecurity and political/military insecurity. The paper highlights the interdependence between energy infrastructure and energy security, as well as the vulnerability of power grids to cyberattacks, natural disasters and consumer pressures. In addition, socio-economic, technological and political issues are addressed, providing an integrated view of the phenomenon. Finally, national, regional and bilateral mitigation, limitation and restoration (resilience) procedures and measures are proposed in the event of an electricity crisis—blackout. Full article

The instability of the geopolitical situation due to the high terrorist danger leads to the need to take into account at the planning stage the capabilities of intruders to perform UAV flight missions. A general method for analyzing the process of cargo delivery by UAVs (Unmanned Aerial Vehicles) to hard-to-reach areas during emergencies has been proposed. This method allows for the evaluation of UAV effectiveness based on the probability of successful cargo delivery within a specified time limit. The method is based on applying topological transformation techniques to stochastic networks. The cargo delivery process is modeled as a stochastic network, followed by the determination of its equivalent function and the use of Heaviside decomposition to calculate the distribution function and the expected delivery time. This presentation of the studied process for the first time made it possible to take into account the impact on the flight mission of the UAV of the destructive impact from the attacker. This approach allows the destructive effects on the UAV from malicious interference to be considered. The input data used for the analysis are parameters that characterize the properties of individual processes within the stochastic network, represented as branches, which are computed using methodologies published in earlier studies. It has been demonstrated that the resulting distribution function of the mission completion time can be accurately approximated by a gamma distribution with a level of precision suitable for practical applications. In this case, the gamma distribution parameters are determined using the equivalent function of the stochastic network. The proposed method can be used by flight planners when scheduling UAV operations in emergency zones, especially in scenarios where there is a risk of malicious interference. Full article

In Ten Little Indians, Sherman Alexie presents nine poignant and emotionally resonant stories about Native Americans’ struggle with alienation and stereotypes. Instead of focusing merely on the ethnic identity of American Indians, Alexie writes about a particular group of people sharing similar circumstances and addresses their common humanity, namely their search for love and respect in urban spaces. Alexie questions the authenticity of Indian identity and asserts that a “mental reservation” exists in the minds of Indian people which significantly influences their perceptions of self and community. Race, as a medium of seeing “the other” permeates U.S. society, especially in the wake of terrorist attacks. However, racial profiling has proven to be an ineffective means of detecting criminals and criminal activities, and has obstructed social relationships, bringing emotions of fear, loneliness and grief to urban Indians. In response to the modernity crisis, Alexie explores the American Indian cosmopolitanism in Ten Little Indians, and envisions a human social community based on reciprocity and mutual respect. His concerns regarding ordinary people’s life experiences and their ways of forming healthy relationships exhibit his considerable hope for “the triumph of the ordinary”. Full article

Mass shootings result in significant casualties. Due to the complexity of buildings, capturing crowd dynamics during mass shooting incidents is particularly challenging. Therefore, it is necessary to study crowd dynamics and the key mechanisms of mass shooting incidents and explore optimal building design solutions to mitigate the damage caused by terrorist attacks and enhance urban safety. In this study, we focused on the Bataclan Shooting (13 November 2015) as the target case. We used an agent-based model (ABM) to model both the attacking force (shooting) and counterforce (anti-terrorism response). According to the real situation, the dynamic behavior of three types of agents (civilians, police, and shooters) during the shooting accident was modeled to explore the key mechanism of individual behavior. Taking civilian casualties, police deaths, and shooter deaths as the real target values, we obtained combinations for optimal solutions fitting the target values. Under the optimal solutions, we verified the effectiveness and robustness of the model. We also used artificial neural networks (ANNs) to detect the predictive stability of the ABM model’s parameters. In addition, we studied the counterfactual situation to explore the impact of police anti-terrorism strategies and building exits on public safety evacuation. The results show that for the real cases, the optimal anti-terrorism size was four police and the optimal response time was 40 ticks. For double-layer buildings, it was necessary to set exits on each floor, and the uniform distribution of exits was conducive to evacuation under emergencies. These findings can improve police patrol routes and the location of police stations and promote the creation of public safety structures, enhancing the urban emergency response capacity and the level of public safety governance. Full article

