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Enhancing Customer Engagement Through Artificial Intelligence Authenticity
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The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1111/jpim.70008#support-information-section .Summary:
• Our study shows that designing authentic AI systems can significantly enhance customer engagement by building trust, raising performance expectations, and encouraging users to invest effort, especially in high-stakes sectors like healthcare.
For managers, this means going beyond efficiency to focus on relationship-building.
• Authentic AI should blend functional traits (accuracy, credibility) with emotional traits (realism, connectedness, social presence, and individuality) to align with evolving customer expectations.
Managers can achieve this by personalizing interactions based on customer history, enabling AI to recall previous conversations, and adapting tone to emotional cues to create a sense of continuity and care.
• Tailoring which authenticity components to emphasize (e.g., credibility in healthcare, social presence in retail) and ensuring regular audits, updates, and human oversight can improve engagement, build loyalty, and deliver stronger returns on AI investments.Given the limited research on the factors and mechanisms underlying artificial intelligence (AI) authenticity, we examine its use in fostering breakthrough knowledge and enhancing customer engagement. We devised a robust model grounded in mind perception and social exchange theories, with a focus on the outcomes of AI authenticity. Tested across 452 virtual health home stations, the findings reveal that both performance expectation and effort expectation serve as mediators between AI authenticity and customer engagement. This research provides managers with comprehensive insights into the defining attributes and operational mechanics of AI authenticity, thereby highlighting its critical importance in boosting customer engagement.The authors received no specific funding for this work
Observation of Coherent (1020) Meson Photoproduction in Ultraperipheral PbPb Collisions at √<sub>NN</sub> = 5.36 TeV
No full textA version of the article is available at arXiv:2504.05193v2 [nucl-ex] (https://arxiv.org/abs/2504.05193). Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/HIN-24-009 (CMS Public Pages). Subjects: Nuclear Experiment (nucl-ex); High Energy Physics - Experiment (hep-ex). Report number: CMS-HIN-24-009, CERN-EP-2025-051. Journal reference: Phys. Rev. Lett. 135 (2025) 262301. Related DOI: https://doi.org/10.1103/2ssw-wwyy. Submission history: From: The CMS Collaboration: [v1] Mon, 7 Apr 2025 15:43:00 UTC (419 KB); [v2] Mon, 12 Jan 2026 21:51:05 UTC (474 KB).The first observation of coherent (1020) meson photoproduction off heavy nuclei is presented using ultraperipheral lead-lead collisions at a center-of-mass energy per nucleon pair of 5.36 TeV. The data were collected by the CMS experiment and correspond to an integrated luminosity of 1.62 μ⁻¹. The (1020) meson signals are reconstructed via the +− decay channel. The production cross section is presented as a function of the (1020) meson rapidity in the range 0.3<||<1.0, probing gluons that carry a fraction of the nucleon momentum () around 10⁻⁴. The observed cross section exhibits little dependence on rapidity and is significantly suppressed, by a factor of ∼5, compared to a baseline model that treats a nucleus as a collection of free nucleons. Theoretical models that incorporate the nuclear shadowing effect generally provide a better description of the (1020) data than those incorporating gluon saturation. This study establishes a powerful new tool for exploring nuclear effects and nuclear gluonic structure in the small- regime at a unique energy scale bridging the perturbative and nonperturbative quantum chromodynamics domains.SCOAP³
GNSS/MEMS INS tightly coupled algorithm for agricultural machinery navigation enhanced by random forest-based behavioral state awareness
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Data will be made available on request.Global navigation satellite system (GNSS)/micro-electro-mechanical systems inertial navigation system (MEMS INS) algorithm is widely used in agricultural machinery navigation. However, several issues remain noteworthy, uneven terrain induces more high-frequency noise than other environments, which severely affects the accuracy of MEMS INS. In addition, occlusion environment, such as field windbreak, degrades GNSS signal quality. Although Butterworth filter and non-holonomic constraints (NHC) have been validated as effective solutions for these issues, which still face the following limitations in agricultural scenarios. This is because the power spectral density (PSD) of MEMS INS data exhibits distinct energy distribution among different states, therefore it is unreasonable to apply uniform cutoff frequency same as classic Butterworth filter. Additionally, jumping and slipping