Study on the Fluid-Solid Coupling Seepage of the Deep Tight Reservoir Based on 3D Digital Core Modeling

Deep tight reservoirs exhibit complex stress and seepage fields due to varying pore structures,thus the seepage characteristics are significant for enhancing oil production.This study conducted triaxial compression and permeability tests to investigate the mechanical and seepage properties of tight sandstone.A digital core of tight sandstone was built using Computed Tomography(CT)scanning,which was divided into matrix and pore phases by a pore equivalent diameter threshold.A fluid-solid coupling model was established to investigate the seepage characteristics at micro-scale.The results showed that increasing the confining pressure decreased porosity,permeability,and flow velocity,with the pore phase becoming the dominant seepage channel.Cracks and large pores closed first under increasing pressure,resulted in a steep drop in permeability.However,permeability slightly decreased under high confining pressure,which followed a first-order exponential function.Flow velocity increased with seepage pressure.And the damage mainly occurred in stress-concentration regions under low seepage pressure.Seepage behavior followed linear Darcy flow,the damage emerged at seepage entrances under high pressure,which decreased rock elastic modulus and significantly increased permeability.

Digital Economy and Corporate Innovation-Washing--An Empirical Study on How Information Mitigates Policy Distortion

As stated in the Report to the 20th National Congress of the Communist Party of China(CPC),innovation remains at the heart of China’s modernization drive,and it is vital to optimize the allocation of innovation resources,deepen structural scientific and technological reforms,and enhance the overall performance of China’s innovation system.Government incentives have boosted firm R&D and innovation efforts;however,they have also triggered an innovation dilemma where enterprises,capitalizing on their informational advantages,resort to innovation-washing behaviors that undermine the intended purpose of the policies.Based on the information asymmetry theory,this paper conducts an empirical study on how the digital economy affects firms’innovation-washing behavior.The development of the regional digital economy could suppress firm innovation-washing behavior in the region,and such a mitigation effect is primarily caused by an increase in the number of digital industry professionals.According to our heterogeneity analysis,the digital economy has a greater impact on firm innovation-washing behavior for certain types of enterprises,including non-state-owned enterprises(non-SOEs),small and medium-sized enterprises(SMEs),enterprises in less competitive industries,and enterprises in unfavorable business environments.Our mechanism analysis revealed that the digital economy may restrain innovation-washing behavior by reducing information asymmetry between enterprises and external stakeholders.In terms of economic outcomes,the digital economy has the potential to directly influence firm innovation output while also indirectly mitigating the subsequent decline in innovation output by discouraging innovation-washing.This paper enriches the research findings on how the digital economy breaks down“information silos”and offers a potential solution to the“emphasis on input and quantity over quality and efficiency”phenomenon in science and technology innovation practices.

Side-channel free quantum digital signature with source monitoring

Quantum digital signature(QDS)can guarantee the information-theoretical security of a signature with the fundamental laws of quantum physics.However,most current QDS protocols do not take source security into account,leading to an overestimation of the signature rate.In this paper,we propose to utilize Hong–Ou–Mandel interference to characterize the upper bound of the source imperfections,and further to quantify information leakage from potential side-channels.Additionally,we combine decoy-state methods and finite-size analysis in analyzing the signature rate.Simulation results demonstrate the performance and feasibility of our approach.Our current work can improve the practical security of QDS systems,thereby promoting their further networked applications.

Spatial Pattern and Influencing Factors of China’s Digital Trade Resilience under the Impact of Trade Frictions

In the era of the digital economy,digital trade has demonstrated strong vitality,becoming a crucial driving force for the highquality development of national and regional economies.However,understanding the resilience of digital trade in the face of external crises is an important topic.Taking the backdrop of Sino-US trade friction,this paper constructs a resilience index system for digital trade.It utilizes entropy method,kernel density estimation,and ArcGIS mapping to calculate and visually analyze the resilience of China’s digital trade from 2017 to 2021.Additionally,a Tobit model is constructed to explore the main influencing factors of digital trade resilience patterns.The research findings indicate:1)temporally,during the period of Sino-US trade friction,China’s digital trade resilience shows an overall upward trend,but there are regional differences in resilience levels across the country,with a severe polarization phenomenon.2)Spatially,high resilience is observed in the eastern and central regions of China,while the western and northeastern regions exhibit low resilience.3)From a dimensional perspective,the resistance of digital trade resilience displays a spatial distribution of high values in the east and low values in the west.The recovery force is aggregated along coastal areas,and the renewal force tends to aggregate along the eastern coastline.4)Factors such as economic scale,industrial structure,urbanization rate,government fiscal expenditure,and technological talents significantly promote the enhancement of digital trade resilience.This study reveals the dynamic characteristics and influencing factors of digital trade resilience in responding to external shocks,providing theoretical basis and policy suggestions for enhancing digital trade resilience,and promoting high-quality economic development in China.

