Search Results (10)

Background: Stalking is a well-established and studied crime in the forensic field. Nevertheless, research on the psychological aspects of stalking behaviors remains limited due to the lack of specific assessment tools. This two-phase research project aims to propose and validate a new instrument—the Stalking Assessment Questionnaire (SAQ)—to identify the possible latent psychological dimensions characterizing early stalking tendencies. Methods: During the first phase of questionnaire development, a thematic focus group comprising five psychologists generated 55 items. These items underwent preliminary screening with a sample of 85 students to assess clarity and redundancy; this process addressed semantic issues and resulted in a revised 48-item version. In the second validation phase (Study 1), the 48-item SAQ was administered to a sample of 349 male students whose demographic profiles matched those typically associated with potential stalkers; following this, 15 items were retained. In Study 2, the 15-item SAQ was cross-validated on an independent sample of 380 male students. To assess its validity, correlations were analyzed with a battery of personality inventories, including the LSRP, ECR-R, AQ, PESES, SRSS, RelRQ, ASI-S, and BIDR-6. Results: Following item and factor analyses, a model comprising two latent factors—Insistence (SAQ-INS) and Exaggerated Jealousy (SAQ-EXJ)—and 15 indicators emerged. Internal consistency was robust, with a Cronbach’s alpha of 0.87. In Study 2, as hypothesized, SAQ-EXJ correlated positively with anger and hostility (AQ) and with antisocial and impulsive traits (LSRP-F2), although these associations were modest (r = 0.30). Among the significant Pearson’s correlations, three were found to be substantial (r > 0.50): specifically, those between the SAQ and anxious attachment style (ECR-Ranx), relational rumination (RelRQ), and sexism (ASI-S). Conclusions: In conclusion, the final SAQ structure revealed two primary factors—Insistence and Exaggerated Jealousy—that account for stalking as a continuous construct. These factors demonstrated significant associations with several critical personality traits. The final questionnaire comprises 24 items, including nine fillers; consequently, it is efficient to administer and suitable for both research and psycho-educational interventions among adolescents and other potentially vulnerable populations. Full article

As Unmanned Aerial Vehicles (UAVs) become integral to critical infrastructure, ranging from precision agriculture to emergency disaster recovery, their security becomes a matter of systemic resilience. This paper provides a comprehensive thematic survey of the security landscape for unmanned devices, bridging the gap between low-level hardware vulnerabilities and high-level mission failures. We propose a multidimensional taxonomy that categorizes challenges into hardware roots of trust, swarm intelligence threats, and domain-specific applications. A primary focus is placed on the Resource–Security Paradox, where the energy cost of heavy cryptographic or AI defenses directly reduces flight endurance, creating a trade-off that adversaries exploit through battery-exhaustion attacks. Beyond standard threats, we analyze emerging risks in additive manufacturing supply chains, the “Sim-to-Real” gap in AI-driven perception, and the legal necessity of Digital Forensic Readiness (DFR) for post-incident attribution. Through a systematic review of defensive frameworks, including lightweight encryption, Mamba-KAN anomaly detection, and blockchain-anchored logging, we evaluate the effectiveness of current solutions against complex adversarial models. Finally, we identify critical research gaps, providing a roadmap for security-by-design in the next generation of critical infrastructure swarms. Full article

This study presents a comparative analysis of cylindrical lithium-ion cell architectures, tracing the evolution from the conventional tabbed design (18650/21700) to the large-format 4680 cell with its tabless current collectors. This architectural shift is driven by the imperative to minimise internal ohmic resistance and enhance thermal management in high-power automotive battery applications. Forensic investigation reveals that the 4680 design replaces localised, high-resistance tab connections with a distributed, low-impedance interface, necessitating the adoption of advanced manufacturing techniques, including long ultrasonic torsional welding and highly controlled high-power density laser welding. Crucially, the welding of external aluminium busbars to the cell relies on sophisticated microstructural engineering, particularly for the challenging dissimilar Aluminium-Steel (Al-Steel) anode weld. This weld format employs a spiral laser path to limit the formation of brittle aluminium-iron (Al-Fe) intermetallic compounds (IMCs), leveraging the steel cell casing’s nickel plating to promote a more ductile Al-Fe-Ni phase for improved joint reliability. Furthermore, the 4680 cell incorporates a significantly thicker casing (≈0.54 to 0.7 mm) for enhanced mechanical strength. In conclusion, the 4680 cell achieves superior performance through robust mechanical design and advanced welding processes that prioritise microstructurally sound, low-resistance interfaces. Full article

