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Development of Biocompatible Barium peroxide/Pluronic F127/L-ornithine Composite for Enriched Antimicrobial, Antioxidant and Anticancer Potential: An in vitro Study
Osteosarcoma (MG-63) is a type of bone cancer affects mostly adolescents and young adults. Disease-causing microorganisms like Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Candida albicans pose serious illness in humans. There is a need to develop multifunctional composite to combat cancer and other most common disease caused by disease causing microorganisms. In this context, BaO2 and pluronic F127, L-Ornithine coated BaO2 (BaO2-PF127-LO) composite have been prepared and characterized by XRD, FTIR, UV-Vis, SEM, HRTEM, EDAX, and XPS analytical techniques. BaO2 and BaO2-PF127-LO were orthorhombic crystalline structure and the crystallite size was found as 32nm for BaO2 and 26nm for modified BaO2 PL studies revealed the green emission observed at 506nm for BaO2-PF127-LO composite which is absent in the case of bare BaO2. Antimicrobial activity of BaO2 and BaO2-PF127-LO was investigated. MTT assay was performed to determine the anticancer potential while the DPPH free radical scavenging assay was carried out to determine the antioxidant potential. The experiment study revealed that the BaO2-PF127-LO exhibited enhanced antimicrobial, antioxidant, and anticancer activity and low toxicity when compared to pristine BaO2. The experimental results revealed that the BaO2-PF127-LO composite holds promising potential for biomedical applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Development of Biocompatible Barium peroxide/Pluronic F127/L-ornithine Composite for Enriched Antimicrobial, Antioxidant and Anticancer Potential: An in vitro Study
Osteosarcoma (MG-63) is a type of bone cancer affects mostly adolescents and young adults. Disease-causing microorganisms like Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Candida albicans pose serious illness in humans. There is a need to develop multifunctional composite to combat cancer and other most common disease caused by disease causing microorganisms. In this context, BaO2 and pluronic F127, L-Ornithine coated BaO2 (BaO2-PF127-LO) composite have been prepared and characterized by XRD, FTIR, UV-Vis, SEM, HRTEM, EDAX, and XPS analytical techniques. BaO2 and BaO2-PF127-LO were orthorhombic crystalline structure and the crystallite size was found as 32nm for BaO2 and 26nm for modified BaO2 PL studies revealed the green emission observed at 506nm for BaO2-PF127-LO composite which is absent in the case of bare BaO2. Antimicrobial activity of BaO2 and BaO2-PF127-LO was investigated. MTT assay was performed to determine the anticancer potential while the DPPH free radical scavenging assay was carried out to determine the antioxidant potential. The experiment study revealed that the BaO2-PF127-LO exhibited enhanced antimicrobial, antioxidant, and anticancer activity and low toxicity when compared to pristine BaO2. The experimental results revealed that the BaO2-PF127-LO composite holds promising potential for biomedical applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Microgrid Energy Management- An Optimization Approach for Operational Cost Reduction
Optimization-based energy management and the related economic viability analysis of replacing a diesel generator alone-based microgrid with a PV, battery, fuel cell and diesel generator-based hybrid microgrid to minimize the operations cost, considering battery degradation and emissions, are presented in this work. The fuel cell considered here is the hydroplus fuel cell, which has minimum emissions, and eliminates the need for hydrogen storage. Mathematical modeling is based on experimentally obtained parameters for fuel consumption coefficients and emissions. The study considers an islanded mode of operation with two different scenarios of microgrid configuration, the first case with the hybrid microgrid working under optimal power conditions, and the second case with only diesel generator available to meet the load demand, for four representative months of the year. Comparing the operations cost under the two scenarios, replacement of a diesel generator-based microgrid, with a PV/battery/hydroplus fuel cell/diesel generator based microgrid resulted in reduction of daily operations cost by 54.06%, 35.25%, 34.38% and 32.71% for the months of January, April, July and October respectively. A sensitivity analysis with varied costs of fuel, operation and maintenance, and battery degradation proved that irrespective of these costs, a considerable amount of reduction in the operations cost is achieved. The results presented here are highly beneficial for application in microgrids worldwide. 2025 IEEE. -
Energy management of hybrid microgrids A comparative study with hydroplus and methanol based fuel cells
