bluuebunny/crossref_metadata_2025_split huggingface dataset:
Which direction for stakeholder capitalism? Approaches and reporting towards POP accounting
Authors: Biancone Paolo Pietro , Secinaro Silvana , Brescia Valerio , Calandra Davide 
Published: May 2024

AbstractOur study uncovers the evolving landscape of stakeholder capitalism. This paradigm recognises the intrinsic value of capital among diverse stakeholders and underscores the importance of engaging them in the long‐term value‐generation process. Through bibliometric analysis, we explore the multifaceted nature of stakeholder capitalism, its historical evolution, and the current debates surrounding its implementation, particularly in social reporting and integrated performance representation. Our findings illuminate the growing emphasis on POP accounting as a potential bridge between traditional shareholder‐centric models and a more inclusive stakeholder‐oriented approach. POP accounting emerges as a vital tool for demystifying complex financial data, offering a transparent, accessible narrative that resonates with broader stakeholders. By integrating insights from various sectors and geographical regions, this paper sheds light on the practical implications of adopting POP accounting within stakeholder capitalism. It suggests it could catalyse a more democratic, transparent, and sustainable corporate governance framework. Our research contributes to the ongoing corporate responsibility and governance discourse, providing actionable insights for businesses, policymakers, and academics committed to fostering an equitable, stakeholder‐inclusive future.
Using seasonal oscillations in fin ray microchemistry to chemically age Lake Sturgeon
Authors: Taylor Alaina A. , Loeppky Alison R. , Stadig Margaret H. , Anderson W. Gary 
Published: May 2024

Abstract

Objective
Nonlethally sampled pectoral fin rays are commonly used as aging structures for Lake Sturgeon Acipenser fulvescens, but they tend to underestimate the true age in older, slow-growing individuals (age &gt; 14 years). Current aging practices involve counting bands along the structure, which are construed as annuli. Oscillations of certain trace elements corresponding with annuli have been seen across various fish species, with patterns continuing to the marginal edge of hard structures. This study explored the aging of fin rays by using microchemistry patterns in Lake Sturgeon of known age (n = 94; ages 5–21) to determine the potential use of this method as an alternative or supplementary aging technique.

Methods
Elements were chosen for age determination analysis by examining the relationship between profile minima/maxima and visually interpreted annuli. Fish were assigned ages using three different methods: (1) traditional interpretation (counting annuli along the structure), (2) chemical interpretation (examination of seasonal variations in elemental profiles with visually identified annuli), and (3) a statistical model (multivariate multiple changepoint analysis with finite differencing using raw elemental profiles).

Result
Mean absolute differences between age estimates and known age were significantly higher for the traditional interpretation method than for the chemical interpretation method. The mean coefficient of variation in estimated age was 11.14% for the traditional interpretation method and 4.04% for the chemical interpretation method. The changepoint model was able to correctly classify age for 100% of the samples within ±1 year in one population (ages 5–8) but could not classify samples from the second population (ages 12–21).

Conclusion
Our results suggest that chemical aging techniques could provide more reliable age estimates for juvenile and subadult Lake Sturgeon when fin rays are the only aging option. Further work is required to determine the applicability of the model for assigning ages to older fish and for use with different populations and structures.
Low‐concentration imiquimod treatment promotes enhanced skin barrier functions through epidermal melanization reaction regulation
Authors: Lin Tzu‐Kai , Tsai Chia‐Lun , Tsai Bruce Chi‐Kang , Kuo Chia‐Hua , Ho Tsung‐Jung , Hsieh Dennis Jine‐Yuan , Kuo Wei‐Wen , Huang Chih‐Yang 
Published: May 2024