In the current context of sustainability management and energy insecurity, amplified by the military instability determined by the war between Russia and Ukraine, and the increasingly frequent occurrence of a series of plausible scenarios for disasters or energy blackouts worldwide, this work is a real and applicable model for regional states that would like to critically analyze the situation of their energy security through identifying all the plausible risk scenarios targeting the energy critical infrastructures. The study has identified and assessed two of the most plausible risk scenarios (a natural disaster and a terrorist attack) in the case of a strategic power substation of 220 kV, 400 kV, or 750 kV undergoing a blackout effect. After having assessed the risks, the safety strategy for Romania’s national power system has been elaborated together with the safety strategy for the European Power system-ENTSO-E (European Network of Transmission System Operators for Electricity). The results of the study match other specialized works from different European countries and might represent a model for other types of energy safety risk assessments and for other types of critical infrastructures that are vital for the modern European society and for sustainability management. Full article

Small unmanned aerial systems have become increasingly prevalent in various fields, including agriculture, logistics and the public sector, but concerns over misuse, such as military intrusions and terrorist attacks, highlight the necessity for effective aerial surveillance. Although conventional radar systems can detect large areas, they face challenges in accurately identifying small drones. In contrast, vision sensors offer high-resolution identification but encounter challenges in long-range detection and real-time processing. To address these limitations, this study proposes a vision sensor-based detection framework, termed the noise suppression super-resolution detector (NSSRD). To ensure the reliability and real-time capability of small drone detection, NSSRD integrates image segmentation, noise suppression, super-resolution transformation, and efficient detection processes. NSSRD divides the surveillance area into uniform sections, applies a bilateral filter to suppress noise before passing the images to an object detection model, and uses a region of interest selection process to reduce the detection area and computational load. The experimental results demonstrate that NSSRD outperforms existing models, achieving a 24% improvement in the true positive rate and a 25% increase in recall at an altitude of 40 m, validating its superior performance. Full article

Objective: Exposure of emergency service personnel to disasters can lead to significant mental health challenges. The psychological impact of intentionally caused disasters, such as terrorist attacks, tends to be more severe than that of natural disasters. While much research has focused on terrorist attacks, little is known about the effects of intentional vehicular assaults (IVAs). This study examines the impact of an IVA on the mental health of firefighters. We hypothesized that firefighters deployed to the scene (deployed group (DG)) would experience more mental health problems compared to those not on duty (comparison group (CG)). Methods: The study included n = 115 firefighters, with 60 in the DG and 55 in the CG from the same units. Validated psychometric tools were used to assess anxiety, panic attacks (PHQ-D), and post-traumatic stress symptoms (PCL-5). Participation was voluntary, and informed consent was obtained. The study received approval from the Charité Berlin Ethics Committee (number: EA4/085/18). Results: A significantly higher prevalence of panic attacks was found in the DG (12.5%) compared to the CG (1.8%), with an odds ratio of 8.0 (95% CI: 1.0–67.3). Correlation analysis revealed a significant positive relationship between non-occupational tasks and hostility (r = 0.312, p = 0.015, n = 60), while parenthood had no significant effect on panic attacks or generalized anxiety. Conclusion: These results highlight the severe mental health impact of intentional disasters like IVAs on firefighters, emphasizing the need for targeted psychological support and interventions. Future research should focus on tailored interventions to address the high prevalence of panic attacks among this population. Full article

This paper presents the design of a system to support the identification of victims of disasters and terrorist attacks. The system, called ID Victim (IDV), is a web application using a mobile app and data server. The DVI (Disaster Victim Identification) procedure, an international standard developed by Interpol, is used. The purpose of the IDV system is to facilitate and expedite the process of determining victims’ identities. A neural identification module was developed and trained on approximately 13,000 images from the LFW dataset and fine-tuned using 400 simulated PostMortem (PM) and AnteMortem (AM) images. Postmortem data include photographs of victims while antemortem data consist of pre-disaster photos of potential victims. The module generates a hypothesis, linking PM to AM, which is then verified. The module achieved test identification accuracy of up to 60% for 25 sample PM and AM sets. The system partially automates photo comparisons by DVI teams, improving efficiency, reducing identification time, and limiting the exposure of operators to graphic images. Implementing the system as a mobile application accelerates the process by enabling direct data entry during victim examinations on-site. Full article

