Improve Cost Efficiency Research Articles

Development and validation of a novel AI framework using NLP with LLM integration for relevant clinical data extraction through automated chart review.

The accurate extraction of surgical data from electronic health records (EHRs), particularly operative notes through manual chart review (MCR), is complex, crucial, and time-intensive, limited by human error due to fatigue and the level of training. This study aimed to develop and validate a novel Natural Language Processing (NLP) algorithm integrated with a Large Language Model (LLM; GPT4-Turbo) to automate the extraction of spinal surgery data from EHRs. The algorithm employed a two-stage approach. Initially, a rule-based NLP framework reviewed and classified candidate segments from the text, preserving their reference segments. These segments were then verified in the second stage through the LLM. The primary outcomes of this study were the accurate extraction of surgical data, including the type of surgery, levels operated, number of disks removed, and presence of intraoperative incidental durotomies. Secondary objectives explored time efficiency, tokenization lengths, and costs. The performance of the algorithm was assessed across two validation databases, analyzing metrics such as accuracy, sensitivity, discrimination, F1-score, and precision, with 95% confidence intervals calculated using percentile-based bootstrapping. The NLP + LLM algorithm markedly outperformed all performance metrics, demonstrating significant improvements in time and cost efficiency. These results suggest the potential for widespread adoption of this technology.

Strategic Migration of Adobe Experience Manager : A Comprehensive Framework for On-Premise to Cloud Transition

This article examines the strategic migration of Adobe Experience Manager (AEM) from on-premise environments to cloud platforms, addressing the growing demand for scalable and efficient content management solutions in the digital landscape. Through a comprehensive analysis of migration processes, this research presents a systematic framework for organizations undertaking AEM cloud transitions. The article investigates key components of migration, including code refactoring, configuration adjustments, content transfer strategies, and environment adaptation. Utilizing a mixed-method approach, incorporating both quantitative performance metrics and qualitative case study analysis, we evaluate the efficacy of migration tools such as Adobe's Cloud Acceleration Manager and custom scripts for business logic. Our findings reveal significant improvements in scalability, cost-efficiency, and system performance post-migration, while also highlighting potential challenges and mitigation strategies. This article contributes to the body of knowledge on enterprise content management systems and provides practical insights for organizations considering AEM cloud migration, offering a roadmap for successful transition in an increasingly cloud-centric technological ecosystem.

Clarify the process of overshoot voltage generation of proton exchange membrane electrolyzer under intermittent operation

Overshoot voltage phenomenon often occurs when the proton exchange membrane (PEM) electrolyzer is in the intermittent operation, which makes H2 production energy consumption increase significantly and its lifetime reduce rapidly, especially to the high-power electrolyzers in the industrial applications. Up to now, the phenomenon has been rarely understood and its process is elusive. Therefore, in this work, firstly, we find that the polarization curve of PEM electrolyzers happening S distortion synchronize with the appearance of overshoot voltage phenomenon. Secondly, through in-situ Raman characterization, we find that involvement and disappearance of H2O in the hydrogen evolution reaction (HER) is the key factor causing and resolving this phenomenon. Finally, we used EPMA to exclude metal cations affection. Also, by micro-CT, EIS test, visualization PEM electrolyzer inside model and COMSOL electromagnetic simulation, we find that anode catalyst layer porosity reduction directly affects water absorption of membrane as well as current variation leads to eddy currents generation which is deepen unequal current distribution. These are two important reasons for the involvement of H2O in HER. In summary, these findings elucidate the mechanism of overshoot voltage phenomenon for the first time, which contributes to design novel electrical protection schemes and advanced membrane electrodes for PEM electrolyzers, thus they can help to achieve cost reduction and efficiency improvement in the green hydrogen industry.

