Search Results (259)

This study investigates how demographic characteristics, severity of intimate partner violence (IPV), social support, gender equality awareness, and demographic factors (e.g., living with children at home) influence help-seeking behaviors among 2527 IPV-experienced women in Beijing, Shanghai, Guangzhou, and Shenzhen. Drawing on the help-seeking model and conservation of resource theory, the study distinguishes between formal (e.g., police, legal aid) and informal (e.g., family, friends) help-seeking. Logistic regression results reveal that greater violence severity, stronger perceived social support, and higher gender equality awareness significantly increase both formal and informal help-seeking. Notably, living with children is associated with a higher likelihood of seeking formal help, possibly due to increased concerns for children’s safety and the desire to change the abusive environment. While help-seeking behavior is on the rise overall, particularly among women with strong support networks and progressive gender attitudes, structural and cultural barriers remain. The findings underscore the need to improve public education, reduce stigma, and enhance accessibility of support systems. This study contributes to the growing literature on IPV in China and provides evidence for refining policy interventions and service delivery. Full article

The application of artificial intelligence within forensic image analysis marks a significant step forward for the non-destructive examination of evidence, a crucial practice for maintaining the integrity of a crime scene. While non-destructive testing (NDT) methods are established, the integration of AI, particularly for analyzing ballistic evidence, requires further exploration. This preliminary study directly addresses this gap by focusing on the use of deep learning to automate the analysis of bullet holes. This work investigated the performance of two state-of-the-art convolutional neural networks (CNNs), YOLOv8 and R-CNN, for detecting ballistic markings in digital images. The approach treats digital image analysis itself as a form of non-destructive testing, thereby preserving the original evidence. The findings demonstrate the potential of AI to augment forensic investigations by providing an objective, data-driven alternative to traditional assessments and increasing the efficiency of evidence processing. This research confirms the feasibility and relevance of leveraging advanced AI models to develop powerful new tools for Forensic Science. It is expected that this study will contribute worldwide to help (1) the police indict criminals and prove innocence; (2) the justice system judges and proves people guilty of their crimes. Full article

The purpose of this study is to provide a context-based empirical investigation of the racialized effect of policing on the financial performance of Black entrepreneurs. Given the historical role of race in policing in the United States, we expect that the degree of the policing of the Black population in a state will be negatively associated with the financial performance of Black entrepreneurs in the state. The sample for this study is drawn from quarterly police stop data across 14 states from the Stanford Open Policing Project, which is matched with state-level data from the Merchant Maverick ranking of best states for Black entrepreneurs. The sample size is 164 observations over 2013–2015 pertaining to police search rates of Blacks. Findings from the moderated, multivariate regression analysis reveals that the adverse effect of the policing of Black Americans on Black entrepreneurs’ financial performance can be relieved by state-level religiosity and the legalization of marijuana (or cannabis; a mind-altering drug produced from the hemp plant). This research demonstrates the important role of religious and legal institutional mechanisms in countering the economically destructive effects of policing on Black entrepreneurship in the United States. Full article

The rapid rise of AI-driven cybercrime and deepfake fraud poses complex organisational challenges for US law enforcement, particularly the Federal Bureau of Investigation (FBI). Applying Maguire’s (2003) police organisation theory, this qualitative single-case study analyses the FBI’s structure, culture, technological integration, and inter-agency collaboration. Findings underscore the organisational strengths of the FBI, including a specialised Cyber Division, advanced detection tools, and partnerships with agencies such as the Cybersecurity and Infrastructure Security Agency (CISA). However, constraints, such as resource limitations, detection inaccuracies, inter-agency rivalries, and ethical concerns, including privacy risks associated with AI surveillance, hinder operational effectiveness. Fragmented global legal frameworks, diverse national capacities, and inconsistent detection of advanced deepfakes further complicate responses to this issue. This study proposes the establishment of agile task forces, public–private partnerships, international cooperation protocols, and ethical AI frameworks to counter evolving threats, offering scalable policy and technological solutions for global law enforcement. Full article