The detection of highly toxic chemicals such as phosgene is crucial for addressing the severe threats to human health and public safety posed by terrorist attacks and industrial mishaps. However, timely and precise monitoring of phosgene at a low cost remains a significant challenge. This work is the first to report a novel fluorescent system based on the Intramolecular Charge Transfer (ICT) effect, which can rapidly detect phosgene in both solution and gas phases with high sensitivity by integrating a benzo[1,2-b:6,5-b’]dithiophene-4,5-diamine (BDTA) probe. Among existing detecting methods, this fluorescent system stands out as it can respond to phosgene within a mere 30 s and has a detection limit as low as 0.16 μM in solution. Furthermore, the sensing mechanism was rigorously validated through high-resolution mass spectrometry (HRMS) and density functional theory (DFT) calculations. As a result, this fluorescent probing system for phosgene can be effectively adapted for real-time, high-sensitivity sensing and used as a test strip for visual monitoring without the need for specific equipment, which will also provide a new strategy for the fluorescent detection of other toxic materials. Full article

Pattern recognition algorithms have been used to make it possible for computer vision to self-train and comprehend visual input. Advanced measurements have been required every time for the early detection of armed threats in order to decrease accidents and terrorist attacks. Weapon detection systems have mostly been used in public spaces such as stadiums, airports, key squares, and battlefields, whether they are in urban or rural settings, to achieve better security objectives. Based on cloud architecture, DL and ML algorithms have been used by contemporary closed-circuit television surveillance and control systems to detect weapons. In addition to using the Raspberry Pi as an edge device and an efficient model to construct a weapons detection system, edge computing is used to address these problems. The text report includes the image processing results. Soldiers can outfit themselves with the recommended edge node and headphones, and the visual data output will allow them to receive alerts about armed threats. Furthermore, we can improve our method’s performance by adding more training data and changing the network architecture. The primary object of this paper is to build a model for detecting weapons such as pistols and rifles. The model developed in this research detects weapons such as pistols and rifles in an average time of 1.30 s. Full article

As the digital environment progresses, the complexities of cyber threats also advance, encompassing both hostile cyberattacks and sophisticated cyber espionage. In the face of these difficulties, cooperative endeavours between state and non-state actors have attracted considerable interest as crucial elements in improving global cyber resilience. This study examines cybersecurity governance’s evolving dynamics, specifically exploring non-state actors’ roles and their effects on global security. This highlights the increasing dangers presented by supply chain attacks, advanced persistent threats, ransomware, and vulnerabilities on the Internet of Things. Furthermore, it explores how non-state actors, such as terrorist organisations and armed groups, increasingly utilise cyberspace for strategic objectives. This issue can pose a challenge to conventional state-focused approaches to security management. Moreover, the research examines the crucial influence of informal governance processes on forming international cybersecurity regulations. The study emphasises the need for increased cooperation between governmental and non-governmental entities to create robust and flexible cybersecurity measures. This statement urges policymakers, security experts, and researchers to thoroughly examine the complex relationship between geopolitics, informal governance systems, and growing cyber threats to strengthen global digital resilience. Full article