AbstractThe primary function of the skin is to form a mechanical, permeability, antimicrobial, and ultraviolet radiation barrier, which is essential for maintaining physiological homeostasis. Our previous studies demonstrated that cutaneous pigmentation could promote skin barrier function in addition to providing anti‐ultraviolet irradiation defense. The present study aimed to develop a new regimen that enhances skin barrier function by regulating skin pigmentation using low‐concentration imiquimod. Results showed that topical application of low‐concentration imiquimod effectively induced skin hyperpigmentation in the dorsal skin and external ear of mice without inducing inflammatory cell infiltration. An in vitro study also revealed that low‐concentration imiquimod did not induce any cytotoxic effects on melanoma cells but triggered excessive melanin synthesis. In coculture systems, low‐concentration imiquimod was noted to increase tyrosinase activity in a broader cellular context, revealing the potential role of neighboring cells in melanin production. The next‐generation sequencing result indicated that PKCη and Dnm3 might regulate melanin synthesis and release during imiquimod treatment. Overall, our study presents new insights into the regulation of melanin production by low‐concentration imiquimod, both in a mice model and cultured cells. Furthermore, our study highlights the potential benefits of imiquimod in promoting melanin synthesis without causing skin disruptions or inducing inflammation, validating its potential to serve as a method for enhancing skin barrier functions by regulating the epidermal melanization reaction.
Future of durum wheat research and breeding: Insights from early career researchers
Authors: Peters Haugrud Amanda R. , Achilli Ana Laura , Martínez‐Peña Raquel , Klymiuk Valentyna 
Published: May 2024

AbstractDurum wheat (Triticum turgidum ssp. durum) is globally cultivated for pasta, couscous, and bulgur production. With the changing climate and growing world population, the need to significantly increase durum production to meet the anticipated demand is paramount. This review summarizes recent advancements in durum research, encompassing the exploitation of existing and novel genetic diversity, exploration of potential new diversity sources, breeding for climate‐resilient varieties, enhancements in production and management practices, and the utilization of modern technologies in breeding and cultivar development. In comparison to bread wheat (T. aestivum), the durum wheat community and production area are considerably smaller, often comprising many small‐family farmers, notably in African and Asian countries. Public breeding programs such as the International Maize and Wheat Improvement Center (CIMMYT) and the International Center for Agricultural Research in the Dry Areas (ICARDA) play a pivotal role in providing new and adapted cultivars for these small‐scale growers. We spotlight the contributions of these and others in this review. Additionally, we offer our recommendations on key areas for the durum research community to explore in addressing the challenges posed by climate change while striving to enhance durum production and sustainability. As part of the Wheat Initiative, the Expert Working Group on Durum Wheat Genomics and Breeding recognizes the significance of collaborative efforts in advancing toward a shared objective. We hope the insights presented in this review stimulate future research and deliberations on the trajectory for durum wheat genomics and breeding.
Variable PFAS removal by adsorbent media with sufficient prediction of breakthrough despite reduced contact time at pilot scale
Authors: Pannu Manmeet W. , Huang Andrew , Plumlee Megan H. 
Published: May 2024

AbstractOne alternative adsorbent (AA) and five ion exchange (IX) resins were tested for the removal of per‐ and polyfluoroalkyl substances (PFAS) from groundwater in pilot‐scale columns for up to 19 months using empty bed contact times (EBCTs) representative of full‐scale treatment. For the six detected PFAS in the pilot feed water, the long‐chain PFAS (perfluorooctanoic acid [PFOA], perfluorooctanesulfonic acid [PFOS], and perfluorohexanesulfonic acid [PFHxS]) were well removed with only PFOA, which is a perfluoroalkyl carboxylic acid (PFCA) eventually breaking through as the media became exhausted. Perfluorobutanesulfonic acid (PFBS), a short‐chain perfluorosulfonic acid (PFSA), was also well removed, whereas short‐chain PFCAs (perfluoropentanoic acid [PFPeA] and perfluorobutanoic acid [PFBA]) were not removed (i.e., immediate breakthrough). Overall, IX and AA demonstrated superior removal of PFSAs compared to PFCAs (i.e., later breakthrough of PFSAs translating to longer media life). Media life varied, ranging from 6 to 15 months before adsorbents reached a significant PFOA breakthrough. The performance of the two adsorbents piloted at shorter EBCT reasonably predicted the longer (representative) pilot EBCT results (within ±20–30%) for the same adsorbents following data scaling. This suggests that pilot‐scale testing may be conducted at a faster pace and therefore more economically.Practitioner Points
Long‐chain PFAS (PFOA, PFOS, and PFHxS) were well removed by five ion exchange and one alternative adsorbent tested herein.
One short‐chain PFAS (PFBS) was well removed with no removal of two other short‐chain PFAS (PFBA and PFPeA).
Performance of the two adsorbents piloted at shorter EBCT reasonably predicted the longer (representative) pilot EBCT results for the same adsorbents following data scaling.
Artificial Intelligence in Professional and Vocational Training
Authors: Ciavaldini-Cartaut Solange , Métral Jean-François , Olry Paul , Guidoni-Stoltz Dominique , Gagneur Charles-Antoine 
Published: May 2024