Street crime is a critical public concern, attracting wide social and research attention. Conventional solutions to reduce street crimes are dispatching more police force in patrol and installing more cameras for street surveillance, which, however, suffer from huge manpower and financial consumption and limited performance. Inspired by the wide application of Unmanned Aerial Vehicles (UAVs) in policing and other related missions such as street surveillance, we investigate the use of UAVs in patrolling along high-risk streets to deter street crimes. UAVs significantly outperform police officers and street cameras in terms of cost reduction and deterring performance improvement. Technically, this paper proposes a data-driven framework to schedule the patrol UAVs, including an online patrol path planning module and an offline UAV station siting module. In the first module, the street-level deterring effect of the UAVs is estimated using a prediction-enhanced method, which guides the UAVs to patrol the high-risk streets more efficiently. Evolved from the path planning algorithm, the second module utilizes a data-driven method to estimate the deterring effect of the candidate UAV stations with different numbers of UAVs. Then both the location of the UAV stations and the UAVs at each station are determined. The proposed framework is comprehensively evaluated using a 6-year crime dataset of the Denver city. The results show that the proposed framework improves the deterring effect by 58.49% on average, and up to 157.32% in extreme cases compared to baselines. Full article

A series of incidents involving damage to vehicle speed sensor cables occurred in an urban area in Japan. At the request of the police, DNA analysis was conducted to identify the animal species responsible. Swab samples collected from the damaged sections of the cables were subjected to PCR testing using mtDNA fragments. Sequencing analysis with universal primers (SCPH02500, SCPL02981) detected DNA from the Japanese marten (Martes melampus). A comprehensive examination that included morphological analysis of the cable damage and consideration of the ecological characteristics of the Japanese martens suggested that the damage was likely caused by this species. DNA analysis using mtDNA markers is a valuable tool for species identification in wildlife forensic veterinary investigations and serves as important scientific evidence in criminal cases involving animals. The findings from this case may contribute to future investigations in forensic veterinary science and ecological research and may also inform measures to prevent human–wildlife conflicts involving animals. Full article

This study examines the relationship between organizational commitment and administrative management within a public service institution operating in an emerging governance context. Grounded in the three-component model of organizational commitment (affective, continuance, and normative) and classical administrative theory (planning, organizing, directing, and controlling), the research investigates how internal psychological bonds among frontline personnel influence institutional performance. A quantitative, cross-sectional, non-experimental design was applied, surveying 30 operational police officers using validated Likert-scale instruments. The results reveal a strong and statistically significant positive correlation between organizational commitment and administrative management (Spearman’s ρ = 0.775, p < 0.01), with normative commitment displaying the highest effect size (ρ = 0.812). These findings underscore the critical role of ethical obligation, loyalty, and affective alignment in enhancing managerial coherence and institutional responsiveness. The study contributes to ongoing debates on public sector reform and strategic human capital management by emphasizing the need for emotionally engaged and ethically anchored personnel. It aligns with Sustainable Development Goals (SDGs) 16 (Peace, Justice, and Strong Institutions) and 8 (Decent Work and Economic Growth), promoting inclusive, accountable governance and resilient administrative practices in resource-constrained environments. Full article

The aim of this study was to investigate whether juror characteristics, namely, age, attitudes surrounding coercive control and psychopathic personality traits (PPT), can influence Guilty or Not Guilty verdicts in a developed coercive control trial. One hundred and thirty-five participants (N = 135) completed an online survey consisting of elements of a mock coercive control trial and three questionnaires: the Coercive Control subsection of the Modern Adolescent Dating Violence Attitudes (MADVA (CC)) Scale, the Psychopathic Personality Traits Scale—Revised (PPTS-R) and the Juror Decision Scale (JDS). The results of the analysis demonstrated significant positive correlations between MADVA (CC) scores and all four subscales of the PPTS-R, highlighting the relationship between psychopathy traits and coercive control attitudes. Binary logistic regression findings showed that higher scores on the MADVA (CC) Scale were the only significant predictor of returning a Not Guilty verdict. Those who also returned a Not Guilty verdict had more accepting controlling behaviour attitudes, scored higher for defendant believability and were less confident in their overall decision. Findings from the current study highlight the significance of attitudes in a juror decision-making context. The significance of attitudes may also be applicable to police officers and other agencies within the criminal justice system. Additional efforts need to be made regarding the identification of coercive control tactics, and training programmes should be implemented within the police to increase identification of these behaviours in order and to improve case progression. This may increase the likelihood of a jury being required in these cases. Furthermore, Not Guilty verdicts were given with significantly less confidence than Guilty verdicts, although they have the same influence at trial. More research needs to be carried out to explore the development and maintenance of accepting attitudes towards coercive control, and there is a need for better education regarding coercive control to attempt to tackle harmful attitudes towards it and aim for fairer trials. Full article