Digital signal acquisition system for complex nuclear reaction experiments

A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.

Effectiveness of RESET care program: A real-world-evidence on managing non-alcoholic fatty liver disease through digital health interventions

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)management requires sustainable lifestyle modifications.This study aimed to evaluate the effectiveness of the RESET care plan,a comprehensive program that is an integrated personalized diet,exercise,and cognitive behavior therapy,delivered via MyTatva’s digital health application enabled through a body composition analyzer(BCA)and smartwatch.AIM To evaluates the effectiveness of the comprehensive program delivered via My-Tatva’s digital health app enabled through internet of thing devices.METHODS This retrospective observational study analyzed deidentified data from 22 par-ticipants enrolled in the MyTatva RESET care program.Participants were divided into three groups:Group A,diet plan;Group B,diet+exercise plan;and Group C,diet+exercise+cognitive behavioral therapy plan.Participants were provided with a BCA and smartwatch for continuous monitoring of anthropometric para-meters.Statistical analysis,including one-way ANOVA and post-hoc Tukey’s Honest Significant Difference test,was conducted to compare mean changes in anthropometric parameters across the groups.INTRODUCTION Non-alcoholic fatty liver disease(NAFLD)has emerged as a global health burden,affecting approximately 1 in 4 in-dividuals worldwide.NAFLD ranges from simple steatosis(fat accumulation)to non-alcoholic steatohepatitis(NASH),and its global prevalence in the general population is estimated between 6.3%and 33%,with NASH affecting 3-5%[1,2].Obesity is a major risk factor of NAFLD,with studies showing that the likelihood of developing NAFLD increases 5-fold at a body mass index(BMI)of 30-32.5 kg/m²and up to 14-fold at BMI of 37.5-40 kg/m²compared to a BMI of 20-22.5 kg/m²[3,4].Effective NAFLD management requires both dietary and physical activity modifications.Healthy weight loss with sustained muscle mass plays a pivotal role,with a reduction of 3%-5%decreasing hepatic steatosis,5%-7%improving NASH conditions,and 10%or more needed to reverse hepatic fibrosis[5].Management also normalizes elevated liver enzymes(aspartate aminotransferase and alanine aminotransferase),enhances insulin sensitivity,and thereby reduces cardiovascular risk by improving endothelial function and increasing cardiorespiratory fitness[6].However,diet or exercise alone is often not as effective as a combined approach.Integrating both balanced dietary changes and increased physical activity yields more sustainable improvements in NAFLD and overall metabolic health[1,7].Traditional intervention methods usually involve in-person consultations,which often lack real-time and continuous patient monitoring.The recommendation of drastic changes in diet and exercise can also be overwhelming for patients,leading to low adherence rates.Many patients struggle to maintain these changes in the long-term due to a lack of con-tinuous motivational support[8,9].In recent years,the health ecosystem has witnessed a significant shift toward digital health platforms,which complement pharmacological treatments in chronic disease management,and increase scala-bility.These platforms provide continuous monitoring and personalized support,helping to bridge the gap between health care setups and patients[10].Recent digital advances enable internet of things(IoT)devices to be integrated into such management plans to track health metrics,to address the limitations of traditional methods[11,12].The MyTatva digital health application offers the RESET plan,a novel comprehensive approach for NAFLD mana-gement by integrating personalized support from nutrition,physiotherapy,and cognitive behavioral therapy(CBT)coaches.We aimed to evaluate the effectiveness of the RESET plan by analyzing the reduction in anthropometric para-meters across three different digital intervention groups.