Energy management is essential for the efficient operation of microgrids with reduced energy costs and minimized emissions. Energy management of PV/battery/fuel cell/diesel generator-based microgrid to minimize the operations cost considering battery degradation and emissions for a fully functional microgrid existing in the campus of Sultan Qaboos University, Oman, is presented in this work. A microgrid with a state-of-the-art hydroplus fuel cell without the necessity for hydrogen storage is presented in this study with experimentally obtained parameters. Also, a comparison of operations cost with microgrids using two different technologies of PEM fuel cells, one with hydroplus fuel cell and the second with the methanol fuel cell which requires provision for hydrogen storage is performed with three different cases; the scheduled, grid-tied, and islanded with different scenarios under grid-tied mode. The analysis proved that using a hydroplus fuel cell instead of a methanol fuel cell with hydrogen storage reduces the cost of the daily operation by 6.9% in the scheduled mode and 18.2% in the islanded mode. In the grid-tied mode three different grid limits, 20 kW, 15 kW, and 10 kW are considered. The analysis showed no reduction, 1.3% and 5.9% reduction in the operations cost respectively. The results obtained are highly promising to be applied in microgrids where conventional fuel cells are currently employed. The new technology of fuel cells introduced in this study, possesses the advantages of near zero emissions and reduced operations costs besides avoiding the perilousness of hydrogen storage. 2024 Hydrogen Energy Publications LLC -
A comprehensive review on energy management strategy of microgrids
Renewable energy resources are a one-stop solution for major issues that include drastic climate change, environmental pollution, and the depletion of fossil fuels. Renewable energy resources, their allied storage devices, load supplied, non-renewable sources, along with the electrical and control devices involved, form the entity called microgrids. Energy management systems are essential in microgrids with more than one energy resource and storage system for optimal power sharing between each component in the microgrid for efficient, reliable and economic operation. A critical review on energy management for hybrid systems of different configurations, the diverse techniques used, forecasting methods, control strategies, uncertainty consideration, tariffs set for financial benefits, etc. are reviewed in this paper. The novelty of reformer based fuel cells, which generates hydrogen on demand, thereby eliminating the requirement of hydrogen storage and lowest carbon footprint is discussed for the first time in this paper. The topics requiring extended research and the existing gap in literature in the field of energy management studies are presented in the authors perspective, which will be helpful for researchers working in the same specialization. Papers are segregated based on multiple aspects such as the configuration, in particular, grid-tied, islanded, multi microgrids, the control strategies adopted besides the identification of limitations/factors not considered in each work. Moreover, at the end of each section, the literature gap related to each category of segregated group is identified and presented. 2023 The Author(s) -
Novel HGDBO: A Hybrid Genetic and Dung Beetle Optimization Algorithm for Microarray Gene Selection and Efficient Cancer Classification; [Nuevo HGDBO: Un Algoritmo Hrido de Optimizaci Genica y de Escarabajos Peloteros para la Selecci de Genes en Microrrays y la Clasificaci Eficiente del Ccer]
Introduction: ovarian cancer ranked as the seventh most common cancer and the eighth leading cause of cancer-related mortality among women globally. Early detection was crucial for improving survival rates, emphasizing the need for better screening techniques and increased awareness. Microarray gene data, containing numerous genes across multiple samples, presented both opportunities and challenges in understanding gene functions and disease pathways. This research focused on reducing feature selection time in large gene expression datasets by applying a hybrid bio-inspired method, HGDBO. The goal was to enhance classification accuracy by optimizing gene subsets for improved gene expression analysis. Method: the study introduced a novel hybrid feature selection method called HGDBO, which combined the Dung Beetle Optimization (DBO) algorithm with the Genetic Algorithm (GA) to improve microarray data analysis. The HGDBO method leveraged the exploratory strengths of DBO and the exploitative capabilities of GA to identify relevant genes for disease classification. Experiments conducted on multiple microarray datasets showed that the hybrid approach offered superior classification performance, stability, and computational efficiency compared to traditional methods. Ovarian cancer classification was performed using Nae Bayes (NB) and Random Forest (RF) algorithms. Results and Discussion: the Random Forest model outperformed the Nae Bayes model across all metrics, achieving higher accuracy (0,96 vs. 0,91), precision (0,95 vs. 0,91), recall (0,97 vs. 0,90), F1 score (0,95 vs. 0,91), and specificity (0,97 vs. 0,86). Conclusions: these results demonstrated the effectiveness of the HGDBO method and the Random Forest classifier in improving the analysis and classification of ovarian cancer using microarray gene data. 2024; Los autores. -
End-to-End Encryption in Resource-Constrained IoT Device