Digital tools in primary total knee arthroplasty-Prevalence in the German-speaking region

Digital tools are being increasingly used worldwide in primary knee arthroplasty. This study aimed to analyze the utilization density of digital tools, the preferred alignment strategies, and the obstacles and benefits of implementing these technologies in German-speaking countries. An online survey with 57questions about digital tools in primary knee arthroplasty and their usage was conducted among members of the Arthroplasty Working Group (AE). The survey included questions on navigation, robotics, patient-specific instruments, individualized implants, and augmented reality. The survey revealed that 18% of hospitals use navigation and 17% use robotic systems in primary total knee arthroplasty surgery. The main reasons for not implementing supportive technologies were high acquisition and ongoing costs, as well as longer surgical duration. Patient-specific instruments and individualized implants currently play aminor role. Patient-specific alignment strategies, such as kinematic (navigation: 35%; robotics: 44%) and functional alignment (navigation: 15%; robotics: 35%), are preferred in this context. With conventional instrumentation predominantly mechanical alignment was applied (79%). The results indicate arelatively high utilization density of digital tools, which are mainly used to perform personalized alignment strategies in primary knee arthroplasty in German-speaking countries. This was particularly evident in high-volume hospitals. Economic aspects were the main reasons for not using these technologies. Future developments should aim to simplify the systems and thus achieve improved cost efficiency.

Micro Gas Turbines in the Global Energy Landscape: Bridging the Techno-Economic Gap with Comparative and Adaptive Insights from Internal Combustion Engines and Renewable Energy Sources

This paper investigates the potential of Micro Gas Turbines (MGTs) in the global shift towards low-carbon energy systems, particularly focusing on their integration within microgrids and distributed energy generation systems. MGTs, recognized for their fuel flexibility and efficiency, have yet to achieve the commercialization success of rival technologies such as Internal Combustion Engines (ICEs), wind turbines, and solar power (PV) installations. Through a comprehensive review of recent techno-economic assessment (TEA) studies, we highlight the challenges and opportunities for MGTs, emphasizing the critical role of TEA in driving market penetration and technological advancement. Comparative analysis with ICE and RES technologies reveals significant gaps in TEA activities for MGTs, which have hindered their broader adoption. This paper also explores the learning and experience effects associated with TEA, demonstrating how increased research activities have propelled the success of ICE and RES technologies. The analysis reveals a broad range of learning and experience effects, with learning rates (α) varying from 0.1 to 0.25 and experience rates (β) from 0.05 to 0.15, highlighting the significant role these effects play in reducing the levelized cost of energy (LCOE) and improving the net present value (NPV) of MGT systems. Hybrid systems integrating MGTs with renewable energy sources (RESs) and ICE technologies demonstrate the most substantial cost reductions and efficiency improvements, with systems like the hybrid renewable energy CCHP with ICE achieving a learning rate of α = 0.25 and significant LCOE reductions from USD 0.02/kWh to USD 0.017/kWh. These findings emphasize the need for targeted TEA studies and strategic investments to unlock the full potential of MGTs in a decarbonized energy landscape. By leveraging learning and experience effects, stakeholders can predict cost trajectories more accurately and make informed investment decisions, positioning MGTs as a competitive and sustainable energy solution in the global energy transition.

An efficient and noticeable wet etching method for PZT and its application in scanning mirrors

This study introduces an innovative wet etching method for magnetron sputtering lead zirconate titanate (PZT) thin films, leveraging a solution of HBF4 as the etchant and HCl for intermediate product removal. Compared to traditional dry etching techniques, the focus is on improving cost efficiency and etching performance. Wet etching offers numerous advantages, including lower costs, faster etching rates, minimal lateral etching, and smoother etch profiles, making it a viable alternative for fabricating MEMS piezoelectric devices. The effectiveness of this method was substantiated through the production and performance assessment of a 1D scanning mirror, demonstrating that the wet etched PZT retained its piezoelectric properties and was efficiently integrated into MEMS applications without adverse effects on its piezoelectric functionality. Results confirm that this wet etching approach not only maintains the structural integrity of PZT films but also supports the manufacturing of MEMS devices with precise dimensional control and reliable operational performance.

Intelligent energy management system of hydrogen based microgrid empowered by AI optimization technique

Microgrids powered by hydrogen often face challenges in effectively managing energy over an extended duration due to the intermittent nature of renewable energy sources (RES) and fluctuating loads. This research emphasizes the use of AI technologies, including machine learning to improve the efficiency of intelligent energy management system (IEMS), hydrogen storage, fuel cell consumption, and power system quality improvement. A novel approach integrating Isolation Forest Ensemble (IFE) and Modified Water Wave Optimization (MWWO) has been proposed to enhance energy management and to improve the power quality. This method combines the population size with precision and accuracy. The effectiveness of this study has been assessed against established methods (AVO, PSO & IPSO, MFO, SAG & XGBoost, MILP, and QTLBO) concerning numerous factors including component sizing, economics, reliability, and efficiency of microgrid. The precision level of the proposed technique is approximately 83 %. The primary benefit of this research is the improvement of power quality and cost-efficiency in hydrogen based microgrids, attained through optimized and intelligent energy management system. This article furnishes evidence indicating the superiority of the anticipated approach. This study utilizes MATLAB/Simulink and PyCharm framework for its investigation and projection.