frequently occur, which can invalidate the zero-velocity assumption of NHC. Therefore, given the limitations of previous studies, this paper proposes a random forest (RF)-based model to identify machinery states and predict body-frame (right and up) velocities. Then, adaptive cutoff frequencies are selected for the Butterworth filter. Furthermore, the measurement and stochastic models of NHC are optimized by states and body-frame velocities. Experiments show that the proposed algorithm can achieve centimeter-level positioning accuracy and the heading angle error of only 0.33°.This work was supported by the Programs of the National Natural Science Foundation of China (42374025). This work was also supported by the Program of China Scholarship Council (CSC) under Grant 202406560066
A novel multi-scale quadratic convolutional network for bearing fault diagnosis: Handling noisy conditions
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Data will be made available on request.Despite recent advances in deep learning-based fault diagnosis, it is challenging to build a reliable fault diagnosis model for rolling bearings under noisy conditions. Rolling bearing vibration signals are frequently corrupted by various types of noises, which poses significant challenges for accurate fault feature extraction and degrades diagnostic performance. This paper proposes a multi-scale hybrid information fusion method based on a quadratic embedded-attention convolutional network (MSHQAN) for bearing fault diagnosis. Specifically, a multi-scale feature extraction (MFE) module is proposed to extract representative features from the vibration signals. In the MFE module, a quadratic mixed layer is introduced to model the complex nonlinear relationships and multi-scale features in the vibration signal. Furthermore, a spatial-refined feature unit is put forward to refine the features extracted by the quadratic mixed unit to obtain discriminative spatial features. Additionally, a hybrid feature weight fusion module is proposed to achieve optimal fusion of cross-scale hybrid features via an adaptive weight allocation strategy. Moreover, a quadratic mixed-convolutional pooling module is developed to further strengthen the discriminative representation of fault-related features through in-depth refinement. To enhance model interpretability, a Grad-CAM++ method is employed to identify fault-related regions under noisy conditions. Experimental results validate the effectiveness of the proposed MSHQAN on two public bearing datasets.This work was supported in part by the Shanghai Special Fund for Promoting High Quality Industrial Development Project under grant GYQJ-2023-1-06, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Zonotopic Polynomial Set-Membership Fusion Estimation for Nonlinear Systems via Carleman Approximation: An Encoding-Decoding Scheme
Get PDFIn this paper, the zonotopic set-membership estimation (SME) problem is addressed for a class of nonlinear systems subjected to an encoding-decoding scheme, where the measurement information of each sensor is encoded and then transmitted to the remote fusion center. The objective of this paper is to develop a zonotope-based weighted measurement fusion method to fuse the received decoding signals, and to design a zonotopic SME algorithm that fully utilizes the higher-order partial derivatives of the nonlinear functions based on the fused signal. A zonotope-based weighted measurement fusion (WMF) method is proposed by means of the full rank decomposition technique, which enables the fusion of the decoding signals by solving a weighted least squares problem. To design the desired SME algorithm, the nonlinear system is first transformed into a linear time-varying system using the Carleman approximation technique. Then, based on the fused signal, a Kalman-type estimator is constructed and the zonotopes encompassing the prediction error and the estimation error are recursively calculated. The estimator parameter is obtained by minimizing the F -radius of the zonotope enclosing the estimation error at each time instant. Furthermore, effect of the system smoothness level on the F -radius is intensively analyzed. It is shown that incorporating the higher-order partial derivatives into the design of the SME algorithm enables the extraction of additional state constraints, and that the number of extractable constraints increases monotonically with the smoothness level. A method is subsequently proposed to leverage these constraints in order to improve the estimation accuracy. Moreover, the WMF method is proven to provide an equivalent estimation accuracy as compared to the most commonly used parallel fusion method while possessing lower computational complexity. Finally, two simulation experiments are conducted to demonstrate the efficacy and utility of the SME method.This work was supported in part by the National Natural Science Foundation of China under Grants 62373103, 62403130, and 62573121; in part by the Jiangsu Provincial Scientific Research Center of Applied Mathematics of China under Grant BK20233002; in part by the Natural Science Foundation of Jiangsu Province of China under Grant BK20241286; in part by the Jiangsu Funding Program for Excellent Postdoctoral Talent of China under Grant 2024ZB601; in part by the China Postdoctoral Science Foundation-CCTEG Joint Support Program under Grant 2025T055ZGMK; in part by the Royal Society of the UK; and in part by the Alexander von Humboldt Foundation of Germany