Internet of Things (IoT) technologies will interconnect with a wide range of network devices, regardless of their local network and resource capacities. Ensuring the security, communication, and privacy protection of end-users is a major concern in IoT development. Secure communication is a significant requirement for various applications, especially when communication devices have limited resources. The emergence of IoT also necessitates the use of low-power devices that interconnect with each other for essential processing. These devices are expected to handle large amounts of monitoring and control data while having limited capabilities and resources. The algorithm used for secure encryption should protect vulnerable devices. Conventional encryption methods such as RSA or AES are computationally expensive and require large amounts of memory, which can adversely affect device performance. Simplistic encryption techniques are easily compromised. To address these challenges, an effective and secure lightweight cryptographic process is proposed for computer devices. This process utilizes a symmetrical encryption key block, incorporating a custom proxy network (SP) and a modified Feistel architecture. Security analysis and performance evaluation results demonstrate that the proposed protocol is secure and energy-efficient. The symmetric key encryption scheme is based on sequences in the Feistel cipher, with multiple rounds and sub-keys generated using principles derived from genetic algorithms. This proposed algorithm minimizes processing cycles while providing sufficient security. 2013 IEEE. -
Integrated hybrid membrane system for enhanced water treatment and desalination for environmental preservation
Technology advancements in desalination, water treatment, and energy efficiency are crucial to preserving our planet. It is critical to find solutions for the future that save natural resources and lessen environmental damage because the freshwater shortage is getting worse, and energy demand is increasing. They face various obstacles, even though their breakthroughs are extremely important. Lot of energy can be utilized for the traditional desalination techniques, as it negatively impacts the environment. Then, the process of the existing Water Treatment (WT) are expensive and ineffective. An Integrated Hybrid Membrane System for Enhanced WT (IHMS-EWT) is a unique technique for WT and desalination was suggested in this study. The integration of many membrane procedures like nanofiltration, reverse and forward osmosis, and membrane distillation, and these will helps in facilitating the best WT and desalination methods. Due to the incorporating Renewable Energy (RE), the IHMS-EWT also demonstrates the (SWMS) Sustainable Water Management System, as it enhances the EE and thereby reducing the environmental impact. The great potential in the wide range of applications was offered by the IHMS-EWT technique. Providing the decentralized WT solutions in the remote areas, this unique approach has the ability to reduce the fresh water scarcity in the coastal areas based on the demands of the municipal, industrial and agricultural demands. The environmental sustainability throughout the lenghthy operations was ensured by the support of IHMS-EWT. It also helps in providing resilience in the crisis situations. The cost-effective evaluations, operating parameter optimization, and performance prediction of the method was enabled by employing the computational modelling. Through simulatimg different contexts, the effective configurations and operational techniques are focussed on the study for enhancing the IHMS-EWT technology.The model shift in the SWM, the IHMS-EWT technique addresses the main problems and brings one step for more secure environment. Comparing to other existing methods, Improving the water purification by 98.2 %, 94.2 % efficiency rate, the EC prediction rate of 96.2 %, the cost-effectiveness rate by 82.4 % and the performance rate by 96.7 % by the suggested IHMS-EWT model and it was demonstrated by the outcomes of the experiment. 2024 The Authors -
Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19
The uncertainty in life plans, restrictions on physical classrooms, loss of jobs, large number of infections and deaths due to COVID-19 are some significant causes of concern for the public as well as Governments all over the globe. Moreover, the exponential increase in the number of infected people in a short time is responsible for the collapse of the health industry during the pandemic caused by COVID-19. The health experts recommended that the quick and early diagnosis followed by treatment of patients in isolation is a way to minimize its spread and save lives. The objective of this research is to propose a customized SEIR model to predict the trends of vaccination in the USA. The experimental results prove that the Moderna vaccine reports the efficacy of 93%, which is higher than the Pfizer and Johnson and Johnson vaccines. 2022 ACM. -
Optimization-Based Cash Management Model for Microfinance Applications Using GSA and PSO
