مطالب

Background: Since the advent of modern policing, technological innovations in communication and information management have significantly shaped investigative practices and crime detection strategies. Aims: The current research study explores the transformative role of Artificial Intelligence in modern crime detection and prevention across diverse domains including cybercrime, environmental crime, financial fraud, and urban surveillance. Methodology: Employing a qualitative meta-synthesis methodology, the research critically examines peer-reviewed literature published between the years 2015 and 2025 to identify emerging trends, technological innovations, and socio-legal implications associated with AI-driven policing. Findings: The key findings highlight the integration of machine learning, computer vision, and natural language processing techniques into the predictive and real-time law enforcement systems. These technologies have demonstrably enhanced the accuracy, efficiency, and responsiveness of crime prevention strategies. However, the current study also reveals significant challenges, including algorithmic bias, lack of transparency, and inadequate regulatory oversight, particularly in socially stratified or underregulated contexts. Conclusion: The current article underscores the necessity of embedding explainability, accountability, and human oversight into Artificial Intelligence systems to ensure the ethical and equitable implementation of AI-driven policing systems.

This study examines how news headlines about the October 7, 2023, Gaza crisis employ linguistic structures to convey predetermined framing and reinforce power dynamics. Drawing on Information Structure Theory and the analytical framework of information packing theory, a corpus of 50 headlines from major international outlets (The New York Times, Reuters, CNN, AP, BBC, The Guardian, Al Jazeera) published between October 2023 and July 2025 was analyzed using qualitative discourse analysis. Information Structure Theory examines how speakers and writers organize and highlight pieces of information in sentences, such as what is presented as known or new, important or backgrounded, to guide the listener or reader’s attention and interpretation. The study investigates how syntactic and grammatical choices frame events, highlight causes, assign or obscure responsibility, and shape readers’ interpretations and thematic focus. Findings reveal that headlines systematically manipulate information structures to achieve pragmatic effects. Here, foregrounding (preposing) emphasizes key actors or consequences; postposing constructions activate presuppositions and dramatize urgency; passive voice, inversion, and interrogatives obscure responsibility and subtly assign or obscure blame; also, expansion constructions (relative clauses, appositives, and parentheticals) enrich context and amplify humanitarian or emotional dimensions. Overall, the study shows that linguistic choices function as pragmatic tools for managing discourse, framing narratives, and influencing perceptions of accountability. These results underscore the ideological and power dynamics embedded in news production and highlight the importance of analyzing information structures to understand how media discourse shapes public understanding and meaning.

The aim of this paper is to examine both the potential and limitations of Hegelianism in contemporary epistemology. To achieve this, the paper first explores Robert Brandom's interpretation of Phenomenology of Spirit in his 2019 work, Spirit of Trust. In this context, Hegel is positioned as a precursor to the holistic, historical, and social dimensions of belief, as well as a critic of the empiricist intuitions prevalent in modernity, aligning with the framework of American inferentialism. This section demonstrates that it is possible to discuss the constitution of concepts without invoking sensations or immediate knowledge. The paper then turns to the reception of Brandom’s proposal by scholars such as Richard Rorty and Slavoj Žižek, who concurs that Brandom falls short in maintaining a radical stance toward empiricism, and highlight the ethical and political challenges inherent in Brandom’s neo-Hegelian inferentialism. In this section, it becomes evident that Brandom’s concept of the Hegelian absolute and his notion of remembrance cannot be reconciled with a conception of reality as negative and contingent, a view that assumes progressiveness—something Žižek, in contrast, succeeds in recognizing within Hegel's philosophy.