Background: The literature highlights the profound psychological impact of war on children, families, and communities, emphasizing the prevalence of Post-Traumatic Stress Disorder (PTSD), anxiety, and other symptoms among affected individuals. Interventions, such as Child-Parent Psychotherapy (CPP) and music therapy, show promise in mitigating trauma effects, underscoring the need for holistic approaches that address familial and community dynamics alongside individual well-being. Methods: Aiming to explore the influences of dyadic music therapy sessions on parents’ capacity to support their children, this study involved four families displaced from their home-kibbutz as result of a terrorist attack. All dyads participated in music therapy sessions with a focus on parent–child interactions and trauma processing (CPP informed). Embedded in a qualitative, phenomenological approach, the research utilized interpretative phenomenological analysis (IPA) and micro-analytic methods to explore meaningful moments in the music therapy sessions. Results: Findings identified four central categories: (1) Discovering the child’s grounding song: identifying resources; (2) Musical improvisation sets the grounds for parent–child mutual recognition of the child’s traumatic experience; (3) Musical performance empowers child and parent; (4) A sense of agency is gained through controlling the musical environment. Conclusions: The significance of restoring the children’s freedom of play, the parents’ sense of competency, and of enhancing families’ capacity to connect to their traumatic experiences through the musical environment is discussed. Full article

This article explores the pervasive influence of conspiracy theories, specifically the New World Order (NWO) and Golden Billion theories, within the context of the ongoing conflict between Russia and Ukraine. These theories form key narrative frameworks in Russian state media and global conspiracy communities, shaping perceptions of geopolitical events. This study dissects four pivotal episodes within the Russia–Ukraine conflict to illustrate how conspiracy theories shape public perception and policy direction, further entrenching ideological divides. In the first episode of the 2022 full-scale invasion, narratives of the Golden Billion were utilised to justify the attack, presenting Russia as a bastion against the Western elite’s plans to dominate the global economy and resources. The second episode examines the attack on Mariupol in 2022, framed by Russian propaganda as a necessary act to thwart the supposed expansion of NATO and the EU, underpinned by the NWO agenda aiming to dilute Russian influence in Eastern Europe. The third episode analyses the Nord Stream pipeline sabotage in 2022, interpreted by some conspiracy theorists as an act by the NWO to destabilise Europe’s energy security, thus consolidating control over energy routes and resources. The fourth episode delves into the 2024 Moscow terrorist attacks, which were seen by some as either a false flag operation conducted by Western powers or as a legitimate repercussion of Western encroachment orchestrated to weaken Russia’s resolve and international standing. Each episode is contextualised within a broader conspiratorial framework, highlighting the dualistic nature of the NWO and Golden Billion theories that paint the conflict not merely as territorial disputes but as a clash between fundamentally opposing worldviews and global orders. This narrative analysis not only underscores the role of conspiracy theories in shaping geopolitical discourse but also demonstrates their utility in mobilising domestic support, framing international criticism, and justifying military actions. Our findings suggest that these conspiratorial narratives provide a resilient, albeit misleading, lens through which supporters of the Kremlin’s policies can rationalise the war, attributing complex sociopolitical dynamics to the malevolent machinations of a global elite. This study contributes to understanding how modern conflicts are interpreted through ancient conspiratorial lenses, impacting national and international policy and public opinion. Full article

With the frequent occurrence of natural disasters and the acceleration of urbanization, it is necessary to carry out efficient evacuation, especially when earthquakes, fires, terrorist attacks, and other serious threats occur. However, due to factors such as small targets, complex posture, occlusion, and dense distribution, the current mainstream algorithms still have problems such as low precision and poor real-time performance in crowd person detection. Therefore, this paper proposes EAAnet, a crowd person detection algorithm. It is based on YOLOv5, with CBAM (Convolutional Block Attention Module) introduced into the backbone, BiFPN (Bidirectional Feature Pyramid Network) introduced into the neck, and combined with a loss function of CIoU_Loss to better predict the person number. The experimental results show that compared with other mainstream detection algorithms, EAAnet has achieved significant improvement in precision and real-time performance. The precision value of all categories was 78.6%, which was increased by 1.8. Among these, the categories of riders and partially visible person were increased by 4.6 and 0.8, respectively. At the same time, the parameter number of EAAnet is only 7.1M, with a calculation amount of 16.0G FLOPs. Therefore, it is proved that EAAnet has the ability of the efficient real-time detection of the crowd person and is feasible in the field of emergency management. Full article