bluuebunny/crossref_metadata_2025 huggingface dataset:
CRISPR/Cas9-mediated germline mutagenesis in the subsocial parasitoid wasp,Sclerodermus guani
Authors: Ye Zi , Fan Guanzhen , Wei Yun , Li Li , Liu Feng
Published: January 2025

The ectoparasitoid waspSclerodermus guani(Hymenoptera: Bethylidae), as a subsocial insect, is widely applied in biological control against beetle vectors of pine wood nematodes. Despite significant advances in behavioral research, functional genetics inS. guaniremains underdeveloped due to the absence of efficient gene manipulation tools. In this study, we employed CRISPR-mediated mutagenesis to achieve germline gene knockout targeting the eye pigment associated genekynurenine 3-monooxygenase(KMO). Phylogenetic analysis revealed thatS. guaniKMO shares a close relationship with its homolog inProrops nasuta(Hymenoptera: Bethylidae). Two single-guide RNAs (sgRNAs), coupled with Cas9 protein with and without nuclear localization signal (NLS) were tested. Both sgRNAs induced specificin vitroDNA cleavage andin vivoheritable indels at the target genomic loci. Homozygous null mutant females and males exhibit a white-eye phenotype, which was identified during pupal stage. Optimal editing efficiencyin vivowas achieved using the Cas9-NLS variant. Given the complication of germline gene editing in eusocial Hymenopterans, the application of CRISPR in the subsocial parasitoid waspS. guaniprovides an accessible research platform for the molecular evolution of insect sociality.
Identifying Opportunities for Fluid Balance Optimization in Critically Ill Children
Authors: Hasson Denise , Shah Ami , Braun Chloe G. , Kothari Ulka , Drury Steve , Dapul Heda , Fitzgerald Julie C. , Dixon Celeste , Barbera Andrew , Odum James , Terry Nina , Weiss Scott L. , Martin Susan D. , Dziorny Adam C.
Published: January 2025

Introduction

Fluid overload (FO), a state of pathologic positive cumulative fluid balance (CFB), is common in Pediatric Intensive Care Units (PICU) and associated with morbidity and mortality. Because different PICUs may have unique needs, barriers, and limitations to accurately report fluid balance (FB) and reduce FO, understanding the drivers of positive FB is needed. We hypothesize CFB >5% and >10% is common within initial days of PICU admission, but that reasons for high %CFB will vary across sites, as will barriers to accurate FB recording and opportunities to improve FB recording and management.

Methods

Concurrent mixed methods study utilizing a retrospective observational cohort design and prospective interview and survey design performed at four tertiary pediatric ICUs. FB data was extracted from the electronic health record. A federated data collection framework allowed for rapid data aggregation. The primary outcome was %CFB on PICU days 1 and 2, defined as total intake minus total output divided by PICU admission weight. Chi-square test and Wilcoxon rank sum tests compared results across and within sites.

Results

Amongst 3,071 PICU encounters, day 2 CFB >5% varied from 39% to 54% (p=0.03) and day 2 CFB >10% varied from 16% to 25% (p=0.04) across sites. Urine occurrence recordings and patients receiving >100% Holliday-Segar fluids on Day 1 differed across sites (p<0.001). Sites discussed overall FB and specific FB goals on rounds with differing frequency (42-73% and 19-39%, respectively), but they reported similar barriers to accurate FB reporting and achievable opportunities to improve FB measurements.

Conclusion

Day 2 CFB >5% and >10% was common among PICU encounters but proportion of patients varied significantly across PICUs. Individual ICUs have different drivers of FO that must be targeted to improve FB management.
Longitudinal associations between childhood socioeconomic position and adolescent eating disorder symptoms: findings from the ALSPAC cohort
Authors: Hahn Jane S. , Flouri Eirini , Harrison Amy , Lewis Glyn , Solmi Francesca
Published: January 2025

Background

The recorded incidence of eating disorders is elevated in people from higher socioeconomic positions, but self-reported eating disorder symptoms are more common in those from lower socioeconomic positions in cross-sectional studies. Longitudinal studies investigating the role of different socioeconomic indicators in the aetiology of a range of eating disorder symptoms might avoid biases associated with the use of clinical samples but have multiple limitations. We aimed to investigate the association between early childhood socioeconomic indicators and eating disorder symptoms across adolescence.

Method

We used data from the Avon Longitudinal Study of Parents and Children. Parental income, education, occupation, and financial hardship were reported by mothers between 32 weeks of gestation and 47 months postpartum. Area-level deprivation was derived from the Office for National Statistics indicators linked to the participant’s residential post code at 32 weeks gestation. Outcomes were disordered eating (restrictive eating, binge eating, and purging), weight and shape concerns, and body dissatisfaction at age 14, 16, and 18 years. To model these associations, we used univariable and multivariable multilevel logistic and linear regression, and linear regression models.

