bluuebunny/crossref_metadata_2025_split huggingface dataset:
Talking Houses: Transforming Touristic Buildings into Intelligent Characters in Augmented Reality
Authors: Kalloori Saikishore , Chalumattu Ribin , Chalet François , Zimper Martin , Klingler Severin , Gross Markus 
Published: January 2023

AbstractAugmented reality (AR) technologies can enhance the user’s experience of visiting attractions, shops, and restaurants by using AR-based virtual elements and additional information about the places they are visiting. In this work, we transform the city landscape or iconic buildings into a unique experience by bringing iconic characters onto the buildings to increase users’ engagement. Our techniques transform buildings or parts of a building into a virtual character with which the user can interact. We designed two unique experiences: (a) ‘The Square’ in which the character will talk about the building’s history and other anecdotes about the area, and (b) ‘The Hunt’ in which the user is involved in a scavenger hunt where they have to identify buildings using the hints given by virtual characters. We have conducted a live user study to assess our prototype’s usability. Our preliminary experimental results demonstrated that our prototype has high usability and users using our system felt a pleasant and enjoyable experience.
Assessing Turnover Intentions of Algorithmically Managed Hospitality Workers
Authors: Segovia-Perez Mónica , Jianu Brana , Tussyadiah Iis 
Published: January 2023

AbstractEmployee turnover has been one of the main concerns facing the hospitality industry. This issue seems to be aggravated in artificial intelligence (AI) environment, where AI implementation is associated with pressure, job alienation, and labor replacement, increasing workers’ desire to quit their job. To analyze the relationship between AI awareness, job alienation, discrimination, and turnover intention, an online survey was distributed to hospitality employees (n = 450). From a series of independent-samples T-tests and regression analyses, this study found employees’ turnover intentions are significantly associated with employees’ concerns of being replaced by AI, perception of job alienation, and workplace discrimination. Importantly, current algorithmically managed workers tend to feel more powerless and discriminated against, and thus have higher turnover intentions. Recommendations for practice and future research are provided.
Older Adults’ Perceptions of Digital Cultural Tourism in ‘Super-Aged’ Nations: The Case of Finland and Japan
Authors: Zainal Abidin Husna , Tuomi Aarni , Moreira Kares Elina 
Published: January 2023

AbstractOlder adults have been recognized as a key tourist segment for cultural tourism. Despite the growing population of older adults, limited research have explored their experiences and needs within digital cultural experiences. Therefore, this research note takes on an exploratory approach in understanding older adults’ perceptions towards digital cultural experiences in the context of two ‘super-aged’ nations: Finland and Japan. The findings illustrate that differences do exist, and that Finnish older adults are found to be more open to technology-use in the context of digital cultural experiences than their Japanese counterparts. Implications for e-tourism research and management are discussed.
A Re-rank Algorithm for Online Hotel Search
Authors: Cavenaghi Emanuele , Camaione Lorenzo , Minasi Paolo , Sottocornola Gabriele , Stella Fabio , Zanker Markus 
Published: January 2023

AbstractRecommender Systems were created to support users in situations of information overload. However, users are consciously or unconsciously influenced by several factors in their decision-making. We analysed a historical dataset from a meta-search booking platform with the aim of exploring how these factors influence user choices in the context of online hotel search and booking. Specifically, we focused our study on the influence of (i) ranking position, (ii) number of reviews, (iii) average ratings and (iv) price when analysing users’ click behaviour. Our results confirmed conventional wisdom that position and price were the “two elephants in the room” heavily influencing user decision-making. Thus, they need to be taken into account when, for instance, trying to learn user preferences from clickstream data. Using the results coming from this analysis, we performed an online A/B test on this meta-search booking platform comparing the current policy with a price-based re-rank policy. Our online experiments suggested that, although in offline experiments items with lower prices tend to have a higher Click-Through Rate, in an online context a price-based re-rank was only capable to improve the Click-Through Rate metric for the first positions of the recommended lists.
Spatial Spillover Effects of the Digital Economy on Tourism Demand: Evidence from China
Authors: Liu Zhen , Kim Yoo Ri 
Published: January 2023

AbstractDespite widespread concerns about the effect of the digital economy on productivity, few studies have examined the relationship between the digital economy and tourism demand. Based on 285 China’s prefectural-level city statistical data and big data from 2011 to 2019, a comprehensive index of the digital economy is developed and a spatial econometric model is employed to investigate such relationship. The result shows that the growth of the digital economy has positive spatial spillover effects on tourism demand, contributing to extending the impact of the digital economy on tourism demand from the spatial perspective and providing insights for policymakers on regional cooperation in the digitalisation context.
Holographic non-Fermi liquids at large d
Authors: Kachru Shamit , Shyani Milind 
Published: January 2023

