Innovative infrastructure projects are changing how cities and industries are developed by using advanced technologies to improve efficiency, sustainability, and resilience. These projects focus on managing infrastructure assets more effectively through real-time monitoring, predictive maintenance, and data-driven decisions. In this context, digital twin technology plays a key role by providing a virtual model of physical systems that updates in real time. By synchronizing real-time data with simulation models, digital twins support enhanced situational awareness, scenario testing, and performance optimization. However, implementing digital twins involves a complex process that introduces multidimensional risks, many of which are poorly understood. This study addresses the gap by identifying and analyzing key risk factors associated with digital twin adoption. A hybrid approach combines a systematic literature review, expert validation from 19 professionals, and fuzzy Decision-Making Trial and Evaluation Laboratory analysis to map and prioritize 15 critical risks across four categories: Technological, Governance/Ethical, Social, and Economic. Results indicate that economic challenges are central drivers, while data privacy and security, computational resource limitations, lack of transparency, job displacement, and high implementation costs represent significant secondary risks. Expert consultations identified practical strategies to reduce the top risks, including strong data governance, gradual (iterative) technology rollout, continuous performance monitoring, and designing systems with users in mind. These strategies directly address the most critical risks highlighted in the analysis. The structured risk framework provides actionable insights for policymakers and practitioners, supporting informed decision-making and robust risk management strategies. These findings enhance understanding of potential barriers and contribute to more sustainable and responsible deployment of digital twin technology in infrastructure and beyond.
In this research, the solitary wave solutions, the periodic type, and single soliton solutions are attained. The coupled fractional Lakshmanan–Porsezian–Daniel (LPD) equation is depicted the wave pulses’ physical properties in birefringent optical fibres containing two vector solitons. Here, the Paul–Painlevé operator is employed to investigate kink soliton solutions. Also, the new modified exponential Jacobi technique is used to find periodic wave and soliton, bright-dark soliton. By utilizing symbolic computation and the applied methods, the mentioned system is successfully investigated. The coupled fractional LPD model is exhibited the travelling waves, as shown by the research in the current paper. Through three-dimensional graph, contour graph, density graph, complex-plot, and two-dimensional design using Maple, the physical features of single soliton and periodic wave solutions are explained all right. The findings the investigated model’s broad variety of explicit solutions are demonstrated. As a result, the exact solitary wave solutions to the studied issues, including solitary, single soliton, and periodic wave solution are found. It is shown that the approach is practical and flexible in mathematical physics. All outcomes in this work are necessary to understand the physical meaning and behavior of the explored results and shed light on the significance of the investigation of several nonlinear wave phenomena in sciences and engineering.
The Next Generation mobile network expected to be fully automated to meet the growing need for data rates and quality in communication. These prodigious demands have also increased the amount of data being handled in these wireless networks. The cellular networks can leverage vital data about the user and the network conditions providing all-inclusive visibility and intelligence in communication. Emerging analytic technologies such as big data and neural networks have been used to unearth vital insight from network traffic to assist intelligent models in routing packets. Reactive protocols are an emerging model in the intelligent routing of traffic in ad-hoc networks. In this paper, we first utilize the reactive protocols to route traffic in a wireless network while analyzing anomalous behavior. In the case of anomaly detection in wireless communication, combined performance indicators to identify outliers. The detected outliers been compared with the ground data and routes created using the reactive protocols. The combination of reactive protocols and the key performance indicators in network performance uncovered anomalies leading to segregation of these traffic in routing. From the results, it is evident that an abrupt surge in the traffic indicated an anomaly and identify the areas of interest in a network especially for resource and path allocation and fault avoidance. A MATLAB GUI was used to simulate the reactive protocols for routing of traffic and generation of data sets that analyze in Microsoft Excel to characterize the key performance indicators of the network.
This comprehensive review delineates the latest advancements in stimuli-responsive drug delivery systems engineered for the targeted treatment of breast carcinoma. The manuscript commences by introducing mammary carcinoma and the current therapeutic methodologies, underscoring the urgency for innovative therapeutic strategies. Subsequently, it elucidates the logic behind the employment of stimuli-responsive drug delivery systems, which promise targeted drug administration and the minimization of adverse reactions. The review proffers an in-depth analysis of diverse types of stimuli-responsive systems, including thermoresponsive, pH-responsive, and enzyme-responsive nanocarriers. The paramount importance of material choice, biocompatibility, and drug loading strategies in the design of these systems is accentuated. The review explores characterization methodologies for stimuli-responsive nanocarriers and probes preclinical evaluations of their efficacy, toxicity, pharmacokinetics, and biodistribution in mammary carcinoma models. Clinical applications of stimuli-responsive systems, ongoing clinical trials, the potential of combination therapies, and the utility of multifunctional nanocarriers for the co-delivery of assorted drugs and therapies are also discussed. The manuscript addresses the persistent challenge of drug resistance in mammary carcinoma and the potential of stimuli-responsive systems in surmounting it. Regulatory and safety considerations, including FDA guidelines and biocompatibility assessments, are outlined. The review concludes by spotlighting future trajectories and emergent technologies in stimuli-responsive drug delivery, focusing on pioneering approaches, advancements in nanotechnology, and personalized medicine considerations. This review aims to serve as a valuable compendium for researchers and clinicians interested in the development of efficacious and safe stimuli-responsive drug delivery systems for the treatment of breast carcinoma.
In this study, a novel GO/Fe@TANG composite catalyst was designed by functionalizing graphene oxide (GO) with iron (Fe) and incorporating a hydrogen (H2) trapping TANG COF. This catalyst was evaluated under mild conditions using a multifunctional MEA/EDA DES that serves as a solvent, an electrolyte and a CO trapping agent. The system efficiently catalyzed the electrochemical carbonylation and hydrogenation of various substrates, including nitrobenzene derivatives 1(a-j), chlorobenzene derivatives 2(a-d), monoxide carbon (CO) 3(a), and H2 gas 4(a), to afford N-phenylbenzamide derivatives 5(a-m) in high yields ranging from 91% to 96% under mild conditions (room temperature, 1.5 h, 15 mA). The MOF displayed a high specific surface area of 1105 m2 g-1 and maintained its catalytic performance over 9 consecutive reuse cycles. Extensive characterization techniques such as FT-IR, SEM, TEM, EDX mapping, TGA, BET, 1H NMR, CHN, CV, and XPS confirmed the structural, morphological, thermal, and chemical properties of both the catalyst and synthesized products 5(a-m). This work demonstrates an effective, environmentally friendly electrocatalytic system that integrates iron-based porous materials and multifunctional electrolytes, achieving sustainable synthesis of valuable amide derivatives in a streamlined, high-yielding manner aligned with green chemistry principles.
