Integrating Artificial Intelligence and Customer Experience

Artificial intelligence (AI) has been widely adopted in the service sector to enhance the customer experience and gain a competitive advantage. However, there are a limited number of papers that focus on the relationship between AI and customer experience, and there is no clear framework to reveal how AI influences the customer experience. Therefore, this paper will address how AI affects the customer experience and develop a conceptual framework of AI applications in customer experience along the customer journey. A two-step research design is adopted in this paper. The first phase aims to identify a framework through an extensive systematic literature review of the relevant databases. The findings cover three main themes: AI experience, AI functions, and AI services. A research framework is created on the basis of the findings. This paper contributes to consumer behavior and services by integrating AI with customer experience and providing a comprehensive framework for guiding future research. The study also offers practical implications for practitioners to enhance customer experience

Evaluation of trial reintroductions of two extinct in the wild reptile species on Christmas Island

Conservation reintroductions play a vital role in the recovery of threatened species, and clear goals and objectives are essential for evaluating their effectiveness. In this study, we assessed short-term success (<18 months) of trial reintroductions of the Extinct in the Wild blue-tailed skink (Cryptoblepharus egeriae) and Lister's gecko (Lepidodactylus listeri) on Christmas Island. Our evaluation criteria focused on body condition, reproduction, habitat suitability, survival and population growth. In 2018 and 2019, 170 C. egeriae and 160 L. listeri were translocated from a local captive breeding facility to a 2600 m2 outdoor fenced enclosure designed to exclude a predatory snake. Despite body condition declining immediately following release for both species, it had improved by 6 months post-release. We also detected successful reproduction in both species. Apparent survival was high for C. egeriae but low for L. listeri, and population growth was only evident in C. egeriae. We were unable to determine whether low survival of L. listeri in the release site was due to high post-release dispersal (beyond the exclosure) or mortality. Both species selected habitats that contained high rock and log cover and avoided areas with low ground cover. Appropriate assessment criteria, as utilized in this study, enable objective and timely evaluations of reintroduction success, thereby facilitating the improvement and refinement of reintroduction protocols. Our study showed that C. egeriae can establish (in the short- to medium-term) in a site from which a principal threat has been excluded and undergo rapid population growth, whereas under current conditions L. listeri cannot. However, we also demonstrate that such medium-term success may not lead to long-term success, as the rapid increase in C. egeriae population was reversed between 29 and 31 months after release because the barrier used to exclude an invasive predator, the wolf snake (Lycodon capucinus), was breached

Continuous Purchase Intention of Organic Personal Care Products: Evidence from India

This study was undertaken to understand the antecedents of continuous purchase intention (CPI) of organic personal care products (OPCPs). It draws on the theory of planned behavior and the stimulus–organism–response theory to build an integrative conceptual framework. Most past studies have been conducted in developed countries, where the organic products market is more evolved. Partial least squares path modeling was used to examine various relationships among a sample of 1,378 consumers in India who buy only OPCPs. Product knowledge (PK) is the strongest influencer of attitude which has a high impact on satisfaction which in turn affects CPI positively. PK has greater significance in developing countries which have a higher share of counterfeit and unbranded products. While many studies have been conducted on CPI of organic food, there are only a few on OPCP. Among these, studies on the CPI of OPCP in developing countries are scarce

Influence of Fabric Structure of Aramid-Reinforced Polycarbonate Composites on Its Ballistic Resistance Verified by Experiment and Simulation

Previous research on the influence of fabric structure on ballistic performance has predominantly concentrated on the pure fabric level. In order to gain an insight into the relationship between fabric structure of composite materials and ballistic resistance, this study investigates the ballistic properties of laminates made by compounding polycarbonate (PC) with four commonly used woven fabrics, namely plain, twill, basket, and satin. The corresponding numerical model has been established, and the damage mechanism is analyzed. The experimental results indicate that the fabric structure with a lower number of interlacing points, namely satin, shows an improvement in energy absorption by 7.1-17.1% compared to other fabric structures with more interlacing points. Additionally, an in-depth analysis of the residual velocity and stress distribution during penetration process by examining the damage morphology of the four types of laminates reveals that woven fabrics with a lower number of interlacing points have a faster stress propagation rate and greater in-plane and transverse strains. This work can provide theoretical guidance for optimizing bulletproof materials and designing fabric structures more efficiently