Abstract
Motivated by the results of Dynamical Mean Field Theory, we study the two-point function of fermions moving in a charged black brane background in AdSd+1 in the limit of large d. We observe the emergence of a locally critical form of the fermion self-energy, with a strongly constrained range of possible scaling behaviors at large d. Novelties compared to the analysis in d = 3, 4 include an enlarged regime of temperatures where the results apply, and the analytical tractability of the calculations.
Descalarization by quenching charged hairy black hole in asymptotically AdS spacetime
Authors: Chen Qian , Ning Zhuan , Tian Yu , Wang Bin , Zhang Cheng-Yong 
Published: January 2023

Abstract
In this work, we study the real-time dynamics of the charged hairy black hole with the time-dependent source of scalar field in asymptotically anti-de Sitter (AdS) spacetime. The numerical results reveal a novel descalarization mechanism. In order to obtain the hairy black hole as the initial data for the quench process, we first analyze the quasi-normal modes of the massive complex scalar field on the Reissner-Nordström anti-de Sitter (RN-AdS) black hole background. We find the dominant unstable modes for large and small RN-AdS black holes come from the zero-damped modes and AdS modes, respectively. Then, the unstable RN-AdS black holes are perturbed to trigger the transition to hairy black holes. With the hairy black hole in hand, we specify a time dependent scalar source for the system. As the source is turned on, the electric charge, energy and scalar condensation of the system start to oscillate with the entropy increasing monotonically. Finally, with the decay of the scalar source, the system gradually settles down to a new state. Interestingly, the final state of the evolution could be a hairy black hole with less scalar condensation, a RN-AdS black hole or a Schwarzschild-AdS black hole, which depends on the quench strength. However, as long as the quench strength is large enough, the system always loses all the electric charge and converges to the Schwarzschild-AdS black hole.
Is FDI a potential tool for boosting firm’s performance? Firm level evidence from Ecuador
Authors: Camino-Mogro Segundo , Bermúdez-Barrezueta Natalia , Armijos Mary 
Published: January 2023

AbstractIn developing countries, the evidence regarding the direct and indirect effects of FDI on economic and financial performance at the firm level is mixed. To contribute to this literature, we provide empirical evidence of direct and indirect effects of FDI on firm’s performance, using return on assets (ROA), gross revenues and gross revenues growth rate as performance measures. We examine the private formal enterprise sector in Ecuador from 2007 to 2018. Our identification strategy relies on the use of the Generalized Method of Moments (GMM) methodology for dynamic panel data which allows us to control for potential endogeneity, autocorrelation and heteroskedasticity issues. The results suggest that firms with inward FDI grow faster than their counterparts, and firms with higher amounts of FDI as a share of total revenues have on average higher levels of gross revenues. Moreover, we find negative horizontal wages and gross revenues spillover effects on gross revenues growth rates, but positive horizontal gross revenues spillover effects on ROA. There is also significant evidence of negative horizontal spillover effects in all economic sectors, whereas evidence for forward and backward spillovers is heterogeneous across them.
Tits (Paridae sp.) use social information when locating and choosing nest lining material
Authors: Vistalli Sally , Jäger Tim , Aplin Lucy M. , Wild Sonja 
Published: January 2023

Abstract
As an important determinant of reproductive success, avian nest building is under strong selection and requires behavioral plasticity to optimize conditions in which offspring develop. Learning is a one form of plasticity that allows adaptation to the local environment. Birds may refine nest-building behavior with personal experience or use social information to guide their choices. While there is mounting evidence for an effect of experience-based learning on nest building and social information use when selecting nesting material in the laboratory, experimental evidence for social information use in wild birds is lacking. Here, we provided sources of two differently colored wool as nest lining material in a wild mixed-species community of tits (Paridae sp.) to investigate experimentally (i) whether females use social information to locate lining materials and (ii) whether preferences for specific materials (here color) are socially influenced. We investigated pathways of social transmission through a foraging association and a spatial breeding network using the time of arrival at the wool in a network-based diffusion analysis. Our results gave evidence that birds learned about the location of lining resources from foraging associates. Furthermore, we found significant non-random clustering of wool colors in nest boxes across the study area, suggestive of a social influence on selecting lining materials. Taken together, we provide quantitative evidence for a role of social information use in both finding and selecting lining material in wild tits and demonstrate that social information use constitutes an important factor towards behavioral plasticity in nest building in wild birds.

