Demystifying App Performance Optimization: From Cold Starts to Seamless Transitions

Purpose : The research aimed to analyze how user engagement acted as a mediating factor in the association among various aspects of the OTT platform experience and overall user satisfaction (US). Integrating the technology acceptance model into this study provided insights into user experience with OTT platforms. Design/Methodology/Approach : This study used a quantitative approach. It was based on primary data collected from a sample of 384 OTT users via a structured survey. The study tested the impact of perceived usefulness (PU) and social influence (SI) on user satisfaction (US). The study also delineated the mediating role of user engagement and the moderating effect of technological readiness (TR) on the US. Moreover, the study tested the impact of predictor variables on the response variable using PLS-SEM. Findings : The study found that the US was vital for OTT platforms to remain competitive and deliver an extraordinary user experience. User engagement (UE) was a noteworthy positive mediator between user experience and satisfaction. A positive user experience led to superior engagement, which, in turn, amplified satisfaction. Practical Implications : This study’s findings offered valuable insights for OTT service providers, underscoring the importance of enhancing platform usability, leveraging SI, and upholding UE to optimize US. The platform managers gave greater consideration to visual elements, such as colors, design, and structure, which improved the sensorial experience. Originality/Value : This study offered unique insights into OTT platforms in the US, focusing on the mediating role of UE in relation to PU, SI, US, and technological readiness.

This review aims to identify the contribution of user experience features and underlying technical features to sustained engagement in unguided chatbots for improving health-related behaviors. Following PRISMA-2020 guidelines, we conducted a systematic review, searching PubMed, ACM, APA PsycINFO, Cochrane, Web of Science, and IEEE Xplore from June to September 2022 and updated in April 2025. Data was analyzed via Synthesis without Meta-Analysis (SWiM), to understand the relationship between user engagement overall and individual experience metrics. Customizable avatars and flexible input interactions may enhance overall user engagement. Conversely, pre-scripted content that lacks personalization and emotional support negatively impacts user satisfaction and adherence to health interventions. Other features contributing to sustained engagement are in-app technical assistance, user learning features, and crisis support systems. A strong positive correlation (r = 0.808, n = 16) was observed between user satisfaction and engagement, specifically for satisfaction dimensions including need fulfillment (r = 0.872, n = 6), willingness to recommend chatbot (r = 0.817, n = 4) and user enjoyment (r = 0.971, n = 3) in SWiM analysis. The limited application of large language models and retrieval augmented generation techniques may constrain the quality of support available to users and overall sustained engagement. Effective unguided chatbot design requires an emphasis on interactive educational elements, in-app technical assistance and crisis support, and personalized content. This can be achieved with high context awareness, input understanding, and quality content generation. Our findings suggest that user satisfaction is a primary driver of sustained engagement, though further research is needed to validate individual user satisfaction features for sustained engagement.

HNN-based generalized predictive control for turbofan engine direct performance optimization

Much research in information retrieval (IR) focuses on optimization of the rank of relevant retrieval results for single shot ad hoc IR tasks. Relatively little research has been carried out on user engagement to support more complex search tasks. We seek to improve user engagement for IR tasks by providing richer representation of retrieved information. It is our expectation that this strategy will promote implicit learning within search activities. Specifically, we plan to explore methods of finding semantic concepts within retrieved documents, with the objective of creating improved document surrogates. Further, we would like to study search effectiveness in terms of different facets such as the user's search experience, satisfaction, engagement and learning. We intend to investigate this in an experimental study, where our richer document representations are compared with the traditional document surrogates for the same user queries.

lnformation system will never run cource, but requires support from thte users participation. The users participation in the development of the informotion systems expected can give the efectivity -from information system that is reflected on the users satisfaction. This study does not only examine the relationship between the users participation and the users satisfoction in the development of the information system, but also enhancing the job experience as moderating variable. The objective of this study is to find empirical evidence whether the job experience give a significant impact to the moderating variable in the relationship between the users participation and the users satisfaction in the development of the information system. The analysis indicated that the job experience statistically influenced the relationship between the users porticipation and the users satisfaction in the development of the informationsystemKeywords : The users participation, The users satisfaction, The job experience.

In recent years, mobile health (mHealth) applications have revolutionized healthcare by improving accessibility, boosting patient engagement, and simplifying health management processes. However, despite their increasing popularity, there is still a significant lack of understanding regarding how demographic factors shape user perceptions and interactions with these tools. This research aims to assess user satisfaction and the perceived value of the Sehhaty app among residents of Hail City, Saudi Arabia, while also examining how demographic variables influence user engagement. The findings emphasize the necessity of incorporating demographic insights into the design of mHealth applications and introduce the Integrated Digital Health Engagement Model (IDHEM) as a novel theoretical framework. A cross-sectional study design was implemented, using an electronic survey distributed to 333 users of the Sehhaty app. The survey evaluated key aspects such as ease of use, user satisfaction, system information organization, and perceived usefulness. Convenience sampling was utilized to ensure participation from a wide range of demographic groups. Descriptive statistics and Pearson correlation analysis were conducted to explore the relationships between demographic characteristics and user perceptions. The study revealed high levels of user satisfaction, with 94% of participants reporting that the app was easy to use, resulting in an overall satisfaction score of 4.56 out of 5. Significant correlations were identified between demographic factors like age, gender, and employment status, suggesting that personalized development approaches can significantly enhance user engagement. The Sehhaty app shows great promise in enhancing healthcare access and management, especially among younger and female users. The findings underscore the importance of considering demographic factors in the design of mHealth applications to better meet diverse user needs. Additionally, this study introduces the IDHEM, providing a new framework for understanding user behavior and guiding the development of future digital health solutions.