The TESS-Keck Survey. XXIV. Outer Giants May Be More Prevalent in the Presence of Inner Small Planets

We present the results of the Distant Giants Survey, a 3 yr radial velocity (RV) campaign to search for wideseparation giant planets orbiting Sun-like stars known to host an inner transiting planet. We defined a distant giant (DG) to have a = 1–10 au and M i p sin = 70–4000 M⊕ = 0.2–12.5 MJ, and required transiting planets to have a < 1 au and Rp = 1–4 R⊕. We assembled our sample of 47 stars using a single selection function and observed each star at monthly intervals to obtain ≈30 RV observations per target. The final catalog includes a total of 12 distant companions: four giant planets detected during our survey, two previously known giant planets, and six objects of uncertain disposition identified through RV/astrometric accelerations. Statistically, half of the uncertain objects are planets and the remainder are stars/brown dwarfs. We calculated target-by-target completeness maps to account for missed planets. We found evidence for a moderate enhancement of DGs in the presence of close-in small planets (CSs), P(DG|CS) =31 11 12 - + %, over the field rate of P(DG) =16 %2 2 - + . No enhancement is disfavored (p ∼ 8%). In contrast to a previous study, we found no evidence that stellar metallicity raises the enhancement of P(DG|CS) over P(DG). We found evidence that DG companions preferentially accompany shorter-period CS planets and have lower eccentricities than randomly selected giant planets. This points toward a nuanced picture of dynamically cool formation in which giants interact with, but do not disrupt, their inner systems

AIAA SciTech Forum 2025

Optimising a vehicle's design and trajectory simultaneously to maximise a mission objective, which we term co-design, may be particularly suited to hypersonic vehicles. Trajectories of these vehicles cover a wide flight envelope and will likely have influential thermal, dynamic pressure, and stability constraints. The lack of established reference vehicles and the lack of obvious nominal operating points at which to optimise a vehicle's design can complicate traditional methods in which separate tools are used for aerodynamic design, thermal protection design, and trajectory planning. Conversely, directly modelling the influence of each design parameter on an overall mission objective provides a simplified and systematic method to reach high-performing designs with potentially fewer design iterations. This paper describes the continued work of the authors to develop a computationally tractable co-design framework suitable for use with high-fidelity computational fluid dynamics. Additional design parameters impose very low marginal computational cost, which permits vehicle designs with many degrees of freedom. The method is demonstrated by finding the optimal design of two vehicles subject to geometric, internal volume, and static stability constraints. Each vehicle is designed for an optimum three degree-of-freedom trajectory subject to different trajectory constraints, resulting in two distinct vehicle designs. We demonstrate the superior performance of a vehicle executing its co-designed trajectory compared to the optimal trajectory of a second vehicle subject to its non-designed constraints, in turn highlighting the utility of the co-design method. Moreover, the framework is well-suited to incorporate thermal constraints and propulsion models in future work. Moreover, replacing the current approximate aerodynamic model with high-fidelity computational fluid dynamics, and incorporating thermal constraints and propulsion models, will likely further differentiate vehicles designed for specific missions

Thermoplastic Elastomer-Reinforced Hydrogels with Excellent Mechanical Properties, Swelling Resistance, and Biocompatibility

Strong and tough hydrogels are promising candidates for artificial soft tissues, yet significant challenges remain in developing biocompatible, anti-swelling hydrogels that simultaneously exhibit high strength, fracture strain, toughness, and fatigue resistance. Herein, thermoplastic elastomer-reinforced polyvinyl alcohol (PVA) hydrogels are prepared through a synergistic combination of phase separation, wet-annealing, and quenching. This approach markedly enhances the crystallinity of the hydrogels and the interfacial interaction between PVA and thermoplastic polyurethane (TPU). This strategy results in the simultaneous improvement of the mechanical properties of the hydrogels, achieving a tensile strength of 11.19 ± 0.80 MPa, toughness of 62.67 ± 10.66 MJ m−3, fracture strain of 1030 ± 106%, and fatigue threshold of 1377.83 ± 62.78 J m−2. Furthermore, the composite hydrogels demonstrate excellent swelling resistance, biocompatibility, and cytocompatibility. This study presents a novel approach for fabricating strong, tough, stretchable, biocompatible, and fatigue- and swelling-resistant hydrogels with promising applications in soft tissues, flexible electronics, and load-bearing biomaterials