Alexa,let's train now!——A systematic review and classification approach to digital and home-based physical training interventions aiming to support healthy cognitive aging

Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the recommended level of regular physical activity calls for further public health actions.In this context,digital and home-based physical training interventions might be a promising alternative to center-based intervention programs.Thus,this systematic review aimed to summarize the current state of the literature on the effects of digital and home-based physical training interventions on adult cognitive performance.Methods:In this pre-registered systematic review(PROSPERO;ID:CRD42022320031),5 electronic databases(PubMed,Web of Science,Psyclnfo,SPORTDiscus,and Cochrane Library)were searched by 2 independent researchers(FH and PT)to identify eligible studies investigating the effects of digital and home-based physical training interventions on cognitive performance in adults.The systematic literature search yielded 8258 records(extra17 records from other sources),of which 27 controlled trials were considered relevant.Two reviewers(FH and PT)independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise(TESTEX scale).Results:Of the 27 reviewed studies,15 reported positive effects on cognitive and motor-cognitive outcomes(i.e.,performance improvements in measures of executive functions,working memory,and choice stepping reaction test),and a considerable heterogeneity concerning study-related,population-related,and intervention-related characteristics was noticed.A more detailed analysis suggests that,in particular,interventions using online classes and technology-based exercise devices(i.e.,step-based exergames)can improve cognitive performance in healthy older adults.Approximately one-half of the reviewed studies were rated as having a high risk of bias with respect to completion adherence(≤85%)and monitoring of the level of regular physical activity in the control group.Conclusion:The current state of evidence concerning the effectiveness of digital and home-based physical training interventions is mixed overall,though there is limited evidence that specific types of digital and home-based physical training interventions(e.g.,online classes and step-based exergames)can be an effective strategy for improving cognitive performance in older adults.However,due to the limited number of available studies,future high-quality studies are needed to buttress this assumption empirically and to allow for more solid and nuanced conclusions.

Digital Twin Technology of Human-Machine Integration in Cross-Belt Sorting System

The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting systems stand out as the most crucial.However,despite their high degree of automation,the workload for operators has intensified owing to the surging volume of express items.In the era of Industry 5.0,it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems.Striking a balance between efficiency in handling express items and operator well-being is challenging.Digital twin technology offers a promising solution in this respect.A realization method of a human-machine integrated digital twin is proposed in this study,enabling the interaction of biological human bodies,virtual human bodies,virtual equipment,and logistics equipment in a closed loop,thus setting an operating framework.Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources,construction of the relationship between operator fatigue and operation efficiency based on physiological measurements,virtual model construction,and an online optimization module based on real-time simulation.The feasibility of the proposed method was verified in an express distribution center.

Digital Advisory Systems in Zimbabwean Agriculture: Opportunities and Constraints

The adoption of digital advisory systems is transforming smallholder agriculture in Zimbabwe, a country where agriculture remains the primary livelihood for most of the population. Despite significant investments in digital technologies, agricultural productivity continues to underperform. This study explores the barriers preventing the scaling of digital advisory services among smallholder farmers and identifies strategies to optimize their adoption. Using a mixed-methods approach, data were collected from 854 smallholder farmers, 40 extension staff, and 8 development workers across six districts in Zimbabwe. The study reveals a high mobile penetration rate of 91%, higher than the 85% reported in the literature. However, challenges such as limited digital literacy, poor network connectivity, and financial constraints hinder the effective use of mobile advisory services. The findings also highlight a strong reliance on basic communication tools like SMS (42.83%) and WhatsApp (25.14%) for receiving agricultural information, while more advanced tools like mobile apps have lower adoption. Key recommendations include investing in nationwide digital literacy programs, incentivizing mobile network operators to improve rural connectivity, and developing human-centered, scalable digital solutions tailored to farmers’ needs. Furthermore, integrating AI-driven advisory systems with popular platforms like WhatsApp could significantly enhance the delivery of site-specific, actionable farming advice. This research provides insights into how digital advisory systems can be leveraged to improve agricultural productivity in Zimbabwe and other similar contexts.

Construction of BDS Spatiotemporal Information Agricultural Product Digital Credit System

Spatiotemporal information,positioning and navigation services have become important elements of new type infrastructure.The rapid development of global digital trade provides a large-scale application scenario for the use of Beidou Navigation Satellite System(BDS)spatiotemporal information to support the certification of origin of agricultural products.The BDS spatiotemporal information agricultural product digital credit system uses such modules as BDS,spatiotemporal information collection,spatiotemporal coding,and spatiotemporal blockchain.It incorporates multi-level joint supervision mechanisms such as government,associations,and users.Starting from the initial production link of agricultural products,it realizes the correspondence and locking of online and offline products,effectively improves the integrity and credibility of information in the production process,finished product quality and circulation process of products,effectively manages the green production and anti-channel conflicts of producers,and provides credible information for consumers,thus realizing the digital credit certification of products.The successful practice of characteristic agricultural products in Yunnan Province has verified the application ability of the BDS spatiotemporal information agricultural product digital credit system.This system has played a significant role in promoting the online and offline locking,credible information,effective supervision and high quality and high price of characteristic agricultural products from the field.The BDS provides services for global digital trade and contributes to the further enhancement of the global application scale of GNSS.

Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information Systems

In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

Optimizing near-carbon-free nuclear energy systems:advances in reactor operation digital twin through hybrid machine learning algorithms for parameter identification and state estimation

Accurate and efficient online parameter identification and state estimation are crucial for leveraging digital twin simulations to optimize the operation of near-carbon-free nuclear energy systems.In previous studies,we developed a reactor operation digital twin(RODT).However,non-differentiabilities and discontinuities arise when employing machine learning-based surrogate forward models,challenging traditional gradient-based inverse methods and their variants.This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues.An efficient modular RODT software framework that incorporates these methods into its post-evaluation module is presented for comprehensive comparison.The methods were rigorously assessed based on convergence profiles,stability with respect to noise,and computational performance.The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications,balancing accuracy and efficiency with a prediction error rate of only 1%and processing times of less than 0.1 s.Contrastingly,algorithms such as FSA,DE,and ADE,although slightly slower(approximately 1 s),demonstrated higher accuracy with a 0.3%relative L_2 error,which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring,systematic diagnosis of off-normal events,and lifetime management strategies.The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.

Digital Human Rights from the Perspective of System Theory——Concept Definition, Social Function, and Constitutional Basis

The three core issues in the“digital human rights”debate are whether“digital human rights”are possible,necessary,and feasible.Both sides of the debate focus on discovering the value of“digital human rights”to individuals from a semantic level,but ignore the significance of“digital human rights”to the whole society and its subsystems at the level of social structure.By introducing Niklas Luhmann's System Theory,this observation blind spot can be eliminated.Fundamental rights are devoted to directly shaping not a physiological-psychological“individual”as a social environment but a social“person”that can be included by social systems.It is clear that digital human rights are the right to participate in digital communication of a“human”as a“person”,so they are possible in terms of conceptual definition.Digital human rights can help“people”lower the threshold for participation in digital communication,limit the excessive expansion of social systems,and promote the free and complete expression of body and mind,so they are necessary for social functions.There are limitations in the existing two ideas of“incorporating digital human rights into the constitution”.Based on the new construction idea of System Theory of Law,digital human rights as the right to participate in digital communication can be typified into digital communication in social sub-fields such as politics,economy,science,and art.The right to participate constructs a complete digital human rights system,making it feasible on the basis of the constitution.

A digital twins enabled underwater intelligent internet vehicle path planning system via reinforcement learning and edge computing

The Autonomous Underwater Glider(AUG)is a kind of prevailing underwater intelligent internet vehicle and occupies a dominant position in industrial applications,in which path planning is an essential problem.Due to the complexity and variability of the ocean,accurate environment modeling and flexible path planning algorithms are pivotal challenges.The traditional models mainly utilize mathematical functions,which are not complete and reliable.Most existing path planning algorithms depend on the environment and lack flexibility.To overcome these challenges,we propose a path planning system for underwater intelligent internet vehicles.It applies digital twins and sensor data to map the real ocean environment to a virtual digital space,which provides a comprehensive and reliable environment for path simulation.We design a value-based reinforcement learning path planning algorithm and explore the optimal network structure parameters.The path simulation is controlled by a closed-loop model integrated into the terminal vehicle through edge computing.The integration of state input enriches the learning of neural networks and helps to improve generalization and flexibility.The task-related reward function promotes the rapid convergence of the training.The experimental results prove that our reinforcement learning based path planning algorithm has great flexibility and can effectively adapt to a variety of different ocean conditions.

Control Strategies for Digital Twin Systems

With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.