Potential Application of Electronic Road Pricing (ERP) on Bandung City Roads

This research investigates the potential implementation of Electronic Road Pricing (ERP) in Bandung City, Indonesia, focusing on its effectiveness in reducing traffic congestion. The study employs a quantitative approach using a survey method, experiments, and statistical analyses to evaluate ERP's impact on road traffic performance and cost efficiency. The research design includes traffic volume analysis, vehicle operating costs, and data collection through questionnaires from Bandung residents selected randomly. The research subjects include frequent road users in congested areas, and the study was conducted in 2023. Using binary logistic regression, the results show significant shifts in road user behavior, with reductions in traffic volumes of 33% on Jalan Sukajadi, 38% on Jalan Dr. Djunjunan, and 23% on Jalan Terusan Jakarta. Additionally, ERP was found to improve cost efficiency in traffic management. The study concludes that ERP is a promising solution for managing congestion in Bandung, with broader implications for other congested cities in Indonesia.

Optimizing Supply Chain Transparency and Customer Compatibility with AI-Driven Models

As global supply chains become increasingly complex, the adoption of artificial intelligence (AI) technologies has emerged as a critical strategy for enhancing operational transparency and improving customer compatibility. This study investigates the application of AI-driven models in optimizing supply chain performance, focusing on predictive analytics, real-time data integration, and customer-centric personalization. A comprehensive experimental framework was employed, evaluating five distinct AI configurations against four key performance criteria: operational transparency, customer compatibility, cost efficiency, and delivery performance. Results demonstrated that the Real-Time Data Integration Model achieved a 20% improvement in operational transparency, allowing for enhanced visibility into inventory management and more agile responses to dynamic demand fluctuations. Additionally, the Customer-Centric Personalization Model increased customer satisfaction by 10%, emphasizing the critical role of tailored service delivery in modern supply chain management. The Cost Optimization Model yielded significant cost reductions, improving cost efficiency by 18%, though it showed a marginal decrease in customer compatibility. The findings highlight the trade-offs between cost efficiency and customer-centric strategies, suggesting that a balance is required to achieve a well-rounded and sustainable supply chain model. This research underscores the transformative potential of AI in driving efficiency, transparency, and customer satisfaction. Future work should explore the integration of advanced technologies such as 5G and further investigate scalable AI solutions capable of addressing the evolving challenges faced by global supply chains.

Impact of heterogenous capabilities on export performance amid the digital transformation

We investigate the effects of adopting digital technology on export performance of Korean manufacturing firms amidst the digital transformation. We recognize firm-level capabilities should be closely associated with adoption of rapidly progressing digital technology but also with export performance. And our data indicates that the most common purpose of digital technology adoption is to launch new products to the market. Hence, we consider that technology adoption is a strategic and purposeful decision to gain competitive edge mostly by producing new product, and treating technology adoption exogenous can be misleading. Due to the endogeneity and selection issues in technology adoption, the endogenous switching regression is applied to this study as Coad et al. (2020). On technology adoption decision, we find external innovative resources from strategic alliance in addition to internal innovative capabilities stand out. Given technology adoption decision, internal capabilities like patent rights and international affiliation are complementary factors to export growth. The treatment effect analysis has implications as follows: the result on contribution of technology adoption to export growth for actually adopting firms is rather small, and shows heterogenous innovation, organizational, and external capabilities are still critical factors as much as new products embedding high-end digital technology; the result on non-adopting firms indicates potential of advanced digital technology to improve export performance by helping to produce such new products if they were actually capable to do it. In sum, our findings provide another evidence that structurally positive interaction between innovative activities and export performance as Aw et al. (2011), since adoption of digital technology to products itself is innovative in the digital transformation. Furthermore, the result is consistent with the capability theory in that heterogenous innovative and complementary capabilities determine strategic technology adoption and export performance simultaneously. Finally, our findings indicate that the digital transformation might be still at the early stage. The fact that Korean firms have adopted advanced digital technology mainly for new products can be interpreted as an indicator of early development stage of transformation, since firms concentrate on product innovation than process innovation to gain competitive edge at the early stage (Utterback and Abernathy, 1975). Thus, we expect that further evolution of digital transformation can facilitate process innovation, then contribute to firm performance by improving cost efficiency that should be tackled in the upcoming study.