Purpose : This study systematically reviews the advantages and disadvantages of using ChatGPT in higher education. Method : This systematic review adheres to PRISMA guidelines. The search was conducted using the terms "ChatGPT" and "chatbot" for the years 2021–2024 in Google Scholar, ResearchGate, Web of Science, and PubMed via Publish or Perish (version 8). A total of 365 records were retrieved, and after screening, 35 relevant studies were included. Findings : The analysis indicate that 66% of the reviewed studies highlighted the benefits of ChatGPT in higher education, including enhancements in cognitive and learning skills, support for research and writing, improvements in language and communication, and automation of certain tasks to increase efficiency. Additionally, advantages such as 24/7 availability, quick responses, topic diversity, privacy, and easy access to past interactions were noted. Among the advantages that received the most attention are optimization of academic training, enhancement of cognitive and learning skills, and assistance in the research and development process. However, 75% of the studies discussed disadvantages, including concerns about plagiarism, ethical issues, negative perceptions, lack of audiovisual communication, absence of human interaction, technical limitations, and restricted multi-dimensional engagement.  Among the most prominent disadvantages are ethical concerns, plagiarism, and lack of uniformity in responses. Conclusion : While ChatGPT offers significant benefits in education, its limitations require careful consideration to ensure responsible and effective use. Specifically, to address these disadvantages, practical measures such as the development of policies and ethical guidelines should be implemented to ensure responsible and optimal use of this technology in education.

In this research, first the financial criteria used in capital decision-making were identified and refined, then the most effective criteria were selected based on the deep learning algorithms including: RF, XGBoost, and LightGBM. In this stage, 11 factors were selected from the 35 factors found in previous research. In the next stage, based on the Forensic-Based Investigation algorithm (FBI), feasible investment options were identified and the internal rate of return was calculated over a 5-year period, and 42 companies that had an internal rate of return higher than the risk-free investment were selected as feasible investment options. During the next stage, different random combinations were used as investment portfolios using three methods: equal weight allocation, mean-variance model, and hierarchical risk preference model. Investment weights were determined for each invested share (combination) and investment returns were evaluated using different metrics. Finally, in order to validate the findings, the feasible investment options were divided into two categories of companies active in the financial industry and others, and the superiority of decision-making (higher returns) in a dynamic process was accepted.

The topic of Iranian identity is one that many are willing to recognize, while only a minority choose to reject it. The author of the book in question belongs to the latter group. The title suggests that the author intends to challenge both Iran and the historical foundations of Iranian and national identity. Influenced by contemporary theoretical discussions that overlook the historical and cultural contexts of the nations being examined, he tends to regard Iran and its national identity as constructs devised by Orientalists. He does not acknowledge the historical importance and development of the term "Iran" itself. The author of the book Iran as Imagined Nation: The Construction of National Identity, who draws inspiration from Edward Said's Orientalism and Benedict Anderson's Imagined Communities, contends that both Iranian and non-Iranian authors view Iranian and national identity as a historical phenomenon. These authors, influenced by racial and ideological perspectives and western methodologies, have narrated history in a way that is both ahistorical and misleading, replacing genuine historical events with fabricated stories. This article does not critique every chapter of the book Iran as Imagined Nation: The Construction of National Identity. Instead, it will concentrate on chapters that present weak or incorrect claims regarding Iran's historical roots, its attributes, and its ethnic and linguistic diversity, with the aim of clarifying and illuminating these issues.

In Bird Cottage by Eva Meijer, the main character blurs the dualistic dichotomies between humans and animals by applying ethical practices, morality, and emotion. Ecofeminists stand against the Western reason/emotion dichotomy, and they mutilate human/animal dichotomies by cherishing ethics and morality. In literature and environmental concerns the traces of Ethics and Ecofeminism should be followed. Hence, in this article, by referring to theoreticians like Carolyn Merchant, Gwen Hunnicutt, Lori Gruen, and other eminent critics, Bird Cottage by Eva Meijer is analyzed through an ethical-ecofeminist perspective, not only to show the influence of ethics on deforming dualisms between humans and nonhumans, which is a purpose of ecofeminism, but also to show the social influence of dualistic and non-dualistic relations on humans by following and not following ethics. Considering ecofeminism and its scope in this analysis, it is concluded that Meijer in Bird Cottage emphasizes utilizing ethics and environmental justice in seeking non-dualistic coexistence with nonhumans and, in the interim, she deforms Western human/animal dualism by referring to Len’s attitude and her actions toward wild birds.