Revisiting Press Freedom in Nigeria: The Buhari Years (2015-2023)
Get PDFSix and half decades after independence, political journalism remains endangered in one of Africa’s largest democracies- Nigeria. The key battle revolved around transparency in public office, its reportage and people’s right to know. This two-pronged study probed press freedom under President Mohammadu Buhari’s watch between 2015 and 2023. Specifically, it examined the political, legal and physical context in which the press operated and explored its consequences, if any, on Nigeria’s democracy. It investigated the power of incumbency against the nuances of a political press. Using the normative theory as its theoretical framework, it adapted Reporters Without Borders’ press freedom indicators for its analysis. Findings reveal an enduring pattern- the political wing of Nigeria’s supposedly liberal, plural and commercial press has become dysfunctional. Its operational context now lies in a highly contested space; shaped by political affiliations, illiberal regulations, state interference and self-censorship. Buhari’s relations with the press reflected his militarist ideology, evoked ethnic tensions; and exposed the impotence of Nigeria’s state agencies. A perilous path lies ahead for press and politics when shackled this way
Search for charged-lepton flavour violation in top quark interactions with an up-type quark, a muon, an d a τ lepton in proton-proton collisions at √s = 13 TeV
Get PDFA version of the article is available at arXiv:2504.08532v2 [hep-ex] (https://doi.org/10.48550/arXiv.2504.08532). Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/TOP-22-011 (CMS Public Pages). Report number: CMS-TOP-22-011, CERN-EP-2025-029. Journal reference: JHEP 12 (2025) 065. Submission history: From: The CMS Collaboration: [v1] Fri, 11 Apr 2025 13:41:47 UTC (2,542 KB); [v2] Wed, 7 Jan 2026 14:34:33 UTC (2,541 KB).A search for charged-lepton flavour violation (CLFV) in top quark (t) production and decay is presented. The search uses proton-proton collision data corresponding to 138 fb collected with the CMS experiment at √s = 13 TeV. The signal consists of the production of a single top quark via a CLFV interaction or top quark pair production followed by a CLFV decay. The analysis selects events containing a hadronically decaying lepton and a muon of opposite electric charge, as well as at least three jets, one of which is identified as originating from the fragmentation of a bottom quark. Machine learning classification techniques are used to distinguish signal from standard model background events. The results of this search are consistent with the standard model expectations. The upper limits at 95% confidence level on the branching fraction B for CLFV top quark decays to a muon, a lepton, and an up or a charm quark are set at B(t → μτu) (0.04, 0.08, and 0.12) 10, and B(t → μτc) (0.81, 1.71, and 2.05) 10 for scalar, vector, and tensor-like operators, respectively.SCOAP3
Simulating Visual Impairments in XR: Toward Virtual Player Models for Inclusive Design
Get PDFConference paper and poster presented at the BCS HCI 2025 Human Centred Approaches and their Impact on AI System Design Application and Evaluation, Cardiff, UK, 9-11 November 2025. Conference theme: Span across 3 days, the conference’s theme of HCI4AI explored topics such as Explainable AI (XAI) and User Trust; Conversational Interfaces and Chatbots; Ethical AI in UX Design; Bias and Fairness in AI-powered UX; Human-Centered AI and Interaction Design; HCI and Healthcare (eHealth, mHealth, assistive tech, telemedicine); Privacy, Security, and Ethical UX and more.This work presents a novel approach to assessing accessibility in Extended Reality (XR) through the
development of Virtual Player Models (VPMs) for simulating visual impairments. Grounded in qualitative
insights from visually impaired users and informed by clinical vision parameters, each VPM encodes visual
perceptual traits and adaptive strategies using a structured, JSON-based approach. These models can
be integrated into XR design workflows to simulate user experiences in real time, supporting early-stage
identification of accessibility barriers. We demonstrate the concept through a prototype VPM schema and
outline its potential for extending accessible design practices in XR development
Durability and Microstructural Evolution of PVA-Fiber-Reinforced Concrete Under Coupled Sulfate Attack and Freeze–Thaw Conditions