Learning from life, Enabling artificial intelligence: Scientific historical insights from the Nobel Prize in physics

The 2024 Nobel Prize in Physics recognized John Hopfield and Geoffrey Hinton for their transformative contributions to artificial neural networks, sparking widespread debate within the academic community. Why was a physics prize awarded to researchers in artificial intelligence (AI)? How have their achievements influenced the historical trajectory of AI? This article adopts a history-of science perspective to trace the evolution of neural network technologies, from Hopfield networks to the Boltzmann machine. It examines the interdisciplinary nexus between physics and AI, highlighting its broader implications for future scientific advancements

Nurturing resilience and healing from within: The impact of an 8-week yoga program on nursing students

Background/Objectives: Nursing students encounter significant stress due to the demanding nature of their academic and clinical training, negatively impacting their mental health and overall wellbeing. Self-care strategies, such as yoga, have been suggested to effectively manage stress and promote resilience. Despite the growing recognition of the importance of self-care in nursing education, there is limited research on the specific benefits of yoga. This study aimed to explore the experiences and perceived benefits associated with undergraduate nursing students’ participation in an 8-week yoga study. Methods: A qualitative study using a hermeneutic phenomenological approach was conducted. Participants were Baccalaureate nursing students from an Australian university. Data were collected through semi-structured interviews and analysed using reflexive thematic analysis. Reporting methods followed the consolidated criteria for reporting qualitative research guidelines. Results: Among the 14 students who participated, three main themes emerged: “Me Time”, highlighting the importance of prioritising self-care; “Slowing Down,” emphasising the psychological benefits of yoga; and “Self-Acceptance,” reflecting personal growth and improved self-awareness. Participants reported reduced stress, improved mood, and enhanced physical and mental wellbeing. Conclusion: Students who participated in yoga were positively impacted through greater stress management and wellbeing. As nursing students transition into the workplace, the ability to manage stress and maintain mental wellbeing becomes even more critical. The high-pressure environment of healthcare settings can exacerbate stress, leading to burnout and decreased job satisfaction. By incorporating self-care practices such as yoga into their routine, nursing students can develop resilience and coping mechanisms that will benefit them as students and throughout their careers

Satellite-based data for agricultural index insurance: a systematic quantitative literature review

Index-based insurance (IBI) is an effective tool for managing climate risk and promoting sustainable development. It provides payouts based on a measurable index. Remote sensing data obtained from satellites, planes, UAVs, or drones can be used to design index-based insurance products. However, the extent to which satellite-based data has been used for different crop types and geographical regions has not been systematically explored. To bridge this gap, a systematic quantitative literature review was conducted to examine the use of satellite-based datasets in designing index-based insurance products. The review analyzed 89 global studies on four major types of crops: cereals, pastures and forages, perennial crops, and others (i.e., vegetables, oilseed crops, fruits, nuts, etc.). The analysis revealed a rising interest of developing index-based insurance solutions utilizing satellite-based data, particularly after 2015. Datasets from land surface Earth observation satellites were utilized in 91 % of studies with satellite-based data, outnumbering those from weather satellites. The Normalized Difference Vegetation Index (NDVI) was the most prominent satellite-retrieved vegetation index, featured in 61.2 % of studies utilizing satellite imagery, revealing its effectiveness at designing and developing IBI for various crops. It has also been found that satellite-based vegetation health indices outperform weather indices and reduce basis risk with higher-spatial-resolution data. Most studies have focused on cereal crops, with fewer studies focusing on perennial crops. Countries in Asia and Africa were the most interested regions. However, research has focused on specific countries and has not been adequately spread across different regions, especially developing countries. The review suggests that satellite-based datasets will become increasingly important in designing crop-index-based insurance products. This is due to their potential to reduce basis risk by providing high resolution with adequately long and consistent datasets for data-sparse environments. The review recommends using high-spatial- and high-temporal-resolution satellite datasets to further assess their capability to reduce basis risk