Findings

The sample included 7,824 participants (48.9% females; 3.8% minoritised ethnic background). Greater financial hardship was associated with increased odds of disordered eating (Odds Ratio= 1·06, 95%CI 1·04 to 1·10) and greater weight and shape concerns (Mean difference[MD] = 0·02, 95%CI 0·01 to 0·04) and body dissatisfaction (MD= 0·22 95%CI 0·06 to 0·37). Lower parental education was associated with 1.80 higher odds of disordered eating (95% CI 1·46 to 2·23).

Interpretation

Our findings point to potential socioeconomic inequalities in eating disorder identification in clinical settings, which need to be understood and addressed. Reducing population-level socioeconomic inequalities could also aid eating disorder prevention.

Funding source

Mental Health Research UK, Wellcome Trust, UK Medical Research Council
COVID-19 Vaccine Uptake and its Determinants in Cameroon: A Systematic Review and Meta-analysis
Authors: Cheuyem Fabrice Zobel Lekeumo , Amani Adidja , Achangwa Chabeja , Ajong Brian Ngongheh , Minkandi Claude Axel , Zeh Myriam Mathilde Mbia Kouda , Ntsek Larissa Linda Eyenga , Essomba Jacques Philippes , Jiogue Rudy Chiozem , Ndagijimana Olivier , Nchanji Ndzi Etienne , Danwang Celestin
Published: January 2025

Background

COVID-19 vaccination is crucial for mitigating the pandemic’s impact. However, vaccine hesitancy and access challenges have hindered global vaccination efforts. This meta-analysis aimed to estimate the pooled COVID-19 vaccine uptake proportion and identify associated determinants in Cameroon.

Methods

This review, conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, identified articles through searches of electronic databases, including PubMed, Scopus, Web of Science, ScienceDirect, and Google Scholar, as well as through gray literature. The search encompassed published and unpublished studies from 2021 to 2024 reporting on COVID-19 vaccine uptake and/or acceptance in Cameroon. Extracted data were compiled in a Microsoft Excel spreadsheet and analyzed using R statistical software (version 4.4.2). A random-effects model was employed when heterogeneity exceeded 50%. Publication bias was assessed using funnel plots, Egger’s test, and Begg’s test. Meta-regression was used to explore the influence of study characteristics.

Results

Twenty-two studies, encompassing 24,130 participants, were included. The pooled vaccine uptake proportion was 37.14% (95% CI: 29.24-45.05), with substantial heterogeneity (I² = 98.2%,p<0.001). Subgroup analyses revealed lower uptake among the general population (23.18%; 95% CI: 10.11-36.25) and in community settings (16.0%; 95% CI: 0.97-31.04) compared with healthcare workers (42.12%; 95% CI: 34.14-50.09). Younger age (OR = 0.53; 95% CI: 0.42-0.67) was inversely associated with vaccine uptake, while being in a partnership (OR = 1.59; 95% CI: 1.11-2.27) was positively associated. Higher levels of education (OR = 1.75; 95% CI: 1.56-1.97), urban residence (OR = 1.66; 95% CI: 1.21-2.29).

Conclusion

This meta-analysis revealed a suboptimal pooled COVID-19 vaccine uptake required to ensure a herd immunity. The results of this meta-analysis underline the crucial need to step up efforts to improve vaccination coverage, particularly among the most vulnerable populations. Identifying and addressing the factors underlying this low coverage is imperative if public health objectives are to be met. Public health interventions should be tailored to address the specific concerns and needs of different age groups and marital statuses.
Temporal Dynamics of Microbial Communities in Anaerobic Digestion: Influence of Temperature and Feedstock Composition on Reactor Performance and Stability
Authors: Piercy Ellen , Sun Xinyang , Ellis Peter R. , Taylor Mark , Guo Miao
Published: January 2025

Anaerobic digestion (AD) offers a sustainable biotechnology to recover resources from carbon- and nutrient-rich wastewater streams, such as food-processing wastewater. Despite the wide adoption of crude wastewater characterisation, the impact of detailed chemical fingerprinting on AD remains underexplored. This study investigated the influence of fermentation-wastewater composition and operational parameters on AD over time to identify critical parameters influencing microbiome diversity and reactor performance. Eighteen bioreactors were operated under various operational conditions using mycoprotein fermentation wastewater. Detailed chemical analysis fingerprinted the molecules in the fermentation-wastewater throughout the AD process including sugars, sugar alcohols and volatile fatty acids (VFAs). High-throughput sequencing revealed distinct microbiome profiles linked to temperature and reactor configuration, with mesophilic conditions supporting a more diverse and densely connected microbiome. Importantly, significant elevations inMethanomassiliicoccuswere correlated to high butyric acid concentrations and decreased biogas production, further elucidating the role of this newly discovered methanogen in AD. Reactors from different experimental runs had distinct VFA profiles, which impacted microbial taxonomy and diversity. Dissimilarity analysis demonstrated the importance of individual VFAs, sugars and sugar alcohols on microbiome diversity, highlighting the need for detailed chemical fingerprinting in AD studies of microbial trends. Furthermore, machine learning models predicting reactor performance achieved high accuracy based on operational parameters and microbial taxonomy. Operational parameters were found to have the most substantial influence on chemical oxygen demand removal, whilstOscillibacterand twoClostridiumspecies were highlighted as key factors in biogas production. By integrating detailed chemical and biological fingerprinting with explainable machine learning models this research presents a novel approach to advance our understanding of AD microbial ecology, offering insights for industrial applications of sustainable waste-to-energy systems.
Nanopore-based consensus sequencing enables accurate multimodal tumor cell-free DNA profiling
Authors: Chen Li-Ting , Jager Myrthe , Rebergen Dàmi , Brink Geertruid J. , van den Ende Tom , Vanderlinden Willem , Kolbeck Pauline , Pagès-Gallego Marc , van der Pol Ymke , Besselink Nicolle , Moldovan Norbert , Hami Nizar , Kloosterman Wigard P. , van Laarhoven Hanneke , Mouliere Florent , Zweemer Ronald , Lipfert Jan , Derks Sarah , Marcozzi Alessio , de Ridder Jeroen
Published: January 2025