This paper investigates the flame behavior and smoke pattern characteristics of lithium-ion battery (LIB) fires using an integrated experimental and numerical simulation approach. Based on fire dynamics theory, a jet flame model for LIB thermal runaway (TR) is developed to analyze the flame height and dynamic characteristics. The results reveal two distinct regimes in LIB jet flames: momentum-controlled dominance in the early TR stage (lasting approximately 3 s) and buoyancy-controlled dominance in subsequent combustion. The jet flame shifts from a momentum-dominated regime (Fr > 5) to a buoyancy-dominated plume (Fr < 5) as the vent velocity decays below 12 m/s. The simulated flame heights align with experimental measurements and the Delichatsios model, validating the numerical approach. Furthermore, the distribution of flame components (e.g., H₂, CO, CO₂, CH₄, C₂H₄) is analyzed, highlighting the influence of multi-component gases on combustion heterogeneity. Smoke pattern analysis demonstrates that soot deposition varies significantly between momentum- and buoyancy-controlled stages, with the former producing darker, concentrated deposits and the latter yielding wider, lighter patterns. These findings provide a theoretical basis for forensic fire investigation (accident reconstruction) and targeted suppression strategies for different combustion stages. Full article

Understanding vehicle acceleration behavior during intersection departures is critical for advancing traffic safety, sustainable mobility, and intelligent transport systems. This study presents a high-resolution kinematic analysis of 714 vehicle departures from signalized intersections, encompassing straight crossings, left turns, and right turns, and involving a diverse sample of internal combustion engine (ICE), hybrid electric (HEV), and battery electric vehicles (BEV). Using synchronized Micro Electro-Mechanical Systems (MEMS) accelerometers and Real-Time Kinematic (RTK)-GPS systems, the study captures longitudinal acceleration and velocity profiles over fixed distances. Results indicate that BEVs exhibit significantly higher acceleration and final speeds than ICE and HEV vehicles, particularly during straight crossings and longer left-turn maneuvers. Several mathematical models—including polynomial, arctangent, and Akçelik functions—were calibrated to describe acceleration and velocity dynamics. Findings contribute by modeling jerk and delay propagation, supporting better calibration of AV acceleration profiles and the optimization of intersection control strategies. Moreover, the study provides validated acceleration benchmarks that enhance the accuracy of forensic engineering and road accident reconstruction, particularly in scenarios involving intersection dynamics, and demonstrates that BEVs accelerate more rapidly than ICE and HEV vehicles, especially in straight crossings, with direct implications for traffic simulation, ADAS calibration, and urban crash analysis. Full article

Performance validity tests (PVTs) and symptom validity tests (SVTs) are central to evaluating neuropsychological test results in clinical adult ADHD assessments. Although their relationships have been widely examined, the constructs these measures assess remain poorly understood in applied contexts. This study investigates the conceptual similarities and distinctions of performance validity measures, i.e., the Groningen Effort Test (GET), the Medical Symptom Validity Test (MSVT), and the Amsterdam Short-Term Memory (ASTM) test, within a comprehensive diagnostic battery for adult ADHD. The diagnostic battery included symptom self-reports and a continuous performance test (CPT). Network and factor analyses investigated these relationships. A three-factor structure was hypothesized, consisting of (1) performance validity measures, (2) continuous performance measures, and (3) symptom reports (including embedded SVTs). Data from a large clinical referral sample (N = 461) of adults with suspected ADHD were analyzed to explore these constructs. Network analysis revealed that the PVTs did not form a cohesive network with CPT measures. Symptom reports, including embedded SVTs, formed their own cluster, separate from performance-based attention measures. Factor analysis rejected a unified construct of performance validity measures. Regression analysis showed that cognitive deficits, education level, and impulsivity predicted ASTM test performance, whilst the MSVT and GET did not. These findings suggest that PVTs should be interpreted in the context of ADHD assessment, particularly in high-stakes forensic evaluations, where the accuracy of performance evaluation is critical. Future research should explore multidimensional models of performance validity, addressing domain-specific underperformance and individual variability in ADHD evaluations. Full article