Enhancing transjugular intrahepatic portosystemic shunt procedure efficiency with digital subtraction angiography image overlay technology in esophagogastric variceal bleeding

BACKGROUND Transjugular intrahepatic portosystemic shunt(TIPS)is a pivotal intervention for managing esophagogastric variceal bleeding in patients with chronic hepatic schistosomiasis.AIM To evaluate the efficacy of digital subtraction angiography image overlay tech-nology(DIT)in guiding the TIPS procedure.METHODS We conducted a retrospective analysis of patients who underwent TIPS at our hospital,comparing outcomes between an ultrasound-guided group and a DIT-guided group.Our analysis focused on the duration of the portosystemic shunt puncture,the number of punctures needed,the total surgical time,and various clinical indicators related to the surgery.RESULTS The study included 52 patients with esophagogastric varices due to chronic hepatic schistosomiasis.Results demonstrated that the DIT-guided group expe-rienced significantly shorter puncture times(P<0.001)and surgical durations(P=0.022)compared to the ultrasound-guided group.Additionally,postoperative assessments showed significant reductions in aspartate aminotransferase,B-type natriuretic peptide,and portal vein pressure in both groups.Notably,the DIT-guided group also showed significant reductions in total bilirubin(P=0.001)and alanine aminotransferase(P=0.023).CONCLUSION The use of DIT for guiding TIPS procedures highlights its potential to enhance procedural efficiency and reduce surgical times in the treatment of esophagogastric variceal bleeding in patients with chronic hepatic schistoso-miasis.

Research on Smart Energy Monitoring and Management System Based on Digital Twin Technology

Smart energy monitoring and management system lays a foundation for the application and development of smart energy. However, in recent years, the work efficiency of smart energy development enterprises has generally been low, and there is an urgent need to improve the application efficiency, resilience and sustainability of smart energy monitoring and management system. Digital twin technology provides a data-centric solution to improve smart energy monitoring and management system, bringing an opportunity to transform passive infrastructure assets into data-centric systems. This paper expounds on the concept and key technologies of digital twin, and designs a smart energy monitoring and management system based on digital twin technology, which has dual significance for promoting the development of smart energy field and promoting the application of digital twin.

Rapid Parameter-Optimizing Strategy for Plug-and-Play Devices in DC Distribution Systems under the Background of Digital Transformation

By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and reliably access DistributedGenerator(DG)and Energy Storage Systems(ESS),exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play(PnP)operations.However,during device plug-in and-out processes,improper systemparametersmay lead to small-signal stability issues.Therefore,before executing PnP operations,conducting stability analysis and adjusting parameters swiftly is crucial.This study introduces a four-stage strategy for parameter optimization to enhance systemstability efficiently.In the first stage,state-of-the-art technologies in measurement and communication are utilized to correct model parameters.Then,a novel indicator is adopted to identify the key parameters that influence stability in the second stage.Moreover,in the third stage,a local-parameter-tuning strategy,which leverages rapid parameter boundary calculations as a more efficient alternative to plotting root loci,is used to tune the selected parameters.Considering that the local-parameter-tuning strategy may fail due to some operating parameters being limited in adjustment,a multiparameter-tuning strategy based on the particle swarm optimization(PSO)is proposed to comprehensively adjust the dominant parameters to improve the stability margin of the system.Lastly,system stability is reassessed in the fourth stage.The proposed parameter-optimization strategy’s effectiveness has been validated through eigenvalue analysis and nonlinear time-domain simulations.

Digital Payment Systems in Urban Media Landscapes:The Evolution and Impact of Apple Pay on Urban Life and Consumer Behavior

This study examines the transformative impact of Apple Pay on urban landscapes and socioeconomic frameworks,with a particular focus on spending patterns and retail dynamics in metropolitan areas.By evaluating the adoption levels,the technological support,and the social impact of Apple Pay,the study shows that the service is both a catalyst for the development of digital payment and a sign of an increasing social gap.Although it has rapidly transformed Retail Enterprises and supported the construction of smart cities,especially in major world cities such as New York,London,and Tokyo,the work has brought out notable digital divides.Although Apple Pay,with more than 75%of iPhone users and 9,000 banks in 60 world areas and regions,has impacts that are not the same across urban populations,the study shows that while large format retailers have effectively adopted Apple Pay for value-added services to consumers and enhanced payment efficiency,small businesses encounter significant barriers in implementation.Additionally,the technology leverages smartphone usage and banking relationships,which does not address considerable urban population demographics and deeper issues of technology exclusion and inequality in the contemporary city.Such results call for attaining a just society’s technological advancement for efficiencies while still catering to all groups of urban dwellers.