Shallow genome-wide cell-free DNA (cfDNA) sequencing holds great promise for non-invasive cancer monitoring by providing reliable copy number alteration (CNA) and fragmentomic profiles. Single nucleotide variations (SNVs) are, however, much harder to identify with low sequencing depth due to sequencing errors. Here we present Nanopore Rolling Circle Amplification (RCA)-enhanced Consensus Sequencing (NanoRCS), which leverages RCA and consensus calling based on genome-wide long-read nanopore sequencing to enable simultaneous multimodal tumor fraction estimation through SNVs, CNAs, and fragmentomics. Efficacy of NanoRCS is tested on 18 cancer patient samples and seven healthy controls, demonstrating its ability to reliably detect tumor fractions as low as 0.24%. In vitro experiments confirm that SNV measurements are essential for detecting tumor fractions below 3%. NanoRCS provides the opportunity for cost-effective and rapid processing, which aligns well with clinical needs, particularly in settings where quick and accurate cancer monitoring is essential for personalized treatment strategies.
Mixing angle of
K1(1270/1400)
and the
KK¯1(1400)
molecular interpretation of
η1(1855)
Authors: Liu Zheng-Shu , Chen Xu-Liang , Lian Ding-Kun , Li Ning , Chen Wei
Published: January 2025

Owing to the SU(3) symmetry breaking effect, the axial-vector kaons K1(1270) and K1(1400) are established to be mixtures of two P-wave K1A(P31) and K1B(P11) states. In QCD sum rules, we propose a new construction of the K1 current operators and calculate the two-point correlation functions by including the next-to-leading order four-quark condensates. The mixing angle is determined as θ=(46.95−0.23+0.25)° by reproducing the masses of K1(1270) and K1(1400). We further compose the KK¯1(1270) and KK¯1(1400) interpolating currents with exotic quantum numbers JPC=1−+ to investigate the possible molecular interpretation of the recently observed η1(1855) state. We calculate the correlation functions and perform the QCD sum rule analyses for these two molecular systems. However, the spectral functions are found to be negative in physical regions so that they are not able to provide reliable investigations of the KK¯1 molecular states.

Published by the American Physical Society
2025
Gauss relations in Feynman integrals
Authors: Feng Tai-Fu , Zhou Yang , Zhang Hai-Bin
Published: January 2025

Embedding Feynman integrals in Grassmannians, we can write Feynman integrals as some finite linear combinations of generalized hypergeometric functions. In this paper, we present a general method to obtain Gauss relations among those generalized hypergeometric functions. The hypergeometric expressions of Feynman integral are continued from a connected component to another by the inverse Gauss relations, then continued to the whole domain of definition by the Gauss-Kummer relations. The Laurent series of the Feynman integral around the space-time dimension D=4 is obtained by the Gauss adjacent relations, where the coefficient of the term with power of D−4 is given as the linear combinations of hypergeometric functions with integer parameters. As examples, we illustrate how to obtain the expressions for the Feynman integrals of the 1-loop self-energy and a 2-loop massless triangle diagram in the domains of definition.

Published by the American Physical Society
2025
Decoherence of quantum superpositions by Reissner-Nordström black holes
Authors: Li Ran
Published: January 2025

Recently, it was shown by Danielson (DSW) that, for the massive or charged body in a quantum spatial separated superposition state, the presence of a black hole can decohere the superposition inevitably toward capturing the radiation of soft photons or gravitons [D. L. Danielson , Black holes decohere quantum superpositions, ; D. L. Danielson , Killing horizons decohere quantum superpositions, ; D. L. Danielson , Local description of decoherence of quantum superpositions by black holes and other bodies, ]. In this work, we study the DSW decoherence effect for the static charged body in the Reissner-Nordström black holes. By calculating the decohering rate for this case, it is shown that the superposition is decohered by the low-frequency photons that propagate through the black hole horizon. For the extremal Reissner-Nordström black hole, the decoherence of quantum superposition is completely suppressed due to the black hole Meissner effect. It is also found that the decoherence effect caused by the Reissner-Nordström black hole is equivalent to that of an ordinary matter system with the same size and charge.