Background and Objectives: Burnout syndrome is increasingly recognized as a significant occupational hazard among forensic medicine professionals, a population exposed to intense psychological stress and complex work demands. This study aimed to assess the prevalence of burnout, job satisfaction, and unconditional self-acceptance among forensic personnel in Romania and to explore potential predictors and mediators of burnout within this context. Materials and Methods: A cross-sectional survey was conducted among 153 forensic medicine professionals from 31 counties across Romania. Participants completed a battery of standardized instruments, including the Maslach Burnout Inventory—General Survey (MBI-GS), the Job Satisfaction Survey (JSS), and the Unconditional Self-Acceptance Questionnaire (USAQ). Cut-off scores for burnout subscales were established using the 75th percentile. Data were analyzed to identify demographic, occupational, and psychological correlates of burnout. Descriptive statistics were used to summarize sample characteristics and burnout prevalence. Group comparisons were made across demographic and professional categories. A mediation model was tested to evaluate whether unconditional self-acceptance mediated the relationship between job satisfaction and burnout. We hypothesized that job satisfaction would be negatively associated with burnout symptoms and that unconditional self-acceptance would mediate this relationship, acting as a protective psychological factor. Results: Approximately a quarter of respondents met the criteria for high total burnout, emotional exhaustion, and professional inefficacy, while cynicism was present in a fifth of participants. Burnout was more prevalent among younger workers, forensic medicine residents, and those working in the capital. Job satisfaction was generally high, but lower in women, younger individuals, and residents. Nearly half of the participants reported low or very low self-acceptance. Mediation analysis revealed that unconditional self-acceptance partially mediated the relationship between job satisfaction and burnout, suggesting a protective psychological mechanism. Conclusions: This study highlights the considerable burden of burnout among forensic medicine professionals in Romania and identifies job dissatisfaction and low self-acceptance as key contributors. Findings underscore the need for targeted interventions aimed at enhancing job satisfaction and emotional resilience, particularly in vulnerable subgroups. Institutional efforts that support mental well-being, foster emotional coping, and improve organizational dynamics are essential to reduce burnout in this high-risk population. Full article

The surge in lithium-ion battery (LIB) use, essential for mass-scale renewable energy storage, raises concerns about fire hazards. However, to date, there is a lack of industry-wide understanding of large-scale LIB fire propagation. This paper suggests a translational forensic approach to promote fire safety awareness and introduces the cellular automata (CA) model coupled with the Monte Carlo (MC) approach to address the complex fire propagation simulation within an energy storage system (ESS). The objective is to demonstrate that the CA-MC model can provide a flexible and scalable connection for all levels of battery fire studies. The numerical model is coupled with experimental tests which have been performed to establish the actual timing of fire propagation from a single source. Cellular automata simulation, conducted through hybrid modeling and an applied risk analysis approach to evaluate fire hazards associated with LIBs, offers crucial insights into potential risks. The results demonstrate that, with fire incident initiation at a probability of 0.1 (10%), 33% of batteries will burn, and at a probability of 0.6 (60%) and beyond, the entire battery module will face complete burndown. Achieving full combustion of the entire module will take only approximately 42 timesteps on average, indicating rapid fire propagation. The actual time for a complete fire to occur in the battery module has been estimated to be 304 s per timestep, or 3.5 h total. Using this example, it is shown that the CA-MC approach can be extended to many other aspects of battery fire studies and is ideal as a translational tool, spanning all domains of the LIB industry. Full article

The ubiquitous deployment of Li-ion batteries (LIBs) in more demanding applications has reinforced the need to understand the root causes of thermal runaway. Herein, we perform a forensic simulation of a real-case failure scenario, using localised heating of Li(Ni_0.5Mn_0.3Co_0.2)O₂ versus graphite 18650 cylindrical cells. This study determined the localised temperatures that would lead to venting and thermal runaway of these cells, as well as correlating the gases produced as a function of the degradation pathway. Catastrophic failure, involving melting (with internal cell temperatures exceeding 1085 °C), deformation and ejection of the cell componentry, was induced by locally applying 200 °C and 250 °C to a fully charged cell. Conversely, catastrophic failure was not observed when the same temperatures were applied to the cells at a lower state of charge (SOC). This work highlights the importance of SOC, chemistry and heat in driving the thermal failure mode of Ni-rich LIB cells, allowing for a better understanding of battery safety and the associated design improvements. Full article

The parameter extraction of parameters for Li-ion batteries is regarded as a critical topic for assessing the performance of battery energy storage systems (BESSs). The supply–demand algorithm (SDA) is used in this work to identify a storage system’s unknown parameters. The parameter-extracting procedure is represented as a nonlinear optimization task in which the state of charge (SOC) is approximated using nonlinear features related to the battery current and the initial SOC condition. Furthermore, the open-circuit voltage is approximated using the resulting SOC, which is performed in a nonlinear formula, as well. When used in the dynamic nonlinear BESS model, the SDA was used to verify the fitness values and standard deviation error. Furthermore, the results that were acquired using SDA are compared to recently developed approaches, which are the gradient-based, tuna swarm, jellyfish, heap-based, and forensic-based optimizers. Simulated studies were paired with experiments for the 40 Ah Kokam Li-ion battery and the ARTEMIS driving-cycle pattern. The numerical outcomes showed that the proposed SDA is an approach which is excellent at identifying the parameters. Furthermore, when compared to the other current optimization techniques, for both the Kokam Li-ion batteries and the ARTEMIS drive-cycle pattern, the suggested SDA exhibited substantial precision. Full article