The impact of colonization on identity construction has emerged as a critical area of inquiry, particularly among postcolonial writers, novelists, and theorists. This paper investigates the psychological and cultural ramifications of colonial domination on the identity formation of colonized individuals, with particular emphasis on experiences of alienation and identity loss. Kiran Desai’s novel The Inheritance of Loss (2006) is analyzed through the theoretical frameworks of Stuart Hall’s concept of cultural identity and Frantz Fanon’s exploration of colonial trauma and its effects on subjectivity. This study contends that colonization fundamentally disrupts the continuity of cultural identity and induces a condition of psychological fragmentation, resulting in enduring displacement, alienation, and a decentered sense of self among the colonized. The findings demonstrate that in The Inheritance of Loss, colonial trauma manifests through internalized cultural inferiority, linguistic alienation, and intergenerational identity rupture, particularly visible in the judge’s self-erasure and Biju’s diasporic disillusionment. These experiences reveal a uniquely postcolonial condition of fractured identity, marked by alienation, double displacement, and a decentered sense of self rooted in the enduring psychological legacies of colonial domination.

Objective : This study investigates how waste storage, waste quality, and market dynamicity influence the economic and environmental performance of industrial symbiosis networks in Iran’s food sector.  Methodology: A hybrid simulation approach, combining agent-based modeling and discrete event simulation, is employed to analyze the dynamics of industrial symbiosis networks in the food sector in Iran. This integrated method enables a detailed examination of how waste quality, storage duration, and market dynamicity jointly affect network performance. The model is implemented and simulated using AnyLogic software. Results : The simulation results demonstrate that effective management of waste storage is essential for improving the economic and environmental performance of industrial symbiosis networks in the food sector. Extending the storage duration allows firms to better align waste supply with demand, which is particularly valuable in volatile markets. However, the benefits of longer storage depend on waste quality: for high-quality waste, additional storage costs are offset by higher exchange values, while for low-quality waste, prolonged storage mainly increases costs and reduces profitability. The study also finds that waste storage strategies can substantially buffer the negative effects of market fluctuations. Conclusion : This paper advances circular economy research by presenting an analytical framework that integrates agent-based modeling and discrete event simulation to analyze industrial symbiosis networks. The findings suggest that managing storage duration can improve economic and environmental outcomes, while waste storage strategies help firms mitigate the negative impacts of market volatility. These insights can help managers and policymakers improve waste management in Iran’s food sector.

Background: This study explores the paradoxical role of artificial intelligence as both a tool of exploitation within surveillance capitalism and a force for resilience in disaster risk management, highlighting the ethical and governance challenges that arise at the intersection of these domains. Aims: This article aims to enable the ethical use of AI in DRM while insulating public systems from the structural harms of commercial data exploitation. Methodology: Drawing from a comparative qualitative analysis of 35 academic sources, the study investigates how BigTech corporations and data brokers leverage AI to commodify personal data, consolidate informational power, and erode democratic agency. Results: The present study critically examines the dual role of artificial intelligence in contemporary digital society, contrasting its exploitative deployment within surveillance capitalism with its constructive use in disaster risk management (DRM). Simultaneously, it highlights a parallel body of research showcasing AI’s capacity to enhance early warning systems, situational awareness, and post-disaster recovery, especially in resource-constrained and climate-vulnerable regions. Conclusion: To reconcile these conflicting trajectories, the article proposes the Public AI for Resilience (PAIR) framework—a governance model grounded in data sovereignty, public infrastructure, algorithmic explainability, and cross-sectoral collaboration. Ultimately, the article argues for a normative recalibration of AI governance that prioritizes equity, transparency, and collective resilience over market imperatives, demonstrating that AI’s public good potential can be realized without surrendering to surveillance-based capitalism.