Gender-based violence (GBV) is a profound and pervasive societal issue, disproportionately affecting women across diverse settings, including homes, workplaces, and public spaces. Despite its prevalence, significant challenges impede research on GBV, particularly regarding data collection, analysis, and ethical handling. This study investigates the complexities inherent in GBV research, focusing on the obstacles posed by under-reporting, ethical considerations, data quality, and the need for cross-comparative standards. Using a combination of police records, web scraping, news reports, and survey data from USAID’s Demographic and Health Surveys (DHS), our study examines strategies to work with sensitive GBV datasets, while maintaining data integrity. Our study advocates for improved demographic surveying and data integration methodologies that can enhance data accuracy and comparability. The findings suggest that while technological advancements, particularly generative AI and machine learning approaches, offer promising avenues for automating survey processes, reducing costs, and enhancing data collection efficiency, they present the limitations of secondary datasets, a lack of data disaggregation, and discrepancies in data coding systems, which highlight the necessity of refining global data standards. Full article

Facial soft tissue reconstruction is an important tool in forensic investigations, especially when conventional identification methods are unsuccessful. This paper presents a digital workflow for facial reconstruction and identity verification using computer vision techniques applied to two forensic cases. The first case involves a cold case from 1993, in which a manual reconstruction by Prof. Helmer was conducted in 1994. We digitally reconstructed the same individual using CAD software (Blender), enabling a direct comparison between manual and digital techniques. To date, the deceased remains unidentified. The second case, from 2021, involved a digitally reconstructed face that was later matched to a missing person through DNA analysis. Here, comparison material was available, including an official photograph. A police officer involved in the case noted a “striking resemblance” between the reconstruction and the photograph. To evaluate this subjective impression, we performed quantitative analyses using three face recognition models (Dlib-based method, VGG-Face, and GhostFaceNet). The models did not indicate significant similarity, highlighting a gap between human perception and algorithmic assessment. These findings suggest that current face recognition algorithms may not yet be fully suited to evaluating reconstructions, which tend to deviate in subtle but critical facial features. To achieve better facial recognition results, further research is required to generate more anatomically accurate and detailed reconstructions that align more closely with the sensitivity of AI-based identification systems. Full article

The S$\grave{ọ}$r$\grave{ọ}$-Sókè movement, sparked by Nigeria’s 2020 #EndSARS protests, represents a pivotal stand against systemic injustice, with its Yoruba rallying cry “S$\grave{ọ}$r$\grave{ọ}$-sókè” (“Speak Up” or “Speak Louder”) capturing the collective demand to end police brutality, notably, by the Special Anti-Robbery Squad (SARS). This study employs Digital Artivism as its theoretical lens to investigate the fusion of art and activism within the movement, analyzing how creative and performative expressions amplified its message and mobilized diverse populations. Applying Feldman’s Model of Art Criticism, it dissects the theatrical elements of selected protest artworks, revealing their role in inciting resistance and fostering solidarity in the pursuit of justice. By situating S$\grave{ọ}$r$\grave{ọ}$-Sókè within global discourses on art and social justice, this research underscores its significance as a model of artivism’s power to challenge oppressive systems and inspire collective action. The critique of these artworks illustrates their lasting influence on Nigeria’s socio-political landscape and their resonance with worldwide struggles against systemic violence and inequality. Highlighting the transformative potential of theatrical activism, this study advances understanding of how digital artivism can unite voices, elevate causes, and drive societal change. Full article

This article addresses the impact of generative artificial intelligence on the creation of composite sketches for police investigations. The automation of this task, traditionally performed through artistic methods or image composition, has become a challenge that can be tackled with generative neural networks. In this context, technologies such as Generative Adversarial Networks, Variational Autoencoders, and Diffusion Models are analyzed. The study also focuses on the use of advanced tools like DALL-E, Midjourney, and primarily Stable Diffusion, which enable the generation of highly detailed and realistic facial images from textual descriptions or sketches and allow for rapid and precise morphofacial modifications. Additionally, the study explores the capacity of these tools to interpret user-provided facial feature descriptions and adjust the generated results accordingly. The article concludes that these technologies have the potential to automate the composite sketch creation process. Therefore, their integration could not only expedite this process but also enhance its accuracy and utility in the identification of suspects or missing persons, representing a groundbreaking advancement in the field of criminal investigation. Full article