The rapid growth of digital payment systems has intensified competition among e-wallet providers, making user loyalty a critical challenge. This study examines the role of user satisfaction as a mediating variable in the relationship between transaction security and customer engagement on loyalty toward the DANA e-wallet service. The research was conducted using a quantitative approach, with data collected through questionnaires distributed to DANA users in Sumbawa City. A total of respondents were selected using purposive sampling, and the data were analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS). The results show that user satisfaction has a positive and significant effect on user loyalty. Transaction security and customer engagement both significantly influence user satisfaction, while their direct effects on loyalty are not fully consistent without the presence of satisfaction. Further analysis confirms that user satisfaction significantly mediates the effect of transaction security and customer engagement on loyalty. These findings indicate that loyalty toward e-wallet services is not formed solely through technical features or interaction intensity, but through users' evaluative experiences that lead to satisfaction. Transaction security creates a sense of trust and comfort, while customer engagement enriches user experience; However, both factors contribute to long-term loyalty only when they result in user satisfaction. This study highlights the strategic importance of prioritizing user satisfaction to transform secure systems and engagement initiatives into sustainable loyalty within digital financial services.

Anion exchange membrane fuel cells (AEMFCs) are the most promising low-temperature fuel cells and have received extensive attention. Compared to PEMFCs, the cost per unit of power can be significantly reduced for AEMFCs because, in theory, they allow the usage of non-precious metal catalysts and low-cost cell components. Owing to the development of advanced materials and performance improvement strategies, AEMFCs have achieved new records in both initial performance and durability. However, the high performance currently achieved is contingent on certain conditions, e. g., high Pt loading, large gas flowrates, and operation in pure O2 , which are far from practical applications. Therefore, the transition to commercially relevant performance and durability is the next goal of AEMFCs. This paper reviews the performance data of H2 -fueled AEMFCs since 2010 and summarizes possible performance optimization schemes, which can provide useful insights for developing next-generation AEMFCs.

The purpose of this study is to examine the effect of the disabled activity support service on the use satisfaction of people who have used facilities for the disabled, and to determine whether the disabled s participation in social activities acts as a parameter in the relationship of the effect. The subject of this study was collected from persons with disabilities using the activity support service for the disabled in Seoul and Gyeonggi Province, and the results of the study were analyzed using SPSS/WIN 22.0 for technical statistics, multiple regression analysis and mediation effect verification method for a total of 473 copies. Is as follows. First, it was found that the disabled activity support service had a significant effect on user satisfaction. Looking at the sub-factors of the activity support service for the disabled, it was found that daily life support, the level of user rights recognition, and the degree of service use all had a great influence on user satisfaction. Second, it was found that the disabled activity support service had a significant effect on users participation in social activities. Third, it was found that users participation in social activities had a significant effect on user satisfaction. Fourth, social activity participation showed a significant mediating effect in relation to the effect of the disabled activity support service on user satisfaction. Looking at the sub-factors of the activity support service for the disabled, the daily life support, the level of user rights recognition, and the degree of service use all had significant mediating effects. Finally, if the social bond is expanded to encourage the participation of the disabled in social activities based on the results of this study, the effect of the disabled activity support service on user satisfaction will increase, and the institutional effectiveness of the disabled activity support service is expected.

Sports injuries are a significant concern for athletes, often leading to performance decline, financial losses, and long-term health issues. With the advancement of artificial intelligence (AI), data-driven models have emerged as effective tools to predict injury risk and support preventive strategies. This study investigates the application of three AI approaches-Logistic Regression, Decision Trees, and Deep Learning-for athlete injury prediction. Logistic Regression is employed as a baseline statistical model to identify linear risk factors, while Decision Trees capture non-linear relationships and provide interpretable decision rules. Deep Learning techniques, particularly neural networks, are applied to handle complex, high-dimensional data, such as biometric, physiological, and training load variables. Model performance is evaluated using standard metrics including accuracy, precision, recall, and F1-score. The comparative analysis highlights the strengths and limitations of each approach, emphasizing tradeoffs between interpretability and predictive power. Findings suggest that while Logistic Regression and Decision Trees are valuable for transparent and explainable predictions, Deep Learning achieves superior accuracy in capturing hidden patterns within athlete datasets. This research contributes to the development of intelligent sports science frameworks, enabling coaches, medical professionals, and athletes to implement data-driven strategies for injury prevention and performance optimization. This study presents a comparative analysis of three AI-based techniques-Logistic Regression, Decision Trees, and Deep Learning-for predicting injuries in athletes. The obtained outcomes indicate how successful the two suggested models are in letting the transfer learning model achieve Linear regression accuracy of 93.15% and RNN accuracy of 91.24%.