AbstractThis chapter explores challenges linked to AI integration in professional training, emphasising the need to question the learning analytics generated during activities involving humans or living entities. The intersection of initial and ongoing training poses a design challenge: making AI tools acceptable for both training and the workplace. This chapter critically examines the nature and quality of the initial data and learning analytics using educational data mining through three case studies of adaptive learning environments. The first case study addresses the challenges of modelling Comté cheese manufacturing. The second case study describes Silva Numerica, a digital forest simulator, exploring how AI, as a learning tool, can contribute to realistic modelling while addressing didactic obstacles. The third case delves into AI's role in automotive mechanics training, emphasising the need for visibility in cognitive inference processes. The chapter concludes by addressing data reliability concerns in AI systems and proposing education and training strategies to overcome such challenges.
Citizenship, Censorship, and Democracy in the Age of Artificial Intelligence
Authors: Matusevych Tetiana , Romero Margarida , Strutynska Oksana 
Published: May 2024

AbstractThis chapter delves into the ethical dilemmas that arise from the incorporation of artificial intelligence (AI) into the field of education. It emphasises the importance of media literacy, AI literacy, and critical use of digital technologies in order to combat information conflicts, political manipulation, and AI inequality, among other issues. Potential threats to citizenship, such as AI censorship and disinformation, are examined in this chapter. Discourse is devoted to the dangers of deepfake technology as it pertains to the dissemination of false information and the manipulation of public sentiment; the significance of comprehending AI fundamentals and enforcing ethical standards is underscored. Notwithstanding the potential hazards, this chapter acknowledges the prospective advantages of AI in the field of education, which encompass gamification and adaptive learning paths. The text culminates by emphasising the significance of AI acculturation in enabling individuals to comprehend the ethical intricacies and arrive at well-informed judgements regarding the impact of AI on democracy, education, and citizenship.
Affordances for AI-Enhanced Digital Game-Based Learning
Authors: Romero Margarida , Lameras Petros , Arnab Sylvester 
Published: May 2024

AbstractThis chapter investigates the dynamic synergy between pedagogy, social dynamics, and technological developments in Digital Game-Based Learning (DGBL), which is enhanced by artificial intelligence (AI). The chapter navigates through educational modifications, learner profiling challenges, social enhancements, and technical considerations, emphasising AI's revolutionary influence. The topic expands on the critical interaction between learning analytics and machine learning, demonstrating AI's promise for personalised and adaptable DGBL experiences. The practical ramifications of real-time feedback in AI-driven DGBL are discussed, with the goal of providing timely instruction and encouraging positive behaviours. Finally, the chapter sheds light on the collaborative evolution of AI-enhanced education, providing useful insights for educators, instructional designers, and developers in creating optimised digital learning environments.
Feynman rules and loop structure of Carrollian amplitudes
Authors: Liu Wen-Bin , Long Jiang , Ye Xiao-Quan 
Published: May 2024