Banks and businesses use cash as a means for exchange in finance on a regular basis to please customers. Making decisions about cash management can be challenging because banks must keep significant sums of cash in order to sustain high levels of client satisfaction. In this paper, linear PSO and GSA models are given for estimating the daily cash demand of a bank by taking into account the variables Year of Reference (RY), Years Month (My), Months Day (Dm), Days Week (Dw), Payday Effect Salary (Se), and Holiday Effect (He). Using PSO and GSA in MATLAB, the algorithms for estimating both the model coefficients for short term are implemented from the real data of a specific bank branch. The proposed system's overall cost is minimized using a fitness function. It was discovered that the results are in good accord with the observed data and that the PSO-based cash management model outperformed other models with superior accuracy. The models are then used for future cash management for validation. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Next-Generation Connectivity in A Heterogenous Railway World
Global System for Mobile communication - Railway (GSM-R) is widely used for operational communications between train and signaler. However, there is a need to define a successor that addresses: obsolescence, radio spectrum demand and the enabling of a range of emerging digital applications such as radio-based signaling and Automatic Train Control (ATC). Therefore, the International Union of Railways (UIC) started the initiative to develop the Future Railway Mobile Communication System (FRMCS). This article describes an Adaptable Communication System (ACS) that is being developed jointly by industry and railway operators as a possible successor covering all types of railways and all aspects of the FRMCS. A pragmatic approach is suggested that considers diverse railway settings and makes use of various radio access technologies. Countries, geographical regions and infrastructure managers differ concerning available radio technologies, but use of a suitable ACS could pave the way towards innovation in the railway sector. For this adaptive concept we discuss several network models and enhancements including satellite communications (SatCom), Software-Defined Networking (SDN) integration and antenna systems that support multiple bearers in one. For SatCom a software defined radio (SDR) prototype using random access is presented that is able to fulfill the requirements of ETCS. We found that SDN can be used for dynamically changing the access technology for critical and non-critical railway use cases. Furthermore, we present an antenna prototype that can be used for 5G, GSM, WLAN and LTE in parallel which saves limited mounting surface on the train. 1979-2012 IEEE. -
A PV-Powered Single Phase Seven-Level Invertera's Photocurrent and Injected Power
The PV inverter in this study is linked to the grid and its performance analysis is evaluated using a PI controller. It is a single phase multi-level PV inverter. The major objective of this research is to increase efficiency and eliminate harmonics caused by DC link voltage fluctuations created by Maximum Power Point Tracking (MPPT) during foggy situations. PV inverters generate and inject actual power into the main grid. This study uses a transformer-less photovoltaic inverter to cut down on losses, cost, and size. A transformer-less multilayer inverter is described in this paper. There is no high-frequency leakage current since that inverter can distribute both actual and reactive electricity. MATLAB/Simulink software was used to analyze and assess the effects of various PV-based seven-level techniques on the devicea's Maximum Power Point Tracking (MPPT) performance. The Authors, published by EDP Sciences, 2024. -
Wireless Network Security Using Load Balanced Mobile Sink Technique
Real-time applications based on Wireless Sensor Network (WSN) technologies are quickly increasing due to intelligent surroundings. Among the most significant resources in the WSN are battery power and security. Clustering stra-tegies improve the power factor and secure the WSN environment. It takes more electricity to forward data in a WSN. Though numerous clustering methods have been developed to provide energy consumption, there is indeed a risk of unequal load balancing, resulting in a decrease in the networks lifetime due to network inequalities and less security. These possibilities arise due to the cluster heads limited life span. These cluster heads (CH) are in charge of all activities and control intra-cluster and inter-cluster interactions. The proposed method uses Lifetime centric load balancing mechanisms (LCLBM) and Cluster-based energy optimization using a mobile sink algorithm (CEOMS). LCLBM emphasizes the selection of CH, system architectures, and optimal distribution of CH. In addition, the LCLBM was added with an assistant cluster head (ACH) for load balancing. Power consumption, communications latency, the frequency of failing nodes, high security, and one-way delay are essential variables to consider while evaluating LCLBM. CEOMS will choose a cluster leader based on the influence of the fol-lowing parameters on the energy balance of WSNs. According to simulated find-ings, the suggested LCLBM-CEOMS method increases cluster head selection self-adaptability, improves the networks lifetime, decreases data latency, and bal-ances network capacity. 2023, Tech Science Press. All rights reserved. -
Crystallographic and computational investigation of a bent-core Schiff base Ni(ii) complex with DNA and protein binding studies