Heat and mass transfer in MHD flow of SWCNT and graphene nanoparticles suspension in Casson fluid

AbstractThe exceptional mechanical properties of carbon nanotubes (CNTs) and graphene nanoparticles, particularly their high aspect ratio and flexibility, position them as highly promising materials for the next generation of armor technology. Their incorporation into protective wear, such as bullet‐proof vests, offers the potential for significant improvements in both performance and cost efficiency. By replacing traditional materials with CNTs and graphene, the durability and maintenance of these protective devices could be substantially enhanced, leading to more effective and sustainable solutions for personal safety. This study focuses on the complex phenomena of heat and mass transport within a suspension of CNTs and graphene nanoparticles dispersed in a Casson fluid, particularly under the influence of an applied magnetic field. The analysis begins by reformulating the governing equations using similarity variables to transform them into a dimensionless form to simplify the problem. The resulting dimensionless equations are then solved using the three‐stage Lobatto IIIa finite difference method, a robust numerical technique well‐suited for solving boundary value problems in fluid dynamics. The results of this investigation highlight a significant 78.41% reduction in skin friction when compared with traditional CNT‐water nanofluid systems. This considerable decrease in skin friction not only reveals the superior performance of the CNT‐graphene nanofluid suspension but also opens up new possibilities for the design and development of advanced protective materials. These findings contribute to the growing body of knowledge on nanofluid applications and offer valuable insights for future research in the field of advanced armor technology.

Optimizing Sugarcane Clonal Propagation In Vitro by Using Calcium Ammonium Nitrate and Ammonium Sulfate.

To replace explosive nitrate-based chemicals in MS medium, this study developed a new, safer, and more cost-effective method using fertilizer-grade calcium ammonium nitrate and ammonium sulfate. This approach replaces ammonium nitrate and potassium nitrate, ensuring both safety and cost efficiency for sugarcane propagation. Six local sugarcane varieties-Zhongtang1 (ZT1), Zhongtang3 (ZT3), Zhongtang6 (ZT6), Guitang42 (GT42), Guitang44 (GT44), and Guiliu 07150 (GT07150)-were used. In the control group (Ck), nitrate ions (NO3-) were 39.28 mM, and ammonium ions (NH4+) were 20.49 mM, with a 2:1 ratio. In the treatment groups, the concentrations of nitrate ions (NO3-) and ammonium ions (NH4+) included treatment 1 (19.69 mM NO3- and 10.3 mM NH4+), treatment 2 (29.54 mM and 15.44 mM), treatment 3 (39.38 mM and 20.59 mM), treatment 4 (49.225 mM and 25.74 mM), treatment 5 (59.07 mM and 30.89 mM), and treatment 6 (68.915 mM and 36.03 mM), respectively, all with the same 2:1 ratio. Fifty bottles per treatment, with three replicates, were used for each sugarcane plantlets treatment. After five subcultures, the optimal ratio was determined by assessing morphological and physiological parameters, nitrogen levels, and SOD enzyme activity. The results indicated that treatment 3 (39.38 mM and 20.59 mM) and treatment 4 (49.225 mM and 25.74 mM) had the best morphological and physiological indicators. The optimal doses of calcium ammonium nitrate and ammonium sulfate were found in treatments 3 and 4, as well as in the control, with no significant difference among them. However, treatment 3, due to its lower dose, was more cost effective. To improve cost efficiency in practical production, it is recommended to use the lower concentration ratio of treatment 3 for plant tissue culture plantlets.

Fair Competition Review System and cross-regional capital flow: Evidence from China

Breaking local protectionism and market segmentation to promote the free flow of production factors between regions is crucial for building a unified national market in China. Introduced in 2016, the Fair Competition Review System (FCRS) restricts local governments’ abuse of administrative power to limit competition. The system corrects market failures and weakens regional barriers, establishing market competition by evaluating policies and regulations for anti-competitive practices. This study investigated the impact of the FCRS on cross-regional capital flow through subsidiaries in different regions. Using data from Chinese-listed companies between 2011 and 2022, this empirical study found that capital flow significantly increased after the system's implementation. Cross-regional flow was stronger in areas with higher reduced administrative barriers, lower tax burdens, and lower capacity utilization rates. This suggests that the primary mechanisms driving capital flow were expansion and cost-efficiency improvements. Heterogeneity tests indicate that the system exhibited a stronger impact on promoting cross-regional capital flow for private enterprises and those with low investment efficiency and weaker profitability. These findings suggest that the FCRS effectively regulates administrative monopolies, reduces regional barriers, and facilitates freer capital flow between regions, contributing to a unified national market in China.