Published by the American Physical Society
2025
Probing entanglement dynamics and topological transitions on noisy intermediate-scale quantum computers
Authors: Chang Huai-Chun , Hsu Hsiu-Chuan , Lin Yu-Cheng
Published: January 2025

We simulate quench dynamics of the Su-Schrieffer-Heeger (SSH) chain on IBM quantum computers, calculating the Rényi entanglement entropy, the twist order parameter, and the Berry phase. The latter two quantities can be deduced from a slow-twist operator defined in the Lieb-Schultz-Mattis theorem. The Rényi entropy is obtained using a recently developed randomized measurement scheme. The twist order parameter and the Berry phase are measured without the need for additional gates or ancilla qubits. We consider quench protocols in which a trivial initial state evolves dynamically in time under the topological SSH Hamiltonian in the fully dimerized limit (the flat-band limit). During these quenches, there are persistent and periodic oscillations in the time evolution of both entanglement entropy and twist order parameter. Through the implementation of error mitigation techniques using a global depolarizing ansatz and postselection, our simulations on the IBM devices yield results that closely match exact solutions.

Published by the American Physical Society
2025
Measuring the angular momentum of a neutron using Earth's rotation
Authors: Geerits Niels , Sponar Stephan , Steffen Kyle E. , Snow William M. , Parnell Steven R. , Mauri Giacomo , Smith Gregory N. , Dalgliesh Robert M. , de Haan Victor
Published: January 2025

A coupling between Earth's rotation and orbital angular momentum (OAM), known as the Sagnac effect, is observed in entangled neutrons produced using a spin-echo interferometer. After correction for instrument systematics the measured coupling is within 5% of theory, with an uncertainty of 7.2%. The OAM in our setup is transverse to the propagation direction and scales linearly with neutron wavelength (4–12.75 Å), so the Sagnac coupling can be varied without mechanically rotating the device, which avoids systematic errors present in previous experiments. The detected transverse OAM of our beam corresponds to 4098±295ℏÅ−1,105 times lower than in the previous neutron experiments. This demonstrates the feasibility of using the Sagnac effect to definitively measure neutron OAM and paves the way towards a future observation of the quantum Sagnac effect.

Published by the American Physical Society
2025
Systematic analysis of an attosecond pulse generation by a subcycle laser field
Authors: Rajpoot Rambabu , Takahashi Eiji J.
Published: January 2025

We investigated the influence of subcycle driving fields on high-order harmonic generation (HHG), with a focus on driver's intrinsic chirp, carrier-envelope phase (CEP), and number of laser cycles. Our findings reveal that the center frequency of a laser pulse scales as τ−5/4 with pulse duration τ, and that attochirp exhibits a similar dependence on pulse duration. Additionally, we identified CEP-specific trends in harmonic yield: it increases as τ5/4 for ϕ0=0∘ and decreases as τ−4.1 for ϕ0=−90∘. Although subcycle pulses can generate intense isolated attosecond pulses (IAPs), they also tend to produce higher attochirp and reduced cutoff energies. However, effective compensation for attochirp can mitigate these drawbacks, thereby increasing the capability of subcycle pulses to generate short-duration, high-intensity IAPs. These results offer valuable insights into HHG using subcycle pulses and have important implications for the advancement of ultrafast light sources and the understanding of ultrafast phenomena at the attosecond timescale.

Published by the American Physical Society
2025
Pb164
: A possible heaviest
N=Z
doubly magic nucleus
Authors: Naito Tomoya , Kimura Masaaki , Sasano Masaki
Published: January 2025

We confirm by using the Skyrme Hartree-Fock-Bogoliubov calculation that Pb164 is a possible heaviest N=Z doubly magic nucleus whose lifetime is long enough to be measured on accelerator experiments. We estimate the proton-emission and alpha-decay half-lives of Pb164. The estimated proton-emission half-life ranges from 0.1ps to 10ns, while the alpha decay can be safely neglected.

Published by the American Physical Society
2025
Blueprint for All-to-All-Connected Superconducting Spin Qubits
Authors: Pita-Vidal Marta , Wesdorp Jaap J. , Andersen Christian Kraglund
Published: January 2025

Andreev (or superconducting) spin qubits (ASQs) have recently emerged as a promising qubit platform that combines superconducting circuits with semiconductor spin degrees of freedom. While recent experiments have successfully coupled two ASQs, how to realize a scalable architecture for extending this coupling to multiple distant qubits remains an open question. In this work, we resolve this challenge by introducing an architecture that achieves all-to-all connectivity between multiple remote ASQs. Our approach enables selective connectivity between any qubit pair while keeping all other qubit pairs uncoupled. Furthermore, we demonstrate the feasibility of efficient readout using circuit quantum electrodynamics techniques and compare different readout configurations. Our architecture shows promise both for gate-based quantum computing and for analog quantum simulation applications by offering higher qubit connectivity than alternative solid-state platforms.

