Search Results (24)

Gun violence is a global problem that affects communities and individuals, posing challenges to safety and well-being. The use of autonomous weapons detection systems could significantly improve security worldwide. Despite notable progress in the field of weapons detection closed-circuit television-based systems, several challenges persist, including real-time detection, improved accuracy in detecting small objects, and reducing false positives. This paper, based on our extensive experience in this field and successful private company contracts, presents a detection scheme comprising two modules that enhance the performance of a renowned detector. These modules not only augment the detector’s performance but also have a low negative impact on the inference time. Additionally, a scale-matching technique is utilised to enhance the detection of weapons with a small aspect ratio. The experimental results demonstrate that the scale-matching method enhances the detection of small objects, with an improvement of +13.23 in average precision compared to the non-use of this method. Furthermore, the proposed detection scheme effectively reduces the number of false positives (a 71% reduction in the total number of false positives) of the baseline model, while maintaining a low inference time (34 frames per second on an NVIDIA GeForce RTX-3060 card with a resolution of 720 pixels) in comparison to the baseline model (47 frames per second). Full article

The current review explores multiple definitions of school shootings used by myriad data collection platforms and by various scholars. Importantly, the impacts of definitional discrepancies on inclusion criteria, data divergence, research, policy, and public perception are discussed at length. The review concludes with a call to Criminologists and school gun violence scholars to better collaborate on what should be considered a “school shooting” and lists five benefits that may result from modifying school gun violence definitions and data collection methodologies. Full article

Gun and street group violence remains a serious problem in cities across the United States and the focused deterrence strategy has been a widely applied law enforcement intervention to reduce it. Although two meta-analytical studies concluded that the intervention had a significant effect on violence, questions remain about how violence changes across space and time during and after the intervention. This study applies novel geospatial analyses to assess spatiotemporal changes in gun violence before, during, and after the implementation of Philadelphia Focused Deterrence. Emerging hot spot analysis employing Space-Time cubes of ten annual time bins (2009–2018) at the Thiessen polygon level was used to detect and categorize patterns. The analyses revealed a non-significant decreasing trend across the ten-year period. Furthermore, there were ninety-three statistically significant hot spots categorized into four hot spot patterns: fourteen new hot spots; twenty-three consecutive; one persistent; and fifty-three sporadic. There was no evidence showing statistically significant hot spots for the “diminishing” pattern. Knowledge of these patterns that emerge across micro-locations can be used by law enforcement practitioners to complement data-driven problem solving and fine tune these strategies and other place-based programming. Policymakers can use findings to prioritize resources when developing complementary prevention and intervention efforts by tailoring those efforts to the different emergent patterns. Full article

Over the years, the field of forensic anthropology has become more diverse, bringing unique perspectives to a previously homogeneous field. This diversification has been accompanied by recognizing the need for advocacy and activism in an effort to support the communities we serve: marginalized communities that are often overrepresented in the forensic population. As such, forensic anthropologists see the downstream effects of colonialism, white supremacy, inequitable policies, racism, poverty, homophobia, transphobia, gun violence, and misogyny. Some argue that advocacy and activism have no place in forensic anthropological praxis. The counterarguments for engaging in advocacy and activism uphold white, heterosexual, cisgender, and ableist privilege by arguing that perceived objectivity and unbiased perspectives are more important than personally biasing experiences and positionality that supposedly jeopardize the science and expert testimony. Advocacy and activism, however, are not new to the practice of anthropology. Whether through sociocultural anthropology, archaeology, or other areas of biological anthropology, activism and advocacy play an important role, using both the scientific method and community engagement. Using a North American approach, we detail the scope of the issues, address how advocacy and activism are perceived in the wider discipline of anthropology, and define ways in which advocacy and activism can be utilized more broadly in the areas of casework, research, and education. Full article

Gun violence and mass shootings kill and injure people, create psychological trauma, damage properties, and cause economic loss. The loss from gun violence can be reduced if we can detect the gunshot early and notify the police as soon as possible. In this project, a novel gunshot detector device is developed that automatically detects indoor gunshot sound and sends the gunshot location to the nearby police station in real time using the Internet. The users of the device and the emergency responders also receive smartphone notifications whenever the shooting happens. This will help the emergency responders to quickly arrive at the crime scene, thus the shooter can be caught, injured people can be taken to the hospital quickly, and lives can be saved. The gunshot detector is an electronic device that can be placed in schools, shopping malls, offices, etc. The device also records the gunshot sounds for post-crime scene analysis. A deep learning model, based on a convolutional neural network (CNN), is trained to classify the gunshot sound from other sounds with 98% accuracy. A prototype of the gunshot detector device, the central server for the emergency responder’s station, and smartphone apps have been developed and tested successfully. Full article