Intimate partner violence (IPV) is a public health and social problem worldwide. However, most studies have concentrated on violence against women and not also against men. Interventions for victimized men will only be successful if there is a better understanding of the real experiences, as narrated by the victims themselves, and how these impact their health and wellbeing. This study aimed to investigate the experiences of intimate partner violence, health, and wellbeing among men in east-central Sweden. Data were gathered using eleven in-depth, semi-structured interviews with men who were victims of IPV. Four categories emerged from the analyses: experiences of abuse in the relationship; feelings of isolation, loneliness, and shame; perceived deterioration of health and wellbeing; and negative experiences with public services. The findings indicate that interviewees experienced psychological (rather than physical) violence at the hands of their intimate partner. The abuse had consequences for their health and wellbeing, as they experienced stress, anxiety, depression, and suicidal thoughts. In some instances, it affected their health behavior, as they reverted to alcohol and drug use to cope with the abuse. Moreover, the interviewees felt lonely and unwilling to disclose their suffering because of fear of what family, friends, society, and professionals across different services would think of them. Also, they experienced negative responses from the health and social care services and police when seeking help, which made them even more entrenched in their fear of disclosing the suffering caused by the abuse. Full article

Background: Capsaicin is commonly used as a flavoring and a riot control agent. However, long-term exposure or high doses can cause acute lung injury in military and police personnel. The mechanisms underlying capsaicin-induced pulmonary toxicity remain unclear. Therefore, this study investigated the molecular mechanisms involved in capsaicin-induced acute lung injury using C57BL/6N mice. Methods: Through both transcriptomic and proteomic analyses of mouse lung tissue, we identified the involvement of the TNF signaling pathway in capsaicin-mediated acute lung injury. Next, we explored the role of TNF signaling in the progression of acute lung injury to identify potential therapeutic targets. In a capsaicin-induced acute lung injury mouse model and A549 cells, we assessed the therapeutic potential of the TNF-α antibody Nerelimomab. Compared with the control group, TNF-α up-regulation was observed, which correlated with increased pathological changes and elevated IL-6 (p < 0.01) and IL-18 (p < 0.01) levels, both in vivo and in vitro. Results: Flow cytometry revealed that compared to the capsaicin group, Nerelimomab treatment reduced the number of capsaicin-induced apoptotic cells (p < 0.001) and was associated with an increased Bcl-2/Bax ratio (p < 0.01) and reduced cleaved caspase 3 expression (p < 0.001). Analysis of A549 cells treated with capsaicin and Nerelimomab corroborated these results. These findings confirm the involvement of the TNF signaling pathway in capsaicin-induced acute lung injury and the apoptosis of alveolar epithelial cells. Conclusions: In conclusion, capsaicin inhalation can cause acute lung injury, and targeting the TNF signaling pathway offers a promising therapeutic strategy. Nerelimomab demonstrates significant potential in alleviating acute lung injury by inhibiting inflammatory mediator release and diminishing apoptosis. Based on transcriptomic and proteomic analyses, this study highlights the crucial role of the TNF signaling pathway in capsaicin-induced acute lung injury and supports the therapeutic efficacy of Nerelimomab in reducing epithelial apoptosis. Full article

Pedestrian safety is a critical concern worldwide, as pedestrians account for nearly a quarter of all road crash deaths. In Poland, in the last decade, the number of pedestrians killed in road accidents varied from 25 to 30% of all road accident victims each year. A similar tendency is observed in EU countries, but the average number of pedestrian fatalities is lower and amounts to 20%. Numerous activities have been undertaken to improve the safety of vulnerable road users. Land planning plays a crucial role in enhancing pedestrian safety. Effective land-use planning can mitigate risks by integrating pedestrian-friendly infrastructure into urban design. Numerous measures have been implemented to improve the safety of vulnerable road users, including education campaigns, speed reduction measures, and infrastructure enhancements. One of the latest initiatives involves enhancing the visibility of pedestrian crossings through the installation of additional lighting systems. In order to assess the effects of the undertaken activities, a number of zebra crossings with and without additional luminance were investigated. Crash data gained from police statistics, along with the calculated crash rates (CRs), were utilized to evaluate changes in safety performance at selected crosswalks. For this purpose, a „before–after” method was applied. Importantly, the research results did not show a clear impact of additional lighting on reducing the number of road crashes and they highlight that other factors, including the geometric characteristics of crossings and their location and proximity to land uses generating significant pedestrian traffic, significantly influence crash rates. Full article