The rational design and synthesis of a three-ring bent-core Schiff base ligand, (E)-4-(trifluoromethyl)phenyl-3-((4-butoxy-2-hydroxybenzylidene)amino)-2-methylbenzoate (HL), and its mononuclear Ni(ii) complex, [Ni(L)2] (1), are described. The presence of a polar CF3 group and a flexible butoxy chain imparts amphiphilic character to HL and induces aggregation-induced emission (AIE) behavior. Coordination with NiCl2 yields a square-planar complex, as confirmed by spectroscopic methods, single-crystal X-ray diffraction analysis, and topological analysis. Fluorescence and SEM studies substantiate the aggregation propensity of HL. Density functional theory (DFT) and natural bond orbital (NBO) analyses reveal pronounced ligand-to-metal charge transfer in (1) and a moderate HOMOLUMO gap of 4.00 eV, indicative of kinetic stability and optoelectronic relevance. Complex (1) exhibits strong binding affinity toward duplex DNA and serum proteins (BSA and HSA), evidenced by red-shifted fluorescence enhancement at 475 nm and low detection limits (0.0750.188 M). Molecular docking further supports stable BSA binding (?8.52 kcal mol?1), highlighting the potential of this Ni(ii) system for biomolecular recognition. This journal is The Royal Society of Chemistry, 2026 -
Application of SWOT And Breakeven Analysis in Strategic Decision-Making: A Quantitative Approach
This chapter investigates the extent to which the conjunction of SWOT analysis and quantitative analysis (such as breakeven analysis) enhances the quality of strategic decision-making. In addition to the usual limitations of a qualitative SWOT analysis, the paper embraces financial feasibility tools and promotes a multi-criteria decisionmaking approach. After a brief initial chapter noting the rationale for combining qualitative and quantitative analyses in the strategic planning process, the chapter continues with the theoretical foundation relating to strategic decision-making models (including SWOT, breakeven analysis, Analytic Hierarchy Process (AHP), Hybrid SWOT-AHP, and Quantitative Strategic Planning Matrix (QSPM). A casestudy approach with examples from both the private and public sectors illustrates the practical application of these tools through numerical data tables, breakeven calculations, and decision matrices. 2026 by IGI Global Scientific Publishing. -
Mapping location and identity in the works of indian english novelists:
This thesis examines the context of location in relation to constructs of identity in Salman Rushdie s MC, Vikram Seth s ASB and Amitav Ghosh s TSL. It is contended that articulation of selfhood is achieved through its interaction with narrative constructions of space and these depictions serve to map representations of nation. Writers migrant experiences are shown to have a bearing on the aesthetics and geopolitics of these representations. Even though these texts challenge the reductive processes of homogenization at work in the formation of nationalcultural identities, it is contended that they foreground transnational lifestyles and identities.Some of the questions that the thesis asks are: Does the cultural-geographical location of the writer shape the aesthetics of the work? If so, to what extent? In what ways does the diasporic newlineexperience influence the (re)presentation of mediated and inter-connected spaces? How is a newlinecharacter, who does not share the author s diasporic location and experience, depicted? Do the works cater to a Western readership by presenting a palatable version that is only purportedly transnational? Or, are the writers lapsing into a master narrative of universalism? newlineThe creative paradigm allows for the unfolding of the enigma of identity by the interplay of the questions surrounding place - Where am I and what is my place in the world, which reveals who I am. There are real geographies of social action, as well as metaphorical spaces and sites of power that have to be understood in their own right and in the context of shared loci that come together to construct identity. Thus, a comparative study of the novels is conducted on various registers such as dynamics of space, negotiation of borders and boundaries, delineation of multiple identities and representation of nation via language and history. The thesis argues for newlineaesthetic negotiation of borders across locations that maybe geographic and psychic; in order to grapple with and empower subjectivities. -
CORPORATE SOCIAL RESPONSIBILITY: BRIDGING MANAGEMENT PRACTICES AND COMMUNITY DEVELOPMENT
The paper discusses Corporate Social Responsibility (CSR) as a mediating strategy between corporate management and community development in the diverse situations. Indeed, acknowledging the fact that CSR is no longer a pure concept of voluntary charity, but rather a significant part of business logic, the study was conducted with a qualitative and posthumanistic approach through the prism of situated inquiry. Semi-structured interviews with document and artefact analysis, and some field observation was conducted in India, Nigeria, and Saudi Arabia with 27 participants who were corporate managers and NGO and community stakeholders. Findings show that on one hand CSR is integrated as a strategy with organizational objectives, but on the other hand the perceptions differ so much. Interactions historically and the level of participatory planning tended to focus relationships. Digital dashboards were a form of technology that mediated transparency but posed the threat of dehumanizing engagement. There were continuation tensions between performance-based strategies and community-based ethics. The research comes to the conclusion that effective CSR presupposes a combination of strategic intent and trust-building and shared responsibility. It is suggested that collaborative project design, long-term partnership, and proper technological support are to be used as, rather than a substitute to direct community interaction. This issue is to be investigated in the future with respect to how non-human forces and time processes can determine the impressions and results of CSR. On the whole, the study highlights that the transformative aspect of CSR is adaptive, relational, and circumstentially-sensitive practices. 