Published by the American Physical Society
2025
Study on corrosion monitoring and assessment method of reinforced concrete based on multi-sensor fusion
Authors: Lin Xumei , Wang Peng , Wang Shiyuan , Shen Jiahui
Published: January 2025

Purpose

The purpose of this paper is to investigate the accurate monitoring and assessment of steel bar corrosion in concrete based on deep learning multi-sensor information fusion method. The paper addresses the issue of traditional corrosion assessment models relying on sufficient data volume and low evaluation accuracy under small sample conditions.

Design/methodology/approach

A multi-sensor integrated corrosion monitoring equipment for reinforced concrete is designed to detect corrosion parameters such as corrosion potential, current, impedance, electromagnetic signal and steel bar stress, as well as environmental parameters such as internal temperature, humidity and chloride ion concentration of concrete. To overcome the small amount of monitoring data and improve the accuracy of evaluation, an improved Siamese neural network based on the attention mechanism and multi-loss fusion function is proposed to establish a corrosion evaluation model suitable for small sample data.

Findings

The corrosion assessment model has an accuracy of 98.41%, which is 20% more accurate than traditional models.

Practical implications

Timely maintenance of buildings according to corrosion evaluation results can improve maintenance efficiency and reduce maintenance costs, which is of great significance to ensure structural safety.

Originality/value

The corrosion monitoring equipment for reinforced concrete designed in this paper can realize the whole process of monitoring inside the concrete. The proposed corrosion evaluation model for reinforced concrete based on Siamese neural network has high accuracy and can provide a more accurate assessment model for structural health testing.
Gain scheduling of backstepping sliding mode controller using optimized type-1 Sugeno fuzzy logic approach for quadcopter
Authors: Sharma Arpit , Lather Jagdeep Singh
Published: January 2025

Purpose

This paper aims to propose an optimized type-1 Sugeno fuzzy logic backstepping sliding mode controller (T1-SFL-BSMC) to control the altitude and rotational behaviour of a quadcopter. The proposed controller improves the performance of the system by overcoming the limitations of conventional trial-and-error techniques for BSMC gain design.

Design/methodology/approach

In this study, the type-1 Sugeno fuzzy logic controller (T1-SFLC) technique is proposed which dynamically modifies the BSMC gains. In addition, the parameters of T1-SFLC are further tuned by five different optimization techniques, namely, genetic algorithm, particle swarm optimization (PSO), pattern search (PS), simulated annealing (SA) and adaptive neural network (ANN).

Findings

The effectiveness of these optimization techniques in tuning the T1-SFLCs for the gain scheduled BSMC is evaluated in terms of time response metrics; rising time, settling time and root mean square error (RMSE) for altitude and rotational behaviour. The results demonstrated that PSO-optimized T1-SFL-BSMC provides better responses in terms of time response metrices with reduced rise and settling times and minimized RMSE when compared to other optimized T1-SFL-BSMC.

Originality/value

This paper proposes a novel approach for controlling quadcopters by combining fuzzy logic with a BSMC. It is then improved by using many optimization strategies. A more dependable and effective approach to controller design is provided by the suggested method, which is essential for unmanned aerial vehicle applications.
“Hey librarian, what can AI and analytics do for you”: a systematic literature review and sociotechnical perspective
Authors: Bawack Ransome , Bawack Roseline
Published: January 2025

Purpose

This study aims to provide an in-depth overview of current research on artificial intelligence (AI) and analytics applications in library operations, emphasizing their adoption’s technical and social implications.

Design/methodology/approach

The study follows the PRISMA guidelines to synthesize existing research on AI and analytics in academic libraries. This review uses sociotechnical systems (STS) theory as a framework to evaluate the technical aspects and social dynamics involved in integrating these technologies.

Findings

The findings indicate that AI and analytics can significantly enhance library resource management, decision-making and user services. However, ethical, social and technical challenges, including staff training and collaboration, must be addressed to ensure responsible implementation.

Originality/value

This study provides the first STS-informed analysis focusing on applying AI and analytics within academic library operations. It offers actionable insights into these technologies’ unique applications and potential, bridging a gap in the literature on library-specific operational management.
Promoting health behavioral intention through short videos: roles of audiovisual cross-modal correspondence in health communication
Authors: Xu Yanrun , Jiang Tingting , Hu Xiao , Tian Huiyi
Published: January 2025

Purpose

Health short videos are serving as a powerful tool for encouraging individuals to actively adopt healthier behaviors. The sensory cues applied in these videos can be useful for engaging peripheral processing and enhancing attitudes. While previous research has examined the effects of various single cues, this study features a pioneering attempt to explore the roles of audiovisual cross-modal correspondence, encompassing multisensory cues perceived through different modalities, in health communication.

Design/methodology/approach

A 2 (color: warm/cool) × 2 (music tempo: fast/slow) between-subjects experiment was conducted to observe 120 participants’ responses to a health short video promoting eye health that was created using four different combinations of background color and background music tempo.