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The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.To address the engineering challenge of durability deterioration in concrete structures in the cold and saline regions in northern China, this study investigated PVA fiber-reinforced concrete under combined sulfate attack and freeze–thaw cycles using PVA fiber volume fractions (0%, 0.1%, 0.3%, 0.5%) and salt-freeze cycles (0, 25, 50, 75, 100, 125, 150 cycles) as key variables. By testing the mechanical and microscopic properties of the specimens after salt-freeze, the degradation law of macroscopic performance and the evolution mechanism of microscopic structure of PVA fiber concrete under different volume fractions are analyzed, and the salt-freeze damage evolution equation is established based on the loss rate of relative dynamic elastic modulus. The results show that the addition of PVA fibers has no significant inhibitory effect on the surface erosion of concrete, and the degree of surface spalling of concrete still increases with the increase in the number of salt-freeze cycles. With the increase in the number of salt-freezing cycles, the mass, relative dynamic elastic modulus and cube compressive strength of the specimens first increase and then decrease, while the splitting tensile strength continuously decreases. The volume fraction of 0.3% PVA fibers has the most significant effect on improving the cube compressive strength and splitting tensile strength of concrete, and at the same time, it allows concrete to reach its best salt-freezing resistance. PVA fibers contribute to a denser microstructure, inhibit the development of micro-cracks, delay the formation of erosion products, and enhance the salt-freezing resistance of concrete. The damage degree D of relative dynamic elastic modulus for PVA fiber concrete exhibits a cubic functional relationship with the number of salt-freeze cycles N, and the correlation coefficient R2 is greater than 0.88. The equation can accurately describe the damage and deterioration law of PVA fiber concrete in the salt-freeze coupling environment. In contrast to numerous studies on single-factor exposures, this work provides new insights into the degradation mechanisms and optimal fiber dose for PVA fiber concrete under the synergistic effect of combined sulfate and freeze-thaw attacks, a critical scenario for infrastructure in cold saline regions. This study can provide theoretical guidance for the durability assessment and engineering application of PVA fiber concrete in cold and saline regions.This research was supported by Henan Science and Technology Research Project, grant number 252102320092 and Henan Natural Science Foundation, grant number 232300420107
The performance, health and development of youth women's footballers: A systematic scoping review
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The authors confirm that the data supporting the findings of this study are available within its supplementary materials.Supplementary Material is available online at: https://journals.sagepub.com/doi/10.1177/17479541251411068#supplementary-materials .The primary aim of this scoping review was to summarise the current scientific literature on the performance, health and development of youth women's footballers. The review provides a summary of the research topics, including methodological approaches adopted and key findings, and identifies gaps in the literature. A systematic search of electronic databases was conducted in December 2023 and June 2025, with keywords relating to the population, football, and performance, health and development. Studies which involved youth women's footballers playing at any competitive standard, and quantified at least one aspect of performance, health or development were included. Of the 16,473 studies identified in the database searches, 294 studies met the eligibility criteria to be included in the review. Of the eight research topics investigating the performance, health and development of youth women's footballers, physical qualities was the most investigated ( n = 119; 40%), followed by injury ( n = 49; 17%), biomechanics ( n = 40; 14%), psychology ( n = 31; 11%), match-play ( n = 20; 7%), nutrition ( n = 14; 5%), fatigue and recovery ( n = 13; 4%) and training load ( n = 8; 3%). Players competing in regional (42%) and national competitions (32%), and within an U17 age-group (23%) were the most investigated. Over half of all studies (56%) were published from 2020 onwards, demonstrating recent rapid growth in youth women's football literature. This comprehensive resource can be used to inform practices supporting the performance, health and development of youth women's footballers across various competitive standards. Furthermore, multiple research areas are highlighted as underdeveloped, and areas for future research concerning this population to explore.The authors received no financial support for the research, authorship, and/or publication of this article
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