2025. This is an open-access article distributed under the terms of the Creative Commons Attribution License. (https://cre-ativecommons.org/licenses/by/4.0/). -
The Impact of AI on Digital Marketing Across Various Industries: Unveiling New Possibilities Across Industries
Artificial Intelligence (AI) is revolutionizing digital marketing by enhancing the effectiveness of strategies through automation, data- driven insights, and personalized customer engagement. This paper presents a cross- industry analysis to understand the impact of AI on digital marketing effectiveness across various sectors. The primary objective of this research is to examine how AI-powered tools and techniques are reshaping marketing practices and optimizing consumer interactions. Industries such as retail, healthcare, finance, and entertainment are leveraging AI for customer segmentation, personalized recommendations, chatbots, predictive analytics, and automated content creation. By evaluating case studies and industry reports, this study aims to identify key trends and best practices adopted by successful organizations. This research also investigates the challenges faced by companies when implementing AI in digital marketing, such as data privacy concerns, ethical implications, and the integration of AI with existing marketing strategies. 2026, IGI Global Scientific Publishing. All rights reserved. -
Applying a Multi-Agent Simulation Model for Examining Restorative Justice-Based Intervention in the Criminal Justice System: A Legal and Technological Perspective
Previous studies on Restorative Justice (RJ) have focused on the theoretical underpinnings of RJ and its processes. Several systematic literature reviews on RJ point out its potential to assist in victim healing much better compared to the traditional criminal justice system. However, the potential and viability of RJ largely remain in the theoretical landscape. Few empirical studies or simulations have been conducted to explore the viability of this practice in the legal domain. Furthermore, apart from purely studying RJ, literature also points towards its potential use in addressing child sexual abuse cases (CSA) by providing a child and victim-centric approach. However, the practicality of this claim remains scant in present times. Given the gap in the global discourse on the use of RJ as an intervention strategy in the criminal justice system, this paper outlines a computational framework for including RJ into the legal system. The paper does so by applying a Multi-Agent Simulation model (MAS). By utilising JADE for agent orchestration and NetLogo for a visual structure, the framework encodes multiple stakeholders such as accused/ offender, victim, counsellors and judges as autonomous agents with state vectors, utility performance and ACL-communication. The criminal justice system is compared to the restorative justice system using metrics like resolution rate, time, victim healing, rehabilitation and reintegration into the community. Through this paper, a foundation is laid for the potential of RJ in CSA. This paper will enable law and policy makers to consider introducing alternative practices like RJ. 2026 IEEE. -
Artificial Intelligence in Detecting and Mitigating Online Child Sexual Abuse: Approaches and Solutions
Previous research papers have discussed whether Artificial Intelligence (AI) -based tools like Chat Bots, Law-U Model, and Sweetie. 20 have the potential to mitigate online child sexual abuse. The literature review indicates that AI tools promise good intervention and prevention strategies for several tech-based companies like Google and Microsoft. However, there is a lack of systematic study on AI tools' potential uses, limitations, and legal risks. This paper conducts a systematic literature review to explore the uses and limitations of AI-based interventions in combating online child sexual abuse. It explores the legal and ethical risks of deploying such technological innovations from the viewpoint of data protection, privacy, and security. The authors use the PRISMA technique and thematically answer the research questions. Data are collected from reliable sources such as Statista and the World Health Organisation. The findings of this paper highlight the potential uses of AI for law agencies, forensic experts, victims, and technology companies. The research reports the absence of a sufficient legal framework for the governance and accountability of AI tools. The findings further indicate the need for clarification in the law regarding the legal status of AI tools like Sweetie 2.0. Lastly, this paper offers a framework for harmonizing AI usage with human rights standards. 2025 IEEE.