Findings

It was found that the congruent color–tempo pairings, that is blue & slow and orange & fast, led to more positive attitudes toward the videos than the incongruent pairings, that is blue & fast and orange & slow. The effect of cross-modal correspondence on attitude was fully mediated by processing fluency, with gender acting as a moderator between the two variables. Furthermore, individuals’ attitudes toward a short video positively influenced their health behavioral intentions.

Originality/value

These findings not only lend support to the theoretical framework of “multisensory cues-fluency-attitude-intention” chain for persuasion purposes but also have practical implications for creating effective health short videos.
Implementing the what I need (WIN) plan in a community forensic intellectual disability team
Authors: Clarke Sadie , Smith Andy , Chester Verity , Patteril Elizabeth , Alexander Regi
Published: January 2025

Purpose

Government policy in the UK is emphasising a shift from inpatient to community-based management of those with intellectual disabilities and forensic needs. However, community services can be reluctant to accept patients deemed ready for discharge by inpatient forensic teams, and this leading to delayed discharges. An evidence-based discharge communication tool based on a comprehensive needs assessment is therefore required for patients with intellectual disabilities and forensic needs.

Design/methodology/approach

The purpose of this paper is to describe the development and implementation of the What I Need (WIN) plan in a Community Forensic Intellectual Disability Team. The WIN plan aims to create an effective discharge communication tool through carrying out a needs assessment based on the Camberwell Assessment of Need – Forensic Version (CANFOR).

Findings

The team and its stakeholders have observed several benefits following implementation of the WIN plan. The WIN is patient led and generates constructive dialogue around needs, risks and strengths between the patient, their family/carers and staff/clinicians. It is multidisciplinary, efficient to complete and collates information on individual patients’ current and historical forensic risks and needs in one document.

Originality/value

While delays in discharging in this population have been extensively studied, communication tools to support the process of discharge have received less focus. This paper describes the development and implementation of a discharge communication tool that incorporates risk management strategies for patients with intellectual disabilities and forensic needs.
How short video platforms retain customers: focusing on the roles of user stickiness and flow experience
Authors: Jia Yanglei , Zheng Keke , Liu Xinglong , Guo Xiang
Published: January 2025

Purpose

The highly competitive atmosphere of the short video platforms has increased their similarity, while users possess remarkably diverse preferences, complicating the improvement of user stickiness. To address this issue, this research investigates the effects of different factors, including perceived usefulness, ease, enjoyment, interactivity, and social influence, on user stickiness.

Design/methodology/approach

To estimate these effects, it employs partial least square-structural equation modeling (PLS-SEM), technology acceptance model (TAM3) and theory of planned behavior (TPB) to analyze data collected from a questionnaire distributed among online users between July 20, 2023 and October 28, 2023.

Findings

The results indicate that all the studied factors have positive and significant effects on user stickiness. In addition, they confirmed the considerable effect of flow experience on the relationships between these factors and user stickiness, particularly in interactivity.

Originality/value

These findings show the short video platforms how to manage different factors effectively in stickiness to increase their uniqueness among competitors, attracting and keeping different users by covering their diverse preferences.
The impact of platform affordance on the representation of iconic architecture: a case study of Markthal across visual social media
Authors: Zhang Shuyu , Zhang Gong
Published: January 2025

Purpose

This paper explores how platforms shape the representation of iconic architecture across visual social media platforms, particularly how their unique features and affordances impact these representations.

Design/methodology/approach

This paper develops an integrated framework connecting iconic architecture representation, platform affordance and triadic spatial theory. Taking Rotterdam’s Markthal as a case study and collecting multimodal data from TikTok, Instagram and Google Maps, the paper uses a mixed-methods approach that integrates content analysis with qualitative coding and quantitative image/video label detection and image clustering.

Findings

TikTok is more associated with enriching lived space by enabling users to share vibrant, personal experiences and activities. Instagram influences perceived space more by shaping how users view and experience the physical environment through curated visual content. Meanwhile, Google Maps effectively shapes conceived and perceived space by users’ feedback of place ratings and reviews.

Research limitations/implications

Understanding how platform affordances influence the representation of iconic architecture helps designers and researchers generate design strategies and guides marketers in strategically selecting effective social media platforms for architecture promotion.

Originality/value

This research addresses the gap in understanding the impact of platform affordances on social media representations, especially through comparisons across multiple visual social media platforms. Its novel contribution is introducing the concept of affordance from media studies to architecture and urban studies while enhancing traditional text analysis with computational methods for analysing videos and images.
Dine with me, not your smartphone! Negative impacts of companion phubbing on dining experience satisfaction
Authors: Kikumori Mai , Ishii Ryuta
Published: January 2025

Purpose

Prior research indicates that phubbing – ignoring others and focusing on one’s smartphone – in romance-, work- and education-related situations can seriously damage interpersonal relationships. Despite the fact that phubbing during dining occurs often, prior research has not focused on this behavior. In a situation of hedonic consumption such as restaurant dining, affects such as emotion and mood play an important role in determining consumption satisfaction and consumer behavior. Accordingly, this study aims to examine the impact of phubbing during dining on consumer satisfaction with their dining experience. It also identifies the psychological mechanisms underlying this effect, highlighting the mediating role of affect.