The increasing popularity of wearable electronic devices has led to the rapid development of flexible energy conversion systems. Flexible rechargeable zinc-air batteries (ZABs) with high theoretical energy densities demonstrate significant potential as next-generation flexible energy devices that can be applied in wearable electronic products. The design of highly efficient and air-stable cathodes that can electrochemically catalyze both the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are highly desirable but challenging. Flexible carbon-based catalysts for ORR/OER catalysis can be broadly categorized into two types: (i) self-supporting catalysts based on the in situ modification of flexible substrates; (ii) non-self-supporting catalysts based on surface coatings of flexible substrates. Methods used to optimize the catalytic performance include doping with atoms and regulation of the electronic structure and coordination environment. This review summarizes the most recently proposed strategies for the synthesis of designer carbon-based electrocatalysts and the optimization of their electrocatalytic performances in air electrodes. And we significantly focus on the analysis of the inherent active sites and their electrocatalytic mechanisms when applied as flexible ZABs catalysts. The findings of this review can assist in the design of more valuable carbon-based air electrodes and their corresponding flexible ZABs for application in wearable electronic devices.

Sleep restriction is genetically influenced, disrupting neurophysiological mechanisms that regulate chronobiology. This dysfunction impairs metabolic and sensorimotor functions, altering nociception and increasing the risk of inflammation and musculoskeletal injuries in athletes. Consequently, certain genetic polymorphisms stand out as biomarkers of this profile and the consequent reduction in athletic performance. This review seeks to correlate evidence on the variants associated with sleep modulation with alterations in athletic performance and to understand their physiological contributions. A search of studies in Portuguese and English indexed in SciELO and PubMed/MEDLINE (2013-2025) was conducted using the descriptors “sleep”, “pain”, “genetic polymorphisms”, and “sport”. Twenty articles were selected, including reviews, clinical studies, and meta-analyses. The Val66Met (BDNF) polymorphism is linked to increased chronic pain, sleep disorders, and fatigue; Y362H (DEC2) promotes reduced restorative sleep and greater resistance to its deprivation; and PER3 (VNTR) is associated with worse cognitive performance, executive function, and sustained attention. This reveals a complex interaction among neurophysiological, genetic, and environmental factors crucial to athletic health. Specifically, sleep deprivation dysregulates pain modulation, exacerbating inflammatory responses and injury risk. The connection between sleep, pain, and athletic performance is multifactorial. Future research could yield more effective, personalized strategies for injury prevention and performance optimization.

Comprehensive Summary Understanding the solution‐state aggregation of conjugated polymers is essential for controlling their film microstructure and improving optoelectronic device performance. However, resolving aggregate structures in donor:acceptor blends remains challenging due to limited contrast and the multicomponent nature of these systems. Here, we selectively deuterate the side chains of poly(3‐hexylthiophene) (P3HT) to produce P3HT‐D, substantially increasing its neutron scattering length density (SLD). This isotopic modification enables high‐contrast small‐angle neutron scattering (SANS) analysis of polymer aggregation in solutions of polymer:nonfullerene acceptor (NFA) blends. The enhanced contrast overcomes the deficiencies of conventional X‐ray scattering and microscopy, allowing for unambiguous determination of chain conformation and aggregate structure. Photodiodes incorporating P3HT‐D show improved responsivity and achieve a high specific detectivity of 5.67 × 10 13 Jones. These improvements are attributed to refined film morphology, improved miscibility, and reduced nonradiative recombination facilitated by isotopic substitution. Our findings demonstrate that side‐chain deuteration provides a dual benefit: (i) enabling precise structural characterization and (ii) tuning intermolecular interactions to improve device performance. This study establishes side‐chain deuteration as a versatile strategy for structural analysis, microstructure engineering, and performance optimization in conjugated polymer–based organic photodiodes.

Optimum atomic concentration in structurally disordered nanoporous Pt–Co alloys with the strongest mechanical properties

Mobile application developers have started to realize that quality plays a vital role in increasing the popularity of mobile applications (apps), thereby directly influencing economical profit (in-app purchases revenue) and app-related success factors (i.e., number of downloads). Therefore, developers have become increasingly concerned with taking preemptive actions to ensure the quality of their apps. In general, developers have been relying on testing as their main quality assurance practice. However, little is known about how much mobile app testing contributes to increasing user level satisfaction. In this paper we investigate to what extent testing mobile apps contributes to achieving higher user satisfaction. To this end, we probed into whether there is a relation between having automated tests and overall user satisfaction. We looked into users ratings, which express their level of satisfaction with apps, and users reviews, which often include bug (i.e., fault) reports. By analyzing a quantitative indicator of user satisfaction (i.e., user rating), we found that there is no significant difference between apps with automated tests and apps that have been developed without test suites. We also applied sentiment analysis on user reviews to examine the main differences between apps with and without test suites. The results of our review-based sentiment analysis suggest that most apps with and without test suites score quite high for user satisfaction. In addition, we found that update-related problems are far more common in apps with test suites, while apps without test suites are likely to have battery-drain problems.