Abstract
In this paper, we derive the Carrollian amplitude in the framework of bulk reduction. The Carrollian amplitude is shown to relate to the scattering amplitude by a Fourier transform in this method. We propose Feynman rules to calculate the Carrollian amplitude where the Fourier transforms emerge as the integral representation of the external lines in the Carrollian space. Then we study the four-point Carrollian amplitude at loop level in massless Φ4 theory. As a consequence of Poincaré invariance, the four-point Carrollian amplitude can be transformed to the amplitude that only depends on the cross ratio z of the celestial sphere and a variable χ invariant under translation. The four-point Carrollian amplitude is a polynomial of the two-point Carrollian amplitude whose argument is replaced with χ. The coefficients of the polynomial have branch cuts in the complex z plane. We also show that the renormalized Carrollian amplitude obeys the Callan-Symanzik equation. Moreover, we initiate a generalized Φ4 theory by designing the Feynman rules for more general Carrollian amplitude.
Spinning particle geometries in AdS3/CFT2
Authors: Li Ziyi 
Published: May 2024

Abstract
We study spinning particle/defect geometries in the context of AdS3/CFT2. These solutions lie below the BTZ threshold, and can be obtained from identifications of AdS3. We construct the Feynman propagator by solving the bulk equation of motion in the spinning particle geometry, summing over the modes of the fields and passing to the boundary. The quantization of the scalar fields becomes challenging when confined to the regions that are causally well-behaved. If the region containing closed timelike curves (CTCs) is included, the normalization of the scalar fields enjoys an analytical simplification and the propagator can be expressed as an infinite sum over image geodesics. In the dual CFT2, the propagator can be recast as the HHLL four-point function, where by taking into account the PSL(2, ℤ) modular images, we recover the bulk computation. We comment on the casual behavior of bulk geometries associated with single-trace operators of spin scaling with the central charge below the BTZ threshold.
Symmetry restoration and uniformly accelerated observers in Minkowski spacetime
Authors: Salluce Domenico Giuseppe , Pasini Marco , Flachi Antonino , Pittelli Antonio , Ansoldi Stefano 
Published: May 2024

Abstract
We reassess the problem of symmetry restoration induced by observers’ acceleration within the context of interacting quantum field theories in Minkowski spacetime. We argue that the imposition of a frame-independent renormalization condition negates any observed symmetry restoration by a Rindler observer. Technically, we compute the one-loop effective potential of a λφ4 theory for an accelerated observer, employing a distinct methodology from prior investigations. Emphasizing the intricacies of the model’s renormalization, the analysis offers novel insights into the interplay between acceleration and spontaneous symmetry breaking in quantum field theory.
Inscribing geodesic circles on the face of the superstratum
Authors: Guo Bin , Hampton Shaun D. , Warner Nicholas P. 
Published: May 2024

Abstract
We use families of circular null geodesics as probes of a family of microstate geometries, known as (1, 0, n) superstrata. These geometries carry a left-moving momentum wave and the behavior of some of the geodesic probes is very sensitive to this background wave. The left-moving geodesics behave like BPS particles and so can be placed in circular orbits anywhere in the geometry and actually “float” at fixed radius and angle in the three-dimensional “capped BTZ” geometry. The right-moving geodesics behave like non-BPS particles. We show that they provide a simple geometric characterization of the black-hole bound: when the momentum charge of the geometry is below this bound, such geodesics can be placed anywhere, but exceeding the bound, even by a small amount, means these geodesics are restricted to the deep interior of the geometry. We also show that for left-moving string probes, the tidal forces remain comparable with those of global AdS3. Nevertheless, for some of these probes, the “bumps” in the geometry induce an oscillatory mass term and we discuss how this can lead to chaotic scrambling of the state of the string.
Fractional particle and sigma model
Authors: Vancea Ion V. 
Published: May 2024