Abdominal injuries in children caused by guns are a rare clinical entity globally. But, in countries with undefined legal regulations and in war zones, urban violence is a tremendous social problem among older children and adolescents. This manuscript provides details regarding two cases of severe gunshot injuries in young children. The injuries were very complicated and included damage to the parenchymatous and hollow organs and major blood vessels. The clinical presentation on admission was severe and dramatic, but the patients survived. However, one patient developed numerous complications that required repeated surgical interventions and long treatment. This article provides a detailed description of injuries and how to treat them. Patient care requires a multidisciplinary approach, and the initial decision on further treatment depends on the patient’s hemodynamic stability. Full article

Introduction. Environmental Health in a Global World at New York University was re-designed as a class participatory effort, challenging undergraduate students to understand environmental hazards and the resultant adverse health outcomes by embracing the inherent complexity of environmental risks and proposing solutions. Methods. Following introductory lectures, students are placed into teams and assigned a specific perspective, or avatar, which includes learning to see the challenge from the perspective of a technical expert such as a biologist, an engineer, or an anthropologist. The teams then design specific systems maps to visualize the complex interactions that lead to adverse health outcomes after a given environmental exposure. The maps highlight potential leverage points where relatively minor interventions can provide a disproportionate benefit in health outcomes. The teams then explore potential interventions and identify the potential unintended consequences of those actions, develop and advocate for innovative new strategies to mitigate risk and improve outcomes. Results and Discussion. Over the past 5 years, we have taught this methodology to over 680 students with strong, student-oriented results. The teams created and presented more than 100 strategies, addressing a diverse set of environmental challenges that include water contamination, gun violence, air pollution, environmental justice, health security, and climate change. Developing the strategies helped the students understand environmental threats in a more holistic way, provided them with some agency in finding solutions, and offered an opportunity for them to improve their presentation skills. The responses in course evaluations have been enthusiastic, with many students reporting a deep impact on their college experience. Full article

This paper discusses the implications of Sarah Josepha Hale’s polarizing opposition to the franchise of women on her legacy award, given to many authors since its inception, but most notably to contemporary women writers whom Hale likely would have rejected. In 2019, the award went to Jodi Picoult, an author who bridges journalistic writing on topics such as abortion, white supremacy, and gun violence, among others, with fiction novel writing. Hale’s own works are archived through the Richards Free Library, and as such, the award is given for the entire collective body of work of one nominated literary person. The award impacts not only Picoult’s career but Hale’s legacy as an open opposer to the franchise of women, as well as the opportunities for contemporary women writers. Full article

This article explores the motivations behind adherents to Christian nationalism using several inter-related psychoanalytic theoretical lenses. Following a description of Christian nationalist beliefs, four conscious motivations for joining will be outlined first, including recruitment tactics/evangelization that fulfill the need for belonging and a sense of sacred purpose, the fear of loss of white social status, fear of loss of patriarchal authority and hierarchy, and the allure of conspiracy theories such as QAnon for conservative Christians. This will be followed by a more in-depth discussion of unconscious dynamics that can fuel individuals’ adoption of a Christian-nationalist belief system, including group dynamics and Freud’s insights into the power of a charismatic leader, the allure of guns reflecting deeper unconscious fears of emasculation, paranoid splitting and the role of trauma, and, finally, the ways in which this segment of American Christianity may be unconsciously carrying disavowed and split-off aggression towards other Christians—and how better integration might be achieved through nonviolent resistance to injustice, and positive political engagement. Full article

The United States has had more mass shooting incidents than any other country. It is reported that more than 1800 incidents occurred in the US during the past three years. Mass shooters often display warning signs before committing crimes, such as childhood traumas, domestic violence, firearms access, and aggressive social media posts. With the advancement of machine learning (ML), it is more possible than ever to predict mass shootings before they occur by studying the behavior of prospective mass shooters. This paper presents an ML-based system that uses various unsupervised ML models to warn about a balanced progressive tendency of a person to commit a mass shooting. Our system used two models, namely local outlier factor and K-means clustering, to learn both the psychological factors and social media activities of previous shooters to provide a probabilistic similarity of a new observation to an existing shooter. The developed system can show the similarity between a new record for a prospective shooter and one or more records from our dataset via a GUI-friendly interface. It enables users to select some social and criminal observations about the prospective shooter. Then, the webpage creates a new record, classifies it, and displays the similarity results. Furthermore, we developed a feed-in module, which allows new observations to be added to our dataset and retrains the ML models. Finally, we evaluated our system using various performance metrics. Full article