Significance statement
As vessels of reproduction, avian nests are under strong selection to provide optimized conditions for developing offspring. Learning is one mechanism that allows individuals to adapt to local environmental conditions. Previous work has shown that nest-building birds use both social information and personal experience to refine their nests. Yet, evidence for social information use for nest construction in the wild has been purely anecdotal and experimental evidence lacking. Here, we demonstrate for the first time experimentally that in wild tits (Paridae sp.), females rely on social information from their foraging associates to locate and choose material to line their nests. This research highlights the importance of social information use as a potential mechanism of behavioral plasticity in wild nest-building birds.
Analyzing web searches for axial spondyloarthritis in Germany: a novel approach to exploring interests and unmet needs
Authors: Berr Kristina , Tizek Linda , Schielein Maximilian C. , Welcker Martin , Knitza Johannes , Kleinert Stefan , Zink Alexander 
Published: January 2023

AbstractAxial spondyloarthritis (axSpA) is an underdiagnosed condition with a high disease burden. Due to delayed diagnosis and limited access to specialist care, conventional health data might not sufficiently capture the perspective of affected individuals. The aim of this study was to assess public interest, unmet needs, and disease burden of axSpA in Germany through the analysis of thematic, geographic, and temporal patterns in national web search data. Google Ads Keyword Planner was used to identify axSpA-related keywords and their monthly search volume in Germany between January 2017 and December 2020. Identified keywords were qualitatively categorized into six categories. Overall, 265 axSpA-related keywords with a search volume of 3,881,490 queries were identified. Nearly 81% of the total search volume was assigned to the category terms and definition, while 19% referred to either outcomes, symptoms, diagnosis, management, or causes. In the category outcomes, prognostic outcomes like “life expectancy” generated more searches than physical manifestations like “pain”. Less populated cities showed significantly more searches per 100,000 inhabitants than larger cities. Searches were seasonally stable with a Germany-wide peak in July 2017. This study provides an overview of public interest in axSpA based on web search data in Germany. The identified search patterns could be used to guide public health campaigns and optimize axSpA management in Germany.
Home-based immersive virtual reality physical rehabilitation in paediatric patients for upper limb motor impairment: a feasibility study
Authors: Phelan Ivan , Carrion-Plaza Alicia , Furness Penny J , Dimitri Paul 
Published: January 2023

AbstractUpper limb motor impairment (ULMI) rehabilitation is a long-term, demanding and challenging process to recover motor functionality. Children and adolescents may be limited in daily life activities due to reduced functions such as decreased joint movement or muscle weakness. Home-based therapy with Immersive Virtual Reality can offer greater accessibility, delivery and early rehabilitation to significantly optimise functional outcomes and quality of life. This feasibility study aimed to explore the perceptions and impacts of an immersive and interactive VR scenario suitable for ULMI rehabilitation for children at home. It was analysed using mixed methods (quantitative and qualitative) and from a multidirectional perspective (patients, clinicians and family members). Amongst the main results, it was found that IVR for ULMI home rehabilitation (1) is easy to learn and acceptable; (2) improves motor function; (3) reduces the difficulty in the reproduction of therapeutic movements; (4) is motivating and enjoyable and (5) improves quality of life. This study is the first study on the use of IVR applied to home rehabilitation of ULMI in children. These results suggested that similar outcomes may be possible with self-directed IVR home rehabilitation compared to face to face conventional rehabilitation, which can be costly to both the patient and the healthcare system, decreasing the length of stay at the hospital and treatment duration. It has also presented an innovative solution to the Covid-19 emergency where children could not receive their clinic therapy. Further research is recommended to understand better the mechanisms involved in physiotherapeutic recovery and how IVR rehabilitation helps to improve conventional treatments.Trial Registration Protocol ID NCT05272436. Release Date: 9th March 2022.
Sensitivity analysis of combinatorial optimization problems using evolutionary bilevel optimization and data mining
Authors: Schulte Julian , Nissen Volker 
Published: January 2023

AbstractSensitivity analysis in general deals with the question of how changes in input data of a model affect its output data. In the context of optimization problems, such an analysis could, for instance, address how changes in capacity constraints affect the optimal solution value. Although well established in the domain of linear programming, sensitivity analysis approaches for combinatorial optimization problems are model-specific, limited in scope and not applicable to practical optimization problems. To overcome these limitations, Schulte et al. developed the concept of bilevel innovization. By using evolutionary bilevel optimization in combination with data mining and visualization techniques, bilevel innovization provides decision-makers with deeper insights into the behavior of the optimization model and supports decision-making related to model building and configuration. Originally introduced in the field of evolutionary computation, most recently bilevel innovization has been proposed as an approach to sensitivity analysis for combinatorial problems in general. Based on previous work on bilevel innovization, our paper illustrates this concept as a tool for sensitivity analysis by providing a comprehensive analysis of the generalized assignment problem. Furthermore, it is investigated how different algorithms for solving the combinatorial problem affect the insights gained by the sensitivity analysis, thus evaluating the robustness and reliability of the sensitivity analysis results.
No Consumer Is an Island—Relational Disclosure as a Regulatory Strategy to Advance Consumer Protection Against Microtargeting
Authors: Davola A. , Querci I. , Romani S. 
Published: January 2023