Abstract
We introduce a classical fractional particle model in ℝn, extending the Newtonian particle concept with the incorporation of the fractional Laplacian. A comprehensive discussion on kinetic properties, including linear momentum and kinetic energy, is provided. We further derive the equations of motion and discuss the symmetries of the system. The Green’s function method is employed to solve the equations of motion in a general case. We illustrate the theory with three important examples: the free fractional particle, the fractional harmonic oscillator, and the charged fractional particle that interacts locally with the electromagnetic field. We use the results of the extension problem by Caffarelli and Silvestre, to construct the associated classical local sigma model for the fractional particle. The sigma model is then quantized using the canonical quantization method, and we compute the vacuum energy at the boundary.
Why artificial intelligence needs sociology of knowledge: parts I and II
Authors: Collins Harry 
Published: May 2024

AbstractRecent developments in artificial intelligence based on neural nets—deep learning and large language models which together I refer to as NEWAI—have resulted in startling improvements in language handling and the potential to keep up with changing human knowledge by learning from the internet. Nevertheless, examples such as ChatGPT, which is a ‘large language model’, have proved to have no moral compass: they answer queries with fabrications with the same fluency as they provide facts. I try to explain why this is, basing the argument on the sociology of knowledge, particularly social studies of science, notably ‘studies of expertise and experience’ and the ‘fractal model’ of society. Learning from the internet is not the same as socialisation: NEWAI has no primary socialisation such as provides the foundations of human moral understanding. Instead, large language models are retrospectively socialised by human intervention in an attempt to align them with societally accepted ethics. Perhaps, as technology advances, large language models could come to understand speech and recognise objects sufficiently well to acquire the equivalent of primary socialisation. In the meantime, we must be vigilant about who is socialising them and be aware of the danger of their socialising us to align with them rather than vice-versa, an eventuality that would lead to the further erosion of the distinction between the true and the false giving further support to populism and fascism.
How does artificial intelligence work in organisations? Algorithmic management, talent and dividuation processes
Authors: Martorell Joan Rovira , Tirado Francisco , Blasco José Luís , Gálvez Ana 
Published: May 2024

AbstractThis article analyses the forms of dividuation workers undergo when they are linked to technologies, such as algorithms or artificial intelligence. It examines functionalities and operations deployed by certain types of Talent Management software and apps—UKG, Tribepad, Afiniti, RetailNext and Textio. Specifically, it analyses how talented workers materialise in relation to the profiles and the statistical models generated by such artificial intelligence machines. It argues that these operate as a nooscope that allows the transindividual plane to be quantified through a process known as dividuation. Finally, by way of conclusion, the notion of the dividual is presented as the logic that characterises the human–machine relationship in the case of artificial intelligence and as the horizon of what Felix Guattari called “machinic capitalism”.
The extimate core of understanding: absolute metaphors, psychosis and large language models
Authors: Heimann Marc , Hübener Anne-Friederike 
Published: May 2024

AbstractThis paper delves into the striking parallels between the linguistic patterns of Large Language Models (LLMs) and the concepts of psychosis in Lacanian psychoanalysis. Lacanian theory, with its focus on the formal and logical underpinnings of psychosis, provides a compelling lens to juxtapose human cognition and AI mechanisms. LLMs, such as GPT-4, appear to replicate the intricate metaphorical and metonymical frameworks inherent in human language. Although grounded in mathematical logic and probabilistic analysis, the outputs of LLMs echo the nuanced linguistic associations found in metaphor and metonymy, suggesting a mirroring of human linguistic structures. A pivotal point in this discourse is the exploration of “absolute metaphors”—core gaps in reasoning discernible in both AI models and human thought processes and central to the Lacanian conceptualization of psychosis. Despite the traditional divide between AI research and continental philosophy, this analysis embarks on an innovative journey, utilizing Lacanian philosophy to unravel the logic of AI, using concepts established in the continental discourse on logic, rather than the analytical tradition.