This review article highlights the disparities evident in pediatric trauma care in the United States. Social determinants of health play a significant role in key aspects of trauma care including access to care, gun violence, child abuse, head trauma, burn injuries, and orthopedic trauma. We review the recent literature as it relates to these topics. The findings from these recent studies emphasize the important principle that trauma care for children should be designed with a focus on equity for all children. Full article

Gun violence has been on the rise in recent years. To help curb the downward spiral of this negative influence in communities, machine learning strategies on gunshot detection can be developed and deployed. After outlining the procedure by which a typical type of gunshot-like sounds were measured, this paper focuses on the analysis of feature importance pertaining to gunshot and gunshot-like sounds. The random forest mean decrease in impurity and the SHapley Additive exPlanations feature importance analysis were employed for this task. From the feature importance analysis, feature reduction was then carried out. Via the Mel-frequency cepstral coefficients feature extraction process on 1-sec audio clips, these extracted features were then reduced to a more manageable quantity using the above-mentioned feature reduction processes. These reduced features were sent to a random forest classifier. The SHapley Additive exPlanations feature importance output was compared to that of the mean decrease in impurity feature importance. The results show what Mel-frequency cepstral coefficients features are important in discriminating gunshot sounds and various gunshot-like sounds. Together with the feature importance/reduction processes, the recent uniform manifold approximation and projection method was used to compare the closeness of various gunshot-like sounds to gunshot sounds in the feature space. Finally, the approach presented in this paper provides people with a viable means to make gunshot sounds more discernible from other sounds. Full article

Urban gun violence is a critical human health and social justice issue. Strategies to reduce urban gun violence are increasingly being taken out of the domain of police and into community-based programs. One such community-driven gun violence reduction program analyzed here is called Advance Peace. Advance Peace (AP) uses street outreach workers as violence interrupters and adult mentors to support the decision making and life chances of those at the center of urban gun violence. We reported on the impact Advance Peace had on gun violence and program participants in the City of Sacramento, California, from 2018–2019. Using an interrupted time series model, we attributed a gun violence reduction of 18% city wide and up to 29% in one of the AP target neighborhoods from the intervention. We also found that of the 50 participants in the Advance Peace Sacramento program 98% were alive, 90% did not have a new gun charge or arrest, 84% reported an improved outlook on life, all received cognitive behavioral therapy, and 98% reported that their AP outreach worker was one of the most important adults in their life. Advance Peace is a viable community-driven, urban gun violence, and healing-focused program. Full article

Non-prescription steroid use can negatively impact adolescent physical and mental health and wellbeing. Determining correlates of this risk behavior is needed to help mitigate its prevalence. Two potential correlates are physical activity and school safety. The purpose of this study was to examine the associations of physical activity, school safety, and non-prescription steroid use within a sample of adolescents from the 2015–2019 US National Youth Risk Behavior Survey (YRBS). A multi-stage cluster sampling procedure yielded a representative sample of US adolescents from the 2015–2019 YRBS (n = 44,066; 49.6% female). Two latent variables indicating physical activity and unsafe schools were the independent variables. The dependent variable was a self-report of non-prescription steroid use. A weighted structural equation model examined the associations between physical activity and unsafe schools with non-prescription steroid use, controlling for age, sex, BMI %tile, race/ethnicity, and sexual minority status. The latent physical activity variable did not associate with non-prescription steroid use (β = 0.007, 95%CI: −0.01–0.02, p = 0.436); however, the unsafe schools latent variable did associate with non-prescription steroid use (β = 0.64, 95%CI: 0.59–0.69, p < 0.001). An unsafe school environment may be a determinant of non-prescription steroid use in adolescents. Physical activity behaviors did not associate with steroid use. Full article

Gun violence drastically increased in urban cities following the ease of shutdown restrictions associated with the Coronavirus Pandemic. The association of gun violence and COVID-19 has highlighted the importance of taking a public health perspective, particularly as it relates to impacts on the Black community. In this article we discuss macro-level factors and community traumas in the city of New Orleans, an area that has had longstanding issues related to gun violence. Community structural issues, traumatic stress from disasters, and recommendations to address disparities in social determinants of health are discussed. Full article