Design/methodology/approach

Survey data were collected from 740 Japanese consumers and structural equation modeling was performed to test the hypotheses.

Findings

The results show that phubbing during dining negatively impacts consumers’ dining experiences; the effect is mediated by social exclusion and mood, and mood in particular is a strong mediator.

Originality/value

This study contributes to better understanding of consumer behavior by indicating the harmful effect of phubbing on service outcomes and clarifying the psychological mechanisms underlying phubbing during dining.
Customer experience and sustainability in social, environmental and economic contexts
Authors: Saini Shivani
Published: January 2025

Purpose

The purpose of this paper is to introduce a new conceptual framework that integrates customer experience and sustainability across social, environmental and economic dimensions to facilitate sustainable development.

Design/methodology/approach

Sustainability is widely recognized from an industrial perspective; however, the relationship between customer experience and sustainability has been limitedly explored in the existing literature. An ethnographic study of two international retail chains has been undertaken, using illustrative case studies to assess the companies’ sustainability practices across social, environmental and economic dimensions.

Findings

This research emphasizes the importance of enhancing customer experiences to align sustainable practices with consumer expectations. The findings of this study indicate that social sustainability should be prioritized in consumer lives by maintaining high-quality living standards, while environmental sustainability should focus on creating experiences that encourage sustainable lifestyle choices. Economic sustainability should be operationalized by concentrating on mutually beneficial performance areas. Overall, companies must adopt a holistic approach that integrates the social, environmental and economic dimensions into sustainability practices to drive positive customer experiences.

Originality/value

This study examines the sustainability performance of retail companies across social, environmental and economic dimensions. This study introduces a novel approach to sustainable development through the customer experience perspective.
Exploring the effectiveness of AI-generated learning materials in facilitating active learning strategies and knowledge retention in higher education
Authors: Aluko Henry Adeyemi , Aluko Ayodele , Offiah Goodness Amaka , Ogunjimi Funke , Aluko Akinseye Olatokunbo , Alalade Funmi Margareth , Ogeze Ukeje Ikechukwu , Nwani Chinyere Happiness
Published: January 2025

Purpose

This study aims to explore the intersection of AI-generated learning materials and active learning strategies in higher education artificial intelligence (AI) is bringing about changes and opening up new possibilities for an improved and more efficient higher education. However, the argument is that its use in education/classroom should be informed by verifiable evidence as well as best practice, which this scholarly work helps build evidence-based research to assess this technology in higher education.

Design/methodology/approach

Primary data was collected through structured questionnaire administered online via Google form. Based on the non-probability sampling technique, 300 higher education tutors and students across the UK were purposively targeted, out of which 218 (72.7%) response rate was achieved. Data was analyzed using descriptive statistics with the aid of Statistical Package for Social Sciences, whereby regression, correlation and Chi-square tests were conducted to determine the statistical significance, direction and strength of the relationship between the measured variables.

Findings

This study revealed that AI-generated learning materials support active learning strategies that enable students to actively engage in their learning, likewise enabling students to develop deeper understanding of their course content with significantly better knowledge retention, which is critical to the learning process. However, findings further revealed that acceptance/regular use of AI-generated learning materials is still below par across the higher education institutions, and there is major concern that the benefits may not be fully realized due to barriers to adoption.

Research limitations/implications

There are limitations that future studies can improve on, especially in terms of methodology. Pragmatism is a philosophical research stance that integrates quantitative data collection with qualitative data (such as interviews) and will ask in-depth questions to gain holistic quality data for such empirical. Future studies can also improve on the research scope to allow for generalizability of findings and check for potential biases in the data collection, analysis and interpretation processes.

Originality/value

Despite the huge anticipation regarding how AI technology could transform teachers’ roles in higher education, concrete research into AI-generated learning materials and actual impact in facilitating active learning strategies and knowledge retention is currently lacking. This study presents theoretical models on AI acceptance in higher education and explored the Technology, Pedagogical and Content Knowledge framework to inform empirical information on how AI can support active learning strategies and students’ knowledge retention.
Innovators and transformers: envisioning a revolution in middle mile logistics with extended range cargo drones
Authors: Purtell Clinton T. , Manuj Ila , Pohlen Terrance L. , Garg Vipul , Porchia Jamie , Hill Michael James
Published: January 2025

Purpose

This paper investigates the integration of middle mile drones (MMD) into logistics operations, addressing two key questions: (1) What are the drivers, financial implications and upcoming innovations associated with integrating drones into MM logistics? and (2) What challenges need to be overcome for successful implementation of drones in MM logistics?

Design/methodology/approach

The study combines expertise from an industry professional with over ten years of experience in drone operations and logistics applications, along with insights gained from discussions with 33 industry executives.

Findings

The research identifies several unique advantages of integrating drones into MM logistics, including their potential to improve operational efficiency in challenging environments. However, significant challenges related to scalability, evolving airframe designs and operational constraints remain. Early-stage use cases demonstrate the viability of MMD technologies in lower-risk logistics environments, but broader implementation requires overcoming the identified challenges.