Leveraging AWS and Java Microservices: An Analysis of Amazon\'s Scalable E-commerce Architecture

Abstract: This article presents a comprehensive case study of Amazon's journey in building a robust and scalable e-commerce platform capable of handling millions of daily transactions while maintaining high availability and performance. We examine the critical architectural decisions that facilitated Amazon's transition from a monolithic structure to a microservices-based architecture, leveraging Java and various AWS cloud services. The article explores key components of Amazon's scalable infrastructure, including the implementation of DynamoDB for high-performance database needs and the use of Elastic Load Balancing to ensure fault tolerance. We analyze the challenges encountered during this transformation and the solutions developed to address them. The article also discusses the resulting improvements in scalability, reliability, and cost-efficiency that have contributed to Amazon's position as the world's largest online retailer. Our findings provide valuable insights into best practices for architecting large-scale, cloud-native e-commerce platforms and offer implications for future developments in the field of distributed systems and cloud computing

The bus selection based on PV curve for the photovoltaic integration into power grid

Thanks to cost reduction, efficiency improvement, and fast advancement in power electronics, renewable energy, particularly solar power is increasing exponentially in the global energy sector. On the one hand, the integration of solar energy into the electricity is subject to a number of technical and non-technical challenges. Technical challenges include uncertainty of output power, system stability, imbalance between supply and demand, lack of reactive power, harmonics, angular stability, etc. The non-technical challenges include environmental, social and economic issues. On the other hand, the voltage profile in the weak nodes of the system is improved by the integration of solar power. The main purpose of the work is to identify buses which are suitable for the solar plant integration in the Albanian Power System (APS) based on the Power – Voltage (PV) curve method. The APS is modelled as an 18-bus grid (220 kV and 400 kV). The system simulation has been performed in the software PSS/E. Based on the critical point values of the PV curves methodology, two buses are identified as the most suitable for solar plant integration in the applications.

Analysis of the Use of Environmentally Friendly Building Materials and Construction Waste Management on Cost Efficiency and Project Sustainability in Karawang

This study investigates the impact of environmentally friendly building materials and construction waste management on cost efficiency and project sustainability in Karawang. A quantitative analysis was conducted using a sample of 150 respondents from the construction sector, with data collected through a structured survey based on a Likert scale of 1 to 5. Structural Equation Modeling-Partial Least Squares (SEM-PLS 3) was employed to analyze the relationships between the variables. The results show that both environmentally friendly materials and construction waste management significantly improve cost efficiency and project sustainability. Construction waste management exhibited a stronger influence on both outcomes, emphasizing its importance in reducing costs and promoting environmental responsibility. The findings suggest that adopting sustainable construction practices can enhance financial performance while contributing to long-term sustainability, offering valuable insights for construction companies and policymakers.

Advancing spatial analysis of invasive species movement data to improve monitoring, control programs and decision making: feral cat home range as a case study

Context Many invasive animals are typically active across large areas, making monitoring and control programs expensive. To be efficacious, monitoring devices and control tools need to be strategically located to maximise the probability of encounter. This requires an understanding of how the target species uses the landscape, through identifying key habitat or landscape features that are preferred and used disproportionately more frequently by the species. Spatial analysis of animal movements can help identify high use areas. Aims The variability introduced by different range calculation methods can lead to uncertainty in subsequent habitat analyses. We aimed to determine which method is superior for accurate delineation of core areas for feral cats. Methods We analysed spatial data from 35 collared feral cats across four Australian study sites between 2016 and 2019, and compared the core areas generated using seven commonly used home range estimation methods. Key results We found that the α-hull method provided a higher precision of polygon placement, resulting in lower Type I and II errors and higher conformity to landscape features than other methods. The α-hull used a single default parameter and required no subjective input, making it a more objective, superior method. Conclusions We recommend that the α-hull method be used to define core activity areas for feral cats, enabling more robust habitat analysis, and identification of key habitat and landscape features to strategically target for monitoring and control programs. Implications This strategic approach could significantly improve cost efficiencies, particularly where existing management is widely dispersed, and core activity areas are clumped.