AbstractPresently, most business-to-consumer interaction uses consumer profiling to elaborate and deliver personalized products and services. It has been observed that these practices can be welfare-enhancing if properly regulated. At the same time, risks related to their abuses are present and significant, and it is no surprise that in recent times, personalization has found itself at the centre of the scholarly and regulatory debate. Within currently existing and forthcoming regulations, a common perspective can be found: given the capacity of microtargeting to potentially undermine consumers’ autonomy, the success of the regulatory intervention depends primarily on people being aware of the personality dimension being targeted. Yet, existing disclosures are based on an individualized format, focusing solely on the relationship between the professional operator and its counterparty; this approach operates in contrast to sociological studies that consider interaction and observation of peers to be essential components of decision making. A consideration of this “relational dimension” of decision making is missing both in consumer protection and in the debate on personalization. This article defends that consumers’ awareness and understanding of personalization and its consequences could be improved significantly if information was to be offered according to a relational format; accordingly, it reports the results of a study conducted in the streaming service market, showing that when information is presented in a relational format, people’s knowledge and awareness about profiling and microtargeting are significantly increased. The article further claims the potential of relational disclosure as a general paradigm for advancing consumer protection.
Prevalence of Hepatitis B and Hepatitis C in Migrants from Sub-Saharan Africa Before Onward Dispersal Toward Europe
Authors: Saaed Frhat M. A. , Ongerth Jerry E. 
Published: January 2023

AbstractViral hepatitis is a global health care challenge due to its worldwide distribution, chronic persistence, complications, and high prevalence with unchecked conditions in areas like sub-Saharan Africa. A high proportion of asymptomatic infections allows serious complications and poses infection risk to destination populations. This study aimed to determine the prevalence of both HBV and HCV among 3248 migrants from different parts of sub-Saharan Africa newly arrived at Kufra, Libya, a remote agricultural North African city. All these migrants were required by the Libyan authorities to undergo a complete medical check-up for different purposes such as joining new jobs, and obtaining licenses for trade and commerce. UAT sera from 3248 migrants, aged 18–53 years, attending the Al Kufra city hospital from January 01 to December 31, 2019, were screened for HBsAg and anti-HCV antibody by rapid tests and positive samples were further tested by ELISA method. The results showed that 761/3248 (23.4%) of the migrants were positive for HBV and 1014/3248 (31.2%) were positive for HCV. Migrants from sub-Saharan Africa carry high rates of HBV and HCV infection. This suggests the importance of increased attention to actions to deal with findings among positive migrants, and for awareness about risks of transmission to the local population. Study results indicate the value of routine migrant monitoring, the need for awareness in destination country health authorities, and the potential for impact on migrant destination populations.
The Utility of Oncology Information Systems for Prognostic Modelling in Head and Neck Cancer
Authors: Kotevski Damian P. , Smee Robert I. , Field Matthew , Broadley Kathryn , Vajdic Claire M. 
Published: January 2023

AbstractCancer centres rely on electronic information in oncology information systems (OIS) to guide patient care. We investigated the completeness and accuracy of routinely collected head and neck cancer (HNC) data sourced from an OIS for suitability in prognostic modelling and other research. Three hundred and fifty-three adults diagnosed from 2000 to 2017 with head and neck squamous cell carcinoma, treated with radiotherapy, were eligible. Thirteen clinically relevant variables in HNC prognosis were extracted from a single-centre OIS and compared to that compiled separately in a research dataset. These two datasets were compared for agreement using Cohen’s kappa coefficient for categorical variables, and intraclass correlation coefficients for continuous variables. Research data was 96% complete compared to 84% for OIS data. Agreement was perfect for gender (κ = 1.000), high for age (κ = 0.993), site (κ = 0.992), T (κ = 0.851) and N (κ = 0.812) stage, radiotherapy dose (κ = 0.889), fractions (κ = 0.856), and duration (κ = 0.818), and chemotherapy treatment (κ = 0.871), substantial for overall stage (κ = 0.791) and vital status (κ = 0.689), moderate for grade (κ = 0.547), and poor for performance status (κ = 0.110). Thirty-one other variables were poorly captured and could not be statistically compared. Documentation of clinical information within the OIS for HNC patients is routine practice; however, OIS data was less correct and complete than data collected for research purposes. Substandard collection of routine data may hinder advancements in patient care. Improved data entry, integration with clinical activities and workflows, system usability, data dictionaries, and training are necessary for OIS data to generate robust research. Data mining from clinical documents may supplement structured data collection.