Research limitations/implications

As MMD logistics is a nascent field, the study is exploratory and based on early-stage use cases and expert discussions. The limited scope of practical implementations may restrict the generalizability of the findings. Future research should focus on larger-scale operations and empirical studies of MMD integration in diverse logistics contexts.

Practical implications

The findings offer valuable insights for practitioners related to the costs, benefits and challenges of integrating drones into logistics operations and for policymakers related to societal implications, workforce development, privacy and safety concerns, and environmental impact.

Originality/value

This paper contributes to the evolving understanding of drone applications in MM logistics by presenting early use cases and identifying both challenges and opportunities for MMD technology and offers a foundation for future research and practice in this emerging domain.
Integrating spatial cognition and SLAM for improved performance of autonomous material handling robots in dynamic stockyard environments
Authors: Li Yuan , Chen Ling , Chen Mengfan , Qian Xuesheng
Published: January 2025

Purpose

The purpose of this study is to detail the design and development of a robust and practical perception system for autonomous material handling robots (AMHRs) operating within industrial stockyards. This system aims to support simultaneous localization and mapping (SLAM) while generating large-scale spatial cognition, ensuring accurate, low-latency, and scalable operations in demanding industrial environments.

Design/methodology/approach

The proposed perception system integrates multimodal perception sensors, efficient algorithms and commercial hardware devices to o provide SLAM-based large-scale spatial cognition for distributed AMHRs. The system’s design emphasizes practicality, efficiency and readiness for real-world deployment, ensuring it meets the stringent requirements of accuracy, latency and scalability.

Findings

Experiments conducted in a real industrial stockyard environment demonstrate the practicality and robustness of the perception system. The system exhibits high performance in state estimation, stockpile modeling accuracy and motion spatial cognition, confirming its effectiveness for AMHR operations.

Practical implications

The developed system was practically used at Tianjin Port, demonstrating the potential for widespread industrial application, offering a scalable and efficient solution for AMHR operations. Its integration into diverse industrial settings can lead to significant improvements in material handling processes, contributing to enhanced productivity and operational efficiency.

Originality/value

This work presents an innovative perception system that combines advanced SLAM-based spatial cognition akin to that of the brain with practical deployment considerations. The system’s design and implementation address the specific challenges of AMHRs in industrial environments, providing a novel solution for enhancing the operational efficiency and adaptability of autonomous robots in stockyards and similar settings.
Research on financial fraud detection by integrating latent semantic features of annual report text with accounting indicators
Authors: Liu Weilong , Wang Zhongguo , Zhang Xv
Published: January 2025

Purpose

This paper aims to integrate the latent semantic features of annual report text with accounting indicators to construct a financial fraud identification model, and quantitatively analyze the impact of different corporate risks on financial fraud behavior in different industries, providing a reference for identifying financial fraud.

Design/methodology/approach

This paper obtains 3,860 corporate annual report samples and accounting indicators from 2001 to 2020 through crawlers and the CSMAR database as our experimental subjects. By integrating latent semantic features with accounting indicators and textual language features, a new indicator system group is constructed. Based on this indicator system group, multiple model identification effects are compared and a stacking-based enterprise financial fraud identification model is constructed. In addition, an econometric model is established to verify the impact of latent semantic features related to enterprises on corporate financial fraud.

Findings

The experimental results show that the constructed stacking-based enterprise financial fraud identification model performs better than other machine learning models and can effectively identify financial fraud. The econometric model established for the latent semantic information of annual reports explains the impact of different corporate trends on fraud behavior in different industries.

Originality/value

This paper combines the textual latent semantic features of annual reports with accounting indicators, expands the scope of data analysis, introduces the idea of ensemble learning, updates the financial fraud identification algorithm and constructs an econometric model for further analysis, providing a reference for financial fraud identification.
Evaluating the influence of digital financial inclusion on financial crises and economic cycles: a Bayesian logistic regression insight
Authors: Le Quoc Dinh , Nguyen Quoc Huy , Nguyen Van Hai
Published: January 2025

Purpose

This paper aims to examine the impact of Digital Financial Inclusion (DFI) on three key economic aspects: banking crises, economic expansion and economic downturns across 93 countries from 2004 to 2017.

Design/methodology/approach

Bayesian Logit regression models provide important insights into how DFI influences these economic factors.

Findings

The findings show that DFI has a modest positive effect on banking crises (coefficients: 0.002–0.027), but rapid growth could increase crisis risks if not regulated. DFI positively impacts economic expansion (coefficients: 0.003–0.012), supporting growth at reasonable levels. For economic downturns, DFI has a negative effect, potentially reducing recession risks, though the impact is small. Regionally, DFI helps mitigate banking crises and downturns in Africa, Latin America and Asia, but in Europe, it slightly increases risks, suggesting potential instability if not properly managed.

Originality/value

The study provides original insights into the nuanced effects of DFI on banking crises, economic expansion and economic downturns across different regions, offering valuable policy recommendations based on these findings.