Low-Voltage Water Pump System Based on Permanent Magnet Synchronous Motor

This paper designs a safe, low-cost, and efficient permanent magnet synchronous motor (PMSM) booster pump system. The aim is to enhance the pump’s safety and reduce the incidence of electric shock accidents, while also achieving cost reduction and efficiency improvement. The pump components are made of a plastic material, and a safe voltage of 36 V is used as the operating voltage. Additionally, the PMSM is chosen to replace the induction motor (IM) as the pump’s driving device, utilizing sensorless control and field-weakening control strategies. The study results show that when the flow rate is 1.51 m3/h, the efficiency of the PMSM low-voltage pump can reach up to 20.86%. At the same flow rate of 1 m3/h, compared to other pumps, the PMSM low-voltage pump exhibits higher head, energy savings, and efficiency. The proposed PMSM low-voltage pump offers advantages such as high efficiency, energy savings, safety, and low cost. This study provides a reference for the domestic PMSM pump industry.

Letter to the editor: Prospective analysis of STRATAFIX™ symmetric PDS plus suture for fascial closure in spinal surgery: a pilot study.

Spine surgery is essential for restoring alignment, stability, and function in patients with cervical spine injuries, especially when instability, pain, deformity, or progressive nerve damage is present. Effective wound closure is vital in these procedures, aiming to promote rapid healing, reduce infection risks, enable early mobilization, and ensure satisfactory cosmetic results. However, there is limited evidence on the optimal wound closure technique for posterior spine surgery, highlighting the need for innovative approaches. A study by Glener et al. evaluated the effectiveness of STRATAFIX™ Symmetric barbed sutures compared to traditional braided absorbable sutures in spinal surgery. In a randomized trial involving 20 patients, the STRATAFIX™ group demonstrated a shorter mean closure time and significantly fewer sutures used, though without a statistically significant reduction in closure time. No significant differences were observed in postoperative complications between the groups during a six-month follow-up. While the findings suggest potential cost savings and efficiency improvements with STRATAFIX™, the study's small sample size and short follow-up period limit its generalizability. Furthermore, AI-based models, such as the Xception deep learning model, show promise in improving suture training accuracy for medical students, which could enhance surgical outcomes and reduce complications. Despite the promising results, further research with larger sample sizes, extended follow-up periods, and multi-center trials is necessary to validate the effectiveness of barbed sutures like STRATAFIX™ in neurosurgery. The integration of AI in surgical training and continued exploration of innovative techniques are essential to advancing the field and optimizing patient care in spinal surgery.

Establishing an Evaluation Indicator System for User Satisfaction With Hypertension Management Apps: Combining User-Generated Content and Analytic Hierarchy Process.

Hypertension management apps (HMAs) can be effective in controlling blood pressure, but their actual impact is often suboptimal. Establishing a user satisfaction evaluation indicator system for HMAs can assist app developers in enhancing app design and functionality, while also helping users identify apps that best meet their needs. This approach aims to improve the overall effectiveness of app usage. This study aims to systematically collect data on HMAs and their user reviews in the United States and China. It analyzes app usage patterns and functional characteristics, identifies factors influencing user satisfaction from existing research, and develops a satisfaction evaluation indicator system to provide more accurate recommendations for improving user satisfaction. We conducted a descriptive statistical analysis to assess the development status of HMAs in both countries and applied the task-technology fit model to evaluate whether the app functionalities align with business needs. We separately summarized the factors influencing user satisfaction in both countries from previous research, utilized the analytic hierarchy process to develop an evaluation indicator system for HMA user satisfaction, and calculated satisfaction levels. Based on these findings, we propose improvements to enhance app functionality and user satisfaction. In terms of current development status, there were fewer HMAs and user reviews in China compared with the United States. Regarding app functional availability, fewer than 5% (4/91) of the apps achieved a demand fulfillment rate exceeding 80% (8/10). Overall, user satisfaction in both countries was low. In the United States, user satisfaction was lowest for advertising distribution, data synchronization, and reliability. By contrast, Chinese apps need improvements in cost efficiency and compatibility.